Results for 'Data Dispersion'

943 found
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  1.  60
    Cloud-Based Secure Storage: A Framework for Efficient Encryption, Decryption, and Data Dispersion.M. Arul Selvan - 2024 - Journal of Science Technology and Research (JSTAR) 5 (1):427-434.
    The exponential growth of cloud storage has necessitated advanced security measures to protect sensitive data from unauthorized access. Traditional encryption methods provide a layer of security, but they often lack the robustness needed to address emerging threats. This paper introduces an optimized framework for secure cloud storage that integrates data encryption, decryption, and dispersion using cutting-edge optimization techniques. The proposed model enhances data security by first encrypting the data, then dispersing it across multiple cloud servers, (...)
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  2.  42
    OPTIMIZED CLOUD SECURE STORAGE: A FRAMEWORK FOR DATA ENCRYPTION, DECRYPTION, AND DISPERSION.S. Yoheswari - 2024 - Journal of Science Technology and Research (JSTAR) 5 (1):415-426.
    The exponential growth of cloud storage has necessitated advanced security measures to protect sensitive data from unauthorized access. Traditional encryption methods provide a layer of security, but they often lack the robustness needed to address emerging threats. This paper introduces an optimized framework for secure cloud storage that integrates data encryption, decryption, and dispersion using cutting-edge optimization techniques. The proposed model enhances data security by first encrypting the data, then dispersing it across multiple cloud servers, (...)
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  3.  50
    Enhanced Secure Cloud Storage: An Integrated Framework for Data Encryption and Distribution.M. Arulselvan - 2024 - Journal of Science Technology and Research (JSTAR) 5 (1):416-427.
    Traditional encryption methods provide a layer of security, but they often lack the robustness needed to address emerging threats. This paper introduces an optimized framework for secure cloud storage that integrates data encryption, decryption, and dispersion using cutting-edge optimization techniques. The proposed model enhances data security by first encrypting the data, then dispersing it across multiple cloud servers, ensuring that no single server holds the complete dataset. Decryption occurs only when the dispersed data fragments are (...)
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  4. Generalized plithogenic whole hypersoft set, PFHSS-Matrix, operators and applications as COVID-19 data structures.Shazia Rana, Muhammad Saeed, Madiha Qayyum & Florentin Smarandache - 2023 - Journal of Intelligent and Fuzzy Systems 44.
    This article is a preliminary draft for initiating and commencing a new pioneer dimension of expression. To deal with higher-dimensional data or information flowing in this modern era of information technology and artificial intelligence, some innovative super algebraic structures are essential to be formulated. In this paper, we have introduced such matrices that have multiple layers and clusters of layers to portray multi-dimensional data or massively dispersed information of the plithogenic universe made up of numerous subjects their attributes, (...)
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  5. 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 paper discusses (...)
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  6. Undersampling Aware Learning based Fetal Health Prediction using Cardiotocographic Data.M. Shyamala Devi - 2021 - Turkish Online Journal of Qualitative Inquiry (TOJQI) 12 (6):7730-7749.
    With the current improvement of development towards pharmaceutical, distinctive ultrasound methodologies are open to find the fetal prosperity. It is analyzed with diverse clinical parameters with 2-D imaging and other test. In any case, prosperity desire of fetal heart still remains an open issue due to unconstrained works out of the hatchling, the minor heart appraise and inadequate of data in fetal echocardiography. The machine learning strategies can find out the classes of fetal heart rate which can beutilized for (...)
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  7. Learning Organizations and Their Role in Achieving Organizational Excellence in the Palestinian Universities.Mazen J. Al Shobaki, Samy S. Abu Naser, Youssef M. Abu Amuna & Amal A. Al Hila - 2017 - International Journal of Digital Publication Technology 1 (2):40-85.
    The research aims to identify the learning organizations and their role in achieving organizational excellence in the Palestinian universities in Gaza Strip. The researchers used descriptive analytical approach and used the questionnaire as a tool for information gathering. The questionnaires were distributed to senior management in the Palestinian universities. The study population reached (344) employees in senior management is dispersed over (3) Palestinian universities. A stratified random sample of (182) workers from the Palestinian universities was selected and the recovery rate (...)
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  8. Trends of Palestinian Higher Educational Institutions in Gaza Strip as Learning Organizations.Samy S. Abu Naser, Mazen J. Al Shobaki, Youssef M. Abu Amuna & Amal A. Al Hila - 2017 - International Journal of Digital Publication Technology 1 (1):1-42.
    The research aims to identify the trends of Palestinian higher educational institutions in Gaza Strip as learning organizations from the perspective of senior management in the Palestinian universities in Gaza Strip. The researchers used descriptive analytical approach and used the questionnaire as a tool for information gathering. The questionnaires were distributed to senior management in the Palestinian universities. The study population reached (344) employees in senior management is dispersed over (3) Palestinian universities. A stratified random sample of (182) employees from (...)
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  9. Archaeological Facts in Transit: The ‘Eminent Mounds’ of Central North America.Alison Wylie - 2010 - In Peter Howlett & Mary S. Morgan (eds.), How well do facts travel?: the dissemination of reliable knowledge. New York: Cambridge University Press. pp. 301-322.
    Archaeological facts have a perplexing character; they are often seen as less likely to “lie,” capable of bearing tangible, material witness to actual conditions of life, actions and events, but at the same time they are notoriously fragmentary and enigmatic, and disturbingly vulnerable to dispersal and attrition. As Trouillot (1995) argues for historical inquiry, the identification, selection, interpretation and narration of archaeological facts is a radically constructive process. Rather than conclude on this basis that archaeological facts and fictions are indistinguishable, (...)
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  10. Kapitał społeczny ludzi starych na przykładzie mieszkańców miasta Białystok.Andrzej Klimczuk - 2012 - Wiedza I Edukacja.
    "Kapitał społeczny ludzi starych na przykładzie mieszkańców miasta Białystok" to książka oparta na analizach teoretycznych i empirycznych, która przedstawia problem diagnozowania i używania kapitału społecznego ludzi starych w procesach rozwoju lokalnego i regionalnego. Kwestia ta jest istotna ze względu na zagrożenia i wyzwania związane z procesem szybkiego starzenia się społeczeństwa polskiego na początku XXI wieku. Opracowanie stanowi próbę sformułowania odpowiedzi na pytania: jaki jest stan kapitału społecznego ludzi starych mieszkających w Białymstoku, jakim ulega przemianom i jakie jest jego zróżnicowanie? Ludzie (...)
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  11. Creative Thinking and Problem-Solving: Can Preservice Teachers Think Creatively and Solve Statistics Problems?Leslie B. Bacangallo, Roshell T. Buella, Kristine Y. Rentasan, Jupeth Pentang & Ronalyn Bautista - 2022 - Studies in Technology and Education 1 (1):14-27.
    Math prospective teachers must be able to think creatively and solve problems. The study looked into preservice teachers’ creative thinking and problem-solving abilities in statistics. The investigation was guided by a correlational design in a public university in the Philippines. Stratified random sampling was used to select the 103 study participants from two teacher education programs. Through google forms, data were collected using Torrance et al. (2008)’s tests of creative thinking and researcher-made statistics problem test. The findings revealed that (...)
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  12. In the Net of Abductions: on Juliette Peirce’s Identity.Vitaly Kiryushchenko - 2010 - Russian Journal of Communication 3 (1-2):123-146.
    In spite of all the industrious efforts Peirce scholars have made so far, Peirce’s biography still retains a number of gaps, among which the problem of identity of Peirce’s second wife, Juliette Froissy, stands out most significantly. It is all the more important that, as some scholars suggest, the discovery of any reliable facts about Juliette could provide an explanation to some of the decisions Peirce had made, which irrevocably changed the course of his life, as well as his semiotic (...)
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  13. DIGITIZED EDUCATION AS TEACHING MODALITIES AS RELATED TO TEACHERS’ PERFORMANCE IN PRIVATE AND PUBLIC SCHOOLS IN PILA, LAGUNA.Angela Marie T. Martinez - 2022 - International Journal of Research Publications 107 (1):74-91.
    The objective of this study was to determine the teachers? performance in Digitized Education in Private and Public Schools in Pila, Laguna and their performance at school through different teaching modalities. It sought to answer three basic questions. What is the extent of the digitized education using different modalities as to Online teaching and learning, Modular Teaching/ Learning, Flexible and Blended Teaching and Learning?; What is the level of teachers? performance in terms of IPCRF Individual Performance Commitment Review Form) and (...)
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  14. Overhead Cross Section Sampling Machine Learning based Cervical Cancer Risk Factors Prediction.A. Peter Soosai Anandaraj, - 2021 - Turkish Online Journal of Qualitative Inquiry (TOJQI) 12 (6): 7697-7715.
    Most forms of human papillomavirus can create alterations on a woman's cervix that can lead to cervical cancer in the long run, while others can produce genital or epidermal tumors. Cervical cancer is a leading cause of morbidity and mortality among women in low- and middle-income countries. The prediction of cervical cancer still remains an open challenge as there are several risk factors affecting the cervix of the women. By considering the above, the cervical cancer risk factor dataset from KAGGLE (...)
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  15. Data is the new gold, but efficiently mining it requires a philosophy of data.Data Thinkerr - 2023 - Data Thinking.
    Fixing the problem won’t be easy, but humans’ sharpened focus on an emerging philosophy of data might give us some clue about where we will be heading for.
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  16. The 1 law of "absolute reality"." ~, , Data", , ", , Value", , = O. &Gt, Being", & Human - manuscript
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  17. (1 other version)Open data, open review and open dialogue in making social sciences plausible.Quan-Hoang Vuong - 2017 - Nature: Scientific Data Updates 2017.
    Nowadays, protecting trust in social sciences also means engaging in open community dialogue, which helps to safeguard robustness and improve efficiency of research methods. The combination of open data, open review and open dialogue may sound simple but implementation in the real world will not be straightforward. However, in view of Begley and Ellis’s (2012) statement that, “the scientific process demands the highest standards of quality, ethics and rigour,” they are worth implementing. More importantly, they are feasible to work (...)
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  18. Big Data, epistemology and causality: Knowledge in and knowledge out in EXPOsOMICS.Stefano Canali - 2016 - Big Data and Society 3 (2).
    Recently, it has been argued that the use of Big Data transforms the sciences, making data-driven research possible and studying causality redundant. In this paper, I focus on the claim on causal knowledge by examining the Big Data project EXPOsOMICS, whose research is funded by the European Commission and considered capable of improving our understanding of the relation between exposure and disease. While EXPOsOMICS may seem the perfect exemplification of the data-driven view, I show how causal (...)
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  19. 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 to (...)
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  20. Brain Data in Context: Are New Rights the Way to Mental and Brain Privacy?Daniel Susser & Laura Y. Cabrera - 2023 - American Journal of Bioethics Neuroscience 15 (2):122-133.
    The potential to collect brain data more directly, with higher resolution, and in greater amounts has heightened worries about mental and brain privacy. In order to manage the risks to individuals posed by these privacy challenges, some have suggested codifying new privacy rights, including a right to “mental privacy.” In this paper, we consider these arguments and conclude that while neurotechnologies do raise significant privacy concerns, such concerns are—at least for now—no different from those raised by other well-understood (...) collection technologies, such as gene sequencing tools and online surveillance. To better understand the privacy stakes of brain data, we suggest the use of a conceptual framework from information ethics, Helen Nissenbaum’s “contextual integrity” theory. To illustrate the importance of context, we examine neurotechnologies and the information flows they produce in three familiar contexts—healthcare and medical research, criminal justice, and consumer marketing. We argue that by emphasizing what is distinct about brain privacy issues, rather than what they share with other data privacy concerns, risks weakening broader efforts to enact more robust privacy law and policy. (shrink)
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  21. Big Data and Changing Concepts of the Human.Carrie Figdor - 2019 - European Review 27 (3):328-340.
    Big Data has the potential to enable unprecedentedly rigorous quantitative modeling of complex human social relationships and social structures. When such models are extended to nonhuman domains, they can undermine anthropocentric assumptions about the extent to which these relationships and structures are specifically human. Discoveries of relevant commonalities with nonhumans may not make us less human, but they promise to challenge fundamental views of what it is to be human.
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  22. 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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  23. What is data ethics?Luciano Floridi & Mariarosaria Taddeo - 2016 - Philosophical Transactions of the Royal Society A 374 (2083):20160360.
    This theme issue has the founding ambition of landscaping Data Ethics as a new branch of ethics that studies and evaluates moral problems related to data (including generation, recording, curation, processing, dissemination, sharing, and use), algorithms (including AI, artificial agents, machine learning, and robots), and corresponding practices (including responsible innovation, programming, hacking, and professional codes), in order to formulate and support morally good solutions (e.g. right conducts or right values). Data Ethics builds on the foundation provided by (...)
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  24. Big data and their epistemological challenge.Luciano Floridi - 2012 - Philosophy and Technology 25 (4):435-437.
    Between 2006 and 2011, humanity accumulated 1,600 EB of data. As a result of this growth, there is now more data produced than available storage. This article explores the problem of “Big Data,” arguing for an epistemological approach as a possible solution to this ever-increasing challenge.
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  25. Dispersing the Responsibility for Crime.Clayton Morgareidge - unknown
    Althusser contrasts the Repressive State Apparatus (or RSA) with the Ideological State Apparatus (or ISA). His favored example of the ISA is the school, because it trains citizens in the virtues of work and patriotism as well as inculcating, by precept and discipline, the necessary attitudes and skills for fulfilling the roles assigned to them by their social class in the capitalist..
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  26. Data models, representation and adequacy-for-purpose.Alisa Bokulich & Wendy Parker - 2021 - European Journal for Philosophy of Science 11 (1):1-26.
    We critically engage two traditional views of scientific data and outline a novel philosophical view that we call the pragmatic-representational view of data. On the PR view, data are representations that are the product of a process of inquiry, and they should be evaluated in terms of their adequacy or fitness for particular purposes. Some important implications of the PR view for data assessment, related to misrepresentation, context-sensitivity, and complementary use, are highlighted. The PR view provides (...)
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  27.  92
    AI training data, model success likelihood, and informational entropy-based value.Quan-Hoang Vuong, Viet-Phuong La & Minh-Hoang Nguyen - manuscript
    Since the release of OpenAI's ChatGPT, the world has entered a race to develop more capable and powerful AI, including artificial general intelligence (AGI). The development is constrained by the dependency of AI on the model, quality, and quantity of training data, making the AI training process highly costly in terms of resources and environmental consequences. Thus, improving the effectiveness and efficiency of the AI training process is essential, especially when the Earth is approaching the climate tipping points and (...)
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  28.  58
    Efficient Data Center Management: Advanced SLA-Driven Load Balancing Solutions.M. Arul Selvan - 2024 - Journal of Science Technology and Research (JSTAR) 5 (1):368-376.
    In modern data centers, managing the distribution of workloads efficiently is crucial for ensuring optimal performance and meeting Service Level Agreements (SLAs). Load balancing algorithms play a vital role in this process by distributing workloads across computing resources to avoid overloading any single resource. However, the effectiveness of these algorithms can be significantly enhanced through the integration of advanced optimization techniques. This paper proposes an SLA-driven load balancing algorithm optimized using methods such as genetic algorithms, particle swarm optimization, and (...)
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  29.  42
    Optimizing Data Center Operations with Enhanced SLA-Driven Load Balancing".S. Yoheswari - 2024 - Journal of Science Technology and Research (JSTAR) 5 (1):368-376.
    The research introduces a novel framework that incorporates real-time monitoring, dynamic resource allocation, and adaptive threshold settings to ensure consistent SLA adherence while optimizing computing performance. Extensive simulations are conducted using synthetic and real-world datasets to evaluate the performance of the proposed algorithm. The results demonstrate that the optimized load balancing approach outperforms traditional algorithms in terms of SLA compliance, resource utilization, and energy efficiency. The findings suggest that the integration of optimization techniques into load balancing algorithms can significantly enhance (...)
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  30.  44
    Big Data Ethics in Education and Research.Nicolae Sfetcu - 2023 - It and C 2 (3):26-35.
    Big data ethics involves adherence to the concepts of right and wrong behavior regarding data, especially personal data. Big Data ethics focuses on structured or unstructured data collectors and disseminators. Big data ethics is supported, at EU level, by extensive documentation, which seeks to find concrete solutions to maximize the value of big data without sacrificing fundamental human rights. The European Data Protection Supervisor (EDPS) supports the right to privacy and the right (...)
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  31.  42
    New paper about data publishing in DSI.Admin Portal - 2024 - Sm3D Portal.
    This post is to inform you about the publishing of an online-first version of our article titled “Critical remarks on current practices of data article publishing: issues, challenges, and recommendations”. The manuscript has gone through approximately 18 months of preparation and peer review to appear in the journal Data Science and Informetrics (DSI), finally.
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  32. Data Mining in the Context of Legality, Privacy, and Ethics.Amos Okomayin, Tosin Ige & Abosede Kolade - 2023 - International Journal of Research and Innovation in Applied Science 10 (Vll):10-15.
    Data mining possess a significant threat to ethics, privacy, and legality, especially when we consider the fact that data mining makes it difficult for an individual or consumer (in the case of a company) to control accessibility and usage of his data. Individuals should be able to control how his/ her data in the data warehouse is being access and utilize while at the same time providing enabling environment which enforces legality, privacy and ethicality on (...)
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  33.  86
    Data Synthesis for Big Questions: From Animal Tracks to Ecological Models.Rose Trappes - 2024 - Philosophy, Theory, and Practice in Biology 16 (1):4.
    This paper addresses a relatively new mode of ecological research: data synthesis studies. Data synthesis studies involve reusing data to create a general model as well as a reusable, aggregated dataset. Using a case from movement ecology, I analyse the trade-offs and strategies involved in data synthesis. Like theoretical ecological modelling, I find that synthesis studies involve a modelling trade-off between generality, precision and realism; they deal with this trade-off by adopting a pragmatic kludging strategy. I (...)
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  34. Data subject rights as a research methodology: A systematic literature review.Adamu Adamu Habu & Tristan Henderson - 2023 - Journal of Responsible Technology 16 (C):100070.
    Data subject rights provide data controllers with obligations that can help with transparency, giving data subjects some control over their personal data. To date, a growing number of researchers have used these data subject rights as a methodology for data collection in research studies. No one, however, has gathered and analysed different academic research studies that use data subject rights as a methodology for data collection. To this end, we conducted a systematic (...)
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  35. Environmental Impact of Sustainability Dispersion of Chlorine Releases in Coastal Zone of Alexandra: Spatial-Ecological Modeling.Mohammed El Raey & Moustafa Osman Mohammed - 2024 - International Journal of Environmental and Ecological Engineering 18 (1):21-28.
    The spatial-ecological modeling is relating sustainable dispersions with social development. Sustainability with spatial-ecological model gives attention to urban environments in the design review management to comply with Earth’s system. Naturally exchanged patterns of ecosystems have consistent and periodic cycles to preserve energy flows and materials in Earth’s system. The Probabilistic Risk Assessment (PRA) technique is utilized to assess the safety of an industrial complex. The other analytical approach is the Failure-Safe Mode and Effect Analysis (FMEA) for critical components. The plant (...)
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  36. Big Data Analytics in Healthcare: Exploring the Role of Machine Learning in Predicting Patient Outcomes and Improving Healthcare Delivery.Federico Del Giorgio Solfa & Fernando Rogelio Simonato - 2023 - International Journal of Computations Information and Manufacturing (Ijcim) 3 (1):1-9.
    Healthcare professionals decide wisely about personalized medicine, treatment plans, and resource allocation by utilizing big data analytics and machine learning. To guarantee that algorithmic recommendations are impartial and fair, however, ethical issues relating to prejudice and data privacy must be taken into account. Big data analytics and machine learning have a great potential to disrupt healthcare, and as these technologies continue to evolve, new opportunities to reform healthcare and enhance patient outcomes may arise. In order to investigate (...)
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  37. Data Science and Mass Media: Seeking a Hermeneutic Ethics of Information.Christine James - 2015 - Proceedings of the Society for Phenomenology and Media, Vol. 15, 2014, Pages 49-58 15 (2014):49-58.
    In recent years, the growing academic field called “Data Science” has made many promises. On closer inspection, relatively few of these promises have come to fruition. A critique of Data Science from the phenomenological tradition can take many forms. This paper addresses the promise of “participation” in Data Science, taking inspiration from Paul Majkut’s 2000 work in Glimpse, “Empathy’s Impostor: Interactivity and Intersubjectivity,” and some insights from Heidegger’s "The Question Concerning Technology." The description of Data Science (...)
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  38.  96
    ADVANCE DATA SECURITY IN CLOUD NETWORK SYSTEMS.Tummalachervu Chaitanya Kanth - 2023 - Journal of Science Technology and Research (JSTAR) 4 (1):29-36.
    This research presents a novel and efficient public key cryptosystem known as the Enhanced Schmidt Samoa (ESS) cryptosystem, proposed to safeguard the data of a single owner in cloud computing environments. Data storage is a one-time process in the cloud, while data retrieval is a frequent operation. Experimental results demonstrate that the ESS cryptosystem offers robust data confidentiality in the cloud, surpassing the security provided by traditional cryptosystems. The research also introduces a secure cloud framework designed (...)
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  39. 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 audience (...)
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  40. Big Data and reality.Ryan Shaw - 2015 - Big Data and Society 2 (2).
    DNA sequencers, Twitter, MRIs, Facebook, particle accelerators, Google Books, radio telescopes, Tumblr: what do these things have in common? According to the evangelists of “data science,” all of these are instruments for observing reality at unprecedentedly large scales and fine granularities. This perspective ignores the social reality of these very different technological systems, ignoring how they are made, how they work, and what they mean in favor of an exclusive focus on what they generate: Big Data. But no (...)
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  41. Data, Privacy, and the Individual.Carissa Véliz - 2020 - Center for the Governance of Change.
    The first few years of the 21st century were characterised by a progressive loss of privacy. Two phenomena converged to give rise to the data economy: the realisation that data trails from users interacting with technology could be used to develop personalised advertising, and a concern for security that led authorities to use such personal data for the purposes of intelligence and policing. In contrast to the early days of the data economy and internet surveillance, the (...)
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  42. Sense-data and the philosophy of mind: Russell, James, and Mach.Gary Hatfield - 2002 - Principia 6 (2):203-230.
    The theory of knowledge in early twentieth-century Anglo American philosophy was oriented toward phenomenally described cognition. There was a healthy respect for the mind-body problem, which meant that phenomena in both the mental and physical domains were taken seriously. Bertrand Russell's developing position on sense-data and momentary particulars drew upon, and ultimately became like, the neutral monism of Ernst Mach and William James. Due to a more recent behaviorist and physicalist inspired "fear of the mental", this development has been (...)
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  43. Is semantic information meaningful data?Luciano Floridi - 2007 - Philosophy and Phenomenological Research 70 (2):351-370.
    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 (SDI) 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 (...)
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  44. 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 the (...)
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  45. Data and the Good?Daniel Susser - 2022 - Surveillance and Society 20 (3):297-301.
    Surveillance studies scholars and privacy scholars have each developed sophisticated, important critiques of the existing data-driven order. But too few scholars in either tradition have put forward alternative substantive conceptions of a good digital society. This, I argue, is a crucial omission. Unless we construct new “sociotechnical imaginaries,” new understandings of the goals and aspirations digital technologies should aim to achieve, the most surveillance studies and privacy scholars can hope to accomplish is a less unjust version of the technology (...)
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  46. Reframing data ethics in research methods education: a pathway to critical data literacy.Javiera Atenas, Leo Havemann & Cristian Timmermann - 2023 - International Journal of Educational Technology in Higher Education 20:11.
    This paper presents an ethical framework designed to support the development of critical data literacy for research methods courses and data training programmes in higher education. The framework we present draws upon our reviews of literature, course syllabi and existing frameworks on data ethics. For this research we reviewed 250 research methods syllabi from across the disciplines, as well as 80 syllabi from data science programmes to understand how or if data ethics was taught. We (...)
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  47. Using Linguistics Corpus Data Analysis to Combat PRC's Cognitive Infiltration.Jr-Jiun Lian - 2024 - 2024 Annual Conference of the Communication Association: International Academic Conference on Communication and Democratic Resilience.
    In light of Taiwan's extensive exposure to the Chinese Communist Party's "cognitive domain infiltration warfare," this paper proposes new response mechanisms and strategies for cybersecurity and national defense. The focus is primarily on assessing the CCP's cognitive infiltration tactics to develop policy recommendations in cybersecurity linguistics. These recommendations are intended to serve as a reference for future national defense and information security policies. Within the constraints of limited resources, this study attempts to provide an integrated analysis method combining qualitative and (...)
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  48. How Data Governance Principles Influence Participation in Biodiversity Science.Beckett Sterner & Steve Elliott - 2023 - Science as Culture.
    Biodiversity science is in a pivotal period when diverse groups of actors—including researchers, businesses, national governments, and Indigenous Peoples—are negotiating wide-ranging norms for governing and managing biodiversity data in digital repositories. These repositories, often called biodiversity data portals, are a type of organization for which governance can address or perpetuate the colonial history of biodiversity science and current inequities. Researchers and Indigenous Peoples are developing and implementing new strategies to examine and change assumptions about which agents should count (...)
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  49. Using models to correct data: paleodiversity and the fossil record.Alisa Bokulich - 2018 - Synthese 198 (Suppl 24):5919-5940.
    Despite an enormous philosophical literature on models in science, surprisingly little has been written about data models and how they are constructed. In this paper, I examine the case of how paleodiversity data models are constructed from the fossil data. In particular, I show how paleontologists are using various model-based techniques to correct the data. Drawing on this research, I argue for the following related theses: first, the ‘purity’ of a data model is not a (...)
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  50. OPTIMIZING DATA SCIENCE WORKFLOWS IN CLOUD COMPUTING.Tummalachervu Chaitanya Kanth - 2024 - Journal of Science Technology and Research (JSTAR) 4 (1):71-76.
    This paper explores the challenges and innovations in optimizing data science workflows within cloud computing environments. It begins by highlighting the critical role of data science in modern industries and the pivotal contribution of cloud computing in enabling scalable and efficient data processing. The primary focus lies in identifying and analyzing the key challenges encountered in current data science workflows deployed in cloud infrastructures. These challenges include scalability issues related to handling large volumes of data, (...)
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