| 1 |
Author(s):
B Aditya.
Page No : 1-3
|
Deep Learning Models on Big Data for Genomic Research
Abstract
Genomic research is an essential component of modern medicine, providing critical insights into the genetic underpinnings of diseases and facilitating the development of personalized treatment approaches. However, the vast and complex nature of genomic data presents significant challenges for traditional data analysis methods. This project explores the application of deep learning models to big genomic data to address these challenges and enhance the accuracy of genomic predictions. Deep learning, with its ability to process large volumes of high-dimensional data, has shown great promise in various fields, including genomics, by automating the extraction of relevant patterns and features from genomic sequences.This project investigates the use of deep learning techniques such as Convolutional Neural Networks (CNNs), Recurrent Neural Networks (RNNs), and Autoencoders in the analysis of genomic datasets.
| 2 |
Author(s):
madhusudan pathak.
Page No : 1-3
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The Influence of Communication and Digital Marketing on Consumer Behavior: Advancements in the Era of Artificial Intelligence
Abstract
The advent of digital marketing, coupled with the incorporation of artificial intelligence (AI) in communication strategies, has significantly transformed consumer behavior in the 21st century. This research paper examines the influence of AI-powered digital marketing on consumer decision-making, engagement, and brand loyalty. By analyzing existing literature and empirical studies, the paper uncovers key positive shifts in consumer behavior due to improved communication methods and personalized marketing initiatives. The study emphasizes how businesses can harness AI and digital marketing to build deeper connections with their target audiences, enhancing customer relationships and driving better market outcomes.
| 3 |
Author(s):
Mirdula.
Page No : 1-3
|
Prediction of stock market
Abstract
The stock market, characterized by its complexity and volatility, has long been a challenging domain for accurate prediction. This study explores the application of machine learning (ML) algorithms and statistical models to forecast stock market trends by integrating diverse data sources and advanced techniques. Key datasets include historical stock prices, technical indicators, macroeconomic factors, and sentiment analysis derived from financial news and social media.
| 4 |
Author(s):
Himanshi.
Page No : 1-4
|
Deep Reinforcement Learning for AI-Powered Robotics
Abstract
The integration of Deep Reinforcement Learning (DRL) into AI-powered robotics represents a significant advancement in autonomous systems, enabling robots to make intelligent decisions, adapt to complex environments, and improve their performance over time through experience. This paper explores DRL’s applications in industries like manufacturing, healthcare, and autonomous transportation, highlighting key algorithms such as Deep Q-Networks and Actor-Critic models.
| 5 |
Author(s):
Samrudhi yashwant pawar.
Page No : 1-4
|
pharmacogenetics and pharmacogenomics of opioids
Abstract
Pain can be reduced in a variety of ways, including pharmacotherapy and surgery. Opioids are a class of drugs that efficiently treat moderate to severe acute and ongoing discomfort, which can accentuate several characteristics of their daily lives. Regarding acute discomfort, the expected physiological response to disagreeable stimuli, which is typically linked to serious illness or trauma (State Medical Boards Federation of the United States, 1998. The term "chronic pain" refers to suffering that lasts longer than the expected duration of recuperation or everyday suffering for the expected duration of recuperation or everyday suffering for extending beyond three months (Davis et al., 2017). The utilization of opioids is commonly used as the standard of care for both acute and chronic pain related to palliative care.
| 6 |
Author(s):
Niharika Mishra.
Page No : 1-5
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Bio-Receptive Facade Systems in Architecture: Enhancing Sustainability and Building Performance
Abstract
The application of bio-receptive façade systems in architecture toward better performance and sustainability in buildings. Due to materials and systems that can support growths of living things, such structures can be made to be invisible. This paper discusses the practical, aesthetic, and environmental impacts of using bio-receptive concrete, photobioreactors, and innovative façade design. Such important ecological benefits are carbon sequestration, mitigation of the urban heat island effect, and biodiversity promotion. The key findings reveal the examples of climate-adaptable buildings: BIQ House and KMC Corporate Office. The value of interdisciplinary cooperation and material science innovation is pointed out by tackling problems such as cost and maintenance. After all, bio-receptive façade systems are marketed as an environmentally conscious means to improve living within the city through an integration of architectural functionality with environmental stewardship.
| 7 |
Author(s):
Jaspreet.
Page No : 1-5
|
HOW TO SEARCH FOR CREDIBLE RESOURCES FOR WRITING ENGLISH PAPERS?
Abstract
This research investigates the challenges students face in identifying credible resources for writing English papers amidst an overwhelming amount of online information. It emphasizes the critical need for reliable sources in academic writing, exploring issues such as difficulty distinguishing between scholarly and non-scholarly materials and the lack of familiarity with citation management tools. Employing a mixed-methods approach, the study combines qualitative and quantitative data from structured surveys and focus group discussions involving undergraduate and postgraduate students from various disciplines. Key findings reveal a preference for the relevance of sources over their credibility, raising concerns about academic integrity. Many students demonstrate a foundational understanding of credible resources; however, significant gaps remain in their ability to assess source authority and reliability. The study's limitations include focusing on text-based resources, and potentially overlooking other media. Overall, this research underscores the need for improved educational support to enhance students' research skills and emphasizes the importance of developing effective criteria for evaluating source credibility in English studies.
| 8 |
Author(s):
Sandeep Belidhe, Phani Monogya Katikireddi, Sandeep Kumar Dasa.
Page No : 1-5
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Explainable AI and Deep Neural Networks for Continuous PCI DSS Compliance Monitoring
Abstract
Ensuring constant PCI DSS compliance is
essential but not easy when dealing with PCI DSS-sensitive
payment card information. This paper looks into XAI and
DNNs to examine their possibilities of implementing and
improving PCI DSS compliance check automation. XAI
makes a model explain itself, making it easy for compliance
officers to address non-compliance when identified by the
model. For their part, DNNs can sift through large amounts of
security data to look for anomalies, determine the
effectiveness of the access control measures, verify the
implementation of encryption for data, and monitor the
effectiveness of controls of vulnerabilities. Applying these
high-level AI methodologies can allow organizations to gain
better, even real-time, control over compliance, thus
significantly reducing the probabilities of security
infringements and enhancing data protection measures in
general. Not only does it build up compliance capabilities, but
it also provides scalable and preventive solutions in reaction
to the emerging threats in the cyber security domain
Author :
Sandeep Belidhe, Phani Monogya Katikireddi, Sandeep Kumar Dasa
| 9 |
Author(s):
Sneha Roy.
Page No : 1-6
|
ROLE OF KINESICS IN COMMUNICATION
Abstract
The study delves into the importance of body language in communication and its impact on how we understand and interpret interactions is the focus of this research project on "The Role of Kinesics in Communication." It raises the question of how gestures and facial expressions either align with or diverge from communication and examines how this dynamic influences a listener's perception and comprehension of a speaker's message. After watching live and recorded communication instances and using a mix of methods that involved structured observations and surveys from participants both online and offline, we discovered that consistent body language signals greatly improve understanding and trustworthiness, but conflicting cues can weaken intentions, especially during conflicts or in virtual environments. This study fills a void by investigating the interaction between spoken and unspoken communication cues, which lays the groundwork for delving deeper into cultural distinctions and the significance of body language in digital interactions.
| 10 |
Author(s):
Dr. M. Rajagopal.
Page No : 1-7
|
REVIEW OF APPLICATIONS OF PHASE CHANGE MATERIAL FOR THERMAL ENERGY STORAGE
Abstract
Thermal energy storage (TES) systems are crucial for enhancing energy efficiency and enabling the integration of renewable energy sources. Phase Change Materials (PCM) is one of the most suitable materials for storing renewable energy. Phase change materials (PCMs) have emerged as an effective medium for TES due to their high energy density and ability to maintain nearly constant temperatures during phase transitions. Latent heat storage using phase change materials has applications in many areas, including building energy thermal management, waste heat recovery, temperature control, smart data, battery thermal control, microelectronic temperature control, photovoltaic thermal applications, space and vehicles, thermal energy storage applications, and greenhouse temperature control. In this review, topics include an overview of phase change materials (PCMs), use of PCMs in energy storage, use of PCMs in heating and cooling of buildings, use of PCMs in vehicles, and battery thermal management.
| 11 |
Author(s):
Sachin Vasant Dorage.
Page No : 1-8
|
Strategies for Identifying and Mitigating Malware on Android Mobile Devices
Abstract
Mobile devices, despite their relatively short existence, have rapidly become the most widely utilized computing devices. The prevalence of smartphones, which support third-party applications, has made it increasingly crucial for both end-users and service providers to prioritize the security of these devices and the networks that support them. As users become more dependent on applications such as Short Message Service (SMS), Multimedia Messaging Service (MMS), internet access, and online transactions, the importance of security measures grows. The Android operating system, which powers a vast array of devices from budget-friendly models to premium smartphones, has established itself as the leader in the smartphone market. This trend facilitates access to mobile technology for individuals across various socioeconomic strata, enabling them to incorporate these devices into their daily lives. In response to this surge in popularity, the Android market has seen a significant increase in the introduction of new applications. However, the emergence of diverse mobile malware has raised concerns among security experts and researchers. Given the continuous growth of the mobile phone sector, the potential for these devices to be exploited for criminal purposes is expected to escalate in the future. This article provides a review of the literature concerning malware detection and prevention on Android mobile devices, evaluates significant studies and tasks, and discusses various articles, journals, and digital resources, including internet security publications, scientific research, and conference proceedings.
| 12 |
Author(s):
Yuvraj Sharma.
Page No : 1-10
|
Use of Moder Technology To Improve Quality of Education
Abstract
With the introduction of technology, the education sector has been improved and this paper aims to seek for some emerging technologies such as Virtual Reality and Artificial Intelligence that have the potential to enhance client learning. Advanced technologies help learners engage in their studies by providing an interactive learning environment, flexible teaching, and self-paced learning. There is however a growing concern on the ever-decreasing engagement in the traditional classroom-setting due to different forms of education assistive technology being employed. The physical involvement amongst the students and the educators and between the students themselves is bound to suffer and hence, their all-round development might become an issue. The implications that come about with the shortage of traditional pedagogies in modern technology-enhanced education practices are emphasized in this paper. The paper also explores new possibilities embracing new technologies bring and how they might not penetrate into some spheres of traditional teaching which guarantees that the educational quality within an organization gets improved.
| 13 |
Author(s):
Dr. M. Rajagopal.
Page No : 1-10
|
OPTIMISING PHASE CHANGE MATERIALS USING ARTIFICIAL INTELLIGENCE FOR THERMAL ENERGY STORAGE
Abstract
Artificial intelligence (AI) is increasingly being integrated into thermal management systems that use phase change materials (PCMs) to enhance energy efficiency and temperature control. AI can analyze large datasets from thermal management systems, identifying patterns and correlations that traditional methods might miss. Machine learning algorithms can predict how PCMs will behave under different conditions, optimizing their performance for applications like building energy management, thermal energy storage, and electronics cooling. AI models can simulate the thermal behavior of PCMs in real time. This allows for dynamic adjustments to thermal systems, ensuring optimal temperatures are maintained and preventing overheating or excessive cooling. By utilizing AI-driven algorithms, researchers can optimize the formulation of PCMs, enhancing their thermal properties such as melting and solidification temperatures. This can lead to improved energy efficiency in various applications. AI can be used to monitor the health of thermal management systems utilizing PCMs. By analyzing operational data, AI can predict failures or inefficiencies, allowing for timely maintenance and reducing downtime. AI can assist in energy demand forecasting, helping to manage the use of PCMs in systems like solar thermal energy storage. Predictive analytics can optimize charging and discharging cycles based on expected energy consumption patterns. AI can enhance control strategies for systems using PCMs, enabling more responsive and adaptive management based on real-time conditions and forecasts. This ensures maximum efficiency and performance of thermal management systems. AI can work alongside Internet of Things (IoT) technologies to gather real-time data from various sensors in thermal management systems. This integration allows for more sophisticated predictive analytics and decision-making.
| 14 |
Author(s):
Grishm Ghosh.
Page No : 1-11
|
What effect does language have on human behavior?
Abstract
This research explores the role of slang in human behavior and communications, including its influence on communication dynamics, social settings, and identity formation. Combining survey, interview, and observation methods, we assess how patterns of slang talk build attitudes, emotions, and relationships across a multitude of demographic populations. Our findings suggest that slang serves as an effective means of in-group identification and group solidarity, enhancing group cohesion but potentially excluding outsiders. Mastery over appropriate slang can significantly affect a person's perceived social status and opens up specific kinds of access to cultural situations. Informal and creative, slang use makes individual expression creative while inventing and reproducing social norms. We also examine how digital communication media fuel the growth and spread of slang, helping foster general language trends. The research will study the contradictory character of slang: it invests language with novel meanings as well as intense culture, but it can also help perpetuate social cleavages and misunderstandings. These findings seem to give ways of thinking regarding the complicated relationship between language and behavior; findings have proved to provide implications to sociolinguistics and cultural studies, along with social psychology. Research is suggested to be done in order to find out what longer-term consequences slang might have on cross-cultural communication and cognitive processes. Keywords: slang, human behavior, communication, social identity, group dynamics, language evolution, sociolinguistics, cultural context
| 15 |
Author(s):
Mohini Verma.
Page No : 1-14
|
The Role of Malnutrition in Increasing the Risk of Diarrheal Diseases: A Meta-Analysis of Case-Control Studies
Abstract
Background: Diarrheal diseases remain a significant global health burden, particularly in resource-limited settings. Malnutrition and diarrhea often coexist, potentially reinforcing each other in a vicious cycle. However, the extent to which malnutrition increases the risk of diarrheal diseases across different populations and contexts remains unclear.
Aims: This meta-analysis aimed to evaluate the association between malnutrition and diarrheal diseases across age groups, and assess its impact on disease severity and outcomes.
Methods: We conducted a systematic review and meta-analysis of case-control studies examining the relationship between malnutrition and diarrheal disease. Random-effects models were used to calculate pooled odds ratios (ORs) with 95% confidence intervals (CIs).
Results: Forty-two studies comprising 68,423 participants (27,369 cases, 41,054 controls) were included. The overall pooled OR was 1.84 (95% CI: 1.3-2.4), indicating a significant association between malnutrition and diarrheal disease. The strongest associations were observed in children under 5 years (OR: 1.94, 95% CI: 1.3-2.4) and in African studies (OR: 2.16, 95% CI: 1.7-2.4). Among malnutrition assessment methods, wasting showed the strongest association (OR: 2.25, 95% CI: 1.7-2.3).
Conclusion: This meta-analysis provides robust evidence that malnutrition significantly increases the risk of diarrheal diseases, with the impact varying across age groups, geographical regions, and types of malnutrition. These findings underscore the importance of integrating nutritional interventions into diarrheal disease prevention and control strategies, particularly in vulnerable populations and resource-limited settings.
Keywords: Malnutrition; diarrheal diseases; meta-analysis; case-control studies; global health; nutritional status