Category Archives: Uncategorized

Authors: Tando Kulesi

Abstract: Targeted drug delivery represents a transformative approach in modern therapeutics, aiming to precisely deliver pharmaceutical agents to specific tissues, cells, or intracellular compartments. This approach significantly improves therapeutic efficacy while minimizing off-target side effects commonly associated with conventional systemic drug administration. Nanocarriers—engineered nanoscale vehicles such as liposomes, polymeric nanoparticles, dendrimers, and metallic nanostructures—have become central to targeted drug delivery due to their tunable physicochemical properties and ability to navigate complex biological environments. Despite their promise, designing nanocarriers that achieve optimal targeting, stability, and controlled release remains a challenging task involving multifaceted biological and physicochemical interactions. Artificial Intelligence (AI), especially through machine learning and deep learning, is revolutionizing this design process by enabling the analysis and interpretation of complex datasets, predicting nanocarrier behavior in biological systems, and optimizing their design parameters for improved performance. This paper thoroughly reviews the current advances in applying AI for the design of nanocarriers, explores successful case studies, discusses inherent challenges, and envisions future directions that could dramatically accelerate nanomedicine development and personalized healthcare.

DOI: http://doi.org/10.61137/ijsret.vol.8.issue6.544

 

Published by: vikaspatanker

Authors: Harshita Shukla, Archit Budiyal, Assistant Professor Er. Vivek Agnihotri

Abstract: The global rise in energy demand and environmental degradation, largely due to industrialization and rapid population growth, has highlighted the urgent need for sustainable waste management and alternative energy solutions. Plastic waste, in particular, poses a serious ecological challenge because of its non-biodegradable nature and the drawbacks of traditional disposal methods like landfilling, incineration, and mechanical recycling, which often result in harmful environmental and health impacts. This study focuses on pyrolysis, a thermochemical process conducted in the absence of oxygen, to convert plastic waste—specifically polypropylene—into valuable fuel products such as pyrolytic oil, non- condensable gases, and char. The pyrolytic oil obtained from this process has calorific properties similar to conventional fossil fuels, making it a promising substitute. Pyrolysis is also capable of processing mixed and unwashed plastics, reducing the need for pre- treatment and minimizing toxic emissions compared to incineration. This research explores the efficiency and fuel yield of plastic waste pyrolysis under controlled conditions, demonstrating its potential as a sustainable waste-to-energy method. The findings support the integration of pyrolysis into circular economy strategies by addressing plastic pollution and contributing to clean energy generation.

DOI: http://doi.org/10.61137/ijsret.vol.11.issue3.125

 

 

Published by: vikaspatanker

Authors: MA. Michelle V. Valles

Abstract: This study investigates the implementation of the Revised Computerization Program (D.O. No. 16, s. 2023) and its impact on organizational performance within the San Pedro City Schools Division. Utilizing a descriptive research design, data were collected from 345 respondents (supervisors, school administrators, teachers, and non-teaching personnel) through surveys and documentary analysis. The study employed statistical tools such as weighted mean, ANOVA, Pearson correlation, and t-test to analyze the data. Findings reveal that while the program is generally implemented, significant challenges persist, particularly concerning inadequate hardware infrastructure, insufficient teacher training, and unreliable internet connectivity. Despite these challenges, a strong positive correlation was found between the program's implementation and organizational performance. Based on these findings, a proposed intervention scheme (PACTS: Program for Advancing Computerization and Technologies in Schools) is presented and deemed highly acceptable by respondents. This scheme, which includes targeted strategies for hardware upgrades, enhanced teacher training, and improved internet access, is recommended for implementation to further enhance the effectiveness of the Revised Computerization Program and optimize organizational performance within the San Pedro City Schools Division.

 

 

Published by: vikaspatanker

Authors: Research Scholar Aman Malik

Abstract: The rapid deployment of Artificial Intelligence (AI) across diverse sectors—including healthcare, transportation, finance, and governance—has prompted pressing legal and ethical concerns, especially in technologically emerging economies like India. This paper critically examines the legal and ethical challenges surrounding the integration of AI systems in practical applications, with a focus on the Indian regulatory landscape. While AI promises efficiency and innovation, it also raises fundamental questions of accountability, privacy, bias, and transparency. Key issues such as the attribution of liability for autonomous decisions, the ethical implications of algorithmic discrimination, and the lack of a clear legal framework for AI-generated data and actions are discussed. The paper further explores the limitations of existing Indian laws, including the Information Technology Act, 2000 and the absence of a dedicated AI or data protection statute (pre-GDPR adaptation). Drawing on global standards and domestic case studies, this study proposes a need for robust regulatory mechanisms, ethical design protocols, and sector-specific governance to ensure responsible AI deployment. The findings aim to contribute to the evolving discourse on AI governance and serve as a foundational reference for future legal reforms in India.

 

Published by: vikaspatanker

Authors: Raghu V Kaspa, Ramya K Cherukuvada

 

Abstract: Simulated Annealing (SA) is a probabilistic technique used for approximating the global optimum of a given function, with origins in statistical mechanics. It has found widespread utility in optimization problems central to machine learning (ML), particularly where the solution space is large and complex. This paper investigates the theoretical underpinnings of SA, explores its applications within ML domains, compares it with other optimization algorithms, and evaluates its performance. The work concludes with a discussion on SA's strengths and limitations in the context of modern ML challenges. The purpose of this research is to position SA as a viable tool in the ML optimization toolkit, particularly for tasks involving large, multi-modal search spaces where deterministic methods may falter.

DOI: 10.61137/ijsret.vol.11.issue3.124

 

Published by: vikaspatanker

Authors: Raghu V Kaspa, Ramya K Cherukuvada

Abstract: Simulated Annealing (SA) is a probabilistic technique used for approximating the global optimum of a given function, with origins in statistical mechanics. It has found widespread utility in optimization problems central to machine learning (ML), particularly where the solution space is large and complex. This paper investigates the theoretical underpinnings of SA, explores its applications within ML domains, compares it with other optimization algorithms, and evaluates its performance. The work concludes with a discussion on SA's strengths and limitations in the context of modern ML challenges. The purpose of this research is to position SA as a viable tool in the ML optimization toolkit, particularly for tasks involving large, multi-modal search spaces where deterministic methods may falter.

 

 

Published by: vikaspatanker

Authors: Raghu V. Kaspa, Kevin Camenzuli, Salai S

 

Abstract: The car rental industry faces increasingly complex challenges in optimizing fleet utilization, responding to demand variability, and managing operational costs. As competition intensifies and consumer expectations evolve, effective fleet management has become more vital than ever. Operations Research (OR) provides a suite of mathematical models, optimization techniques, and decision-making frameworks that help car rental firms streamline their operations. This paper explores how OR methodologies can be applied to key aspects of fleet management, including demand forecasting, fleet sizing and composition, vehicle allocation and relocation, and dynamic pricing. It also analyzes real-world case studies where OR tools have been successfully implemented and examines current challenges and future directions for the industry. By employing OR, car rental companies can improve operational efficiency, boost profitability, and offer better customer experiences.

DOI: 10.61137/ijsret.vol.11.issue3.123

 

Published by: vikaspatanker

Authors: Siddharth Gupta, Vineet Gupta, Muskan Jaiswal, Karishma Priya Dwivedi

Abstract: Artificial Intelligence (AI) is rapidly transforming healthcare by enhancing diagnostics, optimizing treatments, and improving operational efficiency. This paper presents a detailed analysis of AI applications in healthcare, case studies, data insights, challenges, risks, and future directions. It leverages clinical datasets and published research to examine the practical impact of AI on patient care and hospital systems.

 

 

Published by: vikaspatanker

Authors: Assistant Professor Ms. Shruti Rawat, Anmol Choudhary

Abstract: The primary objective of this research is to examine and analyze the impact of cultural diversity on the overall effectiveness and productivity of teams operating inside international organizations. The primary objective of this research is to bridge the existing knowledge deficit in the domain of cross-cultural management and organizational behavior. This is achieved by conducting an investigation into the intricate association between cultural diversity and team performance inside MNCs. In the context of this study, a mixed-methods approach is considered the most suitable methodology. This methodology enables a thorough examination of the correlation between cultural diversity and team performance, encompassing the utilization of both quantitative and qualitative data. The results emphasize the importance for MNCs to implement comprehensive strategies that take into account the specificities of leadership, organizational culture, and team dynamics in order to effectively use the benefits of cultural diversity. By engaging in such practices, firms can effectively tackle the complexities associated with cultural diversity and bolster their global competitive advantage. Through the implementation of these strategies, MNCs have the opportunity to effectively utilize the advantages presented by cultural diversity, hence enhancing their competitive advantage within the global market.

DOI: http://doi.org/

Published by: vikaspatanker

Authors: Shriram Deshpande, Shridhar Dhaduti, Rahul Meeshi, Daneshwari Jambagi

 

Abstract: Adequate quality and reliability of drinking water is vital for all inhabitants and for agriculture and industrial applications. Solar desalination is impactful method for getting potable water from brackish/wastewater in hot climatic condition and/or remote area where the scarcity of water as well as for electricity. In recent years, attention has been focused on development of various designs of solar still in order to overcome limitations possesses by conventional single basin single slope solar still. Pyramid solar still is one of the outcomes of such a development. This project reviews the development in the field of pyramid solar still as well as the various techniques to improve the performance of still. From the review on research carried out by the various researchers, it has been found that pyramid solar still is more efficient and economical in compare to conventional single slope single basin still.

DOI: http://doi.org/10.61137/ijsret.vol.11.issue3.122

 

Published by: vikaspatanker