• Journal of the Korean Association of Geographic Information Studies
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• v.18 no.3
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• pp.76-88
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• 2015

This paper presents a classification method based on the combination of active learning with temporal contextual information extracted from past land-cover maps for the classification of crop cultivation areas. Iterative classification based on active learning is designed to extract reliable training data and cultivation rules from past land-cover maps are quantified as temporal contextual information to be used for not only assignment of training data but also relaxation of spectral ambiguity. To evaluate the applicability of the classification method proposed in this paper, a case study with MODIS time-series vegetation index data sets and past cropland data layers(CDLs) is carried out for the classification of corn and soybean in Illinois state, USA. Iterative classification based on active learning could reduce misclassification both between corn and soybean and between other crops and non crops. The combination of temporal contextual information also reduced the over-estimation results in major crops and led to the best classification accuracy. Thus, these case study results confirm that the proposed classification method can be effectively applied for crop cultivation areas where it is not easy to collect the sufficient number of reliable training data.

• The Magazine of the IEIE
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• v.11 no.5
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• pp.42-50
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• 1984

국내의 다음세대 컴퓨터 개발을 위한 VLSI 설계와 CAD 분야에 대한 연구 방향을 제시한다. 연구의 목표는 국제적으로 경쟁할 수 있는 VLSI 설계능력과 백만개 정도의 트랜지스터로 자성된 회로를 경제적으로 설계하기 위한 CAD 기술과 System의 확립이다. ·새로운 회로 구조와 알고리즘에 대한 연구 · CAD 도구와 언어의 개발에 관한 첨단 CAD 기술개발연구 · VLSI 설계에 필요한 CAD 도구 이용과 개발에 필요한 표준 인터페이스, 네트워킹, 컴퓨팅 하드웨어. 시스템 소프트웨어에 대한 연구등의 부분으로 크게 나눌 수 있다. 이용 가능한 CAD system을 평가하고 개선하며 첨단 CAD에 대한 소프트웨어와 하드웨어에 대해 · 컴퓨팅 하드웨어 · 프로그램 분위기 · 네트워킹 능력 ·자료 교환을 위한 표준인터페이스 등에 관해 조사분석도 병행한다. CAD에 관한 세부적인 연구 과제는 · 시스템 사양언어 · 설계 검증 ·시스템시뮬레이션· 설계 합성 · 설계 해석· 설계 방법론·디바이스와 공정 모델링 프로그램 등이다. 고속 계산용 VLSI에 관한 구조와 알고리즘은 행렬 계산을 위한 ·분산 배열 처리 회로 ·시스토릭 (Systolic) 배열 회로 ·셀률라(Cellular) 논리 회로 · 3차원 배열 회로 와 · 비규칙적 계산 알고리즘을 갖는 VLSI가 있다. VLSI설계훈련과 CAD 기술 축적을 위해 CAD enter를 설립하여 전국적인 CAD 네트워킹을 관계 연구소와 여러 대학에 가설하며, MPC 계획을 추진한다. VLSI설계 가능성이 입증되면 VLSI 설계능력을 더욱 향상 시키기 위해 0.5∼1.0mm기술의 silicon faundary를 설립한다. 연구 개발 조직은 대학, 산업체. 연구소가 삼위일체가 되어 수행될 수 있도록 연구 개발 위원회를 설치 운영하며 경쟁적이며 경제적으로 연구 업무를 집행하는 것이 바람직하다.았다.형질에 관여하는 귀전자에 미치는 기구에 대하여 검토할 여타가 있다고 보여진다. 분해능의 특징으로 미루어 앞으로는 레이저를 이용한 계측 방법이 그 주류를 이룰 것으로 사료된다. 우선 본 해설은 기체의 온도 및 농도의 광학적 측정방법중 Raman산란광 검출법에 대하여 실제로 측정하는 입장에서 간단히 소개한다.lity)이, 높은 $GA_3$함량에 기인된다'는 주장은 본실험(本實驗)으로 부인(否認)되었다. 따라서, 응용학적(應用學的) 측면에서 고려해 볼 때, 리베스식물(植物)의 육종기간 단축을 위한 모든 화아분화(花芽分化) 촉진 조치는 P.J.-식물(植物)이 20. node이상 생육하였을 때 취하는 것이 효율적인 것으로 결론 지어진다.앞당겨진 7月 셋째 週였다. 8. Culex (Culex) tritaeniorhynchus summoro년의 最大發生 peak는 1981年, 1982年 모두 8月 둘째 週였다. 9. Anopheles (Anopheles) sinensis의 最大發生 peak는 1981年에 7月 다섯째 週, 1982年은 2週 앞당겨진 7月 셋째 週였다. 10. 重要 3種의 最大 peak를 比城하면 Culex (Culex) pipiens pallens와 Anopheles (Anopheles) sinensis는 1981年과 1982年 모두 最大 peak時期가 同一하였으며, Culex (Culex) tritaeniorhynchus summoro년는 2年間 모두 8月둘째 週에 나타났다.osterior to manubrium and anterior to aortic arch) replacing the normal mediastinal fat. (2) In benign thymoma, the marging of the mass was smooth and the normal fat

• Journal of the Institute of Electronics Engineers of Korea CI
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• v.49 no.2
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• pp.29-37
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• 2012

An experiment for an optimized automatic greenhouse environment in a flower farming greenhouse by building a ubiquitous sensor network with various sensors was conducted and the results were evaluated. And various culturing environmental information and data in the greenhouse were collected and analyzed. Then, the greenhouse was designed to maintain the best culturing environment on the basis of existing recommended optimized figures. By measuring the growth of the crops in the greenhouse, A system which controls facilities in the greenhouse to maintain the best culturing environment in accordance with change in the environment was analyzed.Computer simulation result proced that we discovered that controlling the facilities and the artificial light source increased production, enhanced quality, reduced labor and heating cost immensely. The experiment has proved that the u-flower farming system can maximize the income of farm families by sending warning messages to users of this system when weather suddenly changes so that users may cope with such changes and maintain the best culturing environment.

• Proceedings of the KSCN Conference
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• 2003.11a
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• pp.1089-1090
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• 2003

본 연구는 대구ㆍ경북지역 대장직장암 환자의 일반 생활 상황과 식행동 특성을 분석 평가하여 지역민의 대장직장암 예방을 위한 영양교육에 활용할 수 있는 식생활 관련 기초 자료를 얻고자 수행되었다. 최근 경북대학교 병원에서 대장직장암 진단을 받고 입원한 수술 전후 환자 123명 (남 79명, 여 44명)을 환자군 대상으로 하였고 대장질환이 없는 정형외과 환자 등 182명(남 117명, 여 65명)을 비교군 대상으로 하였다. 대상자의 일반 특성, 식습관, 식행동 특성, 식품섭취 빈도 등의 내용을 포함한 설문지를 이용하여 개인 면담을 통하여 조사하였다. 현재 BMI와 과거 가장 높았던 체중의 BMI는 남녀 모두 환자군에서 유의하게 높게 나타났다. 환자군의 교육 수준은 비교군에 비해 낮았고 주 거주지역 분포는 농촌이 가장 많았으며 가계 소득은 환자군에서 비교군에 비하여 높은 것으로 나타났다. 주요 일상활동 강도는 비교군에 비해 환자군에서 유의적으로 가벼운 것으로 나타났다. 발병 전 일상생활에서 느끼는 스트레스의 정도가 환자군에서 비교군에 비해 유의적으로 높았던 것으로 나타났다. 자신의 성격 유형을 비관적인 것으로 생각하는 비율과 가족의 암 병력이 환자군에서 유의적으로 높게 나타났다 식사의 규칙성에서도 환자군에서 끼니를 거르는 비율이 유의적으로 높았다. 환자군은 비교군에 비해 육식을 유의적으로 높게 선호하였으며 외식시 고기류를 선호하는 비율이 높았다. 평소 물 섭취량은 환자군에서 비교군에 비해 적었다. 환자군이 비교군에 비해 짠맛에 대한 선호도가 유의적으로 높았고 단 맛과 매운 맛은 비교군에 비해 싫어하는 경향을 보였으며 기름진 맛을 선호하는 경향이 환자군에서 유의하게 높았다. 환자군에서 굽기, 튀기기를 좋아하는 경향이 유의적으로 높았다. 환자군에서 음주 빈도, 음주량 그리고 커피 섭취량이 높게 나타났으며, 1일 흡연량이 많았고, 흡연 시작 연령은 빨랐으며, 금연 연령은 늦어 흡연 기간이 유의적으로 긴 것으로 나타났다. 환자군의 영양지식 정도와 영양태도는 비교군에 비해 유의적으로 낮았고 환자군의 영양지식 수준이 높을수록 좋은 영양태도를 가지는 것으로 나타났다. 과거 10년간 식품 섭취 빈도 조사 결과 환자군은 등푸른 생선류와 콩류 및 된장, 두부를 비교군에 비해 유의적으로 더 많이 섭취하였고 해조류, 생 녹황색채소류, 익힌 녹황색 및 담색채소류와 녹차를 더 적게 섭취한 것으로 나타났다. 본 연구의 결과는 일상생활의 스트레스와 가족의 암 병력 및 비관적 성격 유형이 대장직장암 발병의 위험인자가 될 수 있음을 제시하며 육식 선호, 적은 양의 물 섭취, 짜고 기름진 맛에 대한 높은 기호도, 음주, 흡연, 커피의 섭취 그리고 나쁜 식습관이 대장직장암 발생과 관련된 식생활 위험인자가 될 수 있음을 제시한다. 해조류, 녹황색채소, 담색채소, 녹차가 대장직장암 발생의 보호인자의 가능성도 제시되었다. 따라서 향후 지역적 식문화 특성을 고려한 보다 광범위하고 체계적인 조사 연구를 통해 이 지역의 대장직장암 발생의 위험인자와 보호인자를 재확인할 필요가 있다고 보며 본 연구의 결과는 지역민의 대장직장암 예방을 위한 영양교육 자료로서 활용될 수 있다고 본다.

• Journal of Bio-Environment Control
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• v.10 no.1
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• pp.42-49
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• 2001

This study was carried out to develop a fuzzy control technique of ventilation window for controlling a temperature in a greenhouse. To reduce the fuzzy variables, the inside air temperature shop was taken as one of fuzzy variables, because the inside air temperature variation of a greenhouse by ventilation at the same window aperture is affected by difference between inside and outside air temperature, outside wind speed and the wind direction. Therefore, the antecedent variables for fuzzy algorithm were used the control error and its slop, which was same value as the inside air temperature slop during the control period, and the conclusion variable was used the window aperture opening rate. Through the basic and applicative control experiment with the control period of 3 minutes the optimum ranges of fuzzy variables were decided. The control error and its slop were taken as 3 and 1.5 times compared with target error in steady state, and the window opening rate were taken as 30% of full size of the window aperture. To evaluate the developed fuzzy algorithm in which the optimized 19 rules of fuzzy production were used, the performances of fuzzy control and PID control were compared. The temperature control errors by the fuzzy control and PID control were lower than 1.3$^{\circ}C$ and 2.2$^{\circ}C$ respectively. The accumulated operating size of the window, the number of operating and the number of inverse operating for the fuzzy control were 0.4 times, 0.5 times and 0.3 times of those compared with the PID control. Therefore, the fuzzy control can operating the window more smooth and reduce the operating energy by 1/2 times of PID control.

• The Transactions of the Korea Information Processing Society
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• v.7 no.11S
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• pp.3702-3713
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• 2000

Telecommunications standards have two different types of regulations: one is a law. enacted by government which all telecommunications related industries must observe. The other is a recommendatory standards. formulated by either government agency or some standardization organizations. Observation of these standards is not obligatory. However, technical standards are strict laws and ordinances based on common judgement and various conditions for evaluation of levels and limits. This paper deals with enhancing productivity of enactment and revision of technical standards. Through database of above related information we secure information continuity and public property of cyber space for the public. In this paper. we also classify recent data within the website in and out of the country offering four different methods of information retrieval and management system. The four retrieval methods suggested in this paper are itemized keyword retrieval. hierarchical retrieval, regulatory keyword retrieval and chronological keyword retrieval. These various retrieval methods provide the public with information of enactment and amendment of laws and regulations in the cyber space. thereby guarantees the sharing of information. Finally the important feature of the information retrieval system implemented in this paper is the online updating capability of law and regulations through the internet.

• Journal of Internet Computing and Services
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• v.17 no.6
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• pp.123-131
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• 2016

Process mining in big data environment utilize a number of data were generated from the business process. It generates lots of knowledge and insights regarding implementation and improvement of the process through the event log of the company's enterprise resource planning (ERP) system. In recent years, various research activities engaged with the audit work of company organizations are trying actively by using the maximum strength of the mining process. However, domestic studies on applicable sales auditing system for the process mining are insufficient under big data environment. Therefore, we propose process-mining methods that can be optimally applied to online and traditional auditing system. In advance, we propose continuous monitoring information system that can early detect and prevent the risk under the big data environment by monitoring risk factors in the organizations of enterprise. The scope of the research of this paper is to design a pre-verification system for risk factor via practical examples in sales auditing. Furthermore, realizations of preventive audit, continuous monitoring for high risk, reduction of fraud, and timely action for violation of rules are enhanced by proposed sales auditing system. According to the simulation results, avoidance of financial risks, reduction of audit period, and improvement of audit quality are represented.

• Journal of the Korea Academia-Industrial cooperation Society
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• v.12 no.9
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• pp.3887-3896
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• 2011

This study was intended to measure the level of psychosocial stress among nurses working for a university hospital and to reveal its related factors. The self-administered questionnaires were given to 450 nurses during the period from October 1st to 31st, 2010. As a results, the level of psychosocial stress was 10.2% in normal group, 64.0% in potential stresses group, and 25.8% in high risk stress group. In correlation, psychosocial stress was positively correlated with job demand, but it was negatively correlated with job autonomy, supervisor and colleague support. For the results of hierarchial multiple regression analysis, the level of psychosocial stress was influenced by the variables of regular exercise, quality of sleep, subjective status of health, shift work, fit to the job, job demand, job autonomy and supervisor support. Especially, the psychosocial stress was higher related with the contents of job stress increased with explanatory powers of 18.1% on the psychosocial stress.

• Journal of KIISE
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• v.42 no.8
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• pp.998-1009
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• 2015

In recent years, there has been a growing interest in RDFS Inference to build a rich knowledge base. However, it is difficult to improve the inference performance with large data by using a single machine. Therefore, researchers are investigating the development of a RDFS inference engine for a distributed computing environment. However, the existing inference engines cannot process data in real-time, are difficult to implement, and are vulnerable to repetitive tasks. In order to overcome these problems, we propose a method to construct an in-memory distributed inference engine that uses a parallel graph structure. In general, the ontology based on a triple structure possesses a graph structure. Thus, it is intuitive to design a graph structure-based inference engine. Moreover, the RDFS inference rule can be implemented by utilizing the operator of the graph structure, and we can thus design the inference engine according to the graph structure, and not the structure of the data table. In this study, we evaluate the proposed inference engine by using the LUBM1000 and LUBM3000 data to test the speed of the inference. The results of our experiment indicate that the proposed in-memory distributed inference engine achieved a performance of about 10 times faster than an in-storage inference engine.

• Journal of the Institute of Electronics and Information Engineers
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• v.53 no.3
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• pp.59-66
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• 2016

This paper presents an empirical evaluation on dimensionality reduction strategies by which dissimilarity-based classifications (DBC) can be implemented efficiently. In DBC, classification is not based on feature measurements of individual objects (a set of attributes), but rather on a suitable dissimilarity measure among the individual objects (pair-wise object comparisons). One problem of DBC is the high dimensionality of the dissimilarity space when a lots of objects are treated. To address this issue, two kinds of solutions have been proposed in the literature: prototype selection (PS)-based methods and dimension reduction (DR)-based methods. In this paper, instead of utilizing the PS-based or DR-based methods, a way of performing DBC in Eigen spaces (ES) is considered and empirically compared. In ES-based DBC, classifications are performed as follows: first, a set of principal eigenvectors is extracted from the training data set using a principal component analysis; second, an Eigen space is expanded using a subset of the extracted and selected Eigen vectors; third, after measuring distances among the projected objects in the Eigen space using $l_p$-norms as the dissimilarity, classification is performed. The experimental results, which are obtained using the nearest neighbor rule with artificial and real-life benchmark data sets, demonstrate that when the dimensionality of the Eigen spaces has been selected appropriately, compared to the PS-based and DR-based methods, the performance of the ES-based DBC can be improved in terms of the classification accuracy.