• 제어로봇시스템학회:학술대회논문집
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• 2005.06a
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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.

• The Journal of the Korean Society for Microbiology
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• v.7 no.1
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• pp.43-49
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• 1972

Mycotic infection seems to be increasing in importance as the causal agents of disease in man, especially invaders in already debilitated persons. This paper presents the identification of 39 stock strains of yeast like cells which were isolated from patients at National Medical Center. It reveals 21 strains of C. albicans, 5 strains of T. glabrata, 4 strains of C. tropicalis, one strain of T. mogii & 8 strains of unidentified.

• KSII Transactions on Internet and Information Systems (TIIS)
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• v.7 no.11
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• pp.2690-2701
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• 2013

Humans are able to recognize small number of people they know well by the way they walk. This ability represents basic motivation for using human gait as the means for biometric identification. Such biometric can be captured at public places from a distance without subject's collaboration, awareness or even consent. Although current approaches give encouraging results, we are still far from effective use in practical applications. In general, methods set various constraints to circumvent the influence factors like changes of view, walking speed, capture environment, clothing, footwear, object carrying, that have negative impact on recognition results. In this paper we investigate the influence of walking speed variation to different visual based gait recognition approaches and propose normalization based on geometric transformations, which mitigates its influence on recognition results. With the evaluation on MoBo gait dataset we demonstrate the benefits of using such normalization in combination with different types of gait recognition approaches.

• IE interfaces
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• v.19 no.4
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• pp.333-341
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• 2006

RFID (Radio Frequency Identification) is a technology that can input identification information to microchip and make goods, animals, persons recognized, chased, and managed using radio frequency, and is founded on the core technology of ubiquitous environment of the future. In this paper, we propose a RFID integrated system designed to manage the lifecycle of an individual product efficiently. The proposed system can enable traceability and visibility of items through their entire life by integrating distribution and banking information on the basis of EPCglobal Network. It may provide the infra of Digital Manufacturing and RTE (Real Time Enterprise) and effective information sharing structure with existing legacy system (ERP, CRM, SCM) by real time.

• Journal of Preventive Medicine and Public Health
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• v.34 no.3
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• pp.277-283
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• 2001

Objectives : To investigate the prevalence of hazardous and harmful alcohol use, which are a subthreshold of alcohol related disorders, Methods : Direct-interview questionnaires to 1,183 rural persons (489 male, 694 female) were conducted in Chungju-city from July 2 to 20, 1998. As a screening instrument, the alcohol use disorders identification test (AUDIT) was used. Results : The prevalence of alcohol use was 41.7%. In males, it was 66.3% and in females, it was 24.4%. The mean of the AUDIT score of males and females was 13.2 and 5.6, respectively. As WHO guideline, the prevalence of hazardous alcohol use in males and females was 80.3% and 20.7%, respectively. This suggests that the prevalence of 'hazardous drinking' and 'harmful drinking' was 45.4% and 29.3% for males and 1.2% and 2.4% for females, respectively. Conclusions : This study presented the prevalence of hazardous and harmful drinking of a rural population in Korea and reviewed those health problems. Further evaluation to detect and treat lower alcoholic drinkers is recommended.

• KSII Transactions on Internet and Information Systems (TIIS)
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• v.13 no.10
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• pp.5144-5160
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• 2019

Secret sharing is an effective way of protecting secret messages. However, the traditional secret sharing schemes are considered meaningless due to malicious people attention which might raise risks. To overcome the weakness, this paper presents an effective secret sharing scheme with the functionality of cheater identification, based on meaningful QR code. The secret message will be split and concealed in the padding region of cover QR codes with the assistance of Latin square and it can be completely restored when all the involved participants cooperate. The concealing strategy exploits the characteristic of Reed-Solomon (RS) code to ensure the strong robustness of generated QR code pseudo-shares. The meaningful QR code pseudo-shares help to reduce the curious of unrelated persons. Some experiments were done to evaluate the performance of proposed scheme. The results showed that the proposed scheme is feasible, efficient and secure compared to the other existing schemes. It also achieves a higher secret payload and maintains stronger robustness.

• International Journal of Computer Science & Network Security
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• v.22 no.6
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• pp.319-331
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• 2022

The latest global COVID-19 pandemic has made the use of facial masks an important aspect of our lives. People are advised to cover their faces in public spaces to discourage illness from spreading. Using these face masks posed a significant concern about the exactness of the face identification method used to search and unlock telephones at the school/office. Many companies have already built the requisite data in-house to incorporate such a scheme, using face recognition as an authentication. Unfortunately, veiled faces hinder the detection and acknowledgment of these facial identity schemes and seek to invalidate the internal data collection. Biometric systems that use the face as authentication cause problems with detection or recognition (face or persons). In this research, a novel model has been developed to detect and recognize faces and persons for authentication using scale invariant features (SIFT) for the whole segmented face with an efficient local binary texture features (DLBP) in region of eyes in the masked face. The Fuzzy C means is utilized to segment the image. These mixed features are trained significantly in a convolution neural network (CNN) model. The main advantage of this model is that can detect and recognizing faces by assigning weights to the selected features aimed to grant or provoke permissions with high accuracy.

• The Journal of Korean Institute of Communications and Information Sciences
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• v.24 no.12B
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• pp.2415-2423
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• 1999

We propose a new optical method which conceals the data of authorized persons by encryption before they are stored or compared in the pattern recognition system for security systems. This proposed security system is made up of two subsystems : a proposed optical encryption system and a pattern recognition system based on the JTC which has been shown to perform well. In this system, each image of authorized persons as a reference image is stored in memory units through the proposed encryption system. And if a fingerprint image is placed in the input plane of this security system for access to a restricted area, the image is encoded by the encryption system then compared with the encrypted reference image. Therefore because the captured input image and the reference data are encrypted, it is difficult to decrypt the image if one does not know the encryption key bit stream. The basic idea is that the input image is encrypted by performing optical XOR operations with the key bit stream that is generated by digital encryption algorithms. The optical XOR operations between the key bit stream and the input image are performed by the polarization encoding method using the polarization characteristics of LCDs. The results of XOR operations which are detected by a CCD camera should be used as an input to the JTC for comparison with a data base. We have verified the idea proposed here with computer simulations and the simulation results were also shown.

• KSII Transactions on Internet and Information Systems (TIIS)
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• v.15 no.12
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• pp.4456-4475
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• 2021

The system for re-identifying persons is used to find and verify the persons crossing through different spots using various cameras. Much research has been done to re-identify the person by utilising features with deep-learned or hand-crafted information. Deep learning techniques segregate and analyse the features of their layers in various forms, and the output is complex feature vectors. This paper proposes a distinctive framework called Integrated Level Feature Pattern (ILFP) framework, which integrates local and global features. A new deep learning architecture named modified XceptionNet (m-XceptionNet) is also proposed in this work, which extracts the global features effectively with lesser complexity. The proposed framework gives better performance in Rank1 metric for Market1501 (96.15%), CUHK03 (82.29%) and the newly created NEC01 (96.66%) datasets than the existing works. The mean Average Precision (mAP) calculated using the proposed framework gives 92%, 85% and 98%, respectively, for the same datasets.

• Korean Journal of Social Welfare
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• v.59 no.4
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• pp.217-244
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• 2007

The purpose of the research is to understand the life of persons with disabilities caused by an accident by reconstructing their post-accident experiences. As a research tool, Fritz $Sch{\ddot{u}}tze's$ narrative interview was used, and three cases were analyzed in terms of a 'process structure of life'. After the researcher reconstructed each case, she sorted the cases comprehensively both according to the common features as well as to the differences among them. In doing so, the researcher came up with three characteristics of persons with disabilities caused by an accident. First, rather than identifying with their present life, the interviewees identified themselves with their life before the accident happened. Such identification problem is connected with their problem of accepting their handicap. And the interviewees identified themselves with disability groups. It showed that they feel more comfortable and secure among other people with disabilities than with families or friends. This makes them stay in the group of the disabled, in which they can understand and respect each other, rather than staying in a group in which people discriminate the disabled from able bodied and do not accept the disabled as equal members. Second, in their narration the interviewees told stories emphasizing their life after the accident happened. This feature can be compared with the experiences of those persons who underwent a trauma. Finally, it was found that our country's welfare policy for persons with disabilities caused by an accident is designed without differentiating people according to gender or educational background. Through these findings, the researcher intends to reflect on our country's current social welfare services and to look for new methods in order to implement proper social welfare practices.