Volume 9 | Issue 8

 Abstract

Multimodal neuroimaging analysis offers promising potential for enhancing the diagnosis of Alzheimer's disease and its subtypes. This work proposes an end-to-end framework that integrates structural MRI, synthetically generated PET images, and cognitive test scores to improve diagnostic accuracy and cognitive phenotype characterization. A 2D CycleGAN model is employed to synthesize PET scans from MRI inputs, preserving structural and metabolic consistency, as validated by SSIM and PSNR metrics. The synthesized PET images are labeled using a fine-tuned Inception-based classifier trained on the Kaggle OASIS dataset, achieving a classification accuracy of 98.08%. Patient-level features from both MRI and PET modalities are extracted using ResNet, while cognitive test scores are used to assign phenotypes through a decision tree classifier. Feature-level fusion is then performed to cluster patients into severity-based groups, highlighting the added value of multimodal integration. This framework demonstrates the potential of multimodal pipelines for Alzheimer's diagnosis, providing a foundation for future clinical decision support systems.

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Multimodal fusion, Alzheimer's diagnosis, PET synthesis, CycleGAN, cognitive phenotyping, decision tree, ResNet, Inception, clustering, MRI.

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Supervised machine learning algorithms play a critical role in solving classification problems across science and engineering. This study presents a comparative evaluation of four widely used supervised classification models--Logistic Regression, Support Vector Machine (SVM), K-Nearest Neighbors (KNN), and Decision Tree--using the Iris and Wine benchmark datasets. An experimental design was adopted with an 80/20 stratified train-test split, standard normalization, and label encoding to ensure fair comparison across models. Performance was assessed using accuracy, precision, recall, and F1-score to capture both correctness and robustness of predictions. Results show that SVM consistently achieves the highest accuracy (0.98 for Iris and 0.88 for Wine), followed closely by Logistic Regression, while KNN and Decision Tree generally exhibit lower performance, reflecting sensitivity to feature scaling and over fitting, respectively. These findings confirm that classifier effectiveness strongly depends on dataset characteristics, including separability and feature distributions. The study underscores the necessity of empirical benchmarking when selecting classification algorithms for real-world problems rather than relying on default or heuristic choices. Future research should extend this comparison to ensemble and deep-learning-based classifiers and incorporate larger, higher-dimensional engineering datasets to enhance generalizability

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Supervised machine learning, Classification algorithms, Support Vector Machine (SVM), Logistic Regression, K-Nearest Neighbors (KNN)

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Technological advances plus the evolving work and family roles of women in this country have contributed to the business environment of the 21st century. The changing roles of women in India have led to their greater participation in the employment sector and changes in many aspects of Indian life.

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WORKING WOMEN AND THEIR PROBLEMS IN INDIA

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The growing demand for sustainable and energy-efficient cooling solutions in industrial applications has intensified interest in refrigeration systems powered by renewable energy sources. Conventional vapour compression refrigeration systems are heavily dependent on electrical energy derived from fossil fuels, leading to increased operating costs and environmental concerns. In this context, the present work focuses on the design and performance evaluation of a solar-assisted vapour absorption refrigeration system (VARS) intended for industrial cooling applications. The proposed system integrates a solar thermal energy collector with a vapour absorption refrigeration cycle, utilizing low-grade heat energy to drive the refrigeration process. Ammonia-water is considered as the working fluid pair due to its suitability for industrial-scale cooling. The system design parameters, including generator temperature, absorber efficiency, and heat exchanger effectiveness, are analyzed under varying solar radiation conditions. Performance evaluation is carried out in terms of coefficient of performance (COP), cooling capacity, thermal efficiency, and energy savings. The experimental and analytical results demonstrate that solar energy can effectively supplement conventional heat sources, leading to a significant reduction in electrical energy consumption and operational costs. The study confirms that solar-assisted VARS offers a viable, environmentally friendly, and economically attractive alternative for industrial cooling applications, particularly in regions with high solar insolation.

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 Keywords

Solar-Assisted Refrigeration, Vapour Absorption Refrigeration System, Industrial Cooling, Renewable Energy, Thermal Performance, Coefficient of Performance (COP).

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The Soldier Safety and Monitoring System is a comprehensive solution that enhances battlefield survivability and situational awareness for soldiers. By leveraging a network of wearable sensors, including smart watches, body sensors, and head-mounted displays, the system continuously monitors soldiers 'vital signs, such as heart rate ,body temperature, and hydration levels. This data, combined with real-time environmental information like air quality, radiation levels, and chemical threats, is transmitted wirelessly to a central command and control center. Employing advanced PCB Technology, the system analyzes this data stream to identify potential threats, predict health risks, and provide personalized insights into each soldier's physical and cognitive state. This proactive approach enables rapid response to injuries, optimized medical resource allocation, and enhanced soldier well-being. Furthermore, the system provides soldiers with real-time battlefield intelligence, including enemy locations, friendly forces positions, and dynamic threat assessments, significantly improving their situational awareness and decision-making capabilities. By integrating these technologies, the Soldier Safety and Monitoring System aims to minimize the human cost of warfare while ensuring the safety and effectiveness of military personnel.

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Soldier Safety, Monitoring System, Battlefield Survivability, Situational Awareness, Wearable Sensors, AI-powered Analytics, Vital Signs, Environmental Hazards, Real-time Intelligence, Rapid Response, Threat Detection, Health Risks, Personalized Insights,MedicalResourceAllocation,SoldierWell-being,BattlefieldIntelligence,EnemyLocations,FriendlyForces, Decision-Making Capabilities, Human Cost of Warfare, Military Personnel.

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Green banking mainly focuses in promoting environment-friendly practices and reduce carbon footprint from the day-to-day banking activities. Each and every small 'Green' step taken by banks would go a long way in building a greener future. Presently, banks encourage their customers to subscribe for e-statements and other electronic formats of communication to reduce paper consumption. It is an important step taken by banks towards converting Indian economy into a sustainable digital economy. Through this paper, the researcher tried to find out the steps or ways adopted by banks to go green. The Study would also try to examine whether there is any significant difference between the banks in relation to implementation of green banking initiatives. An emphasis will also be made in order to find out the various challenges faced by banks in implementing the green banking initiatives.

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Bank, Green, Sustainability

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Over the past few decades, higher education has undergone significant academic and administrative reforms. A key change has been the shift from the conventional annual system to a semester system, and subsequently, to a Choice Based Credit System (CBCS), as recommended by the Gnanam Committee. The University Grants Commission mandated the adoption of CBCS in all universities and higher education institutions starting from 2015. This reform aims to align Indian higher education with global standards and meet the demands of the 21st-century knowledge landscape. However, empirical studies have highlighted issues such as a skill gap, particularly in communication skills, rendering many graduates unemployable. Additionally, outdated syllabi, limited course flexibility, lack of student mobility, and inadequate evaluation systems have been concerns. CBCS was introduced to address these issues, focusing on learner-centric methods, interdisciplinary approaches, skill-based courses, and flexibility. This paper examines the challenges and issues faced in the practical implementation of CBCS.

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learner-centric approach, interdisciplinary approach, Choice Based Credit System.

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Concrete, the most widely used construction material in the world, is highly susceptible to microcracking due to the combined effects of environmental exposure and mechanical stress. Water, chlorides, and sulfates can penetrate through these microcracks, accelerating deterioration. Conventional repair methods are often labour-intensive, time-consuming, and costly. In contrast, self-healing concrete offers the ability to autonomously seal cracks and restore structural functionality. Microbial-based systems have gained significant attention due to their unique healing mechanism and performance characteristics. These systems rely on microbial-induced calcite precipitation (MICP), typically triggered by specific strains of urealytic bacteria. Polymer-based self-healing systems, particularly those utilizing superabsorbent polymers (SAPs), depend on physical swelling and water retention to block cracks and support autogenous healing. This comparative study evaluates both self-healing strategies with a focus on their crack-sealing capability, mechanical strength recovery, durability enhancement, and practical feasibility. The analysis is grounded in an extensive review of peer-reviewed literature. Microbial-based systems offer promising eco-friendly and sustainable healing, particularly in moist environments, but face challenges related to bacterial survivability and uniform distribution. On the other hand, SAP-based systems, though associated with higher costs and potential long-term chemical interactions, provide rapid and repeatable healing with better integration into the concrete matrix. The study suggests that hybrid and next-generation integrated systems represent a forward-looking approach to improving infrastructure resilience by tailoring self-healing strategies to specific structural and environmental conditions.

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 Keywords

Self-healing concrete; microbial-induced calcite precipitation; superabsorbent polymers; infrastructure durability; crack healing mechanisms; sustainable materials; strength recovery; durability performance; autonomous repair systems; polymer-based healing; microbial healing systems; MICP; SAP; concrete rehabilitation; eco-efficient construction materials.

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Chaolung Sukapha, the first Ahom king in medieval period, was the founder of the Ahom kingdom in Assam. A Tai prince originally from Mong Mao, (which is now included within the Dehong-Dai Singhpho Autonomous Prefecture of Yunnan in Peoples Republic of China), the kingdom he established in 1228 existed for nearly six hundred years and in the process unified the various tribal and non-tribal peoples of the region that left a deep impact on the region. He was a brave and courageous dignitary who enlightened every part of his kingdom. His good governance not only influenced the Ahom kingdom but also the other small states in Assam, then known as Kamrup. To make the Ahom dynasty powerful and permanent he undertook conciliatory measures towards the neighbouring kings. He appointed Katakis and two chief Buragohain and Borgohain which were most essential for the foundation, growth and prosperity of his newly established regime. Through this study, an effort has made to draw the role of Sukapha in founding Ahom dynasty in Assam and to understand his relation with other neighbouring countries in maintaining peace. In reference to his position in Assam's history the honorific Chaolung is generally associated with his name (Chao: lord; Lung great).

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Ahom Kingdom, Ahom dynasty, Assam, brave, founder, good governance, states.

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Intherapidlyevolvingfieldofartificialintelligence,voiceassistantshavebecomeanintegralpartofmoderntechnology,significantlyimprovinghuman-computerinteraction.ThisprojectfocusesonthedevelopmentofanadvancedAI-poweredvoiceassistantdesignedtostreamlinevarioustasksthroughintelligentvoicecommands.Unliketraditionalvoiceassistantsthatprimarilyperformpredefinedtasks,thissystemoffersanexpandedrangeoffunctionalities,includingsendingWhatsAppvoicemessageswithoutmanualinput,openingwebsitesdirectlyviavoicecommands,performingreal-timeYouTubesearches,generatingtextandimagesusingAImodels,andanalyzingdocumentsforcontentextraction.

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Advance Smart Assistant for Differently able Persons Using Artificial Intelligence

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The seminar paper is based on the topic "Early Indo-Arab Relations: A Study". It is an important and feasible research topic in present day research scenario. The Arabs have a deep rooted association with India from the dated back in respect of inter-cultural dialogues and exchanges between two age-old civilizations. There are a lot of historical evidences for this time tested cultural tie up. As we find in religious sources, the first human being, Adam is believed to have landed in Sri Lanka and reached Arabia via India. Finally, he met Eve in Saudi Arabia' Adam is believed to have landed in dajna which means south. Adam was landed in India from the heaven of sky. He set his first step in Sri Lanka, which was a part of the greater India. Several goods like perfumes and spices were on move to the Arab world from South India. So, it bears an ample evidence for maritime mercantile relations between India and the Arab world. This paper highlights the early Indo-Arab relations in respect of business, economy, history, culture and believes.

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Indo-Arab, Inter-Cultures, Socio-Economic, Business, Thought and Believes, Innovation.

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Abstract: Agriculture is the oldest and largest means of livelihood of mankind. It is the parent source of food supply of all living beings. The nomadic people extracted food in natural ways by fruits gathering and hunting roaming from one place to another place. Germination of thrown seeds gave the ideation of planting that conceived the knowledge of agriculture. The natural practice of agriculture continued dates long, but alarming growth of population changes the situation. Modernization of agriculture has been the one and only way of raising agricultural productivity that has made people chemical and mechanical loving. Extensive cultivation is no longer remaining alternative means for raising agricultural production. Excessive use of chemical fertilizer and pesticides has risen the health hazard of human being. Presently, there has been wider discussion on the negative impact of such intensive way of cultivation. There has been the feeling of embracing organic cultivation among the health sensitive people. Of course, such number is meagre. In true sense, indigenous agricultural knowledge is an important national human capital to improve crop productivity and enhance sustainable agricultural development. Fostering and documentation of indigenous agricultural knowledge can promote the wider use of organic crop production methods and sustain environmental health. Present study is an attempt of picturing the need of IAK at present situation. The study will be conducted through using both primary and secondary sources of information.

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Keywords: Agriculture, food, IAK, modernization in agriculture, sustainable agriculture and environment etc.

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Cloud computing is a newly evolved technology for complex systems that allow on- demand, flexible, scalable, and low cost services with massive-scale services sharing among plentiful users. The wide receiver of the cloud computing idea has brought about significant effects in both fixed and mobile communication systems prompting frontline research to give fitting System protocols and network architecture, alongside resource administration/management components. In cloud computing, access control and security are two major problems. Therefore, Security of both services and users is a substantial issue for the uses and trust of the cloud computing. This paper audits recent works concentrating on security issues, solutions, and difficulties in cloud computing infrastructure.

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Cloud Computing, Cloud Security, Cloud Computing Infrastructure, User Authentication.

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Dams located in seismically active regions are highly susceptible to structural damage due to strong ground motions. Several small to medium-sized dams, ranging in height from 10 to 25 meters, have experienced various forms of distress, including longitudinal cracks along the crest and failures of upstream and downstream slopes. Chang Dam, situated in the Kachchh region of Gujarat, India, was among the most severely affected structures, highlighting the need for a detailed seismic stability assessment. This study employs PLAXIS, a widely used finite element software for geotechnical analysis, to model and evaluate the seismic response of Chang Dam under different ground motion intensities. The numerical analysis considers factors such as soil-structure interaction, dynamic loading, and deformation patterns to assess the dam's stability and failure mechanisms. By simulating real earthquake conditions, the study provides insights into the dam's vulnerability and helps identify critical failure zones. The findings from this analysis contribute to a better understanding of the seismic performance of embankment dams and offer valuable input for developing improved design and retrofitting strategies. This study underscores the importance of advanced seismic assessment techniques to enhance the resilience of critical infrastructure in earthquake-prone regions.

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Seismic Response, Ground Motion, Structural Stability, Finite Element Analysis, Dynamic Loading, Seismic Performance, Earthquake-Prone Regions

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Water quality is important from health, environment as well as economic point of view. Treated water reuse is associated with some potential risks especially when the treatment is not adequate. The present study aims to determine the corrosive and scaling potential of secondary treated wastewater used in Hanumangarh. In this study, secondary treated water from SARAS dairy and GB sewage treatment plant, Hanumangarh was collected for a period of one year. Langelier Saturation Index (LSI) and Aggressive Index (AI) were calculated using various water quality parameters. It was found that nature of treated water was from slight corrosion to slight scale with overall faint scale coating. The concordance between the analysis of chemical water quality and national standards could not be sufficient to confirm the water quality balance in terms of corrosion and scaling potential.

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secondary treated wastewater, corrosion indices, scaling potential, LSI, AI.

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Abstract: Iris Murdoch, renowned for her dual role as both a novelist and philosopher, challenges modern moral philosophies through her literary works. This research paper examines how Murdoch critiques the dominant ethical frameworks of the 20th century--particularly existentialism, utilitarianism and behaviourism--by integrating her philosophical ideas into the narratives and moral dilemmas of her characters. Analysing key novels such as The Sea, The Sea, The Bell and The Black Prince, this paper seeks to reveal how Murdoch advocates for moral realism, the existence of objective goodness, and the importance of attention and moral perception as counterpoints to modern ethical relativism and subjectivity.

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Existentialism, utilitarianism and behaviourism, ethical relativism, attention, self- transcendence and objective goodness

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 Abstract

Healthcare systems across the globe are increasingly strained by rising patient demands, escalating costs, and the necessity for efficient resource utilization. In this context, the adoption of data-driven approaches for healthcare resource management has emerged as a transformative strategy, offering the potential to optimize the allocation of critical resources such as hospital beds, medical staff, and equipment. This research research examines the implementation of a data-driven resource management system in a large urban hospital, providing a comprehensive case study that illustrates the system's impact on operational efficiency, cost reduction, and patient satisfaction. The study details how the hospital integrated diverse data sources, including electronic health records (EHRs), patient admission logs, and staffing schedules, into a centralized database. Utilizing advanced predictive analytics and machine learning algorithms, the system was able to forecast patient demand, optimize resource allocation in real-time, and ensure that resources were deployed where they were most needed. The results of the implementation were significant: the hospital saw a 15% increase in bed occupancy rates, a 10% reduction in patient wait times, a 12% boost in staff productivity, and a 5% reduction in operational costs. Moreover, patient satisfaction improved by 8%, underscoring the positive impact of the optimized resource management on patient care. However, the study also identifies several challenges associated with implementing data-driven systems, such as the need for high-quality data, the importance of gaining user trust and adoption, and the ethical considerations inherent in algorithm-driven decision-making. The case study highlights the importance of addressing these challenges through robust data governance, effective change management, and ensuring fairness and transparency in resource allocation processes. This research contributes to the growing body of literature on data-driven healthcare by providing empirical evidence of the benefits and challenges associated with such systems. It argues that while data-driven approaches hold significant promise for enhancing healthcare resource management, their successful implementation requires careful planning, ongoing evaluation, and a commitment to ethical practices. As healthcare systems continue to evolve, the insights from this case study can inform future efforts to optimize resource management and improve patient outcomes through the strategic use of data and analytics.

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Healthcare resource management, Data-driven approaches, Predictive analytics, Machine learning algorithms, Operational efficiency, Patient demand forecasting, Resource allocation optimization, Patient satisfaction, Data integration, Ethical considerations in AI.

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Microservices architecture has emerged as a dominant design paradigm for building scalable, resilient, and flexible applications in today's cloud-native environments. Unlike traditional monolithic architectures, microservices break down applications into small, independent services that can be developed, deployed, and scaled independently. This approach offers significant benefits, particularly in terms of scalability, which is crucial for handling the growing demands of modern applications. This paper explores various microservices design patterns and their impact on scalability. Design patterns, such as the API Gateway, Circuit Breaker, Service Discovery, and Event Sourcing, are essential in addressing the challenges that arise in microservices architectures, including service communication, fault tolerance, and data consistency. By implementing these patterns, organizations can enhance the scalability of their applications, ensuring that they can efficiently manage increased workloads without compromising performance or reliability. The API Gateway pattern, for instance, plays a pivotal role in managing client requests and routing them to the appropriate microservices. This pattern not only simplifies communication but also allows for the independent scaling of services, enabling better resource utilization. Similarly, the Circuit Breaker pattern helps in maintaining system stability by preventing cascading failures during high-load conditions, thereby supporting scalable and resilient operations. Service Discovery is another crucial pattern that facilitates dynamic routing and load balancing, which are vital for maintaining performance as the number of services increases. By enabling services to register and discover each other automatically, this pattern ensures that microservices can scale horizontally with minimal manual intervention. Additionally, Event Sourcing offers a powerful mechanism for managing state and ensuring data consistency across distributed services, which is often a challenge in scalable microservices architectures. While these design patterns significantly enhance scalability, they also introduce complexities, particularly in areas such as distributed data management, latency, and system coordination. The paper discusses these challenges and provides insights into how they can be mitigated through best practices and advanced architectural strategies. For instance, adopting a polyglot persistence approach and implementing eventual consistency models can help address the challenges of data management in a scalable microservices environment. Furthermore, the paper examines case studies from various industries, illustrating how organizations have successfully leveraged microservices design patterns to achieve scalable solutions. These real-world examples underscore the practical benefits and challenges of adopting microservices, offering valuable lessons for organizations looking to enhance their systems' scalability. In conclusion, microservices design patterns play a critical role in determining the scalability of modern applications. By carefully selecting and implementing these patterns, organizations can build systems that not only scale efficiently but also remain resilient and flexible in the face of evolving business needs. The ongoing evolution of microservices architecture and its associated design patterns will continue to drive innovation in scalable system design, making it an essential area of focus for architects and developers alike.

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Microservices, design patterns, scalability, API Gateway, Circuit Breaker, Service Discovery, Event Sourcing, cloud-native, distributed systems, fault tolerance.

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Creative Commons Attribution 4.0 and The Open Definition

 Abstract

Several mathematical concepts share a common feature that acts as a link between them. One such connection between the mathematical concepts of Group, Group Actions, and Homotopy is that they all involve projective maps. This underlying commonality allows us to establish a relationship between them, prompting a focused study of Group Actions and Homotopy to uncover this connection. While these concepts have each been the subject of extensive individual research, there has been little effort to determine if one can lead to the other and the conditions for such an interlinking function. Additionally, identifying Group Actions can be more challenging than finding Homotopic maps. Therefore, we anticipate that discovering an interlink could be beneficial. By relating these concepts on a common platform, we aim to determine if they can coexist through a single function. As a step in this direction, this paper is a part of the work that is about the condition for functions to be Homotopic under a Group Action and conversely. Here we derive the condition for a Homotopy to induce a group action. Our aim is to find a single map which can give rise to a Homotopy and a Group Action simultaneously. The extension of Homotopy to sets, vector-fields etc., serves to meet this purpose. Similarly, we extend Group Actions to general sets (Set-Action). We obtain conditions for a Homotopy to be a group, Action. This study serves as an approach to find Group Actions using existing Homotopy. Thus, we show here that a Homotopy leads to group action between two functions with special properties and theorems on these.

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 Keywords

Homotopy, Group Action, Induced Homotopy, Induced Group Action, Linking Group Action and Homotopy.

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 Abstract

The transition towards electric vehicles (EVs) marks a significant paradigm shift in the transportation sector, with profound impacts on power systems globally. This research paper provides a comprehensive analysis of the effect of EVs on power systems, addressing key challenges and opportunities arising from their integration. We examine the intricate dynamics between EV charging behavior and grid stability, emphasizing the importance of innovative solutions such as smart charging algorithms and demand response mechanisms to mitigate peak demand impacts. Furthermore, we investigate the grid integration challenges posed by EVs, including distribution and transmission infrastructure constraints, voltage stability issues, and the imperative for strategic grid modernization initiatives. Energy demand and supply implications are explored, with a focus on optimizing EV charging profiles, leveraging renewable energy sources, and exploring the potential of vehicle-to-grid (V2G) technologies to enhance grid flexibility. Environmental considerations are also scrutinized, evaluating the net environmental benefits of EV adoption and the role of policy frameworks in incentivizing sustainable transportation solutions. Real-world case studies and pilot projects illustrate best practices and lessons learned in EV-grid integration, while also highlighting opportunities for innovation and collaboration across stakeholders. The paper concludes with a discussion on future research directions, emphasizing the need for continued interdisciplinary efforts to address emerging challenges and unlock the full potential of electric vehicles as a cornerstone of a resilient, low-carbon energy future

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Electric Vehicle, Power System and Smart grid

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Creative Commons Attribution 4.0 and The Open Definition