Digital transformation has become essential for organizations aiming to remain competitive and agile in a rapidly evolving technological landscape. Cloud computing plays a foundational role in enabling this transformation by offering scalable infrastructure, flexible services, and cost-efficient solutions. This paper presents a strategic roadmap for enterprises seeking to undergo digital transformation through cloud adoption. The roadmap integrates key migration stages, governance structures, and capability enhancements required to unlock the full value of cloud technologies. Drawing upon recent research, industry best practices, (...) and enterprise case studies, we propose a phased approach that aligns cloud adoption with business goals. A comparative table of cloud service models and a figure illustrating the transformation journey are included. The conclusion highlights long-term implications, including organizational change, innovation acceleration, and digital maturity. (shrink)

Jonathan Lear argues that the established purgation, purification, and cognitive stimulation interpretations of Aristotle’s concepts of catharsis and tragic pleasure are off the mark. In response, Lear defends an anti-cognitivist account, arguing that it is the pleasure associated with imaginatively “living life to the full” and yet hazarding nothing of importance that captures Aristotle’s understanding of catharsis and tragic pleasure. This analysis reveals that Aristotle’s account of imagination in conjunction with his understanding of both specific intellectual virtues and rational emotions (...) of an educated citizen not only tells against Lear’s anti-cognitivist construal, but also divulges an alternative cognitive stimulation reading. (shrink)

This paper defends the position that the supposed gap between biological altruism and psychological altruism is not nearly as wide as some scholars (e.g., Elliott Sober) insist. Crucial to this defense is the use of James Mark Baldwin's concepts of “organic selection”and “social heredity” to assist in revealing that the gap between biological and psychological altruism is more of a small lacuna. Specifically, this paper argues that ontogenetic behavioral adjustments, which are crucial to individual survival and reproduction, are also crucial (...) to species survival. In particular, it is argued that human psychological altruism is produced and maintained by various sorts of mimicry and self-reflection in the aid of both individual and species survival. The upshot of this analysis is that it is possible to offer an account of psychological altruism that is closelytethered to biological altruism without reducing entirely the former to thelatter. (shrink)

The paper explores the philosophical foundations and historical context of Fascism, tracing its roots from ancient idealist thought to its practical implementation in the 20th century. It examines the progression of ideas from Heraclitus’ doctrine of change to Plato’s Theory of Forms, Kant’s Transcendental Idealism, and Hegel’s Absolute Idealism, culminating in Giovanni Gentile’s Actual Idealism. Gentile’s philosophy, which emphasizes the collective will and the subordination of individual desires to the state, serves as the intellectual basis for fascism.

Both before and after the publication of Isaac Newton’s particulate theory of light, numerous wave theories of light were advanced by both philosophers and scientists (e.g., René Descartes, Thomas Hobbes, Robert Hooke, Francesco Grimaldi, and Christiaan Huygens). What is peculiar about this list, as frequently found in the scholarly literature on light, is that it refers to individuals who do not extend much further back than the seventeenth century. A close examination of Aristotle’s account of color and light in comparison (...) to Christiann Huygens’ theory of color and light, however, reveals that Aristotle deserves to be recognized as one who antedates and foreshadows these modern wave theorists. Indeed, we shall argue that Aristotle offered the first wave theory of color and light. On Aristotle’s theory, light is the actualization of a transparent medium such as air or water that makes possible the dissemination of color through the medium in a manner analogous to the dissemination of sound through air or water. (shrink)

Grounding chains are usually taken to be top-ist, grounded in the largest entity (the cosmos), or bottom-ist, grounded in the smallest entity(ies) (mereological atoms). Between these two, middle-ism, the view that grounding chains terminate in middle-sized entities (like iPhones, toasters, amoebae), is almost never considered. Sarah Bernstein in her paper Could a middle level be the most fundamental? argues for the plausibility for middle-ism. In this paper I argue against Bernstein in that middle-ism is a view much more problematic than (...) top-ism or bottom-ism. This is shown in three ways. The paper first shows how the middle level itself is problematic. The second problem is that middle-ism leads to a contradiction with respect to the notion of relative fundamentality, and third, middle-ism creates fatal problems for the parthood relation. Through these three issues, the paper shows how middle-ism is problematic in lieu of having fatal problems which refrain it from serving as the theory to explain fundamentalia and subsequently grounding structures. (shrink)

In this paper, I draw attention to various doctrines common to different Vedāntic traditions. In particular, I pay close attention to the doctrine of beginningless _karman_. I also note that this doctrine seems to stand in tension with Leibnizian Cosmological Arguments (LCAs) and Kalām Cosmological Arguments (KCAs). This tension arises because defenders of these arguments argue that an infinite causal regress or an actual infinite cannot be physically instantiated and because the doctrine of beginningless _karman_ seems to imply that such (...) a regress or actual infinite can be physically instantiated. I address this tension by showing that not all interpretations of beginningless _karman_ involve an infinite causal regress or an actual infinite. I close this paper by highlighting a few features that Vedāntic traditions have that make them more resistant to some objections to LCAs and KCAs. (shrink)

Albert Jonsen and Stephen Toulmin have argued that the best way to resolve complex “moral” issues in clinical settings is to focus on the details of specific cases. This approach to medical decision-making, labeled ‘casuistry’, has met with much criticism in recent years. In response to this criticism, Carson Strong has attempted to salvage much of Jonsen’s and Toulmin’s version of casuistry. He concludes that much of their analysis, including Jonsen’s further elaboration about the casuistic methodology, is on the mark. (...) In this essay, the details of Jonsen’s and Toulmin’s version of casuistry and the major criticisms against their approach to clinical decision-making are explicated. Furthermore, it is argued that Strong’s salvage efforts fail to deflect these criticisms. The upshot of this analysis, which includes a few additional criticisms, is that Jonsen’s and Toulmin’s version of casuistry is not an appropriate framework from which to resolve complex “moral” issues in clinical settings. (shrink)

Overview of the global warming/climate change debate.

Defenders of evolutionary medicine claim that medical professionals and public health officials would do well to consider the role of evolutionary biology with respect to the teaching, research, and judgments pertaining to medical theory and practice. An integral part of their argument is that the human body should be understood as a bundle of evolutionary compromises. Such an appreciation, which includes a proper understanding of biological function and physiological homeostasis, would provide a crucial perspective regarding the understanding and securing of (...) human health needs currently lacking in the medical arena. (shrink)

John Searle offers what he thinks to be a reasonable scientific approach to the understanding of consciousness. I argue that Searle is demanding nothing less than a Kuhnian-type revolution with respect to how scientists should study consciousness given his rejection of the subject-object distinction and affirmation of mental causation. As part of my analysis, I reveal that Searle embraces a version of emergentism that is in tension, not only with his own account, but also with some of the theoretical tenets (...) of science. I conclude that Searle has offered little to motivate scientists to adopt his proposal. (shrink)

In a recent commentary, Kim and colleagues argued that minimal-risk research should be deregulated so that such studies do not require review by an institutional review board. They claim that regulation of minimal-risk studies provides no adequate counterbalancing good and instead leads to a costly human subjects oversight system. We argue that the counterbalancing good of regulating minimal-risk studies is that oversight exists to ensure that respect for persons and justice requirements are satisfied when they otherwise might not be.

We argue that distinct conditionals—conditionals that are governed by different logics—are needed to formalize the rules of Truth Introduction and Truth Elimination. We show that revision theory, when enriched with the new conditionals, yields an attractive theory of truth. We go on to compare this theory with one recently proposed by Hartry Field.

This is a book review/critical review of Jackson and Depew's _Darwinism, Democracy, and Race: American Anthropology and Evolutionary Biology in the Twentieth Century_.

Debates about God’s personhood, or lack thereof, are central to philosophy of religion. This paper aims to advance these debates by presenting the “greatness of personhood argument” for God’s personhood and a dilemma for those who deny God’s personhood. I also consider various objections to this argument and this dilemma and argue that they fail. Notably, my reasoning in defence of personal theism is cross-cultural insofar as personal theists across various religious traditions can use it. Thus, this paper defends personal (...) theism in a manner that can bring Western and non-Western theists into closer dialogue regarding the topic of God’s personhood. (shrink)

Popular imaginations and receptions of Hinduism often neglect to consider its theological dimensions that conceive of the divine reality along conceptual pathways analogous to those of the major Judeo-Christian religious traditions. Thus, within Western scholarship, there have been no systematic attempts to delineate central doxastic elements within the Caitanya Vaiṣṇava tradition by suggesting correlations with distinctive Christian concepts, and this scholarly lacuna within Caitanya Vaiṣṇavism restricts comparative theological dialogue between Caitanya Vaiṣṇavism and Christianity. In order to address this lacuna, I (...) demonstrate that aspects of Caitanya Vaiṣṇavism’s theological framework can be conceptualized in conversation with their Christian counterparts. -/- By illustrating certain parities between the theological frameworks of Caitanya Vaiṣṇavism and Christianity, I also aim to pave the way for further comparative theological dialogue between these two religious traditions. In particular, I propose that Caitanya Vaiṣṇavism’s theological framework enables the tradition to become a suitable dialogical partner to Christianity in comparative theodicy. I also suggest and put into practice a criterion that can be helpful for refining the comparative theodical exchanges between Caitanya Vaiṣṇavism and Christianity. (shrink)

In this paper, we defend universalism, which we understand to be the thesis that all individuals will eventually attain communion with God, in a Vedāntic context. We first outline the specific ontological commitments that our view requires, such as the doctrines of karman and reincarnation, and we note one Vedāntic tradition that holds to all these commitments. We then outline the conceptual merits of our view. We also argue that certain objections to universalism do not undermine our view, as reincarnation (...) and karman provide a means for all individuals to eventually freely choose to devote themselves to God, making it extremely likely that all individuals will attain salvation. (shrink)

This paper identifies a puzzle in Miranda Fricker's account of testimonial injustice, the puzzle of hearer culpability: how is it possible for hearers to be culpable for beliefs they form on the basis of stereotypes and prejudices that regularly bypass conscious thought? In trying to solve this puzzle, I consider one way to hold hearers culpable despite stereotypes and prejudices bypassing conscious thought, that is, by focusing on the hearer's upstream epistemic practices. I then show that even factoring in upstream (...) epistemic practices, there are cases where the speaker sustains testimonial injustice without the hearer being culpable. To account for these cases then I suggest redefining testimonial injustice in a way that recognizes the role of wider structural factors, and not just individual failings. I sketch a view of this structural dimension of testimonial injustice, drawing on our understanding of another kind of epistemic injustice, hermeneutical injustice. Taking account of this structural dimension, I then offer a richer account of hearer culpability, one that understands culpability to fall on a spectrum. (shrink)

Traditionally, the problem of evil, in its various formulations, has been one of the strongest objections against perfect being theism. In the voluminous literature on this problem, the motif of evil has usually been discussed with respect to human flourishing. In recent decades more focused attention has been paid to animal suffering and the philosophical problems that such suffering poses for perfect being theists. However, this growing body of literature, in Anglo-American philosophical milieus, is largely aimed at sketching a specifically (...) Christian or Christianity-inflected theodicy that would reconcile animal suffering with the existence of an omni-God. In contrast, there are few, if any, systematic attempts to put forth a Hindu theodicy that aims to offer morally justifiable reasons that God has for allowing animal suffering. In this article, we address this scholarly lacuna by illustrating how a Hindu perfect being theist might respond to the problem of animal suffering. (shrink)

Book Review of Brian Fay's Contemporary Philosophy of Social Science.

Recently, Erik Baldwin and Tyler McNabb have brought Madhva's epistemological framework into active dialogue with Alvin Plantinga's religious epistemology and have argued that individuals within Madhva's tradition cannot make full use of Plantinga's epistemology, according to which, Christian belief resists de jure objections and can also have warrant. While I do not contest this specific claim, I demonstrate that an analysis of Madhva's epistemological framework reveals that this framework has its own resources through which it can resist de jure objections. (...) I address various objections to the rationality of Mādhvic belief and conclude that there are no de jure objections to Mādhvic belief that are independent of de facto objections. (shrink)

Black theology is a contemporary mode of theology that critically engages with specific theological motifs in order to affirm the humanity of blacks and emancipate them from white racism. At present, much black theological discourse occurs in Christian contexts, and thus, Hindu religious traditions are bereft of the socially transformative insights that such discourse produces. However, in this paper, I demonstrate that black theological motifs are present within Hindu theological frameworks as well. Specifically, I construct a distinctively Hindu black theology (...) by drawing upon certain theological motifs present within the theological framework of the Caitanya Vaiṣṇava Vedānta tradition. After constructing this black theology, I demonstrate its socio-theological implications and explain how it can fulfil the black theological aim of liberating blacks from white racism. (shrink)

Generative Artificial Intelligence (AI) has emerged as a transformative force in various fields such as art, healthcare, and entertainment. At the core of generative AI is the architecture of neural networks, which enables machines to produce content such as images, music, text, and even video. This paper explores the underlying architecture of generative models, focusing on neural networks that have revolutionized the creative and problem- solving capabilities of AI. We examine key types of generative neural networks, including Generative Adversarial Networks (...) (GANs), Variational Autoencoders (VAEs), and Transformer-based models, which utilize deep learning techniques to generate new data samples. By analysing the architecture of these neural networks, we aim to uncover how they function at a fundamental level, enabling AI to mimic complex human tasks. We delve into the technical aspects of each model, highlighting their strengths, limitations, and real-world applications. GANs, with their generator and discriminator networks, create new content by optimizing against each other, while VAEs leverage probabilistic encoding for generating data. Transformer models, on the other hand, have taken the spotlight due to their ability to understand long-range dependencies in data, making them invaluable in natural language processing and multimodal tasks. The paper also considers the challenges and ethical considerations in the use of generative AI, particularly regarding bias, authenticity, and societal impact. The findings of this study provide a comprehensive understanding of generative AI’s architecture and its potential future developments. (shrink)

The editorial introduces issue 21.1 of Technoetic Arts via a critical reflection on the artificial intelligence hype (AI hype) that emerged in 2022. Tracing the history of the critique of Large Language Models, the editorial underscores that there are substantial ethical challenges related to bias in the training data, copyright issues, as well as ecological challenges which the technology industry has consistently downplayed over the years. -/- The editorial highlights the distinction between the current AI technology’s reliance on extensive pre-existing (...) human-generated data for pattern recognition and the performative process inherent in art practice. Patterns of creative output can be replicated without a thorough understanding of underlying concepts. In contrast, the performative process of art practice, as explored through the conceptual frameworks of creativity by Noam Chomsky, Charles Sanders Peirce, and Roger T. Ames and discussed in previous publications by this editorial's author, creates concepts and continually ‘strives to extend itself towards the unknown.’ -/- Following this introductory section, the editorial provides an overview of the ten articles featured in this issue of Technoetic Arts. The first four texts engage with emerging technologies from various perspectives in art and design. The subsequent six articles, part of a special section titled 'Perspectives from Chandigarh,' reflect a quest for meaningful existence within colonial, patriarchal, and biopolitical structures that frame everyday practices of exclusion and oppression. (shrink)

Cloud computing has transformed data storage and processing, but the scale and complexity of these environments have also introduced new vulnerabilities. As cyber threats grow in sophistication, ensuring robust cloud security requires advanced computing power. High-Performance Computing (HPC) techniques—traditionally associated with scientific modeling and big data analysis—are now being adapted to address the challenges of cloud security. This paper explores how HPC architectures and techniques, including parallel processing, GPU acceleration, and distributed computing, are being leveraged to strengthen security in cloud (...) environments. We assess the integration of HPC with real-time threat detection, cryptographic operations, and machine learning-based intrusion detection systems (IDS), while also evaluating their impact on overall system performance. A proposed framework outlines the architecture of an HPC-enhanced cloud security system, and the paper concludes with future research directions for scalable and secure cloud infrastructures. (shrink)

The processing of time intervals in the sub- to supra-second range by the brain is critical for the interaction of primates with their surroundings in activities, such as foraging and hunting. For an accurate processing of time intervals by the brain, representation of physical time within neuronal circuits is necessary. I propose that time dimension of the physical surrounding is represented in the brain by different types of neuronal oscillators, generating spikes or spike bursts at regular intervals. The proposed oscillators (...) include the pacemaker neurons, tonic inputs, and synchronized excitation and inhibition of inter-connected neurons. Oscillators, which are built inside various circuits of brain, help to form modular clocks, processing time intervals or other temporal characteristics specific to functions of a circuit. Relative or absolute duration is represented within neuronal oscillators by “neural temporal unit,” defined as the interval between regularly occurring spikes or spike bursts. Oscillator output is processed to produce changes in activities of neurons, named frequency modulator neuron, wired within a separate module, represented by the rate of change in frequency, and frequency of activities, proposed to encode time intervals. Inbuilt oscillators are calibrated by (a) feedback processes, (b) input of time intervals resulting from rhythmic external sensory stimulation, and (c) synchronous effects of feedback processes and evoked sensory activity. A single active clock is proposed per circuit, which is calibrated by one or more mechanisms. Multiple calibration mechanisms, inbuilt oscillators, and the presence of modular connections prevent a complete loss of interval timing functions of the brain. (shrink)

Big data has increasingly been recognized as a transformative force in the sports industry, offering insights that were once impossible to gather through traditional methods. By leveraging vast amounts of real-time data from wearable devices, sensors, and video analysis, big data analytics can help athletes and teams make informed decisions to enhance performance, prevent injuries, and optimize training. This paper explores the role of big data in sports performance analytics, focusing on its application across various sports domains, including training optimization, (...) injury prevention, and game strategy. The study highlights key data sources, methodologies, and real-world case studies where big data analytics has led to significant improvements in sports performance. The potential for big data to revolutionize the future of sports is vast, with its continued evolution poised to impact athlete training, team management, and overall game strategies. (shrink)

Transfer learning has emerged as a powerful technique to overcome the limitations imposed by insufficient data in machine learning models. In many real-world applications, the amount of labeled data available for training is limited, making it difficult to train deep learning models effectively. Transfer learning addresses this challenge by leveraging knowledge gained from pre-trained models on large datasets and applying it to a new, related task with limited data. This allows models to benefit from previously learned features, reducing the need (...) for extensive labeled datasets. In low-data regimes, where the availability of labeled data is scarce, transfer learning has shown significant promise in fields such as medical imaging, natural language processing (NLP), and computer vision. It enables the transfer of learned representations from one domain to another, improving model accuracy and efficiency without the need for large-scale labeled data. However, transfer learning is not without its challenges. One of the key obstacles is the domain gap between the source and target domains, which can lead to suboptimal performance if the features learned in the source domain do not generalize well to the target task. Additionally, fine-tuning pre-trained models and selecting the right pre-trained source models pose significant difficulties. This paper provides an in-depth exploration of the role of transfer learning in low-data regimes, highlighting its applications, challenges, and methodologies. It presents a comparative analysis of transfer learning techniques across different domains, offering insights into the effectiveness and limitations of various strategies. We also explore current research directions and propose best practices for leveraging transfer learning in lowdata scenarios. (shrink)

This paper seeks to put forward an alternative approach to Psychological Egoism which attempts to capture what Psychological Egoism often alludes to. Thoughts of selfishness, thinking about one’s own role and gain in any action or event, the moralization of the concept of selfishness - all of these prompt us to think of humans as psychological egoists. Yet, certain examples such as a soldier jumping up on a grenade seemingly debunk the concept of Psychological Egoism. This paper seeks to redefine (...) and expand the basic tenets of want, Self, desire, Selfishness, behaviour, etc., to better explain the phenomena, behaviour and Self, that Psychological Egoism alludes to. This paper will do so by increasing the scope of the Self, and what it means to be Selfish through Humanist and Social psychology, and attempt to show how humans act in accordance with this new framework of psychological egoism. Various examples are to be used to demonstrate the application of this alternative approach, and, their real-world and moral consequences. (shrink)

As digital transformation accelerates, organizations are increasingly reliant on cloud-based services for flexibility, scalability, and cost-efficiency. However, the proliferation of cloud technologies has introduced new, sophisticated cybersecurity challenges. The traditional perimeter-based security model is no longer sufficient in safeguarding critical data and applications. This paper explores the evolving landscape of cybersecurity in the context of cloud computing and presents strategies for mastering security in the digital age. We discuss the importance of securing cloud-native applications, the role of advanced technologies such (...) as artificial intelligence (AI), machine learning (ML), blockchain, and quantum computing in securing cloud environments, and how organizations can implement a proactive security posture. By focusing on a multi-layered security framework, this paper provides insights into securing data, ensuring privacy, managing identity and access, and maintaining compliance in increasingly complex and dynamic cloud environments. (shrink)

Accurately predicting store sales is essential for businesses to optimize inventory management, marketing strategies, and staffing. Traditional sales prediction models often rely on historical data and simple linear trends, but these methods can be limited in capturing the complexity of factors that affect sales. This paper explores the application of machine learning (ML) algorithms to predict store sales, considering factors like promotions, holidays, weather conditions, and seasonal trends. We analyze various machine learning models, evaluate their performance, and demonstrate how they (...) can be used to improve sales forecasting and operational efficiency. (shrink)

The Artificial Intelligence (AI) is being used in healthcare in Jordan, paying special attention to the ethical and legal issues it brings. Although AI can greatly benefit health services by enhancing diagnostics, patient care, and how things run smoothly, it also raises some worries about data privacy, transparency, and following the rules. To understand the situation in Jordan better, the study involved a discussion group with healthcare workers, legal professionals, and AI experts. The results indicate that while the Jordanian government (...) is eager to embrace AI, there are some missing pieces when it comes to laws specifically for AI systems. Participants stressed the importance of strong regulations, clear ethical guidelines, and solid training for healthcare staff to make sure AI is used safely and fairly. If these issues are addressed, it could really change the way healthcare is delivered while ensuring that patient trust and ethical standards are upheld. (shrink)

Unlike other writing systems that are readily classifiable as alphabetic or syllabic in their structure, the Indic Devanagari script (of which Hindi is an example) has properties of both syllabic and alphabetic writing systems. Whereas Devanagari consonants are written in a linear left-to-right order, vowel signs are positioned nonlinearly above, below, or to either side of the consonants. This fact results in certain words in Hindi for which, in a given syllable, the vowel precedes the consonant in writing but follows (...) it in speech. The current research exploited this property of the script to examine when the disparity between spatial and temporal sequenc- ing would incur a processing cost and the implications of the findings from naming speed, accuracy, and writing order for the level at which words in Devanagari are segmented. The results support a partly phonemic and partly syllabic level of segmentation, consistent with the structural hybridity of the script. (shrink)

Drowsiness is a manner wherein one degree of awareness is reduced due to lacking of sleep or exhaustion and it may cause the driver fall into sleep quietly. A Drowsy or sleepy driver is not able to determine while he/she can have an out of control sleep. Fall asleep crushes are very extreme in terms of injury. Recent statistics estimate that annually 1,200 deaths and 76,000 injuries can be caused to exhaustion or drowsiness related crashes. More than 25% of highway (...) traffic accidents are caused as result of driver exhaustion. Reduce the risk of an accident by warning the driver of his/her drowsiness. This project is mainly based on four components 1) Face and Eye detection: Performs scale invariant detection using Haar Cascade Classifier perform through a webcam. 2) Eye feature extraction: Eye features are extracted using Hough Circle and 3) Extract single eye 4) Edge detection and perform drowsiness detection on it. In the proposed method, following the face detection step, the facial components those are more important and considered as the most effective for drowsiness, are extracted and tracked in video sequence frames. The system has been tested and implemented in a real environment. The contribution work is when drowsiness detected, after it will give alarm warning signal to the driver. (shrink)

The Internet of Things (IoT) is transforming industries by enabling devices to gather and share data. However, IoT devices often face limitations in processing power, storage, and energy consumption, restricting their ability to make complex decisions in real time. To address these challenges, cloud-assisted edge AI combines the advantages of edge computing and cloud-powered machine learning models, enabling IoT devices to make intelligent decisions at the edge while leveraging cloud resources for more complex processing tasks. This paper explores the integration (...) of edge AI with cloud assistance, demonstrating how this hybrid approach enhances decision-making capabilities in IoT devices. The paper examines key concepts, the architecture of cloud-assisted edge AI systems, application areas, and the benefits of combining edge and cloud computing. Furthermore, challenges such as latency, data privacy, and integration issues are discussed, alongside future directions for this technology in IoT applications. (shrink)

The deep learning methods for dealing with multi-class imbalance in water quality data are comprehensively examined in this paper. The findings show a notable increase in publications, especially since 2021, and a clear preference for deep learning techniques when classifying imbalanced data. Background: A thorough review of the body of literature included articles from significant digital libraries that were published between January 2012 and December 2024. Based on several important factors, such as commonly used datasets and types, years of publication, (...) different sources, research and empirical types, assessment measures, and development tools, 59 articles were chosen and examined. Objective: This study examines how deep learning techniques respond to data that is unbalanced when there are multiple classes and how the deep learning models' large capacity and intricate structures make them appropriate for these kinds of tasks, with an emphasis on water datasets. Conclusion: The paper emphasizes the difficulties with data diversity and computing efficiency, along with possible solutions for reliable real-world applications. It also discusses innovative solutions that enhance the reliability of real-world applications. (shrink)

Convolutional Neural Networks (CNNs) have revolutionized the field of computer vision, achieving state-of-the-art performance in tasks such as image classification, object detection, and semantic segmentation. This paper explores the latest advancements in CNN architectures, techniques, and applications, highlighting their evolution and impact on image-based tasks. We discuss the development of deeper and more efficient networks, the integration of transfer learning, the use of novel activation functions, and the application of CNNs in real-world scenarios such as medical imaging and autonomous driving. (...) We also review the trade-offs in computational efficiency and model performance, presenting a comparative study of the most prominent CNN architectures. Lastly, we examine future directions, including the role of unsupervised learning and hybrid models. (shrink)

As cyber threats become more sophisticated and perimeter-based defenses grow obsolete, Zero Trust Architecture (ZTA) has emerged as a transformative cybersecurity model. Zero Trust operates on the principle of "never trust, always verify," ensuring continuous authentication, least privilege access, and micro-segmentation. This paper explores the core concepts, benefits, and challenges of implementing Zero Trust in enterprise environments. Through a detailed review of recent literature, comparative analysis with traditional security models, and an architectural overview, this study demonstrates that ZTA significantly enhances (...) security posture against internal and external threats. The paper also outlines implementation strategies, highlighting the need for identity-centric and policy-driven approaches. (shrink)

As machine learning (ML) models become increasingly complex, their opacity presents a significant challenge for decision-making, particularly in high-stakes areas such as healthcare, finance, and law enforcement. These "black-box" models, while powerful, lack transparency, making it difficult for human decision-makers to trust and understand model predictions. Explainable AI (XAI) aims to address this issue by developing techniques to interpret and explain the outputs of ML models. This paper explores the importance of XAI in fostering trust, accountability, and fairness in AI-driven (...) decision-making systems. We review popular explainability methods such as LIME, SHAP, and counterfactual explanations, and present a comparative analysis of their effectiveness in different domains. We also discuss the ethical and regulatory implications of using XAI in real-world applications. (shrink)

Sign Language recongnition is getting more and more attention of the researchers due to its widespread applicability in many fileds. Conversation between both the deaf and the general population is becoming exceedingly challenging, and there is no reputable translator accessible in society to aid. This program enables real- time voice and signal language translation, in distinctive : 1. Recognizing male or female signals 2. Establishing a system learning model for interpreting image-to-text data. 3. Seeking innovative terms Four. 4. Constructing Sentences.5. (...) After creating all of the content. 6. Is to obtain the audio output. The goal of this research is yto develop a framework for potential sign language interpreter who could also translate conversations between sign languages into written and spoken English. If there had a translator like this, it would be much easier for many deaf and partially deaf people to interact with others in everyday situations. (shrink)

Generative Artificial Intelligence (AI) has revolutionized numerous industries by enabling the creation of realistic and novel content across various mediums, including art, music, writing, and video. However, with this power comes a significant set of ethical challenges. These challenges revolve around issues such as authorship, deception, bias, and the potential for misuse. This paper explores the ethical concerns surrounding generative AI, examining the delicate balance between creativity and deception. By analyzing the implications of AI-generated content, including deepfakes and synthetic media, (...) the study investigates the risks associated with AI in terms of misinformation, intellectual property rights, and the authenticity of creative work. Additionally, the paper evaluates current ethical frameworks and proposes guidelines for the responsible use of generative AI. Ultimately, it aims to provide a comprehensive overview of the ethical landscape in the realm of AI-generated content. (shrink)

The increasing demand for sustainable agriculture and efficient water usage has driven the innovation of smart irrigation systems. This paper presents a Smart Irrigation System powered by Internet of Things (IoT) technology, aimed at automating the irrigation process using real-time soil moisture and weather data. The system leverages a combination of sensors, microcontrollers, cloud services, and mobile applications to monitor and control irrigation activities remotely. It ensures efficient water management, reduces manual intervention, and improves crop yield. The proposed system demonstrates (...) the potential of IoT in transforming traditional farming into a data-driven, eco-friendly process. (shrink)

It has been observed that a wide range of students apply for different kinds of exams, including institutional, non-institutional, and occasionally even competitive ones. We are often dealing with multiple-choice questions in several tests because they are objective in nature. In these cases, automated scoring is typically applied. However, we still face difficulties when it comesto automating the scoring for subjective papers. The primary goal of our research is to design an algorithm that can automate the evaluation of answers. By (...) using a machine learning approach, we aim to develop a system that can maintain the scoring process while reducing the amount of human effort required. This would not only streamline the evaluation of subjective answers but also improve efficiency and consistency in grading. (shrink)

The proposed system employs AI technologies to analyze hand gestures in real-time as it functions for emergency alert transmission through CCTV camera feeds but works independently from verbal or physical signals. The system operates with Python-based technologies and OpenCV for live video streaming alongside MediaPipe for hand landmark detection through a standard webcam. The system detects predefined gestures including emergency signals through closed fists combined with stop gestures using open palms and victory signs by checking the relative landmark positions on (...) hands. In case the system detects an emergency gesture it retrieves positioning data through IPbased geolocation before automatically sending a message with gesture details and timestamp and coordinates. The system distributes the alert distribution task to different threads to maintain live video streaming processing continuity. The system contains a cooldown function that blocks subsequent alerts when they occur within short time periods. Low-end hardware and accessibility through lack of sensor dependency enable the system to deliver efficient operations. The system provides discreet signals for emergency help requests which prove useful to endangered individuals and people with disabilities and medical patients in crisis situations. Future improvements will create facial authentication capability in addition to SMS monitoring and mobile software release which will turn this product into a life-saving solution for public protection agencies. (shrink)

In this paper, we assess the impact of extended reality technologies as they relate to sexual forms of harassment. We begin with a brief history of the nature of sexual harassment itself. We then offer an account of extended reality technologies focusing specifically on psychological and hardware elements most likely to comprise what has been referred to as “the metaverse”. Although different forms of virtual spaces exist (i.e., private, semi-private, and public), we focus on public social metaverse spaces. We do (...) this to better explain how the concept of sexual harassment must be adjusted to such spaces and how approaches aimed at mitigating harassment must be sensitive to the type of metaverse spaces users utilize. We then offer a typology of sexual harassment for the metaverse focusing on three distinct forms of sexual harassment: (1) invariant (2) mixed variance or modified and (3) unique or metaverse specific. Although existing normative and legal frameworks may function well with respect to the first and, possibly, second forms of harassment, we argue such frameworks will not helpfully address metaverse-specific harassment. Ultimately, the changing nature of privately owned public spaces (POPS) which metaverses are likely to represent pose distinct ethical and regulatory challenges. (shrink)