Electricity demand in any region reflects its socio-economic dynamics, climatic conditions, and demographic characteristics. Bihar, a highly burgeoning state in India, exhibits peculiar electricity consumption patterns influenced by its rural-urban divide, dependence on agriculture, and acceleration of industrialization. This study looks into Bihar's load characteristics from a seasonal and diurnal perspective. The demand analysis would consider factors like temperature, humidity, and socio-economic activities that could be modeled as predictors for demand variations established through historical data and linear regression. It would (...) be useful for capacity planners and policymakers to improve grid management and planning. (shrink)

International trade enables countries to expand their markets, access more products, improve resource allocation, and boost economic growth by leveraging comparative advantage and specialization. The aim of this article is to analyze the primary factors that influence Malawi’s international trade flows. The study is relevant because it examines Malawi’s trade patterns with its main partners, which include surrounding nations and traditional trade allies. The novelty is that, through the analysis, the research offers valuable insights into the primary factors that influence (...) Malawi’s international commerce. Panel data is gathered from various sources, including the International Monetary Fund (IMF) and World Bank, covering the period from 2000 to 2023 for 11 countries that are trading partners with Malawi. We employ the Bayesian Mindsponge gravity methodology. The results show that the economic size (characterized by the gross domestic product) of the origin and destination countries, bilateral agreements, and the population size of the destination country have a beneficial impact on Malawi’s exports. In conclusion, Malawi’s export performance is significantly enhanced by the economic size of both Malawi and its trading partners, the existence of bilateral agreements, and the population size of the destination countries, underscoring the importance of strategic economic partnerships and targeted trade policies in boosting Malawi’s international trade. We recommend Malawi authorities focus on strengthening bilateral agreements and targeting trade relationships with larger and more populous economies to boost international trade. (shrink)

The authors propose a new IoT-enabled bio-impedance device using the ESP32 microcontroller to facilitate real-time health monitoring. Bioimpedance analysis is a non-invasive method to assess various physiological parameters, including body composition, hydration status, and tissue health. By integrating bio-impedance analysis with IoT capabilities, the proposed device enables continuous data acquisition and remote monitoring, thereby enhancing personalized healthcare management. The ESP32's low-power consumption and built-in Wi-Fi and Bluetooth functionalities make it an ideal platform for this application. The device transmits bioimpedance measurements (...) to a cloud-based platform, where data is stored and analyzed, providing healthcare professionals and users with accessible, real-time health information. The proposed device demonstrates accurate impedance measurements and reliable data transmission, highlighting the potential of IoT-based bioimpedance devices in advancing remote health monitoring solutions. (shrink)

In an increasingly digital world, ensuring the security and transparency of financial transactions is paramount for businesses across industries. Blockchain technology, known for its decentralized, immutable ledger, offers a transformative solution to enhance financial transaction security, traceability, and transparency. SAP, a global leader in enterprise resource planning (ERP) systems, is integrating blockchain technology into its platforms to provide organizations with secure, transparent, and efficient financial processes. By leveraging blockchain in SAP S/4HANA, SAP Cloud Platform, and SAP Leonardo, businesses can enable (...) real-time financial transactions, reduce fraud, and ensure compliance with regulatory standards. This paper explores the integration of blockchain technology with SAP systems, discussing its benefits, challenges, and real-world applications in financial transactions, while also providing a roadmap for organizations looking to adopt this integrated approach. (shrink)

As data analytics continues to revolutionize industries, the need for responsible data handling has never been more pressing. The vast amount of personal and sensitive data being collected, analyzed, and shared raises significant concerns regarding privacy and ethics. While data analytics offers powerful insights that drive business decisions, it also introduces risks related to misuse, discrimination, and breaches of privacy. This paper explores the ethical and privacy challenges surrounding data analytics, proposing a balanced approach that allows organizations to derive meaningful (...) insights while safeguarding individual rights. By examining current best practices and frameworks, this study aims to provide guidelines for maintaining privacy and ethical standards in data analytics. (shrink)

The objective of this study is to incorporate topological space into the realm of n-Cylindrical Fuzzy Neutrosophic Sets (n-CyFNS), which are the most novel type of fuzzy neutrosophic sets. In this paper, we introduce n-Cylindrical Fuzzy Neutrosophic Topological Spaces (n-CyFNTS), n-Cylindrical Fuzzy Neutrosophic (n-CyFN) open sets, and n-CyFN closed sets. We also defined the n-CyFN base, n-CyFN subbase, and some related theorems here.

The advent of cloud computing has revolutionized how machine learning (ML) models are developed, trained, and deployed. By providing scalable, on-demand infrastructure, cloud platforms empower researchers, startups, and enterprises to leverage advanced ML capabilities without the burden of maintaining expensive hardware. This paper explores best practices and diverse use cases for implementing machine learning in the cloud, focusing on resource optimization, workflow automation, and model lifecycle management. Cloud-based machine learning offers several strategic benefits including cost-efficiency, ease of access to high- (...) performance computing (HPC), and the integration of managed services for data preprocessing, model training, deployment, and monitoring. Popular services such as Amazon SageMaker, Google Cloud Vertex AI, and Microsoft Azure ML provide comprehensive environments that simplify end-to-end ML development. However, challenges such as data privacy, vendor lock-in, and cost unpredictability remain persistent concerns. This paper reviews recent literature and analyzes real-world applications of cloud ML in industries like healthcare, finance, and retail. It outlines a research methodology centered around evaluating ML workflows across leading cloud platforms, followed by a discussion of key findings on performance, cost, and scalability. A structured workflow is proposed to guide practitioners in selecting appropriate tools and architectures. Furthermore, the paper identifies the primary advantages and drawbacks of cloud-based ML, concluding with recommendations for overcoming current limitations and future research directions. Use cases such as fraud detection, medical diagnostics, customer segmentation, and predictive maintenance demonstrate the transformative potential of cloud-based ML when implemented with best practices. By highlighting successful implementations and addressing operational trade-offs, this work serves as a practical guide for decision-makers and ML practitioners aiming to maximize the value of machine learning in the cloud. Through a comprehensive examination of tools, techniques, and real-world scenarios, it aims to contribute to more efficient, ethical, and scalable ML solutions. (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)

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)

This study explores experiences of ex-incels—men who have withdrawn from incel communities—through eleven qualitative interviews analysed using R.W. Connell’s hegemonic masculinity (HM) framework. Findings reveal some ex-incels adopt flexible masculinities, while others struggle with prescriptive norms perpetuated by the anti-feminist ‘manosphere’. Findings spotlight identity reconstructions, where men both reject and remain influenced by rigid archetypes, performing hybrid masculinities. This study deepens understanding of incel ideology, its impact on identity, and interplay between inceldom and masculinities via contributing to hybrid masculinities theorising. (...) Insights presents applications for gender theory and inform further research on HM’s influence within unique cultural contexts. (shrink)

The ethics of immigration is currently marked by a division between realists and idealists. The idealists generally focus on formulating morally ideal immigration policies. The realists, however, tend to dismiss these ideals as far-fetched and infeasible. In contrast to the idealists, the realists seek to resolve pressing practical issues relating to immigration, principally by advancing what they consider to be actionable policy recommendations. In this article, I take issue with this conception of realism. I begin by surveying the way in (...) which it exemplifies what certain political theorists have recently called ‘problem-solving’ realism – a species of realism which they reject as incoherent. These theorists demonstrate that what counts as a ‘feasible’ solution is far harder to establish than most problem-solving realists would have us believe. Applying this general critique to the specific domain of immigration ethics turns out to radically undermine the notion of realism that prevails in this sphere of applied ethics. I conclude that we should therefore revise our conception of what constitutes a genuinely realist approach to the problem of immigration. (shrink)

We propose a formal framework for interpretable machine learning. Combining elements from statistical learning, causal interventionism, and decision theory, we design an idealised explanation game in which players collaborate to find the best explanation for a given algorithmic prediction. Through an iterative procedure of questions and answers, the players establish a three-dimensional Pareto frontier that describes the optimal trade-offs between explanatory accuracy, simplicity, and relevance. Multiple rounds are played at different levels of abstraction, allowing the players to explore overlapping causal (...) patterns of variable granularity and scope. We characterise the conditions under which such a game is almost surely guaranteed to converge on a optimal explanation surface in polynomial time, and highlight obstacles that will tend to prevent the players from advancing beyond certain explanatory thresholds. The game serves a descriptive and a normative function, establishing a conceptual space in which to analyse and compare existing proposals, as well as design new and improved solutions. (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 integration of artificial intelligence (AI) into drug discovery is revolutionizing the pharmaceutical industry by accelerating the development of novel therapeutics. AI-powered tools enable researchers to process vast datasets, identify drug candidates, and predict their efficacy and safety with unprecedented speed and accuracy. This paper explores the transformative impact of AI on drug discovery, highlighting key advancements in machine learning algorithms, deep learning, and predictive modeling. Additionally, it addresses the challenges associated with AI implementation, including data quality, regulatory hurdles, (...) and ethical considerations. By analyzing case studies of AI-driven pharmaceutical breakthroughs, this paper underscores AI's potential to streamline drug development, reduce costs, and address unmet medical needs. The future of drug discovery is poised to shift dramatically as AI continues to advance, offering promising solutions for improving human health. (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)

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)

The aim of this study was to identify the obstacles facing the application of knowledge management and its impact on performance at Palestine Technical University-Kadoorei from the point of view of employees and to detect the differences between the average views of the study sample on the subject of the study according to some variables such as (gender, nature of work, Education Level, specialization, years of experience). The study followed the descriptive analytical method and the questionnaire as a tool for (...) study. It was distributed to 74 employees. After the questionnaire was distributed, the data was collected and coded and entered into the computer and processed statistically using the SPSS program. The study found that the percentage of approval of the obstacles to the application of knowledge management at Palestine Technical University-Kadoorei differed between few and large, and the relative weight of the axis was complete (68.2). The degree of awareness of the workers of the reality of performance excellence at the University of Palestine Technical-Kadoorei was between medium and very large. There is an impact of the constraints of the application of knowledge management on performance excellence at Palestine Technical University-Kadoorei. In light of the results of the previous study, the researchers recommended that the importance of knowledge management should be taken into account in order to raise the university's reputation and reputation at home and abroad and improve its services to students and the local community. And to promote the exchange of experiences and knowledge with local, regional and international universities in order to enhance the knowledge and preserve it and provide modern and sophisticated scientific techniques and use them in administrative and academic work at the university. (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)

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

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

Abstract: 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)

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

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)

Background Men with antisocial personality disorder show lifelong abnormalities in adaptive decision making guided by the weighing up of reward and punishment information. Among men with antisocial personality disorder, modifi cation of the behaviour of those with additional diagnoses of psychopathy seems particularly resistant to punishment. Methods We did a case-control functional MRI (fMRI) study in 50 men, of whom 12 were violent off enders with antisocial personality disorder and psychopathy, 20 were violent off enders with antisocial personality disorder but (...) not psychopathy, and 18 were healthy non-off enders. We used fMRI to measure brain activation associated with the representation of punishment or reward information during an event-related probabilistic response-reversal task, assessed with standard general linear-model-based analysis. Findings Offenders with antisocial personality disorder and psychopathy displayed discrete regions of increased activation in the posterior cingulate cortex and anterior insula in response to punished errors during the task reversal phase, and decreased activation to all correct rewarded responses in the superior temporal cortex. This finding was in contrast to results for off enders without psychopathy and healthy non-off enders. Interpretation Punishment prediction error signalling in off enders with antisocial personality disorder and psychopathy was highly atypical. This finding challenges the widely held view that such men are simply characterised by diminished neural sensitivity to punishment. Instead, this fi nding indicates altered organisation of the information processing system responsible for reinforcement learning and appropriate decision making. This difference between violent offenders with antisocial personality disorder with and without psychopathy has implications for the causes of these disorders and for treatment approaches. (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)

It is in recent times that the working conditions of the rural and farm workers have drawn special attention on account of escalating exposure to toxins like pesticides. Detection and diagnosis of pesticide poisonings at the initial stages become crucial to save the patient at the earliest stage of medical interventions and to forestall longterm complications. Even so, few rural communities still lack access to high-tech equipment and techniques in diagnostics. To resolve this problem, this project introduces a data-driven methodology (...) using Supervised Machine Learning (SML) methods for the efficient and accurate diagnosis of pesticide poisoning using clinical and biochemical markers. The main contribution of this research is the development and application of a systematic methodology called Data Refinement Cycle with Supervised Machine Learning (DRC–SML). This model was created to offer a complete, applicable, and reproducible methodology that directs a Data Science project from start to finish. It consists of phases like data collection, data preprocessing, missing value handling, encoding and scaling, model selection, performance metrics, and preparation for deployment. In contrast to most current methodologies, which only deal with isolated phases of the data pipeline, DRC–SML guarantees an overall workflow that facilitates a smooth transition between the steps and uniform results. (shrink)

Abstract. This study explores the use of convolutional neural networks (CNNs) for classifying different pineapple varieties, specifically pineapples and mini pineapples. By using a dataset of pineapple images, the research demonstrates the effectiveness of a pre-trained VGG16-based CNN model in accurately classifying these fruit categories. The model achieved over 99% accuracy on both the training and validation sets. The performance of the CNN was compared to traditional machine learning algorithms to highlight the advantages of deep learning in image classification tasks. (...) The results underscore the model’s ability to generalize well to the classification task, offering insights into feature extraction from complex image datasets. (shrink)

Abstract. This study investigates the application of convolutional neural networks (CNNs) to the task of classifying male and female eyes. Using a dataset of eye images, the research explores the potential of deep learning to accurately distinguish between the genders based solely on eye features. The proposed CNN model achieved 94% accuracy on the training set and 91% on the validation set. The study addresses the challenges and limitations in feature extraction from eye images and compares the proposed model with (...) traditional machine learning approaches. The results demonstrate the model's robustness, providing significant insights into gender recognition through partial facial analysis. (shrink)

Stretching is one of the important things to do before doing a physical activity. Stretching helps you to avoid possible injuries, muscle soreness and even improve overall performance. The researcher came up with an idea to create a modified stretching routine to assess if our created modified stretching is better than the traditional stretching. This study aims to assess the impact or the effect of the created modified stretching routine to the performance of students. This study utilizes the quasi-experimental research (...) design. In analyzing the data, descriptive statistics and multiple linear regression are being utilized. Overall, based on the results, utilizing modified stretching routine has a positive impact to the student’s performance. There is a significant difference on the student’s performance when they use the modified stretching routine than the traditional stretching routine. From the data collected, it shows that students who uses the modified stretching routine definitely improve their flexibility, cardiovascular endurance and muscular endurance. (shrink)

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)

It is part of an old folklore that logic should not have existential theo- rems or existential validities. One should not prove in pure logic the existence of anything whatsoever; nothing could be proved by means of logic alone to necessarily exist. Whatever exists might not exist. This standpoint has been expressed by several philosophers from different traditions, such as Hume, Kant, Orenstein and Quine. We now set the stage by examining some issues. Our main question is: “Do we actually (...) have existential theorems in logic?” Two possible attitudes towards this question are as follows. A desideratum: logic should not have any existential theorems. A fact: logic does not have any existential theorems. (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)

There are three questions associated with Simpson’s Paradox (SP): (i) Why is SP paradoxical? (ii) What conditions generate SP?, and (iii) What should be done about SP? By developing a logic-based account of SP, it is argued that (i) and (ii) must be divorced from (iii). This account shows that (i) and (ii) have nothing to do with causality, which plays a role only in addressing (iii). A counterexample is also presented against the causal account. Finally, the causal and logic-based (...) approaches are compared by means of an experiment to show that SP is not basically causal. (shrink)

This paper critically engages Philip Mirowki's essay, "The scientific dimensions of social knowledge and their distant echoes in 20th-century American philosophy of science." It argues that although the cold war context of anti-democratic elitism best suited for making decisions about engaging in nuclear war may seem to be politically and ideologically motivated, in fact we need to carefully consider the arguments underlying the new rational choice based political philosophies of the post-WWII era typified by Arrow's impossibility theorem. A distrust of (...) democratic decision-making principles may be developed by social scientists whose leanings may be toward the left or right side of the spectrum of political practices. (shrink)

The article concerns the interpretation of Aquinas' philosophy in the thougt of the swiss theologian Hans Urs Von Balthasar.

The aim of this study is to explore the relationship between the decision support systems and re-engineering in the Palestinian universities in Gaza Strip. A descriptive approach was used where a questionnaire was developed and distributed to a stratified random Sample. (500) questionnaires were distributed and (449) were returned, response rate (89.8%). The study reached many results such as: There is A statistically significant relationship at a significant level (α ≤ 0.04) between the decision support systems and re-engineering in the (...) universities under investigation. There are differences in the answers of the respondents concerning the relationship between decision support systems and re-engineering due to the gender of the respondents in favor of the males. There are differences in the answers of the respondents for the dimension (managerial support for the decision support systems) in favor of those in the age group between (45-55) years and more than (55) years, and due to the educational level in favor of those holding master degrees, and due to the name of the university in favor of the Islamic university, Al azhar university, Al aqsa university, respectively and due to the years of experience in favor of those who have (15-20) years of experience and (21) years and more. The study reached many Conclusions such as: In order to be able to cope with globalization and its technical aspects, the Palestinian universities in Gaza should focus on the process of re-engineering. The importance of this tendency should be clarified to the top management of these universities specially those who are not willing to do so. The universities should be encouraged to start implementing it’s re-engineering programs while developing the infrastructure for their information technology as a whole, and the decision support systems in particular. The top management in the universities should increase their dependence, support and use of the decision support systems in the decision-making process. The top management should also diagnose the problems and encourage the employees to use the decision support systems and overcome the obstacles that may hinder the development of the decision support systems. (shrink)

Rawls offers three arguments for the priority of liberty in Theory, two of which share a common error: the belief that once we have shown the instrumental value of the basic liberties for some essential purpose (e.g., securing self-respect), we have automatically shown the reason for their lexical priority. The third argument, however, does not share this error and can be reconstructed along Kantian lines: beginning with the Kantian conception of autonomy endorsed by Rawls in section 40 of Theory, we (...) can explain our highest-order interest in rationality, justify the lexical priority of all basic liberties, and reinterpret Rawls’ threshold condition for the application of the priority of liberty. Perhaps unsurprisingly, this Kantian reconstruction will not work within the radically different framework of Political Liberalism. (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)

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.

Aristotle’s dialogue Protrepticus is not only his earliest work of ethics but also the root of all his subsequent investigations into ethics. Here we explore the various ways Aristotle retained in memory the contents of the Protrepticus and redeployed them in the Eudemian Ethics, including the common books. Since Aristotle himself does not explicitly acknowledge the foundational significance of the Protrepticus to his later works, our exploration must proceed on the basis of our knowledge of the earlier work, which can (...) then related to comparable passages in the treatises. But the Protrepticus is a lost work, unlike the EE and the EN, in the sense that no medieval manuscripts of it have survived. And so it first needs to be reconstructed on the basis of the streams of reception that deposited information in surviving works by later ancient authors. We begin in part 1 by reviewing the surviving evidence of the Protrepticus before presenting our wider reconstruction and conception of the work as a dialogue in part 2. In part 3, we discuss ideas and arguments in the reconstructed dialogue that are retained and redeployed in the Eudemian Ethics, focussing on the account of intellectual virtues in EE v and the introduction and methodological framework in EE i-ii.1. (shrink)

The critique of philosophical foundations of neoclassical economics is significant, because of its hegemony on economic education and research programs in Iran and worldwide academies. Due to an epistemological fallacy, methodological individualism plays a prominent role in the philosophy of economic; since the ontological aspects of economy are reduced to methodological considerations. Accordingly, critique of methodological individualism is regarded as the main entry for philosophical analysis of neoclassical economics. This article aims to analyze and appraise the methodological individualism from critical (...) realism’s point of view. Critical realism is taken as a stand for criticizing methodological individualism, because critical realism and neoclassical economics as a positive approach to economics, both share a realistic worldview. The critical realism’ critique of methodological individualism is bases on analyzing the concepts of formalism, syllogism, social atomism, isolation and reduction. From critical realism’ point of view because of unrealistic postulations of methodological individualism, neoclassical economics is turned to an abstract and deductive science such as mathematics with a low potentiality of explanation. (shrink)

The Principle of Identity of Indiscernibles (PII) is the focus of much controversy in the history of Metaphysics and in contemporary Physics. Many questions rover the debate about its truth or falsehood, for example, to which objects the principle applies? Which properties can be counted as discerning properties? Is the principle necessary? In other words, which version of the principle is the correct and is this version true? This thesis aims to answer this questions in order to show that PII (...) is a necessarily true principle of metaphysics. To accomplish this task, the reader will find, in this thesis, an encyclopaedical introduction to the history of PII and to the reasons it matters so much, followed by a presentation of the most famous arguments against it and the defences used against these arguments. Then, the reader finds in-depth discussion of the minutiae involved in postulating the principle as to make clear what is in fact being attacked and defended. With these preliminaries solved, a deeper analysis of these defences is presented aiming to discover which is the most appropriate example to use against the attacks to the principle. This analysis allowed a classification of these defences in four families with different strategies within them. Finally, with these defensive strategies at hand we are able to confront alleged counterexamples to PII in Mathematics with the intention to test these defences. (shrink)

When the NCAA adopted new rules allowing athletes to profit off their name, image, and likeness (NIL), few people took more interest than Reggie Bush who famously relinquished the Heisman trophy after being ruled retroactively ineligible for receiving "impermissible benefits." Bush has argued for his reinstatement and the "return" of his Heisman. In this paper, I argue that, while the NCAA never should have required players to be amateurs in the first place, Bush should not be reinstated or have the (...) Heisman "returned." Properly understood, Reggie Bush never won the Heisman Trophy in the first place, so "returning" it would be to rewrite history — almost literally, to move the goalposts. -/- Forthcoming in "College Sports and Ethics" by Lexington Books. (shrink)

The article entitled “Cultural evolution in Vietnam’s early 20th century: A Bayesian networks analysis of Hanoi Franco-Chinese house designs” investigates how diverse cultures and religious creeds influenced the architecture of Hanoi in the early 20th century.

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.

Heidegger’s “Evening Conversation: In a Prisoner of War Camp in Russia, between a Younger and an Older Man”, one of three dialogues composed by Heidegger after the defeat of National Socialist Germany published in Country Path Conversations explores the being-historical situation and fate of the German people by turning to the early Daoist text of the Zhuangzi. My article traces how Heidegger interprets fundamental concepts from the Zhuangzi, mediated by way of Richard Wilhelm’s translation Das wahre Buch vom südlichen Blütenland, (...) such as naturalness, letting/releasement, the unnecessary and the useless in the context of his hermeneutical and political situation. I consider to what extent this dialogue, along with his other discussions of the Zhuangzi and intensive engagement with the Daodejing from 1943 to 1950, constitute a “Daoist turn” in Heidegger’s thinking that helped shape his Postwar thought. (shrink)