Philosophical counselling is generally understood as a movement in practical philosophy that helps counselees, i.e. clients, resolve everyday problems with the help of philosophy. Moving outside of the scope of what philosophy can do, however, is a problem. More specifically, when the philosophical counsellor moves outside of the so-called realm of philosophy into the realm of psychotherapy, i.e. medical framework, problem resolution and ameliorative goals might be on the table. This plays into the hands of critics who state that philosophical (...) counselling is encroaching on the terrain of the mental health professions without, inter alia, the proper evidence of its treatment efficacy. This paper is an attempt to keep the philosophical counsellor in the realm of philosophy, and by doing this to keep them busy with philosophising as such, i.e. philosophising as an end in itself. In particular, the article focuses on a novel interpretation of how to approach the counselee’s problem so that the philosophical counsellor does not fall prey to problem resolving and ameliorative endeavours. To substantiate this novel reinterpretation to the counselee’s problem, I turn to the notions of the Pyrrhonian aporia and the Derridean perhaps, in conjunction with a crucial position exclusively available to the counselee in philosophical counselling. (shrink)

Method in philosophical counselling is still a contentious topic. That is, there is no consensus on whether the philosophical counsellor should have a method in her practice to help the counsellee resolve philosophical problems. Some philosophical counsellors claim that there should not be any rigid adherence to method(s) as this will render philosophy too dogmatic. Philosophical counselling, in light of this view, promotes a kind of mutual philosophising sans definite goal with the counsellee. What I call "dissentient philosophical counselling" takes (...) this claim even further: the philosophical counsellor lives/practices her philosophical counselling, that is, she embodies and practices philosophy as a way of life. This view is posed as a response to contemporary conceptualisations of philosophical counselling where the philosophical counsellor might stand in a disembodied relationship with her method(s) and tries to have a conversation "from nowhere". Dissentient philosophical counselling, even though more focused on living philosophically , still suffers from certain shortcomings. In this paper, I firstly showcase how even the seemingly innocuous but important question "How might one live?" suffers from a lack of much needed nuance. And secondly, I introduce, via a fictional narrative, a provisional way of practicing this reworked dissentient philosophical counselling. I do this by, firstly, introducing African conversational philosophy, via its method of conversationalism, and secondly, I introduce a peculiar version of Pyrrhonian scepticism especially regarding the notion of bios adoxastōs (life without dogma). (shrink)

Philosophical counselling, a relatively new field in practical philosophy, offers to potentially edify the layperson’s everyday life with the help of philosophy. This lofty ideal is upheld by philosophical practitioners introducing various contemporary philosophies to its growing literature. However, many philosophical traditions beyond contemporary philosophy still somewhat suffer from an unwarranted neglect. Presently, African philosophy faces an almost complete absence in the philosophical counselling literature. It is thus a given that a prevalent lack of inquiry exists regarding its use in (...) philosophical counselling. Despite this silence, fertile grounds exist for innovative contributions to further advance the development of African philosophy in philosophical counselling. -/- In this talk, I will introduce a novel reading of African philosophy to the literature of philosophical counselling. This understanding of African philosophy is greatly inspired and influenced by the work of Tsenay Serequeberhan and Jonathan Chimakonam. More specifically, the notion of African philosophy gathered from these philosophers seek to advance the critical interpretation/hermeneutic actualised from a specific philosophical place or lifeworld through the method of conversationalism. Furthermore, the very rootedness of this notion of philosophy, stemming from a concrete lifeworld, actively problematises philosophies that reproduce a supposed and untenable value neutrality. -/- Developing this understanding of African philosophy in a philosophical counselling context, I offer an initial critique of uncritical applications of philosophies originating from distinct philosophical places under the guise of a value neutrality. In maintaining this unwarranted silence on different philosophical traditions, philosophical counsellors might promote the use of philosophies as if universally applicable. And secondly, I propose that following from this understanding of African philosophy, philosophical counselling as such can begin to foster an environment in which new concepts can be co-created. Consequently, and in conjunction with conversationalism, radically new ways of being/becoming can be explored which might hold greater contextual significance. (shrink)

Contemporary philosopher David Benatar has advanced the self-evidently controversial claim that “coming into existence is always a harm.” Benatar’s argument turns on the basic asymmetry between pleasure and pain, an asymmetry he seeks to explain by the principle that those who never exist cannot be deprived. Benatar’s import is almost incredible: humans should cease to procreate immediately, thereby engendering the extinction of the species—a view known as “anti-natalism.” According to many of his readers, the ancient Hebrew sage Qoheleth expresses a (...) pessimistic nihilism that runs as thick as Benatar’s. Prima facie grounding for this assertion is that Qoheleth, like Benatar, raises the issue of whether coming into existence may be a harm—and gives an affirmative answer. In two passages, Ecclesiastes 6:1-6 and 4:1-3, Qoheleth declares that an unborn hypothetical person is “better off” than their existent counterpart. Yet the meaning and implication of these words is far from obvious. Does Qoheleth imply that the non-exister’s state, and non-existence in general, is universally superior to existence? Or is he instead speaking exceptionally, of particular persons in rare circumstances? By examining the two “better”-statements in their literary context, I will argue that Qoheleth intends these examples as exceptions. He does not go so far as to make the supremely nihilistic claim that coming into existence is always, or even generally, a net harm; yet, he does concede that in certain cases, it can be. Beyond this, I will explore how the two thinkers’ divergent conclusions can be traced to a deeper difference of philosophical method. This question concerning non-existence opens a window to Qoheleth’s broader scheme of values and therefore serves as a surprisingly useful entry point by which to engage his philosophy. The paper utilizes the methodology Jaco Gericke has recently termed “philosophical criticism,” but specifically applied to Qoheleth. (shrink)

Philosophical counselling is generally understood as the discussion or resolution of everyday problems with the help of philosophy. However, few agree on this definition. This leads to a crisis of definition for philosophical counselling which in turn causes practical problems regarding, inter alia, the teaching of future philosophical counsellors, the question of method, and the potential scope of philosophical counselling. I identify in this study a prevalent therapeutic thesis on the nature of philosophical counselling which ties together some of the (...) more popular conceptions of philosophical counselling. This thesis predominates when philosophical counsellors focus on the counselling part and neglect the philosophical part of philosophical counselling. This stance keeps philosophical counselling firmly contained within a medico-therapeutic framework. In opposition to this predominant view, I propose a reconceptualisation of philosophical counselling which does not subscribe to the therapeutic thesis and by implication works outside of a medical framework. More specifically, in fleshing out my non-therapeutic understanding of philosophical counselling, I propose twelve context-dependent conditions of philosophical counselling by drawing on a Pyrrhonian disposition and also on examples of philosophical counsellors who begin to work outside of the medico-therapeutic framework. I argue that these conditions should be met for philosophical counselling to stay firmly within the realm of philosophy as an aim in itself, thereby remaining true to its origin and basic orientation, and drawing on its innate strengths. With this fundamental reconceptualisation and the accompanying twelve context-dependent conditions, I propose a novel account of philosophical counselling which (i) does not subscribe to the therapeutic thesis, (ii) gives a novel answer to the problem of educating future philosophical counsellors, and (iii) has a clear scope of potential counselees. (shrink)

Philosophical counselling is typically conceptualised as a praxis going beyond academic and theoretical philosophy. However, two problems soon follow, namely the lack of agreed-upon methods and a substantial neglect of different philosophical traditions informing its practice. In this article, I propose reconceptualising philosophical counselling as a distinct method through which academic philosophy can be practised. This allows me to introduce an understanding of African philosophy, inspired by African philosophers Chimakonam and Serequeberhan, that might encourage the philosophical counsellor to render academic (...) philosophy more applicable to the counselee. Moreover, it allows for embodied voices talking from an embedded African lifeworld to create new and more relevant concepts that emerge from that lifeworld. (shrink)

At the heart of philosophical counselling, an emerging field of practical philosophy, is a modest claim, that the lay public can benefit from all that philosophy has to offer. If accepted, this claim suggests that different philosophical traditions should be incorporated into the philosophical counselling discourse. Even though various philosophical traditions have slowly been incorporated, there are sparse mentions of African philosophy in the philosophical counselling literature. However, Ubuntu philosophy has recently garnered some attention. Nonetheless, in this talk I address (...) this dearth of African philosophical input through the introduction of two alternative notions of African philosophy, namely, African hermeneutics and conversational philosophy. These two schools of thought provide valuable and enriching insights to the philosophical counselling discourse. Through this introduction, I aim to transform two key mechanisms as found in the philosophical counselling literature. These mechanisms, that of a hermeneutical happening and collaborative philosophising, invaluable as they are to our understanding of philosophical counselling, lack a certain contextual nuance and situated sensitivity. Consequently, a problematic value-neutrality is continually reproduced; the philosophical counsellor then emerges as an “unprejudiced and value neutral educator”. With the help of African hermeneutics and conversational philosophy, I aim to positively transform these mechanisms. This transformation involves taking seriously the situated and contextual response, emerging from and responding to, in this case, an African lifeworld. Resultant is an interpretive actualisation through a collaborative undertaking rooted in the very conditions of the philosophical conversation. (shrink)

Contributions of Pierre Hadot pertaining to the notion of philosophy as a way of life have had a profound and enduring influence upon philosophical counselling theory and practice. Various philosophical counsellors, such as Robert Walsh and Arto Tukiainen, have embraced this imperative by living their philosophical counselling practice. Nonetheless, a prevailing trend among these practitioners lies in their exclusive reliance upon either the ancient Greek philosophical tradition as expounded by Hadot, or in their adaptation of contemporary Western philosophies. Regrettably, a (...) conspicuous omission prevails with respect to the incorporation of contemporary African philosophies, notably their philosophical praxes as a way of life/living, within the discourse of contemporary philosophical counselling. The integration of African philosophies into the discourse of philosophical counselling literature holds significant promise, particularly concerning the potential to impact ways of living within a Southern African context. Within the wider landscape of contemporary African philosophy, certain authors have already conceptualised ubuntu philosophy as a way of life/living. This talk, notwithstanding, undertakes to introduce two different African philosophies, namely, hermeneutic African philosophy and conversational philosophy. A novel interpretation of these philosophies will be advanced, positioning them as praxes for philosophical counselling. Emphasis is placed on an interpretative actualisation in response to lived experiences, contextualised within a conversational framework. The implications for philosophical counselling are threefold: firstly, the disclosing of alternative ways of life/living and being/becoming, along with the creation of new concepts; secondly, a profound accentuation of the relational dimension in philosophical counselling, underscored by the notion of collaborative philosophising that emerges from the dynamic interaction between the philosophical counsellor and the counselee; thirdly, a reworked understanding of philosophical counselling that moves beyond methodological constraints while embracing the transformative potential of reflective, creative, and critical conversations. (shrink)

Philosophical counselling, a contemporary movement in practical philosophy, continually expands its discourse by introducing novel philosophical ideas and different traditions. Nevertheless, a conspicuous silence persists regarding the introduction of African philosophies in its discourse. This issue becomes apparent when the question “How might one live?”—a fundamental question that the philosophical counsellor deals with—is adequately investigated. However, its current formulation suffers greatly from a much-needed nuance concerning temporal and contextual awareness. To address and transcend this shortcoming, I turn to two distinct (...) African philosophies, namely, the hermeneutic philosophy of Tsenay Serequeberhan and the conversational method of philosophising advocated by Jonathan O. Chimakonam. By incorporating these philosophies, my aim is twofold: first, to promote an interpretative actualisation situated within a conversational framework that might lead to the creation of new concepts and/or the disclosing of different ways of being/becoming, and second, to draw attention to an underlying assumption that might maintain the neglect of philosophical traditions beyond Western philosophy. (shrink)

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

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)

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)

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

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

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

There is a shortage of clergy, at least in the Roman Catholic Church. Protestant churches in general are experiencing more of a distribution or placement challenge than a shortage. The two greatest hindrances to addressing the Protestant clergy distribution challenge are a lack of adequate compensation for clergy and the undesirable geographical location of a number of churches, as perceived by clergy. Influences such as secularisation, duality of vocation, time management, change in type of ministry, family issues, congregational and denominational (...) conflict, burnout, sexual misconduct, divorce or marital problems, and suicide, affect clergy. Studies on the shortage of clergy have been conducted mostly in the USA and Europe and not in South Africa. This article focuses on the research gap by means of a practical theological grounded theory exploration of the exodus of clergy. Grounded theory methodology is used to identify the reasons why clergy trained at a Bible college of a Protestant charismatic mega church leave full-time pastoral ministry. Findings correspond to previous studies with two reasons appearing more frequently than others: responding to a call and leadership related issues. Firstly, respondents differed in their replies with respect to reconciling their exit from full-time pastoral ministry with their call. The replies included not being called, a dual call, or called but left anyway. Secondly, respondents indicated that leadership influence was mostly negative with regard to affirming their call. (shrink)

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

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

Abstract: A corn crop typically refers to a large-scale cultivation of corn (also known as maize) for commercial purposes such as food production, animal feed, and industrial uses. Corn is one of the most widely grown crops in the world, and it is a major staple food for many cultures. Corn crops are grown in various regions of the world with different climates, soil types, and farming practices. In the United States, for example, the Midwest is known as the "Corn (...) Belt" due to its extensive corn production. Corn crops can be grown using a variety of methods, including conventional tillage, no-till farming, and the use of genetically modified crops. Due to its importance, there is a need for discovering the corn diseases and treating them. The aim of this study is to propose a deep learning model for the classification of corn leaf diseases based on Convolutional Neural Network. A model for classifying maize diseases was developed using a dataset for classifying Corn diseases that contains 4 classes of disease. The dataset was collected from Keggel website. The proposed model was trained, validated, and tested. The F1-score (99.83%), Recall (99.83%), precision (99.83%), Accuracy (99.83%). (shrink)

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

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

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

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

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

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)

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

heart attack analysis & prediction dataset is a major cause of death worldwide. Early detection and intervention are essential for improving the chances of a positive outcome. This study presents a novel approach to predicting the likelihood of a person having heart failure using a neural network model. The dataset comprises 304 samples with 11 features, such as age, sex, chest pain type, Trtbps, cholesterol, fasting blood sugar, resting electrocardiogram results, maximum heart rate achieved, exercise-induced angina, oldpeak, ST_Slope, and HeartDisease. (...) A neural network model with four layers (1 input, 2 hidden, 1 output) was trained on the dataset and achieved an accuracy of 88% and an average error of 0078296. The most influential factors in heart failure prediction were found to be oldpeak, ST_Slope, sex, fastingBS, chestPainType, exerciseAngina, cholesterol, restingBP, maxHR, restingBP, and age. This study provides a valuable tool for early detection and intervention of heart failure, thereby contributing to the field of health and medicine. (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.

Intelligent Tutoring Systems (ITS) has a wide influence on the exchange rate, education, health, training, and educational programs. In this paper we describe an intelligent tutoring system that helps student study computer networks. The current ITS provides intelligent presentation of educational content appropriate for students, such as the degree of knowledge, the desired level of detail, assessment, student level, and familiarity with the subject. Our Intelligent tutoring system was developed using ITSB authoring tool for building ITS. A preliminary evaluation of (...) the ITS was done by a group of students and teachers. The results were acceptable. (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)

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

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

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

One of the many arguments against capital punishment is that execution is irrevocable. At its most simple, the argument has three premises. First, legal institutions should abolish penalties that do not admit correction of error, unless there are no alternative penalties. Second, irrevocable penalties are those that do not admit of correction. Third, execution is irrevocable. It follows that capital punishment should be abolished. This paper argues for the third premise. One might think that the truth of this premise is (...) self-evident. But in his paper “Is the Death Penalty Irrevocable?” Mike Davis argues that it is false: the death penalty is not irrevocable. While Davis’ argument is itself somewhat compelling, it receives additional support from work in the metaphysics of death, specifically the literature on posthumous harm. Strengthened in this way, the argument deserves careful consideration. I begin with a quick sketch of Davis’ argument, then show how the Pitcher-Feinberg theory of posthumous harm enables a more robust argument against the irrevocability of capital punishment, defending their theory of harm against standard objections in the literature. Having established the coherency of the robust argument, I conclude that it nevertheless fails to make the case against irrevocability. This is because it ignores the full set of practical requirements incumbent on legal institutions that wrongly punish someone. (shrink)

As the debate between realists and empiricists in the philosophy of science drags on, one point of consensus has emerged: no one wants to be a manifestationalist. The manifestationalist is a kind of radical empiricist who argues that science provides theories that aim neither at a true picture of the entire world, nor even an empirically adequate picture that captures the world in all its observable respects. For manifestationalists, science aims only at providing theories that are true to the observed (...) aspects of reality. If the guiding idea of empiricism is that experience, and experience alone, provides us with knowledge about the world, then manifestationalism is an exceptionally strict empiricist perspective on science. Manifestationalism has primarily served within a reductio: certain empiricist views and arguments, when taken to their logical conclusion, lead to manifestationalism and so cannot be correct. The reductio works only because manifestationalism is widely agreed to be a non-starter. However, this consensus against manifestationalism is based on a single argument. We contest this assessment of manifestationalism and show that the primary argument against manifestationalism fails to hit its target. We do not intend to offer a manifesto for manifestationalism. Rather, we aim to vindicate it from a false accusation. Manifestationalism may not be the correct view of science, but the objections levied against it so far can be met. (shrink)

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

The research aims to identify the reality of modern methods applied in the process of performance assessments of employees in the municipalities of Gaza-strip, Complete Census method of community study was used, (571) questionnaires were distributed to all members of the community study, (524) questionnaires were recovery with rate of (91.76%). The most important findings of the study: There were statistically significant relationship differences between the applications of modern methods in the performance assessments of employees in the municipalities of Gaza-strip. (...) There was statistically significant relationship between the evaluation criteria that fit the required performance and the application of standards evaluations on performance of employees in the municipalities of Gaza-strip. There was statistically significant relationship between the use of methods, models for the evaluation of appropriate functions and the application of the performance assessments of employees in the municipalities of Gaza-strip. There was statistically significant relationship between the feedback and the application of performance assessments of employees in the municipalities of Gaza-strip. There was statistically significant relationship between the efficient, professional assessors and the application of the performance assessments of employees in the municipalities of Gaza-strip. There was statistically significant relationship between the extent of awareness of subordinates, participation in the evaluation of their performance and the application of the performance assessments of employees in the municipalities of Gaza-strip. The research also concluded a series of recommendations, including: that the design of evaluation models must be done with the participation of the employees and inform them of it, and that a date must be set to provide feedback and discuss the results with them, that they should be allowed grievance in front of an ad hoc committee in accordance with the known system. Direct manager must inform employees of their performance assessment date, discuss the results of the evaluation with them, and others should be involved with the direct manager of employees in their performance evaluation. The application of modern methods of performance evaluation through the good and purposeful planning should be used, analyzing and employing the results in administrative decisions regarding the employees, and the application of modern methods must be used in an effective and efficient performance evaluation. (shrink)

Abstract: In recent years, the outbreak of various poultry diseases has posed a significant threat to the global poultry industry. Therefore, the accurate and timely detection of chicken diseases is critical to reduce economic losses and prevent the spread of diseases. In this study, we propose a method for classifying chicken diseases using a convolutional neural network (CNN). The proposed method involves preprocessing the chicken images, building and training a CNN model, and evaluating the performance of the model. The dataset (...) used in this study comprises chicken images of three different diseases: Newcastle disease, avian influenza, and infectious bursal disease. The proposed method achieved an overall F1-score of 99.04% in classifying the chicken diseases. The results demonstrate the effectiveness of using CNN in classifying chicken diseases and provide a promising approach for early detection and diagnosis of poultry diseases. (shrink)

As a contribution to a wider discussion on moral discernment in theological anthropology, this paper seeks to answer the question “What is the impact of mental illness on an individual’s ability to make moral decisions?” Written from a clinical psychiatric perspective, it considers recent contributions from psychology, neuropsychology and imaging technology. It notes that the popular conception that mental illness necessarily robs an individual of moral responsibility is largely unfounded. Most people who suffer from mental health problems do not lose (...) the capacity to make moral decisions, and mental illness on its own rarely explains anti-social or criminal behaviour. Moreover, the assumptions of some scientists, that recent developments in neuropsychology and brain imaging suggest biological determinism, must be treated with caution. (shrink)

Abstract: Context: grapevine leaves are an important agricultural product that is used in many Middle Eastern dishes. The species from which the grapevine leaf originates can differ in terms of both taste and price. Method: In this study, we build a deep learning model to tackle the problem of grape leaf classification. 500 images were used (100 for each species) that were then increased to 10,000 using data augmentation methods. Convolutional Neural Network (CNN) algorithms were applied to build this model (...) specifically using the pre-trained model on top of the VGG16 architecture. Then, dense layers were added to classify the output of the Convolutional layers and classify outputs to the five classes (species) the leaf belonged to. Results: It was found that feature extraction without fine-tuning the convolutional layers yielded poor results, about 86% accuracy, while training the whole network along with some data preprocessing gave the best results, about 99.45% accuracy on the testing dataset. Conclusions: The proposed CNN model is an effective one for the problem of classification of grape leaf species. (shrink)

Abstract: Artificial Intelligence (AI) is rapidly becoming a cornerstone of modern healthcare, offering unprecedented capabilities in diagnostics, treatment planning, patient care, and healthcare management. This paper explores the transformative impact of AI on the healthcare sector, examining how it enhances patient outcomes, improves the efficiency of medical practices, and introduces new ethical and operational challenges. By analyzing current applications such as AI-driven diagnostic tools, personalized medicine, and hospital management systems, this paper highlights the significant advancements AI has brought to the (...) field. However, the integration of AI also raises concerns related to data privacy, algorithmic bias, and the displacement of healthcare professionals. This study provides a comprehensive overview of these developments, offering insights into the future potential of AI in revolutionizing healthcare while addressing the ethical considerations that must accompany its adoption. The findings suggest that while AI holds the promise of transforming healthcare delivery, careful consideration of its implications is essential to ensure equitable and effective implementation. (shrink)

I wish to defend the claim that given the content and structure of any moral theory we are likely to find palatable, there is no way of uniquely breaking down that theory into either consequentialist or deontological elements. Indeed, once we examine the actual structure of any such theory more closely, we see that it can be classified in either way arbitrarily. Hence if we ignore the metaethical pronouncements often made by adherents of the consequentialist-deontological distinction, we are quickly led (...) to the conclusion that this distinction contributes nothing of consequence to an understanding of moral theory. I will try to show that there are basically two reasons for this. First, what we mean by the terms endemic to the consequentialist-deontological distinction have no unique references to particular states of affairs in actual cases of moral decision making. Hence we may justify any such concrete moral decision by reference to typically consequentialist or deontological reasoning indifferently. Second, scrutiny of actual and viable moral theories reveals a much finer-grained structure than the consequentialist-deontological taxonomy can capture. And it is this structure, rather than simple attention to consequences or principles, that determines practical moral decision making. We would thus do better to develop the richer vocabulary of causes and constituents, goals and effects, states and events (mental, social, or physical). So in the end, the consequentialist-deontological distinction is irrelevant at the normative level of actual moral reasoning, whereas at the metaethical level it crudely schematizes two opposing types of dummy theory, neither of which is convincing, upon reflection, to any practicing moral philosopher. (shrink)

Abstract: The integration of Artificial Intelligence (AI) into medical imaging represents a transformative shift in healthcare, offering significant improvements in diagnostic accuracy, efficiency, and patient outcomes. This paper explores the application of AI technologies in the analysis of medical images, focusing on techniques such as convolutional neural networks (CNNs) and deep learning models. We discuss how these technologies are applied to various imaging modalities, including X-rays, MRIs, and CT scans, to enhance disease detection, image segmentation, and diagnostic support. Additionally, the (...) paper addresses the challenges faced in AI-driven medical imaging, including data quality, model interpretability, and ethical considerations. By examining recent advancements and real-world case studies, this paper provides insights into the current state of AI in medical imaging and its potential future directions. The findings highlight the ongoing evolution of AI technologies and their crucial role in advancing medical diagnostics and treatment strategies. (shrink)

Most readers believe that it is difficult, verging on the impossible, to extract concrete prescriptions from the ethics of Emmanuel Levinas. Although this view is largely correct, Levinas’ philosophy can, with some assistance, generate specific duties on the part of legal actors. In this paper, I argue that the fundamental premises of Levinas’ theory of justice can be used to construct a prohibition against capital punishment. After analyzing Levinas’ concepts of justice, responsibility, and interruption, I turn toward his scattered remarks (...) on legal institutions, arguing that they enable a sense of interruption specific to the legal domain. It is here that we find the conceptual resources most important to my Levinasian abolition. I argue that the interruption of legal justice by responsibility implies what I call the principle of revisability. The principle of revisability states a necessary condition of just legal institutions: To be just, legal institutions must ensure the possibility of revising any and all of their rules, principles, and judgments. From this, the argument against capital punishment easily follows. Execution is a legal act, perhaps the only legal act, that cannot be undone. An application of the principle of revisability to this fact leads to the conclusion that legal institutions cannot justly impose capital punishment. After defending these points at length, I conclude with some observations on the consequences of the principle of revisability for law more generally. (shrink)

Abstract: Artificial Intelligence (AI) is transforming the agricultural sector, enhancing both productivity and sustainability. This paper delves into the impact of AI technologies on agriculture, emphasizing their application in precision farming, predictive analytics, and automation. AI-driven tools facilitate more efficient crop and resource management, leading to higher yields and a reduced environmental footprint. The paper explores key AI technologies, such as machine learning algorithms for crop monitoring, robotics for automated planting and harvesting, and data analytics for optimizing resource use. Additionally, (...) it discusses challenges like data privacy, barriers to technology adoption, and the ethical implications of AI in farming. Integrating AI into agricultural practices holds the promise of greater efficiency and sustainability, paving the way for future innovations. (shrink)

This article brings an account of reasonable expectations to bear on the question of when unauthorized immigrants have a right to be regularized—that is, to be formally guaranteed freedom from the threat of deportation. Contrary to the current literature, which implicitly relies on a flawed understanding of reasonable expectations, this article argues that only those unauthorized immigrants who have both been tacitly permitted by the state despite lacking formal authorization and have remained long enough to develop deep social roots in (...) the state have a right to regularization. (shrink)

The first part of this chapter defends the claim that the over-incarceration of disadvantaged social groups is unjust. Many arguments for penal reform are based on the unequal distribution of punishment, most notably disproportionate punishment of the poor and people of color. However, some philosophers use a noncomparative conception of desert to argue that the justice of punishment is independent of its distribution. On this view, which has significant influence in 14th Amendment jurisprudence, unequal punishment is not unjust. After detailing (...) the “noncomparativist challenge,” this chapter argues that Levinasian conceptions of desert enable a theory of penal justice according to which comparative considerations are essential. In so doing, it shows that the noncomparativist challenge can be met. The chapter concludes by considering whether Levinasian conceptions of desert and responsibility show members of socially advantaged groups to be more blameworthy for their wrongdoing than members of disadvantaged groups. (shrink)

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

Critics have recently argued that reliabilists face trade-off problems, forcing them to condone intuitively unjustified beliefs when they generate lots of true belief further downstream. What these critics overlook is that reliabilism entails that there areside-constraintson belief-formation, on account of which there are some things you should not believe, even if doing so would have very good epistemic consequences. However, we argue that by embracing side-constraints the reliabilist faces a dilemma: she can either hold on to reliabilism, and with it (...) aforementioned side-constraints, but then needs to explain why we should allow the pursuit of justification to get in the way of the acquisition of true belief; or she can deny that there are side-constraints – and in effect give up on reliabilism. We'll suggest that anyone moved by the considerations that likely attract people to reliabilism in the first place – the idea the true belief is good, and as such should be promoted – should go for the second horn, and instead pursue a form ofepistemic utilitarianism. (shrink)