• Steel and Composite Structures
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• 제42권1호
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• pp.23-32
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• 2022

In this paper, a nonlinear numerical method to solve the large deflection problem is introduced. And the non-dimensional load-deflection behavior of functionally graded carbon nanotube-reinforced composite (FG-CNTRC) plates is parametrically investigated. The large deflection problem is formulated according to the von Kármán nonlinear theory and the (1,1,0)^* hierarchical model, and it is approximated by 2-D natural element method (NEM). The shear locking phenomenon is suppressed by the selectively reduced integration method. The nonlinear matrix equations are solved by combining the incremental loading scheme and the Newton-Raphson iteration method. The proposed method is validated from the benchmark experiments, where the propose method shows an excellent agreement with the reference methods. The nonlinear behavior of FG-CNTRC plates is evaluated in terms of the non-dimensional load-deflection curve, and it is parametrically investigated with respect to the existence/non-existence and gradient pattern of CNTs, the width-to-thickness and aspect ratios of plates and the type of boundary conditions. The non-dimensional central deflection is significantly reduced when CNTs and added, and it decreases with the volume fraction of CNTs. But, it shows a uniform increase in proportion to the width-to-thickness and aspect ratios. Both the gradient pattern of CNTs and the type of boundary conditions do also show the remarkable effects.

• 한국자동차공학회논문집
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• 제10권1호
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• pp.1-8
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• 2002

Metal surface temperatures around the combustion chamber in a gasoline engine directly affect thermal durability and performance of the engine. Metal surface temperatures are influenced by many cooling factors such as drilled water passage, deflector, combustion chamber wall thickness, pillar, and coolant flow pattern. The object of this study is to learn how the coolant passages and coolant flow pattern in an engine influence to the engine metal surface temperature at engine full load and speed. From the test result, it is suggested a plan to reinforce the engine stiffness and to reduce the thermal stress simultaneously. Also, approaches are introduced to reduce the thermal load on the engine by adjusting the discharging direction from the water pump and by optimizing the water transfer holes in the cylinder head gasket. These methods and the optimized engine cooling system, which were suggested in this paper, were adapted for an engine in progress to eliminate the exhaust valve seat wear.

• 한국지능시스템학회논문지
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• 제15권7호
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• pp.805-812
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• 2005

본 논문은 스마트 홈과 같이 다양한 센서 및 제어 네트워크가 밀집되어 있는 유비쿼터스 환경 하에서 복잡한 인터페이스의 사용에 대한 사용자의 인지 부담(cognitive load)을 줄이고, 개인화된(personalized) 서비스를 자율적으로 제공하기 위한 새로운 사용자 행동 패턴 선호도 학습기법을 제안하였다. 이를 위해 지식 발견(knowledge discovery)을 위한 평생 학습(life-long learning)의 관점에서 퍼지귀납(fuzzy inductive) 학습 방법론을 제안하며, 이것은 수치 데이터로부터 입력 공간에 대한 효율적인 퍼지 분할(fuzzy partition)을 얻어내고 일관성 있는(consistent) 퍼지 상관 롤(fuzzy association rule)을 얻어내도록 한다.

• 한국기후변화학회지
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• 제5권4호
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• pp.291-300
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• 2014

In this study, we investigated the activity data and basic data of the surface of the water within the ship to be operated by lakes and rivers inland. In this study previously, there was no survey activity data of Ferry and Cruise ship in Korea. In order to ensure the basic data and development of measures to reduce efficiently by local governments, these studies should be performed. Therefore, in the present study was survey the activity data such as cruising time and engine load factor and the specifications of the vessels. As a result, by analyzing the cruising pattern according to the area and the purpose of the cruise, to calculate the emissions of greenhouse gases.

• 한국정보과학회:학술대회논문집
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• 한국정보과학회 2008년도 한국컴퓨터종합학술대회논문집 Vol.35 No.1 (C)
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• pp.26-30
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• 2008

Currently an automated methodology based on data mining techniques is presented for the prediction of customer load patterns in long duration load profiles. The proposed our approach consists of three stages: (i) data pre-processing: noise or outlier is removed and the continuous attribute-valued features are transformed to discrete values, (ii) cluster analysis: k-means clustering is used to create load pattern classes and the representative load profiles for each class and (iii) classification: we evaluated several supervised learning methods in order to select a suitable prediction method. According to the proposed methodology, power load measured from AMR (automatic meter reading) system, as well as customer indexes, were used as inputs for clustering. The output of clustering was the classification of representative load profiles (or classes). In order to evaluate the result of forecasting load patterns, the several classification methods were applied on a set of high voltage customers of the Korea power system and derived class labels from clustering and other features are used as input to produce classifiers. Lastly, the result of our experiments was presented.

• 전기학회논문지
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• 제66권3호
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• pp.587-592
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• 2017

In the three-phase four-wire low-voltage power distribution equipment, single-phase and three-phase load have been used mainly mixed. Also linear and nonlinear loads have been used together in the same conditions. In a three-phase four-wire distribution line, the current distribution of three-phase linear load is almost constant in each phase during driving or stopping, but the single-phase load is different from each other for each phase in accordance with the operation and stop. So that the voltage unbalance is caused by the current difference of each phase. In the three-phase four-wire distribution system, non-linear load is used with linear load. The presence of single-phase nonlinear loads can produce an increase in harmonic currents in three-phase and neutral line. It can also cause voltage unbalance. In the present study, we analyzed for the voltage unbalance fluctuations by the operation pattern of the single and three-phase linear and non-linear load in three-phase four-wire low voltage distribution system.

• 대한전기학회:학술대회논문집
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• 대한전기학회 2003년도 학술회의 논문집 정보 및 제어부문 B
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• pp.588-591
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• 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.

• KSII Transactions on Internet and Information Systems (TIIS)
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• 제8권9호
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• pp.2982-3003
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• 2014

With the explosive deployment of the wireless communications technology, the increased QoS requirement has sparked keen interest in network planning and optimization. As the major players in wireless network optimization, the BS's resource utilization and mobile user's QoS can be improved a lot by the load-balancing technology. In this paper, we propose a load-balancing strategy that uses Coordinated Multiple Points (CoMP) technology among the Base Stations (BS) to effectively extend network coverage and increase edge users signal quality. To use universally, different patterns of load-balancing based on CoMP are modeled and discussed. We define two QoS metrics to be guaranteed during CoMP load balancing: call blocking rate and efficient throughput. The closed-form expressions for these two QoS metrics are derived. The load-balancing capacity and QoS performances with different CoMP patterns are evaluated and analyzed in low-dense and high-dense traffic system. The numerical results present the reasonable CoMP load balancing pattern choice with guaranteed QoS in each system.

• Design & Manufacturing
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• 제16권3호
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• pp.28-33
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• 2022

The recent increasing application rate of advanced high-strength steel(AHSS) for automotive parts makes it difficult to ensure the durability of forming tools. Significant load and friction generated during the piercing process of AHSS increase the wear rate and the damage degree to dies. These harsh process conditions also yield product failures, such as dimensional inconsistency of pierced holes and insufficient quality of hole's sheared edge. This study analyzed the effect of punch wear on the sheared surface of pierced parts and the forming load during the piercing process. Wear-shaped punches showed approximately 20% higher piercing load than normal-shaped punches, and the rollover ratio of the sheared surface also increased. It is considered that the dull edge of wear-shaped punches does not penetrate directly into the material but shears after tensioning it in a piercing direction. In addition, wear-shaped punches experienced compressive load even after completing the piercing process during the down-stroke and tensile load during the up-stroke. This load variation is related to the smaller diameter piercing holes produced by wear-shaped punches compared to normal-shaped punches. Thus, we demonstrated the predictability of the wear level of dies through a comparative analysis of the piercing load pattern.

• 한국정밀공학회지
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• 제29권2호
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• pp.229-238
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• 2012

This study is to compare muscle strength between isotonic exercise and isotonic & isokinetic exercise. Participants are 12-man and 10-woman whom they are healthy without medical history in shoulder, elbow and lumbar joint. We performed experiment total 4-weeks that exercise 3-days a week each exercise pattern. We measured shoulder, elbow and lumbar joint torque with BIODEX and circumference of muscle in upper arms once a week. The result showed that isotonic & isokinetic exercise pattern significantly more improved joint torque in shoulder, elbow, lumbar than isotonic exercise pattern. Because that isotonic & isokinetic exercise pattern supplied muscle strengthen and caused muscle contraction. This exercise pattern can be used new exercise training method for major athlete and normal people. Also this pattern can be used rehabilitation treatment.