• Proceedings of the Korean Society for Agricultural Machinery Conference
• /
• 2017.04a
• /
• pp.168-168
• /
• 2017

ICT 융합 스마트팜 내의 환경계측 센서, 영상 및 사양관리 시스템의 증가에도 불구하고 이들 장비에서 확보되는 데이터를 적절히 유효하게 활용하는 기술이 미흡한 실정이다. 돈사의 경우 가축의 복지수준, 성장 변화를 실시간으로 모니터링 및 예측할 수 있는 데이터 분석 및 모델링 기술 확보가 필요하다. 이를 위해선 가축의 생리적 변화 및 행동적 변화를 조기에 감지하고 가축의 복지수준을 실시간으로 감시하고 분석 및 예측 기술이 필요한데 이를 위한 대표적인 정보 통신 공학적 접근법 중에 하나가 Data mining 이다. Data mining에 대한 연구 수행에 필요한 다양한 소프트웨어 중에서 Open source로 제공이 되는 4가지 도구를 비교 분석하였다. 스마트 돈사 내에서 열환경 모델링을 목표로 한 데이터 분석에서 고려해야할 요인으로 데이터 분석 알고리즘 도출 시간, 시각화 기능, 타 라이브러리와 연계 기능 등을 중점 적으로 분석하였다. 선정된 4가지 분석 도구는 1) R(https://cran.r-project.org), 2) OpenCV(http://opencv.org), 3) OpenNN (http://www.opennn.net), 4) Orange(http://orange.biolab.si) 이다. 비교 분석을 수행한 운영체제는 Linux-Ubuntu 16.04.4 LTS(X64)이며, CPU의 클럭속도는 3.6 Ghz, 메모리는 64 Gb를 설치하였다. 개발언어 측면에서 살펴보면 1) R 스크립트, 2) C/C++, Python, Java, 3) C++, 4) C/C++, Python, Cython을 지원하여 C/C++ 언어와 Python 개발 언어가 상대적으로 유리하였다. 데이터 분석 알고리즘의 경우 소스코드 범위에서 라이브러리를 제공하는 경우 Cross-Platform 개발이 가능하여 여러 운영체제에서 개발한 결과를 별도의 Porting 과정을 거치지 않고 사용할 수 있었다. 빌트인 라이브러리 경우 순서대로 R 의 경우 가장 많은 수의 Data mining 알고리즘을 제공하고 있다. 이는 R 운영 환경 자체가 개방형으로 되어 있어 온라인에서 추가되는 새로운 라이브러리를 클라우드를 통하여 공유하기 때문인 것으로 판단되었다. OpenCV의 경우 영상 처리에 강점이 있었으며, OpenNN은 신경망학습과 관련된 라이브러리를 소스코드 레벨에서 공개한 것이 강점이라 할 수 있다. Orage의 경우 라이브러리 집합을 제공하는 것에 중점을 둔 다른 패키지와 달리 시각화 기능 및 망 구성 등 사용자 인터페이스를 통합하여 운영한 것이 강점이라 할 수 있다. 열환경 모델링에 요구되는 시간 복잡도에 대응하기 위한 부가 정보 처리 기술에 대한 연구를 수행하여 스마트팜 열환경 모델링을 실시간으로 구현할 수 있는 방안 연구를 수행할 것이다.

• Journal of Intelligence and Information Systems
• /
• v.8 no.1
• /
• pp.103-117
• /
• 2002

Recently, many researchers have developed applications for automated contract and negotiation using agent technologies on electronic commerce. Especially, they have tried to study negotiation mechanism applying agent instead of buyers and sellers. Traditional researches, however, often had limitations. In the researches of automated negotiation, the agents had to negotiate with the other agents for a simple negotiation issue because the mechanisms were naive. In the researches of negotiation by user interaction, the agents did not have supported the procedures and methodologies for making the automated negotiation but only supported the users by providing communication environment during the negotiation process by users. In this paper, we propose efficient negotiation model using the modified negotiation model of the game theory. In the proposed model, the agents negotiate automatically with the partner agent and make good benefits by the strategic method during the negotiation process. Each agent makes negotiation issues with user's requirements and exchanges its suggestion alternatively in each step of the negotiation process. The agent evaluates degree of satisfaction for the opposite's suggestion and uses it in the next step of suggestion. To find out the negotiation strategies of opposite side, the agent uses teaming by weights of issues. As a result, the agent improves each own benefits for the contract and reduces the unbalance of its benefits through the proposed negotiation mechanism. We implement the negotiating agents according to the proposed mechanism and prove the efficiency of the proposed model by various experimentation.

• Journal of Bio-Environment Control
• /
• v.27 no.1
• /
• pp.27-33
• /
• 2018

This study was performed to review the domestic and international smart farm service model based on the convergence of agriculture and information & communication technology and derived various factors needed to improve the Korean smart greenhouse. Studies on modelling of crop growth environment in domestic smart farms were limited. And it took a lot of time to build research infrastructure. The cloud-based research platform as an alternative is needed. This platform can provide an infrastructure for comprehensive data storage and analysis as it manages the growth model of cloud-based integrated data, growth environment model, actuators control model, and farm management as well as knowledge-based expert systems and farm dashboard. Therefore, the cloud-based research platform can be applied as to quantify the relationships among various factors, such as the growth environment of crops, productivity, and actuators control. In addition, it will enable researchers to analyze quantitatively the growth environment model of crops, plants, and growth by utilizing big data, machine learning, and artificial intelligences.

• Fire Science and Engineering
• /
• v.34 no.1
• /
• pp.103-114
• /
• 2020

The purpose of this study is to investigate the effect of apartment residents' safety education satisfaction and the application of fire protection plans on fire safety awareness. The analysis results are as follows. First, the low levels of satisfaction with safety education content had a negative effect on anxiety about fire safety. This means that apartment residents' low levels of interest or participation in education affected their safety awareness, which prevented them from securing safety from fire. It is necessary for control staff to have a positive impact on their educational satisfaction via the learning support information system, among others, in order to create a satisfying education and safety culture. Second, competence in the execution of firefighting plans had a positive effect on fire safety awareness. These results indicate that apartment residents do not have the opportunity to access the education and training necessary for safety, nor the legal responsibility to complete mandatory safety education, which leads to their lack of safety awareness. Therefore, the control staff need to raise awareness of fire safety and the importance of participating in safety education among apartment residents by strengthening and activating the execution of firefighting plans in order to ensure safe living. Third, the competency of the firefighting plans moderated the effects of apartment residents' educational satisfaction on their awareness of fire safety.

• KSCE Journal of Civil and Environmental Engineering Research
• /
• v.34 no.3
• /
• pp.955-963
• /
• 2014

The objective of this study is to identify ways to resolve conflicts arising from building new roads or expanding existing roads by introducing negotiation techniques to the Jeju government. A case of city planning (Jungjeong-ro, Seogwipo City, Jeju Special Self-Governing Province) was analyzed in this study in an aspect of negotiation. In the case, the Committee for Promoting and Vitalizing Jungjeong-ro conducted negotiations from February, 2011 to December, 2011. This study proposes ways to establish systems which resolve problems during negotiation processes and frame concepts related to negotiation in the overall administrative systems. Firstly, setting up a negotiation management team within the provincial office and supporting it fully is needed. Secondly, there should be a process in which decisions made by the negotiation team become authoritative. Thirdly, for smooth negotiation processes, it is necessary to formulate ground rules and make negotiating parties obey them thoroughly. Fourthly, a negotiation clinic team should be established at the Jeju provincial government. Fifthly, there should be a negotiation school within the framework of human resources development. Sixthly, If officials do their negotiation jobs positively, a reward system should be established to give them adequate rewards. Lastly, concept of negotiation should take root in administration in general.

• KIPS Transactions on Software and Data Engineering
• /
• v.2 no.8
• /
• pp.535-542
• /
• 2013

Since case-based reasoning(CBR) has many advantages, it has been used for supporting decision making in various areas including medical checkup, production planning, customer classification, and so on. However, there are several factors to be set by heuristics when designing effective CBR systems. Among these factors, this study addresses the issue of selecting appropriate neighbors in case retrieval step. As the criterion for selecting appropriate neighbors, conventional studies have used the preset number of neighbors to combine(i.e. k of k-nearest neighbor), or the relative portion of the maximum similarity. However, this study proposes to use the absolute similarity threshold varying from 0 to 1, as the criterion for selecting appropriate neighbors to combine. In this case, too small similarity threshold value may make the model rarely produce the solution. To avoid this, we propose to adopt the coverage, which implies the ratio of the cases in which solutions are produced over the total number of the training cases, and to set it as the constraint when optimizing the similarity threshold. To validate the usefulness of the proposed model, we applied it to a real-world target marketing case of an online shopping mall in Korea. As a result, we found that the proposed model might significantly improve the performance of CBR.

• Journal of Korea Water Resources Association
• /
• v.54 no.12
• /
• pp.1285-1294
• /
• 2021

In recent years, as rainfall is concentrated and rainfall intensity increases worldwide due to climate change, the scale of flood damage is increasing. Rainfall of a previously unobserved magnitude falls, and the rainy season lasts for a long time on record. In particular, these damages are concentrated in ASEAN countries, and at least 20 million people among ASEAN countries are affected by frequent flooding due to recent sea level rise, typhoons and torrential rain. Korea supports the domestic flood warning system to ASEAN countries through various ODA projects, but the communication network is unstable, so there is a limit to the central control method alone. Therefore, in this study, an artificial intelligence-based flood prediction model was developed to develop an observation station that can observe water level and rainfall, and even predict and warn floods at once at one observation station. Training, validation and testing were carried out for 0.5, 1, 2, 3, and 6 hours of lead time using the rainfall and water level observation data in 10-minute units from 2009 to 2020 at Junjukbi-bridge station of Seolma stream. LSTM was applied to artificial intelligence algorithm. As a result of the study, it showed excellent results in model fit and error for all lead time. In the case of a short arrival time due to a small watershed and a large watershed slope such as Seolma stream, a lead time of 1 hour will show very good prediction results. In addition, it is expected that a longer lead time is possible depending on the size and slope of the watershed.

• Journal of the Korea Convergence Society
• /
• v.12 no.3
• /
• pp.247-259
• /
• 2021

This study aimed to look for educational ways to prepare for the future society for education and people of talent who will lead the post-COVID-19 era. To this end, the factors necessary for the type of future talent in the post-COVID-19 era were identified by analyzing Big data. Based on the deducted factors composing the type of talent in the post-COVID-19 era, policy direction according to the emergence of the post-COVID-19 era were deducted through the interviews with the group of experts and delphi survey, and on the basis of this, this study sought for"a plan for the educational change in line with cultivation of people of talent in the post-COVID-19 era. The results of this study are as follows. First, through the big data analytics and analysis of the interviews, convergence, ICT utilization ability, creativity, self-regulated competency and leadership were found to be the factors necessary for the type of talent in the post-COVID-19 era. Second, it considered the innovation of digital education system and the support for vulnerable classes as the issue for cultivation of people of talent in the post-COVID-19 era. Third, the most important policy with regard to the educational direction for cultivation of people of talent in the post-COVID-19 era was cultivation of convergence talents. Convergence is a very important variable in the post-COVID-19 era since it creates new values by connecting things that are separated from each other. Hopefully, this study will build a basis for competency development, education and training in preparation for the post-COVID-19 era.

• The Journal of the Korea institute of electronic communication sciences
• /
• v.18 no.5
• /
• pp.953-964
• /
• 2023

Climate change is undeniably the most urgent challenge that humanity faces today. Despite this, the level of public awareness and understanding of climate change remains insufficient, indicating a need for more proactive education and the development of supportive content. In particular, it is crucial to intensify climate change education during elementary and secondary schooling when values and ethical consciousness begin to form. However, there is a significant lack of age-appropriate, experiential educational content. To address this, our study has developed an innovative 3D simulator, enabling learners to indirectly experience the effects of climate change, specifically sea-level rise. This simulator considers not only sea-level rise caused by climate change but also storm surges, which is a design based on the analysis of long-term wave observation big data. To make the simulator accessible and engaging for students, we utilized the 'Unity' game engine. We further propose using this simulator as a part of a comprehensive educational program on climate change.

• Journal of Korean Home Economics Education Association
• /
• v.35 no.3
• /
• pp.117-133
• /
• 2023

This study investigates the perceptions, Stages of Concern (SoC), and Levels of Use (LoU) regarding process-based assessment among Home Economics (HE) teachers to determine the necessary support for its implementation in schools. Data were gathered from a survey administered to HE teachers. The results are as follows. First, HE teachers viewed process-based assessment favorably, valuing its multifaceted evaluation approach over result-based assessment. The feedback from process-based assessments was seen as an opportunity for reflection for both educators and students. While some teachers expressed uncertainty about the optimal timing of implementation, they generally demonstrated a sound understanding of the feedback concept within the assessment process. HE teachers were predominantly concerned with their own professional expertise and the learning outcomes of their students. The majority of HE teachers have utilized process-based assessments for at least one semester. None deemed it irrelevant to their practice or showed disinterest in its adoption. Those who had yet to implement it were either in the first(introduction) or the second(preparation) stages.