This case study is a retrospection of my family’s experiences that highlight several ELE facets. Following a description, we attempt to explain some of these phenomena from the perspectives of science and other germane disciplines.

How might people be wronged in relation to their feelings, moods, and emotions? Recently philosophers have begun to investigate the idea that these kinds of wrongs may constitute a distinctive form of injustice: affective injustice. In previous work, we have outlined a particular form of affective injustice that we called emotional imperialism. This paper has two main aims. First, we aim to provide an expanded account of the forms that emotional imperialism can take. We will do so by drawing inspiration (...) from William Reddy’s (2001) concept of an emotional regime and investigating ways in which colonial powers of the eighteenth to twentieth centuries sought to impose their emotional regimes on their colonial subjects. Second, we will offer more expansive accounts of both emotional imperialism and affective injustice that can accommodate these additional forms of emotional imperialism. (shrink)

It has become increasingly common to talk about the second person in the theory of mind debate. While theory theory and simulation theory are described as third person and first person accounts respectively, a second person account suggests itself as a viable, though wrongfully neglected third option. In this paper I argue that this way of framing the debate is misleading. Although defenders of second person accounts make use of the vocabulary of the theory of mind debate, they understand some (...) of the core expressions in a different way. I will illustrate this claim by focusing on Reddy’s and Gallagher’s accounts and argue that these authors use the notions of knowing and of understanding other minds differently than traditionally assumed. As a consequence, second person accounts thus conceived do not directly address the questions that gave rise to the theory of mind debate. They invite us, however, to critically reflect upon the way the debate has been set up. (shrink)

Heidegger’s analysis of human existence has long been criticized for ignoring the full possibilities of human encounter. This article finds a basis for the criticism in recent infancy research. It presents evidence for a second-person structure in our earliest encounters: An infant first becomes present to herself as the focal center of a caregiver’s gazing, smiling, or vocalization. The exchange in which the self thus appears is termed a You–I event. Such an event, it is held, cannot be assimilated into (...) Heidegger’s Dasein analysis. The article locates the origins of temporality in the early playful exchanges that make up You–I events. The dread of losing the You is seen as the original form of what Heidegger calls dread in the face of death. The apparently self-sufficient self of the cogito first emerges, it is held, when the child becomes capable of playing the role of a You toward herself. This happens especially through talking “with oneself,” as in “inner” speech. The postinfancy self is here interpreted as a derivative of the You–I event. It is argued that because inner speech frees the child from a felt dependence on others for self-awareness, they are no longer experienced in their full significance. The loss of fullness extends to all beings, including the self, with the result that beings are, as Heidegger puts it, depleted of being. (PsycINFO Database Record (c) 2014 APA, all rights reserved). (shrink)

Bu çalışmada Metin Erksan’ın 1965 yapımı Sevmek Zamanı filminin “bir resme âşık olma” hikâyesi gibi görünen anlatısının aslında dönemin varoluşçu felsefesinin Türkiye’deki özgün bir yansıması olduğu ve bunun da filmdeki kadın karakter ile kurulduğu gösterilecektir. Yazıda filmde beliren temsil, korku, özgürlük ve iletişim temaları öncelikle Platon’un mağara alegorisi ve Heidegger’in varoluşçu felsefesinin Dasein (orada-varlık) kavramına başvurularak ele alınacaktır. Filmde âşık olduğunu söylemekten çekinen Halil’in Meral’in temsiline kaçışı resmin bakışındaki iyilik ve sevgi ile açıklanır. Doğada insanların uzağında yaşayan ve çalışan Halil (...) arkadaşı Mustafa’nın kötülük uyarısı ile Meral’den kaçmaktan vazgeçip onunla konuşmaya karar verir. Halil’in kaçışındaki korkunun kaynağı Halil’in varoluşunun Meral tarafından tanınıp onaylanmaması ihtimali olsa da Meral’in Halil’in varoluşuna özgürce ve ihtimamla yaklaşarak Halil’in korkusunu daha derin bir varoluşsal kaygı ve özgürlükle karşı karşıya getirir. Yazı Meral’in Halil ile aynı moda girebilip onu anlayabilmesi ve bu güce sahip olmasının ikisi arasında iletişimi mümkün kıldığını iddia etmektedir. Yazıda en son filmin toplumsal gerçekçi yanında kadın sorununun nasıl şekillendiği ortaya konulacaktır. Meral Halil’i tanısa, kendisi Halil tarafından tanınsa bile kendi sınıfından gelen bir tanıma reddi ile karşılaşmaktadır. Bu tanımamanın ölüm kadar sert bir şiddete ulaşmasının nedeni ise ekonomik sınıfı değil cinsiyetidir. (shrink)

What happens to the inner light of consciousness with the death of the individual body and brain? Reductive materialism assumes it simply fades to black. Others think of consciousness as indicating a continuation of self, a transformation, an awakening or even alternatives based on the quality of life experience. In this issue, speculation drawn from theoretic research are presented. -/- Table of Contents Epigraph: From “The Immortal”, Jorge Luis Borges iii Editor’s Introduction: I Killed a Squirrel the Other Day, Gregory (...) M. Nixon iv-xi Research Essays The Tilde Fallacy and Reincarnation: Variations on a "Skeptical" Argument Teed Rockwell 862-881 Death, Consciousness, and Phenomenology, Steve Bindeman 882-899 The Idealist View of Consciousness After Death, Bernardo Kastrup 900-909 Consciousness, a Cosmic Phenomenon—A Hypothesis, Eva Déli 910-930 The Theory of a Natural Afterlife: A Newfound, Real Possibility for What Awaits Us at Death, Bryon K. Ehlmann 931-950 Near-Death Cases Desegregating Non-Locality/Disembodiment via Quantum Mediated Consciousness: An Extended Version of the Cell-Soul Pathway, Contzen Pereira & J Shashi Kiran Reddy 951-968 On the Possible Existence of Quantum Consciousness After Brain Death, Massimo Pregnolato & Alfredo Pereira Jr. 969-991 Science and Postmortem Survival, Edward F. Kelly 992-1011 Explorations ISS Theory: Cosmic Consciousness, Self, and Life Beyond Death in a Hyperdimensional Physics, Chris H. Hardy 1012-1035 Does the Consciousness End, Remain Awake, or Transform After Death? Radivoj Stankovich (with Micho Durdevich) 1036-1050 Big Bang Spirituality, Life, and Death, Ken Bausch 1051-1063 Death, Consciousness and the Quantum Paradigm, Ronald Peter Glasberg 1064-1077 Living With Limits: The Continuum of Consciousness, Donald Brackett 1078-1098 Mysticism, Consciousness, Death, Mike Sosteric 1099-1118 What Dies? Eternalism and the Afterlife in William James, Jonathan Bricklin 1119-1140 Theories of Consciousness and Death: Does Consciousness End, Continue, Awaken, or Transform When the Body Dies? Roger Cook 1141-1153 It’s the Other Way Around: Matter is a Form of Consciousness and Death is the End of the Illusion of Life in the World, James P. Kowall & Pradeep B. Deshpande 1154-1208 Statements A Feminine Vision for the World Consciousness, & a New Outrageous Ontology, Lorna Green 1209-1217 The Mask of Eternity: The Quest for Immortality and the Afterlife, Iona Miller 1218-1228 Are We Really “such stuff as dreams are made on”? Chris Nunn 1229-1225 Is the Afterlife a Non-Question? (Let's Hope Not), Deepak Chopra 1226-1230 Life After Death? An Improbable Essay, Stuart Kauffman 1231-1236. (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)

How do we know what we know? • How do we perceive ourselves and the world around? • Is what we perceive the only reality that exists? (or) • Is there a different reality other than what we perceive? (Not referring to the source of C, but to the CoC, in the very limit of our physical structure).

The Internet of Things (IoT) is a rapidly growing technology that connects and integrates billions of smart devices, generating vast volumes of data and impacting various aspects of daily life and industrial systems. However, the inherent characteristics of IoT devices, including limited battery life, universal connectivity, resource-constrained design, and mobility, make them highly vulnerable to cybersecurity attacks, which are increasing at an alarming rate. As a result, IoT security and privacy have gained significant research attention, with a particular focus on (...) developing anomaly detection systems. In recent years, machine learning (ML) has made remarkable progress, evolving from a lab novelty to a powerful tool in critical applications. ML has been proposed as a promising solution for addressing IoT security and privacy challenges. In this article, we conducted a study of the existing security and privacy challenges in the IoT environment. Subsequently, we present the latest ML-based models and solutions to address these challenges, summarizing them in a table that highlights the key parameters of each proposed model. Additionally, we thoroughly studied available datasets related to IoT technology. Through this article, readers will gain a detailed understanding of IoT architecture, security attacks, and countermeasures using ML techniques, utilizing available datasets. We also discuss future research directions for ML-based IoT security and privacy. Our aim is to provide valuable insights into the current state of research in this field and contribute to the advancement of IoT security and privacy. (shrink)

Recent studies show that racism still exists in the American medical profession, the fact of which legitimizes the historically long-legacy of mistrust towards medical profession and health authorities among African Americans. Thus, it was suspected that the participation of black patients in end-of-life care has always been significantly low stemmed primarily from their mistrust of the medical profession. On the other hand, much research finds that there are other reasons than the mistrust which makes African Americans feel reluctant to the (...) end-of-life care, such as cultural-religious difference and genuine misunderstanding of the services. If so, two crucial questions are raised. One is how pervasive or significant the mistrust is, compared to the other factors, when they opt out of the end-of-life care. The other is if there is a remedy or solution to the seemingly broken relationship. While no studies available answer these questions, we have conducted an experiment to explore them. The research was performed at two Philadelphia hospitals of Mercy Health System, and the result shows that Black patients’ mistrust is not too great to overcome and that education can remove the epistemic obstacles as well as overcome the mistrust. (shrink)

There is no doubt that custard apple diseases are among the important reasons that destroy the Custard Apple plant and its agricultural crops. This leads to obvious damage to these plants and they become inedible. Discovering these diseases is a good step to provide the appropriate and correct treatment. Determining the treatment with high accuracy depends on the method used to correctly diagnose the disease, expert systems can greatly help in avoiding damage to these plants. The expert system correctly diagnoses (...) Custard Apple disease to make it easier for farmers to find the right treatment based on the appropriate diagnosis. Objectives: A specialized syllable language system was established for the diagnosis of Custard Apple plant disease. (shrink)

Background: Depression (major depressive disorder) is a common and serious medical illness that negatively affects how you feel, the way you think and how you act. Fortunately, it is also treatable. Depression causes feelings of sadness and/or a loss of interest in activities once enjoyed. It can lead to a variety of emotional and physical problems and can decrease a person’s ability to function at work and at home. Depression affects an estimated one in 15 adults (6.7%) in any given (...) year. And one in six people (16.6%) will experience depression at some time in their life. Depression can strike at any time, but on average, first appears during the late teens to mid-20s. Women are more likely than men to experience depression. Some studies show that one-third of women will experience a major depressive episode in their lifetime. Objectives: The main goal of this expert system is to get the appropriate diagnosis of disease and the correct treatment and give the appropriate method of treatment through several tips that concern the disease and how to treat it and we will see it through the application on the expert system. Methods: in this paper the design of the proposed Expert System which was produced to help Psychologist in diagnosing depression disease through its symptoms such as: a loss of energy, a change in appetite, sleeping more or less, anxiety, reduced concentration, indecisiveness, restlessness, feelings of worthlessness, guilt or hopelessness and thoughts of self-harm or suicide. The proposed expert system presents an overview about depression disease is given, the cause of diseases is outlined and the treatment of disease whenever possible is given out. SL5 Object Expert System language was used for designing and implementing the proposed expert system. Results: The proposed depression disease diagnosis expert system was evaluated by psychologist students and they were satisfied with its performance. Conclusions: The Proposed expert system is very useful for psychologist, patients with depression and newly graduated psychologist. (shrink)

The aim of this paper is to evaluate the critical success factors and investigate the benefits that might be gained once implementing Electronic Customer Relationship Management at HEI from employee perspective. The study conducted at Al Quds Open University in Palestine and data collected from (300) employee through a questionnaire which consist of four variables. A number of statistical tools were intended for hypotheses testing and data analysis, including Spearman correlation coefficient for Validity, reliability correlation using Cronbach’s alpha, and Frequency (...) and Descriptive analysis. The overall findings of the current study show that all the features were important for staff and it was critical success factors, at the same time, websites were providing all the features discussed by the theory whereas staff showed their willingness to use those features if provided. It is also discovered that implementing Electronic Customer Relationship Management can cause staff retention, were provided efficiently and needed to be improved. Research limitations: The survey findings were based on QOU employee in Palestine, UAE and KSA branches not included in the study. (shrink)

The study aimed to identify the relationship between correcting the deviations in the measurement of performance and achieving the objectives of control and the performance of the job at the Islamic University in the Gaza Strip. To achieve the objectives of the research, the researchers used the descriptive analytical approach to collect information. The questionnaire consisted of (20) statements distributed to three categories of employees of the Islamic University (senior management, faculty members, their assistants and members of the administrative board). (...) A random sample of 314 employees was selected and 276 responses were retrieved with a recovery rate of 88.1%. The Statistical Analysis Program (SPSS) was used to enter, process, and analyze the data. The results of the study showed a positive relationship between correcting deviations in performance measurement and achieving the control objectives represented by the functional performance in the Islamic University from the point of view of the members (senior management, faculty and their assistants, and the administrative board), where the relative weight of all the paragraphs was (74.25%). The study recommended the need to ensure that the actual performance of the planned performance is matched and decisions are taken to correct the serious deviations and take the necessary measures in terms of retraining and change in regulations, wages and bonuses and punishment of the culprit, neglect and negligence by mistake. (shrink)

This paper aims at helping trainees to overcome the difficulties they face when dealing with Arduino platform by describing the design of a desktop based intelligent tutoring system. The main idea of this system is a systematic introduction into the concept of Arduino platform. The system shows the circuit boards of Arduino that can be purchased at low cost or assembled from freely-available plans; and an open-source development environment and library for writing code to control the board topic of Arduino (...) platform. The system is adaptive with the trainee’s individual progress. The system functions as a special tutor who deals with trainees according to their levels and skills. Evaluation of the system has been applied on professional and unprofessional trainees in this field and the results were good. (shrink)

The study aims to identify the efficiency of the university education performance from the perspective of postgraduate and undergraduate students in international and Palestinian universities. The analytical descriptive approach was used for this purpose and the questionnaire was used as a main tool for data collection. The study community consists of: post graduate students, (23850) graduate students and (146355) undergraduate students. The sample of the study was 378 graduate students and 383 undergraduate students. The random stratified sample was used. The (...) Statistical Package of Social Sciences (SPSS) was also used for data analysis. The study reached a number of results, the most important of which are: The level of efficiency of educational performance in Palestinian and international universities from the point of view of postgraduate and undergraduate students was high. And that there are significant differences between the average views of the sample of the study on the efficiency of educational performance in Palestinian and international universities attributed to the University and to the benefit of international universities. The study concluded many recommendations, the most important of which is the necessity of continuing to develop e-learning strategies that affect the efficiency of educational performance and research commensurate with the university's position in the local and international community, which puts it on the best classification between local and international universities through e-learning. (shrink)

This paper presents the design and development of intelligent tutoring system for teaching Oracle. The Oracle Intelligent Tutoring System (OITS) examined the power of a new methodology to supporting students in Oracle programming. The system presents the topic of Introduction to Oracle with automatically generated problems for the students to solve. The system is dynamically adapted at run time to the student’s individual progress. An initial evaluation study was done to investigate the effect of using the intelligent tutoring system on (...) the performance of students. (shrink)

Abstract: Smoke detectors are critical devices for early fire detection and life-saving interventions. This research paper explores the application of Artificial Neural Networks (ANNs) in smoke detection systems. The study aims to develop a robust and accurate smoke detection model using ANNs. Surprisingly, the results indicate a 100% accuracy rate, suggesting promising potential for ANNs in enhancing smoke detection technology. However, this paper acknowledges the need for a comprehensive evaluation beyond accuracy. It discusses potential challenges, such as overfitting, dataset size, (...) and class imbalance, and presents strategies employed to address these issues. Additionally, the paper emphasizes the importance of alternative evaluation metrics, including precision, recall, and F1-score, to assess the model's performance comprehensively. Detailed information regarding the model architecture, data preprocessing, and hyperparameter tuning is provided to enhance the reproducibility of the research. The study also discusses ethical considerations and the implications of false positives and false negatives in smoke detection applications. While achieving 100% accuracy is a notable accomplishment, this paper calls for cautious interpretation and further validation in real-world settings. It concludes by highlighting areas for future research and improvement in smoke detection technology, emphasizing the need for practical deployment and the reduction of false alarms. (shrink)

Origin of life on earth transpired once and from then on, it emerges as an endless eternal process. Matter and energy are constants of the cosmos and the hypothesis is that the origin of life is a moment when these constants intertwined or interacted. Energy from the cosmos interacted with inorganic matter to support matter with retention of this riveted energy, as energy to be circulated within the primitive channelized structures to conserve energy by the materialization of the proton homeostasis (...) mechanisms developed from the obtainable inorganic matter. The driver for these processes as we now confirm, exists in the quantum world and through quantum phenomenal processes could have combined these constants to create the magic of life. Primitive earth was a chemical reactive system that triggered a macromolecular evolution by means of open thermodynamic systems, driven by cyclic gradients of temperature, electromagnetic radiation and chemical potentials which sustained life and proto-consciousness in the first life forms driven by the quantum processes. The origin of life is always an intriguing topic but the purpose for finding the cause should never be inclined towards obliterating it; for if that is the case, the further we seek, the farther it will go. (shrink)

Abstract: Online book review platforms generate vast user data, making accurate rating prediction crucial for personalized recommendations. This research explores neural networks as simple models for predicting book ratings without complex algorithms. Our novel approach uses neural networks to predict ratings solely from user-book interactions, eliminating manual feature engineering. The model processes data, learns patterns, and predicts ratings. We discuss data preprocessing, neural network design, and training techniques. Real-world data experiments show the model's effectiveness, surpassing traditional methods. This research can (...) enhance user experience, book catalog organization, and aid publishers, simplifying recommendation processes and providing tailored suggestions based on user preferences. (shrink)

A new translation and edition of Aristotle's Protrepticus (with critical comments on the fragments) -/- Welcome -/- The Protrepticus was an early work of Aristotle, written while he was still a member of Plato's Academy, but it soon became one of the most famous works in the whole history of philosophy. Unfortunately it was not directly copied in the middle ages and so did not survive in its own manuscript tradition. But substantial fragments of it have been preserved in several (...) works by Iamblichus of Chalcis, a third century A.D. neo-Pythagorean philosopher and educator. On the basis of a close study of Iamblichus' extensive use and excerption of Aristotle's Protrepticus, it is possible to reconstruct the backbone of the lost work, and then to flesh it out with the other surviving reports about the work from antiquity (for example in Alexander of Aphrodisias and other ancient commentators on Aristotle). It is also possible to identify several papyrus fragments of the work, and many references and literary allusions in later authors, especially Cicero, whose own lost dialogue Hortensius was a defense of philosophy modeleld on Aristotle's. (shrink)

Cardiovascular diseases, including heart disease, pose a significant global health challenge, contributing to a substantial burden on healthcare systems and individuals. Early detection and accurate prediction of heart disease are crucial for timely intervention and improved patient outcomes. This research explores the potential of neural networks in predicting heart disease using a dataset collected from Kaggle, consisting of 1025 samples with 14 distinct features. The study's primary objective is to develop an effective neural network model for binary classification, identifying the (...) presence or absence of heart disease. The neural network architecture includes an input layer, a hidden layer, and an output layer, designed to capture intricate relationships within the dataset. Rigorous training and validation processes, accompanied by data preprocessing steps, ensure the model's robustness and generalization capabilities. The results demonstrate promising performance, with an accuracy of 92% and an average error of 0.062. Moreover, an analysis of feature importance highlights key predictors, including "oldpeak," "thalach," "trestbps," "ca," "thal," "cp," "chol," "sex," "restecg," "age," "slope," "fbs," and "exang." This research contributes to the field of predictive healthcare by leveraging neural networks to enhance heart disease prediction. The developed model offers the potential for early identification of individuals at risk, facilitating timely medical interventions and ultimately improving public health. Further exploration of machine learning techniques in healthcare promises to reshape disease prediction and prevention strategies. (shrink)

Learning programming is thought to be troublesome. One doable reason why students don’t do well in programming is expounded to the very fact that traditional way of learning within the lecture hall adds more stress on students in understanding the Material rather than applying the Material to a true application. For a few students, this teaching model might not catch their interest. As a result, they'll not offer their best effort to grasp the Material given. Seeing however the information is (...) applied to real issues will increase student interest in learning. As a consequence, this may increase their effort to be taught. In the current paper, we try to help students learn C# programming language using Intelligent Tutoring System. This ITS was developed using ITSB authoring tool to be able to help the student learn programming efficiently and make the learning procedure very pleasing. A knowledge base using ITSB authoring tool style was used to represent the student's work and to give customized feedback and support to students. (shrink)

In these days, there is an increasing technological development in intelligent tutoring systems. This field has become interesting to many researchers. In this paper, we present an intelligent tutoring system for teaching mathematics that help students understand the basics of math and that helps a lot of students of all ages to understand the topic because it's important for students of adding and subtracting. Through which the student will be able to study the course and solve related problems. An evaluation (...) of the intelligent tutoring systems was carried out and the results were encouraging. (shrink)

Papaya is a tropical fruit with a green cover, yellow pulp, and a taste between mango and cantaloupe, having commercial importance because of its high nutritive and medicinal value. The process of sorting papaya fruit based on maturely is one of the processes that greatly determine the mature of papaya fruit that will be sold to consumers. The manual grading of papaya fruit based on human visual perception is time-consuming and destructive. The objective of this paper is to the status (...) classification of papaya fruits if it's mature or partially matured or unmatured. A deep learning technique that was extensively applied to image recognition was used. The trained model achieved an accuracy of 100% on a held-out test set, demonstrating the feasibility of this approach. Classification model of VGG16 achieved a 100% accuracy and 112 seconds of training time. (shrink)

The evolution of Intelligent Tutoring System (ITS) is the result of the amount of research in the field of education and artificial intelligence in recent years. English is the third most common languages in the world and also is the internationally dominant in the telecommunications, science and trade, aviation, entertainment, radio and diplomatic language as most of the areas of work now taught in English. Therefore, the demand for learning English has increased. In this paper, we describe the design of (...) an Intelligent Tutoring System for teaching English language grammar to help students learn English grammar easily and smoothly. The system provides all topics of English grammar and generates a series of questions automatically for each topic for the students to solve. The system adapts with all the individual differences of students and begins gradually with students from easier to harder level. The intelligent tutoring system was given to a group of students of all age groups to try it and to see the impact of the system on students. The results showed a good satisfaction of the students toward the system. (shrink)

Abstract: The COVID-19 pandemic has posed unprecedented challenges to global healthcare systems, necessitating accurate and timely forecasting of cases for effective mitigation strategies. In this research paper, we present a novel approach to predict COVID-19 cases using Artificial Neural Networks (ANNs), harnessing the power of machine learning for epidemiological forecasting. Our ANNs-based forecasting model has demonstrated remarkable efficacy, achieving an impressive accuracy rate of 97.87%. This achievement underscores the potential of ANNs in providing precise and data-driven insights into the dynamics (...) of the pandemic. However, this paper underscores the critical importance of a comprehensive evaluation beyond accuracy, including metrics such as sensitivity, specificity, and the area under the ROC curve (AUC-ROC), to assess the model's performance robustness. The research paper offers detailed insights into the architecture of the ANN model, encompassing critical hyperparameters, data preprocessing techniques, and regularization strategies employed to optimize model accuracy. Ethical considerations surrounding data privacy and potential biases within the COVID-19 dataset are also addressed. While the achieved accuracy is a significant milestone, this study underscores the dynamic and evolving nature of the pandemic, necessitating continuous model refinement and validation. Furthermore, it emphasizes the importance of considering false positives and false negatives in the context of public health decision-making. In conclusion, this research contributes to the arsenal of tools available for pandemic management by showcasing the potential of ANNs in COVID-19 case forecasting. It encourages ongoing exploration and adaptation of predictive models to enhance their applicability in real-world public health scenarios, ultimately contributing to more effective pandemic control and response efforts. (shrink)

Abstract: Sign language recognition is one of the most rapidly expanding fields of study today. Many new technologies have been developed in recent years in the fields of artificial intelligence the sign language-based communication is valuable to not only deaf and dumb community, but also beneficial for individuals suffering from Autism, downs Syndrome, Apraxia of Speech for correspondence. The biggest problem faced by people with hearing disabilities is the people's lack of understanding of their requirements. In this paper we try (...) to fill this gap. By trying to translate sign language using artificial intelligence algorithms, we focused in this paper using transfer learning technique based on deep learning by utilizing a MobileNet algorithm and compared it with the previous paper results[10a], where we get in the Mobilenet algorithm on the degree of Accuracy 93,48% but the VGG16 the accuracy was 100% For the same number of images (43500 in the dataset in size 64*64 pixel ) and the same data split training data into training dataset (70%) and validation dataset(15%) and testing dataset(15%) and 20 epoch . (shrink)

In this paper an Artificial Neural Network (ANN) model was used to help cars dealers recognize the many characteristics of cars, including manufacturers, their location and classification of cars according to several categories including: Buying, Maint, Doors, Persons, Lug_boot, Safety, and Overall. ANN was used in forecasting car acceptability. The results showed that ANN model was able to predict the car acceptability with 99.12 %. The factor of Safety has the most influence on car acceptability evaluation. Comparative study method is (...) suitable for the evaluation of car acceptability forecasting, can also be extended to all other areas. (shrink)

In this paper, we present a case of a boy – Noah Wall, who till today surprises the world of neuroscience with his will to grow his brain and survive. The case presented in this study sets a stepping stone in understanding the advent of the will to make a choice, from a neuro-quantum mechanics interpretation. We propose that besides our internal states of choices (neurogenesis, neuroplasticity, cell differentiation, etc.) we also relate with external states of choices (love, compassion, empathy, (...) emotions, etc.) that contributes to its emergence. Quantum uncertainty seems to support the existence of a fundamental property based on which the universe functions; which means that even the nothing of free space has a small chance of containing something. Outcomes are not determined by prior or random events but by consciousness that gives rise to these outcomes. This provides us a lead into understanding the existence of the will and the origin of choice when we look deeper into the realms of the implausible interpretations of quantum mechanics. Free will is the ability for the mind to choose between possible outcomes. Willful power is therefore not only a psychological intervention but also a biological and quantum intervention, where we have the capacity to make choices about what direction we will take, making a change to the systematic functioning of our body. (shrink)

In this paper an Artificial Neural Network (ANN) model was used to help cars dealers recognize the many characteristics of cars, including manufacturers, their location and classification of cars according to several categories including: Make, Model, Type, Origin, DriveTrain, MSRP, Invoice, EngineSize, Cylinders, Horsepower, MPG_Highway, Weight, Wheelbase, Length. ANN was used in prediction of the number of miles per gallon when the car is driven in the city(MPG_City). The results showed that ANN model was able to predict MPG_City with 97.50 (...) % accuracy. The factor of DriveTrain has the most influence on MPG_City evaluation. Similar studies can be carried out for the evaluation of other characteristics of cars. (shrink)

Abstract: Lotteries have long been a source of fascination and intrigue, offering the tantalizing prospect of unexpected fortunes. In this research paper, we delve into the world of lottery predictions, employing cutting-edge AI techniques to unlock the secrets of lottery outcomes. Our dataset, obtained from Kaggle, comprises historical lottery draws, and our goal is to develop predictive models that can anticipate future winning numbers. This study explores the use of deep learning and time series analysis to achieve this elusive feat. (...) Through rigorous experimentation and data-driven approaches, we seek to determine the viability of AI in the realm of lottery predictions. Our findings reveal both the promise and limitations of AI in this context, shedding light on the complexities of lottery data and the potential need for quantum computing as a last resort. (shrink)

Abstract: Fruits are a rich source of energy, minerals and vitamins. They also contain fiber. There are many fruits types such as: Apple and pears, Citrus, Stone fruit, Tropical and exotic, Berries, Melons, Tomatoes and avocado. Classification of fruits can be used in many applications, whether industrial or in agriculture or services, for example, it can help the cashier in the hyper mall to determine the price and type of fruit and also may help some people to determining whether a (...) certain type of fruit meets their nutritional requirement. In this paper, machine learning based approach is presented for classifying and identifying 10 different fruit with a dataset that contains 6847 images use 4793 images for training, 1027 images for validation and 1027 images for testing. A deep learning technique that extensively applied to image recognition was used. We used 70% from image for training and 15% from image for validation 15% for testing. Our trained model achieved an accuracy of 100% on a held-out test set, demonstrating the feasibility of this approach. (shrink)

In this paper, we present an intelligent tutoring system developed to help students in learning Computer Theory. The Intelligent tutoring system was built using ITSB authoring tool. The system helps students to learn finite automata, pushdown automata, Turing machines and examines the relationship between these automata and formal languages, deterministic and nondeterministic machines, regular expressions, context free grammars, undecidability, and complexity. During the process the intelligent tutoring system gives assistance and feedback of many types in an intelligent manner according to (...) the behavior of the student. An evaluation of the intelligent tutoring system has revealed reasonably acceptable results in terms of its usability and learning abilities are concerned. (shrink)

A pineapple is a tropical plant with eatable leafy foods most monetarily critical plant in the family Bromeliaceous. The pineapple is native to South America, where it has been developed for a long time. The acquaintance of the pineapple with Europe in the seventeenth century made it a critical social symbol of extravagance. Since the 1820s, pineapple has been industrially filled in nurseries and numerous tropical manors. Further, it is the third most significant tropical natural product in world creation. In (...) the twentieth century, Hawaii was a prevailing maker of pineapples, particularly for the US, be that as it may, by 2016, Costa Rica, Brazil, and the Philippines represented almost 33% of the world's creation of pineapples. In this paper, machine learning based approach is presented for identifying type pineapple with a dataset that contains 1,311images use 946 images for training, 197 images for validation and 168 images for testing. A deep learning technique that extensively applied to image recognition was used. use 70% from image for training and 30% from image for validation. Our trained model achieved an accuracy of 100% on a heldout test set. (shrink)

The article studies the impact of Fintech on entrepreneurship in Arabic region by using Crowdfunding platforms as the field of study. The article focuses on Arabic Crowdfunding platforms. The population of (12) platforms consist of: individuals, entrepreneurs, investors, employees at Crowdfunding platforms. Descriptive and quantitative approach used in this article, and a questionnaire used as a tool to collect primary data. The results indicate an impact for Fintech on entrepreneurship in general and obvious obstacles to use it widely in Arabic (...) region cause of legislations or e-payments. The article recommended more awareness for innovative products and services such as Fintech, Crowdfunding and adopting the culture of e-business models. Also the article promoting the process of developing regulations that organize e-business models, especially Fintech and Crowdfunding, the use of modern communication technology to serve the development of society, more interest to innovation and creativity as a key factor for entrepreneurial success. (shrink)

The study aimed to identify the knowledge management processes and their role in achieving competitive advantage at Al-Quds Open University. The study was based on the descriptive analytical method, and the study population consists of academic and administrative staff in each of the branches of Al-Quds Open University in (Tulkarm, Nablus and Jenin). The researchers selected a sample of the study population by the intentional non-probability method, the size of (70) employees. A questionnaire was prepared and supervised by a number (...) of specialists in order to obtain the results of the study. The study concluded that there is a positive direct relationship, that is, the higher the degree of application of knowledge management processes, the greater the degree of competitive advantage. Knowledge Technology came first with a score of 80.02% on all items. Competitive advantage came second with 81.74%. In the third place came "knowledge generation" where the total score on all paragraphs in this area (78.24%). In the fourth place, "knowledge transfer" (77.21%). "Developing and storing knowledge" came in fifth place (77.13%). "Acquisition of knowledge" came in sixth place (76.45%). Knowledge Organization ranked seventh (74.26%). The study recommended that the university should enable the employees to benefit from the experiences and expertise available to help generate knowledge. The University encourages the creation of knowledge through the system of incentives and open the way for creators to apply their creations and spread and invest in excellence and creativity. The university should design work performance levels based on the integration of knowledge and organize it according to policies that support freedom of research. The need for Palestinian universities to adopt a knowledge management approach. The need to adopt a system of incentives that rewards cognitive efforts, and give workers enough freedom to enable them to apply their knowledge. (shrink)

The research aims to study the role of strategic and operational planning as approach for crises management in UNRWA - Gaza Strip field- Palestine. Several descriptive analytical methods were used for this purpose and a survey as a tool for data collection. Community size was (881), and the study sample was stratified random (268). The overall findings of the current study show that strategic and operational planning is performed in UNRWA. The results of static analysis show that there are a (...) relation between strategic and operational planning and crises management. In spite this relation existence, it need more improvement and expanding. Also there are shortcomings in the way that organization manages the crises before and after they occur. A crisis management is only practicing during the crisis. The study suggests that UNRWA must invest in more resources to enhance strategic and operational palming and improve other methods to face potential crises in the future. (shrink)

Brain tumors pose significant challenges in modern healthcare, with accurate and timely diagnosis crucial for determining appropriate treatment strategies. Artificial intelligence has made significant advancements in recent years. Rule-based expert systems (if-then rule-based systems) have emerged as a promising approach for clinical decision-making in brain tumor diagnosis. In this paper, we present "A CLIPS-Based Expert System for Brain Tumor Diagnosis," which leverages a set of 14 if-then rules to diagnose brain tumors with three possible outcomes: 1) Confirm the diagnosis of (...) a brain tumor, 2) Consider the possibility of a brain tumor that has metastasized, and 3) Consider the possibility of a brain tumor. Our expert system offers a user-friendly interface, enabling users to select symptoms and receive a diagnosis based on the provided information. This paper discusses the expert system's development, implementation, and evaluation, highlighting its potential to facilitate brain tumor diagnosis and decision-making in clinical settings. Additionally, we provide a literature review that contextualizes our expert system within the broader landscape of rule-based expert systems for brain tumor diagnosis, examining their effectiveness, limitations, and challenges. (shrink)

In fact, people get neck problems due to something such as sports or woke and Wrong sleep habits. In this paper an expert system was designed to help users to correctly diagnose neck problems world (muscle spasm, Muscle aches, Meningitis, herniated cervical disc, Fibromyalgia, Cervical spondylosis, Trigger points) with some information about the disease and self-care. Java language was used to design and implement this expert system.

Abstract: The Knowledge-Based System for Diagnosing Breast Cancer aims to support medical students in enhancing their education regarding diagnosis and counseling. The system facilitates the analysis of biopsy images under a microscope, determination of tumor type, selection of appropriate treatment methods, and identification of disease-related questions. According to the Ministry of Health's annual report in Gaza, there were 7,069 cases of breast cancer between 2009 and 2014, with 1,502 cases reported in 2014. In an era dominated by visual information, where (...) 65% of the population are visual learners, the Knowledge-Based System serves as an effective tool to aid long-term information retention by utilizing visual and textual resources. The system features a user-friendly interface, enabling students to diagnose the disease and expand their understanding. Furthermore, it can be accessed via smartphones. The Knowledge-Based System comprises three primary components: Firstly, it provides specific patient-oriented questions to familiarize students with the questioning process. Secondly, it facilitates the analysis of biopsy sample images to determine their integrity and identify potential infections. Lastly, the system incorporates animated videos illustrating various approaches for treating breast cancer. (shrink)

The cucumber is a creeping vine that roots in the ground and grows up trellises or other supporting frames, wrapping around supports with thin, spiraling tendrils. The plant may also root in a soilless medium, whereby it will sprawl along the ground in lieu of a supporting structure. The vine has large leaves that form a canopy over the fruits. Among these common diseases, we single out the diseases that affect the cucumber, which is affected by about 22 diseases, with (...) different symptoms for each disease. Today, technology is facilitating human life in all areas of life, and among these facilities are expert systems that have become an integral part of human life as they contain several systems and areas, for example: Artificial Intelligence (AI), which refers to systems or devices that simulate Human intelligence to perform tasks that can improve itself based on some human information, and other areas, and with reference to expert systems and their importance to humans, an integrated expert system has been created in the agricultural field that diagnoses cucumber diseases using CLIPS Expert System language Delphi language. The system was used to design and implement the proposed expert system. The system facilitates the diagnosis of cucumber-related diseases. There is no doubt that this expert system will help farmers and those involved in the agricultural field to diagnose cucumber-related diseases. Objectives: is to help farmers diagnose pear diseases in the correct way and how to treat these diseases. Method: The system contains a program that diagnoses 22 diseases that affect cucumber. Results: The expert system was evaluated by farmers and praised for helping them with it. Conclusion: The expert system for diagnosing cucumber diseases is effective and usable. (shrink)

There is no doubt that tomato diseases are one of the important reasons that destroy the tomato plant and its crops. This leads to clear damage to these plants and they become inedible. Discovering these diseases after a good step for proper and correct treatment. Determining the treatment with high accuracy depends on the method used in the diagnosis. Correctly, expert systems can greatly help to avoid damage to these plants. The expert system diagnoses tomato disease correctly to facilitate farmers (...) to find the correct treatment based on the appropriate diagnosis. Objectives: An expert system has been established based on CLIPS to diagnose tomato plant disease. (shrink)

Water quality assessment is critical for environmental sustainability and public health. This research employs neural networks to predict water quality, utilizing a dataset of 21 diverse features, including metals, chemicals, and biological indicators. With 8000 samples, our neural network model, consisting of four layers, achieved an impressive 94.22% accuracy with an average error of 0.031. Feature importance analysis revealed arsenic, perchlorate, cadmium, and others as pivotal factors in water quality prediction. This study offers a valuable contribution to enhancing water quality (...) monitoring and decision-making for stakeholders and policymakers. (shrink)

Abstract— This study aimed to identify the degree of use of the capabilities of decision-support systems in Palestinian institutions higher education, Aqsa University in Gaza - a case study. The study used a analytical descriptive approach, and the researchers used the of questionnaire tool to collect the data, the researchers using stratified random sample distributed (150) questioners to the study population and (126) was obtained back with rate of 84%. The study showed that the most important results are: that senior (...) management supports the existence of decision support systems and that there is approval by the respondents on the paragraphs of the use of the capabilities of decision support systems in general. And that there are no significant differences between the averages of the answers of respondents differences about the degree of use of decision support systems capabilities attributed to personal data. The study also concluded a series of recommendations including: increasing the adoption of the senior management decision support in their decision-making systems. And increased regulatory attention to the potential available to decision support systems directly to the senior management in the Palestinian universities in the Gaza Strip. There is an increased interest in the physical and technical possibilities available for the use of decision support systems. There is an increased interest in human potential available for the use of decision support systems. Investment of information available to universities in building the capacities of integration techniques and other information technology capabilities. The empowerment of human resources in universities and participating in making decisions concerning the construction of the capabilities of information technology. (shrink)

Abstract: The sinking of the RMS Titanic in 1912 remains a poignant historical event that continues to captivate our collective imagination. In this research paper, we delve into the realm of data-driven analysis by applying Artificial Neural Networks (ANNs) to predict the chances of survival for passengers aboard the Titanic. Our study leverages a comprehensive dataset encompassing passenger information, demographics, and cabin class, providing a unique opportunity to explore the complex interplay of factors influencing survival outcomes. Our ANN-based predictive model (...) achieved an accuracy rate of 78%, shedding light on the underlying patterns within the data. However, this paper underscores the multifaceted nature of survival prediction and acknowledges several challenges. These include missing data imputation, feature engineering, and the inherent noise within historical datasets. We further discuss the importance of model evaluation metrics, showcasing not only accuracy but also precision, recall, and F1-score as essential indicators of predictive performance. The research paper meticulously outlines the architecture of the ANN model, emphasizing the key hyperparameters, activation functions, and regularization techniques employed in model development. Additionally, we address ethical considerations related to data handling and potential biases within the dataset. While our achieved accuracy is a notable achievement, this study emphasizes the importance of interpreting the results with due caution. It underscores the need for a holistic perspective that considers the practical implications of false positives and false negatives, especially in the context of a disaster scenario. In conclusion, this research contributes to our understanding of survival prediction in historical events like the Titanic disaster using modern machine learning techniques. It calls for further exploration and refinement of predictive models, with a focus on enhancing the interpretability and generalizability of such models to real-world applications. (shrink)

This research paper presents the development and evaluation of an expert system for diagnosing kidney diseases. The expert system utilizes a decision-making tree approach and is implemented using the CLIPS and Delphi frameworks. The system's accuracy in diagnosing kidney diseases and user satisfaction were evaluated. The results demonstrate the effectiveness of the expert system in providing accurate diagnoses and high user satisfaction.

Vertigo is a common symptom that can result from various underlying diseases and conditions, ranging from benign to severe. Accurate and timely diagnosis of the cause of vertigo is crucial for appropriate management and treatment. In this research, we propose the development of an expert system for vertigo diseases diagnosis, utilizing artificial intelligence (AI) and the proposed Expert System which was produced to help assist healthcare professionals in diagnosing the cause of vertigo based on a patient's symptoms, medical history, and (...) other relevant clinical information. The proposed expert system presents an overview about vertigo diseases are given, the cause of disease is outlined and the treatment or recommendation of disease whenever possible is given out. CLIPS language was used for designing and implementing the proposed expert system. The potential of the proposed expert system lies in its ability to enhance the accuracy and efficiency of vertigo diagnosis, as well as assist in the proper referral and management of patients. (shrink)

Abstract: This research focuses on utilizing Artificial Neural Networks (ANNs) to predict Audit Risk accurately, a critical aspect of ensuring financial system integrity and preventing fraud. Our dataset, gathered from Kaggle, comprises 18 diverse features, including financial and historical parameters, offering a comprehensive view of audit-related factors. These features encompass 'Sector_score,' 'PARA_A,' 'SCORE_A,' 'PARA_B,' 'SCORE_B,' 'TOTAL,' 'numbers,' 'marks,' 'Money_Value,' 'District,' 'Loss,' 'Loss_SCORE,' 'History,' 'History_score,' 'score,' and 'Risk,' with a total of 774 samples. Our proposed neural network architecture, consisting of three (...) layers (1 input, 1 hidden, and 1 output), forms the core of this study. While it may seem simple, the power of ANNs lies not in complexity but in their ability to uncover intricate data patterns. The model underwent rigorous training and validation, resulting in remarkable outcomes—an accuracy of 100% and an average error rate of 0.000015. In addition to performance metrics, our research investigates feature importance, revealing the key contributors to Audit Risk prediction. Notably, 'Sector_score,' 'PARA_A,' 'SCORE_A,' 'PARA_B,' 'SCORE_B,' 'TOTAL,' 'numbers,' 'marks,' 'Money_Value,' 'District,' 'Loss,' 'Loss_SCORE,' 'History,' and 'History_score' emerged as the most influential factors, shedding light on the elements crucial for precise risk assessment. This study advances Audit Risk prediction models and highlights the potential of ANNs in strengthening financial system integrity and fraud prevention. The insights gained from our findings offer practical guidance for stakeholders in the audit and financial sectors. (shrink)

Abstract: Purpose - This study aimed to analyze the relationship between the determinants of organizational justice and their relationship to conscientious behavior from the point of view of officers working in the Palestinian police in Gaza Strip. Methodology - The study relied on the descriptive and analytical approach, using the questionnaire, targeting a stratified random sample of (400) officers, who hold the rank of captain and above, from the study population of 1550 officers. The study tool was distributed among the (...) sample members in all departments and governorates. Police in Gaza Strip. (353) questionnaires were retrieved, with a recovery rate of (88.3%). Findings - The existence of a positive correlation between the determinants of organizational justice and the behavior of conscience, and the existence of organizational justice in general in a medium degree and the order of its determinants is as follows: fairness of dealings and to a large degree, followed by fairness of procedures and a medium degree, and finally distribution fairness was to a small degree, while the behavior of conscience awareness came to a large extent. Significance - The existence of statistically significant differences between the respondents' averages of responding to the searched relationship due to the variables (type of administration, age group, job title, military rank, years of service). Recommendations - Work to take into account the fairness of distribution by providing adequate and fair salaries, granting bonuses for the additional efforts exerted, and budgeting in the distribution of duties and job burdens, as well as recommending attention to the interests of employees when making decisions and involving them in formulating them, explaining their justifications, and creating an organizational climate dominated by a sense of justice. (shrink)