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)

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.

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 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.

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)

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)

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)

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)

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 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)

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)

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)

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)

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)

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)

This article investigates the hitherto under-examined relations between affirmative action, paternalism and respect. We provide three main arguments. First, we argue that affirmative action initiatives are typically paternalistic and thus disrespectful towards those intended beneficiaries who oppose the initiatives in question. Second, we argue that not introducing affirmative action can also be disrespectful towards these potential beneficiaries because such inaction involves a failure to adequately recognize their moral worth. Third, we argue that the paternalistic disrespect involved in affirmative action is (...) alleviated when the potential beneficiaries’ preferences against such initiatives are adaptive. We conclude that although there is a relevant sense in which paternalistic affirmative action is disrespectful, it may well be more disrespectful not to pursue such policies. (shrink)

Recent theorizing argues that online communication technologies provide powerful, although precarious, means of emotional regulation. We develop this understanding further. Drawing on subjective reports collected during periods of imposed social restrictions under COVID-19, we focus on how this precarity is a source of emo-tional dysregulation. We make our case by organizing responses into five distinct but intersecting dimensions wherein the precarity of this regulation is most relevant: infrastructure, functional use, mindful design (individual and social), and digital tact. Analyzing these reports, (...) along with examples of mediating technologies (i.e., self-view) and common interactive dynamics (e.g., gaze coordination), we tease out how breakdowns along these dimensions are sources of affective dysregulation. We argue that the adequacy of available technological resources and competencies of various kinds matter greatly to the types of emotional experiences one is likely to have online. Further research into online communication technologies as modula-tors of both our individual and collective well-being is urgently needed, especially as the echoes of the digital push that COVID-19 initiated are set to continue rever-berating into the future. (shrink)

The aim of this paper is to evaluate the critical success factors and investigate the benefits that might be gained once implementing Electronic Customer Relationship Management at HEI from employee perspective. The study conducted at Al Quds Open University in Palestine and data collected from (300) employee through a questionnaire which consist of four variables. A number of statistical tools were intended for hypotheses testing and data analysis, including Spearman correlation coefficient for Validity, reliability correlation using Cronbach’s alpha, and Frequency (...) and Descriptive analysis. The overall findings of the current study show that all the features were important for staff and it was critical success factors, at the same time, websites were providing all the features discussed by the theory whereas staff showed their willingness to use those features if provided. It is also discovered that implementing Electronic Customer Relationship Management can cause staff retention, were provided efficiently and needed to be improved. Research limitations: The survey findings were based on QOU employee in Palestine, UAE and KSA branches not included in the study. (shrink)

Stephen Law developed a challenge to theism, known as the evil-god challenge (Law (2010) ). The evil-god challenge to theism is to explain why the theist’s responses to the problem of evil are any better than the diabolist’s – who believes in a supremely evil god – rejoinders to the problem of good, when all the theist’s ploys (theodicy, sceptical theism, etc.) can be parodied by the diabolist. In the first part of this article, I extend the evil-god challenge by (...) showing that additional theist replies to the problem of evil (more theodicies, the privation view of evil, and others) also may be appropriated, with just as much plausibility, in support of the diabolist position. In the second part of the article, I defend the evil-god challenge against several objections. (shrink)

The standard view of "believes" and other propositional attitude verbs is that such verbs express relations between agents and propositions. A sentence of the form “S believes that p” is true just in case S stands in the belief-relation to the proposition that p; this proposition is the referent of the complement clause "that p." On this view, we would expect the clausal complements of propositional attitude verbs to be freely intersubstitutable with their corresponding proposition descriptions—e.g., "the proposition that p"—as (...) they are in the case of "believes." In many cases, however, intersubstitution of that-clauses and proposition descriptions fails to preserve truth value or even grammaticality. These substitution failures lead some philosophers to reject the standard view of propositional attitude reports. Others conclude that propositional attitude verbs are systematically ambiguous. I reject both these views. On my view, the that-clause complements of propositional attitude verbs denote propositions, but proposition descriptions do not. (shrink)

I defend the view that a reason for someone to do something is just a reason why she ought to do it. This simple view has been thought incompatible with the existence of reasons to do things that we may refrain from doing or even ought not to do. For it is widely assumed that there are reasons why we ought to do something only if we ought to do it. I present several counterexamples to this principle and reject some (...) ways of understanding "ought" so that the principle is compatible with my examples. I conclude with a hypothesis for when and why the principle should be expected to fail. (shrink)

Extensive measurement is the standard measurement-theoretic approach for constructing a ratio scale. It involves the comparison of objects that can be concatenated in an additively representable way. This paper studies the implications of extensively measurable welfare for social choice theory. We do this in two frameworks: an Arrovian framework with a fixed population and no interpersonal comparisons, and a generalized framework with variable populations and full interpersonal comparability. In each framework we use extensive measurement to introduce novel domain restrictions, independence (...) conditions, and constraints on social evaluation. We prove a welfarism theorem for these domains and characterize the social welfare functions that satisfy the axioms of extensive measurement at both the individual and social levels. The main results are simple axiomatizations of strong dictatorship in the Arrovian framework and classical utilitarianism in the generalized framework. (shrink)

Is shadowboxing an effective form of functional exercise? What physiological and morphological changes result from an exercise program based exclusively on shadowboxing for 3 weeks? To date, no empirical research has focused specifically on addressing these questions. Since mixed martial arts (MMA) is the fastest growing sport in the world, and since boxing and kickboxing fitness classes are among the most popular in gyms and fitness clubs worldwide, the lack of research on shadowboxing and martial arts-based fitness programs in the (...) extant literature is a shortcoming that the present article aims to address. This case study involved a previously sedentary individual engaging in an exercise program based exclusively on shadowboxing for 3 weeks. Body composition and heart rate data were collected before, throughout, and upon completion of the 3-week exercise program to determine the effectiveness of shadowboxing for functional fitness purposes. An original shadowboxing program prepared by an Everlast Master Instructor and NASM Certified Personal Trainer (NASM-CPT) and Performance Enhancement Specialist (NASM-PES) was used for this 3-week period. The original shadowboxing program with goals, techniques, and combinations to work on throughout the 3-week program is included in this article. This case study demonstrates that a 3-week exercise program based exclusively on shadowboxing can increase aerobic capacity, muscle mass, bone mass, basal metabolic rate, and daily calorie intake, and decrease resting heart rate, fat mass, body fat percentage, and visceral fat rating in a previously sedentary individual. The results of this research demonstrate that shadowboxing can be a safe and effective form of exercise leading to morphological and physiological improvements including fat loss and increased aerobic capacity. The results of this research also demonstrate that the Tanita BC-1500 is a reliable tool for individuals to evaluate their own fitness progress over time. (shrink)

I argue that an individual has aspects numerically identical with it and each other that nonetheless qualitatively differ from it and each other. This discernibility of identicals does not violate Leibniz's Law, however, which concerns only individuals and is silent about their aspects. They are not in its domain of quantification. To argue that there are aspects I will appeal to the internal conflicts of conscious beings. I do not mean to imply that aspects are confined to such cases, but (...) the best way to start is to recognize them experientially. We can feel the conflicts within ourselves. In doing so we can feel some of our aspects. I will try to enhance our understanding of the concept of aspect by listing and formalizing some principles for its use. After that I will argue that all sorts of individual things have aspects, not just people who are conflicted. (shrink)

This paper considers three possible ways of understanding the claim that the American criminal justice system is racist: individualist, “patterns”-based, and ideology-based theories of institutional racism. It rejects an individualist explanation of institutional racism because such an explanation fails to explain the widespread prevalence of anti-black racism in this system or indeed in the United States. It considers a “patterns” account of institutional racism, where consistent patterns of disparate racial effect mimic the structure of intentional projects of racial subjugation like (...) slavery or Jim Crow. While a “patterns” account helpfully directs attention to the effects of policies and practices that make up an institution, it does not fully explain the deep roots of anti-blackness in the criminal justice system in the United States. The paper concludes by defending an ideology-based theory of institutional racism for understanding the criminal justice system because the stereotype of the black criminal has a mutually reinforcing relationship with the patterns of disparate outcome for black people in the criminal justice system. This relationship creates a looping effect where the stereotype of the black criminal fuels the disproportionate involvement of black people in the criminal justice system, and the disproportionate representation of black people with felony records, in prisons, brutalized in police encounters, and so on reinforces the idea that black people are especially prone to criminality. Ideological approaches to racism that integrate attention to the patterns of disparate effect best explain what it means to say that the criminal justice system is racist. (shrink)

This paper seeks to extend my recent work on quantum perception (Rosen, 2021) to the phenomenon of quantum entanglement. In the first section, I summarize the earlier work, noting how the conventional approach to observing photons is rooted in an objectivist philosophy that serves as an obstacle to probing the underlying quantum reality. In the summary provided, I bring out the intimate relationship between observer and observed in the quantum world, and the need for a new, proprioceptive mode of observation (...) linked to phenomenological philosophy. The second part of the paper builds on the earlier effort by applying the proprioceptive observation of photons to the phenomenon of entanglement. The basic proposition is that proprioceptive observers of entangled photons may become entangled with each other. I propose an experiment that tests this hypothesis. In concluding, I explore the possibility that a quantum internet of proprioceptively engaged participants could create an ontologically entangled society. (shrink)

Against caricatures of the poet-philosopher Friedrich Schiller as an unoriginal popularizer of Kant, or a forerunner of totalitarianism, Frederick Beiser reinterprets him as an innovative, classical republican, broadening his analysis to include Schiller’s poetry, plays, and essays not widely available in English translation, such as the remarkable essay, “On Grace and Dignity.” In that spirit, the present article argues that the latter text, misperceived by Anglophone critics as self-contradictory, is better understood as centering on gender and dance. In brief, grace (...) is a virtuous power of beautiful gestures associated with women, while dignity is a power of sublime gestures associated with men, and the improvised combination thereof is a divinely androgynous power of gesture that I term “stateliness,” in a three-step choreography of aesthetic education. (shrink)

I argue that the three strongest arguments against metaphysical libertarianism—the randomness objection, the constitutive luck objection, and the physicalist objection—are actually unsuccessful and therefore that metaphysical libertarianism is more plausible than the common philosophical wisdom allows. My more positive thesis, what I will refer to as “Agent Exceptionalism,” is that, when making decisions and performing actions, human beings can indeed satisfy the four conditions of metaphysical libertarianism: the control condition, the rationality condition, the ultimacy condition, and the physicalism condition.

This Discussion Piece is a response to Mark Windsor's Discussion Piece (2023) 'Photographic Registers are Latent Images', which is a response to my article, (2021) 'Invisible Images and Indeterminacy: Why we need a Multi-stage Account of Photography' JAAC 79(2) 161-174.. -/- I argue that a photosensitive surface does not produce invisible pictorial features when it is exposed to light, and conclude, contra Windsor, that a photographic register is not a latent image. I argue that Windsor does not succeed in defending (...) a single-stage account of photography and I reconfirm that a multi-stage account is correct. (shrink)

The study aimed to investigate the reality of spreading the culture of entrepreneurship at Al-Azhar University from the point of view of students of the Faculty of Engineering and Information Technology and diagnose the most important obstacles that limit its activation. The researchers used the descriptive approach (survey) to achieve the objectives of the study, and relied on the questionnaire as a tool for applied study. The study concluded that: The reality of spreading the culture of entrepreneurship at Al-Azhar University (...) from the point of view of the students participating in the study came with an average degree of approval, while the most important obstacles and possible proposals for activating it came with a high degree of approval, which indicates the existence of strengths of Al-Azhar University in spreading the culture of entrepreneurship among students. Deficiencies must be corrected through proposals. In light of the results of the study, it was possible to develop a number of recommendations that can contribute to activating the culture of entrepreneurship at Al-Azhar University. Including the establishment of a specialized center for entrepreneurship within the university, develop a declared strategic plan to spread and develop the culture of entrepreneurship, allocate a sufficient budget to sponsor and support entrepreneurial ideas and projects for students and provide specialized cadres and certified trainers in the field of entrepreneurship. (shrink)

Organismal death is foundational to the evolution of life, and many biological concepts such as natural selection and life history strategy are so fashioned only because individuals are mortal. Organisms, irrespective of their organization, are composed of basic functional units—cells—and it is our understanding of cell death that lies at the heart of most general explanatory frameworks for organismal mortality. Cell death can be exogenous, arising from transmissible diseases, predation, or other misfortunes, but there are also endogenous forms of death (...) that are sometimes the result of adaptive evolution. These endogenous forms of death—often labeled programmed cell death, PCD—originated in the earliest cells and are maintained across the tree of life. Here, we consider two problematic issues related to PCD (and cell mortality generally). First, we trace the original discoveries of cell death from the nineteenth century and place current conceptions of PCD in their historical context. Revisions of our understanding of PCD demand a reassessment of its origin. Our second aim is thus to structure the proposed origin explanations of PCD into coherent arguments. In our analysis we argue for the evolutionary concept of PCD and the viral defense-immunity hypothesis for the origin of PCD. We suggest that this framework offers a plausible account of PCD early in the history of life, and also provides an epistemic basis for the future development of a general evolutionary account of mortality. (shrink)

This paper explores the idea of robust discursive equality on which respect-based conceptions of justificatory reciprocity often draw. I distinguish between formal and substantive discursive equality and argue that if justificatory reciprocity requires that people be accorded formally equal discursive standing, robust discursive equality should not be construed as requiring standing that is equal substantively, or in terms of its discursive purchase. Still, robust discursive equality is purchase sensitive: it does not obtain when discursive standing is impermissibly unequal in purchase. (...) I then showcase different candidate conceptions of purchase justice, and draw conclusions about the substantive commitments of justificatory reciprocity. (shrink)

This is an earlier version of the argument presented as the appendix to the author's final book, Peri Physeos.

Ideas for integrating AI into politics are now emerging and advancing at accelerating pace. This chapter highlights a few different varieties and show how they reflect different assumptions about the value of democracy. We cannot make informed decisions about which, if any, proposals to pursue without further reflection on what makes democracy valuable and how current conditions fail to fully realize it. Recent advances in political philosophy provide some guidance but leave important questions open. If AI advances to a state (...) where it can secure superior political outcomes, leading perspectives in political philosophy suggest that democracy may become obsolete. If we find this suggestion troubling, we need to put the case for democracy on stronger foundations. (shrink)

Mango is an economically significant fruit crop cultivated in various tropical and subtropical regions around the world. However, the productivity and quality of mangoes can be severely impacted by a range of pests. This research paper introduces an innovative approach to identify mango pests using an expert system. The expert system integrates knowledge from entomology and plants to provide accurate identification of common mango pests. The paper outlines the development and implementation of the expert system using Clips shell, which utilizes (...) rule-based techniques to analyze symptoms associated with mango pests. By inputting observed symptoms, such as leaf spots, fruit damage, leaf mild and stem cankers the system can accurately identify the specific pest species affecting the mango tree. For each pest, the paper discusses their specific symptoms and Favorable conditions that affect the mango plant. By understanding the identification and symptoms of these pests, mango growers and agricultural professionals can implement appropriate pest management strategies to mitigate the economic losses caused by these insects. The research presented in this paper aims to contribute to the body of knowledge on mango pest management, facilitating sustainable mango production and ensuring the availability of high-quality mangoes in global markets. (shrink)

Abortion bans have been characterized as cruel especially in not allowing exceptions for rape or incest. The article first examines one approach to morally justifying bans based on the Doctrine of Double Effect (DDE) which distinguishes morally between killing or letting die intending death versus doing so only foreseeing death. It then presents some criticisms of the implications of the DDE but also argues that what the doctrine permits helps provide a ground for the permissibility of abortions even if the (...) fetus is a person. Whether there are limits on applying this argument is also considered. In conclusion, the article considers whether and why not permitting exceptions to bans for rape and incest is cruel and whether cruelty is a ground for opposition to bans. (shrink)

This paper argues for a conception of the natural rights of non-human animals grounded in Kant’s explanation of the foundation of human rights. The rights in question are rights that are in the first instance held against humanity collectively speaking—against our species conceived as an organized body capable of collective action. The argument proceeds by first developing a similar case for the right of every human individual who is in need of aid to get it, and then showing why the (...) situation of animals is similar. I first review some of the reasons why people are resistant to the idea that animals might have rights. I then explain Kant’s conception of natural rights. I challenge the idea that duties of aid and duties of kindness to animals fit the traditional category of “imperfect duties” and argue that they are instead cases of “imperfect right.” I explain how you can hold a right against a group, and why it is legitimate to conceive of humanity as such a group. I then argue that Kant’s account of the foundation of property rights is grounded in a conception of the common possession of the Earth that grounds a right to aid and the rights of animals to be treated in ways that are consistent with their good. Finally, I return to the objections to the idea that animals have rights and offer some responses to them. (shrink)

We critique two popular philosophical definitions of intellectual humility: the “low concern for status” and the “limitations-owning.” accounts. Based upon our analysis, we offer an alternative working definition of intellectual humility: the virtue of accurately tracking what one could non-culpably take to be the positive epistemic status of one’s own beliefs. We regard this view of intellectual humility both as a virtuous mean between intellectual arrogance and diffidence and as having advantages over other recent conceptions of intellectual humility. After defending (...) this view, we sketch remaining questions and issues that may bear upon the psychological treatment of intellectual humility such as whether evidence will help determine how this construct relates to general social humility on the one hand, and intellectual traits such as open-mindedness, curiosity, and honesty on the other. (shrink)

The author presents reasons for thinking that the evil we observe in the world is not even prima facie evidence against the existence of God.

Readers assume that commonplace properties of the real world also hold in realistic fiction. They believe, for example, that the usual physical laws continue to apply. But controversy exists in theories of fiction about whether real individuals exist in the story’s world. Does Queen Victoria exist in the world of Jane Eyre, even though Victoria is not mentioned in it? The experiments we report here find that when participants are prompted to consider the world of a fictional individual (“Consider the (...) world of Jane Eyre…”), they are willing to say that a real individual (e.g., Queen Victoria) can exist in the same world. But when participants are prompted to consider the world of a real individual, they are less willing to say that a fictional individual can exist in that world. The asymmetry occurs when we ask participants both if a real person is in the character’s world and if the person would appear there. However, the effect is subject to spatial and temporal constraints. When the person and the character share spatial and temporal settings, interchange is more likely to occur. These results shed light on the author’s implicit contract with the reader, which can license the reader to augment a fictional world with features that the author only implicates as part of the work’s background. (shrink)

There is a curious phenomenon where people from marginalized populations are taken to be arrogant when they show no signs of superiority. In effect, their actions are misconstrued, and their attitudes are rendered unintelligible. Given that arrogance is standardly taken to be a flaw in one’s moral character, understanding such misattributions should give us insight into the affective marginalization many people face. This talk aims to give a thorough exploration of arrogance under oppression. I argue that arrogance is a kind (...) of self-preoccupation that involves projecting one’s values, goals, and concerns onto others as if they were objective values, goals, and concerns. When the affectively marginalized communicate their self-respect through things like protest, people mistake that self-respect as self-preoccupation given how the affectively marginalized are constructed. Furthermore, given how affective marginalization not only inhibits how the marginalized are understood by others, but inhibits their own affective lives, I argue that taking up an arrogant attitude is not always morally vicious, but can be a beautiful form of political resistance but all things considered good. (shrink)

Philosophers of race and other writers in the Black and Latinx intellectual traditions have remarked on what it is like to live under “the racial gaze,” to be shaped and limited by the way whites perceive us. However, little work has been spent developing how the racial gaze functions in whites’, and other racially privileged people’s, moral psychology. I argue in this paper that there is a morally objectionable way of perceiving people of color. This claim builds on an insight (...) from Iris Murdoch that our perception can be morally evaluable and extends it to issues of race. I articulate how racial stereotypes and misvaluing distort one’s perception of people of color and that these distortions are organizing around a dominant conception for race that plays an important role in the oppression of people of color. I believe understanding racist perception lays a foundation for understanding the moral dimensions of interpersonal (as opposed to structural) racism. (shrink)

ABSTRACT According to David Lewis, alteration is "qualitative difference between temporal parts of something." It follows that moments, since they are simple and lack temporal parts, cannot alter from future to present to past. Here then is another way to put McTaggart's paradox about change in tense. I will appeal to my theory of Aspects to rebut the thought behind this rendition of McTaggart. On my theory, it is possible that qualitatively differing things be numerically identical. I call these differing, (...) numerically identical things "aspects." I will argue that alteration can be a qualitative difference between temporal aspects of something that lacks temporal parts. So a moment can alter in tense. By rejecting Lewis's assumption my theory can solve this version of McTaggart's paradox. (shrink)