A challenge to Kant’s less known duty of self-knowledge comes from his own firm view that it is impossible to know oneself. This paper resolves this problem by considering the duty of self-knowledge as involving the pursuit of knowledge of oneself as one appears in the empirical world. First, I argue that, although Kant places severe restrictions on the possibility of knowing oneself as one is, he admits the possibility of knowing oneself as one appears using methods from empirical anthropology. (...) Second, I show that empirical knowledge of oneself is fairly reliable and is, in fact, considered as morally significant from Kant’s moral anthropological perspective. Taking these points together, I conclude that Kant’s duty of self-knowledge exclusively entails the pursuit of empirical self-knowledge. (shrink)

Today the whole world is facing a very difficult time due to corona virus which initially originated in Wuhan city of China. In China an unusual pneumonia was noticed earlier which later recognized as a pandemic. There have been two events in the past wherein crossover of animal corona viruses to humans has resulted in severe disease, one was SARS-CoV and the other was MERS-CoV. The genetic sequence of the COVID19 showed more than 80% similarities to SARS-CoV and 50% to (...) the MERSCoV. Corona viruses are enveloped positive sense single-stranded RNA virus belongs to a large family in which all strains of the family do not have virulent capacity. World Health Organisation has classified COVID-19 as a β CoV of group 2B. Structurally, SARS-CoV-2 has four main structural proteins and several accessory proteins through which it enters into the cell. This virus enters the through ACE2 receptors, which are found on various organs in human body. After entering into one body, it enters to another body via transmission through sneezing, coughing etc. People who have had diabetes, chronic respiratory disease, cardiovascular disease, or even high blood pressure and cancer are at higher risk of coronavirus. (shrink)

Although there is such a thing as Indian thought, it seems to play no role in the way social sciences and philosophy are practiced in India or elsewhere. The problem is not only that we no longer employ terms such as atman, avidya, dharma to reflect on our experience; the terms that we do indeed use—sovereignty, secularism, rights, civil society and political society, corruption—seem to insulate our experience from our reflection. This paper will outline Gandhi’s framing of our predicament in (...) Hind Swaraj. It will then discuss three very different examples taken from our peculiar life with concepts that will also serve to clarify and illustrate the framework I am outlining. It will then very briefly discuss how Gandhi saw the Gita as showing him a way out of the predicament. (shrink)

Purpose: The aim of this study is to examine how the integration of Emotional Intelligence (EI) and Artificial Intelligence (AI) in leadership can enhance leadership effectiveness and influence the development of future leaders. -/- Design / Method / Approach: The research employs a mixed-methods approach, combining qualitative and quantitative analyses. The study utilizes secondary data sources, including scholarly articles, industry reports, and empirical studies, to analyze the interaction between EI and AI in leadership settings. -/- Findings: The findings reveal that (...) the integration of EI and AI significantly improves decision-making, strategic planning, talent management, and communication within organizations. Leaders who leverage both EI and AI experience higher employee satisfaction, improved team performance, and enhanced organizational outcomes. -/- Theoretical Implications: This study contributes to leadership theory by introducing a novel framework that demonstrates the complementary roles of EI and AI in leadership. -/- Practical Implications: The research offers practical guidelines for leadership development, emphasizing the need for future leaders to integrate EI and AI skills in order to navigate complex business environments successfully. -/- Originality / Value: The paper provides an original framework for the integration of EI and AI in leadership, offering new insights into how these two elements can work together to improve leadership effectiveness. -/- Research Limitations / Future Research: Future research should further explore the empirical impact of EI and AI integration in various industries and leadership levels to generalize findings across broader contexts. -/- Paper Type: Conceptual -/- . (shrink)

Bortolotti’s Delusions and Other Irrational Beliefs defends the view that delusions are beliefs on a continuum with other beliefs. A different view is that delusions are more like illusions, that is, they arise from faulty perception. This view, which is not targeted by the book, makes it easier to explain why delusions are so alien and disabling but needs to appeal to forensic aspects of functioning.

In this paper, I aim to resolve the Frierson-Grenberg debate on the nature of Kant’s account of moral motivation that took place in the third issue of Con-textos Kantianos. In their respective interpretations, Frierson and Grenberg fail to accommodate the a priori status of moral feeling when incorporating it into Kant’s moral motivational structure. In response, I provide a novel transcendental interpretation – one that takes the a priori moral feeling both as an incentive of morality and as that which (...) conditions the possibility of morality in human agents. I argue that Kant developed the notion of moral feeling solely in order to resolve the problem of motivational skepticism concerning the moral law. Since this problem occurs as a part of Kant’s search for the supreme principle of morality, the notion of moral feeling becomes a part of both Kant’s moral motivational structure and his argument to justify the moral law. (shrink)

The purpose of this work is to compare the ways in which relational databases—more especially, Microsoft SQL Server—and non-relational databases—MongoDB—handle unstructured data in JSON format. Although a lot of study has been done comparing different database management systems in terms of security, performance, and other aspects, little is known about how these databases are evaluated according to the type of data they handle. The main goal of this study is to examine the various features that relational and non-relational databases provide (...) for handling JSON data. We will conduct a number of tests to do this, making sure that the relevant data doesn't need to be normalised. To draw a conclusion, the outcomes of these studies will thereafter be examined. (shrink)

In the context of mid-level professional writing jobs, we examine the productivity effects of a generative artificial intelligence technology, namely the assistive chatbot ChatGPT. We used ChatGPT to randomly expose half of the 444 college-educated professionals to occupation-specific, incentive-based writing tasks in a preregistered online experiment. Our results show that ChatGPT considerably increases average productivity: output quality improves by 0.4 standard deviations and task completion time drops by 0.8 standard deviations. By compressing the production distribution, ChatGPT also lessens worker inequality, (...) mainly helping individuals with lesser starting abilities. ChatGPT shifts the focus of activities from rough-drafting to idea generation and editing, thereby replacing worker effort rather than enhancing worker skills. Furthermore, exposure to ChatGPT increases job satisfaction and self-efficacy while also heightening both concerns and excitement about automation technologies. (shrink)

Through an examination of Stack Overflow posts, this study explores Docker-related subjects and difficulties in order to pinpoint common problems and patterns in Docker development. We created an extensive dataset of Docker conversations by utilising both tag-based and content-based filtering techniques. These conversations were categorised using Latent Dirichlet Allocation (LDA) topic modelling, which showed that the most common theme is Application Development, which includes topics like Framework Management, Coding Problems, Data Transfer, and Docker-specific frameworks. Because of Docker's strong market presence, (...) developers are very interested in using it to build and manage apps, as evidenced by this dominant category. The study highlights important areas of interest and difficulty within the Docker community and offers insightful information on the many technical and operational problems faced by Docker developers. These findings offer guidance for future research, tool development, and educational resources, aiming to address the evolving needs of Docker practitioners and enhance the overall development experience. (shrink)

In the current digital environment, cyberattacks continue to pose a serious risk and difficulty. Internet of Things (IoT) devices are becoming more and more vulnerable due to security problems like ransomware, malware, poor encryption, and IoT botnets. These flaws may result in ransom demands, data tampering, illegal access, and system risks. Creating strong cybersecurity procedures for contemporary smart environments is essential to resolving these problems. This strategy uses proactive network traffic monitoring to spot any dangers in the Internet of Things (...) ecosystem. Our approach is to improve Smart Environments' security and awareness of potential threats. Two IoT gateways were used to examine the effectiveness and performance of a deep neural network (DNN) model. The results were promising: the model caused an average increase of less than 30 kb/s in network bandwidth and a mere 2% rise in CPU usage. Additionally, memory and power consumption were minimal, with 0.42 GB and 0.2 GB of memory usage for NVIDIA Jetson and Raspberry Pi devices, respectively, and an average 13.5% increase in power consumption per device. The machine learning models achieved nearly 93% detection accuracy and a 92% F1 score on the datasets used. Our framework demonstrates an effective and efficient method for detecting malware and attacks in Smart Environments. (shrink)

During an epidemic, it is very important to follow the instructions issued by the official authorities. One big step at this point is Social Distancing. It is very difficult for the authorities to keep a detailed look at whether social distancing norms are being followed or not. We meet situations where instead of following these rules patiently, people become frightened and often crowd the space. Therefore, for simple monitoring for the authorities (e.g. police officers) we propose a solution using the (...) Deep Learning process that will notify them as soon as a public violation occurs i.e., if the number of people is above the specified limit (the limit on the number of people that are allowed to be in one place at a time, specified by the government) or if the distance among two people is less than the specified limit. This program will not only reduce the effort and effort required to manually inspect each and every nearby location, but also help in saving time with the help of fast analysis in simple terms, CCTV cameras will help simultaneously monitor each public places. (shrink)

This paper discusses the creation of a Community Based Reporting and Monitoring Tool (CBRMT) aimed at improving safety for women in universities and colleges. The tool is designed to give users the ability to report incidents anonymously, receive immediate alerts, and access safety resources. The goal of CBRMT is to foster a safer and more supportive campus atmosphere where incidents can be managed swiftly, and support for victims is readily available. Through these initiatives, the tool aspires to encourage a safer, (...) more responsible, and inclusive culture across campuses globally. (shrink)

For computer simulation models to usefully inform climate risk management, uncertainties in model projections must be explored and characterized. Because doing so requires running the model many times over, and because computing resources are finite, uncertainty assessment is more feasible using models that demand less computer processor time. Such models are generally simpler in the sense of being more idealized, or less realistic. So modelers face a trade-off between realism and uncertainty quantification. Seeing this trade-off for the important epistemic issue (...) that it is requires a shift in perspective from the established simplicity literature in philosophy of science. (shrink)

Predictive analytics, empowered by generative AI and cloud technologies, has the potential to revolutionize educational practices by facilitating early intervention and proactive support for students. This chapter explores the integration of predictive analytics in educational settings, focusing on how datadriven insights can identify at- risk students and tailor interventions to their specific needs. By leveraging generative AI algorithms, educators can analyze vast amounts of data, including academic performance, engagement levels, and socio- emotional factors, to predict potential challenges before they escalate. (...) The chapter highlights case studies that demonstrate successful implementations of predictive analytics in schools and universities, showcasing improved student outcomes, enhanced engagement, and more personalized learning experiences. Additionally, it discusses the ethical considerations and challenges associated with data privacy and bias in AI systems. (shrink)

As the systematic revolution converges computing technologies with Artificial Intelligence (AI) applications, various industries have been transformed, ranging from healthcare to finance. This paper presents an extensive review of the progress achieved through this synergy, alongside the challenges and possible future perspectives. The methodology used in this study is a literature review supported by a theoretical model illustrating the integration of AI with computing. The findings reveal that computational capabilities, data processing speeds, and AI model efficiencies have drastically improved. However, (...) significant roadblocks persist, particularly in data privacy, ethical considerations, and hardware limitations. These challenges underscore the need for addressing the field’s boundless potential for breakthroughs. Existing hurdles, such as the lack of robust regulations, call for timely intervention. As we move forward, this paper emphasizes the necessity for ongoing innovation and the development of comprehensive policies to navigate the evolving landscape. Ultimately, our conclusion highlights the critical importance of preparing for these challenges to fully realize the transformative potential of the AI and computing synergy. (shrink)

Because of advanced automation, data exchange, and cyber-physical systems, traditional project risk management strategies are losing their effectiveness in the era of Industry 4.0. This study investigates how integrating Industry 4.0 technology into project risk management frameworks can have real-world implications. Using technologies like artificial intelligence (AI), big data analytics, and the Internet of Things (IoT), it proposes a new framework that enhances risk identification, assessment, and mitigation methods. In order to demonstrate how Industry 4.0 is transforming risk management practices, (...) this article examines real-world case studies and industry implementations. The framework addresses significant opportunities and challenges to provide practitioners with useful insights for adapting to the evolving technological context. The findings suggest that incorporating Industry 4.0 technologies can significantly improve risk management efficiency and project outcomes, offering a pathway for organizations to navigate the complexities of modern project environments. (shrink)

In one of his earliest dialogues, the Soliloquia, Augustine identifies the liberal arts (disciplinae) with truth (veritas), and employs this somewhat puzzling identification as a premise in his infamous proof of the immortality of the soul (Sol. 2.24). In this paper, I examine Augustine’s argument for this peculiar identification. Augustine maintains both (1) that the constituent propositions of the liberal arts are true, and (2) that the liberal art of dialectic (disciplina disputandi) is the “truth through which all disciplines are (...) true” (Sol. 2.21). I argue that Augustine identifies the liberal arts with truth because (1) the constituent propositions of the liberal arts are learned, and (2) dialectic’s structure is essential to the liberal arts. I further suggest that the subject matter of each liberal art reflects a distinct segment of intelligible reality, that is, the realm of the intelligible Forms. (shrink)

The Unified Medical Language System and the Gene Ontology are among the most widely used terminology resources in the biomedical domain. However, when we evaluate them in the light of simple principles for wellconstructed ontologies we find a number of characteristic inadequacies. Employing the theory of granular partitions, a new approach to the understanding of ontologies and of the relationships ontologies bear to instances in reality, we provide an application of this theory in relation to an example drawn from the (...) context of the pathophysiology of hypertension. This exercise is designed to demonstrate how, by taking ontological principles into account we can create more realistic biomedical ontologies which will also bring advantages in terms of efficiency and robustness of associated software applications. (shrink)

With the growth of data, data-intensive approaches for sustainability are becoming widespread and have been endorsed by various stakeholders. To understand their implications, in this paper data-intensive approaches for sustainability will be explored by conducting an extensive review. The current data-intensive approaches are defined as an amalgamation of traditional data-collection methods, like surveys and data from monitoring networks, with new data-collection methods that involve new information communication technology. Based on a comprehensive review of the current dataintensive approaches for sustainability, key (...) challenges are identified: the lack of data availability, diverse indicators developed from a narrowly viewed base, diverse definitions and values, skewed global representation, and the lack of social and economic information collected, especially among the business indicators. To clarify the implications of these trends, four major research assumptions regarding dataintensive approaches are elaborated: the methodology, epistemology, normativity, and ontology. Caution is required when data-intensive approaches are masked as “objective”. Overcoming this issue requires interdisciplinary and community-based approaches that can offer ways to address the subjectivities of data-intensive approaches. The current challenges to interdisciplinarity and community-based approaches are also identified, and possible solutions are explored, so that researchers can employ them to make the best use of data-intensive approaches. (shrink)

This project focuses on developing a community-based reporting and monitoring tool to improve women’s safety in colleges and universities. The tool allows users to anonymously report unsafe incidents, harassment, or suspicious activities, with features for immediate alerting to campus authorities and support groups. It integrates GPS tracking for emergencies and data visualization to monitor safety trends. Built using Java, XML, and Android Studio, the platform fosters collaboration between students, faculty, and administrators, encouraging proactive safety measures. By enabling discreet reporting and (...) real-time monitoring, the tool aims to create a safer campus environment for women. (shrink)

With the advent of the “Clean India” campaign in India, a renewed focus on cleanliness has started, with a special focus on sanitation. There have been efforts in the past to provide sanitation related services. However, there were several challenges in provisioning. Provision of sanitation is a public health imperative given increased instances of antimicrobial resistance in India. This paper focuses on sanitation provisioning in the city of Mumbai, especially in the slums of Mumbai. The paper compares and contrasts different (...) models of sanitation provision including supply-led provisioning of sanitation by the Indian government to demand-led provisioning of sanitation through a World Bank funded “Slum Sanitation Program” (SSP). The paper also outlines a comparative perspective on the implementation and usage of toilet blocks. The author presents the theory of social networks and positive peer pressure and argues that these will amplify the effect of other incentives. With the help of an illustration, this paper concludes that the sustainable sanitation policy should look at facilitating and creating the infrastructure as a network and not strictly at building toilet blocks. (shrink)

In this paper, a framework incorporating flexibility as a characteristic is proposed for designing complex, resilient socio-ecological systems. In an interconnected complex system, flexibility allows prompt deployment of resources where they are needed and is crucial for both innovation and robustness. A comparative analysis of flexible manufacturing systems, economics, evolutionary biology, and supply chain management is conducted to identify the most important characteristics of flexibility. Evolutionary biology emphasises overlapping functions and multi-functionality, which allow a system with structurally different elements to (...) perform the same function, enhancing resilience. In economics, marginal cost and marginal expected profit are factors that are considered to be important in incorporating flexibility while making changes to the system. In flexible manufacturing systems, the size of choice sets is important in creating flexibility, as initial actions preserve more options for future actions that will enhance resilience. Given the dynamic nature of flexibility, identifying the characteristics that can lead to flexibility will introduce a crucial dimension to designing resilient and sustainable socio-ecological systems with a long-term perspective in mind. (shrink)

There is a need for enterprises to incorporate information on the environment into decision making and to take action on ecological restoration. Within academia, a comprehensive understanding of the impacts on how business can serve sustainability transformation is still lacking as diverging holistic approaches and reductive approaches cloud academic thinking. The authors take a science-policy interface perspective to cover the role of cognitive proximity, matching and coordination of scientific knowledge from diverse stakeholders for effective policy making and implementation. We show (...) through a literature review that temporal and spatial scales, soil and land degradation, institutions and ecosystem, and the role of human behavior and narrative are not adequately emphasized in sustainability research. A scale-based picture, focusing on landscapes, institutions and practices is proposed which can be used to align diverse fields by acting as “bridge” for improved science policy interface and decision making, facilitated through cognitive proximity, matching, and coordination. A case study on a business association from South India is used to demonstrate the scales based approach in practice. A scale-based approach can play a key role in connecting human behaviour, a social science thematic topic, with ecosystems, a natural science thematic topic. (shrink)

Location analytics is key to get into the current market. It deals with movements data of customer which tells about the customer’s lifestyle, their behavior through understanding the visiting pattern. A geo-fence is a virtual boundary for a real-world geographic area. A geo-fence can be generated as per user’s need by considering different radius, or a geo-fence can be a predefined set of boundaries. Geo-fencing is use of geo-fence. Geo fencing is a feature that uses the global positioning system (GPS) (...) to define geographical boundaries. It has widely increasing scope. Very few applications are dealing with geo-notifications that are intended to inform the mobile/stationary user proactively about location specific information. The technology behind proactive location-based services is called Geo-fencing. (shrink)

This comprehensive article explores the convergence of cloud computing and Java technologies, highlighting their synergistic relationship in modern software development. It examines key concepts in cloud computing, including virtualization, microservices architecture, CI/CD practices, and serverless computing. The article also discusses various cloud service models (SaaS, PaaS, and IaaS), their applications, and essential tools and technologies for cloud development. A financial institution's infrastructure modernization case study illustrates the practical implementation of these concepts, demonstrating how cloud technologies and Java can enhance agility, (...) reliability, cost-efficiency, and innovation in traditional industries. (shrink)

The project is aimed at an arduous task of precise identification of medicinal plant species with the problem being pertinent in those industries that include botany, Ayurveda, pharmacology, and biomedical research. Most of the traditional identification methods are quite serious challenges for users, researchers, and students because they are usually time-consuming, knowledge-intensive, and prone to human errors. Our proposal develops an advanced web-based application for this process by utilizing state-of-the-art methods in image processing and machine learning. We will create a (...) platform where users can upload or take pictures of plant specimens and obtain accurate identifications and comprehensive medical information by using machine learning algorithms with plant species image datasets. This application is done in a way that the interface would be user-friendly and favor research, identification, and learning, especially for Ayurvedic practitioners, biomedical specialists, botanists, and students. Therefore, our project is aimed at developing an exhaustive and reliable solution for medicinal plant identification and study by overcoming the deficiencies of existing systems, such as a small dataset, poor variable quality, and lack of complete medicinal information. (shrink)

An important part of the Unified Medical Language System (UMLS) is its Semantic Network, consisting of 134 Semantic Types connected to each other by edges formed by one or more of 54 distinct Relation Types. This Network is however for many purposes overcomplex, and various groups have thus made attempts at simplification. Here we take this work further by simplifying the relations which involve the three Semantic Types – Diagnostic Procedure, Laboratory Procedure and Therapeutic or Preventive Procedure. We define operators (...) which can be used to generate terms instantiating types from this selected set when applied to terms designating certain other Semantic Types, including almost all the terms specifying clinical tasks. Usage of such operators thus provides a useful and economical way of specifying clinical tasks. The operators allow us to define a mapping between those types within the UMLS which do not represent clinical tasks and those which do. This mapping then provides a basis for an ontology of clinical tasks that can be used in the formulation of computer-interpretable clinical guideline models. (shrink)

The art of prediction of stock market volatility has always been a most challenged interdisciplinary research problem among scientist due to its highly non- linear nature of market flow. This paper tries to analysis the historical data of BSE Sensex using extreme volatilities estimators, GARCH, ANN and new proposed Text Mining approach for stock market predictions. Finally experimental results illustrates that the new proposed Text model can able to predict the volatilities of the stock price better than other models.

Andrea Kern contends that perceptual experience is perceptual knowledge if our self-consciously held capacity for perceptual knowledge is “perfectly” actualized. I argue that this view requires further justification. First, Kern is unable to support her claim that an awareness of our self-conscious capacity for perceptual knowledge is “contained” in all our perceptions. Second, Kern’s claim that perception includes the idea of the conditions of perception is potentially inconsistent with her denial that perceptual experience enables perceptual knowledge.

The Silent 'I' in Anger explores the deep-seated nature of anger and the transformative power of self-awareness. In the midst of emotional storms, the "I" within us remains silent, observing and offering a path to inner peace. This book serves as a guide for understanding anger not as an enemy, but as an opportunity for personal growth and emotional mastery. Through powerful insights and practical techniques, Ranjeet Kumar (Moksh) uncovers the quiet eye at the center of the storm—a place (...) of stillness that allows us to harness our emotions, rather than be overwhelmed by them. Discover how embracing this silent "I" can lead to profound calm in the chaos of life. (shrink)

Cloud computing has revolutionized how businesses operate by providing scalable infrastructure, cost efficiency, and flexibility. However, as organizations increasingly migrate sensitive data and mission-critical applications to the cloud, securing these resources has become more complex. This paper explores the concept of building resilient security layers in the cloud, an essential approach to mitigate cyber threats and safeguard digital assets. We examine the various security challenges in cloud environments, including data breaches, misconfigurations, and insider threats, and offer solutions to address them (...) through a layered security approach. By leveraging technologies such as encryption, identity management, access control, threat intelligence, and security automation, organizations can create robust defenses against emerging cyber risks. The paper also highlights the role of advanced tools, including Artificial Intelligence (AI), Machine Learning (ML), and blockchain, in enhancing the resilience of cloud security frameworks. Through case studies and best practices, we provide insights into how organizations can implement these security layers effectively, ensuring that their cloud infrastructure remains secure and reliable in the face of evolving threats. (shrink)

Plant health monitoring is crucial for sustainable agriculture, as early detection of diseases can prevent significant crop losses. This study presents a deep learning-based approach using the YOLO (You Only Look Once) model for real-time plant disease detection. The model is trained on a curated dataset of diseased and healthy plant leaves, enabling accurate classification and identification of plant conditions. The methodology involves image preprocessing, feature extraction, and YOLO inference for detection. A webbased interface is developed using Streamlit, allowing users (...) to upload images of plant leaves for analysis. Upon detection of a disease, the system provides preventive measures and treatment suggestions to help farmers and agriculturists mitigate the impact. The integration of Streamlit ensures an accessible and userfriendly platform, with the potential for future deployment as a standalone application. The proposed system enhances precision in disease identification, offering an efficient, scalable, and practical solution for plant health monitoring. (shrink)

This research focuses on developing an advanced UAV detection system using state-of-theart YOLOv8 and YOLOv9 models. By training these models on diverse datasets, we aim to enhance real-time detection accuracy and precision under various environmental conditions. The system is designed to improve UAV safety and minimize bird collisions. Through rigorous benchmarking, we demonstrate significant improvements in detection performance, accuracy, and computational efficiency compared to existing approaches. A user-friendly web interface, built using HTML, CSS, and Flask, provides real-time visualization of detection (...) results and system performance. This innovative system holds immense potential for applications in defense, airspace safety, wildlife conservation, and other UAV-dependent sectors. (shrink)

Wild Wise Weird: The Kingfisher Story Collection is an imaginative anthology that blends whimsical, wise, and strange tales. Filled with adventures, life lessons, and unique insights, it offers engaging and thought-provoking stories for readers of all ages. Perfect for fans of fantasy and the surreal, this collection captivates and inspires.

This paper explores the intersection between Advaita Vedanta's non-dualistic conception of consciousness and the evolving field of quantum physics, offering a dialogue between ancient metaphysical insights and modern scientific thought. Advaita Vedanta, an Indian philosophical tradition, posits that consciousness is the fundamental reality, transcending the material world, which it views as an illusion, or Maya. Similarly, contemporary developments in quantum physics challenge the classical materialistic worldview by revealing that reality, at its most fundamental level, is interconnected, probabilistic, and observer-dependent. This (...) philosophical dialogue aims to bridge these two domains by examining how quantum phenomena, such as wave-particle duality, non-locality, and the observer effect, resonate with Advaita’s concept of Brahman as the ultimate, non-dual consciousness. By exploring parallels between these seemingly disparate fields, this paper questions the limitations of materialistic interpretations of consciousness and proposes that quantum physics could offer a scientific framework to support Advaita’s assertion that consciousness is the substratum of reality. The discussion further investigates how the observer effect in quantum mechanics might align with the Advaitic principle that reality is shaped by consciousness. This study contributes to contemporary debates in the philosophy of mind and philosophy of science by proposing a unified model of consciousness that transcends dualistic divisions between mind and matter, advancing the possibility of a deeper metaphysical understanding of the universe. (shrink)

We provide a methodology for the creation of ontological partitions in biomedicine and we test the methodology via an application to the phenomenon of blood pressure. An ontology of blood pressure must do justice to the complex networks of intersecting pathways in the organism by which blood pressure is regulated. To this end it must deal not only with the anatomical structures and physiological processes involved in such regulation but also with the relations between these at different levels of granularity. (...) For this purpose our ontology offers a variety of distinct partitions � of substances, processes and functions � and integrates these together within a single framework via transitive networks of part-whole and dependence relations among the entities in each of these categories. The paper concludes with a comparison of this methodology with the approaches of GOTM, KEGG, DIP and BIND and provides an outline of how the methodology is currently being applied in the field of biomedical database integration. (shrink)

The project aims to address the critical need for a robust explosion risk assessment tool in the oil and gas industry, particularly in oil and gas refinery environments where safety is paramount. Traditional methods of threat assessment are often manual, subjective, and limited in their capacity to provide real-time insights, which poses significant challenges for industry professionals in managing potential hazards. Our project leverages real-time weather data and machine learning algorithms to develop an advanced web application designed to identify and (...) assess threat zones within oil and gas refineries. By utilizing refinery-specific datasets, real-time weather parameters, and machine learning models, the application enables users to upload or access refinery data, select industry-specific details, and receive accurate risk predictions along with stability class assessments. The application integrates the OpenWeatherMap API to provide up-to-date weather information, while a Random Forest classifier used for gas classification and some other parameters are calculated and trained on relevant features such as wind speed, cloud cover, and insolation levels to predict explosion risks. Designed with an intuitive, user-friendly interface, this tool will be invaluable for safety engineers, refinery managers, and environmental professionals, facilitating proactive risk management and informed decision-making. By addressing limitations in current risk assessment methods—such as limited access to real-time environmental data, variable risk levels, and lack of predictive analytics—our project aims to provide a comprehensive, data-driven solution for managing safety and mitigating risks in high-stakes industrial environments. (shrink)

The advancement of machine learning (ML) has revolutionized healthcare by enabling the early detection and diagnosis of multiple diseases. This paper presents a Multiple Disease Prediction System using machine learning algorithms to analyze patient data and predict the likelihood of diseases such as diabetes, heart disease, and kidney disease. The proposed model utilizes various ML classifiers, including Decision Trees, Random Forest, Support Vector Machines (SVM), and Neural Networks, to enhance prediction accuracy. The system aims to provide a costeffective, accurate, and (...) efficient tool for healthcare professionals and patients. (shrink)

By examining and comparing Gandhi’s statement that the Bihar earthquake of 1934 should be seen as divine punishment for the sin of untouchability with a similar claim in Kant’s writings, I argue that while Gandhi and Kant are, broadly speaking, remarkably similar in the way in which they relate morality, religion, and politics in conceptualising the categories of faith and superstition, they also seem to differ in their vocabularies and the propositional content of their respective moral psychologies. However, if we (...) are committed to dialogue across cultures, then the differences between Gandhi and Kant need not preclude reflective conversation between them. (shrink)

This project focuses on simplifying the legal documentation process for small businessesand individuals in India. Utilizing advanced technologies such as Optical Character Recognition (OCR) and AI-driven models, the system automatically drafts and simplifies complex legaldocuments. The platform features a user-friendly interface for easy input, integration withup-to-date legal resources, and ensures strict data privacy and security. By reducing the time, effort, and potential errors associated with legal documentation, the assistant aims to improve accessibility to legal services and promotegreater access to justice. (...) This documentation provides a comprehensive guide to the design, features, and implementation of the AI-powered solution. (shrink)

: In the realm of insurance, accurately predicting the charges or premiums that a policyholder will pay is a critical task. Traditional models may not fully capture the complexities involved due to the multifaceted nature of insurance data. This paper explores the use of machine learning (ML) techniques to predict insurance charges, providing a more data-driven and potentially more accurate method compared to conventional approaches. We will analyze various machine learning models, evaluate their performance, and discuss their potential for use (...) in insurance companies to enhance pricing accuracy and efficiency. (shrink)

The Legal Document Assistant project aims to make legal documentation more accessible and manageable for individuals and small businesses in India. Using artificial intelligence (AI), the platform simplifies the creation, updating, and management of legal documents for non-lawyers. Key features include a user-friendly interface that ensures accuracy and compliance with local regulations. A machine learning algorithm generates documents based on user inputs. To enhance security, the system uses One-Time Password authentication, requiring all parties to validate changes or updates, ensuring secure (...) and authorized modifications. By facilitating the creation of verified and legally sound documents, the Legal Document Assistant project makes legal services more accessible, minimizes errors, and saves time for individuals and small businesses across India. n. (shrink)

The goal of this project is to create a prototype smart farm using Internet of Things (IoT) technology. Developing an Internet of Things feeding control system and designing and implementing environmental monitoring and control systems for farm housing are the primary objectives. The development method uses open-source hardware and software and is conducted in pig farms in the Thai region of Nakhon Si Thammara. An ESP8266 Wi-Fi microcontroller is crucial to the system design, allowing several sensors to be connected to (...) the server and actuators to be controlled. The MQTT protocol is used to transmit data over a secure wireless local network. The data flow is designed using Node-RED, and storage is handled using a NoSQL database such as InFluxDB. The feeding control system achieved a 100% compliance rate by following instructions continuously. End customers can utilise a web application on their PCs or cellphones to obtain real-time data and operate the system. Furthermore, the collected data is processed and analysed as big data, which facilitates the analysis of climate change trends in the vicinity of the study site and forecasting. The overall performance rating of the system received great marks from users, averaging 4.40 out of 5 with a 0.46 standard deviation. As a result, the created IoT system functions as a prototype that may be further enhanced for use in bigger farms or other agricultural environments. (shrink)

In this essay, I investigate if self-respect as Robin Dillon conceives of it in her essay “Self-Respect: Moral, Emotional, Political” can be taught if we presuppose Barbara Herman’s theory of moral education. For Dillon, self-respect is a nonpropositionally held and emotionally forged interpretive orientation that determines one’s understanding of oneself. Further, it cannot be reconstituted through reason if it has been damaged. The claim that reason cannot remedy a lack of self-respect in persons is at odds with Herman’s reason-based training (...) in value. I argue that we do not have sufficient grounds to think that Herman’s reason-based training in value cannot help instil Dillon-type self-respect. (shrink)

This project aims to provide a comprehensive placement preparation platform designed for college campus placements, utilizing a modern tech stack to deliver a robust and efficient solution. Built with Node.js and integrated with MySQL Workbench for database management, this web application centralizes critical resources such as company-specific interview experiences, placement materials, preparation roadmaps, and eligibility criteria. Students can create an account and log in to access these resources, ensuring they have organized and up-to-date information to guide their preparation. With its (...) efficient backend powered by Node.js and structured data storage in MySQL, the platform delivers a seamless and responsive user experience. By addressing common challenges in placement preparation—fragmented information access, outdated resources, and lack of guided preparation paths—this application provides a centralized, user-friendly solution to enhance students' readiness and increase their chances of success in campus recruitment efforts. (shrink)

How can we make moral progress on factory farming? Part of the answer lies in human moral psychology. Meat consumption remains high, despite increased awareness of its negative impact on animal welfare. Weakness of will is part of the explanation: acceptance of the ethical arguments doesn’t always motivate changes in dietary habits. However, we draw on scientific evidence to argue that many consumers aren’t fully convinced that they morally ought to reduce their meat consumption. We then identify two key psychological (...) mechanisms—motivated reasoning and social proof—that lead people to resist the ethical reasons. Finally, we show how to harness these psychological mechanisms to encourage reductions in meat consumption. A central lesson for moral progress generally is that durable social change requires socially-embedded reasoning. (shrink)

In this paper current author proposes a need for studying intricate differences between psychological aspects, factors, cognitions, affect, behaviour and related dynamics. It can be promoted as a separate branch within the domain of Psychology as Intricacy Psychology. Case history taking for the new Intervention Meditation of current author is proposed in line with capturing such intricacies of the client. The current also proposes to study the intricacies belonging to ‘Self’ as an important factor within his new Intervention Meditation approach. (...) View of Self in line with current author’s new Intervention Meditation is also outlined. This paper is at the initial stage of the series of papers planned to develop his new Intervention Meditation approach which is entirely different from all other meditations in vogue. (shrink)

Arguments attempting to debunk moral beliefs, by showing they are unjustified, have tended to be global, targeting all moral beliefs or a large set of them. Popular debunking arguments point to various factors purportedly influencing moral beliefs, from evolutionary pressures, to automatic and emotionally-driven processes, to framing effects. We show that these sweeping arguments face a debunker’s dilemma: either the relevant factor is not a main basis for belief or it does not render the relevant beliefs unjustified. Empirical debunking arguments (...) in ethics can avoid this predicament, but only if they are refocused on highly selective classes of moral belief. Experimental data can combine with familiar consistency reasoning to reveal that like cases are not being treated alike. Selective debunking arguments are unlikely to yield sweeping sceptical conclusions, but they can lead to rational moral change. (shrink)

The present paper aims to study the origin and the development of karma and rebirth theory, which was the outcome of the collective historical experiment of multiple social groups under the socially shared ideological philosophical system of Ancient India. The existing historiography looked at it as a superfi- cial system dealing with certain ideas around religion and ritual. Therefore, it missed out on the other aspects related to it, which evolved around the notion of penance and punishment. That internalizes the (...) social order and justified the unaccounted inequalities by forcing individuals to self-surrender for violation of social and legal limitations of the concerned society. This present paper is going to look at this primary idea by focusing on multiple forms of karma and rebirth and the idea of the body in the same as depicted in Manusmrti. In addi tion to this, it will also check the inter-mixture of social and religious morality in the same through the historical process of ethnicization by making the base to the existing socio-economic environment of the concerned period. (shrink)

The AICTE approval process for institutions plays a critical role in regulating technical education in India, ensuring quality and adherence to established standards. However, the current system is cumbersome, leading to delays and inefficiencies. This paper proposes the development of an AI-powered assistive portal that automates key stages of the approval process. The portal aims to reduce manual errors, provide real-time feedback, and enhance user experience for stakeholders, thereby improving overall system efficiency and transparency.