Results for 'Data-driven analysis'

987 found
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  1. A conceptual framework for data-driven sustainable finance in green energy transition.Omotayo Bukola Adeoye, Ani Emmanuel Chigozie, Ninduwesuor-Ehiobu Nwakamma, Jose Montero Danny, Favour Oluwadamilare Usman & Kehinde Andrew Olu-Lawal - 2024 - World Journal of Advanced Research and Reviews 21 (2):1791–1801.
    As the world grapples with the urgent need for sustainable development, the transition towards green energy stands as a critical imperative. Financing this transition poses significant challenges, requiring innovative approaches that align financial objectives with environmental sustainability goals. This review presents a conceptual framework for leveraging data-driven techniques in sustainable finance to facilitate the transition towards green energy. The proposed framework integrates principles of sustainable finance with advanced data analytics to enhance decision-making processes across the financial ecosystem. (...)
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  2. Going in, moral, circles: A data-driven exploration of moral circle predictors and prediction models.Hyemin Han & Marja Graham - manuscript
    Moral circles help define the boundaries of one’s moral consideration. One’s moral circle may provide insight into how one perceives or treats other entities. A data-driven model exploration was conducted to explore predictors and prediction models. Candidate predictors were built upon past research using moral foundations and political orientation. Moreover, we also employed additional moral psychological indicators, i.e., moral reasoning, moral identity, and empathy, based on prior research in moral development and education. We used model exploration methods, i.e., (...)
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  3. Who's Anthropocene?: a data driven look at the prospects for collaboration between natural science, social science, and the humanities.Carlos Santana, K. Petrozzo & Timothy Perkins - 2024 - Digital Scholarship in the Humanities 39 (2):723-735.
    Although the idea of the Anthropocene originated in the earth sciences, there have been increasing calls for questions about the Anthropocene to be addressed by pan-disciplinary groups of researchers from across the natural sciences, social sciences, and humanities. We use data analysis techniques from corpus linguistics to examine academic texts about the Anthropocene from these disciplinary families. We read the data to suggest that barriers to a broadly interdisciplinary study of the Anthropocene are high, but we are (...)
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  4. Enabling the Nonhypothesis-Driven Approach: On Data Minimalization, Bias, and the Integration of Data Science in Medical Research and Practice.C. W. Safarlou, M. van Smeden, R. Vermeulen & K. R. Jongsma - 2023 - American Journal of Bioethics 23 (9):72-76.
    Cho and Martinez-Martin provide a wide-ranging analysis of what they label “digital simulacra”—which are in essence data-driven AI-based simulation models such as digital twins or models used for i...
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  5. Non-Conscious Data Collection: A Critical Analysis of Risks and Public Perspectives.Matomäki Sofia - 2024 - Dissertation, Aalto University School of Business
    This literature review explores the issues and risks in non-conscious data collection and evaluates people’s attitudes towards it. In the modern world, data is one of the most valuable resources, yet studies focused on the potential negative implications of the new data-driven technologies are lacking. Therefore, this thesis conducts a comprehensive literature review to identify and assess risks in non-conscious data collection technologies that are most relevant and referenced in current literature. Accordingly, the most prominent (...)
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  6. Predictive Analysis of Lottery Outcomes Using Deep Learning and Time Series Analysis.Asil Mustafa Alghoul & Samy S. Abu-Naser - 2023 - International Journal of Engineering and Information Systems (IJEAIS) 7 (10):1-6.
    Abstract: Lotteries have long been a source of fascination and intrigue, offering the tantalizing prospect of unexpected fortunes. In this research paper, we delve into the world of lottery predictions, employing cutting-edge AI techniques to unlock the secrets of lottery outcomes. Our dataset, obtained from Kaggle, comprises historical lottery draws, and our goal is to develop predictive models that can anticipate future winning numbers. This study explores the use of deep learning and time series analysis to achieve this elusive (...)
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  7. Driven to extinction? The ethics of eradicating mosquitoes with gene-drive technologies.Jonathan Pugh - 2016 - Journal of Medical Ethics 42 (9):578-581.
    Mosquito-borne diseases represent a significant global disease burden, and recent outbreaks of such diseases have led to calls to reduce mosquito populations. Furthermore, advances in ‘gene-drive’ technology have raised the prospect of eradicating certain species of mosquito via genetic modification. This technology has attracted a great deal of media attention, and the idea of using gene-drive technology to eradicate mosquitoes has been met with criticism in the public domain. In this paper, I shall dispel two moral objections that have been (...)
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  8. AI-Driven Organizational Change: Transforming Structures and Processes in the Modern Workplace.Mohammed Elkahlout, Mohammed B. Karaja, Abeer A. Elsharif, Ibtesam M. Dheir, Basem S. Abunasser & Samy S. Abu-Naser - 2024 - Information Journal of Academic Information Systems Research (Ijaisr) 8 (8):38-45.
    Abstract: Artificial Intelligence (AI) is revolutionizing organizational dynamics by reshaping both structures and processes. This paper explores how AI-driven innovations are transforming organizational frameworks, from hierarchical adjustments to decentralized decision-making models. It examines the impact of AI on various processes, including workflow automation, data analysis, and enhanced decision support systems. Through case studies and empirical research, the paper highlights the benefits of AI in improving efficiency, driving innovation, and fostering agility within organizations. Additionally, it addresses the challenges (...)
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  9. Annotating affective neuroscience data with the Emotion Ontology.Janna Hastings, Werner Ceusters, Kevin Mulligan & Barry Smith - 2012 - In Janna Hastings, Werner Ceusters, Kevin Mulligan & Barry Smith (eds.), Third International Conference on Biomedical Ontology. ICBO. pp. 1-5.
    The Emotion Ontology is an ontology covering all aspects of emotional and affective mental functioning. It is being developed following the principles of the OBO Foundry and Ontological Realism. This means that in compiling the ontology, we emphasize the importance of the nature of the entities in reality that the ontology is describing. One of the ways in which realism-based ontologies are being successfully used within biomedical science is in the annotation of scientific research results in publicly available databases. Such (...)
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  10. Ihde’s Missing Sciences: Postphenomenology, Big Data, and the Human Sciences.Daniel Susser - 2016 - Techné: Research in Philosophy and Technology 20 (2):137-152.
    In Husserl’s Missing Technologies, Don Ihde urges us to think deeply and critically about the ways in which the technologies utilized in contemporary science structure the way we perceive and understand the natural world. In this paper, I argue that we ought to extend Ihde’s analysis to consider how such technologies are changing the way we perceive and understand ourselves too. For it is not only the natural or “hard” sciences which are turning to advanced technologies for help in (...)
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  11.  30
    Dredging Analysis and Decision Support System.K. Mahesh - 2024 - International Journal of Engineering Innovations and Management Strategies 1 (5):1-15.
    Dredging operations are essential for maintaining navigable waterways, but determining the ideal time to dredge requires a multifaceted approach, incorporating both environmental and operational variables. This paper presents the Dredging Analysis and Decision Support System (DADSS), a data-driven solution that employs historical sedimentation data, weather patterns, and water flow statistics to optimize dredging decisions. The system leverages Random Forest Classifier and Regressor models to predict the need for dredging and estimate associated costs. Key inputs include sedimentation (...)
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  12. Ontology-based fusion of sensor data and natural language.Erik Thomsen & Barry Smith - 2018 - Applied ontology 13 (4):295-333.
    We describe a prototype ontology-driven information system (ODIS) that exploits what we call Portion of Reality (POR) representations. The system takes both sensor data and natural language text as inputs and composes on this basis logically structured POR assertions. The goal of our prototype is to represent both natural language and sensor data within a single framework that is able to support both axiomatic reasoning and computation. In addition, the framework should be capable of discovering and representing (...)
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  13. Smart worlds and broken habits - A contextual analysis of the technological relations of post-phenomenology.Maria Brincker - 2024 - In Line Ryberg Ingerslev & Karl Mertens (eds.), Phenomenology of Broken Habits: Philosophical and Psychological Perspectives on Habitual Action. New York, NY: Routledge. pp. 133-159.
    We expand and transform our habitual agency with countless technologies most moments of the day. Our environments, bodies, thoughts and social interactions are thoroughly shaped and mediated by tapestries of interweaving layers of old and new technologies. Perhaps this intimate relation with technology is at the core of our humanity. But our relation to technology has also repeatedly been feared as a Faustian deal that will be the dystopian end of us, or—in more utopian viewpoints— will bring us beyond our (...)
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  14. Predicting Students' end-of-term Performances using ML Techniques and Environmental Data.Ahmed Mohammed Husien, Osama Hussam Eljamala, Waleed Bahgat Alwadia & Samy S. Abu-Naser - 2023 - International Journal of Academic Information Systems Research (IJAISR) 7 (10):19-25.
    Abstract: This study introduces a machine learning-based model for predicting student performance using a comprehensive dataset derived from educational sources, encompassing 15 key features and comprising 62,631 student samples. Our five-layer neural network demonstrated remarkable performance, achieving an accuracy of 89.14% and an average error of 0.000715, underscoring its effectiveness in predicting student outcomes. Crucially, this research identifies pivotal determinants of student success, including factors such as socio-economic background, prior academic history, study habits, and attendance patterns, shedding light on the (...)
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  15. The Fate of Explanatory Reasoning in the Age of Big Data.Frank Cabrera - 2021 - Philosophy and Technology 34 (4):645-665.
    In this paper, I critically evaluate several related, provocative claims made by proponents of data-intensive science and “Big Data” which bear on scientific methodology, especially the claim that scientists will soon no longer have any use for familiar concepts like causation and explanation. After introducing the issue, in Section 2, I elaborate on the alleged changes to scientific method that feature prominently in discussions of Big Data. In Section 3, I argue that these methodological claims are in (...)
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  16. Ontology-based knowledge representation of experiment metadata in biological data mining.Scheuermann Richard, Kong Megan, Dahlke Carl, Cai Jennifer, Lee Jamie, Qian Yu, Squires Burke, Dunn Patrick, Wiser Jeff, Hagler Herb, Herb Hagler, Barry Smith & David Karp - 2009 - In Chen Jake & Lonardi Stefano (eds.), Biological Data Mining. Chapman Hall / Taylor and Francis. pp. 529-559.
    According to the PubMed resource from the U.S. National Library of Medicine, over 750,000 scientific articles have been published in the ~5000 biomedical journals worldwide in the year 2007 alone. The vast majority of these publications include results from hypothesis-driven experimentation in overlapping biomedical research domains. Unfortunately, the sheer volume of information being generated by the biomedical research enterprise has made it virtually impossible for investigators to stay aware of the latest findings in their domain of interest, let alone (...)
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  17.  20
    Analytics Based on Government Land Information System (GLIS) Data.R. Mrudula - 2025 - International Journal of Engineering Innovations and Management Strategies 1 (9):1-10.
    The Government Land Information System (GLIS) dataset provides detailed data on land use patterns, population distribution, and demographic characteristics across all States and Union Territories. This dataset serves as an essential tool for making data-driven decisions in areas such as urban planning, infrastructure development, environmental protection, and socio-economic advancement. The goal of analysing this dataset is to uncover key insights into current land use trends and their effects on sustainable urban development. By studying land use changes, the (...)
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  18. Predictive Modeling of Smoke Potential Using Neural Networks and Environmental Data.Abu Al-Reesh Kamal Ali, Al-Safadi Muhammad Nidal, Al-Tanani Waleed Sami & Samy S. Abu-Naser - 2023 - International Journal of Engineering and Information Systems (IJEAIS) 7 (9):38-46.
    This study presents a neural network-based model for predicting smoke potential in a specific area using a Kaggle-derived dataset with 15 environmental features and 62,631 samples. Our five-layer neural network achieved an accuracy of 89.14% and an average error of 0.000715, demonstrating its effectiveness. Key influential features, including temperature, humidity, crude ethanol, pressure, NC1.0, NC2.5, SCNT, and PM2.5, were identified, providing insights into smoke occurrence. This research aids in proactive smoke mitigation and public health protection. The model's accuracy and feature (...)
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  19. Exploring the relationship between purpose and moral psychological indicators.Hyemin Han - 2024 - Ethics and Behavior 34 (1):28-39.
    ABSTRACT In the present study, I explore the relationship between purpose, which was measured by the Claremont Purpose Scale, and moral psychological indicators, moral reasoning, moral identity, and empathy. Purpose was quantified in terms of three subcomponents: meaning, goal, and beyond-the-self motivation. Moral reasoning was assessed in terms of utilization of postconventional moral reasoning. Moral identity was examined with two subscales: moral internalization, and symbolization. Among diverse subscales of empathy, I focused on empathic concern and perspective taking, which have been (...)
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  20. Chances of Survival in the Titanic using ANN.Udai Hamed Saeed Al-Hayik & Samy S. Abu-Naser - 2023 - International Journal of Academic Engineering Research (IJAER) 7 (10):17-21.
    Abstract: The sinking of the RMS Titanic in 1912 remains a poignant historical event that continues to captivate our collective imagination. In this research paper, we delve into the realm of data-driven analysis by applying Artificial Neural Networks (ANNs) to predict the chances of survival for passengers aboard the Titanic. Our study leverages a comprehensive dataset encompassing passenger information, demographics, and cabin class, providing a unique opportunity to explore the complex interplay of factors influencing survival outcomes. Our (...)
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  21. An Analysis of the Relationship between Foreign Trade and Economic Growth in Myanmar during 1990-2014.Kyaw Kyaw Lynn - 2014 - International Journal of Business and Administrative Studies 1 (4):114-131.
    This study analyzes the relationship between foreign trade and economic growth in Myanmar over the period 1990-2014. It covers the annual data of GDP, Export and Import of Myanmar from 1980 to 2014. This study adopts two major methodological approaches – exploratory data analysis and descriptive analysis. For the first approach, Augmented Dickey-Fuller (ADF) unit root test and Granger causality test are used under the framework of Vector Autoregressive (VAR) model, which have almost never been studied (...)
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  22. ImmPort, toward repurposing of open access immunological assay data for translational and clinical research.Sanchita Bhattacharya, Patrick Dunn, Cristel Thomas, Barry Smith, Henry Schaefer, Jieming Chen, Zicheng Hu, Kelly Zalocusky, Ravi Shankar & Shai Shen-Orr - 2018 - Scientific Data 5:180015.
    Immunology researchers are beginning to explore the possibilities of reproducibility, reuse and secondary analyses of immunology data. Open-access datasets are being applied in the validation of the methods used in the original studies, leveraging studies for meta-analysis, or generating new hypotheses. To promote these goals, the ImmPort data repository was created for the broader research community to explore the wide spectrum of clinical and basic research data and associated findings. The ImmPort ecosystem consists of four components–Private (...)
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  23. No wisdom in the crowd: genome annotation at the time of big data - current status and future prospects.Antoine Danchin - 2018 - Microbial Biotechnology 11 (4):588-605.
    Science and engineering rely on the accumulation and dissemination of knowledge to make discoveries and create new designs. Discovery-driven genome research rests on knowledge passed on via gene annotations. In response to the deluge of sequencing big data, standard annotation practice employs automated procedures that rely on majority rules. We argue this hinders progress through the generation and propagation of errors, leading investigators into blind alleys. More subtly, this inductive process discourages the discovery of novelty, which remains essential (...)
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  24. Artificial Intelligence and Theory of Mind.David Matta - manuscript
    The essay explores the intersection of the Theory of Mind (T.O.M.) and Artificial Intelligence (AI), emphasizing the potential for AI to emulate cognitive processes fundamental to human social interactions. T.O.M., a concept crucial for understanding and interpreting human behavior through attributed mental states, contrasts with AI's behaviorist approach, which is rooted in data-driven pattern analysis and predictions. By examining foundational insights from cognitive sciences and the operational models of AI, this analysis highlights the potential advancements and (...)
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  25. How tracking technology is transforming animal ecology: epistemic values, interdisciplinarity, and technology-driven scientific change.Rose Trappes - 2023 - Synthese 201 (4):1-24.
    Tracking technology has been heralded as transformative for animal ecology. In this paper I examine what changes are taking place, showing how current animal movement research is a field ripe for philosophical investigation. I focus first on how the devices alter the limitations and biases of traditional field observation, making observation of animal movement and behaviour possible in more detail, for more varied species, and under a broader variety of conditions, as well as restricting the influence of human presence and (...)
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  26.  70
    Student Dropout Analysis for School Education.J. Siva Prashanth - 2024 - International Journal of Engineering Innovations and Management Strategies 1 (1):1-12.
    This project explores the issue of high dropout rates in school education. We utilize a machine learning-driven approach to analyze data on student demographics, academic performance, attendance, and socioeconomic factors. By identifying at-risk students early, we aim to provide targeted interventions that will reduce dropout rates. This document outlines the structure, methodology, and findings of the project, leveraging techniques such as data preprocessing, model training, hyperparameter tuning, and risk stratification.
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  27.  40
    A Large-Scale Empirical Study Identifying Practitioners' Perspectives on Challenges in Docker Development: Analysis using Stack Overflow.Sharma Sakshi - 2024 - International Journal of Innovative Research in Computer and Communication Engineering 12 (2):1104-1111.
    This study investigates Docker-related topics and challenges through an analysis of Stack Overflow posts to identify prevalent issues and trends in Docker development. By leveraging both tag-based and content-based filtering methods, we compiled a comprehensive dataset of Docker discussions. Latent Dirichlet Allocation (LDA) topic modeling was employed to categorize these discussions, revealing that Application Development is the predominant focus, encompassing areas such as Framework Management, Coding Issues, Data Transfer, and Dockerspecific frameworks. This dominant category reflects developers' substantial interest (...)
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  28. Harnessing Artificial Intelligence to Enhance Medical Image Analysis.Malak S. Hamad, Mohammed H. Aldeeb, Mohammed M. Almzainy, Shahd J. Albadrasawi, Musleh M. Musleh, Bassem S. Abu-Nasser & Samy S. Abu-Naser - 2024 - International Journal of Academic Health and Medical Research (IJAHMR) 8 (9):1-7.
    Abstract: The integration of Artificial Intelligence (AI) into medical imaging marks a transformative advancement in healthcare, significantly enhancing diagnostic accuracy, efficiency, and patient outcomes. This paper delves into the application of AI technologies in medical image analysis, with a particular focus on techniques such as convolutional neural networks (CNNs) and deep learning models. We examine how these technologies are employed across various imaging modalities, including X-rays, MRIs, and CT scans, to improve disease detection, image segmentation, and diagnostic support. Furthermore, (...)
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  29. OPTIMIZING CONSUMER BEHAVIOUR ANALYTICS THROUGH ADVANCED MACHINE LEARNING ALGORITHMS.S. Yoheswari - 2024 - Journal of Science Technology and Research (JSTAR) 5 (1):360-368.
    Consumer behavior analytics has become a pivotal aspect for businesses to understand and predict customer preferences and actions. The advent of machine learning (ML) algorithms has revolutionized this field by providing sophisticated tools for data analysis, enabling businesses to make data-driven decisions. However, the effectiveness of these ML algorithms significantly hinges on the optimization techniques employed, which can enhance model accuracy and efficiency. This paper explores the application of various optimization techniques in consumer behaviour analytics using (...)
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  30. (1 other version)On some unwarranted tacit assumptions in cognitive neuroscience.Rainer Mausfeld - 2012 - Frontiers in Cognition 3 (67):1-13.
    The cognitive neurosciences are based on the idea that the level of neurons or neural networks constitutes a privileged level of analysis for the explanation of mental phenomena. This paper brings to mind several arguments to the effect that this presumption is ill-conceived and unwarranted in light of what is currently understood about the physical principles underlying mental achievements. It then scrutinizes the question why such conceptions are nevertheless currently prevailing in many areas of psychology. The paper argues that (...)
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  31.  54
    Векторизація обчислень для оптимізації коду на мові програмування Python.Олексій Земляний & Олег Байбуз - 2024 - Challenges and Issues of Modern Science 3:144-149.
    Purpose. The purpose of this study is to explore vectorization as an engineering technique to improve the performance and readability of Python code, particularly in data processing tasks. We aim to demonstrate the benefits of vectorization through practical examples involving the handling of missing data. Design / Method / Approach. To achieve the research goals, we performed a comparative analysis between loop-based and vectorized implementations. Specifically, two versions of a function were developed to identify columns containing missing (...)
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  32. Predicting Carbon Dioxide Emissions in the Oil and Gas Industry.Yousef Mohammed Meqdad & Samy S. Abu-Naser - 2023 - International Journal of Academic Information Systems Research (IJAISR) 7 (10):34-40.
    Abstract: This study has effectively tackled the critical challenge of accurate calorie prediction in dishes by employing a robust neural network-based model. With an outstanding accuracy rate of 99.32% and a remarkably low average error of 0.009, our model has showcased its proficiency in delivering precise calorie estimations. This achievement equips individuals, healthcare practitioners, and the food industry with a powerful tool to promote healthier dietary choices and elevate awareness of nutrition. Furthermore, our in-depth feature importance analysis has shed (...)
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  33. AI in HRM: Revolutionizing Recruitment, Performance Management, and Employee Engagement.Mostafa El-Ghoul, Mohammed M. Almassri, Mohammed F. El-Habibi, Mohanad H. Al-Qadi, Alaa Abou Eloun, Bassem S. Abu-Nasser & Samy S. Abu-Naser - 2024 - International Journal of Academic Applied Research (Ijaar) 8 (9):16-23.
    Artificial Intelligence (AI) is rapidly transforming Human Resource Management (HRM) by enhancing the efficiency and effectiveness of key functions such as recruitment, performance management, and employee engagement. This paper explores the integration of AI technologies in HRM, focusing on their potential to revolutionize these critical areas. In recruitment, AI-driven tools streamline candidate sourcing, screening, and selection processes, leading to more accurate and unbiased hiring decisions. Performance management is similarly transformed, with AI enabling continuous, data-driven feedback and personalized (...)
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  34. Predicting Life Expectancy in Diverse Countries Using Neural Networks: Insights and Implications.Alaa Mohammed Dawoud & Samy S. Abu-Naser - 2023 - International Journal of Academic Engineering Research (IJAER) 7 (9):45-54.
    Life expectancy prediction, a pivotal facet of public health and policy formulation, has witnessed remarkable advancements owing to the integration of neural network models and comprehensive datasets. In this research, we present an innovative approach to forecasting life expectancy in diverse countries. Leveraging a neural network architecture, our model was trained on a dataset comprising 22 distinct features, acquired from Kaggle, and encompassing key health indicators, socioeconomic metrics, and cultural attributes. The model demonstrated exceptional predictive accuracy, attaining an impressive 99.27% (...)
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  35. On the Compatibility of Connectionism and Cognitive Linguistics.Mark Collier - 1998 - Center for Research in Language 11 (4):3-11.
    Is PDP Connectionism compatible with Cognitive Linguistics? It is unfortunate that this question has not received the attention it deserves, since at stake is the very possibility of a unified "West Coast Cognitive Science" approach to language. Part I of this paper argues that a systematic approach to the question of compatibility must involve an enumeration and analysis of the general principles used by each research program in their linguistic explanations. This approach is carried out in Parts II and (...)
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  36. AI-Enabled Human Capital Management: Tools for Strategic Workforce Adaptation.M. Arulselvan - 2025 - Journal of Science Technology and Research (JSTAR) 5 (1):530-538.
    This paper explores the application of AI-driven HR analytics in shaping workforce agility, focusing on how real-time data collection, analysis, and modeling foster an adaptable workforce. It highlights the role of predictive analytics in forecasting workforce needs, identifying skill gaps, and optimizing talent deployment. Additionally, the paper discusses how AI enhances strategic decision-making by providing precise metrics and insights into employee behavior, productivity, and satisfaction. The integration of AI into HR systems ultimately shifts HR from a traditionally (...)
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  37. The Middle Class: Philosophical, Political, and Historical Perspectives.Philipp W. Rosemann, Joshua S. Parens & José Espericueta (eds.) - 2020 - San José, Costa Rica: Editorial Universidad Costa Rica.
    In the summer of 2016, the University of Dallas and the Instituto Tecnológico Autónomo de México organized a conference to discuss the topic of the middle class and its continued decline—recognizing that, despite some historical, political and cultural differences, healthy democracies throughout the hemisphere depend upon a strong and prosperous middle class. This volume brings together contributions by nine scholars from both institutions. The chapters reflect diverse disciplinary perspectives that are historical, political, economic, anthropological, and philosophical. Despite this diversity, the (...)
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  38.  97
    Preserving our humanity in the growing AI-mediated politics: Unraveling the concepts of Democracy (民主) and People as the Roots of the state (民本).Manh-Tung Ho & My-Van Luong - manuscript
    Artificial intelligence (AI) has transformed the way people engage with politics around the world: how citizens consume news, how they view the institutions and norms, how civic groups mobilize public interests, how data-driven campaigns are shaping elections, and so on (Ho & Vuong, 2024). Placing people at the center of the increasingly AI-mediated political landscape has become an urgent matter that transcends all forms of institutions. In this essay, we argue that, in this era, it is necessary to (...)
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  39. Crime Prediction Using Machine Learning and Deep Learning.S. Venkatesh - 2024 - Journal of Science Technology and Research (JSTAR) 6 (1):1-13.
    Crime prediction has emerged as a critical application of machine learning (ML) and deep learning (DL) techniques, aimed at assisting law enforcement agencies in reducing criminal activities and improving public safety. This project focuses on developing a robust crime prediction system that leverages the power of both ML and DL algorithms to analyze historical crime data and predict potential future incidents. By integrating a combination of classification and clustering techniques, our system identifies crime-prone areas, trends, and patterns. Key parameters (...)
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  40. CareerBot: Advanced AI Mentorship for Students’ Career Aspirations and Planning.P. Selvaprasanth - 2024 - Journal of Science Technology and Research (JSTAR) 5 (1):610-620.
    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. The methodology involves data collection through user inputs, preprocessing of data for analysis, and the creation of a robust system architecture comprising frontend interfaces, backend servers, and database management. The implementation of the application involves a comprehensive technology stack, including Python for AI algorithms, TensorFlow for ML models, React.js for front (...)
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  41.  99
    A Comprehensive Evaluation and Methodology on Enhancing Computational Efficiency through Accelerated Computing.Sankara Reddy Thamma - 2024 - Journal of Science Technology and Research (JSTAR) 5 (1):517-525.
    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, (...)
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  42. Information and Communications Technology in Romania - Comparative Analysis with the EU, Social Impact, Challenges and Opportunities, Future Directions.Nicolae Sfetcu - 2024 - Bucharest, Romania: MultiMedia Publishing.
    The modern global technological landscape is shaped by rapid advances and interconnectivity, leading to a complex ecosystem of innovation, competition and collaboration. Significant developments are being seen in artificial intelligence, telecommunications, biotechnology and energy technologies. Digitalization is redefining industries such as healthcare, transport and finance, while cross-border data flows and 5G infrastructure are accelerating global connectivity. Key players such as the United States, China and Japan are investing heavily in research and development, pushing the capabilities of AI and quantum (...)
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  43. Finding a Basic Interpretive Unit through the Human Visual Perception and Cognition-A Comparison between Filmmakers and Audiences.Lingfei Luan - 2016 - Dissertation,
    The analysis method and paradigm of film have become a controversial topic in the data-driven era. Film, is not only an attractive industry that can achieve filmmakers’ imagination but has become a perfect stimulus to understand human being’s mental activity. The core research in this study is to examine the impact of filmmaking experience and the role of narrative denoters from filmmakers’ construction to audiences’ interpretation. Based on previous studies and integrating cognitive approaches, the thesis re-explores the (...)
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  44.  89
    Optimizing Workforce Agility with AI-Enhanced Human Resource Analytics.M. Sheik Dawood - 2024 - Journal of Science Technology and Research (JSTAR) 5 (1):515-525.
    This paper explores the application of AI-driven HR analytics in shaping workforce agility, focusing on how real-time data collection, analysis, and modeling foster an adaptable workforce. It highlights the role of predictive analytics in forecasting workforce needs, identifying skill gaps, and optimizing talent deployment. Additionally, the paper discusses how AI enhances strategic decision-making by providing precise metrics and insights into employee behavior, productivity, and satisfaction. The integration of AI into HR systems ultimately shifts HR from a traditionally (...)
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  45.  65
    EduCareer: Smart AI-Based Career Guidance and Skill Development for Students.M. Sheik Dawood - 2024 - Journal of Science Technology and Research (JSTAR) 5 (1):630-640.
    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 (...)
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  46.  65
    InspireNext: Enabling Students to Build Careers with AI-Powered Tools and Insights.S. Yogeswari - 2024 - Journal of Science Technology and Research (JSTAR) 5 (1):615-625.
    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 (...)
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  47.  56
    What makes readers love a fiction book?Viet-Phuong La & Minh-Hoang Nguyen - 2024 - Sm3D Portal.
    With the advancement of information technology and publishing systems, the number of authors writing books and the abundance of advice for them have proliferated across the writing community and various forums. However, advice is mostly subjective and based primarily on personal experience. To the best of our knowledge, data-driven, quantitative analyses offering actionable insights remain scarce. Therefore, this study can be considered one of the first attempts to address this question using a quantitative approach. -/- The Amazon book (...)
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  48.  71
    OPTIMIZING CONSUMER BEHAVIOUR ANALYTICS THROUGH ADVANCED MACHINE LEARNING ALGORITHMS.Yoheswari S. - 2024 - Journal of Science Technology and Research (JSTAR) 5 (1):362-370.
    Consumer behavior analytics has become a pivotal aspect for businesses to understand and predict customer preferences and actions. The advent of machine learning (ML) algorithms has revolutionized this field by providing sophisticated tools for data analysis, enabling businesses to make data-driven decisions. However, the effectiveness of these ML algorithms significantly hinges on the optimization techniques employed, which can enhance model accuracy and efficiency. This paper explores the application of various optimization techniques in consumer behaviour analytics using (...)
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  49.  20
    The Role of AGI in Achieving Universal Balance and Overcoming Dogmatic Limitations.Angelito Malicse - manuscript
    The Role of AGI in Achieving Universal Balance and Overcoming Dogmatic Limitations -/- Introduction -/- Human civilization has long been shaped by a complex interplay of natural laws, societal structures, religious beliefs, and scientific progress. While religion has provided moral guidance and a sense of purpose, it has also been a source of dogma—rigid, unquestionable beliefs that resist scrutiny. At the same time, scientific advancements have sought to uncover objective truths, yet they often struggle to address deeper existential questions. -/- (...)
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  50.  20
    The Science of Balanced Leadership and Competition: The Role of AI Technology as a Guide.Angelito Malicse - manuscript
    The Science of Balanced Leadership and Competition: The Role of AI Technology as a Guide -/- Introduction -/- Leadership and competition are two fundamental forces that shape human societies, economies, and institutions. However, their effectiveness depends on how they are managed. When leadership is imbalanced, it leads to corruption, authoritarianism, or inefficiency. When competition is unregulated, it creates inequality, exploitation, and instability. The science of balanced leadership and competition is an approach that integrates principles of natural balance, ethical decision-making, and (...)
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