• Journal of Korean Society of Steel Construction
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• v.24 no.3
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• pp.325-336
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• 2012

Smart base isolation systems developed for structures in high seismic regions cannot be directly applied to structures in regions of low-to-moderate seismicity, such as Korea. Therefore, the problems that occur by applying the smart base isolation system for high seismic regions to the structures in regions of low-to-moderate seismicity have been investigated in this study. To this end, a five-story building is used as an example, and an MR damper and low damping elastomeric bearings were used to compose a smart base isolation system. Artificial earthquakes are simulated for ground motions in regions of high and low-to-moderate seismicity. Based on numerical simulation results, the MR damper capacity that can provide good control is quite different among regions of high and low-to-moderate seismicity. Moreover, it is noted that the properties of a smart base isolation system for the regions of low-to-moderate seismicity should be carefully designed because the base isolation effects of the smart base isolation system for high seismic regions deteriorate when it is applied to the structures in regions of low-to-moderate seismicity.

• Journal of the Institute of Electronics and Information Engineers
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• v.51 no.6
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• pp.276-281
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• 2014

Necessities of a traffic means work a car in the modern society human to an usability of a life is enjoying. On the other hand, the damage by traffic accident increment the human quotient worked as we were in proportion to the vehicle which increased. Passing an examination moves necessarily on an obstacle to suddenly appear at the fronts if a car travels and the vehicles which stopped suddenly. Dynamic passing an examination about an obstacle turn on Vehicle Emergency Lamp to by hand when is unhurried, and can turn off, but to appear urgently dynamic passing an examination in time human is instinctive, but cannot inform an emergency to a back vehicle, and a rear-end collision occurs. A car we synthesize a speed of a vehicle, and this unit analyzes as we use GPS, and to drive runs Vehicle Emergency Lamp to automatic in the situations that shall turn on emergencies etc. If a speed of a vehicle continuously slows down in too high-speed driving or low-speed driving, or we are stopped, Vehicle Emergency Lamp is always turned on. It was built if we rise again as clearing itself from risk, and a speed of a vehicle judges, and we turn off Vehicle Emergency Lamp to automatic. It runs till rear-end collision sensor operates, and by hand reset does Vehicle Emergency Lamp a driving vehicle collides from behind to a back vehicle or when a driving vehicle was overthrown. It is shortened very much to the chain rear-end collision traffic accident that is a traffic accident of large size if we use this unit. And we did authentication through the experiment which a driver was helpful to unnecessary operation and a relaxed safe driving during drivings.

• The Journal of Korean Institute of Communications and Information Sciences
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• v.35 no.4B
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• pp.566-575
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• 2010

In recent, artificial immune system has become an important research direction in the anomaly detection of networks. The conventional artificial immune systems are usually based on the negative selection that is one of the computational models of self/nonself discrimination. A main problem with self and non-self discrimination is the determination of the frontier between self and non-self. It causes false positive and false negative which are wrong detections. Therefore, additional functions are needed in order to detect potential anomaly while identifying abnormal behavior from analogous symptoms. In this paper, we design novel network attack detection and response schemes based on artificial immune system, and evaluate the performance of the proposed schemes. We firstly generate detector set and design detection and response modules through adopting the interaction between dendritic cells and T-cells. With the sequence of buffer occupancy, a set of detectors is generated by negative selection. The detection module detects the network anomaly with a set of detectors and generates alarm signal to the response module. In order to reduce wrong detections, we also utilize the fuzzy number theory that infers the degree of threat. The degree of threat is calculated by monitoring the number of alarm signals and the intensity of alarm occurrence. The response module sends the control signal to attackers to limit the attack traffic.

• Journal of KIISE:Databases
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• v.28 no.3
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• pp.494-511
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• 2001

In the environment that database management systems manage disk spaces for storing databases directly, this paper proposes a correct and efficient scheme of performing pending actions for the removal of database files. As for performing pending actions, upon performing recovery, the recovery process must identify unperformed pending actions of not-yet-terminated transactions and then perform those actions completely. Making the recovery process identify those actions through the analysis of log records in the log file is the basic idea of this paper. This scheme, as an extension of the execution of transactions, fuzzy checkpoint, and recovery of ARIES, uses the following methods: First, to identify not-yet-terminated transactions during recovery, transactions perform pending actions after writing 'pa_start'log records that signify both the commit of transactions and the start of executing pending actions, and then write 'eng'log records. Second, to restore pending-actions-lists of not-yet-terminated transactions during recovery, each transaction records its pending-actions-list in 'pa_start'log record and the checkpoint process records pending-actions-lists of transactions that are decided to be committed in 'end_chkpt'log record. Third, to identify the next pending action to perform during recovery, whenever a page is updated during the execution of pending actions, transactions record the information that identifies the next pending action to perform in the log record that has the redo information against the page.

• Journal of Korean Society of Transportation
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• v.19 no.6
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• pp.75-87
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• 2001

Inter-port competition is fiercer than in the past because of technological evolution in transport systems : the increasing side of containerships implies only a few calls in three or four ports at each end of the trade and the rest of the traffic being served by smaller feederships. It is therefore essential for big ports to be selected as one of these calls by the main shipowners, consortia and alliances to avoid rmarginalisation. In order to compete effectively, many ports have been obliged to modernise and extend considerably its existing ports or to build new port facilities. With the advent of major environmental legislation around the world, however, amenities such as fish and wildlife, clean air and water, access to the waterfront, and view protection took on greater importance. Ports are now being forced to incorporate environmental considerations into their planning and management functions in order to avoid additional costs or timing delays. The aim of this paper is to analyse the port value by which port comparison(or selection) will be made with HFP(Hierarchical Fuzzy Process) method. This was done by extracting and grouping the evaluation factors of port value by port experts : facility and location factor, logistics service factor environment and amenity factor, city and economic factor, and human and system factor. For empirical test of this method, 6 major ports in Northeast Asia were chosen and analysed. The order of importance for five evaluation factors were 1) facility and location factor 2) logistics service factor 3) human and system factor, 4) city and economic factor, and 5) environment and amenity factor. This means that geographical location and logistics services are still being considered as the most important factor to call the port by port users. even though environment and amenity factor shows relatively low figure. Among 6 major ports, Port of Kobe was ranked the first position in a comprehensive evaluation, while Ports of Busan and Kwangyang were 4th and 5th respectively. This implies that Port of Busan should make much efforts to enhance the existing facilities as well as management system.

• Journal of Korea Water Resources Association
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• v.44 no.12
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• pp.1015-1029
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• 2011

Conventional MCDA techniques have been used in the field of water resources in the past. A GIS can offer an effective spatial data-handling tool that can enhance water resources modeling through interfaces with sophisticated models. However, GIS systems have a limited capability as far as the analysis of the value structure is concerned. The MCDA techniques provide the tools for aggregating the geographical data and the decision maker's preferences into a one-dimensional value for analyzing alternative decisions. In other words, the MCDA allows multiple criteria to be used in deciding upon the best alternatives. The combination of GIS and MCDA capabilities is of critical importance in spatial multi-criteria analysis. The advantage of having spatial data is that it allows the consideration of the unique characteristics at every point. The purpose of this study is to identify, review, and evaluate the performance of a number of conventional MCDA techniques for integration with GIS. Even though there are a number of techniques which have been applied in many fields, this study will only consider the techniques that have been applied in floodplain decision-making problems. Two different methods for multi-criteria evaluation were selected to be integrated with GIS. These two algorithms are Compromise Programming (CP), Spatial Compromise Programming (SCP). The target region for a demonstration application of the methodology was the Suyoung River Basin in Korea.

• Proceedings of the Korea Water Resources Association Conference
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• 2017.05a
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• pp.264-264
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• 2017

국외의 상수도 원격검침 시스템 내 데이터 전송방식은 도시 규모, 계량기의 밀도, 전력공급 여부 및 통신망의 설치 여부 등을 종합적으로 고려하여 결정되었다. 대부분의 스마트워터미터 제조업체들은 계량기의 부호기가 공급하는 판독 내용(데이터)을 전송할 검침단말기와 근거리 통신망(neighborhood area network)을 연계하여 개발 및 판매하였으며, 자체 소유 통신 프로토콜을 사용하여 라디오 주파수(RF) 통신 기술을 사용하고 있다. 광역통신망(wide area network)의 경우, 노드(말단의 계량기 및 센서)들과 이에 연결된 통신망 들을 포함한 네트웍의 배열이나 구성이 스타(star), 메쉬(mesh), 버스(bus), 나무(tree) 등의 형태로 통신망이 구성되어 있으나, 스타와 메쉬형 통신망 구성형태가 가장 널리 활용되는 것으로 조사되었다. 시스템 통합운영관리 업체들인 IBM, Oracle, Itron 등은 용수 인프라 관리 또는 통합네트워크 솔루션 등의 통합 물관리 시스템(integrated water management system)을 개발하여 현장적용을 하고 있으며, 원격검침 시스템을 통해 고객들의 현재 소비량과 과거 누적 소비량, 누수 감지 서비스 및 실시간 요금 고지 등을 실시간으로 웹 포털과 앱을 통해 제공하고 있다. 또한, 일부 제조업체들은 도시 용수공급/소비 관리자가 주민의 용수사용량을 모니터링하여 일평균 용수사용량 및 사용 경향을 파악하고, 누수를 검지하여 복구 및 용수 사용 지속가능성 지수를 제시하고, 실시간으로 주민의 용수사용량 관련 데이터를 모니터링하여 용수공급의 최적화를 위한 의사결정지원 서비스를 용수공급자에게 제공하고 있다. 최근에는 인공지능을 활용해 가정용수의 용도별(세탁용수, 화장실용수, 샤워용수, 식기세척용수 등) 사용량 곡선을 패터닝하여 profiling 기법을 도입해, 스마트워터미터에서 용수사용량이 통합되어 검지될 시 용수사용량의 세부 용도별 re-profiling 기법을 도입하여 가정용수내 과소비되는 지점을 도출 후 절감을 유도하는 기술이 개발 중이다. 또한, 미래 용수 사용량 예측을 위해 다양한 시계열 자료를 분석하는 선형 종속 모형(자기회귀모형, 자기회귀이동평균모형, 자기회귀적분이동평균모형 등)과 비선형 종속 모형(Fuzzy Logic, Neural Network, Genetic Algorithm 등)을 활용한 예측기능이 구축되어 상호 비교하여 최적의 용수사용량 예측 도구를 제공되고 있다.

• Journal of the Korean Regional Science Association
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• v.34 no.4
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• pp.3-18
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• 2018

These days, regional innovation draws more attention than ever as a growth engine for regional economies, and governments put a variety of efforts to establish Regional Innovation systems(RISs). In this circumstance, this study aims to analyze types of RISs and the combinations of the factors influencing innovation performance as measured by patent application. Most of previous works have depended on case-oriented or variable-oriented strategy to classify types of RISs or to analyze the effects on performance of innovation factors, having some limitations: Variable-oriented approaches fail to capture complex combinatory effects of factors, while case-oriented approaches tend to depend on subjective interpretation. This study made use of the recently proposed fs/QCA(Fuzzy-set Qualitative Comparative Analysis) to overcome the limitations of those strategies. Based on the theory of RIS, three factors for regional innovation-input, infrastructure, and network-are used to classify 16 Korean Provinces. The results show that eight types of regional innovation types are identified, and that most of the regions are classified into either IN-type, equipped with high levels of Input and Network, or F-type, with high levels of infrastructure. In addition, applying seven sub-variables of the three factors to the fussy-set combination factor analysis, we examine a combination of factors influencing patent application. The results show that regions with high levels of R&D expense, valid patent, industry-academia cooperation, IP budget, and TLO values, and low IP capital almost always have a high level of patent application. Therefore, for regional innovation, the public sector needs to provide institutional support for R & D personnel training. It is also important to for both the public and the private sectors to make efforts to stimulate IP financing.

• Journal of Korean Society of Industrial and Systems Engineering
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• v.46 no.4
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• pp.199-208
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• 2023

Taguchi method is one of the most popular approaches for design optimization such that performance characteristics become robust to uncontrollable noise variables. However, most previous Taguchi method applications have addressed a single-characteristic problem. Problems with multiple characteristics are more common in practice. The multi-criteria decision making(MCDM) problem is to select the optimal one among multiple alternatives by integrating a number of criteria that may conflict with each other. Representative MCDM methods include TOPSIS(Technique for Order of Preference by Similarity to Ideal Solution), GRA(Grey Relational Analysis), PCA(Principal Component Analysis), fuzzy logic system, and so on. Therefore, numerous approaches have been conducted to deal with the multi-characteristic design problem by combining original Taguchi method and MCDM methods. In the MCDM problem, multiple criteria generally have different measurement units, which means that there may be a large difference in the physical value of the criteria and ultimately makes it difficult to integrate the measurements for the criteria. Therefore, the normalization technique is usually utilized to convert different units of criteria into one identical unit. There are four normalization techniques commonly used in MCDM problems, including vector normalization, linear scale transformation(max-min, max, or sum). However, the normalization techniques have several shortcomings and do not adequately incorporate the practical matters. For example, if certain alternative has maximum value of data for certain criterion, this alternative is considered as the solution in original process. However, if the maximum value of data does not satisfy the required degree of fulfillment of designer or customer, the alternative may not be considered as the solution. To solve this problem, this paper employs the desirability function that has been proposed in our previous research. The desirability function uses upper limit and lower limit in normalization process. The threshold points for establishing upper or lower limits let us know what degree of fulfillment of designer or customer is. This paper proposes a new design optimization technique for multi-characteristic design problem by integrating the Taguchi method and our desirability functions. Finally, the proposed technique is able to obtain the optimal solution that is robust to multi-characteristic performances.

• Journal of Intelligence and Information Systems
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• v.21 no.1
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• pp.119-142
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• 2015

With the explosive growth in the volume of information, Internet users are experiencing considerable difficulties in obtaining necessary information online. Against this backdrop, ever-greater importance is being placed on a recommender system that provides information catered to user preferences and tastes in an attempt to address issues associated with information overload. To this end, a number of techniques have been proposed, including content-based filtering (CBF), demographic filtering (DF) and collaborative filtering (CF). Among them, CBF and DF require external information and thus cannot be applied to a variety of domains. CF, on the other hand, is widely used since it is relatively free from the domain constraint. The CF technique is broadly classified into memory-based CF, model-based CF and hybrid CF. Model-based CF addresses the drawbacks of CF by considering the Bayesian model, clustering model or dependency network model. This filtering technique not only improves the sparsity and scalability issues but also boosts predictive performance. However, it involves expensive model-building and results in a tradeoff between performance and scalability. Such tradeoff is attributed to reduced coverage, which is a type of sparsity issues. In addition, expensive model-building may lead to performance instability since changes in the domain environment cannot be immediately incorporated into the model due to high costs involved. Cumulative changes in the domain environment that have failed to be reflected eventually undermine system performance. This study incorporates the Markov model of transition probabilities and the concept of fuzzy clustering with CBCF to propose predictive clustering-based CF (PCCF) that solves the issues of reduced coverage and of unstable performance. The method improves performance instability by tracking the changes in user preferences and bridging the gap between the static model and dynamic users. Furthermore, the issue of reduced coverage also improves by expanding the coverage based on transition probabilities and clustering probabilities. The proposed method consists of four processes. First, user preferences are normalized in preference clustering. Second, changes in user preferences are detected from review score entries during preference transition detection. Third, user propensities are normalized using patterns of changes (propensities) in user preferences in propensity clustering. Lastly, the preference prediction model is developed to predict user preferences for items during preference prediction. The proposed method has been validated by testing the robustness of performance instability and scalability-performance tradeoff. The initial test compared and analyzed the performance of individual recommender systems each enabled by IBCF, CBCF, ICFEC and PCCF under an environment where data sparsity had been minimized. The following test adjusted the optimal number of clusters in CBCF, ICFEC and PCCF for a comparative analysis of subsequent changes in the system performance. The test results revealed that the suggested method produced insignificant improvement in performance in comparison with the existing techniques. In addition, it failed to achieve significant improvement in the standard deviation that indicates the degree of data fluctuation. Notwithstanding, it resulted in marked improvement over the existing techniques in terms of range that indicates the level of performance fluctuation. The level of performance fluctuation before and after the model generation improved by 51.31% in the initial test. Then in the following test, there has been 36.05% improvement in the level of performance fluctuation driven by the changes in the number of clusters. This signifies that the proposed method, despite the slight performance improvement, clearly offers better performance stability compared to the existing techniques. Further research on this study will be directed toward enhancing the recommendation performance that failed to demonstrate significant improvement over the existing techniques. The future research will consider the introduction of a high-dimensional parameter-free clustering algorithm or deep learning-based model in order to improve performance in recommendations.