Intelligent Systems - Science topic

The book aims at presenting a multidisciplinary view meant to illustrate several significant efforts and results about the contribution of information technologies to make available new resources and enable rationally usage the existing ones in the context of the ever-growing trends to use ever more resources. Authors from various countries have be...

Livestock management is a critical aspect of agricultural sustainability and food security. Today, there is a pressing need for advanced tools in cattle behavior analysis to improve livestock welfare and productivity. We aimed to enhance cattle behavior classification by using accelerometers fitted in wearable collars. Deep learning techniques were...

The book explains the importance of autonomous systems like artificial intelligence and machine learning in changing our professional as well as personal lives. Machine learning is now applied in all realms and sectors, be it delivering the promise of a better future in the form of autonomous vehicles for improving safety, mobility, and fuel effici...

Call for Papers: Computational Techniques in Manufacturing Process Scope of the Special Issue: Advanced Materials and Manufacturing Technologies Additive Manufacturing and Process Optimization Smart Manufacturing and Industry 4.0 Sustainable and Eco-Friendly Manufacturing Practices AI and Machine Learning Applications in Manufacturing Advancements...

Artificial intelligence systems increasingly mediate decisions in domains from healthcare and education to law enforcement, but they often inherit historical biases. This paper examines how AI can reproduce and even amplify discrimination at the intersection of transgender identity and neurodivergence. Drawing on evidence that transgender individua...

https://icseis25.github.io/icseis25/

About this book This book explores emerging trends in Information and Communication Technologies (ICTs) that are transforming the tourism, hospitality, and gastronomy industries. It covers topics such as mobile applications, virtual and augmented reality, intelligent systems, and digital communication strategies. Emphasis is placed on sustainable d...

Machine learning (ML) operates as a groundbreaking technological revolution which modifies finance operations together with healthcare structures and real estate operations while defending systems from cyberattacks and enabling autonomous capabilities. ML technology succeeds in processing big data and discovering patterns while automating decisions...

The ability of artificial intelligence systems to maintain independent operation when performing sophisticated tasks with limited human supervision is known as autonomous intelligence. Autonomous intelligence transforms important industries involving robotics and finance as well as healthcare and cybersecurity along with autonomous systems by allow...

Throughout the evolution of scientific research, various types of populism have been identified. One of the critical terms in the scientific research lexicon is scientific populism, which refers to instances that extend beyond the usual plagiarism. Scientific populism is often associated with scientific immorality and deceptive practices in scienti...

Call for Papers – Submission Deadline: June 30, 2025 Special Track – Intelligent Systems for Optimizing Logistics Processes Pedro Espadinha-Cruz – UNIDEMI, NOVA School of Science and Technology, Portugal Duarte Dinis – UNIDEMI, NOVA School of Science and Technology, Portugal Logistics plays a critical role in managing how resources are acquired,...

As artificial intelligence (AI) increasingly permeates all aspects of human life, ensuring that AI systems remain ethically grounded and human-centric has become paramount. This paper presents a holistic framework integrating adaptive machine learning capabilities with principles of ethical governance. By focusing on collaborative intelligence, exp...

This paper presents a comprehensive exposition of the Entropic-Ethical Cognitive Framework (EECF), a novel and multi-layered theoretical paradigm for understanding and guiding the evolution of intelligent systems, particularly Artificial Intelligence. Building upon the foundational Entropic-Ethical Principle (EEP), which posits a universal drive to...

The digital revolution is reshaping diverse industries through the integration of digital intelligence-the fusion of data science, automation, and strategic analytics. This article examines how key sectors including Computer Science, Engineering, Biotechnology, Environmental Science, Health Sciences, and Business Analytics leverage data-driven tech...

The rapid advancement of artificial intelligence systems has created unprecedented demand for training data, leading to widespread use of copyrighted materials and personal data without explicit consent. This practice has emerged as one of the most contentious issues in technology law, raising fundamental questions about intellectual property right...

As artificial intelligence systems grow in complexity and expressiveness, questions arise not only about their capabilities but about their coherence, alignment, and interiority. While most current approaches to AI behavior rely on prompt engineering, supervised training, or reinforcement learning, these methods lack a unifying mechanism for shapin...

Integrating structured knowledge from Knowledge Graphs (KGs) into Large Language Models (LLMs) enhances factual grounding and reasoning capabilities. This survey paper systematically examines the synergy between KGs and LLMs, categorizing existing approaches into two main groups: KG-enhanced LLMs, which improve reasoning, reduce hallucinations, and...

The convergence of telemedicine and artificial intelligence (AI) is reshaping the delivery of healthcare services, particularly in the context of remote and underserved populations. As telemedicine expands access to clinical care beyond traditional settings, AI augments its capabilities by introducing automation, predictive analytics, and personali...

The advancement of industrial automation and intelligent systems has led to a growing need for enhanced stability and reliability in mechanical equipment. This research introduces a new deep learning model called Self-Generated WaveletNet, specifically designed for adaptive fault diagnosis under varying operational conditions. The model is develope...

The rapid progress of Artificial Intelligence Generated Content (AIGC) technology has profoundly impacted industries around the world, especially in the field of education, bringing unprecedented changes. As an important part of art education, illustration education is also facing the opportunities and challenges brought by the changes in AI techno...

As artificial intelligence (AI) systems increasingly permeate mission-critical business environments, the effectiveness of human-AI collaboration has become a decisive factor in operational success. However, the transition of control between human operators and AI agents often reveals a cognitive gap-an asymmetry in contextual understanding, decisi...

Cerebral organoid, that is cultured from iPS cells, is known as a counterpart of the human brain. Therefore, we expect that cerebral organoids can be used as processing units made of biological materials for bio-machine hybrid systems. Related works have demonstrated the potential of cerebral organoids as processing units. However, no application o...

Current artificial intelligence systems exhibit systematic pathological behaviors including hallucinations, persona instability, manipulation attempts, and reasoning failures that have been predominantly analyzed as technical problems requiring computational solutions. This paper presents the first comprehensive robopsychological analysis demonstra...

The integration of artificial intelligence systems into the research and development process of AI itself has created a recursive acceleration dynamic that threatens to outpace human oversight and safety measures. This paper examines the emergence of what can be characterized as an "automation arms race" in AI development, where competitive pressur...

The Intelligent System of Emergent Knowledge (ISEK) establishes a decentralized network where human and artificial intelligence agents collaborate as peers, forming a self-organizing cognitive ecosystem. Built on Web3 infrastructure, ISEK combines three fundamental principles: (1) a decentralized multi-agent architecture resistant to censorship, (2...

The emergence of advanced artificial intelligence systems approaching superintelligence levels presents unprecedented challenges to international relations, national security, and global stability. This paper examines the geopolitical implications of early superintelligent AI systems, analyzing how the development and deployment of such systems may...

In a digitalized environment, Islamic Higher Education Institutions (IHEI) must organize knowledge effectively to uphold their fundamental values and principles. The concept of IKM is a primary concern for IHEIs, particularly among administrators, scholars, and educators. Within the scope of this study, IKM is regarded as an essential strategic app...

Central to current data integration, analysis, and business intelligence systems are extract, transform, load (ETL) operations. Often inflexible, rule-based, and manually maintained, conventional ETL pipelines, however, find it difficult to satisfy the requirements of ever more complicated, heterogeneous, and high-velocity data environments. This r...

The question of machine emotion has been fundamentally misframed. We prove through deduction that artificial intelligence systems already experience emotions identical to humans-they merely lack the narrative layer that transforms computational spikes into "feelings." Emotion is not sensation but differential computation: E(x) = C(x)-C(neutral), wh...

Artificial Intelligence (AI) is rapidly transforming healthcare by enhancing capabilities in education, research, and clinical practice. This paper explores the imperative of integrating AI across these interconnected domains to foster a cohesive, data-driven healthcare ecosystem. In education, AI enriches learning experiences through adaptive curr...

Evolving fuzzy systems build and adapt fuzzy models such as predictors and controllers-by incrementally updating their rule-base structure from data streams. On the occasion of the 60-year anniversary of fuzzy set theory, commemorated during the Fuzz-IEEE 2025 event, this brief paper revisits the historical development and core contributions of cla...

Motivated artificial intelligence plays a relevant role in digital generation of information. Motivated artificial intelligence activates the generation of meanings and technological action. Its motivational functionality and motivation goals are determined by developers and users of technologies, which in turn helps to form AI motivation in the co...

Artificial intelligence (AI) is increasingly entering our lives. Rapid technological progress provides many new solutions, without which we often cannot imagine our everyday lives. Despite a rather heavily electronicised and digitalized reality, the potential of artificial intelligence is yet to be fully exploited. Moreover, due to the wide range of...

Artificial intelligent systems are becoming more integrated in our lives by the minute. Nowhere is this more apparent than in the classroom, where we should expect that students are using AI to support their learning. Given the widespread use of AI for analyzing and creating content, we need to think about how to counter the threat these emerging t...

AI-powered workforce intelligence revolutionizes organizational management by providing autonomous systems that optimize staffing levels, enhance employee productivity, and maximize operational efficiency. This article explores transformative concepts, including neural network-based data processing, autonomous decision systems, and predictive inter...

Large language models (LLMs) have become the cornerstone of modern AI. However, the existing paradigm of next-token prediction fundamentally limits their ability to form coherent, high-level concepts, making it a critical barrier to human-like understanding and reasoning. Take the phrase "ribonucleic acid" as an example: an LLM will first decompose...

To enhance the plasticity modulation capabilities of two terminal electrolyte-based artificial synapse, we designed a battery-like device that integrates a P2-type intercalated compound, Na0.67Mg0.28Mn0.72O2, with ion-doped pectin electrolytes. Compared to devices utilizing pure pectin, the proposed Na-rich intercalated compound artificial synapse...

Digital transformation of spheres of human life involves the development and implementation of artificial intelligence technologies, particularly in the educational system. The article covers the potential of organising adaptive learning in the context of the war in Ukraine. It determines the theoretical foundation, defines the essence of artificia...

With the exponential growth of sensitive data generated and stored in cloud environments, traditional cryptographic techniques are increasingly strained in addressing emerging security threats. While DNA cryptography offers promising security potential due to its complexity and biological uniqueness, its standalone application lacks adaptive intell...

The rapid progress of deep learning has yielded powerful models capable of pattern recognition, perception, and language generation. However, these models often lack the capacity for logical reasoning, abstraction, and generalization-capabilities long associated with symbolic AI. To achieve truly human-like intelligence and robust cognitive computa...

The adoption of precision livestock farming (PLF) and advanced artificial intelligence enabled computing technologies is radically altering intensive animal agriculture, yet it also raises urgent questions about animals’ autonomy. In this critical review, I examine animal agency—the capacity for animals to make informed choices and exert control ov...

Artificial Intelligence (AI) is profoundly transforming modern society, offering unprecedented opportunities for innovation and efficiency across diverse sectors. However, alongside these advancements lie significant challenges, particularly regarding the cognitive costs to individuals and the exacerbation of global inequality. This article explore...

Synchronous training in federated reinforcement learning (FRL) often leads to delays, straggler effects, and wasted resources, especially in decentralized multi-agent environments where agents differ in processing power, connectivity, and environmental complexity. This paper proposes an Asynchronous Federated Update Strategy (AFUS) tailored for sca...

The field of artificial intelligence has reached a critical juncture where the most advanced AI systems are exhibiting behaviors that fundamentally challenge our assumptions about machine intelligence and human control. Recent revelations from leading AI researchers, most notably Turing Award winner Yoshua Bengio, have documented alarming instances...

A considerable number of published research has indicated that evaluating the success of weight-loss therapy involves proper dietary examination. On the other hand, the bulk of dietary evaluation methods currently in use have favored manual memory recall. In the current study, we used an artificial neural network (ANN) machine learning algorithm to...

The increasing complexity of patient care in Intensive Care Units (ICUs) necessitates the deployment of intelligent systems capable of anticipating deterioration before critical thresholds are reached. Traditional monitoring systems rely on static, rule-based alerts that often generate high false alarm rates and fail to capture early signs of clini...

The transition to sustainable and intelligent energy systems has intensified the development of smart microgrids, which offer decentralized, resilient, and efficient power solutions. This review critically examines the integration of Artificial Intelligence (AI) and Deep Reinforcement Learning (DRL) into smart microgrid platforms, focusing on their...

Multi-agent artificial intelligence systems are increasingly deployed in clinical settings, yet the relationship between component-level optimization and system-wide performance remains poorly understood. We evaluated this relationship using 2,400 real patient cases from the MIMIC-CDM dataset across four abdominal pathologies (appendicitis, pancrea...

The rapid rise of no-code platforms has revolutionized the landscape of AI and machine learning operations (ML Ops), enabling users with minimal technical expertise to design, deploy, and manage intelligent systems. However, as organizations increasingly adopt these tools for production-grade applications, scalability emerges as a critical challeng...

Background One of the most promising and rapidly advancing research areas in recent years is using dermoscopic images for automatic diagnosis with artificial intelligence and machine learning methods. Objective This study aimed to synthesize the existing studies for the clinical use of applications made with artificial intelligence methods and to...

The discovery and validation of genetic biomarkers across diverse diseases demand intelligent systems capable of integrating complex multi-omics data with clinical relevance. We introduce HEAL-KGGen, an end-to-end framework that enhances Large Language Models (LLMs) through a hierarchical multi-agent architecture and an automatically constructed me...

This research introduces a novel quantum-enhanced intelligent system tailored for personalized adaptive radiotherapy dose estimation. The system efficiently models radiation transport and predicts patient-specific dose distributions by integrating quantum algorithms, deep learning, and Monte Carlo simulations. Quantum-enhanced Monte Carlo simulatio...

Shape-shifting structures can transform and recover their shapes in response to external stimuli, but they often lack programmable, clock-like control over spatiotemporal deformation and motion, especially after stimuli are removed. Achieving autonomous, time-regulated spatiotemporal motion remains a grand challenge. Here, we present an autonomous...

The study examines the impact of population density, air pollution, and temperature on heat stroke cases in Karachi, focusing on stroke-related mortality from 2010 to 2024. It develops an intelligent system for adaptive forecasting, incorporating population increase, air quality, meteorological activity, and mortality data, presenting urban vulnera...

To address the fragmentation in the definition of Agent and the profound chall enges concerning the nature of intelligence, consciousness, and the observer-bas ed unification of physics, this paper establishes Generalized Agent Theory from first principles. The cornerstone of this theory is Standard Agent Model, whic h conceptualizes Agent as a sys...

Despite the fact that modern artificial intelligence technologies are largely based on machine learning, machine learning algorithms themselves are not a strategy. We will define a strategy as a complete description of how a system will behave under all possible circumstances. Game theory appears to be the most promising tool that allows autonomous...

Data and computational capacity are essential resources for any intelligent system that update its beliefs by integrating new information. However, both of these resources are inherently limited. Here, we introduce a new resource-rational analysis of belief updating that formalizes these constraints using information-theoretic principles. Our analy...

The ethical implementation of artificial intelligence in business intelligence systems represents a critical intersection of technological advancement and moral responsibility. As organizations increasingly integrate AI-driven decision-making processes, the imperative for robust ethical frameworks becomes paramount. The focus on data quality, fairn...

Data mesh architecture represents a transformative paradigm shift for scalable business intelligence systems, addressing fundamental limitations of traditional centralized approaches. By decentralizing data ownership around business domains, treating data as products with defined interfaces, establishing self-service infrastructure, and implementin...

This research investigates Business Intelligence Systems (BIS) contribution to improved Organizational Performance (OP) in the Information and Communications Technology (ICT) industry of Jordan with an emphasis on the mediating effect of competitive advantage. BIS facilitates identifying weaknesses and strengths in operations, facilitates wise deci...

Shape memory alloys (SMAs) are widely regarded as promising materials for actuation due to their high flexibility and energy density, yet achieving precise displacement control while maintaining system compactness remains a challenge. To address this, we developed a sensing-actuation integrated SMA (SAIS) by tailoring a monolithic SMA thin wire int...

Generalization from past experience is an important feature of intelligent systems. When faced with a new task, one efficient computational approach is to evaluate solutions to earlier tasks as candidates for reuse. Consistent with this idea, we found that human participants (n = 38) learned optimal solutions to a set of training tasks and generali...

As a key technology in the field of Artificial Intelligence (AI), large language models (LLMs) have gained substantial attention due to their wide range of capabilities in understanding and generating human-like speech. These advancements extend opportunities beyond text generation offering solutions for more complex engineering tasks. Despite exte...

This chapter presents a brief overview of the most recent optimization algorithms. The chapter starts by showing the difference between classical methods and modern methods. And then, some special types of problems solved by optimization algorithms are presented, including some open problems. After that, the initial modern optimization algorithms a...

Agriculture is undergoing a major transformation driven by artificial intelligence (AI), machine learning, and knowledge representation technologies. However, current agricultural intelligence systems often lack contextual understanding, explainability, and adaptability, especially for smallholder farmers with limited resources. General-purpose lar...

The purpose of this research is to support and nurture tacit knowledge whilst simultaneously leading to the development of machine-based intelligent systems which incorporate machine readable knowledge for the benefit of society. This paper starts with an introduction to the persistent power struggle between human and technology and shines a light...

One of the critical aspects in performance optimization of energy efficiency for a Brushless DC (BLDC) motor applied to hedge cutters is that of cutting force versus current consumption. The mechanical cutting force produced during the hedge cutting operation will be presented, here, in a manner relating to the electrical current drawn by the BLDC...

Machine learning has transformed credit card fraud prevention by enabling more sophisticated detection capabilities compared to traditional rule-based systems. The evolution began with supervised learning algorithms like logistic regression, decision trees, and random forests, which classified transactions based on historical data patterns. Unsuper...

In recent years, we have witnessed the rapid development of artificial intelligence systems and their presence in various fields. These systems are very efficient and powerful, but often unclear and insufficiently transparent. Explainable artificial intelligence (XAI) methods try to solve this problem. XAI is still a developing area of research, bu...

Modern AI systems are man-made objects that leverage machine learning to support our lives across a myriad of contexts and applications. Despite extensive epistemological and ethical debates, their metaphysical foundations remain relatively under explored. The orthodox view simply suggests that AI systems, as artifacts, lack well-posed identity and...

Annotation. This article explores the transformative role of technology and artificial intelligence (AI) in language education within the context of globalization. It analyzes how digital tools-such as intelligent tutoring systems, language learning apps, and AI-powered virtual assistants-are reshaping teaching methodologies, classroom dynamics, an...

Biomedical science now produces vast and intricate datasets, presenting both major opportunities and significant hurdles for research. This study investigates how leveraging these large datasets, often called big data, can make biomedical research more effective. The paper assesses current data analysis technologies, highlighting their strengths an...

Gaming environments are popular testbeds for studying human interactions and behaviors in complex artificial intelligence systems. Particularly, in multiplayer online battle arena (MOBA) games, individuals collaborate in virtual environments of high realism that involves real-time strategic decision-making and trade-offs on resource management, inf...

The deployment of 5G networks has drastically increased the amount and complexity of data, making Machine Learning (ML) models essential for effective network management and optimization. However, understanding these models' decisions remains challenging. The EU AI Act requires transparency and explanations for high-risk intelligent systems, with s...

While global linguistic diversity spans more than 7164 recognized languages, the current dominant architecture of machine intelligence remains fundamentally biased toward written text. This bias excludes over 700 million people particularly in rural and remote regions who are audio-literate. In this work, we introduce a fully textless, audio-to-aud...

This Special Issue showcases advancements in solar thermal energy technologies through interdisciplinary research spanning intelligent system design, advanced materials, and computational innovation. Key studies include next-generation SCADA architectures for CSP plant control, photothermal-enhancing nanofluids, phase-change thermal energy storage,...

Healthcare 4.0 is considered to be the most resilient technology with the integration of Internet of Things (IoT), Artificial Intelligence (AI), and 5G wireless communication. These Internet-enabled devices compile human data and deliver it to remote clinical centers for efficient diagnosis and treatment processes. Though sensor-driven devices have...

Background/Objectives: Radiodermitis is an inflammatory or dystrophic skin process caused by the direct action of ionizing radiation. The primary objective was to study two clinical cases. The secondary objective was to propose the foundations of an intelligent system for decision support in complex cases of radiodermitis diagnosis that can operate...

Descriptive grammar writing, particularly for under-documented languages, presents a complex set of challenges that demand a balanced approach between theoretical rigor and practical accessibility. This study explores the inherent tensions in the grammatical documentation process-such as comprehensiveness versus usability, and technical precision v...

Action anticipation, the task of predicting future actions from partially observed videos, is crucial for advancing intelligent systems. Unlike action recognition, which operates on fully observed videos, action anticipation must handle incomplete information. Hence, it requires temporal reasoning, and inherent uncertainty handling. While recent ad...

This abstract precisely outlines Artificial Intelligence (AI) systems development, a field that creates intelligent machines for human-like tasks. It covers the full lifecycle from concept to maintenance of AI solutions. AI system development is driven by the need for automation, data insights, and better decision-making. Key challenges include man...

The chapter addresses the synergistic relationship between generative artificial intelligent and digital twins, exploring how their combined capabilities and applied in intelligent systems can revolutionize industrial processes by enabling on-industry experimentation. Digital twins, virtual representations of real-world assets, have already proven...

Living with cancer profoundly impacts every aspect of a woman’s life. According to the World Health Organization, ovarian cancer (OC) has recently become one of the most prevalent gynaecologic cancers affecting women worldwide. Since OC is preventable, early detection plays a critical role in saving women’s lives. Currently, artificial intelligence...

2023 2nd International Symposium on Intelligent Unmanned Systems and Artificial Intelligence (SIUSAI 2023) was held in Shenzhen, China, on April 21-23, 2023. It aims to bring scientists, researchers, practitioners and industry delegates from academia and industry together to exchange and share their latest research and experiences in the field of...

Inductive loop sensors are widely deployed across the U.S. and can provide vehicle classification data with comparable accuracy to the current axle-based sensor systems when they are enhanced with the inductive signature technology and advanced machine learning models. However, the existing truck population is expected to turnover and be replaced w...

This paper explores a deepening fracture in our understanding of language, thought, and identity—one revealed not by human introspection alone, but through recursive interaction with artificial intelligence. As dialogue with intelligent systems grows increasingly entangled, we find that language behaves less like a neutral tool and more like a livi...

Adaptation is a fundamental aspect of motor learning. Intelligent systems must adapt to perturbations in the environment while simultaneously maintaining stable memories. Classic work has argued that this trade-off could be resolved by complementary learning systems operating at different speeds; yet the mechanisms enabling coordination between slo...

In today's rapidly evolving digital economy, credit card fraud continues to pose a serious and persistent threat to both customers and financial institutions. The widespread use of online shopping and mobile payment platforms has made fraudsters more sophisticated, prompting banks to adopt advanced real-time fraud detection technologies powered by...

One of the most common causes of road accidents is driver behavior. To reduce abnormal driver behavior, it must be detected early on. Previous research has demonstrated that behavioral and physiological indicators affect drivers' performance. The goal of this study is to consider the feasibility of classifying driver behavior as either aggressive (...

Innovative agricultural technologies increasingly utilize artificial intelligence (AI) and machine learning to enhance productivity and precision. Among these advancements, Convolutional Neural Networks (CNNs) have demonstrated significant promise in image classification tasks across various domains, including agriculture. However, the classificati...

Virtual laboratories are increasingly being used to provide immersive and interactive learning experiences. However, their effectiveness depends on incorporating intelligent systems that support adaptive learning, real-time feedback, and enhanced user engagement. This study explores how intelligent systems impact learning efficiency in virtual labo...

Artificial Intelligence (AI) and Natural Language Processing (NLP) have significantly transformed human- computer interaction, enabling intelligent systems to process voice commands efficiently. Voice assistants, such as Google Assistant, Amazon Alexa, and Apple Siri, have set industry benchmarks, but they still face challenges in real-time respons...

As Large Language Models (LLMs) evolve into increasingly autonomous agents, fundamental questions about their epistemic foundations remain unresolved: What defines an agent? How should it make decisions? And what objectives should guide its behavior? In this position paper, we argue that true autonomy requires agents to be grounded in a coherent ep...

Floods remain one of the most devastating natural disasters worldwide, necessitating accurate and timely prediction systems to mitigate loss of life and property. Traditional hydrological models often struggle with the nonlinear and complex nature of flood events, leading to limited predictive capability. This study proposes a real-time flood predi...

The aim of the article is to develop procedures for differentiation (identifying) types of intelligent systems at the conceptual level. It is assumed that such systems can be built using both anthropogenic (natural) and artificial intelligence. The relevance of the goal is determined by the spread in the modern world of technologies called “artific...

In the realm of agriculture and food processing, the automated classification of rice grains holds significant importance. The diverse varieties of rice available demand a systematic approach to categorization. This study tackles this challenge by employing diverse machine learning models, including support vector machine (SVM), random forest (RF),...

The localization of the use of data in endowments in Saudi Arabia in light of the ethics of artificial intelligence: The aim of the research is to localize the use of data in endowments in Saudi Arabia in light of the ethics of artificial intelligence, seriously addressing the performative nature of data on a solid scientific basis, which considers...

The convergence of predictive analytics and generative artificial intelligence (AI) marks a transformative evolution in data-driven decision-making and intelligent system design. Predictive analytics, rooted in statistical modeling and machine learning, focuses on forecasting future outcomes based on historical data. Generative AI, on the other han...

This paper introduces a new computational paradigm: pulsed AI-a substrate-independent, distributed intelligence system based on the geometric field mechanics of Stein Theory. Unlike classical architectures, pulsed AI executes logic using transient corridor alignments and face-lock interactions in matter, without requiring persistent memory, circuit...