The results show that the hybrid CNN-LSTM model outperforms the individual models in terms of prediction accuracy and robustness, suggesting that combining convolutional layers with recurrent units is beneficial for capturing both spatial and temporal patterns in air quality data. This study demonstrates the potential of deep learning methods to offer real-time, accurate air quality forecasting systems, which can aid policymakers and urban planners in managing air pollution more effectively.

By leveraging convolutional neural networks (CNNs), recurrent neural networks (RNNs), and transformers, this research presents an intelligent malware detection framework capable of identifying both known and zero-day threats. The methodology involves feature extraction from static, dynamic, and hybrid malware datasets, followed by training DL models to classify malicious and benign software with high precision. A robust experimental setup evaluates the framework using benchmark malware datasets, yielding a 96% detection accuracy and demonstrating resilience against adversarial attacks. Real-time analysis capabilities further improve (...) response times, reducing the risk of potential damage. The study also incorporates visualization tools to provide interpretable insights into model decisions, enhancing transparency for cybersecurity practitioners. Concluding with a discussion on the challenges and future prospects, this research paves the way for scalable, AI-driven solutions to combat evolving cyber threats. (shrink)

This project, titled Bird Species Identification Using Deep Learning, aims to develop a robust system that can identify bird species from images with high precision. The core of this project involves training a CNN model on a diverse dataset of bird images. This dataset includes species from various geographical locations and environments, capturing a wide range of appearances, postures, and behaviors. By preprocessing and augmenting the dataset, the model is designed to handle challenges such as variations in lighting, background noise, (...) and partial occlusions. The implementation of this project has numerous practical applications. For instance, it can be integrated into mobile or web-based platforms to provide real-time bird identification tools for researchers, birdwatchers, and environmental agencies. It can also be utilized in wildlife monitoring programs to track species distribution and migration patterns. Furthermore, the system can support educational initiatives, allowing individuals to learn about bird species and their significance in the ecosystem. (shrink)

The model's performance is evaluated using metrics such as accuracy, precision, recall, and F1-score, ensuring comprehensive validation. Results indicate significant accuracy improvements over traditional machine learning approaches, demonstrating the potential of deep learning in species identification. This project holds promise for applications in wildlife monitoring, ecological research, and educational tools, promoting awareness and conservation efforts. Future work may include integrating the system into mobile applications or deploying it for real-time bird species identification in field conditions.

Consumers often buy products not because of their attributes per se but rather because of the ultimate benefits that these attributes provide, in turn leading to the satisfaction of ultimate values. And Apple is a type of company which understand their customers & future aspects of innovation in a way that no other companies do. That’s the reason that apple is at No. 1 place in Top 50 Most innovative companies. This article endeavors to recognize the consumer perception towards the (...) Apple products and what is Apple’s ideology. In this article the researcher has listed down 12 variables which affect the consumer behavior most while purchasing Apple products. (shrink)

The study outlines the technical challenges encountered during migration, including data compatibility issues, schema conversion, and security compliance, as well as strategies to mitigate these obstacles. Testing and validation techniques are applied throughout the migration, highlighting essential checkpoints to confirm data accuracy and optimal performance in the Snowflake environment. Postmigration performance metrics are evaluated to illustrate improvements in query execution, scalability, and overall system efficiency compared to the legacy system. The results underscore the advantages of Snowflake’s architecture in handling high-volume, (...) concurrent queries without compromising speed or accuracy. (shrink)

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. The (...) tools and techniques used were simple percentage, chi-square and ANOVA. (shrink)

his project aims to provide an automated system for accurately estimating the calorie content of food and beverages using advanced deep learning algorithms. With the increasing demand for health-conscious individuals, there is a need for a reliable, efficient, and easy-to-use tool that can help users make informed dietary choices. The project utilizes image processing techniques and deep learning models, such as Convolutional Neural Networks (CNN), to analyze food images and predict the corresponding calorie content. The system works by first capturing (...) an image of the food or beverage, which is then processed and passed through a pre-trained deep learning model. (shrink)

Cloud storage's scalability, accessibility, and affordability have made it essential in the digital age. Data security and privacy remain a major issue due to the large volume of sensitive data kept on cloud services. Traditional encryption is safe but slows data recovery, especially for keyword searches. Secure, fine-grained access control and quick keyword searches over encrypted data are possible using attribute-based keyword search (ABKS). This study examines how ABKS might optimize search efficiency and data security in cloud storage systems. We (...) examine index compression, query processing improvement, and encryption optimization to decrease computational cost and preserve security. After a thorough investigation, the article shows how these methods may boost cloud storage system performance, security, and usability. Tests show that improved ABKS speeds up search searches and lowers storage costs, making it a viable cloud storage alternative. Exploring sophisticated machine learning algorithms for predictive search improvements and strengthening ABKS against emerging security vulnerabilities are future research priorities. (shrink)

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. The Genetic Ranking Optimization Algorithm (GROA) is used to rank phishing content (...) based on multiple features by optimizing the ranking system through iterative selection and weighting. Dynamic weighting further enhances the process by adjusting the weights of features based on their importance in real-time. This hybrid approach enables the model to learn from the data, improving classification over time. (shrink)

This project aims to develop a machine learning-based predictive model for diagnosing CKD at an early stage. By utilizing a range of clinical features such as age, blood pressure, blood sugar, and other relevant biomarkers, we employ machine learning algorithms, including Decision Trees, Random Forests, and Support Vector Machines (SVM), to predict the likelihood of a patient developing CKD. The dataset used in this study includes medical records of patients with various kidney conditions, and preprocessing techniques such as normalization and (...) missing data handling are applied to ensure the model’s robustness. The performance of the model is evaluated using metrics such as accuracy, precision, recall, and F1-score to ensure reliable predictions. (shrink)

Cloud computing has transformed data management and storage by providing unmatched scalability, flexibility, and cost-effectiveness. However, rising cloud storage use has raised data security and privacy issues. As sensitive data being outsourced to third-party cloud providers, security is crucial. Traditional encryption methods secure data but make data recovery difficult. Specifically, efficiently searching encrypted data without compromising security is difficult.

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 accuracy levels of VGG19 and 3D CNN are compared using the performance metrics. This comparison helps in identifying which model performs better in the task of facial reconstruction from distorted images. Visualizing the results in the form of a graph provides a clear and concise way to understand the comparative performance of the algorithms. The ultimate goal of this project is to develop a system that can accurately reconstruct distorted faces, which can be invaluable in identifying accident victims or (...) assisting in medical treatments. By providing a reliable method for facial reconstruction, this technology can potentially save lives and improve outcomes for individuals involved in accidents. (shrink)

The framework leverages a hybrid cloud architecture, combining the scalability of public clouds with the security of private clouds. By employing a combination of client-side hashing, metadata indexing, and machine learning-based duplicate detection, the framework achieves significant storage savings without compromising data integrity. Real-time testing on a hybrid cloud setup demonstrated a 65% reduction in storage needs and a 40% improvement in data retrieval times. Additionally, the system employs blockchain for immutable logging of deduplication activities, enhancing transparency and traceability. This (...) study concludes with an evaluation of the deduplication framework's impact on cost efficiency, system performance, and potential scalability. Future enhancements aim to integrate multi-cloud interoperability and advanced compression algorithms to further refine storage management. (shrink)

The rapid advancement of artificial intelligence (AI) technologies has revolutionized various industries, including the realm of education and career guidance. This project endeavors to harness the power of AI to develop a sophisticated career guidance application that offers personalized and effective recommendations to students and job seekers. The primary objective of this project is to address the limitations of traditional career guidance methods, which often lack customization and fail to adapt to individual preferences, skills, and aspirations. Through the integration of (...) AI algorithms, NLP techniques, and ML models, our application aims to provide accurate interest assessments, skill matching, and tailored educational pathways. The scope of the project encompasses the design, development, and implementation of AI-driven functionalities such as interest assessment, skill analysis, resume building, and personalized recommendations. T. (shrink)

The dataset is preprocessed to remove noise and augmented to address the issue of class imbalance. The CNN model is then trained, validated, and tested on this dataset. The results indicate that the deep learning model achieves a classification accuracy of over 95% for most plant diseases. Additionally, the system is designed to provide real-time feedback to farmers, helping them take immediate corrective action. This automated approach eliminates the need for expert human intervention and can be deployed on mobile devices (...) for ease of use in rural areas. The potential future applications of this system include integration with precision agriculture techniques and expansion to a wider range of crops. (shrink)

Underwater Wireless Sensor Networks (UWSNs) are pivotal for various applications, including oceanographic data collection, environmental monitoring, and naval operations. However, the harsh underwater environment poses challenges in designing efficient routing protocols, especially concerning energy consumption and data transmission reliability. This paper proposes an optimized depth-based routing protocol for energy-aware data transmission in UWSNs, focusing on minimizing energy usage while ensuring robust data delivery. The protocol dynamically adjusts transmission power based on node depth and residual energy, reducing communication overhead and prolonging (...) network lifetime. (shrink)

The model is trained on a large dataset containing images of various food items along with their nutritional information. After preprocessing the input image, the model classifies the food and estimates the calorie count by leveraging its learned features. The estimated calorie value is then displayed to the user in real-time. This project leverages key technologies, including image recognition, deep learning, and nutrition analysis. It is designed to be integrated into mobile applications or web platforms, allowing users to track their (...) daily caloric intake efficiently. The system's accuracy is continuously improved through training on a diverse dataset, ensuring reliable calorie estimation across different food items. (shrink)

The proposed system combines predictive analytics and historical data to flag potential emergencies before they occur. The visual analytics platform provides comprehensive reports to healthcare providers, enabling them to monitor trends, identify risk factors, and make informed decisions. This approach significantly enhances patient care by minimizing delays in response and improving overall health outcomes. The system's architecture, based on big data frameworks, supports scalable and efficient data processing. The study demonstrates how the integration of predictive models and data visualization tools (...) can revolutionize health alert systems, making them more responsive and adaptive to individual patient needs. Future enhancements will focus on incorporating machine learning models for more personalized predictions and extending the system's capabilities to remote patient care. (shrink)

The integration of robotics and stock management systems has revolutionized warehouse operations, offering greater efficiency, accuracy, and flexibility. This paper presents an optimal design for integrating robotic systems with stock management for pick-and-place operations in warehousing environments. The primary objective of this research is to enhance the precision and speed of stock handling while minimizing human intervention and error. Our design incorporates state-of-the-art sensors, real-time tracking systems, and autonomous robots programmed with advanced algorithms for object identification, gripping, and movement.

The Internet of Things (IoT) wireless LAN in healthcare has moved away from traditional methods that include hospital visits and continuous monitoring. The Internet of Things allows the use of certain means, including the detection, processing and transmission of physical and biomedical parameters. With powerful algorithms and intelligent systems, it will be available to provide unprecedented levels of critical data for real-time life that are collected and analyzed to guide people in research, management and emergency care. This chapter provides a (...) quick overview of IoT features and how they relate to wireless discovery and technology to deploy the medical applications you need. In the world, the revolution in any industry is to connect your products and devices to the Internet and make them independent and remotely connected, so that anyone can use and view them from anywhere and anytime. The Internet of Things provides us with a home automation system that uses smart devices to overcome this obstacle, allowing us to easily manage our appliances. A smart city is a vision to integrate a variety of information and communication solutions for residents with essential services, such as smart parking on all streets. The main motivation for using the Internet for parking objects is simply collecting data to get free parking. The IoT-based RTSSPS architecture is divided into three parts: a WSN-based smart street parking module, an IoT-based smart street parking module, and an IoT-based smart street parking module. IoT-based cloud with street parking algorithm, rating and future directions. (shrink)

This study explores the role of government policies, public-private partnerships, and emerging technologies in bridging the digital divide, ensuring inclusive and equitable access to quality education for all students. By analyzing case studies and statistical data, this research identifies key areas where the EdTech revolution can be leveraged to close gaps in the education system while fostering innovation in pedagogical practices. Finally, the paper presents recommendations for ensuring that the EdTech revolution contributes to systemic equity, rather than exacerbating existing disparities.

My aim in this paper is to critically evaluate the debate surrounding the distinction between phenomenal and representational character of conscious experience which is one of the important debates in contemporary philosophy of mind and consciousness studies. The main objective of this paper is to seek an answer to the question- whether the content of conscious experience is phenomenal or intentional, or both? In the introduction, I will introduce the phenomenal and representational as two significant properties of consciousness. In the (...) first part, I will articulate the debate regarding the distinction between phenomenal and representational character of consciousness. Here I will argue that the phenomenal and representational properties of experience are not mutually exclusive of each other as many philosophers have taken them to be and one can be understood in relation to the other. In relation to the above distinction, many theories of consciousness have been developed emphasizing on the one or the other property of consciousness. My second objective in this paper is to argue against the strong or reductive representationalism. In relation to this, I will discuss Michael Tye’s position as a representative of strong representationalism. In the third part, I will argue against it drawing sources from the works of various non-reductive representationalists particularly from Tim Crane’s version of representationalism. In the final section, I will try to defend a position which may be called phenomenological representationalism where I will try to reconcile the divide between phenomenology and intentionality. In this context, I will argue, on the one hand, against the Cartesian notion of subjectivity which leads to pure phenomenal consciousness and, on the other hand, against the physical explanation of consciousness which leads to strong representationalism. (shrink)

My aim in this paper is to critically evaluate the debate between John McDowell and Michael Friedman on the nature of understanding and relativism. McDowell in his magnum opus Mind and World, has argued in favour of the view that the way we are open to reality is constituted by concepts. According to him, our openness to reality is placed in the space of reasons which is nothing but space of concepts. Friedman in his critical and detail review of McDowell’s (...) book has taken McDowell’s project in his book in particular and in his philosophy in general as the project of not constructing philosophical theories but of exorcising the philosophical traditions. It is indeed so as McDowell himself has acknowledged because he closely follows Wittgensteinian quietism in his approach to various philosophical problems. While explaining how our knowledge and perception of the world among other things are placed in the space of reasons, towards the end of his book, McDowell relates space of reasons to language and tradition. Space of reasons, in his opinion, can be understood, in terms of initiating ourselves into language and inheriting the tradition. He thus says, “…the sort of language into which human beings are first initiated, serves as a repository of tradition, a store of historically accumulated wisdom about what is reason for what.” And this is Gadamer in significant sense. (shrink)

Accelerated computing leverages specialized hardware and software techniques to optimize the performance of computationally intensive tasks, offering significant speed-ups in scientific, engineering, and data-driven fields. This paper presents a comprehensive study examining the role of accelerated computing in enhancing processing capabilities and reducing execution times in diverse applications. Using a custom-designed experimental framework, we evaluated different methodologies for parallelization, GPU acceleration, and CPU-GPU coordination. The aim was to assess how various factors, such as data size, computational complexity, and task concurrency, (...) impact processing efficiency. (shrink)

Furthermore, the paper delves into the role of hospital management and policy in easing the digital transition and fostering a more harmonious work-life balance. By analyzing technological tools and frameworks in telemedicine, the research identifies areas where improvements can be made, offering recommendations for enhancing doctors' digital efficiency while promoting better work-life harmony. This study contributes to understanding how technology can be harnessed to benefit healthcare professionals, particularly in managing the dual demands of professional duties and personal well-being.

Philosophers throughout the ages have struggled to explain the way or ways by which we can acquire knowledge about the external world. With an aim to meet the skeptical challenges regarding the possibility of knowledge, various accounts of knowledge have been developed across philosophical traditions. The worry to meet skeptical challenges is implicitly or explicitly present in almost every philosophical account of knowledge. Many philosophers, while explaining about the nature and the possibility of knowledge, have talked about placing it in (...) the space of reasons or space of justifications. So, I think one of the ways in which we can respond to skeptical challenges is by developing a proper understanding of the space of reasons and justifications where we place our knowledge. When we talk about the space of reasons, it is also important to highlight, in this context, its relationship with the natural world. I would like to emphasize in this regard that there has been a normative turn specifically in the works of John McDowell and Robert Brandom after the naturalistic turn in epistemology. But one can ask- why is there a need of a normative turn after a seemingly successful naturalistic turn in epistemology? I call them normative epistemologists those who have argued that knowledge should be understood by placing it properly in the space of reasons which is necessarily a normative space. I think John McDowell, Robert Brandom and their philosophical heroes Immanuel Kant and G. W. F. Hegel fall into this category of epistemologists. Normative epistemologists have always argued that a philosophical account of knowledge in order to meet the skeptical challenges has to place our knowledge satisfactorily in the space of reasons and various ways of placing knowledge in the space of reasons have been developed in this regard. The significant questions that have been asked in this context are- what could be the best plausible way to place knowledge in the space of reasons? Is placing knowledge in the space of reasons enough to avoid the skeptical challenges regarding the possibility of knowledge? According to some philosophers, the skeptical problems arise because of a certain misunderstanding of space of reasons i.e. the interiorization of the space of reasons. On the interiorized conception of the space of reasons, there is need of extra elements beyond the space of reasons which are required for our knowledge but are not part of the logical space. In this paper, my aim, following Kant and McDowell, is to propose a critique of interiorized conception of space of reasons and show how this conception leads to various problems regarding the possibility of knowledge. In this context, I will specifically discuss argument from illusion as a skeptical challenge for the possibility of knowledge and McDowell’s response to it. In the second part of my paper, my aim is to discuss the debate between McDowell and Brandom on the nature and extent of the space of reasons. (shrink)

The relationship between experience and thought is one of the distinctive problems in contemporary philosophy and has significant implications for both philosophy of mind and epistemology. John McDowell in his Magnum Opus Mind and World has argued in favour of a rational and conceptual relationship between experience and thought. In our understanding of the relationship between experience and thought, in his opinion, we fall into an “intolerable oscillation” between Myth of the Given and Coherentism. One of these pitfalls, he specifically (...) targets, is Davidson’s coherentism according to which there cannot be rational relationship between experience and thought. The point Davidson makes is that our perception of the world cannot give justification to our beliefs about the world. Only a belief, in his opinion, can justify another belief and this is considered to be one of the most controversial claims in contemporary philosophy. Both Davidson and McDowell would agree that the root of the problem pertaining to the relationship between experience and thought lies in the relationship between reason and nature (rationality and natural world). In this paper, my aim is to critically evaluate the debate between Davidson and McDowell about the relationship between experience and thought in connection with their views on the relationship between reason and nature. I will argue that a rational relation between experience and thought is necessary for our thought to have a genuine content from the external world. (shrink)

Advancements in cloud technologies have increased the infrastructural needs of data centers due to storage needs and processing of extensive dimensional data. Many service providers envisage anomaly detection criteria to guarantee availability to avoid breakdowns and complexities caused due to large-scale operations. The streaming log data generated is associated with multi-dimensional complexity and thus poses a considerable challenge to detect the anomalies or unusual occurrences in the data. In this research, a hybrid model is proposed that is motivated by deep (...) belief criteria and meta-heuristics. Using Search-and-Rescue—BrainStorm Optimization (SAR-BSO), a hybrid feature selection (FS) and deep belief network classifier is used to localize and detect anomalies for streaming data logs. The significant contribution of the research lies in FS, which is carried out using SAR-BSO which increases the detection power of the model as it selects the most significant variables by minimizing redundant features. The evaluation of accuracy is efficiently improved when compared with the predictable methods, such as Extract Local Outlier Factor (ELOF), Track-plus, Hybrid Distributed Batch Stream (HDBS), IForestASD, DBN, BSO-based Feature Selection with DBN, Genetic Algorithm-Deep Belief Network (GA-DBN), Mutual Information-Deep Belief Network (MI-DBN), information entropy-Deep Belief Network(I + DBN), Flat Field-Deep Belief Network (FF + DBN), African Vulture Optimization Algorithm-Deep Belief Network(AVOA + DBN), Gorilla Troop Optimizer-Deep Belief Network(GTO-DBN), and SARO-based Feature Selection with DBN. Further, the accurate detection of the anomalies in the data stream is established by the Deep Belief Neural Network (DBN) classifier. The model’s efficacy is determined using Apache, Hadoop, HDFS, Spark, and Linux datasets and evaluated against existing similar models. The model efficiency is provided using multiple evaluation metrics and is found effective. From the experimentation, the accuracy of the proposed model is found to be 93.3, 95.4, 93.6, 94.2, and 93.5% respectively for the dataset such as Apache, Hadoop, HDFS, spark, and Linux. This enhancement in accuracy is due to the selection of optimal features by the proposed SAR-BSO algorithm. (shrink)

This volum includes 37 papers of mathematics or applied mathematics written by the author alone or in collaboration with the following co-authors: Cătălin Barbu, Mihály Bencze, Octavian Cira, Marian Niţu, Ion Pătraşcu, Mircea E. Şelariu, Rajan Alex, Xingsen Li, Tudor Păroiu, Luige Vlădăreanu, Victor Vlădăreanu, Ştefan Vlăduţescu, Yingjie Tian, Mohd Anasri, Lucian Căpitanu, Valeri Kroumov, Kimihiro Okuyama, Gabriela Tonţ, A. A. Adewara, Manoj K. Chaudhary, Mukesh Kumar, Sachin Malik, Alka Mittal, Neetish Sharma, Rakesh K. Shukla, Ashish K. Singh, Jayant (...) Singh, Rajesh Singh, V.V. Singh, Hansraj Yadav, Amit Bhaghel, Dipti Chauhan, V. Christianto, Priti Singh, and Dmitri Rabounski. (shrink)

What role does the wild duck play in Ibsen's famous drama? I argue that, besides mirroring the fate of the human cast members, the duck is acting as animal subject in a quasi-experiment, conducted in a private setting. Analysed from this perspective, the play allows us to discern the epistemological and ethical dimensions of the new scientific animal practice (systematic observation of animal behaviour under artificial conditions) emerging precesely at that time. Ibsen's play stages the clash between a scientific and (...) a romantic understanding of animals that still constitutes the backdrop of most contemporary debates over animals in research. Whereas the scientific understanding reduces the animal's behaviour, as well as its environment, to discrete and modifiable elements, the romantic view regards animals as being at one with (or violently disconnected from) their natural surroundings. (shrink)

There are many things—call them ‘experts’—that you should defer to in forming your opinions. The trouble is, many experts are modest: they’re less than certain that they are worthy of deference. When this happens, the standard theories of deference break down: the most popular (“Reflection”-style) principles collapse to inconsistency, while their most popular (“New-Reflection”-style) variants allow you to defer to someone while regarding them as an anti-expert. We propose a middle way: deferring to someone involves preferring to make any decision (...) using their opinions instead of your own. In a slogan, deferring opinions is deferring decisions. Generalizing the proposal of Dorst (2020a), we first formulate a new principle that shows exactly how your opinions must relate to an expert’s for this to be so. We then build off the results of Levinstein (2019) and Campbell-Moore (2020) to show that this principle is also equivalent to the constraint that you must always expect the expert’s estimates to be more accurate than your own. Finally, we characterize the conditions an expert’s opinions must meet to be worthy of deference in this sense, showing how they sit naturally between the too-strong constraints of Reflection and the too-weak constraints of New Reflection. (shrink)

The impressive variation amongst biological individuals generates many complexities in addressing the simple-sounding question what is a biological individual? A distinction between evolutionary and physiological individuals is useful in thinking about biological individuals, as is attention to the kinds of groups, such as superorganisms and species, that have sometimes been thought of as biological individuals. More fully understanding the conceptual space that biological individuals occupy also involves considering a range of other concepts, such as life, reproduction, and agency. There has (...) been a focus in some recent discussions by both philosophers and biologists on how evolutionary individuals are created and regulated, as well as continuing work on the evolution of individuality. (shrink)

I discuss two types of evidential problems with the most widely touted experiments in evolutionary psychology, those performed by Leda Cosmides and interpreted by Cosmides and John Tooby. First, and despite Cosmides and Tooby's claims to the contrary, these experiments don't fulfil the standards of evidence of evolutionary biology. Second Cosmides and Tooby claim to have performed a crucial experiment, and to have eliminated rival approaches. Though they claim that their results are consistent with their theory but contradictory to the (...) leading non-evolutionary alternative, Pragmatic Reasoning Schemas theory, I argue that this claim is unsupported. In addition, some of Cosmides and Tooby's interpretations arise from misguided and simplistic understandings of evolutionary biology. While I endorse the incorporation of evolutionary approaches into psychology, I reject the claims of Cosmides and Tooby that a modular approach is the only one supported by evolutionary biology. Lewontin's critical examinations of the applications of adaptationist thinking provide a background of evidentiary standards against which to view the currently fashionable claims of evolutionary psychology. (shrink)

In this paper, we argue that, barring a few important exceptions, the phenomenon we refer to using the expression “being moved” is a distinct type of emotion. In this paper’s first section, we motivate this hypothesis by reflecting on our linguistic use of this expression. In section two, pursuing a methodology that is both conceptual and empirical, we try to show that the phenomenon satisfies the five most commonly used criteria in philosophy and psychology for thinking that some affective episode (...) is a distinct emotion. Indeed, being moved, we claim, is the experience of a positive core value (particular object) perceived by the moved subject as standing out (formal object) in the circumstances triggering the emotion. Drawing on numerous examples, we describe the distinctively rich phenomenology characteristic of the experience as well as the far-reaching action-tendencies and functions associated with it. Having thus shown that the candidate emotion seem to satisfy the five criteria, we go on, in section three, to compare it with sadness and joy, arguing that it should not be confused with either. Finally, in section four, we illustrate the explanatory power of our account of “being moved” by showing how it can shed light on, and maybe even justify, the widespread distrust we feel towards the exhibition of ‘sentimentality’. On the whole and if we are right, we have uncovered an emotion which, though never or rarely talked about, is of great interest and no small importance. (shrink)

I argue that there can be no such thing as a borderline case of the predicate ‘phenomenally conscious’: for any given creature at any given time, it cannot be vague whether that creature is phenomenally conscious at that time. I first defend the Positive Characterization Thesis, which says that for any borderline case of any predicate there is a positive characterization of that case that can show any sufficiently competent speaker what makes it a borderline case. I then appeal to (...) the familiar claim that zombies are conceivable, and I argue that this claim entails that there can be no positive characterizations of borderline cases of ‘phenomenally conscious’. By the Positive Characterization Thesis, it follows that ‘phenomenally conscious’ can not have any borderline cases. (shrink)

Chest pain is the pain felt in the chest by infants, children and adolescents. In most cases the pain is not associated with the heart. It is mainly recognized by the observance or report of pain by the infant, child or adolescent by reports of distress by parents or care givers. Chest pain is not unusual in children. Lots of children are seen in ambulatory clinics, emergency rooms and hospitals and cardiology clinics. Usually there is a benign cause for the (...) pain for utmost children. Certain patients have conditions that are serious and perhaps life-threatening. Chest pain in pediatric patients needs careful physical examination and a detailed history that would point to the possibility of a serious cause. Researches of pediatric chest pain are scarce. It has been difficult to create evidence-based guidelines for evaluation. In this paper we propose an expert system to help doctors and parents, and care giver in diagnosing chest pain in infants and children. This expert System is design and implemented in SL5 Object language. (shrink)

Recent epistemology offers an account of what it is to know other persons. Such views hold promise for illuminating several issues in philosophy of religion, and for advancing a distinctive approach to religious epistemology. This paper develops an account of interpersonal knowledge, and clarifies its relation to propositional and qualitative knowledge. I then turn to our knowledge of God and God's knowledge of us, and compare my account of interpersonal knowledge with important work by Eleonore Stump on "Franciscan" knowledge. I (...) examine how interpersonal knowledge may figure in liturgical practice, in diffusing the problem of divine hiddenness, and in motivating a novel understanding of divine love. I also explore the possibility of epistemic injustice arising from dismissal or neglect of our religious testimony to one another, or of divine testimony to humanity, focusing specifically on the import of interpersonal knowledge. (shrink)

Fragmentalism was first introduced by Kit Fine in his ‘Tense and Reality’. According to fragmentalism, reality is an inherently perspectival place that exhibits a fragmented structure. The current paper defends the fragmentalist interpretation of the special theory of relativity, which Fine briefly considers in his paper. The fragmentalist interpretation makes room for genuine facts regarding absolute simultaneity, duration and length. One might worry that positing such variant properties is a turn for the worse in terms of theoretical virtues because such (...) properties are not involved in physical explanations and hence theoretically redundant. It will be argued that this is not right: if variant properties are indeed instantiated, they will also be involved in straightforward physical explanations and hence not explanatorily redundant. Hofweber and Lange, in their ‘Fine’s Fragmentalist Interpretation of Special Relativity’, object that the fragmentalist interpretation is in tension with the right explanation of the Lorentz transformations. It will be argued that their objection targets an inessential aspect of the fragmentalist framework and fails to raise any serious problem for the fragmentalist interpretation of special relativity. (shrink)

The study aims to identify the efficiency of the university education performance from the perspective of postgraduate and undergraduate students in international and Palestinian universities. The analytical descriptive approach was used for this purpose and the questionnaire was used as a main tool for data collection. The study community consists of: post graduate students, (23850) graduate students and (146355) undergraduate students. The sample of the study was 378 graduate students and 383 undergraduate students. The random stratified sample was used. The (...) Statistical Package of Social Sciences (SPSS) was also used for data analysis. The study reached a number of results, the most important of which are: The level of efficiency of educational performance in Palestinian and international universities from the point of view of postgraduate and undergraduate students was high. And that there are significant differences between the average views of the sample of the study on the efficiency of educational performance in Palestinian and international universities attributed to the University and to the benefit of international universities. The study concluded many recommendations, the most important of which is the necessity of continuing to develop e-learning strategies that affect the efficiency of educational performance and research commensurate with the university's position in the local and international community, which puts it on the best classification between local and international universities through e-learning. (shrink)

Frankfurt cases are supposed to provide us with counterexamples to the principle of alternative possibilities. Among the most well known responses to these cases is what John Fischer has dubbed the flicker of freedom strategy. Here we revisit a version of this strategy, which we refer to as the fine-grained response. Although a number of philosophers, including some who are otherwise unsympathetic to Frankfurt’s argument, have dismissed the fine grained response, we believe there is a good deal to be said (...) on its behalf. We argue, in particular, that reflection on certain cases involving omissions undermines the main objections to the response and also provides the groundwork for an argument in support of it. (shrink)

Many epistemologists endorse true-belief monism, the thesis that only true beliefs are of fundamental epistemic value. However, this view faces formidable counterexamples. In response to these challenges, we alter the letter, but not the spirit, of true-belief monism. We dub the resulting view “inquisitive truth monism”, which holds that only true answers to relevant questions are of fundamental epistemic value. Which questions are relevant is a function of an inquirer’s perspective, which is characterized by his/her interests, social role, and background (...) assumptions. Using examples of several different scientific practices, we argue that inquisitive truth monism outperforms true-belief monism. (shrink)

Human cognition is extended and enacted. Drawing the boundaries of cognition to include the resources and attributes of the body and materiality allows an examination of how these components interact with the brain as a system, especially over cultural and evolutionary spans of time. Literacy and numeracy provide examples of multigenerational, incremental change in both psychological functioning and material forms. Though we think materiality, its central role in human cognition is often unappreciated, for reasons that include conceptual distribution over multiple (...) material forms, the unconscious transparency of cognitive activity in general, and the different temporalities of metaplastic change in neurons and cultural forms. (shrink)

According to the fitting attitude (FA) analysis of value concepts, to conceive of an object as having a given value is to conceive of it as being such that a certain evaluative attitude taken towards it would be fitting. Among the challenges that this analysis has to face, two are especially pressing. The first is a psychological challenge: the FA analysis must call upon attitudes that shed light on our value concepts while not presupposing the mastery of these concepts. The (...) second challenge is normative: the FA analysis must account for the fittingness of the relevant attitudes in terms of a kind of normativity intimately related to these attitudes, but again without presupposing the mastery of the relevant value concepts. In this paper, we show that real progress is possible if we pay close attention to the nature of the attitudes recruited by the analysis. More specifically, we claim that an FA analysis that appeals to emotions conceived as evaluative attitudes — as opposed to, for instance, evaluative judgements or evaluative perceptions — has the best prospects of meeting the two challenges and of putting the FA analysis on a strong footing. (shrink)

I demonstrate that a "speech act" theory of meaning for imperatives is—contra a dominant position in philosophy and linguistics—theoretically desirable. A speech act-theoretic account of the meaning of an imperative !φ is characterized, broadly, by the following claims. -/- LINGUISTIC MEANING AS USE !φ’s meaning is a matter of the speech act an utterance of it conventionally functions to express—what a speaker conventionally uses it to do (its conventional discourse function, CDF). -/- IMPERATIVE USE AS PRACTICAL !φ's CDF is to (...) express a practical (non-representational) state of mind—one concerning an agent's preferences and plans, rather than her beliefs. -/- Opposed to speech act accounts is a preponderance of views which deny that a sentence's linguistic meaning is a matter of what speech act it is used to perform, or its CDF. On such accounts, meaning is, instead, a matter of "static" properties of the sentence—e.g., how it depicts the world as being (or, more neutrally, the properties of a model-theoretic object with which the semantic value of the sentence co-varies). On one version of a static account, an imperative 'shut the window!' might, for instance, depict the world as being such that the window must be shut. -/- Static accounts are traditionally motivated against speech act-theoretic accounts by appeal to supposedly irremediable explanatory deficiencies in the latter. Whatever a static account loses in saying (prima facie counterintuitively) that an imperative conventionally represents, or expresses a picture of the world, is said to be offset by its ability to explain a variety of phenomena for which speech act-theoretic accounts are said to lack good explanations (even, in many cases, the bare ability to offer something that might meet basic criteria on what a good explanation should be like). -/- I aim to turn the tables on static accounts. I do this by showing that speech act accounts are capable of giving explanations of phenomena which fans of static accounts have alleged them unable to give. Indeed, for a variety of absolutely fundamental phenomena having to do with the conventional meaning of imperatives (and other types of practical language), speech act accounts provide natural and theoretically satisfying explanations, where a representational account provides none. (shrink)

This paper is an examination of the concept of recognition and its connection with identity and respect. This is related to the question of how women are or are not adequately recognised or respected for their achievements in sport and whether eliminating sex segregation in sport is a solution. This will require an analysis of the concept of excellence in sport, as well as the relationship between fairness and inclusion in an activity that is fundamentally about bodily movement. I argue (...) that attempts to address the problem of women’s recognition in sport need to do so in ways that neither eliminate sport as a fairness regulated system for developing individual excellence in bodily movement nor that prevent women’s achievement of sporting excellence, with the regard that belongs to them. Doing this requires us to decide whether sport is about champions or about individual excellence. (shrink)

This article investigates the relationships between forms of humor that conjure up possible worlds and real-world social critiques. The first part of the article will argue that subversive humor, which is from or on behalf of historically and continually marginalized communities, constitutes a kind of aesthetic experience that can elicit enjoyment even in adversarial audiences. The second part will be a connecting piece, arguing that subversive humor can be constructed as brief narrative thought experiments that employ the use of fictionalized (...) scenarios to facilitate an open, playful attitude, encouraging a space for collaborative interpretation. This interaction between humorist and audience is an aesthetic experience that is enjoyable in and of itself, as the feelings of mirth are intrinsically valuable. But connected to the “Ha-ha!” experience of these sorts of humorous creations is an “Aha!” or potentially revelatory experience that is a mixture of cognitive comprehension and motivated (emotional) response. The third part of the article will attempt to go beyond the consciousness-raising element with an account of how such possible worlds created in the realm of imagination through subversive humor can bleed into the real world of flesh and blood people. Finally, an example of subversive humor will be analyzed. (shrink)

Quality of will accounts of moral responsibility hold that ill will is necessary for blameworthiness. But all such accounts are false to ordinary moral practice, which licenses blame for agents who act wrongly from epistemically unreasonable ignorance even if the act is not ill willed. This should be especially concerning to Strawsonians about moral responsibility, who think the genuine conditions of blameworthiness are derived from the standards internal to our practice. In response, I provide a theory of moral blameworthiness on (...) which ill will is not necessary for blameworthiness. On the view I defend, “Rational Capacitarianism,” agents are blameworthy whenever they act wrongly from an unreasonable attitude which is attributable to them, where an attitude is attributable to an agent just in case she has the capacity to assess reasons for and against the attitude and modulate the attitude in light of these assessments. Acting from unreasonable ignorance is just a special case of acting from an unreasonable attitude. My theory contrasts both with both quality of will accounts of blameworthiness and the Capacitarian view, which specifies that agents who act wrongly from ignorance are culpable if they could and should have known better. On Capacitarianism, a variety of awareness-relevant capacities are pertinent, including memory; on my view it is only failures of rational capacities that render the agent culpable, because only failures of rational capacities are attributable to the agent. (shrink)

ABSTRACTThis essay offers a reconfiguration of the possibility‐space of positions regarding the metaphysics and epistemology associated with historical knowledge. A tradition within analytic philosophy from Danto to Dummett attempts to answer questions about the reality of the past on the basis of two shared assumptions. The first takes individual statements as the relevant unit of semantic and philosophical analysis. The second presumes that variants of realism and antirealism about the past exhaust the metaphysical options . This essay argues that both (...) of these assumptions should be rejected. It develops as an alternative an irrealist account of history, a view based in part on work by Leon Goldstein and Ian Hacking. On an irrealist view, historical claims ought to be treated as subject to the same conditions and caveats that apply to any theory of empirical or scientific knowledge. Irrealism argues for pasts as made and not found. The argument emphasizes the priority of classification over perception in the order of understanding and so verification. Because nothing a priori anchors practices of classification, no sense can be attached to claims that some single structure must or does determine what events take place in human history. Irrealism denies to realism the very intelligibility of any imagined view from nowhere, that is, a determinately configured past subsisting sub specie aeternitatis. A plurality of pasts exists because constituting a past always depends to some degree on socially mediated negotiations of a fit between descriptions and experience. (shrink)