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Modified Usability Framework for Disaster Apps:A Qualitative Thematic Analysis of User Reviews

International Journal of Disaster Risk Science 2020年第5期11卷 615-629页

作者： Marion Lara Tan raj prasanna Kristin Stock Emma EHDoyle Graham Leonard David Johnston Joint Centre for Disaster Research Massey UniversityWellington 6021New Zealand School of Natural and Computational Sciences Massey UniversityAlbany 0632New Zealand GNS Science AvalonLower Hutt 5010New Zealand

The public has access to a range of mobile applications(apps)for ***,there has been limited academic research conducted on disaster apps and how the public perceives their *** study explores end-users'perceptions of the usability of disaster *** proposes a conceptual framework based on insights gathered from thematically analyzing online *** study identifies new usability concerns particular to disaster apps'use:(1)content relevance depends on the app's purpose and the proximate significance of the information to the hazard event's time and location;(2)app dependability affects users'perceptions of usability due to the lifesafety association of disaster apps;(3)users perceive advertisements to contribute to their cognitive load;(4)users expect apps to work efficiently without unnecessary consumption of critical phone resources;(5)appropriate audio interface can improve usability,as sounds can boost an app's alerting aspect;and,finally(6)in-app browsing may potentially enhance users'impression of the structure of a disaster *** a result,this study argues for focussed research and development on public-facing disaster *** research should consider the conceptual framework and concerns presented in this study when building design guidelines and theories for disaster apps.

关键词： Disaster apps End-user perspective Human-computer interaction Usability

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An Approach to Parallelization of SIFT Algorithm on GPUs for Real-Time Applications

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Journal of Computer and Communications 2016年第17期4卷 18-50页

作者： Raghu raj prasanna Kumar Suresh Muknahallipatna John McInroy Department of Electrical Engineering University of Wyoming Laramie USA

Scale Invariant Feature Transform (SIFT) algorithm is a widely used computer vision algorithm that detects and extracts local feature descriptors from images. SIFT is computationally intensive, making it infeasible for single threaded im-plementation to extract local feature descriptors for high-resolution images in real time. In this paper, an approach to parallelization of the SIFT algorithm is demonstrated using NVIDIA’s Graphics Processing Unit (GPU). The parallel-ization design for SIFT on GPUs is divided into two stages, a) Algorithm de-sign-generic design strategies which focuses on data and b) Implementation de-sign-architecture specific design strategies which focuses on optimally using GPU resources for maximum occupancy. Increasing memory latency hiding, eliminating branches and data blocking achieve a significant decrease in aver-age computational time. Furthermore, it is observed via Paraver tools that our approach to parallelization while optimizing for maximum occupancy allows GPU to execute memory bound SIFT algorithm at optimal levels.

关键词： Scale Invariant Feature Transform (SIFT) Parallel Computing GPU GPU Occupancy Portable Parallel Programming CUDA

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The Impact of Body Mass Index on Assisted Reproductive Treatments

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Open Journal of Obstetrics and Gynecology 2017年第5期7卷 562-570页

作者： prasanna raj Supramaniam Monica Mittal Lee Nai Lim Department of Women and Children Milton Keynes University Hospital Milton Keynes UK Department of Women and Children Oxford University Hospitals NHS Foundation Trust Oxford UK

Multiparity amongst women with a body mass index (BMI) ≥ 30 Kg/m2 is a common occurrence despite there being a known clear association with a decline in fecundity in women who are overweight or obese. These women, also pose further concerns, as they are at increased risk of antenatal complications such as preeclampsia and gestational diabetes. Over the years, a number of different modalities of fertility treatments have been tried and tested in this cohort of women to find the optimal treatment to improve their reproductive capacity. There has been an exponential increase in knowledge and understanding towards managing patients with a raised BMI, particularly through assisted reproductive treatments. Although the efficacies of various forms of fertility treatments have been shown to be affected by a rise in BMI, there is yet to be a definitive understanding as to the optimal management of these patients. The literature supports weight loss alone as an effective intervention in improving the reproductive capacity of women with a raised BMI with unexplained infertility. Furthermore, if live birth rate is taken as the desired outcome measure, then ovarian drilling and in vitro fertilisation (IVF) treatment have been shown to yield the best results in overweight and obese patients when comparisons are drawn to other interventions such as natural conception and treatment with clomiphene citrate.

关键词： Assisted Reproductive Treatments Body Mass Index Live Birth Rate Overweight Obesity

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Real-Time Range of Motion Measurement of Physical Therapeutic Exercises

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Journal of Computer and Communications 2017年第9期5卷 19-42页

作者： Raghu raj prasanna Kumar Suresh Muknahallipatna John McInroy Mark McKenna Lori Franc National Center for Atmospheric Research Boulder CO USA Dept. of Electrical Engineering University of Wyoming Laramie WY USA Premier Bone & Joint Centers Laramie WY USA

Physical therapeutic exercise (PTE) is the planned process of performing bodily movements, postures, or physical activities to provide a patient with the ability to remediate or prevent impairments at a minimum. The efficacy of the PTE involves measuring accurately the range of motion (ROM) of joint functions and parameters that indicate the onset of fatigue, jerky motion, and muscle/joint resistance to the PTE. A physical therapist (PT) typically determines the efficacy of a PTE by measuring joint angles in clinical diagnosis to assess the ROM using the simple device Goniometer since motion capture systems are generally expensive, difficult to use, and currently not suited for real-time operations. The joint angle measurement using Goniometer suffers from low accuracy, low reliability and subjective. Furthermore, a patient when performing PTE by themselves at remote locations like their home or community centers cannot use a Goniometer to determine the efficacy. In this study, we present the approach of using an inexpensive, simple human motion capture system (HMCS) consisting of a single camera and a graphical processing unit (GPU) to perform the efficacy of the PTE in real-time. The approach involves the use of general purpose graphic processing unit (GPGPU) computer vision technique to track and record human motion and relate the tracked human motion to the prescribed physical therapy regimen in real-time. We have developed a tracking algorithm derived from the Klein’s algorithm known as the Modified Klein’s algorithm (MKA) capable of tracking human body parts while the original Klein’s algorithm was only capable of tracking objects with sharp edges. The MKA algorithm is further modified for parallel execution on a GPU to operate in real-time. Using the GPU, we are able to track multiple markers in a high definition (HD) frame of the HD video in 1.77 msecs achieving near real-time capability of ROM measurements. Furthermore, the error in the ROM measurements in

关键词： Computer vision Therapeutic Exercise GPU Parallel Programming

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