• 대한한방내과학회지
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• 제30권1호
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• pp.200-211
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• 2009

There are many reports about correlations between meteorological elements and stroke. In Oriental medicine, it is recognized that the weather affects the human body and diseases, but there are few studies about the correlation between meteorological elements and pattern identification of stroke. 105 stroke patients classified into fire-heat pattern or dampress-phlegm pattern were registered during the study period. We took the measurement of each meteorological element (atmospheric pressure, temperature, humidity, wind speed) according to pattern identification and analyzed pattern identification into two groups according to mean of each meteorological element during the study period. Mean temperature was higher with the heat-fire pattern than with the dampness-phlegm pattern. Heat-fire pattern also had higher frequency when temperature was higher than mean temperature. There was no correlation between atmospheric pressure, relative humidity, or wind speed and pattern identification.

• 대한전자공학회:학술대회논문집
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• 대한전자공학회 2002년도 하계종합학술대회 논문집(5)
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• pp.137-140
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• 2002

We introduce a personal identification method which can find user's ID without any help of the user. To do this, there has been two approaches, vision-based and pressure-based. Pressure-based approach has some advantages compared than vision-based one in the aspects of illumination, occlusion, and the amount of data. In the previous study about pressure-based personal identification, there are some restrictions about human body posture for extracting normalized footprints. Since this approach cannot be extended unconscious and continuos identification, we suppose more natural method and verified it by experiments.

• 전기학회논문지
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• 제61권8호
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• pp.1164-1171
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• 2012

Recently, machine olfactory systems as an artificial substitute of the human olfactory system are being studied actively because they can scent dangerous gases and identify the type of gases in contamination areas instead of the human. In this paper, we present an effective design method for the gas identification system. Even though dimensionality reduction is the very important part, in pattern analysis, We handled effectively the dimensionality reduction by grouping the sensors of which the measured patterns are similar each other, where genetic algorithms were used for combination optimization. To identify the gas type, we constructed the hierarchical rule base with two frames by using rough set theory. The first frame is to accept measurement characteristics of each sensor and the other one is to reflect the identification patterns of each group. Thus, the proposed methods was able to accomplish effectively dimensionality reduction as well as accurate gas identification. In simulation, we demonstrated the effectiveness of the proposed methods by identifying five types of gases.

• Journal of Information Science Theory and Practice
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• 제6권4호
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• pp.28-38
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• 2018

Wikipedia is composed of millions of articles, each of which explains a particular entity with various languages in the real world. Since the articles are contributed and edited by a large population of diverse experts with no specific authority, Wikipedia can be seen as a naturally occurring body of human knowledge. In this paper, we propose a method to automatically identify key entities and relations in Wikipedia articles, which can be used for automatic ontology construction. Compared to previous approaches to entity and relation extraction and/or identification from text, our goal is to capture naturally occurring entities and relations from Wikipedia while minimizing artificiality often introduced at the stages of constructing training and testing data. The titles of the articles and anchored phrases in their text are regarded as entities, and their types are automatically classified with minimal training. We attempt to automatically detect and identify possible relations among the entities based on clustering without training data, as opposed to the relation extraction approach that focuses on improvement of accuracy in selecting one of the several target relations for a given pair of entities. While the relation extraction approach with supervised learning requires a significant amount of annotation efforts for a predefined set of relations, our approach attempts to discover relations as they occur naturally. Unlike other unsupervised relation identification work where evaluation of automatically identified relations is done with the correct relations determined a priori by human judges, we attempted to evaluate appropriateness of the naturally occurring clusters of relations involving person-artifact and person-organization entities and their relation names.

• 조명전기설비학회논문지
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• 제28권3호
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• pp.63-71
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• 2014

A single-inverted-pendulum model is presented to simulate and predict the passive response of human balance control. This simplified biomechanical model was comprised of a torsional spring and damper, and a lump mass. An estimation of frequency response function was conducted to parameterize the complexity. The frequency domain identification method is used to identify the parameters of the model. The equivalent viscoelastic parameters of standing body were obtained and there was good conformity between the simulation and experimental result.

• 제어로봇시스템학회:학술대회논문집
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• 제어로봇시스템학회 2005년도 ICCAS
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• pp.1202-1205
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• 2005

This paper describes a method for vision-based person identification that can detect, track, and recognize person from video using multiple cues: height and dressing colors. The method does not require constrained target's pose or fully frontal face image to identify the person. First, the system, which is connected to a pan-tilt-zoom camera, detects target using motion detection and human cardboard model. The system keeps tracking the moving target while it is trying to identify whether it is a human and identify who it is among the registered persons in the database. To segment the moving target from the background scene, we employ a version of background subtraction technique and some spatial filtering. Once the target is segmented, we then align the target with the generic human cardboard model to verify whether the detected target is a human. If the target is identified as a human, the card board model is also used to segment the body parts to obtain some salient features such as head, torso, and legs. The whole body silhouette is also analyzed to obtain the target's shape information such as height and slimness. We then use these multiple cues (at present, we uses shirt color, trousers color, and body height) to recognize the target using a supervised self-organization process. We preliminary tested the system on a set of 5 subjects with multiple clothes. The recognition rate is 100% if the person is wearing the clothes that were learned before. In case a person wears new dresses the system fail to identify. This means height is not enough to classify persons. We plan to extend the work by adding more cues such as skin color, and face recognition by utilizing the zoom capability of the camera to obtain high resolution view of face; then, evaluate the system with more subjects.

• 국제학술발표논문집
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• The 6th International Conference on Construction Engineering and Project Management
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• pp.313-316
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• 2015

Construction is one of the most dangerous job sectors, which reports tens of thousands of time-loss injuries and deaths every year. These disasters incur delays and additional costs to the projects. The safety management needs to be on the top primary tasks throughout the construction to avoid fatal accidents and to foster safe working environments. One of the safety regulations that are frequently violated is the wearing of personal protection equipment (PPE). In order to facilitate monitoring of the compliance of the PPE wearing regulations, this paper proposes a vision based method that automatically identifies whether workers wear hard hats and safety vests. The method involves three modules - human body detection, identification of safety vest wearing, and hard hat detection. First, human bodies are detected in the video frames captured by real-time on-site construction cameras. The detected human bodies are classified into with/without wearing safety vests based on the color features of their upper parts. Finally, hard hats are detected on the nearby regions of the detected human bodies and the locations of the detected hard hats and human bodies are correlated to reveal their corresponding matches. In this way, the proposed method provides any appearance of the workers without wearing hard hats or safety vests. The method has been tested on onsite videos and the results signify its potential to facilitate site safety monitoring.

• International Journal of Human Ecology
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• 제8권1호
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• pp.9-18
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• 2007

This study focuses on the relationship between ethnic identity of Asian-Americans and their appreciation of their ethnic body features, based on reference group theory. A convenience sample of 60 male and 52 female students from various Asian ethnicities attending a mid-western university was used for the study. A 2 (gender) by 2 (ethnic identification) by 2 (socializing group) analysis of covariance (ANCOVA) on body image satisfaction as dependent variable and Body Mass Index score as a covariate was conducted. A significant main effect of ethnic identification was found, which indicates the more respondents identified with their ethnic group, the more likely they were to be satisfied with their appearance. The social group affiliation main effect was not significant. The impact of ethnic identification was significant only for those respondents who socialize more with Americans than with Asians. The results support the idea that one's ethnic group functions as a reference group, which influences body image appraisals.

• Imaging Science in Dentistry
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• 제34권3호
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• pp.151-157
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• 2004

Purpose : To evaluate the quantitative accuracy of three-dimensional (3D) images by means of comparing distance measurements on the 3D images with direct measurements of dry human skull according to slice thickness and scanning modes. Materials and Mathods : An observer directly measured the distance of 21 line items between 12 orthodontic landmarks on the skull surface using a digital vernier caliper and each was repeated five times. The dry human skull was scanned with a Helical CT with various slice thickness (3, 5, 7 mm) and acquisition modes (Conventional and Helical). The same observer measured corresponding distance of the same items on reconstructed 3D images with the internal program of V-works 4.0/sup TM/(Cybermed Inc., Seoul, Korea). The quantitative accuracy of distance measurements were statistically evaluated with Wilcoxons' two-sample test. Results: 11 line items in Conventional 3 mm, 8 in Helical 3mm, 11 in Conventional 5mm, 10 in Helical 5mm, 5 in Conventional 7mm and 9 in Helical 7mm showed no statistically significant difference. Average difference between direct measurements and measurements on 3D CT images was within 2mm in 19 line items of Conventional 3mm, 20 of Helical 3mm, 15 of Conventional 5mm, 18 of Helical 5mm, II of Conventional 7mm and 16 of Helical 7mm. Conclusion: Considering image quality and patient's exposure time, scanning protocol of Helical 5mm is recommended for 3D image analysis of the skull in CT.

• 한국생물공학회:학술대회논문집
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• 한국생물공학회 2003년도 생물공학의 동향(XIII)
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• pp.340-340
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• 2003