• KIPS Transactions on Software and Data Engineering
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• v.3 no.8
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• pp.299-308
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• 2014

Various literatures related computing of information processing have been recently shown the researches inspired from the remarkably excellent human capabilities which recognize and categorize very complex visual patterns such as body motions and facial expressions. Applied from human's outstanding ability of perception, the classification function of visual sequences without context information is specially crucial task for computer vision to understand both the coding and the retrieval of spatio-temporal patterns. This paper presents a biological process based action recognition model of computer vision, which is inspired from visual information processing of human brain for action recognition of visual sequences. Proposed model employs the structure of neural fields of bio-inspired visual perception on detecting motion sequences and discriminating visual patterns in human brain. Experimental results show that proposed recognition model takes not only into account several biological properties of visual information processing, but also is tolerant of time-warping. Furthermore, the model allows robust temporal evolution of classification compared to researches of action recognition. Presented model contributes to implement bio-inspired visual processing system such as intelligent robot agent, etc.

• Journal of Oral Medicine and Pain
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• v.23 no.2
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• pp.127-141
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• 1998

This study was performed to investigate the clinical features of internal derangement of temporomandibular joint. For this study, 117 patients with temporomandibular disorders and 81 dental students without any signs and symptoms of temporomandibular disorders were selected as the patients group and as the control group, respectively. Preferred chewing side, Angle's classification, lateral guidance pattern, maximal mouth opening range, and affected side were recorded clinically. Head and shouldeer posture was measured in a groundplate on which square diagram of five centimeters each had been drawn, and cephalograph was also taken for measurement of head and neck posture. Sonopak of Biopak system (Bioresearch inc., USA) was used to record joint vibration for evaluation of internal healthy status of temporomandibular joint. The data collected were analyzed by SAS statistical program. The results of this study were as follows : 1. Frequency of left side chewing subjects was higher in patients than in control group, but there was no difference in distribution of subjects by Angle's classification. Other types was prvalent in patients whereas group function was more in control group for lateral guidance pattern. 2. As to lateral guidance pattern by clinical diagnosis, patients with internal derangement and/or degenerative joint disease showed higher frequency was consistent with the result by Sonopak impression. 3. There was no difference for shoulder height between the two groups, however, tilting of head and backward extension of cervical spine was more frequent in control group. 4. Acromion was positioned more anteriorly in patients with internal derangement and/or degenerative joint disease than in control group and angle between eye and tragus was larger in patients. Patients with degenerative joint disease showed more flexed head posture than control group did in cephalometric profile. 5. Maximal mouth opening range in patients with internal derangement was the least in all subgroups in patients classified by Sonopak impression.

• The KIPS Transactions:PartC
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• v.13C no.7 s.110
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• pp.859-864
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• 2006

The openness of the Web allows any user to access almost any type of information easily at any time and anywhere. However, with function of easy access for useful information, internet has dysfunctions of providing users with harmful contents indiscriminately. Some information, such as adult content, is not appropriate for all users, notably children. Additionally for adults, some contents included in abnormal porn sites can do ordinary people's mental health harm. In the meantime, since Internet is a worldwide open network it has a limit to regulate users providing harmful contents through each countrie's national laws or systems. Additionally it is not a desirable way of developing a certain system-specific classification technology for harmful contents, because internet users can contact with them in diverse way, for example, porn sites, harmful spams, or peer-to-peer networks, etc. Therefore, it is being emphasized to research and develop context-based core technologies for classifying harmful contents. In this paper, we propose an efficient text filter for blocking harmful texts of web documents using context-based technologies.

• The Journal of the Korea institute of electronic communication sciences
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• v.16 no.6
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• pp.1081-1088
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• 2021

The modern wireless communication system employes the beamforming technique based on a massive array antenna with a number of elements, for supporting the smooth communication services. A reliable beamforming technology requires the Angle-of-Arrival(: AOA) information for the signal incident to the receiving antenna, which is generally estimated by the high-resolution AOA estimation algorithm such as Multiple Signal Classification(: MUSIC). Although the MUSIC algorithm has the excellent estimation performance, it is difficult to estimate AOA in real time for the massive array antenna due to the extremely high computational complexity. In order to enhance this problem, in this paper, we propose the cascade AOA estimation algorithm based on a Flexible Massive Concentric Circular Array(: FMCCA) antenna with the On/Off function for antenna elements. The proposed cascade algorithm consists of the CAPON algorithm using some elements among entire antenna elements and the Beamspace MUSIC algorithm using entire elements. We provide computer simulation results for various scenarios to demonstrate the AOA estimation performance of the proposed approach.

• Journal of Multimedia Information System
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• v.9 no.2
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• pp.113-120
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• 2022

Mongolian folk songs are inspired by Mongolian labor songs and are classified into long and short songs. Mongolian long songs have ancient origins, are rich in legends, and are a great source of folklore. So it was inscribed by UNESCO in 2008. Mongolian written literature is formed under the direct influence of oral literature. Mongolian long song has 3 classes: ayzam, suman, and besreg by their lyrics and structure. In ayzam long song, the world perfectly embodies the philosophical nature of world phenomena and the nature of human life. Suman long song has a wide range of topics such as the common way of life, respect for ancestors, respect for fathers, respect for mountains and water, livestock and animal husbandry, as well as the history of Mongolia. Besreg long songs are dominated by commanded and trained characters. In this paper, we proposed a method to classify their 3 types of long songs using machine learning, based on their lyrics structures without semantic information. We collected lyrics of over 80 long songs and extracted 11 features from every single song. The features are the name of a song, number of the verse, number of lines, number of words, general value, double value, elapsed time of verse, elapsed time of 5 words, and the longest elapsed time of 1 word, full text, and type label. In experimental results, our proposed features show on average 78% recognition rates in function type machine learning methods, to classify the ayzam, suman, and besreg classes.

• Journal of the Korean Society of Physical Medicine
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• v.18 no.1
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• pp.99-110
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• 2023

PURPOSE: This study was conducted to suggest a way to easily understand and utilize the International Classification of Functioning, Disability and Health (ICF) or Korean Standard Classification of Functioning, Disability and Health (KCF), a common and standard language related to health information. METHODS: The tools used by physical therapists to evaluate the functioning of neurological patients were collected from 10 domestic hospitals. By applying the ICF linking rule, two experts compared, analyzed, and linked the concepts in the items of the collected tools and the ICF/KCF codes. The frequency of use of the selected tool, the matching rate of the liking results of two experts, and the number of the codes linked were treated as descriptive statistics and the code set was presented as a list. RESULTS: The berg balance scale, trunk impairment scale, timed up and go test, functional ambulation category, 6 Minute walk test, manual muscle test, and range of motion measurements were the most commonly used tools for evaluating the functioning. The total number of items of the seven tools was 33, and the codes linked to the ICF/KCF were 69. Twenty-two codes were mapped, excluding duplicate codes. Ten codes in the body function, 11 codes in the activity, and one code in the environmental factor were included. CONCLUSION: The information on the development process of the code set will increase the understanding of ICF/KCF and the developed code set can conveniently be used for collecting patients' functioning information.

• Journal of Electrical Engineering and Technology
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• v.12 no.6
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• pp.2388-2398
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• 2017

In this study, we propose a robust face recognition system to pose variations based on automatic pose estimation. Radial basis function neural network is applied as one of the functional components of the overall face recognition system. The proposed system consists of preprocessing and recognition modules to provide a solution to pose variation and high-dimensional pattern recognition problems. In the preprocessing part, principal component analysis (PCA) and 2-dimensional 2-directional PCA ($(2D)^2$ PCA) are applied. These functional modules are useful in reducing dimensionality of the feature space. The proposed RBFNNs architecture consists of three functional modules such as condition, conclusion and inference phase realized in terms of fuzzy "if-then" rules. In the condition phase of fuzzy rules, the input space is partitioned with the use of fuzzy clustering realized by the Fuzzy C-Means (FCM) algorithm. In conclusion phase of rules, the connections (weights) are realized through four types of polynomials such as constant, linear, quadratic and modified quadratic. The coefficients of the RBFNNs model are obtained by fuzzy inference method constituting the inference phase of fuzzy rules. The essential design parameters (such as the number of nodes, and fuzzification coefficient) of the networks are optimized with the aid of Particle Swarm Optimization (PSO). Experimental results completed on standard face database -Honda/UCSD, Cambridge Head pose, and IC&CI databases demonstrate the effectiveness and efficiency of face recognition system compared with other studies.

• The Transactions of The Korean Institute of Electrical Engineers
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• v.64 no.6
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• pp.940-947
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• 2015

A Sitting posture is a very important issue for moderns who is mostly sedentary. Also, a wrong sitting posture causes back-pain and spinal disease. Many researchers have been proposed numerous approaches that classifying and monitoring for a sitting posture. In this paper, we proposed a real-time sitting posture monitoring system that was developed to measure pressure distribution in the human body. The proposed system consists of a pressure sensing module (six pressure sensors), data acquisition and processing module, a communication module and a display module for an individual sitting posture monitoring. The developed monitoring system can classify into five sitting postures, such as a correct sitting, sitting on forward inclination, leaning back sitting, sitting with a right leg crossed and a left leg crossed. In addition, when a user deviates from the correct posture, an alarm function is activated. We selected two kinds of chairs, one is rigid material and fixed form, the other one is a soft material and can adjust the height of a chair. In the experiments, we observed appearance changes for subjects in consequence of a comparison between before the correction of posture and after the correction of posture when using the proposed system. The data from twenty four subjects has been classified with a proposed classifier, achieving an average accuracy of 83.85%, 94.56% when the rigid chair and the soft chair, respectively.

• Journal of Korean Society for Geospatial Information Science
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• v.16 no.4
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• pp.3-10
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• 2008

Cadastral map is a public book that has been composed by continuous parcel having location, number, classification, boundary and an area based on Cadastral Law. A few years ago, cadastral map had been managed by form drawn on 2 dimension plane paper with 7 regular scales. Recently as computer systems are upgrading, cadastral map was able to have a chance to develope one step. Its type has been remade from raster to vector. In result, the cadastral map of vector type becomes to apply variously. Therefore, digital cadastral map has been ready a system to be use with multi-propose by KLIS(Korean Land Information System). In this research, it concretely want presentation of status using land more than original parcel on basic coordination cadastral map and KLIS(Korean Land Information System). The cadastral map is composed as parcel unit was applied by new presentation technique to "Model Research on One Parcel Presentation Technique for Land Status of Cadastral Map". The function of cadastral map on One Parcel Presentation Technique which is not only location relation of possession right and expression of states using land in 28 classifications demonstrated on the cadastral law but also used as foundation data of GIS construct business is developed by lines and classification of parcel to center around public sites of roads, rails, drains and rivers. especially, this research is composed of technique elevation and development of One Parcel Projection Technique of cadastral map in using object of roads among public sites.

• Clinics in Shoulder and Elbow
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• v.21 no.2
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• pp.59-66
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• 2018

Background: Massive, irreparable rotator cuff tears (RCTs) are a challenging clinical problem in young patients. In recent years, arthroscopic superior capsular reconstruction (ASCR) is a popular treatment in the massive, irreparable RCTs. However, studies reporting clinical results of ASCR are rare in the literature. Methods: Between 2013 and 2015, six patients underwent ASCR. One patient treated with dermal allograft, while five patients with autogenous fascia lata graft. Demographic data, as well as preoperative and last follow-up clinical data including pain, range of motion (ROM), strength, American Shoulder and Elbow Surgeons system, the Constant system, the University of California at Los Angeles system, the Simple Shoulder Test, and the Shoulder Pain and Disability Index system were obtained. Acromiohumeral distances and Hamada classification were measured on standard anteroposterior x-ray. Results: All patients were men, and the average age was $59.5{\pm}4.18years$ (range, 53-65 years).The minimum follow-up was 18 months with a mean follow-up was $27.33{\pm}7.58months$ (range, 18-36). All patients had postoperative improvement in pain scores and functional scores. The ROM and strength did not improve after surgery. The Hamada score progressed of radiographic stage in 2 patients. In the case of dermal allograft, there was graft failure 6 weeks after ASCR. Conclusions: Our results support the ASCR as a viable treatment for surgical salvage in massive, irreparable RCTs. This treatment option may provide patients with decreased pain and increased function. And studying our case of dermal allograft failure provides opportunities to decrease graft failure in ASCR using dermal allograft.