| 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
|
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
|
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):
Sandeep Belidhe, Phani Monogya Katikireddi, Sandeep Kumar Dasa.
Page No : 1-5
|
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
| 8 |
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.
| 9 |
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.