India dropped its target of 500 GW of renewable energy capacity fossil fuel sources by 2030. Its responsibilities the United Nations Framework Convention Climate Change [UNFCCC],and reducing radiations by one billion tonnes by the end of the decade at the COP26 conference, held in Glasgow in November 2022. Researchers are continually searching for inexhaustible and reasonable energy sources. Solar energy is one of the greenest sources of energy and is also one of the cleanest. The most important factor in using (...) solar energy is the location of the solar power plant. The main objective of this study is to find the best location for a new solar power plant in a specific region called Bundelkhand region of Uttar Pradesh in India. Here we offer an extension of ELECTRE III method as two-phase Pythagorean neutrosophic elimination and choice translating reality PN-ELECTRE-III) method to adapt with fuzzy, ambiguous, unsure, and indeterminate criteria. The Pythagorean neutrosophic numbers [PNNs] used by the group decision support system of PN-ELECTRE III to measure performance of the alternatives. The options are entirely outclassed in the subsequent stage in view of the past stage's evaluations of them. By defining PNN we describe the technique of indifference threshold functions, preference treshold and veto threshold functions, which provide a more stable basis to drop outranking relations. By calculating the concordance credibility, discordance credibility and net credibility degrees of each alternative, the ranking module of the PN-ELECTRE III approach is made simpler. In order to confirm the applicability of the strategy suggested in this paper, the location selection problem for solar plants is finaly solved. (shrink)

The rapid advancement of Artificial Intelligence (AI) and the developments of Large Language Models (LLMs) like Generative Pretrained Transformers (GPTs) have significantly influenced content creation in scholarly communication and across various fields. This paper presents a comparative analysis of the content reliability between human-generated and GPT-generated scholarly articles. Recent developments in AI suggest that GPTs have become capable in generating content that can mimic human language to a greater extent. This highlights and raises questions about the quality, accuracy, and reliability (...) of such content, especially in academic contexts. Statistical evaluations and quantitative assessments conducted in this study uncover key differences in content accuracy, coherence, citation usage, and overall reliability between human and GPT-generated articles. The paper also examines the potential biases, the role of context, and the implications of AI-generated content for the future of scholarly communication. The study concludes with framework for predictive model indicating the potential future impact of GPT-driven content creation and recommendations for ensuring content quality and ethical considerations in AI usage. (shrink)

Facial Expression conveys non-verbal cues, which plays an important role in interpersonal relations. The Cognitive Emotion AI system is the process of identifying the emotional state of a person. The main aim of our study is to develop a robust system which can detect as well as recognize human emotion from live feed. There are some emotions which are universal to all human beings like angry, sad, happy, surprise, fear, disgust and neutral. The methodology of this system is based on (...) two stages- facial detection is done by extraction of Haar Cascade features of a face using Viola Jones algorithm and then the emotion is verified and recognized using Artificial Intelligence Techniques. The system will take image or frame as an input and by providing the image to the model the model will perform the preprocessing and feature selection after that it will be predict the emotional state. (shrink)

This fourteenth volume of Collected Papers is an eclectic tome of 87 papers in Neutrosophics and other fields, such as mathematics, fuzzy sets, intuitionistic fuzzy sets, picture fuzzy sets, information fusion, robotics, statistics, or extenics, comprising 936 pages, published between 2008-2022 in different scientific journals or currently in press, by the author alone or in collaboration with the following 99 co-authors (alphabetically ordered) from 26 countries: Ahmed B. Al-Nafee, Adesina Abdul Akeem Agboola, Akbar Rezaei, Shariful Alam, Marina Alonso, Fran Andujar, (...) Toshinori Asai, Assia Bakali, Azmat Hussain, Daniela Baran, Bijan Davvaz, Bilal Hadjadji, Carlos Díaz Bohorquez, Robert N. Boyd, M. Caldas, Cenap Özel, Pankaj Chauhan, Victor Christianto, Salvador Coll, Shyamal Dalapati, Irfan Deli, Balasubramanian Elavarasan, Fahad Alsharari, Yonfei Feng, Daniela Gîfu, Rafael Rojas Gualdrón, Haipeng Wang, Hemant Kumar Gianey, Noel Batista Hernández, Abdel-Nasser Hussein, Ibrahim M. Hezam, Ilanthenral Kandasamy, W.B. Vasantha Kandasamy, Muthusamy Karthika, Nour Eldeen M. Khalifa, Madad Khan, Kifayat Ullah, Valeri Kroumov, Tapan Kumar Roy, Deepesh Kunwar, Le Thi Nhung, Pedro López, Mai Mohamed, Manh Van Vu, Miguel A. Quiroz-Martínez, Marcel Migdalovici, Kritika Mishra, Mohamed Abdel-Basset, Mohamed Talea, Mohammad Hamidi, Mohammed Alshumrani, Mohamed Loey, Muhammad Akram, Muhammad Shabir, Mumtaz Ali, Nassim Abbas, Munazza Naz, Ngan Thi Roan, Nguyen Xuan Thao, Rishwanth Mani Parimala, Ion Pătrașcu, Surapati Pramanik, Quek Shio Gai, Qiang Guo, Rajab Ali Borzooei, Nimitha Rajesh, Jesús Estupiñan Ricardo, Juan Miguel Martínez Rubio, Saeed Mirvakili, Arsham Borumand Saeid, Saeid Jafari, Said Broumi, Ahmed A. Salama, Nirmala Sawan, Gheorghe Săvoiu, Ganeshsree Selvachandran, Seok-Zun Song, Shahzaib Ashraf, Jayant Singh, Rajesh Singh, Son Hoang Le, Tahir Mahmood, Kenta Takaya, Mirela Teodorescu, Ramalingam Udhayakumar, Maikel Y. Leyva Vázquez, V. Venkateswara Rao, Luige Vlădăreanu, Victor Vlădăreanu, Gabriela Vlădeanu, Michael Voskoglou, Yaser Saber, Yong Deng, You He, Youcef Chibani, Young Bae Jun, Wadei F. Al-Omeri, Hongbo Wang, Zayen Azzouz Omar. (shrink)

This eleventh volume of Collected Papers includes 90 papers comprising 988 pages on Physics, Artificial Intelligence, Health Issues, Decision Making, Economics, Statistics, written between 2001-2022 by the author alone or in collaboration with the following 84 co-authors (alphabetically ordered) from 19 countries: Abhijit Saha, Abu Sufian, Jack Allen, Shahbaz Ali, Ali Safaa Sadiq, Aliya Fahmi, Atiqa Fakhar, Atiqa Firdous, Sukanto Bhattacharya, Robert N. Boyd, Victor Chang, Victor Christianto, V. Christy, Dao The Son, Debjit Dutta, Azeddine Elhassouny, Fazal Ghani, Fazli Amin, (...) Anirudha Ghosha, Nasruddin Hassan, Hoang Viet Long, Jhulaneswar Baidya, Jin Kim, Jun Ye, Darjan Karabašević, Vasilios N. Katsikis, Ieva Meidutė-Kavaliauskienė, F. Kaymarm, Nour Eldeen M. Khalifa, Madad Khan, Qaisar Khan, M. Khoshnevisan, Kifayat Ullah,, Volodymyr Krasnoholovets, Mukesh Kumar, Le Hoang Son, Luong Thi Hong Lan, Tahir Mahmood, Mahmoud Ismail, Mohamed Abdel-Basset, Siti Nurul Fitriah Mohamad, Mohamed Loey, Mai Mohamed, K. Mohana, Kalyan Mondal, Muhammad Gulfam, Muhammad Khalid Mahmood, Muhammad Jamil, Muhammad Yaqub Khan, Muhammad Riaz, Nguyen Dinh Hoa, Cu Nguyen Giap, Nguyen Tho Thong, Peide Liu, Pham Huy Thong, Gabrijela Popović‬‬‬‬‬‬‬‬‬‬, Surapati Pramanik, Dmitri Rabounski, Roslan Hasni, Rumi Roy, Tapan Kumar Roy, Said Broumi, Saleem Abdullah, Muzafer Saračević, Ganeshsree Selvachandran, Shariful Alam, Shyamal Dalapati, Housila P. Singh, R. Singh, Rajesh Singh, Predrag S. Stanimirović, Kasan Susilo, Dragiša Stanujkić, Alexandra Şandru, Ovidiu Ilie Şandru, Zenonas Turskis, Yunita Umniyati, Alptekin Ulutaș, Maikel Yelandi Leyva Vázquez, Binyamin Yusoff, Edmundas Kazimieras Zavadskas, Zhao Loon Wang.‬‬‬‬. (shrink)

This volum includes 37 papers of mathematics or applied mathematics written by the author alone or in collaboration with the following co-authors: Cătălin Barbu, Mihály Bencze, Octavian Cira, Marian Niţu, Ion Pătraşcu, Mircea E. Şelariu, Rajan Alex, Xingsen Li, Tudor Păroiu, Luige Vlădăreanu, Victor Vlădăreanu, Ştefan Vlăduţescu, Yingjie Tian, Mohd Anasri, Lucian Căpitanu, Valeri Kroumov, Kimihiro Okuyama, Gabriela Tonţ, A. A. Adewara, Manoj K. Chaudhary, Mukesh Kumar, Sachin Malik, Alka Mittal, Neetish Sharma, Rakesh K. Shukla, Ashish K. Singh, Jayant (...) Singh, Rajesh Singh, V.V. Singh, Hansraj Yadav, Amit Bhaghel, Dipti Chauhan, V. Christianto, Priti Singh, and Dmitri Rabounski. (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)

Samuel Scheffler has argued that people value tradition for its own sake because they view it as accumulated experience, and as playing an important role in forming their personal integrity, structuring their lives, and providing them with a sense of belonging. These reasons, according to Scheffler, are de facto justifications that people offer for choosing to act on purely traditional grounds. In this essay, I argue that these de facto reasons must be supplemented if they are to be seen as (...) de jure rational grounds for valuing tradition for its own sake. Such a supplementation would open up the possibility of articulating a coherent theory of moderate cosmopolitanism. (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)

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)

that can serve as a foundation for more refined ontologies in the field of proteomics. Standard data sources classify proteins in terms of just one or two specific aspects. Thus SCOP (Structural Classification of Proteins) is described as classifying proteins on the basis of structural features; SWISSPROT annotates proteins on the basis of their structure and of parameters like post-translational modifications. Such data sources are connected to each other by pairwise term-to-term mappings. However, there are obstacles which stand in the (...) way of combining them together to form a robust meta-classification of the needed sort. We discuss some formal ontological principles which should be taken into account within the existing datasources in order to make such a metaclassification possible, taking into account also the Gene Ontology (GO) and its application to the annotation of proteins. (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)

There are a number of existing classifications and staging schemes for carcinomas, one of the most frequently used being the TNM classification. Such classifications represent classes of entities which exist at various anatomical levels of granularity. We argue that in order to apply such representations to the Electronic Health Records one needs sound ontologies which take into consideration the diversity of the domains which are involved in clinical bioinformatics. Here we outline a formal theory for addressing these issues in a (...) way that the ontologies can be used to support inferences relating to entities which exist at different anatomical levels of granularity. Our case study is the colon carcinoma, one of the most common carcinomas prevalent within the European population. (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)

The National Cancer Institute’s Thesaurus (NCIT) has been created with the goal of providing a controlled vocabulary which can be used by specialists in the various sub-domains of oncology. It is intended to be used for purposes of annotation in ways designed to ensure the integration of data and information deriving from these various sub-domains, and thus to support more powerful cross-domain inferences. In order to evaluate its suitability for this purpose, we examined the NCIT’s treatment of the kinds of (...) entities which are fundamental to an ontology of colon carcinoma. We here describe the problems we uncovered concerning classification, synonymy, relations and definitions, and we draw conclusions for the work needed to establish the NCIT as a reference ontology for the cancer domain in the future. (shrink)

In today’s competitive job market, job seekers often struggle to find suitable employment due to limited support and fragmented resources across various platforms. The PGRKAM Web Application addresses these challenges by centralizing employment data into a single, user-friendly platform that enhances job search efficiency. The application consolidates job listings from multiple sources, offers real-time notifications, and provides personalized job recommendations. It is structured with a two-tiered service model: a free version offering access to job listings and essential search features, and (...) a subscription-based version providing advanced support, including performance analysis, personalized training suggestions, and a structured feedback system to continuously improve employability. Optimized for web access and designed to support regional economic growth, the PGRKAM Web Application empowers job seekers with relevant, real-time data, ultimately increasing their chances of securing meaningful employment in Punjab. (shrink)

This paper provisionally offers a way of addressing the predicament of a person who does not feel at home in her own concepts, because these concepts were once forced upon her by a colonial regime. If the goal for a person in such a circumstance is to overcome this alienation through intellectual means, then one way in which this might be accomplished would be to develop a hermeneutics that would enable her to ascertain the alienating aspects of her existing concepts. (...) To this end, I outline a hermeneutical strategy which requires that, in reading the colonizer’s textual tradition, the colonized/ex–colonized person must heuristically presuppose that her current concepts are entirely determined by this tradition unless these concepts can be shown to resist such determination on reflective–systematic grounds. (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)

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)

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)

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)

In this essay, I investigate one aspect of Kant’s larger theory of the transcendental self. In the Prolegomena, Kant says that the transcendental self can be represented as a feeling of existence. In contrast to the view that Kant errs in describing the transcendental self in this fashion, I show that there exists a strand in Kant’s philosophy that permits us to interpret the representation of the transcendental self as a feeling of existence—as the obscurely conscious and temporally inaccessible modification (...) of the state of the discursive subject, which is built into all the representations of such a subject. I also provide an account of how the transcendental self can be legitimately understood both as an epistemic condition for the possibility of experience as well as the representation of a non-naturalistic feeling of existence. (shrink)

Can reasoning improve moral judgments and lead to moral progress? Pessimistic answers to this question are often based on caricatures of reasoning, weak scientific evidence, and flawed interpretations of solid evidence. In support of optimism, we discuss three forms of moral reasoning (principle reasoning, consistency reasoning, and social proof) that can spur progressive changes in attitudes and behavior on a variety of issues, such as charitable giving, gay rights, and meat consumption. We conclude that moral reasoning, particularly when embedded in (...) social networks with mutual trust and respect, is integral to moral progress. (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)

Evidence-based medicine relies on the execution of clinical practice guidelines and protocols. A great deal of of effort has been invested in the development of various tools which automate the representation and execution of the recommendations contained within such guidelines and protocols by creating Computer Interpretable Guideline Models (CIGMs). Context-based task ontologies (CTOs), based on standard terminology systems like UMLS, form one of the core components of such a model. We have created DAML+OIL-based CTOs for the tasks mentioned in the (...) WHO guideline for hypertension management, drawing comparisons also with other related guidelines. The advantages of CTOs include: contextualization of ontologies, providing ontologies tailored to specific aspects of the phenomena of interest, dividing the complexity involved in creating ontologies into different levels, providing a methodology by means of which the task recommendations contained within guidelines can be integrated into the clinical practices of a health care set-up. (shrink)

Ontological principles are needed in order to bridge the gap between medical and biological information in a robust and computable fashion. This is essential in order to draw inferences across the levels of granularity which span medicine and biology, an example of which include the understanding of the roles of tumor markers in the development and progress of carcinoma. Such information integration is also important for the integration of genomics information with the information contained in the electronic patient records in (...) such a way that real time conclusions can be drawn. In this paper we describe a large multi-granular datasource built by using ontological principles and focusing on the case of colon carcinoma. (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)

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)

Kant interpreters are divided on the question of whether determinate cognition plays a role in the harmony of the faculties in aesthetic judgement. I provide a ‘non-cognitive’ interpretation that allows Kant’s statements regarding judgements of natural beauty to cohere such that determinate cognition need not be taken to perform any role in such judgements. I argue that, in aesthetic harmony, judgement privileges the free activity of the imagination over the cognizing function of the understanding for the purpose of unifying the (...) object, although the free imagination cannot violate the obscure concepts and principles of ordinary common sense. (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)

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)

Security is a major concern on the internet, and Distributed Denial of Service (DDoS) attacks are a significant threat. These attacks overwhelm network resources and use up bandwidth, making it difficult for legitimate users to access services. One challenge in dealing with DDoS attacks is telling the difference between a sudden increase in traffic from real users, known as a "flash crowd," and actual attack traffic. This paper looks at different existing solutions for detecting DDoS attacks and explains how these (...) methods help reduce their impact. As more businesses move to cloud-based services, the risk of DDoS attacks has increased. These attacks can seriously disrupt organizations by overloading their network resources and making important services unavailable. Traditional defense methods, like firewalls, are no longer enough to handle the scale and complexity of modern DDoS attacks. To address this issue, We propose a new approach that utilizes the implementation of deep learning models to detect DDoS attacks in cloud environments. Our method uses various features from network traffic to train machine learning algorithms, aiming to effectively identify DDoS attacks in real-time with high accuracy. (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)

Quality assurance in large terminologies is a difficult issue. We present two algorithms that can help terminology developers and users to identify potential mistakes. We demon­strate the methodology by outlining the different types of mistakes that are found when the algorithms are applied to SNOMED-CT. On the basis of the results, we argue that both formal logical and linguistic tools should be used in the development and quality-assurance process of large terminologies.

In this paper, a new Intervention Meditation approach is outlined by the current author. To overcome lack of clarity in defining meditation, a new universal Operational definition of meditation is proposed with elaborative explanation. The new meditation approach has multitude of deeper concepts from Bhagavad Gita and modern psychology and the expert / Guru of the proposed method must be a qualified and experienced before getting trained on this approach specifically. This paper elevates meditation from a casual approach level to (...) a separate systematic branch of psychology level. (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)

1. Over the last 50 years or so, and especially over the last few decades, the U.S. and many other societies have undergone a large, rapid, and broad decline in anti-gay attitudes. The magnitude, s...

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)

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 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)

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 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.

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.

The AWSAR Job Portal is developed to provide job seekers with a platform to register, log in, and apply for jobs with ease. The purpose of this project was to create a full-stack web application, ensuring smooth user experience and addressing common challenges such as responsiveness and compatibility across browsers. The project used technologies like React.js, Tailwind CSS for frontend development, and Node.js with Express.js for backend management. MongoDB was implemented for database storage. The key challenge faced was the unresponsiveness (...) of the 'Apply to a job' button post-login, which was successfully resolved through code optimization. This manuscript discusses the system's architecture, methodology, issues encountered, and future enhancements. (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)

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)

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)

Gross Domestic Product is an total estimate of country’s economy, in terms of total productive output. It is of great importance to policy makers and central banks to know its trend and predict possible changes. It is of huge importance to coverage policy makers and central banks to know its trend and predict possible changes. This gives accurate assessment of the future state of the economy – whether it is heading toward expansion or contraction – such that preemptive actions can (...) be taken as appropriate. Reliable forecasting of GDP is a very important tool in the macro- economic toolbox. Unfortunately, national economies are very complicated and it isn't clean to version them accurately, not to mention expect their behavior. GDP forecast are very uncertain and unavoidably short-term. In this work we plan to use decision tree, bootstrap bagging and random forest. The motive for using these algorithms is that the random forest combines trees with the belief of an ensemble. Thus, the trees are weak learners and the random forest is a strong learner. The runtime of random forest is pretty fast, and they are able to handle an unbalanced and missing data. Bootstrap bagging reduces variance and helps to avoid over fitting. And by through the use of decision tree we can predict the classes for our training data. In this work we plan to implement a system that will help in GDP prediction. Manually it is very difficult and time consuming, tedious work to analyze data of whole country’s economical progress based on total production in country and all investments. We can take help of Machine Learning in this task. This will make our job easy and will give results in much less time. (shrink)