• Journal of the Institute of Electronics Engineers of Korea SP
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• v.47 no.4
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• pp.28-34
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• 2010

In this paper, we proposed an algorithm for utilizing visual information for non-contact predicting method of friction coefficient. Coefficient of friction is very important in driving on road and traversing over obstacle. Our algorithm is based on terrain classification for visual image. The proposed method, non-contacting approach, has advantage over other methods that extract material characteristic of road by sensors contacting road surface. This method is composed of learning group(experiment, grouping material) and predicting friction coefficient group(Bayesian classification prediction function). Every group include previous work of vision. Advantage of our algorithm before entering such terrain can be very useful for avoiding slippery areas. We make experiment on measurement of friction coefficient of terrain. This result is utilized real friction coefficient as prediction method. We show error between real friction coefficient and predicted friction coefficient for performance evaluation of our algorithm.

• Journal of the Korea Academia-Industrial cooperation Society
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• v.18 no.12
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• pp.613-619
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• 2017

Recently, the development and production of weapons systems for military products have been increasing. Therefore, there is a need for an efficient quality control method suitable for limited resources and manpower for the manufactured military products. Military munitions are characteristically developed and produced as business contract units. In addition, business and quality control are done by contract. For this reason, many contracts are concluded in one producer and similar products are often produced. Business and quality control also require extensive manpower and effort. If a company produces several similar products, a more efficient management approach is required. This study therefore examines these problems in an attempt to present solutions by analyzing the types of munitions contracts and the characteristics of products produced by one company. Based on the results, a method is proposed to manage the contract-specific management methods by company, that is, by business site. The method is applied to an engine manufacturing company and the integrated management plan is verified and its effectiveness confirmed. The effect of facility-wide method was a reduction of QA manpower and an improvement in maintaining quality assurance and stability through management of the workforce and contract grouping method.

• Journal of Korea Water Resources Association
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• v.49 no.12
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• pp.1007-1014
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• 2016

The FORGEX (Focused Rainfall Growth Extension) method was developed to estimate rainfall quantiles in the United Kingdom. This method does not need any regional grouping and can estimate rainfall quantiles with relatively long return period. The spatial dependence formula (ln $N_e$) was derived to consider the distance from growth curve of proper population to the distributed network maximum (netmax) data using the UK rainfall data. For this reason, there is an inaccurate problem in rainfall quantiles when this formula is applied in Korea. In this study, the new formula was derived in order to improve such shortcomings using rainfall data of 64 sites from the Korea Meteorological Administration (KMA). A 42-year period (1973~2014) was taken as the reference period from rainfall data, then the formula was derived using three parameters such as rainfall duration, number of site, area of network. Then the new formula was applied to the FORGEX method for regional rainfall frequency analysis. In addition, rainfall quantiles were compared with those from the UK formula. As a result, the new formula shows more accurate results than the UK formula, in which the FORGEX method by the UK formula underestimates rainfall quantiles. Finally, the new improved formula may estimate accurate rainfall quantiles for long return period.

• Journal of Industrial Convergence
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• v.20 no.12
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• pp.195-202
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• 2022

Underground Geospatial Information Map Management System(UGIMMS) integrates various underground facilities in the underground space into 3D mesh data, and supports to check the 3D image and location of the underground facilities in the mobile app. However, there is a problem that it takes a long time to run in the app because various underground facilities can exist in some areas executed by the app and can be seen layer by layer. In this paper, we propose a deep learning-based K-means vertex clustering algorithm as a method to reduce the execution time in the app by reducing the size of the data by reducing the number of vertices in the 3D mesh data within the range that does not cause a problem in visibility. First, our proposed method obtains refined vertex feature information through a deep learning encoder-decoder based model. And second, the method was simplified by grouping similar vertices through K-means vertex clustering using feature information. As a result of the experiment, when the vertices of various underground facilities were reduced by 30% with the proposed method, the 3D image model was slightly deformed, but there was no missing part, so there was no problem in checking it in the app.

• Journal of the Institute of Electronics Engineers of Korea CI
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• v.45 no.2
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• pp.26-32
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• 2008

Video compression schemes have been developed and used for many years. Currently, H.264/AVC is the most efficient video coding standard. The H.264/AVC baseline profile adopts CAVLC(Context-Adaptive Variable Length Coding) method as an entropy coding method. CAVLC gives better performance in compression ratios than conventional VLC(Variable Length Coding). However, because CAVLC decoder uses a lot of VLC tables, the CAVLC decoder requires a lot of area in terms of hardware. Conversely, since it must look up the VLC tables, it gives a worse performance in terms of software. In this paper, we propose a new hierarchical grouping method for the VLC tables. We can obtain an index of codes in the reconstructed VLC tables by simple arithmetic operations. In this method, the VLC tables are accessed just once in decoding a symbol. We modeled the proposed algorithm in C language, compiled under ARM ADS1.2 and simulated it with Armulator. Experimental results show that the proposed algorithm reduces execution time by about 80% and 15% compared with the H.264/AVC reference program JM(Joint Model) 10.2 and the arithmetic operation algorithm which is recently proposed, respectively.

• Journal of Sasang Constitutional Medicine
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• v.12 no.1
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• pp.48-62
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• 2000

Creativity is the most important characteristic and ability in the 21st century. Recently leading people in Korean society are aware of the significance of the enhancement of the creativity. However, Korean students are less likely to take initiative or depart from standard ways of thinking or doing things, because Korean Confucius culture puts an emphasis on collectivism. An individual has an obligation to conform in order to avoid conflict and maintain social harmony. The rule of respecting parents and teachers leads to a lack of self-expression and entails silence. Brainstorming technique developed by American Osbron, who originated the group brainstorming in 1953, is the most popular creative thinking method for the students. Brainstorming technique has two principles : ideation can be more productive if criticism is concurrently excluded; The more ideas the better. In doing BS, each panel should consist of chairperson, an assistant chairperson, recorder, and 10 others including 2-3 females. However there are several problems in doing group BS, such as production blocking, uniformity thinking, evaluation apprehension, and social loafing. This study was undertaken to investigate the proper way of forming Brainstorming groups with Korean students according to the Sasang Constitutional Medicine originated by Korean Lee Je-ma in 1894. Human beings are classified in four group in Sasang Constitutional Medicine : Taeyang-In, Teaum-In, Soyang-In and Soum-In. Two Yang-Ins are more self-expressive : Taeyang-In has very unique ides and thoughts; Soyang-In is very humorous and like to present his/her ideas. On the other hand, two Um-Ins are passive and are not likely to speak out their ideas in group. Therefore, in this investigation firstly, the brainstorming group was formed with two Yang-Ins (Taeyang-In and Soyang-In) and two Um-Ins(Taeum-In and Soum-In) separately and secondly, Yang-Ins and Um-Ins were mixed. And the first method was compared with the second method in terms of the degree of participation of the group members and finally the better grouping method to produce more and better ideas was discussed and suggested for the educational system.

• The Journal of The Korea Institute of Intelligent Transport Systems
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• v.12 no.1
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• pp.1-14
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• 2013

Annual average daily traffic (AADT) serves the important basic data in transportation sector. Despite of its importance, AADT is estimated through permanent traffic counts (PTC) at limited locations because of constraints in budget and so on. At most of locations, AADT is estimated using short-term traffic counts (STC). Though many studies have been carried out at home and abroad in an effort to enhance the accuracy of AADT estimate, the method to simplify average STC data has been adopted because of application difficulty. A typical model for estimating AADT is an adjustment factor application model which applies the monthly or weekly adjustment factors at PTC points (or group) with similar traffic pattern. But this model has the limit in determining the PTC points (or group) with similar traffic pattern with STC. Because STC represents usually 24-hour or 48-hour data, it's difficult to forecast a 365-day traffic variation. In order to improve the accuracy of traffic volume prediction, this study used the geostatistical approach called co-kriging and according to their reports. To compare results, using 3 methods : using adjustment factor in same section(method 1), using grouping method to apply adjustment factor(method 2), cokriging model using previous year's traffic data which is in a high spatial correlation with traffic volume data as a secondary variable. This study deals with estimating AADT considering time and space so AADT estimation is more reliable comparing other research.

• Journal of Convergence Society for SMB
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• v.6 no.1
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• pp.33-38
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• 2016

Disease of patient who visited the hospital can cause different symptoms of the disease, depending on the environment and lifestyle. Recent medical services offered in patients has changed in the environment that can be selected for treatment by analyzing the patient according to the disease symptoms. In this paper, we propose an efficient method to manage disease control because the treatment method may change at any patients suffering from the disease according to the patient conditions by grouping the different treatments to patients for disease information. The proposed scheme has a feature that can be ingested by the patient big disease information, as well as to improve the treatment efficiency of the medical treatment the increase patient satisfaction. The proposed sheme can handle big data by clustering of disease information for patients suffering from diseases such as patient consent small groups. In addition, the proposed scheme has the advantage that can be conveniently accessed via a particular keyword, the treatment method according to patient disease information. The experimental results, the proposed method has been improved by 23% in terms of efficiency compared to conventional techniques, disease management time is gained 11.3% improved results. Medical service user satisfaction seen from the survey is to obtain a high 31.5% results.

• Journal of the Korea Academia-Industrial cooperation Society
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• v.20 no.3
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• pp.65-70
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• 2019

The purpose of this study is to understand the college students' needs for software curriculum which based on surveys from educational satisfaction of the software lecture evaluation, as well as to find out the improvement plan by applying the text content analysis method. The research method used the text content analysis program to calculate the frequency of words occurrence, key words selection, co-occurrence frequency of key words, and analyzed the text center and network analysis by using the network analysis program. As a result of this research, the decent points of the software education network are mentioned with 'lecturer' is the most frequently occurrence after then with 'kindness', 'student', 'explanation', 'coding'. The network analysis of the shortage points has been the most mention of 'lecture', 'wish to', 'student', 'lecturer', 'assignment', 'coding', 'difficult', and 'announcement' which are mentioned together. The comprehensive network analysis of both good and shortage points has compared among key words, we can figure out difference among the key words: for example, 'group activity or task', 'assignment', 'difficulty on level of lecture', and 'thinking about lecturer'. Also, from this difference, we can provide that the lack of proper role of individual staff at group activities, difficult and excessive tasks, awareness of the difficulty and necessity of software education, lack of instructor's teaching method and feedback. Therefore, it is necessary to examine not only how the grouping of software education (activities) and giving assignments (or tasks), but also how carried out group activities and tasks and monitored about the contents of lectures, teaching methods, the ratio of practice and design thinking.

• Journal of the Korea Convergence Society
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• v.7 no.6
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• pp.237-247
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• 2016

This study analyzed quantitative effects of ISMS certification. To measure the company value change the stock data was used and the methodology of event study was also applied. Event study methodology is a method of analyzing the effects of information or public announcement about certain events on the stock market through abnormal return of stock price. First, ISMS certification was acquired followed by the measurement of abnormal excess return of company. Based on the increase or decrease of abnormal excess return, the group was classified. There are 3 types of groups("Increase", "Reduce", "Maintain"). Next, the cluster analysis was performed for each group. Cluster analysis or clustering is the task of grouping a set of objects in such a way that objects in the same group (called a cluster) are more similar (in some sense or another) to each other than to those in other groups(clusters). The purpose of this study is to have a quantitative measurement of performance of ISMS certification. So, the result of this study will be promoted a company's ISMS certification acquisition. And it would further be beneficial to your company's information security activities.