• Journal of the Korea Society of Computer and Information
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• v.21 no.6
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• pp.9-19
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• 2016

In finance literature, stock liquidity showing how stocks can be cashed out in the market has received rich attentions from both academicians and practitioners. The reasons are plenty. First, it is known that stock liquidity affects significantly asset pricing. Second, macroeconomic announcements influence liquidity in the stock market. Therefore, stock liquidity itself affects investors' decision and managers' decision as well. Though there exist a great deal of literature about stock liquidity in finance literature, it is quite clear that there are no studies attempting to investigate the stock liquidity issue as one of decision making problems. In finance literature, most of stock liquidity studies had dealt with limited views such as how much it influences stock price, which variables are associated with describing the stock liquidity significantly, etc. However, this paper posits that stock liquidity issue may become a serious decision-making problem, and then be handled by using data mining techniques to estimate its future extent with statistical validity. In this sense, we collected financial data set from a number of manufacturing companies listed in KRX (Korea Exchange) during the period of 2010 to 2013. The reason why we selected dataset from 2010 was to avoid the after-shocks of financial crisis that occurred in 2008. We used Fn-GuidPro system to gather total 5,700 financial data set. Stock liquidity measure was computed by the procedures proposed by Amihud (2002) which is known to show best metrics for showing relationship with daily return. We applied five data mining techniques (or classifiers) such as Bayesian network, support vector machine (SVM), decision tree, neural network, and ensemble method. Bayesian networks include GBN (General Bayesian Network), NBN (Naive BN), TAN (Tree Augmented NBN). Decision tree uses CART and C4.5. Regression result was used as a benchmarking performance. Ensemble method uses two types-integration of two classifiers, and three classifiers. Ensemble method is based on voting for the sake of integrating classifiers. Among the single classifiers, CART showed best performance with 48.2%, compared with 37.18% by regression. Among the ensemble methods, the result from integrating TAN, CART, and SVM was best with 49.25%. Through the additional analysis in individual industries, those relatively stabilized industries like electronic appliances, wholesale & retailing, woods, leather-bags-shoes showed better performance over 50%.

• Journal of Life Science
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• v.15 no.4 s.71
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• pp.590-594
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• 2005

In this study, the wastewater treatment was conducted to evaluate the removal efficiency of total nitrogen from synthetic wastewater in the F-STEP PROCESS $(anaerobic{\rightarrow}\;oxic\;{\rightarrow}\;anoxic)$ with loess ball as support metrics. The average removal efficiencies of total nitrogen and ammonia nitrogen were $83.0\%\;and\;84.4\%$, respectively. The average nitrification efficiency at the oxic area was $60.9\%$ in the pH range of effluent water between 4.8 and 6.0. On the other hand, in the case of pH range of effluent water between 6.5 and 7.5, the denitrification efficiency at the anoxic area was $96.3\%$. The average concentration of COD was 12.8 ppm and the removal efficiency of COD in the F-STEP PROCESS were $96.3\%$. In the case of SS, the average concentration was $7.0\%$ at the effluent.

• Journal of the Korean Data and Information Science Society
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• v.22 no.6
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• pp.1153-1166
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• 2011

Detecting misbehavior in vehicular ad-hoc networks is very important problem with wide range of implications including safety related and congestion avoidance applications. Most misbehavior detection schemes are concerned with detection of malicious nodes. In most situations, vehicles would send wrong information because of selfish reasons of their owners. Because of rational behavior, it is more important to detect false information than to identify misbehaving nodes. In this paper, we propose the variable precision rough sets based misbehavior detection scheme which detects false alert message and misbehaving nodes by observing their action after sending out the alert messages. In the proposed scheme, the alert information system, alert profile is constructed from valid actions of moving nodes in vehicular ad-hoc networks. Once a moving vehicle receives an alert message from another vehicle, it finds out the alert type from the alert message. When the vehicle later receives a beacon from alert raised vehicle after an elapse of time, then it computes the relative classification error by using variable precision rough sets from the alert information system. If the relative classification error is lager than the maximum allowable relative classification error of the alert type, the vehicle decides the message as false alert message. Th performance of the proposed scheme is evaluated as two metrics: correct ratio and incorrect ratio through a simulation.

• The KIPS Transactions:PartD
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• v.14D no.5
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• pp.555-564
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• 2007

Internet streaming systems consist of a media server, a streaming sewer, and terminals. The media server delivers multimedia contents such as video and/or audio to the streaming server, which distributes the contents to terminals as well. Existing Internet streaming systems have a bottleneck problem in the streaming server because of the limit of the processing capacity of the streaming server and therefore a streaming server can not accomodate more terminals than the limit. As a solution to this problem, P2P streaming systems have been lately proposed and investigated, using P2P distributed architectures. Actually, however, there exist many difficulties in the design and implementation of P2P streaming systems, because it needs many real computers and various network constructions. In this paper, we have proposed and defined a P2P streaming system model such as the architectural model, the timing model, the behavior model, and the performance metrics. And also we have implemented an NS2 based P2P streaming system simulator called P2PStreamSim. Finally, we have verified it through test simulations and analyzed the results.

• The KIPS Transactions:PartD
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• v.15D no.1
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• pp.61-72
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• 2008

One of the most significant tasks of software development project is to know how much it will be the software development cost in the early stage of software development cycle. The software development environment and technology are changing very rapidly. For accuracy, we should apply those to the software cost estimation. And it is important that we select the suitable adjustment factor and the value of a suitable adjustment factor. For that, this paper have applied the method of AHP. And we have also analyzed the sensitivity of the adjustment factor which is influenced by decision metrics. In conclusion, the value of the application type adjustment factor is responded more sensitively to the data complexity and the control complexity than processing complexity. And the value of the language adjustment factor is responded more sensitively to the supplying manpower and the time of the coding than the time of the debugging. In the future, we will research the selection of an additional adjustment factor and a suitable value of the adjustment factor which are influenced by the environment and the technology of the domestic software development. And then, in the language adjustment factor, we will try to calculate the value about the individual programming language.

• Korean Journal of Environmental Biology
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• v.31 no.4
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• pp.440-447
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• 2013

The ecological health, based on the Index of Biological Integrity (IBI) and Qualitative Habitat Evaluation Index (QHEI) was evaluated in 10 stream sites of Southern Han River. Eleven parameters of 12 parameters (Karr 1981) were modified for the application of regional Korean circumstance. The ecological health, based on IBI grade, was in "good condition" and the IBI score ranged from 33 to 47. Nine parameters of the original 12-parameter metrics in QHEI model (Plafkin et al. 1989) were applied in the habitat assessment. The mean QHEI model values were judged as "partially supporting" and ranged from 75 (non-supporting) to 109 (supporting). Comparative analyses revealed that values of IBI and QHEI models were greater in Gj stream than Ig- and Dn streams. The analysis of fish compositions showed that the proportions of insectivore, omnivore, and carnivore were 61.9%, 19%, and 9.5%, respectively. According to tolerance guild analysis, sensitive species and tolerant species were 76.1% and 4.7%, respectively, indicating a healthy trophic state in terms of food chain. The analysis by habitat guild type indicated that riffle benthic species dominated (57.1%) when compared to water column species (28.5%). The introduced species and individuals with diseases or external abnormality were not observed. Overall, the model values of IBI and QHEI suggested that the ecological health was maintained well in this upstream region.

• Journal of Intelligence and Information Systems
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• v.25 no.4
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• pp.89-103
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• 2019

Recently, various approaches to recommendation systems have been studied in terms of the quality of recommendation system. A recommender system basically aims to provide personalized recommendations to users for specific items. Most of these systems always recommend the most relevant items of users or items. Traditionally, the evaluation of recommender system quality has focused on the various predictive accuracy metrics of these. However, recommender system must be not only accurate but also useful to users. User satisfaction with recommender systems as an evaluation criterion of recommender system is related not only to how accurately the system recommends but also to how much it supports the user's decision making. In particular, highly serendipitous recommendation would help a user to find a surprising and interesting item. Serendipity in this study is defined as a measure of the extent to which the recommended items are both attractive and surprising to the users. Therefore, this paper proposes an application of serendipity measure to recommender systems to evaluate the performance of recommender systems in terms of recommendation system quality. In this study we define relevant or attractive unexpectedness as serendipity measure for assessing recommendation systems. That is, serendipity measure is evaluated as the measure indicating how the recommender system can find unexpected and useful items for users. Our experimental results show that highly serendipitous recommendation such as item-based collaborative filtering method has better performance than the other recommendations, i.e. user-based collaborative filtering method in terms of recommendation system quality.

• Journal of KIISE:Information Networking
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• v.30 no.4
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• pp.461-473
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• 2003

Multimedia applications are much more sensitive to QoS(Quality of Service) than text based ones due to their data continuity. In order to provide a fast moving MH(Mobil Host) using multimedia application with a consistent QoS,an efficient call admission mechanism is in need. This paper proposes the 2SCA(2-Step Call Admission) scheme based on cal admission scheme using pripority to guarantee the consistent QoS for mobile multimedia applications. A calls of MH are classified new calls, hand-off calls, and QoS upgrading calls. The 2SCA is composed of the basic call admission and advanced call admission; the former determines the call admission based on bandwidth available in each cell and the latter determines the call admission by applying DTT(Delay Tolerance Time), PQeueu(Priority Queue), and UpQueue(Upgrade Queue) algorithm according to the type of each call blocked at the basic call admission stage. In order to evaluate the performance of our mechanism, we measure the metrics such as the dropping probability of new calls, dropping probability of hand-off calls, and bandwidth utilization. The result shows that the performance of our mechanism is superior to that of existing mechanisms such as CSP(Complete Sharing Policy), GCP(Guard Channel Policy) and AGCP(Adaptive Guard Channel Policy).

• Journal of the Korea Academia-Industrial cooperation Society
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• v.12 no.4
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• pp.1844-1866
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• 2011

In a home network system, each customer electronic device has the control data format chosen by its manufacturing company and there are various types of digital devices and protocols. Besides the mutual operating environments among the various devices are dissimilar. Affected by the characteristics explained above, home network systems can hardly support the crucial functions, such as data compatibility, concurrency control, and dynamic plug-in. Thus, the home network system shows relatively poor reusability. In this paper, we suggest design technique of configurable framework, which can widely support the variability, to increase the reusability of the home network system. We extract the different parts of the home network system as variation points, and define them as the variability types. We design a structure of configurable framework, and suggest customization technique of configurable framework through selection technique and plug-in technique. Also, we prove the reusability by applying the proposed framework and it methods to real-world home network systems and analyzing the measurement results of these case studies using software metrics. We can expect the proposed approach provides better reusability than the existing them by analyzing those measurement results.

• Journal of the Korea Academia-Industrial cooperation Society
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• v.1 no.1
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• pp.91-100
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• 2000

In 1997 the recession of Korean economy brought about the bankruptcy of large corporations and the large size of non-Performing financial assets which led to IMF financial crisis. One of the major reasons for IMF financial crisis was poor loan management of domestic financial institutions . During the restructuring process of financial institutions since the IMF financial crisis, the importance of the loan management has been recognized. Especially. financial institutions' credit allocation had been concentrated on a few big conglomerates and their subsidies as well as some specific business areas. Hence, risk-diversifying portfolio effects were not reflected in any loan portfolios. The IMF financial crisis in 1997 has clearly showed that credit-risk management is essential not only for individuals' loan but also for portfolios consisting of various loans The main objective of this paper is to provide some suggestions on the direction for financial institutions in Korea to improve their loan portfolio management. Particularly, for the effective management of loan portfolios, this paper introduces quantitative credit-risk management schemes such as KMV models and CreditMetrics which are commonly used in financial institutions in advanced countries. Financial institutions in Korea should make their best efforts to establish a more scientific as well as quantitative loan portfolio management.