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79,172 results

1. Science paper or big data? Assessing invasion dynamics using observational data.

Author

Clubley CH, Firth LB, Wood LE, Bilton DT, Silva TAM, and Knights AM

Subjects
Animals, Europe, Introduced Species, Big Data, Ostreidae
Abstract

Non-native species are spreading at an unprecedented rate over large spatial scales, with global environmental change and growth in commerce providing novel opportunities for range expansion. Assessing the pattern and rate of spread is key to the development of strategies for safeguarding against future invasions and efficiently managing existing ones. Such assessments often depend on spatial distribution data from online repositories, which can be spatially biased, imprecise, and lacking in quantity. Here, the influence of disparities between occurrence records from online data repositories and what is known of the invasion history from peer-reviewed published literature on non-native species range expansion was evaluated using 6693 records of the Pacific oyster, Magallana gigas (Thunberg, 1793), spanning 56 years of its invasion in Europe. Two measures of spread were calculated: maximum rate of spread (distance from introduction site over time) and accumulated area (spatial expansion). Results suggest that despite discrepancies between online and peer-reviewed data sources, including a paucity of records from the early invasion history in online repositories, the use of either source does not result in significantly different estimates of spread. Our study significantly improves our understanding of the European distribution of M. gigas and suggests that a combination of short- and long-range dispersal drives range expansions. More widely, our approach provides a framework for comparison of online occurrence records and invasion histories as documented in the peer-reviewed literature, allowing critical evaluation of both data sources and improving our understanding of invasion dynamics significantly., Competing Interests: Declaration of competing interest The authors declare that they have no known competing financial interests or personal relationships that could have appeared to influence the work reported in this paper., (Copyright © 2023 The Authors. Published by Elsevier B.V. All rights reserved.)

Published
2023
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3. Big Data Techniques Utilization in Intelligent Transportation System Environment

Author

Sharma, Sumit, Aujla, Gagangeet Singh, Bali, Rasmeet Singh, Filipe, Joaquim, Editorial Board Member, Ghosh, Ashish, Editorial Board Member, Prates, Raquel Oliveira, Editorial Board Member, Zhou, Lizhu, Editorial Board Member, Challa, Rama Krishna, editor, Aujla, Gagangeet Singh, editor, Mathew, Lini, editor, Kumar, Amod, editor, Kalra, Mala, editor, Shimi, S. L., editor, Saini, Garima, editor, and Sharma, Kanika, editor

Published
2024
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4. A Meta-data Based Feature Selection Mechanism to Identify Suspicious Reviews

Author

Boparai, Rajdavinder Singh, Bhatia, Rekha, Filipe, Joaquim, Editorial Board Member, Ghosh, Ashish, Editorial Board Member, Prates, Raquel Oliveira, Editorial Board Member, Zhou, Lizhu, Editorial Board Member, Challa, Rama Krishna, editor, Aujla, Gagangeet Singh, editor, Mathew, Lini, editor, Kumar, Amod, editor, Kalra, Mala, editor, Shimi, S. L., editor, Saini, Garima, editor, and Sharma, Kanika, editor

Published
2024
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6. Job Scheduling for Big Data Processing in YARN to Enhancing Performance

Author

Grover, Reshu, Agarwal, Manisha, Kacprzyk, Janusz, Series Editor, Gomide, Fernando, Advisory Editor, Kaynak, Okyay, Advisory Editor, Liu, Derong, Advisory Editor, Pedrycz, Witold, Advisory Editor, Polycarpou, Marios M., Advisory Editor, Rudas, Imre J., Advisory Editor, Wang, Jun, Advisory Editor, Nagar, Atulya K., editor, Jat, Dharm Singh, editor, Mishra, Durgesh Kumar, editor, and Joshi, Amit, editor

Published
2024
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7. Improving Diplomatic Mission Service Production with Big Data: The Case of Indonesian Embassy in Moscow

Author

Winata, Muhamad, Panfilov, Peter, Chaari, Fakher, Series Editor, Gherardini, Francesco, Series Editor, Ivanov, Vitalii, Series Editor, Haddar, Mohamed, Series Editor, Cavas-Martínez, Francisco, Editorial Board Member, di Mare, Francesca, Editorial Board Member, Kwon, Young W., Editorial Board Member, Tolio, Tullio A. M., Editorial Board Member, Trojanowska, Justyna, Editorial Board Member, Schmitt, Robert, Editorial Board Member, Xu, Jinyang, Editorial Board Member, Durakbasa, Numan M., editor, and Gençyılmaz, M. Güneş, editor

Published
2024
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8. A Novel Real-Time Data-Based PEMFC Performance Evaluation Model Using Improved PCA-Kmeans-XGBoost for PEMFC Hybrid Vehicles in China

Author

Yuan, Xinjie, Zhuang, Linlin, Hou, Zhongjun, China Society of Automotive Engineers, Angrisani, Leopoldo, Series Editor, Arteaga, Marco, Series Editor, Chakraborty, Samarjit, Series Editor, Chen, Jiming, Series Editor, Chen, Shanben, Series Editor, Chen, Tan Kay, Series Editor, Dillmann, Rüdiger, Series Editor, Duan, Haibin, Series Editor, Ferrari, Gianluigi, Series Editor, Ferre, Manuel, Series Editor, Jabbari, Faryar, Series Editor, Jia, Limin, Series Editor, Kacprzyk, Janusz, Series Editor, Khamis, Alaa, Series Editor, Kroeger, Torsten, Series Editor, Li, Yong, Series Editor, Liang, Qilian, Series Editor, Martín, Ferran, Series Editor, Ming, Tan Cher, Series Editor, Minker, Wolfgang, Series Editor, Misra, Pradeep, Series Editor, Mukhopadhyay, Subhas, Series Editor, Ning, Cun-Zheng, Series Editor, Nishida, Toyoaki, Series Editor, Oneto, Luca, Series Editor, Panigrahi, Bijaya Ketan, Series Editor, Pascucci, Federica, Series Editor, Qin, Yong, Series Editor, Seng, Gan Woon, Series Editor, Speidel, Joachim, Series Editor, Veiga, Germano, Series Editor, Wu, Haitao, Series Editor, Zamboni, Walter, Series Editor, Zhang, Junjie James, Series Editor, and Tan, Kay Chen, Series Editor

Published
2024
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9. Machine-Learning Holistic Review in Tourism and Hospitality

Author

Ashqar, Rashed Isam, Ramos, Célia M. Q., Filipe, Joaquim, Editorial Board Member, Ghosh, Ashish, Editorial Board Member, Prates, Raquel Oliveira, Editorial Board Member, Zhou, Lizhu, Editorial Board Member, M. A. Musleh Al-Sartawi, Abdalmuttaleb, editor, Helmy Abd Wahab, Mohd, editor, and Hussainey, Khaled, editor

Published
2024
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12. Optimizing Parallelization Strategies for the Big-Means Clustering Algorithm

Author

Mussabayev, Ravil, Mussabayev, Rustam, Filipe, Joaquim, Editorial Board Member, Ghosh, Ashish, Editorial Board Member, Prates, Raquel Oliveira, Editorial Board Member, Zhou, Lizhu, Editorial Board Member, Olenev, Nicholas, editor, Evtushenko, Yuri, editor, Jaćimović, Milojica, editor, Khachay, Michael, editor, and Malkova, Vlasta, editor

Published
2024
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14. On the Automated Text Report Generation in Open Transport Data Analysis Platform

Author

Bulygin, Mark, Namiot, Dmitry, Goos, Gerhard, Founding Editor, Hartmanis, Juris, Founding Editor, Bertino, Elisa, Editorial Board Member, Gao, Wen, Editorial Board Member, Steffen, Bernhard, Editorial Board Member, Yung, Moti, Editorial Board Member, Vishnevskiy, Vladimir M., editor, Samouylov, Konstantin E., editor, and Kozyrev, Dmitry V., editor

Published
2024
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16. Anomaly Detection and Categorization for a Data Quality Management Framework in Financial Regulatory Reporting

Author

Tafech, Aya, van der Aalst, Wil, Series Editor, Ram, Sudha, Series Editor, Rosemann, Michael, Series Editor, Szyperski, Clemens, Series Editor, Guizzardi, Giancarlo, Series Editor, Sales, Tiago Prince, editor, de Kinderen, Sybren, editor, Proper, Henderik A., editor, Pufahl, Luise, editor, Karastoyanova, Dimka, editor, and van Sinderen, Marten, editor

Published
2024
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17. Assessing the Feasibility and Scalability of Using Spark for Identifying Tip Burn Diseases in Strawberry Leaves

Author

Prathyuma, V., Hareesh Teja, S., Suganeshwari, G., Divya, S., Kacprzyk, Janusz, Series Editor, Gomide, Fernando, Advisory Editor, Kaynak, Okyay, Advisory Editor, Liu, Derong, Advisory Editor, Pedrycz, Witold, Advisory Editor, Polycarpou, Marios M., Advisory Editor, Rudas, Imre J., Advisory Editor, Wang, Jun, Advisory Editor, Das, Swagatam, editor, Saha, Snehanshu, editor, Coello Coello, Carlos A., editor, and Bansal, Jagdish C., editor

Published
2024
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18. Big Data-Based Risk Assessment Model for Dangerous Goods Transportation: A Case Study for Liguria Region in Italy

Author

Soussi, Abdellatif, Tomasoni, Angela Maria, Zero, Enrico, Sacile, Roberto, Kacprzyk, Janusz, Series Editor, Gomide, Fernando, Advisory Editor, Kaynak, Okyay, Advisory Editor, Liu, Derong, Advisory Editor, Pedrycz, Witold, Advisory Editor, Polycarpou, Marios M., Advisory Editor, Rudas, Imre J., Advisory Editor, Wang, Jun, Advisory Editor, Nagar, Atulya K., editor, Jat, Dharm Singh, editor, Mishra, Durgesh, editor, and Joshi, Amit, editor

Published
2024
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19. Development and Application of Oil On-Line Monitoring and Intelligent Diagnosis System for Automotive Stamping Press Driven by Big Data

Author

Jianxin, Wang, Jinliang, Fang, Xu, Zhao, Wenlong, Yan, Qiushi, Zhu, China Society of Automotive Engineers, Angrisani, Leopoldo, Series Editor, Arteaga, Marco, Series Editor, Chakraborty, Samarjit, Series Editor, Chen, Jiming, Series Editor, Chen, Shanben, Series Editor, Chen, Tan Kay, Series Editor, Dillmann, Rüdiger, Series Editor, Duan, Haibin, Series Editor, Ferrari, Gianluigi, Series Editor, Ferre, Manuel, Series Editor, Jabbari, Faryar, Series Editor, Jia, Limin, Series Editor, Kacprzyk, Janusz, Series Editor, Khamis, Alaa, Series Editor, Kroeger, Torsten, Series Editor, Li, Yong, Series Editor, Liang, Qilian, Series Editor, Martín, Ferran, Series Editor, Ming, Tan Cher, Series Editor, Minker, Wolfgang, Series Editor, Misra, Pradeep, Series Editor, Mukhopadhyay, Subhas, Series Editor, Ning, Cun-Zheng, Series Editor, Nishida, Toyoaki, Series Editor, Oneto, Luca, Series Editor, Panigrahi, Bijaya Ketan, Series Editor, Pascucci, Federica, Series Editor, Qin, Yong, Series Editor, Seng, Gan Woon, Series Editor, Speidel, Joachim, Series Editor, Veiga, Germano, Series Editor, Wu, Haitao, Series Editor, Zamboni, Walter, Series Editor, Zhang, Junjie James, Series Editor, and Tan, Kay Chen, Series Editor

Published
2024
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20. Exploration and Practice of Predictive Maintenance Technology in Automobile Factories

Author

Hao, Zhiqiang, Li, Guojun, Chen, Lei, Niu, Jingcheng, China Society of Automotive Engineers, Angrisani, Leopoldo, Series Editor, Arteaga, Marco, Series Editor, Chakraborty, Samarjit, Series Editor, Chen, Jiming, Series Editor, Chen, Shanben, Series Editor, Chen, Tan Kay, Series Editor, Dillmann, Rüdiger, Series Editor, Duan, Haibin, Series Editor, Ferrari, Gianluigi, Series Editor, Ferre, Manuel, Series Editor, Jabbari, Faryar, Series Editor, Jia, Limin, Series Editor, Kacprzyk, Janusz, Series Editor, Khamis, Alaa, Series Editor, Kroeger, Torsten, Series Editor, Li, Yong, Series Editor, Liang, Qilian, Series Editor, Martín, Ferran, Series Editor, Ming, Tan Cher, Series Editor, Minker, Wolfgang, Series Editor, Misra, Pradeep, Series Editor, Mukhopadhyay, Subhas, Series Editor, Ning, Cun-Zheng, Series Editor, Nishida, Toyoaki, Series Editor, Oneto, Luca, Series Editor, Panigrahi, Bijaya Ketan, Series Editor, Pascucci, Federica, Series Editor, Qin, Yong, Series Editor, Seng, Gan Woon, Series Editor, Speidel, Joachim, Series Editor, Veiga, Germano, Series Editor, Wu, Haitao, Series Editor, Zamboni, Walter, Series Editor, Zhang, Junjie James, Series Editor, and Tan, Kay Chen, Series Editor

Published
2024
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21. The Importance of Big Data and IoT in Smart Cities

Author

Duque, Jorge, Kacprzyk, Janusz, Series Editor, Gomide, Fernando, Advisory Editor, Kaynak, Okyay, Advisory Editor, Liu, Derong, Advisory Editor, Pedrycz, Witold, Advisory Editor, Polycarpou, Marios M., Advisory Editor, Rudas, Imre J., Advisory Editor, Wang, Jun, Advisory Editor, Nagar, Atulya K., editor, Jat, Dharm Singh, editor, Mishra, Durgesh, editor, and Joshi, Amit, editor

Published
2024
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22. Hash Edward Curve Signcryption for Secure Big Data Transmission

Author

Sangeetha, S., Suresh Babu, P., Filipe, Joaquim, Editorial Board Member, Ghosh, Ashish, Editorial Board Member, Prates, Raquel Oliveira, Editorial Board Member, Zhou, Lizhu, Editorial Board Member, Aurelia, Sagaya, editor, J., Chandra, editor, Immanuel, Ashok, editor, Mani, Joseph, editor, and Padmanabha, Vijaya, editor

Published
2024
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23. A Digital Ecosystem for Improving Product Design

Author

Lefebvre, Sylvain, Lecointre, Michaël, Lardeux, Benoit, Guyader, Jean-Marie, Aubrun, Olivier, Touré, Birane, Jridi, Maher, Filipe, Joaquim, Editorial Board Member, Ghosh, Ashish, Editorial Board Member, Prates, Raquel Oliveira, Editorial Board Member, Zhou, Lizhu, Editorial Board Member, Chbeir, Richard, editor, Benslimane, Djamal, editor, Zervakis, Michalis, editor, Manolopoulos, Yannis, editor, Ngyuen, Ngoc Thanh, editor, and Tekli, Joe, editor

Published
2024
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24. Towards a Data Provenance Collection and Visualization Framework for Monitoring and Analyzing HPC Environments

Author

Sukhija, Nitin, Bautista, Elizabeth, Schultz, Adam, Whitney, Cary, Davis, Thomas, Filipe, Joaquim, Editorial Board Member, Ghosh, Ashish, Editorial Board Member, Prates, Raquel Oliveira, Editorial Board Member, Zhou, Lizhu, Editorial Board Member, Chbeir, Richard, editor, Benslimane, Djamal, editor, Zervakis, Michalis, editor, Manolopoulos, Yannis, editor, Ngyuen, Ngoc Thanh, editor, and Tekli, Joe, editor

Published
2024
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25. Association Rule Mining for Multifactorial Diseases: Survey and Opportunities

Author

Amraoui, Hend, Mhamdi, Faouzi, Filipe, Joaquim, Editorial Board Member, Ghosh, Ashish, Editorial Board Member, Prates, Raquel Oliveira, Editorial Board Member, Zhou, Lizhu, Editorial Board Member, Chbeir, Richard, editor, Benslimane, Djamal, editor, Zervakis, Michalis, editor, Manolopoulos, Yannis, editor, Ngyuen, Ngoc Thanh, editor, and Tekli, Joe, editor

Published
2024
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29. Reflections on the 1962 Paper "The Statistician in Medicine" by Sir Austin Bradford Hill.

Author

Lin X

Subjects
Causality, Humans, Reproducibility of Results, Big Data
Abstract

This article provides reflections on the 1962 paper by Sir Austin Bradford Hill, entitled "The Statistician in Medicine." It discusses several key takeaways of this paper, including causal inference for big data, reproducibility and replicability in science, and integration of statistics and data science with domain science., (© 2020 John Wiley & Sons, Ltd.)

Published
2021
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33. Integrating China in the International Consortium for Personalised Medicine: a position paper on innovation and digitalization in Personalized Medicine

Author

Flavia Beccia, Marzia Di Marcantonio, Francesco Andrea Causio, Lena Schleicher, Lili Wang, Chiara Cadeddu, Walter Ricciardi, and Stefania Boccia

Subjects
European Union, China, Big Data, ICT solutions, Innovation, funding, Public aspects of medicine, RA1-1270
Abstract

Abstract Background The advent of Personalized Medicine (PM) holds significant promise in revolutionizing healthcare by tailoring treatments to individual patients based on their data. However, its successful implementation requires the seamless integration of innovative technologies and presents formidable challenges in terms of sustainability. To tackle these challenges head-on, the International Consortium for Personalized Medicine (ICPerMed) was established, and the IC2PerMed project, as part of this consortium, seeks to foster collaboration between the European Union (EU) and China in the field of Personalized Medicine. Based on the results collected by the project, the objective of this study is to discern the key priorities for the implementation of Personalised Medicine concerning Information and Communication Technologies (ICT) and Big Data and digital solutions, with a particular emphasis on data management and protection. Methods A Delphi survey was conducted to gather expert’s consensus on the main priorities for actions on Information and Communication Technologies (ICT) and Big Data and digital solutions in the field of Personalized Medicine. Results The survey identified seven priorities in the area of Big Data and digital solutions, including data interoperability, standards, security measures, and international partnerships. Additionally, twelve priorities were identified for the innovation-to-market process, emphasizing cost-effectiveness, need assessment, and value definition in resource allocation. Conclusions The effective implementation of new technologies in Personalized Medicine research and practice is essential for the advancement of healthcare systems in both the European and Chinese contexts. The identified priorities play a pivotal role in promoting the sustainability of health systems and driving innovation in the implementation of Personalized Medicine. Addressing challenges related to data interoperability, standards, security, international collaboration, cost-effectiveness, and value assessment is of utmost importance in order to propel the progress of Personalized Medicine in healthcare systems.

Published
2024
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36. Is Artificial Intelligence Really the Next Big Thing in Learning and Teaching in Higher Education? A Conceptual Paper.

Author

Xianghan (Christine) O'Dea and O'Dea, Mike

Subjects
ARTIFICIAL intelligence, HIGHER education, PEDAGOGICAL content knowledge
Abstract

Artificial Intelligence in higher education (AIED) is becoming a more important research area with increasing developments and application of AI within the wider society. However, as yet AI based tools have not been widely adopted in higher education. As a result there is a lack of sound evidence available on the pedagogical impact of AI for learning and teaching. This conceptual paper thus seeks to bridge the gap and addresses the following question: is artificial intelligence really the new big thing that will revolutionise learning and teaching in higher education? Adopting the technological pedagogical content knowledge (TPACK) framework and the Unified Theory of Acceptance and Use of Technology (UTAUT) as the theoretical foundations, we argue that Artificial Intelligence (AI) technologies, at least in their current state of development, do not afford any real new advances for pedagogy in higher education. This is mainly because there does not seem to be valid evidence as to how the use of AI technologies and applications has helped students improve learning, and/or helped tutors make effective pedagogical changes. In addition, the pedagogical affordances of AI have not yet been clearly defined. The challenges that the higher education sector is currently experiencing relating to AI adoption are discussed at three hierarchical levels, namely national, institutional and personal levels. The paper ends with recommendations with regard to accelerating AI use in universities. This includes developing dedicated AI adoption strategies at the institutional level, updating the existing technology infrastructure and upskilling academic tutors for AI. [ABSTRACT FROM AUTHOR]

Published
2023
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37. Machine learning and big data analytics in bipolar disorder: A position paper from the International Society for Bipolar Disorders Big Data Task Force.

Author

Passos IC, Ballester PL, Barros RC, Librenza-Garcia D, Mwangi B, Birmaher B, Brietzke E, Hajek T, Lopez Jaramillo C, Mansur RB, Alda M, Haarman BCM, Isometsa E, Lam RW, McIntyre RS, Minuzzi L, Kessing LV, Yatham LN, Duffy A, and Kapczinski F

Subjects
Advisory Committees, Bipolar Disorder epidemiology, Data Science, Humans, Phenotype, Prognosis, Risk Assessment, Big Data, Bipolar Disorder therapy, Clinical Decision-Making, Machine Learning, Suicidal Ideation
Abstract

Objectives: The International Society for Bipolar Disorders Big Data Task Force assembled leading researchers in the field of bipolar disorder (BD), machine learning, and big data with extensive experience to evaluate the rationale of machine learning and big data analytics strategies for BD., Method: A task force was convened to examine and integrate findings from the scientific literature related to machine learning and big data based studies to clarify terminology and to describe challenges and potential applications in the field of BD. We also systematically searched PubMed, Embase, and Web of Science for articles published up to January 2019 that used machine learning in BD., Results: The results suggested that big data analytics has the potential to provide risk calculators to aid in treatment decisions and predict clinical prognosis, including suicidality, for individual patients. This approach can advance diagnosis by enabling discovery of more relevant data-driven phenotypes, as well as by predicting transition to the disorder in high-risk unaffected subjects. We also discuss the most frequent challenges that big data analytics applications can face, such as heterogeneity, lack of external validation and replication of some studies, cost and non-stationary distribution of the data, and lack of appropriate funding., Conclusion: Machine learning-based studies, including atheoretical data-driven big data approaches, provide an opportunity to more accurately detect those who are at risk, parse-relevant phenotypes as well as inform treatment selection and prognosis. However, several methodological challenges need to be addressed in order to translate research findings to clinical settings., (© 2019 John Wiley & Sons A/S. Published by John Wiley & Sons Ltd.)

Published
2019
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38. The plan to mine the world's research papers.

Author

Pulla P

Subjects
Big Data economics, Data Mining trends, Datasets as Topic economics, Datasets as Topic legislation & jurisprudence, India, Open Access Publishing economics, Research Report, Unsupervised Machine Learning legislation & jurisprudence, Unsupervised Machine Learning trends, Big Data supply & distribution, Data Mining methods, Datasets as Topic supply & distribution, Information Dissemination legislation & jurisprudence, Information Dissemination methods, Open Access Publishing legislation & jurisprudence, Research
Published
2019
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39. Mining and Analysis of Search Interests Related to Online Learning Platforms from Different Countries Since the Beginning of COVID-19

Author

Thakur, Nirmalya, Khanna, Karam, Cui, Shuqi, Azizi, Nazif, Liu, Zihui, Goos, Gerhard, Founding Editor, Hartmanis, Juris, Founding Editor, Bertino, Elisa, Editorial Board Member, Gao, Wen, Editorial Board Member, Steffen, Bernhard, Editorial Board Member, Yung, Moti, Editorial Board Member, Zaphiris, Panayiotis, editor, Ioannou, Andri, editor, Sottilare, Robert A., editor, Schwarz, Jessica, editor, Fui-Hoon Nah, Fiona, editor, Siau, Keng, editor, Wei, June, editor, and Salvendy, Gavriel, editor

Published
2023
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41. Applications of Big Data in Various Fields: A Survey

Author

Mondal, Sukhendu S., Mondal, Somen, Adhikari, Sudip Kumar, Kacprzyk, Janusz, Series Editor, Pal, Nikhil R., Advisory Editor, Bello Perez, Rafael, Advisory Editor, Corchado, Emilio S., Advisory Editor, Hagras, Hani, Advisory Editor, Kóczy, László T., Advisory Editor, Kreinovich, Vladik, Advisory Editor, Lin, Chin-Teng, Advisory Editor, Lu, Jie, Advisory Editor, Melin, Patricia, Advisory Editor, Nedjah, Nadia, Advisory Editor, Nguyen, Ngoc Thanh, Advisory Editor, Wang, Jun, Advisory Editor, Bhattacharyya, Siddhartha, editor, Das, Gautam, editor, De, Sourav, editor, and Mrsic, Leo, editor

Published
2023
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42. One Case of THOUGHT: Industry-University Converged Education Practice on Open Source

Author

Yu, Zhiyi, Li, Chao, Hu, Chaochen, Chen, Zhen, Yao, Yandong, Wu, Jiang, Wang, Hao, Du, Jialun, Guo, Min, Wang, Haoyu, Li, Weimin, Li, Xiu, Ma, Xiaodong, Zhangi, Yisong, Li, Shuangshou, Filipe, Joaquim, Editorial Board Member, Ghosh, Ashish, Editorial Board Member, Prates, Raquel Oliveira, Editorial Board Member, Zhou, Lizhu, Editorial Board Member, Hong, Wenxing, editor, and Weng, Yang, editor

Published
2023
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45. The European Federation of Organisations for Medical Physics (EFOMP) White Paper: Big data and deep learning in medical imaging and in relation to medical physics profession.

Author

Kortesniemi M, Tsapaki V, Trianni A, Russo P, Maas A, Källman HE, Brambilla M, and Damilakis J

Subjects
Europe, Health Personnel, Humans, Societies, Medical, Big Data, Deep Learning, Diagnostic Imaging methods, Health Physics methods
Abstract

Big data and deep learning will profoundly change various areas of professions and research in the future. This will also happen in medicine and medical imaging in particular. As medical physicists, we should pursue beyond the concept of technical quality to extend our methodology and competence towards measuring and optimising the diagnostic value in terms of how it is connected to care outcome. Functional implementation of such methodology requires data processing utilities starting from data collection and management and culminating in the data analysis methods. Data quality control and validation are prerequisites for the deep learning application in order to provide reliable further analysis, classification, interpretation, probabilistic and predictive modelling from the vast heterogeneous big data. Challenges in practical data analytics relate to both horizontal and longitudinal analysis aspects. Quantitative aspects of data validation, quality control, physically meaningful measures, parameter connections and system modelling for the future artificial intelligence (AI) methods are positioned firmly in the field of Medical Physics profession. It is our interest to ensure that our professional education, continuous training and competence will follow this significant global development., (Copyright © 2018 Associazione Italiana di Fisica Medica. Published by Elsevier Ltd. All rights reserved.)

Published
2018
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46. HR Analytics and Achieving Competitive Advantage for Organizations Through Big Data: A Conceptual Paper.

Author

Mohamed, Doaa and Shehata, Gamal M.

Subjects
COMPETITIVE advantage in business, BIG data, TELECOMMUNICATION employees, MIDDLE managers, HUMAN resources departments, ARTIFICIAL intelligence
Abstract

In light of artificial intelligence and new technologies, organizations have to follow new ways of working with different skill sets to achieve strategic goals. Therefore, human resource analytics is the scientific solution that enables organizations to make important decisions related to human capital and strategic business and thus gain a competitive advantage. Through new technologies comes the role of big data, as it works to establish the reputation of human resources as a strategic business partner that makes decisions driven by analytics. Evidence-based decisions, therefore, all equal a significant competitive advantage. This conceptual paper aims to understand the relationship between human resource analytics and achieving a competitive advantage in the presence of big data. This study will use quantitative data through a survey list that will be distributed to middle managers and human resources employees of the telecommunications company sector in Egypt. [ABSTRACT FROM AUTHOR]

Published
2023
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48. Monitoring and Forecasting Crop Yields

Author

Makarovskikh, Tatiana, Panyukov, Anatoly, Abotaleb, Mostafa, Filipe, Joaquim, Editorial Board Member, Ghosh, Ashish, Editorial Board Member, Prates, Raquel Oliveira, Editorial Board Member, Zhou, Lizhu, Editorial Board Member, Sokolinsky, Leonid, editor, and Zymbler, Mikhail, editor

Published
2023
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50. A Large Scale IoT Botnet Attack Detection Using Ensemble Learning

Author

Jwalin, B., Saravanan, S., Filipe, Joaquim, Editorial Board Member, Ghosh, Ashish, Editorial Board Member, Prates, Raquel Oliveira, Editorial Board Member, Zhou, Lizhu, Editorial Board Member, Garg, Deepak, editor, Narayana, V. A., editor, Suganthan, P. N., editor, Anguera, Jaume, editor, Koppula, Vijaya Kumar, editor, and Gupta, Suneet Kumar, editor

Published
2023
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