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Browsing by Author "Mitropoulos-Rundus, David"

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    Checklist for Expert Evaluation of HMIs of Automated Vehicles—Discussions on Its Value and Adaptions of the Method within an Expert Workshop
    Schömig, Nadja; Wiedemann, Katharina; Hergeth, Sebastian; Forster, Yannick; Muttart, Jeffrey; Eriksson, Alexander; Mitropoulos-Rundus, David; Grove, Kevin; Krems, Josef; Keinath, Andreas; Neukum, Alexandra; Naujoks, Frederik (MDPI, 2020-04-24)
    Within a workshop on evaluation methods for automated vehicles (AVs) at the Driving Assessment 2019 symposium in Santa Fe; New Mexico, a heuristic evaluation methodology that aims at supporting the development of human–machine interfaces (HMIs) for AVs was presented. The goal of the workshop was to bring together members of the human factors community to discuss the method and to further promote the development of HMI guidelines and assessment methods for the design of HMIs of automated driving systems (ADSs). The workshop included hands-on experience of rented series production partially automated vehicles, the application of the heuristic assessment method using a checklist, and intensive discussions about possible revisions of the checklist and the method itself. The aim of the paper is to summarize the results of the workshop, which will be used to further improve the checklist method and make the process available to the scientific community. The participants all had previous experience in HMI design of driver assistance systems, as well as development and evaluation methods. They brought valuable ideas into the discussion with regard to the overall value of the tool against the background of the intended application, concrete improvements of the checklist (e.g., categorization of items; checklist items that are currently perceived as missing or redundant in the checklist), when in the design process the tool should be applied, and improvements for the usability of the checklist.
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    The evaluation of chest images compressed with JPEG and wavelet techniques
    Wen, Cathlyn Y. (Virginia Tech, 1996)
    Image compression reduces the amount of space necessary to store digital images and allows quick transmission of images to other hospitals, departments, or clinics. However, the degradation of image quality due to compression may not be acceptable to radiologists or it may affect diagnostic results. A preliminary study was conducted using several chest images with common lung diseases and compressed with JPEG and wavelet techniques at various ratios. Twelve board-certified radiologists were recruited to perform two types of experiments. In the first part of the experiment, presence of lung disease, confidence of presence of lung disease, severity of lung disease, confidence of severity of lung disease, and difficulty of making a diagnosis were rated by radiologists. The six images presented were either uncompressed or compressed at 32:1 or 48:1 compression ratios. In the second part of the experiment, radiologists were asked to make subjective ratings by comparing the image quality of the uncompressed version of an image with the compressed version of the same image, and judging the acceptability of the compressed image for diagnosis. The second part examined a finer range of compression ratios (8:1, 16:1, 24:1, 32:1, 44:1, and 48:1). In all cases, radiologists were able to judge the presence of lung disease and experienced little difficulty diagnosing the images. Image degradation perceptibility increased as the compression ratio increased; however, among the levels of compression ratio tested, the quality of compressed images was judged to be only slightly worse than the original image. At higher compression ratios, JPEG images were judged to be less acceptable than wavelet-based images but radiologists believed that all the images were still acceptable for diagnosis. These results should be interpreted carefully because there were only six original images tested, but results indicate that compression ratios of up to 48:1 are acceptable using the two medically optimized compression methods, JPEG and wavelet techniques.