• Journal of Information Science Theory and Practice
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• v.7 no.4
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• pp.56-64
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• 2019

Planting intercropping in rubber plantations is another alternative for generating more income for farmers. However, farmers still lack the knowledge of choosing plants. In addition, information for decision making comes from many sources and is knowledge accumulated by the expert. Therefore, this research aims to create a decision support system for growing rubber trees for individual farmers. It aims to get the highest income and the lowest cost by using semantic web technology so that farmers can access knowledge at all times and reduce the risk of growing crops, and also support the decision supporting system (DSS) to be more intelligent. The integrated intercropping ontology and rule are a part of the decision-making process for selecting plants that is suitable for individual rubber plots. A list of suitable plants is important for decision variables in the allocation of planting areas for each type of plant for multiple purposes. This article presents designing and developing the intercropping ontology for DSS which defines a class based on the principle of intercropping in rubber plantations. It is grouped according to the characteristics and condition of the area of the farmer as a concept of the rubber plantation. It consists of the age of rubber tree, spacing between rows of rubber trees, and water sources for use in agriculture and soil group, including slope, drainage, depth of soil, etc. The use of ontology for recommended plants suitable for individual farmers makes a contribution to the knowledge management field. Besides being useful in DSS by offering options with accuracy, it also reduces the complexity of the problem by reducing decision variables and condition variables in the multi-objective optimization model of DSS.

• Journal of Intelligence and Information Systems
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• v.11 no.2
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• pp.175-195
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• 2005

사례기반추론(case-based reasoning)은 사례간 유사도를 평가하여 유사한 이웃사례를 찾아내고, 이웃사례의 결과를 이용하여 새로운 사례에 대한 예측결과를 생성하는 전통적인 인공지능기법 중 하나다. 이러한 사례기반추론이 최근 적용이 쉽고 간단하다는 장점과 모형의 갱신이 실시간으로 이루어진다는 점 등으로 인해, 온라인 환경에서의 고객관계관리를 위한 도구로 학계와 실무에서 주목을 받고 있다 하지만, 전통적인 사례기반추론의 경우, 타 인공지능기법에 비해 정확도가 상대적으로 크게 떨어진다는 점이 종종 문제점으로 제기되어 왔다. 이에, 본 연구에서는 사례기반추론의 성과를 획기적으로 개선하기 위한 방법으로 유전자 알고리즘을 활용한 사례기반추론의 동시 최적화 모형을 제안하고자 한다. 본 연구가 제안하는 모형에서는 기존 연구에서 사례기반추론의 성과에 중대한 영향을 미치는 요소들로 제시된 바 있는 사례 특징변수의 상대적 가중치 선정(feature weighting)과 참조사례 선정(instance selection)을 유전자 알고리즘을 이용해 최적화함으로서, 사례간 유사도를 보다 정밀하게 도출하는 동시에 추론의 결과를 왜곡할 수 있는 오류사례의 영향을 최소화하고자 하였다. 제안모형의 유용성을 검증하기 위해, 본 연구에서는 국내 한 전문 인터넷 쇼핑몰의 구매예측모형 구축사례에 제안모형을 적용하여 그 성과를 살펴보았다. 그 결과, 제안모형이 지금까지 기존 연구에서 제안된 다른 사례기반추론 개선모형들은 물론, 로지스틱 회귀분석(LOGIT), 다중판별분석(MDA), 인공신경망(ANN), SVM 등 다른 인공지능 기법들에 비해서도 상대적으로 우수한 성과를 도출할 수 있음을 확인할 수 있었다.

• Journal of Intelligence and Information Systems
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• v.13 no.4
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• pp.121-135
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• 2007

Constraint directed scheduling techniques, representing problem constraints explicitly and constructing schedules by constrained heuristic search, have been successfully applied to real world scheduling problems that require satisfying a wide variety of constraints. However, there has been little basic research on the representation and optimization of the objective value of a schedule in the constraint directed scheduling literature. In particular, the cost objective is very crucial for enterprise decision making to analyze the effects of alternative business plans not only from operational shop floor scheduling but also through strategic resource planning. This paper aims to explicitly represent and optimize the total cost of a schedule including the tardiness and inventory costs while satisfying non-relaxable constraints such as resource capacity and temporal constraints. Within the cost based scheduling framework, a cost propagation algorithm is presented to update cost information throughout temporal constraints within the same job.

• The Journal of the Institute of Internet, Broadcasting and Communication
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• v.21 no.5
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• pp.89-94
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• 2021

Recently, manufacturing companies are introducing many intelligent production processes that apply IIoT/ICT to improve competitiveness, and a system that maintains availability, improves productivity, and optimizes management costs is needed as a preventive measure using environmental data generated from air ejectors. Therefore, in this study, a dedicated control board was developed and LoRa communication module was applied to remotely control it to collect and manage information about compressors from cloud servers and to ensure that all operators and administrators utilize common data in real time. This dramatically reduced M/S steps, increased system operational availability, and reduced local server operational burden. It dramatically reduced maintenance latency by sharing system failure conditions and dramatically improved cost and space problems by providing real-time status detection through wired and mobile utilization by maintenance personnel.

• Journal of the Korea Society of Computer and Information
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• v.24 no.8
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• pp.19-28
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• 2019

In this paper, an online video summarization algorithm based on multiple object detection is proposed. As crime has been on the rise due to the recent rapid urbanization, the people's appetite for safety has been growing and the installation of surveillance cameras such as a closed-circuit television(CCTV) has been increasing in many cities. However, it takes a lot of time and labor to retrieve and analyze a huge amount of video data from numerous CCTVs. As a result, there is an increasing demand for intelligent video recognition systems that can automatically detect and summarize various events occurring on CCTVs. Video summarization is a method of generating synopsis video of a long time original video so that users can watch it in a short time. The proposed video summarization method can be divided into two stages. The object extraction step detects a specific object in the video and extracts a specific object desired by the user. The video summary step creates a final synopsis video based on the objects extracted in the previous object extraction step. While the existed methods do not consider the interaction between objects from the original video when generating the synopsis video, in the proposed method, new object clustering algorithm can effectively maintain interaction between objects in original video in synopsis video. This paper also proposed an online optimization method that can efficiently summarize the large number of objects appearing in long-time videos. Finally, Experimental results show that the performance of the proposed method is superior to that of the existing video synopsis algorithm.

• Journal of Internet Computing and Services
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• v.20 no.1
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• pp.1-10
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• 2019

Since big-data text mining extracts many features and data, clustering and classification can result in high computational complexity and low reliability of the analysis results. In particular, a term document matrix obtained through text mining represents term-document features, but produces a sparse matrix. We designed an advanced genetic algorithm (GA) to extract features in text mining for detection model. Term frequency inverse document frequency (TF-IDF) is used to reflect the document-term relationships in feature extraction. Through a repetitive process, a predetermined number of features are selected. And, we used the sparsity score to improve the performance of detection model. If a spam mail data set has the high sparsity, detection model have low performance and is difficult to search the optimization detection model. In addition, we find a low sparsity model that have also high TF-IDF score by using s(F) where the numerator in fitness function. We also verified its performance by applying the proposed algorithm to text classification. As a result, we have found that our algorithm shows higher performance (speed and accuracy) in attack mail classification.

• Journal of the Korea Institute of Information and Communication Engineering
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• v.23 no.4
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• pp.365-373
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• 2019

An Image Infra-Red(IIR) seeker is widely used for precision guided munitions to provide intelligent and precise target detection in terms of high kill probability. However, there have been issues in determining the performance versus cost trade-offs due to high cost of seeker comparing to other units of the munitions. In this paper, performance/cost evaluations have been carried out to find the most cost-effective solution for developing the IIR seekers. The relationships between the critical parameters and cost are investigated to determine the optimal point which represents the low cost with high performance. It is expected that the presented approach will be able to be used for guidelines to select the appropriate IIR seeker for the given operating conditions and can be useful to estimate the cost effectiveness of the precision guided munitions at early design stage.

• Convergence Security Journal
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• v.21 no.2
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• pp.67-79
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• 2021

Lessons Learned(LL) is a military term defined as all activities that promote future development by finding problems and need improvement in education and reality in the field of warfare development. In this paper, we focus on presenting actual examples and applying AI analysis inference techniques to solve revealed problems in promoting LL activities, such as long-term analysis, budget problems, and necessary expertise. AI legal advice services using cognitive computing-related technologies that have already been practical and in use, were judged to be the best examples to solve the problems of LL. This paper presents intelligent LL inference techniques, which utilize AI. To this end, we want to explore theoretical backgrounds such as LL analysis definitions and examples, evolution of AI into Machine Learning, cognitive computing, and apply it to new technologies in the defense sector using the newly proposed L²-OODA ensemble algorithm to contribute to implementing existing power improvement and optimization.

• Journal of Digital Convergence
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• v.19 no.8
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• pp.219-224
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• 2021

The convergence of various industries has removed the boundaries of software application fields and reduced the restrictions on convergence fields. Software requirements are diversified and they want to reconfigure software requirements in a fast cycle. Since various changes in requirements have to be accepted technically, research on methodologies and standards to increase the efficiency of software productivity and methods for standardizing and producing software are needed. In this study, we studied how the reusability and complexity of the software asset reconfiguration system appeared according to the developer's characteristics and environment to utilize the assets optimized in previous studies. At this time, we measured how the change in complexity according to the usability and asset composition method that appears according to the developer's characteristics appears, but there is a limit to the collected data, so it is necessary to secure the quality of the measured value through continuous data collection. In addition, an intelligent system application plan is needed to supplement the problem of context classification in the use stage of complex assets.

• Journal of the Korea Academia-Industrial cooperation Society
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• v.21 no.12
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• pp.702-708
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• 2020

Recently, as LED display systems have become larger, research on effective power control methods for the systems has been in progress. This paper proposes a power control method to minimize power loss due to the difference in LED characteristics for each channel of a backlight unit (BLU) system. The proposed LED driver IC has a power optimization function and detects the minimum headroom voltage for constant current operation of all channels and linearly controls the DC-DC converter output. Thus, it minimizes power consumption due to unnecessary additional voltage. In addition, it does not require a voltage sensing comparator or a voltage generation circuit for each channel. This has a great advantage in reducing the chip size and for stabilization when implementing an integrated circuit. In order to verify the proposed function, an IC was designed using Cadence and Synopsys' design tools, and it was fabricated with a Magnachip 0.35um 5V/40V CMOS process. The experiments confirmed that the proposed power control method controls the minimum required voltage of the BLU system.