• 한국컴퓨터정보학회논문지
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• 제10권3호
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• pp.249-257
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• 2005

본 논문에서는 IPv6 기반 자동화된 공격 대응도구 알고리즘을 제안하였다. 현재는 IPv6에서 사용할 응용 프로그램 및 표준화에 초점을 두고 연구가 진행중에 있어 향후 IPv6의 보안에 대해서는 아직 연구가 미흡한 상태이다. 본 논문에서 제안한 방법은 IPv6에서 발생할 수 있는 공격과 기존 IPv4에서의 공격을 탐지하고 자동화된 대응방법을 통해 개인의 정보보호가 가능하다. 일반적으로 침입 탐지 시스템의 경우 탐지만 하기 때문에 피해는 계속 반복적이다. 따라서 본 연구에서는 이러한 문제점을 직시하고 조기에 연구함으로써 문제 해결방안을 제시하고자 한다. 본 논문에서 제안한 알고리즘은 리눅스 기반에서 IPv6망을 구축하여 실험 하였다. 실험 결과, 제안한 알고리즘을 이용하여 효율적으로 공격을 검출할 수 있었다.

• Structural Engineering and Mechanics
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• 제83권1호
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• pp.79-92
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• 2022

In this paper, the impact of a vernacular pozzolanic kaolinite mine on concrete alkali-silica reaction and strength has been evaluated. For making the samples, kaolinite powder with various levels has been used in the quality specification test of aggregates based on the ASTM C1260 standard in order to investigate the effect of kaolinite particles on reducing the reaction of the mortar bars. The compressive strength, X-Ray Diffraction (XRD) and Scanning Electron Microscope (SEM) experiments have been performed on concrete specimens. The obtained results show that addition of kaolinite powder to concrete will cause a pozzolanic reaction and decrease the permeability of concrete samples comparing to the reference concrete specimen. Further, various machine learning methods have been used to predict ASR-induced expansion per different amounts of kaolinite. In the process of modeling methods, optimal method is considered to have the lowest mean square error (MSE) simultaneous to having the highest correlation coefficient (R). Therefore, to evaluate the efficiency of the proposed model, the results of the support vector machine (SVM) method were compared with the decision tree method, regression analysis and neural network algorithm. The results of comparison of forecasting tools showed that support vector machines have outperformed the results of other methods. Therefore, the support vector machine method can be mentioned as an effective approach to predict ASR-induced expansion.

• 한국수자원학회논문집
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• 제56권11호
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• pp.705-720
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• 2023

국내에서는 지속적인 상수도 수질사고 발생으로 인해 수돗물 수질에 대한 이용자 불신이 확산되고 있다. 특히, 수질사고 외에도 수돗물에 포함된 염소 성분 등으로 인해 맛, 냄새 등에 대한 이용자들의 수질민원 또한 지속적으로 발생하고 있다. 따라서 상수도 사업자들은 이용자에게 공급되는 잔류염소농도가 충분히 잔류하면서도 과도하게 유지되지 않도록, 시간적(Scheduling) 및 공간적(Rechlorination) 관점에서 상수관망 내 잔류염소농도가 균등하게 분포하도록 다양한 방법을 검토 및 적용하고 있다. 본 연구에서는 상수관망 해석을 통한 월별 잔류염소농도 최적 관리 방법의 일환으로, 대규모 상수관망시스템을 대상으로 Lab-scale 실험을 통한 수체반응계수, EPANET 수질해석을 통한 관체반응계수 등 관망 수질반응계 수를 온도별로 추정하고, 온도별 수질반응계수를 바탕으로 염소투입농도 조건에 따른 월별 잔류염소농도 분포 현황을 분석하였다. 분석 결과, 온도 조건이 달라짐에 따라 잔류염소농도 하한 및 상한기준을 만족시킬 수 있는 효율적인 염소투입농도 조건 또한 달라지므로, 월별 잔류염소농도의 공간적 분포를 고려하여 구체적이고 정량적인 염소투입 계획 수립이 필요한 것으로 판단된다.

• 제어로봇시스템학회:학술대회논문집
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• 제어로봇시스템학회 1996년도 한국자동제어학술회의논문집(국내학술편); 포항공과대학교, 포항; 24-26 Oct. 1996
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• pp.282-285
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• 1996

In the water purification plant, the raw water is promptly purified by injecting chemicals. The amount of chemicals is directly related to water quality such as turbidity, temperature, pH and alkalinity. At present, however, the process of chemical reaction to the turbidity has not been clarified as yet. Since the process of coagulant dosage has no feedback signal, the amount of chemical can not be calculated from water quality data which were sensed from the plant. Accordingly, it has to be judged and determined by Jar-Test data which were made by skilled operators. In this paper, it is concerned to model and control the coagulant dosing process using jar-test results in order to predict optimum dosage of coagulant, PAC(Polymerized Aluminium Chloride). The considering relations to the reaction of coagulation and flocculation, the five independent variables(turbidity, temperature, pH, Alkalinity of the raw water, PAC feed rate) are selected out and they are put into calculation to develope a neural network model and a fuzzy model for coagulant dosing process in water purification system. These model are utilized to predict optimum coagulant dosage which can minimize the water turbidity in flocculator. The efficacy of the proposed control schemes was examined by the field test.

• Journal of Microbiology and Biotechnology
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• 제15권1호
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• pp.161-174
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• 2005

Abstract Glycolysis has a main function to provide ATP and precursor metabolites for biomass production. Although glycolysis is one of the most important pathways in cellular metabolism, the details of its regulation mechanism and regulating chemicals are not well known yet. The regulation of the glycolytic pathway is very robust to allow for large fluxes at almost constant metabolite levels in spite of changing environmental conditions and many reaction effectors like inhibitors, activating compounds, cofactors, and related metal ions. These changing environmental conditions and metabolic reaction effectors were focused on to understand their roles in the metabolic networks. In this study, we have investigated for construction of the regulatory map of the glycolytic metabolic network and tried to collect all the effectors as much as possible which might affect the glycolysis metabolic pathway. Using the results of this study, it is expected that a complex metabolic situation can be more precisely analyzed and simulated by using available programs and appropriate kinetic data.

• 한국정보통신학회논문지
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• 제12권8호
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• pp.1434-1440
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• 2008

전송률 기반의 흐름 제어 및 정체 제어 메커니즘을 사용하는 무선 네트워크에서 양방향 TCP/IP 연결의 성능을 연구한다. 전송률 기반의 흐름 제어를 이용하여 데이터의 흐름을 원활하게 유지함으로써, TCP 윈도우 흐름 제어에서 나타났던 다양한 유형의 버스트 현상을 제거하거나 완화시키는데 논하고, 대기열에서 전송률 제어 채널을 통해 실행되는 동안 버스트 반응에 의해 TCP ACK 압축 문제가 발생한다. 소스 IP 대기열의 주기적인 버스트 반응을 분석하여, 양방향 트래픽으로 인해 쓰루풋 저하됨으로써 향상된 퍼포먼스와 상황에 적용 가능한 쓰루풋 저하 예측을 나타내어 대기열의 최대값을 성능분석 한다.

• KSII Transactions on Internet and Information Systems (TIIS)
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• 제18권8호
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• pp.2157-2177
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• 2024

Demand response (DR) refers to the customers' active reaction with respect to the changes of market pricing or incentive policies. DR plays an important role in improving network reliability, minimizing operational cost and increasing end users' benefits. Hence, the integration of DR in the microgrid (MG) management is gaining increasing popularity nowadays. This paper proposes a day-ahead MG scheduling framework in conjunction with DR and investigates the impact of DR in optimizing load profile and reducing overall power generation costs. A linear responsive model considering time of use (TOU) price and incentive is developed to model the active reaction of customers' consumption behaviors. Thereafter, a novel multi-swarm sine cosine algorithm (MSCA) is proposed to optimize the total power generation costs in the framework. In the proposed MSCA, several sub-swarms search for better solutions simultaneously which is beneficial for improving the population diversity. A cooperative learning scheme is developed to realize knowledge dissemination in the population and a competitive substitution strategy is proposed to prevent local optima stagnation. The simulation results obtained by the proposed MSCA are compared with other meta-heuristic algorithms to show its effectiveness in reducing overall generation costs. The outcomes with and without DR suggest that the DR program can effectively reduce the total generation costs and improve the stability of the MG network.

• 한국재료학회지
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• 제9권4호
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• pp.373-377
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• 1999

The cure mechanicsm and cure kinetics of diglycidyl ether of bisphenol A(DGEBA)/4,4'-methylene dianiline(MDA)/nitrile(MN, SN, GN) systems were studied by FT-IR and DSC to develop new applications in the biomedical polymer fields. The network structure of the DGEBA/MDA system was changed to the chain-extended network structure by the addition of nitriles. The reactions contributed to the chain extension were the primary amine-nitrile and hydroxyl-nitrile reactions. The chain-extended network structure could be indirectly proved by the decrement of T\ulcorner and the increment of impact strength with the increasing nitrile content. The cure rate of DGEBA/MDA/nitrile system was lower than that of DGEBA/MDA system due to the disturbance of nitrile group in the reaction of primary amine and epoxide groups.

• 제어로봇시스템학회:학술대회논문집
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• 제어로봇시스템학회 1991년도 한국자동제어학술회의논문집(국내학술편); KOEX, Seoul; 22-24 Oct. 1991
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• pp.1002-1005
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• 1991

It is important to express the specific growth rate of a fermentation reaction as a function of substrate and product concentration in developing bioprocess automation techniques such as modeling of the reactor and controlling it via an advanced control scheme. Typical methods of identification utilize graphical representation of the rate constant data or nonlinear regression with an appropriate noise filter. But the former method fails when the data are erroneous and the latter are mathematically complicated to apply in the field. Neural network is another candidate for the identification from time series data since it is insensitive to the random data error and easy to implement. In this study, we will develop a neural network method of specific growth rate estimation from the time series state variable data and test the performance.

• 대한기계학회:학술대회논문집
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• 대한기계학회 2008년도 추계학술대회A
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• pp.894-899
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• 2008

Measured sensor datum from a quadruped robotics is commonly used for recognizing physical environment information which controls the posture of robotics. We can advance the ambulation with this sensed information and need to synthesize various sensors for obtaining accurate data, but most of these sensors are expensive and require excessive load for the operation. Those defects can be serious problem when it comes to the prototype's practicality and mass production, and maintenance of the system. This paper suggests virtual sensor technology for avoiding previous defects and presents ways to apply a theory to a walking robotics through virtual sensor information which is trained with several kinds of actual sensor information from the prototype system; the general algorithm is initially based on the neural network theory of back propagation. In specific, we verified a possibility of replacing the virtual sensor with the actual one through a reaction force measurement experiment.