| 1 |
Author(s):
Ms.Pranita Kanadkhedkar, Ms.Shruti Kokadwar, Ms.Nita Lohar.
Page No : 1-2
|
AUTOMATIC ACCIDENT AVOIDING CAR
Abstract
The Automatic Accident Avoiding Car is an intelligent vehicle safety system designed to reduce road accidents by detecting obstacles and taking preventive actions automatically. The system uses sensors such as ultrasonic sensors, infrared (IR) sensors, and microcontrollers to continuously monitor the surroundings of the vehicle. When an obstacle or another vehicle is detected within a predefined distance, the system alerts the driver and automatically slows down or stops the vehicle to prevent a collision.
The primary objective of this project is to enhance road safety by minimizing human errors,
which are one of the major causes of traffic accidents. The system operates in real time, providing quick response and efficient obstacle detection. It can be implemented in automobiles, autonomous vehicles, and smart transportation systems to improve safety and reduce accident rates.
| 2 |
Author(s):
Mr.N.LOGESH.
Page No : 1-3
|
PATIENT-PERCEIVED DIMENSIONS OF TOTAL QUALITY SERVICE IN HEALTHCARE
Abstract
This assessment paper intends to perceive estimations of patient-saw full scale quality organization (TQS) in the restorative administrations division. Further, the impact of the estimations of patient-saw TQS on calm satisfaction is investigated. A study has been made considering a wide composition review of investigation in organization quality and in light of responses of the pilot diagram among patients starting late discharged from facility. The instrument thusly made has been investigated for its psychometric properties using trial of trustworthiness and authenticity. Various backslide assessment has been utilized to take a gander at the impact of the estimations of patient-saw quality on patient satisfaction. Discoveries feature seven undeniable estimations of patient-saw TQS and the associations among them. Positive and basic associations among the estimations and patient satisfaction have been found. Commitment to investigate on social protection organizations by the improvement of a broad instrument of patient-saw social protection quality. This instrument would engage patients to offer contribution to recuperating offices concerning nature of human administrations got by them. Mending offices could use this analysis to separate their execution, gage getting satisfaction and benchmark their execution against forceful recuperating offices. This paper portrays a total instrument of patient-saw social protection quality.
| 3 |
Author(s):
Mr.N.LOGESH.
Page No : 1-3
|
A STUDY ON BENEFITS TO THE ORGANIZATION DUE TO INVENTORY CONTROL AND TECHNIQUES
Abstract
The past assessment tackle material and budgetary production network organization has generally grasped fringe examination what's more, EOQ model, which rely upon the ordinary idea of personal circumstance intensification or "Efficiencies". Regardless, this idea consistently drives those strong endeavors in a store system to have their more fragile assistants' benefits by association reserve approach; as such outcomes in the break of the cash related streams along the chain. This paper discusses the intrigue unbalance inside such a little structure and its negative effects; at that point proposes a way to deal with decide it from viewpoint of association and cooperation. An essential model of stable money stream along generation system is given.
| 4 |
Author(s):
Prajota D. Shrimanwar.
Page No : 1-3
|
Design and Implementation of Smart Irrigation System Using ESP8266
Abstract
Smart irrigation has become an essential solution for efficient water management in agriculture. Traditional irrigation methods often lead to water wastage and require continuous human supervision. This paper presents the design and implementation of a low-cost ESP8266-based smart irrigation system capable of monitoring soil moisture and automatically controlling water supply. The system provides real-time monitoring and automated irrigation, ensuring optimal water utilization. Experimental results demonstrate reliable performance, reduced water consumption, and improved irrigation efficiency. The proposed system is economical, easy to implement, and suitable for agricultural fields, gardens, and greenhouse applications.
Index Terms— ESP8266, Smart Irrigation System, Soil Moisture Sensor, Water Pump, Agriculture Automation, Embedded Systems.
| 5 |
Author(s):
Pankaja t.
Page No : 1-3
|
A Study on the Effectiveness of Employment Background Verification in Reducing Hiring Risks
Abstract
Employment Background Verification (EBV) has become an indispensable component of contemporary recruitment practices as organizations increasingly seek to minimize hiring risks and improve workforce quality. The rise in résumé fraud, falsified educational credentials, identity theft, and inaccurate employment records has made systematic background verification essential for informed hiring decisions. This study examines the effectiveness of employment background verification in reducing hiring risks and enhancing recruitment quality.
A quantitative research design was adopted using a structured questionnaire administered to 100 respondents involved in recruitment and background verification activities. Data were analyzed using IBM SPSS Statistics. Statistical tools such as descriptive statistics, reliability analysis, correlation, regression, independent sample t-test, one-way ANOVA, and chi-square test were employed to examine the relationship between employment background verification and hiring risk reduction.
The findings indicate that comprehensive background verification significantly enhances employer confidence, improves recruitment quality, and minimizes the likelihood of hiring unsuitable candidates. The study concludes that employment background verification should be considered a strategic risk management practice rather than merely an administrative recruitment process. Organizations should adopt standardized and technology-enabled verification systems to improve recruitment effectiveness and organizational performance.
Keywords: Employment Background Verification, Hiring Risks, Recruitment, Employee Screening, Human Resource Management, Risk Management.
| 6 |
Author(s):
Nagesh Soule.
Page No : 1-3
|
UPI Payment Convenience and Its Impact on Impulsive Buying Behaviour Among Consumers
Abstract
The Unified Payments Interface (UPI) has become the dominant mode of digital payment in India, prized for its speed, ease of use, and seamless integration into everyday purchases. While UPI's convenience benefits are well documented, less is known about how specific dimensions of the UPI experience - ease of use, speed and availability, promotional incentives, and trust and security - jointly predict impulsive buying behaviour among consumers. This study examines these relationships using primary survey data from 81 valid respondents, measured through a 20-item structured questionnaire combining four Yes/No items capturing impulsive buying behaviour and sixteen five-point Likert items across four predictor constructs. The instrument demonstrated acceptable to good reliability (Cronbach's alpha = 0.762 overall). Descriptive results show respondents rate UPI highly on Ease of Use (M = 4.19) and Speed & Availability (M = 3.94), while Promotional Influence (M = 2.81) and Trust & Security (M = 3.30) were rated more moderately. Regression analysis revealed that Promotional Influence (β = 0.263) and Trust & Security (β = 0.265) were the strongest predictors of impulsive buying behaviour, while Ease of Use and Speed & Availability showed negligible unique contribution once the other constructs were accounted for (R² = 0.155). These findings suggest that impulsive UPI-driven purchases are shaped more by promotional incentives and payment confidence than by sheer usability or speed, offering practical implications for retailers, fintech platforms, and policymakers concerned with responsible digital spending.
| 7 |
Author(s):
Vasundhara Saluja, Dr Vibha Kapoor.
Page No : 1-4
|
A RESEARCH ON REPOSITIONING KHADI AS A SUSTAINABLE FASHION TEXTILE
Abstract
The growing appetite for sustainable fashion has opened doors to resurrect traditional textiles that represent environmental and social responsibility. Khadi, one of India’s most sustainable hand-spun and hand-woven textiles, continues to struggle for greater acceptance among today’s urban consumers as a result of its traditional image and poor market placement. The study analyzes the possibilities of converting Khadi into a modern sustainable fashion material that resonates with the changing customer preferences and lifestyles. To explore the customer perception and market challenges, a mixed-method approach combining literature review, analysis of KVIC sales data, consumer surveys, case studies of sustainable fashion firms and focus group discussions was utilized. The findings reveal that even if consumers are aware of the sustainability characteristics of Khadi, the adoption of Khadi is limited by perceptions of design, branding and accessibility. The study indicates that the modern product innovation, effective branding, digital marketing and lifestyle-oriented positioning can greatly improve the consumer acceptance. The study combines sustainability with fashion and marketing perspectives, to provide a practical framework for enhancing the relevance of Khadi in the contemporary fashion business and also helping to the preservation of India’s textile legacy and promotion of sustainable consumption.
| 8 |
Author(s):
Aman Kumar.
Page No : 1-4
|
RESUME-IQ: AI POWERED RESUME ANALYZER
Abstract
In today's competitive job market, a well
structured and keyword-optimized resume
plays a decisive role in securing employment
opportunities. However, most candidates lack
the tools or expertise to evaluate and improve
their resumes effectively. Resume-IQ is an AI
powered web application designed to bridge
this gap by providing intelligent, automated
resume analysis and personalized feedback.
The system accepts resumes in PDF format,
extracts textual content, and leverages the
LLaMA 3.1 large language model via the Groq
API to analyze the resume against a user
provided job description. It evaluates key
parameters such as ATS (Applicant Tracking
System) compatibility, skill match percentage,
missing keywords, and overall presentation
quality. Feedback is delivered both on-screen
and via email using Resend API for email
delivery. The backend is developed using
Node.js and Express.js, ensuring a lightweight
and scalable architecture. This paper presents
the design, methodology, implementation, and
results of the ResumeIQ system, demonstrating
its effectiveness as a smart career assistance
tool.
| 9 |
Author(s):
vedanti pramod kaulwar.
Page No : 1-4
|
fire detection and alarm system using temperature sensor
Abstract
Fire accidents are one of the major causes of loss of life and property in homes, industries, offices, and public places. Early detection of fire is essential to minimize damage and ensure the safety of people. The Fire Detection and Alarm System Using a Temperature Sensor is a simple, low-cost, and reliable system designed to detect abnormal increases in temperature and provide an immediate warning through an alarm.
| 10 |
Author(s):
HARSHIT UPADHYAY.
Page No : 1-4
|
DESIGN AND ANALYSIS OF LEG GUARD OF TWO-WHEELER FOR OPTIMIZATION OF WEIGHT AND STRENGTH
Abstract
This study presents the design, explicit dynamic analysis, and material optimization of a diamond-shaped two-wheeler leg guard.
A three-dimensional leg guard model was developed in CATIA V5 and analyzed in ANSYS 19.0 Explicit Dynamics under an
impact condition against a fixed concrete block. Four materials—SS202, SS440C, Mild Steel, and Titanium Alloy—were
evaluated under identical geometry, meshing, and loading conditions. A 10 mm tetrahedral mesh was used, with an initial velocity
of 8560 mm/s and an analysis end time of 0.005841 s. The numerical response was assessed using maximum equivalent (von
Mises) stress and total deformation, while theoretical load-carrying capacity and component weight were calculated from material
yield strength, tube cross-sectional area, and density. The calculated load-carrying capacities were 32.39, 53.01, 53.01, and 97.53
kN for SS202, SS440C, Mild Steel, and Titanium Alloy, respectively. The corresponding weights were 1.56, 1.54, 1.62, and 0.89
kg. A Weighted Sum Method, with priorities of 0.8 for strength and 0.2 for weight, identified Titanium Alloy as the optimum
material with a score of 1. The study demonstrates a numerical material-selection approach for achieving a lightweight leg guard
with improved theoretical strength performance.
| 11 |
Author(s):
Akshatha N.
Page No : 1-4
|
Predictive Analysis of Lead Conversion Using CRM Data in the EdTech Industry: A Study at Intellipaat
Abstract
Customer Relationship Management (CRM) systems are central to how Education Technology (EdTech) companies manage enquiries, yet the data captured in such systems is not always analysed for its predictive value. This study examines lead conversion at Intellipaat, a Bengaluru-based EdTech company, by combining CRM-related organisational context observed during an internship with a structured questionnaire administered to 103 individuals who had enquired about Intellipaat's certification programmes, of whom 88 confirmed an actual enquiry. Frequency and percentage analysis, Cronbach's Alpha, Chi-Square tests, Pearson/Spearman correlation and binary logistic regression were used to examine counsellor-interaction quality, lead source, learner satisfaction/trust, and counselling and decision-factor ratings in relation to conversion. Lead source was significantly associated with enquiry outcome (χ² = 25.287, df = 12, p = 0.014), while overall satisfaction was strongly correlated with trust (r = 0.848) and willingness to enrol again (r = 0.822). Counsellor satisfaction alone was not significant (χ² = 6.745, df = 8, p = 0.564), and the logistic regression model was not significant (p = 0.672). The findings indicate that structured, CRM-recorded behavioural data offers a more promising foundation for predictive lead scoring than survey-based perception composites alone.
Key Words: Customer Relationship Management, Lead Conversion, Predictive Analytics, EdTech, Lead Scoring, Logistic Regression.
| 12 |
Author(s):
ABHISHEK Channappa Borakanavar.
Page No : 1-4
|
The Impact of Artificial Intelligence on Credit Risk Assessment and Lending Decision-Making in India’s FinTech Industry
Abstract
The rapid expansion of India's FinTech sector has accelerated the adoption of Artificial Intelligence (AI) in credit risk assessment and lending decision-making. This study examines how AI-driven analytics influence the accuracy of credit evaluation, the speed of loan processing, and the overall quality of lending decisions among FinTech, banking, and NBFC professionals. A descriptive and analytical research design was adopted, drawing on primary data collected from 120 respondents through a structured questionnaire, supplemented by secondary literature. Data were analyzed using percentage analysis, mean and standard deviation, correlation, and multiple regression in MS Excel. The analysis indicates a positive and statistically significant relationship between AI adoption and both credit risk assessment efficiency and lending decision quality, while also highlighting challenges such as data quality, model interpretability, and regulatory alignment. The study concludes that AI adoption, when supported by robust governance and skilled personnel, meaningfully strengthens credit risk assessment and lending outcomes in India's FinTech industry, and offers practical recommendations for FinTech firms, digital lenders, banks, and NBFCs.
| 13 |
Author(s):
Nabil Suleiman.
Page No : 1-4
|
The incredible journey of cybersecurity: from military origins to a recession-proof business opportunity.
Abstract
Since the first network was created in 1969 by the Defense Advanced Research Projects Agency, for both the Military MILnet and the civil ARPAnet, the purpose was to give remote access, at the time the risk of cyber breaches was not taken into consideration.
This research analyzes the risk, giving birth to the need or demand for security, making cybersecurity a market product or service aimed to satisfy that demand.
As the use of the internet has been growing to the level of involving any business activity, is a must to protect this business from unwanted risks.
| 14 |
Author(s):
DIVYA SM.
Page No : 1-5
|
A STUDY ON WOMEN FACULTY WELFARE MEASURES IN PG COLLEGE IN BALLARI CITY
Abstract
This study examines the welfare measures provided to women faculty members in selected PG colleges in Ballari City and assesses their level of satisfaction. A descriptive research design was adopted, and primary data were collected from 100 women faculty members using a structured questionnaire through convenience sampling. The findings indicate that most respondents are satisfied with welfare measures such as maternity benefits, paid leave, medical facilities, and grievance redressal mechanisms. The study concludes that effective welfare measures improve job satisfaction, employee well-being, and work performance. It recommends strengthening welfare policies to create a more supportive and inclusive workplace for women faculty.
Keywords: Women Faculty, Welfare Measures, Job Satisfaction, Higher Education, PG Colleges, Ballari City.
| 15 |
Author(s):
Mahima M Naik .
Page No : 1-5
|
Sovereign Green Bonds and India’s Climate Finance Strategy: An Empirical Assessment of Pricing, Demand, and Comparative Positioning
Abstract
India's Sovereign Green Bond (SGrB) programme, launched in January 2023, was designed to serve three purposes at once: to lower the government's own cost of borrowing through a pricing discount known as the greenium, to widen the base of climate-conscious investors, and to signal institutional credibility on climate commitments to international markets. This paper offers an empirical, data-grounded assessment of how far the programme has achieved these aims over its first three years of operation, drawing on Reserve Bank of India auction records, market commentary, and a comparative review of four other emerging-market sovereign issuers: Chile, Indonesia, Nigeria, and Poland. The analysis finds that India's greenium has been inconsistent rather than dependable: an early positive differential gave way to a confirmed negative greenium of 9 basis points at the August 2024 auction, meaning the government paid a premium rather than a discount to issue green. Investor demand, measured through subscription ratios, has also weakened over time, from 4.11 times the notified amount at the debut auction to close to parity by mid-2024. Placed alongside Chile, Indonesia, and Nigeria, India's cumulative issuance covers under 1 per cent of its own annual climate finance requirement, a smaller share than Chile's, though larger than Nigeria's. The paper concludes that SGrBs have, so far, functioned more effectively as an instrument of institutional signalling and market development than as a reliable source of cost savings, and it sets out specific, data-supported recommendations for improving reporting transparency, deepening the domestic investor base, and scaling issuance.
Keywords: Sovereign Green Bonds, Greenium, Climate Finance, India, Reserve Bank of India, Comparative Analysis, Sustainable Finance
| 16 |
Author(s):
Vasundhara Saluja, Dr Vibha Kapoor.
Page No : 1-5
|
Accessing the millennial mass consumer demand for Khadi
Abstract
"Sustainability" has been a popular word these days; people the world over has realized the need to produce and consume responsibly. Fashion businesses are not behind, often discussing the concepts of recycling, reuse, repair, rent, environmentally friendly fabrics, and many more, which are sold as environmental lifesavers. As sustainable fashion shows gain mainstream attention and designers experiment with sustainable production processes, Khadi has also gained popularity as a sustainable fabric. Not just government initiatives have been leveraged to the fabric of freedom, but a few Indian textile makers have also taken up the initiative to adopt Khadi clusters and produce more of it. The aim is to revive Khadi, the fabric that once symbolized freedom, as it may be losing its relevance today. Though the statistical figures for KVIC and luxury designers using Khadi show a rise in sales, they are still far behind the numbers needed to catch up with the sales of any fast fashion product, nor is it a common choice for millennials. This research aims to understand modern-day mass consumers' perceptions of the fabric. A survey will be conducted to understand the preferences so that the fashion makers can use it as a business opportunity.
Keywords: Khadi, Mass market, Millennials, Consumer Perception
| 17 |
Author(s):
Shrinivas Shinde.
Page No : 1-5
|
EV Charging Slot Booking System Using Java
Abstract
The rapid growth of electric vehicles (EVs) has created an urgent need for reliable and efficient charging infrastructure. Existing EV charging stations face challenges such as long wait times, uncoordinated slot scheduling, and uneven distribution of charging resources, particularly during peak hours. This paper proposes an Online EV Charging Slot Booking System developed using Java, designed to streamline and automate the slot booking process. The system provides real-time slot availability, location-based station discovery using the Haversine formula, OTP-secured payment verification, and role-based interfaces for users, station owners, and administrators. A cloud-based MySQL database ensures centralized data management and prevents double-booking. Implemented with a Java backend framework, the system integrates geolocation APIs and a responsive web interface to deliver a seamless user experience. Experimental evaluation demonstrates significant improvements in station utilization, reduced waiting times, and enhanced user satisfaction. The modular architecture supports future integration with IoT devices, dynamic pricing, and smart grid technologies.
| 18 |
Author(s):
Shubham Singh.
Page No : 1-5
|
Adaptive Terrain Memory Navigation: A Modular Fail-Safe for Unmanned Aerial Vehicles in Satellite-Navigation-Denied Environments
Abstract
Tactical unmanned aerial vehicles (UAVs) rely almost exclusively on GPS and a radio-control (RC) link for navigation and recovery. Either link can fail independently — through deliberate jamming or spoofing, terrain and weather blockage, or physical damage to the receiver hardware — and a UAV with no independent means of localisation typically drifts, strikes terrain, and is destroyed in the resulting fall. This paper presents Adaptive Terrain Memory Navigation (ATMN), a fail-safe safety system rather than a primary navigation system. Its LiDAR and Simultaneous Localisation and Mapping (SLAM) stack run continuously in the background throughout the sortie, building a terrain map and tracking the UAV's position, but this output does not participate in flight control while GPS and RC remain available. Navigation authority passes to ATMN the instant either GPS or RC signal is lost, without waiting for both to fail together, and reverts automatically once both are confirmed restored. On engagement, ATMN holds the aircraft within its self-built terrain map and retraces the last known safe corridor, preventing the uncontrolled descent that would otherwise destroy the airframe. It is built as a modular, platform-agnostic add-on connecting through the standard MAVLink payload interface, requiring no modification to the host airframe or flight-control software. We present the system architecture, an either-link trigger logic, a nine-item bill of materials totalling 462.6 g and 20.7 W at a cost of approximately ₹1.6 lakh per unit, detailed power and weight budget calculations against a publicly specified commercial hexacopter platform, and a comparative evaluation against alternative approaches.
| 19 |
Author(s):
Ashraf Ali, Priyank Srivastava, Lalit Jain.
Page No : 1-5
|
Harmonic Mitigation in Nonlinear Load Systems Using D-STATCOM
Abstract
Nonlinear loads such as adjustable speed drives, rectifiers, and power electronic converters inject significant harmonic currents into the power system, degrading power quality and causing excessive Total Harmonic Distortion (THD). This paper presents a simulation-based performance analysis of a Distribution Static Compensator (D-STATCOM) for harmonic mitigation under nonlinear load conditions. A MATLAB/Simulink model is developed to evaluate the system with and without the D-STATCOM. Without compensation, the voltage and current THD is observed to be approximately 27.21%, which is far above the limit recommended by IEEE Std. 519. With the D-STATCOM connected, the THD is reduced to approximately 7.58%, and the source current waveform becomes near-sinusoidal. The results demonstrate that the proposed D-STATCOM effectively mitigates harmonics and improves power quality, and directions for further improvement toward full standard compliance are discussed.
| 20 |
Author(s):
A.V. Bokare.
Page No : 1-5
|
Performance Evaluation of K-Type Thermocouple-Based Temperature Measurement Using ESP32
Abstract
This paper describes the experimental testing of a temperature measurement system that uses a K-type thermocouple and an ESP32 microcontroller. The experimental setup was designed to measure temperatures ranging from 25°C to 600°C, with a laboratory furnace serving as the heat source. The K-type thermocouple was connected to the ESP32 via a MAX6675 converter, which translates thermocouple signals into digital data. The temperature readings were then displayed on the ESP32 Serial Monitor. To assess the accuracy of the system, the temperature values recorded by the ESP32-based system were compared to those from a standard reference meter at various temperature points. The collected data were examined to evaluate how closely the measurements from the system matched the reference values. The findings indicate that the readings from the ESP32-based system closely align with those from the standard meter across the tested temperature range. This comparison confirms that the integration of a K-type thermocouple with the ESP32 provides consistent and dependable temperature readings. The developed system serves as an affordable option for laboratory temperature monitoring and has potential for expansion into real-time monitoring, data recording, and IoT-enabled high-temperature measurement applications.
| 21 |
Author(s):
Sukeshni Moon.
Page No : 1-5
|
Comprehensive Literature Review: Artificial Intelligence and Corporate Culture
Abstract
Artificial intelligence has fundamentally transformed how organizations operate, learn, and compete in the modern business environment. Rather than functioning as merely a technological implementation challenge, AI adoption represents a profound cultural and organizational shift that touches every aspect of corporate operations [1]. The relationship between artificial intelligence and corporate culture is multifaceted and reciprocal while organizations must reshape their cultures to effectively leverage AI capabilities, simultaneously, AI technologies are reshaping workplace norms, beliefs, and behaviors [1].
As AI becomes increasingly embedded within organizational frameworks, executives face a critical decision: develop a digital knowledge-powered culture to harness AI's potential, or risk losing competitive advantage in an AI-centric economy [2]. The evidence consistently demonstrates that effective AI implementation requires planning, ethics, and fundamental alignment between technology and corporate culture [3]. This alignment extends across multiple organizational levels from individual roles and group dynamics to organizational strategy and market positioning requiring systematic attention to how AI reshapes jobs, enhances collaboration, and transforms corporate decision-making processes [4].
| 22 |
Author(s):
Nikita Katti.
Page No : 1-5
|
Impact of Robotic Process Automation on Cost Reduction and Process Accuracy
Abstract
Robotic Process Automation (RPA) has become an important approach to automating repetitive, rule-based and high-volume business activities across modern organizations. This study examines how RPA contributes specifically to cost reduction and process accuracy, two outcomes that strongly influence the business case for automation. The paper adopts a structured literature-review approach and synthesizes findings from peer-reviewed studies and research reports on RPA, business process automation and organizational implementation. The review indicates that RPA can reduce operational costs by lowering manual effort, shortening processing time, increasing throughput and supporting continuous execution of standardized tasks. The literature also indicates that software bots can improve process accuracy by executing predefined rules consistently and reducing errors associated with repetitive manual data entry and transfer. However, these benefits are not automatic. Poorly selected processes, unstable applications, weak governance, inadequate exception handling and insufficient change management can reduce or even offset the expected value. The study therefore proposes that organizations evaluate RPA using a combined cost-and-accuracy framework rather than treating automation only as a headcount-reduction initiative. The findings provide practical guidance for managers seeking to prioritize RPA opportunities and establish measurable performance indicators.
Key Words: Robotic Process Automation, cost reduction, process accuracy, operational efficiency, business process automation, digital transformation
| 23 |
Author(s):
Naresh Ganesh Botalawar.
Page No : 1-5
|
Wireless charging road system for electric vehicles
Abstract
This paper presents a Wireless Charging Road System for Electric Vehicles based on Dynamic Wireless Power Transfer (DWPT) technology to overcome the limitations of conventional stationary charging infrastructure. The proposed system uses segmented transmitter coils embedded beneath the road pavement, an 85 kHz SiC MOSFET high-frequency inverter, and a vehicle-mounted receiver consisting of a DD-geometry coil, synchronous rectifier, and DC-DC converter connected to the vehicle battery management system. A real-time Vehicle-to-Infrastructure (V2I) communication and control system manages vehicle identification, coil segment activation, power negotiation, and safety monitoring. Foreign Object Detection (FOD) and Living Object Protection (LOP) systems provide additional safety during operation. The prototype achieved 92.4% coil-to-coil efficiency and 83.6% end-to-end grid-to-battery efficiency on a 200-metre test corridor at vehicle speeds of 30–120 km/h. The system enables continuous charging while the vehicle is moving, helping to reduce range anxiety and potentially reducing the required battery capacity by 40–60%.
| 24 |
Author(s):
G S RANGASWAMY.
Page No : 1-6
|
Impact of Automation on Operational Efficiency in Fund Accounting Processes at State Street Corporation: Mediating Role of Process Integration and Moderating Role of Digital Transformation
Abstract
Abstract— Global custodian banks operate fund accounting functions that process trillions of dollars in daily net asset value calculations, reconciliations, and regulatory reporting, making operational efficiency in this function a direct driver of cost, risk, and client trust. State Street Corporation, which reported approximately $53.8 trillion in assets under custody and administration and around 52,000 employees across more than 100 markets at the end of 2025, exemplifies the scale at which fund accounting automation decisions play out. Industry surveys indicate that automation adoption in financial-services back offices remains uneven: while a majority of institutions have begun deploying robotic process automation and workflow tools, many finance leaders report that only a modest share of their processes are actually automated end-to-end, and technology-transformation programmes at asset managers and custodians have been associated with efficiency gains of roughly 30 percent when implemented as integrated, firm-wide initiatives rather than isolated tools. This proposed study develops and operationalises a research model in which Automation affects Operational Efficiency in fund accounting both directly and indirectly through Process Integration, with the strength of this relationship contingent on the organisation's Digital Transformation maturity. Grounded in the Resource-Based View, Dynamic Capabilities Theory, and the Technology-Organization-Environment framework, the paper develops five hypotheses, a four-construct measurement model, and a nine-step PLS-SEM based analysis plan for testing the proposed moderated-mediation model using primary survey data from fund accounting, operations, and technology professionals. The paper is intended as a replicable, publication-ready research design rather than a report of completed fieldwork, and it identifies the data-collection and measurement steps required before the model can be estimated.
Keywords: automation, operational efficiency, fund accounting, process integration, digital transformation, robotic process automation, custodian banks, PLS-SEM.
| 25 |
Author(s):
Diwakar H G.
Page No : 1-6
|
Crowdfunding Platforms in India: Regulatory Gaps and Innovations
Abstract
India's crowdfunding ecosystem is experiencing remarkable growth, driven by digital penetration, smartphone adoption, and a burgeoning entrepreneurial culture. Platforms such as Ketto, Milaap, Wishberry, and Fuel A Dream have mobilized billions of rupees for causes ranging from medical emergencies and disaster relief to creative arts and early-stage startups. Yet crowdfunding in India operates in a regulatory environment that straddles securities law, digital lending regulation, data protection law, foreign exchange management, banking regulation, and consumer protection, without a unified framework governing its operations. This paper examines the structural landscape of crowdfunding in India as it stands at the close of 2025, the critical regulatory gaps that expose investors, donors, and platform operators to significant risks, and the innovations that industry stakeholders have pioneered to self-regulate and build trust. The study adopts an exploratory mixed-methods research design, combining a structured quantitative survey of 150 retail investors, 40 NGO operators, and 20 platform compliance officers with semi-structured qualitative interviews, analysed using descriptive and inferential statistics (including a Chi-Square test of independence) alongside thematic analysis. Drawing on this primary evidence, recent legislative developments — including the RBI's Digital Lending Guidelines and the Digital Personal Data Protection Act, 2023 — and comparative international frameworks, the study underscores the urgent need for a dedicated regulatory architecture that fosters innovation while safeguarding all participants
| 26 |
Author(s):
Sandhiya R.
Page No : 1-6
|
AI-Driven Smart Agriculture: An Integrated Approach for Soil Analysis, Irrigation and Crop-Fertilizer Recommendation
Abstract
The proposed system is an IoT-based smart agriculture monitoring and automation system designed to improve crop productivity, optimize water usage, and enable real-time decision-making. Traditional farming methods rely on manual monitoring and fixed irrigation schedules, leading to water wastage and inefficient resource utilization. To overcome these issues, the system integrates sensors, automation, and cloud-based monitoring into a single solution. Environmental sensors such as soil moisture, temperature, and humidity continuously monitor field conditions. The collected data is processed by a microcontroller, which compares values with predefined thresholds and automatically controls irrigation systems like pumps and valves. This ensures optimal water usage and reduces manual effort. For communication, Wi-Fi modules such as ESP8266/ESP32 transmit data to cloud platforms like ThingSpeak, where it is stored, analyzed, and visualized as graphs, allowing farmers to monitor fields remotely through mobile devices or computers. The system also provides alerts and remote control features, enabling quick action during abnormal conditions. Overall, the system is cost-effective, scalable, and energy-efficient, improving productivity while conserving water and supporting sustainable smart farming practices.
| 27 |
Author(s):
Nandish Gali.
Page No : 1-6
|
Effect of psychological toll of constant emotional engagement in digital spaces towards consumer loyalty
Abstract
Digital platforms have become central to how brands sustain relationships with consumers, using constant notifications, personalised content and emotionally charged messaging to hold attention across social media, apps and loyalty ecosystems. While this sustained emotional engagement is designed to strengthen brand attachment, it can also impose a psychological toll on consumers in the form of digital fatigue, social comparison pressure, engagement overload and perceived inauthenticity. This study examines how the psychological toll of constant emotional engagement in digital spaces affects consumer loyalty, with reference to consumers who interact with the digital and social media platforms of Shri Renuka Industries. We examine digital emotional fatigue, social comparison and validation pressure, engagement and notification overload, and perceived authenticity erosion as dimensions of psychological toll that influence consumer loyalty. Data was collected using a structured questionnaire administered to consumers who actively follow or engage with the company's digital platforms and analysed using statistical methods. The results show that all four dimensions of psychological toll exert a significant negative influence on consumer loyalty, with digital emotional fatigue emerging as the strongest predictor. The study contributes to the growing literature on digital marketing fatigue and relationship marketing, and offers managerial insights for organisations seeking to sustain consumer loyalty while moderating the emotional demands of digital engagement strategies
| 28 |
Author(s):
Jeeva G.
Page No : 1-6
|
Effectiveness of Collaborative Models and Governance Mechanisms Between AI and Human in Supply Chain Management
Abstract
Digital platforms have become central to how brands sustain relationships with consumers, using constant notifications, personalised content and emotionally charged messaging to hold attention across social media, apps and loyalty ecosystems. While this sustained emotional engagement is designed to strengthen brand attachment, it can also impose a psychological toll on consumers in the form of digital fatigue, social comparison pressure, engagement overload and perceived inauthenticity. This study examines how the psychological toll of constant emotional engagement in digital spaces affects consumer loyalty, with reference to consumers who interact with the digital and social media platforms of Shri Renuka Industries. We examine digital emotional fatigue, social comparison and validation pressure, engagement and notification overload, and perceived authenticity erosion as dimensions of psychological toll that influence consumer loyalty. Data was collected using a structured questionnaire administered to consumers who actively follow or engage with the company's digital platforms and analysed using statistical methods. The results show that all four dimensions of psychological toll exert a significant negative influence on consumer loyalty, with digital emotional fatigue emerging as the strongest predictor. The study contributes to the growing literature on digital marketing fatigue and relationship marketing, and offers managerial insights for organisations seeking to sustain consumer loyalty while moderating the emotional demands of digital engagement strategies.
| 29 |
Author(s):
karthik.
Page No : 1-6
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Impact of Inventory Management Practices on Sales Performance of Industrial Products in a Manufacturing Company
Abstract
Digital platforms have become central to how brands sustain relationships with consumers, using constant notifications, personalised content and emotionally charged messaging to hold attention across social media, apps and loyalty ecosystems. While this sustained emotional engagement is designed to strengthen brand attachment, it can also impose a psychological toll on consumers in the form of digital fatigue, social comparison pressure, engagement overload and perceived inauthenticity. This study examines how the psychological toll of constant emotional engagement in digital spaces affects sales performance, with reference to consumers who interact with the digital and social media platforms of the Manufacturing Company. We examine digital emotional fatigue, social comparison and validation pressure, engagement and notification overload, and perceived authenticity erosion as dimensions of psychological toll that influence sales performance. Data was collected using a structured questionnaire administered to consumers who actively follow or engage with the company's digital platforms and analysed using statistical methods. The results show that all four dimensions of psychological toll exert a significant negative influence on sales performance, with digital emotional fatigue emerging as the strongest predictor. The study contributes to the growing literature on digital marketing fatigue and relationship marketing, and offers managerial insights for organisations seeking to sustain sales performance while moderating the emotional demands of digital engagement strategies.
| 30 |
Author(s):
J S Vikas.
Page No : 1-6
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A Study on the Impact of AI-Driven KYC Verification on Customer Onboarding Efficiency in Digital Payment Platforms
Abstract
India's financial inclusion journey has been reshaped by the convergence of banks, non-banking financial companies (NBFCs), and FinTech startups, supported by public digital infrastructure such as UPI, Aadhaar, the Account Aggregator framework, and the Open Credit Enablement Network (OCEN). While policy-level progress is well documented, comparatively little empirical work captures how ordinary customers perceive these collaborative arrangements. This study examines customer perception of collaborative FinTech services and their contribution to financial inclusion, with specific attention to trust, accessibility, and technology adoption. A descriptive, quantitative research design was adopted, using a structured questionnaire administered to 150 respondents selected through convenience sampling across urban and semi-urban locations in Karnataka. Data were analysed using frequency distributions, percentage analysis, and a chi-square test of independence to examine the association between exposure to collaborative FinTech models and perceived financial inclusion. The results indicate that respondents view bank-NBFC-startup collaboration favourably, particularly for digital lending and payment accessibility, though trust and rural reach remain comparative weak points. The chi-square analysis supports rejection of the null hypothesis, indicating a statistically significant relationship between collaborative FinTech adoption and perceived financial inclusion. The paper concludes with practical suggestions for banks, regulators, and FinTech firms seeking to deepen inclusive finance in India.
Key Words: FinTech collaboration, financial inclusion, NBFCs, digital lending, customer perception, UPI ecosystem.
| 31 |
Author(s):
Shivprashant Jatav, Ruchika Saini and Sumit Kumar Rai .
Page No : 1-6
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Finite Element Dynamic Modeling and Experimental Validation of a Ball-Bearing-Supported Rotor System Using Line Body Elements in ANSYS Workbench
Abstract
Rotodynamic analysis plays a critical role in evaluating the structural integrity and operational stability of high-speed turbomachinery. Traditional finite element (FE) modelling often employs computationally intensive three-dimensional solid elements, which significantly increase degree-of-freedom count and processing overhead. This study presents a streamlined yet highly accurate finite element modelling framework for a single disc, ball-bearing-supported rotor system using one-dimensional line body elements in ANSYS Workbench. The shaft continuum is discretized using Timoshenko beam elements (BEAM188) incorporating shear deformation, rotary inertia, gyroscopic coupling, and distributed material damping. Concentrated disc inertia is represented using zero-dimensional point mass elements (MASS21), while flexible bearing supports with direct radial and cross-coupled angular stiffness and damping are modelled via specialized spring damper elements (COMBI214) and custom APDL command scripts. Modal analysis is conducted under stationary and spinning conditions to identify natural frequencies, mode shapes, and critical whirl speeds via Campbell diagrams. Furthermore, forced vibration responses are evaluated in both frequency (harmonic analysis) and time domains (transient dynamic analysis) under rotating unbalance excitation (dynamic analysis) under rotating unbalance excitation (m=e 0.00157 kg⋅m m=e 0.00157 kg⋅m). Numerical). Numerical results demonstrate exceptional agreement with experimental benchmarks from literature, with natural frequency prediction errors remaining below 2.89% across all investigated modes and an identified first critical speed of 1416.2 RPM. Transient response profiles accurately capture the steady-state vibration amplitudes and orbital trajectories across varied rotational speeds (700 RPM, 910 RPM, and 1200 RPM). The proposed line-element methodology drastically reduces computational complexity while maintaining high fidelity, offering an efficient framework for industrial rotodynamic design, model updating, and diagnostic assessment. results demonstrate exceptional agreement with experimental benchmarks from literature, with natural frequency prediction errors remaining below 2.89% across all investigated modes and an identified first critical speed of 1416.2 RPM. Transient response profiles accurately capture the steady-state vibration amplitudes and orbital trajectories across varied rotational speeds (700 RPM, 910 RPM, and 1200 RPM). The proposed line-element methodology drastically reduces computational complexity while maintaining high fidelity, offering an efficient
framework for industrial rotodynamic design, model updating, and diagnostic assessment.
| 32 |
Author(s):
RADHIKA.
Page No : 1-6
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A STUDY ON FINANCIAL WELL BEING AND INVESTMENT BEHAVIOUR OF GEN Z INVESTORS
Abstract
The research is concerned with the financi al health and investment behavior of Gener ation Z (Gen Z) investors in India. Currentl y, a lot of teenagers use social media for sa ving and investing their funds. This researc h aims at understanding social influences o n young people investment behaviorit also explores their relationship with money.The study is based on primary data collected fr om 210 Gen Z respondents in the Ballari re gion of Karnataka using a structured Googl e Forms questionnaire. Sampling convenie nce is used to collect information. Most pe ople are investing now, they save regularly for their expenses; they plan monthly bud gets and set targets prior to investing. Fami ly members, friends, social media and fina nce experts affect them while investing. N evertheless, some people like making inves tments according to their own research and choice. It is also found that there is an ass ociation between investment interest and fi nancial health.This research concludes wit h an improvement of people’s understanding of money management and investment habits among young adults (Gen z) to improve their economic well being over time. T he results might help students, educational institutions, banks, and financial organizations to promote financial literacy among young investors.
| 33 |
Author(s):
Dikshita Soni .
Page No : 1-6
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Exploring defence style in management students: A DS-40 based study with special reference to BITM MBA students
Abstract
ABSTRACT:
This study explores the defense styles of MBA students at BITM using the Defense Style Questionnaire (DSQ-40) developed by Andrews, Singh, and Bond (1993). Defense mechanisms are unconscious psychological processes that help individuals manage stress, anxiety, and emotional conflicts. The study examines the prevalence of mature, neurotic, and immature defense styles and analyses differences based on demographic factors such as gender and year of study. Understanding these defense styles provides insights into students' emotional adjustment, resilience, and readiness for managerial roles. The findings are expected to support the development of effective counselling, mentoring, and student well-being programs in management education.
| 34 |
Author(s):
A santhoshi.
Page No : 1-6
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CORPORATE RELATIONSHIP MANAGEMENT AND ITS EFFECT ON ORGANIZATIONAL PERFORMANCE
Abstract
Relationship Management among Corporations plays an important role in fostering good relations
between corporations and other corporations taking into consideration the corporate relationships. The
aim of the study is to examine the impact of CRM in relation to the performance of the corporation,
particularly in relation to training and placement.The study was carried out at IPCS Global LLP, an
organization for skill development and training which offers technical education, certification, placement
support, and corporate training. There has been significant growth in the skill development sector in India
because of technological advancement and the increasing need for skilled professionals. Corporate
relations are very important for successful placements and the growth of organizations in the industry
| 35 |
Author(s):
Rahul Hansda , Ruchi Gaur.
Page No : 1-6
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A User-Centred Approach to Trust, Sizing Confidence, and Checkout Usability in Fashion E-Commerce
Abstract
Purpose — This study explores the user needs and experience challenges associated with discovering, evaluating, and purchasing fashion online, focusing on Gen Z and Millennial shoppers. It examines product discovery, sizing and fit confidence, trust, checkout friction, sustainability signalling, and responsive, accessible design. Based on these insights, it proposes a user-centred approach to designing a more trustworthy, editorial, and low-friction fashion e-commerce experience, developed through the design of a live platform, Marzena.
Design/methodology/approach — A user-centred design (UCD) approach structured around the Double-Diamond model was adopted. Secondary research into Gen Z and Millennial fashion behaviour was combined with a competitive audit of leading fashion platforms. The findings informed personas, empathy and journey maps, information architecture, user flows, a component-driven design system, low- to high-fidelity screens, an interactive prototype, and moderated usability testing focused on the checkout flow.
Findings — Users experience friction across product discovery, fit and sizing confidence, trust, and most acutely checkout. They value editorial, content-first discovery, transparent pricing, immersive product media, a short and clear mobile checkout, and credible sustainability cues. Reducing checkout steps and surfacing trust signals emerged as the highest-impact design opportunities.
Practical implications — The study demonstrates how user research and a reusable design system can inform fashion platforms that simplify discovery, comparison, and purchase while remaining consistent, responsive, and accessible.
Originality/value — The study contributes an editorial-first, checkout-focused, user-centred perspective to fashion e-commerce, translating consumer needs into concrete design decisions and positioning trust, sustainability signalling, and responsive accessibility as core considerations.
| 36 |
Author(s):
Manoj B. Maurya, Nitin K. Dhote.
Page No : 1-6
|
MPPT in Solar Photovoltaic Systems with AI Modules for Partial Shading Conditions
Abstract
This paper introduces an AI-driven MPPT framework designed to address real-time power optimization challenges caused by PSCs. The system consists of five interconnected modules: contextual hierarchical transfer graph embedding (CHTGE) is used for transfer learning across various environmental conditions through policy graphs based on shading history and weather context. The spatio-temporal feature attention-based indexing (STFAI) module aids in detecting transient phenomena by using attention maps that are temporally synchronized and derived from real-time multimodal sensor data. In the third module, differential contextual residual optimization (DCRO) corrects inaccuracies and achieves rapid stabilization by applying residual corrections in highly variable environments. Outputs from conventional MPPT methods are enhanced with multi-agent decision fusion using quantum-inspired adaptive logic (MADF-QAL). Evolution-based causal disentanglement networks (ECDN) offer fault localization and explainability through latent representation. The proposed framework offers an interpretable, resilient, and intelligent MPPT control suitable for real-world operating conditions.
| 37 |
Author(s):
Soumili Maitra.
Page No : 1-7
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Determinants of Airport Passenger Satisfaction: A PLS-SEM Approach Using ASQ Survey Data from Sixteen Major Indian Airports
Abstract
The aviation industry has transformed into a highly competitive, service-oriented sector where passenger satisfaction serves as a vital indicator of operational excellence and financial viability.1 Beyond reputation, satisfaction directly drives commercial performance; industry data suggests a 1% improvement in global passenger satisfaction correlates with a 1.5% increase in non-aeronautical revenue.1 This study investigates the determinants of satisfaction across sixteen Airports Authority of India (AAI) airports using Partial Least Squares Structural Equation Modelling (PLS-SEM) based on 2025 Airport Service Quality (ASQ) Departure Survey data.1 The ASQ program, developed and administered by the Airports Council International (ACI), is a globally recognized passenger service benchmarking tool that provides standardized measures of passenger satisfaction directly at the day of service.1 The survey evaluates 31 specific service parameters alongside one overall affect, representing Overall Satisfaction.1 Initial structural iterations revealed severe multicollinearity among primary customer contact points, inducing suppression effects and theoretically inconsistent negative path coefficients. To resolve this, a reflective-reflective hierarchical component model (HCM) is proposed as a theoretical solution.
The empirical structural model evaluated using 2025 data successfully explains 65.1% of the variance in overall passenger satisfaction (R² = 0.651). The analysis identifies Security Screening (SS) (β = 0.911, p < 0.001) and Throughout the Airport (TTA) (β = 0.678, p < 0.001) as the primary positive drivers of satisfaction, while highlighting severe multicollinearity and suppression effects resulting in negative path coefficients for Check-In (β = –0.588), Shopping/Dining (β = –0.719), and Ease of Access (β = –0.360). These findings offer an empirically validated roadmap for airport managers to prioritize digital infrastructure and streamline terminal processing to maximize non-aeronautical revenue.
| 38 |
Author(s):
D Mehraj.
Page No : 1-7
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The Study of Changing workplace culture in Gen Z in Banking sector
Abstract
The banking sector is undergoing a significant cultural shift with the growing presence of Generation Z employees, who bring distinct expectations around flexibility, transparency, purpose, and work-life balance. However, banks often struggle to align traditional organizational practices with these evolving expectations, leading to gaps in employee satisfaction and engagement. This study examines the changing workplace culture and its impact on Gen Z employees in the banking sector using a descriptive research design. Primary data were collected from 100 Gen Z bank employees through a structured questionnaire. The findings indicate that flexible work arrangements, transparent communication, and participative leadership are the most valued cultural shifts, while inconsistent policy implementation and limited authenticity in wellbeing initiatives remain key challenges. The study highlights the importance of adaptive, inclusive HR practices in improving job satisfaction, engagement, and retention among Gen Z employees in the banking sector.
| 39 |
Author(s):
Dr. Zulkharnain Mohammad.
Page No : 1-7
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Latest Research Techniques for Developing Non-Enzymatic Electrochemical Sensors
Abstract
Non-enzymatic electrochemical sensors have emerged as a transformative technology for real-time detection of biomolecules, offering superior stability, cost-effectiveness, and operational simplicity compared to traditional enzymatic sensors. This comprehensive review examines the latest research techniques (2023–2025) in developing non-enzymatic electrochemical sensors, with emphasis on advanced nanomaterial strategies, fabrication methodologies, and signal transduction mechanisms. Recent innovations include transition metal oxide nanocomposites, carbon-based nanomaterials, metal-organic frameworks (MOFs), and hybrid nanostructures that demonstrate exceptional electrocatalytic activity. State-of-the-art sensors achieve detection limits in the picomolar to micromolar range with sensitivities exceeding 10,000 μA mM⁻¹ cm⁻² for glucose detection. This paper systematically analyzes electrode materials, synthesis techniques, performance metrics, and emerging challenges in translating laboratory prototypes to clinical and point-of-care applications. The review provides critical insights into structure-performance relationships and identifies future research directions for next-generation non-enzymatic sensors.
| 40 |
Author(s):
Sandhya Lagade.
Page No : 1-7
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Secure Multi-Node Automotive Monitoring and Control System Using CAN FD Communication Protocol
Abstract
Modern automobiles rely on multiple Electronic Control Units (ECUs) for monitoring, control, safety, and automation functions. Efficient and secure communication among these ECUs is essential for reliable vehicle operation. Conventional Controller Area Network (CAN) systems suffer from limitations such as restricted payload capacity, lack of built-in security, vulnerability to unauthorized node access, and limited scalability. This paper presents a Secure Multi-Node Automotive Monitoring and Control System using CAN with Flexible Data Rate (CANFD) communication protocol. The proposed system employs a distributed ECU architecture with four intelligent nodes: (1) Cabin Temperature & Cooling Fan Control, (2) Oil Monitoring (temperature and level), (3) Rain Detection & Smart Lighting, and (4) Security Monitoring (gas concentration and door status). A Master ECU supervises the entire system and implements Hash-based Message Authentication Code (HMAC) with SHA-1 algorithm for secure node authentication. The system is implemented using Arduino Uno controllers, MCP2518FD CANFD modules, and various sensors including DS18B20, MQ7, rain sensor, LDR, and magnetic door sensors. Experimental results demonstrate reliable CANFD communication, successful node authentication, real-time monitoring, intelligent automation, and enhanced security capabilities. The distributed architecture reduces computational load on the central controller while improving system scalability, reliability, and modularity for modern automotive applications.
| 41 |
Author(s):
Nawang Thinlas , Ruchi Gaur .
Page No : 1-7
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Visual Modernity and Operational Speed in POS Interfaces
Abstract
Abstract
Purpose – This study examines how a restaurant point-of-sale (POS) interface can be modernised without sacrificing the operating speed that restaurant staff depend on during peak service. It addresses a tension that surfaced repeatedly during a benchmark of leading platforms: the products that look most contemporary are not always the ones that bill fastest, and the products that bill fastest often look dated.
Design/methodology/approach – A benchmark-led design approach was adopted. Three established platforms were studied from official sources and verified review material: Petpooja and Posist/Restroworks in the Indian market, and Square for Restaurants as an international design reference. Findings were restricted to what could be confirmed from source material, with unverifiable interface details excluded rather than assumed. The verified patterns were translated into design principles, an information architecture, three user flows, and three competing wireframe directions for the order-taking screen.
Findings – Six patterns were shared across all three platforms: speed as the primary selling point, touch-first controls with large targets, single-screen or minimal-navigation layouts, colour used functionally rather than decoratively, offline capability, and companion applications for tableside ordering and kitchen display. The three wireframe directions produced a measurable trade-off between menu visibility and ticket stability, which is documented rather than resolved by assertion.
Practical implications – The study offers a method for design work carried out under restricted access to both end users and the live product, a common constraint in short industry engagements. It also demonstrates the value of documenting competing layout directions with explicit trade-offs rather than presenting a single solution as settled.
Originality/value – Most writing on POS design attends to the customer-facing transaction. This study addresses the staff-facing interface, where the operator is a trained repeat user working at speed. It also treats aggregator integration, specifically Swiggy and Zomato order handling, as a first-class design problem rather than an afterthought.
| 42 |
Author(s):
Sharmila De, Ruchi Gaur.
Page No : 1-7
|
Designing an HR Webpage to Streamline Inquiries and Information Access
Abstract
Purpose – This study outlines the development of a user-centric webpage for the Human Resource Development (HRD) department at a premier Mini Ratna public sector enterprise. The primary objective was to reduce the high volume of telephonic inquiries regarding internships by providing a dedicated, self-serve digital information hub, while simultaneously centralizing the training calendar for current employees.
Design/methodology/approach – A comprehensive UI/UX design process was utilized, beginning with information architecture to logically organize internship details and internal training schedules. The interface was developed in Figma. The design prioritized clear content cards and responsive adaptation to ensure the information was easily accessible across mobile, tablet, and desktop devices.
Findings – The study demonstrates that strategically migrating frequently requested information into a highly accessible digital format effectively addresses administrative bottlenecks. By creating a clear visual hierarchy for internship guidelines and training dates, the HR department can confidently redirect repetitive phone inquiries to the webpage.
Practical implications – The project resulted in a fully responsive, high-fidelity prototype accompanied by comprehensive developer handoff documentation. This digital asset provides the enterprise with a practical solution to minimize manual inquiry handling, freeing up administrative time while proactively informing prospective interns and current staff.
Originality/value – This research highlights how targeted user experience interventions can solve specific, real-world communication challenges within a major public sector enterprise.
| 43 |
Author(s):
Rupesh Chandrasen Londhe.
Page No : 1-8
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Catalysts for SDG Attainment: Validating the IIC Pathway in Indian Higher Education
Abstract
Higher Education Institutions (HEIs) are increasingly recognized as pivotal actors in advancing the United Nations Sustainable Development Goals (SDGs). In India, the Ministry of Education’s Innovation Cell (MIC) established Institution’s Innovation Councils (IICs) to embed innovation and entrepreneurship education into academic ecosystems. Yet, empirical evidence on how IIC functions translate into SDG aligned outcomes remains limited. This study addresses that gap by adopting an explanatory sequential mixed methods design. Quantitative content analysis of IIC activity reports (2022–2024) and Yukti NIR (Nation Innovation Repository) submissions was complemented by qualitative interviews with IIC presidents, faculty coordinators, student innovators, and industry mentors. Results reveal that IIC activities cluster around five stages—ecosystem creation, capacity building, solution development, validation & scaling, and impact recognition—collectively forming the IIC Pathway Model. Case examples include a low cost water purifier (SDG 3, SDG 6, SDG 11), a solar micro grid startup (SDG 7, SDG 13), and sustainable product ventures (SDG 8, SDG 9). The model demonstrates how structured innovation processes operationalize SDGs at the institutional level.
| 44 |
Author(s):
Sushant Puramwar .
Page No : 1-8
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Plant Disease Prediction System Using Deep Learning and Image Analysis
Abstract
Plant diseases pose a significant threat to agricultural productivity, causing substantial economic losses and food security challenges worldwide. Traditional disease identification relies on manual visual inspection, which is time-consuming, subjective, and often inaccessible to small-scale farmers. This paper presents an automated Plant Disease Prediction System utilizing deep learning techniques for disease identification from leaf images. The proposed system employs the MobileNetV2 architecture pre-trained on ImageNet, fine-tuned for classification of tomato and potato leaf diseases. The model was trained and evaluated on the PlantVillage dataset, comprising images of healthy and diseased leaves across multiple disease categories. The system achieves 90.47\% classification accuracy with a precision of 91.18\% and provides a user-friendly web interface for disease diagnosis. Experimental results demonstrate the effectiveness of the proposed approach in enabling rapid, accurate, and accessible plant disease detection, contributing to sustainable agricultural practices and improved crop management.
| 45 |
Author(s):
Rahul N.
Page No : 1-8
|
Consumer Perception of Voice Search Marketing and Its Impact on Online Shopping Decisions
Abstract
Voice assistants have reached a large share of Indian smartphone users, and a substantial marketing literature now treats voice search as the next major channel for online retail. The behaviour of consumers has been slower to cooperate. This study examines how consumers perceive voice search marketing and how those perceptions translate, or fail to translate, into online shopping decisions. A structured survey of 412 online shoppers measured seven perception constructs, voice search usage intensity and the influence of voice on purchase decisions, alongside the specific shopping tasks for which voice is actually used. Reliability was acceptable throughout, with Cronbach's alpha between 0.725 and 0.852. Usage falls away sharply as tasks move from information towards transaction: 49.0 per cent of respondents had asked a general product question by voice, 35.7 per cent had used it to find a nearby store, 19.7 per cent to re-order a familiar item and only 4.6 per cent had ever completed a purchase end to end by voice. A hierarchical regression explained 38.6 per cent of variance in purchase decision influence. Trust in voice-delivered results carried the largest standardised coefficient at 0.224, closely followed by perceived usefulness at 0.221 and perceived accuracy at 0.218, with usage intensity contributing 0.196. Perceived ease of use had no independent effect at all. Bootstrap mediation confirmed a significant but partial indirect path from usefulness through usage to purchase influence, accounting for 19.1 per cent of the total effect. Cluster analysis identified three segments, with a voice-led group of 19.9 per cent generating almost all the transactional behaviour observed. The study argues that voice search should be treated as a discovery and reassurance channel rather than a transaction channel, and that marketing investment should follow the tasks consumers actually delegate to voice.
| 46 |
Author(s):
Dr. Gopal Chand.
Page No : 1-8
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KEY DRIVERS OF OVERALL PASSENGER SATISFACTION IN AIRPORT SERVICE QUALITY (ASQ) SURVEY AT AAI MAJOR AIRPORTS.
Abstract
This study investigates the principal determinants of overall passenger satisfaction at 14 major airports operated by the Airports Authority of India (AAI), using the Airport Service Quality (ASQ) survey framework developed by the Airports Council International (ACI). The ASQ survey measures 31 service quality parameters across eight thematic dimensions, with an additional 32nd parameter capturing overall satisfaction. Quarterly data for 2024 (Q1–Q4) from 14 airports were analyzed using Pearson correlation analysis to identify which parameters and thematic groups exert the strongest influence on overall satisfaction scores.
The findings reveal that Staff Service Quality is the most critical determinant of overall satisfaction (r = 0.73, p < 0.001), followed by Airport Environment & Comfort (r = 0.62) and Security & Check-in Process (r = 0.58). At the individual parameter level, the courtesy and helpfulness of shopping/dining staff, airport staff in general, and health safety perceptions emerge as the top three predictors. Airports such as Goa (GOI) and Chennai (MAA) consistently achieved the highest overall satisfaction scores, while Srinagar (SXR) exhibited the most significant performance gap. These findings offer actionable, evidence-based insights for airport operators to prioritize service improvement initiatives that yield the greatest impact on passenger satisfaction.
Keywords: Airport Service Quality, ASQ, ACI, Passenger Satisfaction, AAI Airports, Pearson Correlation, Service Quality Dimensions
| 47 |
Author(s):
Dasari Manasa.
Page No : 1-8
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AN EMPIRICAL ANALYSIS OF EMPLOYEE RETENTION STRATEGIES IN INDIAN CORPORATE ORGANIZATIONS
Abstract
Employee retention has become a critical concern for organizations operating in today's competitive and rapidly changing business environment. The ability to retain skilled and experienced employees is essential for maintaining organizational productivity, reducing recruitment costs, and sustaining long-term business performance. Frequent employee turnover leads to increased hiring and training expenses, disruption of business operations, and the loss of valuable organizational knowledge. Consequently, organizations are increasingly focusing on implementing effective employee retention strategies that promote employee satisfaction, commitment, and loyalty.
The present study aims to examine the effectiveness of employee retention strategies adopted by Indian corporate organizations and to analyze their influence on employees' intention to remain with their organizations. The research follows a quantitative approach based on primary data collected through a structured questionnaire administered to employees working in various corporate organizations. The study considers major retention factors such as compensation and benefits, career development opportunities, work-life balance, employee recognition, leadership support, training and development, and organizational culture. Statistical techniques including descriptive statistics, correlation analysis, and multiple regression analysis were employed to examine the relationships among the study variables.
The findings indicate that organizations implementing comprehensive employee retention practices experience higher levels of employee satisfaction, stronger organizational commitment, and lower turnover intentions. Among the various retention strategies, career development opportunities, supportive leadership, employee recognition, and a positive organizational culture emerged as the most influential determinants of employee retention. The study concludes that organizations should adopt integrated human resource practices that combine financial and non-financial incentives to create a motivated and committed workforce. The findings offer valuable insights for HR professionals, corporate managers, and policymakers in designing employee-centric retention strategies that contribute to organizational sustainability and long-term success.
Keywords: Employee Retention, Human Resource Management, Employee Turnover, Organizational Commitment, Job Satisfaction, Corporate Organizations
| 48 |
Author(s):
Gayatri Harikrishna Udawant.
Page No : 1-8
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Smart Attendance System Using Face Recognition
Abstract
The Smart Attendance System using Face Recognition is a computer-vision-based solution developed to automate attendance marking through a laptop camera. The project addresses common difficulties associated with manual registers, identification cards, and touch-based biometric methods, including time consumption, human errors, duplicate entries, and proxy attendance. The implemented system is developed in Python and uses OpenCV and a face-recognition library to process live video. Facial images of authorized users are registered first and converted into numerical facial encodings. During operation, frames from the laptop camera are resized for faster processing, faces are detected, and the resulting encodings are compared with stored encodings using Euclidean Distance. When a valid match is obtained, the attendance module records the recognized name with the current date and time in an Excel sheet and checks previous entries to avoid duplicate marking. Testing of the working model showed successful face detection and recognition under normal operating conditions, responsive live processing after image downscaling, and immediate digital attendance updating. The prototype therefore demonstrates a practical, contactless, and low-additional-hardware approach for attendance management in educational and organizational environments.
Key Words: Face recognition, smart attendance, computer vision, facial encoding, Euclidean Distance, OpenCV.
| 49 |
Author(s):
RAJARAJESWARI K.
Page No : 1-8
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Beyond Automation: Reimagining Marketing Management Through Human–AI Collaboration
Abstract
The rapid advancement of Artificial Intelligence (AI) is transforming marketing management by enhancing data-driven decision-making, customer insights, and strategic planning. While AI has demonstrated remarkable capabilities in processing vast amounts of market information and generating predictive insights, effective marketing decisions continue to rely on human expertise, creativity, ethical judgment, and contextual understanding. Consequently, the concept of Human–AI Collaboration has emerged as a strategic approach that combines the analytical capabilities of AI with human intuition and managerial experience to improve marketing effectiveness. Despite growing interest in AI-enabled marketing, existing studies primarily focus on AI adoption and automation, with limited attention given to the collaborative relationship between humans and AI in marketing decision-making.
This study proposes a conceptual framework to examine the influence of Human–AI Collaboration on Marketing Performance through the mediating roles of Marketing Agility and Decision Quality. Drawing on Dynamic Capability Theory and Socio-Technical Systems Theory, the study argues that collaborative intelligence enables organizations to respond more effectively to dynamic market conditions, improve strategic decision-making, and achieve superior marketing outcomes. The proposed framework also suggests that AI Literacy may strengthen the effectiveness of Human–AI Collaboration by enabling marketers to interpret and utilize AI-generated insights more efficiently.The study contributes to the marketing management literature by extending the understanding of collaborative intelligence beyond AI adoption and emphasizing the complementary roles of humans and AI in organizational decision-making. The proposed framework offers practical implications for marketing managers seeking to integrate AI technologies while preserving human creativity and strategic judgment. Furthermore, it provides a foundation for future empirical research examining Human–AI Collaboration as a critical capability for sustainable marketing performance in the era of intelligent technologies.
Keywords: Human–AI Collaboration, Marketing Decision-Making, Marketing Agility,Decision Quality,Marketing Performance,Collaborative Intelligence.
| 50 |
Author(s):
DIVYANSHI AGRAHARI , Ruchi Gaur.
Page No : 1-8
|
Rethinking Home Tutoring Through User Experience
Abstract
Purpose – The main aim of this study is to explore user needs and experience challenges associated with finding and selecting home tutors through digital platforms. The study focuses particularly on trust, tutor verification, safety, affordability, flexible scheduling, tutor–student matching, and progress tracking from the perspectives of parents and students. Based on these insights, the study proposes a user-centred approach to designing a more accessible and trustworthy home tutoring experience.
Design/methodology/approach – A user-centred design approach was adopted. Qualitative insights were gathered through interviews with potential users to understand their experiences, concerns, expectations, and difficulties in finding and managing home tutors. A competitive audit of existing tutoring platforms was also undertaken to identify gaps in usability, tutor verification, reviews, communication, payment, progress tracking, and tutor matching. The findings informed the development of personas, empathy maps, user journeys, user stories, information architecture, user flows, and an interactive prototype.
Findings – The findings indicate that users experience difficulties in identifying qualified and trustworthy tutors and have concerns regarding safety, privacy, unclear pricing, unreliable reviews, and poor tutor–student matching. Users also expressed the need for flexible scheduling, transparent information, easy communication, demo classes, and progress updates.
Practical implications – The study demonstrates how user research can inform the design of digital tutoring platforms that simplify tutor discovery, comparison, booking, communication, and learning management.
Originality/value – The study contributes a user-centred perspective to digital home tutoring by bringing together the experiences of parents and students and translating their needs into a proposed UX solution. It highlights trust, personalization, and usability as important considerations in designing more effective digital home tutoring experiences.
| 51 |
Author(s):
Dr. Srilatha Toomula, Dr. G. Sabitha.
Page No : 1-8
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Impact of Artificial Intelligence in Precision Agriculture: Insights from Farmer Surveys and Secondary Market Analysis
Abstract
Precision agriculture has developed as an important technique for solving global food security concerns while also improving environmental sustainability, resource conservation, and economic prosperity. Precision farming is a scalable and sustainable method to improving agricultural resilience and productivity through data-driven farm management, as agricultural systems confront increasing pressures from population increase, climate change, and depleting natural resources. The incorporation of Artificial Intelligence (AI) into precision agriculture has hastened the shift to intelligent and sustainable farming systems. AI-powered solutions provide real-time monitoring, predictive analytics, and automated decision-making, which improves agricultural efficiency and reduces waste. Among these innovations, smart irrigation systems utilize soil moisture sensors, weather forecasting models, and IoT-enabled monitoring devices to optimize water application, resulting in improved water-use efficiency and enhanced crop productivity. Similarly, unmanned aerial vehicles (UAVs), commonly known as agricultural drones, have become indispensable tools for crop surveillance, disease detection, nutrient assessment, weed identification, and precision pesticide application, enabling farmers to monitor field conditions with high spatial and temporal resolution. This study investigates the role of Artificial Intelligence (AI) in promoting sustainable agricultural practices through precision farming technologies.
Specifically, it examines the adoption of AI-enabled smart irrigation systems and various categories of agricultural drones used for field monitoring, crop health assessment, and resource management. The empirical research is based on 116 primary survey responses from farmers from various sections of Telangana State, providing information about their awareness, adoption, and perceptions of AI-driven precision agriculture. To validate and contextualize these findings, the study compares primary survey responses to secondary market data from 2023 acquired from Market.us. Exploratory Data Analysis (EDA) is used to compare AI-driven precision agriculture against conventional farming approaches. EDA provides a strong analytical framework for detecting hidden patterns, trends, anomalies, and correlations in both primary and secondary datasets. By combining farmer-level data with industry market figures, the study provides a thorough knowledge of AI adoption, field variability, and resource use.
The findings promote evidence-based decision-making, increase operational efficiency, and highlight AI technology' promise for promoting sustainable, resilient, and data-driven agricultural production systems.
Keywords: Precision Farming, Artificial Intelligence, Exploratory Data Analysis, Analytics
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Author(s):
Ankita Kumari, Ruchi Gaur.
Page No : 1-8
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Human-Centred Design and Evaluation of a Low-Cost Smart Cane for Independent Mobility of Visually Impaired Users
Abstract
Independent mobility is an important aspect of daily life for visually impaired people. The conventional white cane helps users identify obstacles through physical contact, but it provides limited warning about obstacles before they are reached. This study presents the design and evaluation of a low-cost smart cane developed to provide early obstacle awareness through ultrasonic sensing and haptic feedback.
The study follows a human-centred design approach, with emphasis on usability, accessibility, safety, and ease of interaction. The proposed prototype uses an Arduino Uno with ultrasonic sensors to detect obstacles and provides alerts through vibration, supported by an LED indicator. The design process included problem identification, concept development, hardware selection, circuit design, prototyping, programming, structural development, assembly, and real-world testing. Initial testing was carried out with different stationary and moving objects to examine obstacle detection and to adjust the sensitivity of the system and reduce unnecessary alerts.
The study further proposes user-based evaluation to understand how effectively users can interpret the haptic feedback and how the device supports their perceived safety, confidence, and independent mobility. Rather than focusing only on the technical functioning of the device, the study considers the interaction between the user and the assistive technology.
The research aims to identify the strengths and limitations of a low-cost smart cane and provide design recommendations for improving its usability and practical application. The study contributes to the growing field of assistive technology by exploring how simple sensing and haptic feedback can be integrated into a familiar mobility aid to provide additional support for visually impaired users.
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Author(s):
Charvi Sharma, Samiti Gupta, Navrose Virk, Ruchi Gaur.
Page No : 1-8
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A Study on the Impact of Parking System on Customer Satisfaction and Patronage
Abstract
Parking is an important part of the overall shopping experience, yet it is often treated as a secondary facility in mall planning and management. With the increasing use of private vehicles, customers frequently face problems such as limited parking availability, long waiting times, congestion, unclear parking systems, high parking charges, and difficulty in locating vacant spaces, particularly during weekends and peak hours. These issues can create frustration before customers even enter the mall and may influence their overall satisfaction and willingness to return. This study explores the relationship between mall parking facilities, customer satisfaction, and customer patronage, with a focus on understanding how parking experiences influence visitors’ perceptions and behaviour.
The study adopts a design-oriented approach to understand parking as part of the overall customer journey rather than only as a functional infrastructure problem. Primary data will be collected through a structured questionnaire from mall visitors who use parking facilities. The study will examine key factors including parking availability, ease of finding a space, waiting time, parking charges, accessibility, safety, cleanliness, signage, and overall convenience. Customer feedback and existing research on parking management and customer satisfaction will be analysed to identify recurring pain points and opportunities for improvement. A user-centred perspective will be used to understand the needs, expectations, and difficulties experienced by customers throughout the parking process.
The study is expected to highlight how the quality of parking facilities can influence customers’ overall experience and their intention to revisit a mall. A convenient, safe, and well-managed parking system can reduce stress and contribute positively to customer satisfaction, while inadequate parking and inefficient management may discourage repeat visits and affect patronage. From a practical perspective, the findings can help mall managers and designers identify specific parking-related issues and develop more user-centered solutions. Improvements such as clearer wayfinding and signage, better space allocation, efficient parking management systems, improved accessibility, and greater transparency in parking charges can make the parking experience more convenient. The study therefore aims to demonstrate that parking should be considered an integral part of mall experience design and not merely as a supporting facility.
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Author(s):
Shoba HN.
Page No : 1-9
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The Data Paradox in Human Resource Management: Examining the Impact of Employee Data Availability and Information Overload on HR Decision-Making Quality
Abstract
Human Resource Management is becoming increasingly
data-driven as organizations rely on digital HR systems,
HR analytics, and employee information to support
decision-making. While the availability of employee data
can improve the quality of HR decisions, excessive
information may create challenges such as information
overload, making it difficult for HR professionals to
identify relevant insights. This phenomenon is referred to
as the Data Paradox.
The present study examines the impact of Employee Data
Availability and Information Overload on HR Decision
Making Quality. A quantitative research approach was
adopted, and primary data were collected through a
structured questionnaire from 150 respondents. The
collected data were analyzed using descriptive statistics,
reliability analysis, correlation, and regression analysis to
examine the relationships among the study variables.
The findings are expected to provide insights into how
organizations can effectively manage employee data
while minimizing information overload to improve HR
decision-making. The study emphasizes that the quality
of HR decisions depends not only on the availability of
data but also on the ability to manage and interpret
information effectively.
Keywords: Human Resource Management, Employee
Data Availability, Information Overload, HR Analytics,
HR Decision-Making Quality, Data-Driven HRM.
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Author(s):
Preshita Raut¹, Tusharkumar Sangada², Sucheta Karande².
Page No : 1-9
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Phytochemical Profiling of Ficus religiosa Using Solvent Extractions with Antimicrobial Assay and Antioxidant Analysis
Abstract
Ficus religiosa (L.) Roxb.,the Peepal tree, a large and evergreen medicinal plant of the sacred fig family, has many therapeutic uses in traditional medicine. In the present investigation, we conducted a qualitative and quantitative phytochemical profile of F. religiosa leaf extracts and determined the in vitro antibacterial, antifungal, and antioxidant activities of the extracts, thus providing a scientific basis for its ethnomedicinal use. Sequential extractions of both the Leaf and Stem were performed with polar solvents in following order: distilled water, followed by methanol, chloroform and ethyl acetate for 4 h each. Results: Qualitative screening detected high amounts of tannins and phenols, especially in methanolic and aqueous extracts, whereas saponins, steroids, cardiac glycosides, terpenoids, and coumarins were also present. A marker for all solvents but concentrated, alkaloids, anthraquinones, and anthocyanins were also absent across the board. The total phenolic, tannin, and flavonoid contents, as determined by quantitative spectrophotometric analysis, were 8.68 mg/g (R² = 0.9443), 506 mg/g (R²=0.9817), and 47.8 mg/g, respectively (R²=0.9462). Antibacterial activity tested using the agar well diffusion method showed low inhibition zones (0.1–0.3 mm) only for the methanolic extracts of four bacterial strains, with Serratia marcescens being the most sensitive, followed by Pseudomonas putida, and Enterobacter cloacae. DMSO and methanol also showed antifungal activity against Aspergillus niger at 4 mm and 1 mm, respectively. Antioxidant activity (FRAP method) showed the highest absorbance at 60 µl concentration (O.D. = 0.604). Together, these findings highlight the potential of F. religiosa as an excellent source of bioactive compounds for pharmaceutical standardization and drug development.
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Author(s):
Sonam, Vasudha.
Page No : 1-9
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Artificial Intelligence and Creativity in UI/UX Design: A Review of Emerging Research
Abstract
The increasing adoption of Artificial Intelligence (AI) tools in UI/UX design has significantly transformed the design process, particularly in ideation, templates creation, prototyping and interface designing to development stage. AI tools also support visual creation, layout structuring, automation of repetitive tasks, and generation of multiple design variations within a short time. The long-term use of AI tools for design consideration on creativity, divergent thinking and originality remains insufficiently explored. This paper presents the literature review of examining the relationship between AI tools and creativity practice in UI UX design and how the use of AI tools affects the designers' skills. The reviews discuss studies related to generative AI, human AI collaboration, cognitive load on designers' skills, and creativity support systems. Findings from existing studies show that AI tools improve efficiency and provide multiple ideas, but at the same time concern remains regarding creativity, originality, and similar design outcomes. Studies also indicate that excessive reliance on AI tools may gradually weaken designers’ creative skills and independent design approaches. Based on the literature review, it highlights the importance of human and AI collaboration, but the future research focuses on creativity, cognitive engagement, and design practices in AI assisted environment. The findings further emphasize that AI should function as a supportive tool rather than a replacement for human creativity in UI/UX design practices.
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Author(s):
Jeremy Ponseelan J.
Page No : 1-9
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TINYML: BRINGING MACHINE LEARNING TO RESOURCE-CONSTRAINED EMBEDDED SYSTEMS
Abstract
Abstract:Tiny machine learning is an emerging approach that enables machine learning models to operate directly on resource-constrained embedded devices. This review aims to examine the principles, technologies, applications, challenges and future directions of machine learning on low-power embedded systems. A structured review of existing research was conducted by examining developments in embedded hardware, software frameworks, model optimisation techniques and application areas. Particular attention was given to quantisation, pruning, knowledge distillation and lightweight neural network architectures, which reduce memory requirements, computational complexity and energy consumption while maintaining useful prediction accuracy. The review also examines applications in healthcare, smart agriculture, environmental monitoring, industrial systems and wearable devices. The findings indicate that local machine learning inference can reduce communication requirements and processing delays while enabling intelligent decision-making on resource-constrained devices. However, limitations in memory, computational capability, energy availability, model accuracy and security continue to present significant challenges. Emerging approaches such as on-device learning, federated learning, energy harvesting and hardware–software co-design provide promising opportunities for addressing these limitations. Overall, the review demonstrates that machine learning on resource-constrained embedded systems has significant potential to transform conventional sensing devices into intelligent, low-power systems capable of real-time local decision-making.
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Author(s):
Megha Mallikarjun Patil.
Page No : 1-10
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From Reporting to Strategy: The Evolution of FP & A in Technology Enterprises
Abstract
Financial Planning and Analysis (FP&A) has moved from a compliance-oriented, backward-looking discipline into a forward-facing strategic capability, and nowhere is this shift more visible than in technology enterprises, where intangible assets, subscription-based revenue, rapid product cycles and volatile capital markets demand a different kind of finance function. This conceptual review traces that transformation across three dimensions: the structural drivers reshaping FP&A's mandate, the digital and analytical tools enabling the shift, and the organizational practices that embed finance as a business partner rather than a scorekeeper. Drawing on foundational management-control theory, the resource-based view of the firm, and contemporary industry research, the paper argues that FP&A's strategic value now rests on three interlocking capabilities: integrated planning that connects financial and operational data, analytically driven forecasting supported by automation and artificial intelligence, and continuous, KPI-based performance dialogue with the business. The review also examines the persistent obstacles to this transformation, including data fragmentation, talent gaps and governance risk, before outlining implications for finance leaders and directions for future research, including autonomous planning systems and the integration of non-financial and ESG metrics into core planning processes.
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Author(s):
Rabikanta Mahananda 1, Dr. Sarala Dasari 2, Priyanka Patra 3 .
Page No : 1-11
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Quantifying The Invisible Economic Loss: An Empirical Econometric Analysis of Socio-Cultural Barriers to Female Labor Force Underutilization in Western Odisha
Abstract
Quantifying the micro-foundations of gendered labour inefficiencies is critical for unlocking
sub-national development and optimizing regional female human capital allocation. This study
investigates the "Invisible Economic Loss" arising from socio-cultural bottlenecks that relegate
highly literate women to unpaid domestic labour within the Bijepur Block of Bargarh District
in Western Odisha. Utilizing primary field survey data and an Ordinary Least Squares (OLS)
multiple linear regression framework, the study model about the structural tension between
institutionalized barriers and mitigating assets. The econometric diagnostics yield exceptional
explanatory power (R2 = 0.950, F = 446.7), providing definitive empirical grounds to reject the
null hypothesis. The estimation reveals that family restrictions (𝛽1 = 30.85, p < 0.001$) and
rigid patriarchal norms (𝛽2 = 14.85, p < 0.001) operate as the dominant drivers of
macroeconomic leakage, while educational attainment and domestic autonomy serve as vital
insulating factors. Reclaiming this misallocated capital requires synchronized regional
infrastructure and community-led socio-cultural modernization.
Keywords: Invisible Economic Loss, Rural female skills Underutilization, OLS Regression,
Socio-Cultural Bottlenecks, Bijepur Block in Western Odisha.
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Author(s):
VIDHWAN GUNTOJU.
Page No : 1-12
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AI-DRIVEN ROAD DAMAGE ASSESSMENT USING DRONE-CAPTURED IMAGES AND DEEP LEARNING-BASED OBJECT DETECTION
Abstract
Timely detection of road-surface defects such as potholes, longitudinal cracks, alligator cracking, and patch repairs is essential
for keeping transportation networks safe and for planning cost-effective maintenance. Manual road surveys remain slow, expensive, and
place field personnel at risk, which motivates automated alternatives. This paper presents an AI-driven pipeline that pairs Unmanned Aerial
Vehicle (UAV) image acquisition with deep-learning-based object detection to identify and localize road damage without requiring an
inspector to walk or drive the surveyed stretch. Drone imagery is first passed through a preprocessing stage — resizing, contrast
normalization, and Gaussian-filter-based noise suppression — before being fed to a Convolutional Neural Network (CNN) detection
backbone. Successive members of the YOLO object-detection family, namely YOLOv4, YOLOv5, and a Transformer-Prediction-Head
variant of YOLOv5, were trained on a merged corpus built from the public RDD2022 road-damage dataset and a regional Spanish road
imagery collection, so that the resulting detector generalizes across differing pavement types, marking conventions, and camera geometries.
Afourth configuration, YOLOv7, was additionally evaluated to gauge how far continued progression within the YOLO family alone could
push detection accuracy. On a held-out test split, the detectors reached a mean Average Precision at an IoU threshold of 0.5 (mAP@0.5) of
26.8% for the YOLOv4 baseline, 59.9% for YOLOv5, 65.7% for the Transformer-augmented YOLOv5 variant, and 73.2% for YOLOv7,
indicating that both architecture progression and attention-based prediction heads improve localization of irregularly shaped defects such as
alligator cracks. The complete system is delivered as a Django web application with separate user and administrator roles, allowing non
technical maintenance staff to upload imagery, trigger detection, and review flagged damage on a dashboard, while administrators retrain
and monitor the underlying model. The results suggest that combining UAV-based data collection with modern anchor-based and
transformer-augmented detectors is a practical route toward continuous, low-cost, low-risk road-condition monitoring for municipal and
highway authorities.
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Author(s):
Sandhya Lagade.
Page No : 1-14
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Comprehensive Survey on CAN, CAN FD, and Automotive Security: Evolution, Challenges, and Future Directions
Abstract
The Controller Area Network (CAN) protocol has been the backbone of in-vehicle communication systems for over three decades. As modern vehicles evolve into highly connected cyber-physical systems with increased electronic content, advanced driver assistance capabilities, and connectivity features, automotive communication networks face unprecedented challenges related to bandwidth limitations, real-time performance, and cybersecurity threats. This comprehensive survey presents a systematic review of CAN protocol fundamentals, the evolution toward CAN with Flexible Data-Rate (CAN FD), automotive network security vulnerabilities, attack vectors, defense mechanisms, and emerging trends in secure automotive communication. The paper analyzes classical CAN architecture, frame structure, arbitration mechanisms, and error-handling capabilities. It examines CAN FD enhancements including increased payload capacity, dual bit-rate transmission, and backward compatibility considerations. A detailed investigation of automotive cybersecurity threats—including message injection, replay attacks, denial-of-service attacks, ECU spoofing, and remote exploitation—is presented along with cryptographic countermeasures, intrusion detection systems, secure gateways, and authentication protocols. The survey also explores standardization efforts including ISO 11898, SAE J1939, AUTOSAR security specifications, and emerging technologies such as Automotive Ethernet, Time-Sensitive Networking (TSN), and blockchain-based security frameworks. Critical analysis of over 30 research contributions reveals that while CAN FD addresses bandwidth limitations, comprehensive security solutions require multi-layered defense strategies combining authentication, encryption, anomaly detection, and secure software update mechanisms. Future research directions include lightweight cryptography for resource-constrained ECUs, machine-learning-based intrusion detection, quantum-resistant security protocols, and integration with Vehicle-to-Everything (V2X) communication infrastructure. This survey provides researchers, automotive engineers, and security practitioners with a consolidated understanding of state-of-the-art automotive communication technologies and security methodologies essential for designing next-generation secure connected vehicles.
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Author(s):
GAHAN K NAIK.
Page No : 1-18
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Ethical Issues in AI-Based Digital Marketing: A Corporate Social Responsibility (CSR) Perspective
Abstract
Artificial intelligence has transformed digital marketing by enabling automated personalization, audience targeting, and decision-making. While these technologies improve marketing efficiency, they also introduce ethical concerns such as privacy violations, opaque consent mechanisms, algorithmic bias, discriminatory targeting, manipulative interface design, and undisclosed AI-generated content. This study examines these challenges from a Corporate Social Responsibility (CSR) perspective and proposes an integrated governance framework using Explainable Artificial Intelligence (XAI) and machine learning to identify, predict, and mitigate ethical risks in AI-driven marketing campaigns. The study demonstrates that AI-assisted governance significantly improves ethical risk prediction and resource allocation compared to conventional compliance-based approaches. The proposed framework helps organizations strengthen transparency, accountability, fairness, and responsible marketing practices while enhancing stakeholder trust and long-term sustainability
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Author(s):
Rahul N.
Page No : 1-19
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Impact of Material Procurement and Inventory Management on Construction Project Efficiency at Design Space Architects and Hexagon Construction
Abstract
Materials absorb the largest single share of a construction project's cost, yet the procurement and inventory practices that govern them are still treated in many firms as a clerical function rather than a management one. This study examines how material procurement and inventory management affect project efficiency at two Bengaluru firms with deliberately contrasting operating models: Design Space Architects, a design-led practice that delivers through appointed contractors, and Hexagon Construction, a midsized contracting firm running its own sites and stores. Evidence was assembled from two sources: a structured survey of 168 staff across the two organisations covering five dimensions of practice, and a ledger of 312 completed material work packages carrying cost variance, schedule slippage, inventory holding and emergency-purchase data. Reliability was acceptable on every scale, with Cronbach's alpha between 0.829 and 0.878. Regression on perceived project efficiency explained 47.7 per cent of variance. Inventory control practice carried the largest standardised coefficient at 0.345, followed by supplier selection and evaluation at 0.247 and procurement planning at 0.161; material handling and wastage control contributed nothing once the other dimensions were held constant. The firm indicator was not significant, which means the observed efficiency gap between the two organisations was accounted for by their practices rather than by their type. Inventory holding days were essentially unrelated to schedule slippage, while emergency purchases correlated with it at 0.35, a pattern indicating that carrying more stock on site does not buy schedule protection. An ABC analysis found six categories carrying 71.3 per cent of annual spend, and a simulation redistributing an unchanged budget of control effort towards them reduced work packages overrunning by more than six per cent from 43.3 to 31.7 per cent. The study contributes firm-level evidence on which procurement and inventory practices actually move project efficiency, and which are merely conventional.
