We propose a novel color image arrangement method using an elastic transform based on histogram matching on some kinds of axes. The axes include the lightness axis and Principal Component (PC) axes obtained from Principal Component Analysis (PCA) in the RGB three-dimensional vector space that is an attribute space of color image. In this paper, we mainly present the principle of its automated color arrangement method especially based on Histogram Matching based on Gaussian Distribution (HMGD). Then, in order to detect the single-peak of histogram, we propose the method based on the curvature computation for the cumulative histogram. Furthermore, we conducted a questionnaire survey in order to investigate compare the changes in the feeling impression at the time of performing between Histogram Equalization (HE) processing and HMGD processing. As the result, we verify that where we perform HMGD processing to the images which have single-peak-histogram the feeling impression of images are improved.

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Various vocal sounds are generated by the complex articulations of human vocal organs under the feedback control mechanisms using the auditory system. By reconstructing a human vocal system mechanically, the authors have developed a talking robot based on the physical models of vocal organs. The robotic system consists of motor-controlled vocal organs such as vocal cords, a vocal tract, a nasal cavity and an auditory system to generate a natural voice imitating a human vocalization. By introducing an auditory feedback learning of the mechanical systems, the robot is able to autonomously reproduce a human-like vocal articulation using its vocal organs to generate human-like vocal sounds. In vocalization, the vibration of vocal cords generates a source sound, and then the sound wave is led to a vocal tract, which works as a resonance filter to determine the spectrum envelope. For the autonomous acquisition of the robot's vocal articulation skills, the resonance characteristics given by the articulatory motions are adaptively acquired by the auditory feedback control. In this study, a human-like expressive speech production by the talking robot is introduced for the vocal communication with a human. A human generates speech by controlling their own vocal organs for changing the speech expressions such as the volume and the intonations. To realize the human-like expressive speech, a suitable control method for the mechanical organs has to be established. In the first part of the paper, the construction of the talking robot and the autonomous acquisition of the vocalization using a self-organizing map will be described, and then the articulatory motions for producing human-like speech with various expressions will be introduced for realizing expressive speech communication with a human.

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Numerical simulations were performed using super-resolution images and barrel-distorted images to improve the viability of the authors' previous work regarding single-view-based ear biometrics. Empirical demonstrations show that, using barrel-distorted images and super-resolution images, accuracy decreases. However, our present proposed method for model normal vector creation applied to these images compensated for losses in accuracy. Furthermore, an experimental investigation of the influence of earrings on results is included. The difference between the averaged rank between images of subjects with and without earrings at each input angle was found to be statistically insignificant.

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The purpose of this study is to evaluate sleep comfort of bed mattresses with different elastic moduli for each body region by measuring physiological and psychological responses. We measured the blood flow of the biceps femoris using near-infrared spectroscopy (NIRS) from the viewpoint of hemodynamics and shape of the back in a supine posture when a person is lying on mattresses with different elastic moduli for each body region. Conventional sleep evaluations were performed to record physiological responses during sleep by polysomnographs (PSG) and actigraphs. Psychological responses during sleep were also evaluated by using the profile of mood states (POMS) test. The results from NIRS revealed that intramuscular metabolic reaction is different according to the sleep posture. Sleep evaluations by PSG and actigraphs showed no significant differences between these mattresses, whereas significant differences were found in the POMS test between some of them. We surmised that difference in hemodynamics is one of the factors in sleep comfort that changes the mood after getting up.

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Apparel is the single largest export commodity in Sri Lanka. Over the recent years, the country has become the high-end producer for some of the world's top fashionable brands, where design and low cost manufacturing play key roles when it comes to marketing. This paper looks at how Kansei Engineering can be introduced for Sri Lankan apparel designers. The application of Kansei Engineering in mass production of apparel is done in two steps. First, the consumer's preferences or Kansei are segmented by conducting a survey and applying cluster analysis. In the second step, the orders from different brand marketers are aggregated in a way to optimize the mass production by applying Kansei preference model. An example shows how seven large orders from four brand marketers are categorized in to two segments by using a metric based on cluster centroid.

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Some cameras, especially in the case of assembling line-sensor 3CCD cameras, may generate non-suitable images which include phenomena called “pixel shifts.” This paper describes such a phenomenon, its numerical analysis and comparison between professional determination and machine detection. If there is such a pixel shift in the image, a user of camera may be suffering from a lack of precision of the image to be measured or utilized for image understanding. In a conventional approach of manufacturing line-sensor 3CCD cameras, some specialists have determined whether phenomena of pixel shifts occurs or not in the image. They have reported performance evaluation for the relevant camera which monitors the image before shipping camera. We had already proposed a numerical method to detect occurrence of pixel shift in the image with Lagrange interpolation function, calculated the values of the level for occurrence of pixel shift quantitatively. In the previously comparison, our calculated results had been perfectly consistent with determination by some specialist. And moreover, we have applied our approach into another kind sets of 20 samples of camera-monitored image and compared determination by another specialist with our corresponding results. By means of Kansei evaluation of human sensitivity, we have discriminated difference of specialist's determination and our numerical approach.

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Erratum
International Journal of Affective Engineering, Vol. 14 (2015) No. 2 Special Issue on 2013 ICBAKE, Part 2 p. 85-93

Author's Affiliation
Incorrect: *** Taiwan National University of Arts, 66 Daci-village, Guantian-district, Tainan 72045, Taiwan
Correct: *** Tainan National University of the Arts, 66 Daci-village, Guantian-district, Tainan 72045, Taiwan

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