• Journal of Intelligence and Information Systems
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• v.25 no.2
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• pp.77-97
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• 2019

The large amount of data that emerges from the initial connection environment of the Fourth Industrial Revolution is a major factor that distinguishes the Fourth Industrial Revolution from the existing production environment. This environment has two-sided features that allow it to produce data while using it. And the data produced so produces another value. Due to the massive scale of data, future information systems need to process more data in terms of quantities than existing information systems. In addition, in terms of quality, only a large amount of data, Ability is required. In a small-scale information system, it is possible for a person to accurately understand the system and obtain the necessary information, but in a variety of complex systems where it is difficult to understand the system accurately, it becomes increasingly difficult to acquire the desired information. In other words, more accurate processing of large amounts of data has become a basic condition for future information systems. This problem related to the efficient performance of the information system can be solved by building a semantic web which enables various information processing by expressing the collected data as an ontology that can be understood by not only people but also computers. For example, as in most other organizations, IT has been introduced in the military, and most of the work has been done through information systems. Currently, most of the work is done through information systems. As existing systems contain increasingly large amounts of data, efforts are needed to make the system easier to use through its data utilization. An ontology-based system has a large data semantic network through connection with other systems, and has a wide range of databases that can be utilized, and has the advantage of searching more precisely and quickly through relationships between predefined concepts. In this paper, we propose a defense ontology as a method for effective data management and decision support. In order to judge the applicability and effectiveness of the actual system, we reconstructed the existing air force munitions situation management system as an ontology based system. It is a system constructed to strengthen management and control of logistics situation of commanders and practitioners by providing real - time information on maintenance and distribution situation as it becomes difficult to use complicated logistics information system with large amount of data. Although it is a method to take pre-specified necessary information from the existing logistics system and display it as a web page, it is also difficult to confirm this system except for a few specified items in advance, and it is also time-consuming to extend the additional function if necessary And it is a system composed of category type without search function. Therefore, it has a disadvantage that it can be easily utilized only when the system is well known as in the existing system. The ontology-based logistics situation management system is designed to provide the intuitive visualization of the complex information of the existing logistics information system through the ontology. In order to construct the logistics situation management system through the ontology, And the useful functions such as performance - based logistics support contract management and component dictionary are further identified and included in the ontology. In order to confirm whether the constructed ontology can be used for decision support, it is necessary to implement a meaningful analysis function such as calculation of the utilization rate of the aircraft, inquiry about performance-based military contract. Especially, in contrast to building ontology database in ontology study in the past, in this study, time series data which change value according to time such as the state of aircraft by date are constructed by ontology, and through the constructed ontology, It is confirmed that it is possible to calculate the utilization rate based on various criteria as well as the computable utilization rate. In addition, the data related to performance-based logistics contracts introduced as a new maintenance method of aircraft and other munitions can be inquired into various contents, and it is easy to calculate performance indexes used in performance-based logistics contract through reasoning and functions. Of course, we propose a new performance index that complements the limitations of the currently applied performance indicators, and calculate it through the ontology, confirming the possibility of using the constructed ontology. Finally, it is possible to calculate the failure rate or reliability of each component, including MTBF data of the selected fault-tolerant item based on the actual part consumption performance. The reliability of the mission and the reliability of the system are calculated. In order to confirm the usability of the constructed ontology-based logistics situation management system, the proposed system through the Technology Acceptance Model (TAM), which is a representative model for measuring the acceptability of the technology, is more useful and convenient than the existing system.

• KOREAN JOURNAL OF CROP SCIENCE
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• v.66 no.2
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• pp.155-170
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• 2021

Oats (Avena sativa L.) represent a good forage crop for cultivation in regions with short growing periods and/or cool weather, such as the mountainous areas of southern Korea. In this study, using the Korean elite summer oat varieties 'High speed' and 'Dark horse', we aimed to determine the optimal time to plant and harvest forage oats seeded in spring and summer in a mountainous area. Seeds were planted three times from late February and early August at 9- or 10-days intervals, respectively, and plants were harvested three times from late May to October at 10-day intervals. The experiment was carried out in an upland field (Jangsu-gun Jeonbuk) in 2015 and 2016. We investigated the changes in forage yield (FY) and quality [crude protein (CP) and total digestible nutrient (TDN) contents] based on the time of planting and harvest. Neither the forage quality nor yield of either spring and summer oats was significantly influenced by the time of planting. The CP of spring oats harvested three times at 10-day intervals from late May was 12.0%, 8.2%, and 6.5%, thereby indicating a reduction with a delay in the time of harvest. In summer oats, CP ranged from 8.4% to 8.7%, although unlike CP in spring oats, was not significantly influenced by the time of harvest. For both forage types, harvest time had no significant effect on TDN. The FY of spring oats harvested in late May and early and mid-June was 10.2, 18.7, and 19.5 ton ha^-1, respectively, with that of oats harvested on the latter two dates being significantly increased by 83% and 91%, respectively, compared with that in late May. Similarly, the FY of spring oats harvested in late October and early and mid-November was 7.1, 12.5, and 12.1 ton ha^-1, respectively, with that of oats harvested on the latter two dates being significantly increased by 75% and 71%, respectively, compared with that in late October. Taking into consideration forage yield and quality (not less than 8% CP), it would be profitable to plant spring oats in the mountainous areas of southern Korea until March 15 and harvest around June 10, whereas summer oats could be beneficially planted until August 25 and harvested from early November.

• Journal of Intelligence and Information Systems
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• v.24 no.3
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• pp.67-88
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• 2018

Until recently, as we recognize the significance of sustainable growth and competitiveness of small-and-medium sized enterprises (SMEs), governmental support for tangible resources such as R&D, manpower, funds, etc. has been mainly provided. However, it is also true that the inefficiency of support systems such as underestimated or redundant support has been raised because there exist conflicting policies in terms of appropriateness, effectiveness and efficiency of business support. From the perspective of the government or a company, we believe that due to limited resources of SMEs technology development and capacity enhancement through collaboration with external sources is the basis for creating competitive advantage for companies, and also emphasize value creation activities for it. This is why value chain network analysis is necessary in order to analyze inter-company deal relationships from a series of value chains and visualize results through establishing knowledge ecosystems at the corporate level. There exist Technology Opportunity Discovery (TOD) system that provides information on relevant products or technology status of companies with patents through retrievals over patent, product, or company name, CRETOP and KISLINE which both allow to view company (financial) information and credit information, but there exists no online system that provides a list of similar (competitive) companies based on the analysis of value chain network or information on potential clients or demanders that can have business deals in future. Therefore, we focus on the "Value Chain Network System (VCNS)", a support partner for planning the corporate business strategy developed and managed by KISTI, and investigate the types of embedded network-based analysis modules, databases (D/Bs) to support them, and how to utilize the system efficiently. Further we explore the function of network visualization in intelligent value chain analysis system which becomes the core information to understand industrial structure ystem and to develop a company's new product development. In order for a company to have the competitive superiority over other companies, it is necessary to identify who are the competitors with patents or products currently being produced, and searching for similar companies or competitors by each type of industry is the key to securing competitiveness in the commercialization of the target company. In addition, transaction information, which becomes business activity between companies, plays an important role in providing information regarding potential customers when both parties enter similar fields together. Identifying a competitor at the enterprise or industry level by using a network map based on such inter-company sales information can be implemented as a core module of value chain analysis. The Value Chain Network System (VCNS) combines the concepts of value chain and industrial structure analysis with corporate information simply collected to date, so that it can grasp not only the market competition situation of individual companies but also the value chain relationship of a specific industry. Especially, it can be useful as an information analysis tool at the corporate level such as identification of industry structure, identification of competitor trends, analysis of competitors, locating suppliers (sellers) and demanders (buyers), industry trends by item, finding promising items, finding new entrants, finding core companies and items by value chain, and recognizing the patents with corresponding companies, etc. In addition, based on the objectivity and reliability of the analysis results from transaction deals information and financial data, it is expected that value chain network system will be utilized for various purposes such as information support for business evaluation, R&D decision support and mid-term or short-term demand forecasting, in particular to more than 15,000 member companies in Korea, employees in R&D service sectors government-funded research institutes and public organizations. In order to strengthen business competitiveness of companies, technology, patent and market information have been provided so far mainly by government agencies and private research-and-development service companies. This service has been presented in frames of patent analysis (mainly for rating, quantitative analysis) or market analysis (for market prediction and demand forecasting based on market reports). However, there was a limitation to solving the lack of information, which is one of the difficulties that firms in Korea often face in the stage of commercialization. In particular, it is much more difficult to obtain information about competitors and potential candidates. In this study, the real-time value chain analysis and visualization service module based on the proposed network map and the data in hands is compared with the expected market share, estimated sales volume, contact information (which implies potential suppliers for raw material / parts, and potential demanders for complete products / modules). In future research, we intend to carry out the in-depth research for further investigating the indices of competitive factors through participation of research subjects and newly developing competitive indices for competitors or substitute items, and to additively promoting with data mining techniques and algorithms for improving the performance of VCNS.

• Proceedings of the Korean Society for Food Science of Animal Resources Conference
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• 1995.11a
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• pp.1-48
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• 1995

식생활은 인간 생활의 주체이고 먹는다는 것은 그 수단이다. 그중 중요한 하나의 명제는 인간이 놓여진 여러 환경에서 어떻게 건강을 유지하고 그 개체가 소유하고 있는 능력을 최대치까지 생리적으로 성장 발전시킴과 동시에 최대한 수명을 연장시키기 위한 식물 섭취방법을 마이크로 레벨까지 해명하는데 있다. 인간은 일생동안 엄청난 양의 음식물을 먹는다(70세 수명일 경우 200만 파운드 즉 체중의 1,400배). 그러나 먹기는 먹되 자신의 건강과 장수를 위하여 어떤 음식을 어떻게 선택하여 어떻게 먹어야 하는 문제가 매우 중요하다. 최근 우리나라도 국민 소득이 늘면서 식생활은 서구화 경향으로 기우는 듯하다. 공해를 비롯한 수입식품 등 여러 가지 문제점이 제기됨에 따라 자연식과 건강식을 주장하는 소리가 높이 일고 있다. 그중에는 축산 식품이 콜레스테롤 함량이 다른 식품에 비하여 높게 함유하고 있다는 것으로 심혈관질환의 주범인양 무차별 강조하는 나머지 육식공포 내지는 계란 등의 혐오감 마저 불러 일으키는 경향까지 있는 듯하다. 따라서 본논고에서는 축산식품중의 콜레스테롤 함량수준이 과연 성인병의 주범인지 아니면 다른 지방산과 관련해서 올바르게 평가하고 그 문제점과 대책을 개관해 보고 요약하면 다음과 같다. 1. 사람은 유사이래 본능적으로 주변의 식물이나 동물의 고기를 먹고 성장하여 자손을 증식시키고 어느 사이에 늙으면 죽음을 맞이 하는 싸이클을 반복하면서 기나긴 세월동안 진화를 하여 오늘날의 인간으로서의 자태를 이루었다. 유인원과 같은 인류의 선조들은 수렵을 통해 육식을 많이 하였을 것이므로 인간은 원래 육식동물이 아닐까? 구석기시대의 유물을 보면 많은 뼈가 출토되고 “얄타미라”나 “라스코” 동굴벽화가 선명하게 묘사되고 있다. 2. 우리나라 선조 승구족의 일파가 백두산을 비롯한 만주 송화강 유역에 유입되면서 수렵과 목축을 주요 식품획득의 수단으로 식품문화권을 형성하면서 남하하여 한반도 민족의 조상인 맥족(貊族)으로 맥적(貊炙)이라고 하는 요리(오늘날의 불고기)를 먹었다는 기록이 있다. 3. 인간의 수명을 1900년대로 거슬러 올라가서 뉴질랜드가 세계최장수국(호주는 2위)로서 평균수명은 남자 58세, 여자 69세인 반면 일본과 한국은 당시 남자 36세, 여자 37세이던 것이 일본은 1989년에 이르러 세계 최장수국으로 등장했으나 1990년 당시 뉴질랜드${\cdot}$호주 등은 목축 및 밀(小麥) 생산국가였기 때문이라는 것과 일본은 오늘날 합리적인 식생활 국가라는 것을 간과해서는 안된다. 4. 우리나라 10대 사망원인중 (1994년도) 뇌혈관질환이 1위, 교통사고 2위, 암이 3위 순위로서 연령별로는 10~30대의 불의의 사고(교통사고), 40~60대는 암, 70대 이상은 뇌혈관질환이 가장 많다. 구미${\cdot}$일 7개국 정상국가들은 심질환 사망이 가장 높다. 5. 식생활의 변화에 있어서 우리나라는 주식으로 섭취해 왔던 곡류는 70년 대비 94년에는 0.7배 감소된 반면 육류 5배, 계란 2.4배, 우유는 무려 29.3배 증가되었다. 식생활 패턴이 서구화 경향으로 바뀌는 것 같다. 6. 71년도 우리나라의 지질섭취량은 국민 1인당 1일 평균 13.1g에 섭취에너지의 5.7%수준이었으나 92년도에는 34.5g으로서 총에너지 섭취량의 16.6%에 달하고 총섭취 지방질중 동물성 섭취 비율은 47%를 차지 한다. 국민 평균 혈청콜레스테롤 농도는 80년에 비해 88년에는 11%가 증가되었고 80년에 210mg/dl 이상 되는 콜레스테롤 혈증인 사람의 비율이 5%에서 88년에는 23%로 크게 증가했다. 7. 세계 정상국가들의 단백질 즉 축산식품의 섭취는 우리나라보다 적게는 2배, 많게는 6~7배 더 섭취하고 90년도 우리나라의 지질섭취량은 일본의 1/3수준에 불과하다. 8. 콜레스테롤은 인체를 비롯한 모든 동물체에 필수적으로 분포하고 있는 것으로 체내 존재하고 있는 총량은 90~150g, 이중 혈청콜레스테롤은 4%(6g)를 차지하고 있음에도 불구하고 이 아주 적은 콜레스테롤에 일희일비(一喜一悲) 논쟁은 60~70년 끄러오고 있다. 9. 콜레스테롤의 생체내 기능으로서는 (1) 세포벽의 지지물질 (2) 신경세포 보호막물질 (3) 담즙산의 합성 (4) 비타민 D의 합성 (5) 임신시에 반듯이 필요한 분자 (6) 기타 여러 가지 기능을 수행하는 것으로 필수적인 물질이다. 10. 우리가 식이를 통해서 섭취 콜레스테롤을 550mg정도를 섭취한다고 하더라도 이 정도의 양은 배설 소모되는 양과 거의 맞먹는 양이다. 피부와 땀샘에서 소실되는 양만도 100~300mg에 달하기 때문에 미국농무성에서 섭취량을 300mg로 제한하는 것은 무의미하다. 11. 콜레스테롤 운반체로서의 지단백질은 그 밀도가 낮은 것으로부터 킬로미크론(chylomicron), 초저밀도 지단백질(VLDL), 저밀도 지단백질(LDL) 및 고밀도 지단백질(HDL)으로 나누는데 LDL은 혈청콜레스테롤 중 약 70%, HDL은 약20%를 함유한다. 12. 혈중 콜레스테롤 수준에 영향을 미치는 요인을 열거하여 보면 다음과 같다. 1) 음식을 통해서 섭취되는 콜레스테롤 중 단지 10~40%정도가 흡수되고, 체내에서 합성되는 콜레스테롤이 증가할수록 식이콜레스테롤은 실제 혈청콜레스테롤 수준에 거의 영향을 미치지 않으므로 식이중함량에 대하여 공포를 느끼고 기피할 필요가 없다. 2) 고도불포화지방산, 단가불포화지방산, 포화지방산의 비 즉 P/M/S의 비가 균형되도록 권장한다. 3) 동맥경화를 비롯한 성인병의 원인이 되는 혈전증에는 EPA의 양을 높여줌으로서 성인병을 예방할 수 있다. 4) 오메가6지방산 아라키도닉산과 오메가3지방산인 EPA로 유도되는 에이코사에노이드 또는 프로스타노이드는 오메가6와 3지방산을 전구체로 하여 생합성되는 중요한 생리활성 물질이다. 5) 사람은 일반적으로 20세에서 60세까지 나이를 먹어감에 따라 혈중 콜레스테롤 수준이 증가하고 60세 이후부터는 일정한 수준을 유지하며 심장보호성 HDL-콜레스테롤은 감소하는 반면에 죽상경화성 LDL콜레스테롤은 증가한다. 6) 높은 HDL콜레스테롤 수준이 심장병 발생 위험요인을 감소시키는 기능을 갖고 있기 때문에 좋은 HDL이라 부르고, LDL은 나쁜 콜레스테롤이라 부르기도 하는데, 이것은 유전적 요인보다도 환경적 요인이 보다 큰 영향을 미친다. 7) 이것은 생활 형태와 영양섭취상태를 포함해서 개인적 생활패턴에 영향을 받는다. 8) 많은 실험에서 혈중 콜레스테롤 상승은 노년의 가령(加齡)에 적응하기 위한 자연적 또는 생리적인 세포의 생화학적이고 대사적인 기능을 위해 필수적일 수 있다는 것을 간과해서는 안될 것이다. 이 점으로 미루어 노년의 여성들을 위한 콜레스테롤 농도를 200mg/dl이 가장 알맞은 양이 아닌 듯하다. 9) 스트레스는 두가지 모양으로 유발되는데 해로은 스트레스(negative), 이로운 스트레스(positive)로서 긴장완화는 혈중 콜레스테롤 농도를 10% 떨어진다. 10) 자주 운동을 하는 사람들은 혈중 HDL콜레스테롤치가 운동을 하지 않는 사람보다 높다. 육체적인 운동의 정도와 혈중 HDL콜레스테롤 농도와는 정비례한다. 11) 흡연은 지방을 흡착시키므로 혈전증의 원이이 되며 혈관속의 HDL농도를 감소시킨다. 12) 에너지의 과잉섭취에 의한 체중 증가느 일반적으로 지단백질대사에 영향을 미치고, 간에서는 콜레스테롤 과잉 생산과 더불어 VLDL콜레스테롤의 LDL콜레스테롤 혈증을 나타냄으로 운동과 더불어 비만이 되지 않도록 하여야 한다. 13. 콜레스테롤 함량에 대한 조절기술 1) 식품의 우열을 평가할 때 단순히 동물성 또는 식물성 식품으로 분류해서 총괄적으로 논한다는 것은 지양되어야 한다. 이것은 그 식품에 함유하고 있는 지방산의 종류에 따라서 다르기 때문이다. 2) 인체의 원할한 기능 유지를 위해서는 P /M /S비율 뿐만 아니라 섭취 지방질의 오메가6 /오메가3계 지방산의 비율이 모두 적절한 범위에 있어야 하며 한두가지 지방산만이 과량일 때는 또 다른 불균형을 일으킬 수 있다는 점을 알아야 한다. 3) 닭고기는 오메가6지방산 함량을 높이기 위하여 사료중에 등푸른 생선이나 어분이나 어유를 첨가하여 닭고기는 첨가수준에 따라 증가됨을 알 수 있다. 4) 오늘날 계란내의 지방산 조성을 변화시켜 난황내의 오메가 3계열 지방산 함량을 증가시킨 계란의 개발이 활발해졌다. 14. 계란 콜레스테롤에 대한 소비자들의 부정적 인식을 불식시키고자 계란의 클레스테롤 함량을 낮추는 과제가 등장하면서 그 기술개발이 여러모로 시도되고 있으나 아직 실용 단계에 이르지 못했다. 15. 계란의 콜레스테롤 문제에 대한 대책으로서 난황의 크기를 감소시키는 방법에 대한 연구도 필요하다. 16. 계란 중 콜레스테롤 함량 분석치는 표현 방식에 따라서 소비자들을 혼란시킬 가능성이 있다. 또한 과거에는 비색법으로 분석했으나 오늘날은 효소법으로 분석하면 분석치에 상당한 차이가 있다. 17. 소비자의 요구를 만족시키고 버터 소비를 촉진시키기 위해 콜레스테롤을 감소시키는 물리적${\cdot}$생물학적 방식이 제안되어 있으나 현장적용이 가능한 것은 아직 없다. 18. 우리나라에서 이미 시판되고 있는 DHA우유가 선보였고 무콜레스테롤 버터의 경우 트란스(trans)형 지방산에 관해서는 논란의 여지가 많을 것이다. 끝으로 국가 목표의 하나는 복지사회 건설에 있고 복지국가 실현에는 국민 기본 욕망의 하나인 식생활 합리화가 선행되어야 한다. 소득이 늘고 국가가 발전해감에 따라 영양식${\cdot}$건강식 및 기호식을 추구하게 됨을 매우 당연한 추세라 하겠다. 우리의 식생활이 날로 향상되어 지난날의 당질 위주에서 점차 축산물쪽으로 질적 개선이 이루어진다는 것은 고무적임에 틀림없다. 이 축산물을 통한 풍요로운 식의 문화를 창출하면서 건강과 장수 그리고 후손에 이르기까지 번영하고 국가 경쟁력 강화에 심혈을 기우려야 할 때이다.

• Journal of Intelligence and Information Systems
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• v.19 no.3
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• pp.1-23
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• 2013

To discover significant social issues such as unemployment, economy crisis, social welfare etc. that are urgent issues to be solved in a modern society, in the existing approach, researchers usually collect opinions from professional experts and scholars through either online or offline surveys. However, such a method does not seem to be effective from time to time. As usual, due to the problem of expense, a large number of survey replies are seldom gathered. In some cases, it is also hard to find out professional persons dealing with specific social issues. Thus, the sample set is often small and may have some bias. Furthermore, regarding a social issue, several experts may make totally different conclusions because each expert has his subjective point of view and different background. In this case, it is considerably hard to figure out what current social issues are and which social issues are really important. To surmount the shortcomings of the current approach, in this paper, we develop a prototype system that semi-automatically detects social issue keywords representing social issues and problems from about 1.3 million news articles issued by about 10 major domestic presses in Korea from June 2009 until July 2012. Our proposed system consists of (1) collecting and extracting texts from the collected news articles, (2) identifying only news articles related to social issues, (3) analyzing the lexical items of Korean sentences, (4) finding a set of topics regarding social keywords over time based on probabilistic topic modeling, (5) matching relevant paragraphs to a given topic, and (6) visualizing social keywords for easy understanding. In particular, we propose a novel matching algorithm relying on generative models. The goal of our proposed matching algorithm is to best match paragraphs to each topic. Technically, using a topic model such as Latent Dirichlet Allocation (LDA), we can obtain a set of topics, each of which has relevant terms and their probability values. In our problem, given a set of text documents (e.g., news articles), LDA shows a set of topic clusters, and then each topic cluster is labeled by human annotators, where each topic label stands for a social keyword. For example, suppose there is a topic (e.g., Topic1 = {(unemployment, 0.4), (layoff, 0.3), (business, 0.3)}) and then a human annotator labels "Unemployment Problem" on Topic1. In this example, it is non-trivial to understand what happened to the unemployment problem in our society. In other words, taking a look at only social keywords, we have no idea of the detailed events occurring in our society. To tackle this matter, we develop the matching algorithm that computes the probability value of a paragraph given a topic, relying on (i) topic terms and (ii) their probability values. For instance, given a set of text documents, we segment each text document to paragraphs. In the meantime, using LDA, we can extract a set of topics from the text documents. Based on our matching process, each paragraph is assigned to a topic, indicating that the paragraph best matches the topic. Finally, each topic has several best matched paragraphs. Furthermore, assuming there are a topic (e.g., Unemployment Problem) and the best matched paragraph (e.g., Up to 300 workers lost their jobs in XXX company at Seoul). In this case, we can grasp the detailed information of the social keyword such as "300 workers", "unemployment", "XXX company", and "Seoul". In addition, our system visualizes social keywords over time. Therefore, through our matching process and keyword visualization, most researchers will be able to detect social issues easily and quickly. Through this prototype system, we have detected various social issues appearing in our society and also showed effectiveness of our proposed methods according to our experimental results. Note that you can also use our proof-of-concept system in http://dslab.snu.ac.kr/demo.html.

• KOREAN JOURNAL OF CROP SCIENCE
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• v.8 no.1
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• pp.129-177
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• 1970

For the purpose of establishing the systematized technical scheme of the cooperative rice cultivation which has most significant impact to improve rice productivity and the farm management, the author have studied the cultivation practices, and the variation of rice growth and yield between the cooperative rice cultivation and the individual rice cultivation at random selected 18 paddy fields. The author also have investigated through comparative method on the cultivation practices, management, organization and operation scheme of the two different rice cultivation methods at 460 paddy fields. The economic feasibility has been ana lysed and added in this report. The results obtained from this study are summarized as follows; 1. In the nursery, the average amount of fertilizer application, especially, phosphate and potassium, and the frequency of chemicals spray for the disease, insect and pest control at the cooperative rice cultivation are significantly higher than those of the individual rice cultivation. 2. The cultivation techniques of the cooperative rice farming after the transplanting can be characterized by a) the earlier transplanting of rice, b) the denser hills per unit area and the lesser number of seedlings per hill, c) the application of larger quantities of fertilizer including nitrogen, phosphate and potassium, d) more divided application of fertilizers, split doses of the nitrogen and potassium, e) the increased frequencies of the chemicals spray for the prevention of disease, insect and pest damages. 3. The rate of lodging in the cooperative rice cultivation was slightly higher than that of the individual rice cultivation, however, the losses of rice yield owing to the occurrence of rice stem borer and grass leaf roller in the cooperative rice cultivation were lower than that of the individual rice cultivation. 4. The culm length, panicle length, straw weight and grain-straw ratio are respectively higher at the cooperative rice cultivation, moreover, the higher variation of the above factors due to different localities of the paddy fields found at the individual rice cultivation. 5. The number of panicles, number of flowers per panicle and the weight of 1, 000 grains, those contributing components to the rice yield were significantly greater in the cooperative rice cultivation, however, not clear difference in the maturing rate was observed. The variation coefficient of the yield component in the cooperative cultivation showed lower than that or the individual rice cultivation. 6. The average yield of brown rice per 10 are in the cooperative rice cultivation obtained 459.0 kilograms while that of the individual rice cultivation brought 374.8 kilograms. The yield of brown rice in the cooperative rice cultivation increased 84.2 kilogram per 10 are over the individual rice cultivation. With lower variation coefficient of the brown rice yield in the cooperative rice cultivation, it can be said that uniformed higher yield could be obtained through the cooperative rice cultivation. 7. Highly significant positive correlations shown between the seeding date and the number of flowers per panicle, the chemical spray and the number of flowers per panicle, the transplanting date and the number of flowers per panicle, phosphate application and yield, potassium application and maturing rate, the split application of fertilizers and yield. Whilst the significant negative correlation was shown between the transplanting date and the maturing rate 8. The results of investigation from 480 paddy fields obtained through comparative method on the following items are identical in general with those obtained at 18 paddy fields: Application of fertilizers, chemical spray for the control of disease, insects and pests both in the nursery and the paddy field, transplanting date, transplanting density, split application of fertilizers and yield n the paddy fields. a) The number of rice varieties used in the cooperative rice cultivation were 13 varieties while the individual rice cultivation used 47 varieties. b) The cooperative rice cultivation has more successfully adopted improved cultivation techniques such as the practice of seed disinfection, adoption of recommended seeding amount, fall ploughing, application of red soil, introduction of power tillers, the rectangular-type transplanting, midsummer drainage and the periodical irrigation. 9. The following results were also obtained from the same investigation and they are: a) In the cooperative rice cultivation, the greater part of the important practices have been carried out through cooperative operation including seed disinfection, ploughing, application of red soil and compost, the control of disease, insects and pests, harvest, threshing and transportation of the products. b) The labor input to the nursery bed and water control in the cooperative rice cultivation was less than that of the individual rice cultivation while the higher rate of labor input was resulted in the red soil and compost application. 10. From the investigation on the organization and operation scheme of the cooperative rice cultivation, the following results were obtained: a) The size of cooperative rice cultivation farm was varied from. 3 ha to 7 ha and 5 ha farm. occupied 55.9 percent of the total farms. And a single cooperative farm was consisted of 10 to 20 plots of paddies. b) The educational back ground of the staff members involved in the cooperative rice cultivation was superior than that of the individual rice cultivation. c) All of the farmers who participated to the questionaires have responded that the cooperative rice cultivation could promise the increased rice yield mainly through the introduction of the improved method of fertilizer application and the effective control of diseases, insects and pests damages. And the majority of farmers were also in the opinion that preparation of the materials and labor input can be timely carried out and the labor requirement for the rice cultivation possibly be saved through the cooperative rice cultivation. d) The farmers who have expressed their wishes to continue and to make further development of the cooperative rice cultivation was 74.5 percent of total farmers participated to the questionaires. 11. From the analysis of economical feasibility on the two different methods of cultivation, the following results were obtained: a) The value of operation cost for the compost, chemical fertilizers, agricultural chemicals and labor input in the cooperative rice cultivation was respectively higher by 335 won, 199 won, 288 won and 303 won over the individual rice cultivation. However, the other production costs showed no distinct differences between the two cultivation methods. b) Although the total value of expenses for the fertilizers, agricultural chemicals, labor input and etc. in the cooperative rice cultivation were approximately doubled to the amount of the individual rice cultivation, the net income, substracted operation costs from the gross income, was obtained 24, 302 won in the cooperative rice cultivation and 20, 168 won was obtained from the individual rice cultivation. Thereby, it can be said that net income from the cooperative rice cultivation increased 4, 134 won over the individual rice cultivation. It was revealed in this study that the cooperative rice cultivation has not only contributed to increment of the farm income through higher yield but also showed as an effective means to introduce highly improved cultivation techniques to the farmers. It may also be concluded, therefore, the cooperative rice cultivation shall continuously renovate the rice production process of the farmers.

• Journal of Intelligence and Information Systems
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• v.26 no.1
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• pp.1-21
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• 2020

With the rapid development of artificial intelligence technology, various techniques have been developed to extract meaningful information from unstructured text data which constitutes a large portion of big data. Over the past decades, text mining technologies have been utilized in various industries for practical applications. In the field of business intelligence, it has been employed to discover new market and/or technology opportunities and support rational decision making of business participants. The market information such as market size, market growth rate, and market share is essential for setting companies' business strategies. There has been a continuous demand in various fields for specific product level-market information. However, the information has been generally provided at industry level or broad categories based on classification standards, making it difficult to obtain specific and proper information. In this regard, we propose a new methodology that can estimate the market sizes of product groups at more detailed levels than that of previously offered. We applied Word2Vec algorithm, a neural network based semantic word embedding model, to enable automatic market size estimation from individual companies' product information in a bottom-up manner. The overall process is as follows: First, the data related to product information is collected, refined, and restructured into suitable form for applying Word2Vec model. Next, the preprocessed data is embedded into vector space by Word2Vec and then the product groups are derived by extracting similar products names based on cosine similarity calculation. Finally, the sales data on the extracted products is summated to estimate the market size of the product groups. As an experimental data, text data of product names from Statistics Korea's microdata (345,103 cases) were mapped in multidimensional vector space by Word2Vec training. We performed parameters optimization for training and then applied vector dimension of 300 and window size of 15 as optimized parameters for further experiments. We employed index words of Korean Standard Industry Classification (KSIC) as a product name dataset to more efficiently cluster product groups. The product names which are similar to KSIC indexes were extracted based on cosine similarity. The market size of extracted products as one product category was calculated from individual companies' sales data. The market sizes of 11,654 specific product lines were automatically estimated by the proposed model. For the performance verification, the results were compared with actual market size of some items. The Pearson's correlation coefficient was 0.513. Our approach has several advantages differing from the previous studies. First, text mining and machine learning techniques were applied for the first time on market size estimation, overcoming the limitations of traditional sampling based- or multiple assumption required-methods. In addition, the level of market category can be easily and efficiently adjusted according to the purpose of information use by changing cosine similarity threshold. Furthermore, it has a high potential of practical applications since it can resolve unmet needs for detailed market size information in public and private sectors. Specifically, it can be utilized in technology evaluation and technology commercialization support program conducted by governmental institutions, as well as business strategies consulting and market analysis report publishing by private firms. The limitation of our study is that the presented model needs to be improved in terms of accuracy and reliability. The semantic-based word embedding module can be advanced by giving a proper order in the preprocessed dataset or by combining another algorithm such as Jaccard similarity with Word2Vec. Also, the methods of product group clustering can be changed to other types of unsupervised machine learning algorithm. Our group is currently working on subsequent studies and we expect that it can further improve the performance of the conceptually proposed basic model in this study.

• Journal of Intelligence and Information Systems
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• v.18 no.3
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• pp.137-152
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• 2012

In the generation of Web 2.0, as many users start to make lots of web contents called user created contents by themselves, the World Wide Web is overflowing by countless information. Therefore, it becomes the key to find out meaningful information among lots of resources. Nowadays, the information retrieval is the most important thing throughout the whole field and several types of search services are developed and widely used in various fields to retrieve information that user really wants. Especially, the legal information search is one of the indispensable services in order to provide people with their convenience through searching the law necessary to their present situation as a channel getting knowledge about it. The Office of Legislation in Korea provides the Korean Law Information portal service to search the law information such as legislation, administrative rule, and judicial precedent from 2009, so people can conveniently find information related to the law. However, this service has limitation because the recent technology for search engine basically returns documents depending on whether the query is included in it or not as a search result. Therefore, it is really difficult to retrieve information related the law for general users who are not familiar with legal terms in the search engine using simple matching of keywords in spite of those kinds of efforts of the Office of Legislation in Korea, because there is a huge divergence between everyday words and legal terms which are especially from Chinese words. Generally, people try to access the law information using everyday words, so they have a difficulty to get the result that they exactly want. In this paper, we propose a term mapping methodology between everyday words and legal terms for general users who don't have sufficient background about legal terms, and we develop a search service that can provide the search results of law information from everyday words. This will be able to search the law information accurately without the knowledge of legal terminology. In other words, our research goal is to make a law information search system that general users are able to retrieval the law information with everyday words. First, this paper takes advantage of tags of internet blogs using the concept for collective intelligence to find out the term mapping relationship between everyday words and legal terms. In order to achieve our goal, we collect tags related to an everyday word from web blog posts. Generally, people add a non-hierarchical keyword or term like a synonym, especially called tag, in order to describe, classify, and manage their posts when they make any post in the internet blog. Second, the collected tags are clustered through the cluster analysis method, K-means. Then, we find a mapping relationship between an everyday word and a legal term using our estimation measure to select the fittest one that can match with an everyday word. Selected legal terms are given the definite relationship, and the relations between everyday words and legal terms are described using SKOS that is an ontology to describe the knowledge related to thesauri, classification schemes, taxonomies, and subject-heading. Thus, based on proposed mapping and searching methodologies, our legal information search system finds out a legal term mapped with user query and retrieves law information using a matched legal term, if users try to retrieve law information using an everyday word. Therefore, from our research, users can get exact results even if they do not have the knowledge related to legal terms. As a result of our research, we expect that general users who don't have professional legal background can conveniently and efficiently retrieve the legal information using everyday words.

• Journal of Aquaculture
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• v.21 no.4
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• pp.339-345
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• 2008

Farming of the fleshy shrimp Fenneropenaeus chinensis which is a major cultured species in the west coast of South Korea, has been suffered :trom mass mortality due to disease epizootics including viruses. Since the Pacific white shrimp Litopenaeus vannamei was introduced to Korea in 2003, farming of this species has rapidly increased for years, occupying 62.5% of total cultured shrimp production in 2007. However the studies on L. vannamei culture methods for shrimp farming situations in Korea are very limited. Nursery culture of shrimp larvae has some advantages including increased survival, improved feed efficiencies, enhanced growth performance and reduced grow-out period. In this study, L. vannamei postlarvae (${PL_3}-{PL_{10}}$) with a density of $3,750-9,090/m^3$ were cultured in four raceways under limited water exchange condition for 35 days. Survival was the highest (93.6%) in tank stocked with $4,090/m^3$ and was the lowest in tank with $9,090/m^3$ (58.1 %). Mean body weight at harvest ranged from 0.071 to 0.108 g, and FCR was 0.59-0.70 in all tanks. Concentration of total ammonia nitrogen was increased up to 20 ppm on day 10 in all tanks and thereafter gradually decreased by the third week of culture. Nitrite-nitrogen was rapidly increased from the third week, representing bio-floc condition by developed nitrifying bacterial community. Of the present nursery system some modification of structure and consideration for commercial scale are needed in order to be implemented to shrimp farmers.

• Journal of Animal Science and Technology
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• v.49 no.5
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• pp.677-688
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• 2007

돼지를 포함한 대부분의 동물은 일정한 발정주기를 가지고 일정한 시기에 배란을 하는 자연배란동물이지만, 토끼, 고양이, 밍크 등의 암놈은 교미자극에 의해 배란이 일어나는 유기배란동물이다. 또한 1년에 한 번만 발정하는 단발정동물과 1년에 수차례 발정하는 다발정동물이 있다. 이 중에서 모돈은 1년에 수차례 발정하는 다발정 동물로서 발정기에 들면 비발정기와는 다른 행동을 나타낸다(Diehl 등, 2001). 양돈가의 수익을 최대화하기 위해서는 비생산일수를 최소로 줄여야 한다. 모돈의 비생산일수를 줄일 수 있는 한 가지 방법은 성공적으로 교배를 시키는 것이다. 이처럼 성공적으로 교배를 시키기 위해서는 수정적기를 정확히 예측해야 한다. 만약 수정적기를 정확히 판단하지 못하여 수태가 되지 않으면, 비생산일수가 늘어나 손실을 입게 된다. 따라서 수정적기를 정확히 판단하는 것은 모돈의 성공적인 인공수정에 있어서 중요한 요소이다. 수정적기는 배란이 일어나기 전 10시간에서 12시간 사이이며, 발정이 시작되는 시점을 기준으로 하였을 때 경산돈의 경우 26시간에서 34시간 사이이고 미경산돈의 경우는 18시간에서 26시간 사이이다(Evans 등, 2001). 현재 하루에 두 번 모돈의 발정을 확인하는 것이 일반화되어 있으며, 이 때 웅돈을 접촉시키거나 육안관찰을 통하여 발정 유무를 판단한다. 이러한 방법에는 숙련된 기술과 풍부한 경험이 요구될 뿐만 아니라 총 소요노동력의 30% 정도가 요구된다(Perez 등, 1986). 하루에 두 번밖에 발정을 감지하지 않기 때문에 발정이 언제 시작되었는지를 정확히 알 수 없으며, 또한 발정의 대부분이 새벽에 시작되므로 수정적기를 정확히 판단하기란 매우 어렵다. 만약 발정을 감지했더라도 적기에 인공수정을 하지 못한다면, 수태율이 낮아지므로 경제적 손실이 초래된다. 현재 이러한 문제점 때문에 2회에서 3회에 걸쳐 인공수정을 하고 있으나 이에 따른 소요비용과 소요노동력 등은 양돈가의 부담을 가중시키는 요인이 되고 있다. 돼지는 발정기가 되면 비발정기에 나타내지 않던 외음부의 냄새를 맡는 행동, 귀를 세우는 행동 및 승가허용 행동 등을 나타낸다(Diehl 등, 2001). 또한 돼지는 비발정기에 비하여 발정기에 더 많은 활동량을 나타낸다(Altman, 1941; Erez and Hartsock, 1990). Freson 등(1998)은 스톨에서 개별적으로 사육되고 있는 모돈의 활동량을 적외선센서를 이용하여 측정함으로써 발정을 86%까지 감지하였다고 보고하였다. 그러나 이 연구는 단지 모돈의 발정을 감지하였을 뿐 번식관리에 있어서 가장 중요한 수정적기의 판단 기준을 제시하지 못하였다. 따라서, 본 연구는 스톨에서 사육되는 모돈의 활동량을 측정함으로써 발정시작시각을 감지하고 이를 기준으로 인공수정적기를 예측할 수 있는 인공수정적기 예측 장치를 개발한 후 이의 성능을 농장실증실험을 통하여 시험하고자 수행되었다.