Freud proposes that in unconscious processing, logical connections are also (heavily) based upon phonological similarities. Repressed concerns, for example, would also be expressed by way of phonologic ambiguity. In order to investigate a possible unconscious influence of phonological similarity, 31 participants were submitted to a tachistoscopic subliminal priming experiment, with prime and target presented at 1ms. In the experimental condition, the prime and one of the 2 targets were phonological reversed forms of each other, though graphemically dissimilar (e.g., “nice” and (...) “sign”); in the control condition the targets were pseudo-randomly attributed to primes to which they don’t belong. The experimental task was to “blindly” pick the choice most similar to the prime. ERPs were measured with a focus on the N320, which is known to react selectively to phonological mismatch in supraliminal visual word presentations. The N320 amplitude-effects at the electrodes on the midline and at the left of the brain significantly predicted the participants’ net behavioral choices more than half a second later, while their subjective experience is one of arbitrariness. Moreover, the social desirability score (SDS) significantly correlates with both the behavioral and the N320 brain responses of the participants. It is proposed that in participants with low SDS the phonological target induces an expected reduction of N320 and this increases their probability to pick this target. In contrast, high defensive participants have a perplexed brain reaction upon the phonological target, with a negatively peaking N320 as compared to control and this leads them to avoid this target more often. Social desirability, which is understood as reflecting defensiveness, might also manifest itself as a defense against the (energy-consuming) ambiguity of language. The specificity of this study is that all of this is happening totally out of awareness and at the level of very elementary linguistic distinctions. (shrink)

Our approach is based on a tri-partite method of integrating psychodynamic hypotheses, cognitive subliminal processes, and psychophysiological alpha power measures. We present ten social phobic subjects with three individually selected groups of words representing unconscious conflict, conscious symptom experience, and Osgood Semantic negative valence words used as a control word group. The unconscious conflict and conscious symptom words, presented subliminally and supraliminally, act as primes preceding the conscious symptom and control words presented as supraliminal targets. With alpha power as a (...) marker of inhibitory brain activity, we show that unconscious conflict primes, only when presented subliminally, have a unique inhibitory effect on conscious symptom targets. This effect is absent when the unconscious conflict primes are presented supraliminally, or when the target is the control words. Unconscious conflict prime effects were found to correlate with a measure of repressiveness in a similar previous study (Shevrin et al., 1992, 1996). Conscious symptom primes have no inhibitory effect when presented subliminally. Inhibitory effects with conscious symptom primes are present, but only when the primes are supraliminal, and they did not correlate with repressiveness in a previous study (Shevrin et al., 1992, 1996). We conclude that while the inhibition following supraliminal conscious symptom primes is due to conscious threat bias, the inhibition following subliminal unconscious conflict primes provides a neurological blueprint for dynamic repression: it is only activated subliminally by an individual's unconscious conflict and has an inhibitory effect specific only to the conscious symptom. These novel findings constitute neuroscientific evidence for the psychoanalytic concepts of unconscious conflict and repression, while extending neuroscience theory and methods into the realm of personal, psychological meaning. (shrink)

As organizations increasingly adopt multi-cloud and hybrid cloud strategies, the need for efficient management of resources across diverse cloud environments becomes more complex. Azure Arc, a key offering from Microsoft, enables organizations to extend Azure services and management to any infrastructure, whether on-premises, in other clouds, or at the edge. By offering a unified platform for managing hybrid and multi-cloud environments, Azure Arc enhances governance, security, and resource optimization across various infrastructures. This paper explores how Azure Arc optimizes hybrid cloud (...) architectures by enabling seamless management, enhanced scalability, and better compliance across different cloud platforms. It also discusses key use cases, benefits, and challenges of adopting Azure Arc, with practical guidance on how to leverage this solution to streamline operations and improve cost efficiency in a multi-cloud ecosystem. The paper aims to provide IT leaders with actionable insights for deploying Azure Arc to create a resilient, flexible, and optimized hybrid cloud environment. (shrink)

This research paper delves into the realm of Financial Network Analytics, unraveling the opportunities and challenges it presents in the domains of systemic risk management and investment analysis. The study navigates the intricate web of interconnected financial entities, employing advanced analytics techniques to uncover meaningful insights. Through a comprehensive exploration, the paper identifies opportunities for leveraging financial network data to enhance systemic risk detection mechanisms and refine investment strategies. Simultaneously, it addresses the inherent challenges, such as data complexity and dynamic (...) network structures, offering nuanced perspectives on their implications. The findings contribute to the evolving landscape of financial analytics, providing a foundation for the development of robust tools and methodologies that can aid financial institutions and investors in navigating the complexities of modern financial networks. (shrink)

Technology-enhanced learning settings are changing quickly and complexly in the contemporary digital era, making it possible for students with disabilities to learn more effectively than before. The words "multisensory" and "media" together, however, suggest that this strategy entails incorporating several sensory modalities in educational media to improve learning experiences for children with disabilities. It can entail integrating visual, aural, tactile, and kinesthetic elements to meet various learning requirements and styles. This article examines how Mulsemedia, one of these cutting-edge technologies, enhances (...) learning methodologies, improving the teaching and learning of unique pedagogies and emphasizing teaching and learning-related modules for students with special needs. The researchers used a qualitative research design to understand and review the ten papers with secondary data based connected to mulsemedia in special education: A novel teaching approach for the next generation. The article also describes the extremely encouraging outcomes of case studies conducted with engineering students with disabilities in several schools in India. This critical article finds that multimedia-enhanced instruction significantly improves special students' learning experiences and ability to learn new information for future development. (shrink)

Deep learning, a transformative force in computational biology, has reshaped biological data analysis and interpretation terrain. This review delves into the multifaceted role of deep knowledge in this field, exploring its historical roots, inherent advantages, and persistent challenges. It investigates explicitly its application in two pivotal domains: DNA sequence classification, where it has been used to identify disease-causing mutations, and protein structure prediction from sequence data, where it has enabled the accurate determination of protein tertiary structures. Moreover, it offers a (...) glimpse into the future trajectory of this dynamic field, sparking intrigue and excitement about the potential of deep learning. Deep learning, a powerful tool in computational biology, can be traced back to the inception of 'threshold logic,' a fusion of algorithmic principles and mathematical frameworks devised to mimic cognitive processes. This seminal breakthrough, which introduced the concept of a threshold function that could be used to model complex decision-making processes, paved the way for deep learning to decipher intricate patterns embedded within vast biological datasets. Deep learning presents many benefits, including precise disease diagnosis, novel drug discovery, and personalized medicine facilitation. Its prowess lies in handling vast, intricate datasets while enhancing generalization capabilities, a testament to its evolution and development that we can appreciate. (shrink)

Over the last few years, personal health monitoring wearable devices have emerged as innovative applications of Artificial Intelligence (AI) in the healthcare industry as they help in real time analysis and prediction of health standardized check-ups and health management. To navigate through the current trends, new technologies and developments, the prospects are as follows: The article also gives a logical look at the state of the art of such devices, enumerating the advantages and drawbacks, as well as outlining the main (...) ethical issues. In terms of method, it also discusses different AI approaches, data acquisition procedures, and those integrating systems used in the context of health monitoring. The finding and implication section discusses the findings of the current trend and the possibility of improvement in application and user acceptance. The last section provides a prognosis on what the area of personal health monitoring might look like in the future, as well as the position of AI in the optimisation of patient experience. (shrink)

In today’s rapidly evolving financial landscape, the adoption of Artificial Intelligence (AI) and Machine Learning (ML) technologies, coupled with the deployment of Business Rules Management Systems (BRMS), has transformed how financial transactions are conducted, monitored, and secured. With fraud, particularly in check deposit transactions, becoming increasingly sophisticated, financial institutions are turning to AI and ML to enhance their risk management strategies. This paper explores the integration of AI-driven models and business rules in financial transactions, focusing on their application in fraud (...) detection and prevention. We also examine the associated challenges, such as data privacy, ethical concerns, and the need for regulatory frameworks, while outlining the opportunities that lie ahead for future financial innovation. (shrink)

This research paper explores effective governance strategies aimed at ensuring consistency and compliance within Business Rules Management Systems (BRMS). As organizations increasingly rely on BRMS to streamline decision-making processes, the need for robust governance becomes paramount. The abstract delves into the challenges posed by evolving business environments and complex regulatory landscapes, emphasizing the significance of maintaining rule consistency and compliance. The paper investigates diverse governance models and their applicability in promoting adherence to business rules across organizational units. Additionally, it addresses (...) the role of technology in facilitating governance mechanisms, including version control, audit trails, and automated monitoring. The study contributes valuable insights to both academia and practitioners by offering a nuanced understanding of governance strategies crucial for fostering reliability, uniformity, and compliance within BRMS. (shrink)

This research paper explores the dynamic integration of artificial intelligence (AI) and machine learning (ML) to enhance Business Rules Management Systems (BRMS) for the facilitation of agile business strategies. In the evolving landscape of digital enterprises, the demand for adaptive and responsive decision-making processes is paramount. The abstract investigates the symbiotic relationship between AI, ML, and BRMS, elucidating their combined potential to empower organizations in crafting agile and resilient business strategies. The study delves into the mechanisms by which AI and (...) ML augment traditional BRMS, offering predictive insights, optimizing decision rules, and fostering real-time adaptability. Through a comprehensive analysis, the research aims to provide valuable insights into the transformative capabilities of this integrated approach, shedding light on its implications for business agility, competitiveness, and strategic innovation. (shrink)

Today’s food industry across the world is facing never-ending difficulties in meeting customers’ expectations of safe and quality food. Such of them include issues to do with contamination, adulteration, and ensuring quality standards of the products when manufactured in large quantities and distributed to different areas. This has called for new solutions, which have come in the form of Artificial Intelligence (AI), which offers solutions to challenges in food safety and quality control in detection, monitoring and management. The present deployment (...) of AI in this field will also be discussed in this paper by virtue of machine learning algorithms, computer vision, industrial robots, and the IoT. With the help of AI, the safety and quality of food products can be improved as well as the food industry can obtain more accurate and real-time data for analysis, maintenance, and risk assessment. The application of AI systems in food safety and quality assurance provides not only reliability and decreased chances of human mistakes but efficiency as well. This paper aims to systematically summarize the current research achievements, methods, and application practices of AI in food safety and quality control. In effect, this paper presents a qualitative case analysis and research evidence that demonstrate the opportunities and risks arising from the implementation of AI technologies in the food sector. The analysis goes further considering the future trends and possible advancements oriented to creating a clear and prospective route for the researchers and specialists in the spheres of AI application for food safety and quality control. (shrink)

This research paper investigates the transformative applications of data visualization techniques in the realm of financial crime detection, with a specific emphasis on addressing the challenges posed by credit card fraud and money laundering. The abstract explores the intricate landscape of visualizing financial data to uncover patterns, anomalies, and potential illicit activities. Through a comprehensive review of existing methodologies and case studies, the paper illuminates the pivotal role data visualization plays in enhancing the efficiency and accuracy of fraud detection systems. (...) By synergizing advanced visualization tools with machine learning algorithms, the study aims to provide insights into how financial institutions can bolster their defenses against evolving threats. Ethical considerations, usability, and the real-world impact of data visualization in combating financial crime are also scrutinized. This research contributes to the evolving discourse on leveraging visualization technologies to fortify financial systems against illicit activities, fostering a proactive and responsive approach to safeguarding economic ecosystems. (shrink)

This paper examines how predictive analytics enhances risk management in financial institutions. Advanced tools like machine learning and statistical modeling help predict risks, identify trends, and implement strategies to prevent losses by analyzing historical and real-time data. It covers the use of predictive analytics for credit risk, market risk, operational risk, and fraud detection, with practical case studies. Additionally, it discusses challenges, ethical issues, and prospects in this field.

A CONSTRUCTIVE CRITIQUE OF THE FOUNDATIONS OF PHILOSOPHY: Abstract of the Ph.D. Dissertation By Ramesh N. Patel June, 1970 -/- Philosophy pursues a rational explication of our understanding, experiences, and values in terms of objective truth and reality. Conspicuously, its view of rationality has been rigid and preconceived. Application of the preconceived reason in the explication of the essential features of our world fails and issues in a network of dialectical tangles. These artificially created tangles pose a unique intellectual (...) challenge, but the perennial failure to resolve them limits the intellectual response of philosophers to remaining caught in the tangles, or to taking intuitively favorable sides, or to simply denouncing the tangles as meaningless. Each is understandable. -/- Superficially, traditional philosophical reason looks like a correct tool for the explication of our world of common sense, but its applications to the world result in logical tangles showing its inadequacy. The philosopher’s faith in such reason ends up in one of two positions: abandoning our world in the interests of such reason, or embodying itself in the world through a special form of reason. Plato took the first and Aristotle took the second position. My analysis shows that Plato failed to explicate the relation between his world of Forms and our world of particulars, and, more importantly, between the Forms and the intuitive reason which grasps them. Aristotle, in my analysis, cannot conceal that the law of noncontradiction is a mere exhortation and has no descriptive necessity with respect to thought, things, or meaning. We also find such dialectical difficulties in Augustine, Hume and Strawson. -/- “Microphilosophical feasibilism” is our proposal for the best treatment, if not the definitive solution, of these problems. Instead of separating philosophical method into logic, epistemology, axiology, and metaphysics on the one side, and partitioning the projected results of philosophizing into validity, truth, valuation, and reality on the other, we need to start philosophizing with a general distinction between “method employed” and “intended result.” This distinction is not pre-colored by claims to ultimate verities. It is a direct aid to understanding. I consider the basic inevitable paradox that a philosopher should explain not only our understanding of experience but also his philosophizing itself. The circularity between “method employed” and “intended result” needs to be admitted as an initial fact about reason rather than circumvented by an implausibly claimed capacity of philosophical reason to formally transcend everything including this circularity. -/- Presuppositions are reduced to a minimum inevitable number. Being our primary microphilosophical criteria, they are reason, experience, and value in their minimal sense. They cannot be plausibly substituted or further reduced. They cannot be preferred one or more to others arbitrarily. We show how, in microphilosophy they coincide or synchronize. Jointly and basically, they form the minimum method employed. The initial, basic, intended result is called minimum feasibility. The fundamental circularity between method and result leaves no way out but to ground self-reference in such a manner that method and result “logico-genetically” coincide. Two extreme situations are avoided: “the logical zero-situation” where nothing is true or real, and “the credulous open situation” where everything is true or real. Finding a mean manifests a basic value. If the meaning of truth and reality is to be preserved, the basic value must have a clear impact and express descriptive rather than revisionary reason. -/- Several other stringent demands are raised as conditions which microphilosophy should fulfil to achieve feasibility. The final, joint, outcome of both “method” and “result,” in the thesis of microphilosophical feasibilism, is formulated thus: Self refers freely and symbolically to itself, own person, own body, material bodies, other persons’ bodies, other persons, and other selves. -/- Ramesh N. Patel Doctor of Philosophy in Philosophy conferred in June, 1970 University of New Mexico, Albuquerque, N.M. (shrink)

The integration of Artificial Intelligence (AI) and Machine Learning (ML) into the research landscape has transforming almost every extending field, including pharmaceutical research. The idea of drug discovery itself is very conventional and has long been criticized for being overly lengthy and expensive, which sometimes may take more than 10 years and billions of dollars to develop a certain drug. AI and ML formulate the future of the drug discovery process by using big data to provide preliminary drug candidates more (...) effectively. This paper overviews the innovations defined by AI and ML in the field of drug discovery, major achievements, techniques, and use cases. Additionally, we explore how AI algorithms can enter biological data, inspect drug-target relations, determine optimal drug design, and potentially recompose famous drugs. This means through using big data with the help of AI in the process of research, previously undisclosed patterns that help in developing effective treatments for patients are found. The paper also addresses the related issues and limitations in applying AI in this domain, namely, data quality issues, the interpretability of AI solutions, and some ethical concerns. Herein, to provide a concrete foundation to the concepts mentioned so far, we discuss the different AI applications and case studies in drug discovery from a survey of the available literature. The article also provides information regarding the methodologies used in AI-enabled drug discovery like deep learning, reinforcement learning, and natural language processing. Moreover, we compare the use of conventional and artificial intelligence methods, while demonstrating what is good and what maybe in both. The results section offers a review and an integration of the most recent objectives and recommendations for subsequent research instruction. Therefore, despite these prohibitive AI and ML forecasts for drug discovery improvement, continuous interaction between computational scientists, biologists, and regulatory authorities is functional to fully unlock this potential. (shrink)

In this paper current author proposes a need for studying intricate differences between psychological aspects, factors, cognitions, affect, behaviour and related dynamics. It can be promoted as a separate branch within the domain of Psychology as Intricacy Psychology. Case history taking for the new Intervention Meditation of current author is proposed in line with capturing such intricacies of the client. The current also proposes to study the intricacies belonging to ‘Self’ as an important factor within his new Intervention Meditation approach. (...) View of Self in line with current author’s new Intervention Meditation is also outlined. This paper is at the initial stage of the series of papers planned to develop his new Intervention Meditation approach which is entirely different from all other meditations in vogue. (shrink)

The increasing complexity and demands of next-generation networks necessitate the integration of Artificial Intelligence (AI) to enhance their efficiency and security. This article explores advancements in AI-driven communication systems, focusing on optimizing network performance, ensuring robust security measures, and addressing the challenges of scalability and real-time adaptability. By analyzing case studies, emerging technologies, and recent research, this study highlights AI's transformative potential in redefining communication systems for future applications.

Artificial Intelligence (AI) and Machine Learning (ML) are transforming the insurance industry by optimizing risk assessment, fraud detection, and customer service. However, the rapid adoption of these technologies raises significant ethical concerns, particularly regarding bias and fairness. This chapter explores the ethical challenges of using AI and ML in insurance risk management, focusing on bias mitigation and fairness enhancement strategies. By analyzing real-world case studies, regulatory frameworks, and technical methodologies, this chapter aims to provide a roadmap for developing ethical AI/ML (...) systems in the insurance sector. It highlights the importance of transparency, accountability, and inclusivity in ensuring equitable outcomes. (shrink)

In today’s digital landscape, businesses face increasing pressure to maintain service continuity and data availability, especially in the face of potential service disruptions or disasters. Traditional single-cloud deployments can be vulnerable to outages, data loss, and geographical limitations. As a result, multi-cloud strategies have emerged as a solution for achieving higher resilience, disaster recovery (DR), and business continuity. By leveraging multiple cloud service providers (CSPs), organizations can architect redundancy, improve service availability, and ensure faster recovery in the event of a (...) failure. This paper explores the importance of multi-cloud strategies for resilience and disaster recovery, focusing on key components like data replication, geographic distribution, failover mechanisms, and backup strategies. We discuss architectural patterns, best practices, and challenges of implementing multi-cloud disaster recovery solutions. Additionally, we present case studies that highlight how multi-cloud strategies enhance business resilience and improve operational continuity during disruptions. (shrink)

Individuals come across extreme Uncertainty situations, feeling rounded–up 360 degrees, as if trapped inside Chakra Vyuha (wheel form strategy). For uncertainty is often related to future, the concept of Future Time perspective (FTP) is relied upon for attaining positive states. But FTP is a critical factor which works both positively and negatively depending on other factors intervening. For politicians and businessmen such states of being trapped in Chakra Vyuha, can mean end of their political life or business life. In the (...) current paper, the author describes the introspection of a Subject while he attempted to alter his Future Time perspective. This introspective report further gave clue for Merged Time Perspective or Seamless Time Horizon instead of FTP and also that Regulatory Focus and Resistance To Change need to be combined, coalesced and treated on a single continuum. Current author also has proposed a therapy outline to help businessmen and politicians to come out of devastating situations in which they feel rounded – up by opponents 360 degrees. (shrink)

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

Everything and every word about spirituality have already been said but the practical utility of spiritual wisdom in day to day life to achieve success and live a blissful life is lacking. Spiritual wisdom not only shows us the path of salvation and freedom but also helps us to figure out the solutions for every problem in all walks of human life and civilization. Spirituality is a well-defined, scientific way to get any goal in life whether it is for justified (...) worldly desires or to fulfil the urge of salvation with a blissful route. The book is an important read for the present generation, i.e. our youth as well as the persons those who want to touch the divinity within. Due to the universal nature of Spiritual Wisdom, it is bound to be on the shelves of the coming generation as spiritual science is not something that can be restricted to any one generation. The book itself contains the aura of mysticism and a touch of the great teaching taken from the scriptures. The book will teach how spiritual wisdom may change a person’s life. (shrink)

We normally function through the mind without knowing the mechanics of understanding. This book teaches us how to make thoughts and how to control once mind, so that we can live peaceful life and achieve the highest goal of life, i.e. self-realization. Book also deals with the fundamentals of life and spirituality. Book has written in a simple language so that most of the peoples will understand the real essence of the life. The author has discussed about the complex messages (...) of the Vedanta, in a thoughtful manner. The author discusses about Jiva, Jagat, Ishvara and Spiritual life in his book by referencing verses from the Bhagwat Gita, Vedanta and Shrimad Bhagwat Mahapuran in very simple language. The purpose of writing this book is to understand our intrinsic nature. Book is so enriched with the wisdom that everyone should read it at least once. (shrink)