In contemporary Western analytic philosophy, the classic analogical argument explaining our knowledge of other minds has been rejected. But at least three alternative positive theories of our knowledge of the second person have been formulated: the theory-theory, the simulation theory and the theory of direct empathy. After sketching out the problems faced by these accounts of the ego’s access to the contents of the mind of a “second ego”, this paper tries to recreate one argument given by Abhinavagupta (Shaiva philosopher (...) of recognition) to the effect that even in another’s body, one must feel and recognize one’s own self, if one is able to address that embodied person as a “you”. The otherness of You does not take away from its subjectivity. In that sense, just as every second person to whom one could speak is, first, a person, she is also a first person. Even as I regret that I do not know exactly how some other person is feeling right now, I must have some general access to the subjective experience of that other person, for otherwise what is it that I feel so painfully ignorant about? My subjective world is mine only to the extent that I recognize its continuity with a sharable subjective world where other I-s can make a You out of me. (shrink)

In The Mushroom at the End of the World: On the Possibility of Life in Capitalist Ruins, Anna Lowenhaupt Tsing explains how bare land is formed. Capitalism produces ‘ruins’ by stripping living beings of the capacity to form their own ecological relations, a necessary condition for the reproduction of life. Contemporary capitalism alienates living beings from ecological relations, i.e. capitalism generates “the ability to stand alone, as if the entanglements of living did not matter. Through alienation, people and things become (...) mobile assets; they can be removed from their lifeworlds in distance-defying transport to be exchanged with other assets from other life worlds, elsewhere” (Tsing 2021, 5). Cutting the threads of the web of life through capitalist alienation, however, produces bare land as a side effect, infertile waste deprived of the means to reproduce itself without capitalist support. Alienation is the deracination of living beings from their lifeworld, transforming them into passive cogs for capitalist accumulation. However, Tsing upholds matsutake mushrooms, rare fungi popular among Japa- nese foodies, as exemplars of the resilience of ecological relations. Even amidst ruins, matsutakes successfully form beneficial relations with other living beings, like pine trees, other fungi and human beings. The insistent capacity to regenerate ecological relations is the ineluctable means of reproduction for the matsutake mushroom. Even at the end of the world, the matsutake persists by perpetually co-producing new lifeworlds for itself and fellow living beings (see also Haraway 2016). I claim that Tsing’s approach to capitalist alienation is descriptively convinc- ing but lacks the affective force for ecological class consciousness. Tsing surveys the web of life from the perspective of living beings quite distant from humankind, articulating a theoretical diagnosis rather than a political exhortation. On an affective level, it is challenging to generate ecological class consciousness among the (presumably) human readers of my chapter if they are presented with only the biographies of mushrooms growing far beyond my home. As Chantal Mouffe (2018, 72) argues, the construction of an emphatically political identity requires an appeal to the affects, like hope, indignation or compassion. Latour and Schultz also stress that ecological politics currently suffers from an affective misalignment, with people failing to identify with the fate of their increasingly inhospitable environments (2022, 47). Why would European humans care about these unknown fungi? The reproduction of our CO2-intensive livelihoods largely depends on the emission of bare land elsewhere, so in the short run, we stand to benefit more from putting our heads in the sand. I employ Chakrabarty’s (2021) suggestion of grounding post-humanist politics first in strategic anthropocentrism to subsequently push for a post-humanist expansion of our human understanding. One must first feel personally interpellated by the crisis of the global means of reproduction before one can grasp the need for an ecological class politics beyond human confines. I turn to John Steinbeck’s 1939 novel The Grapes of Wrath as a kindred spirit with more mobilising potential. Steinbeck tells the story of a family of impoverished farmers from Oklahoma, the Joads, travelling to California in pursuit of a better life, yet only encountering more poverty, exploitation and anti-immigrant racism. Steinbeck describes in detail the environmental and social devastation, but he focuses on the commodified labour power of migrant farmers rather than commodified mushrooms. Steinbeck’s main characters are also uprooted from their entangled histories in the land and community of rural Oklahoma, but they present a more familiar face of the ecological class deprived of the means of reproduction. Steinbeck’s outcry against alienation-as-deracination is clear, but the shift in perspective facilitates the empathetic outrage required for building ecological class consciousness. Steinbeck’s strategic anthropocentrism helps human readers understand why alienation-as-deracination is a concern. (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)

Governments are increasingly making use of field experiments to evaluate policy interventions in the spheres of education, public health and welfare. However, the research ethics literature is largely focused on the clinical context, leaving investigators, institutional review boards and government agencies with few resources to draw on to address the ethical questions they face regarding such experiments. In this article, we aim to help address this problem, investigating the conditions under which informed consent is required for ethical policy research conducted (...) or authorized by government. We argue that investigators need not secure participants' informed consent when conducting government policy experiments if: the government institution conducting or authorizing the experiment possesses a right to rule over the spheres of policy targeted by the research; and data collection does not involve the violation of participants' autonomy rights. (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)

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)

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)

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)

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)

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)

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 Heart Attack is the Cardiovascular Disease (CVD) which causes the most deaths among CVDs. We collected a dataset from Kaggle website. In this paper, we propose an ANN model for the predicting whether a patient has a heart attack or not that. The dataset set consists of 9 features with 1000 samples. We split the dataset into training, validation, and testing. After training and validating the proposed model, we tested it with testing dataset. The proposed model reached an accuracy (...) of 98.01% on the Heart Disease Dataset. (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 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.

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)

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

The purpose of this research is to identify the extent of the efficiency of the internal control environment in the Palestinian higher educational institutions in Gaza Strip from the perspective of employees in the Palestinian universities in Gaza Strip, where researchers used in the study five universities. The researchers adopted in their study the descriptive and analytical approach. The research community consists of administrative employees and academic employees with administrative duties. Senior management or the University Council was excluded. The study (...) population compromises of (392) employees. A stratified random sample was chosen and (197) questionnaires were distributed. (160) questionnaires were received back with a return rate of (81.2%).The researchers used a questionnaire to collect that which then was analyzed using (SPSS) to get the results. The research found the following results: the absence of a fundamental difference between the responses of males and females. The lack of significant difference between the responses of the respondents attributed to the variable age. The lack of significant difference between the responses of the respondents attributed to the variable of years of service. And the existence of a fundamental difference between the responses of the respondents attributed to the university variable. The existence of a fundamental difference between the responses of the respondents attributed to the Qualification variable. The existence of a fundamental difference between the responses of the respondents attributed to the administrative level variable. The research found a group of recommendations including: the need to raise awareness of censorship as the basis for the protection of employees in all administrative levels from making mistake.Updating the systems and instructions of control periodically and parallel with the scientific progress and technology.Benefit from regional and international experiences in the application of internal control standards which commensurate with the administrative system of the institution. (shrink)

This study aims to look at the role of the practice of excellence strategies in education in achieving sustainable competitive advantage for the Higher educational institutions of the faculty of Engineering and Information Technology at Al-Azhar University in Gaza, a model, and the study considered the competitive advantage of educational institutions stems from the impact on the level of each student, employee, and the institution. The study was based on the premise that the development of strategies for excellence in education, (...) and its implementation is a vital important prerequisite to achieve sustainable competitive advantage in higher educational institutions. The study followed a systematic exploratory descriptive methodology through review of the theoretical literature, and the adoption of the experience of the Faculty of Engineering and Information Technology at Al-Azhar University in Gaza as a model for its unique experience in the field of excellence in education. The study results showed that the most important are: There is a strong correlation between the level of exercising excellence strategies in education and the achievement of higher educational institutions to the sustainable competitive advantage. The results include a general required number of important sub results on the subject of the model - Faculty of Engineering and Information Technology at Al-Azhar University in Gaza as follows: - The student considered the academic focus of the operation in the development process of the workers’ skills, particularly academics at the university helps to distinguish students and increase the employment rate after graduation. - The existence of consistency in development efforts and quality improvement for all three levels (student, employee, and the university), and this contributes to the Faculty excellence. - The Faculty has been able to achieve competitive advantages by offering excellent services without harming the efficiency, and this alone is a great success because improving service properties requires great investments, which negatively affect the continued institutional development. The study also reached a set of recommendations as follows: - The need to exercise excellence strategies in education, excellence reward at the national level, and those higher educational institutions follow the criteria for measuring the competitive advantages of its institutions always. - There is a need to increase efforts to implement programs of excellence, the allocation of adequate time, reward outstanding efforts as well. There is a necessity for each faculty to achieve competitive advantage and sustainability, using the general philosophies of competitive advantage, but with a different strategically content from what is in the private commercial sector, it reflects the Faculties mission and objectives, depending on making improvements and excellence in processes that ensure the safety of its outputs. As well as the need to find a balance between the work of teaching and research work of the faculty members, this has important implications regarding the criteria used in the process of excellence evaluation. The study recommended the adoption of strategies for excellence in education on a national public policy level mainly in the processes of change in higher education institutions. The need to support the existence of a common understanding of the efforts of excellence to create a general culture that appreciates excellence in faculties and universities. This underlines the need for transparent, fair rewards systems, to encourage innovation in education. The need to conduct a comprehensive surveys on the graduates of faculties and universities including the areas of employment and skills, because that will give accurate indications of the graduates and will help to establish a link to a more precise about the relationship of excellence strategies with the competitive advantages. (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)

Abstract: Forests are areas with a high density of trees, and they play a vital role in the health of the planet. They provide a habitat for a wide variety of plant and animal species, and they help to regulate the climate by absorbing carbon dioxide from the atmosphere. While in 2010, the world had 3.92Gha of forest cover, covering 30% of its land area, in 2019, there was a loss of forest cover of 24.2Mha according to the Global Forest (...) Watch institute. Discovery and classification depend on human experience and effort, so the error in the results of this process can lead to forest fires and disasters. Therefore, deep learning algorithms from artificial intelligence and machine learning sciences have been applied to help specialists avoid false or inaccurate diagnoses when detecting Forest fires in images using a pre-trained convolutional neural network called VGG16. The model was customized to fit the Forest fires classification and then applied to a dataset consisting of (14,000) of the Forests collected from the Kaggle depository. We trained, validated, and tested the modified VGG16 model. The proposed VGG16 model obtained Precision (99.96%), Recall (99.96%), and F1-Score (99.96%). (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)

Abstract: People all over the world have been drinking tea for thousands of centuries, and for good reason. Many types of teas can help you stay healthy by boosting your immune system, reducing inflammation, and even preventing cancer and heart disease. There is sufficient material to show that regularly consuming tea can improve your health over the long term. A deep learning model that categorizes tea disorders has been completed. When focusing on the tea, we must also focus on and (...) take into account the diseases that harm it. The aim of this paper is to diagnose tea diseases based on a dataset containing 8000 picture and 8 classes .The model gave the final accuracy test with an F1-score of 99.41% in an estimated time 3 second, as with these results it proved its effectiveness and good ability in the classification test. (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)

Abstract: Heart attacks, or myocardial infarctions, are a leading cause of mortality worldwide. Early prediction and accurate analysis of potential risk factors play a crucial role in preventing heart attacks and improving patient outcomes. In this study, we conduct a comprehensive review of datasets related to heart attack analysis and prediction. We begin by examining the various types of datasets available for heart attack research, encompassing clinical, demographic, and physiological data. These datasets originate from diverse sources, including hospitals, research institutions, (...) and public health agencies. Our analysis aims to identify common features, data quality, and potential biases in these datasets. Next, we explore the predictive modeling techniques employed in heart attack prediction. Machine learning algorithms, such as decision trees, support vector machines, and deep neural networks, have gained prominence in predicting heart attacks. We discuss the strengths and limitations of these methods and highlight recent advancements in predictive modeling. Furthermore, we delve into the critical risk factors associated with heart attacks. Factors such as age, gender, hypertension, diabetes, and cholesterol levels are examined for their significance in predicting cardiac events. We also investigate the role of lifestyle factors, including smoking, diet, and physical activity, in heart attack risk assessment. Additionally, this review addresses the importance of data preprocessing and feature engineering in improving prediction accuracy. Feature selection methods, missing data handling, and data scaling techniques are discussed to enhance the robustness of heart attack prediction models. In conclusion, this comprehensive dataset review provides valuable insights into the state of heart attack analysis and prediction. It serves as a resource for researchers and healthcare professionals seeking to better understand the datasets available for heart attack research and the methods employed for accurate prediction. Ultimately, our efforts in dataset analysis and predictive modeling contribute to the advancement of preventive cardiology and the reduction of heart attack-related morbidity and mortality. (shrink)

As sustainable tourism gains increasing attention, understanding the factors that influence travelers' motivation to engage with sustainable travel agents becomes crucial. This study investigates the moderating effect of social media usage on the relationship between the perceived value of websites and motivational factors for sustainable travel agents. The study proposes that social media usage acts as a moderator in shaping the relationship between the perceived value of websites and motivational factors. This study has utilized smart tourism. Therefore, independent variable motivation (...) in terms of informativeness gratification and gratification acted as moderating variables. This study has utilized an online questionnaire adapted from a standardized questionnaire based on the literature review. Moreover, a total of 146 managers were surveyed in which they were required to respond to 55 items that elicited the 7 variables social media use, Propensity, perceived website value, motivating factors, entertainment gratification, informativeness gratification, sustainable smart tourism. The data were analyzed by SPSS and PLS-SEM. The findings indicated that relevance and importance of social media use and sustainable smart tourism. The result revealed that 7 hypotheses had a significant relationship. 3 hypotheses did not show a moderating effect. Overall, this study extends the understanding of sustainable smart tourism. These findings will benefit travel agents’ managers in Malaysia to better understand the role of social media use and utilize it towards developing sustainable sustainable smart tourism. (shrink)

Web page phishing is a type of phishing attack that targets websites. In a web page phishing attack, the attacker creates a fake website that looks like a legitimate website, such as a bank or credit card company website. The attacker then sends a fraudulent message to the victim, which contains a link to the fake website. When the victim clicks on the link, they are taken to the fake website and tricked into entering their personal information.Web page phishing attacks (...) are a serious threat to online security. They can be very effective, as they often look very convincing. To protect yourself from web page phishing attacks, you should be suspicious of any emails or messages that ask for your personal information. Do not click on links in emails or messages from unknown senders. If you are unsure whether a website is legitimate, do not enter your personal information. Therefore, in this study, we present a novel approach to detect whether a web page is phishing or legitimate using a neural network model. (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)

The study aimed to identify the leadership features and their relationship to increasing achievement motivation among Palestinian police employees in Gaza Strip in light of the Corona pandemic. To achieve the study’s objectives, the researchers used the descriptive method in its analytical method, using a questionnaire applied to the police officers at the Central Governorate Police Station, whose number is (113) individuals. They were chosen in a stratified, random manner, and the study resulted in a set of results, the most (...) important of which is that the effect of leadership characteristics of Palestinian police employees in Gaza Strip, which came with a relative weight (76.20%), which is, to a large extent, the level of increase in achievement motivation among employees in the Palestinian Police in Gaza Strip. Gaza under the outbreak of the Corona epidemic? Which came with a relative weight (82.40%), which is to a large extent. While it resulted in a positive correlation between the impact of leadership characteristics and the increase in achievement motivation, there are no statistically significant differences between the averages of the study sample's estimates about the impact The leadership characteristics of the Palestinian Police in Gaza Strip are attributed to the variable of the age group, academic qualification, scientific specialization, scientific experience. There are no statistically significant differences between the averages of the estimates of the individuals of the study sample about The achievement motivation in the Palestinian Police in Gaza Strip is attributable to a variable, age group, academic qualification, scientific specialization, scientific experience, and in light of these results the researchers suggested a set of recommendations, the most important of which are: The need to tighten penalties for individuals by the Central Governorate Police Station for violating the instructions issued by the Ministry Interior In light of the outbreak of the Corona epidemic, increased interest in preparing and organizing specialized training courses and programs in the field of dealing with all different segments in order to preserve the lives of people from the Corona epidemic. (shrink)

A hypergroup, as a generalization of the notion of a group, was introduced by F. Marty in 1934. The first book in hypergroup theory was published by Corsini. Nowadays, hypergroups have found applications to many subjects of pure and applied mathematics, for example, in geometry, topology, cryptography and coding theory, graphs and hypergraphs, probability theory, binary relations, theory of fuzzy and rough sets and automata theory, physics, and also in biological inheritance.

The aim behind analyzing the Goodreads dataset is to get a fair idea about the relationships between the multiple attributes a book might have, such as: the aggregate rating of each book, the trend of the authors over the years and books with numerous languages. With over a hundred thousand ratings, there are books which just tend to become popular as each day seems to pass. We proposed an Artificial Neural Network (ANN) model for predicting the overall rating of books. (...) The prediction is based on these features (bookID, title, authors, isbn, language_code, isbn13, # num_pages, ratings_count, text_reviews_count), which were used as input variables and (average_rating) as output variable for our ANN model. Our model were created, trained, and validated using data set in JNN environment, which its title is “Goodreads-books”. Model evaluation showed that the ANN model is able to predict correctly 99.78% of the validation samples. (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 study aimed to identify E- Learning strategies and their relation to the efficiency of research performance in foreign and Palestinian universities (University of Ottawa, Munster, Suez Canal, Al-Azhar, Islamic, Al-Aqsa). The analytical descriptive approach was used for this purpose, and relying on the questionnaire as a main tool for data collection. The study society is from the senior management, where the number of senior management in the universities in question is 206. The random stratified sample was selected and (SPSS) (...) was used for statistical data analysis. The study found a significant relationship between E- Learning strategies and the efficiency of research performance in universities. It also reached the participation of senior management in the research that develops the university performance in the Palestinian universities. The senior management indicated that they do not care to follow the policies of implementing the development of scientific research. While the senior management in foreign universities indicated that they are interested in following up the policies of implementing the development of scientific research. The study also showed that senior management in Palestinian universities does not care about providing the appropriate budget for E- Learning. The study recommended that the senior management of Palestinian universities should provide an E- Learning budget and encourage employees to continue using E- Learning strategies. The administration in the Palestinian universities should adopt and support outstanding research, and the need to encourage interest in the implementation of policies for the development of scientific research. (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)

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)

The study aimed to identify the level of organizational performance in ceramic companies in the Tenth of Ramadan City, where the researchers used the descriptive analytical method, through a questionnaire distributed. The study reached a set of results, the most important of which are: the presence of a clear consensus of the study sample from the members of the senior management that all dimensions of the balanced scorecard variable are largely present in the ceramic companies under study, and the results (...) showed the approval of the study sample of workers in an average way on the application of the financial dimension and that it is applied Well, the approval of the study sample of the employees in an average way that tends to decline on the degree of application of the customer dimension and that it is applied by the senior management in an inappropriate way, the approval of the study sample of the employees in a large way on the degree of application of the internal operations dimension and that it is applied by the senior management in a large and appropriate way, approval The study sample of workers applying the learning and growth dimension is moderately low and it is applied inappropriately by the senior management. The study presented a set of recommendations, the most important of which are: working on clarifying and translating the vision and strategy of the institution, working on clarifying the strategy and linking it to the goals, planning and setting goals and arranging strategic initiatives, promoting strategic feedback. (shrink)

The paper argues that the moral philosophy of Thomas Hobbes is unified by a complex conception of reason that imposes consistency norms of both rationality and reasonableness. Hobbes’s conceptions of rightness as reciprocity, and moral goodness as sociability belong to an original and attractive moral theory that is neither teleological nor classically deontological, nor as interpreters have variously argued, subjectivist, contractarian, egoist, or dependent on divine command.

This article considers the significance of the Blessed Isles in Nietzsche’s Thus Spoke Zarathustra. They are the isolated locale to which Zarathustra and his fellow creators retreat in the Second Part of the book. I trace Zarathustra’s Blessed Isles back to the ancient Greek paradisiacal afterlife of the makarōn nēsoi and frame them against Nietzsche’s Platonic conception of philosophers as “commanders and legislators,” but I argue that they represent something more like a modern Epicurean Garden. Ultimately, I suggest that Zarathustra’s (...) Epicurean impulse toward withdrawal (whether into a sequestered friendship community or mountain solitude) undermines his Platonic attempts at great politics. (shrink)

The pandemic of COVID-19 prompted several paradigm shifts throughout society, including in education. This study aimed to examine the relationships of students' engagement in online synchronous collaborative learning activities (OSCLA) with their self-efficacy (LSE), peer social support (LPSS), state of well-being (SWB), and level of academic performance (LAP). A total of 176 Filipino Grade 12 SHS students, 18 years old and older, from a private educational institution were purposively selected for this study. Data were generated using an online survey. Results (...) show that collaborative learning activities are frequently conducted (median = 4) in their synchronous online classes. It also revealed that their LSE is high (median = 4), their LPSS is high (median = 4), their LE is moderate (median = 3), their SWB is high (median = 4), and their LAP is high (median = 94.85). The results showed a statistically significant correlation of their LSE (r = 0.69, p 0.001) and LPSS with their OSCLA LE (r = 0.438, p 0.001). A statistically significant positive moderate correlation between LE and SWB (r = 0.536, p 0.001) was also found, however, no correlation was found between their OSCLA LE and LAP (r = 0.065, p = 0.393). Thus, the use of a well-designed OSCLA is strongly recommended as it positively impacts students' SWB but should be regularly reviewed for its effectiveness in sustaining improvement in the LAP of the students. (shrink)

This review essay of Economics Rules situates Dani Rodrik’s contribution with respect to the 2007–2008 global economic crisis. This financial meltdown, which the eurozone did not fully recover from before the Covid-19 pandemic, led to soul- searching among economists as well as a call for heterodox economic approaches. Yet, over the past decade, instead the economics profession has maintained its orthodoxy. Rodrik’s Economics Rules offers a critique of the economics profession that is castigating but mild. It calls for economists to (...) use more and diverse models without becoming wedded to any single model or an overarching vision. Yet Rodrik ratifies many of the benchmark models standard to orthodox economics and provides little ground for a fundamental rethinking of the discipline. This essay analyses the conservatism underlying Rodrik’s approach, which upholds general equilibrium theory and rational expectations underlying the efficient market hypothesis. It argues that the economics discipline’s scope-creep to maintain its applicability to all human decision-making, and its acceptance of all-inclusive utility functions, crowds out moral sentiments and civic virtue. Thus. it argues that rather than urging economists simply to be more cautious in their application of models to address particular social concerns, instead economists must recognise their discipline’s inherent limitations. (shrink)

Abstract: background: Dental and oral health is an essential part of your overall health and well-being. Poor oral hygiene can lead to dental cavities and gum disease, and has also been linked to heart disease, cancer, and diabetes. Maintaining healthy teeth and gums is a lifelong commitment. The earlier you learn proper oral hygiene habits — such as brushing, flossing, and limiting your sugar intake — the easier it’ll be to avoid costly dental procedures and long-term health issues. (Healthline, n.d.) (...) Objectives The main goal of this expert system is to get the appropriate diagnosis of disease and the correct treatment by presenting suggestions on Tooth Problems to the user by asking about symptoms. (shrink)

First paragraph: In the 1980s I went through a phase of writing limericks during idle moments when I lacked something to read. The result was a set of 27 limericks about cybernetics (Umpleby 1992). I occasionally use the limericks in class to restate a theoretical point. Limericks bring a smile and demonstrate that cybernetics can be approached in a variety of ways. Below are three limericks from this collection. The last was written by Ernst von Glasersfeld. It seems Ernst believed (...) that I was overly concerned with "reality" as opposed to perception, or at least that I had not captured the point that he was trying to make. (shrink)

Brain-related diseases are among the most difficult diseases due to their sensitivity, the difficulty of performing operations, and their high costs. In contrast, the operation is not necessary to succeed, as the results of the operation may be unsuccessful. One of the most common diseases that affect the brain is Alzheimer’s disease, which affects adults, a disease that leads to memory loss and forgetting information in varying degrees. According to the condition of each patient. For these reasons, it is important (...) to classify memory loss and to know the patient at what level and his assessment of Alzheimer's disease through CT scans of the brain. In this thesis, we review ways and techniques to use deep learning classification to classifying the Alzheimer's Disease The proposed method used to improve patient care, reduce costs, and allow fast and reliable analysis in large studies. The model will be designed using Python language for implementing the system, which is very useful for doctors, classifying the Alzheimer's Disease, was used. The model used 70% from image for training and 30% from image for validation, our trained model achieved an accuracy of 100% on a held-out test set. (shrink)

This article defends the conclusion that the soccer World Cup in Qatar should not be boycotted by rich countries from the Global North. This conclusion is underpinned by considerations about the economic background conditions in guest workers’ home countries. Three arguments are considered for the view that the World Cup should be boycotted. It is argued that each of these arguments is unsound. Section 7 contains a discussion of an argument for a boycott that centers on the process through which (...) Qatar was awarded the World Cup. This argument is rejected. The article lists several ways in which guest workers in Qatar are wronged, but this fact about how guest workers are treated does not justify a boycott by rich countries from the Global North. (shrink)

There are three questions associated with Simpson’s paradox (SP): (i) Why is SP paradoxical? (ii) What conditions generate SP? and (iii) How to proceed when confronted with SP? An adequate analysis of the paradox starts by distinguishing these three questions. Then, by developing a formal account of SP, and substantiating it with a counterexample to causal accounts, we argue that there are no causal factors at play in answering questions (i) and (ii). Causality enters only in connection with action.

Although social scientists have identified diverse behavioral patterns among children from dissimilarly structured families, marketing scholars have progressed little in relating family structure to consumption-related decisions. In particular, the roles played by members of single-mother families—which may include live-in grandparents, mother’s unmarried partner, and step-father with or without step-sibling(s)—may affect children’s influence on consumption-related decisions. For example, to offset a parental authority dynamic introduced by a new stepfather, the work-related constraints imposed on a breadwinning mother, or the imposition of adult-level (...) household responsibilities on children, single-mother families may attend more to their children’s product preferences. -/- Without a profile that includes socio-economic, behavioral, and psychological aspects, efficient and socially responsible marketing to single-mother households is compromised. Relative to dual-parent families, single-mother families tend to have fewer resources and less buying power, children who consume more materialistic and compulsively, and children who more strongly influence decision making for both own-use and family-use products. Timely research would ensure that these and other tendencies now differentiate single-mother from dual-parent families in ways that marketers should address. Hence, our threefold goal is (1) to consolidate and highlight gaps in existing theory applied to studying children’s influence on consumption-related decision making in single-mother families, and (2) to propose a hybrid framework that merges two theories conducive to such research, and (3) to identify promising research propositions for future research. (shrink)

In the first chapter of his Knowledge and Lotteries, John Hawthorne argues that thinkers do not ordinarily know lottery propositions. His arguments depend on claims about the intimate connections between knowledge and assertion, epistemic possibility, practical reasoning, and theoretical reasoning. In this paper, we cast doubt on the proposed connections. We also put forward an alternative picture of belief and reasoning. In particular, we argue that assertion is governed by a Gricean constraint that makes no reference to knowledge, and that (...) practical reasoning has more to do with rational degrees of belief than with states of knowledge. (shrink)

Kyle Stanford’s reformulation of the problem of underdetermination has the potential to highlight the epistemic obligations of scientists. Stanford, however, presents the phenomenon of unconceived alternatives as a problem for realists, despite critics’ insistence that we have contextual explanations for scientists’ failure to conceive of their successors’ theories. I propose that responsibilist epistemology and the concept of “role oughts,” as discussed by Lorraine Code and Richard Feldman, can pacify Stanford’s critics and reveal broader relevance of the “new induction.” The possibility (...) of unconceived alternatives pushes us to question our contemporary expectation for scientists to reason outside of their historical moment. (shrink)

By the end of his life Plato had rearranged the theory of ideas into his teaching about ideal numbers, but no written records have been left. The Ideal mathematics of Plato is present in all his dialogues. It can be clearly grasped in relation to the effective use of mathematical modelling. Many problems of mathematical modelling were laid in the foundation of the method by cutting the three-level idealism of Plato to the single-level “ideism” of Aristotle. For a long time, (...) the real, ideal numbers of Plato’s Ideal mathematics eliminates many mathematical problems, extends the capabilities of modelling, and improves mathematics. (shrink)