The view that to act is to cause change and that to be an agent is to be the causer of an action’s result has gained traction in the past twenty years or so. This view seems to have two significant corollaries. First, there is no distinction between doing an action and causing its result. Second, any two actions that have the same result will turn out to be identical. Ruben (2018) has recently used the first corollary to challenge the (...) view, and the second corollary raises further problems for the view. This article aims to refine this view and defend it against the challenges that arise out of its two corollaries. It is argued that being the cause of an action’s result is not the same as being its causer and that doing an action is not just causing its result but causing it in a specific way. (shrink)

Ricoeur’s application of phenomenology to the existential human condition brings us to an understanding of human freedom in the light of an embodied human existence that is acting or willing or choosing freely, voluntarily, and responsibly. Human will is not therefore a concept or an abstract manipulated by the powers of the intellectuals. Rather, it is about man’s action, his agency, his being a doer, the one willing, instead of being just the one thinking or loving. Likewise, Ricoeur’s recourse to (...) existentialism sheds light to our faulted condition. We could say of a negation of man as a willing being: while man is capable of willing, he wills with recognition of his limitations. He always wills within the bounds of his finitude. Indeed, there is always this tension yet there is also this fusion. Nonetheless, it is possible for man to live in this contradiction as contradictions. Man is harmonic in contradictions. His will is always his ability, not his in- or dis-ability. (shrink)

Scientific management introduced a novel way of organizing work and measuring productivity into the modern workplace. With a stopwatch and a clever method of analysis, Frederick Winslow Taylor is either acclaimed or reviled, depending on the audience, for giving industrial/organizational consultancy a groundbreaking tool: the efficiency study. What is less well known is that the American pragmatist John Dewey criticized scientific management for its dualistic assumptions, for treating workers as pure doers or “muscle” and management as pure thinkers or “brains” (...) in an efficient, though inhumane, work process. The first section of this paper examines the similarities and differences between Dewey’s and Taylor’s respective conceptions of science and management. In the second section, I consider Dewey’s critique of scientific management in his book Democracy and Education. The paper concludes with some thoughts about the implications of Dewey’s critique of Taylorism for organizational theory and industrial relations today. (shrink)

This article recapitulates and develops the attempts in the Nietzschean traditions to address and overcome the proliferation of nihilism that Nietzsche predicted to unfold in the next 200 years (WP 2). Nietzsche approached nihilism not merely as a psychology but as a labyrinthic and pervasive historical process whereby the highest values of culture and founding assumptions of philosophical thought prevented the further flourishing of life. Therefore, he thought nihilism had to be encountered and experienced on many, often opposing, fronts to (...) be fully consumed and left behind. Thus, just as Nietzsche captured the subtle reinventions of nihilism in new forms in his time, in the new doers assumed behind new deeds (WP 488), this article focuses on the contemporary tectonic shifts brought by digital technology and challenges subjectivation and narrativization of algorithmic will to power in human-like interfaces such as ChatGPT. Having identified philosophers and himself as the most advanced nihilists in their overvaluation of truth, in the 4th part of Thus Spoke Zarathustra, Nietzsche grappled with the difficult, perhaps impossible, temporality of post-nihilistic historicity that oscillates between highest creativity and highest truths, especially in the sections entitled The Shadow and At Noon whereby he explored new temporal techniques to evade the relapses into temporal nihilisms of the notions of linear progress or eternity (TSZ, 4). By drawing on this juncture, this article offers ways to address transfigurations of nihilism behind new technological performances of subjectivity. The article points toward creative temporalities beyond narrativity and subjectivity insofar as the statistical operations and probabilistic estimations of language-models exceed grammatical construction of meaning. This multifaceted application of his thought on the contemporary ontic reality is necessary to perceive our comet's incalculable movement as a veritable ray of sunshine. (shrink)

The paper discusses the issue of psychophysical agency in the context of Indian philosophy, focusing on the oldest preserved texts of the classical tradition of Sāṃkhya–Yoga. The author raises three major questions: What is action in terms of Sāṃkhyakārikā (ca. fifth century CE) and Yogasūtra (ca. third century CE)? Whose action is it, or what makes one an agent? What is a right and morally good action? The first part of the paper reconsiders a general idea of action – including (...) actions that are deliberately done and those that ‘merely’ happen – identified by Patañjali and Ῑśvarakṛṣṇa as a permanent change or transformation (pariṇāma) determined by the universal principle of causation (satkārya). Then, a threefold categorization of actions according to their causes is presented, i.e. internal agency (ādhyātmika), external agency (ādhibhautika) and ‘divine’ agency (ādhidaivika). The second part of the paper undertakes the problem of the agent’s autonomy and the doer’s psychophysical integrity. The main issues that are exposed in this context include the relationship between an agent and the agent’s capacity for perception and cognition, as well as the crucial Sāṃkhya–Yoga distinction between ‘a doer’ and ‘the self’. The agent’s self-awareness and his or her moral self-esteem are also briefly examined. Moreover, the efficiency of action in present and future is discussed (i.e. karman, karmāśaya, saṃskāra, vāsanā), along with the criteria of a right act accomplished through meditative insight (samādhi) and moral discipline (yama). (shrink)

Cosmic Justice Hypotheses. -/- This applied-logic lecture builds on [1] arguing that character traits fostered by logic serve clarity and understanding in ethics, confirming hopeful views of Alfred Tarski [2, Preface, and personal communication]. Hypotheses in one strict usage are propositions not known to be true and not known to be false or—more loosely—propositions so considered for discussion purposes [1, p. 38]. Logic studies hypotheses by determining their implications (propositions they imply) and their implicants (propositions that imply them). Logic also (...) studies hypotheses by seeing how variations affect implications and implicants. People versed in logical methods are more inclined to enjoy working with hypotheses and less inclined to dismiss them or to accept them without sufficient evidence. Cosmic Justice Hypotheses (CJHs), such as “in the fullness of time every act will be rewarded or punished in exact proportion to its goodness or badness”, have been entertained by intelligent thinkers. Absolute CJHs, ACHJs, imply that it is pointless to make sacrifices, make pilgrimages, or ask divine forgiveness: once acts are done, doers must ready themselves for the inevitable payback, since the cosmos works inexorably toward justice. Ceteris Paribus CJHs, CPCJHs, on the other hand, such as “in the fullness of time every act will be rewarded or punished in exact proportion to its goodness or badness—other things being equal”, leave room for exceptions. For example, some people subscribing to Ceteris Paribus CJHs think that certain bad acts can be performed with impunity as long as certain procedures are carried out previous to, or simultaneous with, or even after the acts. Belief Ceteris Paribus CJHs has been exploited by unscrupulous “spiritual leaders” who claim to have power to grant exceptions. In opposition to belief in CPCJHs are CJHs that hold belief in CPCJHs to be inherently wrong and subject to punishment. Other variants of CJHs are Cumulative Cosmic Justice Hypotheses, such as “in the fullness of time every person will be rewarded or punished in exact proportion to the net goodness or badness of their acts”. Still other variants include the Hereditary Cumulative Cosmic Justice Hypotheses, such as “in the fullness of time every person will be rewarded or punished in exact proportion to the net goodness or badness of their ancestors’ acts”. [1] JOHN CORCORAN, Inseparability of Logic and Ethics, Free Inquiry, S. 1989, pp. 37–40. [2] ALFRED TARSKI, Introduction to Logic, Dover, 1995. (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)

Abstract: Online book review platforms generate vast user data, making accurate rating prediction crucial for personalized recommendations. This research explores neural networks as simple models for predicting book ratings without complex algorithms. Our novel approach uses neural networks to predict ratings solely from user-book interactions, eliminating manual feature engineering. The model processes data, learns patterns, and predicts ratings. We discuss data preprocessing, neural network design, and training techniques. Real-world data experiments show the model's effectiveness, surpassing traditional methods. This research can (...) enhance user experience, book catalog organization, and aid publishers, simplifying recommendation processes and providing tailored suggestions based on user preferences. (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)

The research aims to identify the trends of Palestinian higher educational institutions in Gaza Strip as learning organizations from the perspective of senior management in the Palestinian universities in Gaza Strip. The researchers used descriptive analytical approach and used the questionnaire as a tool for information gathering. The questionnaires were distributed to senior management in the Palestinian universities. The study population reached (344) employees in senior management is dispersed over (3) Palestinian universities. A stratified random sample of (182) employees from (...) the Palestinian universities was selected and the recovery rate was (69.2%). Statistical analysis (SPSS) program was used for analysis and processing the data. The study found the following results: There is an agreement about: the importance of the focus of "organizational structure" with an average approval, the importance of "technological infrastructure" axis with high approval, and the importance of "strategic" with an average approval. The results concluded that the study sample agree on the importance of "organizational dimension" highly. The results showed that the sample believe that the "strategic leadership" level in the universities got medium-approval. There is a fair level agreement about the axis of interest "teams / committees". There is an agreement about the importance of the "human dimension" moderately. The results showed that the sample is highly agreed about the importance of focus of the "knowledge management", and the focus of the "continuing education". They agreed weakly to somewhat about the importance of the focus of "scientific research", moderately agree about the importance of the center of "institutional culture", agree moderately on the importance of "cognitive dimension". The results showed that the sample largely agree on the importance of the focus of "strategic partnerships and alliances". They agree highly on the axis "keep up with the labor market" and on the focus of the importance of "technology incubators". The results showed that the sample moderately agree about the importance of the theme on "consulting and training", the importance of the focus of "social responsibility", and the focus of the "Community dimension". The study found a group of recommendations including: there is a need to provide suitable environment that achieve learning organizations. There is a need to develop the technological infrastructure (hardware, software, networks, databases, and human skills) because of the great advantages that they offer. The universities need to adopt knowledge management in the academic and administrative departments because knowledge is the core of the work of these departments. The establishment of technology incubators in universities to adopt outstanding university research projects, to protect, to supports, and to market them; furthermore, to develop the capabilities and skills of employees in the field of information technology. (shrink)

Corruptionism is the view that following physical death, the human being ceases to exist but their soul persists in the afterlife. Survivalism holds that both the human being and their soul persist in the afterlife, as distinct entities, with the soul constituting the human. Each position has its defenders, most of whom appeal both to metaphysical considerations and to the authority of St Thomas Aquinas. Corruptionists claim that survivalism violates a basic principle of any plausible mereology, while survivalists tend to (...) reject the principle, though without as much detail as one would like. In this paper I examine both the key exegetical issues and the mereological question, arguing that Aquinas cannot be shown to have supported the principle in question, and that the principle should be rejected on independent grounds. If correct, some key planks in support of survivalism are established, with others to await further examination. (shrink)

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

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)

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)

Trans rights advocacy is a social justice movement that is transforming language practices relating to gender. Research has highlighted the fact that language which constructs gender as binary harms trans people, and some trans studies researchers have developed guidelines for honouring trans people’s names and pronouns. The language of academic writing is an area of discussion where questions of trans rights and trans experiences have not yet been addressed. This paper draws on two data sources to explore the citation experiences (...) and practices of trans scholars and activists: a web-based archive of writers’ perspectives built between 2015 and 2016; and a corpus-based study of 14 research articles published in TSQ: Transgender Studies Quarterly. Our analysis highlights the sensitivity that is required of colleagues who work with transgender authors’ writing, furthering our understanding of citation as a collaborative and potentially intimate and caring practice. Practices of referring to work by trans scholars pose ethical questions about the social relations expressed in citation in general, enabling applied language scholars to develop a new and different awareness of the sociality of citation. (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: 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)

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: 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)

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: 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: 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)

Rainfall prediction is one of the challenging tasks in weather forecasting. Accurate and timely rainfall prediction can be very helpful to take effective security measures in dvance regarding: on-going construction projects, transportation activities, agricultural tasks, flight operations and flood situation, etc. Data mining techniques can effectively predict the rainfall by extracting the hidden patterns among available features of past weather data. This research contributes by providing a critical analysis and review of latest data mining techniques, used for rainfall prediction. In (...) our proposed system we propose a new forecasting method that uses a Convolutional Neural Network monthly rainfall for a selected location. In our proposed system we are going to forecast the rainfall result based on the mean square error, mean absolute error and root mean square error, which we get in train and test of the dataset based deep learning technique. (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)

The production of Ordinary Portland Cement (OPC) causes havoc to the environment due to the emission of CO 2 as well mining also results in unrecoverable loss to nature. Estimated carbon This Project deals with the details of optimized Mix Design for normal strength concrete using packing density method. Dredged Marine Sand (DMS) which is produced during the operation of dredging. DMS is mixed with M-Sand in different ratios & Packing density is obtained using sieve analysis experimentally. This ratio’s of (...) different fine aggregate is introduced into the geopolymer concrete is the concrete in which alternate material for cement is used also alkali activated solution is used and Concrete made up of cement, aggregates, water & additives is the world's most consumed construction material since it is found to be more versatile, durable and reliable. Concrete is the second most consumed material after water which required large quantities of Portland cementemissions from cement production in 1994 were 307 MtC, 160 MtC from calcination, and 147 MtC from energy use which account for 5% of 1994 global anthropogenic CO 2 emissions. (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)

Artificial Intelligence (AI) is rapidly transforming Human Resource Management (HRM) by enhancing the efficiency and effectiveness of key functions such as recruitment, performance management, and employee engagement. This paper explores the integration of AI technologies in HRM, focusing on their potential to revolutionize these critical areas. In recruitment, AI-driven tools streamline candidate sourcing, screening, and selection processes, leading to more accurate and unbiased hiring decisions. Performance management is similarly transformed, with AI enabling continuous, data-driven feedback and personalized development plans that (...) align with organizational goals. Furthermore, AI facilitates more engaging and tailored employee experiences by leveraging predictive analytics to anticipate and address employee needs. Despite these advancements, the paper also addresses the ethical considerations and challenges associated with AI in HRM, including data privacy concerns and the risk of over-reliance on automated systems. Through a comprehensive analysis, this paper aims to provide insights into how AI can be strategically leveraged to optimize HRM practices, while highlighting the need for a balanced approach that integrates human judgment with technological innovation. (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)

ALTERNATIVE FOODS IN THE FORMULATION OF DIETS FOR GOATS AND SHEEP ABSTRACT Alternative nutrition refers to the use of unconventional ingredients or agro-industrial byproducts in formulating diets that would otherwise be discarded (Moraes, et al., 2011). Providing nutritional support to animals is essential in optimizing digestibility, associated with good management and water availability, which increases the producer's profitability. The search for alternative foods to meet market demand can arise for several reasons, whether to obtain a greater supply of feed during (...) the seasons, always maintaining a favorable trade balance with regard to the cost of the diet, bringing this These foods that are used to feed sheep and goats have been carried out more effectively, however, these foods must provide the supply of all nutrients. Furthermore, these foods have economic viability and nutritional values capable of supplementing the nutritional needs of small ruminants, such as: Whey, mandacaru, beans and castor seeds. Keyword: small ruminants, food, nutritional management. (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: The convergence of nanotechnology and artificial intelligence (AI) represents a transformative frontier in modern science, with the potential to revolutionize multiple industries, particularly healthcare. Nanotechnology enables the manipulation of matter at the atomic and molecular scale, while AI offers sophisticated data analysis, pattern recognition, and decision-making capabilities. This paper explores the synergies between these two fields, focusing on their impact on medical diagnostics, targeted drug delivery, and personalized treatments. By leveraging AI's predictive power and nanotechnology's precision, healthcare can achieve (...) unprecedented levels of accuracy in disease detection and treatment, leading to improved patient outcomes. Beyond healthcare, this convergence extends to environmental monitoring, smart materials, and manufacturing, offering solutions to some of the world’s most pressing challenges. The paper also discusses the ethical considerations and potential risks of integrating AI with nanotechnology, emphasizing the need for responsible innovation. Together, AI and nanotechnology hold the promise of reshaping industries and improving quality of life on a global . (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)

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: The integration of Artificial Intelligence (AI) into educational technology has revolutionized learning through Intelligent Tutoring Systems (ITS). These systems harness AI to deliver personalized, adaptive instruction that caters to individual student needs, thereby enhancing learning outcomes and engagement. This paper explores the evolution and impact of ITS, highlighting key AI technologies such as machine learning, natural language processing, and adaptive algorithms that underpin their functionality. By examining various case studies and applications, the paper illustrates how ITS have transformed traditional (...) educational practices and identifies the challenges and limitations associated with their implementation, including data privacy concerns and system biases. The discussion also extends to future directions in ITS development, emphasizing emerging trends and potential advancements. Ultimately, this paper aims to provide a comprehensive understanding of how ITS leverage AI to enhance educational experiences and propose pathways for future research in this dynamic field. (shrink)

Abstract: Artificial Intelligence (AI) is revolutionizing organizational dynamics by reshaping both structures and processes. This paper explores how AI-driven innovations are transforming organizational frameworks, from hierarchical adjustments to decentralized decision-making models. It examines the impact of AI on various processes, including workflow automation, data analysis, and enhanced decision support systems. Through case studies and empirical research, the paper highlights the benefits of AI in improving efficiency, driving innovation, and fostering agility within organizations. Additionally, it addresses the challenges associated with AI (...) integration, such as resistance to change, ethical concerns, and data security issues. The paper concludes by offering insights into future trends and implications for organizations navigating the evolving landscape of AI-driven change. (shrink)

Many teachers experience decreased motivation and dissatisfaction due to a lack of support from school leaders, which ultimately impacts the quality of teaching and learning. This study analyzes the relationship between teachers' motivation and satisfaction with school leadership using correlational and regression approaches. This study used a quantitative descriptive-correlational research design. Sixty-one primary school teachers participated in this study as respondents, who were selected through simple random sampling. Data were collected using a validated research questionnaire consisting of motivation and satisfaction. (...) The research instrument was subjected to a reliability test with Cronbach's alpha to ensure consistency using the instrument in the form of a questionnaire sheet. Data analysis used descriptive statistics, Pearson product-moment correlation, Spearman rho correlation, chi-square test, ordinary least square (OLS) regression, and logit regression to determine the strength and direction of the relationship between variables. The regression results further showed that increased satisfaction with school leadership predicted higher levels of teacher motivation. It is concluded that improving school leadership practices can significantly contribute to increased teacher motivation, improving teaching quality and overall school performance. Therefore, it is recommended that school leaders receive targeted training to develop leadership skills that can increase teacher satisfaction and motivation. (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: The integration of Artificial Intelligence (AI) into leadership practices is transforming organizational dynamics and This decision-making processes. paper explores how AI can enhance leadership effectiveness by providing data-driven insights, optimizing decision-making, and automating routine tasks. It also examines the challenges leaders face in adopting AI, including ethical considerations, potential biases in AI systems, and the need for upskilling. By analyzing current applications of AI in leadership and discussing future trends, this study aims to provide a comprehensive overview of the (...) opportunities AI presents for effective leadership and the strategies required to address its associated challenges. (shrink)

What is freedom? The contemporary history of humanity is a quest for enduring human freedom over oppression, subjugation and tyranny of many forms. In that pursuit, many wars have been fought, and millions of lives have perished, and many ideologies were born. In simple terms, freedom to the ability to act or change without being constrained. Freedom manifests when obstacles to initiate change or to express free will are removed. From a needs perspective, freedom is when an individual can pursue (...) his or her needs, wants and aspirations freely. However, freedom may not be absolute; some constraints or caveats can manifest from personal ethics and morality, family, cultural, faith systems and governance structures. It may also differ from one society to another. From a religious or philosophical perspective, freedom is often associated with liberty and autonomy, and only exist in a human realm. This type of freedom is also known as political freedom expressed in the forms of human rights and civil liberties, which are often legislated and protected by laws. Nonetheless, the limits and depths of political freedoms such as freedom of choice, assembly, association, and freedom of expression are often debated and sometimes challenged through modern history. (shrink)

Abstract: The integration of Artificial Intelligence (AI) into leadership practices is rapidly transforming organizational dynamics and decision-making processes. This paper explores the ways in which AI enhances leadership effectiveness by providing data- driven insights, optimizing decision-making, and automating routine tasks. Additionally, it examines the challenges leaders face when adopting AI, including ethical considerations, potential biases in AI systems, and the need for upskilling. By analyzing current applications of AI in leadership and discussing future trends, this study aims to offer a (...) comprehensive overview of the opportunities AI presents for effective leadership, as well as the strategies required to address its associated challenges. (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: As artificial intelligence (AI) technologies become more integrated across various sectors, ethical considerations in their development and application have gained critical importance. This paper delves into the complex ethical landscape of AI, addressing significant challenges such as bias, transparency, privacy, and accountability. It explores how these issues manifest in AI systems and their societal impact, while also evaluating current strategies aimed at mitigating these ethical concerns, including regulatory frameworks, ethical guidelines, and best practices in AI design. Through a comprehensive (...) analysis of these challenges and proposed solutions, this paper seeks to contribute to the ongoing discourse on responsible AI development, emphasizing the need for a balance between technological advancement and ethical integrity. (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)

De burgemeester van Etterbeek liet tijdens de afgelopen periode van vrieskou daklozen van straat halen. Soms tegen hun wil in. Omdat het soms nodig is om mensen tegen zichzelf te beschermen.

Abstract: Early detection of breast cancer plays a pivotal role in improving patient prognosis and reducing mortality rates. Recent technological advancements have significantly enhanced the accuracy and effectiveness of breast cancer screening methods. This paper explores the latest innovations in early detection, including the evolution of digital mammography, the impact of 3D mammography (tomosynthesis), and the use of advanced imaging techniques such as molecular imaging and MRI. Furthermore, the integration of artificial intelligence (AI) in diagnostic tools is discussed, highlighting how (...) machine learning algorithms are refining imaging analyses and reducing diagnostic errors. Advances in genetic screening, liquid biopsies, and biomarkers are also examined, showcasing their potential in identifying high-risk individuals and enabling personalized treatment plans. This paper provides insights into the future of breast cancer detection, outlining both the opportunities and challenges that lie ahead in adopting these innovative technologies to improve patient outcomes. (shrink)

Socioeconomic status refers to the family's social and economic standing in society. It is measured by combining an individual or group's economic and social position, which is often based on income, education, and occupation. It significantly affects academic performance and even one's health status. The pandemic changed the educational system, causing a huge transition from traditional learning methods to online learning. This shift resulted in confusion, burden, and difficulty among students from different walks of life. This study was conducted to (...) determine the academic stress on online learning among nursing students in relation to their economic status and their ability to access technology. The study utilized a quantitative-correlational method aided by a standard questionnaire. Two hundred thirty-six University of Bohol nursing students enrolled in the second semester of SY 2021–2022 were included in the study by random selection. Data revealed a significant correlation between economic status and the level of stress related to academic expectations and a significant correlation between economic status and access to technology after being subjected to the Spearman rho test of correlation. However, no significant correlation was found between access to technology and the respondents' level of academic stress. (shrink)