Volume 13 | Issue 2

 Abstract

Smart appliances that are more dependable and efficient must be developed in order to build and create smart grids. We will create a cost-effective solution for the distribution transformer to prevent thermal overload in order to contribute to smart work. Overloading damages the greatest distribution transformer in India, but because of its high cost, no intelligent protection is yet in place. Overload reduces efficiency and increases the risk of overheating or burning the secondary winding. Therefore, the transformer can be protected by lowering the additional load. A transformer safety sensor timer circuit can be used to do this. The transformer safety feature immediately cuts off the excess load when it above the reference value. As a result, damage can be avoided and transformer safety devices operate effectively in overload and overheat situations.

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 Keywords

Transformer, Thermal Overload Protection, Sensor, Extra Load, Efficient

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The Partition of India in 1947 and the division of Germany during the Cold War represent monumental disruptions in modern history, marked by displacement, identity crises, and intergenerational trauma. This study examines these themes primarily through Amitav Ghosh's The Shadow Lines, complemented by Anna Funder's Stasiland as a comparative lens. Together, these works explore the profound human cost of borders, both physical and psychological, and their impact on individuals and communities. The Shadow Lines reflects the blurred and arbitrary nature of borders, delving into the intergenerational trauma and fragmented identities that arise from the Partition of Bengal. It highlights the personal and collective struggles of belonging amidst forced migration and political upheaval. Stasiland extends this inquiry into the context of a divided Germany, documenting the stories of those who lived under surveillance and oppression, capturing the resilience of individuals in reclaiming their voices. This research also discusses the continued relevance of these narratives in addressing modern issues like forced migration, rising nationalism, and intergenerational trauma. Furthermore, it explores new areas of inquiry, such as the role of memory and silence in healing, the gendered dimensions of trauma, and the universal parallels between regional and global partitions. By analyzing these themes, the study underscores the critical role of literature in preserving memory, fostering empathy, and helping societies heal after immense disruptions.

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 Keywords

Borders of Belonging: Identity, Displacement, and the Legacy of Partition in Literature

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Abstract A UNESCO World Heritage site and one of the eight "hottest" biodiversity hotspots in the world, the Western Ghats are experiencing severe environmental deterioration as a result of deforestation, unchecked urbanization, agricultural growth, and climate change. Millions of people's access to clean water is at risk, endemic species are in danger, and ecological equilibrium is upset. Unrestrained use of natural resources has resulted in soil erosion, habitat fragmentation, and a rise in conflicts between people and animals. Furthermore, the region's susceptibility to landslides and biodiversity loss is made worse by unpredictable monsoons and warming temperatures. The main causes of environmental deterioration in the Western Ghats are investigated in this paper, along with their socioeconomic and ecological repercussions. To prevent more harm and protect this vital biological zone, immediate conservation measures, sustainable land-use plans, and more stringent environmental laws are required.

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 Keywords

Keywords Western Ghats, environmental degradation, biodiversity loss, deforestation, climate change, habitat fragmentation, water security, conservation strategies, sustainable development, and ecological imbalance.

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The concept of transforming waste into a resource is a cornerstone of the circular economy, addressing the dual challenges of waste management and resource scarcity. This research explores the design and development of an AI-powered marketplace that facilitates the effective utilization of waste as a resource. The proposed system leverages artificial intelligence (AI) to classify, value, and redistribute waste materials, connecting producers with recyclers, upcyclers, and end-users. Core functionalities of the AI agent include waste identification, dynamic pricing, demand-supply matching, and predictive analytics for waste generation and resource needs. IoT integration and blockchain technology ensure transparency, trace- ability, and real-time data management. The study also highlights key use cases, challenges, and the environmental and economic impact of implementing such a marketplace. Through simulations and real- world data analysis, the research demonstrates the potential of AI-driven systems to revolutionize waste management, reduce environmental impact, and create a sustainable resource loop.

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 Keywords

Artificial Intelligence, IoT, Blockchain, Waste Classification, Circular Economy, Smart Waste Management.

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As technology advances, many challenges faced by individuals can be addressed. One such challenge is the difficulty faced by people with blindness in traveling safely. For them, navigating the world is a significant concern. To address this, an intelligent electric vehicle is needed. This vehicle integrates a variety of technologies, such as ultrasonic sensor for obstacle detection, edge and road recognition, and infrared-based obstacle avoidance, GPS and map-guided location assistance, GSM-based emergency support, and a semi-automatic control system for operation. We propose a fully intelligent electric vehicle designed specifically for the blind, which can be successfully implemented. The vehicle is built to navigate footpaths and follow all traffic signals, ensuring its practicality in real-world scenarios. The development of an automatic solar-driven rickshaw for blind people aims to improve the mobility and independence of visually impaired individuals by combining renewable energy with advanced assistive technology. This system integrates a solar-powered electric motor with an autonomous navigation system, providing an eco-friendly and self-driving transportation solution. The rickshaw is equipped with sensors, including ultrasonic, GPS, and obstacle detection technology, allowing it to navigate safely and efficiently in various environments. Additionally, a voice-assisted interface guides the user to the desired location, offering a seamless experience without the need for manual operation or external assistance. By utilizing solar energy, the rickshaw ensures sustainability and reduces operational costs. This innovation addresses the unique transportation challenges faced by blind individuals, promoting inclusivity and autonomy in daily life while contributing to environmental sustainability.

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E-Rickshaw, Solar, Vehicle for blind people

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The fast food industry has experienced significant growth in recent years, driven by changing consumer lifestyles, urbanization, and increasing demand for convenience. Customer satisfaction plays a crucial role in determining the success and sustainability of fast food outlets. This study aims to analyze customer satisfaction towards the fast food industry in Coimbatore city, considering factors such as food quality, service efficiency, pricing, hygiene, ambiance, and brand perception. A survey-based approach was employed to gather insights from consumers regarding their expectations and experiences. Primary and secondary data was used for this study. The data were collected from 100 respondents through questionnaire. Percentage analysis, Chi-Square, and Anova used for this study. The findings highlight key determinants of customer satisfaction and provide recommendations for fast food businesses to enhance their services and customer retention. The study also explores the impact of digitalization, home delivery services, and promotional strategies on consumer preferences. The results offer valuable insights for fast food operators in Coimbatore to improve their offerings and maintain a competitive edge in the market.

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 Keywords

Customer Satisfaction, Fast Food Industry, Service Quality, Consumer Preferences, Coimbatore

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 Abstract

Ayurveda the science of life deals with health as well as curative aspect of diseases, the same time various diagnostic aspects of diseases also mentioned in Ayurvedic classics, such as Trividha Rogi Pariksha (Threefold Examination), Sadvidha Pariksha (Sixfold Examination), Aststhan Pariksha, Dashvidha Rogi Pariksha (Tenfold Examination) and Pratyatmik Linga. The diagnosis is based on two levels in Ayurveda that is Rogi Pariksha and Roga Pariksha. The Roga Pariksha is mentioned as Pratyatmik Linga and subtype of Lakshana of Vyadhi. There is confusion in all subtypes of Vyadhis look similar and certain Lakshana difficult to identify like Khrata and Rukshata in liquid substances. Also certain symptoms are very difficult to appreciate or generalized in a group of people few examples Laghuta, Guruta etc, and certain symptoms are unchanged till now like pain radiation in case of Gradhrasi. This problem may be answered as the symptatology is of two types; one is Subject based and another is objective. The subjective type may refer as principle based and objective type may be observation based. Ayurveda deals in diagnostic method with its tools like: Trividha Rogi Parikshha, Sadvidha Pariksha, Ashthsthan Pariksha, and Dashvidh Rogi Parikshha etc.

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Diagnostic Aspect, Ayurveda, Trividha Rogi Parikshha, Dashvidh Rogi Parikshha, Ashthsthan Pariksha etc.

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Abstract: In today's world, artificial intelligence is essential. The science of computers defines AI research as the study of intelligent agents. Whether on purpose or not, most people in today's world use computerized information processing technologies. Already, artificial intelligence (AI) is altering the way we live. A gadget that monitors its environment and takes steps to increase the possibility of reaching a goal. A database may accept a selection of users and articles as input, and its output will be a harsh recommendation. The user can enter data into the system either orally or in writing. A novel method for intelligent search is presented in this research. In general, a large number of people employ helpers worldwide. The provocative of using virtual assistant technology is discussed in this study. The application of virtual assistants, which can benefit humanity in many domains, is also introduced in this study. One significant emerging feature that will transform people's lives is voice control. Mobile phones, desktop computers, and laptops can all be equipped with voice assistants. Now by the using Assistant on any electrical device, voice assistant is a software agent that can understand human speech and answer in machine language.

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 Keywords

Keywords: Perception, artificial intelligence, Python, Voice Assistant, Chatbot.

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The rapid advancement of technology has paved the way for innovative solutions in remote healthcare monitoring, particularly through the integration of the Internet of Things (IoT), cloud computing, web applications, and artificial intelligence (AI)/machine learning (ML). This paper presents a comprehensive real-time e-healthcare monitoring system designed to collect, transmit, analyse, and visualize patient health data remotely. The system utilizes IoT-enabled sensors connected to an ESP32 microcontroller to gather vital signs, including heart rate, body temperature, and oxygen levels. The collected data is transmitted securely to a cloud-based database, where it is processed and made accessible via a web interface for healthcare professionals. Additionally, AI/ML algorithms are employed to analyze trends in patient data, enabling predictive healthcare insights and early detection of anomalies. By combining these technologies, the proposed system aims to enhance remote patient care, improve healthcare accessibility, and facilitate timely medical interventions.

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 Keywords

IoT, Real-time health monitoring, Cloud storage, ESP32 microcontroller, Web dashboard, AI in healthcare, Machine learning, Predictive analytics, Anomaly detection, Smart healthcare systems, Remote healthcare, Vital signs monitoring, Remote patient monitoring.

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In today's age of competition, the mathematical skills are highly required. The fast calculations are the pillars to clear any competitive exams. Vedic mathematics not on ly makes someone calculations speedy but also saves the time. Vedic mathematics should be implemented from school level to increase the interest of students in the subject. Vedic mathematics depends upon sixteen sutras of Sanskrit.

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Vedic, sutras, mathematics, calculations

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With the growing demand for personalized skincare, this project combines advancements in Artificial Intelligence (AI), dermatology, and nutrition to develop a comprehensive solution for tailored skincare recommendations. The existing system utilizes custom Convolutional Neural Network (CNN) models for basic skin condition detection, providing a foundation for personalized skincare. However, the proposed system enhances the precision of skin analysis by employing advanced CNN models, such as ResNet50, to improve accuracy in identifying various skin conditions. By integrating dermatological data with nutritional insights, the system offers highly personalized skincare routines that are specifically designed based on the user's unique skin type, condition, and dietary habits. This innovative approach bridges the gap between healthcare and AI, empowering users with actionable recommendations to optimize their skin health. By delivering personalized advice, the system not only supports skincare but also promotes a holistic understanding of how diet influences skin health, ultimately guiding users towards healthier skin through data-driven, customized care

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 Keywords

Personalized Skincare, Dermatology, Convolutional Neural Network (CNN), Skin Type, ResNet50, Nutritional Insights, Artificial Intelligence (AI)

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 Abstract

Infertility is a significant global health issue that affects millions of individuals and couples worldwide. It is defined as the inability to conceive after one year of regular, unprotected sexual intercourse and can result from a variety of medical, environmental, and lifestyle factors. The prevalence of infertility has been rising in both developed and developing countries due to factors such as delayed childbearing, increased prevalence of lifestyle diseases (like obesity and diabetes), and environmental pollutants. Despite its widespread impact, infertility remains a sensitive and often stigmatized issue, which limits open discussions and access to care. This paper explores the global burden of infertility, examining its causes, socioeconomic impact, and the challenges faced by individuals seeking fertility treatment. Additionally, it highlights disparities in access to fertility services, particularly in low- and middle-income countries, where cultural, financial, and infrastructural barriers significantly hinder treatment availability. The paper also reviews advancements in assisted reproductive technologies and their potential to address infertility, alongside the ethical considerations surrounding these treatments. Addressing infertility as an international health problem requires a multifaceted approach that includes improved awareness, better access to healthcare services, and global collaboration to reduce the stigma and barriers to treatment.

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Infertility, International health problem

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The present study focuses on enhancing the solubility and dissolution characteristics of Aceclofenac, a Biopharmaceutical Classification System (BCS) Class II drug with poor aqueous solubility, using the solid dispersion technique. The study employs two methods: fusion and solvent evaporation, incorporating PEG 6000 and PVP K32 as hydrophilic carriers. Preformulation studies, including FTIR analysis, confirmed no significant drug-excipient interactions, ensuring compatibility. Solid dispersions were prepared and evaluated for micrometric properties, flowability, in vitro drug release, and stability. Results: The results demonstrated a significant improvement in solubility and dissolution rates, particularly with the formulation ASDF3 (fusion method with PEG 6000), which exhibited superior dissolution characteristics compared to ASDS3 (solvent evaporation with PVP K32). Based on in vitro drug release studies, the solid dispersion method effectively improved the dissolution profile of Aceclofenac, highlighting its potential for enhancing the bioavailability of poorly soluble drugs. The findings suggest that polymer selection and preparation method significantly influence the drug's solubility and dissolution behaviour.

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Solubility, Aceclofenac, Solid Dispersion, and Rate of Dissolution.

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 Abstract

Vital capacity is crucial for athletes who must perform with endurance and strength for extended periods while maintaining a breathing mechanism. The present study comprised 20 male students of the University College of Physical Education and 20 other male post-graduation students of Bangalore University. The researcher used descriptive statistics and independent t-test tools to interpret the data. The mean value of other post-graduation students (OPS) and physical education students (PES) at Bangalore University is 3.76 and 4.18, respectively. The median values of OPS and PES at Bangalore University are 4.57 and 4.16, respectively. The standard deviation of OPS and PES at Bangalore University is 0.55 and 0.33, respectively. The minimum values of OPS and PES at Bangalore University are 2.53 and 3.58, respectively. The P-value is 0.002893. Since the p-value is less than 0.05 at the 1% level of significance. It is concluded that the vital capacity of PES is higher than that of OPS at Bangalore University.

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 Keywords

OPS: Other post-graduation students. PES: Physical education students. Vital capacity, T test

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 Abstract

This study examines consumer perceptions of reading English newspapers, with a specific focus on Coimbatore City. The growing impact of digital media on traditional print journalism has sparked a rethinking of consumer attitudes toward newspapers. This study looks at a variety of factors, including demographic impacts, preferences, reading patterns, and the perceived value of English newspapers among Coimbatore residents. The study polls a representative sample of newspaper readers to determine their reasons for reading, the type of information they prefer, and how frequently they consume newspapers. The findings are intended to provide insights into how English newspapers are evaluated in terms of reliability, relevance, and efficacy in providing customers' information demands.

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 Keywords

language,kwoledge,leadership,information

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As a selective serotonin reuptake inhibitor (SSRI), fluvoxamine has shown promise in large-scale, double-blind, randomized, controlled trials including people with panic disorder, obsessive-compulsive disorder (OCD), and social anxiety disorder (SAD). Furthermore, patients with a variety of obsessive-compulsive spectrum disorders, such as binge eating disorder, bulimia nervosa, pathological gambling, and body dysmorphic disorder, as well as those with post-traumatic stress disorder, have shown benefits. Fluvoxamine was the first SSRI to be licensed for the treatment of OCD in children and adolescents, and numerous well-controlled trials have confirmed its efficacy in treating OCD, SAD, and other anxiety disorders. Like other SSRIs, fluvoxamine is generally well tolerated; the most frequent adverse effect is nausea. It is not sedative or impairs cognitive function.

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 Keywords

Selective serotonin reuptake inhibitors (SSRIs), anxiety disorders, panic disorder, obsessive-compulsive disorder (OCD), social anxiety disorder (SAD), sexual dysfunction, drowsiness, cognitive impairment, and fluoxamine maleate.

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Artificial intelligence (AI) is a technology that creates computers that ensure that humans prepare things that involve intelligence. Natural Language Processing (NLP) is an extensively deliberated and explored topic at present. It is a subject that forms part of artificial intelligence (AI), which has attracted further consideration for demonstrating and examining human languagecomputationally. Its application has multiplied in numerous arenas like medicine, information extraction, email filters, machine translation, customer support, chatbots and virtual assistants, summarizations, etc. Different algorithms utilized for NLP are primarily reliant on the recurrent neural network. In the past few years, NLP has seen main developments as a result of the availability of enormous datasets, complex algorithms such as neural networks, and robust technology. This created a potential for machines to read and examine the unstructured input in the form of video, voice and writing. This review paper focus on the influence of machine learning in NLP. Also, highlights on Deep learning architecture, particularly recurrentneuralnetwork (RNN) and its variant, such as Long Short-Term Memory (LSTM). Furthermore, recent advancements in NLP and the application of NLP are discussed. This paper also examines the challenges and limitations of NLP. Finally, NLP in the health sector, finance, and conversational AI will also be addressed.

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Natural Language Processing (NLP), Deep Learning, Machine Learning, Recurrent Neural Network (RNN), Long Short-Term Memory (LSTM), Artificial Intelligence (AI), Morphological Analysis, Syntactic Analysis, Semantic Analysis, Discourse Analysis, Pragmatic Analysis, Chatbot, Generative Pre-Training (GPT).

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The Common Technical Document (CTD) was introduced to streamline the drug registration process over many countries, including the US, EU, and Japan, by standardizing the structure and content of regulatory dossiers. The aim of this strategy is to reduce the time, resources, and complexity required for pharmaceutical industries to secure marketing authorization in many nations. quality control, resource constraints, and language barriers continue to impact the execution of CTD, particularly in developing countries like India. The Common Technical Document (CTD) was introduced to streamline the drug registration process over many countries, including the US, EU, and Japan, by standardizing the structure and content of regulatory dossiers. the aim of this strategy is to reduce the time, resources, and complexity required for pharmaceutical industries to secure marketing authorization in many nations. quality control, resource constraints, and language barriers continue to impact the execution of CTD, particularly in developing countries like India. administrative data, technical summaries, quality data, non-clinical study reports, and clinical study reports are all covered in the five modules in which CTD is divided. The adoption of the CTD facilitates faster regulatory reviews, improved communication between regulatory bodies, and the potential for electronic submissions. in spite these Benefit, challenges such as regulatory harmonization issues, the volume and difficulty of data, quality control, resource constraints, and language barriers continue to impact the implementation of CTD, particularly in developing countries like India. This article explores the structure, advantages, challenges, and limitations of the CTD, offering insights into its global impact and the hurdles faced by the pharmaceutical industry in regulatory submissions.

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Regulatory Dossier : An Overview On CTD

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Assessing AI uses in institutions of higher learning has triggered this study, where the researcher seeks to establish what faculty feel and think about technologies concerning performance evaluation systems based on artificial intelligence. The study also focuses on how these experiences are influenced by demographic characteristics such as age, gender, education level, and teaching experience in a diverse sample from Coimbatore District. Altogether, the responses were largely positive, and the AI works as it is recognized for providing reasonable and unbiased comments that can benefit career development and correlate the work satisfaction. However, there are some lose ends with regards to lack of human intervention, a potential for algorithmic bias, lack of accountability. Concern with job and promotion opportunities and work-life imbalance also brings focus on segments that crave change. The present work mentions the strong connections between the experiences of faculty and demographic factors and concludes that there ought to be different approaches to AI implementation. To ensure that the system is effective and fair the research offers information on potential development which includes: a dual approach where the AI works under the supervision of managers and coaches while at the same time finding ways of maintaining work-life equilibrium.

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 Keywords

AI-driven evaluations, job satisfaction, faculty perceptions, algorithmic bias, transparency, professional development.

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The power sector plays a crucial role in economic development, but traditional financial assessments often overlook hidden costs such as environmental degradation, regulatory compliance, and public health impacts. This study explores the hidden financial burdens faced by power sector companies, with a specific focus on TATA Power. Using a mixed-method research approach, the study incorporates financial ratio analysis, regression models, and comparative performance evaluation (2015-2024) to assess the economic impact of hidden costs. Findings indicate that environmental costs, regulatory obligations, and health-related liabilities significantly affect profitability and investment decisions. While compliance measures increase operational costs in the short term, they enhance long-term sustainability and financial stability. The study emphasizes the need for transparent financial reporting, efficiency optimization, and regulatory reforms to mitigate hidden costs. Recommendations include greater investments in renewable energy, adoption of advanced emission control technologies, and regulatory cost-sharing frameworks. The findings provide valuable insights for investors, policymakers, and industry leaders, helping them develop strategies to balance profitability with sustainability in the power sector.

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 Keywords

Hidden Costs, Power Sector, Regulatory Compliance, Environmental Impact, Financial Performance

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