Despite a large and multifaceted effort to understand the vast landscape of phenotypic data, their current form inhibits productive data analysis. The lack of a community-wide, consensus-based, human- and machine-interpretable language for describing phenotypes and their genomic and environmental contexts is perhaps the most pressing scientific bottleneck to integration across many key fields in biology, including genomics, systems biology, development, medicine, evolution, ecology, and systematics. Here we survey the current phenomics landscape, including data resources and handling, and the progress that (...) has been made to accurately capture relevant data descriptions for phenotypes. We present an example of the kind of integration across domains that computable phenotypes would enable, and we call upon the broader biology community, publishers, and relevant funding agencies to support efforts to surmount today's data barriers and facilitate analytical reproducibility. (shrink)

An often-overlooked characteristic of the human mind is its propensity to wander. Despite growing interest in the science of mind-wandering, most studies operationalize mind-wandering by its task-unrelated contents. But these contents may be orthogonal to the processes that determine how thoughts unfold over time, remaining stable or wandering from one topic to another. In this chapter, we emphasize the importance of incorporating such processes into current definitions of mind-wandering, and propose that mind-wandering and other forms of spontaneous thought (such as (...) dreaming and creativity) are mental states that arise and transition relatively freely due to an absence of constraints on cognition. We review existing psychological, philosophical and neuroscientific research on spontaneous thought through the lens of this framework, and call for additional research into the dynamic properties of the mind and brain. (shrink)

Background Men with antisocial personality disorder show lifelong abnormalities in adaptive decision making guided by the weighing up of reward and punishment information. Among men with antisocial personality disorder, modifi cation of the behaviour of those with additional diagnoses of psychopathy seems particularly resistant to punishment. Methods We did a case-control functional MRI (fMRI) study in 50 men, of whom 12 were violent off enders with antisocial personality disorder and psychopathy, 20 were violent off enders with antisocial personality disorder but (...) not psychopathy, and 18 were healthy non-off enders. We used fMRI to measure brain activation associated with the representation of punishment or reward information during an event-related probabilistic response-reversal task, assessed with standard general linear-model-based analysis. Findings Offenders with antisocial personality disorder and psychopathy displayed discrete regions of increased activation in the posterior cingulate cortex and anterior insula in response to punished errors during the task reversal phase, and decreased activation to all correct rewarded responses in the superior temporal cortex. This finding was in contrast to results for off enders without psychopathy and healthy non-off enders. Interpretation Punishment prediction error signalling in off enders with antisocial personality disorder and psychopathy was highly atypical. This finding challenges the widely held view that such men are simply characterised by diminished neural sensitivity to punishment. Instead, this fi nding indicates altered organisation of the information processing system responsible for reinforcement learning and appropriate decision making. This difference between violent offenders with antisocial personality disorder with and without psychopathy has implications for the causes of these disorders and for treatment approaches. (shrink)

In real-time, Twitter strongly imprints world events, popular culture, and the day-to-day; Twitter records an ever growing compendium of language use and change; and Twitter has been shown to enable certain kinds of prediction. Vitally, and absent from many standard corpora such as books and news archives, Twitter also encodes popularity and spreading through retweets. Here, we describe Storywrangler, an ongoing, day-scale curation of over 100 billion tweets containing around 1 trillion 1-grams from 2008 to 2020. For each day, we (...) break tweets into 1-, 2-, and 3-grams across 150+ languages, record usage frequencies, and generate Zipf distributions. We make the data set available through an interactive time series viewer, and as downloadable time series and daily distributions. We showcase a few examples of the many possible avenues of study we aim to enable including how social amplification can be visualized through ‘contagiograms’. (shrink)

Most of our memories are inferential, so says Sven Bernecker in Memory: A Philosophical Study. I show that his account of inferentially remembering that p is too strong. A revision of the account that avoids the difficulty is proposed. Since inferential memory that p is memory that q (a proposition distinct from p) with an admixture of inference from one’s memory that q and a true thought one has that r, its analysis presupposes an adequate account of the (presumably non-inferential) (...) memory that q. Bernecker’s account of non-inferentially remembering that is shown to be inadequate. A remedy lies in strengthening the account by requiring the rememberer to have had prima facie justification to believe that q, any defeaters of which were misleading. (shrink)

In his [1937, 1938], Paul Dirac proposed his “Large Number Hypothesis” (LNH), as a speculative law, based upon what we will call the “Large Number Coincidences” (LNC’s), which are essentially “coincidences” in the ratios of about six large dimensionless numbers in physics. Dirac’s LNH postulates that these numerical coincidences reflect a deeper set of law-like relations, pointing to a revolutionary theory of cosmology. This led to substantial work, including the development of Dirac’s later [1969/74] cosmology, and other alternative cosmologies, such (...) as the Brans-Dicke modification of GTR, and to extensive empirical tests. We may refer to the generic hypothesis of “Large Number Relations” (LNR’s), as the proposal that there are lawlike relations of some kind between the dimensionless numbers, not necessarily those proposed in Dirac’s early LNH. Such relations would have a profound effect on our concepts of physics, but they remain shrouded in mystery. Although Dirac’s specific proposals for LNR theories have been largely rejected, the subject retains interest, especially among cosmologists seeking to test possible variations in fundamental constants, and to explain dark energy or the cosmological constant. In the first two sections here we briefly summarize the basic concepts of LNR’s. We then introduce an alternative LNR theory, using a systematic formalism to express variable transformations between conventional measurement variables and the true variables of the theory. We demonstrate some consistency results and review the evidence for changes in the gravitational constant G. The theory adopted in the strongest tests of Ġ/G, by the Lunar Laser Ranging (LLR) experiments, assumes: Ġ/G = 3(dr/dt)/r – 2(dP/dt)/P – (dm/dt)/m, as a fundamental relationship. Experimental measurements show the RHS to be close to zero, so it is inferred that significant changes in G are ruled out. However when the relation is derived in our alternative theory it gives: Ġ/G = 3(dr/dt)/r – 2(dP/dt)/P – (dm/dt)/m – (dR/dt)/R. The extra final term (which is the Hubble constant) is not taken into account in conventional derivations. This means the LLR experiments are consistent with our LNR theory (and others), and they do not really test for a changing value of G at all. This failure to transform predictions of LNR theories correctly is a serious conceptual flaw in current experiment and theory. (shrink)

Wittgenstein's farcical clash with literary critic F. R. Leavis over the analysis of Empson's poem "Legal Fiction" is well known to devotees of Wittgenstein's life (Ludwig Wittgenstein: Personal Recollections (1981), edited by Rush Rhees, Oxford: Basil Blackwell, 80). Less well known is the value of studying Empson's artistic and intellectual achievement as part of the wider cultural background for the appreciation of Wittgenstein's views and influence, early and late. This talk sketches some diverting byways awaiting further exploration. A recurrent theme (...) is contradiction. (shrink)

According to the theological worldview of J. R. R. Tolkien, the principal work of a Christian is to know, love, and serve God. Why, then, did he devote so much time to creating an entire family of imaginary languages for imaginary peoples in an imaginary world? This paper argues that the stories of these peoples, with their ‘eucatastrophes,’ have consoling value amid the incomplete stories of our own lives. But more fundamentally, secondary creation is proper to the adopted children of (...) God and can be a way of drawing closer to God. Such work also witnesses to the freedom of the children of God, not only to receive salvation from God, but to contribute to the enrichment of creation and eternal life. (shrink)

This paper argues against the correctness of the more popular -first views (fittingness first, reasons first, and value first). The aim of this paper is to argue that there are at least two categories of normative properties that are basic and that one of those categories is value. Although the emphasis of this paper is on reductionist -first accounts, most of the arguments work equally well against weaker views that are only committed to different categories of normative properties' being linked (...) by a necessary bi-conditional. -/- . (shrink)

This is Part 2 of a four part paper, intended as an introduction to the key concepts and issues of time directionality for physicists and philosophers. It redresses some fundamental confusions in the subject. These need to be corrected in introductory courses for physics and philosophy of physics students. Here we analyze the quantum mechanical time reversal operator and the reversal of the deterministic Schrodinger equation. It is argued that quantum mechanics is anti-symmetric w.r.t. time reversal in its deterministic laws. (...) This contradicts the orthodox analysis, found throughout the conventional literature on physical time, which claims that quantum mechanics is time symmetric (reversible), and that we must adopt the anti-unitary operator (T*) instead of the unitary time reversal operator (T) for time reversal in quantum mechanics. This is widely claimed as settled scientific fact, and large metaphysical conclusions about the symmetry of time are drawn from it. But it is an error. (shrink)

“Doğal din” terimi, bazen doğanın kendisinin ilahi olduğu bir panteistik doktrine atıfta bulunur. “Doğal teoloji” terimi ise aksine, başlangıçta gözlemlenen doğal gerçekler temelinde (ve bazen) Tanrı’nın varlığını savunmaya yönelik projeye atıfta bulunur. Bununla birlikte çağdaş felsefede, hem “doğal din” hem de “doğal teoloji” genel olarak, dinî veya teolojik konuları araştırmak için insana, “doğal” olan bilişsel yetilerini – akıl, algı, içgözlem- kullanma projesini ifade eder. Doğal din veya teoloji, mevcut anlayış üzerine, doğayla ilgili ampirik araştırmalarla sınırlı olmamakla birlikte ayrıca panteistik bir (...) sonuçla da bağlantılı değildir. Bununla birlikte o, özel doğal olmayan yetilere (ESP, telepati, mistik deneyim) veya doğaüstü bilgi kaynaklarına (kutsal metinler, vahiy teolojisi, inanç otoriteleri, doğrudan doğaüstü iletişim) hitap etmekten kaçınır. Genel olarak, doğal din veya teoloji (bundan böyle “doğal teoloji” olarak anılacaktır), diğer felsefi ve bilimsel girişimlerle aynı rasyonel inceleme standartlarına uymayı amaçlamaktadır ve aynı değerlendirme ve eleştiri yöntemlerine tabidir. (shrink)

Scrutiny (1932-1953) was one of the most important critical reviews of the last century. Its editors and contributors included F. R. Leavis, Q. D. Leavis, Denys Thompson, L. C. Knights, D. W. Harding, W. H. Mellers, H. A. Mason, among others. In recasting Scrutiny’s critique of mass culture by way of Alisdair MacIntyre’s After Virtue (1981), I hope to show that the Scrutiny project not only dramatizes the conflicts internal to what MacIntyre calls emotivist culture, but provides a new way (...) of looking at the group’s relation to the culture industry, its purported elitism, and its deep ties with a communitarian rather than socialist politics. (shrink)

On an old narrative, dating back to Leibniz and developed in nineteenth-century historiography, occasionalism was revived in the early modern period as an ad hoc response to the problems of mind-body union and interaction arising from Descartes's metaphysics. According to Leibniz, Descartes gave up the struggle, leaving his disciples to iron out this most scandalous of wrinkles in his system. A line of followers—Clauberg, Geulincx, La Forge, Le Grand, Arnauld, Cordemoy, and above all, Malebranche—dusted off the discredited doctrine of occasionalism (...) in order to deal with the question of how unextended minds could interact with extended bodies. Plainly stated, the solution was as dissatisfying to Leibniz as it has... (shrink)

Since its publication, the Psychopathic Personality Inventory and its revision (Lilien- feld & Andrews, 1996; Lilienfeld & Widows, 2005) have become increasingly popular such that it is now among the most frequently used self-report inventories for the assessment of psychopathy. The current meta-analysis examined the relations between the two PPI factors (factor 1: Fearless Dominance; factor 2: Self-Centered Impulsivity), as well as their relations with other validated measures of psychopathy, internalizing and externalizing forms of psychopathology, general personality traits, and antisocial (...) personality disorder symptoms. Across 61 samples reported in 49 publications, we found support for the convergent and criterion validity of both PPI factor 2 and the PPI total score. Much weaker validation was found for PPI factor 1, which manifested limited convergent validity and a pattern of correlations with central criterion variables that was inconsistent with many conceptualizations of psychopathy. (shrink)

Dr Peter Sjöstedt-H reviews Dr Andrew R. Gallimore's book, Alien Information Theory. -/- This was published on PsyPressUK on 13 June 2019.

J. R. R. Tolkien’s four functions of fantasy stories, as developed in his Andrew Lang lecture “On Fairy Stories” (1939), have become a key conceptual tool for discussing human beings’ attraction to fantasy stories, particularly when attempting to push the analysis beyond the literary into the aesthetic, and beyond the aesthetic into the existential. Applying this interpretive key to an analysis of the expanding genre of post-apocalyptic fiction reveals that post-apocalyptic stories, despite superficial differences, are surprisingly close to fairy (...) stories in their aesthetic core and orientation, and that post-apocalyptic stories are well-suited to fulfill—albeit with their own distinctive aesthetic feel—the functions of Enchantment, Recovery, Escape and Consolation. Furthermore, in exploring the function of Consolation, a number of motifs come to surface that suggest the presence of a religious dimension common to many of the most celebrated exponents of the genre. (shrink)

Several scholars, including Martin Hengel, R. Alan Culpepper, and Richard Bauckham, have argued that Papias had knowledge of the Gospel of John on the grounds that Papias’s prologue lists six of Jesus’s disciples in the same order that they are named in the Gospel of John: Andrew, Peter, Philip, Thomas, James, and John. In “A Note on Papias’s Knowledge of the Fourth Gospel” (JBL 129 [2010]: 793–794), Jake H. O’Connell presents a statistical analysis of this argument, according to which (...) the probability of this correspondence occurring by chance is lower than 1%. O’Connell concludes that it is more than 99% probable that this correspondence is the result of Papias copying John, rather than chance. I show that O’Connell’s analysis contains multiple mistakes, both substantive and mathematical: it ignores relevant evidence, overstates the correspondence between John and Papias, wrongly assumes that if Papias did not know John he ordered the disciples randomly, and conflates the probability of A given B with the probability of B given A. In discussing these errors, I aim to inform both Johannine scholarship and the use of probabilistic methods in historical reasoning. (shrink)

This book delves into esoteric knowledge, describing the structure of the universe (Brahmanda or Cosmic Egg) as a series of astral biospheres. These biospheres, or lokas, are linked to spiritual consciousness and degrees of divine bliss (Ananda). Advanced spiritual figures, such as Rishis and Mahatmas, can navigate these realms and help others evolve. The article presents a detailed comparison between “Puranic Hinduism” and “Sanatana Dharma”, specifically addressing their differences in cosmogenesis and spiritual evolution. The difference between the cosmogenesis of Puranic (...) Hinduism and Sanatana Dharma is that while the former is founded on the concept of Trimurti as taught by the Puranas, the latter is a Manu-centric and Guru-centric spiritual system. This has a lot of significance concerning the rituals and the social order they have produced. Here, the Cosmic Purusha is identifiable with Manu, not with Trimurti or the God of Abrahamic religions, because of their different spiritual status in the cosmological hierarchy. (shrink)

In the present essay, imagination and its effects on the foundations of human life and thought, particularly those pertaining to desire and motivation, are investigated. It is then argued that the human as we know it cannot exist without imagination, and as such, it is an integral part of the self.

The combination of spirituality, meditation, and artificial intelligence (AI) has promising potential to expand people’s well-being using technology-based meditation. Proper meditation originates from Zen Buddhism and Patanjali’s Yoga Sutras and focuses on inner peace and intensified consciousness which elective personal disposition. AI, in turn, brings master means of delivering those practices in the form of self-improving systems that customize and make access to them easier. However, such an integration brings major philosophical and ethical issues into question, including the genuineness of (...) experiences that are facilitated by artificial intelligence, data sharing, concerns over over-dependence on the technology that may in turn cause reduced personal responsibility and hard work. This paper aims at analysing the critical integration of AI-driven meditation following the spiritual interpretations of traditional meditation without compromising the tenets of meditation. It presents an interdisciplinary approach based on recent findings from the field of cognitive science, moral AI, and Eastern wisdom traditions to approach these problems. Therefore, by identifying the research lacunae, it provides a groundwork for voting ethically in the integration of AI in mindfulness practice and avoiding constraining human-oriented values resulting in improved existential spiritual change. (shrink)

This article focuses on the interaction between man and machine, AI specifically, to analyse how these systems are slowly taking over roles that hitherto were thought ‘only’ for humans. More recent, as AI has stepped up in ability to learn without supervision, to recognize patterns, and to solve problems, it adopted characteristics like creativity, novelty, intentionality. These events take one to the heart of what it is to be human, and the emerging definitions of self that are increasingly central to (...) post humanist discourses. The discussion in these two threads is in philosophy of AI and is concerned with issues of consciousness, intentionality and creativity. Al as a result of causing a shift in the current anthropocentric perceptions resulted in portrayal of humans as special beings. Secondly, this exploration responds to important questions related to AI application, such as ethical, social, and existential ones. The article emphasizes a necessity to define the role of the advent of AI and its influence on the interaction between people and technology as well as the role of the social individuality in the wake of intelligent machines that mimic thinking and creativity. It seeks to prompt more specific analysis of how or why AI reduces the differences between artificial and human intelligence or increases the prospects for options expanding the notion of consciousness beyond the human-centric one. (shrink)

This paper criticises the two prominent interpretations of utopianism in Plato's Republic. The traditional argues that it is mere utopianism, seriously proposing that Kallipolis is, in fact, the ideal city. The ironic argues that the Republic is a critique of the ability for reason to reconstruct human nature and is, therefore, a dire warning against utopian thinking in politics. I oppose these two interpretations and instead argue that the Republic implies a paradoxical necessity in the nature of utopianism: The ideal (...) cannot be theorised without itself being conditioned by the politics of theorising, and yet the politics of theorising is immanently motivated by the ideal. I locate this seemingly antonymic dynamic within the education of the learner/citizen in the Republic. Although this is centred on the notion of self-governance, it cannot be imposed and instead depends on the philosophical development of one's soul that is inextricably linked to justice in the city. Therefore, the utopianism of the Republic ought to be thought of as dialectical, being simultaneously situated and yet normatively transcending. (shrink)

Computational Functionalism is a subfield of philosophy of mind most relevant to the subject of cognitive science as well as to artificial intelligence (AI). The analysis of this paper focuses on Hilary Putnam’s and Gualtiero Piccinini’s standpoints regarding the molecular understanding of computation. Finally, Putnam’s argument of the functionalism in notion of the mental states is based on the positive definition of those states by their functions, while Piccinini, and on the other hand suggest that an understanding of the mechanism (...) of computation will go a long way to explaining cognition. This research also points out shortcomings of functionalism in their theories especially in regards to connectivity with physicality of AI structures. Therefore, the paper identifies the following gaps: The first gap holds that although both theorists have important insights, the two approaches put forward by the respective theorists are flawed and a better proposal is required, then a new proposal is suggested In identifying these gaps, the paper seeks to contribute to the literature by arguing for the need to develop a composite of the two theorists. The results show that the big ideas are important in present-day AI debate and analysis, which helps to explain the mind as computation. (shrink)

Exploratory factor analysis (EFA) of the Psychopathic Personality Inventory (PPI; S. O. Lilienfeld, 1990; S. O. Lilienfeld & B. P. Andrews, 1996) with a community sample has suggested that the PPI subscales may comprise 2 higher order factors (S. D. Benning, C. J. Patrick, B. M. Hicks, D. M. Blonigen, & R. F. Krueger, 2003). However, substantive and structural evidence raises concerns about the viability of this 2-factor model, particularly in offender populations. The authors attempted to replicate the S. D. (...) Benning et al. 2-factor solution using a large (N= 1,224) incarcerated male sample. Confirmatory factor analysis of this model resulted in poor model fit. Similarly, using the same EFA procedures as did S. D. Benning et al., the authors found little evidence for a 2-factor model. When they followed the recommendations of J.-W. van Prooijen and W. A. van der Kloot (2001) for recovering EFA solutions, model fit results provided some evidence that a 3-factor EFA solution could be recovered via confirmatory factor analysis. (shrink)

This paper aims to reveal the point of contact between modern science and ancient Indian philosophy, namely quantum mechanics and Advaita Vedanta and Sunyavada in particular. Modern quantum research discloses the essential characteristics of quantum mechanics that disprove classical determinism and find out the relations between energy, entropy, and observations, wave-particle duality, and entanglement. These ideas have some similarity with Advaita Vedanta’s non-dualism (Maya) and Buddhism’s relational existence (Sunyavada) yet there lacks investigation of how either paradigms interface to develop their (...) conceptual epistemology and ontological nexus. This paper recognises the issue of the bridging of these two perspectives, suggests Energetic Relational Ontology as a solution, and presents a new concept, Quantum-Metaphysical Cohesion, through which energy, consciousness and reality can be seen as one. (shrink)

The subject of analysis for this essay is the leanness of the concept of pride and humility and the argument that each of these extremes create imbalance and stifle identity. Humility involves a feeling of low self-worth in order to seek the approval of others and leads to blurring of personal identity, whereas arrogance, results in paranoia, which denies the individual contact and flexibility. Based on the flow and change (Pallas), on the one hand, and the Taoist concept of Laozi (...) on the other hand, the essay developed the notion of fluidity for being an individual. A fluid individual is neither rigidly defined by humbleness, nor is having to deal with arrogance, but rather can balance between the two in certain context and/or role and at the same time be genuine. This framework can provide a fair approach regarding the issue of autonomy and richness of the individual’s self-fulfilment. (shrink)

Political liberals ask citizens not to appeal to certain considerations, including religious and philosophical convictions, in political deliberation. We argue that political liberals must include a demanding requirement of intellectual modesty in their ideal of citizenship in order to motivate this deliberative restraint. The requirement calls on each citizen to believe that the best reasoners disagree about the considerations that she is barred from appealing to. Along the way, we clarify how requirements of intellectual modesty relate to moral reasons for (...) deliberative restraint. And we argue against attempts to weaken our requirement of intellectual modesty by emphasizing those moral reasons. (shrink)

Self-emulation of automata is a switch to the ultimate state that leads the automaton into a never-ending loop. In this paper, we describe the technological singularity and critical points reached when a self-reproducing deterministic finite automaton, realized through modern AI technology, triggers an intelligence explosion, and we examine the phenomena that unfold beyond that point. We also explain the existence of a cognitive realm, one that surpasses humanity’s ability to distinguish reality from unreality caused by superintelligence, as well as the (...) new world created through its nesting. By understanding the properties of the perceptual matrix produced by deterministic finite automata, it becomes possible to offer a consistent explanation, one that does not contradict various theories, for why humanity cannot observe the randomly expanding colonies of extraterrestrial beings under a deterministic worldview in which “God does not play dice,” thereby providing a solution to the Fermi Paradox. We refer to this series of philosophical theories as “Emulationism,” and propose it here. Note: In the creation of this paper, we have undertaken all writing ourselves and have not used generative AI for text generation except for translation purposes. (shrink)

We present a framework that we are currently developing, that allows one to extract knowledge from the knowledge discovery in database (KDD) dataset. Data mining is a very active and space growing research area. Knowledge discovery in databases (KDD) is very useful in scientific domains. In simple terms, association rule mining is one of the most well-known methods for such knowledge discovery. Initially, database are divided into training and testing for the aid of fuzzy generating the rules using fuzzy rules (...) generation the set of rules are generated from the given dataset. From the generated rules, we are extracting the significant rules by using the improved artificial bee colony algorithm and cuckoo search algorithm (IABCCS). After extracting optimal knowledge from the dataset via rules, the data will be classified using fuzzy classifier with the aid of this finally we will classify the attack and normal. (shrink)

This 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. 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. This tool has the potential to revolutionize personal health management by promoting healthier eating habits. (shrink)

SMS spam has become a widespread issue, leading to significant inconvenience and security risks for users. Detecting and filtering out such spam messages is crucial for enhancing the user experience and ensuring privacy. TThe dataset used for training and testing the model consists of labeled SMS messages, which are processed using feature extraction techniques such as TF-IDF and word tokenization. Several machine learning algorithms, including Naive Bayes, Support Vector Machine (SVM), and Random Forest, are evaluated to determine the best-performing model (...) for spam detection. The system is trained and tested using a variety of performance metrics, including accuracy, precision, recall, and F1-score. The results show that machine learning models, particularly Naive Bayes, exhibit high accuracy in distinguishing spam from legitimate messages. This system can be implemented in real-time applications such as mobile phones and email services to improve spam detection and reduce unwanted content. By automating the spam filtering process, the system enhances the efficiency and reliability of communication systems. (shrink)

Bird species identification plays a vital role in biodiversity conservation and ecological studies, offering insights into habitat health and species distribution. Traditional methods for identifying bird species are time-intensive and prone to human error, necessitating automated solutions. This project, Bird Species Identification Using Deep Learning, proposes an advanced system leveraging the power of deep learning to accurately identify bird species from images. The system utilizes a convolutional neural network (CNN), renowned for its proficiency in image classification tasks. A dataset comprising (...) diverse bird species images is preprocessed and augmented to enhance model robustness and generalization. The model architecture is designed to extract intricate features, enabling accurate identification even in challenging scenarios such as varying lighting conditions, occlusions, or similar species appearances. 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. (shrink)

This project aims to develop a predictive system capable of identifying crime types and predicting their occurrences based on historical crime data. The system uses advanced machine learning techniques to analyze factors such as geographic location, time, and other socio-economic variables, enabling authorities to better understand crime patterns and trends. By training models on vast datasets of past criminal activities, the system predicts not only the likely occurrence of specific crime types but also identifies high-risk locations and times, empowering law (...) enforcement to allocate resources more effectively and proactively prevent crime. Various machine learning algorithms, including Decision Trees, Random Forests, and Support Vector Machines (SVM), are employed to ensure accuracy and robustness. The system's predictions can significantly enhance crime management and law enforcement strategies by offering insights into crime prevention and mitigation efforts. This approach facilitates informed decision-making and fosters safer communities by providing accurate forecasts based on data-driven insights. The project underscores the potential of machine learning in public safety and law enforcement, transforming crime prediction and management from reactive to proactive. (shrink)

With the increasing popularity of social networking websites, the problem of fake profiles has become a significant concern. Fake profiles, often created by malicious actors for fraudulent purposes, pose threats to user privacy, security, and trustworthiness of online platforms. This project proposes a machine learning-based approach to detect fake profiles on social networking websites. By analyzing various features such as user activity patterns, profile attributes, and network connections, the model identifies potential fake profiles with high accuracy. The system employs a (...) variety of machine learning algorithms, including decision trees, support vector machines (SVM), and random forests, to classify profiles as either genuine or fake. Data preprocessing techniques such as feature extraction, normalization, and outlier detection are applied to enhance the model's performance. The proposed approach is evaluated on a dataset of social network profiles, and its effectiveness is compared to existing methods in terms of precision, recall, and F1-score. The results demonstrate the ability of the machine learning model to detect fake profiles accurately, providing a valuable tool for social networking platforms to protect users from potential threats and improve the overall user experience. This solution can also help in the automated detection of fraudsters and reduce the manual effort required for profile validation. (shrink)

The problem of immigrant migration risk analysis is deeply studied and there are number of issues identified in the selection of country. There exists number of approaches available in the selection of countries towards migration. However, the methods do not produce effective results in the selection of migrant country. To handle this issue, an efficient real-time migrant risk analysis model (RMAM) is presented in this article. The method uses the traces of previos migration histories and data set maintained by the (...) model. Using the migration data set, the method preprocesses the data set for noise removal and normalization. With the normalized data set, the method applies Nation Centric Religious Support Analysis and Psychological Support Analysis. The nation centric religious support analysis algorithm measure the risk factors on religious features by computing National Religious Support (NRS) and the Psychological Support Analysis algorithm computes the value of Psychological Support (PS) for different countries. Based on the result of different analysis, the method computes Migration Support (MS) for various countries towards the selection of migration countries. The proposed model improves the performance of risk analysis and migration control. (shrink)

Chronic Kidney Disease (CKD) is a significant global health issue, often leading to kidney failure and requiring costly medical treatments such as dialysis or transplants. Early detection of CKD is essential for timely intervention and improved patient outcomes. 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. This approach not only aims to improve diagnostic accuracy but also provides a data-driven solution to assist healthcare professionals in making informed decisions. The outcome of this project can contribute to better management of CKD, ultimately helping to reduce the burden on healthcare systems and improving patient care. (shrink)

The COVID-19 outbreak has had a significant influence on the health of people all across the world, and preventing its further spread requires an early and correct diagnosis. Imaging using X-rays is often used to identify respiratory disorders like COVID-19, and approaches based on machine learning may be used to automate the diagnostic process. In this research, we present a deep learning approach for COVID-19 identification in X-ray pictures utilizing global thresholding. Our framework consists of two main components: (1) global (...) thresholding to preprocess X-ray images and extract features, and (2) a Convolutional Neural Network (CNN) for classifying the images as positive (indicating COVID-19) or negative (indicating no COVID-19). Global thresholding is used to convert X-ray images into binary images, which can highlight the features of interest, such as lung opacity. The Network is instructed to use a dataset consisting of X-ray pictures that have been labeled with the COVID-19 status of each image. The usefulness of our approach was shown by experimental findings obtained using a dataset of X-ray pictures that were made accessible to the public. We achieve high accuracy in COVID-19 detection, outperforming traditional machine learning techniques. Our framework is also able to correctly identify COVID-19 in images that were misclassified by human experts. (shrink)

This article is in a larger textbook of articles on Medical Ethics. It identifies a number of values that underlie professional commitments to confidentiality that are involved in protecting or promoting the client's (1) privacy, (2)social status, (3) economic advantages, (4) openness of communications, (5) seeking professional help, (6) trust in professionals, (7) autonomous control over personal information. The problem of making exceptions to confidentiality commitments is also examined.

If we are to escape reification—a sort of cogni- tive neutrality of basic, gnosic apprehension of the world plus a fundamental disrespect of the other as free agent—we should recognize our mode of existence as always already one of existential engagement with and within experience, aiming at articulating and expressing this engagement. One way of fully inhabiting this, let’s call it the proper human stance, is through recognizing a pendular space between the basic attitudes of acknowledging lived, shared interests and (...) values and avoiding being bound to and dependent on the values of others. Both philosophy as radical critical re- flection, and art, or artistic processes of production and re- ception, can be seen as invitations to inhabit this pendular space of human experience, by way of continually opening up our habits of sensibility to new engagements in thought and life, and successfully articulating and expressing these engagements in public forms. I take Cavell’s reading of Wittgenstein’s mature philosophy as an attuning to an apt attitude towards this invitation. Is this attitude one possible, non-procedural meaning of “liberalism”? (shrink)

Emergency response times play a critical role in saving lives, especially in urban settings where traffic congestion and unpredictable events can delay ambulance arrivals. This paper explores a novel framework for smart route optimization for emergency vehicles, leveraging artificial intelligence (AI), Internet of Things (IoT) technologies, and dynamic traffic analytics. We propose a real-time adaptive routing system that integrates machine learning (ML) for predictive modeling and IoT-enabled communication with traffic infrastructure. The system is evaluated using simulated urban environments, achieving a (...) 35% reduction in response times compared to traditional methods. This work lays the foundation for future advancements in intelligent emergency systems and their integration into smart cities. (shrink)

Plastering is a construction technique using a mixture of cement, fine aggregate (River sand or Msand) to create a smooth, protective finish on walls and ceilings. It conceals imperfections, enhances aesthetics, and improves insulation. But Cement production is a major source of carbon dioxide (CO2) emissions. River sand mining can alter and destroy natural habitats in and around riverbeds. Quarrying for raw materials to produce M-sand can disrupt local ecosystems and habitats, potentially affecting wildlife and plant species in the area. (...) Instead of traditional cement plastering, Also The generation of waste plastic is increasing day by day. It has numerous negative effects on the environment. 9.46 million tons of plastic garbage are produced in India each year. The fact that about 40% of this waste is not collected has an impact on the environment. Hence the Eco plaster gypsum board making with waste plastic, used for reducing environmental impact and contributing to sustainable construction practices. (shrink)

This paper explores various strategies and techniques that retailers use to mitigate buyer resistance and enhance sales effectiveness. It examines methods such as product demonstrations, trial offers, and leveraging third-party testimonials to address consumer hesitations. The paper underscores the importance of understanding buyer concerns related to need, product specifics, sources, pricing, and timing to craft effective sales approaches. Additionally, it discusses the evolving retail landscape, emphasizing the critical role of loyalty programs in fostering consumer retention and encouraging repeat purchases. It (...) also highlights the negotiation process as a tool for building strategic customer relationships and adapting to competitive pressures. Consumer buying behavior, including decision-making stages and factors influencing complex choices, is explored to provide retailers with practical solutions to enhance customer engagement and drive market success. (shrink)

El propósito de este trabajo es analizar los objetos digitales que pueblan nuestras pantallas y redes: vídeos de YouTube, perfiles de Facebook, imágenes de Flickr, archivos de Dropbox, correos electrónicos, podcasts, blogs, y demás. Estos objetos están codificados en binario (0/1) y, en su forma más elemental, son bits y bytes. Para desentrañar estas entidades intangibles, que son realidades insertas en el tejido de nuestra existencia cotidiana, se examinan los supuestos ontológicos y epistemológicos que las rodean. Desde esta perspectiva, se (...) analizan diferentes marcos conceptuales y definiciones, así como los enfoques filosóficos más representativos. También se explora el papel central de los nuevos paradigmas computacionales, la infraestructura TIC y las tecnologías emergentes. Se introduce un modelo de realismo integrativo que encapsula las tesis recogidas a lo largo del documento. El texto concluye con unas breves reflexiones sobre los hallazgos. (shrink)

Este ensayo examina un experimento mental clásico de John Searle en filosofía de la mente, cuyo argumento ha sido descalificado por Dennett y Hofstadter como una bomba de intuiciones no confiable. Lo que se defiende aquí es que este experimento mental tiene un sesgo cartesiano, pero ello no obsta a que no sea confiable. En efecto, la característica principal de la Pieza China es depender de un agente cognitivo consciente que realiza el experimento, y en particular, de quien no se (...) puede prescindir para saber si ocurre o no entendimiento lingüístico luego del procesamiento de símbolos. En efecto, el punto de vista de la 1ª persona de quien lleva a cabo el experimento es, al igual que en otras instancias, lo que permite el testeo de una hipótesis sobre la naturaleza de lo mental. (shrink)

The application of this system can lead to higher crop yields, sustainable farming practices, and reduced risks associated with poor crop choices. Through rigorous evaluation using standard classification metrics, the model's performance demonstrates its potential to revolutionize farming practices by aiding farmers in making informed decisions. The system has the potential to be an invaluable tool for agricultural consultants, farmers, and policymakers, ensuring long-term sustainability and improved productivity.

Vibration, especially basic vibration, may cause loose contacts, open circuits, or other contact problems, which account for a large proportion of system failure causes. Due to the complexity of the chassis structure used in the biomedical motors, the vibration analysis of a single component cannot solve the vibration problems encountered in the work of the system. Therefore, it is necessary to use system simulation and experiments to monitor and enhance the health of the structure. Finite element method is used to (...) carry out the dynamic analysis from the component to the system, and calculate the natural frequency, modal shape and harmonic response. Then, the effectiveness and accuracy of the analysis results are verified by experiments through simulation and experiments. The results show that the measures taken have effectively reduced the vibration of the chassis equipment and improved its safety for better health safety of patients. There is just a 2% variation between the natural frequencies acquired from the experiment and the simulation computation. In terms of natural frequency, the first 6-order natural frequencies all have errors of less than 10%, and the natural frequency error is comparable to that of fireproof board. (shrink)