Results for 'data analysis'

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  1. Transforming Data Analysis through AI-Powered Data Science.Mathan Kumar - 2023 - Proceedings of IEEE 2 (2):1-5.
    AI-powered records science is revolutionizing the way facts are analyzed and understood. It can significantly improve the exceptional of information evaluation and boost its speed. AI-powered facts technological know-how enables access to more extensive, extra complicated information sets, faster insights, faster trouble solving, and higher choice making. Using the use of AI-powered information technological know-how techniques and tools, organizations can provide more accurate outcomes with shorter times to choices. AI-powered facts technology also offers more correct predictions of activities and developments (...)
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  2. Data Analysis, Analytics in Internet of Things and BigData.Mohammad Nezhad Hossein Shourkaei, Damghani Hamidreza, D. Leila & Hosseinian Heliasadat - 2019 - 4th International Conference on Combinatorics, Cryptography, Computer Science and Computation 4.
    The Internet-of-Things (IoT) is gradually being established as the new computing paradigm, which is bound to change the ways of our everyday working and living. IoT emphasizes the interconnection of virtually all types of physical objects (e.g., cell phones, wearables, smart meters, sensors, coffee machines and more) towards enabling them to exchange data and services among themselves, while also interacting with humans as well. Few years following the introduction of the IoT concept, significant hype was generated as a result (...)
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  3. Contents, vehicles, and complex data analysis in neuroscience.Daniel C. Burnston - 2020 - Synthese 199 (1-2):1617-1639.
    The notion of representation in neuroscience has largely been predicated on localizing the components of computational processes that explain cognitive function. On this view, which I call “algorithmic homuncularism,” individual, spatially and temporally distinct parts of the brain serve as vehicles for distinct contents, and the causal relationships between them implement the transformations specified by an algorithm. This view has a widespread influence in philosophy and cognitive neuroscience, and has recently been ably articulated and defended by Shea. Still, I am (...)
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  4. A Multi-wavelength Data Analysis with Multi-mission Space Telescopes.Yang I. Pachankis - 2022 - International Journal of Innovative Science and Research Technology 7 (1):701-708.
    The article summarizes the software tool on astrophysical analysis with multi-wavelength space telescope data. It recaps the evidence analysis conducted on the Kerr-Newman black hole (KNBH). It was written prior to the article Research on the Kerr-Newman Black Hole in M82 Confirms Black Hole and White Hole Juxtapose not soon after the experiment. The conducted analysis suggested Hawking radiation is caused by the movement of ergosurfaces of the BH and serves as the primal evidence for black (...)
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  5. Political communication in Social Networks Election campaigns and digital data analysis: a bibliographic review.Luca Corchia - 2019 - Rivista Trimestrale di Scienza Dell’Amministrazione (2):1-50.
    The outcomes of a bibliographic review on political communication, in particular electoral communication in social networks, are presented here. The electoral campaigning are a crucial test to verify the transformations of the media system and of the forms and uses of the linguistic acts by dominant actors in public sphere – candidates, parties, journalists and Gatekeepers. The aim is to reconstruct the first elements of an analytical model on the transformations of the political public sphere, with which to systematize the (...)
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  6. Jacques Lacan’s Registers of the Psychoanalytic Field, Applied using Geometric Data Analysis to Edgar Allan Poe’s “The Purloined Letter”.Fionn Murtagh & Giuseppe Iurato - manuscript
    In a first investigation, a Lacan-motivated template of the Poe story is fitted to the data. A segmentation of the storyline is used in order to map out the diachrony. Based on this, it will be shown how synchronous aspects, potentially related to Lacanian registers, can be sought. This demonstrates the effectiveness of an approach based on a model template of the storyline narrative. In a second and more Comprehensive investigation, we develop an approach for revealing, that is, uncovering, (...)
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  7. Neutrosophic Association Rule Mining Algorithm for Big Data Analysis.Mohamed Abdel-Basset, Mai Mohamed, Florentin Smarandache & Victor Chang - 2018 - Symmetry 10 (4):1-19.
    Big Data is a large-sized and complex dataset, which cannot be managed using traditional data processing tools. Mining process of big data is the ability to extract valuable information from these large datasets. Association rule mining is a type of data mining process, which is indented to determine interesting associations between items and to establish a set of association rules whose support is greater than a specific threshold. The classical association rules can only be extracted from (...)
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  8. The application of the nominal scale of measurement in research data analysis.Delight Omoji Idika, Valentine Joseph Owan & Victor Ubugha Agama - 2023 - Prestige Journal of Education 6 (1):190-198.
    Appropriate measurement scales are fundamental in data analysis, allowing researchers to categorise, select appropriate statistical methods, and analyse and interpret their data accurately. The nominal scale is one such measurement scale in behavioural sciences, which is crucial in organising data into distinct categories. This paper provides an overview of the nominal measurement scale in research data analysis. It explains the characteristics and role of the nominal scale in organising data into distinct categories. The (...)
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  9. A Review Paper on Scope of Big Data Analysis in Heath Informatics.Kazi Md Shahiduzzaman, Lusekelo Kibona & Hassana Ganame - 2018 - International Journal of Engineering and Information Systems (IJEAIS) 2 (5):1-8.
    Abstract— The term Health Informatics represent a huge volume of data that is collected from different source of health sector. Because of its’ diversity in nature, quite a big number of attributes, numerous amount data, health informatics can be considered as Big Data. Therefore, different techniques used for analyzing Big Data will also fit for Health Informatics. In recent years, implementation of Data Mining on Health Informatics brings a lot of fruitful outcomes that improve the (...)
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  10. Comparative study of manual and computerized software techniques of data management and analysis in educational research.Valentine Joseph Owan & Bassey Asuquo Bassey - 2018 - International Journal of Innovation in Educational Management (IJIEM) 2 (1):35-45.
    The study was conducted to compare manual and computerized software techniques of data management and analysis in educational research. Specifically, the study investigated whether there was a significant difference in the results of Pearson correlation, independent t-test and ANOVA obtained from using manual and computerized software technique of data analyses. Three null hypotheses were formulated accordingly to guide the study. The study adopted a quasi-experimental research design where several data were generated by the researchers and analyzed (...)
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  11. An Analysis of Recent Empirical Data on ‘Ought’ Implies ‘Can’.Yishai Cohen - 2018 - Philosophia 46 (1):57-67.
    Recent experimental studies dispute the position that commonsense morality accepts ‘Ought’ Implies ‘Can’, the view that, necessarily, if an agent ought to perform some action, then she can perform that action. This paper considers and supports explanations for the results of these studies on the hypothesis that OIC is intuitive and true.
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  12. Academic Placement Data and Analysis: 2016 Final Report.Carolyn Dicey Jennings, Patrice Cobb, Bryan Kerster, Chelsea Gordon, Angelo Kyrilov, Evette Montes, Sam Spevack, David W. Vinson & Justin Vlasits - 2016 - APA Grant Funds: Previously Funded Projects.
    Academic Placement Data and Analysis (APDA), a project funded by the American Philosophical Association (APA) and headed by Carolyn Dicey Jennings (UC Merced), aims “to make information on academic job placement useful to prospective graduate students in philosophy.” The project has just been updated to include new data, which Professor Jennings describes in a post at New APPS. She also announces a new interactive data tool with which one can sift through and sort information. (from Daily (...)
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  13. NEUTROSOPHIC THEORY AND SENTIMENT ANALYSIS TECHNIQUE FOR MINING AND RANKING BIG DATA FROM ONLINE EVALUATION.C. Manju Priya - 2022 - Journal of Science Technology and Research (JSTAR) 3 (1):124-142.
    A huge amount of data is being generated everyday through different transactions in industries, social networking, communication systems etc. Big data is a term that represents vast volumes of high speed, complex and variable data that require advanced procedures and technologies to enable the capture, storage, management, and analysis of the data. Big data analysis is the capacity of representing useful information from these large datasets. Due to characteristics like volume, veracity, and velocity, (...)
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  14. The epistemological foundations of data science: a critical analysis.Jules Desai, David Watson, Vincent Wang, Mariarosaria Taddeo & Luciano Floridi - manuscript
    The modern abundance and prominence of data has led to the development of “data science” as a new field of enquiry, along with a body of epistemological reflections upon its foundations, methods, and consequences. This article provides a systematic analysis and critical review of significant open problems and debates in the epistemology of data science. We propose a partition of the epistemology of data science into the following five domains: (i) the constitution of data (...)
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  15. Academic Placement Data and Analysis (APDA) 2021 survey of philosophy Ph.D. students and recent graduates: Demographic data, program ratings, academic job placement, and nonacademic careers.Carolyn Dicey Jennings & Alex Dayer - 2021 - Metaphilosophy 53 (1):100-133.
    Doctoral graduates in philosophy are an excellent source of information about the discipline: they are at the cutting edge of research trends, have an inside view of researchfocused departments, and their employment prospects provide early insights on the future health of the discipline. We report on the results of a survey sent to recent PhD graduates and current students, as well as data gathering efforts by Academic Placement Data and Analysis that have taken place over the past (...)
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  16. Data management practices in Educational Research.Valentine Joseph Owan & Bassey Asuquo Bassey - 2019 - In P. N. Ololube & G. U. Nwiyi (eds.), Encyclopedia of institutional leadership, policy, and management: A handbook of research in honour of Professor Ozo-Mekuri Ndimele. pp. 1251-1265.
    Data is very important in any research experiment because it occupies a central place in making decisions based on findings resulting from the analysis of such data. Given its central role, it follows that such an important asset as data, deserve effective management in order to protect the integrity and provide an opportunity for effective problem-solving. The main thrust of this paper was to examine data management practices that should be adopted by scholars in maintaining (...)
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  17. A Comparative Analysis of Data Mining Techniques on Breast Cancer Diagnosis Data using WEKA Toolbox.Majdah Alshammari & Mohammad Mezher - 2020 - (IJACSA) International Journal of Advanced Computer Science and Applications 8:224-229.
    Abstract—Breast cancer is considered the second most common cancer in women compared to all other cancers. It is fatal in less than half of all cases and is the main cause of mortality in women. It accounts for 16% of all cancer mortalities worldwide. Early diagnosis of breast cancer increases the chance of recovery. Data mining techniques can be utilized in the early diagnosis of breast cancer. In this paper, an academic experimental breast cancer dataset is used to perform (...)
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  18. Exploring age-related patterns in internet access: Insights from a secondary analysis of New Zealand survey data.Edgar Pacheco - 2024 - Media Peripheries 18 (1):38-56.
    About thirty years ago, when the Internet started to be commercialised, access to the medium became a topic of research and debate. Up-to-date evidence about key predictors, such as age, is crucial because of the Internet's ever-changing nature and the challenges associated with gaining access to it. This paper aims to give an overview of New Zealand's Internet access trends and how they relate to age. It is based on secondary analysis of data from a larger online panel (...)
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  19. Macro-Scale Population Patterns in the Kofun Period of the Japanese Archipelago: Quantitative Analysis of a Larger Sample of Three-Dimensional Data from Ancient Human Crania.Hisashi Nakao, Akihiro Kaneda, Kohei Tamura, Koji Noshita & Tomomi Nakagawa - 2024 - Humans 4 (2):131–147.
    The present study collected a larger set of three-dimensional data on human crania from the Kofun period (as well as from previous periods, i.e., the Jomon and Yayoi periods) in the Japanese archipelago (AD 250 to around 700) than previous studies. Three-dimensional geometric morphometrics were employed to investigate human migration patterns in finer-grained phases. These results are consistent with those of previous studies, although some new patterns were discovered. These patterns were interpreted in terms of demic diffusion, archaeological findings, (...)
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  20. 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 risks (...)
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  21. CIDO, a community-based ontology for coronavirus disease knowledge and data integration, sharing, and analysis.Oliver He, John Beverley, Gilbert S. Omenn, Barry Smith, Brian Athey, Luonan Chen, Xiaolin Yang, Junguk Hur, Hsin-hui Huang, Anthony Huffman, Yingtong Liu, Yang Wang, Edison Ong & Hong Yu - 2020 - Scientific Data 181 (7):5.
    Ontologies, as the term is used in informatics, are structured vocabularies comprised of human- and computer-interpretable terms and relations that represent entities and relationships. Within informatics fields, ontologies play an important role in knowledge and data standardization, representation, integra- tion, sharing and analysis. They have also become a foundation of artificial intelligence (AI) research. In what follows, we outline the Coronavirus Infectious Disease Ontology (CIDO), which covers multiple areas in the domain of coronavirus diseases, including etiology, transmission, epidemiology, (...)
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  22. Students' awareness, willingness and utilisation of facebook for research data collection: Multigroup analysis with age and gender as control variables.Valentine Joseph Owan, Moses Eteng Obla, Michael Ekpenyong Asuquo, Mercy Valentine Owan, Godian Patrick Okenjom, Stephen Bepeh Undie, Joseph Ojishe Ogar & Kelechi Victoria Udeh - 2023 - Journal of Pedagogical Research 7 (4):369-399.
    Previous research has extensively analysed teachers' and students' Facebook use for instructional engagement, writing, research dissemination and e-learning. However, Facebook as a data collection mechanism for research has scarcely been the subject of previous studies. The current study addressed these gaps by analysing students' awareness, willingness, and utilisation of Facebook for research data collection [RDC]. This study aimed to predict students’ Facebook use for research data collection based on their awareness and willingness and to determine age and (...)
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  23. Data quality, experimental artifacts, and the reactivity of the psychological subject matter.Uljana Feest - 2022 - European Journal for Philosophy of Science 12 (1):1-25.
    While the term “reactivity” has come to be associated with specific phenomena in the social sciences, having to do with subjects’ awareness of being studied, this paper takes a broader stance on this concept. I argue that reactivity is a ubiquitous feature of the psychological subject matter and that this fact is a precondition of experimental research, while also posing potential problems for the experimenter. The latter are connected to the worry about distorted data and experimental artifacts. But what (...)
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  24. 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. At (...)
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  25. Data Analytics in Higher Education: Key Concerns and Open Questions.Alan Rubel & Kyle M. L. Jones - 2017 - University of St. Thomas Journal of Law and Public Policy 1 (11):25-44.
    “Big Data” and data analytics affect all of us. Data collection, analysis, and use on a large scale is an important and growing part of commerce, governance, communication, law enforcement, security, finance, medicine, and research. And the theme of this symposium, “Individual and Informational Privacy in the Age of Big Data,” is expansive; we could have long and fruitful discussions about practices, laws, and concerns in any of these domains. But a big part of the (...)
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  26. Sentiment analysis on online social network.Vijaya Abhinandan - forthcoming - International Journal of Computer Science, Information Technology, and Security.
    A large amount of data is maintained in every Social networking sites.The total data constantly gathered on these sites make it difficult for methods like use of field agents, clipping services and ad-hoc research to maintain social media data. This paper discusses the previous research on sentiment analysis.
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  27. 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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  28. Consideration on the Flow Velocity in the Experimental Analysis of the Flame Displacement Speed Using DNS Data of Turbulent Premixed Flames with Different Lewis Numbers.Kazuya Tsuboi - 2014 - Open Journal of Fluid Dynamics 4 (3):278-287.
    The flame displacement speed is one of the major characteristics in turbulent premixed flames. The flame displacement speed is experimentally obtained from the displacement normal to the flame surface, while it is numerically evaluated by the transport equation of the flame surface. The flame displacement speeds obtained both experimentally and numerically cannot be compared directly because their definitions are different. In this study, two kinds of experimental flame displacement speeds—involving the mean inflow velocity and the local flow velocity—were simulated using (...)
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  29. Data Mining the Brain to Decode the Mind.Daniel Weiskopf - 2020 - In Fabrizio Calzavarini & Marco Viola (eds.), Neural Mechanisms: New Challenges in the Philosophy of Neuroscience. Springer.
    In recent years, neuroscience has begun to transform itself into a “big data” enterprise with the importation of computational and statistical techniques from machine learning and informatics. In addition to their translational applications such as brain-computer interfaces and early diagnosis of neuropathology, these tools promise to advance new solutions to longstanding theoretical quandaries. Here I critically assess whether these promises will pay off, focusing on the application of multivariate pattern analysis (MVPA) to the problem of reverse inference. I (...)
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  30. Research Data Preservation Practices of Library and Information Science Faculties.A. Subaveerapandiyan & Anuradha Maurya - 2022 - Defence Journal of Library and Information Science Technology 42 (4):259-264.
    Digitisation of research data is widely increasing all around the world because it needs more and development of enormous digital technologies. Data curation services are starting to offer many libraries. Research data curation is the collective invaluable and reusable information of the researchers. Collected data preservation is more important. The majority of the higher education institutes preserved the research data for their students and researchers. It is stored for a long time using various formats. It (...)
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  31. Implementation of Data Mining on a Secure Cloud Computing over a Web API using Supervised Machine Learning Algorithm.Tosin Ige - 2022 - International Journal of Advanced Computer Science and Applications 13 (5):1 - 4.
    Ever since the era of internet had ushered in cloud computing, there had been increase in the demand for the unlimited data available through cloud computing for data analysis, pattern recognition and technology advancement. With this also bring the problem of scalability, efficiency and security threat. This research paper focuses on how data can be dynamically mine in real time for pattern detection in a secure cloud computing environment using combination of decision tree algorithm and Random (...)
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  32. Research participants’ perceptions and views on consent for biobank research: a review of empirical data and ethical analysis.Flavio D’Abramo, Jan Schildmann & Jochen Vollmann - 2015 - BMC Medical Ethics 16 (1):60.
    Appropriate information and consent has been one of the most intensely discussed topics within the context of biobank research. In parallel to the normative debate, many socio-empirical studies have been conducted to gather experiences, preferences and views of patients, healthy research participants and further stakeholders. However, there is scarcity of literature which connects the normative debate about justifications for different consent models with findings gained in empirical research. In this paper we discuss findings of a limited review of socio-empirical research (...)
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  33. Comparative views on research productivity differences between major social science fields in Vietnam: Structured data and Bayesian analysis, 2008-2018.Quan-Hoang Vuong, La Viet Phuong, Vuong Thu Trang, Ho Manh Tung, Nguyen Minh Hoang & Manh-Toan Ho - manuscript
    Since Circular 34 from the Ministry of Science and Technology of Vietnam required the head of the national project to have project results published in ISI/Scopus journals in 2014, the field of economics has been dominating the number of nationally-funded projects in social sciences and humanities. However, there has been no scientometric study that focuses on the difference in productivity among fields in Vietnam. Thus, harnessing the power of the SSHPA database, a comprehensive dataset of 1,564 Vietnamese authors (854 males, (...)
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  34. Attitudes Toward Mandatory COVID-19 Vaccination in Germany A representative analysis of data from the socio-economic panel for the year 2021.Christoph Schmidt-Petri, Carsten Schröder & Thomas Rieger - 2022 - Deutsches Ärzteblatt International 119:335-41.
    Background: Adequate immunity to COVID-19 apparently cannot be attained in Germany by voluntary vaccination alone, and therefore the introduction of mandatory COVID-19 vaccination is still under consideration. We present findings on the potential acceptance of such a requirement by the German population, and we report on the reasons given for accepting or rejecting it and how these reasons vary according to population subgroup. -/- Methods: We used representative data from the Socio-Economic Panel for the period January to December 2021. (...)
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  35. Asking about data: exploring different realities of data via the social data flow network methodology.Brian Ballsun-Stanton - unknown
    What is data? That question is the fundamental investigation of this dissertation. I have developed a methodology from social-scientific processes to explore how different people understand the concept of data, rather than to rely on my own philosophical intuitions or thought experiments about the “nature” of data. The evidence I have gathered as to different individuals' constructions of data can be used to inform further inquiry of data and the design of information systems. My research (...)
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  36. An Exploratory Analysis of the Development of Philippine Regions.Starr Clyde Sebial - 2019 - International Journal of Innovation, Creativity and Change 8 (2):129-145.
    The Philippines is one of the fast-growing economies in the South-East Asian and the Pacific region. This study considered eight factors: HEI PRC rate, crime rate, education, employment, health, poverty, income, and basic family amenities of the 17 regions of the country, all taken from the year 2012 databases of the Philippine Statistics Authority (PSA), the Philippine Institute for Development Studies (PIDS) and Open Data Philippines. Principal Component Analysis (PCA) generated the indices of the six factors and Cluster (...)
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  37. Data management practices and educational research effectiveness of university lecturers in South-South Nigeria.Valentine Joseph Owan, Francisca Nonyelum Odigwe & Bassey Asuquo Bassey - 2020 - Journal of Educational and Social Research 10 (3):24-34.
    The existing body of knowledge has witnessed gaps arising from the paucity of research literature on the quality of educational research output in higher education. This study shows how the management of data in higher education affects the quality of academic research conducted by university lecturers in South-South Nigeria. A sample of 602 lecturers were accessed during data collection and responded to two questionnaires (Data Management Practices Questionnaire – DMPQ and "Educational Research Effectiveness Questionnaire – EREQ). Multiple (...)
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  38. Are generics and negativity about social groups common on social media? A comparative analysis of Twitter (X) data.Uwe Peters & Ignacio Ojea Quintana - 2024 - Synthese 203 (6):1-22.
    Many philosophers hold that generics (i.e., unquantified generalizations) are pervasive in communication and that when they are about social groups, this may offend and polarize people because generics gloss over variations between individuals. Generics about social groups might be particularly common on Twitter (X). This remains unexplored, however. Using machine learning (ML) techniques, we therefore developed an automatic classifier for social generics, applied it to 1.1 million tweets about people, and analyzed the tweets. While it is often suggested that generics (...)
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  39. 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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  40. Bayesian analysis in social sciences.Minh-Hoang Nguyen - 2021 - Scholarly Community Encyclopedia.
    Given the reproducibility crisis (or replication crisis), more psychologists and social-cultural scientists are getting involved with Bayesian inference. Therefore, the current article provides a brief overview of programs (or software) and steps to conduct Bayesian data analysis in social sciences.
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  41. Open Data for Crime and Place Research: A Practical Guide in R.Samuel Langton & Reka Solymosi - 2020 - Leeds, UK: University of Leeds.
    Access to data in crime and place research has traditionally been reserved for those who have the means to collect fresh data themselves, pay for access, or obtain data through formal data sharing agreements. Even when access is granted, the usage of these data often comes with conditions that circumscribe how the data can be used through licensing or policy (Kitchin, 2014). Even the public dissemination of findings which emerge from analysis might be (...)
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  42. Big Data technology.Nicolae Sfetcu - manuscript
    Big Data must be processed with advanced collection and analysis tools, based on predetermined algorithms, in order to obtain relevant information. Algorithms must also take into account invisible aspects for direct perceptions. Big Data issues is multi-layered. A distributed parallel architecture distributes data on multiple servers (parallel execution environments) thus dramatically improving data processing speeds. Big Data provides an infrastructure that allows for highlighting uncertainties, performance, and availability of components. DOI: 10.13140/RG.2.2.12784.00004 .
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  43. Enabling posthumous medical data donation: a plea for the ethical utilisation of personal health data.Luciano Floridi, Mariarosaria Taddeo & Jenny Krutzinna - 2019 - In Peter Dabrock, Matthias Braun & Patrik Hummel (eds.), The Ethics of Medical Data Donation. Springer Verlag.
    This article argues that personal medical data should be made available for scientific research, by enabling and encouraging individuals to donate their medical records once deceased, in a way similar to how they can already donate organs or bodies. This research is part of a project on posthumous medical data donation developed by the Digital Ethics Lab at the Oxford Internet Institute. Ten arguments are provided to support the need to foster posthumous medical data donation. Two major (...)
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  44. Classificatory Theory in Data-intensive Science: The Case of Open Biomedical Ontologies.Sabina Leonelli - 2012 - International Studies in the Philosophy of Science 26 (1):47 - 65.
    Knowledge-making practices in biology are being strongly affected by the availability of data on an unprecedented scale, the insistence on systemic approaches and growing reliance on bioinformatics and digital infrastructures. What role does theory play within data-intensive science, and what does that tell us about scientific theories in general? To answer these questions, I focus on Open Biomedical Ontologies, digital classification tools that have become crucial to sharing results across research contexts in the biological and biomedical sciences, and (...)
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  45.  80
    Reconciling Data Actionability and Accountability in Global Health Research.Nathanael Sheehan & Sabina Leonelli - manuscript
    All too often, the requirements for actionability and accountability of data infrastructures are conceptualised as incompatible and leading to a trade-off situation where increasing one will unavoidably decrease the other. Through a comparative analysis of two data infrastructures used to share genomic data about the SARS-COV-2 virus, we argue that making data actionable for knowledge development involves a commitment to ensuring that the data in question are representative of the phenomena being studied and accountable (...)
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  46. Enabling posthumous medical data donation: an appeal for the ethical utilisation of personal health data.Jenny Krutzinna, Mariarosaria Taddeo & Luciano Floridi - 2019 - Science and Engineering Ethics 25 (5):1357-1387.
    This article argues that personal medical data should be made available for scientific research, by enabling and encouraging individuals to donate their medical records once deceased, similar to the way in which they can already donate organs or bodies. This research is part of a project on posthumous medical data donation developed by the Digital Ethics Lab at the Oxford Internet Institute at the University of Oxford. Ten arguments are provided to support the need to foster posthumous medical (...)
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  47. 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 new (...)
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  48. From data to semantic information.Luciano Floridi - 2003 - Entropy 5:125–145.
    There is no consensus yet on the definition of semantic information. This paper contributes to the current debate by criticising and revising the Standard Definition of semantic Information as meaningful data, in favour of the Dretske-Grice approach: meaningful and well-formed data constitute semantic information only if they also qualify as contingently truthful. After a brief introduction, SDI is criticised for providing necessary but insufficient conditions for the definition of semantic information. SDI is incorrect because truth-values do not supervene (...)
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  49. A Framework Proposal for Developing Historical Video Games Based on Player Review Data Mining to Support Historic Preservation.Sarvin Eshaghi, Sepehr Vaez Afshar & Mahyar Hadighi - 2023 - In Saif Haq, Adil Sharag-Eldin & Sepideh Niknia (eds.), ARCC 2023 CONFERENCE PROCEEDING: The Research Design Interface. Architectural Research Centers Consortium, Inc.. pp. 297-305.
    Historic preservation, which is a vital act for conveying people’s understanding of the past, such as events, ideas, and places to the future, allows people to preserve history for future generations. Additionally, since the historic properties are currently concentrated in urban areas, an urban-oriented approach will contribute to the issue. Hence, public awareness is a key factor that paves the way for this conservation. Public history, a history with a public audience and special methods of representation, can serve society in (...)
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  50. Data management practices and educational research effectiveness of university lecturers in South-South Nigeria.Valentine Joseph Owan & Francisca N. Odigwe - 2019 - In Charles A. Shoniregun (ed.), Proceedings of the London International Conference on Education (LICE-2019). pp. 86-94.
    The dishonest practices in the conduct of educational research in South-South region particularly, and Nigeria generally, has called for urgent intervention. This study assessed data management practices and educational research effectiveness of University Lecturers in South-South Nigeria. A sample of 602 lecturers that were accessible during data collection responded to two questionnaires (Data Management Practices Questionnaire – DMPQ and "Educational Research Effectiveness Questionnaire – EREQ). Multiple regression was employed in the analysis of data. Findings revealed (...)
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