• 대한전자공학회논문지
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• 제13권3호
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• pp.1-6
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• 1976

이 논문에서는 Boolean difference를 이용하여 combinational 및 sequential 논리회로에서 발생하는 기능적인 고장에 대한 test pattern을 얻는 방법을 연구하였다. 이 방법은 test pattern을 얻고자 하는 회로의 Boolean 함수의 Boolean difference를 계산하므로써 체계적으로 test pattern을 얻는 절차를 보여주고 있다. 컴퓨터에 의한 실험결과에 의하며 이 방법은 combinational 회로 및 asynchronous sequential 회로에 적합하며, clock이 있는 flip flop을 적당히 모형화함으로서 이 방법을 synchronous sequential회로에도 적용할 수 있음이 입증되었다. In this paper, a method of test pattern generation for the functional failure in both combinational and sequentlal logic networks by using exterded Boole an difference is proposed. The proposed technique provides a systematic approach for the test pattern generation procedure by computing Boolean difference of the Boolean function that represents the Logic network for which the test patterns are to be generated. The computer experimental results show that the proposed method is suitable for both combinational and asynchronous sequential logic networks. Suitable models of clocked flip flops may make it possible for one to extend this method to synchronous sequential logic networks.

• 터널과지하공간
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• 제4권2호
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• pp.132-143
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• 1994

Many methods and techniques to reduce ground vibrations are well known. Some of them are to adopt electric millisecond detonators with a sequential blasting machine or an initiating system with an adequate number of delay intervals. The types of electric detonators manufactured in korea include instantaneous, decisecond and millisecond delays but numbers of delay intervals are only limited from No.1 to No.20 respectively. It is not sufficient to control accurately millisecond time with these detonators in tunnel excavation. Sequential fire time refers to adding an external time delay to a detonators norminal firing time to obtain sequential initiation and it is determined by sequential timer setting. To reduce the vibration level, sequential blasting machine(S.B.M) with decisecond detonators was adopted. A total of 134 blasts was recorede at various sites. Blast-to-structure distances ranged from 20.3 to 42.0 meter, where charge weight varied from 0.24 to 0.75 kg per delay. The results can be summarized as follow: 1. The effects of sequential blasting machine on the vibration level are discussed. The vibration level by S.B.M are decreased approximately 14.38~18.05% compare to level of conventional blasting and cycle time per round can be saved. 2. The empirical equations of particle velocity were obtained in S.B.M and conventional blasting. V=K(D/W1/3)-n, where the values for n and k are estimated to be 1.665 to 1.710 and 93.59 to 137 respectively. 3. The growth of cracks due to vibrations are found but the level fall to within allowable value.

• East Asian mathematical journal
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• 제10권2호
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• pp.271-277
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• 1994

• 한국국방경영분석학회지
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• 제2권1호
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• pp.73-79
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• 1976

• 대한토목학회논문집
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• 제33권5호
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• pp.1797-1807
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• 2013

예상하지 못한 자연 현상으로 인해 붕괴될 가능성을 항상 내포하고 있으며 특히 댐 하류부 지역이 인구밀집 지역이거나 중요 국가 시설물이 위치하고 있는 경우에는 인명 및 재산피해 등 막대한 손실을 초래할 수 있다. 지금까지의 연구는 단독댐 붕괴에 따른 홍수파 해석에 대한 연구는 많이 있었으나 세계적으로 유명한 테네시강 등의 순차적 댐이나 우리나라의 북한강 상류로부터 연속으로 이어진 댐 등에 대한 붕괴 홍수파 해석에 대한 연구는 미흡한 실정이다. 따라서 본 연구의 목적은 순차적 댐 붕괴 홍수파 해석을 통해 순차적 댐 붕괴 첨두유량을 계산하고 하류부에서의 홍수파 전파상황을 예측할 수 있는 해석기법을 제시하는데 있다. 이를 위해 DAMBRK를 이용하여 실제 붕괴 사례 중 순차적 댐 붕괴 사례인 Lawn Lake Dam에 대하여 붕괴 홍수파 해석을 실시하여 댐 붕괴 홍수파 해석 모형의 적절성을 검증하였다. 이를 기초로 하여 가상의 극한홍수에 대하여 국내의 A 댐에 대하여 순차적 댐 붕괴 홍수파 해석을 실시하여 홍수파 전파상황을 예측하였으며, 범람 중요 지점에 대하여 2차원 홍수범람해석을 수행하여 1 2차원 홍수파 해석을 비교 분석한 결과 적합도가 90%를 상회하여 1차원 순차적 댐 붕괴 모의의 정확성을 확인할 수 있었다. 이는 순차적 댐 붕괴와 관련된 하천에서의 방재대책 수립을 위한 기본자료를 제공하는데 기여할 수 있을 것으로 판단된다.

• KSII Transactions on Internet and Information Systems (TIIS)
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• 제11권10호
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• pp.5023-5038
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• 2017

Big data is an emerging technology which deals with wide range of data sets with sizes beyond the ability to work with software tools which is commonly used for processing of data. When we consider a huge network, we have to process a large amount of network information generated, which consists of both normal and abnormal activity logs in large volume of multi-dimensional data. Intrusion Detection System (IDS) is required to monitor the network and to detect the malicious nodes and activities in the network. Massive amount of data makes it difficult to detect threats and attacks. Sequential Pattern mining may be used to identify the patterns of malicious activities which have been an emerging popular trend due to the consideration of quantities, profits and time orders of item. Here we propose a sequential pattern mining algorithm with fuzzy logic feature selection and fuzzy weighted support for huge volumes of network logs to be implemented in Apache Hadoop YARN, which solves the problem of speed and time constraints. Fuzzy logic feature selection selects important features from the feature set. Fuzzy weighted supports provide weights to the inputs and avoid multiple scans. In our simulation we use the attack log from NS-2 MANET environment and compare the proposed algorithm with the state-of-the-art sequential Pattern Mining algorithm, SPADE and Support Vector Machine with Hadoop environment.

• International Journal of Quality Innovation
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• 제4권1호
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• pp.131-147
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• 2003

This paper considers that a public department under specialized TQM manpower constraints have to implement multiple total quality management (TQM) policies to promote its service performance (fundamental goal) by adopting a centralized sequential advancement strategy (CSAS). Under CSAS, the decision-makers (DMs) start off by focusing specialized TQM manpower on a single policy, then transfer the specialized TQM manpower to the next policy when the first policy reaches the predetermined implementation time limit (in terms of education and training). Suppose that each TQM policy has a different desirous education and training goal. When the desirous goals for all TQM policies are achieved, we say that the fundamental goal will be satisfied. Within the limitation of total implementation period of time for all policies, assume the desirous goals for all TQM policies cannot be achieved completely. Under this premise, the optimal implementation sequence for all TQM policies must be calculated to maximize the weighted achievement of the desirous goal. We call this optimization problem a TQM case of "centralized sequential decision-making problem (CSDMP)". The achievement of the desirous goal for each TQM policy is usually affected by the experience in prior implemented policies, which makes solving CSDMP quite difficult. As a result, this paper introduces the concepts of sequential effectiveness and path effectiveness. The structural properties are then studied to propose theoretical methods for solving CSDMP. Finally, a numerical example is proposed to demonstrate CSDMP′s usability.

• 전기학회논문지
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• 제62권10호
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• pp.1354-1360
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• 2013

In transmission system, reclosing scheme is very useful method to improve continuity of power supply and reliability of system. Especially, high speed reclosing which is used generally in transmission systems has a benefit improving transient stability. However, the reclosing can jeopardize the stability under the condition having high difference of voltage phase angle between both ends. Thus, this paper proposes optimal sequential reclosing scheme to improve transient stability due to reclosing operation. The optimal sequential reclosing is that each phase is closed sequentially considering transient energy. In this paper, 345kV and 154kV transmission system is modeled using EMTP (ElectroMagnetic Transient Program) to verify the performance and effectiveness of optimal sequential reclosing on transient stability. Also, Integral Square Error(ISE) method is used to assess the transient stability.

• Structural Engineering and Mechanics
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• 제51권6호
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• pp.989-1003
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• 2014

In the preliminary design stage of an RC 3D-frame, repeated sequential analyses to determine optimal members' sizes and the investigation of the parameters required to minimize the differential column shortening are computational effort consuming, especially when considering various types of loads such as dead load, temperature action, time dependent effects, construction and live loads. Because the desired accuracy at this stage does not justify such luxury, two backpropagation feedforward artificial neural networks have been proposed in order to approximate this information. Instead of using a commercial software package, many references providing advanced principles have been considered to code a program and generate these neural networks. The first one predicts the typical amount of time between two phases, needed to achieve the minimum maximorum differential column shortening. The other network aims to prognosticate sequential analysis results from those of the simultaneous analysis. After the training stages, testing procedures have been carried out in order to ensure the generalization ability of these respective systems. Numerical cases are studied in order to find out how good these ANN match with the sequential finite element analysis. Comparison reveals an acceptable fit, enabling these systems to be safely used in the preliminary design stage.

• 대한기계학회논문집A
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• 제31권1호
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• pp.55-61
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• 2007

Recently simulation model becomes an essential tool for analysis and design of a system but it is often expensive and time consuming as it becomes complicate to achieve reliable results. Therefore, high-fidelity simulation model needs to be replaced by an approximate model, the so-called metamodel. Metamodeling techniques include 3 components of sampling, metamodel and validation. Cross-validation approach has been proposed to provide sequnatially new sample point based on cross-validation error but it is very expensive because cross-validation must be evaluated at each stage. To enhance the cross-validation of metamodel, sequential sampling method using candidate points and representative cross-validation is proposed in this paper. The candidate and representative cross-validation approach of sequential sampling is illustrated for two-dimensional domain. To verify the performance of the suggested sampling technique, we compare the accuracy of the metamodels for various mathematical functions with that obtained by conventional sequential sampling strategies such as maximum distance, mean squared error, and maximum entropy sequential samplings. Through this research we team that the proposed approach is computationally inexpensive and provides good prediction performance.