This thesis considers the notion of intergenerational justice. I consider intertemporal justice largely through the lens of John Rawls’s theory of justice. Nonetheless, Rawls incorrectly gives priority to the principle of reciprocity in his theory. I correct Rawls’s misunderstanding concerning reciprocity. I also discuss the often-overlooked importance of natural duties to Rawls’s theory. I add the condition of vulnerability to Rawls’s circumstances of justice. By making these changes I give priority to impartiality in Rawls’s theory, remove the difficulties created by (...) Rawls’s present-time-of-entry interpretation, remove the need for Rawls’s motivational assumption, and remove the chance-timing of a person’s birth as an arbitrary contingency and basis for bias in the decision-making of those behind the veil of ignorance. (shrink)

Nietzsche and Foucault famously employ a philosophical method of “genealogy” and apply it to the realm of morality in particular. In this article I would like to do two main things: I will begin by offering a contribution toward a sort of “genealogy of genealogy,” that is, toward an account of how the method emerged historically. I will then give an explanation of how the method is supposed to work. In a subsequent, companion article in this journal, “Genealogy and Morality,” (...) I will discuss the method’s application to morality in some concrete ways. (shrink)

In a previous article in this journal, “Genealogy,” I offered a sort of “genealogy of genealogy,” an account of the method’s development, according to which it mainly grew, not from English or French antecedents, but out of a German tradition that began with Herder and then continued with Hegel before eventually culminating in Nietzsche himself. [...] Presupposing this account of the method of genealogy, the present article will consider the method in relation to one of its most important areas of (...) application: morality. (shrink)

My thanks to Anik Waldow and Charles Wolfe for their work in producing a volume celebrating our late dear friend Stephen Gaukroger (1950-2023): The Shaping of the Sciences: Essays in Honour of Stephen Gaukroger, edited by Charles Wolfe and Anik Waldow (Springer, 2025). This is my contribution, pp. 187-194 / ISBN: 978-3-031-76036-5.

Anglophone attention to issues of race and racism, with particular attention to Kant and other members of the German Enlightenment, has long been hampered by a lack of critical editions in English. While this is no longer significantly true for Kant studies, it continues to be the case for many of the most relevant works by Georg Forster and Christoph Meiners. This is a problem for philosophers working exclusively in English, and it is one that is only exacerbated by (...) the field’s general lack of interest in not just the intellectual history of philosophy and its figures, but in analyses published in languages other than English today. Ahistorical, monolinguistic approaches become especially problematic, however, when it comes to the philosophical analysis of race and racism, given the need to approach such topics from multiple angles at once—historical, political, cultural, economic, and legal—a fact that is no less true for scholarship on the figures of the eighteenth century than it is for the study of the present one. My aim in what follows therefore is to fill in a bit of the bigger picture, the specific context within which a writer like Georg Forster and his cohort were working, in order to better frame the kinds of specialised discussions of Kant’s philosophy of race that we find today. (shrink)

A long critical notice of Michael Forster's recent book, "Kant and Skepticism." We argue that Forster's characterization of Kant's response to skepticism is both textually dubious and philosophically flawed. -/- .

"...T S Eliot was unimpressed by Freud. Eliot preferred the more approachable Roger Vittoz. It was only Scofield Thayer, who in his prolonged therapy with Sigmund Freud can be said to have brought anything Freudian in the classically psychoanalytic sense to Modernism." This is from the review. The review of the book is contrarian as the book under review is. The salient points of the book are interrogated in this review.

This volume assembles 18 of Eckart Förster’s most important essays, written between 1987 and 2022, all of which touch upon the theme of limits of cognition. Among the issues tackled are Kant’s Opus Postumum, Goethe’s project of a scientia intuitiva or science of the intuitive understanding, the significance of §§76–77 of the third Critique for post-Kantianism, the case for Hölderlin’s authorship of the Oldest System-Programme of German Idealism, and Hegel’s early ideas on logic and phenomenology. In this review, I discuss (...) the volume focusing on three aspects. (i) I give a brief outline of its structure and goals; (ii) I investigate some of its highlights and central themes; and (iii) I place Förster’s picture of Kant and post-Kantianism within current scholarship and confront it with an alternative interpretive option: a reading of Kant as concerned with non-contrastive limits of cognition and intelligibility. (shrink)

The present paper has two objectives. First, it explicates the story, initially portrayed by Eckart Förster (2012), that allegedly philosophy started with publishing of Kant’s CPR and ended a quarter century later when Hegel’s Phenomenology of Mind appeared. We address the questions in what sense this happened and how is this development to be interpreted? Secondly, we demonstrate that similar radical transition from new, “true” beginning of philosophy to its apparent finishing took place in two other, high profile occasions in (...) the history of Western philosophy, in two key points of its development: in the years 390–365 BC, between the early and the late Plato, and between 1898 and 1922, between Russell and Wittgenstein’s Tractatus. These three short-lived, spectacular transitions from philosophy’s alleged start to its alleged ultimate accomplishment give us good reason to speak about a specific 25-years principle in philosophy. In a peculiar way, this principle reveals philosophy’s true nature. (shrink)

This paper offers a new interpretation of Kant's relationship with skepticism in the Groundwork for the Metaphysics of Morals. My position differs from commonly held views in the literature in two ways. On the one hand, I argue that Kant's relationship with skepticism is active and systematic (contrary to Hill, Wood, Rawls, Timmermann, and Allison). On the other hand, I argue that the kind of skepticism Kant is interested in does not speak to the philosophical tradition in any straightforward sense (...) (contrary to Forster and Guyer). On my reading, Kant takes up a skeptical method in the Groundwork as a way of exposing certain obstacles in our ordinary and philosophical thinking about morality. The central obstacle he is interested in is practical in character, arising from a natural tendency we have to rationalize against the moral law. In attempting to resolve this tendency, I argue, the Groundwork turns out to have a profoundly educative task. (shrink)

In his 1802 article for the Critical Journal, “Relationship of Skepticism to Philosophy,” Hegel attempts to articulate a form of skepticism that is “at one with every true philosophy.” Focusing on the priority that Hegel gives to ancient skepticism over its modern counterpart, Michael Forster and other commentators suggest that it is Pyrrhonism that Hegel views as one with philosophy. Since Hegel calls attention to the persistence of dogmatism even in the work of Sextus Empiricus, however, I argue that (...) it is only a sublated form of Pyrrhonism, what in the Phenomenology of Spirit he calls “self-completing skepticism,” that Hegel takes to be part of genuine philosophical cognition. In this way, I hope to show that the insight that motivates Hegel’s engagement with skepticism in the 1802 essay comes to inform the philosophical itinerary of the Phenomenology of Spirit. (shrink)

Focusing on Immanuel Kant's lectures on anthropology, the essay endeavors to address long-standing concerns regarding both the relationship between these empirical investigations and Kant's better known universalism, and more pressingly, between Kant's own racism on display in the lectures, and his simultaneous promotion of a universal moral theory that would unhesitatingly condemn such attitudes. -/- Reprinted in: 'Philosophies of Difference: Nature, Racism, and Sexuate Difference' edited by R. Gustafsson, R. Hill, and H. Ngo (Routledge, 2019), pp. 125-144.

I am not going to solve in this paper the plethora of problems and riddles surrounding Spinoza’s scientia intuitiva, but I do hope to break some new ground and help make this key doctrine more readily understandable. I will proceed in the following order (keep in mind the word ‘proceed’). I will first provide a close preliminary analysis of the content and development of Spinoza’s discussion of scientia intuitiva in the Treatise on the Emendation of the Intellect and the Ethics. (...) In the second part, I will address two closely related questions which have drawn the attention of many readers: (i) Is scientia intuitiva a cognition that is inferential? and (ii) Is scientia intuitiva a kind of cognition that is closely tied to causation? To the surprise of many, I will argue that Spinoza’s intuitive knowledge is both inferential and causal (in a certain rigid sense of ‘inferential’ and ‘causal’ to be explained below). In the third and final part, I will explain Spinoza’s preference for scientia intuitiva and his frequent use of mathematical examples, and then attempt to map the major remaining questions and problems surrounding the doctrine. (shrink)

Kant's response to scepticism in the Critique of Pure Reason is complex and remarkably nuanced, although it is rarely recognized as such. In this paper, I argue that recent attempts to flesh out the details of this response by Paul Guyer and Michael Forster do not go far enough. Although they are right to draw a distinction between Humean and Pyrrhonian scepticism and locate Kant's response to the latter in the Transcendental Dialectic, their accounts fail to capture two important (...) aspects of this response. The first is that Kant's response to Pyrrhonian scepticism is also a response to Hume. The second is that aspects of this response are decidedly positive. In particular, I argue (1) that Kant believed Hume's scepticism manifested important elements of Pyrrhonian scepticism and (2) that both Pyrrhonian scepticism and Hume had a significant positive influence on the development of the Transcendental Dialectic. (shrink)

György Lukács’s Marxist phase is usually associated with his passage from neo-Kantianism to Hegelianism. Nonetheless, Nietzschean influences have been covertly present in Lukács’s philosophical development, particularly in his uncompromising distaste for the bourgeois society and the mediocrity of its quotidian values. A closer glance at Lukács’s corpus discloses that the influence of Nietzsche has been eclipsed by the Hegelian turn in his thought. Lukács hardly ever mentions the weight of Nietzsche on his early thinking, an influence that makes cameo appearances (...) throughout his lifetime writings. During the period of his adherence to a Stalinist approach to communism, his new subjectivity seems to be re-constituted through a disavowal of his earlier romantic anti-capitalism. Implicit in Lukács’s attack on Nietzsche in the Destruction of Reason (1952) is an acerbic reaction to the mute presence of the latter in his earlier thought. Apart from his ignorance of the unreliability of the collection of the Will to Power edited by Peter Gast and Elisabeth Förster-Nietzsche, his battle against the anti-proletariat Nietzsche in the Destruction is waged on a metaphysical, non-historical plain. Lukács’s pre-Marxist works (Soul and Form, On Poverty of Spirit, and The Theory of the Novel) in a sense betray the instance of a writer who writes most of someone where he omits his name. Thus perceived, Lukács’s early corpus lends itself to a symptomatic reading. -/- This essay seeks to extract the Nietzschean undercurrents of Lukács’s work through a reflection on the romantic anti-capitalist tendencies that the young Lukács shared with Nietzsche. For although it may appear that Nietzsche lacked a clear politics, his criticism of the bourgeois ethos as a structure based on debt/guilt [Schuld], and his critique of modern value-system and nihilism paved the way for the emergence of Lukács’s theory of reification. Nietzsche’s category of 'transvaluation of values’ suggests a total transfiguration of reality, a radical rupture with the ordinary state of things, and as such carries within itself a revolutionary promise. Drawing a distinction between political romanticism and romantic politics, I argue that romantic anti-capitalism contains a potential for the latter. The essay further traces the link between Lukács’s ‘romantic politics’ and the persistence of a thought of the tragic (a ‘tragic vision’) in his texts that, despite its temporary decline during his realist period, is undismissable in different constellations of his thought. (shrink)

On a very natural conception of sets, every set has an absolute complement. The ordinary cumulative hierarchy dismisses this idea outright. But we can rectify this, whilst retaining classical logic. Indeed, we can develop a boolean algebra of sets arranged in well-ordered levels. I show this by presenting Boolean Level Theory, which fuses ordinary Level Theory (from Part 1) with ideas due to Thomas Forster, Alonzo Church, and Urs Oswald. BLT neatly implement Conway’s games and surreal numbers; and a (...) natural extension of BLT is definitionally equivalent with ZF. (shrink)

Eighteenth-century German writers with broad interests in natural history, and in particular, in the kind of ethnographic reports typically included in travel and expedition narratives, had to be able to access and read the original reports or they had to work with translations. The translators of these reports were, moreover, typically forced more than usual into the role of interpreter. This was especially the case when it came to accounts wherein vocabulary did not exist or was at least not settled, (...) and more importantly where scientific understanding was uncertain or altogether lacking, a situation that could only make the creation of semantic categories all the more significant. With this state of affairs in mind, this essay concentrates on Immanuel Kant’s work to develop a specialised racial vocabulary, and does so in a manner that reveals the importance of Buffon’s account of variation as a resource for Kant, even as Kant sought to position the new vocabulary as an improved template for transforming taxonomy or Naturbeschreibung into a genuine historical science or Naturgeschichte. (shrink)

This essay lays out the historical case for a broader assessment of Kant’s relationship to Blumenbach by focusing first on Kant’s review of Herder in 1785 as the best lens through which to understand not only their respective theories of generation but indeed the specific motivation leading to Kant’s support for Blumenbach at all. The results of this inquiry will suggest that while Kant might have been interested in gaining the support of the rising star of the Göttingen medical faculty, (...) Blumenbach’s own theories did little to influence Kant’s approach to either generation-theory or race. (shrink)

Excerpt: In this essay I explore the nature of the necessity of historical development in Nietzsche’s genealogy of Judeo-Christian moral values. I argue that the progression of moral stages in Nietzsche’s study is ordered in such a way that the failure of each stage is logically and structurally necessary, that each failure structures the resultant system or paradigm, but that the historical manifestation of moral paradigms coinciding with predicted or projected theoretical structures is contingent upon a multitude of other historical (...) factors. Therefore, the systematic internal failures of moral stages allow for, but do not cause, successive events. (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.

The study aimed to identify the relationship between correcting the deviations in the measurement of performance and achieving the objectives of control and the performance of the job at the Islamic University in the Gaza Strip. To achieve the objectives of the research, the researchers used the descriptive analytical approach to collect information. The questionnaire consisted of (20) statements distributed to three categories of employees of the Islamic University (senior management, faculty members, their assistants and members of the administrative board). (...) A random sample of 314 employees was selected and 276 responses were retrieved with a recovery rate of 88.1%. The Statistical Analysis Program (SPSS) was used to enter, process, and analyze the data. The results of the study showed a positive relationship between correcting deviations in performance measurement and achieving the control objectives represented by the functional performance in the Islamic University from the point of view of the members (senior management, faculty and their assistants, and the administrative board), where the relative weight of all the paragraphs was (74.25%). The study recommended the need to ensure that the actual performance of the planned performance is matched and decisions are taken to correct the serious deviations and take the necessary measures in terms of retraining and change in regulations, wages and bonuses and punishment of the culprit, neglect and negligence by mistake. (shrink)

rtificial Intelligence (AI) is swiftly becoming a fundamental element in modern healthcare, bringing unparalleled capabilities in diagnostics, treatment planning, patient care, and healthcare management. This paper delves into AI's transformative impact on the healthcare sector, highlighting how it enhances patient outcomes, boosts the efficiency of medical practices, and introduces new ethical and operational challenges. Through an analysis of current applications such as AI-driven diagnostic tools, personalized medicine, and hospital management systems, the paper underscores the significant advancements AI has introduced to (...) the field. However, the integration of AI also presents concerns related to data privacy, algorithmic bias, and the displacement of healthcare professionals. This study provides a thorough overview of these developments, offering insights into AI's future potential to revolutionize healthcare while addressing the ethical considerations necessary for its responsible adoption. The findings suggest that while AI has the potential to transform healthcare delivery, careful consideration of its implications is essential for ensuring its equitable and effective implementation. (shrink)

Abstract: Lemons are an important fruit that have a wide range of uses and benefits, from culinary to health to household and beauty applications. Deep learning techniques have shown promising results in image classification tasks, including fruit quality detection. In this paper, we propose a convolutional neural network (CNN)-based approach for detecting the quality of lemons by analysing visual features such as colour and texture. The study aims to develop and train a deep learning model to classify lemons based on (...) their quality, evaluate the model's performance, compare it to traditional machine learning approaches, and identify key factors that affect the model's performance. The dataset used in the study consists of approximately 2533 images of lemons and an empty surface, divided into training, test, and validation data, and includes images of both good and bad quality lemons under different lighting conditions. The deep learning model achieved an accuracy of 99.74% on the test dataset and outperformed traditional machine learning approaches. The developed model has the potential to improve efficiency and accuracy in lemon quality control in the agriculture and food industry. (shrink)

Abstract: Artificial Intelligence (AI) has rapidly evolved, offering transformative capabilities for business decision-making. This paper explores how AI can be leveraged to enhance strategic decision-making in business contexts. It examines the integration of AI-driven analytics, predictive modeling, and automation to improve decision accuracy and operational efficiency. By analyzing current applications and case studies, the paper highlights the opportunities AI presents, including enhanced data insights, risk management, and personalized customer experiences. Additionally, it addresses the challenges businesses face in adopting AI, such (...) as data privacy concerns, integration issues, and the need for skilled personnel. The paper concludes with recommendations for effectively implementing AI solutions to maximize their benefits while navigating potential pitfalls. (shrink)

Abstract: Dates are the fruit of date palm trees, and it is one of the fruits famous for its high nutritional value. It is a summer fruit spread in the Arab world. In the past, the Arabs relied on it in their daily lives. Dates take an oval shape and vary in size from 20 to 60 mm in length and 8 to 30 mm in diameter. The ripe fruit consists of a hard core surrounded by a papery cover called (...) the tartar that separates the core from the fleshy part that is eaten. Historians disagreed about the place of its origin, so some historians expressed their belief that it had originated around the Arabian Gulf, and some of them say that the oldest known information about palm trees was in Babylon 4 thousand years ago BC. It is known about the ancient Egyptians using dates in wine. Dates contain a high nutritional value and are considered a basic food for man since ancient times. The fruits of dates are considered the highest fruits in containing sugars. These components vary according to the nature of the fruit, whether it is wet, semi-dry or dry, as well as according to the environmental conditions surrounding the trees. The components of the fruits also differ in different varieties and increase the percentage of sugars in dates is 70-78% of the fruit’s components. These sugars are characterized by their rapid absorption and transfer into the blood directly, digestion and burning. 10 dates (about 100 grams) per day provide a person with all his daily needs of magnesium, manganese, copper, sulfur and half of his needs of calcium and potassium. In this paper we presented a system that recognize the nine types of dates based on deep learning using python on Colab, and classifying using a dataset contain 1350 images. Our trained model achieved an accuracy of 99.44% on a proven test set. (shrink)

Abstract: Artificial Intelligence (AI) is revolutionizing the agricultural sector by enhancing productivity and sustainability. This paper explores the transformative impact of AI technologies on agriculture, focusing on their applications in precision farming, predictive analytics, and automation. AI-driven tools enable more efficient management of crops and resources, leading to improved yields and reduced environmental impact. The paper examines key AI technologies, including machine learning algorithms for crop monitoring, robotics for automated planting and harvesting, and data analytics for optimizing resource use. Additionally, (...) it addresses challenges such as data privacy, technology adoption barriers, and the ethical implications of AI in farming. By integrating AI into agricultural practices, the industry can achieve greater efficiency and sustainability, paving the way for future advancements. (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)

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)

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: Artificial Intelligence (AI) has rapidly advanced, offering significant potential to transform business decision-making. This paper delves into how AI can be harnessed to enhance strategic decision-making within business contexts. It investigates the integration of AI-driven analytics, predictive modeling, and automation, emphasizing their role in improving decision accuracy and operational efficiency. By examining current applications and case studies, the paper underscores the opportunities AI offers, including improved data insights, risk management, and personalized customer experiences. It also addresses the challenges businesses (...) face when adopting AI, such as data privacy concerns, integration difficulties, and the need for skilled professionals. The paper concludes by offering recommendations for successfully implementing AI solutions to maximize benefits while mitigating potential challenges. (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)

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)

The evolution of Intelligent Tutoring System (ITS) is the result of the amount of research in the field of education and artificial intelligence in recent years. English is the third most common languages in the world and also is the internationally dominant in the telecommunications, science and trade, aviation, entertainment, radio and diplomatic language as most of the areas of work now taught in English. Therefore, the demand for learning English has increased. In this paper, we describe the design of (...) an Intelligent Tutoring System for teaching English language grammar to help students learn English grammar easily and smoothly. The system provides all topics of English grammar and generates a series of questions automatically for each topic for the students to solve. The system adapts with all the individual differences of students and begins gradually with students from easier to harder level. The intelligent tutoring system was given to a group of students of all age groups to try it and to see the impact of the system on students. The results showed a good satisfaction of the students toward the system. (shrink)

Risk Management Strategies and Investment Behaviors are considered important factors in the investing activities of the retail investors. This study seeks to determine the relationship between Risk Management Strategies and Investment Behavior of Generation Z retail investors. The study is a correlational research and purposive sampling was used to select the respondents for this study. Cochran’s formula was utilized to determine the total sample size or total number of respondents. Spearman’s Rank-Order Correlation was employed to assess the significant relationship of (...) Risk Management Strategies and Investment Behaviors. Based on the results, it showed that risk management strategies have a significant relationship with one or more of the investment behaviors. Risk avoidance has a significant relationship with confirmation bias. Risk reduction has a significant relationship with all of the investment behaviors such as overconfidence, loss-aversion, recency bias, and confirmation bias. Risk transfer shows a significant relationship with only loss-aversion and confirmation bias. And lastly, risk acceptance also has a significant relationship with all of the investment behaviors. This study recommends exploring other types of behavioral biases under cognitive bias and emotional bias to determine their correlation with risk management strategies. Also, broadening the sample size, demographic scope, and geographic scope of the study can improve the generalizability of the study and provide a more comprehensive understanding of the relationship between investment behavior and risk management strategies. The researchers also recommend to utilize interviews and focus group discussions to gain an in-depth understanding of the underlying values and attitudes concerning investment behavior. (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)

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

Abstract: Fish are important for both nutritional and economic reasons. They are a good source of protein, vitamins, and minerals and play a significant role in human diets, especially in coastal and island communities. In addition, fishing and fish farming are major industries that provide employment and income for millions of people worldwide. Moreover, fish play a critical role in marine ecosystems, serving as prey for larger predators and helping to maintain the balance of aquatic food chains. Overall, fish play (...) a vital role in supporting human well-being and the health of our planet. . Fishes have a lots of types such that: Red Mullet, Sea Bass, Striped Red Mullet and Shrimp. Each of them has its own shape and characteristics that differ from other types. We proposed a system that recognize nine types of fishes using deep learning. We trained the model with a dataset that contain 9000 images that were slit into 6300 images for training, 1350 for validation and 1350 for testing. The proposed model achieved accuracy (99.68%), precision (99.69%), recall (99.68%), and f1-score (99.68%). This indicates that our proposed model can effectively predicate and classify different types of fish with very high accuracy. (shrink)

In this paper an Artificial Neural Network (ANN) model was used to help cars dealers recognize the many characteristics of cars, including manufacturers, their location and classification of cars according to several categories including: Buying, Maint, Doors, Persons, Lug_boot, Safety, and Overall. ANN was used in forecasting car acceptability. The results showed that ANN model was able to predict the car acceptability with 99.12 %. The factor of Safety has the most influence on car acceptability evaluation. Comparative study method is (...) suitable for the evaluation of car acceptability forecasting, can also be extended to all other areas. (shrink)

Sacrificial dilemmas such as the trolley problem play an important role in experimental philosophy (x-phi). But it is increasingly argued that, since we are not likely to encounter runaway trolleys in our daily life, the usefulness of such thought experiments for understanding moral judgments in more ecologically valid contexts may be limited. However, similar sacrificial dilemmas are experienced in real life by animal research decision makers. As part of their job, they must make decisions about the suffering, and often the (...) death, of many non-human animals. For this reason, a context-specific investigation of so-called “3R dilemmas” (i.e., dilemmas where there is a conflict between the principles of replacement, reduction, and refinement of the use of animals in research) is essential to improve the situation of both non-human animals and human stakeholders. An approach well suited for such investigation is experimental philosophical bioethics (“bioxphi”), which draws on methods similar to x-phi to probe more realistic, practical scenarios with an eye to informing normative debates and ethical policy. In this article, we argue for a need to investigate 3R dilemmas among professional decision-makers using the tools of bioxphi. In a first step, we define 3R dilemmas and discuss previous investigations of professionals’ attitudes in such cases. In a second step, we show how bioxphi is a promising method to investigate the whys and hows of professional decision-making in 3R dilemmas. In a last step, we provide a bioxphi template for 3R dilemmas, give recommendations on its use, explore the normative relevance of data collected by such means, and discuss important limitations. (shrink)

Abstract: The incorporation of Artificial Intelligence (AI) into educational technology has dramatically transformed learning through Intelligent Tutoring Systems (ITS). These systems utilize AI to offer personalized, adaptive instruction tailored to each student's needs, thereby improving learning outcomes and engagement. This paper examines the development and impact of ITS, focusing on AI technologies such as machine learning, natural language processing, and adaptive algorithms that drive their functionality. Through various case studies and applications, it illustrates how ITS have revolutionized traditional educational methods (...) and addresses the challenges and limitations, including data privacy and system biases. The discussion also covers future directions in ITS development, highlighting emerging trends and potential advancements. The goal is to provide a thorough understanding of how ITS use AI to enhance educational experiences and suggest avenues for future research in this evolving field. (shrink)

Abstract: Fast food refers to quick, convenient, and ready-to-eat meals that are usually sold at chain restaurants or take-out establishments. Fast food is often criticized for its unhealthy ingredients, such as high levels of salt, sugar, and unhealthy fats, and its contribution to the growing obesity epidemic. Despite this, fast food remains popular due to its affordability, convenience, and widespread availability. Many fast food chains have attempted to respond to these criticisms by offering healthier options, such as salads and grilled (...) chicken sandwiches, and by using more natural and locally sourced ingredients. The aim in this paper to propose a deep learning model for the classification of fast food dishes. The proposed model, Xception, was trained on natural images and was fine-tuned to make up the fast food meals. The researchers collected the Fast Food V2 dataset from Kaggle depository, the dataset, contained 20,000 images. The dataset has ten labels of food images comprised of Baked Potato, Burger, Crispy Chicken, Donut, Fries, Hot Dog, Pizza, Sandwich, Taco, and Taquito. The dataset was split into three sets: training, validation and testing. The accuracy, F1-score, recall, precision on the separate test set showed that classification of fast food was accuracy (95.13%), Precision (95.34%), Recall (95.13%), and F1-Score (95.14%). (shrink)

Abstract: Classifying sea animals is an important problem in marine biology and ecology as it enables the accurate identification and monitoring of species populations, which is crucial for understanding and protecting marine ecosystems. This paper addresses the problem of classifying 19 different sea animals using convolutional neural networks (CNNs). The proposed solution is to use a pretrained MobileNetV2 model, which is a lightweight and efficient CNN architecture, and fine-tune it on a dataset of sea animals. The results of the study (...) show that the fine-tuned MobileNetV2 model is able to achieve an accuracy of 85% on the classification task, which is competitive with the state-of-the-art methods. Additionally, the study also found that data augmentation and regularization techniques such as dropout were important for preventing overfitting and improving the performance of the model. This study demonstrates the potential of using pretrained models and efficient CNN architectures for classifying sea animals, and it provides insights into the challenges and best practices for solving this important problem in marine biology and ecology. (shrink)

Abstract: In this study, we explore the challenge of identifying and preventing diseases in apple trees, which is a popular activity but can be difficult due to the susceptibility of these trees to various diseases. To address this challenge, we propose the use of Convolutional Neural Networks, which have proven effective in automatically detecting plant diseases. To validate our approach, we use images of apple leaves, including Apple Rot Leaves, Leaf Blotch, Healthy Leaves, and Scab Leaves collected from Kaggle which (...) is part from the Plant Village dataset. We generate a comprehensive training dataset using techniques such as image filtering, compression, and generation. Our model achieves impressive accuracy scores for all classes, with an overall accuracy of 99.93% on a dataset of 10,000 labeled images . (shrink)

Academic excellence and intelligence are commonly lauded as commendable attributes synonymous with success. However, a disconcerting trend has surfaced within educational institutions, challenging the prevailing narrative of scholastic accomplishment—smart shaming. This research delves into the increasing concern of smart shaming within educational settings, particularly at Immaculate Conception College of Balayan, Inc., questioning the predominant emphasis on academic excellence and intelligence. A qualitative case study design, along with judgmental sampling, was employed to examine fifteen (15) student leaders who had experienced smart (...) shaming on campus. Thematic analysis revealed that sarcastic remarks including "edi wow," "Okay ikaw na matalino," "bidabida," and "sipsip" were a prevalent manifestation of smart shaming, adversely affecting emotional well-being, academic and leadership prowess, mental health, and self-perception. Coping mechanisms, predominantly centered around ignoring and focusing on goals, were identified. The findings underscore the imperative for educators to remain vigilant regarding instances of smart shaming in classrooms, promoting open communication to ensure student well-being. Additionally, guidance counselors play a pivotal role in aiding students in effectively navigating the repercussions of smart shaming. This study advocates for proactive programs and interventions to address and alleviate the deleterious effects of smart shaming on students. (shrink)

Abstract: Tomatoes are among the most popular vegetables in the world due to their frequent use in many dishes, which fall into many varieties in common and traditional foods, and due to their rich ingredients such as vitamins and minerals, so they are frequently used on a daily basis, When we focus our attention on this vegetable, we must also focus and take into consideration the diseases that affect this vegetable, a deep learning model that classifies tomato diseases has been (...) proposed. The aim of this paper is to diagnose tomato diseases based on a dataset containing 11000 picture and 11 classes. The model gave the final accuracy test with Accuracy (99.87%), F1-score (99.87%), Recall (99.87%), and Precision (99.88%) in an estimated time 1.36 second, as with these results it proved its effectiveness and good ability in the classification of the testing data. (shrink)

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

Abstract: 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)

In this paper an Artificial Neural Network (ANN) model was used to help cars dealers recognize the many characteristics of cars, including manufacturers, their location and classification of cars according to several categories including: Make, Model, Type, Origin, DriveTrain, MSRP, Invoice, EngineSize, Cylinders, Horsepower, MPG_Highway, Weight, Wheelbase, Length. ANN was used in prediction of the number of miles per gallon when the car is driven in the city(MPG_City). The results showed that ANN model was able to predict MPG_City with 97.50 (...) % accuracy. The factor of DriveTrain has the most influence on MPG_City evaluation. Similar studies can be carried out for the evaluation of other characteristics of cars. (shrink)

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