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

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)

In today’s rapidly evolving business landscape, organizations must continuously adapt to stay competitive. AI-driven human resource (HR) analytics has emerged as a strategic tool to enhance workforce agility and inform decision-making processes. By leveraging advanced algorithms, machine learning models, and predictive analytics, HR departments can transform vast data sets into actionable insights, driving talent management, employee engagement, and overall organizational efficiency. AI’s ability to analyze patterns, forecast trends, and offer data-driven recommendations empowers HR professionals to make proactive decisions in hiring, (...) skill development, performance management, and retention. (shrink)

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

The 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)

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)

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)

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)

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

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

The 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)

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 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.

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 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)

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)

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)

The rapid adoption of telemedicine has transformed healthcare delivery, especially during the COVID-19 pandemic. This digital shift has enabled medical professionals to offer consultations and manage patients remotely, ensuring continuity of care while reducing exposure risks. However, the integration of telemedicine has presented both opportunities and challenges for doctors, particularly in terms of their work-life balance. This paper explores the digital adaptation of doctors in public and private hospitals concerning telemedicine practices and its impact on their work-life harmony. The study (...) highlights the advantages telemedicine offers, such as increased flexibility, reduced commuting time, and better time management. It also examines the challenges doctors face, including the demands of always being digitally accessible, the learning curve of new technologies, and the difficulty in maintaining boundaries between personal and professional life. Using both quantitative and qualitative data, this research compares the telemedicine adaptation experiences of doctors in public versus private hospitals, considering factors such as hospital infrastructure, support systems, and patient load. (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)

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.

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)

Well prior to the invention of the term ‘biology’ in the early 1800s by Lamarck and Treviranus, and also prior to the appearance of terms such as ‘organism’ under the pen of Leibniz in the early 1700s, the question of ‘Life’, that is, the status of living organisms within the broader physico-mechanical universe, agitated different corners of the European intellectual scene. From modern Epicureanism to medical Newtonianism, from Stahlian animism to the discourse on the ‘animal economy’ in vitalist medicine, models (...) of living being were constructed in opposition to ‘merely anatomical’, structural, mechanical models. It is therefore curious to turn to the ‘passion play’ of the Scientific Revolution – whether in its early, canonical definitions or its more recent, hybridized, reconstructed and expanded versions: from Koyré to Biagioli, from Merton to Shapin – and find there a conspicuous absence of worry over what status to grant living beings in a newly physicalized universe. Neither Harvey, nor Boyle, nor Locke (to name some likely candidates, the latter having studied with Willis and collaborated with Sydenham) ever ask what makes organisms unique, or conversely, what does not. In this paper I seek to establish how ‘Life’ became a source of contention in early modern thought, and how the Scientific Revolution missed the controversy. (shrink)

In recent trends, the pervious concrete has grasped the attention of civil engineers’ research fraternity because of its special application related to drainage aspects. From the past researches, indicated the significant importance of pervious concrete which is also called as permeable concrete or no-fines concrete, used in concrete flat applications allows water from precipitation and its associated sources to pass directly through, thereby decreasing runoff and permitting groundwater recharging. The method of compaction is one of the most important one in (...) judging the mechanical and durability characteristics of any type of concrete. The current study focuses on the effect of the different types of compaction on the compressive strength of the pervious concrete. The types of compaction adopted in this experimental study are with no compaction, with a tamping rod, with a proctor hammer, with a Marshall hammer, and also with a table vibrator. The range of compressive strength of pervious concrete cubes using different compaction methodologies was arrived in the range of 1.18 MPa to 8.63MPa. Compaction by proctor hammer shows a remarkable increase in compressive strength in terms of 29%, 32%, 59%, and 86% over the Tamping rod, Marshall hammer, no compaction, and Table vibrator. Based on these experimental results, it was observed that table vibrator type of compaction was not suitable for pervious concrete, since cement paste was drained at the bottom of specimens. (shrink)

A number of philosophers think that grounding is, in some sense, well-founded. This thesis, however, is not always articulated precisely, nor is there a consensus in the literature as to how it should be characterized. In what follows, I consider several principles that one might have in mind when asserting that grounding is well-founded, and I argue that one of these principles, which I call ‘full foundations’, best captures the relevant claim. My argument is by the process of elimination. For (...) each of the inadequate principles, I illustrate its inadequacy by showing either that it excludes cases that should not be ruled out by a well-foundedness axiom for grounding, or that it admits cases that should be ruled out. (shrink)

This essay is about the relationship between the notions of practical reason, the will, and choice in Kant’s practical philosophy. Although Kant explicitly identifies practical reason and the will, many interpreters argue that he cannot really mean it on the grounds that unless they are distinct, irrational and, especially, immoral action is impossible. Other readers affirm his identification but distinguish the will from choice on the same basis. We argue that proper attention to Kant’s conception of practical reason as a (...) capacity reveals that these distinctions are neither textually grounded nor philosophically necessary. His moral psychology concerns a single capacity, practical reason, which is the will, and whose actualities in this or that individual fall under the title of choice. Practical reason is the will and choice because it is the rational faculty of desire: a rational being’s capacity to be, by means of her representations, the cause of the actuality of their objects. This, we argue, is entailed by his conception of rational action: action not just in accordance with, but in and through the representation of, principles. The possibility of irrational action is explained not by a distinction between capacities but by the finitude, and thereby the fallibility, of human reason. (shrink)

This is the introduction to a collection of essays on 'embodied empiricism' in early modern philosophy and the life sciences - papers on Harvey, Glisson, Locke, Hume, Bonnet, Lamarck, on anatomy and physiology, on medicine and natural history, etc.

How are love and justice related? Iris Murdoch characterizes the former by drawing on the latter. Love, she maintains, is just attention, which in turn triggers acts of compassion. Arguably, for Murdoch, love is the most important moral activity. By engaging in love, she maintains, moral agents progress on their journey from appearances to reality. Through love, they overcome selfish leanings, acquire a clearer vision of the world and, importantly, other individuals, which in turn enables them to act increasingly well. (...) In this paper, I lay Murdoch’s account of love alongside of Aristotle’s notion of philia. Ultimately, I argue that both Murdochian love and Aristotelian philia are crucial for enabling moral progress. I proceed as follows: First, I introduce Murdoch’s view. I then propose a novel reading of an argument from Aristotle’s Nicomachean Ethics in order to explain what I shall call his necessity claim (NC): philia is necessary to a flourishing life. Along the way, I point out ways in which Murdoch’s and Aristotle’s accounts are mutually illuminating. (shrink)

How to conceptualize loving relationships so as to accommodate that just love is geared toward preserving and fostering individual autonomy? To develop an answer, this paper draws on the recent debate on the rational role of experience to motivate a view dubbed Murdochian presentationalism. Murdochian presentationalism takes seriously two presentationalist ideas: 1) individuals harboring different world views who respond to identical situations differently can be equally rational; 2) our views and concepts develop under the constant pressure of experience. It combines (...) these ideas with Murdoch’s tenet that coming to know others (and thus being able to do well by them) requires unselfish love, construed as just attention that involves a continuous refinement of our evaluative concepts and makes us better attuned to what is real. Complemented with a broadly Kantian notion of autonomy, the resulting view fits the bill. The paper ends on a sketch of what is dubbed the ideal lovers’ pledge and a comment on what metaphor the view arrived at suggests for thinking about loving relationships. (shrink)

In recent years, the advent of Artificial Intelligence (AI) has profoundly reshaped the way we access and utilize humanity's vast reservoir of knowledge. Equipped with this powerful tool, I have undertaken a thorough exploration of the Human Mind, motivated by a growing concern: the evident decline in students' enthusiasm for learning. More specifically, as a professor and researcher, my need for understanding has driven me to explore in depth what defines us as Human beings and what sets us apart from (...) other species. This investigative journey prompted me to reevaluate the evolutionary process, revisit Darwin's theories, and contemplate fundamental questions regarding the nature of time and reality. These reflections ultimately culminated in the formulation of a concept we call the ``Total Universe", a realm in which all possible events and interactions coexist. Building on this concept, we formulated a Theory of Consciousness rooted in the exploration of this Universe through our minds. This culminated in the emergence of the ``World of the Mind", which represents Human reality within the Total Universe, the fusion of all existing Human realities. Importantly, this theory not only integrates various theories of consciousness but also provides a clear framework for understanding what it might mean for Artificial Intelligence to attain consciousness. Hence, I invite you to embark on this journey of reflection, guided by this collection of written codes that encapsulate the discoveries made within the Total Universe through my mind, my reality. My perspective may resonate with yours, or it may not, and both are entirely valid. After all, each individual inhabits their own unique reality. (shrink)

There are at least three vaguely atomistic principles that have come up in the literature, two explicitly and one implicitly. First, standard atomism is the claim that everything is composed of atoms, and is very often how atomism is characterized in the literature. Second, superatomism is the claim that parthood is well-founded, which implies that every proper parthood chain terminates, and has been discussed as a stronger alternative to standard atomism. Third, there is a principle that lies between these two (...) theses in terms of its relative strength: strong atomism, the claim that every maximal proper parthood chain terminates. Although strong atomism is equivalent to superatomism in classical extensional mereology, it is strictly weaker than it in strictly weaker systems in which parthood is a partial order. And it is strictly stronger than standard atomism in classical extensional mereology and, given the axiom of choice, in such strictly weaker systems as well. Though strong atomism has not, to my knowledge, been explicitly identified, Shiver appears to have it in mind, though it is unclear whether he recognizes that it is not equivalent to standard atomism in each of the mereologies he considers. I prove these logical relationships which hold amongst these three atomistic principles, and argue that, whether one adopts classical extensional mereology or a system strictly weaker than it in which parthood is a partial order, standard atomism is a more defensible addition to one’s mereology than either of the other two principles, and it should be regarded as the best formulation of the atomistic thesis. (shrink)

Resumo: Neste texto, introduzo algumas questões importantes que fazem parte do debate sobre infiltração pragmática. Além de apresentar e problematizar as principais alegações oferecidas pelos proponentes da infiltração pragmática eu irei contrasta-la com algumas teses mais tradicionais, como a Tese Tradicional sobre o Conhecimento e o Contextualismo Epistêmico. Por fim, apresento uma crítica aos proponentes da infiltração pragmática que parece ainda não ter sido tratada. Concluo que embora controversa, tal tese está longe de ser refutada completamente. Palavras-chave: Conhecimento; Contexto; Justificação; (...) Padrões; Infiltração prática. -/- Abstract: In this paper I introduce some central aspects concerning the debate on pragmatic encroachment. After introducing and discussing the main arguments offered by the pragmatic encroachers advocates I will contrast it with more traditional theses such as the Traditional Analysis of Knowledge and Epistemic Contextualism. Finally, I present an objection to the pragmatic encroachment approach that haven't been treated yet. I conclude that despite its difficulties, the pragmatic encroachment view is far from being refuted. Keywords: Knowledge; Context; Justification; Standards; Pragmatic encroachment. (shrink)

Once one accepts that certain things metaphysically depend upon, or are metaphysically explained by, other things, it is natural to begin to wonder whether these chains of dependence or explanation must come to an end. This essay surveys the work that has been done on this issue—the issue of grounding and infinite descent. I frame the discussion around two questions: (1) What is infinite descent of ground? and (2) Is infinite descent of ground possible? In addressing the second question, I (...) will consider a number of arguments that have been made for and against the possibility of infinite descent of ground. When relevant, I connect the discussion to two important views about the way reality can be structured by grounding: metaphysical foundationalism and metaphysical infinitism. (shrink)

Maureen Donnelly’s (2016) relative positionalism correctly handles any fixed arity relation with any symmetry such a relation can have, yielding the intuitively correct way(s) in which that relation can apply. And it supplies an explanation of what is going on in the world that makes this the case. But it has at least one potential shortcoming — one that its opponents are likely to seize upon: it can only handle relations with fixed arities. It is unable to handle relations with (...) variable arities. I argue that, all else being equal, relative positionalism ought nonetheless to be preferred to its closest competitors — at least to the extent that the explanation it supplies of relational application is plausible — even though those competitors can handle variable arity relations in addition to fixed arity relations. (shrink)

Summary: Throughout the history of science, indeed throughout the history of knowledge, unification has been touted as a central aim of intellectual inquiry. We’ve always wanted to discover not only numerous bare facts about the universe, but to show how such facts are linked and interrelated. Large amounts of time and effort have been spent trying to show diverse arrays of things can be seen as different manifestations of some common underlying entities or properties. Thales is said to have originated (...) philosophy and science with his declaration that everything was, at base, a form of water. Plato’s theory of the forms was thought to be a magnificent accomplishment because it gave a unified solution to the separate problems of the relation between knowledge and belief, the grounding of objective values, and how continuity is possible amid change. Pasteur made numerous medical advancements possible by demonstrating the interconnection between microorganisms and human disease symptoms. Many technological advances were aided by Maxwell’s showing that light is a kind of electromagnetic radiation. The attempt to unify the various known forces is often referred to as “The Holy Grail” of physics. Some philosophers have even suggested that providing explanations is itself just a sort of unifying of our knowledge. But while unification (like simplicity) has often been hailed as a tremendous virtue in science, the meaning of the term is not altogether clear. Scientists often don’t specify what, precisely, they mean by unification. And in cases where what they mean is clear, different thinkers plainly mean different things by the term. What are the various senses of unification, and why has unification been such an important aim in the history of inquiry? (shrink)

One of the main contentions of the framework for Responsible Innovation (RI) is that social and ethical aspects have to be addressed by deliberative engagement with stakeholders and the wider public throughout the innovation process. The aim of this article is to reflect on the question to what extent is deliberative engagement suitable for conducting RI in business. We discuss several tensions that arise when this framework is applied in the business context. Further, we analyse the place of deliberative engagement (...) in several theories of business ethics. We conclude that there remains a tension between the ideal of RI and the way in which the competitive market operates. Hence, RI scholars should reflect more critically on changes that are required in the market in order to make RI possible, modify the ideal of deliberative engagement for RI in business, or attempt to strike a balance between these two responses. (shrink)

Experience, it is widely agreed, constrains our thinking and is also thoroughly theory-laden. But how can it constrain our thinking while depending on what it purports to constrain? To address this issue, I revisit and carefully analyze the account of observation provided by Norwood Russell Hanson, who introduced the term ‘theory-ladenness of observation’ in the first place. I show that Hanson’s account provides an original and coherent response to the initial question and argue that, if suitably developed, his account provides (...) a distinctive, powerful, and attractive alternative to relationalist and standard representationalist conceptions of experience. (shrink)

Kit Fine (2000) breaks with tradition, arguing that, pace Russell (e.g., 1903: 228), relations have neither directions nor converses. He considers two ways to conceive of these new "neutral" relations, positionalism and anti-positionalism, and argues that the latter should be preferred to the former. Cody Gilmore (2013) argues for a generalization of positionalism, slot theory, the view that a property or relation is n-adic if and only if there are exactly n slots in it, and (very roughly) that each slot (...) may be occupied by at most one entity. Slot theory (and with it, positionalism) bears the full brunt of Fine's (2000) symmetric completions and conflicting adicities problems. I fully develop an alternative, plural slot theory (or pocket theory), which avoids these problems, key elements of which are first considered by Yi (1999: 168 ff.). Like the slot theorist, the pocket theorist posits entities (pockets) in properties and relations that can be occupied. But unlike the slot theorist, the pocket theorist denies that at most one entity can occupy any one of them. As a result, she must also deny that the adicity of a property or relation is equal to the number of occupiable entities in it. By abandoning these theses, however, the pocket theorist is able to avoid Fine's problems, resulting in a stronger theory about the internal structure of properties and relations. Pocket theory also avoids a serious drawback of anti-positionalism. (shrink)

Some contemporary philosophers suggest that we know just by introspection that folk psychological states exist. However, such an "armchair refutation" of eliminativism seems too easy. I first attack two strategems, inspired by Descartes, on how such a refutation might proceed. However, I concede that the Cartesian intuition that we have direct knowledge of representational states is very powerful. The rest of this paper then offers an error theory of how that intuition might really be mistaken. The idea is that introspection (...) does not detect any folk psychological states, but rather detects neural states that dispose us to certain sorts of linguistic behavior. Briefly, rather than detecting a mental appearance of the state-of-affairs that I am sitting near the fire, introspection detects a state disposing me to assert "It appears to me that I am sitting by the fire." The nature of this linguistic-dispositional state is then given a connectionist underpinning, where inputs from introspection lead to such assertive behavior. The Cartesian certainty we feel in self-ascribing such appearances is also explained. Even though I do not endorse such an error theory outright, I suggest that its tenability is enough to undercut introspection arguments against eliminativism. (shrink)

In the study of education, as in many more travelled regions of Classical scholarship, democratic Athens is something of a special case. The cautions formulation is appropriate: in the case of education, surprisingly few studies have sought to establish quite how special Athens was, and those which have, have often raised more questions than they answered. The subject itself is partly to blame. The history of education invites comparison with the present day, while those planning the future of education rarely (...) fail to invoke the past. The place of Classical Athens in European culture has ensured a place for Athenian education in almost every debate from the relation between education and democracy to the value of educationversustraining, and as the original champion of causes as varied as mass education, co-education, and the national curriculum. Desirable as it is to be in demand, such treatment is not calculated to produce the most circumspect account of the subject. The study of education is further hampered by the fact that our knowledge of Athenian culture is so vibrant and diverse in some ways and so partial in others. Plato and Aristophanes present a vivid fictional picture of education in the late fifth century. If we add a few passages from Xenophon and Aristotle, a large number of vases depicting men, women, and children reading, playing the lyre, and doing athletics, and one or two archaeological finds of an educational appearance, it is tempting to take the result as a clear portrait of a society at school. (shrink)

Publics trust experts for personal and pro-social reasons. Scientists are among the experts publics trust most, and so, epistemic trust is routinely afforded to them. The call for epistemic trust to be more socially situated in order to account for the impact of science on society and public welfare is at the forefront of enhanced epistemic trust. I argue that the value-free ideal for science challenges establishing enhanced epistemic trust by preventing the inclusion of non-epistemic values throughout the evaluation of (...) evidence and communication of these values. By selectively silencing non-epistemic values, the ideal cannot take into account publics’ social and moral responses to inductive risk, which are instrumental for defining and determining public welfare. Furthermore, by emphasising epistemic values almost exclusively in science education and communication, the value-free ideal is presented to publics in such a way that it becomes a social indicator of trust. I show this through examination of the importance of values in decisions to trust, and conclude that values (and restrictions on them) can be used by lay publics to help decide which experts to trust. (shrink)

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

Can an ugly experiment be a good experiment? Philosophers have identified many beautiful experiments and explored ways in which their beauty might be connected to their epistemic value. In contrast, the present chapter seeks out (and celebrates) ugly experiments. Among the ugliest are those being designed by AI algorithms. Interestingly, in the contexts where such experiments tend to be deployed, low aesthetic value correlates with high epistemic value. In other words, ugly experiments can be good. Given this, we should conclude (...) that beauty is not generally necessary or sufficient for epistemic value, and increasing beauty will not generally tend to increase epistemic value. (shrink)

Synthetic biologists aim to generate biological organisms according to rational design principles. Their work may have many beneficial applications, but it also raises potentially serious ethical concerns. In this article, we consider what attention the discipline demands from bioethicists. We argue that the most important issue for ethicists to examine is the risk that knowledge from synthetic biology will be misused, for example, in biological terrorism or warfare. To adequately address this concern, bioethics will need to broaden its scope, contemplating (...) not just the means by which scientific knowledge is produced, but also what kinds of knowledge should be sought and disseminated. (shrink)

In this article, I suggest that combining resources from philosophy and psychology can yield useful tools for philosophical counselling. More specifically, I argue for three theses: a) Iris Murdoch’s notion of just attention and Marshall Rosenberg’s method of non-violent communication are interestingly compatible; b) engaging in non-violent communication serves to support one’s endeavors to acquire the kind of clear vision Murdoch thinks doing well by others requires; and c) non-violent just communication would be beneficial to both counsellors and counselees and (...) thus a useful resource for philosophical counsellors. (shrink)

According to classical theism, impassibility is said to be systematically connected to divine attributes like timelessness, immutability, simplicity, aseity, and self-sufficiency. In some interesting way, these attributes are meant to explain why the impassible God cannot suffer. I shall argue that these attributes do not explain why the impassible God cannot suffer. In order to understand why the impassible God cannot suffer, one must examine the emotional life of the impassible God. I shall argue that the necessarily happy emotional life (...) of the classical God explains why the impassible God cannot suffer. (shrink)

It is not uncommon to think that the existence of exhaustive and infallible divine foreknowledge uniquely threatens the existence of human freedom. This paper shows that this cannot be so. For, to uniquely threaten human freedom, infallible divine foreknowledge would have to make an essential contribution to an explanation for why our actions are not up to us. And infallible divine foreknowledge cannot do this. There remains, however, an important question about the compatibility of freedom and foreknowledge. It is a (...) question not about the existence of foreknowledge, but about its mechanics. (shrink)

Can the issue of how important it is whether or not there is a God be decided prior to deciding whether or not there is a God? In this paper, I explore some difficulties that stand in the way of answering this question in the affirmative and some of the implications of these difficulties for that part of the Philosophy of Religion which concerns itself with assessing arguments for and against the existence of God, the implications for how its importance (...) may best be defended within secular academe. (shrink)