• 디지털융복합연구
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• 제6권1호
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• pp.123-135
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• 2008

In this study it is aimed to find out the relationship between the effective factors on learning motivation of the digital textbook. To carry on such exploration the learning motivation theory of Keller has been taken as the theoretical background. This is an experimental research with the data collected from 310 students who took the digital textbook class in the computer-mediated environment. It is compared and verified whether the factors causing learning motivation of the ARCS model embedded in the offline class influence on learner's motivation and achievement. With the outcomes, it has been tried to find out some practical suggestions for the achievement of the digital textbook. The results of the data show that the learning motivation of the digital textbook is significantly influence on the learning achievement.

• 한국경영과학회지
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• 제31권2호
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• pp.129-140
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• 2006

Quantity Flexibility contract coordinates individually motivated supplier and buyer to the systemwide optimal outcome by effectively allocating the costs of market demand uncertainty. The main feature of the contract is to couple the buyer's commitment to purchase no less than a certain percentage below the forecast with the supplier's guarantee to deliver up to a certain percentage above. In this paper we refine the previous models by adding some realistic features including the upper and lower limits of the purchase. We also incorporate purchase and canceling costs in a cost function to reflect the real world contracting process more accurately. To obtain the solution of the model, we derive a condition for extreme points using the Leibniz's rule and construct an algorithm for finding the optimal solution of the model. Several examples illustrating the algorithm show that the approach is valid and efficient.

• International Journal of Railway
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• 제8권2호
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• pp.42-45
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• 2015

Alkali-silica reaction (ASR) is a chemical reaction in concrete that alkalis in cement react with reactive silica in aggregate in the presence of water. When ASR takes place, it produces gels that absorb water and expand. Swelling of ASR gels can damage concrete and cause cracking and volume expansion in concrete structure. In this paper, mechanical consequences of ASR on concrete are simulated by a finite element (FE) analysis. An FE model of concrete is built. The evolution of concrete mechanical properties subjected to ASR is achieved by FE analyses. The constitutive model of concrete is attained via the FE analysis. A case study is used to demonstrate the proposed method. The simulated results using the proposed model are in good agreement with the observations of concrete with ASR reported in the literature. The results can be used for a basic research to enhance durability of concrete slab tracks and concrete railway sleepers.

• 한국콘크리트학회:학술대회논문집
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• 한국콘크리트학회 2006년도 추계 학술발표회 논문집
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• pp.153-156
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• 2006

This paper presents an analytical results on limits of debonding failure for RC beams strengthened with near-surface mounted(NSM) CFRP strips. An analytical model was derived to predict the failure mode and the maximum load. An analytical model has two assumptions. The first is that the debonding failure occurs at the epoxy-concrete interfaces. The second is that the debonding failure occurs at the end of the FRP reinforcement due to concentration of shear stress. Results of the comparison of existing test data and analytical model data have predicted the failure mode and the maximum load well. Also, this paper proposed limits of debonding failure to prevent the debonding using the strengthening area and the groove depth.

• 한국정보처리학회:학술대회논문집
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• 한국정보처리학회 2018년도 춘계학술발표대회
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• pp.562-565
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• 2018

A wide range of IoT applications use information collected from networks of sensors for monitoring and controlling purposes. However, the frequent appearance of fault data makes it difficult to extract correct information, thereby sending incorrect commands to actuators that can threaten human privacy and safety. For this reason, it is necessary to have a mechanism to detect fault data collected from sensors. In this paper, we present a trend-adaptive multi-scale principal component analysis (Trend-adaptive MS-PCA) model for data fault detection. The proposed model inherits advantages of Discrete Wavelet Transform (DWT) in capturing time-frequency information and advantages of PCA in extracting correlation among sensors' data. Experimental results on a real dataset show the high effectiveness of the proposed model in data fault detection.

• 한국정보처리학회:학술대회논문집
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• 한국정보처리학회 2001년도 춘계학술발표논문집 (상)
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• pp.507-510
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• 2001

HTTP/1.1 standard reduces latencies and overhead from closing and re-establishing connections by supporting persistent connections as a default, which encourage multiple transfers of objects over one connection. HTTP/1.1, however, does not define explicitly connection-closing time but specifies a certain fixed holding time model. This model may induce wasting server's resource when server maintains conn ection with the idle-state client that requests no data for a certain time. This paper proposes the mechanism of a heuristic connection management supported by the client-side under persistent HTTP, in addition to HTTP/1.1's fixed holding time model on server-side. The client exploits the tag information within transferred HTML page so that decides connection-closing time. As a result, the mechanism allows server to use server's resource more efficiently without server's efforts.

• 한국컴퓨터정보학회:학술대회논문집
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• 한국컴퓨터정보학회 2019년도 제60차 하계학술대회논문집 27권2호
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• pp.267-270
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• 2019

Through this research, the rating data of shops were analyzed. The model was designed for discrete multiple classification as to the corresponding data, and the following experiments were initiated to observe the learned machine. By comparing each benchmarks in the experiments, which contains different setting variables for the machine model, the hit ratio was measured which indicates how much it is matched with the expected label. By analyzing those results from each benchmarks, the model was redesigned one time during the research and the effects of each setting variables on this machine were clarified. Furthermore, the research result left the future works, which are related with how the learning could be improved and what should be designed in the further research.

• 한국정보통신학회:학술대회논문집
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• 한국정보통신학회 2021년도 춘계학술대회
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• pp.338-339
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• 2021

본 논문에서는 변환 학습을 기반으로 한 다중 클래스 이미지 장면 분류 방법을 제안한다. 이미지 분류를 위해 대형 이미지 데이터 세트 ImageNet에 대해 사전 학습 한 ResNet (ResNet) 모델을 사용하는 방법이다. CNN 모델의 이미지 분류 방법에 비해 분류 정확도 및 효율성을 크게 향상시킬 수 있다.

• Journal of Electrical Engineering and information Science
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• 제1권1호
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• pp.118-128
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• 1996

In safety critical hard real-time systems, a timing fault may yield catastrophic results. In order to eliminate the timing faults from the fast responsive real-time control systems, it is necessary to schedule a code based on high precision timing analysis. Further, the schedulability enhancement by having multiple processors is of wide spread interest. However, although an instruction level parallel processing is quite effective to improve the schedulability of such a system, none of the real-time applications employ instruction level parallel scheduling techniques because most of the real-time scheduling models have not been designed for fine-grain execution. In this paper, we present a timing constraint model specifying high precision timing constraints, and a practical approach for constructing static schedules for a VLIW execution model. The new model and analysis can guarantee timing accuracy to within a single machine clock cycle.

• 산업경영시스템학회지
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• 제35권1호
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• pp.66-78
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• 2012

This paper proposes a computation model of the quantity supplied to optimize inventory costs for the fast fashion. The model is based on a forecasting, a store and production capacity, an assortment planning and quick response model for fast fashion retailers, respectively. It is critical to develop a standardized business process and mathematical model to respond market trends and customer requirements in the fast fashion industry. Thus, we define a product supply model that consists of forecasting, assortment plan, store capacity plan based on the visual merchandising, and production capacity plan considering quick response of the fast fashion retailers. For the forecasting, the decomposition method and multiple regression model are applied. In order to optimize inventory costs. A heuristic algorithm for the quantity supplied is designed based on the assortment plan, store capacity plan and production capacity plan. It is shown that the heuristic algorithm produces a feasible solution which outperforms the average inventory cost of a global fast fashion company.