Results for ' Driver Drowsiness Detection'

768 found
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  1.  66
    OPTIMIZED DRIVER DROWSINESS DETECTION USING MACHINE LEARNING TECHNIQUES.S. Yoheswari - 2024 - Journal of Science Technology and Research (JSTAR) 5 (1):395-400.
    Driver drowsiness is a significant factor contributing to road accidents, resulting in severe injuries and fatalities. This study presents an optimized approach for detecting driver drowsiness using machine learning techniques. The proposed system utilizes real-time data to analyze driver behavior and physiological signals to identify signs of fatigue. Various machine learning algorithms, including Support Vector Machines (SVM), Convolutional Neural Networks (CNN), and Random Forest, are explored for their efficacy in detecting drowsiness. The system incorporates (...)
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  2.  60
    Intelligent Driver Drowsiness Detection System Using Optimized Machine Learning Models.M. Arulselvan - 2024 - Journal of Science Technology and Research (JSTAR) 5 (1):397-405.
    : Driver drowsiness is a significant factor contributing to road accidents, resulting in severe injuries and fatalities. This study presents an optimized approach for detecting driver drowsiness using machine learning techniques. The proposed system utilizes real-time data to analyze driver behavior and physiological signals to identify signs of fatigue. Various machine learning algorithms, including Support Vector Machines (SVM), Convolutional Neural Networks (CNN), and Random Forest, are explored for their efficacy in detecting drowsiness. The system (...)
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  3.  56
    Advanced Driver Drowsiness Detection Model Using Optimized Machine Learning Algorithms.S. Arul Selvan - 2024 - Journal of Science Technology and Research (JSTAR) 5 (1):396-402.
    Driver drowsiness is a significant factor contributing to road accidents, resulting in severe injuries and fatalities. This study presents an optimized approach for detecting driver drowsiness using machine learning techniques. The proposed system utilizes real-time data to analyze driver behavior and physiological signals to identify signs of fatigue. Various machine learning algorithms, including Support Vector Machines (SVM), Convolutional Neural Networks (CNN), and Random Forest, are explored for their efficacy in detecting drowsiness. The system incorporates (...)
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  4. Glocalization challenges and the contemporary architecture: systematic review of common global indicators in Aga Khan Award’s winners.Safa Salkhi Khasraghi & Asma Mehan - 2023 - Journal of Architecture and Urbanism 47 (2):135–145.
    Local reports from different international societies have considered the achievement of the successful Glocalized architecture model in line with the 2030 UN Sustainable Development Goals (SDGs). The Aga Khan Cultural Foundation’s International Program for Islamic Architecture has also prioritized the understanding of the success drivers in architectural projects. This study aimed to detect the potentials of the common global indicators to access qualitative design assessment through analyzing the Aga Khan Award’s reports. The selected methodology in the present study is a (...)
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  5. Evidence amalgamation, plausibility, and cancer research.Marta Bertolaso & Fabio Sterpetti - 2019 - Synthese 196 (8):3279-3317.
    Cancer research is experiencing ‘paradigm instability’, since there are two rival theories of carcinogenesis which confront themselves, namely the somatic mutation theory and the tissue organization field theory. Despite this theoretical uncertainty, a huge quantity of data is available thanks to the improvement of genome sequencing techniques. Some authors think that the development of new statistical tools will be able to overcome the lack of a shared theoretical perspective on cancer by amalgamating as many data as possible. We think instead (...)
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  6. Omissive Overdetermination: Why the Act-Omission Distinction Makes a Difference for Causal Analysis.Yuval Abrams - 2022 - University of Western Australia Law Review 1 (49):57-86.
    Analyses of factual causation face perennial problems, including preemption, overdetermination, and omissions. Arguably, the thorniest, are cases of omissive overdetermination, involving two independent omissions, each sufficient for the harm, and neither, independently, making a difference. A famous example is Saunders, where pedestrian was hit by a driver of a rental car who never pressed on the (unbeknownst to the driver) defective (and, negligently, never inspected) brakes. Causal intuitions in such cases are messy, reflected in disagreement about which omission (...)
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  7. Belgium: Adoption of the Sharing Economy.Liesbeth Huybrechts, Shenja van der Graaf, Ruben D'Hauwers & Jo Pierson - 2021 - In Andrzej Klimczuk, Vida Česnuityte & Gabriela Avram (eds.), The Collaborative Economy in Action: European Perspectives. Limerick: University of Limerick. pp. 52-66.
    The debate on the sharing economy in Belgium has been mainly focused on its economic, quantitative, and digital aspects. Given the fact that the adoption of the sharing economy has accelerated lately, this report wanted to contribute to further open up the debate on the adoption of this economy in relation to an aspect that is too little discussed, namely sustainability. Based on some smaller studies, this report identifies different drivers for concrete sustainable sharing economy initiatives to develop that situate (...)
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  8. Artificial Intelligence and Punjabi Culture.D. P. Singh - 2023 - International Culture and Art (Ica) 5 (4):11-14.
    Artificial Intelligence (AI) is a technology that makes machines smart and capable of doing things that usually require human intelligence. AI works by training machines to learn from data and experiences. Such devices can recognize patterns, understand spoken language, see and understand images, and even make predictions based on their learning. Voice assistants like Siri or Alexa can understand our voice commands, answer questions, and perform tasks for us. AI-based self-driving cars can sense their surroundings, make decisions, and drive safely (...)
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  9. Deception Detection Research: Some Lessons for Epistemology.Peter Graham - 2024 - In Waldomiro J. Silva-Filho (ed.), Epistemology of Conversation: First essays. Cham: Springer.
    According to our folk theory of lying, liars leak observable cues of their insincerity, observable cues that make it easy to catch a liar in real time. Various prominent social epistemologists rely on the correctness of our folk theory as empirically well-confirmed when building their normative accounts of the epistemology of testimony. Deception detection research in communication studies, however, has shown that our folk-theory is mistaken. It is not empirically well-confirmed but empirically refuted. Michaelian (2010) and Shieber (2012) have (...)
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  10. Change Detection.Ronald A. Rensink - 2002 - Annual Review of Psychology 53 (1):245-277.
    Five aspects of visual change detection are reviewed. The first concerns the concept of change itself, in particular the ways it differs from the related notions of motion and difference. The second involves the various methodological approaches that have been developed to study change detection; it is shown that under a variety of conditions observers are often unable to see large changes directly in their field of view. Next, it is argued that this “change blindness” indicates that focused (...)
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  11. True Detective: Buddhism, Pessimism or Philosophy?Finn Janning - 2014 - Journal of Philosophy of Life 4 (4).
    The aim of this paper is to raise two questions. The first question is: How is pessimism related to Buddhism (and vice versa)? The second question is: What relation does an immanent philosophy have to pessimism and Buddhism, if any? Using True Detective, an American television crime drama, as my point of departure, first I will outline some of the likenesses between Buddhism and pessimism. At the same time, I will show how the conduct of one of the main characters (...)
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  12.  58
    Machine Learning-Based Cyberbullying Detection System with Enhanced Accuracy and Speed.M. Arulselvan - 2024 - Journal of Science Technology and Research (JSTAR) 5 (1):421-429.
    The rise of social media has created a new platform for communication and interaction, but it has also facilitated the spread of harmful behaviors such as cyberbullying. Detecting and mitigating cyberbullying on social media platforms is a critical challenge that requires advanced technological solutions. This paper presents a novel approach to cyberbullying detection using a combination of supervised machine learning (ML) and natural language processing (NLP) techniques, enhanced by optimization algorithms. The proposed system is designed to identify and classify (...)
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  13. Drivers of organizational creativity.Mats Sundgren, Elof Dimenäs, Jan-Eric Gustafsson & Marcus Selart - 2005 - RandD Management 35:359-374.
    A path model of organizational creativity was presented; it conceptualized the influences of information sharing, learning culture, motivation, and networking on creative climate. A structural equation model was fitted to data from the pharmaceutical industry to test the proposed model. The model accounted for 86% of the variance in the creative climate dependent variable. Information sharing had a positive effect on learning culture, which in turn had a positive effect on creative climate, while there were negative direct effects of information (...)
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  14. Pedestrian detection based on hierarchical co-occurrence model for occlusion handling.Xiaowei Zhang, HaiMiao Hu, Fan Jiang & Bo Li - 2015 - Neurocomputing 10.
    In pedestrian detection, occlusions are typically treated as an unstructured source of noise and explicit models have lagged behind those for object appearance, which will result in degradation of detection performance. In this paper, a hierarchical co-occurrence model is proposed to enhance the semantic representation of a pedestrian. In our proposed hierarchical model, a latent SVM structure is employed to model the spatial co-occurrence relations among the parent–child pairs of nodes as hidden variables for handling the partial occlusions. (...)
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  15. Direct Detection of Relic Neutrino Background remains impossible: A review of more recent arguments.Florentin Smarandache & Victor Christianto - manuscript
    The existence of big bang relic neutrinos—exact analogues of the big bang relic photons comprising the cosmic microwave background radiation—is a basic prediction of standard cosmology. The standard big bang theory predicts the existence of 1087 neutrinos per flavour in the visible universe. This is an enormous abundance unrivalled by any other known form of matter, falling second only to the cosmic microwave background (CMB) photon. Yet, unlike the CMB photon which boasts its first (serendipitous) detection in the 1960s (...)
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  16. Intelligent Plagiarism Detection for Electronic Documents.Mohran H. J. Al-Bayed - 2017 - Dissertation, Al-Azhar University, Gaza
    Plagiarism detection is the process of finding similarities on electronic based documents. Recently, this process is highly required because of the large number of available documents on the internet and the ability to copy and paste the text of relevant documents with simply Control+C and Control+V commands. The proposed solution is to investigate and develop an easy, fast, and multi-language support plagiarism detector with the easy of one click to detect the document plagiarism. This process will be done with (...)
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  17. A Dilemma for Driver on Virtues of Ignorance.Josh Dolin - 2020 - Ethical Theory and Moral Practice 23 (5):889-898.
    For Julia Driver, some virtues involve ignorance. Modesty, for example, is a disposition to underestimate self-worth, and blind charity is a disposition not to see others’ defects. Such “virtues of ignorance,” she argues, serve as counterexamples to the Aristotelian view that virtue requires intellectual excellence. But Driver seems to face a dilemma: if virtues of ignorance involve ignorance of valuable knowledge, then they do not merit virtue status; but if they involve ignorance of trivial knowledge, then they do (...)
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  18. Deepfake detection by human crowds, machines, and machine-informed crowds.Matthew Groh, Ziv Epstein, Chaz Firestone & Rosalind Picard - 2022 - Proceedings of the National Academy of Sciences 119 (1):e2110013119.
    The recent emergence of machine-manipulated media raises an important societal question: How can we know whether a video that we watch is real or fake? In two online studies with 15,016 participants, we present authentic videos and deepfakes and ask participants to identify which is which. We compare the performance of ordinary human observers with the leading computer vision deepfake detection model and find them similarly accurate, while making different kinds of mistakes. Together, participants with access to the model’s (...)
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  19. Introspection Is Signal Detection.Jorge Morales - forthcoming - British Journal for the Philosophy of Science.
    Introspection is a fundamental part of our mental lives. Nevertheless, its reliability and its underlying cognitive architecture have been widely disputed. Here, I propose a principled way to model introspection. By using time-tested principles from signal detection theory (SDT) and extrapolating them from perception to introspection, I offer a new framework for an introspective signal detection theory (iSDT). In SDT, the reliability of perceptual judgments is a function of the strength of an internal perceptual response (signal- to-noise ratio) (...)
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  20.  29
    Real-Time Phishing Detection Using Genetic Algorithm-Based Ranking and Dynamic Weighting Optimization.A. Manoj Prabaharan - 2024 - Journal of Science Technology and Research (JSTAR) 5 (1):491-500.
    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 (...)
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  21. Forest Fire Detection using Deep Leaning.Mosa M. M. Megdad & Samy S. Abu-Naser - 2024 - International Journal of Academic Information Systems Research (IJAISR) 8 (4):59-65.
    Abstract: Forests are areas with a high density of trees, and they play a vital role in the health of the planet. They provide a habitat for a wide variety of plant and animal species, and they help to regulate the climate by absorbing carbon dioxide from the atmosphere. While in 2010, the world had 3.92Gha of forest cover, covering 30% of its land area, in 2019, there was a loss of forest cover of 24.2Mha according to the Global Forest (...)
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  22. Detection of Brain Tumor Using Deep Learning.Hamza Rafiq Almadhoun & Samy S. Abu-Naser - 2022 - International Journal of Academic Engineering Research (IJAER) 6 (3):29-47.
    Artificial intelligence (AI) is an area of computer science that emphasizes the creation of intelligent machines or software that work and reacts like humans, some of the computer activities with artificial intelligence are designed to include speech, recognition, learning, planning and problem solving. Deep learning is a collection of algorithms used in machine learning, it is part of a broad family of methods used for machine learning that are based on learning representations of data. Deep learning is used as a (...)
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  23. Failure to detect mismatches between intention and outcome in a simple decision task.Petter Johansson, Lars Hall, Sverker Sikstrom & Andreas Olsson - 2005 - Science 310 (5745):116-119.
    A fundamental assumption of theories of decision-making is that we detect mismatches between intention and outcome, adjust our behavior in the face of error, and adapt to changing circumstances. Is this always the case? We investigated the relation between intention, choice, and introspection. Participants made choices between presented face pairs on the basis of attractiveness, while we covertly manipulated the relationship between choice and outcome that they experienced. Participants failed to notice conspicuous mismatches between their intended choice and the outcome (...)
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  24. Drivers for the Formation of Informal Financial Associations by Immigrant Entrepreneurs in South Africa: the Case of Cameroonians.Linus Nkem & Robertson K. Tengeh - 2017 - Economica 13 (5):107-122.
    The sometimes, selective exclusion by the legislation and the financial houses of the host country, force immigrants of African origin to setup stokvels to sustain their businesses and livelihood in South Africa. Aim: To provide the basis for inclusive policy initiatives, this paper investigated the drivers for the formation of business support stokvels by Cameroonians in South Africa. Method: The paper adopted a mix research paradigm with the survey questionnaire and personal interviews as the tools of choice. The purposive sampling (...)
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  25.  44
    AN INTRUSION DETECTION SYSTEM MODEL FOR DETECTING KNOWN AND INNOVATIVE CYBER ATTACKS USING SVM ALGORITHM.Selvan Arul - 2021 - Journal of Science Technology and Research (JSTAR) 2 (1):150-157.
    Nowadays, intrusions have become a major problem faced by users. To stop these cyber attacks from happening, the development of a reliable and effective Intrusion Detection System (IDS) for cyber security has become an urgent issue to be solved. The proposed IDS model is aimed at detecting network intrusions by classifying all the packet traffic in the network as benign or malicious classes. The Canadian Institute for Cyber security Intrusion Detection System (CICIDS2017) dataset has been used to train (...)
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  26. Fraudulent Financial Transactions Detection Using Machine Learning.Mosa M. M. Megdad, Samy S. Abu-Naser & Bassem S. Abu-Nasser - 2022 - International Journal of Academic Information Systems Research (IJAISR) 6 (3):30-39.
    It is crucial to actively detect the risks of transactions in a financial company to improve customer experience and minimize financial loss. In this study, we compare different machine learning algorithms to effectively and efficiently predict the legitimacy of financial transactions. The algorithms used in this study were: MLP Repressor, Random Forest Classifier, Complement NB, MLP Classifier, Gaussian NB, Bernoulli NB, LGBM Classifier, Ada Boost Classifier, K Neighbors Classifier, Logistic Regression, Bagging Classifier, Decision Tree Classifier and Deep Learning. The dataset (...)
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  27.  47
    Breakthroughs in Breast Cancer Detection: Emerging Technologies and Future Prospects.Ola I. A. Lafi, Rawan N. A. Albanna, Dina F. Alborno, Raja E. Altarazi, Amal Nabahin, Bassem S. Abu-Nasser & Samy S. Abu-Naser - 2024 - International Journal of Academic Health and Medical Research (IJAHMR) 8 (9):8-15.
    Abstract: Early detection of breast cancer is vital for improving patient outcomes and reducing mortality rates. Technological advancements have significantly enhanced the accuracy and efficiency of screening methods. This paper explores recent innovations in early detection, focusing on the evolution of digital mammography, the benefits of 3D mammography (tomosynthesis), and the application of advanced imaging techniques such as molecular imaging and MRI. It also examines the role of artificial intelligence (AI) in diagnostic tools, showing how machine learning algorithms (...)
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  28.  64
    OPTIMIZED CYBERBULLYING DETECTION IN SOCIAL MEDIA USING SUPERVISED MACHINE LEARNING AND NLP TECHNIQUES.S. Yoheswari - 2024 - Journal of Science Technology and Research (JSTAR) 5 (1):421-435.
    The rise of social media has created a new platform for communication and interaction, but it has also facilitated the spread of harmful behaviors such as cyberbullying. Detecting and mitigating cyberbullying on social media platforms is a critical challenge that requires advanced technological solutions. This paper presents a novel approach to cyberbullying detection using a combination of supervised machine learning (ML) and natural language processing (NLP) techniques, enhanced by optimization algorithms. The proposed system is designed to identify and classify (...)
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  29. In defence of gullibility: The epistemology of testimony and the psychology of deception detection.Kourken Michaelian - 2010 - Synthese 176 (3):399-427.
    Research in the psychology of deception detection implies that Fricker, in making her case for reductionism in the epistemology of testimony, overestimates both the epistemic demerits of the antireductionist policy of trusting speakers blindly and the epistemic merits of the reductionist policy of monitoring speakers for trustworthiness: folk psychological prejudices to the contrary notwithstanding, it turns out that monitoring is on a par (in terms both of the reliability of the process and of the sensitivity of the beliefs that (...)
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  30. Economic drivers of biological complexity.Steve Phelps & Yvan I. Russell - 2015 - Adaptive Behavior 23:315-326.
    The complexity that we observe in nature can often be explained in terms of cooperative behavior. For example, the major transitions of evolution required the emergence of cooperation among the lower-level units of selection, which led to specialization through division-of-labor ultimately resulting in spontaneous order. There are two aspects to address explaining how such cooperation is sustained: how free-riders are prevented from free-riding on the benefits of cooperative tasks, and just as importantly, how those social benefits arise. We review these (...)
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  31. Impact of Applying Fraud Detection and Prevention Instruments in Reducing Occupational Fraud: Case study: Ministry of Health (MOH) in Gaza Strip.Faris M. Abu Mouamer, Youssef M. Abu Amuna, Mohammed K. H. A. L. I. Khalil & Abedallh Aqel - 2020 - International Journal of Academic Accounting, Finance and Management Research (IJAAFMR) 4 (6):35-45.
    The study aimed to identify the effect of applying detection and prevention tools for career fraud in combating and preventing fraud and reducing its risks through an applied study on Palestinian Ministry of Health in Gaza Strip, Palestine. To achieve the objectives of the study, the researchers used the questionnaire as a main tool to collect data, and the descriptive and analytical approach to conducting the study. The study population consisted of (501) supervisory employees working at MOH in Gaza (...)
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  32.  76
    Automated Cyberbullying Detection Framework Using NLP and Supervised Machine Learning Models.M. Arul Selvan - 2024 - Journal of Science Technology and Research (JSTAR) 5 (1):421-432.
    The rise of social media has created a new platform for communication and interaction, but it has also facilitated the spread of harmful behaviors such as cyberbullying. Detecting and mitigating cyberbullying on social media platforms is a critical challenge that requires advanced technological solutions. This paper presents a novel approach to cyberbullying detection using a combination of supervised machine learning (ML) and natural language processing (NLP) techniques, enhanced by optimization algorithms. The proposed system is designed to identify and classify (...)
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  33. Web page phishing detection Using Neural Network.Ahmed Salama Abu Zaiter & Samy S. Abu-Naser - 2023 - International Journal of Engineering and Information Systems (IJEAIS) 7 (9):1-13.
    Web page phishing is a type of phishing attack that targets websites. In a web page phishing attack, the attacker creates a fake website that looks like a legitimate website, such as a bank or credit card company website. The attacker then sends a fraudulent message to the victim, which contains a link to the fake website. When the victim clicks on the link, they are taken to the fake website and tricked into entering their personal information.Web page phishing attacks (...)
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  34. Detecting Health Problems Related to Addiction of Video Game Playing Using an Expert System.Samy S. Abu Naser & Mohran H. Al-Bayed - 2016 - World Wide Journal of Multidisciplinary Research and Development 2 (9):7-12.
    Today’s everyone normal life can include a normal rate of playing computer games or video games; but what about an excessive or compulsive use of video games that impact on our life? Our kids, who usually spend a lot of time in playing video games will likely have a trouble in paying attention to their school lessons. In this paper, we introduce an expert system to help users in getting the correct diagnosis of the health problem of video game addictions (...)
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  35. Detecting Ideology in Our Understanding of Objectivity.Markus Gabriel - 2015 - In Channa van Dijk, Eva van der Graaf, Michiel den Haan, Rosa de Jong, Christiaan Roodenburg, Dyane Til & Deva Waal (eds.), Under Influence - Philosophical Festival Drift (2014). Omnia. pp. 44-63.
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  36. Wave detected by LIGO is not gravitational wave.Alfonso Leon Guillen Gomez - manuscript
    General Relativity defines gravity like the metric of a Lorentzian manifold. Einstein formulated spacetime as quality structural of gravity, i.e, circular definition between gravity and spacetime, also Einstein denoted "Space and time are modes by which we think, not conditions under which we live" and “We denote everything but the gravitational field as matter”, therefore, spacetime is nothing and gravity in first approximation an effect of coordinates, and definitely a geometric effect. The mathematical model generates quantitative predictions coincident in high (...)
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  37. Lung Cancer Detection Using Artificial Neural Network.Ibrahim M. Nasser & Samy S. Abu-Naser - 2019 - International Journal of Engineering and Information Systems (IJEAIS) 3 (3):17-23.
    In this paper, we developed an Artificial Neural Network (ANN) for detect the absence or presence of lung cancer in human body. Symptoms were used to diagnose the lung cancer, these symptoms such as Yellow fingers, Anxiety, Chronic Disease, Fatigue, Allergy, Wheezing, Coughing, Shortness of Breath, Swallowing Difficulty and Chest pain. They were used and other information about the person as input variables for our ANN. Our ANN established, trained, and validated using data set, which its title is “survey lung (...)
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  38. Gulong ng Palad: The Quality of Life, Experiences and Challenges Faced by Female Tricycle Driver.Jhoselle Tus, Ken Andrei Torrero, Aron Bil, Timy Joy Juliano, Angeline Mechille Eugenio Osinaga, Josie Lynn Garcia Parinas, Ramon Principe & Franz Cedrick Yapo - 2023 - Psychology and Education: A Multidisciplinary Journal 7 (1):153-159.
    Tricycles are one of the most popular, most accessible, and least expensive forms of public transit in the Philippines. In addition to being common modes of transportation, motorcycles, and tricycles also contribute significantly to the livelihoods of millions of Filipinos who rely on them for a living. Hence, this study explores the lived experiences and challenges faced by female tricycle drivers. Employing the Interpretative Phenomenological Analysis, the findings of this study were: The participants strive to assist their husbands in providing (...)
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  39. Autism spectrum and cheaters detection.Miguel López Astorga - 2014 - Dialogues in Philosophy, Mental and Neuro Sciences 7 (1):1-10.
    Rutherford and Ray think that human beings have mental mechanisms that help them to detect individuals that, deliberately, do not follow a rule. In the same way, they hold that autism is not a disorder in which these mechanisms are damaged. This idea seems contrary to the thesis, supported by some researchers, that autistic people have a theory of mind deficit. This is because of, if Rutherford and Ray are right, autistic people can detect other people's intentions. In this paper, (...)
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  40.  55
    Adaptive SVM Techniques for Optimized Detection of Known and Novel Cyber Intrusions.M. Arulselvan - 2024 - Journal of Science Technology and Research (JSTAR) 5 (1):398-405.
    The ever-evolving landscape of cyber threats necessitates robust and adaptable intrusion detection systems (IDS) capable of identifying both known and emerging attacks. Traditional IDS models often struggle with detecting novel threats, leading to significant security vulnerabilities. This paper proposes an optimized intrusion detection model using Support Vector Machine (SVM) algorithms tailored to detect known and innovative cyberattacks with high accuracy and efficiency. The model integrates feature selection and dimensionality reduction techniques to enhance detection performance while reducing computational (...)
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  41.  46
    Intelligent Phishing Content Detection System Using Genetic Ranking and Dynamic Weighting Techniques.P. Selvaprasanth - 2024 - Journal of Science Technology and Research (JSTAR) 5 (1):480-490.
    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.
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  42. SVM-Enhanced Intrusion Detection System for Effective Cyber Attack Identification and Mitigation.M. Arul Selvan - 2024 - Journal of Science Technology and Research (JSTAR) 5 (1):397-403.
    The ever-evolving landscape of cyber threats necessitates robust and adaptable intrusion detection systems (IDS) capable of identifying both known and emerging attacks. Traditional IDS models often struggle with detecting novel threats, leading to significant security vulnerabilities. This paper proposes an optimized intrusion detection model using Support Vector Machine (SVM) algorithms tailored to detect known and innovative cyberattacks with high accuracy and efficiency. The model integrates feature selection and dimensionality reduction techniques to enhance detection performance while reducing computational (...)
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  43. Human Symmetry Uncertainty Detected by a Self-Organizing Neural Network Map.Birgitta Dresp-Langley - 2021 - Symmetry 13:299.
    Symmetry in biological and physical systems is a product of self-organization driven by evolutionary processes, or mechanical systems under constraints. Symmetry-based feature extraction or representation by neural networks may unravel the most informative contents in large image databases. Despite significant achievements of artificial intelligence in recognition and classification of regular patterns, the problem of uncertainty remains a major challenge in ambiguous data. In this study, we present an artificial neural network that detects symmetry uncertainty states in human observers. To this (...)
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  44. Technology as Driver for Morally Motivated Conceptual Engineering.Herman Veluwenkamp, Marianna Capasso, Jonne Maas & Lavinia Marin - 2022 - Philosophy and Technology 35 (3):1-25.
    New technologies are the source of uncertainties about the applicability of moral and morally connotated concepts. These uncertainties sometimes call for conceptual engineering, but it is not often recognized when this is the case. We take this to be a missed opportunity, as a recognition that different researchers are working on the same kind of project can help solve methodological questions that one is likely to encounter. In this paper, we present three case studies where philosophers of technology implicitly engage (...)
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  45. Can we detect consciousness in newborn infants?Claudia Passos-Ferreira - 2024 - Neuron 112:1520-1523.
    Conscious experiences in infants remain poorly understood. In this NeuroView, Passos-Ferreira discusses recent evidence for and against consciousness in newborn babies. She argues that the weight of evidence from neuroimaging and behavioral studies supports the thesis that newborn infants are conscious.
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  46. Can Gravitons be Detected?Tony Rothman & Stephen Boughn - 2006 - Foundations of Physics 36 (12):1801-1825.
    Freeman Dyson has questioned whether any conceivable experiment in the real universe can detect a single graviton. If not, is it meaningful to talk about gravitons as physical entities? We attempt to answer Dyson’s question and find it is possible concoct an idealized thought experiment capable of detecting one graviton; however, when anything remotely resembling realistic physics is taken into account, detection becomes impossible, indicating that Dyson’s conjecture is very likely true. We also point out several mistakes in the (...)
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  47. Ontology-based error detection in SNOMED-CT.Werner Ceusters, Barry Smith, Anand Kumar & Christoffel Dhaen - 2004 - Proceedings of Medinfo 2004:482-6.
    Quality assurance in large terminologies is a difficult issue. We present two algorithms that can help terminology developers and users to identify potential mistakes. We demon­strate the methodology by outlining the different types of mistakes that are found when the algorithms are applied to SNOMED-CT. On the basis of the results, we argue that both formal logical and linguistic tools should be used in the development and quality-assurance process of large terminologies.
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  48. Autism spectrum and cheaters detection.Miguel Lopez Astorga - 2014 - Dialogues in Philosophy, Mental and Neuro Sciences 7 (1):1-10.
    Rutherford and Ray think that human beings have mental mechanisms that help them to detect individuals that, deliberately, do not follow a rule. In the same way, they hold that autism is not a disorder in which these mechanisms are damaged. This idea seems contrary to the thesis, supported by some researchers, that autistic people have a theory of mind deficit. This is because of, if Rutherford and Ray are right, autistic people can detect other people’s intentions. In this paper, (...)
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  49. Detecting the Factors Affecting Classroom Dialogue Quality.Chrysi Rapanta, Merce Garcia-Milà, Andrea Miralda Banda & Fabrizio Macagno - 2023 - Linguistics and Education 77:101223.
    Despite the emphasis on dialogue and argumentation in educational settings, still not much is known about how best we can support learners in their interthinking, reasoning, and metadialogic understanding. The goal of this classroom intervention study is to explore the degree of students’ dialogicity and its possible increase during a learning programme implementing dialogic and argument-based teaching goals and principles. In particular, we focus on how students from 5 to 15 years old engage with each other's ideas, and whether/how this (...)
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  50. Responsible Innovation in Social Epistemic Systems: The P300 Memory Detection Test and the Legal Trial.John Danaher - forthcoming - In Van den Hoven (ed.), Responsible Innovation Volume II: Concepts, Approaches, Applications. Springer.
    Memory Detection Tests (MDTs) are a general class of psychophysiological tests that can be used to determine whether someone remembers a particular fact or datum. The P300 MDT is a type of MDT that relies on a presumed correlation between the presence of a detectable neural signal (the P300 “brainwave”) in a test subject, and the recognition of those facts in the subject’s mind. As such, the P300 MDT belongs to a class of brain-based forensic technologies which have proved (...)
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