20,125 research outputs found

    A methodological framework for capturing relative eyetracking coordinate data to determine gaze patterns and fixations from two or more observers

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    While physical activity during cancer treatment is found beneficial for breast cancer patients, evidence indicates ambiguous findings concerning effects of scheduled exercise programs on treatment-related symptoms. This study investigated effects of a scheduled home-based exercise intervention in breast cancer patients during adjuvant chemotherapy, on cancer-related fatigue, physical fitness, and activity level. Sixty-seven women were randomized to an exercise intervention group (n=33, performed strength training 3x/week and 30 minutes brisk walking/day) and a control group (n=34, performed their regular physical activity level). Data collection was performed at baseline, at completion of chemotherapy (Post1), and 6-month postchemotherapy (Post2). Exercise levels were slightly higher in the scheduled exercise group than in the control group. In both groups, cancer-related fatigue increased at Post1 but returned to baseline at Post2. Physical fitness and activity levels decreased at Post1 but were significantly improved at Post2. Significant differences between intervention and control groups were not found. The findings suggest that generally recommended physical activity levels are enough to relief cancer-related fatigue and restore physical capacity in breast cancer patients during adjuvant chemotherapy, although one cannot rule out that results reflect diminishing treatment side effects over time

    Fourteenth Biennial Status Report: März 2017 - February 2019

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    Aerospace Medicine and Biology: A continuing bibliography with indexes, supplement 165, March 1977

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    This bibliography lists 198 reports, articles, and other documents introduced into the NASA scientific and technical information system in February 1977

    Optical techniques for 3D surface reconstruction in computer-assisted laparoscopic surgery

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    One of the main challenges for computer-assisted surgery (CAS) is to determine the intra-opera- tive morphology and motion of soft-tissues. This information is prerequisite to the registration of multi-modal patient-specific data for enhancing the surgeon’s navigation capabilites by observ- ing beyond exposed tissue surfaces and for providing intelligent control of robotic-assisted in- struments. In minimally invasive surgery (MIS), optical techniques are an increasingly attractive approach for in vivo 3D reconstruction of the soft-tissue surface geometry. This paper reviews the state-of-the-art methods for optical intra-operative 3D reconstruction in laparoscopic surgery and discusses the technical challenges and future perspectives towards clinical translation. With the recent paradigm shift of surgical practice towards MIS and new developments in 3D opti- cal imaging, this is a timely discussion about technologies that could facilitate complex CAS procedures in dynamic and deformable anatomical regions

    Towards a human eye behavior model by applying Data Mining Techniques on Gaze Information from IEC

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    In this paper, we firstly present what is Interactive Evolutionary Computation (IEC) and rapidly how we have combined this artificial intelligence technique with an eye-tracker for visual optimization. Next, in order to correctly parameterize our application, we present results from applying data mining techniques on gaze information coming from experiments conducted on about 80 human individuals

    Attention Allocation Aid for Visual Search

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    This paper outlines the development and testing of a novel, feedback-enabled attention allocation aid (AAAD), which uses real-time physiological data to improve human performance in a realistic sequential visual search task. Indeed, by optimizing over search duration, the aid improves efficiency, while preserving decision accuracy, as the operator identifies and classifies targets within simulated aerial imagery. Specifically, using experimental eye-tracking data and measurements about target detectability across the human visual field, we develop functional models of detection accuracy as a function of search time, number of eye movements, scan path, and image clutter. These models are then used by the AAAD in conjunction with real time eye position data to make probabilistic estimations of attained search accuracy and to recommend that the observer either move on to the next image or continue exploring the present image. An experimental evaluation in a scenario motivated from human supervisory control in surveillance missions confirms the benefits of the AAAD.Comment: To be presented at the ACM CHI conference in Denver, Colorado in May 201

    Opinion mining and sentiment analysis in marketing communications: a science mapping analysis in Web of Science (1998–2018)

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    Opinion mining and sentiment analysis has become ubiquitous in our society, with applications in online searching, computer vision, image understanding, artificial intelligence and marketing communications (MarCom). Within this context, opinion mining and sentiment analysis in marketing communications (OMSAMC) has a strong role in the development of the field by allowing us to understand whether people are satisfied or dissatisfied with our service or product in order to subsequently analyze the strengths and weaknesses of those consumer experiences. To the best of our knowledge, there is no science mapping analysis covering the research about opinion mining and sentiment analysis in the MarCom ecosystem. In this study, we perform a science mapping analysis on the OMSAMC research, in order to provide an overview of the scientific work during the last two decades in this interdisciplinary area and to show trends that could be the basis for future developments in the field. This study was carried out using VOSviewer, CitNetExplorer and InCites based on results from Web of Science (WoS). The results of this analysis show the evolution of the field, by highlighting the most notable authors, institutions, keywords, publications, countries, categories and journals.The research was funded by Programa Operativo FEDER Andalucía 2014‐2020, grant number “La reputación de las organizaciones en una sociedad digital. Elaboración de una Plataforma Inteligente para la Localización, Identificación y Clasificación de Influenciadores en los Medios Sociales Digitales (UMA18‐ FEDERJA‐148)” and The APC was funded by the same research gran
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