• International Journal of Fuzzy Logic and Intelligent Systems
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• v.4 no.3
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• pp.292-299
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• 2004

For Web System composed of a variety of hardware, software and network system, there is a wide difference in price, function and capacity. In addition, it is important to select the most suitable system when web system is constructed as the claim of high-quality web service from user has increased. Data of bench-marking is usually employed when the system is selected. Evaluation with the result of bench-marking, however, is not easy at web situation composed of a variety of systems. In this paper, first integrated bench-marking of hardware, software and network system metric were determined, and the plan to effectively compare and evaluate the result of bench-marking by using fuzzy set were offered.

• STI Policy Review
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• v.8 no.2
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• pp.49-74
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• 2017

What are some of the explanations for cross-national diversity of foresight performance among technological followers? Why are some countries more successful than others in learning how to develop national innovation system foresight? This paper argues that the answers are linked to organizational capacities at three different levels: governmental, policy network and social learning. To corroborate this argument, the paper chose Iran and Korea as benchmarking partners, and attempts to find out what makes Iran a slow learner in building innovation system foresight. The conceptual model is an improved model of Saritas's, by integrating Borras' and Andersen's conceptions and classifications. The data are collected from comprehensive interviews in both countries and second-hand data of international indexes. The paper, finally, concludes that it is the weakness of analytical-systemic capacity that impedes and delays the emergence of systemic foresight in Iran, and that this weakness stems from the adverse impacts of the dominant institutions, surrounding the innovation system. The final point is that it is not sufficient for Iran to learn the methods and techniques of foresight from Korea. It should learn how to open its macro-policy towards the global market and design appropriate industrial strategy in a coherent policy-strategy portfolio.

• Proceedings of the Korea Inteligent Information System Society Conference
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• 1999.10a
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• pp.303-311
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• 1999

The amount of financial information in today's sophisticated large data bases is huge and makes comparisons between company performance difficult or at least very time consuming. The purpose of this paper is to investigate whether neural networks in the form of self-organizing maps can be used to manage the complexity in large data bases. This paper structures and analyzes accounting numbers in a large data base over several time periods. By using self-organizing maps, we overcome the problems associated with finding the appropriate underlying distribution and the functional form of the underlying data in the structuring task that is often encountered, for example, when using cluster analysis. The method chosen also offers a way of visualizing the results. The data base in this study consists of annual reports of more than 80 Korean companies with data from the year 1998.

• Journal of the Korean Institute of Intelligent Systems
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• v.20 no.3
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• pp.428-433
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• 2010

The notion "block rotation" denotes the operation of exchanging two consecutive sequences of elements uv to vu. There are three already well-known block rotation algorithms called BlockRotation, Juggling and Reversal algorithm. Recently we presented a novel block rotation algorithm called QuickRotation. In this paper we compare QuickRotation to these three known block rotation algorithms. This comparison covers a complexity analysis as well as benchmarking and shows that a switch to QuickRotation is almost always advantageous.

• The Journal of The Korea Institute of Intelligent Transport Systems
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• v.16 no.5
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• pp.60-71
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• 2017

The purpose of this study is to evaluate vertical moving facilities at subway stations for the elderly users and to analyze their improvement measures. To evaluate vertical moving facilities of the top 31 subway stations with the most trips in Seoul, a data envelopment analysis (DEA) is employed. The input variables for the DEA include the number and percentage of elderly users, which are calculated using smart card data. the output variables consist of the number of elevators and escalators per 100 steps. The results show that the average score of 31 subway stations is 0.62 and four stations, i.e., Jamsil, Gasan Complex, Konkuk University, and Dongmyo, have the highest score. These four subway stations are set as benchmarking groups for the other stations with the lower score. Based on the comparison with the benchmarking groups, the improvement measures for vertical moving facilities of each station are suggested and discussed.

• Proceedings of the Korean Institute of Information and Commucation Sciences Conference
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• 2021.10a
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• pp.147-149
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• 2021

The trend of increasing traffic problems due to the explosion in traffic volume in Sejong City has reached a level that cannot be solved by investment in facility infrastructure, so it is essential to establish an intelligent traffic environment based on data. By benchmarking similar cases in the domestic and overseas, and analyzing the traffic information of Sejong City, we propose a plan to provide parking information using Intelligent CCTV, a smart traffic signal control system, and a safe drop zone. It is expected that this study will a basis for establishing policies of the Sejong City traffic safety strategy in the future.

• Proceedings of the Korea Inteligent Information System Society Conference
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• 2000.11a
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• pp.479-488
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• 2000

다양한 재무정보를 이용하여 기업간 경쟁적 벤치마킹을 수행하는 것은 매우 어려운 작업인 동시에 분석에 상담한 시간이 소요된다. 본 연구에서는 재무정보를 이용한 기업간 경쟁적 벤치마킹을 효과적으로 수행하기 위하여 대표적인 자율신경망 모형인 자기조직화 신경망을 분석에 이용하였다. 자기조직화 신경망은 다차원적인 재무자료를 2차원 출력 공간으로 투영함으로써 결과를 시각화하는데 매우 효과적이며, 시각화된 결과는 재무적인 경쟁우위에 따라 기업을 군집화함으로써 효과적인 경쟁적 벤치마킹을 수행할 수 있도록 한다. 본 연구에서는 1998년. 1999년, 그리고 2000년 상반기까지의 국내 제조업체 재무구조 분석사례에 자기조직화 신경함을 적용하여 재무적 경쟁우위에 따른 기업들의 군집화 모형으로서의 가능성을 제시하였다.

• Journal of the Korean Institute of Intelligent Systems
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• v.25 no.5
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• pp.437-443
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• 2015

This paper presents face recognition based on the fusion of visible image and thermal infrared (IR) texture estimated from the face image in the visible spectrum. The proposed face recognition scheme uses a multi- layer neural network to estimate thermal texture from visible imagery. In the training process, a set of visible and thermal IR image pairs are used to determine the parameters of the neural network to learn a complex mapping from a visible image to its thermal texture in the low-dimensional feature space. The trained neural network estimates the principal components of the thermal texture corresponding to the input visible image. Extensive experiments on face recognition were performed using two popular face recognition algorithms, Eigenfaces and Fisherfaces for NIST/Equinox database for benchmarking. The fusion of visible image and thermal IR texture demonstrated improved face recognition accuracies over conventional face recognition in terms of receiver operating characteristics (ROC) as well as first matching performances.

• Korean Journal of Oriental Medicine
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• v.16 no.3
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• pp.127-133
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• 2010

The purpose of this study is to develop the order communication system for Traditional Korean Medicine(TKM) which can support prescribing decisions and provide the toxicological information. The relative vulnerability of the infrastructure of TKM has made us start the study. We carried out the benchmarking for TKM charting solution firstly, and then designed the intelligent search and supporting method for prescription decisions. We developed of the medical herbs database and the web-based order communication program which can be used in medical field actually. This system supplies a various functions to oriental medical doctors such as management for prescription history, search for herb's effects, generating prescriptions, inventory management, alerting of toxicity and taboo, guideline for taking medicine, and so on. The design and implementation process has been described in this research. We expect that this system will play an important role in electronic medical record(EMR) or electronic health record(EHR) binding diagnosis and management functions.

• Economic and Environmental Geology
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• v.52 no.6
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• pp.637-645
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• 2019

Due to the transformation to the intelligent information society, the rapid change of our life and environment is expected. The Ministry of Science and ICT (MSIT) and the National Research Council of Science and Technology (NST) introduced a five-year government supported research institution's planning and evaluation based on the mid-to long-term perspective. This study collects international benchmarking information including industry, academia, and research fields by collecting mid- and long-term strategy reports from public research institutes, surveys by experts from abroad universities and research institutes, and analyzing overseas market information reports. The British Geological Survey (BGS), the U.S. Geological Survey (USGS) and the japanese geological survey related institutes (AIST-GSJ) plans for three-dimensional national geological information, predictions of geological environmental disasters, and development of important metals and material in the low carbon economic transformation and in the era of the Fourth Industrial Revolution. The mid- and long-term program emphasizes basic and public research on geological information through abroad experts survey such as the IPGP-CNRS etc. The market analysis of the mining automation and digital map sectors has been able to derive the fields in which the role of public research institutes by the market is expected such as data collection on land and in the air, mobile or three-dimensional information production, smooth/fast/real-time maps, custom map design, mapping support to various platforms, geological environmental risk assessment and disaster management information and maps.