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1

Haywood, M. Elizabeth, and Anubha Mishra. "Building a culture of business analytics: a marketing analytics exercise." International Journal of Educational Management 33, no. 1 (2019): 86–97. http://dx.doi.org/10.1108/ijem-03-2018-0107.

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Purpose The purpose of this paper is to describe how brief exercises in introductory and advanced marketing courses can help business students achieve a broader understanding of what Big data and data analytics mean in the workplace. These short analytics problems fit into the culture that we are building at our institution to create analytics cases for courses within our business curriculum. Design/methodology/approach A database of 1,500 customer reviews for a fictitious sporting company was created. Two exercises based on text mining and sentiment analysis were developed to be tested in int
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Ryan, Mark. "Agricultural Big Data Analytics and the Ethics of Power." Journal of Agricultural and Environmental Ethics 33, no. 1 (2019): 49–69. http://dx.doi.org/10.1007/s10806-019-09812-0.

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AbstractAgricultural Big Data analytics (ABDA) is being proposed to ensure better farming practices, decision-making, and a sustainable future for humankind. However, the use and adoption of these technologies may bring about potentially undesirable consequences, such as exercises of power. This paper will analyse Brey’s five distinctions of power relationships (manipulative, seductive, leadership, coercive, and forceful power) and apply them to the use agricultural Big Data. It will be shown that ABDA can be used as a form of manipulative power to initiate cheap land grabs and acquisitions. S
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Yoon, Seung-hye. "Application of Predictive Analytics in Rehabilitation Exercise." Journal of the Korea Academia-Industrial cooperation Society 25, no. 11 (2024): 573–81. https://doi.org/10.5762/kais.2024.25.11.573.

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Filion, Myriam, Anna Schwartz, and Kerry Courneya. "Cancer Exercise Mobile App: Reporting The First Analytics." Medicine & Science in Sports & Exercise 56, no. 10S (2024): 1089. http://dx.doi.org/10.1249/01.mss.0001062112.87359.8b.

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Zheng, Nan, Meng Sun, and Ye Yang. "Visual Analysis of College Sports Performance Based on Multimodal Knowledge Graph Optimization Neural Network." Computational Intelligence and Neuroscience 2022 (July 1, 2022): 1–12. http://dx.doi.org/10.1155/2022/5398932.

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In this paper, through data analysis of multimodal knowledge graph optimized neural network and visual analysis of college students’ sports performance, we use huge graph, a graph database supporting distributed storage, to store domain knowledge in the form of the knowledge graph, use Spring Boot to build a server-side framework, use Vue framework combined with vis.js to visualize relational network graphs, and design and implement a knowledge-oriented. This paper proposes a visual analytics system based on the theory of visual analytics. Based on the idea of visual analytics, this paper pres
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Rodriguez, Michael, and Stefanie L. Boyer. "Artificial Intelligence and the Sales Process: How to Help Sales Students Develop an Analytics Skill Set." Global Research in Higher Education 3, no. 1 (2020): p54. http://dx.doi.org/10.22158/grhe.v3n1p54.

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The following learning protocol provides an opportunity for professors to help students apply artificial intelligence and analytics in a pipeline management exercise. The activity allows advanced sales students to build a predictive sales model in Salesforce.com’s Einstein Analytics Platform. The following innovation walks the educator through the process of accessing the platform, building a model and analyzing outcomes. The exercise provides the opportunity to improve outcomes and act on sales opportunities, simulating the work environment. The article provides teaching tips for success to h
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Gopalakrishna-Remani, Venugopal, John James Cater III, and Jerry James Massey. "Restaurant operations at the Rose Capital Inn: a case study exercise." CASE Journal 12, no. 1 (2016): 104–21. http://dx.doi.org/10.1108/tcj-11-2014-0063.

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Synopsis This case study exercise highlights the importance of food supplier selection and forecasting to minimize food cost and maximize profit for a hotel restaurant. The importance of data analytics in supplier selection is emphasized. The case exercise provides students with a more comprehensive understanding of spoilage and the calculation of food cost percentage, which should save the hotel restaurant under study significant dollars, help the environment, and strengthen the operation. The events described in this case are based on real world experiences. Research methodology This researc
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Jones, Mike, George Collier, David J. Reinkensmeyer, et al. "Big Data Analytics and Sensor-Enhanced Activity Management to Improve Effectiveness and Efficiency of Outpatient Medical Rehabilitation." International Journal of Environmental Research and Public Health 17, no. 3 (2020): 748. http://dx.doi.org/10.3390/ijerph17030748.

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Numerous societal trends are compelling a transition from inpatient to outpatient venues of care for medical rehabilitation. While there are advantages to outpatient rehabilitation (e.g., lower cost, more relevant to home and community function), there are also challenges including lack of information about how patient progress observed in the outpatient clinic translates into improved functional performance at home. At present, outpatient providers must rely on patient-reported information about functional progress (or lack thereof) at home and in the community. Information and communication
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Proulx, Pascale, and Casey Canfield. "The beneficial role of the VAST Challenges in the evolution of GeoTime and nSpace2." Information Visualization 14, no. 1 (2013): 3–9. http://dx.doi.org/10.1177/1473871613487090.

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Oculus participated in the first VAST Challenge in 2006 and in every subsequent year except one. Although we have won 5 awards in the last 7 years, they are not the main reason we spend much time and effort preparing our submission each year. The VAST Challenge has proven to be a valuable exercise in evaluating and refining our tools and our thinking. No organization that has the desire to create the best possible analytic tools should pass by the unique opportunity to work on a realistic set of tasks, against nontoy datasets containing ground truth, and to be evaluated by both senior analysts
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Kucsmik-Horváth, Éva, and Biljana Presnall. "Implementing advanced distribited learning : A case study from Vigorous Warrior 2024 and Clean Care 2024 excercises." Honvédorvos 76, Különszám (2024): 5–19. https://doi.org/10.29068/ho.2024.ksz.5-19.

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Multinational military exercises inherently bring together participants with diverse backgrounds, experience levels, and knowledge bases, creating challenges in achieving uniform preparedness. The pre-training phase plays a critical role in equipping participants for effective engagement in these exercises. Furthermore, the evolving nature of military operations—characterized by increasing multinational collaboration and operational complexity—necessitates innovative training approaches, rapid skill acquisition, and adaptability.1 Integrating Advanced Distributed Learning (ADL) into multinatio
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Aquino, James Roy Vicente, Lovely Joy Mariano Barrientos, Madeline Castro Coloma, Larissa Vivien Santos Lacar, and James Patrick Apostol Acang. "Data Analytics Enforced Content-Based Fitness Recommender System for Individuals without Allergies and Ailments." Journal of Software Engineering: Theories and Practices 2, no. 1 (2017): 11–16. http://dx.doi.org/10.21174/josetap.v2i1.133.

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The society these days is bounded with inactive and unhealthy lifestyle. According to the recent studies, there is a rapid increase of individuals suffering and dying from diseases caused by poor diet and unhealthy lifestyle. In view of this, knowing the right kind of food to eat, and the appropriate exercise is essential in achieving good health. Being fit relates to good health, and healthy living makes life longer and happier. The objective of this study is to develop a system that will recommend its users the appropriate exercise and diet for their daily activities. Exercise and diet plans
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Diaz-del-Pino, Sergio, Pablo Rodriguez-Brazzarola, Esteban Perez-Wohlfeil, and Oswaldo Trelles. "Combining Strengths for Multi-genome Visual Analytics Comparison." Bioinformatics and Biology Insights 13 (January 2019): 117793221882512. http://dx.doi.org/10.1177/1177932218825127.

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The eclosion of data acquisition technologies has shifted the bottleneck in molecular biology research from data acquisition to data analysis. Such is the case in Comparative Genomics, where sequence analysis has transitioned from genes to genomes of several orders of magnitude larger. This fact has revealed the need to adapt software to work with huge experiments efficiently and to incorporate new data-analysis strategies to manage results from such studies. In previous works, we presented GECKO, a software to compare large sequences; now we address the representation, browsing, data explorat
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Yoon, Sunmoo, Joseph E. Schwartz, Matthew M. Burg, et al. "Using Behavioral Analytics to Increase Exercise: A Randomized N-of-1 Study." American Journal of Preventive Medicine 54, no. 4 (2018): 559–67. http://dx.doi.org/10.1016/j.amepre.2017.12.011.

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Kim, SungYe, Ross Maciejewski, Karl Ostmo, Edward J. Delp, Timothy F. Collins, and David S. Ebert. "Mobile Analytics for Emergency Response and Training." Information Visualization 7, no. 1 (2008): 77–88. http://dx.doi.org/10.1057/palgrave.ivs.9500168.

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During emergency response events, situational awareness is critical in effectively managing and safe-guarding civilians and in-field personnel. To better support both command center controllers and in-field operators, we have developed a mobile visual analytics tool to help enhance situational awareness and support rapid decision making. Our mobile visual analytics tool consists of a 2D/3D visualization component, which shows personnel-related information, situational and static scene-related information, integrated multi media playback functionality for personnel outfitted with cameras, and f
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Ismail, Assoujaa. "Designing Effective Threat Hunting to Enhance Security Programs." WSEAS TRANSACTIONS ON COMMUNICATIONS 23 (December 30, 2024): 142–48. https://doi.org/10.37394/23204.2024.23.19.

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Cyber threat hunting is a proactive cybersecurity approach focused on identifying threats that evade traditional security measures. It involves the integration of human expertise, data analytics, and advanced tools to detect anomalies within organizational networks and systems. Despite its potential, many organizations remain dissatisfied with their threat hunting programs due to gaps in required analytical skills and the lack of integration of advanced techniques such as machine learning. This paper explores the design of an effective threat hunting exercise, examining its role in complementi
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Doll, Jessica L. "Developing Workforce Planning Skills in Human Resource Management Courses: A Data-Driven Exercise." Management Teaching Review 7, no. 1 (2021): 89–108. http://dx.doi.org/10.1177/23792981211057227.

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Workforce planning is prevalent and recognized as a good strategic practice in many organizations. However, business students may have little experience with workforce planning or workforce analytics. The purpose of this article is to present a workforce planning exercise for use in a face-to-face or online classroom setting. In this exercise, students practice applying workforce planning concepts to calculate internal employment data, find and collect external employment data, and combine multiple, sometimes conflicting, data to make workforce predictions and recommendations for a hypothetica
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Passfield, Louis, and James G. Hopker. "A Mine of Information: Can Sports Analytics Provide Wisdom From Your Data?" International Journal of Sports Physiology and Performance 12, no. 7 (2017): 851–55. http://dx.doi.org/10.1123/ijspp.2016-0644.

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This paper explores the notion that the availability and analysis of large data sets have the capacity to improve practice and change the nature of science in the sport and exercise setting. The increasing use of data and information technology in sport is giving rise to this change. Web sites hold large data repositories, and the development of wearable technology, mobile phone applications, and related instruments for monitoring physical activity, training, and competition provide large data sets of extensive and detailed measurements. Innovative approaches conceived to more fully exploit th
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Asanka, PPG Dinesh, and Thilini V. Mahanama. "Learning through Simulation: A Role-Based Learning Exercise to Equip Students in Big Data Requirement Elicitation Skills and Challenges." Journal of Computing Theories and Applications 2, no. 1 (2024): 118–30. http://dx.doi.org/10.62411/jcta.10847.

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Bridging the gap between theoretical knowledge and practical application remains challenging in big data education. Our paper proposes a platform where students actively participate in a role-based learning (RBL) exercise designed to simulate real-world big data projects. This RBL exercise assigns each student participant to a business analyst role tasked with eliciting requirements or a customer role that provides those big data requirements. We conducted RBL sessions for postgraduate and undergraduate students learning big data analytics/data warehousing. Through role-playing in a collaborat
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Lin, Shih-Sung, Chien-Wu Lan, Hao-Yen Hsu, and Sheng-Tao Chen. "Data Analytics of a Wearable Device for Heat Stroke Detection." Sensors 18, no. 12 (2018): 4347. http://dx.doi.org/10.3390/s18124347.

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When exercising in a high-temperature environment, heat stroke can cause great harm to the human body. However, runners may ignore important physiological warnings and are not usually aware that a heat stroke is occurring. To solve this problem, this study evaluates a runner’s risk of heat stroke injury by using a wearable heat stroke detection device (WHDD), which we developed previously. Furthermore, some filtering algorithms are designed to correct the physiological parameters acquired by the WHDD. To verify the effectiveness of the WHDD and investigate the features of these physiological p
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Wang, Yu. "Machine learning models applied to predicate post activity oxygen saturation levels." International Journal of Biosensors & Bioelectronics 8, no. 1 (2023): 26–30. http://dx.doi.org/10.15406/ijbsbe.2023.08.00228.

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Machine learning is a rapidly growing field with widespread application in various industries, including healthcare. In recent years, significant advancements in machine learning have enhanced our understanding of data analytics and prediction models in analyzing physiological data, such as blood oxygen levels, heart rate, and blood pressure. This paper focuses on physical activity in adolescence during the pandemic period. The study showed that going outside for a short walk can increase blood oxygen levels. Furthermore, the consumption of certain foods can also raise oxygen saturation levels
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Mathur, Balafakir Subramanian. "Businesses Innovation & AI: How AI and Analytics Can Encourage Innovation." Business & IT XIII, no. 2 (2023): 39–46. http://dx.doi.org/10.14311/bit.2023.02.04.

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Artificial intelligence is about imbuing machines with a kind of intelligence that is largely attributed to humans. Extant literature, in addition to the encounters of ours as providers, indicates that while AI may not be entirely set to take over revolutionary areas within the improvement procedure, it indicates promise as a significant guidance to advancement superiors. In this particular content, we broadly relate to the derivation of PC enabled, data-driven insights, models, and visualizations within the development pastime as innovation analytics. AI may play a crucial role in the innovat
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Avinash Dulam. "Leveraging Data Analytics for Effective Risk Adjustment in the Affordable Care Act: Implications for Health Plan Management." Journal of Computer Science and Technology Studies 7, no. 5 (2025): 290–97. https://doi.org/10.32996/jcsts.2025.7.5.36.

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This article examines the critical role of data analytics in the Affordable Care Act's risk adjustment program, which transfers funds between health plans based on the relative health status of enrolled populations. Risk adjustment serves as a cornerstone mechanism for market stability by redistributing funds from plans with healthier enrollees to those serving higher-risk populations, thereby neutralizing the financial impact of adverse selection. The evolution of analytics in this domain represents a progression from basic descriptive techniques to sophisticated prescriptive approaches that
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Fadloun, Samiha, Khadidja Bennamane, Souham Meshoul, Mahmood Hosseini, and Kheireddine Choutri. "Visual Analytics Using Machine Learning for Transparency Requirements." Mathematics 11, no. 14 (2023): 3091. http://dx.doi.org/10.3390/math11143091.

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Problem solving applications require users to exercise caution in their data usage practices. Prior to installing these applications, users are encouraged to read and comprehend the terms of service, which address important aspects such as data privacy, processes, and policies (referred to as information elements). However, these terms are often lengthy and complex, making it challenging for users to fully grasp their content. Additionally, existing transparency analytics tools typically rely on the manual extraction of information elements, resulting in a time-consuming process. To address th
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Pérez-Marín, Diana, and Silvia Tamayo-Moreno. "Designing Pedagogic Conversational Agents through Data Analysis." TecnoLógicas 23, no. 47 (2020): 243–56. http://dx.doi.org/10.22430/22565337.1455.

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Pedagogical Conversational Agents are systems or programs that represent a resource and a means of learning for students, making the teaching and learning process more enjoyable. The aim is to improve the teaching-learning process. Currently, there are many agents being implemented in multiple knowledge domains. In our previous work, a methodology for designing agents was published, the result of which was Agent Dr. Roland, the first conversational agent for Early Childhood Education. In this paper, we propose the use of Data Analytics techniques to improve the design of the agent. Two new tec
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Narindrarangkura, Ploypun, Panadda Hatthachote, Kanlaya Jongcherdchootrakul, Rungnapha Khiewchaum, and Ram Rangsin. "USING PREDICTIVE ANALYTICS TO IMPROVE SURVEILLANCE OF HEAT-RELATED ILLNESS DURING MILITARY TRAINING." Journal of Southeast Asian Medical Research 8 (October 11, 2024): e0189. http://dx.doi.org/10.55374/jseamed.v8.189.

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Background: Heat-related illnesses are a critical concern for military personnel, especially those unfamiliar with hot climate regions. The Royal Thai Army (RTA) implements a 10-week military training program encompassing four phases: (1) Heat acclimatization training, (2) Combat fundamentals and unarmed combat training, (3) Armed combat training and tactical training, and (4) Field training exercise and evaluations. Objective: This study aimed to conduct a predictive analysis of heat-related illnesses to enhance prevention programs. Methods: The study utilized secondary data from the RTA Medi
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Rosa, Maria J., James Williams, Joke Claeys, et al. "Learning analytics and data ethics in performance data management: a benchlearning exercise involving six European universities." Quality in Higher Education 28, no. 1 (2022): 65–81. http://dx.doi.org/10.1080/13538322.2021.1951455.

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Hill, Anne-Marie, Cathy Said, Cathie Sherrington, et al. "Safe Exercise at Home Website: Keeping Older People Active during COVID-19." Innovation in Aging 4, Supplement_1 (2020): 956–57. http://dx.doi.org/10.1093/geroni/igaa057.3497.

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Abstract Background Physical distancing restrictions, including recommendations to ‘stay home’ during the COVID-19 pandemic has restricted exercise opportunities for older adults. Our group of academic and clinical physiotherapists and a communications expert identified the need to support safe exercise at home to minimise the impact of these restrictions. The project aimed to develop an online, publicly available resource to support older adults to exercise at home. We met virtually and: a) developed home exercise programs for people at three levels of functional ability; b) developed simple
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Raudah, Quds, Estu Meilani, and Nurul Kusuma Wardani. "The Effect of Skipping Exercise on Endurance Level among Adolescents aged 15-18 years in Gribin Volleyball Community Surabaya." JURNAL ILMU-ILMU KESEHATAN 11, no. 1 (2025): 14–21. https://doi.org/10.52741/jiikes.v11i1.125.

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Background: The most frequently encountered problem of individuals who are in transition period from childhood to adulthood is deteriorated cardiorespiratory endurance due to low physical activity. Adolescents had low physical activity because of their sedentary lifestyle. The exercise that could boost their cardiorespiratory endurance is long duration exercise with moderate intensity, such as skipping exercise. Objectives: This study aimed to evaluate the effect of skipping exercise on the endurance level of adolescents age 15-18 years in Gribin Volleyball Community, Surabaya. Methods: This s
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Kadakia, Shevali, Catherine Stratton, Yinfei Wu, Josemari Feliciano, and Yetsa A. Tuakli-Wosornu. "The Accessibility of YouTube Fitness Videos for Individuals Who Are Disabled Before and During the COVID-19 Pandemic: Preliminary Application of a Text Analytics Approach." JMIR Formative Research 6, no. 2 (2022): e34176. http://dx.doi.org/10.2196/34176.

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Background People with disabilities face barriers to in-person physical activity (PA), including a lack of adaptive equipment and knowledgeable instructors. Given this and the increased need for digital resources due to widespread COVID-19 lockdowns, it is necessary to assess the accessibility of digital fitness resources for people with disabilities. To investigate whether YouTube fitness content creators have made videos accessible to people with disabilities would be informative about access to PA during COVID-19 and could also provide insight into the feasibility of individuals who are dis
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Jorgensen, Jens Erik, Tamana Afzali, and Allan Riis. "Effect of differentiating exercise guidance based on a patient’s level of low back pain in primary care: a mixed-methods systematic review protocol." BMJ Open 8, no. 1 (2018): e019742. http://dx.doi.org/10.1136/bmjopen-2017-019742.

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IntroductionLow back pain (LBP) is one of the health conditions that lead to the most disability worldwide. Guidelines aimed at management of LBP recommend non-invasive and non-pharmacological management, including patient education, advice to stay active and exercise therapy; however, the guidelines offer no recommendation as to the allowable level of pain during exercise or how specific levels of pain should be reflected in the stage and progression of exercises or activities. The purpose of this review is to study the effect of differentiation of exercise guidance based on the level of LBP
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Deru, Landon, John Jakicic, and John Thyfault. "447 Effectiveness of the addition of yoga to a behavioral weight loss intervention on measures of glycemic control for adults with overweight or obesity (MOVE for Health Study): A methods description." Journal of Clinical and Translational Science 9, s1 (2025): 132. https://doi.org/10.1017/cts.2024.1044.

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Objectives/Goals: * Examination of the acute glucose-lowering response to physical activity within a comprehensive behavioral weight loss intervention in adults without T2DM. * Explore whether the acute response to yogadiffers from the acute response to brisk walking and to examine whether these responses vary across the intervention period. Methods/Study Population: Participants in the behavioral weight loss and aerobic exercise group will start with 100 minutes per week of moderate-intensity aerobic activity, increasing every four weeks to 250–300 minutes, spread over five days. Activities w
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Shukla, Parag Sunil, and Mayank Mathur. "Conceptualizing the Role of Data Analytics and Technology in E-Governance." International Journal of Business Analytics 7, no. 2 (2020): 1–12. http://dx.doi.org/10.4018/ijban.2020040101.

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Big Data in the current context is an asset for any government body as it helps in efficient and effective governance with the help of technology so as to create and build a citizen centric approach. As digitization has become an integral part of everyday life, data collection has resulted in the accumulation of huge amounts of data that can be used in various beneficial application domains. Effective analysis and utilization of big data is a key factor for success in many business and service domains. The Government of India initiated a Big Data exercise by collecting data in various forms, n
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Nikitkov, Alexey. "Budget Variance Analysis Case: Contrasting Excel with Tableau*." Accounting Perspectives 23, no. 4 (2024): 605–12. https://doi.org/10.1111/1911-3838.12383.

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ABSTRACTThis case not only familiarizes students with data analytics but also demonstrates its practical application. It presents a scenario of an electronic components company, equips students with budgetary and financial performance information, and challenges them to prepare a visual budgetary variance analysis for a board meeting. This hands‐on exercise, conducted first in Excel and then in Tableau, enhances students' analytics skills. The learning tasks include creating formulas that depend on multiple worksheets in Excel, interpreting data results, and importing data into Tableau. Studen
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İbişağaoğlu, Duru. "Integrating Virtual Reality and AI for Enhanced Patient Rehabilitation." Next Frontier For Life Sciences and AI 8, no. 1 (2024): 119. http://dx.doi.org/10.62802/3eas9534.

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The integration of virtual reality (VR) and artificial intelligence (AI) is revolutionizing patient rehabilitation by creating immersive, adaptive, and highly personalized therapeutic environments. By combining the interactivity of VR with the analytical capabilities of AI, rehabilitation programs can be tailored to individual patient needs, promoting faster recovery and greater engagement. This interdisciplinary approach enables real-time tracking of patient progress, adaptive exercise regimens, and predictive analytics for outcome optimization. The use of AI-driven algorithms to analyze biom
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Pizzuti, Carol, Cristiana Palmieri, and Tim Shaw. "Using eHealth Data to Inform CPD for Medical Practitioners: A Scoping Review with a Consultation Exercise with International Experts." Journal of Continuing Education in the Health Professions 43, no. 4S (2023): S47—S58. http://dx.doi.org/10.1097/ceh.0000000000000534.

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Introduction: eHealth data analytics is widely used in health care research. However, there is limited knowledge on the role of eHealth data analysis to inform continuing professional development (CPD). The aim of this study was to collate available research evidence on the use of eHealth data for the development of CPD programs and plans for medical practitioners. Methods: A scoping review was conducted using the six-stage Arksey and O'Malley Framework. A consultation exercise (stage 6) was performed with 15 international experts in the fields of learning and practice analytics to deepen the
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Andrade, Luana Machado, Edite Lago da Silva Sena, and Isabel Silva de Jesus. "The experience of others and becoming a senior citizen." Revista Gaúcha de Enfermagem 35, no. 2 (2014): 14–19. http://dx.doi.org/10.1590/1983-1447.2014.02.41792.

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The study aims to describe the perception of seniors on the exercise of citizenship in the light of the thought of Maurice Merleau-Ponty, based on the notion of the sexed body and the other's body. Discloses was from the participation of 13 elderly, members of acquaintance groups in the city of Jequié/BA, which produced experiential descriptions in three focus group meetings, during the month of April in 2012. Such descriptions were submitted to ambiguity analytics, a technique that consists in suspending the theories and notice the ambiguities inherent in them. From this analysis, two categor
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Zdenka, Cumano, and Sharma Bharti. "Empowering Supply Chain Analytics during the Post-Pandemic Recovery using Power BI." Journal of Management Science and Business Intelligence 7, no. 2 (2022): 1–6. https://doi.org/10.5281/zenodo.7241847.

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The post-pandemic world has exposed companies' various weaknesses in the supply chain strategy, such as product shortages, loss of revenue, high transportation costs, reputational damage, and increased competitive pressures. These manufacturing and logistical constraints have necessitated an expedited manner to generate a visualization dashboard to allow supply chain management executives to exercise rapid, more accurate, and agile decision-making. The utilization of a business intelligence tool such as Microsoft Power BI increases with industries compared to the conventional data analysis
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Rakesh, Anju, and Nisha Chandran. "The Promise of Diversity, Equity and Inclusion in 2021 and Beyond." NHRD Network Journal 14, no. 3 (2021): 314–16. http://dx.doi.org/10.1177/26314541211030590.

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We are living through a very volatile period—one induced and disrupted by the Covid-19 pandemic. Businesses world over have recalibrated (and continue to recalibrate) their systems, processes and protocols to suit the new normal(s). How are progressive organisations approaching diversity, equity and inclusion? What are the promises of this universal talent management dimension of diversity, equity and inclusion (DEI)? This article is an exploration of what DEI holds for the future of organisations, drawing insights from corporate India’s largest diversity analytics exercise—Working Mother and
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Aswati, Aswati, and Dina Erpiana. "PENINGKATAN KENYAMANAN IBU HAMIL TRIMESTER III DENGAN SENAM HAMIL BERBASIS KELUARGA." Jurnal Ilmiah STIKES Yarsi Mataram 12, no. 1 (2022): 1–7. http://dx.doi.org/10.57267/jisym.v12i1.151.

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quality of comfort in pregnant women is very important for the health of the mother and fetus. The cause of the disorder of comfort of pregnant women because, his large stomach, causing the mother to get tired quickly, because caused by the posture that has changed, pregnant women also experience frequent awakening at night to urinate. To overcome this, pregnant gymnastics is done to increase the comfort of pregnant women. Purpose: This study is to describe family nursing care with Efforts to Improve Comfort of Pregnant Women Trimester III. Method: This research is descriptive of analytics wit
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Darwis, A. Muflihah. "Determinant Of Premenstrual Syndrome Complaints On Women Workers." Asian Journal of Healthy and Science 2, no. 5 (2023): 205–12. http://dx.doi.org/10.58631/ajhs.v2i5.49.

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Pre-Menstrual Syndrome (PMS) complaints occur in women with different complaints and causes. This research aimed to determine the determinants of Pre-Menstrual Syndrome complaints in women workers in Makassar City. This type of research is analytics observational, with 203 women workers as a sample that was obtained through the purposive sampling technique. The research was conducted in Makassar City by distributing online questionnaires. This study showed that as many as 188 respondents (92.60%) had experienced PMS complaints with determinants of marital status, exercise, depression, consumpt
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Mansha, Muhammad, Xiuyun Yang, Ahmed Raza Ul Mustafa, and Muhammad Mubashar Nasim. "Empirical Analytics of SAARC vs ASEAN in Perspective of Economic Growth and Capital Accumulation." iRASD Journal of Economics 4, no. 2 (2022): 337–51. http://dx.doi.org/10.52131/joe.2022.0402.0083.

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It is an empirical exercise to build the connection between investment in human/ physical capital and economic growth. A panel data set is targeted by considering twelve selected SAARC and ASEAN economies for the period 2005-2019. To get the empirical findings a unit root analysis is made for data stationarity; the Fully Modified Ordinary Least Square (FMOLS) method is taken in practice to find the association of the investment in human/physical capital with economic growth. Moreover, the Pedroni test is used to examine cointegration among the regressors as well as explained variables. The res
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Dharangutte, Prathamesh, Jie Gao, Elinor Schoenfeld, Zongxing Xie, Yindong Hua, and Fan Ye. "DATA ANALYTICS FOR HEALTH-RELEVANT EVENTS DETECTION BASED UPON LONGITUDINAL FITBIT HEART RATE DATA." Innovation in Aging 7, Supplement_1 (2023): 873. http://dx.doi.org/10.1093/geroni/igad104.2810.

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Abstract The increasing prevalence of wearable devices enables low-cost, long-term collection of health relevant data such as heart rate, exercise, and sleep signals. Currently these data are used to monitor short term changes with limited interpretation of their relevance to health. These data provide an untapped resource to monitor daily and long-term activity patterns. Changes and trends identified from such data can provide insights and guidance to the management of many chronic conditions that change over time. In this study we conducted a machine learning based analysis of longitudinal h
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Geldiev, Ertan Mustafa, Nayden Valkov Nenkov, and Mariana Mateeva Petrova. "EXERCISE OF MACHINE LEARNING USING SOME PYTHON TOOLS AND TECHNIQUES." CBU International Conference Proceedings 6 (September 25, 2018): 1062–70. http://dx.doi.org/10.12955/cbup.v6.1295.

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One of the goals of predictive analytics training using Python tools is to create a "Model" from classified examples that classifies new examples from a Dataset. The purpose of different strategies and experiments is to create a more accurate prediction model. The goals we set out in the study are to achieve successive steps to find an accurate model for a dataset and preserving it for its subsequent use using the python instruments. Once we have found the right model, we save it and load it later, to classify if we have "phishing" in our case. In the case that the path we reach to the discove
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Thraen-Borowski, Keith M., Sarah Weller, and Ciaran Fairman. "The Exercise Oncology Twitter Conference: Disseminating Research in the Age of Social Media." Journal of Clinical Exercise Physiology 9, no. 1 (2020): 40–42. http://dx.doi.org/10.31189/2165-6193-9.1.40.

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ABSTRACT Background: Scientists are using social media to amplify their scientific impact. As such, researchers are looking for novel ways to engage this medium to promote scientific findings and communicate research to a broader audience. Here, we examine the use of a Twitter conference as a means to effectively communicate advances in the field of exercise oncology. Methods: The Exercise Oncology Twitter Conference (ExOncTC) occurred in October 2018. Each presentation consisted of 6 tweets over 15 min. Attendees were able to interact during a presentation via the conference hashtag (#ExOncTC
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Yan, Grace, Dustin Steller, Nicholas M. Watanabe, and Nels Popp. "What Determines User-Generated Content Creation of College Football? A Big-Data Analysis of Structural Influences." International Journal of Sport Communication 11, no. 2 (2018): 219–40. http://dx.doi.org/10.1123/ijsc.2017-0113.

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The question of how and why users engage in sport digital communication endures. In this study, structuration theory is employed to examine how social-media users exercise preferences in the creation of content as they respond to a variety of macrolevel factors pertaining to college football—the type of game, team strength, conference membership, market characteristics, etc. Through hierarchical regression analysis, the results indicate that the presence and timing of college football games, as well as team strength and game outcome, are significant determinants for the patterns of online cont
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Sundari M, Rama, Sai Sreeman Reddy Puchakayala, Kishan Naga Datta Samayamantry, et al. "Smart fitness trainer using an advanced interdisciplinary approach." E3S Web of Conferences 507 (2024): 01043. http://dx.doi.org/10.1051/e3sconf/202450701043.

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The Smart Fitness Trainer represents a pioneering endeavor at the intersection of diverse disciplines, amalgamating computer vision and Internet of Things (IoT) technologies. Its primary objective is to redefine the fitness landscape by introducing real-time exercise form analysis and assistance. Through the fusion of biomechanics, human-computer interaction, and data analytics, this innovative system provides instantaneous visual feedback via a mirror interface, thereby augmenting safety and efficacy during workout sessions. Embracing sophisticated interdisciplinary methodologies, the Smart F
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Ullah, Hidayat, Alaa Ali Hameed, Sanam Shahla Rizvi, Akhtar Jamil, and Se Jin Kwon. "Understanding the User-Generated Geographic Information by Utilizing Big Data Analytics for Health Care." Computational Intelligence and Neuroscience 2022 (October 6, 2022): 1–14. http://dx.doi.org/10.1155/2022/2532580.

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There are two main ways to achieve an active lifestyle, the first is to make an effort to exercise and second is to have the activity as part of your daily routine. The study’s major purpose is to examine the influence of various kinds of physical engagements on density dispersion of participants in Shanghai, China, and even prototype check-in data from a Location-Based Social Network (LBSN) utilizing a mix of spatial, temporal, and visualization methodologies. This paper evaluates Weibo used for big data evaluation and its dependability in some types rather than physically collected proofs by
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Zhang, Yongpeng. "Realizing smart elderly care through exercise and biosensing: Innovative methods for health monitoring and promotion." Molecular & Cellular Biomechanics 22, no. 5 (2025): 1567. https://doi.org/10.62617/mcb1567.

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The incorporation of smart technology in elderly care is improving the way health is managed and promoted for the elderly populations. This paper examines a new elderly care model that employs biosensing and exercise-based solutions for effective care and monitoring of the elderly. An effective system is proposed to integrate various biosensors that can track vital signs like pulse rate, blood oxygen level, muscle activity, and balance, thus providing constant updates on the user’s well-being. To accomplish this, information is collected by advanced data analytics and machine learning algorith
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Carpenter, Chris. "Data-Analytics-Driven Sectorization Review Enables Efficient Reservoir Management." Journal of Petroleum Technology 76, no. 10 (2024): 94–97. http://dx.doi.org/10.2118/1024-0094-jpt.

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_ This article, written by JPT Technology Editor Chris Carpenter, contains highlights of paper SPE 216359, “Data-Analytics-Driven Subsurface Reservoir Sectorization Review of a Giant Abu Dhabi Onshore Field Carbonate Reservoir for Efficient Reservoir Management,” by Khalid Javid, Sara Alshkeili, and Fatema Al-Hammadi, ADNOC, et al. The paper has not been peer reviewed. _ The complete paper discusses an approach used to sectorize a mature onshore Abu Dhabi giant carbonate reservoir for the purposes of reservoir management, offtake, and injection balancing. The reservoir is developed under a lin
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Milne, Dana, Joanna M. Hamilton, Debra McNeil, et al. "Everyone needs robust analytics: Integrating medical ontologies into the Dana-Farber Pathways." Journal of Clinical Oncology 37, no. 27_suppl (2019): 304. http://dx.doi.org/10.1200/jco.2019.37.27_suppl.304.

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304 Background: The majority of clinical data is unstructured. Medical ontologies standardize the language used to communicate diagnoses, symptoms, and procedures used in healthcare. Incorporating medical ontologies into the Dana-Farber Pathways (DFP) provides structure and removes ambiguity by creating definitions for each data point. This exercise was critical for the development of the DFP into a fully automated platform that optimizes clinician workflow, reduces clicks, and expands the potential for data analysis. Methods: The DFP data model was reviewed to identify value sets contained in
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