Article
Computer Science, Cybernetics
Nesrine Mezhoudi, Jean Vanderdonckt
Summary: This paper discusses the proposal of TADAP for achieving runtime adaptive UI through user feedback and machine learning, which allows for cross-cutting impact of adaptation, taking into account user preferences and real-time context.
INTERNATIONAL JOURNAL OF HUMAN-COMPUTER INTERACTION
(2021)
Article
Engineering, Environmental
Yike Shen, Marianthi-Anna Kioumourtzoglou, Haotian Wu, Pantel Vokonas, Avron Spiro III, Ana Navas-Acien, Andrea A. Baccarelli, Feng Gao
Summary: Contemporary environmental health sciences rely on large-scale longitudinal studies to uncover the impact of environmental exposures and behavior factors on disease risk and underlying mechanisms. However, the publications from these studies are often not well-organized or summarized, hampering knowledge dissemination. To address this issue, a Cohort Network is proposed, utilizing a multilayer knowledge graph approach to extract and visualize the connections between exposures, outcomes, and publications. The Cohort Network was applied to 121 peer-reviewed papers from the Veterans Affairs Normative Aging Study, revealing important associations and potential mediators in environmental health research. This approach facilitates knowledge-driven discovery and dissemination in cohort studies with rich information on environmental exposures and health outcomes.
ENVIRONMENTAL SCIENCE & TECHNOLOGY
(2023)
Review
Automation & Control Systems
Uichin Lee, Gyuwon Jung, Eun-Yeol Ma, Jin San Kim, Heepyung Kim, Jumabek Alikhanov, Youngtae Noh, Heeyoung Kim
Summary: With the rise of digital therapeutics, the development of software as a medical device for mobile and wearable devices has become increasingly important. Current evaluations of digital therapeutics primarily focus on effectiveness, but to gain a deeper understanding of engagement and adherence, analysis of contextual and interaction data from these devices is necessary. This review of data-driven analytics provides researchers and practitioners with guidance on exploring and analyzing digital therapeutic datasets, examining contextual patterns, and establishing the relationship between engagement and adherence.
IEEE-CAA JOURNAL OF AUTOMATICA SINICA
(2023)
Article
Robotics
Sang-Ho Hyon, Kazuto Akama
Summary: This research introduces a novel pneumatically controlled hydraulic booster, suitable for water-hydraulic robots, which can easily control water pressure using pneumatic proportional valves and has been applied to underwater robots, demonstrating the potential of the system through experiments.
IEEE ROBOTICS AND AUTOMATION LETTERS
(2021)
Article
Automation & Control Systems
Min-Cheol Kim, Hongseok Choi, Jinlong Piao, Eui-sun Kim, Jong-Oh Park, Chang-Sei Kim
Summary: This article presents a method for remotely manipulating a peg-in-hole task using a cable-driven parallel robot. The study proposes a novel teleoperation approach that allows for fine manipulation in wide workspaces. The results demonstrate the effectiveness of the proposed method in achieving remote fine manipulation with visual feedback and wrench force feeling control.
IEEE-ASME TRANSACTIONS ON MECHATRONICS
(2022)
Article
Automation & Control Systems
Min-Cheol Kim, Hongseok Choi, Jinlong Piao, Eui-sun Kim, Jong-Oh Park, Chang-Sei Kim
Summary: This study developed a novel method for remote fine manipulation using CDPR configurations and an interactive haptic control scheme, successfully completing a remote peg-in-hole task with reduced force and torque requirements.
IEEE-ASME TRANSACTIONS ON MECHATRONICS
(2022)
Review
Agriculture, Dairy & Animal Science
M. van der Voort, D. Jensen, C. Kamphuis, I. N. Athanasiadis, A. De Vries, H. Hogeveen
Summary: Sensor technologies have led to a wealth of data on mastitis detection, with scientific publications increasingly focused on data-driven modeling. Researchers use a variety of methods for classifying and processing data, resulting in confusion for readers from different disciplines.
JOURNAL OF DAIRY SCIENCE
(2021)
Article
Chemistry, Multidisciplinary
Martin Francis Phelan, Mehmet Efe Tiryaki, Jelena Lazovic, Hunter Gilbert, Metin Sitti
Summary: A novel design of MRI-driven microcatheter was proposed in this study, achieving miniaturization and reduced power consumption through optimized control strategies. The implementation of a quad-configuration microcoil design demonstrated improved tip motion control and conservation of power during catheter operations.
Article
Computer Science, Hardware & Architecture
Raphael Silva de Abreu, Douglas Mattos, Joel dos Santos, Gheorghita Ghinea, Debora Christina Muchaluat-Saade
Summary: This article presents a new method for semiautomatic definition of sensory effects in authoring tools, using software components to assist in indicating activation moments of sensory effects according to author preferences. This method is expected to considerably reduce the effort of synchronizing audiovisual content with sensory effects, particularly by easing the author's repetitive task of synchronizing recurring effects with lengthy media.
Article
Computer Science, Software Engineering
Lorenzo Amabili, Kuhu Gupta, Renata Georgia Raidou
Summary: The paper introduces a dual model for designing educational games in visualization based on constructivism and learning-by-playing. Two games are designed: one is based on deconstruction, while the other is based on construction, using the same deck of cards with a design based on popular visualization taxonomies in teaching.
IEEE COMPUTER GRAPHICS AND APPLICATIONS
(2021)
Article
Computer Science, Theory & Methods
Ronan-Alexandre Cherrueau, Marie Delavergne, Alexandre van Kempen, Adrien Lebre, Dimitri Pertin, Javier Rojas Balderrama, Anthony Simonet, Matthieu Simonin
Summary: Despite the importance of experiment-driven research in distributed computing, researchers still face challenges in conducting their experiments efficiently. To address this issue, we have developed EnosLib, a Python library that incorporates best experimentation practices and utilizes modern toolkits to automate deployment and configuration. EnosLib helps researchers in both the development and execution of experimental artifacts across different infrastructures.
IEEE TRANSACTIONS ON PARALLEL AND DISTRIBUTED SYSTEMS
(2022)
Article
Public, Environmental & Occupational Health
Amy Lansky, Holly R. Wethington, Kelly Mattick, Marshall H. Chin, Anita Alston, Julie Racine-Parshall, Sophia L. Minor, Jamaicia Cobb, David P. Hopkins
Summary: This article describes the process and results of selecting priority topics to guide the work of the Community Preventive Services Task Force from 2020 to 2025. The task force started with Healthy People 2020 topics, solicited input from partner organizations and the public, and considered 8 criteria for each topic. After voting and applying decision rules, a total of 9 topics were selected as priorities.
AMERICAN JOURNAL OF PREVENTIVE MEDICINE
(2022)
Review
Endocrinology & Metabolism
Eleonora Molinaro, Maria Cristina Campopiano, Rossella Elisei
Summary: This review examines the various experiences of active surveillance in patients with papillary microcarcinomas and highlights the potential obstacles in implementing it as a routine approach.
EUROPEAN JOURNAL OF ENDOCRINOLOGY
(2021)
Article
Education & Educational Research
Marie K. Heath, Benjamin Gleason, Rohit Mehta, Ted Hall
Summary: The predominance of western paradigms and failure to consider the non-neutrality of schools and technology limits educational technology studies. This narrow approach restricts research on power, collective, and technology intersections, hindering the field's imagination and potential. To address this, three new research frames – Collective Framing, Critical Race Theory (CRT) Framing, and Ecological Framing – are proposed to explore different epistemological, ontological, and axiological approaches in educational technology research. This paper emphasizes the importance of confronting hegemonic western paradigms embedded within the field.
ETR&D-EDUCATIONAL TECHNOLOGY RESEARCH AND DEVELOPMENT
(2023)
Article
Public, Environmental & Occupational Health
Leah Tuzzio, Ellen S. O'Meara, Erika Holden, Michael L. Parchman, James D. Ralston, Jennifer A. Powell, Laura-Mae Baldwin
Summary: This study identified barriers to the implementation of cardiovascular disease risk calculators in primary care, including time constraints, limitations in accessing necessary information for using the calculator, lack of buy-in from clinicians or staff, patient fear of statin medications, and absence of documented clinic workflow for using the calculator. Future research should consider tailoring interventions to address these common barriers in order to improve uptake of cardiovascular disease risk calculation.
AMERICAN JOURNAL OF PREVENTIVE MEDICINE
(2021)
