This paper explores how the diagnosis of mental disorder may affect the diagnosed subject’s self-concept by supplying an account that emphasizes the influence of autobiographical and social narratives on self-understanding. It focuses primarily on the diagnoses made according to the criteria provided by the Diagnostic Statistical Manual of Mental Disorders (DSM), and suggests that the DSM diagnosis may function as a source of narrative that affects the subject’s self-concept. Engaging in this analysis by appealing to autobiographies and memoirs written by (...) people diagnosed with mental disorder, the paper concludes that a DSM diagnosis is a double-edged sword for self- concept. On the one hand, it sets the subject’s experience in an established classificatory system which can facilitate self-understanding by providing insight into subject’s condition and guiding her personal growth, as well as treatment and recovery. In this sense, the DSM diagnosis may have positive repercussions on self-development. On the other hand, however, given the DSM’s symptom-based approach and its adoption of the Biomedical Disease model, a diagnosis may force the subject to make sense of her condition divorced from other elements in her life that may be affecting her mental- health. It may lead her frame her experience only as an irreversible imbalance. This form of self-understanding may set limits on the subject’s hopes of recovery and may create impediments to her flourishing. (shrink)

his article develops a set of recommendations for the psychiatric and medical community in the treatment of mental disorders in response to the recently published fifth edition of the Diagnostic and Statistical Manual of Mental Disorders, that is, DSM-5. We focus primarily on the limitations of the DSM-5 in its individuation of Complicated Grief, which can be diagnosed as Major Depression under its new criteria, and Post-Traumatic Stress Disorder (PTSD). We argue that the hyponarrativity of the descriptions of these disorders (...) in the DSM-5, defined as the abstraction of the illness categories from the particular life contingencies and personal identity of the patient (e.g., age, race, gender, socio-economic status), constrains the DSM-5's usefulness in the development of psychotherapeutic approaches in the treatment of mental disorders. While the DSM-5 is useful in some scientific and administrative contexts, the DSM's hyponarrativity is problematic, we argue, given that the DSMs are designed to be useful guides for not only scientific research, but also for the education of medical practitioners and for treatment development. our goal therefore is to offer suggestions for mental health practitioners in using the DSM-5, so that they can avoid or eliminate the problems that may stem from the limitations of hyponarrativity. When such problems are eliminated, we believe that effective psychotherapeutic strategies can be developed, which would be successful in repairing the very relationships that are strained in mental disorder: the patient's relationship to herself, her physical environment, and her social environment. (shrink)

, Looping Effects, the Self, Psychopathology.

Post-classical period witnessed intense debates on aspects of the Avicennan theory of science. Among them one set of discussions concerned the issue of subject matter (mabāhith al-mawdūʿ) in a science. They were raised by Ṣadr al-Sharīʿa (d. 747/1346) in the introduction of his al-Tawḍīh, a commentary on his legal theory text al-Tanqīḥ. Therein, he raised three questions: (1) whether the subject matter of a science can be multiple, (2) what restricting subject matter of a science means, and (3) whether one (...) thing can be the subject matter of multiple sciences. Taftāzānī (d. 792/1390), a proponent of the Avicennan theory, objected to Ṣadr al-Sharīʿa’s positions in his al-Talwīḥ, the most well-known supercommentary on al-Tawḍīh. The paper analyzes this debate on the issue of subject matter in sciences, and thus sheds light on the reception of an important aspect of the Avicennan theory of science in the postclassical period. (shrink)

There are roughly two main understanding in philosophy of science: Epistemology of Science and Metaphysics of Science. It is examined that some concept such as Laws of Nature, Causation, Time and Space into the metaphysics of Science. In this paper, it has been studied laws of nature which is one the most important subjects in metaphysics of science. Let’s think outside the box, there are three significant views about laws of nature; Regularity Theory, Necessitation Theory and Dispositional Essential views. It (...) has been worked the views of David Lewis in regularity theory. In the section of nomic necessitation we have been scrutinised the arguments put forward by David Armstrong and finally the last section; it has been discussed Alexander Bird’s views of dispositional essentialism comparing with the other two aspects. (shrink)

In Nicomachean Ethics X.7, Aristotle argues that perfect happiness consists in contemplation alone. The question that I want to take up in this essay is whether the superiority of contemplative life fits with Aristotle’s argument for the self-sufficiency of the political life, according to which politics can lead us to happiness without being guided by philosophical knowledge of the highest sort. My basic argument is that, paradoxical as it may seem, Aristotle is led to acknowledge that contemplative life is superior (...) to political life by the same strand of argumentation which makes him plea for the self-sufficiency of the political life in the first place. In order to show how this argument unfolds, I take my point of departure from Aristotle’s analysis of phronēsis as stated in Nicomachean Ethics VI and bring it to bear on his discussion of the respective virtues of the contemplative and political ways of life in Politics VII. (shrink)

Metaphysics, one of the most venerable branches of philosophy, investigates the fundamental nature of being and existence, as well as the structure and laws of reality. This field, significantly shaped by the works of Plato and Aristotle, attributes truth either to universals (Plato’s perspective) or to the essences of particulars (Aristotle’s perspective). This paper explores Neo-Aristotelian metaphysics, integrating and reinterpreting Aristotle’s classical metaphysical understanding in contemporary philosophical discussions. Neo-Aristotelian metaphysics reconfigures Aristotle’s classical concepts in light of modern scientific and philosophical (...) developments. In this context, the approaches of Ellis’s "Scientific Essentialism," Oderberg’s "Real Essentialism," and Bird’s "Dispositional Essentialism" are examined. Dispositional essentialism posits that the essences of entities can be defined by their dispositions and capacities. Alexander Bird argues that natural laws reflect the dispositions of entities, explaining how entities behave under certain conditions. Neo-Aristotelian metaphysics bridges metaphysical realism and naturalism by emphasizing the essences and natures of entities. This paper investigates the principles of dispositional essentialism and Neo-Aristotelian metaphysics, highlighting their contributions and significance in contemporary metaphysical debates. Furthermore, it underscores that the prominence of these approaches today results from their successful integration of modern scientific findings with classical metaphysical principles. By focusing on the essences and potentialities of entities, Neo-Aristotelian metaphysics and dispositional essentialism offer a more comprehensive and coherent metaphysical perspective. These approaches reflect modern philosophy's dynamic nature while revealing classical thought's timeless value. Keywords: Neo-Aristotelianism, Dispositional Essentialism, Metaphysics of Science, Regularity, Laws of Nature. (shrink)

XIX. yüzyılın ilk yarısında Auguste Comte tarafından sistemleştirilen pozitivizm akımı, deneye ve gözleme dayalı bilginin, tek geçerli bilgi türü olacağı varsayımından yola çıkan bir düşünce sistemidir. Pozitivizmi hazırlayan nedenlerin başında Fransız İhtilali ve aydınlanma düşüncesi yer almaktadır. Pozitivizmin Osmanlı düşüncesine girişi, devletin en buhranlı dönemini yaşadığı XIX. Yüzyıla denk gelir. Islahat hareketlerinin hız kazandığı, buna bağlı olarak batıcılık düşüncesinin iyiden iyiye hissedildiği bu yüzyılda, batı kaynaklı düşünce akımları da Osmanlı düşüncesinde kendilerine yer bulmaya başlamışlardır. Batılaşma çerçevesi içerisinde Fransa’ya gönderilen öğrenciler (...) ve tercüme eserler vasıtasıyla kendisini ortaya koyan pozitivizm, dönemin birçok düşünürünü etkilemiştir. Pozitivizmden etkilenen düşünürlerden birisi olarak Abdullah Cevdet, siyasi ve kültürel birçok alanda düşüncelerini bu doğrultuda dile getirmiştir. Cevdet’in düşünceleri başta yaşadığı dönem olmak üzere, kendisinden sonra da günümüze kadar ulaşmış ve pozitivist-materyalist cenahta kendisine yer bulmuştur. Halifelik müessesesini bünyesinde barındıran bir imparatorluk olarak Osmanlı’nın, pozitivist-materyalist görüşleri benimseme eğiliminde çok da istekli bir eğilim sergilemediği düşünülmektedir. Tüm eleştirilere ve kabullenememelere rağmen Abdullah Cevdet ve pozitivist fikirleri son dönem Osmanlı düşüncesinde sağladığı fikri dinamizm sebebiyle, düşünce dünyamız açısından olumlu bir etkiye sahip olmuştur. (shrink)

In this paper, I aim to explore Lewis’s best system analysis and how it can accommodate laws with exceptions. The Best System Account has been introduced to provide an alternative view for both minimalist and counterfactual theories of regularities. Simple regularity theory faces problems in which there is some generalization that seems to be a law or some regularities that are established accidentally. It tries to exclude the accidental generalization from the account. However, the best system analysis can solve the (...) problem of how to distinguish between laws and accidents. (shrink)

The principle of causation is a highly significant concept in the philosophy of science. When we contemplate why the events we encounter in nature occur, we discover the existence of this principle. However, should this principle be interpreted as a product of the knowing subject or as a tool for understanding the regularity of nature independent of the subject's mental production? This study will be shaped by the views of two philosophers (Hume and Kant) who have thought about the principle (...) of causation and will argue that the laws of nature, including this principle, serve as a means to comprehend that nature has a regular structure. Based on the premise that nature is orderly and independent of the human mind, such an approach has become more intriguing in contemporary approaches than the approach that transforms causation into a categorical form. While the compatibility of the human mind with the laws of nature seems important for understanding nature, it is evident that such principles would continue to maintain regularity in nature even in the event of the extinction of the human race. The study aims to shape the position of the principle of causation through the concepts of idea and nature, based on the assumption that nature is in regularity and that we can comprehend this regularity through natural laws like causation. At the same time, it provides details on Hume and Kant's understanding of causation. It summarizes the current causation debate in contemporary philosophy of science through the Humean literature. Keywords: Causation, idea, mind, nature, category, Hume, Kant. (shrink)

Zihin felsefesinin varlığı felsefenin ilk ortaya çıktığı dönemden günümüz felsefesine kadar geniş bir zaman dilimine sahiptir. Zihin felsefesi akademik bir disiplin olarak adından 17. Yüzyıldan itibaren söz ettirmiş olmasına rağmen, bu alanda ele alınan konular Antik Yunan’dan beri tartışılagelmiştir. İnsan kendisi ve çevresindeki dünyanın gerçekliğini sorgulamaya başladığında zihin, bu gerçekliğe anlam kazandırmıştır. Özne ve nesnenin birbirine zıt ve ancak bir o kadar da birbiri için oluşu zihin-beden olgusu içinde düalist ve monist anlam barındırmaktadır. Monist düşüncede kendi içinde önemli görülen, eleyici (...) materyalizm öne çıkmaktadır. Zihnin bileşenlerinin, zihinsel yapının algı, duygu ve düşüncenin var olmadığını savunmaktadırlar. D. (shrink)

In The Context of Laws of Nature Structural Humeanism vs. Classical Humeanism -/- In the context of the laws of nature, philosophers of science have developed some views in order to adopt an attitude towards recurring events in nature. In this respect, it has been discussed whether there is any driving force underlying the regular behaviours and movements we encounter in nature, and two approaches have emerged as a result of the discussion: A view that there are certain driving forces (...) or causal relations in the ground, and an opposing view that claims that there are no causal relations in the ground, but there are regularities in nature. Views such as the latter are generally described as the Humean view. Such views are also called regularity theories. Throughout this article, the statements referred to as regularity are characterised as the Humean view. Since the article will be centred on the Humean view, views such as the first view, such as dispositional essentialism or structural realism, are not the concern of this article. The article favours the Structural Humean approach over the classical Humean approach. The classical Humean approach is centred on the views of David Lewis and is concerned with distinguishing between laws of nature seen as accidental generalisations and regularities. While it tries to make such a distinction by constructing nature through a mosaic, the Structural Humean approach is an approach that develops Lewis’s claims and tries to shape nature with the concept of structure rather than mosaic. Thus, it is seen as an approach that provides more information than the Classical Humean approach in terms of creating a philosophical infrastructure for explaining nature in terms of modern physics. Through Psillos, Structural Humeanism tried to place the concept of natural pattern into the structure in order to gain metaphysical solidity and tried to bring the Structural Humean approach closer to the Structural Realism camp. Thus, the classically epistemologically important Humean approach has made a significant progress in positioning it on the realist wing. As a result of all these studies, the Structural Humean approach has been defended as a philosophical approach that offers useful arguments for modern physics compared to the Classical Humean approach. -/- Keywords: Humeanism, Regularity, Laws of Nature, Best System Account, Structural Humeanism, Natural Patterns. (shrink)

XIX. yüzyılın ilk yarısında A.Comte tarafından sistemleştirilen pozitivizm akımı, deneye ve gözleme dayalı bilginin, tek geçerli bilgi türü olacağı varsayımından yola çıkan bir düşünce sistemidir. Pozitivizmi hazırlayan nedenlerin başında Fransız İhtilali ve aydınlanma düşüncesi yer almaktadır. Pozitivizmin Osmanlı düşüncesine girişi, devletin en buhranlı dönemini yaşadığı XIX. Yüzyıla denk gelir. Islahat hareketlerinin hız kazandığı, buna bağlı olarak batıcılık düşüncesinin iyiden iyiye hissedildiği bu yüzyılda, batı kaynaklı düşünce akımları da Osmanlı düşüncesinde kendilerine yer bulmaya başlamışlardır. Batılaşma çerçevesi içerisinde Fransa’ya gönderilen öğrenciler ve (...) tercüme eserler vasıtasıyla kendisini ortaya koyan pozitivizm, dönemin birçok düşünürünü etkilemiştir. Pozitivizmden etkilenen düşünürlerden birisi olarak Abdullah Cevdet, siyasi ve kültürel birçok alanda düşüncelerini bu doğrultuda dile getirmiştir. Cevdet’in düşünceleri başta yaşadığı dönem olmak üzere, kendisinden sonra da günümüze kadar ulaşmış ve pozitivist-materyalist cenahta kendisine yer bulmuştur. Halifelik müessesesini bünyesinde barındıran bir imparatorluk olarak Osmanlı’nın, pozitivist-materyalist görüşleri benimseme eğiliminde çok da istekli bir eğilim sergilemediği düşünülmektedir. Tüm eleştirilere ve kabullenememelere rağmen Abdullah Cevdet ve pozitivist fikirleri son dönem Osmanlı düşüncesinde sağladığı fikri dinamizm sebebiyle, düşünce dünyamız açısından olumlu bir etkiye sahip olmuştur. (shrink)

Johan van der Walt offers a modest conception of liberal democratic law as a groundless modus vivendi, while at the same time backing up this conception with an ambitious inquiry into the long history of Western metaphysics and the ways in which it shaped legal imagination. There are two main dimensions to my criticism of Van der Walt’s work, and they exactly divide between its modesty and ambition. I contend that the understanding of liberal democratic law as a modus vivendi (...) is too modest insofar as it avoids normative justification, whereas the philosophical storyline is too ambitious insofar as it amplifies the extent to which questions of legal and political theory are embedded in questions of ontology. (shrink)

The mind has always been a peculiar and elusive subject, sparking controversial theories throughout the history of philosophy. The initial theorization of the mind dates back to Orphism, which formulated a dualistic structure of soul and body (Johansen, 1999) [1], laying the foundation for Greek dualism, introspection, and the rise of metaphysical idealism. This ill-empirical stance, especially after Plato’s idea of forms, led to inaccessible theoretical concepts concerning the investigation of the relationship between body and mind. Although diverse theories provide (...) broader insights into such matters, they can also hinder progress if based on unsound methodological hypothesis. The present study aims to employ a rational reexamination of the potentiality of the concepts of mind, using abductive inspection to present a valid grasp through the lens of cognitive neuroscience, philosophy, and interdisciplinary fields. This paper speculates through empirical deduction by analyzing the literature and theories on the concept of mind and its possible implications for singularity via transhumanism. In the contemporary world, humankind is on the edge of singularity due to the exponential growth predicted by Moore’s law (Moore 1965) [2]. While many considered singularity an abstract akin to science fiction, significant projections indicate that the accelerationist change has already begun, irreversibly. This advancement occurs not only in the degree of semiconductors in electronics but also in the amplification of human cognition through external devices enabling compound information flow via the world wide web. However, the conjunction of robotics and AI may outdo humankind in the contest for sovereignty soon due to their advantageous architecture in process design, which increases the systemic risk of extinction for humankind. Achieving total control over AI is unrealistic, as it requires complete supervision over all computers and information processes across the world, rendering any regulatory efforts to foresee augmentation futile. Consequently, this paper proposes the adoption of a neuro-robotic approach, enriched with AI, and implementation through biomedical applications on the human body to augment human cognition and physicality. This study aims to raise awareness against existential risks, emphasizing that reliance solely on AI powered computers could lead to annihilation. It also aims to highlight that biological mind and body is lagging behind the modern science to compete against Artificial Intelligence. Moreover, the foundation of Artificial General Intelligence (AGI) is an epistemic foundation for cognitive machinery enhancement that cannot be reversed once it emergence become apparent, as with Pandora’s Box. Technological singularity (Shanahan, 2015) [3], the point where technology is intelligently engineered to engineer its own sets by compounding all possible implementations of practical and theoretical information, is appearing on the horizon. Even if there is no human agency left on the soil of Earth, there is still no turning back at that point. Humankind must actively hold the key to bend this alteration in a way that aligns with its desires. Therefore, we propose, future for humankind lies with transhumanism. (shrink)

Philosophers and psychologists have advanced a plethora of explanations of the self in relation to narratives, positing varying degrees of connection between them. For some, narratives created by a subject about herself shape her self-constitution (Flanagan 1991; Fivush 1994). For others, they help the subject to participate in social cognition (Hutto 2008). Some represent narratives as merely one basis of personal identity and consider them cognitive tools used by the subject to construct self-concepts (Neisser 1997; Tekin 2011); others render (...) narratives the basis for self-constitution (Dennett 1992; MacIntyre 1981; Schechtman 1996). Some require that the subject create her ‘whole life narrative’ unifying her .. (shrink)

The purpose of this chapter is to describe what we see as several important new directions for philosophy of medicine. This recent work (i) takes existing discussions in important and promising new directions, (ii) identifies areas that have not received sufficient and deserved attention to date, and/or (iii) brings together philosophy of medicine with other areas of philosophy (including bioethics, philosophy of psychiatry, and social epistemology). To this end, the next part focuses on what we call the “epistemological turn” in (...) recent work in the philosophy of medicine; the third part addresses new developments in medical research that raise interesting questions for philosophy of medicine; the fourth part is a discussion of philosophical issues within the practice of diagnosis; the fifth part focuses on the recent developments in psychiatric classification and scientific and ethical issues therein, and the final part focuses on the objectivity of medical research. (shrink)

In this paper, the scientific realism/anti-realism debate, which is one of the most popular topics in the metaphysics of science, will be examined in supporting the realistic wing. In this respect, the discussion will be conducted by keeping the subjects of ‘existence of an external mind-independent world’ and ‘unobservable entities’ at the center of this paper. In the context of understanding the world, ‘Science’ activity is not the sum of the research carried out only by considering empirical data; on the (...) contrary, it will be claimed that it is an endeavor that pursues unknown but interesting things (such as protons, photons, or viruses) and tries to give meaning to the world. Thus, against the empirical rigid attitude of anti-realism –bearing in mind the views of logical positivists; it will be illustrated that scientific realism is an understanding based on metaphysics and has a philosophical basis. (shrink)

Change is omnipotent, differentialism is omnipresent. Philosophy rigorously interrogates perceived realities, employing a disciplined methodology to address the fundamental exis- tential questions: the essence of existence, its underlying reasons, and the processes that sustain it. This exploratory approach, a natural human tendency evident across life stages, has profoundly influenced the development of theories across various disciplines, reshaping our worldview and altering historical narratives. Yet, this iterative process of thought and cognition often culminates in deeply entrenched beliefs, accepted without critical scrutiny (...) and justified by ‘rational methodologies.’ Recognizing these biases, philosophers have histor- ically devised strategies to confront and mitigate such preconceptions. Despite these efforts, the discourse often remains anchored in a self-referential historical context, necessitating a paradigm shift to accommodate the accelerating pace of change. -/- This thesis employs descriptive and normative methods to scrutinize the rational processes of perception, cognition, and action. I introduce the differential framework, a robust construct that encapsulates this cyclical process of sense-making. This framework uses pre-existing understandings as a basis to articulate new perspectives on the evolving world. The dis- course is particularly relevant to the philosophy of mind, information, and ethics, especially as we confront the profound implications of AI and transhumanism. Rapid advancements in these fields challenge our traditional methods and demand adaptive responses, urging a reevaluation of our ethical frameworks and cognitive models in light of emerging realities. This work seeks to bridge the gap between classical philosophical inquiry and the urgent questions posed by the next steps in human evolution, emphasizing the necessity of inte- grating technology with humanity in a way that respects and enhances fundamental human values. (shrink)

Deflationism, one of the influential philosophical doctrines of truth, holds that there is no property of truth, and that overt uses of the predicate "true" are redundant. However, the hypothetical examples used by theorists to exemplify deflationism are isolated sentences, offering little to examine what the predicate adds to meaning within context. We oppose the theory not on philosophical but on empirical grounds. We collect 7,610 occurrences of "it is true that" from 10 influential periodicals published in the United States. (...) We classify and annotate these with respect to the positions of coordinating and subordinating conjunctions that they contain. This way we investigate the contextual relationships between the proposition following "it is true that" with its surroundings. Overall, 34 different syntactical patterns are encountered. In some occurrences of "true", the predicate acts in the same manner as a performative verb does. These occurrences, having been observed in linguistically reliable media, constitute pragmatic counter-examples to deflationism. (shrink)

Glucagon-like peptide-1 (GLP-1) receptor agonists, such as semaglutide, and dual GLP-1 and glucose-dependent insulinotropic polypeptide (GIP) receptor agonists, such as tirzepatide, have been found to be effective for treating obesity and diabetes, significantly reducing weight and the risk or predicted risk of adverse cardiovascular events. There is a global shortage of these medications that could last several years and raises questions about how limited supplies should be allocated. We propose a fair-allocation framework that enables evaluation of the ethics of current (...) practices and could guide governments, professional societies, and physicians in allocation decisions. (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: 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: 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: 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: 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) 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: 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)

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: 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: 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: 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)

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: 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: 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)

The traditional use of conventional media by businesses for audience targeting has shifted with the rise of influencer marketing, notably on platforms like TikTok, posing challenges in content adaptation and technological adaptation. Albert Bandura's Social Cognitive Theory examines factors shaping purchasing behavior, particularly relevant for young professionals. A quantitative correlational study focused on young professionals engaging with TikTok and influenced by Filipino TikTok creators, revealing education level as a key determinant of purchasing behavior. Extended TikTok engagement positively correlates with increased (...) purchasing likelihood. Filipino TikTok influencers significantly impact young professionals' purchasing decisions, emphasizing the need for tailored marketing strategies targeting this demographic. Recommendations were provided for effective influencer and digital marketing strategies targeting young professionals. (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: 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: Early detection of breast cancer is vital for improving patient outcomes and reducing mortality rates. Technological advancements have significantly enhanced the accuracy and efficiency of screening methods. This paper explores recent innovations in early detection, focusing on the evolution of digital mammography, the benefits of 3D mammography (tomosynthesis), and the application of advanced imaging techniques such as molecular imaging and MRI. It also examines the role of artificial intelligence (AI) in diagnostic tools, showing how machine learning algorithms are improving (...) imaging analysis and reducing diagnostic errors. Furthermore, the paper discusses advancements in genetic screening, liquid biopsies, and biomarkers, emphasizing their potential in identifying high-risk individuals and supporting personalized treatment plans. The paper provides a forward-looking perspective on the future of breast cancer detection, addressing both the opportunities and challenges associated with the adoption of these cutting-edge technologies to improve patient outcomes. (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: 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: 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: 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: 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)