• Proceedings of the Korea Institutes of Information Security and Cryptology Conference
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• 2002.11a
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• pp.369-372
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• 2002

An anonymous authentication scheme allows a user to identify himself as a member of a group of users in a secure and anonymous way. It seems to be crucial and indispensable components in English auction, electronic voting and open procurement, which are getting very popular business areas in E-commerce. First, we briefly describe the previous anonymous authentication protocols how to work and what cryptographic techniques adopted to increase performance and achieve anonymity. Second, we compare those protocols from the viewpoint of the communication and computation complexity and the specific cryptographic techniques used in their protocols.

• The Journal of Information Technology
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• v.4 no.1
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• pp.97-108
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• 2001

This thesis is about the design and implementation of the system for controlling Avatar, user's alter ego in a simulated world using the EAI(External Authoring Interface) technology to be able to control VRML(Virtual Reality Modeling Language). In this thesis, user's Avatar described in VRML language embodied interactions to move and show an expression by JAVA according to a user's demand. In the future, this would be able to develop into a research to try to embody and construct a simulated society based on web for the purpose of various integration of society such as cyber government, lecture, trial performance, and auction.

• Proceedings of the Korean Information Science Society Conference
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• 2001.10c
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• pp.637-639
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• 2001

현재의 무선 인터넷 환경에서의 서비스는 HTML 계열의 CHTML, SHTML 등과 WAP 기반의 WML, 그리고 가상머신(VM) 기반에서 C 또는 Java로 구현하여 제공되고 있다. 이들 서비스 중에는 모바일 경매가 있는데 아직까지는 경매진행 과정이 Push 형태의 단문 문자 서비스(SMS)로 이루어지고 있다. 무선환경의 경매 시스템에서도 유선환경에서처럼 실시간으로 입찰자가 경매 진행 상황을 확인 할 수 있어야 한다. 본 논문에서는 무선환경에서 실시간이 지원되는 경매 시스템을 유무선 연동이 가능하도록구현하여 실시간으로 경매된 제품에 대한 입찰가격을 유선 및 무선측에서 확인 할 수 있었다. 구현은 무선 환경을 위한 Java 2 플랫폼인 J2ME와 데스크탑 환경을 위한 J2SE 기반으로 이루어 졌다. 또한 구현된 시스템의 성능을 사용자 접속 수에 따른 처리지연시간과 데이터베이스 연결풀 크기 변화에 따른 시스템의 처리시간 등의 평가 항목을 대상으로 각각 분석하였다.

• Journal of the Korea Society of Computer and Information
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• v.21 no.12
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• pp.107-114
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• 2016

Web system helps high-performance processing for big-data analysis and practical use to make various information using IT resources. The government have started the RPS system in 2012. The system invigorates the electricity production as using renewable energy equipment. The government operates system gathered big-data with various related information system data and the system users are distributed geographically. The companies have to fulfill the system, are available to purchase the REC to other electricity generation company sellers to procure REC for their duty volumes. The REC market operates single auction methods with users a competitive price. But the price have the large variation with various user trading strategy and sellers situations. This papler proposed RPS system modeling and simulation in web environment that is modeled in geographically distributed computing environment for web user with DEVS W/S. Web simulation system base on web service helps to analysis correlation and variables that act on trading price and volume within RPS big-data and the analysis can be forecast REC price.

• Journal of the Korea Institute of Military Science and Technology
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• v.17 no.2
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• pp.167-174
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• 2014

In this paper, we address a task allocation problem for a robot team that performs a search and attack mission. The robots are limited in sensing and communication capabilities, and carry different types of resources that are used to attack a target. The environment is uncertain and dynamic where no prior information about targets is given and dynamic events unpredictably happen. The goal of robot team is to collect total utilities as much as possible by destroying targets in a mission horizon. To solve the problem, we propose a distributed task allocation framework incorporated with effective resource management based on resource welfare. The framework we propose enables the robot team to retain more robots available by balancing resources among robots, and respond smoothly to dynamic events, which results in system performance improvement.

• KSII Transactions on Internet and Information Systems (TIIS)
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• v.9 no.11
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• pp.4311-4330
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• 2015

Cloud computing has become a new paradigm by enabling on-demand provisioning of applications, platforms or computing resources for clients. Workflow scheduling has always been treated as one of the most challenging problems in clouds. Commercial clouds have been widely used in scientific research, such as biology, astronomy and weather forecasting. Certainly, it is very important for a cloud service provider to pursue the profits for the commercial essence of clouds. This is also significantly important for the case of providing services to workflow tasks. In this paper, we address the issues of workflow scheduling in commercial clouds. This work takes the communication into account, which has always been ignored. And then, a topology-based workflow-scheduling algorithm named Resource Auction Algorithm (REAL) is proposed in the objective of getting more profits. The algorithm gives a good performance on searching for the optimum schedule for a sample workflow. Also, we find that there exists a certain resource amount, which gets the most profits to help us get more enthusiasm for further developing the research. Experimental results demonstrate that the analysis of the strategies for most profits is reasonable, and REAL gives a good performance on efficiently getting an optimized scheme with low computing complexity.

• Journal of Intelligence and Information Systems
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• v.21 no.1
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• pp.161-177
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• 2015

With the rapid evolution of technology, the size, number, and the type of databases has increased concomitantly, so data mining approaches face many challenging applications from databases. One such application is discovery of fraud patterns from agricultural product wholesale transaction instances. The agricultural product wholesale market in Korea is huge, and vast numbers of transactions have been made every day. The demand for agricultural products continues to grow, and the use of electronic auction systems raises the efficiency of operations of wholesale market. Certainly, the number of unusual transactions is also assumed to be increased in proportion to the trading amount, where an unusual transaction is often the first sign of fraud. However, it is very difficult to identify and detect these transactions and the corresponding fraud occurred in agricultural product wholesale market because the types of fraud are more intelligent than ever before. The fraud can be detected by verifying the overall transaction records manually, but it requires significant amount of human resources, and ultimately is not a practical approach. Frauds also can be revealed by victim's report or complaint. But there are usually no victims in the agricultural product wholesale frauds because they are committed by collusion of an auction company and an intermediary wholesaler. Nevertheless, it is required to monitor transaction records continuously and to make an effort to prevent any fraud, because the fraud not only disturbs the fair trade order of the market but also reduces the credibility of the market rapidly. Applying data mining to such an environment is very useful since it can discover unknown fraud patterns or features from a large volume of transaction data properly. The objective of this research is to empirically investigate the factors necessary to detect fraud transactions in an agricultural product wholesale market by developing a data mining based fraud detection model. One of major frauds is the phantom transaction, which is a colluding transaction by the seller(auction company or forwarder) and buyer(intermediary wholesaler) to commit the fraud transaction. They pretend to fulfill the transaction by recording false data in the online transaction processing system without actually selling products, and the seller receives money from the buyer. This leads to the overstatement of sales performance and illegal money transfers, which reduces the credibility of market. This paper reviews the environment of wholesale market such as types of transactions, roles of participants of the market, and various types and characteristics of frauds, and introduces the whole process of developing the phantom transaction detection model. The process consists of the following 4 modules: (1) Data cleaning and standardization (2) Statistical data analysis such as distribution and correlation analysis, (3) Construction of classification model using decision-tree induction approach, (4) Verification of the model in terms of hit ratio. We collected real data from 6 associations of agricultural producers in metropolitan markets. Final model with a decision-tree induction approach revealed that monthly average trading price of item offered by forwarders is a key variable in detecting the phantom transaction. The verification procedure also confirmed the suitability of the results. However, even though the performance of the results of this research is satisfactory, sensitive issues are still remained for improving classification accuracy and conciseness of rules. One such issue is the robustness of data mining model. Data mining is very much data-oriented, so data mining models tend to be very sensitive to changes of data or situations. Thus, it is evident that this non-robustness of data mining model requires continuous remodeling as data or situation changes. We hope that this paper suggest valuable guideline to organizations and companies that consider introducing or constructing a fraud detection model in the future.

• Journal of Animal Science and Technology
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• v.64 no.6
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• pp.1077-1091
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• 2022

This study was conducted to determine the rumen fermentation dynamics of lupin flakes and elucidate the effects of lupin flake supplementation on the growth performance, blood metabolites, and carcass characteristics of Hanwoo steers. In vitro and in situ trials of lupin grains and lupin flakes were conducted using three Hanwoo cows with rumen fistulas. The feeding trial included 40 early-fattening Hanwoo steers randomly divided into four groups: control, T1, T2, and T3. Their formula feed contained 0%, 3%, 6%, and 9% lupin flakes, respectively. In vitro rumen pH and ammonia concentrations were lower in the lupin flake group than in the lupin grain group after 6 and 24 h of incubation, respectively (p < 0.05). Concentrations of propionate, butyrate, and total volatile fatty acids were higher in the lupin flake group than in the lupin grain group after 12 h of incubation (p < 0.05), as was the crude protein disappearance rate at 9 and 12 h of rumen fermentation (p < 0.05). Supplementation with lupin flakes did not affect the average daily gain. Compared to that in the control group, dry matter intake was lower in the lupin flake-supplemented groups (p < 0.05); the feed conversion ratio was lower in T2 and T3 (p < 0.05); and plasma total protein concentration in 29-month-old steers was lower in T1 and T3 (p < 0.05). Plasma triglyceride concentration was lower in the lupin flake-supplemented groups than in the control group (p < 0.05). The incidence rate of yield grade A was higher in T1 and T2 than in the control group; the incidence rate of meat quality 1⁺ grade or higher was highest in T2. The carcass auction price was higher in T2 than in the other groups. Overall, compared to whole lupin grains, lupin flakes seem to more substantially affect rumen ammonia concentrations and crude protein disappearance rate. Additionally, we suggest that supplementation with 6% lupin flake formula feed exerts positive effects on the feed conversion ratio, yield grade, and quality grade of Hanwoo steers.

• KIPS Transactions on Computer and Communication Systems
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• v.12 no.9
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• pp.263-272
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• 2023

Industrial Internet of Things (IIoT) is an important factor in increasing production efficiency in industrial sectors, along with data collection, exchange and analysis through large-scale connectivity. However, as traffic increases explosively due to the recent spread of IIoT, an allocation method that can efficiently process traffic is required. In this thesis, I propose a two-stage task offloading decision method to increase successful task throughput in an IIoT environment. In addition, I consider a hybrid offloading system that can offload compute-intensive tasks to a mobile edge computing server via a cellular link or to a nearby IIoT device via a Device to Device (D2D) link. The first stage is to design an incentive mechanism to prevent devices participating in task offloading from acting selfishly and giving difficulties in improving task throughput. Among the mechanism design, McAfee's mechanism is used to control the selfish behavior of the devices that process the task and to increase the overall system throughput. After that, in stage 2, I propose a multi-armed bandit (MAB)-based task offloading decision method in a non-stationary environment by considering the irregular movement of the IIoT device. Experimental results show that the proposed method can obtain better performance in terms of overall system throughput, communication failure rate and regret compared to other existing methods.

• Journal of KIISE:Computer Systems and Theory
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• v.30 no.9
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• pp.477-486
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• 2003

In combinatorial auctions buyers nay bid for arbitrary combinations of goods. But determining the winners of combinatorial auctions who maximize the profit of a seller is known to be NP-complete. A branch-and-bound method can be one of practical algorithm for winner determination. However, bid selection heuristics play a very important role in the efficiency of a branch-and-bound method. In this paper, we designed and implemented an algorithm which used a branch-and-bound method and Linear Programming for winner determination in combinatorial auctions. We propose new bid selection heuristics which consider a branching bid and conflicting bids simultaneously to select a branching bid in the algorithm. In addition, upper bounds are reused to reduce the running time in specific cases. We evaluated the performance of the algorithm by experiments with five data distributions and compared our method with others. The algorithm using heuristics showed a superior efficiency in two data distributions and a similar efficiency in three distributions.