• Proceedings of the Korean Institute of IIIuminating and Electrical Installation Engineers Conference
• /
• 2004.05a
• /
• pp.434-436
• /
• 2004

Load forecasting is essential in the electricity market for the participants to manage the market efficiently and stably. The percentage errors of 24 hourly load forecasting for holidays is relatively large. In this paper, we propose the maximum and minimum load forecasting method for holidays using a fuzz linear regression algorithm. 24 hourly loads are forecasted from the maximum and minimum loads and the 24 hourly normalized values. The proposed algorithm is tested for 24 hourly load forecasting in 1996. The test results show the proposed algorithm improves the accuracy of the load forecasting.

• Proceedings of the KIEE Conference
• /
• 2007.07a
• /
• pp.1720-1721
• /
• 2007

This paper presents a Fuzzy+PID control method for a Bridge Inspection Robot(BIR) system. The BIR has been developed with the aim of checking the safety status of a real bridge, gathering accurate data and performing maintenance. The developed robot system is composed of the specially designed car for bridge inspection, the guide rail and the inspection robot. The proposed Fuzzy+PID controllers are used to track speed reference signal of X axis and position reference signal of Z axis. Experimental results verify that the proposed Fuzz+PID control design method can achieve favorable control performance with regard to external disturbance.

• Proceedings of the Korea Information Processing Society Conference
• /
• 2013.11a
• /
• pp.680-683
• /
• 2013

방화벽, 백신, IPS, 취약점 점검 시스템 등 중요 시스템의 보안을 위해 다수의 소프트웨어들이 운용되고 있다. 그 중 취약점 점검 시스템은 중요 서버의 보안 취약점을 점검하여 사전에 보안 위협을 예방한다는 측면에서 중요하다. 그러나 서버의 취약점을 점검해주는 소프트웨어 자체에 취약점이 존재한다면 취약점 보완을 위해 도입한 시스템이 취약점을 내포하고 있는 모순된 상황을 발생시킨다. 본 논문에서는 취약점 점검 시스템의 매니저와 에이전트의 점검 패킷을 분석하여 데이터 필드에 임의의 값을 주입하는 SPIKE 기반의 퍼즈 테스팅 기법으로 매니저와 에이전트 모두에서 DoS(Denial of Service) 취약점을 발견하였다. 해당 취약점은 다수의 SQL 세션을 생성하고 시스템의 CPU 점유율을 100%로 높여 시스템의 다른 서비스조차 이용할 수 없는 상태를 보였다.

• Journal of the Korea Academia-Industrial cooperation Society
• /
• v.19 no.1
• /
• pp.603-608
• /
• 2018

Although the voltage-applied discharge method is most widely used in the semiconductor and display industries, periodic management costs are incurred because the method causes defects due to the absorption of ambient fine dust and causes emitter tip contamination due to the discharge. The emitter tip contamination problem is caused by the accumulation of fine particles in ambient air due to the corona discharge of the ionizer. Fuzzy ball generation accelerates the wear of the emitter tip and deteriorates the performance of the ionizer. Although a mechanical cleaning method using a manual brush or an automatic brush is effective for contaminant removal, it requires management of additional mechanical parts by the user. In some cases, contaminants accumulated in the emitter may be transferred to the wafer or product. In order to solve this problem, we developed an ionizer for a clean environment that can remove the pencil-type emitter tip and directly ionize the surrounding gas molecules using the tungsten wire located inside the ion tank. As a result of testing and certification by the Korea Institute of Machinery and Materials, the average concentration was $0.7572particles/ft^3$, the decay time was less than two seconds, and the ion valance was 7.6 V, which is satisfactory.

• Journal of the Korea Institute of Information Security & Cryptology
• /
• v.30 no.5
• /
• pp.847-857
• /
• 2020

As IoT equipment is commercialized, Bluetooth or wireless networks will be built into general living devices such as IP cameras, door locks, cars and TVs. Security for IoT equipment is becoming more important because IoT equipment shares a lot of information through the network and collects personal information and operates the system. In addition, web-based attacks and application attacks currently account for a significant portion of cyber threats, and security experts are analyzing the vulnerabilities of cyber attacks through manual analysis to secure them. However, since it is virtually impossible to analyze vulnerabilities with only manual analysis, researchers studying system security are currently working on automated vulnerability detection systems, and Firm-AFL, published recently in USENIX, proposed a system by conducting a study on fuzzing processing speed and efficiency using a coverage-based fuzzer. However, the existing tools were focused on the fuzzing processing speed of the firmware, and as a result, they did not find any vulnerability in various paths. In this paper, we propose IoTFirmFuzz, which finds more paths, resolves constraints, and discovers more crashes by strengthening the mutation process to find vulnerabilities in various paths not found in existing tools.

• Journal of Korea Society of Digital Industry and Information Management
• /
• v.13 no.1
• /
• pp.1-12
• /
• 2017

Recently, the Go game has been performed between the 'AlphaGo' of the DeepMind and Lee Sedol, a famous professional Go-player of Korea, which leads to arise a lot of interests in the AI (Artificial Intelligence) research area. Based on the Fuzzy logic of the AI, we have also developed another game's AI, .i.e., the Yutnori game, one of Korean traditional board games. However, it is not easy and simple to consider all the cases of the Yutnori game since it is a non-perfect information game in terms of the AI. Thus, we have developed the Fuzzy-logic-based AI which tries to simulate humans' selections, meaning that the suggested AI has focused on the humans' choices depending on diverse situations in the Yutnori. With our extensive simulations using the suggested Yutnori AI, we have analyzed its performances with respect to 10 Yutnori situations among various scenarios. In conclusion, our suggested AI have demonstrated that 6 out of 10 situations are exactly same with the humans' choices and the rest 4 cases are also similar to that of human's, which reveals that our Fuzz-logic-based Yutnori AI can effectively simulate human's choices.

• KIPS Transactions on Computer and Communication Systems
• /
• v.2 no.9
• /
• pp.399-404
• /
• 2013

MSEC(Microsoft Security Engineering Center) performed fuzz testing Windows Vista with 350 million test cases for 14 months before launching it. They analyzed crashes resulted from the testing and developed crash analyzer !exploitable based on the data used to determine exploitability. In this paper, we describe how MS crash analyzer determines exploitability of crashes. Besides, we suggest an improvement to overcome the limitations found in the MS crash analyzer during the analysis.

• Proceedings of the KIEE Conference
• /
• 1997.11a
• /
• pp.505-508
• /
• 1997

In this paper, an auto-tuning method for fuzzy controller based on the neural network is presented. The backpropagated error of neural emulator offers the path which reforms the fuzzy controller's membership functions and fuzzy rule, and used for speed control of induction motor. For the torque control method, an indirect vector control scheme with slip calculation is used because of its stable characteristics regardless of speed. Motor input current is regulated by a current controlled voltage source PWM inverter using space voltage vector technique. Also, the scheme of current control fuzzy controller is synchronous reference frame with decoupling term. DSP(TMS320C31) is used to achieve the high speed calculation of the space voltage vector PWM and to build the self-learning fuzz. control algorithm. An IPM is used to simplify hardware design.

• Textile Coloration and Finishing
• /
• v.20 no.4
• /
• pp.15-20
• /
• 2008

The cotton yarn was subjected to bio-polishing treatment with three commercial enzymes(Cellusoft L, Denimax-991L and Denimax-acid) to remove the fuzz on the cotton yarn. Also, enzyme treated cotton yarns were compared with singeing cotton yarns. Experimental variables of enzyme treated cotton yarn were as follow: concentration of enzyme solution and NaOH, dipping time, and processing temperature. The enzymatic treatments were evaluated by analyzing the effect on yarn count, twist contraction, evenness and tenacity. As the results, enzymatic treatment on cotton yarn induced same effects as the traditional singeing treatment. Also, silket treatment of cotton yarn after bio-polishing enhanced the tensile properties of the cotton yarn.

• Proceedings of the KIEE Conference
• /
• 2003.11c
• /
• pp.588-591
• /
• 2003

This paper presents a new short-term load forecasting system using data mining. Since the electric load has very different pattern according to the day, it definitely gives rise to the forecasting error if only one forecasting model is used. Thus, to resolve this problem, the fuzzy model-based classifier and predictor are proposed for the forecasting of the hourly electric load. The proposed classifier is the multi-input and multi-output fuzzy system of which the consequent part is composed of the Bayesian classifier. The proposed classifier attempts to categorize the input electric load into Monday, Tuesday$\sim$Friday, Saturday, and Sunday electric load, Then, we construct the Takagi-Sugeno (T-S) fuzzy model-based predictor for each class. The parameter identification problem is converted into the generalized eigenvalue problem (GEVP) by formulating the linear matrix inequalities (LMIs). Finally, to show the feasibility of the proposed method, this paper provides the short-term load forecasting example.