Abstract: The COVID-19 pandemic has posed unprecedented challenges to global healthcare systems, necessitating accurate and timely forecasting of cases for effective mitigation strategies. In this research paper, we present a novel approach to predict COVID-19 cases using Artificial Neural Networks (ANNs), harnessing the power of machine learning for epidemiological forecasting. Our ANNs-based forecasting model has demonstrated remarkable efficacy, achieving an impressive accuracy rate of 97.87%. This achievement underscores the potential of ANNs in providing precise and data-driven insights into the dynamics (...) of the pandemic. However, this paper underscores the critical importance of a comprehensive evaluation beyond accuracy, including metrics such as sensitivity, specificity, and the area under the ROC curve (AUC-ROC), to assess the model's performance robustness. The research paper offers detailed insights into the architecture of the ANN model, encompassing critical hyperparameters, data preprocessing techniques, and regularization strategies employed to optimize model accuracy. Ethical considerations surrounding data privacy and potential biases within the COVID-19 dataset are also addressed. While the achieved accuracy is a significant milestone, this study underscores the dynamic and evolving nature of the pandemic, necessitating continuous model refinement and validation. Furthermore, it emphasizes the importance of considering false positives and false negatives in the context of public health decision-making. In conclusion, this research contributes to the arsenal of tools available for pandemic management by showcasing the potential of ANNs in COVID-19 case forecasting. It encourages ongoing exploration and adaptation of predictive models to enhance their applicability in real-world public health scenarios, ultimately contributing to more effective pandemic control and response efforts. (shrink)

Abstract: Colon cancer is a prevalent and life-threatening disease, necessitating accurate and timely diagnosis for effective treatment and improved patient outcomes. This research paper presents the development of a knowledge-based system for diagnosing colon cancer using the CLIPS language. Knowledge-based systems offer the potential to assist healthcare professionals in making informed diagnoses by leveraging expert knowledge and reasoning mechanisms. The methodology involves acquiring and structuring medical knowledge specific to colon cancer, followed by the implementation of a knowledge- based system using (...) CLIPS. The system's design integrates relevant medical databases and employs advanced reasoning mechanisms to facilitate accurate diagnosis. Evaluation results demonstrate the system's effectiveness, with high accuracy and sensitivity rates compared to existing methods. The findings highlight the potential of knowledge-based systems in improving clinical practice and patient care. The research contributes to the growing field of medical informatics by demonstrating the feasibility and effectiveness of CLIPS-based knowledge systems for colon cancer diagnosis. Future research can focus on enhancing system performance and expanding its scope to encompass other types of cancer diagnoses. (shrink)

Abstract: Tomatoes are part of the major crops in food security. Tomatoes are plants grown in temperate and hot regions of South American origin from Peru, and then spread to most countries of the world. Tomatoes contain a lot of vitamin C and mineral salts, and are recommended for people with constipation, diabetes and patients with heart and body diseases. Studies and scientific studies have proven the importance of eating tomato juice in reducing the activity of platelets in diabetics, which (...) helps in protecting them from developing deadly blood clots. A tomato classification approach is presented with a data set containing approximately 5,266 images with 7 species belonging to tomatoes. The Neural Network Algorithms (CNN), a deep learning technique applied widely in image recognition, is used for this task. (shrink)

This research paper presents the development and evaluation of an expert system for diagnosing kidney diseases. The expert system utilizes a decision-making tree approach and is implemented using the CLIPS and Delphi frameworks. The system's accuracy in diagnosing kidney diseases and user satisfaction were evaluated. The results demonstrate the effectiveness of the expert system in providing accurate diagnoses and high user satisfaction.

Vertigo is a common symptom that can result from various underlying diseases and conditions, ranging from benign to severe. Accurate and timely diagnosis of the cause of vertigo is crucial for appropriate management and treatment. In this research, we propose the development of an expert system for vertigo diseases diagnosis, utilizing artificial intelligence (AI) and the proposed Expert System which was produced to help assist healthcare professionals in diagnosing the cause of vertigo based on a patient's symptoms, medical history, and (...) other relevant clinical information. The proposed expert system presents an overview about vertigo diseases are given, the cause of disease is outlined and the treatment or recommendation of disease whenever possible is given out. CLIPS language was used for designing and implementing the proposed expert system. The potential of the proposed expert system lies in its ability to enhance the accuracy and efficiency of vertigo diagnosis, as well as assist in the proper referral and management of patients. (shrink)

The article entitled “Cultural evolution in Vietnam’s early 20th century: A Bayesian networks analysis of Hanoi Franco-Chinese house designs” investigates how diverse cultures and religious creeds influenced the architecture of Hanoi in the early 20th century.

Every person has his/her own unique signature that is used mainly for the purposes of personal identification and verification of important documents or legal transactions. There are two kinds of signature verification: static and dynamic. Static(off-line) verification is the process of verifying an electronic or document signature after it has been made, while dynamic(on-line) verification takes place as a person creates his/her signature on a digital tablet or a similar device. Offline signature verification is not efficient and slow for a (...) large number of documents. To overcome the drawbacks of offline signature verification, we have seen a growth in online biometric personal verification such as fingerprints, eye scan etc. In this paper we created CNN model using python for offline signature and after training and validating, the accuracy of testing was 99.70%. (shrink)

Abstract: In this study, we explore the possibility of classifying the plant species. We collected the plant species from Kaggle website. This dataset encompasses 544 samples, encompassing 136 distinct plant species. Recent advancements in machine learning, particularly Artificial Neural Networks (ANNs), offer promise in enhancing plant Species classification accuracy and efficiency. This research explores plant Species classification, harnessing neural networks' power. Utilizing a rich dataset from Kaggle, containing 544 entries, we develop and evaluate a neural network model. Our neural network, (...) featuring a single hidden layer, achieves remarkable results—a staggering 100% accuracy and a minute average error rate of 0.002. Beyond performance metrics, we delve into the intricacies of plant Species classification through feature importance analysis. The most influential features— Vegsout, durflow, semiros, pdias, begflow, wind, leafy, autopoll and insects— uncover the physiological traits underpinning accurate rice classification. This research contributes to advancing rice classification methods and highlights the potential of ANNs in optimizing agricultural practices, ensuring plant safety, and bolstering global trade. (shrink)

Accurate assessment and comprehension of smoking behavior are pivotal for elucidating associated health risks and formulating effective public health strategies. In this study, we introduce an innovative approach to predict and analyze smoking prevalence using an artificial neural network (ANN) model. Leveraging a comprehensive dataset spanning multiple years and geographic regions, our model incorporates various features, including demographic data, economic indicators, and tobacco control policies. This research investigates smoking trends with a specific focus on gender-based analyses. These findings are pivotal (...) for enhancing public health initiatives aimed at mitigating tobacco use, assessing associated health risks, and mitigating smoking-related diseases. (shrink)

Abstract: As artificial intelligence (AI) technologies become increasingly integrated into various sectors, ethical considerations surrounding their development and deployment have become paramount. This paper explores the multifaceted ethical landscape of AI, focusing on key challenges such as bias, transparency, privacy, and accountability. It examines how these issues manifest in AI systems and their impact on society. The paper also evaluates current approaches and solutions aimed at mitigating these ethical concerns, including regulatory frameworks, ethical guidelines, and best practices for AI design. (...) By providing a comprehensive analysis of these challenges and solutions, this paper aims to contribute to the ongoing discourse on responsible AI development and implementation, advocating for a balance between technological innovation and ethical integrity. (shrink)

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

This paper argues that Immanuel Kant’s practical philosophy contains a coherent, albeit implicit, defense of the legitimacy of capital punishment, one that refutes the most important objections leveled against it. I first show that Kant is consistent in his application of the ius talionis. I then explain how Kant can respond to the claim that death penalty violates the inviolable right to life. To address the most significant objection – the claim that execution violates human dignity – I argue that (...) motives of honor, as Kant conceives it, require a rational person to will her own execution, were she to commit murder. (shrink)

The aim of this critical commentary is to distinguish and analytically discuss some important variations in which legal moralism is defined in the literature. As such, the aim is not to evaluate the most plausible version of legal moralism, but to find the most plausible definition of legal moralism. As a theory of criminalization, i.e. a theory that aims to justify the criminal law we should retain, legal moralism can be, and has been, defined as follows: the immorality of an (...) act of type A is a sufficient reason for the criminalization of A, even if A does not cause someone to be harmed. In what follows, I critically examine some of the key definitions and proposals that have, unfortunately, not always been carefully distinguished. Finally, I propose a definition that seems to capture the essence of what many philosophers refer to when they talk about legal moralism, while also providing more clarity. (shrink)

Five arguments are presented in favour of the proposal that people who opt in as organ donors should receive a tax break. These arguments appeal to welfare, autonomy, fairness, distributive justice and self-ownership, respectively. Eight worries about the proposal are considered in this paper. These objections focus upon no-effect and counter-productiveness, the Titmuss concern about social meaning, exploitation of the poor, commodification, inequality and unequal status, the notion that there are better alternatives, unacceptable expense, and concerns about the veto of (...) relatives. The paper argues that none of the objections to the proposal is very telling. (shrink)

This chapter picks up on what Heidegger in his 1949 ‘Letter on ‘Humanism’’ calls ‘the historical in being’, that dimension of being within which, for Heidegger, a ‘productive dialogue’ between phenomenology and existentialism, on the one hand, and Marxism, on the other, ‘first becomes possible.’ It introduces the possibility of this dialogue through a particular, and particularly revealing, problem with The German Ideology: namely, Marx and Engels offer no analysis of the relationship between time, temporality and their materialist concept of (...) history. (shrink)

About 80 % of all convicted have had a prior record of conviction. But how should the state punish repeat offenders (with a prior conviction) as compared with first-time offenders who are convicted? The law in all jurisdictions, a large swathe of public opinion, and the general trend within criminal justice ethics all seem to accept what we may call: -/- Asymmetry A The punishment of repeat offenders should be harsher than the punishment of first-time offenders. -/- This asymmetry is (...) obviously just a rough structure. It leaves a lot of room for interpretation. Several retributivists have argued for progressive loss of mitigation (PLM). On this view, a first-time offender receives a discount on punishment that is gradually lost if he re-offends. When the discount is lost the offender receives the full punishment, and re-offending from that point on will be punished equally. However, recently some retributivists have argued in favour of a cumulative principle (CP) according to which an offender will progressively be punished more severely the more convictions he has accumulated. In sum, in the theoretical literature on the subject, Asymmetry A has been the mantra for several prominent retributivists. The aim of this paper is to point to an all but overlooked logical point in the discussion of punishment and recidivism. This is the point that it follows, from retributivism, that there is a reason - at least in some situations, as we shall see - to support what we may call: -/- Asymmetry B The punishment of repeat offenders should be more lenient than the punishment of first-time offenders. (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)

This study presents the Accra Confession as a theological response to the ecological crisis from a Reformed perspective while also addressing its critical weakness, namely the problem of universality in both Reformed ecclesiology and global approaches to ecological destruction. Because of a fragile universality, both Reformed churches and global institutions find it difficult to agree on a concrete plan to address climate change. Theologically, this difficulty arrives not primarily from disagreement with the existence or causes of climate change but how (...) Christian theological values translate concretely to acts of justice. This study proposes a way to ground these discussions on the concept of dangerous memory by resourcing the theology of Johann Baptist Metz. Dangerous memories allow stories of the suffering vanquished to be constitutive to the construction of caritas, which in turn serves as a suitable theological foundation for addressing differing approaches to engaging climate issues. Reading the Accra Confession as dangerous memory, then, provides a valuable resource to the Reformed community by allowing the testimonies of those affected adversely by climate change to substantially inform theological discourses on climate justice. (shrink)

After the terrorist attacks of September 11, 2001, most legacy airlines filed for bankruptcy protection as a way to cut costs drastically, with the exception of American Airlines. This article applies the Principle of Double-Effect to the act of filing for Chapter 11 bankruptcy protection for reasons of management strategy, in particular, cost-cutting. It argues that the Principle can be a useful tool for discerning the ethicality of the action, and demonstrates the usefulness by proposing three double-effect criteria that, when (...) fulfilled, argues for the ethical justifiability the action in question. (shrink)

Until recently, theorists of creativity have consistently maintained that two necessary conditions must be satisfied in order for us to legitimately ascribe creativity to a given phenomenon: a) that it exhibit novelty, and b) that it possess value. However, researchers investigating malevolent forms of creativity have claimed that the value condition is problematic insofar as we often ascribe creativity to products that are of entirely negative value for us. This has given rise to a number of modified conceptions of the (...) value condition, all of which I argue are inadequate (Sections 1 and 2). To address this issue, I advance a novel conception of creative value (Section 3). My contention is that even though malevolent creative products may be of net-negative value, they are nonetheless endowed with a degree of positive value for the predicating individual – that is, insofar as the salient originality of such products elicits an intrinsically-valuable affect of surprise. In Section 4 I then examine the way in which this affect promotes cultural flourishing and to that extent may be considered instrumentally valuable. The principal conclusion of these observations is that the existence of malevolent creativity does not genuinely controvert the standard view that creative products must possess positive value for the predicating individual. (shrink)

Aunque el derecho probatorio y el derecho procesal se han dedicado desde siempre al estudio de los problemas relacionados con las pruebas y el establecimiento de los hechos en los procesos judiciales, el énfasis ha estado siempre en el aspecto formal, doctrinal y procedimental en detrimento de los fundamentos filosóficos y teóricos. Durante los últimos años ha habido un intento sostenido de explorar estos fundamentos combinando no sólo las herramientas tradicionales proporcionadas por la lógica, la gramática y la retórica, sino (...) también los avances hechos en ciencias como la estadística y la probabilidad, la medicina y la psicología forenses, la psicología de la percepción, la epistemología y la filosofía de la ciencia. El presente libro reúne las contribuciones de destacados juristas y filósofos latinoamericanos a esta nueva perspectiva interdisciplinaria, conocida como epistemología jurídica. El libro está dividido en tres grandes temas: la primera parte explora los problemas epistemológicos del conocimiento de los hechos en los procesos judiciales; la segunda se enfoca en el problema de los estándares de prueba; y la sección final discute el testimonio de los expertos. En su conjunto el libro ofrece un panorama tanto de los problemas centrales de la epistemología jurídica, como del estado del arte de la disciplina. (shrink)

Рассмотрена историческая периодизация формирования цивилизационного подхода. Определен потенциал локальных цивилизаций в ХХІ веке. Исследована цивилизационная структура мировой экономики. Предложен подход к идентификации принадлежности стран к современным локальным цивилизациям. Определены доминирующие локальные цивилизации и их влияние на социально-экономическое развитие общества.

The development of mankind and its concrete manifestations in technical, economic or other spheres is always determined by contradictions, uncertainty and the emergence of non-standard circumstances. At the beginning of the third millennium the world is characterized by acceleration of economic dynamics and complication of the mega environment, which requires mastering the realities of the present and the future. Exactly this problem that necessitates the definition of the Concept and priorities of the direction of socio-economic policy in Ukraine and conducting (...) further research in the field of developing the application framework for their implementation. Definition and development of the paradigm of socio-economic development of Ukraine in the XXI century will create an opportunity to reveal socio-economic and human potential. (shrink)

The current study is conducted to examine the following research questions: 1) How are the father’s interactions with children regarding waste recycling associated with the children’s recycling behaviors? 2) How are the mother’s interactions with children regarding waste recycling associated with the children’s recycling behaviors?

Although social scientists have identified diverse behavioral patterns among children from dissimilarly structured families, marketing scholars have progressed little in relating family structure to consumption-related decisions. In particular, the roles played by members of single-mother families—which may include live-in grandparents, mother’s unmarried partner, and step-father with or without step-sibling(s)—may affect children’s influence on consumption-related decisions. For example, to offset a parental authority dynamic introduced by a new stepfather, the work-related constraints imposed on a breadwinning mother, or the imposition of adult-level (...) household responsibilities on children, single-mother families may attend more to their children’s product preferences. -/- Without a profile that includes socio-economic, behavioral, and psychological aspects, efficient and socially responsible marketing to single-mother households is compromised. Relative to dual-parent families, single-mother families tend to have fewer resources and less buying power, children who consume more materialistic and compulsively, and children who more strongly influence decision making for both own-use and family-use products. Timely research would ensure that these and other tendencies now differentiate single-mother from dual-parent families in ways that marketers should address. Hence, our threefold goal is (1) to consolidate and highlight gaps in existing theory applied to studying children’s influence on consumption-related decision making in single-mother families, and (2) to propose a hybrid framework that merges two theories conducive to such research, and (3) to identify promising research propositions for future research. (shrink)

Consumer behavior analytics has become a pivotal aspect for businesses to understand and predict customer preferences and actions. The advent of machine learning (ML) algorithms has revolutionized this field by providing sophisticated tools for data analysis, enabling businesses to make data-driven decisions. However, the effectiveness of these ML algorithms significantly hinges on the optimization techniques employed, which can enhance model accuracy and efficiency. This paper explores the application of various optimization techniques in consumer behaviour analytics using machine learning algorithms. By (...) focusing on the optimization of key parameters, the study aims to improve the predictive power of models and reduce computational costs. (shrink)

This paper critically engages Philip Mirowki's essay, "The scientific dimensions of social knowledge and their distant echoes in 20th-century American philosophy of science." It argues that although the cold war context of anti-democratic elitism best suited for making decisions about engaging in nuclear war may seem to be politically and ideologically motivated, in fact we need to carefully consider the arguments underlying the new rational choice based political philosophies of the post-WWII era typified by Arrow's impossibility theorem. A distrust of (...) democratic decision-making principles may be developed by social scientists whose leanings may be toward the left or right side of the spectrum of political practices. (shrink)

Data preparation, feature engineering, model training, and performance evaluation are all part of the study methodology. To ensure reliable and broadly applicable models, we utilize optimization techniques like Grid Search and Genetic Algorithms to precisely adjust model parameters. Features including age, blood pressure, cholesterol levels, and lifestyle choices are employed as inputs for the machine learning models in the dataset, which consists of patient medical information. The predictive capacity of the model is evaluated using evaluation measures, such as accuracy, precision, (...) recall, F1-score, and the area under the ROC curve (AUC-ROC). Our findings show that improved machine learning models perform better than conventional methods, offering trustworthy forecasts that can help medical practitioners with early diagnosis and individualized treatment planning. In order to achieve even higher predicted accuracy, the study's conclusion discusses the significance of its findings for clinical practice as well as future improvements that might be made, like adding wearable device data in real-time or investigating deep learning techniques. (shrink)

The world's leading cause of morbidity and death is cardiovascular diseases (CVD), which makes early detection essential for successful treatments. This study investigates how optimization techniques can be used with machine learning (ML) algorithms to forecast cardiovascular illnesses more accurately. ML models can evaluate enormous datasets by utilizing data-driven techniques, finding trends and risk factors that conventional methods can miss. In order to increase prediction accuracy, this study focuses on adopting different machine learning algorithms, including Decision Trees, Random Forest, Support (...) Vector Machines, and Neural Networks, that have been tuned using strategies including hyper parameter selection, crossvalidation, and feature selection. (shrink)

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

The research methodology involves data preprocessing, feature engineering, model training, and performance evaluation. We employ optimization methods such as Genetic Algorithms and Grid Search to fine-tune model parameters, ensuring robust and generalizable models. The dataset used includes patient medical records, with features like age, blood pressure, cholesterol levels, and lifestyle habits serving as inputs for the ML models. Evaluation metrics, including accuracy, precision, recall, F1-score, and the area under the ROC curve (AUC-ROC), assess the model's predictive power.

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. Furthermore, the implementation of an optimized keyword indexing mechanism facilitates fast and accurate search operations, making the protocol well-suited for real-time IoT applications. Extensive experiments were conducted using various IoT datasets to evaluate the performance of the proposed protocol in terms of encryption speed, search efficiency, and overall security. The results demonstrate that the optimized encryption protocol significantly outperforms existing methods, offering a scalable solution that meets the stringent requirements of IoT systems. This research contributes to the field by providing a practical and secure encryption solution that addresses the unique challenges of IoT environments, paving the way for more secure and efficient IoT networks. (shrink)

The producers of Automobile products innovated a new thought of designing the two- wheelers in such a way to attract the women. Today most of the women prefer to travel through two-wheelers. A wide variety of two-wheelers of all category light- weighted, medium – weighted and heavy weighted vehicles have been introduced in the market. The objective of the study is to know the preference and satisfaction of women consumers over two-wheelers and the various aspects, which determines the purchase or (...) buying behavior and to know the expectations of women consumers over two-wheelers. The sample size of the study was conducted in Tiruchirappalli city with 75 respondents through Non-Probability Random Sampling Method. (shrink)

This article defends the conclusion that the soccer World Cup in Qatar should not be boycotted by rich countries from the Global North. This conclusion is underpinned by considerations about the economic background conditions in guest workers’ home countries. Three arguments are considered for the view that the World Cup should be boycotted. It is argued that each of these arguments is unsound. Section 7 contains a discussion of an argument for a boycott that centers on the process through which (...) Qatar was awarded the World Cup. This argument is rejected. The article lists several ways in which guest workers in Qatar are wronged, but this fact about how guest workers are treated does not justify a boycott by rich countries from the Global North. (shrink)

In the first chapter of his Knowledge and Lotteries, John Hawthorne argues that thinkers do not ordinarily know lottery propositions. His arguments depend on claims about the intimate connections between knowledge and assertion, epistemic possibility, practical reasoning, and theoretical reasoning. In this paper, we cast doubt on the proposed connections. We also put forward an alternative picture of belief and reasoning. In particular, we argue that assertion is governed by a Gricean constraint that makes no reference to knowledge, and that (...) practical reasoning has more to do with rational degrees of belief than with states of knowledge. (shrink)

As these opening quotes acknowledge, the Prisoner’s Dilemma (PD) represents a core puzzle within the formal mathematics of game theory.3 Its rise in conspicuity is evident figure 2.1 above demonstrating a relatively steady rise in incidences of the phrase’s usage between 1960 to 1995, with a stable presence persisting into the twenty first century. This famous two-person “game,” with a stock narrative cast in terms of two prisoners who each independently must choose whether to remain silent or speak, each advancing (...) self-interest at the expense of the other and thereby achieving a mutually suboptimal outcome, mires any social interaction it is applied to into perplexity. The logic of this game proves the inverse of Adam Smith’s invisible hand: individuals acting on self interest will achieve a mutually suboptimal outcome. However, as this chapter illuminates, the assumptions underlying game theory drive this conclusion. (shrink)

Consumer behavior analytics has become a pivotal aspect for businesses to understand and predict customer preferences and actions. The advent of machine learning (ML) algorithms has revolutionized this field by providing sophisticated tools for data analysis, enabling businesses to make data-driven decisions. However, the effectiveness of these ML algorithms significantly hinges on the optimization techniques employed, which can enhance model accuracy and efficiency. This paper explores the application of various optimization techniques in consumer behaviour analytics using machine learning algorithms. By (...) focusing on the optimization of key parameters, the study aims to improve the predictive power of models and reduce computational costs. (shrink)

Brought to you by: Crop X editors: Jonathan Alexander Perez, Harmony Smith, Corinne Tendorf, David Turturo, and Derek Rahn Williams. Faculty Advisor: David Turturo; Crop X team included: Chaimae Alehyane, Zachary S. Casey, Suzanna Brinez, Jacob Brown, Elizabeth George, Francisco Javier Muniz Ituarte, Brodey Myers. -/- Credits: Huckabee College of Architecture; Graphic Designers: Studio BLDG (Blossom Liu + Danny Gray); English Editor: Luke Studebaker; Spanish Translator: Jessie Forbes; Printer: Die Keure. Cover Photo: Derek Williams. -/- Generously supported by the Graham (...) Foundation for Advanced Studies in the Fine Arts and the Huckabee College of Architecture, Texas Tech University. (shrink)

The topic of this Handbook entry is the relationship between similarity and dimensional analysis, and some of the philosophical issues involved in understanding and making use of that relationship. Discusses basics of the relationship between units, dimensions, and quantities. It explains the significance of dimensionless parameters, and explains that similarity of a physical systems is established by showing equality of a certain set of dimensionless parameters that characterizes the system behavior. Similarity is always relative -- to some system behavior. Other (...) topics discussed: generalization of the notion of similarity, the difference between relative similarity and partial similarity; how the notion of similarity in science differs from similarity as it has been discussed in recent philosophy. Philosophers' views discussed: R. Giere, N. Goodman, P. Bridgman, and B. Ellis. (shrink)

How ought we to go about metaphysics? An examination of the two poles, Quine and Plato. Why we should be sceptical of the empiricist tendencies but equally wary of the transcendental underpinnings of Platonism. Could a phenomenological approach lead to a compromise?

Data access control is a challenging issue in public cloud storage systems. Ciphertext-Policy Attribute-Based Encryption (CP-ABE) has been adopted as a promising technique to provide flexible, fine-grained and secure data access control for cloud storage with honest-but- curious cloud servers. However, in the existing CP-ABE schemes, the single attribute authority must execute the time-consuming user legitimacy verification and secret key distribution, and hence it results in a single-point performance bottleneck when a CP-ABE scheme is adopted in a large-scale cloud storage (...) system. Users may be stuck in the waiting queue for a long period to obtain their secret keys, thereby resulting in low-efficiency of the system. Although multi authority access control schemes have been proposed, these schemes still cannot overcome the drawbacks of single-point bottleneck and low efficiency, due to the fact that each of the authorities still independently manages a disjoint attribute set. In this paper we propose a system that improves the approach of CP-ABE from text based asymmetric to Image based symmetric approach for faster encryption as well as access to data. We also propose a multiple access policy generation for single user where we will be able to implement one to many and many to many methodology. (shrink)

This essay represents a novel contribution to Nietzschean studies by combining an assessment of Friedrich Nietzsche’s challenging uses of “truth” and the “eternal return” with his insights drawn from Indian philosophies. Specifically, drawing on Martin Heidegger’s Nietzsche, I argue that Nietzsche’s critique of a static philosophy of being underpinning conceptual truth is best understood in line with the Theravada Buddhist critique of “self ” and “ego” as transitory. In conclusion, I find that Nietzsche’s “eternal return” can be understood as a (...) direct inversion of “nirvana”: Nietzsche celebrates profound attachment to each and every moment, independent from its pleasurable or distasteful registry. (shrink)

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. Extensive simulations are conducted using synthetic and real-world datasets to evaluate the performance of the proposed algorithm. The results demonstrate that the optimized load balancing approach outperforms traditional algorithms in terms of SLA compliance, resource utilization, and energy efficiency. The findings suggest that the integration of optimization techniques into load balancing algorithms can significantly enhance (...) the operational efficiency of data centers, paving the way for future advancements in autonomous and self-optimizing data centers. (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)

Define teleology as the view that requirements hold in virtue of facts about value or goodness. Teleological views are quite popular, and in fact some philosophers (e.g. Dreier, Smith) argue that all (plausible) moral theories can be understood teleologically. I argue, however, that certain well-known cases show that the teleologist must at minimum assume that there are certain facts that an agent ought to know, and that this means that requirements can't, in general, hold in virtue of facts about value (...) or goodness. I then show that even if we grant those 'ought's teleology still runs into problems. A positive justification of teleology looks like it will require an argument of this form: O(X); if X, then O(Y); therefore O(Y). But this form of argument isn't in general valid. I conclude by offering two positive suggestions for those attracted to a teleological outlook. (shrink)