• 한국경영과학회지
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• 제36권3호
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• pp.91-105
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• 2011

In this paper, we analyze a logistic system involving a supplier who produces and delivers multiple types of items and a buyer who receives and sells the products to end customers. The buyer controls the inventory level by replenishing each product item up to a given order-up-to-level to cope with stochastic demand of end customers. In response to the buyer's order, the supplier produces or outsources the ordered item and delivers them at the start of each period. For the system described above, a mathematical model for a single type of item was developed from the buyer's perspective. Based on the model, an efficient method to find the cycle length and safety factor which correspond to a local minimum solution is proposed. This single product model was extended to cover a multiple item situation. From the model, algorithms to decide the base cycle length and order interval of each item were proposed. The results of the computational experiment show that the algorithms were able to determine the global optimum solution for all tested cases within a reasonable amount of time.

• Journal of the Korean Data and Information Science Society
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• 제22권4호
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• pp.727-733
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• 2011

주식수익률간의 상관행렬 분석을 통해 유의미한 정보를 추출 활용하는 것은 주식시장을 이해하는데 매우 중요하다. 최근 확률행렬이론을 이용 상관행렬을 분석하는 연구들이 많이 진행되어 왔는데, 본 논문에서는 단일 요인 모형을 확률행렬이론에 적용 한국주식시장에서 주식수익률간의 상관행렬에 관한 유의미한 정보를 추출하였다. 특히 단일 요인을 도입 상관행렬을 분석한 결과가 실제 데이터를 잘 설명함을 관찰하였고, 단일 요인 모형의 유용성을 확인하였다.

• ETRI Journal
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• 제42권5호
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• pp.658-668
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• 2020

In edge computing, most procedures, including data collection, data processing, and service provision, are handled at edge nodes and not in the central cloud. This decreases the processing burden on the central cloud, enabling fast responses to end-device service requests in addition to reducing bandwidth consumption. However, edge nodes have restricted computing, storage, and energy resources to support computation-intensive tasks such as processing deep neural network (DNN) inference. In this study, we analyze the effect of models with single and multiple local exits on DNN inference in an edge-computing environment. Our test results show that a single-exit model performs better with respect to the number of local exited samples, inference accuracy, and inference latency than a multi-exit model at all exit points. These results signify that higher accuracy can be achieved with less computation when a single-exit model is adopted. In edge computing infrastructure, it is therefore more efficient to adopt a DNN model with only one or a few exit points to provide a fast and reliable inference service.

• 대한가정학회지
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• 제30권4호
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• pp.153-165
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• 1992

The objectives of this study were to develop a probabilistic model for both hypotheses testing and mobility prediction. Methodologies being used for the analysis include multivariated analysis for descriptive statistics and logit model for hypotheses testing and prediction. The study used questionaire survey data conducted by Korean Research Institute for Human Settlements (KRIHS) in 1988. There were a total of 1,620 Samples, and both SPSS and Limdep software packages were used for statistical analysis and model testing. The major findings were highlighted as follows; The residential mobility over family life span by the social class were developed with the use of the probability model. Most of households in low class moved downwardly. They had lived the small-owned single detached house in first family life span and moved into the small-rented single detached house in next family life span. Most of households in middle class moved upwardly. They had lived the small-owned apartment in first family life span and moved into the large-owned single detached house in last family life span. Most of households in high class horizontally. They had lived the large-owned single detached house in first family life span and moved into the same one except in last family life span.

• 전력전자학회논문지
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• 제26권3호
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• pp.176-182
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• 2021

This research proposes a high-frequency circuit that can accurately predict the differential mode noise of single-phase inverters at the circuit design stage. Proposed single-phase inverter high frequency circuit in the work is a form in which harmonic impedance components are added to the basic single-phase inverter circuit configuration. For accurate noise prediction, parasitic components present in each part of the differential noise path were extracted. Impedance was extracted using a network analyzer and Q3D in the measurement range of 150 kHz to 30 MHz. A high-frequency circuit model was completed by applying the measured values. Simulations and experiments were conducted to confirm the validity of the high-frequency circuit. As a result, we were able to predict the resonance point of the differential mode voltage extracted as an experimental value with a high-frequency circuit model within an approximately 10% error. Through this outcome, we could verify that differential mode noise can be accurately predicted using the proposed model of the high-frequency circuit without a separate test bench for noise measurement.

• 천문학회보
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• 제44권2호
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• pp.42.3-42.3
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• 2019

We translate Solar Dynamics Observatory/Atmospheric Imaging Assembly (AIA) ultraviolet (UV) multi-channel images into another UV single-channel image using a deep learning algorithm based on conditional generative adversarial networks (cGANs). The base input channel, which has the highest correlation coefficient (CC) between UV channels of AIA, is 193 Å. To complement this channel, we choose two channels, 1600 and 304 Å, which represent upper photosphere and chromosphere, respectively. Input channels for three models are single (193 Å), dual (193+1600 Å), and triple (193+1600+304 Å), respectively. Quantitative comparisons are made for test data sets. Main results from this study are as follows. First, the single model successfully produce other coronal channel images but less successful for chromospheric channel (304 Å) and much less successful for two photospheric channels (1600 and 1700 Å). Second, the dual model shows a noticeable improvement of the CC between the model outputs and Ground truths for 1700 Å. Third, the triple model can generate all other channel images with relatively high CCs larger than 0.89. Our results show a possibility that if three channels from photosphere, chromosphere, and corona are selected, other multi-channel images could be generated by deep learning. We expect that this investigation will be a complementary tool to choose a few UV channels for future solar small and/or deep space missions.

• Journal of Mechanical Science and Technology
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• 제20권11호
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• pp.1891-1897
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• 2006

In this study, a new model to predict the effective elastic constants of composites with spherical fillers is proposed. The original Eshelby model is extended to a finite filler volume fraction without using Mori-Tanaka's mean field approach. When single filler is embedded in the matrix, the effective elastic constants of the composite are computed. The composite is in turn considered as a new matrix, where new single filler is again embedded in the matrix. The predicted results by the present model with a series of embedding procedures are compared with those by Mori-Tanaka, self-consistent, and generalized self-consistent models. It is revealed through parametric studies such as stiffness ratio of the filler to the matrix and filler volume fraction that the present model gives more accurate predictions than Mori-Tanaka model without using the complicated numerical scheme used in self-consistent and generalized self-consistent models.

• 한국정밀공학회지
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• 제12권5호
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• pp.157-165
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• 1995

In this paper the comparison between the neural networks and traditional approaches as nonlinear system identification methods are considered. Two model structures of neural networks are the state space model and the input output model neural networks. The traditional methods are the AutoRegressive eXogeneous Input model and the Nonlinear AutoRegressive eXogeneous Input model. Computer simulation for an analytic dynamic model of a single input single output nonlinear system has been done for all the chosen models. Model validation for the obtained models also has been done with testing inputs of the sinusoidal, ramp and the noise ramp.

• 대한기계학회논문집
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• 제16권9호
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• pp.1605-1614
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• 1992

본 연구에서는 고장력 7075-T73 알루미늄합금에 대하여 변동하중의 기보파형 인 단일과대하중과 고-저(high-low) 블럭하중하의 지연거동에 미치는 과대하중비 %O.L., 기준응력확대계수범위 .DELTA. $K_{b}$ 및 무차원 균열깊이 a/W의 영향을 규명하였 으며, 또한 Wheeler모델의 수정에 의한 예측피로수명을 실험치와 함께 검토하였다.다.

• 한국전자파학회지:전자파기술
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• 제6권3호
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• pp.80-90
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• 1995

마이크로스트립 단일선로, 직각벤드 및 결합선로의 산란행렬을 multipart r$\xi$twork model을 이용하여 1-18GHz 범위에서 계산했다. 단일선로는 평면형 도파관 모텔을 이용하여 해석했다. 직각벤드의 경우는 두개 의 사각형 부분으로 나누어져 각 부분은 단일선로와 같은 방법으로 해석되며, 각 부분의 임피던스 행렬은segmentation 방볍을 이용하여 연결된다. 결합선로 사이의 전자계 결합의 해석에는 Green 함수를 이용하는 기 존의 방법보다 계산시간이 적게 소요되는 새로운 방법이 이용되었다 상기의 세가지 구조에 대한 수치해석 결 과는 SuperCompact의 결과와 잘 일치하며, 이는 상기의 방법이 복잡한 단일 및 결합선로 불연속구조의 해석에 유용하게 사용될 수 있음을 보여준다