• 무역학회지
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• 제46권5호
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• pp.99-113
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• 2021

This study aims to analyze the effect of product information quality and source credibility on product arousal in fresh food website. Despite fresh food websites are selling products with various feature, prior studies have focused on consumer behavior for fresh food website characteristics or specific products without considering the feature of the products. Consumers' attitudes, beliefs, and behaviors vary depending on the feature of the product. In other words, depending on the category of product, the decision making process that consumers purchase products can be differ. So, we classify products considering the feature of these products to examine the effect of information quality and source credibility on product arousal into experience goods and search goods. We surveyed 288 consumers having experience of purchase in fresh food website and verified the hypothesis through One-way ANOVA by classifying the information quality and the source credibility as high level and low level. As a result, there was a difference in product arousal according to the product information quality level and the source credibility level for each product category exposed to the fresh food website. In experience goods, source credibility have a more important effect on product arousal than product information quality, and in search goods, product information quality have a more important effect on product arousal than source credibility.

• 음성과학
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• 제1권
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• pp.7-26
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• 1997

An electromyographic device was used to investigate the relationship between a linguistic hypothesis of tense-lax distinction and muscular activity. Muscle action potentials of the orbicularis oris muscle and the depressor anguli oris muscle were obtained from four subjects using CVCVCV and CVCVC words in English and VCV and CVC words in Korean. Findings: The hypothesis that the speaker may select at least one of muscles involved in the articulation of a phoneme so that the selected muscle could be activated for tense-lax distinction, and either a timing variable or an amplitude variablethe and/or both from the selected muscle distinguish(es) /p/ from /b/ in English and /$p^{h},\;p^{l}$/ from /p/ in Korean, with the English /p/ and the Korean /$p^{h},\;p^{l}$/ being tense, and the Korean unaspirated /p/ and the English /b/ lax, has been verified, except for the case with subject 2 in stressed syllables in English. (2) Thus, the linguistic hypothesis of tense-lax distinction was strongly supported by the muscular activities during the Korean bilabial stops, with /$p^{h}\;and\;p^{l}$/ being tense and /p/ lax. (3) Considering the intermuscle compensation and the interspeaker variabilities in the choice of a muscle or muscles, in English the usability of the feature 'tensity' appeared to be positive rather than negative although further investigations with more subjects remain to take on the muscles associated with the onset/offset of the labial closure, including the respiratory muscles related with the aspiration. The phoneme-sensitive EMG manifestations of stress and possible reasons for the interspeaker variabilities are discussed.

• 한국정보통신학회:학술대회논문집
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• 한국정보통신학회 2016년도 추계학술대회
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• pp.382-383
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• 2016

영상의 캐니 에지 검출은 영상의 가우시안 필터, 기울기(gradient)의 계산, 비최대억제법(Non-maximum suppression), 그리고 이력 임계값(Hypothesis Thresholding)의 4가지로 구성된다. 특징은 에지 영상에서 얻어진 차체, 창문들, 그리고 바퀴들 사이의 비율이 된다. 차량의 이러한 특징이 되는 비율들은 차종마다 각기 다르다. 우리는 여기서 소형 차량에만 본 알고리즘을 적용하여 식별하였다.

• 전기전자학회논문지
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• 제12권1호
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• pp.51-58
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• 2008

This paper presents a new method for building detection and reconstruction from aerial images. In our approach, we extract the useful building location information from the generated disparity map to obtain the segmentation of interested objects and thus reduce significantly unnecessary line segment extracted in low level feature extraction step. Hypothesis selection is carried out by using undirected graph in which close cycles represent complete rooftops hypotheses, and hypothesis are finally tested to contruct building model. We test the proposed method with synthetic images generated from Avenches dataset of Ascona aerial images. The experiment result shows that the extracted 3D line segments of the buildings can be efficiently used for the task of building detection and reconstruction from aerial images.

• 수면정신생리
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• 제9권2호
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• pp.100-105
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• 2002

Personality traits in insomniac patients have been a subject of many studies. A number of these studies have used the MMPI and have demonstrated elevated scores on several clinical scales reflecting somatic concerns, somatization, depression, anxiety, worry and social alienation. And it was suggested that insomnia was due to a process of internalization of psychological distress. Another hypothesis about psychological mechanisms has focused upon worry. Excessive and uncontrollable cognitive activity seem to be a characteristic feature of many insomniacs. One author emphasized the role of the dependency need and found a characteristic pattern among insomniacs. The central feature of this pattern is frustration of dependency need. The purpose of this paper was to review possible personality variable that may be predisposing causal factors of insomnia. Several factors are suggested by many studies, but in order to explore their causal importance other experimental and longitudinal studies are needed.

• 전기학회논문지
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• 제67권11호
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• pp.1486-1495
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• 2018

This paper investigates the autonomous ground vehicle (AGV) localization filter design problem under GNSS-denied environments. It is assumed that the given landmarks do not have unique features due to the lack of a prior knowledge on them. For such case, the AGV may have difficulties in distinguishing the position measurement of the detected landmark from those of other landmarks with the same feature, hence the conventional localization filters are not applicable. To resolve this technical issue, the localization filter design problem is formulated as a special form of the data association determining whether the detected feature is actually originated from which landmark. The measurement hypotheses generated by landmarks with the same feature are evaluated by the nearest neighbor data association scheme to reduce the computational burden. The position measurement corresponding to the landmark with the most probable hypothesis is used for localization filter. Through the experiments in real-driving condition, it is shown that the proposed method provides satisfactory localization performance in spite of using non-unique landmarks.

• 한국음향학회지
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• 제25권8호
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• pp.375-382
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• 2006

본 논문에서는 음성신호에 포함된 감정정보를 자동으로 식별하는 방법과 특정 감정을 검출하는 방법에 대해 다룬다. 자동 감정식별 및 검출을 위해 장구간 (long-term) 음향 특징을 사용하였고, F-score 기반의 특징선택 기법을 적용하여 최적의 특징 파라미터들을 선정하였다. 기존의 일반적인 SVM을 확률출력 SVM으로 변환하여 감정식별 및 감정검출 시스템을 구축하였으며, 가설검정에 기반한 감정검출을 위해 세 가지의 대수 우도비 (log-likelihood) 근사법을 제안하여 그 성능을 비교하였다. SUSAS 데이터베이스를 사용한 실험 결과, F-score를 이용한 특징선택 기법에 의해 감정식별 성능이 향상되었으며, 확률출력 SVM의 유효성을 검증할 수 있었다. 감정검출의 경우, 제안한 방법에 의해 91.3%의 정확도로 화난 감정을 검출할 수 있었다.

• Asia Marketing Journal
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• 제17권1호
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• pp.97-121
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• 2015

In this research, we examine whether and why temporal distance influences evaluations of two different types of brand extensions: concept-based extensions, defined as extensions primarily based on the importance or relevance of brand concepts to extension products; and similarity-based extensions, defined as extensions primarily based on the amount of feature similarity at the product-category level. In Study 1, we test the hypothesis that concept-based extensions are evaluated more favorably when they are framed to launch in the distant rather than in the near future, whereas similaritybased extensions are evaluated more favorably when they are framed to launch in the near rather than in the distant future. In Study 2, we confirm that this time-dependent differential evaluation is driven by the difference in construal level between the bases of the two types of extensions - i.e., brand-concept consistency and product-category feature similarity. As such, we find that conceptbased extensions are evaluated more favorably under the abstract than concrete mindset, whereas similarity-based extensions are evaluated more favorably under the concrete than abstract mindset. In Study 3, we extend to the case for a broad brand (i.e., brands that market products across multiple categories), finding that making accessible a specific product category of a broad parent brand influences evaluations of near-future, but not distant-future, brand extensions. Combined together, our findings suggest that temporal distance influences brand extension evaluation through its effect on the importance placed on brand concepts and feature similarity. That is, consumers rely on different bases to evaluate brand extensions, depending on their perception of when the extensions take place and on under what mindset they are placed. This research makes theoretical contributions to the brand extension research by identifying one important determinant to brand extension evaluation and also uncovering its underlying dynamics. It also contributes to expanding the scope of the construal level theory by putting forth a novel interpretation of two bases of perceived fit in terms of construal level. Marketers who are about to launch and advertise brand extensions may benefit by considering temporal-distance information in determining what content to deliver about extensions in their communication efforts. Conceptual relation of a parent brand to extensions needs to be emphasized in the distant future, whereas feature similarity should be highlighted in the near future.

• 전자공학회논문지SC
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• 제44권1호
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• pp.40-49
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• 2007

운전자를 위한 영상처리 시스템에서 도로 위의 움직이는 물체와 고정된 물체의 구분은 매우 중요한 문제이다. 많은 연구자들이 색상과 경계 기반의 추적 시스템은 'distracted' 현상으로 인해 잘못된 결과를 야기 시키는 데 이것은 동시에 모든 점들이 예상을 벗어난 경우에 대한 문제를 다루지 않기 때문이다. 본 논문에서는 순차적인 몬테카를로 필터를 사용하여 다중 차량 추적에 대응하며 광학적 흐름 기법의 명암 흐름과 히스토그램 기법의 색상 정보의 분포를 결합하여 실시간 시스템의 강인성과 정확성을 향상시킨다. 또한 고정된 물체의 경우 적응하는 입자 수의 밀도를 줄여 시간이 지남에 따라 추적 대상에서 제외된다. 두 개의 큰 흐름으로 나뉘는데 전자는 움직이는 물체와 고정된 물체를 구분하기 위한 예측 단계에 대하여 설명하고 후자는 센서인 영상으로부터 얻어진 정보를 측정 단계로 사용하여 겹쳐진 영역에 대응하는 방법에 대하여 논한다.

• 한국멀티미디어학회논문지
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• 제19권6호
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• pp.1003-1013
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• 2016

This paper proposes a framework of superpixel-based vehicle detection method using plane normal vector in disparity space. We utilize two common factors for detecting vehicles: Hypothesis Generation (HG) and Hypothesis Verification (HV). At the stage of HG, we set the regions of interest (ROI) by estimating the lane, and track them to reduce computational cost of the overall processes. The image is then divided into compact superpixels, each of which is viewed as a plane composed of the normal vector in disparity space. After that, the representative normal vector is computed at a superpixel-level, which alleviates the well-known problems of conventional color-based and depth-based approaches. Based on the assumption that the central-bottom of the input image is always on the navigable region, the road and obstacle candidates are simultaneously extracted by the plane normal vectors obtained from K-means algorithm. At the stage of HV, the separated obstacle candidates are verified by employing HOG and SVM as for a feature and classifying function, respectively. To achieve this, we trained SVM classifier by HOG features of KITTI training dataset. The experimental results demonstrate that the proposed vehicle detection system outperforms the conventional HOG-based methods qualitatively and quantitatively.