| 1 |
Author(s):
Arivazhagan, Malini.
Page No :
|
Diabetics predictions
Abstract
Diabetes mellitus is a chronic heterogeneous metabolic disorder with complex pathogenesis. It is characterized by elevated blood glucose levels or hyperglycemia, which results from abnormalities in either insulin secretion or insulin action or both.
| 2 |
Author(s):
Ayush Bhandari, ApekshaKapadnis, Shashikala Patangade, Akash ZanjariDr. Mahesh Sanghavi.
Page No : 1-4
|
Centralised Dashboard For SNJB COE
Abstract
An increasingly important tool for many sectors, including education, is data analytics. the rapidly evolving market of today. Data analysis, and the interactive dashboards that result from it, have seen a significant increase in popularity in recent years. Dashboards are crucial for saving a significant amount of time for analysts and organizations due of their data representation, which is intuitive to the eye. This is made possible by presenting brief summaries in tables and reducing extensive information into graphs, which provide quick and comprehensive understanding of the current state of affairs. Additionally, these dashboards serve as incredibly useful instruments in the decision-making process, ensuring that decisions are made with great efficiency and knowledge.
Our innovative idea is focused on implementing an interactive dashboard at our esteemed college, Late Sau. K.B.J. College of Engineering, Chandwad, to monitor and optimize every aspect of administrative and academic activities. It has long been the responsibility of department heads and the principal to oversee the execution of various assignments and subsequently report these actions to higher authorities. To address this, we have put out a cutting-edge dashboard solution that goes beyond conventional reporting.
It allows users to explore summaries for a comprehensive and in-depth analysis of all the many aspects of our institution's operations in addition to presenting statistical data as graphs
| 3 |
Author(s):
Nitish Mehlawat.
Page No : 1-6
|
Protection of Rights of Unorganised Laborers in India
Abstract
The unorganised sector in India plays a significant role in the country's economic growth. However, this contribution often goes unnoticed due to the lack of statistical data and proper mechanisms for collecting it. According to estimates from the Union government, approximately 93% of India's total workforce is employed in the unorganised sector, which includes construction workers, beedi rollers, auto drivers, and housekeepers. Despite their significant contribution to the GDP, unorganised workers face numerous challenges, such as job insecurity, long work hours, hazardous working and living conditions, and more. This particularly affects women and children, making them the most vulnerable in these circumstances.
| 4 |
Author(s):
PRASHANT SEHRAWAT.
Page No : 1-7
|
Law Of Environment In India: Problems And Challenges In Its Enforcement
Abstract
While India boasts a plethora of environmental protection legislation, their enforcement has been notably lacking. There is a pressing need for the effective implementation of these laws, as mandated by the Constitution and other environmental statutes. The judiciary, alongside the National Green Tribunal (NGT), has played a commendable role in addressing this issue through creative and innovative interventions. Public Interest Litigations filed in the Supreme Court against industries and Pollution Control Boards have highlighted the necessity for stringent pollution control measures. To ensure the proper execution of these laws, it is imperative to establish adjudicatory bodies comprising both legal and technical experts in each state. Environmental stewardship is not solely the responsibility of the government; it is a collective duty encompassing individuals, associations,societies, industries, and corporations. Upholding environmental integrity aligns with the nation's sustainable development goals and is ingrained as a fundamental duty in Article 51-A(g) of the Indian Constitution.
| 5 |
Author(s):
Bhavana Sanjay Bhatkande .
Page No : 1-7
|
Women Safety Patrolling Robot Using IOT
Abstract
The increasing violence against women has made their safety a key worry everywhere in the world. They are used to being mistreated, either physically or mentally. Victims of workplace and public harassment are giving up on their dreams and ambitions. Despite the enactment of numerous anti-harassment laws by the government, the prevalence of harassment against women has not declined. The best way to lessen violence (robbery, sexual assault, domestic abuse, and so forth) against them is to provide amoral support. Consequently, the Women Safety Patrolling Robot will work to protect women. Current systems record events using CCTV cameras, but this is not a proactive approach for women's safety
| 6 |
Author(s):
AdeshJain1,AtharvaPedraj2,NehaKale3Prof.V.P.Sahane.
Page No : 1-7
|
Sign Analyse: The Hand that Speaks
Abstract
Signalyze is an innovative sign language recognition system designed to bridge the communication gap between deaf and mute individuals and the wider community. Utilizing advanced technologies in computer vision, machine learning, and natural language processing, Signalyze enables accurate interpretation and translation of sign language gestures into readable text and audible speech. The system incorporates a series of sophisticated modules, including video processing, hand detection, gesture classification, emotion detection, and contextual understanding, enhanced by the integration of BERT (Bidirectional Encoder Representations from Transformers) for nuanced language comprehension.
The core functionality begins with the user uploading a video of sign language gestures. The system processes the video to extract frames and detect hand movements using state-of-the-art computer vision techniques. These detected gestures are then classified into corresponding sign language words or phrases. Simultaneously, facial expressions are analyzed to detect emotions, adding an additional layer of contextual understanding. BERT is utilized to interpret the sequence of gestures and emotions, ensuring that the translation accurately reflects the intended meaning. The output is presented in both text and speech forms, providing a comprehensive and user-friendly communication tool.
Signalyze aims to enhance accessibility and inclusivity by empowering deaf and mute individuals to communicate more effectively in various settings, including education, healthcare, and social interactions. This project not only demonstrates the practical application of AI and NLP in solving real-world problems but also emphasizes the importance of technological innovations in promoting equality and inclusivity in communication.Indexterms:OpenCV,TensorFlow,LabelImg,Gesturerecognition.
| 7 |
Author(s):
Sharayu Chopade.
Page No : 1-8
|
SMS based device automation for physically challenged people
Abstract
Home automation has become increasingly popular due to the convenience it offers in accessing and controlling electrical appliances such as lighting systems, washing machines, and refrigerators. However, most of the existing home automation systems are limited by their range and can only be used within a specific area using Bluetooth technology, ZigBee technology, Infrared Remote (IR) controller, or Radio Frequency (RF) technology. This limitation poses a significant risk of electrical disasters and energy wastage when appliances are left on for extended periods. To address these issues, a GSM-based home automation system has been proposed in this paper. The system allows for remote control of electrical devices using SMS commands, making it a more efficient and safe method of controlling home appliances.
Keywords—GSM, loads, LCD, Arduino uno, hardware, software.
| 8 |
Author(s):
Vashitva Guleri, Vikram Rampurkar, Kiran Sonawane, Sujit Patil Pro. Vaibhav V Khond .
Page No : 1-8
|
Design and Development of Earth Tube Heat Exchangers
Abstract
Abstract - Now a days we all apprehensive of
the increasing price of electricity. So, everyone
is moving towards sustainable living. In this
case, Earth Tube Heat Exchanger is the suitable
choice for the HVAC installation. In domestic
structures large quantum of the electricity
needed for heating and cooling purpose. To
reduce the burden on the active system we've
moved e've moved towards a renewable source
of e energy. Earth Tube Heat Exchanger works.
on the basic sasic principles of a heat transfer
and uses geothermal energy as a source of
energy. This design presents the results of
theoretical computation and computer
simulations (analysis) of Earth Tube Heat
Exchanger. By this system, we can achieve full
and partial HVAC installations in the living area.
Analysis of the system is done by using Ansys
CFD analysis.
| 9 |
Author(s):
Mr. S.Venkat Reddy, Ms. Sreenivas Shilpa Shree .
Page No : 1-9
|
A Study On Online Trading with reference to India Infoline
Abstract
Using quantitative research, the study aims to discover trends in the following areas: trading volumes, frequency, and security types on the India Infoline platform. Furthermore, by shedding light on investors' motivations, challenges, and viewpoints on online trading, qualitative methods show how they handle risk and make judgments. The study looks at the legal frameworks and technological procedures that back up online trading platforms like India Infoline. Examining how technology may enhance security, user experience, and the capacity to execute transactions smoothly, it considers the legislative structure that governs online trading operations. This study aims to fill a gap in our understanding of the online trading ecosystem by integrating quantitative and qualitative data, specifically looking at India Infoline. Academics, market participants, and regulators could benefit from a greater understanding of the benefits and drawbacks of online trading if this study's findings are applicable.
| 10 |
Author(s):
Shital Kacharu Jadhav, Prof. M. S. Nimase.
Page No : 1-10
|
Stock Market Prediction Using Machine Learning Techniques
Abstract
The stock market is a very important activity
in the finance business. Its demand is
consistently growing. Stock market prediction
is the process of determining the future value
of company stock or other financial
instruments traded on a financial exchange.
For some decades Artificial Neural Network
(ANN), which is one intelligent data mining
technique has been used for Stock Price
Prediction. It has been trusted as the most
accurate consideration. This paper surveys
different machine learning models for stock
price prediction. We have trained the
available
stockdataofAmericanAirlinesforthisproject.Th
eprogramminglanguagethatwe have used in
this paper is Python. The Machine Learning
(ML) models used in this project are Decision
Tree (DT), Support Vector Regression (SVR),
Random Forest (RF),and ANN. The
datahereissplitinto70%fortrainingand30%fort
esting.The dataset contains stock data for the
last 5 years. From the simulation results, it is
shown that Random Forest performs better as
compared to others. Thus, it can be used in
the real-time implementation
| 11 |
Author(s):
Mrs. P. Nivedita , Ms. Dara Aarthi.
Page No : 1-11
|
A Study on Perspective of Insured towards Claims Management with reference to Zen Insurance
Abstract
The emphasis of Zen Insurance is on constant improvement, which is achieved via the use of feedback channels and ongoing evaluations of staff performance. To ensure it can react to changing market conditions and expanding consumer expectations, the firm asks both its staff and customers for their ideas. As a result of their dedication to transparency, innovation, and customer happiness, Zen Insurance has risen to the top of the insurance claims administration industry. Any insurance company that wants to improve its claims processing and overall performance may use this case study as a guide. In the insurance sector, efficient and effective claims processing is essential. It has an impact on operating expenses, customer happiness, and organizations' capacity to stay in business in the long run. This abstract explores the methods used by Zen Insurance to enhance their claims handling process, with the goal of providing policyholders with a fast, fair, and transparent settlement.
| 12 |
Author(s):
Sukriti Verma.
Page No : 1-11
|
Once Upon A Brand : Crafting Connections through Storytelling in Modern Marketing
Abstract
The power of “Once upon a time” is as powerful as ever in the field of marketing. By weaving creative and compelling narratives that resonate with the audience on a relatable level, brands can build lasting relationships with their consumers. In a world filled with millions of advertisements, the immemorial art of storytelling emerges as a light of authenticity and connection. This research paper dives into the transformative role of storytelling in modern marketing and crafting valuable connections.
The primary purpose of this research is to analyze the mechanisms through which storytelling enhances brand perception and loyalty. This paper aims to uncover the elements that make brand stories compelling and the impact these stories have on consumer behavior. Additionally, this research paper seeks to provide various insights for marketers on integrating storytelling into their strategies effectively.
The findings of this paper reveal that storytelling in marketing significantly boosts brand engagement and loyalty as well as does its part in crafting connections between the sellers and the buyers. Personalization, video storytelling, interactive features and user-generated content are storytelling techniques that drive sales and increase customer engagement.
| 13 |
Author(s):
Mr. Fasi Ur Rehman , Ms. Kasoju Lahari .
Page No : 1-12
|
A Study on Financial Statement Analysis with reference to GVK Power & Infrastructure Pvt Ltd
Abstract
This study aims to analyse GVK Power & Infrastructure Pvt Ltd's financial statements in order to provide light on the company's previous performance, stability, and future prospects. Management, investors, and stakeholders all rely on financial statement analysis to assess the company's financial health, identify trends, and make well-informed decisions. The financial statements covering a certain time period will be reviewed for this analysis. Many financial metrics and statistics, including the company's liquidity, profitability, solvency, and efficiency, may be found in these statements. The study also uses industry standards and comparative analysis to put GVK Power & Infrastructure's financial performance in context. In order to have a better understanding of the firm's SWOT (strengths, weaknesses, opportunities, and threats) in its competitive market environment, this comparison analysis might be useful. Additionally, the research explores the factors that influence GVK Power & Infrastructure's financial performance, such as market dynamics, regulatory environment, operational efficiency, and strategic objectives. Understanding these factors is critical for analysing the company's financial risks and opportunities.
| 14 |
Author(s):
Vikas Raskar,Aditya Khandare,Chandrapal Rokade.
Page No : 1-12
|
Transmission Line Fault Safety
Abstract
The stability and reliability of electrical power systems are essential for the seamless operation of modern societies, with transmission lines serving as the backbone of these systems by transporting electrical energy from power plants to consumers. However, these lines are prone to various faults, such as short circuits, open circuits, and ground faults, which can disrupt power supply and damage infrastructure. Efficient fault detection in transmission lines is thus crucial for maintaining continuous and safe power system operation. Traditional fault detection methods, like impedance-based detection and traveling wave analysis, have been extensively used but have limitations related to system changes and equipment requirements. Recent advancements in sensor technologies and communication systems have enabled more precise and real-time fault detection, while the integration of machine learning techniques has further enhanced fault detection capabilities. Machine learning algorithms can analyze large datasets to identify patterns and anomalies, continuously improving their accuracy and providing real-time fault classification and prediction. This paper reviews the strengths and limitations of traditional and machine learning-based fault detection methods, highlighting the potential of integrated systems. It also discusses the role of modern sensor and communication technologies in improving fault detection effectiveness. The evolution of fault detection techniques signifies a major advancement in ensuring power system stability and reliability, emphasizing the need for ongoing innovation to address the complexities of modern electrical networks.
| 15 |
Author(s):
Sultan Khaibar Safi.
Page No : 1-13
|
Empowering Deep Learning for Images: A Comparative Analysis of Regularization Techniques in CNNs
Abstract
- The remarkable success of Convolutional Neural Networks (CNNs) in image recognition and related tasks has been hampered by the ever-present challenge of overfitting and the pursuit of robust generalization performance. This article meticulously dissects and compares various regularization techniques specifically designed to empower deep learning for image tasks within the context of CNN architectures. We embark on a rigorous exploration of fundamental techniques like L1 and L2 regularization, delving into their theoretical foundations. We further unveil the intricacies of advanced methods such as Dropout, Data Augmentation, Early Stopping, and the synergistic approaches of Elastic Net and Group Lasso regularization. Through a meticulous examination, we unveil the theoretical underpinnings of these techniques, illuminate effective strategies for hyperparameter selection, and elucidate their profound impact on model complexity, weight sparsity, and ultimately, the network's ability to generalize effectively. To empirically validate these insights and solidify our comparative analysis, we conduct controlled experiments utilizing benchmark image datasets. This empirical validation process sheds light on the efficacy of each technique. By meticulously analyzing the trade-offs inherent in these diverse regularization approaches and their suitability for specific image data characteristics and CNN architectures, this article empowers researchers with a comprehensive understanding of these techniques. Armed with this knowledge, researchers can make informed decisions to optimize performance in deep learning tasks involving images, ultimately propelling the field towards ever-greater advancements.
| 16 |
Author(s):
Ishwarya M .
Page No : 1-17
|
Digital Twin Augmented Vision System For Healthcare
Abstract
The Project proposes real-time health data monitoring with Digital Twin with Augmented Vision for the ICU emergency treatment patients, suggesting that this symptom could be used as screening tool to help identify people with potential high-risk cases who could be recommended to treat immediately.
faster treatment in a hospital, it generates a scannable Augmented Vision (AV) code print. Also, the wearable bio-medical sensor data’s also uploading to server system by IoT. By our proposed system, every patient is being addressed by their unique DT based AV code with them.
Whenever people are admitted with severe problems in hospitals such as heart pain, lung problems etc. they will be provided with the AV code. Once admitted the wearable sensors will be deployed and the biomedical value will be sent to the IOT with their unique code. In among the many people in the treatment in the hospital, the senior as to inspect for the treatment in emergency manner to treat him faster and save their life.
The duty doctor will scan the AV code with all patients AV code using android app scanner available, immediately the DT vision Software System fetch the respective persons
data’s the DT vision Software System will show us the details in real-time images as shown in fig(1) and fig(2) for
normal datasets i.e. green DT images for normal stage of and Red DT images the
organ severe affected Persons with the IOT data sets respectively .
By
screening with this the doctor can identify the immediate treatment needed priority people in order, i.e. RED persons as immediate next for the orange DT images peoples and then can check for the greed DT images peoples. Such that doctor can save the life of the emergency patients in a sequence treatment order one by one.
| 17 |
Author(s):
K.Jeevitha .
Page No : 1-23
|
An interweb communication allowed fall observing escorted by health signs
Abstract
In fact, falls exponentially increase with age-related biological changes, which are leading
to a high incidence of falls and fall-related injuries in aging societies. In this context, assistive
devices that could help alleviate this major health problem are a social necessity. Most
traditional medical alert monitoring systems rely on a pendant or button that your loved one
must press in order to call for help. These systems are highly effective and save lives every day.
Some seniors, though, are at a higher risk of falling than others. There is the possibility that
when your loved one falls, they may be unable to press their medical alert button to call for
help.This is where automatic fall detection comes in. The benefits of automatic fall detection
for seniors can be great. Also, if you or your loved one has diabetes or another condition that
increases your risk of falling, this feature might provide you with additional peace of mind. The
accidents are determined with the help of a tilt sensor, a heartbeat sensor, and a temperature
sensor, and the data is displayed on a LCD display and monitored by the Blynk (Android)
application through IOT. If your loved one sustains an injury or becomes unconscious from a
fall and they are alone, their chance of getting help fast is increased significantly by automatic
fall detection technology.