Abstract: The integration of Artificial Intelligence (AI) into leadership practices is rapidly transforming organizational dynamics and decision-making processes. This paper explores the ways in which AI enhances leadership effectiveness by providing data- driven insights, optimizing decision-making, and automating routine tasks. Additionally, it examines the challenges leaders face when adopting AI, including ethical considerations, potential biases in AI systems, and the need for upskilling. By analyzing current applications of AI in leadership and discussing future trends, this study aims to offer a (...) comprehensive overview of the opportunities AI presents for effective leadership, as well as the strategies required to address its associated challenges. (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)

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)

This study employs machine learning to predict diabetes using a Kaggle dataset with 13 features. Our three-layer model achieves an accuracy of 98.73% and an average error of 0.01%. Feature analysis identifies Age, Gender, Polyuria, Polydipsia, Visual blurring, sudden weight loss, partial paresis, delayed healing, irritability, Muscle stiffness, Alopecia, Genital thrush, Weakness, and Obesity as influential predictors. These findings have clinical significance for early diabetes risk assessment. While our research addresses gaps in the field, further work is needed to enhance (...) model generalizability. (shrink)

Accurate assessment and comprehension of smoking behavior are pivotal for elucidating associated health risks and formulating effective public health strategies. In this study, we introduce an innovative approach to predict and analyze smoking prevalence using an artificial neural network (ANN) model. Leveraging a comprehensive dataset spanning multiple years and geographic regions, our model incorporates various features, including demographic data, economic indicators, and tobacco control policies. This research investigates smoking trends with a specific focus on gender-based analyses. These findings are pivotal (...) for enhancing public health initiatives aimed at mitigating tobacco use, assessing associated health risks, and mitigating smoking-related diseases. (shrink)

The study’s goal was to provide an educational intervention in Algebra through GeoGebra that would boost students’ confidence, improve their learning, and correct their most minor mastered skills, allowing them to improve their Algebra performance. The research design was quasi-experimental, with 40 nonrandomly chosen participants comprising the GeoGebra and control groups. Mean and standard deviation was employed to describe the algebra performance and confidence of the respondents. At the same time, independent and dependent t-tests were used to determine the students’ (...) significant difference in algebra performance and confidence in the pre-and post-test between the control and GeoGebra groups. GeoGebra effectively improved algebra confidence, enhanced learning, and remedied the students’ least mastered skills. GeoGebra is recommended as an instructional material in teaching and learning Algebra and can be extended to other mathematics content areas. (shrink)

Abstract: In this study, we explore the possibility of classifying the plant species. We collected the plant species from Kaggle website. This dataset encompasses 544 samples, encompassing 136 distinct plant species. Recent advancements in machine learning, particularly Artificial Neural Networks (ANNs), offer promise in enhancing plant Species classification accuracy and efficiency. This research explores plant Species classification, harnessing neural networks' power. Utilizing a rich dataset from Kaggle, containing 544 entries, we develop and evaluate a neural network model. Our neural network, (...) featuring a single hidden layer, achieves remarkable results—a staggering 100% accuracy and a minute average error rate of 0.002. Beyond performance metrics, we delve into the intricacies of plant Species classification through feature importance analysis. The most influential features— Vegsout, durflow, semiros, pdias, begflow, wind, leafy, autopoll and insects— uncover the physiological traits underpinning accurate rice classification. This research contributes to advancing rice classification methods and highlights the potential of ANNs in optimizing agricultural practices, ensuring plant safety, and bolstering global trade. (shrink)

The problem of other minds has a distinguished philosophical history stretching back more than two hundred years. Taken at face value, it is an epistemological question: it concerns how we can have knowledge of, or at least justified belief in, the existence of minds other than our own. In recent decades, philosophers, psychologists, neuroscientists, anthropologists and primatologists have debated a related question: how we actually go about attributing mental states to others (regardless of whether we ever achieve knowledge or rational (...) justification in this domain). Until the mid-nineties, the latter debate – which sometimes goes under the name of the “mindreading” debate – was characterized by a fairly clear-cut opposition between two theoretical outlooks: “theory-theory” (TT) and “simulation theory” (ST). Theory-theorists typically argued that we attribute mental states to others on the basis of a “theory of mind” that is either constructed in early infancy and subsequently revised and modified (Gopnik 1996), or else is the result of maturation of innate mindreading “modules” (Baron-Cohen 1995). (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)

Today’s everyone normal life can include a normal rate of playing computer games or video games; but what about an excessive or compulsive use of video games that impact on our life? Our kids, who usually spend a lot of time in playing video games will likely have a trouble in paying attention to their school lessons. In this paper, we introduce an expert system to help users in getting the correct diagnosis of the health problem of video game addictions (...) that range from (Musculoskeletal issues, Vision problems and Obesity). Moreover, this expert system provides information about the problem and tell us how we can solve it. SL5 Object expert system language was used to design and implement the expert system. (shrink)

Abstract: Sarcasm is commonly used in news and detecting sarcasm in headline news is challenging for humans and thus for computers. The media regularly seem to engage sarcasm in their news headline to get the attention of people. However, people find it tough to detect the sarcasm in the headline news, hence receiving a mistaken idea about that specific news and additionally spreading it to their friends, colleagues, etc. Consequently, an intelligent system that is able to distinguish between can sarcasm (...) none sarcasm automatically is very important. The aim of the study is to build a sarcasm model that detect headline news using machine and deep learning and attempt to understand how a computer learns the patterns of sarcasm. The dataset used in this study was collected from Kaggle depository. We examined 21 algorithms of machine learning and one deep learning algorithm for detecting sarcasm in headline news. The evaluation metric used in this study are Accuracy, F1-measure, Recall, Precision, and Time needed for training and evaluation. The deep learning model achieved accuracy (95.27%), recall (96.62%), precision (94.15%), F1-score (95.37%) and time needed to train the mode (400 seconds), with loss of around 0.3398. However, the algorithm of machine learning that achieved the highest F1-Score is Passive Aggressive Classifier. It was the top classier for sarcasm detection among the machine learning algorithms with accuracy (95.50%), recall (96.09 %), precision (94.30%), F1-score (95.19%) and time needed to train the mode (0.31 seconds). (shrink)

Contemporary republicanism is characterized by three main ideas: free persons, who are not subject to the arbitrary power of others; free states, which try to protect their citizens from such power without exercising it themselves; and vigilant citizenship, as a means to limit states to their protective role. This book advances an economic model of such republicanism that is ideologically centre-left. It demands an exit-oriented state interventionism, one that would require an activist government to enhance competition and resource exit from (...) dominating relationships within markets of all types, be they marital, labour, or residential. The substantial intervention and redistribution necessitated by such an approach make it leftist, while its tendency to work with rather than against the grain of markets makes it centrist. It is, in short, a contribution to progressive republican political thought, but one that is less social-democratic than market-democratic in character. (shrink)

This paper aims to identify computerized management information systems resources and their relationship to the development of performance in the Electricity Distribution Company in Gaza. This research used two dimensions. The first dimension is computerized management information systems and the second dimension the Development of Performance. The control sample was (063). (360) questioners were distributed and (306) were retrieved back with a percentage of (85%). Several statistical tools were used for data analysis and hypotheses testing, including reliability correlation using Cronbach’s (...) alpha, “ANOVA”, Simple Linear Regression and Step Wise Regression. The overall findings of the current study suggested the presence of a statistically significant relationship between resources (physical, software, and human and organizational) for the computerized management information systems and the development of performance in the Electricity Distribution Company in Gaza. The study recommended the following: The need to strengthen the company's management interest in the potential of computerized management information systems and using them in the computerization of all the company's activities. And the need to involve workers and users in the design of computerized management information systems and assessment and development process. And strengthen the relationship between users and information systems personnel in the department responsible for the system. And it is essential that the company is developing the infrastructure for information technology in general, and computerized management information systems, in particular for the development of performance. And increase interest in providing resources (physical, software, and human and organizational) for the computerized management information systems. The current study is unique by the virtue of its nature, scope and way of implied investigation, as it is the first study at Electricity Distribution Company in Gaza resources explores the status of Computerized management information systems and their relationship to the development of performance in the Electricity Distribution Company in Gaza increasing interest in Computerized management information systems through continuity, keeping pace with technological means and modern techniques. (shrink)

This paper aims to assess knowledge management maturity at HEI to determine the most effecting variables on knowledge management that enhance the total performance of the organization. This study was applied on Al-Azhar University in Gaza strip, Palestine. This paper depends on Asian productivity organization model that used to assess KM maturity. Second dimension assess high performance was developed by the authors. The controlled sample was (364). Several statistical tools were used for data analysis and hypotheses testing, including reliability Correlation (...) using Cronbach’s alpha, “ANOVA”, Simple Linear Regression and Step Wise Regression. The overall findings of the current study suggest that KMM is suitable for measuring and lead to enhance high performance. KMM assessment shows that the university maturity level is in level three. Findings also support the main hypothesis and it is subhypotheses. The most important factors effecting high performance are: Processes, KM leadership, People, KM Outcomes, Knowledge Process. Furthermore the current study is unique by the virtue of its nature, scope and way of implied investigation, as it is the first study at HEI in Palestine explores the status of KMM using the Asian productivity model. (shrink)

In this article, it has been aimed to examine Nietzsche’s main critique towards different understandings of morals in his era. With this criticism, it is aimed to integrally understand the opinions -which are articulated directly or metaphorically- towards morals which have been encountered. In here, while keeping in mind the difference between the concepts of immoralism and amoralism, Nietzsche’s views are interpreted. Being parallel to that aim mentioned above, it has been investigated if there is a thinking in Nietzsche which (...) can be seen as a kind of understanding of morals (maybe as the understanding of morals without morals) or not. And finally, it has been thought that if Nietzsche’s views on morals have any value for the 21st century and upcoming 22nd century human or not, whether there’s something left to learn for this human from his critiques or not. (shrink)

Artificial intelligence (AI) is an area of computer science that emphasizes the creation of intelligent machines or software that work and react like humans. Some of the activities computers with artificial intelligence are designed for include, Speech, recognition, Learning, Planning and Problem solving. Deep learning is a collection of algorithms used in machine learning, It is part of a broad family of methods used for machine learning that are based on learning representations of data. Deep learning is a technique used (...) to produce Pneumonia detection and classification models using x-ray imaging for rapid and easy detection and identification of pneumonia. In this thesis, we review ways and mechanisms to use deep learning techniques to produce a model for Pneumonia detection. The goal is find a good and effective way to detect pneumonia based on X-rays to help the chest doctor in decision-making easily and accuracy and speed. The model will be designed and implemented, including both Dataset of image and Pneumonia detection through the use of Deep learning algorithms based on neural networks. The test and evaluation will be applied to a range of chest x-ray images and the results will be presented in detail and discussed. This thesis uses deep learning to detect pneumonia and its classification. (shrink)

Publication date: 29 September 2016 Source: Author: Samy S. Abu Naser, Mazen J. Al Shobaki, Youssef M. Abu Amuna This paper aims to measure knowledge management maturity in higher education institutions to determine the impact of knowledge management on high performance. Also the study aims to compare knowledge management maturity between universities and intermediate colleges. This study was applied on five higher education institutions in Gaza strip, Palestine. Asian productivity organization model was applied to measure Knowledge Management Maturity. Second dimension (...) which assess high performance was developed by the authors. The controlled sample was. Several statistical tools were used for data analysis and hypotheses testing, including reliability correlation using Cronbach’s alpha, “ANOVA”, Simple Linear Regression and Step Wise Regression. The overall findings of the current study shows that maturity level is in the second level. Findings also support the main hypothesis and it is sub- hypotheses. The most important factors effecting high performance are: Processes, knowledge management leadership, People, knowledge management Outcomes. Furthermore the current study is unique by the virtue of its nature, scope and way of implied investigation, as it is the first comparative study between universities and intermediate colleges in Gaza Strip that explores the status of knowledge management maturity using the Asian productivity Model. (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)

Background: Mint is a grassy, perennial plant, belonging to the oral platoon, fast growing and spreading, its leaves are green in color, fragrant, tart, refreshing, square-shaped leg, bifurcated, erect, ranging in height from (10 - 201 cm). Home to Europe and Asia. The mint plant has many benefits, the most important of which are pain relief, treatment of gallbladder disorders, the expulsion of gases, anti-inflammatory, and relaxing nerves. While the mint plant is the ideal option for the start of gardens, (...) it is prone to some common diseases that affect the plant's growth. Objectives: The main goal of this expert system is to get the appropriate diagnosis of disease and the correct treatment. Methods: In this paper, the design of the proposed Expert System was produced to help Farmers and those interested in agriculture in diagnosing many of the Mint diseases such as Mint rust, Verticillium wilt, Anthracnose, Powdery mildew, Black Stem Rot, Stem and stolon canker, Septoria leaf spot. The proposed expert system presents an overview of mint diseases are given, the cause of diseases outlined and the treatment of disease whenever possible is given out. CLIPS Expert System language was used for designing and implementing the proposed expert system. Results: The proposed Mint diseases diagnosis expert system was evaluated by Agricultural Students at AL Azhar University and some friends interested in agriculture and they were satisfied with its performance. Conclusions: The proposed expert system is very useful for Farmers and those interested in agriculture. (shrink)

Abstract: The Spotify Status Dataset is a valuable resource that provides real-time insights into the operational status and performance of Spotify, a popular music streaming platform. This dataset contains a wide array of information related to server uptime, user activity, service disruptions, and more, serving as a critical tool for both Spotify's internal monitoring and the broader data analysis community. As digital services like Spotify continue to play a central role in music consumption, understanding the platform's status becomes crucial for (...) ensuring a seamless user experience. This dataset offers numerous research and analysis opportunities, whether you're interested in exploring service availability trends or investigating user behavior patterns during service disruptions. This study highlights the significance of the Spotify Status Dataset, its potential applications, and the valuable insights it can offer to various stakeholders, from Spotify engineers working to enhance service reliability to researchers studying the effects of downtime on user engagement. It invites readers on a journey through this dataset to uncover the secrets of Spotify's operational status and its impact on music enthusiasts worldwide. (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.

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 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)

Neurological syndromes in which consciousness seems to malfunction, such as temporal lobe epilepsy, visual scotomas, Charles Bonnet syndrome, and synesthesia offer valuable clues about the normal functions of consciousness and ‘qualia’. An investigation into these syndromes reveals, we argue, that qualia are different from other brain states in that they possess three functional characteristics, which we state in the form of ‘three laws of qualia’. First, they are irrevocable: I cannot simply decide to start seeing the sunset as green, or (...) feel pain as if it were an itch; second, qualia do not always produce the same behaviour: given a set of qualia, we can choose from a potentially infinite set of possible behaviours to execute; and third, qualia endure in short-term memory, as opposed to non-conscious brain states involved in the on-line guidance of behaviour in real time. We suggest that qualia have evolved these and other attributes because of their role in facilitating non-automatic, decision-based action. We also suggest that the apparent epistemic barrier to knowing what qualia another person is experiencing can be overcome by using a ‘bridge’ of neurons; and we offer a hypothesis about the relation between qualia and one's sense of self. (shrink)

Sign Language Recognition (SLR) aims to translate sign language into text or speech in order to improve communication between deaf-mute people and the general public. This task has a large social impact, but it is still difficult due to the complexity and wide range of hand actions. We present a novel 3D convolutional neural network (CNN) that extracts discriminative spatial-temporal features from photo datasets. This article is about classification of sign languages are not universal and are usually not mutually intelligible (...) although there are also similarities among different sign languages. They are the foundation of local Deaf cultures and have evolved into effective means of communication. Although signing is primarily used by the deaf and hard of hearing, hearing people also use it when they are unable to speak, when they have difficulty speaking due to a health condition or disability (augmentative and alternative communication), or when they have deaf family members, such as children of deaf adults. In this article we use the 43500 image in the dataset in size 64*64 pixel by use CNN Architecture and achieved 100% accuracy. (shrink)

there is a communication gap between hearing-impaired people and those with normal hearing, sign language is the main means of communication in the hearing-impaired population. Continuous sign language recognition, which can close the communication gap, is a difficult task since the ordered annotations are weakly supervised and there is no frame-level label. To solve this issue, we compare the accuracy of each model using two deep learning models, Inception and Xception . To that end, the purpose of this paper is (...) By attempting to translate sign language using deep learning models, we focused in this paper a comparing between Inception and Xception ¬¬¬¬¬ algorithm and compared it to previous papers in which we used VGG19[1], mobileNet [2], where we get in the Inception and Xception algorithm on the degree of Accuracy 99.32%, 99,43% respectively. number of images (29000 in the dataset in size 75*75 pixel ) and the data split training data into training dataset (70%) and validation dataset(15%) and testing dataset(15%) and 20 epoch. (shrink)

American Sign Language, or ASL as its acronym is commonly known, is a fascinating language, and many people outside of the Deaf community have begun to recognize its value and purpose. It is a visual language consisting of coordinated hand gestures, body movements, and facial expressions. Sign language is not a universal language; it varies by country and is heavily influenced by the native language and culture. The American Sign Language alphabet and the British Sign Language alphabet are completely contrary. (...) Fingerspelling is one-handed in ASL and two-handed in BSL, with the exception of the letter C. AI technologies, particularly deep learning, can play an important role in breaking down communication barriers between deaf or hearing-impaired people and other communities, significantly contributing to their social inclusion. Recent advances in sensing technologies and AI algorithms have paved the way for the development of a wide range of applications aimed at meeting the needs of the deaf and hearing-impaired communities. To that end, the purpose of this paper is By attempting to translate sign language using artificial intelligence algorithms, we focused in this paper on a transfer learning technique based on deep learning using a ResNet algorithm and compared it to previous papers in which we used VGG19[1]and mobileNet [2], where we get in the ResNet algorithm on the degree of Accuracy 93,48% e number of images (43500 in the dataset in size 64*64 pixel ) and the data split training data into training dataset (70%) and validation dataset(15%) and testing dataset(15%) and 20 epoch. (shrink)

The phenomenon of ambivalence is an important one for any philosophy of action. Despite this importance, there is a lack of a fully satisfactory analysis of the phenomenon. Although many contemporary philosophers recognize the phenomenon, and address topics related to it, only Harry Frankfurt has given the phenomenon full treatment in the context of action theory - providing an analysis of how it relates to the structure and freedom of the will. In this paper, I develop objections to Frankfurt's account, (...) all revolving around the charge that his account contains a serious ambiguity between willing and identifying. With such objections in place, I then develop an analysis that avoids the difficulties and ambiguities that Frankfurt's analysis is prey to. I briefly distinguish ambivalence from other types of internal conflict. This paper aims to offer conceptual clarification on the phenomenon of ambivalence, which will then allow for discussions about the normative merits and demerits of ambivalence, the effects of ambivalence on autonomous action, and methods of resolution of ambivalence. (shrink)

Background: Persimmon is a grassy, perennial plant, belonging to the oral platoon, square-shaped leg, bifurcated, erect, and ranging in height from (10 - 201 cm). Home to Europe and Asia. The Persimmon plant has many benefits, the most important of which are pain relief, treatment of gallbladder disorders, the expulsion of gases, anti-inflammatory, and relaxing nerves. While the Persimmon plant is the ideal option for the start of gardens, it is prone to some common diseases that affect the plant's growth. (...) Objectives: The main goal of this expert system is to get the appropriate diagnosis of disease and the correct treatment. Methods: In this paper, the design of the proposed Expert System was produced to help Farmers and those interested in agriculture in diagnosing many of the Persimmon diseases such as Persimmon rust, Verticillium wilt, Anthracnose, Powdery mildew, Black Stem Rot, Stem and stolon canker, Septoria leaf spot. The proposed expert system presents an overview of Persimmon diseases are given, the cause of diseases outlined and the treatment of disease whenever possible is given out. CLIPS Expert System language was used for designing and implementing the proposed expert system. Results: The proposed Persimmon diseases diagnosis expert system was evaluated by Agricultural Students at AL Azhar University and some friends interested in agriculture and they were satisfied with its performance. Conclusions: The proposed expert system is very useful for Farmers and those interested in agriculture. (shrink)

Artificial intelligence (AI) is an area of computer science that emphasizes the creation of intelligent machines or software that work and reacts like humans, some of the computer activities with artificial intelligence are designed to include speech, recognition, learning, planning and problem solving. Deep learning is a collection of algorithms used in machine learning, it is part of a broad family of methods used for machine learning that are based on learning representations of data. Deep learning is used as a (...) technique to produce brain tumor detection and classification models using Magnetic Resonance Imaging (MRI) imaging for rapid and easy detection and identification of brain tumor. In this thesis, some ways and mechanisms will be reviewed to use deep learning techniques to produce a model for brain tumor detection. The goal is to find a good and effective way to detect brain tumor based on MRI to help the brain doctor in making decisions easily, accurately and rapidly. A recent report by the World Health Organization in February 2018 showed that the death rate from brain cancer or central nervous system (CNS) is the highest in the Asian continent. It is important to detect cancer early so that many of these lives can be saved. The model has been designed and implemented, including a dataset which consist of 10,000 images for brain tumor detection through the use of Deep learning algorithms based on neural networks. For testing, we have used our model, Inception, VGG16, MobileNet and ResNet models. The f-score accuracy we got for each model was as follows: Our model was 98.28, VGG16 was 99.86%, ResNet50 was 98.14%, MobileNet was 88,98%, and InceptionV3 was 99.88%. (shrink)

Many scholars, including G. A. Cohen, Daniel Attas, and George Brenkert, have denied that a Kantian defense of self-ownership is possible. Kant's ostensible hostility to self-ownership can be resolved, however, upon reexamination of the Groundwork and the Metaphysics of Morals. Moreover, two novel Kantian defenses of self-ownership (narrowly construed) can be devised. The first shows that maxims of exploitation and paternalism that violate self-ownership cannot be universalized, as this leads to contradictions in conception. The second shows that physical coercion against (...) rational agents involves a profound status wrong--namely, their treatment as children or animals--and that this system of differential status and treatment (including self-ownership rights for rational agents) can be morally justified by our capacity for autonomy. (shrink)

As these opening quotes acknowledge, the Prisoner’s Dilemma (PD) represents a core puzzle within the formal mathematics of game theory.3 Its rise in conspicuity is evident figure 2.1 above demonstrating a relatively steady rise in incidences of the phrase’s usage between 1960 to 1995, with a stable presence persisting into the twenty first century. This famous two-person “game,” with a stock narrative cast in terms of two prisoners who each independently must choose whether to remain silent or speak, each advancing (...) self-interest at the expense of the other and thereby achieving a mutually suboptimal outcome, mires any social interaction it is applied to into perplexity. The logic of this game proves the inverse of Adam Smith’s invisible hand: individuals acting on self interest will achieve a mutually suboptimal outcome. However, as this chapter illuminates, the assumptions underlying game theory drive this conclusion. (shrink)

Terraforming is a process of planetary engineering by which the extant environment of a planetary body is transformed into an environment capable of supporting human inhabitants. The question I would like to consider in this paper is whether there is any reason to believe that the terraforming of another planet—for instance, the terraforming of Mars—is morally problematic. Topics related to the human exploration of space are not often discussed in philosophical circles. Nevertheless, there exists a growing body of philosophical literature (...) dedicated to sorting out the moral implications of the use of resources from (and in) space. Most of this literature is produced as environmental philosophy. Questions of .. (shrink)

The question of authenticity centers in the lives of women of color to invite and restrict their representative roles. For this reason, Gayatri Chakravorty Spivak and Uma Narayan advocate responding with strategic essentialism. This paper argues against such a strategy and proposes an epistemic understanding of the question of authentic- ity. The question stems from a kernel of truth—the connection between experience and knowledge. But a coherence theory of knowledge better captures the sociality and the holism of experience and knowledge.

Abstract: The study aimed to determine the strategic flexibility and its relationship to the level of quality of services provided, from the viewpoint of the internal beneficiary in non-governmental hospitals in Gaza Strip. The study relied on the descriptive and analytical approach, and the questionnaire was designed as a tool to collect data and consisted of (39) items, and the researchers used the comprehensive survey method, and the number of the study population was (536) individuals, where (434) questionnaires were retrieved, (...) and the recovery rate was (80.97%). The study revealed many results, the most important of which were: the existence of a moderate degree of approval by the study sample individuals on strategic flexibility, as it was evident through the area of strategic flexibility as a whole having a relative weight (60.44%). The study is on the quality of services, as it became clear through the field of service quality obtaining a relative weight (79.90%). The results of the study revealed a statistically significant relationship between strategic flexibility and the quality of services in non-governmental hospitals in Gaza Strip, with a correlation coefficient of 0.490. The study reached many recommendations, the most important of which were: the need to work on appointing young people and those with potentials, because jobs are vacant in the hospitals under study, and the need to seek the help of an administrative staff with scientific and practical qualifications, and to work on updating information systems, archiving and networks through which data and information are transferred between departments And the creation of mechanisms by which stored information can be used to enhance the decision-making process, and an effective system to receive patients' complaints in a manner that ensures rapid response and treatment, to achieve continuous communication between patients and the hospital management, and to notify patients of dealing with the complaints they submit, and work to provide all Medical and health specialties in the hospitals under study, by making use of the medical delegations that visit Gaza Strip, involving them in the treatment processes, bringing in doctors and specialists from abroad, updating the standards related to measuring the services provided to patients on an ongoing basis, based on the suggestions and complaints of patients, and developing facilities in hospitals As well as updating the medical devices and equipment used in hospitals periodically. (shrink)

Artificial intelligence is one of the most rapidly evolving fields today. It is used in the majority of computer science applications nowadays. Expert systems are one of the most valuable types of AI; they are used to deliver predictions and decisions in order to make scientific, medical, and even architectural challenges easier to address; they will eventually take the place of a human expert. Without having to meet with a genuine human specialist, the user will be able to get a (...) precise solution or diagnose to his problem. This study provides an illustration of how computer systems can be used in agriculture. In order to construct an expert system that can forecast a disease based on its symptoms, we chose a Coriander plant and five of its recognized ailments. CLIPS was used to develop the system. This article contains a full summary of the work that has been done. (shrink)

Antimicrobial resistance (AMR) is a global public health disaster driven largely by antibiotic use in human health care. Doctors considering whether to prescribe antibiotics face an ethical conflict between upholding individual patient health and advancing public health aims. Existing literature mainly examines whether patients awaiting consultations desire or expect to receive antibiotic prescriptions, but does not report views of the wider public regarding conditions under which doctors should prescribe antibiotics. It also does not explore the ethical significance of public views (...) or their sensitivity to awareness of AMR risks or the standpoint (self-interested or impartial) taken by participants. Methods: An online survey was conducted with a sample of the U.S. public (n = 158). Participants were asked to indicate what relative priority should be given to individual patients and society-at-large from various standpoints and in various contexts, including antibiotic prescription. Results: Of the participants, 50.3% thought that doctors should generally prioritize individual patients over society, whereas 32.0% prioritized society over individual patients. When asked in the context of AMR, 39.2% prioritized individuals whereas 45.5% prioritized society. Participants were significantly less willing to prioritize society over individuals when they themselves were the patient, both in general (p = .001) and in relation to AMR specifically (p = .006). Conclusions: Participants’ attitudes were more oriented to society and sensitive to collective responsibility when informed about the social costs of antibiotic use and when considered from a third-person rather than first-person perspective. That is, as participants came closer to taking the perspective of an informed and impartial “ideal observer,” their support for prioritizing society increased. Our findings suggest that, insofar as antibiotic policies and practices should be informed by attitudes that are impartial and well-informed, there is significant support for prioritizing society. (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)

This paper aims to measure Knowledge Management Maturity (KMM) in the universities to determine the impact of knowledge management on high performance. This study was applied on Al-Quds Open University in Gaza strip, Palestine. Asian productivity organization model was applied to measure KMM. Second dimension which assess high performance was developed by the authors. The controlled sample was (306). Several statistical tools were used for data analysis and hypotheses testing, including reliability Correlation using Cronbach’s alpha, “ANOVA”, Simple Linear Regression and (...) Step Wise Regression.The overall findings of the current study suggest that KMM is suitable for measuring high performance. KMM assessment shows that maturity level is in level three. Findings also support the main hypothesis and it is sub- hypotheses. The most important factors effecting high performance are: Processes, KM leadership, People, KM Outcomes and Learning and Innovation. Furthermore the current study is unique by the virtue of its nature, scope and way of implied investigation, as it is the first comparative study in the universities of Palestine explores the status of KMM using the Asian productivity Model. (shrink)

Abstract: Heart diseases are increasing daily at a rapid rate and it is alarming and vital to predict heart diseases early. The diagnosis of heart diseases is a challenging task i.e. it must be done accurately and proficiently. The aim of this study is to determine which patient is more likely to have heart disease based on a number of medical features. We organized a heart disease prediction model to identify whether the person is likely to be diagnosed with a (...) heart disease or not using the medical features of the person. We used many different algorithms of machine learning such as Gaussian Mixture, Nearest Centroid, MultinomialNB, Logistic RegressionCV, Linear SVC, Linear Discriminant Analysis, SGD Classifier, Extra Tree Classifier, Calibrated ClassifierCV, Quadratic Discriminant Analysis, GaussianNB, Random Forest Classifier, ComplementNB, MLP Classifier, BernoulliNB, Bagging Classifier, LGBM Classifier, Ada Boost Classifier, K Neighbors Classifier, Logistic Regression, Gradient Boosting Classifier, Decision Tree Classifier, and Deep Learning to predict and classify the patient with heart disease. A quite helpful approach was used to regulate how the model can be used to improve the accuracy of prediction of heart diseases in any person. The strength of the proposed model was very satisfying and was able to predict evidence of having a heart disease in a particular person by using Deep Learning and Random Forest Classifier which showed a good accuracy in comparison to the other used classifiers. The proposed heart disease prediction model will enhances medical care and reduces the cost. This study gives us significant knowledge that can help us predict the person with heart disease. The dataset was collected from Kaggle depository and the model is implemented using python. (shrink)

A liberal antinomy of parenting exists: strong liberal intuitions militate in favor of both denying special resources to parenting projects (on grounds of project-neutrality) and granting them (on grounds of respect for personhood). I show that we can reconcile these two claims by rejecting a premise common to both--viz. that liberalism is necessarily committed to extensive procreative liberties--and limiting procreation and subsequent parenting to adults who meet certain psychological and especially financial criteria. I also defend this argument, which provides a (...) Kantian complement to utilitarian arguments for restricting procreation, against a variety of objections. (shrink)

One critique of the early Daoist texts associated with Laozi and Zhuangzi is that they neglect the human and lack a proper sense of ethical personhood in maintaining the primacy of an impersonal dehumanizing “way.” This article offers a reconsideration of the appropriateness of such negative evaluations by exploring whether and to what extent the ethical sensibility unfolded in the Zhuangzi is aporetic, naturalistic, and/or religious. As an ethos of cultivating life and free and easy wandering by performatively enacting openness (...) and responsiveness to things in an immanent this-worldly context, the Zhuangzi is oriented toward the relational attunement of disposition and practice rather than toward metaphysics or religion in a transcendent sense. It consequently suggests an immanent anarchic ethics without principles while neither forgetting nor reifying the sacred and the mundane in its playful illumination of the biospiritual dynamics of cultivating life. (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)

Mouth ulcers, also known as canker sores, are a common oral health issue affecting a significant portion of the population. Early and accurate diagnosis of mouth ulcers is crucial for effective treatment and prevention of complications. This paper presents an expert system developed using CLIPS (C Language Integrated Production System) to diagnose mouth ulcer disease. The expert system utilizes a rule-based approach, incorporating a comprehensive knowledge base consisting of symptoms, risk factors, and medical literature related to mouth ulcers. By employing (...) an inference engine, the system evaluates patient input against the rules and generates a diagnosis based on the matching symptoms and relevant factors. The system also provides detailed explanations and recommendations for each diagnosis, aiding healthcare professionals and patients in understanding the condition and selecting appropriate treatment options. The development and validation of the expert system involved a multi-step process, including knowledge acquisition, rule formulation, and testing against a diverse dataset of mouth ulcer cases. The system's performance was evaluated by comparing its diagnoses with those made by medical professionals, demonstrating a high level of accuracy and consistency. The implementation of an expert system for diagnosing mouth ulcer disease offers several advantages, including the ability to provide timely and accessible healthcare services, reduce misdiagnosis rates, and assist healthcare professionals in decision-making processes. Moreover, it empowers individuals to make informed decisions about their health and seek appropriate medical intervention. This paper contributes to the field of medical expert systems by showcasing the practical application of CLIPS in the diagnosis of mouth ulcer disease. The results demonstrate the potential of expert systems as valuable tools for healthcare professionals and patients alike, enhancing the efficiency and accuracy of diagnosis in oral health care. (shrink)

Abstract: The emergence of the novel coronavirus (COVID-19) in 2019 has presented the world with an unprecedented global health crisis. The rapid and widespread transmission of the virus has strained healthcare systems, disrupted economies, and challenged societies. In response to this monumental challenge, the intersection of technology and healthcare has become a focal point for innovation. This research endeavors to leverage the capabilities of Artificial Neural Networks (ANNs) to develop an advanced predictive model for forecasting the spread of COVID-19. It (...) involves the collection, analysis, and integration of diverse datasets encompassing epidemiological, clinical, and social factors that influence the virus's dissemination. (shrink)

The study aimed at identifying responsive flexibility and its role in improving service quality, from the point of view of the internal beneficiary in non-governmental hospitals in Gaza Strip. The study relied on the descriptive and analytical approach, and the questionnaire was designed as a tool to collect data, and the researchers used the comprehensive survey method, and the number of the study population was (536) single, where (434) questionnaires were retrieved, and the recovery rate was (80.97%). The study showed (...) many results, the most important of which were: The presence of moderate degree of approval by the study sample on the responsive flexibility, as it was evident through the response flexibility field obtaining a relative weight (60.50%), and the results of the study indicated that there is a high degree of approval by the members of the study sample. On the quality of service, as it was evident through the field of service quality obtaining a relative weight (79.90%). The results of the study revealed a statistically significant relationship between responsive flexibility and service quality in non-governmental hospitals in Gaza Strip, with a correlation coefficient of 0.418, and the results of the study revealed a statistically significant effect between responsive flexibility and service quality in non-governmental hospitals in Gaza Strip. The study reached many recommendations, the most important of which were: Finding mechanisms by which stored information can be used to enhance the decision-making process, and setting up an effective system to receive patients' complaints in a manner that ensures rapid response and treatment, to achieve continuous communication between patients and the hospital management, and to notify patients of abuse With the complaints that they submit, and working to provide all medical and health specialties in the hospitals under study, by making use of the medical delegations that visit Gaza Strip, involving them in the treatment processes, bringing in doctors and specialists from abroad, and updating the standards related to measuring the services provided to patients continuously, based on On patients' suggestions and complaints, developing facilities in hospitals, as well as updating medical devices and equipment used in hospitals periodically. (shrink)

This paper aims to identify computerized management information systems resources and their relationship to the development of performance in the Electricity Distribution Company in Gaza. This research used two dimensions. The first dimension is computerized management information systems and the second dimension the Development of Performance. The control sample was (063). (360) questioners were distributed and (306) were retrieved back with a percentage of (85%). Several statistical tools were used for data analysis and hypotheses testing, including reliability correlation using Cronbach’s (...) alpha, “ANOVA”, Simple Linear Regression and Step Wise Regression. The overall findings of the current study suggested the presence of a statistically significant relationship between resources (physical, software, and human and organizational) for the computerized management information systems and the development of performance in the Electricity Distribution Company in Gaza. The study recommended the following: The need to strengthen the company's management interest in the potential of computerized management information systems and using them in the computerization of all the company's activities. And the need to involve workers and users in the design of computerized management information systems and assessment and development process. And strengthen the relationship between users and information systems personnel in the department responsible for the system. And it is essential that the company is developing the infrastructure for information technology in general, and computerized management information systems, in particular for the development of performance. And increase interest in providing resources (physical, software, and human and organizational) for the computerized management information systems. The current study is unique by the virtue of its nature, scope and way of implied investigation, as it is the first study at Electricity Distribution Company in Gaza resources explores the status of Computerized management information systems and their relationship to the development of performance in the Electricity Distribution Company in Gaza increasing interest in Computerized management information systems through continuity, keeping pace with technological means and modern techniques. (shrink)

We present an axiomatization of non-relativistic Quantum Mechanics for a system with an arbitrary number of components. The interpretation of our system of axioms is realistic and objective. The EPR paradox and its relation with realism is discussed in this framework. It is shown that there is no contradiction between realism and recent experimental results.