International Journal of Integrative Studies (IJIS)
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Exploring the Role of Artificial Intelligence in Drug Discovery and Development
Get PDFThe pharmaceutical research industry has been revolutionized by the use of Artificial Intelligence (AI) at a very rapid rate since it accelerates the development of drugs, simplifies the lead identification process, and reduces the cost of development. Traditional drug discovery procedure is tedious, costly, and lacks high clinical trial success rates. AI technologies, i.e., machine learning (ML), deep learning (DL), natural language processing (NLP), and predictive modeling have become potent tools that are meant to defeat these limitations. Some of the applications of AI include target identification, prediction of molecular properties, virtual screening, de novo drug design, and optimization of clinical trials. The paper discusses the current applications, technology, and benefits of AI in various stages of drug discovery and development, and points out some of the successful cases of AI utilization over the last few years. It looks at the problems of data quality, model interpretability, the ethical issues, and regulations, as well. We will see why AI will transform personalized and precision medicine through the analysis of the recent progress, such as the use of AI in designing molecules through generative AI and in compounds optimization through reinforcement learning. The article recaps the conclusions that pharmaceutical research and development can be revolutionized by AI using the help of human knowledge and vast data infrastructure that will enable them to create drugs significantly quicker, safer, and cheaper
Deep Reinforcement Learning for Smart Traffic Control
Get PDFTraffic jams in urban areas have become a serious issue in the globe with the consequent impact of the long travelling time, use of fuel and pollution. The traditional traffic control schemes are time-based or rule-based schemes, which is not adaptable to the dynamics in the traffic conditions. The present advancement in Deep Reinforcement Learning (DRL) provides a promising framework of smart and responsive controller of traffic lights. This research paper is a summary of the DRL methods applied to implement smart traffic management including model architecture, training environment, performance measures, and deployment challenges. A provided model of traffic signal control by DRA is developed and experimented using simulation through the application of SUMO (Simulation of Urban MObility). The results indicate that large reduction in the mean waiting time and the queue length is also achieved over the conventional fixed time and actuated time control systems. As noted in the research paper, one of the opportunities the DRL can be used to transform the traffic control of the smart city
Amplifying the Heat Transfer is Double Pipe Heat Exchanger with Various Inserts and Nanofluids – Review
Get PDF Techniques to enhance heat transfer rates while at the same time reducing heat exchanger size-and-cost. Passive heat-transfer strategies among them have been found to be extremely effective, and the technique of using inserts has gained considerable importance in terms of enhancing flow turbulence. Comprehensive review on experiments and numerical investigations and different insert designs, and tube geometries, are presented in the current work. These technologies have targeted improving critical performance parameters of heat exchangers. After reading about past methods designed to increase turmoil and system effectiveness, tape inserts are presented up as according to a highly effective description. They have attracted considerable attention and are used extensively to enhance the performance of heat exchangers, particularly with Nanofluids. Studies also show that inserts are very efficient both in laminar-and-turbulent flow regimes and are thus suited for application with Nanofluids to further improve heat transfer
Educational Reform: Addressing the issue of zero Value Education at Secondary Level
Get PDFThe aims of the study are to explore the education system in Poonch district of jammu and Kashmir. In this study the researcher analyses the education reform, address the issue of zero value education at secondary level in Poonch district of jammu and Kashmir. The educational landscape in Tehsil Mankote of Poonch District, Jammu and Kashmir, faces numerous challenges, including infrastructural deficiencies, teacher shortages, mass copying, socioeconomic barriers, and the impacts of frequent ceasefire violations. Inadequate facilities, overcrowded classrooms, outdated curricula, and limited community support undermine educational quality and integrity. Teacher evaluations tied to student performance exacerbate stress and job dissatisfaction among educators. Addressing these issues requires comprehensive educational reforms, focusing on infrastructure development, curriculum and pedagogical updates, continuous teacher training, technology integration, and enhanced community and parental engagement. Additionally, tackling socio-economic barriers through scholarships and flexible schooling options is essential. Some teachers are also engaged in other responsibilities, such as BLOs. The government should take proper initiatives to fill BLOs vacancies to reduce the burden on teachers. Implementing a robust monitoring and evaluation framework, along with measures to curb mass copying, can promote academic integrity and ensure effective education. A holistic approach involving these strategies can transform the educational landscape in Mankote, fostering a more inclusive, equitable, and effective educational system that prepares students for future challenges and opportunities
Empowerment of Women through Self- Help Groups A Case Study of Rajasthan
Get PDFWomen empowerment is the important and primary need to balance between nature and humanity. India is a male dominated country, here saving the girl child is the first and foremost responsibility of the society for itself. However, the alarming rise of female feticide has attracted everyone\u27s attention and these figures have created a great concern among intellectuals and social activists. Many NGOS and Organization focused on addressing sex discrimination issues leading to gender disparities in different area of rural and urban society. NGOS has working towards women empowerment with the formulation of Self – Help group (SHG) and created many SHGs in different district of Rajasthan. Every Group has 15 to 20 members. As per the data provided by Government of Rajasthan, 333489 women have found direct/indirect employment through SHGs in Rajasthan. SHGs have been promoted in all district of under Deendayal Antyodaya Yojna and National Rural Livelihoods Mission and Priyadarshini Yojana
Assessing the Impact of COVID-19 on Small Businesses and Livelihoods in India: Challenges and Recovery Strategies
Get PDFThe COVID-19 pandemic, which originated in Wuhan, China, in December 2019, rapidly spread across the globe, leading to unprecedented public health and economic crises. In India, the government implemented one of the strictest lockdowns in the world on March 25, 2020, to curb the spread of the virus. While the lockdown helped in controlling the initial surge in cases, it had severe repercussions on the country\u27s economy, especially small-size businesses and the livelihoods of millions of informal workers. India’s micro, small, and medium enterprises (MSMEs), which form the backbone of the economy and employ over 111 million people, were hit hard by the restrictions, leading to massive disruptions in production, supply chains, and demand. This paper investigates the impact of the COVID-19 pandemic on small businesses and livelihoods in India, focusing on the sectors most affected, such as retail, hospitality, tourism, and manufacturing. The lockdown-induced disruptions led to significant revenue losses, with many businesses facing closure due to liquidity constraints and the inability to sustain operations. The livelihoods of millions of informal workers, who lacked social security and job protection, were jeopardized as businesses shut down or scaled back operations. The study also examines government interventions, such as the Atmanirbhar Bharat Abhiyan and Emergency Credit Line Guarantee Scheme (ECLGS), aimed at providing financial relief and reviving the small business sector. However, the effectiveness of these measures was hindered by implementation challenges, particularly for businesses in rural areas and those with limited digital access. The paper concludes by highlighting the need for long-term recovery strategies, including digital transformation, enhanced access to credit, and stronger social security for informal workers. These measures are essential to build resilience and ensure sustainable growth for small businesses in a post-pandemic world. This research contributes to the understanding of how crises impact small enterprises and offers policy recommendations for strengthening the sector against future disruptions
Human Rights Law: Principles and Advocacy Dr. Jaspal Kaur
Get PDFThe paper shall introduce the dynamic and quite complex area of international human rights law and state the general principles of the very same which aim at safeguarding the inherent dignity, as well as the fundamental freedoms of all human persons. It directs a doubtful glance at the problem of universality of human rights and the dispute, which borders with cultural relativism. The literature review has assisted the scholarship to bring into the limelight the different scholarly minds and opinions like the philosophical, legal, social-political aspects of it, of course the women rights, and gender equality. This research design is mixed in the sense that, it represents the mutual combination of a doctrinal research of the law with the empirical research of cases to provide the answer to the challenges and the steps toward the full realisation of the protection of human rights and the empowerment of women in particular. The outcomes help to justify the essence of activism and feminist movement in negotiation and protection of human rights standards. Concluding the paper the author says in order to fulfill human rights, powerful intervention of the legal actors and the civil society is required so as to promote justice and combat discrimination and above all on women as it will bring a radical change on how human rights are meant to be addressed in the world
Explainable AI Models for Predictive Maintenance in Smart Manufacturing Systems
Get PDFPredictive maintenance (PdM) is one of the determinants in the smart manufacturing in which the data-driven information is being applied to cut down the amount of maintenance costs and schedule with the down time and increase the overall management of the systems. Using conventional machine learning (ML) models on predictive maintenance on the other hand is not devoid of the issue on transparency and explainability. This current paper is an argument on how to adopt Explainable Artificial Intelligence (XAI) models in predictive maintenance of smart manufacturing systems and is addressed to bridge the gap between the accuracy of predictive maintenance and the interpretability of the models. XAI models seize an opportunity of not only jumping up the quality of decision making processes but also building trust in maintenance predictions among the human operators owing to the clearness and simplicity of the explanations of the processes. Evaluated methods In this paper, some of the XAI methods, such as the decision trees, LIME (Local Interpretable Model-agnostic Explanations), and SHAP (Shapley Additive Explanations), will be analyzed to evaluate and identify their applicability to the predictive maintenance systems. We will also discuss the consequences of implementing the said models in the real manufacturing environments both with regard to the gains as well as the hurdles. The point of the desired result is to demonstrate how explainability in AI models can be applied to ensure that predictive maintenance strategies in smart manufacturing become more solid and acceptable
IS THERE A GENDER WAGE DIFFERENTIAL EVEN AMONG THE MOST HIGHLY EDUCATED
Get PDFEven though gender wage discrimination is an extensively discussed topic, many questions remain unanswered, especially concerning the most highly skilled worker groups. This study estimates the gender wage differential of the most highly educated workers - PhD holders - in the United States. The findings suggest a gender wage gap of 17% and 21%, respectively, in 2013 and 2019. The wage differential was decomposed into observed and unobserved portions using the Oaxaca-Blinder decomposition method. The unobserved gender wage differential was 5% and 12%, respectively, in 2013 and 2019. The unexplainable portion of the wage gap was higher in the business/industry sector compared to the academic sector. Among the observed characteristics, less experience appeared to be a major factor for lower wages among women. Further, the results suggest that even highly educated women earned less than their male counterparts, partly due to occupational segregation – job category, employment category, and the field of study contributed to more than 40% of the observed wage gap in the business/industry sector
Blockchain Forensics: Detecting and Mitigating Malicious Transactions Through AI and Pattern Analysis
Get PDFThe blockchain is among such technologies that have gained the most extraordinary popularity due to cryptocurrencies and are used in different industries because of their decentralization and immutability. This aspect however also introduces the aspect of fraudulent transactions and to curb this aspect well-developed forensics is required to trace the ill motived transactions and neutralize them. Blockchain forensics is concerned with crim investigation, tracking, and prevention, using analysis of data on a blockchain. In some cases, standard approaches just are not enough, transactions are complex as well as large in size. The given paper proposes a technique based on Artificial Intelligence (AI) and pattern analysis methods to make the process of identifications and prevention of malicious transactions in a blockchain more effective. AI can identify complicated pattern and outliers that would have otherwise been undetectable with machine learning models. The research proposal focuses on AI in blockchain forensics, identifying pattern recognition methods, and evaluating the efficiency of these methods in practice. The paper has also suggested that detection of fraudulent transactions, including double-spending, transaction laundering, and phishing attacks, can be accomplished through a new AI-based approach. It has established that AI models hold a great promise of making blockchain forensics more precise and effective and result in quicker and more reliable detecting systems. This paper is relevant to the on-going research in Making blockchain networks secure since the research entails a combined strategy in the detection and prevention of malicious practices