Parkinson's Disease (PD) is a long-term degenerative disorder of the central nervous system that mainly affects the motor system. The symptoms generally come on slowly over time. Early in the disease, the most obvious are shaking, rigidity, slowness of movement, and difficulty with walking. Doctors do not know what causes it and finds difficulty in early diagnosing the presence of Parkinson’s disease. An artificial neural network system with back propagation algorithm is presented in this paper for helping doctors (...) in identifying PD. Previous research with regards to predict the presence of the PD has shown accuracy rates up to 93% [1]; however, accuracy of prediction for small classes is reduced. The proposed design of the neural network system causes a significant increase of robustness. It is also has shown that networks recognition rates reached 100%. (shrink)

Parkinson's Disease (PD) is a long-term degenerative disorder of the central nervous system that mainly affects the motor system. The symptoms generally come on slowly over time. Early in the disease, the most obvious are shaking, rigidity, slowness of movement, and difficulty with walking. Doctors do not know what causes it and finds difficulty in early diagnosing the presence of Parkinson’s disease. An artificial neural network system with back propagation algorithm is presented in this paper for helping doctors (...) in identifying PD. Previous research with regards to predict the presence of the PD has shown accuracy rates up to 93% [1]; however, accuracy of prediction for small classes is reduced. The proposed design of the neural network system causes a significant increase of robustness. It is also has shown that networks recognition rates reached 100%. (shrink)

I am a philosopher with Parkinson’s Disease. Over the past several years I’ve been trying to write about my situation. I wrote about how I was forced to face the disease. I described how the disease twists and distorts my world. Then I asked myself, as a philosophy writer and teacher, whether I could say anything that might help myself or others facing life with Parkinson’s? I found ideas in the ancient Stoics and expanded them with ideas about (...) time, coming up with suggestions for living as excellently as possible despite the disease. Looking at those suggestions, I realized how the special awareness, resolve, and attention I was suggesting would be eaten away by dementia, and I know that a majority of Parkinson’s patients face dementia if they survive long enough. What can philosophy say to me or any person whose self and philosophy are being erased? Writing about such issues has helped me deal with my situation, and maybe my essay might be useful for others dealing with decline. (shrink)

This chapter discusses several kinds of reduction that are often found in the biomedical sciences, in contrast to reduction in fields such as physics. This includes reduction as a methodological assumption for how to investigate phenomena like complex diseases, and reduction as a conceptual tool for relating distinct models of the same phenomenon. The case of Parkinson’s disease illustrates a wide variety of ways in which reductionism is an important tool in medicine.

Since their discovery in the early 1990s, Stem Cell has brought the prospect of radically improving treatments for a host of diseases such as Alzheimer's, Parkinson's disease, cancers and many among other diseases that currently render patients and scientists helpless to combat. With the advent of medical and scientific research, comes the inevitable emergence of ethical controversy that often accompanied major scientific and medical development. The use of Stem Cell is no different. Those who seek to curtail the use (...) of certain stem cell lines, revert to the argument that has defied many medical debates over the previous decades. The destruction of human life to create life is one of the key philosophical points that all anti-stem cell advocates attempt to make. However, the purpose of this paper is to analysis the various aspects of ethical debate concerning the use of stem cells in medical research. (shrink)

Parkinson’s disease is a common movement disorder associated primarily with oxidative stress-mediated degeneration of dopaminergic neurons. Earlier studies showed that Sorghum bicolor-based supplement (SbS) exhibited antioxidant and neuroprotective activities and might likely rescue the death of dopaminergic neurons in Parkinson’s disease. This study examined the effect of SbS on rotenone-induced Parkinsonian-like motor deficits in rats and the involvement of oxidative stress and pro-inflammatory cytokines. Rats were divided into six groups and treated orally with sunflower oil (vehicle-control), rotenone (2.5 (...) mg/kg) alone or in combination with each dose of SbS (50, 100, and 200 mg/kg) and levodopa-carbidopa (10 mg/kg) on an alternate day for 28 days. The changes in motor functions were evaluated on day 28 and the brain concentrations of oxidative stress biomarkers and pro-inflammatory cytokines (tumor necrosis factor-alpha and interleukin-6) were determined. Rotenone caused motor deficits by impaired locomotor activity in the open field test and induced catalepsy in the bar test, which were attenuated by SbS. Rats pretreated with SbS had reduced brain levels of malondialdehyde, nitrite, and pro-inflammatory cytokines compared to rotenone controls. SbS mitigated rotenone-induced depletion of reduced glutathione and antioxidant enzymes in the rat brain. The results suggest that SbS ameliorated rotenone-induced Parkinsonian-like motor dysfunctions by reducing neuronal oxidative stress and pro-inflammatory cytokines in rats. (shrink)

This chapter summarizes the conceptual foundations and research on emotional creativity. Emotional creativity is defined as a pattern of cognitive abilities and personality traits related to originality and appropriateness in emotional experience. This construct pervades human creative performance and represents an important link between emotional experience and cognitive processes. Empirical research in this field has revealed various links of emotional creativity to personality variables (e.g., openness to experience), positive affect, fantasy proneness, coping strategies, post-traumatic growth, better self-understanding, and one’s engagement (...) in practicing creative leisure activities. In the applied settings, emotional creativity has been found to be positively related to the intrinsic motivation of employees, the innovative performance of employees, teaching efficacy, and an increased awareness of professional roles. Interestingly, the available meta-analysis of past studies revealed that women showed significantly higher emotional creativity than men. Emotional creativity has also been found to be lower in older adulthood compared to younger age. Because the levels of emotional creativity were found to be sensitive to the decline of cognitive functions in older adults, their decrease can be considered as one of the indicators of cognitive aging. Recent research in clinical neuropsychology has also revealed that older adults in the early stages of Parkinson’s disease showed decreased emotional creativity compared to healthy older adults. (shrink)

Does DBS change a patient’s personality? This is one of the central questions in the debate on the ethics of treatment with Deep Brain Stimulation (DBS). At the moment, however, this important debate is hampered by the fact that there is relatively little data available concerning what patients actually experience following DBS treatment. There are a few qualitative studies with patients with Parkinson’s disease and Primary Dystonia and some case reports, but there has been no qualitative study yet with (...) patients suffering from psychiatric disorders. In this paper, we present the experiences of 18 patients with Obsessive-Compulsive Disorder (OCD) who are undergoing treatment with DBS. We will also discuss the inherent difficulties of how to define and assess changes in personality, in particular for patients with psychiatric disorders. We end with a discussion of the data and how these shed new light on the conceptual debate about how to define personality. (shrink)

Case reports about patients undergoing Deep Brain Stimulation (DBS) for various motor and psychiatric disorders - including Parkinson’s Disease, Obsessive Compulsive Disorder, and Treatment Resistant Depression - have sparked a vast literature in neuroethics. Questions about whether and how DBS changes the self have been at the fore. The present chapter brings these neuroethical debates into conversation with recent research in moral psychology. We begin in Section 1 by reviewing the recent clinical literature on DBS. In Section 2, we (...) consider whether DBS poses a threat to personal identity. In Section 3 we argue for engagement with recent empirical work examining judgements of when identity changes. We conclude in Section 4 by highlighting a range of ethical issues raised by DBS, including various cross-cultural considerations. (shrink)

Recent developments in neuroscience create new opportunities for understanding the human brain. The power to do good, however, is also the power to harm, so scientific advances inevitably foster as many dystopian fears as utopian hopes. For instance, neuroscience lends itself to the fear that people will be forced to reveal thoughts and feelings which they would not have chosen to reveal, and of which they may be unaware. It also lends itself to the worry that people will be encouraged (...) to submit to medication or surgery which, even if otherwise beneficial, alters their brain in ways that undermine their identity and agency. As Kenneth Foster notes, neural implants can have surprising and unintended adverse effects, even when they help to mitigate the loss of bodily control associated with Parkinson’s disease, or help to provide hearing for children who would otherwise be profoundly deaf. While the risk of adverse outcomes are scarcely specific to neuroscience, he thinks that ‘These issues are perhaps more acute’ with the latter than with other medical interventions, ‘because they are intimately and fundamentally related to a person’s communication with the outside world’. [ 2006 196] -/- Neuroscience, like genomic science, then, is likely to create new ways of harming people. Many of these will involve violations of privacy. However, these are unlikely fundamentally to challenge the reasons to value privacy, or our ability to protect it in the foreseeable future. Rather, I would suggest, the major threat to privacy comes from the difficulty of determining its nature and value and when, if ever, efforts to protect it are justified. So I will start by examining some threats to privacy, and their implications for neuroscience, before turning to philosophical problems in understanding the nature and value of privacy, and the practical consequences of those philosophical difficulties. (shrink)

Abstract: Ensuring the proactive detection of transaction risks is paramount for financial institutions, particularly in the context of managing credit scores. In this study, we compare different machine learning algorithms to effectively and efficiently. The algorithms used in this study were: MLogisticRegressionCV, ExtraTreeClassifier,LGBMClassifier,AdaBoostClassifier, GradientBoostingClassifier,Perceptron,RandomForestClassifier,KNeighborsClassifier,BaggingClassifier, DecisionTreeClassifier, CalibratedClassifierCV, LabelPropagation, Deep Learning. The dataset was collected from Kaggle depository. It consists of 164 rows and 8 columns. The best classifier with unbalanced dataset was the LogisticRegressionCV. The Accuracy 100.0%, precession 100.0%,Recall100.0% and the F1-score (...) 100.0%. However, the best classifier with balanced dataset was the LogisticRegressionCV. The Accuracy 100.0%, precession 100.0%, Recall 100.0% and the F1-score 100.0%. (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)

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)

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

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

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

The Ontology for Biomedical Investigations (OBI) is an ontology that provides terms with precisely defined meanings to describe all aspects of how investigations in the biological and medical domains are conducted. OBI re-uses ontologies that provide a representation of biomedical knowledge from the Open Biological and Biomedical Ontologies (OBO) project and adds the ability to describe how this knowledge was derived. We here describe the state of OBI and several applications that are using it, such as adding semantic expressivity to (...) existing databases, building data entry forms, and enabling interoperability between knowledge resources. OBI covers all phases of the investigation process, such as planning, execution and reporting. It represents information and material entities that participate in these processes, as well as roles and functions. Prior to OBI, it was not possible to use a single internally consistent resource that could be applied to multiple types of experiments for these applications. OBI has made this possible by creating terms for entities involved in biological and medical investigations and by importing parts of other biomedical ontologies such as GO, Chemical Entities of Biological Interest (ChEBI) and Phenotype Attribute and Trait Ontology (PATO) without altering their meaning. OBI is being used in a wide range of projects covering genomics, multi-omics, immunology, and catalogs of services. OBI has also spawned other ontologies (Information Artifact Ontology) and methods for importing parts of ontologies (Minimum information to reference an external ontology term (MIREOT)). The OBI project is an open cross-disciplinary collaborative effort, encompassing multiple research communities from around the globe. To date, OBI has created 2366 classes and 40 relations along with textual and formal definitions. The OBI Consortium maintains a web resource providing details on the people, policies, and issues being addressed in association with OBI. (shrink)

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

Abstract: The aim behind analyzing Google Stock Prices dataset is to get a fair idea about the relationships between the multiple attributes a day might have, such as: the opening price for each day, the volume of trading for each day. With over a hundred thousand days of trading data, there are some patterns that can help in predicting the future prices. We proposed an Artificial Neural Network (ANN) model for predicting the closing prices for future days. The prediction is (...) based on these features (date, opening price, highest price, lowest price, volume), which were used as input variables and (closing price) as output variable for our ANN model. Our model was created, trained, and validated using data set in JNN environment, which its title is “Google-Stock-Prices”. The model evaluation showed that the ANN model is able to predict correctly 99.48% of the validation samples. (shrink)

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

Abstract: This study has effectively tackled the critical challenge of accurate calorie prediction in dishes by employing a robust neural network-based model. With an outstanding accuracy rate of 99.32% and a remarkably low average error of 0.009, our model has showcased its proficiency in delivering precise calorie estimations. This achievement equips individuals, healthcare practitioners, and the food industry with a powerful tool to promote healthier dietary choices and elevate awareness of nutrition. Furthermore, our in-depth feature importance analysis has shed light (...) on the indispensable role played by specific nutritional attributes in calorie estimation. This unveiling of crucial factors provides valuable insights for further research endeavors and practical applications. Notably, this research extends its impact beyond the immediate context by making substantial contributions to the domains of nutrition science and dietary planning. It underscores the transformative potential of artificial intelligence, demonstrating how it can revolutionize our approach to food, nutrition, and health. As the world grapples with the challenges of diet-related health issues and environmental concerns, the accuracy and precision achieved in calorie prediction through neural networks represent a significant stride towards more informed and conscientious dietary practices. In this era of data-driven decision-making, our research paves the way for healthier lifestyles, heightened nutritional awareness, and a more health-conscious society. (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)

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

We assess the state of thinking about gender identities in computer vision through an analysis of how research papers in gender and facial recognition are designed, what claims they make about trans and non-binary people, what values they espouse, and what they describe as ongoing challenges for the field. In our corpus of 50 research papers, the seven papers that consider trans and non-binary identities use questionable assumptions about medicalization as a measure of transness, about gender transition as a linear (...) and bounded process, and about the concept of gender deception. Otherwise, non-normative gender identities are absent and their consideration is in fact hindered by prevailing research values, particularly deeply embedded ones such as performance and accuracy. We point out how the use of shared datasets calcifies binary conceptions of gender. In the way that the field of computer vision conceives of ongoing challenges for its research, it does not yet face questions that trans and non-binary user experiences pose and often falls back on biologically essentialist notions of sex classification. We make two recommendations: that computer vision researchers undertake interdisciplinary work with researchers who study gender as a socio-cultural phenomenon, and that journal editors and conference organizers do the same in peer review and conference acceptance processes. (shrink)

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

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)

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

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

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)

A newborn baby is an infant within the first 28 days of birth. Diagnosis and treatment of infant diseases require specialized medical resources and expert knowledge. However, there is a shortage of such professionals globally, particularly in low-income countries. To address this challenge, a knowledge-based system was designed to aid in the diagnosis and treatment of neonatal diseases. The system utilizes both machine learning and health expert knowledge, and a hybrid data mining process model was used to extract knowledge from (...) a clinical dataset. The PART algorithm achieved the highest performance result with 98.06% accuracy under 10-fold cross-validation, and the generated rules were used to develop the knowledge-based system. The system achieved 90.9% accuracy in system performance testing and 89.2% in user acceptance testing, and is intended to serve as an assistant tool for healthcare experts. (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: The COVID-19 pandemic has posed unprecedented challenges to global healthcare systems, necessitating accurate and timely forecasting of cases for effective mitigation strategies. In this research paper, we present a novel approach to predict COVID-19 cases using Artificial Neural Networks (ANNs), harnessing the power of machine learning for epidemiological forecasting. Our ANNs-based forecasting model has demonstrated remarkable efficacy, achieving an impressive accuracy rate of 97.87%. This achievement underscores the potential of ANNs in providing precise and data-driven insights into the dynamics (...) of the pandemic. However, this paper underscores the critical importance of a comprehensive evaluation beyond accuracy, including metrics such as sensitivity, specificity, and the area under the ROC curve (AUC-ROC), to assess the model's performance robustness. The research paper offers detailed insights into the architecture of the ANN model, encompassing critical hyperparameters, data preprocessing techniques, and regularization strategies employed to optimize model accuracy. Ethical considerations surrounding data privacy and potential biases within the COVID-19 dataset are also addressed. While the achieved accuracy is a significant milestone, this study underscores the dynamic and evolving nature of the pandemic, necessitating continuous model refinement and validation. Furthermore, it emphasizes the importance of considering false positives and false negatives in the context of public health decision-making. In conclusion, this research contributes to the arsenal of tools available for pandemic management by showcasing the potential of ANNs in COVID-19 case forecasting. It encourages ongoing exploration and adaptation of predictive models to enhance their applicability in real-world public health scenarios, ultimately contributing to more effective pandemic control and response efforts. (shrink)

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)

COVID-19 often manifests with different outcomes in different patients, highlighting the complexity of the host-pathogen interactions involved in manifestations of the disease at the molecular and cellular levels. In this paper, we propose a set of postulates and a framework for systematically understanding complex molecular host-pathogen interaction networks. Specifically, we first propose four host-pathogen interaction (HPI) postulates as the basis for understanding molecular and cellular host-pathogen interactions and their relations to disease outcomes. These four postulates cover the evolutionary dispositions involved (...) in HPIs, the dynamic nature of HPI outcomes, roles that HPI components may occupy leading to such outcomes, and HPI checkpoints that are critical for specific disease outcomes. Based on these postulates, an HPI Postulate and Ontology (HPIPO) framework is proposed to apply interoperable ontologies to systematically model and represent various granular details and knowledge within the scope of the HPI postulates, in a way that will support AI-ready data standardization, sharing, integration, and analysis. As a demonstration, the HPI postulates and the HPIPO framework were applied to study COVID-19 with the Coronavirus Infectious Disease Ontology (CIDO), leading to a novel approach to rational design of drug/vaccine cocktails aimed at interrupting processes occurring at critical host-coronavirus interaction checkpoints. Furthermore, the host-coronavirus protein-protein interactions (PPIs) relevant to COVID-19 were predicted and evaluated based on prior knowledge of curated PPIs and domain-domain interactions, and how such studies can be further explored with the HPI postulates and the HPIPO framework is discussed. (shrink)

This study aimed to identify the learning and business incubation processes and their impact on developing the performance of business incubators in Gaza Strip, and the study relied on the descriptive analytical approach, and the study population consisted of all employees working in business incubators in Gaza Strip in addition to experts and consultants in incubators where their total number reached (62) individuals, and the researchers used the questionnaire as a main tool to collect data through the comprehensive survey method, (...) where (55) questionnaires were retrieved with a recovery rate of (88.7%). The results of the study showed that there is a high approval of the variables of the study, where the dimension of incubation operations came with a relative weight (84.89%), followed by the learning dimension which got a relative weight (82.50%), while the performance level of the incubators got a relative weight (80.12%) and as the study results showed There is a positive relationship statistically between the two dimensions of learning and business incubation processes and performance development in business incubators, and the linear regression analysis model showed that the main effect in improving the performance of business incubators is "after business incubation operations" while it showed weak effect after learning. The study came out with several recommendations, the most important of which is that business incubators seek to reinforce the learning process and incubation processes for business, and the need to periodically evaluate their performance, and that a more effective mechanism be designed to follow up with companies after the end of the incubation period and monitor the progress of these companies. (shrink)

There is a loud and persistent drum beat of support for schools, for citizenship, for diversity and inclusion, and increasingly for labor market readiness with very little critical attention to the assumptions underlying these agendas, let alone to their many internal contradictions. Accordingly, in this book I examine the philosophical, motivational, and practical challenges of education theory, policy, and practice in the twenty-first century. As I proceed, I do not neglect the historical, comparative international context so essential to better understanding (...) where we are, as well as what is attainable in terms of educational justice. I argue that we must constructively critique some of our most cherished beliefs about education if we are to save the hope of real justice from the rhetoric of imagined justice. (shrink)

The majority of studies on absorptive capacity (AC) underscore the importance of absorbing technological knowledge from other firms to create economic value. However, to preserve moral legitimacy and create social value, firms must also discern and adapt to (shifts in) societal values. A comparative case study of eight firms in the food industry reveals how organizations prioritize and operationalize the societal value health in product innovation while navigating inter- and intravalue conflicts. The value-sensitive framework induced in this article extends AC (...) by explaining how technically savvy, economic value–creating firms diverge in their receptivity, articulation, and reflexivity of societal values. (shrink)

Abstract— Anatomy of the anterior compartment includes the tibia and the fibula. It also includes the tibialis anterior tendon, the extensor hallucis longus tendon and the extensor digitorum longus tendons. The anterior tibial artery and the deep peroneal nerve and finally the superior and inferior extensor retinaculum. In this paper an expert system was designed to help users to correctly diagnose ankle problems. There are many structures present at the anterior aspect of the ankle; these structures are often susceptible to (...) injury common injuries and conditions around the anterior ankle. Clips expert system language was used to design and implement this expert system. (shrink)

Philosophers of science are increasingly interested in engaging with scientific communities, policy makers, and members of the public; however, the nature of this engagement has not been systematically examined. Instead of delineating a specific kind of engaged philosophy of science, as previous accounts have done, this article draws on literature from outside the discipline to develop a framework for analyzing different forms of broadly engaged philosophy of science according to two key dimensions: social interaction and epistemic integration. Clarifying the many (...) forms of engagement available to philosophers of science can advance future scholarship on engagement and promote more strategic engagement efforts. (shrink)

It is becoming increasingly common for authoritarian regimes to leverage digital technologies to surveil, repress and manipulate their citizens. Experts typically refer to this practice as digital authoritarianism (DA). Existing definitions of DA consistently presuppose a politically repressive agent intentionally exploiting digital technologies to pursue authoritarian ends. I refer to this as the intention-based definition. This paper argues that this definition is untenable as a general description of DA. I begin by illustrating the current predominance of the intention-based definition (Section (...) 2). Section 3 then presents four counterexamples to this definition: benign surveillance; digital sovereignty; attention-harvesting algorithms; and tech-induced loneliness. In each case, we witness authoritarianism being promoted by digital technologies without any evidence of this being intentionally caused by politically repressive agents. Based on these observations, I contend that the intention-based definition is underinclusive and is therefore unsustainable. Section 4 outlines an improved definition of DA – what I call the promotion-based definition. Since this more expansive definition does not posit intentional, politically repressive agency as a precondition of DA, it can accommodate the counterexamples discussed in Section 3. Moreover, it enables us to catch a broader spectrum of cases of DA, such as tech-induced loneliness, which those adhering to the intention-based definition are prone to overlook. After outlining further practical benefits of the promotion-based definition, I argue that we still need to distinguish between intentional and unintentional forms of DA since they call for distinct types of remedial action. -/- . (shrink)

We need modal imagination in order to extend our conception of reality - and, in particular, of human beings - beyond our immediate experience in the indexical present; and we need to do this in order to preserve the significance of human interaction. To make this leap of imagination successfully is to achieve not only insight but also an impartial perspective on our own and others' inner states. This perspective is a necessary condition of experiencing compassion for others. This is (...) the primary thesis I will try to defend in this discussion. (shrink)

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

Abstract: Colon cancer is a prevalent and life-threatening disease, necessitating accurate and timely diagnosis for effective treatment and improved patient outcomes. This research paper presents the development of a knowledge-based system for diagnosing colon cancer using the CLIPS language. Knowledge-based systems offer the potential to assist healthcare professionals in making informed diagnoses by leveraging expert knowledge and reasoning mechanisms. The methodology involves acquiring and structuring medical knowledge specific to colon cancer, followed by the implementation of a knowledge- based system using (...) CLIPS. The system's design integrates relevant medical databases and employs advanced reasoning mechanisms to facilitate accurate diagnosis. Evaluation results demonstrate the system's effectiveness, with high accuracy and sensitivity rates compared to existing methods. The findings highlight the potential of knowledge-based systems in improving clinical practice and patient care. The research contributes to the growing field of medical informatics by demonstrating the feasibility and effectiveness of CLIPS-based knowledge systems for colon cancer diagnosis. Future research can focus on enhancing system performance and expanding its scope to encompass other types of cancer diagnoses. (shrink)

In this book I argue that school integration is not a proxy for educational justice. I demonstrate that the evidence consistently shows the opposite is more typically the case. I then articulate and defend the idea of voluntary separation, which describes the effort to redefine, reclaim and redirect what it means to educate under preexisting conditions of segregation. In doing so, I further demonstrate how voluntary separation is consistent with the liberal democratic requirements of equality and citizenship. The position I (...) defend is not opposed to integration but rather is a justified response to the daily experience of frustration and disappointment with a system that has failed members of marginalized groups for too long. I argue that most voluntary separation experiments in education, far from being motivated by a sense of racial, cultural or religious exclusion, are in fact driven among other things by a desire for a quality education, not to mention community membership and self respect. As such, voluntary separation represents a morally robust pragmatic strategy that is able to answer liberal challenges concerning involuntary stratification, ethnocentrism and democratic deliberation. (shrink)

This study presented the policy of functional integration of the product planning team as a strategy for the development of the pharmaceutical industry in Palestine. The study population consists of all the workers in companies operating in the field of medicine in Palestine, which are (5) companies producing in the West Bank only for pharmaceuticals used by these companies, which are (296) employees, and was used a simple random sample to choose the sample and size (87) employees of the study (...) population, and to achieve the objectives of the study (87) questionnaires were distributed. The descriptive analytical method was used, and SPSS was used to answer and discuss the study's questions. The results showed that there is a significant relationship between the effectiveness of the policy of product development and the competitiveness of pharmaceutical companies in Palestine (West Bank), where the policy of product development efficiency accounts for 56.6% of the total change in the competitiveness of companies. The product quality component was most influential at all levels of product development effectiveness policy, followed by product identification, product cost reduction, packaging and product deletion. The weakest areas of strategic direction in pharmaceutical companies in Palestine (West Bank) are 67%. The weakest aspects of job integration are: non-regular meetings of representatives of different positions to participate in any project related to product development, to achieve spatial convergence of members of the product planning policy team in offices, laboratories and workplaces. (shrink)

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