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)

Can agents rationally inquire into things that they know? On my view, the answer is yes. Call this view the Compatibility Thesis. One challenge to this thesis is to explain why assertions like “I know that p, but I’m wondering whether p” sound odd, if not Moore-Paradoxical. In response to this challenge, I argue that we can reject one or both premises that give rise to it. First, we can deny that inquiry requires interrogative attitudes. Second, we can deny the (...) ignorance norm, on which agents are not permitted to both know and have interrogative attitudes, such as wondering. I argue that there are compelling reasons to deny the former and reasons to question the latter. Both options pave the way for further work on further inquiry. (shrink)

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

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

The proposed model in this paper employs different integrated detectors, such as heat, smoke, and flame. The signals from those detectors go through the system algorithm to check the fire's potentiality and then broadcast the predicted result to various parties using GSM modem associated with the GSM network system. The system uses various sensors to detect fire, smoke, and gas, then transmits the message using GSM module. After the message, send by the module the help arrives in 15 minutes. The (...) system is associated with water pump and a sprinkler. The Water system is associated with a water tank and a sprinkler. The water tank uses a Ultrasonic sensor to monitor the level of water level in the tank for refilling the water tank. Once fire is detected, it automatically sends the emergency message and sprinkles the water. (shrink)

The World Health Organization has declared the outbreak of the novel coronavirus, Covid-19 as pandemic across the world. With its alarming surge of affected cases throughout the world, lockdown, and awareness (social distancing, use of masks etc.) among people are found to be the only means for restricting the community transmission. In a densely populated country like India, it is very difficult to prevent the community transmission even during lockdown without social awareness and precautionary measures taken by the people. Recently, (...) several containment zones had been identified throughout the country and divided into red, orange and green zones, respectively. The red zones indicate the infection hotspots, orange zones denote some infection and green zones indicate an area with no infection. Contact tracing is known to be an effective technique for detecting and monitoring persons who may have been exposed to individuals infected with any communicable disease. While a good number of contact tracing schemas are existent today (eg., in-person and phone interviews, paper forms, email and web based questionnaires and smartphone apps), they often require active user participation and might miss certain COVID-19 transmission. The Android application updates the locations of the areas in a Google map which are identified to be the containment zones. The application also notifies the users if they have entered a containment zone and to achieve all these functionalities, many tools, and APIs from Google like Firebase and Geofencing API are used in this application. Therefore, this application can be used as a tool for creating further social awareness about the arising need of precautionary measures to be taken by the people of India. (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)

Can you rationally double-check what you already know? In this paper, I argue that you can. Agents can know that something is true and rationally double-check it at the very same time. I defend my position by considering a wide variety of cases where agents double-check their beliefs to gain epistemic improvements beyond knowledge. These include certainty, epistemic resilience, and sensitivity to error. Although this phenomenon is widespread, my proposal faces two types of challenges. First, some have defended ignorance norms, (...) on which agents are only allowed to inquire about things they don't already know. Second – motivated by strong conceptions of belief or pragmatic encroachment – some have argued that double-checking destroys knowledge. I argue that these competing views fail to capture both the epistemic value of double-checking and the many reasons why agents might double-check. Moreover, they rely on overly strong assumptions about what inquiry, knowledge, or belief requires. Finally, I marshal linguistic data in favor of the compatibility of knowledge and double-checking. (shrink)

Cardiovascular diseases (CVD) represent a significant cause of morbidity and mortality worldwide, necessitating early detection for effective intervention. This research explores the application of machine learning (ML) algorithms in predicting cardiovascular diseases with enhanced accuracy by integrating optimization techniques. By leveraging data-driven approaches, ML models can analyze vast datasets, identifying patterns and risk factors that traditional methods might overlook. This study focuses on implementing various ML algorithms, such as Decision Trees, Random Forest, Support Vector Machines, and Neural Networks, optimized through (...) techniques like hyperparameter tuning, cross-validation, and feature selection to improve prediction accuracy. (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)

The ever-evolving landscape of cyber threats necessitates robust and adaptable intrusion detection systems (IDS) capable of identifying both known and emerging attacks. Traditional IDS models often struggle with detecting novel threats, leading to significant security vulnerabilities. This paper proposes an optimized intrusion detection model using Support Vector Machine (SVM) algorithms tailored to detect known and innovative cyberattacks with high accuracy and efficiency. The model integrates feature selection and dimensionality reduction techniques to enhance detection performance while reducing computational overhead. By leveraging (...) advanced optimization techniques such as Grid Search and Particle Swarm Optimization (PSO), the proposed SVM-based IDS achieves superior classification results. (shrink)

The paper also discusses the technical architecture, including the network protocols, data management strategies, and user interface design considerations necessary to implement such a system. Additionally, it addresses the challenges related to data security, privacy, and system interoperability. Finally, the paper outlines potential future enhancements, such as the incorporation of AI-driven predictive analytics and advanced AR features, to further elevate the smart home experience.

The research outlines a workflow that incorporates data collection, preprocessing, model training, and optimization. Real-world datasets from retail and e-commerce sectors are utilized to validate the proposed methodology, showcasing substantial improvements in model performance. The results indicate that optimized models not only provide better predictions of consumer behaviour but also enhance customer segmentation and targeting strategies. The study concludes with recommendations for future research, including the exploration of hybrid optimization techniques and the application of these methods in real-time analytics.

It is widely accepted that consent is a normative power. For instance, consent can make an impermissible act permissible. In the words of Heidi Hurd, it “turns a trespass into a dinner party... an invasion of privacy into an intimate moment.” In this chapter, I argue against the assumption that consent has such robust powers for moral transformation. In particular, I argue that there is a wide range of sex that harms or wrongs victims despite being consensual. Moreover, these cases (...) are not limited to those where con- sent is vitiated by background conditions. I start by calling this category of consensual sex Bad Sex. I then distinguish subspecies of this category, including psychological pressure, social coercion, and epistemically unsafe sex. I end by responding to an objection on which we should treat at least some subspecies of Bad Sex as rape. Though this alternative proposal is often motivated by ameliorative and strategic considerations, I argue that such considerations actually count against collapsing the categories of Bad Sex and rape. (shrink)

Phishing attacks remain one of the most prevalent cybersecurity threats, affecting individuals and organizations globally. The rapid evolution of phishing techniques necessitates more sophisticated detection and classification methods. In this paper, we propose a novel approach to phishing content classification using a Genetic Ranking Optimization Algorithm (GROA), combined with dynamic weighting, to improve the accuracy and ranking of phishing versus legitimate content. Our method leverages features such as URL structure, email content analysis, and user behavior patterns to enhance the detection (...) system's decision-making process. (shrink)

Emotion detection and management have emerged as pivotal areas in humancomputer interaction, offering potential applications in healthcare, entertainment, and customer service. This study explores the use of deep learning (DL) models to enhance emotion recognition accuracy and enable effective emotion regulation mechanisms. By leveraging large datasets of facial expressions, voice tones, and physiological signals, we train deep neural networks to recognize a wide array of emotions with high precision. The proposed system integrates emotion recognition with adaptive management strategies that provide (...) personalized feedback and interventions based on detected emotional states. Our approach surpasses traditional machine learning methods, demonstrating superior performance in real-time applications. (shrink)

The proposed IDS model is aimed at detecting network intrusions by classifying all the packet traffic in the network as benign or malicious classes. The Canadian Institute for Cyber security Intrusion Detection System (CICIDS2017) dataset has been used to train and validate the proposed model. The model has been evaluated in terms of the overall accuracy, attack detection rate, false alarm rate, and training overhead. DDOS attacks based on Canadian Institute for Cyber security Intrusion Detection System (KDD Cup 99) dataset (...) has been used to train and validate. For validation, comparison for 2 dataset (CICIDS2017 and KDD Cup 99) is done. Then, to implement the Deep learning algorithms is proposed. Method Classification using SVM algorithm Model predict is done. (shrink)

Slurs possess interesting linguistic properties and so have recently attracted the attention of linguists and philosophers of language. For instance the racial slur "nigger" is explosively derogatory, enough so that just hearing it mentioned can leave one feeling as if they have been made complicit in a morally atrocious act.. Indeed, the very taboo nature of these words makes discussion of them typically prohibited or frowned upon. Although it is true that the utterance of slurs is illegitimate and derogatory in (...) most contexts, sufficient evidence suggests that slurs are not always or exclusively used to derogate. In fact, slurs are frequently picked up and appropriated by the very in-group members that the slur was originally intended to target. This might be done, for instance, as a means for like speakers to strengthen in-group solidarity. So an investigation into the meaning and use of slurs can give us crucial insight into how words can be used with such derogatory impact, and how they can be turned around and appropriated as vehicles of rapport in certain contexts among in-group speakers. In this essay I will argue that slurs are best characterized as being of a mixed descriptive/expressive type. Next, I will review the most influential accounts of slurs offered thus far, explain their shortcomings, then provide a new analysis of slurs and explain in what ways it is superior to others. Finally, I suggest that a family-resemblance conception of category membership can help us achieve a clearer understanding of the various ways in which slurs, for better or worse, are actually put to use in natural language discourse. (shrink)

Two attitudes are possible: one, that the world is an absolute jungle and that the exercise of coercive power by rulers is only a manifestation of this; and the other, that it is both necessary and right that there should be this exercise of power, that through it the world is much less of a jungle than it could possibly be without it, so that one should in principle be glad of the existence of such power, and only take exception (...) to its unjust exercise. (shrink)

In today's data-driven world, the efficient management of network resources is crucial for optimizing performance in data centers and large-scale networks. Load balancing is a critical process in ensuring the equitable distribution of data across multiple paths, thereby enhancing network throughput and minimizing latency. This paper presents a comprehensive approach to load balancing using advanced optimization techniques integrated with multipath routing protocols. The primary focus is on dynamically allocating network resources to manage the massive volume of data generated by modern (...) applications. By leveraging algorithms such as Genetic Algorithms (GA) and Particle Swarm Optimization (PSO), the proposed method efficiently distributes data across multiple paths, ensuring balanced network utilization. The combination of these algorithms with multipath routing significantly reduces congestion and improves overall network performance. (shrink)

While there has been significant discussion in the health sciences and ethics literatures about problems associated with publication practices (e.g., ghost- and gift-authorship, conflicts of interest), there has been relatively little practical guidance developed to help researchers determine how they should fairly allocate credit for multi-authored publications. Fair allocation of credit requires that participating authors be acknowledged for their contribution and responsibilities, but it is not obvious what contributions should warrant authorship, nor who should be responsible for the quality and (...) content of the scientific research findings presented in a publication. In this paper, we review arguments presented in the ethics and health science literatures, and the policies or guidelines proposed by learned societies and journals, in order to explore the link between author contribution and responsibility in multi-author multidisciplinary health science publications. We then critically examine the various procedures used in the field to help researchers fairly allocate authorship. (shrink)

Foundational ontologies, central constructs in ontological investigations and engineering alike, are based on ontological categories. Firstly proposed by Aristotle as the very ur- elements from which the whole of reality can be derived, they are not easy to identify, let alone partition and/or hierarchize; in particular, the question of their number poses serious challenges. The late medieval philosopher Dietrich of Freiberg wrote around 1286 a tutorial that can help us today with this exceedingly difficult task. In this paper, I discuss (...) ontological categories and their importance for foundational ontologies from both the contemporary perspective and the original Aristotelian viewpoint, I provide the translation from the Latin into English of Dietrich's De origine II with an introductory elaboration, and I extract a foundational ontology–that is in fact a single-category one–from this text rooted in Dietrich's specification of types of subjecthood and his conception of intentionality as causal operation. (shrink)

Ontologies are some of the most central constructs in today's large plethora of knowledge technologies, namely in the context of the semantic web. As their coinage indicates, they are direct heirs to the ontological investigations in the long Western philosophical tradition, but it is not easy to make bridges between them. Contemporary ontological commitments often take causality as a central aspect for the ur-segregation of entities, especially in scientific upper ontologies; theories of causality and philosophical ontological investigations often go hand-in-hand, (...) and were essentially inseparable in medieval thought. This constitutes the foundation for a bridge, and this article analyzes the causality-based ontology of the late medieval philosopher Dietrich of Freiberg from the viewpoint of today's upper-ontology engineering. In this bridging attempt, it offers a translation into English of the first part of Dietrich's De origine (abbreviated title) that is a compromise between traditional scholarly translations of medieval Latin philosophical texts and contemporary ontology. (shrink)

Abstract: Smoke detectors are critical devices for early fire detection and life-saving interventions. This research paper explores the application of Artificial Neural Networks (ANNs) in smoke detection systems. The study aims to develop a robust and accurate smoke detection model using ANNs. Surprisingly, the results indicate a 100% accuracy rate, suggesting promising potential for ANNs in enhancing smoke detection technology. However, this paper acknowledges the need for a comprehensive evaluation beyond accuracy. It discusses potential challenges, such as overfitting, dataset size, (...) and class imbalance, and presents strategies employed to address these issues. Additionally, the paper emphasizes the importance of alternative evaluation metrics, including precision, recall, and F1-score, to assess the model's performance comprehensively. Detailed information regarding the model architecture, data preprocessing, and hyperparameter tuning is provided to enhance the reproducibility of the research. The study also discusses ethical considerations and the implications of false positives and false negatives in smoke detection applications. While achieving 100% accuracy is a notable accomplishment, this paper calls for cautious interpretation and further validation in real-world settings. It concludes by highlighting areas for future research and improvement in smoke detection technology, emphasizing the need for practical deployment and the reduction of false alarms. (shrink)

This paper aims to solve a puzzle for instrumental conceptions of epistemic normativity. The puzzle is this: if the usefulness of epistemic norms explains their normative grip on us, why does it seem improper to violate these norms even when doing so would benefit us? To solve this puzzle, we argue that epistemic instrumentalists must adopt a more social approach to normativity. In particular, they should not account for the nature of epistemic normativity by appealing to the goals of individual (...) agents. Rather, they should appeal to norms or rules of inquiry that serve our collective goals. We argue that epistemic normativity grows out of our need to promote a deep kind of coordination in our basic epistemic practices. By subscribing to an appropriate system of norms, we can coordinate epistemic rule-following across the community. This makes testimony more trustworthy and reliable. This account not only solves a puzzle about epistemic instrumentalism but also sheds new light on the foundations of normativity and emphasizes the need for a truly social epistemology. (shrink)

Knowledge representation (KR) is actually more than representation: It involves also inference, namely inference of “new” knowledge, i.e. new facts. Logic programming is a suitable KR medium, but more often than not discussions on this programming paradigm focus on aspects other than KR. In this paper, I elaborate on the general theory of logic programming and give the essentials of two of its main implementations, to wit, Prolog and Datalog, from the viewpoint of deductive computing over knowledge bases, which includes (...) deductive programming. (shrink)

For millennia, knowledge has eluded a precise definition. The industrialization of knowledge (IoK) and the associated proliferation of the so-called knowledge communities in the last few decades caused this state of affairs to deteriorate, namely by creating a trio composed of data, knowledge, and information (DIK) that is not unlike the aporia of the trinity in philosophy. This calls for a general theory of knowledge (ToK) that can work as a foundation for a science of knowledge (SoK) and additionally distinguishes (...) knowledge from both data and information. In this paper, I attempt to sketch this generality via the establishing of both knowledge structures and knowledge systems that can then be adopted/adapted by the diverse communities for the respective knowledge technologies and practices. This is achieved by means of a formal–indeed, mathematical–approach to epistemological matters a.k.a. formal epistemology. The corresponding application focus is on knowledge systems implementable as computer programs. (shrink)

Deference in politics is often necessary. To answer questions like, “Should the government increase the federal minimum wage?” and “Should the state introduce a vaccine mandate?”, we need to know relevant scientific and economic facts, make complex value judgments, and answer questions about incentives and implementation. Lay citizens typically lack the time, resources, and competence to answer these questions on their own. Hence, they must defer to others. But to whom should they defer? A common answer is that they should—or (...) are at least permitted to—defer to co-partisans. This view initially seems attractive on both normative and empirical grounds. Against this, I argue that deference to co-partisans has overlooked moral and epistemic problems. In light of them, I propose several new ways to revise our expectations of citizens in a democracy both individually and institutionally. (shrink)

When we think about agents who change a long-standing belief, we sometimes have conflicting reactions. On the one hand, such agents often epistemically improve. For example, their new belief may be better supported by the evidence or closer to the truth. On the other hand, such agents are often subject to criticism. Examples include politicians who change their minds on whether climate change is occurring or whether vaccines cause autism. What explains this criticism, and is it ever justified? To answer (...) these questions, I introduce the notion of epistemic atonement. By epistemic atonement, I mean the process of making up for one’s previous epistemic failures, including believing badly. Central to my account is the idea that epistemic atonement requires restoring trust and indicating trustworthiness. I flesh out my proposal by drawing on philosophical and empirical literature on apologies, demonstrating that epistemic blame and atonement parallels the moral domain in various under-appreciated respects. (shrink)

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

A. Newell and H. A. Simon were two of the most influential scientists in the emerging field of artificial intelligence (AI) in the late 1950s through to the early 1990s. This paper reviews their crucial contribution to this field, namely to symbolic AI. This contribution was constituted mostly by their quest for the implementation of general intelligence and (commonsense) knowledge in artificial thinking or reasoning artifacts, a project they shared with many other scientists but that in their case was theoretically (...) based on the idiosyncratic notions of symbol systems and the representational abilities they give rise to, in particular with respect to knowledge. While focusing on the period 1956-1982, this review cites both earlier and later literature and it attempts to make visible their potential relevance to today's greatest unifying AI challenge, to wit, the design of wholly autonomous artificial agents (a.k.a. robots) that are not only rational and ethical, but also self-conscious. (shrink)

The article studies the impact of Fintech on entrepreneurship in Arabic region by using Crowdfunding platforms as the field of study. The article focuses on Arabic Crowdfunding platforms. The population of (12) platforms consist of: individuals, entrepreneurs, investors, employees at Crowdfunding platforms. Descriptive and quantitative approach used in this article, and a questionnaire used as a tool to collect primary data. The results indicate an impact for Fintech on entrepreneurship in general and obvious obstacles to use it widely in Arabic (...) region cause of legislations or e-payments. The article recommended more awareness for innovative products and services such as Fintech, Crowdfunding and adopting the culture of e-business models. Also the article promoting the process of developing regulations that organize e-business models, especially Fintech and Crowdfunding, the use of modern communication technology to serve the development of society, more interest to innovation and creativity as a key factor for entrepreneurial success. (shrink)

3rd ed, 2021. A circumscription of the classical theory of computation building up from the Chomsky hierarchy. With the usual topics in formal language and automata theory.

In this paper, I motivate a puzzle about epistemic rationality. On the one hand, there seems to be something problematic about frequently changing your mind. On the other hand, changing your mind once is often permissible. Why do one-off changes of mind seem rationally permissible, even admirable, while constant changes seem quintessentially irrational? The puzzle of fickleness is to explain this asymmetry. To solve the puzzle, I propose and defend the Ratifiable Reasoning Account. According to this solution, as agents redeliberate, (...) they gain two types of evidence. First, they gain inductive evidence that they will not stably settle their belief. Second, this inductive evidence affords higher-order evidence that they are unreliable at assessing the matter at hand. The fact that fickle agents gain this higher-order evidence explains why fickleness can be epistemically—not just practically—irrational. In addition to solving the puzzle, my account captures a wide range of contextual factors that are relevant for our judgments. (shrink)

Not focusing on the history of classical logic, this book provides discussions and quotes central passages on its origins and development, namely from a philosophical perspective. Not being a book in mathematical logic, it takes formal logic from an essentially mathematical perspective. Biased towards a computational approach, with SAT and VAL as its backbone, this is an introduction to logic that covers essential aspects of the three branches of logic, to wit, philosophical, mathematical, and computational.

It has been widely argued that words are analogous to species such that words, like species, are natural kinds. In this paper, I consider the metaphysics of word-kinds. After arguing against an essentialist approach, I argue that word-kinds are homeostatic property clusters, in line with the dominant approach to other biological and psychological kinds.

Many say that ontological disputes are defective because they are unimportant or without substance. In this paper, we defend ontological disputes from the charge, with a special focus on disputes over the existence of composite objects. Disputes over the existence of composite objects, we argue, have a number of substantive implications across a variety of topics in metaphysics, science, philosophical theology, philosophy of mind, and ethics. Since the disputes over the existence of composite objects have these substantive implications, they are (...) themselves substantive. (shrink)

Is capitalism inherently predatory? Must there be winners and losers? Is public interest outdated and free-riding rational? Is consumer choice the same as self-determination? Must bargainers abandon the no-harm principle? Prisoners of Reason recalls that classical liberal capitalism exalted the no-harm principle. Although imperfect and exclusionary, modern liberalism recognized individual human dignity alongside individuals' responsibility to respect others. Neoliberalism, by contrast, views life as ceaseless struggle. Agents vie for scarce resources in antagonistic competition in which every individual seeks dominance. This (...) political theory is codified in non-cooperative game theory; the neoliberal citizen and consumer is the strategic rational actor. Rational choice justifies ends irrespective of means. Money becomes the medium of all value. Solidarity and good will are invalidated. Relationships are conducted on a quid pro quo basis. However, agents can freely opt out of this cynical race to the bottom by embracing a more expansive range of coherent action. (shrink)

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

Plato is associated with the idea that the body holds us back from knowing ultimate reality and so we should try to distance ourselves from its influence. This sentiment appears is several of his dialogues including Theaetetus where the flight from the physical world is compared to becoming like God. In some major dialogues of Plato's later career such as Philebus and Laws, however, the idea of becoming like God takes a different turn. God is an intelligent force that tries (...) to create order in the physical world. I argue that likeness to God in these dialogues involves imitating God's effort by trying to order our bodies, souls, and societies as intelligence directs. Becoming like Plato's God is not to abandon the world. It is to improve it. (shrink)

Current debates surrounding the virtues and shortcomings of randomization are symptomatic of a lack of appreciation of the fact that causation can be inferred by two distinct inference methods, each requiring its own, specific experimental design. There is a non-statistical type of inference associated with controlled experiments in basic biomedical research; and a statistical variety associated with randomized controlled trials in clinical research. I argue that the main difference between the two hinges on the satisfaction of the comparability requirement, which (...) is in turn dictated by the nature of the objects of study, namely homogeneous or heterogeneous populations of biological systems. Among other things, this entails that the objection according to which randomized experiments fail to provide better evidence for causation because randomization cannot guarantee comparability is mistaken. (shrink)

This paper assesses the role of the Refutation of Idealism within the Critique of Pure Reason, as well as its relation to the treatment of idealism in the First Edition and to transcendental idealism more generally. It is argued that the Refutation is consistent with the Fourth Paralogism and that it can be considered as an extension of the Transcendental Deduction. While the Deduction, considered on its own, constitutes a 'regressive argument', the Refutation allows us to turn the Transcendental Analytic (...) into a 'progressive argument' that proceeds by the synthetic method. (shrink)

This article provides an original account of slurs and how they may be differentially used by in-group and out-group speakers. Slurs are first distinguished from other terms and their role in social interaction is discussed. A new distinction is introduced between three different uses of slurs : the paradigmatic derogatory use, non-paradigmatic derogatory use, and non-paradigmatic non-derogatory use. I then account for their literal meaning and explain how a family-resemblance conception of category membership can clarify our understanding of the various (...) natural-language uses of slurs, -. The focus is restricted primarily to race-based and sex-based slurs used in the context of English speakers, and the article concludes with desiderata to be met by any subsequent analyses of slurs. (shrink)

Artificial intelligence (AI) is an area of computer science that emphasizes the creation of intelligent machines or software that work and react like humans. Some of the activities computers with artificial intelligence are designed for include, Speech, recognition, Learning, Planning and Problem solving. Deep learning is a collection of algorithms used in machine learning, It is part of a broad family of methods used for machine learning that are based on learning representations of data. Deep learning is a technique used (...) to produce Pneumonia detection and classification models using x-ray imaging for rapid and easy detection and identification of pneumonia. In this thesis, we review ways and mechanisms to use deep learning techniques to produce a model for Pneumonia detection. The goal is find a good and effective way to detect pneumonia based on X-rays to help the chest doctor in decision-making easily and accuracy and speed. The model will be designed and implemented, including both Dataset of image and Pneumonia detection through the use of Deep learning algorithms based on neural networks. The test and evaluation will be applied to a range of chest x-ray images and the results will be presented in detail and discussed. This thesis uses deep learning to detect pneumonia and its classification. (shrink)

The core objective of this project is to recognize and reconstruct distorted facial images, particularly in the context of accidents. This involves using deep learning techniques to analyze the features of a distorted face and regenerate it into a recognizable form. Deep learning models are wellsuited for this task due to their ability to learn complex patterns and representations from data the input data consists of distorted facial images, typically obtained from MRI scans of accident victims. These images may contain (...) various types of distortions such as swelling, bruising, or other injuries that affect facial appearance. (shrink)

The van Wijngaarden grammars are two-level grammars that present many interesting properties. In the present article I elaborate on six of these properties, to wit, (i) their being constituted by two grammars, (ii) their ability to generate (possibly infinitely many) strict languages and their own metalanguage, (iii) their context-sensitivity, (iv) their high descriptive power, (v) their productivity, or the ability to generate an infinite number of production rules, and (vi) their equivalence with the unrestricted, or Type-0, Chomsky grammars.

Optimization algorithms such as Genetic Algorithms (GA) and Particle Swarm Optimization (PSO) are employed to determine the optimal aggregation and transmission schedules, taking into account factors such as network topology, node energy levels, and data urgency. The proposed approach is validated through extensive simulations, demonstrating significant improvements in energy consumption, packet delivery ratio, and overall network performance. The results suggest that the optimized aggregated packet transmission method can effectively extend the lifespan of duty-cycled WSNs while ensuring reliable data communication. Future (...) work will explore the integration of machine learning techniques for adaptive scheduling and the application of the proposed method to heterogeneous WSNs. (shrink)