In this tenth book of scilogs – called via neutrosophica (the neutrosophic way) –, one may find new and old questions and solutions, referring mostly to topics on NEUTROSOPHY, but also MULTISPACE, with miscellaneous addition of topics on Physics, Mathematics, or Sociology – email messages to research colleagues, or replies, notes about authors, articles, or books, spontaneous ideas, and so on. -/- Exchanging ideas with A. Elhassouny, Junhui Kim, Jeong Gon Lee, Kul Hur, Hojjatollah Farahani, W. B. Vasantha Kandasamy, Said (...) Broumi, Mumtaz Ali, Mohamed Abdel-Basset, Ozen Ozer, Madad Khan, Gheorghe Săvoiu, John Mordeson, Adesina Agboola, Waldyr Rodrigues, Ajay Sharma, Stephen Crothers, Vlad, Dmitri Rabounski, Victor Christianto, Trung Duyên, Mirela Teodorescu, Ioan Aurel Pop.‬‬‬. (shrink)

This paper presents the design and implementation of a pattern-based J2EE application development environment aimed at streamlining the development process, enhancing code quality, and improving maintainability. We begin with an exploration of the fundamental principles of J2EE and the role of design patterns in software engineering. This is followed by a detailed discussion on the selection and application of various design patterns specifically tailored for J2EE, such as Singleton, Factory, Data Access Object (DAO), and Model-View-Controller (MVC).

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)

In ordеr to invеstigatе thе complеx naturе of cognition and its rеlationships, this rеsеarch articlе looks dееply into thе complеx intеrplay bеtwееn human thoughts and information from a philosophical standpoint. This study еxplorеs how psychology and nеurosciеncе intеrsеct in a philosophical sеtting in an еffort to prеsеrvе thoughts as an еxtеnsion of biology. By еxamining how a piеcе of information dеvеlops from a concеpt to an information hazard, thе rеsеarch еxplorеs thе potеntial еffеcts of hazardous information on both individuals and (...) largе groups. Thе study invеstigatеs thе history of information dangеrs and thеir еffеcts on human survival and moral viеwpoints while drawing inspiration from еvolutionary idеas. Thе kеy quеstion is: in tеrms of survival and morality, arе information hazards an assеt or a cursе? Throughout this rеsеarch, thе papеr sееks to clarify thе complеxity of human cognition and its nuancеd intеraction with information, offеring a philosophical prism through which to sее and discuss thе significant еffеcts of idеas in thе contеmporary еra. (shrink)

The author o ers a brief report of introducing the study of religion in India since 194 While doing so he refers to the Constitution of India, so-called Nehruvian Consensus, the Kothari Commission which made an important distinction between ‘religious education’ and ‘educa- tion about religion’, as well as several other bodies responsible for national policy on education, which gave a unique shape of Indian secularism.

The primary goal of this study is to analyse two extremes of leadership ideologies using philosophical notions as a perspective. It accomplishes this by exploring the leadership goals and the concept of freedom advanced by the Buddha and Christ's leadership views. This research will also look into how their leadership style affects society. Using an objective analysis, this study seeks to shed light on the codependent link between freedom, leadership, and the impact on human morality.

This work has done aiming to find out the effect of Covid -19 on the level of Anxiety and level of depression among the undergraduate students who live and study in urban area. As we know that during pandemic situation all classes for schools and colleges has been performed online .This mode of education has come in practice first time in life of students. Hence a level of depression and anxiety may develop in mind of under graduate college going students (...) who have been preparing for graduation and competitive exam. Going through the literature we found that the Hamilton Depression Scale & Hamilton Anxiety scale are suitable to measure Level of anxiety and depression .Both online and offline mode have been used to collect data from male and female candidate .A sample of 50 students male and 50 students have taken from Gwalior and nearby area . Two tailed T test has been done to analyze significant difference between the mean value of level of anxiety and level of depression as well for male and female candidate .Correlation coefficient has been determined to find the relation of variance between level of anxiety and level of depression between male and female students. SPSS software, Microsoft word and excel is use to arrange data, calculation, Tabulation and formation of chart. After data analysis and result and discussion it has concluded that the level of thinking and condition of living standard is almost same for male and female student in urban area .Hence there is no significant difference pertaining to level of anxiety and level of depression between male and female undergraduate student living in urban area. It is also come out that the There is no significance relation in level of anxiety and level of depression between male and female candidate. As we know that the corona virus has been spread in all over the world and so many people had lost their lives .In view of safety measure the government of India imposed lockdown of around 50 days in each part of country. All college and schools are closed and the final exams have also cancelled and many competitive exams have postponed. During this period of lock down undergraduate students have faced so many problems for continuing their study for their end semester exam and competitive exam as well .Due to uncertainty of their exams and their offline classes they experienced some level of depression and anxiety during this period .This project work is the assessment of level of depression and anxiety induced in male and female undergraduate students staying in urban area . (shrink)

Traditional project risk management techniques are becoming less and less effective in the age of Industry 4.0, which is defined by sophisticated automation, data interchange, and cyber-physical systems. It suggests a new framework that improves risk detection, assessment, and mitigation techniques by utilising technology like artificial intelligence (AI), big data analytics, and the Internet of Things (IoT). This paper illustrates how Industry 4.0 is revolutionising risk management procedures by looking at actual case studies and industry implementations. The framework offers practical (...) insights for practitioners looking to adjust to the changing technological landscape by addressing important possibilities and obstacles. According to the research, implementing Industry 4.0 technologies can greatly enhance project results and risk management effectiveness, providing a means for businesses to handle the challenges of contemporary project environments. (shrink)

This study investigates Docker-related topics and challenges through an analysis of Stack Overflow posts to identify prevalent issues and trends in Docker development. By leveraging both tag-based and content-based filtering methods, we compiled a comprehensive dataset of Docker discussions. Latent Dirichlet Allocation (LDA) topic modeling was employed to categorize these discussions, revealing that Application Development is the predominant focus, encompassing areas such as Framework Management, Coding Issues, Data Transfer, and Dockerspecific frameworks. This dominant category reflects developers' substantial interest in leveraging (...) Docker for building and managing applications, driven by Docker's significant market presence. The study provides valuable insights into the diverse technical and operational challenges faced by Docker developers, highlighting key areas of interest and difficulty within the Docker community. 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)

This article presents a comprehensive assessment of web services based on SOAP (Simple Object Access Protocol) and REST (Representational State Transfer) principles, focusing on their application in mobile environments and multimedia conference scenarios. As web services enable seamless communication and data exchange across diverse systems, understanding their performance characteristics in different contexts is crucial. SOAP, with its protocol-driven approach and emphasis on security and reliability, and REST, known for its simplicity, scalability, and efficiency, are evaluated using key performance metrics such (...) as latency, throughput, scalability, and reliability. This assessment aims to highlight the strengths and weaknesses of each approach, providing insights into their suitability for resource-constrained mobile applications and high-performance multimedia conferencing. The results and analysis offer valuable guidance for developers and decision-makers in selecting the most appropriate web service methodology to enhance application performance and user experience in these environments. (shrink)

We investigate the productivity impacts of a generative artificial intelligence technology—specifically, the assistive chatbot ChatGPT—within the realm of mid-level professional writing tasks. In a preregistered online experiment, we assigned occupation-specific, incentivized writing tasks to 444 college-educated professionals, with half of the participants randomly exposed to ChatGPT. Our findings reveal that ChatGPT significantly enhances average productivity: the time taken to complete tasks decreases by 0.8 standard deviations, and output quality improves by 0.4 standard deviations. Additionally, the use of ChatGPT reduces inequality (...) among workers by compressing the productivity distribution, primarily benefiting those with lower initial ability. ChatGPT primarily substitutes for worker effort rather than complementing worker skills, shifting the focus of tasks from rough-drafting to idea generation and editing. Furthermore, exposure to ChatGPT increases job satisfaction and self-efficacy while also heightening both concerns and excitement about automation technologies. (shrink)

Human beings as self-conscious, aesthetic, sympathetic, and empathetic beings develop various ways to live in this world. They continue to aspire for a better version of themselves and their lives. In this process, they developed certain ethical norms, social practices, and ways to perceive and understand this world. These qualities become the basis for proactive steps of spirituality which in turn become the foundation of religion. In human history, religion has helped individuals to fulfill various human needs irrespective of their (...) culture. Despite differences in the content of various religious philosophies, mythological structures, and religious ceremonies, it gave a sense of meaning and purpose to human beings. Because of its omnipresence, many philosophers along with biological and cultural evolutionary researchers have suggested coming up with a universal explanation for religion. -/- Nevertheless, religion was also employed as a means of exploitation by the powerful elites in various societies. Thus, many times, it worked as an orthodox, deceptive, and enslaving force for humanity. Modern thought emphasized the later effects of religion and found it less emancipatory. -/- Hence, enlightenment philosophy focused on rationality as a significant aspect of human beings. Besides, the development of science has unfolded various hidden and hitherto mysterious natural phenomena to mankind. This change has brought rationality to the forefront of human existence every institution began to build around this notion of human being. Even the death of God was announced by Nietzsche with grief in 1885. -/- Was it really the death of God? Can human beings live without religion sanely? These questions become very relevant particularly in recent times when we see resurgence of religious identities in the political and social discourses. However, consumer mythology and consumer culture remain at the forefront while making decisions in our daily lives across cultures. Even sometimes, religious identities are absorbed by powerful market forces; how to understand this contradictory phenomenon? -/- Between both these understandings, this paper sets three objectives for itself – first, to analyze the human need for religion from a psychological and existential perspective. Second, it critically evaluates the secular thesis as put forward by European enlightenment thinkers in the light of contemporary consumerist mythology. The third objective involves a brief description of universal religion and its relevance at this time. (shrink)

In the contemporary era, we identify ourselves based on what we consume or what we possess. Besides, various advertisements, celebrities, and other influential personalities encourage and make us believe that we can make a new identity by consuming a specific brand, or relating to a particular institution or connecting with an extraordinary group, etc. Hence, we tend to identify ourselves with consumer goods. In such conditions, Srimad Bhagwat Gita becomes significantly relevant to look for alternative way of life. This paper (...) attempts to explore the concept of Self in Gita as a model for realizing environmental consciousness. Largely, it will analyse the concepts of Nishkama Karma (Detached Action) and the Self to see what it may contribute in developing an apt environmental consciousness. With the analysis of these concepts the paper tries to probe for an epistemological and metaphysical alternative to the Ecology understanding. (shrink)

Husserl's Phenomenology: A Lacanian and Feminist Reappraisal -/- This study undertakes a comprehensive critique of Edmund Husserl's phenomenology, highlighting its limitations and omissions. Through Lacanian psychoanalysis, feminist perspectives, and intersubjective theories, this analysis challenges Husserl's notions of bracketing, reduction, and absolute givenness. Key concerns include the neglect of unconscious dynamics, symbolic structures, embodied experience, and cultural contexts. Critics such as Zizek, Sartre, Quine, and Rorty are engaged in addressing issues of solipsism, truth, and ideology. This evaluation underscores the need for (...) phenomenology to integrate diverse perspectives, ensuring a more inclusive and nuanced understanding of human experience. -/- Keywords: Husserl, Phenomenology, Lacanian Psychoanalysis, Feminist Theory, Intersubjectivity, Critical Evaluation. (shrink)

Among all non conventional micro machining, electrochemical discharge machining ECDM is having high quality of material removal rate with zero residual stress. This machining has been accepted as a highly modern technology in micromachining. In this paper an effort has been done on micro drilling of glass using electrochemical discharge machining ECDM . A fixed tool and a step down transformer have been used to support the steady machining to increase the accuracy of work piece. The input parameters used in (...) this experiment are voltage, concentration of electrolyte, enter electrode gap and ratio of area of electrode. MRR has been investigated over the input parameters. Feed rate and electrolyte temperature has been made constant of 3µm sec and 30°c respectively. Taguchi method is used to optimize the effect of the process parameters on MRR. The signal to noise S N ratio and the ANOVA analysis are employed to find the contributions of input parameters. Vikrant Sharma | Sunil Kumar "Experimental research to Optimize Process Parameters in Machining of Non Conducting Material with hybrid non conconventional machining" Published in International Journal of Trend in Scientific Research and Development (ijtsrd), ISSN: 2456-6470, Volume-1 | Issue-4 , June 2017. (shrink)

The examination of anomaly process detection using negative selection algorithms and classification techniques focuses on enhancing the ability to identify deviations from expected patterns within complex data sets. Negative selection algorithms, inspired by biological immune systems, offer a novel approach to anomaly detection by efficiently distinguishing between normal and anomalous data points. When combined with various classification techniques, these algorithms can improve the accuracy and robustness of anomaly detection systems. This abstract explores the integration of negative selection algorithms with traditional (...) and advanced classification methods to optimize anomaly detection processes. By leveraging these combined approaches, the study aims to address challenges such as false positives, detection latency, and adaptability to diverse data environments. The findings suggest that the synergy of negative selection algorithms and classification techniques can lead to more precise and reliable detection of anomalies, providing valuable insights for applications across cybersecurity, finance, healthcare, and other critical fields. (shrink)

The viewpoint of the Indian way of thinking is a greater amount of inborn as opposed to outward. Which gives more worth to current realities. In any event, to know the idea of fundamental reality, human insight first needs to know the idea of the outside world. It specifies are additionally predominant in Upanishads, where it has been expressed that faculties are more extraneous while knowing the external world. This research paper particularly centers around the idealist viewpoint with uncommon reference (...) to Indian Philosophy. For a superior understanding, it will be partitioned it into three sections, in the first part, idealistic Upanishdic contemplations will be thought of, in the second part Buddhist optimistic idea will be clarified and in the third part Advaita Vedantic considered vision will be described. (shrink)

Factor Affecting Customer Service in Supply Chain Management of Small and Medium Enterprises: An Empirical Study of Jammu Region -/- Author / Authors : Sanjeev Lalhotra and Prof. B.C Sharma Page no.149-165 Discipline : Applied Economics/ Management/ Commerce Script/language : Roman/English Category : Research paper Keywords: Customer services, Supply Chain Management, Small and Medium Enterprises.

A study was carried out from October, 2020 to September, 2021to investigate the diversity of fishes and the conservation status of Chittaura Jheel (Bahraich), Uttar Pradesh. During the study period, 38 fish species belonging to 28 genera, 14 families and 7 orders have been identified. The order Cypriniformes was found the dominated order with 15 species(39.47%) followed by Siluriformes 10 species (26.31%), Perciformes 4 species (10.52%), Ophiocephaliformes 4 species (10.52%), Synbranchiformes2 species (5.26%), Osteoglossiformes 2 species (5.26%) and Clupiformes 1 species (...) (2.63 %), The present investigation showed that the wetland, Chittaura Jheel possesses rich fish biodiversity but proper conservation measures are required to maintain sustainability and richness of the fish species diversity of that wetland of U.P. According to IUCN, 30 were enlisted as Least Concern (LC), 2 species as near endangered (NE), 3 species as near threatened (NT), 2 listed as Endangered (EN) and 1 species was listed as Vulnerable (VU). There is a need of conservation of fish diversity of this natural wetland. The pressure is increasing day by day due to increasing population, leading to loss of fish diversity hence identifying the problem and making a better management plan is the way for conservation of the fish diversity of the Chittaura Jheel, a wetland of Bahraich district of Uttar Pradesh. (shrink)

This paper examines about suggestions of the motion pictures. A film suggestion is significant in our public activity because of its solidarity in giving upgraded diversion. Such a framework can propose a bunch of motion pictures to clients dependent on their advantage, or the popularities of the films. A proposal framework is utilized to recommend things to buy or to see. They direct clients towards those things which can address their issues through chopping down huge data set of Information. A (...) recommender framework, or a suggestion framework (now and then supplanting 'framework' with an equivalent like stage or motor), is a subclass of data sifting framework that tries to anticipate the "rating" or "inclination" a client would provide for a thing. They are principally utilized in business applications, likewise assist clients with finding the motion pictures of their decisions dependent on the film insight of different clients in proficient and compelling way without burning through much time in pointless perusing. (shrink)

इस पर्चे में मैंने विज्ञान के विकास को आधुनिकता की पृष्टभूमि में मानव-मुक्ति के लक्ष्य की दशा व दिशा के सन्दर्भ में आलोचनात्मक विश्लेषण पद्धति से समझने का प्रयास किया है। इस कार्य के लिए मैंने पेपर में चार प्रमुख बिंदुओं को उढाया है। -/- पहला बिंदु विज्ञान की मूल्य निरपेक्षता (Value neutrality) को लेकर है जिसके तहत मैंने पूँजी के साथ विज्ञान के संबंध को समझने का प्रयास किया है। -/- दूसरे बिंदु में विज्ञान शिक्षा और सामाजिक सरोकार के (...) संबंध को वैज्ञानिक तार्किकता (Scientific rationality) और यांत्रिक तार्किकता (Instrumental rationality) के सन्दर्भ में समझने का प्रयास किया है। -/- तीसरे बिंदु में समाज में विज्ञान के अधिपत्य को लेकर उठाया गया है जिसके कारण विज्ञान का अन्य प्रकार की ज्ञान प्रणालियों से संबंध विच्छेद करने की प्रवित्ति को बढ़ावा मिलता है। -/- चौथे एवं अंतिम बिंदु में मैंने विज्ञान, तकनीक व विज्ञान का समाज के प्रति नैतिक उत्तरदायित्व के अंतरसंबंध को समझने का प्रयास किया है। . (shrink)

Twenty first century is posing unprecedented challenges for the human existence and development. This era has witnessed awesome economic & technological growth, increased connectedness but great poverty, malnutrition, anxiety, mental stress and environmental degradation. Thus, this time depicts great contradiction, uncertainty, and risk. Accordingly, in this era a holistic education system has to deal with the challenges such as population growth, terrorism, environmental degradation, hegemony of machines, mental stress, cultivating creativity, bridging the skill and wisdom gap, and expanding human potential (...) etc. To find a sustainable solution to such challenges, we need to develop a holistic education system which acknowledges various dimension of human being. For this task, this paper will try to highlight some philosophical themes which are commonly suggested by various prominent thinkers such as M.K. Gandhi, R.N. Tagore, J. Krishnamurti, S. Radhakrishnan etc. in India, and J. Dewey, I. Illich, and B. Russell etc. in the west. They have put forward their philosophy to discuss the aims of education which are relevant to this century. In this paper, we will analyze their views from the perspective of the challenges that the twenty-first century world is going to face. Our investigation will analyze agreements and disagreements among the approaches taken by these educators. However, the focus will be on the commonalities, so that we can identify some philosophical themes which can work as the solid foundation for holistic model of education. (shrink)

Cloud computing has transformed data management by providing scalable and on-demand services, but its open and shared infrastructure makes it highly vulnerable to sophisticated cyber threats. Traditional Intrusion Detection Systems (IDS) struggle with dynamic and large-scale cloud environments due to high false positives, limited adaptability, and computational overhead. To address these challenges, this paper proposes an AI-driven Intrusion Detection System (AI-IDS) that leverages deep learning models, including Convolutional Neural Networks (CNN) and Long Short-Term Memory (LSTM) networks, to analyze network traffic, (...) detect anomalies, and identify advanced cyber threats with high accuracy. Unlike rule-based IDS, which rely on static signatures, our model continuously learns from real-time data, improving detection rates while reducing false alarms. The proposed AI-IDS is optimized for cloud infrastructure, ensuring low-latency threat detection, minimal computational burden, and real-time adaptability to emerging attack patterns. Experimental validation on benchmark datasets demonstrates significant improvements in accuracy, precision, and scalability, making AI-powered IDS a crucial innovation in cloud security. (shrink)

In the rapidly evolving digital landscape, cyber threats are becoming increasingly sophisticated, making traditional security measures inadequate. Advanced Threat Detection (ATD) leveraging Artificial Intelligence (AI)-driven anomaly detection systems offers a proactive approach to identifying and mitigating cyber threats in real time. This paper explores the integration of AI, particularly machine learning (ML) and deep learning (DL) techniques, in anomaly detection to enhance cybersecurity defenses. By analyzing vast amounts of network traffic, user behavior, and system logs, AI-driven models can identify deviations (...) from normal patterns, enabling early threat detection and prevention. These systems excel in detecting zero-day attacks, insider threats, and advanced persistent threats (APTs), which often bypass conventional rule-based security mechanisms. Additionally, we discuss the challenges of AI-based anomaly detection, including false positives, model interpretability, and adversarial attacks. The findings emphasize the need for continuous learning and adaptive security frameworks to ensure robust cyber threat detection. The study concludes that AIdriven anomaly detection significantly enhances threat intelligence and response capabilities, making it a vital component of modern cybersecurity strategies. (shrink)

Distributed Cyber-Physical Systems (DCPS) are increasingly vulnerable to security threats due to their complex, interconnected nature. Traditional security mechanisms struggle to ensure trust, integrity, and resilience against malicious attacks and system failures. Blockchain technology, with its decentralized and immutable ledger, offers a promising solution to enhance security in DCPS. This paper explores the integration of blockchain with Practical Byzantine Fault Tolerance (BFT) to address security challenges in DCPS. PBFT consensus mechanisms enable systems to function reliably even in the presence of (...) malicious nodes, ensuring fault tolerance and data integrity. By leveraging blockchain and BFT, this approach mitigates single points of failure, enhances trust among distributed components, and secures communication against cyber threats. This paper presents a detailed analysis of blockchain-based PBFT models for DCPS security, evaluating their performance, scalability, and resilience. The findings demonstrate that integrating blockchain with PBFT enhances system reliability, improves data authenticity, and strengthens overall cybersecurity in DCPS environments. (shrink)

This document provides a brief report on initial research into how argument presentation affects susceptibility to confirmation bias as well as feelings toward political opponents.

This is an introduction to the section on Music and Politics including a description of the context of these essays, their individual contributions and their thematic interrelations.

Homomorphic encryption is a transformative cryptographic technique that enables secure cloud data processing by allowing computations on encrypted data without requiring decryption. Unlike traditional encryption methods, which protect data only at rest and in transit, homomorphic encryption ensures end-to-end security, even during computation. This capability is particularly vital for industries that rely on cloud computing while handling sensitive information, such as finance, healthcare, and government sectors. However, despite its strong security guarantees, the widespread adoption of homomorphic encryption remains limited due (...) to its high computational complexity and performance overhead. This paper examines the role of homomorphic encryption in secure cloud data processing by evaluating its advantages, challenges, and real-world applicability. First, a comprehensive literature review contrasts traditional and homomorphic encryption techniques, highlighting their security implications and efficiency trade-offs. Second, experimental simulations are conducted to assess computation time, scalability, and data transfer efficiency in cloud environments. The results underscore that while homomorphic encryption enhances data security, its feasibility depends on specific use-case requirements, balancing security, performance, and cost. Finally, we explore practical applications such as privacy-preserving data analytics and secure outsourcing of computations, demonstrating how homomorphic encryption can redefine cloud security paradigms. Keywords: Homomorphic encryption, cloud security, encrypted computation, privacy-preserving data processing, secure cloud computing. (shrink)

The increasing complexity and sophistication of cyber threats have rendered traditional perimeter-based security models insufficient for protecting modern digital infrastructures. Zero Trust Architecture (ZTA) has emerged as a transformative cybersecurity framework that operates on the principle of "never trust, always verify." Unlike conventional security models that rely on implicit trust, ZTA enforces strict identity verification, continuous monitoring, least-privilege access, and microsegmentation to mitigate risks associated with unauthorized access and lateral movement of threats. By integrating technologies such as artificial intelligence (AI), (...) machine learning (ML), and behavioral analytics, Zero Trust enhances threat detection, reduces attack surfaces, and ensures a proactive security posture across cloud, on-premises, and hybrid environments. This paper explores the core principles, implementation strategies, and benefits of Zero Trust Architecture, along with its challenges and future trends in cybersecurity. Furthermore, it highlights real-world applications and case studies that demonstrate the effectiveness of ZTA in protecting critical assets against advanced cyber threats. By adopting a Zero Trust approach, organizations can significantly improve their resilience to cyberattacks and ensure robust data protection in an evolving threat landscape. (shrink)

This paper attempts to argue that it is categorization, not generalization, that is more valuable by examining essence, interest, ontology, rationalism, and truth. While generalization is invariably oversimplified, categorization gives an exact insight with a fine grain into the entities by referring to their intrinsic properties. Categorization supplies an ordered, transparent form for knowledge through a rationalist approach, thereby arriving at clearer and more accurate representations of reality. The importance of categorization lies in its philosophical contribution to differentiating things in (...) the world, increasing understanding of related complexities, and hence showing it to be superior to generalization. (shrink)

Generative Adversarial Networks (GANs) have demonstrated significant potential in generating synthetic data for various applications, including those involving sensitive information like healthcare and finance. However, two major issues arise when GANs are applied to sensitive datasets: (i) the model may memorize training samples, compromising the privacy of individuals, especially when the data includes personally identifiable information (PII), and (ii) there is a lack of control over the specificity of the generated samples, which limits their utility for tailored usecases. To address (...) these challenges, we propose a novel framework that integrates differential privacy with latent representation learning to ensure privacy while providing control over the specificity of generated data. Our approach ensures that the synthetic data does not reveal individual data points, and by learning effective latent codes, it allows for the generation of specific and meaningful data. We evaluate our method using the MNIST dataset, showing that it preserves privacy and demonstrates a privacy-utility trade-off, where increased privacy leads to decreased classification accuracy. Additionally, we highlight the computational challenges, as the training process incurs a tenfold increase in time compared to standard GAN models. Finally, we extend our approach to the CelebA dataset, demonstrating how privacy and specificity can be controlled to generate high-quality, private synthetic data. (shrink)

The convergence of cloud computing, blockchain technology, and the emerging era of quantum computing presents significant challenges for data security. This research tackles these growing vulnerabilities by introducing a comprehensive security framework that integrates Quantum Key Distribution (QKD), CRYSTALS-Kyber, and Zero-Knowledge Proofs (ZKPs) to protect data in cloud-based blockchain systems. The primary goal is to safeguard information against quantum threats through QKD, a quantum-secure cryptographic protocol. To enhance resilience against quantum attacks, the framework employs CRYSTALSKyber, a lattice-based encryption mechanism. Additionally, (...) ZKPs are utilized to strengthen privacy and verification processes within cloud and blockchain ecosystems. A key aspect of this study is the performance evaluation of the proposed framework, focusing on encryption and decryption efficiency, quantum key generation rates, and overall system performance. The analysis examines practical considerations such as file size, response time, and computational overhead to assess the framework’s real-world applicability. The findings highlight the framework’s effectiveness in mitigating quantum threats and securing cloud-based blockchain storage. By addressing critical gaps in both theoretical research and practical implementation, this study provides valuable insights for organizations seeking quantum-resistant data security solutions. The framework’s efficiency and scalability demonstrate its feasibility, offering a roadmap for securing cloud environments against the evolving challenges posed by quantum computing and blockchain integration. (shrink)

Generative Adversarial Networks (GANs) have demonstrated significant potential in generating synthetic data for various applications, including those involving sensitive information like healthcare and finance. However, two major issues arise when GANs are applied to sensitive datasets: (i) the model may memorize training samples, compromising the privacy of individuals, especially when the data includes personally identifiable information (PII), and (ii) there is a lack of control over the specificity of the generated samples, which limits their utility for tailored use-cases. To address (...) these challenges, we propose a novel framework that integrates differential privacy with latent representation learning to ensure privacy while providing control over the specificity of generated data. Our approach ensures that the synthetic data does not reveal individual data points, and by learning effective latent codes, it allows for the generation of specific and meaningful data. We evaluate our method using the MNIST dataset, showing that it preserves privacy and demonstrates a privacy-utility trade-off, where increased privacy leads to decreased classification accuracy. Additionally, we highlight the computational challenges, as the training process incurs a tenfold increase in time compared to standard GAN models. Finally, we extend our approach to the CelebA dataset, demonstrating how privacy and specificity can be controlled to generate high-quality, private synthetic data. (shrink)

Deep fakes, a technology enabling the creation of highly realistic fake images and videos through face-swapping, have sparked significant attention due to their potential for misuse. This paper explores the technologies behind deep fakes and categorizes them into four types: deep fake pornography, political campaigns, commercial uses, and creative content. The authors discuss the ethical and regulatory challenges associated with each category. Initially, deep fakes were used maliciously, such as in revenge porn and political manipulation, which led to widespread fear. (...) However, like many technologies before it, deep fakes may eventually become more widely accepted. The paper also examines the role of online platforms and governments in addressing these issues and offers an optimistic view of how the democratization of AI might help resolve the ethical concerns surrounding deep fakes. (shrink)

As cloud-native architectures continue to evolve, microservices have become the foundation for scalable and resilient applications. However, the decentralized nature of microservices introduces significant security challenges, including service-to-service communication security, identity management, and traffic control. Service mesh technologies, such as Istio, Linkerd, and Consul, provide a powerful solution by offering decentralized security enforcement, mutual TLS (mTLS) encryption, fine-grained access control, and observability without modifying application code. This paper explores how service meshes enhance microservices security by implementing zero-trust policies, automatic traffic (...) encryption, and service authentication mechanisms. Through the integration of policy-based access control, workload identity, and anomaly detection, service mesh architectures significantly reduce the risk of unauthorized access, lateral movement attacks, and data breaches. Additionally, this study highlights best practices for deploying secure service meshes in cloud-native environments, ensuring compliance with industry security standards. The findings demonstrate that adopting a service mesh improves security posture while maintaining agility and performance in microservices-based applications. (shrink)

Misinformation has been a persistent and detrimental phenomenon in our society in many ways, including individuals' physical health and economic security. With the advent of short video platforms and associated applications, dissemination of multi-modal misinformation, including images, texts, audios, and videos, have increased these issues. The advent of generative AI models such as ChatGPT and Stable Diffusion has further enhanced the complexity, providing give rise to Artificial Intelligence Generated Content (AIGC) and posing new challenges in the detection and mitigation of (...) misinformation. Therefore, the conventional methods of misinformation detection and intervention have proved to be insufficient in this new paradigm. This paper examines the challenge posed by AIGC in the context of misinformation. It analyzes the problem from a psychological and societal point of view, and investigates the subtle manipulation traces in AIGC at signal, perceptual, semantic, and human levels. Through examining manipulation traces like signal manipulation, semantic inconsistency, logical incoherence, and psychological strategies, our goal is to address AI-generated misinformation and present a conceptual design of systematic explainable solution. Finally, we hope this paper will provide useful insights into the fight against misinformation, especially in the age of AIGC. (shrink)

The assessment of cloud data loss prevention and encryption was the main emphasis of the current study. Cloud computing, another name for cloud-based technologies, boosts organizational effectiveness for appropriate data management procedures. By improving data visualization, cloud-based data loss or leakage prevention (DLP) helps businesses comprehend the risks and problems associated with appropriate data management. This study demonstrated how to handle data with encryption. The growth of company processes and the effective management of all activities through data management can benefit (...) from cloud loss prevention. Cloud computing that is IoT and AI based evaluates the underlying reasons and offers a comprehensive understanding of business issues. As a result, they may encourage ongoing development and enhance their data loss risk management offerings. (shrink)

An increasing number of enterprises are using artificial intelligence (AI) to improve their cyber security and threat intelligence. AI is a type of AI that generates new data independently of preexisting data or expert knowledge. One emerging cyberthreat to systems that has been increasing is adversarial attacks. By generating fictitious accounts and transactions, adversarial attacks can interfere with and take advantage of decentralized apps that operate on the Ethereum network. Because fraudulent materials (such as accounts and transactions) used as malicious (...) payloads can be mistaken for legitimate data, detecting adversarial attacks can be difficult. This paper suggests a paradigm for cyber threat hunting in the Ethereum blockchain that makes use of Adversarial Networks (GAN) and Deep Recurrent Neural Networks (RNN). By considering a variety of sources and data points, this technology enables decision support systems to automatically and rapidly identify threats posed by hackers or other harmful actors. The likelihood of a successful assault can be further decreased by using AI to find weaknesses in an organization's infrastructure. Because security operations centers (SOCs) need to quickly identify threats and take defensive action, this technology is particularly wellsuited for them. AI can give businesses an extra line of defense against increasingly complex threats by integrating intriguing and useful data items that would have otherwise gone unnoticed. (shrink)

The rapid advancement of quantum computing poses a significant threat to classical cryptographic systems, particularly those based on RSA, ECC, and other public-key algorithms. With Shor’s algorithm capable of efficiently factoring large numbers and breaking current encryption standards, the transition to postquantum cryptography (PQC) has become a global priority. This paper explores the impact of quantum computing on cryptographic security, the need for quantum-resistant cryptographic algorithms, and ongoing standardization efforts led by organizations such as NIST. We analyze various post-quantum cryptographic (...) techniques, including lattice-based, hash-based, multivariate, and code-based cryptography, assessing their feasibility for real-world implementation. Additionally, we discuss the challenges associated with transitioning to PQC, including computational overhead, interoperability, and regulatory compliance. As the quantum era approaches, organizations must proactively adopt post-quantum cryptographic solutions to safeguard sensitive data and ensure long-term security in a quantum-capable world. (shrink)

: Ransomware remains one of the most significant cybersecurity threats, evolving rapidly with new attack vectors, encryption techniques, and extortion models. As we enter 2018, ransomware attacks have become more sophisticated, leveraging artificial intelligence (AI), automation, and emerging technologies to bypass traditional security measures. This paper analyzes the latest ransomware trends, including targeted attacks on critical infrastructure, Ransomware-as-a-Service (RaaS), and double/triple extortion tactics. Additionally, it explores advanced mitigation techniques such as AI-driven anomaly detection, zero-trust architectures, blockchain-based security solutions, and proactive (...) threat intelligence frameworks. By examining real-world case studies and industry best practices, this study provides insights into effective countermeasures and future directions for securing digital ecosystems against ransomware threats. The findings aim to assist cybersecurity professionals, policymakers, and organizations in strengthening their defense mechanisms against evolving ransomware threats in 2018 and beyond. (shrink)

t. Intense discussions concerning the hazards and ethical ramifications of artificial intelligence were sparked by its introduction and broad societal adoption. Traditional discriminative machine learning carries hazards that are frequently different from these risks. A scoping review on the ethics of artificial intelligence, with a focus on big language models and text-to-image models, was carried out in order to compile the recent discourse and map its normative notions. Enforcing accountability, responsibility, and adherence to moral and legal standards will become more (...) challenging as artificial intelligence systems get more adept at making decisions on their own. Here, a user-centered, realism-inspired method is suggested to close the gap between abstract concepts and routine research procedures. It lists five particular objectives for the moral application of AI: 1) comprehending model training and output, including bias mitigation techniques; 2) protecting copyright, privacy, and secrecy; 3) avoiding plagiarism and policy infractions; 4) applying AI in a way that is advantageous over alternatives; and 5) employing AI in a transparent and repeatable manner. Every objective is supported by workable plans, real-world examples of abuse, and remedial actions. This paper will discuss the nature of an accountability framework and related concerns in order to enable the organized responsibility for assignment and proof of AI systems. The suggested architecture for regulating AI incorporates crucial components like transparency, human oversight, and adaptability to address the issues with accountability that have been brought to light. Some crucial suggestions for putting the framework into practice and growing it were also provided through industrial case studies, guaranteeing that companies increase compliance, trust, and responsible AI technology adoption. (shrink)

The rapid proliferation of Internet of Things (IoT) devices in smart cities has introduced numerous benefits, enhancing urban efficiency, sustainability, and automation. However, these interconnected systems also pose significant cybersecurity challenges, including data breaches, unauthorized access, and cyberattacks that can compromise critical infrastructure. This paper explores various cybersecurity strategies tailored for IoT environments in smart cities, focusing on encryption techniques, secure authentication mechanisms, network security protocols, and blockchain-based security models. Additionally, it discusses machine learningbased anomaly detection systems to identify potential (...) cyber threats in real time. By analyzing existing security frameworks and emerging solutions, this study provides a comprehensive approach to safeguarding IoT devices in smart urban ecosystems. The findings emphasize the need for a multi-layered security model and proactive threat mitigation strategies to ensure the resilience and integrity of smart city infrastructures. (shrink)

The adoption of multi-cloud environments has become a strategic necessity for organizations seeking scalability, flexibility, and operational efficiency. However, distributing workloads across multiple cloud providers introduces significant security challenges, including authentication vulnerabilities, inconsistent security policies, data breaches, and compliance risks. Traditional security approaches often fail to address the complexity of multi-cloud ecosystems, requiring a more comprehensive risk mitigation strategy. This paper analyses key security risks in multi-cloud architectures and evaluates industry-standard risk assessment frameworks to prioritize effective countermeasures. Our findings indicate (...) that authentication, access control, and secure cloud networking are the most critical areas requiring immediate attention. Threats such as identity mismanagement, insecure data transfers, and lack of unified monitoring further escalate security concerns. To mitigate these risks, we propose a combination of zero-trust architecture, robust identity and access management (IAM), encryption protocols, and AI-driven threat detection. Implementing these strategies can enhance data integrity, regulatory compliance, and overall cloud security posture. By adopting a proactive approach, IT leaders can optimize cybersecurity investments and ensure the resilience of multi-cloud environments. This study provides actionable insights to strengthen security in distributed cloud architectures, enabling organizations to defend against evolving cyber threats. (shrink)

Hybrid cloud environments combine private and public cloud infrastructures to optimize security, scalability, and cost-effectiveness. However, ensuring secure access control in such environments remains a critical challenge due to dynamic workloads, multi-tenancy, and cross-cloud authentication complexities. This paper explores access control models tailored for secure hybrid cloud deployment, focusing on Role-Based Access Control (RBAC), Attribute-Based Access Control (ABAC), and emerging Zero Trust principles. We analyze their effectiveness in mitigating unauthorized access, privilege escalation, and insider threats. Additionally, a novel hybrid model (...) integrating RBAC and ABAC is proposed to enhance security and flexibility while ensuring compliance with regulatory frameworks. The study also highlights the role of federated identity management and blockchain-based access control mechanisms in strengthening authentication and authorization in hybrid cloud environments. The results indicate that adaptive access control strategies can significantly enhance security without compromising performance. Future research should focus on AI-driven access control mechanisms and self-learning security models to further improve dynamic access control in hybrid cloud settings. (shrink)

With the rapid evolution of information technology, malware has become an advanced cybersecurity threat, targeting computer systems, smart devices, and large-scale networks in real time. Traditional detection methods often fail to recognize emerging malware variants due to limitations in accuracy, adaptability, and response time. This paper presents a comprehensive review of machine learning algorithms for real-time malware detection, categorizing existing approaches based on their methodologies and effectiveness. The study examines recent advancements and evaluates the performance of various machine learning techniques (...) in detecting malware with minimal false positives and improved scalability. Additionally, key challenges, such as adversarial attacks, computational overhead, and real-time processing constraints, are discussed, along with potential solutions to enhance detection capabilities. An empirical evaluation is conducted to assess the effectiveness of different machine learning models, providing insights for future research in real-time malware detection. Keywords: Real-t. (shrink)

Valmiki , The Sage of 5th century B.C wrote The Ramayana not to narrate the story of Rama in an absorbing style. Though the epic poem presents Rama’s Journey of life in enchanting poetry , the story and the enchanting poetry are sugar coating or honey to the organic medicine called Kundalini Yoga. Maharshi Valmiki wrote the Ramayana to spread / propagate Kundalini Yoga among the masses. Thus the soul of The Ramayana is Kundalini Yoga / Sri Vidya. Valmiki embedded (...) Kundalini Yoga in the Chapter titled “ Sundara Kanda” . Hanuman and Ravana are Kundalini Yogis of Samaya and Kaula Paths. And in Sundara Kanda , he inserted “ Trijata Swapna “ , dream sequence of a demon and in it embedded the Gayathri Mantra. The concepts of Vishnu and Avatar (reincarnation) were nonexistent during the Ramayana Period. Seshendra Sharma , Scholar - Poet in his Magnum Opus of Research “ Shodasi : Secrets of The Ramayana “ reveals these secrets lying hidden for thousands of years . (shrink)

t. Intense discussions concerning the hazards and ethical ramifications of artificial intelligence were sparked by its introduction and broad societal adoption. Traditional discriminative machine learning carries hazards that are frequently different from these risks. A scoping review on the ethics of artificial intelligence, with a focus on big language models and text-to-image models, was carried out in order to compile the recent discourse and map its normative notions. Enforcing accountability, responsibility, and adherence to moral and legal standards will become more (...) challenging as artificial intelligence systems get more adept at making decisions on their own. Here, a user-centered, realism-inspired method is suggested to close the gap between abstract concepts and routine research procedures. It lists five particular objectives for the moral application of AI: 1) comprehending model training and output, including bias mitigation techniques; 2) protecting copyright, privacy, and secrecy; 3) avoiding plagiarism and policy infractions; 4) applying AI in a way that is advantageous over alternatives; and 5) employing AI in a transparent and repeatable manner. Every objective is supported by workable plans, real-world examples of abuse, and remedial actions. This paper will discuss the nature of an accountability framework and related concerns in order to enable the organized responsibility for assignment and proof of AI systems. The suggested architecture for regulating AI incorporates crucial components like transparency, human oversight, and adaptability to address the issues with accountability that have been brought to light. Some crucial suggestions for putting the framework into practice and growing it were also provided through industrial case studies, guaranteeing that companies increase compliance, trust, and responsible AI technology adoption. (shrink)