The research aims to identify the learning organizations and their role in achieving organizational excellence in the Palestinian universities in Gaza Strip. The researchers used descriptive analytical approach and used the questionnaire as a tool for information gathering. The questionnaires were distributed to senior management in the Palestinian universities. The study population reached (344) employees in senior management is dispersed over (3) Palestinian universities. A stratified random sample of (182) workers from the Palestinian universities was selected and the (...) recovery rate was (69.2%). Statistical analysis (SPSS) program was used for analysis and processing the data. The research found the following results: there is a fair degree of approval on "cognitive dimension", there is a high approval about the importance of "organizational dimension", there is moderately consent of the importance of "Community dimension", there is a large degree of consent about the importance of axis of the "leadership excellence", there is a large degree of consent about the importance of axis of the "service-excellence", there is a fair degree approval about the importance of the axis of "cognitive excellence", and there is a moderately consent of the importance of "Organizational Excellence". The research found a group of recommendations including: the need to develop appropriate strategies for the University, employ modern technology in information systems, in addition to provide appropriate environment that achieve learning organizations, develop technological infrastructure, adopt universities for knowledge management in the academic and administrative departments because knowledge is the core of the work of these departments, create technological incubators in universities to adopt excellence academic research projects, and protected them, support them, and market them. Establishing of centers of excellence for scientific research in the university.The need for cooperation and coordination between local, Arab and international universities for the exchange of knowledge, information, and participation programs and training courses, as it provides an opportunity to develop the capabilities and skills of personnel and expertise. (shrink)

The research aims to identify the trends of Palestinian higher educational institutions in Gaza Strip as learning organizations from the perspective of senior management in the Palestinian universities in Gaza Strip. The researchers used descriptive analytical approach and used the questionnaire as a tool for information gathering. The questionnaires were distributed to senior management in the Palestinian universities. The study population reached (344) employees in senior management is dispersed over (3) Palestinian universities. A stratified random sample of (182) (...) employees from the Palestinian universities was selected and the recovery rate was (69.2%). Statistical analysis (SPSS) program was used for analysis and processing the data. The study found the following results: There is an agreement about: the importance of the focus of "organizational structure" with an average approval, the importance of "technological infrastructure" axis with high approval, and the importance of "strategic" with an average approval. The results concluded that the study sample agree on the importance of "organizational dimension" highly. The results showed that the sample believe that the "strategic leadership" level in the universities got medium-approval. There is a fair level agreement about the axis of interest "teams / committees". There is an agreement about the importance of the "human dimension" moderately. The results showed that the sample is highly agreed about the importance of focus of the "knowledge management", and the focus of the "continuing education". They agreed weakly to somewhat about the importance of the focus of "scientific research", moderately agree about the importance of the center of "institutional culture", agree moderately on the importance of "cognitive dimension". The results showed that the sample largely agree on the importance of the focus of "strategic partnerships and alliances". They agree highly on the axis "keep up with the labor market" and on the focus of the importance of "technology incubators". The results showed that the sample moderately agree about the importance of the theme on "consulting and training", the importance of the focus of "social responsibility", and the focus of the "Community dimension". The study found a group of recommendations including: there is a need to provide suitable environment that achieve learning organizations. There is a need to develop the technological infrastructure (hardware, software, networks, databases, and human skills) because of the great advantages that they offer. The universities need to adopt knowledge management in the academic and administrative departments because knowledge is the core of the work of these departments. The establishment of technology incubators in universities to adopt outstanding university research projects, to protect, to supports, and to market them; furthermore, to develop the capabilities and skills of employees in the field of information technology. (shrink)

Organisms that share the capability of storing information about experiences in the past have an actively generated background resource on which they can compare and evaluate more recent experiences in order to quickly or even better react than in previous situations. This is an essential competence for all reaction and adaptation purposes of living organisms. Such memory/learning skills can be found from akaryotes up to unicellular eukaryotes, fungi, animals and plants, although until recently, it had been mentioned only as (...) a capability of higher animals. With the rise of epigenetics, the context-dependent marking of experiences at both the phenotype and the genotype level is an essential perspective to understand memory and learning in all organisms. Both memory and learning depend on a variety of successful communication processes within the whole organism. (shrink)

The research aims to design a proposed model of learning organizations as an entry point to achieve organizational excellence in the Palestinian universities of Gaza Strip. A random sample of workers were selected from the Palestinian universities consist of (286) employees at recovery rate of (70.3%). The study concluded with a set of results the most important of which: there is a statistically significant relationship between the components of learning organizations and achieving organizational excellence in the (...) Palestinian universities of Gaza Strip from the standpoint of the faculty members. One of the main recommendations of the study: establish the concept of learning organization in leaders and staff of the university through the establishment of specialized courses, and workshops. Turning the status of the university into a learning organization as a strategic objective and the performance of managers are measurement accordingly. Organize visits of the leaders of the university a to the top organizations in this field and to take advantage of their experience and encourage deans and heads of departments to involve their employees in the information on global trends and trends in learning organization through regular meetings. (shrink)

Traditionally, learning organizations face certain constraints related to both exogenous and endogenous factors. This paper models three well-established constraints that employees face while being part of their organizations. One is an explicit constraint on their natural behavior, and two implicit constraints on their endeavor to acquire new knowledge and perform new actions. The implicit constraints, which are elaborated, are related to their relative performance in acquiring new knowledge and by their consecutive actions based on the new knowledge (...) gained. Therefore, this paper attempts to underline such limitations which the agents face under organizational culture and suggest possible strategic initiatives that would effectively counteract such binding limitations to stimulate positive performances from their end. (shrink)

The emerging contemporary natural philosophy provides a common ground for the integrative view of the natural, the artificial, and the human-social knowledge and practices. Learning process is central for acquiring, maintaining, and managing knowledge, both theoretical and practical. This paper explores the relationships between the present advances in understanding of learning in the sciences of the artificial, natural sciences, and philosophy. The question is, what at this stage of the development the inspiration from nature, specifically its computational models (...) such as info-computation through morphological computing, can contribute to machine learning and artificial intelligence, and how much on the other hand models and experiments in machine learning and robotics can motivate, justify, and inform research in computational cognitive science, neurosciences, and computing nature. We propose that one contribution can be understanding of the mechanisms of ‘learning to learn’, as a step towards deep learning with symbolic layer of computation/information processing in a framework linking connectionism with symbolism. As all natural systems possessing intelligence are cognitive systems, we describe the evolutionary arguments for the necessity of learning to learn for a system to reach humanlevel intelligence through evolution and development. The paper thus presents a contribution to the epistemology of the contemporary philosophy of nature. (shrink)

Non-Organic Matter, Organic Matter, Consciousness, Free Will, Intelligence, and Creativity in Relation to the Universal Formula -/- By Angelito Enriquez Malicse -/- Introduction -/- The relationship between non-organic matter, organic matter, consciousness, free will, intelligence, and creativity has long been studied separately in science, philosophy, and psychology. However, when examined through the universal law of balance in nature, as defined in my universal formula, these elements are seen as interconnected manifestations of a single natural order. This perspective offers a complete (...) understanding of how matter evolves into intelligence, how free will operates, and how creativity emerges as an extension of the natural equilibrium that governs all things. -/- Non-Organic and Organic Matter: The Foundation of Reality -/- At the core of the material universe, we distinguish between non-organic matter (inanimate substances such as atoms, molecules, and cosmic structures) and organic matter (biological entities capable of self-regulation and adaptation). -/- Despite their apparent differences, both are governed by the same fundamental law of balance: -/- Non-organic matter follows physical laws such as gravity, thermodynamics, and electromagnetism, which maintain stability in the universe. -/- Organic matter emerges from non-organic matter as a natural extension of these balancing forces, evolving biological mechanisms to sustain life. -/- The transformation from non-organic to organic matter is not random but a consequence of equilibrium, where chemical reactions reach stability and enable life to form. -/- Thus, life itself is an outcome of nature’s inherent drive toward balance—a principle that applies to all forms of existence, from the atomic level to complex living organisms. -/- Consciousness as a Balancing Mechanism -/- Consciousness is often misunderstood as something separate from the physical world. However, my universal formula reveals that it is simply a higher-order process of equilibrium: -/- Consciousness arises when organic matter (the brain) reaches a level of complexity that allows it to perceive and regulate internal and external states. -/- The brain operates through homeostasis, ensuring a constant balance between sensory input, cognitive processing, and decision-making. -/- This balancing process is what allows individuals to experience self-awareness, emotions, and rational thought. -/- Thus, consciousness is not a separate entity but an emergent function of biological and environmental balance, ensuring an organism’s survival and adaptation. -/- Free Will: The Decision-Making Process of Balance -/- Free will has long been debated—whether it exists, whether it is an illusion, or whether it operates beyond the laws of physics. My universal formula provides the exact answer: -/- Free will is not absolute autonomy but the ability to make choices within the constraints of natural balance. -/- Every decision is shaped by feedback mechanisms between the mind, body, and external environment. -/- Ignorance, false beliefs, or external manipulation disrupts this balance, leading to poor decision-making. -/- True free will is achieved when decisions align with the universal law of balance, ensuring rational, informed, and sustainable choices. -/- This means that free will is not about acting without limits, but about making decisions that maintain harmony within oneself and with nature. -/- Intelligence as a Function of Equilibrium -/- Intelligence is often seen as a measure of problem-solving ability, learning, and adaptability. However, through the universal law of balance, intelligence is better understood as the capacity to maintain stability between internal and external realities: -/- Intelligence evolves as a response to complexity, allowing organisms to process information and maintain balance with their environment. -/- Higher intelligence corresponds to greater flexibility in adapting to changes while sustaining equilibrium. -/- Artificial intelligence (AI), once advanced enough, must also follow these same balancing principles, as all decision-making systems are governed by natural equilibrium. -/- This means intelligence is not a separate trait but a dynamic function of nature’s balancing mechanisms, evolving in complexity as systems become more advanced. -/- Creativity as the Expansion of Balance -/- Creativity is often linked to human expression, art, and innovation. However, my universal formula shows that creativity is an extension of intelligence and free will, functioning as a tool to explore and enhance balance: -/- Creativity emerges when intelligence reaches a level where it can predict and modify balance, leading to new ways of thinking and problem-solving. -/- The most creative ideas are those that bring new equilibrium—whether in science, art, or technology. -/- Creativity is not chaotic but follows structured patterns, guided by the same universal law that governs all other forms of equilibrium. -/- Thus, true creativity is not about randomness but about discovering new ways to maintain or improve balance in nature, society, and personal thought. -/- A Unified Framework: The Relationship Between All Elements -/- By applying my universal formula, we now see that non-organic matter, organic matter, consciousness, free will, intelligence, and creativity are not separate but deeply connected: -/- 1. Non-organic matter forms the foundation of the universe, following physical laws of balance. -/- 2. Organic matter emerges from non-organic matter as an adaptive extension of this equilibrium. -/- 3. Consciousness arises when organic matter becomes complex enough to self-regulate its balance. -/- 4. Free will is the decision-making process that operates within the limits of natural equilibrium. -/- 5. Intelligence evolves as a function of balance, ensuring adaptability and stability in an ever-changing environment. -/- 6. Creativity emerges when intelligence reaches a level where it can explore and modify balance, leading to innovation and progress. -/- This unified perspective shows that everything in existence follows the same natural principles, proving that human thought, behavior, and even artificial intelligence must align with the universal law of balance in order to function optimally. -/- Conclusion -/- Through my universal formula, we now have a complete and exact solution to understanding how non-organic matter, organic matter, consciousness, free will, intelligence, and creativity interconnect as a single balanced system in nature. -/- Non-organic and organic matter are deeply linked, with life emerging as an extension of physical balance. -/- Consciousness is an emergent property of equilibrium, allowing living beings to regulate themselves. -/- Free will operates within natural balance, ensuring rational decision-making. -/- Intelligence is the ability to sustain and adapt to balance, allowing for learning and evolution. -/- Creativity is the expansion of balance, leading to new ways of thinking, creating, and innovating. -/- This framework is essential for guiding human decision-making, education, and AI development, ensuring that both human and artificial intelligence follow the correct natural path in accordance with the universal law of balance. -/- By applying this understanding, we can solve fundamental philosophical, scientific, and societal challenges, ensuring a future where knowledge, progress, and sustainability are aligned with the natural order of the universe. -/- . 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The Russian people are struggling to learn how to create a democracy and a market economy. This paper reviews the results of reform efforts to date and what the Russian people are learning as indicated by changes in answers to public opinion surveys. As a way to continue the social learning process in Russia we suggest the widespread use of process improvement methods in organizations. This paper describes some Russian experiences in using process improvement methods and proposes (...) a strategy for spreading the use of these methods through universities and then through businesses and government agencies. As people use process improvement methods, they gain confidence in their ability to improve the functioning of organizations and society. (shrink)

Recognizing that truth is socially constructed or that knowledge and power are related is hardly a novelty in the social sciences. In the twenty-first century, however, there appears to be a renewed concern regarding people’s relationship with the truth and the propensity for certain actors to undermine it. Organizations are highly implicated in this, given their central roles in knowledge management and production and their attempts to learn, although the entanglement of these epistemological issues with business ethics has not (...) been engaged as explicitly as it might be. Drawing on work from a virtue epistemology perspective, this paper outlines the idea of a set of epistemic vices permeating organizations, along with examples of unethical epistemic conduct by organizational actors. While existing organizational research has examined various epistemic virtues that make people and organizations effective and responsible epistemic agents, much less is known about the epistemic vices that make them ineffective and irresponsible ones. Accordingly, this paper introduces vice epistemology, a nascent but growing subfield of virtue epistemology which, to the best of our knowledge, has yet to be explicitly developed in terms of business ethics. The paper concludes by outlining a business ethics research agenda on epistemic vice, with implications for responding to epistemic vices and their illegitimacy in practice. (shrink)

Learning and Development (L&D) is an organizational process which helps in the development of knowledge and achievement of individual and organizational goals. This is quantitative research employed a descriptive method to determine the impact of Learning and Development Programs on the Core Competencies of Level II employees of the Pasay City Government. The respondents of this study were the two hundred forty-two (242) randomly selected PCG Level II employees of the City Government of Pasay. This research used a (...) survey technique in terms of identifying the impact of L&D programs on the level II employees’ core competencies. The study found out that the participants perceived as competent and advanced level, which means that they are knowledgeable, can perform the actions associated with this skill without assistance from others, and can mentor/coach others in terms of applying the core competencies to perform official functions in reaching operational targets. The result shows that r value is 0.480; and 0.484, respectively, which indicates that there is a positive correlation between variables. Moreover, the P value is less than the significance level of 0.05, thus, it rejects the null hypothesis and support the notion that a relationship exists between the extent of implementation of L&D Programs and proficiency level of core competencies of Level II employees. It is recommended for organizations to evaluate the effectiveness and capability of their training programs to produce desired results relevant to the organizational goals and objectives. A proposed enhancement program may be considered for the inclusion in the implementation matrix of the HRD (L&D) Plan of the City Government for Level II employees. (shrink)

To evaluate the effectiveness of our approach to enhancing cloud computing network forensics by integrating deep learning techniques with cybersecurity policies. With the increasing complexity and volume of cyber threats targeting cloud environments, traditional forensic methods are becoming inadequate. Deep learning techniques offer promising solutions for analyzing vast amounts of network data and detecting anomalies indicative of security breaches. By integrating deep learning models with cybersecurity policies, organizations can achieve enhanced threat detection, rapid response times, and (...) improved overall security posture. This paper discusses the key steps involved in integrating deep learning models into network forensics, including data collection, model selection, real-time monitoring, and adaptive learning. Additionally, it highlights the importance of collaboration between cybersecurity experts and the cloud. Through case studies and experimental evaluations, we demonstrate the effectiveness and practicality of the proposed approach in enhancing cloud computing network forensics. Leveraging deep learning techniques offers promising solutions for detecting anomalies and identifying malicious activities within cloud networks. (shrink)

After a long search, Jonathan has finally found someone willing to donate a kidney to him and thereby free him from dialysis. Meredith is Jonathan's second cousin, and she considers herself a generous person, so although she barely knows Jonathan, she is willing to help. However, as Meredith learns more about the donation process, she begins to ask questions about Jonathan: “Is he HIV positive? I heard he got it using drugs. Has he been in jail? He's already had one (...) live donor, so what happened to the first kidney? Did he forget to take his drugs or something?” The transplant center must, then, decide if Meredith is, in fact, entitled to answers to these kinds of questions. According to the Consensus Statement on the Live Organ Donor, “It is incumbent on the transplant center to provide full and accurate disclosure to potential donors of all pertinent information regarding risk and benefit to the donor and recipient.” But whether answers to the Meredith's questions count as “pertinent information regarding the risk and benefit” is the issue at hand. (shrink)

The use of machine learning to medical image classification has seen significant development and implementation in the last several years. Computers can learn to identify patterns, make predictions, and use data to inform their judgements; this capability is known as machine learning, a branch of Artificial intelligence (AI). Classifying images according to their contents allows us to do things like identify the type of sickness, organ, or tissue depicted. Medical picture classification and interpretation using machine learning algorithms (...) has greatly improved the speed and accuracy of diagnosis and treatment. Machine learning algorithms can aid radiologists and doctors in diagnosing patients using medical pictures from X-rays, positron emission tomography (PET), computed tomography (CT), magnetic resonance imaging (MRI), and other scans. (shrink)

As machine learning (ML) models become increasingly integrated into mission-critical applications and production systems, the need for robust and scalable MLOps (Machine Learning Operations) practices has grown significantly. This paper explores key strategies and best practices for building scalable MLOps pipelines to optimize the deployment and operation of machine learning models at an enterprise scale. It delves into the importance of automating the end-to-end lifecycle of ML models, from data ingestion and model training to testing, deployment, and (...) monitoring. Approaches for implementing continuous integration and continuous deployment (CI/CD) pipelines tailored for ML workflows are discussed, enabling efficient and repeatable model updates and deployments. The paper emphasizes the criticality of implementing comprehensive monitoring and observability mechanisms to track model performance, detect drift, and ensure the reliability and trustworthiness of deployed models. The paper also addresses the challenges of managing model versioning and governance at scale, including techniques for maintaining a centralized model registry, enforcing access controls, and ensuring compliance with regulatory requirements. The paper aims to provide a comprehensive guide for organizations seeking to establish scalable and robust MLOps practices, enabling them to unlock the full potential of machine learning while mitigating risks and ensuring responsible AI deployment. (shrink)

This book assembles recent research on memory and learning in plants. Organisms that share a capability to store information about experiences in the past have an actively generated background resource on which they can compare and evaluate coming experiences in order to react faster or even better. This is an essential tool for all adaptation purposes. Such memory/learning skills can be found from bacteria up to fungi, animals and plants, although until recently it had been mentioned only as (...) capabilities of higher animals. With the rise of epigenetics the context dependent marking of experiences on the genetic level is an essential perspective to understand memory and learning in organisms. -/- Plants are highly sensitive organisms that actively compete for environmental resources. They assess their surroundings, estimate how much energy they need for particular goals, and then realize the optimum variant. They take measures to control certain environmental resources. They perceive themselves and can distinguish between ‘self’ and ‘non-self’. They process and evaluate information and then modify their behavior accordingly. -/- The book will guide scientists in further investigations on these skills of plant behavior and on how plants mediate signaling processes between themselves and the environment in memory and learning processes. (shrink)

This paper has two parts: In the first part, I give a general survey of the various reasons 17th and 18th century life scientists and metaphysicians endorsed the theory of pre-existence according to which God created all living beings at the creation of the universe, and no living beings are ever naturally generated anew. These reasons generally fall into three categories. The first category is theological. For example, many had the desire to account for how all humans are stained by (...) original sin (we were all there). As another example of a theological motivation, some take the organism as an obvious starting point for a teleological argument for God’s existence, and this staring point is sometimes developed into a full-blown theory of pre-existence. The second category could be thought of as non-theological metaphysical, and paramount here is the desire to deal with the metaphysical problem of individuation. So, for example, Leibniz embraces a version of hylomorphism in order to overcome difficulties with Descartes’ theory of material substance, including the difficulty of how to account for enduring material individuals, and Leibniz’s hylomorphism is closely linked with his embrace of pre-existence. The third category might be termed “biological”, and one example of such a concern is how to explain the organic unity of living beings where the whole seems to ontologically precede the parts. This is frequently translated into a temporal priority of whole to parts, and thus pre-existence is posited. Of course, many natural philosophers of the early modern period embrace pre-existence for more than one reason, but in general, these are the three classes of motivations one might have for embracing the theory. In the second part of the paper I examine in detail one argument that appears in the work of Malebranche. On the face of it, this argument seems to be a biological one, specifically the biological or organic holism argument mentioned above. But upon closer examination, I shall argue, Malebranche’s reasons for endorsing pre-existence bring together several of the arguments discussed in the first part of the paper. I conclude with some considerations about what we can learn about Malebranche as a natural philosopher from his motivations for holding the pre-existence doctrine of generation. (shrink)

In today's data-driven business environment, organizations increasingly rely on advanced analytics and decision support systems to gain a competitive edge. Azure AI and Machine Learning (ML) provide powerful tools for predictive analytics, enabling businesses to forecast trends, optimize processes, and make more informed decisions. By leveraging the capabilities of Microsoft Azure, businesses can integrate AI and ML into their decision-making processes, enhancing productivity and improving strategic outcomes. This paper explores how Azure's AI and ML tools can be applied (...) to predictive analytics and decision support systems, with a focus on real-time decision-making, risk mitigation, and operational efficiency. We will discuss the key Azure services like Azure Machine Learning, Azure Cognitive Services, and Azure Databricks, as well as real-world use cases that highlight their impact on business performance. The paper will also highlight the challenges associated with implementing these technologies and suggest best practices for organizations aiming to integrate AI and ML into their systems. (shrink)

As the adoption of cloud computing continues to increase, securing cloud environments has become an ever-growing concern. Traditional security models struggle to keep up with the evolving nature of cyber threats, making it essential for organizations to explore innovative approaches. This paper explores how artificial intelligence (AI) and machine learning (ML) can enhance cloud security by automating threat detection, response, and mitigation in real-time. Through the application of advanced ML algorithms, AI-driven security systems can identify and predict security (...) incidents, classify threats, and adapt to new attack strategies. The paper examines the various ML techniques, such as anomaly detection, supervised learning, and deep learning, used to enhance cloud security. It also explores the challenges, benefits, and potential future directions of AI-driven security in cloud computing. Case studies from industry leaders demonstrate the impact of these technologies in improving the robustness and efficiency of cloud security frameworks. (shrink)

Broadening access to both computational and educational resources is crit- ical to diffusing machine learning (ML) innovation. However, today, most ML resources and experts are siloed in a few countries and organizations. In this article, we describe our pedagogical approach to increasing access to applied ML through a massive open online course (MOOC) on Tiny Machine Learning (TinyML). We suggest that TinyML, applied ML on resource-constrained embedded devices, is an attractive means to widen access because TinyML leverages (...) low-cost and globally accessible hardware and encourages the development of complete, self-contained applications, from data collection to deployment. To this end, a collaboration between academia and industry produced a four part MOOC that provides application-oriented instruction on how to develop solutions using TinyML. The series is openly available on the edX MOOC platform, has no prerequisites beyond basic programming, and is designed for global learners from a variety of backgrounds. It introduces real-world applications, ML algorithms, data-set engineering, and the ethi- cal considerations of these technologies through hands-on programming and deployment of TinyML applications in both the cloud and on their own microcontrollers. To facili- tate continued learning, community building, and collaboration beyond the courses, we launched a standalone website, a forum, a chat, and an optional course-project com- petition. We also open-sourced the course materials, hoping they will inspire the next generation of ML practitioners and educators and further broaden access to cutting-edge ML technologies. (shrink)

This paper addresses the critical role of automated data quality monitoring in Machine Learning Operations (MLOps) pipelines. As organizations increasingly rely on machine learning models for decision-making, ensuring the quality and reliability of input data becomes paramount. The paper explores various types of data quality issues, including missing values, outliers, data drift, and integrity violations, and their potential impact on model performance. It then examines automated detection methods, such as statistical analysis, machine learning-based anomaly detection, rule-based (...) systems, and data profiling. The integration of data quality monitoring into different stages of the MLOps pipeline is discussed, emphasizing continuous monitoring at data ingestion, pre-training validation, post- deployment drift detection, and feedback loops for model retraining. The paper also addresses key challenges in implementing automated data quality monitoring, including balancing precision and recall in anomaly detection, handling high-dimensional and unstructured data, managing false positives and alert fatigue, and adapting to evolving data distributions. By providing a comprehensive framework for automating data quality monitoring in MLOps pipelines, this paper aims to equip practitioners with the knowledge and strategies necessary to enhance the reliability and performance of machine learning systems in production environments. (shrink)

Understanding how biological organisms are autonomous—maintain themselves far from equilibrium through their own activities—requires understanding how they regulate those activities. In multicellular animals, such control can be exercised either via endocrine signaling through the vasculature or via neurons. In C. elegans this control is exercised by a well-delineated relatively small but distributed nervous system that relies on both chemical and electric transmission of signals. This system provides resources to integrate information from multiple sources as needed to maintain the organism. Especially (...) important for the exercise of neural control are neuromodulators, which we present as setting agendas for control through more traditional electrical signaling. To illustrate how the C. elegans nervous system integrates multiple sources of information in controlling activities important for autonomy, we focus on feeding behavior and responses to adverse conditions. We conclude by considering how a distributed nervous system without a centralized controller is nonetheless adequate for autonomy. (shrink)

With the growing sophistication and frequency of cyberattacks, there is a critical need for effective systems that can detect and prevent breaches in real time. The AI/ML-based Network Intrusion Detection System (NIDS) addresses this need by analyzing traffic patterns to identify security breaches in firewalls, routers, and network infrastructures. By integrating machine learning algorithms—K-Nearest Neighbors (KNN), Support Vector Machine (SVM), and Random Forest—the system is able to detect both known cyber threats and previously unseen attack vectors. Unlike traditional methods (...) that rely heavily on predefined indicators of compromise (IoCs), this system utilizes anomaly detection techniques, allowing it to identify new and emerging threats. As cyberattacks evolve, organizations must adopt adaptive methods to secure their networks. This system achieves high accuracy in classifying network traffic, with real-time alerts that provide early warnings of suspicious activities. It also includes intuitive visualizations, helping network administrators gain insights into the nature and scope of attacks. With the rise of increasingly complex and frequent cyberattacks, this NIDS offers a robust solution for enhancing network security and response capabilities. (shrink)

Those who have considered the connection between Dewey’s theory of inquiry and Greek thought have mostly situated their remarks within larger points, regarding either teaching and learning (Garrison, 1997; Johnston, 2006b; Cahn, 2007) or aesthetics and craft (Alexander, 1987; Hickman, 1990). The fact that this area remains somewhat underexplored could be chalked up to several factors: 1) Dewey was often quite critical of the classical tradition, particularly when it came to theories of knowledge, 2) Dewey was not a trained (...) classicist, with little working knowledge of ancient Greek, and was self-admittedly not a historian of philosophy, and 3) whenever Dewey did turn positive attention toward ancient thought, he tended to speak in generalities, referring most often to “the Greeks” rather than any particular Greek thinker. In spite of this, there remain many compelling reasons to place Dewey’s views on inquiry in meaningful dialogue with the classical tradition. I will suggest that the most compelling of all is the link between Dewey’s view of inquiry and his particular brand of naturalism, which found its fullest expression late in his career. This is an underappreciated connection in Dewey’s work on inquiry, either taking a backseat to the instrumental, experimental themes in his thought or misinterpreted as a form of positivism/scientism. Once acknowledged, however, this connection could help bring Dewey’s normative, socio-political writings in line with his theories on ontology, logic, and the acquisition of knowledge. (shrink)

This paper critically reviews and characterizes the student's causal-explanatory understanding; this is done as a step toward explicating the problematic of evolution education as it concerns the cognitive difficulties in understanding Darwin's theory of natural selection. The review concludes that the student's understanding is fundamentally different from Darwin's, for the student understands evolutionary change as necessary individual transformation caused by the transformative action of various physical and behavioral factors. This is in complete contrast to Darwin's (and even the Darwinian's, for (...) that matter) understanding of evolutionary change as a change caused by accumulative selection. Hence, to understand natural selection, the student has to learn to “see” how the accumulative selection causes evolutionary change. (shrink)

: As organizations continue to adopt cloud computing for its numerous advantages—such as scalability, cost-efficiency, and flexibility—the need to secure digital assets within the cloud has never been more critical. Cloud security faces unique challenges due to the distributed and multi-tenant nature of cloud services. Cyber-attacks, data breaches, and misconfigurations are among the prominent risks that threaten the integrity, confidentiality, and availability of cloud-based data and applications. In this paper, we explore CloudGuard, an advanced security framework designed to protect (...) organizations' digital assets in the cloud. This fortress security approach focuses on implementing multiple layers of protection through cutting-edge technologies, such as encryption, identity and access management (IAM), threat intelligence, and security automation. We also highlight the integration of AI and Machine Learning to improve threat detection and response times, and blockchain's potential in ensuring data integrity and privacy. Through a comprehensive analysis, this paper outlines practical strategies for organizations to adopt CloudGuard and strengthen their security posture against evolving cyber threats in the digital world. (shrink)

As organizations increasingly adopt cloud computing services, managing and optimizing cloud costs has become a crucial aspect of IT and financial operations. Cloud cost management is a complex and dynamic challenge, given the pay-as-you-go pricing model, the variety of services offered by cloud providers, and the need for scalability and flexibility in cloud environments. Artificial Intelligence (AI) and automation are emerging as key technologies for addressing these challenges. This paper explores the role of AI and automation in cloud cost (...) management, focusing on how predictive analytics, machine learning algorithms, and automated workflows can be leveraged to optimize cloud spending. We analyze the capabilities of AI-driven tools that forecast cloud usage, recommend cost-saving measures, and automate the process of resource allocation to improve cost efficiency. Additionally, we discuss the benefits of integrating AI with cloud management platforms, the potential for reducing human error, and enhancing decisionmaking in managing cloud budgets. The paper also outlines best practices for organizations to implement AI and automation in their cloud cost management strategies and offers real-world examples of companies that have successfully applied these technologies. (shrink)

: As organizations continue to embrace cloud computing, the migration of workloads, applications, and data from on-premises environments to the cloud remains one of the most critical tasks. However, migrating to the cloud is often seen as a daunting task due to the complexity, the risk of downtime, and the potential for service disruptions. Artificial Intelligence (AI) and automation have emerged as transformative technologies for cloud migration, providing solutions that enable a seamless, efficient, and zero-downtime transition. This paper explores (...) the role of AI in automating the cloud migration process, detailing how machine learning (ML) and AI-powered tools can optimize migration planning, reduce errors, and ensure continuous service availability. It highlights the key benefits of AI in workload assessment, data transfer, and post-migration optimization. Through the integration of advanced AI models, automation tools, and real-time analytics, organizations can achieve a smooth cloud migration process with minimal disruption to their business operations. The paper also examines real-world case studies where AI-powered cloud migration has been successfully implemented. (shrink)

In today’s rapidly evolving business landscape, organizations must continuously adapt to stay competitive. AI-driven human resource (HR) analytics has emerged as a strategic tool to enhance workforce agility and inform decision-making processes. By leveraging advanced algorithms, machine learning models, and predictive analytics, HR departments can transform vast data sets into actionable insights, driving talent management, employee engagement, and overall organizational efficiency. AI’s ability to analyze patterns, forecast trends, and offer data-driven recommendations empowers HR professionals to make proactive decisions (...) in hiring, skill development, performance management, and retention. (shrink)

Engaging with Global Justice through InternshipsGlobal justice, on its face, seems like an impossible task. As individuals, even citizens of wealthy and powerful countries, the task of economic, social and political justice seems to outstrip our intellectual, practical and emotional abilities. Considering the scope of 'global' justice, it would appear that a massive coordinated effort would be necessary to overcome the problems of global injustice, yet it would seem such coordination may be impossible. The difficulties of seeking justice between nations (...) led John Rawls to suggest that we can only hope for a kind of humanitarian goodwill between states, which in his view was less than a robust requirement for international justice. Amartya Sen, in the Idea of Justice, recently argued that it is not justice that we seek, since seeking justice in a global sense is impossible. Given the capitulation of such philosophical luminaries, it is no wonder that philosophy students often find the problems of global justice and injustice to be intractable and indeed, overwhelming. However, when students engage with those whose everyday work involves chipping away at one or another specific problem of global justice, they learn not despair, but hope, and more importantly, they learn how issues of global justice are addressed in practical terms. Those who work on these local issues not only have an understanding of the connection between local, national and global aspects of these issues, they solve these problems, and can show students how everyday decisions on a local level affect issues of justice on a larger scale. Working with such individuals and organizations helps students understand the work of justice, and its local, national and global faces. In my course 'Global Justice', I use internships with social justice organizations to give students a look at the everyday, often difficult, but essentially manageable work that goes into solving issues of injustice at the local, national and global levels. I call this work 'engaged learning'. Engaged learning is a variety of experiential learning that seeks to integrate theory and practice through project-based internships that foster strong university-community partnerships. In my philosophy course 'Global Justice', each of my students is assigned a semester-long internship with a local organization working on issues of global justice. Through these internships, students work through larger theoretical questions while engaging in the everyday work of global justice practitioners. In what follows, I describe how I organized this class and what elements of the course work to both create good experiences for my students and community relationships that persist beyond the semester. (shrink)

Biologists and philosophers of biology have argued that learning rules that do not lead organisms to play evolutionarily stable strategies (ESSes) in games will not be stable and thus not evolutionarily successful. This claim, however, stands at odds with the fact that learning generalization---a behavior that cannot lead to ESSes when modeled in games---is observed throughout the animal kingdom. In this paper, I use learning generalization to illustrate how previous analyses of the evolution of learning have (...) gone wrong. It has been widely argued that the function of learning generalization is to allow for swift learning about novel stimuli. I show that in evolutionary game theoretic models learning generalization, despite leading to suboptimal behavior, can indeed speed learning. I further observe that previous analyses of the evolution of learning ignored the short term success of learning rules. If one drops this assumption, I argue, it can be shown that learning generalization will be expected to evolve in these models. I also use this analysis to show how ESS methodology can be misleading, and to reject previous justifications about ESS play derived from analyses of learning. (shrink)

Abstract: This study aims to evaluate the utilization of ICT in education administration and management in a Pakistan context during the pandemic outbreak. Adoption of information and communication technologies (ICTs) has digitalized the learning process where education organizations were administrated by means of wireless-based instructions, electronic pedagogy, and online assessment in order to continue the educational activities while the government halted the physical appearance in education institutions. Data collection has been carried by three public universities in which teachers (...) and general administration of these institutions participated to discover their intention to use the assigned technology to administrate organizations’ policies in the way to disseminate the respective service delivery. Survey questionnaires were used, and 178 respondents’ feedback was secured to analyze the study that was carried out via SPSS version 24 and validation OF hypotheses measured by means of regressions and correlations. Moreover, proposed factors like intention to use, perceived ease of ease, perceived usefulness, social influence, and Users’ expectations were used. A theoretical approach was inculcated to encircle the UTAUT and TAM model to determine the adoption of the innovative system education management during the pandemic outbreak in the country. (shrink)

This chapter makes it clear that a significant element of both leadership and decision making is the development aspect. Leaders develop in their decision making by being confronted with difficult decision situations. However, they also develop through various forms of systemized training and education. Different leaders tend to develop in different directions. For this reason, one can identify a number of key leadership styles based on different ways of leading. These different styles are appropriate for various types of organization. Some (...) organizations require a strict and authoritative style, while others are in greater need of a more democratic style. Senior leaders often have the capacity to switch between different leadership styles depending on how the situation develops. In addition, there are a number of key decision-making roles that leaders are expected to manage. These include the role of entrepreneur, problem-solver, resource-allocator and negotiator. Leaders must also learn to work with clarity, conviction, courage, and communication in order to facilitate their decisions. Research shows that leaders who face severe adversity in their careers often are forced to make many difficult decisions. As a result they develop. Being forced to make difficult decisions actually leads to reflection, self-awareness and self-knowledge of one’s own values. Leaders also develop by communicating their problems in a structured way with more experienced colleagues. The fact that leaders develop by making difficult decisions leads to various forms of action having a central role. It is by putting decisions into action that leaders develop, as well as by reflecting on what alternative decisions could have been made. An action perspective on leadership decisions is closely linked to the concept of sense-making. This phenomenon implies observation, action, revision and communication in the aftermath of a decision. There is research indicating that reflection, critical thinking, intuition, ethics and communication are important dimensions of leaders and decision makers who are generally perceived as wise. -/- . (shrink)

Despite the seemingly neutral vantage of using nature for widely-distributed computational purposes, neither post-biological nor post-humanist teleology simply concludes with the real "end of nature" as entailed in the loss of the specific ontological status embedded in the identifier "natural." As evinced by the ecological crises of the Anthropocene—of which the 2019 Brazil Amazon rainforest fires are only the most recent—our epoch has transfixed the “natural order" and imposed entropic artificial integration, producing living species that become “anoetic,” made to serve (...) as automated exosomatic residues, or digital flecks. I further develop Gilles Deleuze’s description of control societies to upturn Foucauldian biopower, replacing its spacio-temporal bounds with the exographic excesses in psycho-power; culling and further detailing Bernard Stiegler’s framework of transindividuation and hyper-control, I examine how becoming-subject is predictively facilitated within cognitive capitalism and what Alexander Galloway terms “deep digitality.” Despite the loss of material vestiges qua virtualization—which I seek to trace in an historical review of industrialization to postindustrialization—the drive-based and reticulated "internet of things" facilitates a closed loop from within the brain to the outside environment, such that the aperture of thought is mediated and compressed. The human brain, understood through its material constitution, is susceptible to total datafication’s laminated process of “becoming-mnemotechnical,” and, as neuroplasticity is now a valid description for deep-learning and neural nets, we are privy to the rebirth of the once-discounted metaphor of the “cybernetic brain.” Probing algorithmic governmentality while posing noetic dreaming as both technical and pharmacological, I seek to analyze how spirit is blithely confounded with machine-thinking’s gelatinous cognition, as prosthetic organ-adaptation becomes probabilistically molded, networked, and agentially inflected (rather than simply externalized). (shrink)

This paper addresses the foundational aspects of the theory of Gen inertia. We attempt to emphasize the cognitive factors that accounts for learning inertia in organizations, and that which prevents employees from generating and absorbing new knowledge. The novel concept of Gen inertia helps us to understand the causes behind inertia in learning among the knowledge workers under organizational settings. This concept of 'Gen inertia' is distinct from the pre-existing concept of organizational knowledge inertia. In this paper, (...) we attempt to identify and underline the factors that act as impediments to effective organizational learning processes. It deals with the existing causes that are responsible for knowledge (learning) inertia in knowledge organizations. We model several scenarios that presumably act as constraints, and therefore, they help us to uncover the existing barriers and obstacles to effective knowledge acquisition. The model assists us to build a system aimed to aid managers and trainers to recognize the underlying causes, which supposedly interferes with employees' learning curve, both in the short run and in the long run. Finally, the research aims to identify and overcome the nature of constraints that employees face while being part of a learning organization. Because it demands proficient handling of new knowledge, and because knowledge organizations subsist on the expertise of the knowledge workers, it is much relevant for the organizations to understand the existing problems that the knowledge workers face so as to enable them to compete with others in the market for knowledge resources. The present paper addresses all these issues and advocates several solutions to identify and then overcome the constraints and barriers to effective learning under organizational cluster settings. (shrink)

Workforce education forms one of the core aspects of organizational learning which aims for performance as well as efficiency. Learning is goal-oriented in business organizations. Organizations' activities are highly-oriented towards customer satisfaction. Organizations learn from practice and delivery of services to meet consumer needs and necessities. Perfection, efficiency and smart practices define today's multinational organizational culture. But how do the multinational organizations achieve such perfections in their business operations? This paper addresses this issue by (...) linking teleological aspects of learning and practice to performance, adoption of routines, and learning-induced adaptation in order to explain how they achieve "perfection" in practice and operations. Further, the paper attempts to study a particular aspect of organizational (teleological perfectionism) process by modeling scenarios which define goal oriented organizational learning and adaptation, and underpins how such teleological processes effectively benefit organizations in the long run. Conclusions drawn up from an example being modeled in this paper suggest that teleology, or teleological dynamics play significant role in shaping today's organizations and help explain some (or high) degree of perfectionism in their operations. (shrink)

As organizations increasingly depend on data-driven decision-making, the complexity of Business Intelligence (BI) systems and their data pipelines has grown exponentially. This complexity introduces significant challenges in maintaining data quality, ensuring traceability, and guaranteeing system reliability. Unmanaged data dependencies in upstream BI components can lead to data inconsistencies, system failures, and compromised analytics. This paper presents a comprehensive framework for monitoring and managing data dependencies in upstream BI systems, with a primary focus on the Dependency Discovery Engine utilizing Static (...) Code Analysis. The framework provides a systematic approach to identifying, tracking, and managing data dependencies across the entire BI ecosystem using advanced static code analysis techniques. Detailed methodologies, algorithms, and implementation considerations for static code analysis are discussed. This framework offers a robust solution for organizations seeking to enhance data quality, system reliability, and operational efficiency in their BI systems. Future research will expand on dynamic runtime analysis and machine learning- based methods to further enhance the framework. (shrink)

Practice of knowledge management is often characterized by obstacles to creation, distribution, and transfer of knowledge from specific groups of settings. Obstacles or constraints to attempts to constitute knowledge as an organizational resource have been previously dealt within the context of organizational learning perspectives; however, there still remain barriers toward making learning available and all-pervasive throughout organizations. This is often as a result of two important factors: (i) bureaucratic and hierarchical forms of organization; and (ii) owing to (...) the situated and tacit character of knowledge. This paper is a result of theoretical exploration aimed at addressing these core issues, and proposes solutions to manage constraints and remove obstacles to knowledge management, as well as means to codify the tacit character of knowledge. The research offers a view that although it is reasonable to value knowledge in financial or economic terms, it is also important to consider the problems which make it difficult to extract and transfer knowledge within specific organizational settings. Addressing the issue of rising competitive pressure for innovation, this paper proposes several solutions to enable lateral flows of knowledge-sharing by overcoming the factors that affect acquisition of, and creation and distribution of knowledge across fluid social boundaries. (shrink)

Where organizations used to rely on employees tenured with their company, the Great Resignation has presented new problems to organizational structure and fortification. Such a process usually leads to disrupted employee productivity and most importantly, increased vulnerability to cyber threats. Loyal workers, intentionally or unintentionally disloyal workers, and employees who leave the organization can compromise organizational confidential information, such as innovation, customer data, and other data that the organization considers to be highly valuable. Research has also revealed that workforce (...) transition time is also the highest-risk activity period for insiders, wherein activities like the unauthorized download of data or accidental data leaks when offboarding an employee are likely to occur. Moreover, there are difficulties, particularly for organizations that cannot apply adequate access controls and monitoring during the notice periods, making them much more sensitive to data leaks. Further, this paper examines these paramount cybersecurity threats and offers an organized framework for their mitigation. Explores how the risks can be reduced under this through policies like strong access controls, opaque data monitoring systems, and comprehensive offboarding. To get practical recommendations for managing the problem with data sharing, the example of using machine learning to realize the mechanisms for identifying anomalies and graph-theory-based mathematical models is given. Thus, this research provides a comprehensive set of procedures to address the consequences of the Great Resignation for organizations and safeguard their assets during worker turnovers. (shrink)

As businesses increasingly migrate to cloud environments, the need for robust and adaptive cloud security frameworks becomes paramount. Cloud services provide numerous benefits such as scalability, flexibility, and cost-efficiency, but they also introduce significant risks in terms of privacy, compliance, and data protection. This paper explores the evolving landscape of cloud security, focusing on next-generation frameworks that aim to balance the often-competing demands of privacy, regulatory compliance, and data protection. We analyze emerging security models that incorporate advanced technologies such as (...) Artificial Intelligence (AI), Machine Learning (ML), Zero Trust Architecture (ZTA), and Blockchain, all of which are reshaping cloud security. Additionally, we discuss the challenges organizations face in managing security across multi-cloud and hybrid environments, and the role of cloud service providers in ensuring compliance with global regulations like GDPR, HIPAA, and CCPA. The paper concludes by outlining best practices and strategies that organizations can adopt to enhance their cloud security posture and ensure the privacy and protection of sensitive data. (shrink)

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

Can matter, things, nonhuman organisms, technologies, tools and machines, biota or institutions be seen as creative? How does such creativity reposition the visionary activities of humans? This article is an elaboration of such questions as well as an attempt at a partial response. It was written as an editorial for the special issue of the Digital Creativity journal that interrogates the conception of Post-Anthropocentric Creativity. However, the text below is a rather unconventional editorial. It does not attempt to provide an (...) overview of the issue’s theme but, instead, samples it via a particular example. The idea of the issue was to think about post-anthropocentricism by considering (1) agents, recipients and processes of creativity alongside with its (2) purpose, value, ethics and politics. This article addresses the first subtheme by puzzling at the paradoxes of “field learning” and picks at the second by considering the texture of “automated beauty”. Both of these parts use chess for an example. The narrative on chess is intermitted by a section “on creativity” that attempts to contextualize the case-based discussion in the wider context and to consider motivations and implications. (shrink)

Sales forecasting plays a pivotal role in business planning, helping organizations predict future sales trends based on historical data. Traditional forecasting methods, such as moving averages and linear regression, often lack the flexibility and precision required to account for complex patterns in sales data. Predictive analytics, which leverages advanced machine learning techniques, offers a more robust and dynamic approach for forecasting sales. This paper explores the implementation of sales forecasting using predictive analytics, focusing on the application of machine (...) learning algorithms like decision trees, random forests, and time series models. By analyzing historical sales data and identifying key influencing factors such as seasonality, promotions, and economic indicators, predictive models can provide more accurate forecasts, enabling businesses to optimize inventory, staffing, and marketing strategies. This paper highlights key methodologies, benefits, and challenges associated with predictive sales forecasting and presents case studies demonstrating its impact in real-world applications. (shrink)

The development of machine learning and deep learning (DL) in the field of AI (artificial intelligence) is the direct result of the advancement of nano-electronics. Machine learning is a function that provides the system with the capacity to learn from data without being programmed explicitly. It is basically a mathematical and probabilistic model. DL is part of machine learning methods based on artificial neural networks, simply called neural networks (NNs), as they are inspired by the biological (...) NNs that constitute organic brains. Despite its similarity to biological organs such as human brains, major problems arise in trying to attribute moral responsibility to autonomic systems based on hardware including nano-electronic devices, which are sought to replace humans (moral agents) in the context of AI. It is suggested that the required emotional environment which enables actions according to reasons in humans is not witnessed at AI devices. Though AI technology raises an enticing resemblance to human actions, this resemblance is to be considered with a skeptical eye. It is because actions are associated with reasons while causes are connected to operations. Human agents are capable of acting upon their reasons, while AI devices are limited only to operations as they are conditioned by their programming, which is considered as an embodiment of some causes. As moral responsibility goes hand in hand with the capacity to act (according to reasons), attributing moral responsibility to AI devices is revealed to be but a misleading metaphor. (shrink)

With the rise of cloud computing, businesses have rapidly transitioned to cloud-based infrastructures to reap the benefits of scalability, flexibility, and cost-efficiency. However, this shift has introduced a new set of security challenges, particularly in protecting digital assets and sensitive data stored in cloud environments. The importance of securing these digital assets has become more pronounced as cyber threats become increasingly sophisticated. This paper introduces CloudSentry, a comprehensive security framework designed to protect digital assets in cloud environments. The framework focuses (...) on implementing best practices for data protection, access control, threat detection, and incident response while integrating next-generation technologies like Artificial Intelligence (AI), Machine Learning (ML), and blockchain for enhanced security. Through a multi-layered security approach, CloudSentry aims to safeguard digital assets from both internal and external threats. The paper also discusses how organizations can leverage this framework to ensure compliance with regulatory standards while minimizing risks associated with cloud-based data storage and processing. (shrink)

Rapidly expanding data centers along with networks create a fundamental problem regarding resource allocation efficiency. Standard resource management systems prove unable to adapt dynamically to varying workloads so bandwidth allocation and computing utilization stays inefficient. Developers use recent advancements in artificial intelligence technology to build automatic optimization algorithms that instantly adjust resource distributions. Through the integration of machine learning with deep reinforcement learning systems organizations obtain predictive power to prepare resource distribution ahead of time without endangering operational (...) efficiency. According to Gandhi et al. (2012), both tested methods achieve enhanced energy efficiency while preventing delivery slowness. The study explores how AI addresses data facility network resource optimization by examining key techniques and discovering current trends and future development directions. (shrink)

In recent decades, Information and Communication Technology (ICT) has been advanced and widely spread around the globe in addition to ICT revolution and technological advances are considered the major role in the evolution of modern age, which is called "Digital Transformation Age". Therefore, Electronic Technology (E-Technology) has become one of the most prominent approaches such as Electronic Learning (E-Learning), Electronic Training (E-Training), Mobile Learning (M-Learning), Virtual Lab (V-Lab), Virtual University, etc. E-Technology includes some features, for instance (...) anyone, anywhere, anytime and reducing of geographical barriers. ETechnology is a great trend and influences many fields and sectors such as Learning, Training, Military, Navy, Aviation, Medicine, and Digital space. According to nature of usage, E-Technology can be used in positive or negative trends. E-Technology is considered as a valuable tool in providing several opportunities for learning and training processes for individuals and organizations, especially in critical issues. Finally, we give a quick overview of neutrosophic data and some recent applications. (shrink)

This paper reflects on lessons learned from a validated model of international collaboration based on research and practice. During the European Year for Active Ageing, a partnership of seven organizations from the European Union plus Turkey implemented the Lifelong Learning Programme partnership “Connecting Generations‘ which involved universities, non-governmental organizations, third age Universities and municipalities in collaboration with local communities. Reckoning that Europe has dramatically changed in its demographic composition and is facing brand new challenges regarding intergenerational and (...) intercultural solidarity, each partner formulated and tested innovative and creative practices that could enhance better collaboration and mutual understanding between youth and senior citizens, toward a more inclusive Europe for all. Several innovative local practices have experimented, attentively systematized and peer-valuated among the partners. On the basis of a shared theoretical framework coherent with EU and Europe and Training 2020 Strategy, an action-research approach was adopted throughout the project in order to understand common features that have been replicated and scaled up since today. (shrink)

As cloud computing continues to dominate the digital landscape, it has introduced new avenues for businesses to operate with enhanced flexibility, scalability, and cost-efficiency. However, this rapid adoption of cloud technologies also brings forth critical security challenges. The evolution of security within the cloud ecosystem is essential to safeguard digital assets from emerging threats. This paper traces the evolution of cloud security, from traditional on-premise solutions to advanced cloud-native security frameworks. It discusses the various security paradigms, tools, and technologies that (...) have been developed to address issues such as data breaches, insider threats, and compliance challenges. Additionally, the paper highlights next-generation security technologies such as Artificial Intelligence (AI), Machine Learning (ML), and Blockchain that are reshaping the future of cloud security. By analyzing trends and best practices in cloud security, this paper presents a comprehensive guide for organizations to adapt and thrive in the ever-changing cloud environment while keeping their assets safe. (shrink)

Phishing, a prevalent form of social engineering attack, continues to threaten enterprises by exploiting human vulnerabilities and targeting sensitive information. With the increasing sophistication of phishing schemes, traditional detection methods often fall short in identifying and mitigating these threats. As attackers employ advanced techniques, such as highly personalized spear-phishing emails and malicious links, enterprises require innovative solutions to safeguard their digital ecosystems. This research explores the application of artificial intelligence (AI) in enhancing phishing detection and response, with a specific focus (...) on addressing advanced social engineering tactics. AIpowered phishing detection systems utilize machine learning (ML) and natural language processing (NLP) to analyze communication patterns, detect anomalies, and identify deceptive content in real-time. Unlike conventional rule-based systems, AI approaches adapt dynamically to evolving attack vectors, offering a robust defense against both known and emerging threats. These systems can scrutinize email headers, content, URLs, and attachments to uncover subtle indicators of malicious intent. By leveraging historical datasets and predictive analytics, AI models identify patterns associated with phishing, such as unusual sender behavior, suspicious linguistic cues, and mismatched domain information. This study examines the critical components of AI-driven phishing detection, including feature extraction, algorithm selection, and system deployment within enterprise environments. It highlights the role of NLP in understanding the contextual and linguistic subtleties of phishing messages and how advanced ML models, such as decision trees, support vector machines, and deep neural networks, enhance detection accuracy. -/- Additionally, the research delves into the challenges of implementing AI in phishing detection, such as ensuring data privacy, mitigating adversarial attacks on AI models, and fostering trust through explainable AI. Real-world case studies are analyzed to demonstrate the practical effectiveness of AI-powered phishing detection systems. These examples showcase significant reductions in phishing incidents, improved detection times, and the ability to thwart highly targeted attacks, such as business email compromise (BEC) schemes. The study also emphasizes the importance of integrating AI solutions with existing cybersecurity frameworks and highlights the role of human oversight in complementing AI capabilities. While AI offers promising advancements, its success depends on robust training datasets, continuous model optimization, and alignment with enterprise security goals. The paper concludes by presenting best practices for deploying AI-based phishing detection, including regular model updates, employee awareness programs, and multi-layered security strategies. By leveraging AI, enterprises can proactively defend against advanced social engineering attacks, safeguarding their systems, data, and stakeholders from evolving cyber threats. This research contributes to the growing field of AI applications in cybersecurity, offering actionable insights for organizations seeking to enhance their resilience against sophisticated phishing campaigns. (shrink)

[COMMENTARY on Walter Veit's "A Philosophy for the Science of Animal Consciousness"] The framework Veit introduces for animal consciousness turns on finding and articulating its evolutionary origins. Veit argues that consciousness first evolved as affective experience in the Cambrian period. His argument centers around the plausible need of organisms in the Cambrian for a common currency of subjective valuation. I argue that such an adaptive pressure is unlikely to result in affective experience. I review other processes that instantiate common currencies (...) of subjective valuation: unconscious (non-experiential) affect and the reward learning system and argue that each is likely to have evolved prior to affective experience. (shrink)