• 전력전자학회:학술대회논문집
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• 전력전자학회 2012년도 전력전자학술대회 논문집
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• pp.203-204
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• 2012

This paper presents the method to design the inductor and capacitor value considering the ripple component that may be generated by three operating states of the Quasi Z-source inverter at the impedance network. Based on the analysis of each operation mode, the equations of the capacitor voltage and inductor current are derived. In order to simplify the design processing, design equations of the impedance network are derived where the capacitor voltage and inductor current are lineared. The validity of the design method is verified with the simulation result using PSIM and experimental result using 32-bit DSP.

• 대한기계학회논문집A
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• 제26권10호
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• pp.2142-2149
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• 2002

Contacting with ground in the post-card area size only, tire supports entire automobile weight. As well, it characterizes most of automobile running performance. Among the design parameters, the carcass contour becomes a key design factor. This paper deals with the time-effective optimal design of tire crown contour in order to improve the tire wear performance by employing a back-propagation neural network model.

• 정보처리학회논문지C
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• 제11C권1호
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• pp.123-134
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• 2004

동기 망과 전송망에서의 동기클럭 성능은 망의 안정성 화보와 데이터 전송 보장 측면에서 중요한 요소이다. 그러므로 망을 설계할 때 동기망과 전송망의 동기클럭 성능을 분석하기 위하여 다양한 파라메타를 적용할 수 있고, 그리고 최상상태에서 최악상태까지 망에서 나타날 수 있는 여러 가지 입력레벨을 적용할 수 있는 시뮬레이터가 필요하다. 따라서 본 논문에서는 동기망과 전송망에서의 동기클럭 특성을 분석할 수 있는 SNCA와 TNCA를 개발하였고, 또한 개발된 시뮬레이터를 활용하여 다양한 원더생성, 노드 수, 클럭 상태 등의 입력조건에 따른 NEl, NE2, NE3 등 전송망과 DOTS1과 DOTS2 등 동기 망에서의 동기 클럭 특성과 최대 노드수 결과를 얻었다.

• 한국통신학회논문지
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• 제33권10B호
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• pp.904-910
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• 2008

본 논문에서는 군의 요구사항을 고려하여 군 통신망의 서비스와 관련 파라미터들을 연구하고, u-Army 실험망을 시뮬레이션을 통해 성능 측정을 하였다. 이를 바탕으로 전 군에 VoIP를 적용할 수 있는 VoIP 설계 가이드라인을 제시하였다. 측정은 패킷과 콜 시그널링 관점에서 지연과 손실에 관하여 몇 가지 시나리오에 대해 측정하였다. 첫 번째는 독립적인 네트워크 서비스에 따라 만족하는 요구사항을 측정하였다. 두 번째는 통합 서비스에서 지연과 손실에 관하여 백그라운드 트래픽을 증가시키면서 그 결과를 측정하였다. 마지막으로 시뮬레이션에 근거하여 IP PBX 장비의 설치 위치에 따라 네트워크의 구성을 분류하여 설계 가이드라인을 제시하였으며, 현재 군의 고정된 링크의 상황에 맞추어 VoIP 단말기의 수를 정할 수 있도록 계산 방법을 제시하였다.

• 한국정보통신학회:학술대회논문집
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• 한국해양정보통신학회 2002년도 추계종합학술대회
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• pp.382-385
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• 2002

본 연구에서는 LVQ의 성능 개선을 위하여 SOM을 전처리로 이용하여 LVQ 네트워크를 설계한다 제안한 설계 방법에선 SOM을 이용하여 LVQ 네트워크의 출력 뉴런 수와, reference vector의 초기값을 결정한다. SOM을 전처리로 이용한 LVQ를 Fisher의 Iris 데이터에 분류에 적용한 결과 기존의 LVQ보다 분류 성능이 뛰어났다.

• KSII Transactions on Internet and Information Systems (TIIS)
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• 제11권3호
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• pp.1373-1392
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• 2017

WiFi Direct (WD) is a state of the art technology for a Device-to-Device (D2D) communication in 802.11 networks. The performance of the WD system can be significantly affected by some key factors such as the type of application, specifications of MAC and PHY layer parameters, and surrounding environment etc. It is, therefore, important to develop a system model that takes these factors into account. In this paper, we focus on investigating the design parameters of the PHY layer that could maximize the efficiency of the WD 802.11 system. For this purpose, a basic theoretical model is formulated for a WD network under a 2x2 Multiple In Multiple Out (MIMO) TGn channel B model. The design level parameters such as input symbol rate and antenna spacing, as well as the effects of the environment, are thoroughly examined in terms of path gain, spectral density, outage probability and Packet Error Rate (PER). Thereafter, a novel adaptive algorithm is proposed to choose optimal parameters in accordance with the Quality of Experience (QoE) for a targeted application. The simulation results show that the proposed method outperforms the standard method thereby achieving an optimal performance in an adaptive manner.

• 조명전기설비학회논문지
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• 제27권4호
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• pp.48-53
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• 2013

In general, the LLC resonant topology consists of three stages as; square wave generator, resonant network, and rectifier network. LLC resonant converter has the time slowly varying parameters. However, the power LEDs as the load of LLC converter can be regarded as fast time varying parameters. In this paper, the mathematical model of half-bridge resonant converter including with the power LEDs is introduced for the current controller design model. Using this controller design model, the parameter adaptive output feedback controller will be designed to control the power LEDs current. In order to show the validities of the proposed model, the parameter adaptive output feedback controller, the experimental investigation will be presented.

• 한국정밀공학회:학술대회논문집
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• 한국정밀공학회 2000년도 추계학술대회 논문집
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• pp.699-702
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• 2000

The automation and control of robotic welding process is a very complex assignment because the system is affected by a number of variables which are very difficult to determine or predict in practice. Not only the optimization of the robotic welding process is considered from the point of view of the time and the cost of manufacturing. as well as quality of the weldment. the human factors of the production and many other factors must taken into consideration. hi order to determine the optimal parameters of robotic welding process, it is necessary to build a computer model representing all parameters influencing the welding process as well as the mutual dependence between them. This paper presents an approach to modeling the robotic welding process in which all parameters affecting the welding process are included using a neural network. A detailed analysis of the simulation results has been carried out to evaluate the proposed neural network model.

• Design & Manufacturing
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• 제16권3호
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• pp.1-8
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• 2022

In this study, an artificial neural network(ANN) was constructed to establish the relationship between process condition prameters and the qualities of the injection-molded product in the injection molding process. Six process parmeters were set as input parameter for ANN: melt temperature, mold temperature, injection speed, packing pressure, packing time, and cooling time. As output parameters, the mass, nominal diameter, and height of the injection-molded product were set. Two learning structures were applied to the ANN. The single-task learning, in which all output parameters are learned in correlation with each other, and the multi-task learning structure in which each output parameters is individually learned according to the characteristics, were constructed. As a result of constructing an artificial neural network with two learning structures and evaluating the prediction performance, it was confirmed that the predicted value of the ANN to which the multi-task learning structure was applied had a low RMSE compared with the single-task learning structure. In addition, when comparing the quality specifications of injection molded products with the prediction values of the ANN, it was confirmed that the ANN of the multi-task learning structure satisfies the quality specifications for all of the mass, diameter, and height.

• 한국정밀공학회지
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• 제20권11호
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• pp.64-70
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• 2003

This paper suggests a systematic methodology to predict chip forms using the experimental design technique and the neural network. Significant factors determined with ANOVA analysis are used as input variables of the neural network back-propagation algorithm. It has been shown that cutting conditions and cutting tool shapes have distinct effects on the chip forms, so chip breaking. Cutting tools are represented using the Z-map method, which differs from existing methods using some chip breaker parameters. After training the neural network with selected input variables, chip forms are predicted and compared with original chip forms obtained from experiments under same input conditions, showing that chip forms are same at all conditions. To verify the suggested model, one tool not used in training the model is chosen and input to the model. Under various cutting conditions, predicted chip forms agree well with those obtained from cutting experiments. The suggested method could reduce the cost and time significantly in designing cutting tools as well as replacing the“trial-and-error”design method.