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.

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)

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.

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 rise of social media has created a new platform for communication and interaction, but it has also facilitated the spread of harmful behaviors such as cyberbullying. Detecting and mitigating cyberbullying on social media platforms is a critical challenge that requires advanced technological solutions. This paper presents a novel approach to cyberbullying detection using a combination of supervised machine learning (ML) and natural language processing (NLP) techniques, enhanced by optimization algorithms. The proposed system is designed to identify and classify cyberbullying (...) behavior in real-time, analyzing textual data from social media posts to detect harmful content. The model is trained on a large dataset of labeled instances of bullying and non-bullying content, using supervised ML algorithms such as Support Vector Machines (SVM), Decision Trees, and Random Forest. NLP techniques, including sentiment analysis, keyword extraction, and text vectorization, are employed to preprocess and transform the data into a format suitable for machine learning. To optimize the performance of the detection model, techniques such as Grid Search, Genetic Algorithms, and Particle Swarm Optimization are used to fine-tune hyperparameters, resulting in improved accuracy and reduced false positives. The system's effectiveness is validated through experiments conducted on various social media platforms, demonstrating its potential to detect cyberbullying with high precision. Future work will focus on enhancing the model's adaptability to emerging slang and evolving language patterns in social media. Key words: Cyberbullying Detection, Social Media, Supervised Machine Learning, Natural Language Processing (NLP), Optimization Techniques. (shrink)

In modern data centers, managing the distribution of workloads efficiently is crucial for ensuring optimal performance and meeting Service Level Agreements (SLAs). Load balancing algorithms play a vital role in this process by distributing workloads across computing resources to avoid overloading any single resource. However, the effectiveness of these algorithms can be significantly enhanced through the integration of advanced optimization techniques. This paper proposes an SLA-driven load balancing algorithm optimized using methods such as genetic algorithms, particle swarm optimization, and simulated (...) annealing. By focusing on both resource utilization and SLA compliance, the proposed approach aims to reduce latency, improve throughput, and maximize overall system efficiency. The research introduces a novel framework that incorporates real-time monitoring, dynamic resource allocation, and adaptive threshold settings to ensure consistent SLA adherence while optimizing computing performance. (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)

In the modern digital era, cloud storage has become an indispensable service due to its scalability, accessibility, and cost-effectiveness. However, with the vast amount of sensitive information stored on cloud platforms, ensuring data security and privacy remains a critical challenge. Traditional encryption techniques, while secure, often hinder efficient data retrieval, especially when using keyword searches. To address this, attribute-based keyword search (ABKS) offers a promising solution by allowing secure, fine-grained access control and efficient keyword searches over encrypted data.

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)

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 data collected by these sensors are transmitted to a centralized system where optimization algorithms, such as Genetic Algorithms (GA), Particle Swarm Optimization (PSO), and Simulated Annealing (SA), are applied to optimize sensor placement, data transmission, and processing efficiency. This ensures accurate, real-time pollution monitoring and data analysis, providing actionable insights for policymakers, environmental agencies, and the general public. The system's performance is evaluated through simulations and real-world experiments, demonstrating its capability to deliver reliable and timely pollution data. Future work (...) will explore the integration of machine learning techniques for predictive analytics and the expansion of the sensor network for broader coverage. (shrink)

The exponential growth of cloud storage has necessitated advanced security measures to protect sensitive data from unauthorized access. Traditional encryption methods provide a layer of security, but they often lack the robustness needed to address emerging threats. This paper introduces an optimized framework for secure cloud storage that integrates data encryption, decryption, and dispersion using cutting-edge optimization techniques. The proposed model enhances data security by first encrypting the data, then dispersing it across multiple cloud servers, ensuring that no single server (...) holds the complete dataset. Decryption occurs only when the dispersed data fragments are reassembled, which adds an additional layer of security. We also explore various optimization algorithms to improve the efficiency of encryption and dispersion processes, thereby reducing computational overhead while maintaining high security. (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)

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)

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. We also explore the ethical implications and challenges associated with deploying such systems, particularly regarding privacy concerns and the potential for misuse. Through extensive experiments, our model achieved an average accuracy rate of 92%, highlighting its robustness across different environments and user demographics. This research not only contributes to the growing field of affective computing but also lays the groundwork for future developments in emotionally intelligent systems. (shrink)

Driver drowsiness is a significant factor contributing to road accidents, resulting in severe injuries and fatalities. This study presents an optimized approach for detecting driver drowsiness using machine learning techniques. The proposed system utilizes real-time data to analyze driver behavior and physiological signals to identify signs of fatigue. Various machine learning algorithms, including Support Vector Machines (SVM), Convolutional Neural Networks (CNN), and Random Forest, are explored for their efficacy in detecting drowsiness. The system incorporates an optimization technique—such as Genetic Algorithms (...) (GA) or Particle Swarm Optimization (PSO)—to enhance the accuracy and response time of the detection process. The integration of optimization methods ensures that the model adapts to various driving conditions and individual differences, providing a more reliable and robust detection mechanism. Data from multiple sources, including camera feeds and wearable sensors, are used to train and validate the models, ensuring a comprehensive understanding of drowsiness indicators. (shrink)

As the Internet of Things (IoT) continues to expand, ensuring secure and efficient data storage and retrieval becomes a critical challenge. IoT devices, often constrained by limited computational resources, require lightweight encryption protocols that balance security and performance. This paper presents an optimized encryption protocol designed specifically for lightweight, searchable data in IoT environments. The proposed protocol utilizes advanced optimization techniques to enhance the efficiency and security of searchable encryption, enabling rapid data retrieval without compromising the integrity and confidentiality of (...) the data. The protocol leverages a hybrid cryptographic approach, combining symmetric and asymmetric encryption, to ensure robust protection against unauthorized access while maintaining low computational overhead. (shrink)

Nowadays, intrusions have become a major problem faced by users. To stop these cyber attacks from happening, the development of a reliable and effective Intrusion Detection System (IDS) for cyber security has become an urgent issue to be solved. 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. Testing dataset for anomaly detection model classified as attack or normal. Finally, the experimental results shows that the performance metrics such as accuracy, precision, recall and confusion matrix. (shrink)

This eighth volume of Collected Papers includes 75 papers comprising 973 pages on (theoretic and applied) neutrosophics, written between 2010-2022 by the author alone or in collaboration with the following 102 co-authors (alphabetically ordered) from 24 countries: Mohamed Abdel-Basset, Abduallah Gamal, Firoz Ahmad, Ahmad Yusuf Adhami, Ahmed B. Al-Nafee, Ali Hassan, Mumtaz Ali, Akbar Rezaei, Assia Bakali, Ayoub Bahnasse, Azeddine Elhassouny, Durga Banerjee, Romualdas Bausys, Mircea Boșcoianu, Traian Alexandru Buda, Bui Cong Cuong, Emilia Calefariu, Ahmet Çevik, Chang Su Kim, Victor (...) Christianto, Dae Wan Kim, Daud Ahmad, Arindam Dey, Partha Pratim Dey, Mamouni Dhar, H. A. Elagamy, Ahmed K. Essa, Sudipta Gayen, Bibhas C. Giri, Daniela Gîfu, Noel Batista Hernández, Hojjatollah Farahani, Huda E. Khalid, Irfan Deli, Saeid Jafari, Tèmítópé Gbóláhàn Jaíyéolá, Sripati Jha, Sudan Jha, Ilanthenral Kandasamy, W.B. Vasantha Kandasamy, Darjan Karabašević, M. Karthika, Kawther F. Alhasan, Giruta Kazakeviciute-Januskeviciene, Qaisar Khan, Kishore Kumar P K, Prem Kumar Singh, Ranjan Kumar, Maikel Leyva-Vázquez, Mahmoud Ismail, Tahir Mahmood, Hafsa Masood Malik, Mohammad Abobala, Mai Mohamed, Gunasekaran Manogaran, Seema Mehra, Kalyan Mondal, Mohamed Talea, Mullai Murugappan, Muhammad Akram, Muhammad Aslam Malik, Muhammad Khalid Mahmood, Nivetha Martin, Durga Nagarajan, Nguyen Van Dinh, Nguyen Xuan Thao, Lewis Nkenyereya, Jagan M. Obbineni, M. Parimala, S. K. Patro, Peide Liu, Pham Hong Phong, Surapati Pramanik, Gyanendra Prasad Joshi, Quek Shio Gai, R. Radha, A.A. Salama, S. Satham Hussain, Mehmet Șahin, Said Broumi, Ganeshsree Selvachandran, Selvaraj Ganesan, Shahbaz Ali, Shouzhen Zeng, Manjeet Singh, A. Stanis Arul Mary, Dragiša Stanujkić, Yusuf Șubaș, Rui-Pu Tan, Mirela Teodorescu, Selçuk Topal, Zenonas Turskis, Vakkas Uluçay, Norberto Valcárcel Izquierdo, V. Venkateswara Rao, Volkan Duran, Ying Li, Young Bae Jun, Wadei F. Al-Omeri, Jian-qiang Wang, Lihshing Leigh Wang, Edmundas Kazimieras Zavadskas. (shrink)

It seems natural to ask why the universe exists at all. Modern physics suggests that the universe can exist all by itself as a self-contained system, without anything external to create or sustain it. But there might not be an absolute answer to why it exists. I argue that any attempt to account for the existence of something rather than nothing must ultimately bottom out in a set of brute facts; the universe simply is, without ultimate cause or explanation.

I defend the following version of the ought-implies-can principle: (OIC) by virtue of conceptual necessity, an agent at a given time has an (objective, pro tanto) obligation to do only what the agent at that time has the ability and opportunity to do. In short, obligations correspond to ability plus opportunity. My argument has three premises: (1) obligations correspond to reasons for action; (2) reasons for action correspond to potential actions; (3) potential actions correspond to ability plus opportunity. In the (...) bulk of the paper I address six objections to OIC: three objections based on putative counterexamples, and three objections based on arguments to the effect that OIC conflicts with the is/ought thesis, the possibility of hard determinism, and the denial of the Principle of Alternate Possibilities. (shrink)

This essay interprets Butler’s distinction between identity in the loose and popular sense and in the strict and philosophical sense. Suppose there are different standards for counting the same things. Then what are two distinct things counting strictly may be one and the same thing counting loosely. Within a given standard identity is one-one. But across standards it is many-one. An alternative interpretation using the parts-whole relation fails, because that relation should be understood as many-one identity. Another alternative making identity (...) relative to sort fails, because whole and parts can be of the same sort. (shrink)

Replicability and reproducibility of computational models has been somewhat understudied by “the replication movement.” In this paper, we draw on methodological studies into the replicability of psychological experiments and on the mechanistic account of explanation to analyze the functions of model replications and model reproductions in computational neuroscience. We contend that model replicability, or independent researchers' ability to obtain the same output using original code and data, and model reproducibility, or independent researchers' ability to recreate a model without original code, (...) serve different functions and fail for different reasons. This means that measures designed to improve model replicability may not enhance (and, in some cases, may actually damage) model reproducibility. We claim that although both are undesirable, low model reproducibility poses more of a threat to long-term scientific progress than low model replicability. In our opinion, low model reproducibility stems mostly from authors' omitting to provide crucial information in scientific papers and we stress that sharing all computer code and data is not a solution. Reports of computational studies should remain selective and include all and only relevant bits of code. (shrink)

The study aimed at measuring the dominant pattern of leadership and its relation to the performance of the administrative staff in the Palestinian universities. The study community consists of all the administrative staff from Al-Azhar University and the Islamic University, and through the census of the study society it was found to consist of (655) administrative staff. In order to achieve the objectives of the study, the researchers used the method of random sample in the study, and the study was (...) conducted on a sample of (221) administrative staff of the surveyed universities and the response rate was (82.35%). The study found that there is a high degree of satisfaction with the Dominant Pattern of Leadership in the Palestinian universities in Gaza Strip from the point of view of the administrative staff, which reached (71.67%). There is a high level of performance from the point of view of administrative staff, with a percentage of (82.53%). There is a direct correlation between the dominant pattern of leadership and the functional Performance of Administrative Staff, the absence of differences between the sample according to the gender variable in their perception of the dominant pattern of leadership and the functional Performance of Administrative Staff, the absence of differences in the perception of employees of the dominant pattern of leadership and the functional Performance of Administrative Staff depending on the age variable. There are differences of statistical significance according to the variable of scientific qualification in the Dominant Pattern of Leadership, while there were no differences in performance, the differences in the dominant pattern of leadership according to the scientific qualification were in favor of those who obtained the diploma degree compared to other practical qualifications, the absence of differences in the perception of employees of the dominant pattern of leadership and the functional Performance of Administrative Staff depending on the variable years of service, the absence of differences in the perception of employees of the dominant pattern of leadership and the functional Performance of Administrative Staff depending on the variable level of career (Director, Head of Department, and Administrative Officer). There were differences in the perception of workers to the dominant pattern of leadership depending on the variable of the workplace, where there were differences in favor of workers in deanships and colleges compared with the workers in the technical departments. While there were no differences in job performance according to the workplace variable, the existence of differences in the perception of workers to the dominant pattern of leadership depending on the university in which they work in favor of the Islamic University and the absence of differences in performance between the Islamic University and Al-Azhar University. The study reached a number of recommendations, the most important of which is that the interest of the managements of the Palestinian universities in improving the dominant pattern of leadership, to give universities the opportunity to participate in decision-making, the continued administration of universities interest and continuous improvement of the performance of its employees, enhance the periodic evaluation of job performance and to inform employees and express their opinion, solving workers' problems and giving them the opportunity to contribute to solving their own problems, the use of the staff rotation method periodically and strengthening the democratic the dominant pattern of leadership and empowering university staff. -/- . (shrink)

Construing the instantiation of a universal by a particular in terms of my theory of aspects resolves the basic mystery of this "non-relational tie", and gives theoretical unity to the four characteristics of instantiation discerned by Armstrong. Taking aspects as distinct in a way akin to Scotus's formal distinction, I suggest that instantiation is the sharing of an aspect by a universal and a particular--a kind of partial identity. This approach allows me to address Plato's multiple location and One over (...) Many problems, Bradley's problem concerning the instantiation of relations, and the problem of change. (shrink)

You may not know me well enough to evaluate me in terms of my moral character, but I take it you believe I can be evaluated: it sounds strange to say that I am indeterminate, neither good nor bad nor intermediate. Yet I argue that the claim that most people are indeterminate is the conclusion of a sound argument—the indeterminacy paradox—with two premises: (1) most people are fragmented (they would behave deplorably in many and admirably in many other situations); (2) (...) fragmentation entails indeterminacy. I support (1) by examining psychological experiments in which most participants behave deplorably (e.g., by maltreating “prisoners” in a simulated prison) or admirably (e.g., by intervening in a simulated theft). I support (2) by arguing that, according to certain plausible conceptions, character evaluations presuppose behavioral consistency (lack of fragmentation). Possible reactions to the paradox include: (a) denying that the experiments are relevant to character; (b) upholding conceptions according to which character evaluations do not presuppose consistency; (c) granting that most people are indeterminate and explaining why it appears otherwise. I defend (c) against (a) and (b). (shrink)

Imperatives cannot be true or false, so they are shunned by logicians. And yet imperatives can be combined by logical connectives: "kiss me and hug me" is the conjunction of "kiss me" with "hug me". This example may suggest that declarative and imperative logic are isomorphic: just as the conjunction of two declaratives is true exactly if both conjuncts are true, the conjunction of two imperatives is satisfied exactly if both conjuncts are satisfied—what more is there to say? Much more, (...) I argue. "If you love me, kiss me", a conditional imperative, mixes a declarative antecedent ("you love me") with an imperative consequent ("kiss me"); it is satisfied if you love and kiss me, violated if you love but don't kiss me, and avoided if you don't love me. So we need a logic of three -valued imperatives which mixes declaratives with imperatives. I develop such a logic. (shrink)

Why does classical equilibrium statistical mechanics work? Malament and Zabell (1980) noticed that, for ergodic dynamical systems, the unique absolutely continuous invariant probability measure is the microcanonical. Earman and Rédei (1996) replied that systems of interest are very probably not ergodic, so that absolutely continuous invariant probability measures very distant from the microcanonical exist. In response I define the generalized properties of epsilon-ergodicity and epsilon-continuity, I review computational evidence indicating that systems of interest are epsilon-ergodic, I adapt Malament and Zabell’s (...) defense of absolute continuity to support epsilon-continuity, and I prove that, for epsilon-ergodic systems, every epsilon-continuous invariant probability measure is very close to the microcanonical. (shrink)

In the early part of the paper, I attempt to explain a dispute between two parties who endorse the compositionality of language but disagree about its implications: Paul Horwich, and Jerry Fodor and Ernest Lepore. In the remainder of the paper, I challenge the thesis on which they are agreed, that compositionality can be taken for granted. I suggest that it is not clear what compositionality involves nor whether it obtains. I consider some kinds of apparent counterexamples, and compositionalist responses (...) to them in terms of covert indexicality and unspecific meanings. I argue that the last option is the best for most of the cases I consider. I conclude by stressing, as against Horwich and Fodor and Lepore, that the appropriate question concerns the extent to which compositionality obtains in a natural language, rather than whether it obtains or not, so that the answer is essentially messy, requiring detailed consideration of a wide range of examples. (shrink)

In this chapter, we will explore the luck at issue in Gettier-styled counterexamples and the subsequent problem it poses to any viable reductive analysis of knowledge. In the 1st section, we will consider the specific species of luck that is at issue in Gettier counterexamples, then, in the next section, I will briefly sketch a diagnosis of the Gettier Problem and try to explain why the relevant species of luck has proven to be extremely difficult to avoid. And finally, I (...) will consider a prominent objection to the proposed diagnosis of the Problem. (shrink)

According to Hempel's paradox, evidence (E) that an object is a nonblack nonraven confirms the hypothesis (H) that every raven is black. According to the standard Bayesian solution, E does confirm H but only to a minute degree. This solution relies on the almost never explicitly defended assumption that the probability of H should not be affected by evidence that an object is nonblack. I argue that this assumption is implausible, and I propose a way out for Bayesians. Introduction Hempel's (...) paradox, the standard Bayesian solution, and the disputed assumption Attempts to defend the disputed assumption Attempts to refute the disputed assumption A way out for Bayesians Conclusion. (shrink)

We need modal imagination in order to extend our conception of reality - and, in particular, of human beings - beyond our immediate experience in the indexical present; and we need to do this in order to preserve the significance of human interaction. To make this leap of imagination successfully is to achieve not only insight but also an impartial perspective on our own and others' inner states. This perspective is a necessary condition of experiencing compassion for others. This is (...) the primary thesis I will try to defend in this discussion. (shrink)

The Principal Principle (PP) says that, for any proposition A, given any admissible evidence and the proposition that the chance of A is x%, one's conditional credence in A should be x%. Humean Supervenience (HS) claims that, among possible worlds like ours, no two differ without differing in the spacetime-point-by-spacetime-point arrangement of local properties. David Lewis (1986b, 1994a) has argued that PP contradicts HS, and the validity of his argument has been endorsed by Bigelow et al. (1993), Thau (1994), Hall (...) (1994), Strevens (1995), Ismael (1996), Hoefer (1997), and Black (1998). Against this consensus, I argue that PP might not contradict HS: Lewis's argument is invalid, and every attempt – within a broad class of attempts – to amend the argument fails. (shrink)

Three-dimensionalists , sometimes referred to as endurantists, think that objects persist through time by being “wholly present” at every time they exist. But what is it for something to be wholly present at a time? It is surprisingly difficult to say. The threedimensionalist is free, of course, to take ‘is wholly present at’ as one of her theory’s primitives, but this is problematic for at least one reason: some philosophers claim not to understand her primitive. Clearly the three-dimensionalist would be (...) better off if she could state her theory in terms accessible to all. We think she can. What is needed is a definition of ‘is wholly present at’ that all can understand. in this paper, we offer one. (shrink)

Most moral theories share certain features in common with other theories. They consist of a set of propositions that are universal, general, and hence impartial. The propositions that constitute a typical moral theory are (1) universal, in that they apply to all subjects designated as within their scope. They are (2) general, in that they include no proper names or definite descriptions. They are therefore (3) impartial, in that they accord no special privilege to any particular agent's situation which cannot (...) be justified under (2) and (3). These three features do not distinguish moral theories from other theories, nor indeed from most general categorical propositions we assert. Yet, in recent years, these features of moral theories have been the target of a certain concerted and sustained criticism, namely, that to be committed to such a moral theory, or to aspire to act in accordance with its requirements, results in what has come to be known as moral alienation. Moral alienation, according to this criticism, consists in (i) viewing one's ground projects from an impersonal, "moral point of view" engendered by one's acceptance of the theory; (ii) being prepared to sacrifice these projects to the requirements of moral principle; and (iii) making such a sacrifice specifically and self-consciously in order to conform to these requirements. Moral alienation is said to manifest itself in one (or both) of two ways, depending on the nature of the project thus susceptible to sacrifice. One may be alienated from oneself, if the project consists of tastes, convictions, or aspirations that are centrally definitive of one's self. In this case one's commitment to the project can be at best conditional on its congruence with one's moral theory. It is claimed that this must make for a rather tepid and unenthusiastic commitment indeed. Alternatively, one may be alienated from others, if the project is an interpersonal relationship such as a friendship, marriage, or collegial relationship. In this case one's responses to the other are motivated by one's awareness of what one's moral theory requires. It is claimed that this obstructs a genuine and unmediated emotional response to the other as such. My aim here will be to argue that this very compelling criticism - call it the moral-alienation criticism - is nevertheless misdirected. The real culprit is not any particular moral theory, but rather a certain familiar personality type that may or may not adopt it. (shrink)

Software piracy is older than the PC and has been the subject of several studies, which have found it to be a widespread phenomenon in general, and among university students in particular. An earlier study by Cohen and Cornwell from a decade ago is replicated, adding questions about downloading music from the Internet. The survey includes responses from 224 students in entry-level courses at two schools, a nondenominational suburban university and a Catholic urban college with similar student profiles. The study (...) found that there has been few if any changes in student opinions regarding the unauthorized duplication of copy- righted materials. Students generally felt that copying commercial software and downloading music from the Internet was acceptable and found that there was no significant correlation between student attitudes and their school’s religious affiliation or lack thereof. Additionally, the study found that a small but significant percentage of respondents considered the other questionable behaviors as ethically acceptable. Finally, the reasons for these attitudes are discussed as well as what colleges can do to correct the situation. (shrink)

I propose an approach to naturalized philosophy of science that takes the social nature of scientific practice seriously. I criticize several prominent naturalistic approaches for adopting "cognitive individualism", which limits the study of science to an examination of the internal psychological mechanisms of scientists. I argue that this limits the explanatory capacity of these approaches. I then propose a three-level model of the social nature of scientific practice, and use the model to defend the claim that scientific knowledge is socially (...) produced. (shrink)

David Lewis (1980) proposed the Principal Principle (PP) and a “reformulation” which later on he called ‘OP’ (Old Principle). Reacting to his belief that these principles run into trouble, Lewis (1994) concluded that they should be replaced with the New Principle (NP). This conclusion left Lewis uneasy, because he thought that an inverse form of NP is “quite messy”, whereas an inverse form of OP, namely the simple and intuitive PP, is “the key to our concept of chance”. I argue (...) that, even if OP should be discarded, PP need not be. Moreover, far from being messy, an inverse form of NP is a simple and intuitive Conditional Principle (CP). Finally, both PP and CP are special cases of a General Principle (GP); it follows that so are PP and NP, which are thus compatible rather than competing. (shrink)

The problem of evil is an ideal topic for experimental philosophy. Suffering--which is at the heart of most prominent formulations of the problem of evil--is a universal human experience and has been the topic of careful reflection for millennia. However, interpretations of suffering and how it bears on the existence of God are tremendously diverse and nuanced. We might immediately find ourselves wondering why (and how!) something so universal might be understood in so many different ways. Why does suffering push (...) some people toward atheism while pushing others toward deeper faith? What cultural, psychological, or sociological differences account for this diversity of responses? And, importantly, what light might this diversity of responses shed on the problem of evil and how it has been formulated by philosophers in recent years? The primary aim of this paper is to highlight how the tools and resources of experimental philosophy might be fruitfully applied to the problem of evil. In the first section, we review some recent work in this area and describe the current state of this emergent body of literature. In the second section, we review the broader and more recent theoretical developments on the problem of evil. Finally, in the final section, we outline some potential areas of future empirical research that we see as especially promising given those developments. (shrink)

For centuries it has been a mainstay of European and American moral thought that keeping promises—and the allied activity of upholding contracts—is one of the most important requirements of morality. On some historically powerful views the obligation to uphold promises or contracts not only regulates private relationships, but also provides the moral foundation for our duty to support and obey legitimate governments. Some theorists believe that the concept of keeping promises has gradually moved to center stage in European moral thought. (...) They see this movement as part of an historical shift from a moral conception in which an individual’s duties are mainly externally imposed and unalterable, to a conception in which duties are largely chosen by the individual. (shrink)

In this paper, we contend that the “Smith case” in Gettier’s attempt to refute the justified true belief (JTB) account of knowledge does not work. This is because the said case fails to satisfy the truth condition, and thus is not a case of JTB at all. We demonstrate this claim using the framework of Donnellan’s distinction between the referential and attributive uses of definite descriptions. Accordingly, the truth value of Smith’s proposition “The man who will get the job has (...) ten coins in his pocket” partly depends on how Smith uses the definite description “the man who will get the job” when he utters the proposition. Since, upon uttering the proposition, Smith has in mind a particular individual, namely Jones, and not just whoever will fit the attribute specified in the definite description, Smith uses the definite description referentially. And so when it turns out that it is Smith who eventually gets the job, the definite description fails to refer to Jones as intended by Smith, thereby making Smith’s proposition false. To think that Smith’s proposition is still true, in this regard, is to use the definite description attributively—that it is about whoever will fit the definite description. Apparently, when Gettier claims that Smith’s proposition is still true, to demonstrate that it is a case of JTB, he, in effect, imposes his attributive understanding of Smith’s usage of the definite description on Smith’s own epistemic situation. (shrink)

From folk tales to movies, stories possess features which naturally suit them to contribute to the growth of virtue. In this article I show that the fictional exemplars help the learner to grasp the moral importance of internal states and resolves a tension between existing kinds of exemplars discussed by virtue ethicists. Stories also increase the information conveyed by virtue terms and aid the growth of prudence. Stories can provide virtuous exemplars, inform learners as to the nature of the virtues (...) and offer practice in developing situational judgement. As such they are a significant resource for virtue ethics and moral education. (shrink)

The chapter approaches the hermeneutic concept of experience introduced by Hans-Georg Gadamer in Truth and Method (1960) from the perspective of the conceptual history of experience in the Western philosophical tradition. Through an overview of the concept and the epistemological function of experience (empeiria, experientia, Erfahrung) in Aristotle, Francis Bacon, and Hegel, it is shown that the tradition has considered experience first and foremost in methodological terms, that is, as a pathway towards a form of scientific knowledge that is itself (...) increasingly immune to experience. Science strives “beyond” experience because of the limitations inherent in the fundamentally contingent, singular, and negative character of experience: experience comes to us through unpredictable chance encounters and in singular situations and negates, tests, or “imperils” previous knowledge, thereby transforming it. By contrast, philosophical hermeneutics rethinks experience precisely in terms of these limitations. In the hermeneutic approach articulated by Gadamer and Claude Romano, experience is an encounter with the irreducible finitude and historical situatedness of one’s understanding and conceptual framework, an encounter with an otherness that puts our preunderstanding to test and requires us to revise it. Hermeneutic experience is thus a singular event that irreparably transforms us. (shrink)

To make out in what way Einstein’s 1905 ‘annus mirabilis’ writings hang together one has to hang on Einstein’s strive for unity evinced in his stubborn attempts to coordinate with one another the basic research traditions of classical physics. Light quanta hypothesis and special theory of relativity turn out to be mere milestones of maxwellian electrodynamics and statistical thermodynamics reconciliation programme. The conception of luminiferous ether was an insurmountable stumbling block for Einstein’s statistical thermodynamics programme in which the leading role (...) was played by the light quanta paper . (shrink)

In analytic political philosophy, it is common to view state-sponsored injustice as the work of a corporate agent. But as I argue, structural injustice theory provides grounds for reassessing the agential approach, producing new insights into state-sponsored injustice. Using the case of eugenic sterilization in the United States, this article proposes a structurally-sensitive conception of state-sponsored injustice with six components: authorization, protection, systemization, execution, enablement, and norm- and belief-influence. Iris Marion Young’s models of responsibility for agential and structural injustice, and (...) the place of state-sponsored injustice with respect to these models, are also discussed. (shrink)

This paper argues that the behaviorist label yields a caricature of Ryle's position in The Concept of Mind that cannot be adequately fleshed out by reference to the larger corpus of Rylean texts. On the interpretation of Ryle that I offer here, he is best characterized as an "ontological agnostic." Ryle's aim, I believe, is to develop a nondenotational theory of meaning for mental-conduct terms--a theory of meaning which does not presuppose any metaphysical or ontological theory and, hence, does not (...) presuppose behaviorism. (shrink)