• Proceedings of the Korea Institutes of Information Security and Cryptology Conference
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• 1995.11a
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• pp.151-162
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• 1995

보다 짧은 길이의 덧셈/뺄셈 사슬($addition_{traction-chain}$)을 찾는 문제는 정수론을 기반으로 하는 많은 암호시스템들에 있어서 중요한 문제이다. 특히, RSA에서의 모듈라멱승(modular exponentiation)이나 타원 곡선(elliptic curve)에서의 곱셈 연산시간은 덧셈사슬(addition-chain) 또는 덧셈/뺄셈 사슬의 길이와 정비례한다 본 논문에서는 덧셈/뻘셈 사슬을 구하는 새로운 알고리즘을 제안하고, 그 성능을 분석하여 기존의 방법들과 비교한다. 본 논문에서 제안하는 알고리즘은 작은윈도우(small-window) 기법을 기반으로 하고, 뺄셈을사용해서 윈도우의 개수를 최적화함으로써 덧셈/뺄셈 사슬의 길이를 짧게 한다. 본 논문에서 제안하는 알고리즘은 512비트의 정수에 대해 평균길이 595.6의 덧셈/뺄셈 사슬을 찾는다.

• The KIPS Transactions:PartB
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• v.14B no.6
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• pp.461-472
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• 2007

The emphasis in genome projects has Been moving towards the sequence analysis in order to extract biological "meaning"(e.g., evolutionary history of particular molecules or their functions) from the sequence. Especially. palindromic or direct repeats that appear in a sequence have a biophysical meaning and the problem is to recognize interesting patterns and configurations of words(strings of characters) over complementary alphabets. In this paper, we propose an algorithm to identify variable length palindromic pairs(longer than a threshold), where we can allow gaps(distance between words). The algorithm is called palindrome algorithm(PA) and has O(N) time complexity. A palindromic pair consists of a hairpin structure. By composing collected palindromic pairs we build n-pair palindromic patterns. In addition, we dot some of the longest pairs in a circle to represent the structure of a DNA sequence. We run the algorithm over several selected genomes and the results of E.coli K12 are presented. There existed very long palindromic pair patterns in the genomes, which hardly occur in a random sequence.

• Annual Conference of KIPS
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• 2003.11c
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• pp.1803-1806
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• 2003

인터넷의 기반이라 할 수 있는 DNS에 대한 보안 필요성이 대두되면서 DNSSEC(DNS Security)이 연구되고 있다. 이는 공개키 기반의 암호화 알고리즘을 기반으로 신뢰사슬(Chain of Trust) 메카니즘을 이용하여 DNS의 근본적인 취약점인 근원지 인증과 무결성 문제점을 해결한다. DNSSEC의 핵심이라 할 수 있는 신뢰사슬 메카니즘은 시스템의 과부하(Overhead)의 감소를 목표로 하여 여러차례 개선이 이루어지고 있다. 본 논문에서는 DNSSEC의 기본 개념 및 신뢰사슬 메카니즘을 샅펴보며 앞으로 어떤 방향으로 개발이 지속될 것인지에 대해 분석한다.

• The Journal of Society for e-Business Studies
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• v.23 no.1
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• pp.1-22
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• 2018

The value chain has been utilized as a strategic tool to improve competitive advantage, mainly at the enterprise level and at the industrial level. However, in order to conduct value chain analysis at the enterprise level, the client companies of the parent company should be classified according to whether they belong to it's value chain. The establishment of a value chain for a single company can be performed smoothly by experts, but it takes a lot of cost and time to build one which consists of multiple companies. Thus, this study proposes a model that automatically classifies the companies that form a value chain based on actual transaction data. A total of 19 transaction attribute variables were extracted from the transaction data and processed into the form of input data for machine learning method. The proposed model was constructed using the Random Forest algorithm. The experiment was conducted on a automobile parts company. The experimental results demonstrate that the proposed model can classify the client companies of the parent company automatically with 92% of accuracy, 76% of F1-score and 94% of AUC. Also, the empirical study confirm that a few transaction attributes such as transaction concentration, transaction amount and total sales per customer are the main characteristics representing the companies that form a value chain.

• Journal of Distribution Research
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• v.10 no.3
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• pp.1-14
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• 2005

It is important to control performance and a Sustainable Collaboration (SC) for the successful Supply Chain Management (SCM). This research developed a control model which analyzed SCM performances based on a Balanced Scorecard (ESC) and an SC using Support Vector Machine (SVM). 108 specialists of an SCM completed the questionnaires. We analyzed experimental data set using SVM. This research compared the forecasting accuracy of an SCMSC through four types of SVM kernels: (1) linear, (2) polynomial (3) Radial Basis Function (REF), and (4) sigmoid kernel (linear > RBF > Sigmoid > Polynomial). Then, this study compares the prediction performance of SVM linear kernel with Artificial Neural Network. (ANN). The research findings show that using SVM linear kernel to forecast an SCMSC is the most outstanding. Thus SVM linear kernel provides a promising alternative to an SC control level. A company which pursues an SCM can use the information of an SC in the SVM model.

• Journal of Intelligence and Information Systems
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• v.13 no.3
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• pp.47-61
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• 2007

In SCM (supply chain management), companies are pursuing a new approach through which overall functions within the supply chain, ranging from material purchase to production, distribution, and sales are designed, planned, and managed in an integrated way. The core functions among them are production planning and distribution planning. As these problems are mutually related, they should be dealt with simultaneously in an integrated manner. SCM is large-scale and multi-stage problems. Also, its various kinds of internal or external factors can, at any time, dynamically bring a change to the existing plan or situation. Recently, many enterprises are moving toward an open architecture for integrating their activities with their suppliers, customers and other partners within the supply chain. Agent-based technology provides an effective approach in such environments. Multi-agent systems have been proven suitable to represent domains such as supply chain networks which involve interactions among manufacturing organization, their customers, suppliers, etc. with different individual goals and propriety information. In this paper, we propose a multi-agent system based on the genetic algorithm that make it possible to integrate the production and distribution planning on a real-time basis in SCM. The proposed genetic algorithm produced near optimal solution and we checked that there is a great difference in the results between integrated planning and non-integrated planning.

• Journal of the Korean Institute of Intelligent Systems
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• v.20 no.3
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• pp.388-393
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• 2010

Cultural Content Technology(CT, Culture Technology) for the development of cultural industry and the commercialization of technology, cultural contents, media, mount, pass the value chain process and increase the added value of cultural products that are good for all forms of intangible technology. In the field of Culture Technology, Music by analyzing the characteristics of the development of a variety of applications has been studied. Associated with EEG measures and the results of their research in response to musical stimuli are used to detect and study is getting attention. In this paper, the musical stimuli in EEG signals by amplifying the corresponding reaction to the averaging method, ERP (Event-Related Potentials) experiments based on the process of extracting sound methods for removing noise from the ICA algorithm to extract the tone and noise removal according to the results are applied to analyze the characteristics of EEG.

• Journal of Korea Port Economic Association
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• v.37 no.3
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• pp.75-91
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• 2021

Due to increased competition in supply side to reduce operational costs, port professionals have experienced extreme pressure, which demanded academicians to develop the model for efficient port operations from the industry perspective. Among many ports in the world, U.S. ports are our primary interest to analyze in our study for its high volume of cargoes transacted in the U.S. ports. We primarily employed DEA (Data Envelopment Analysis) technique to research the productivity of U.S. ports and applied the algorithm of double bootstrapped DEA proposed by Simar & Wilson (2007) to further investigate the driving forces of the performance of U.S. port operations. The external variables employed in our study comprise onDock Rail, Channel Depth, Location, Area, Acres, ForeignCargoRatio, and TEUChange, out of which onDock Rail, Acres, ForeignCargoRatio, and TEUChange were significant. In order to evaluate the effects of methodology selection, we conducted the same analysis applying the Censored model (Tobit) and contrasted the outcomes drawn from the two different techniques. Based on the findings from this work we proposed managerial implications and concluded.

• Composites Research
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• v.32 no.3
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• pp.163-169
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• 2019

In this paper, we constructed a molecular dynamics (MD) polymer model of PMMA with 95% of conversion by using dynamic polymerization algorithm of a thermoplastic polymer based on free radical polymerization. In this algorithm, we introduced a united-atom level coarse-grained force field that combines the non-bonded terms from the TraPPE-UA force field and the bonded terms from the PCFF force field to alleviate the computation efforts. The molecular weight distribution and the average molecular weight of the polymer were calculated by investigating each chain generated from the free radical polymerization simulation. The molecular weight of the polymer was controlled by the number of initiator radicals presented in the initial state and molecular weight effect to the density, the glass transition temperature, and the mechanical properties were studied.

• The Journal of The Korea Institute of Intelligent Transport Systems
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• v.17 no.6
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• pp.96-110
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• 2018

As the development of ICT has made it easier to collect various traffic information, research on creating new traffic attributes is drawing attention. Estimation and forecasts of demand and traffic volume are one of the main indicators that are essential to traffic operation, assuming that the traffic pattern at a particular node or link is repeated. Traditionally, a survey method was used to demonstrate this similarity on trip behavior. However, the method was limited to achieving high accuracy with high costs and responses that relied on the respondents' memory. Recently, as traffic data has become easier to gather through ETC system, smart card, studies are performed to identify the regularity of trip in various ways. In, this study, route-level trip data collected in Daegu metropolitan city were analyzed to confirm that individual traveler forms a spatially similar trip chain over several days. For this purpose, we newly define the concept of spatial trip regularity and assess the spatial difference between daily trip chains using the sequence alignment algorithm, Dynamic Time Warping. In addition, we will discuss the applications as the indicators of fixed traffic demand and transportation services.