• Proceedings of the KIEE Conference
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• 1993.07a
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• pp.492-494
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• 1993

CMAC (Cerebeller Model Articulation Controller) is kind of Neural Networks that imitate the human cerebellum. For storage and retrieval of learned data, the input of CMAC is used as a key to determine the memory location. he learned information is distributively stored in physical memory. The learning of CMAC is very fast and converged well, therefore, it effects the application of Pattern Recognition. Through the our experiment of Pattern Recognition, we will prove that CMAC is very suitable for On-line real time processing and incremental learning of Neural Networks.

• Tunnel and Underground Space
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• v.4 no.2
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• pp.102-118
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• 1994

Thermomechanical analysis is conducted on the radioactive repository in deep rock mass considering the in-situ stress, excavation and thermal loading of a radioactive waste. Thermomechanical properties of a discontinuous rock mass are estimated by a theoretical method so called sequential analysis. Using the estimated properties as input for finite element analysis, the influence on temperature distribution and thermal stress is analyzed within the scope of 2-dimensional steady state and transient heat transfer and coupled thermal elastic plastic behaviour. Granitic rock mass is taken for this analysis. The analysis is done for two different rock mass conditions, i.e. continuous-homogeneous and highly jointed conditions, for the purpose of comparison. In the case of steady state, the extent of disturbed zone around the storage tunnel due to the heat production of the spent-fuel canister varies depending on the thermomechanical properties of the rock mass. In the case of transient analyses, the response of the jointed rock mass to the thermal loading after radioactive waste disposal varies significantly with time, resulting in dramatic changes in the both size and location of disturbed zone.

• Proceedings of the Korea Information Processing Society Conference
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• 2019.05a
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• pp.398-400
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• 2019

Faced with the increasing demand for image recognition on mobile devices, how to run convolutional neural network (CNN) models on mobile devices with limited computing power and limited storage resources encourages people to study efficient model design. In recent years, many effective architectures have been proposed, such as mobilenet_v1, mobilenet_v2 and PeleeNet. However, in the process of feature selection, all these models neglect some information of shallow features, which reduces the capture of shallow feature location and semantics. In this study, we propose an effective framework based on Feature Pyramid Networks to improve the recognition accuracy of deep and shallow images while guaranteeing the recognition speed of PeleeNet structured images. Compared with PeleeNet, the accuracy of structure recognition on CIFA-10 data set increased by 4.0%.

• Journal of the Korea Institute of Military Science and Technology
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• v.25 no.1
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• pp.108-116
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• 2022

Supply in military operations has a significant impact on overall combat capability and efficiency. Therefore, modernization of military logistics is underway to ensure rapid and accurate distribution. And, effective warehouse management is paramount. This paper proposes a new product allocation model that uses a genetic algorithm. The model considers order frequency and mass of products because the military equipment is usually heavier than available products. A computer simulation shows that products are assigned to optimal locations and reduce the consumed energy for forklifts by more than 25 % with similar travel time. Also, we show the superiority of genetic algorithm by comparing them with other algorithms.

• Proceedings of the Korea Information Processing Society Conference
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• 2009.04a
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• pp.310-312
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• 2009

오늘날 기업은 전국,전세계적으로 storage location을 가지고 있으며, 전세계적으로 가장 많이 사용되는 물류관리시스템으로 SAP R/3을 들수있다. 기업은 비용절감을 위해 통합시스템 구축을 하려한다. 통합시스템 구축시 가장 우선되는 부분인 비용절감, 안정성, 보안성 등을 고려한다. 또한 RFID의 도입은 물류관리시스템에서 입고, 출고의 정확성 및 적재위치로의 관리가 용이하며 선입선출의 편리성을 도모할 수 있다. 따라서 본 논문에서는 RFID활용한 물류관리 middleware 설계방법과 RFC(Remote Function Call)을 활용한 웹과 interface방법 및 UML을활용한 framework 설계하고, 마지막으로 향후 연구과제를 제시하였다.

• Journal of the Korean Society for Marine Environment & Energy
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• v.13 no.3
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• pp.187-197
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• 2010

Carbon dioxide Capture and Storage(CCS) is regarded as one of the most promising options to response climate change. CCS is a three-stage process consisting of the capture of carbon dioxide($CO_2$), the transport of $CO_2$ to a storage location, and the long term isolation of $CO_2$ from the atmosphere for the purpose of carbon emission mitigation. Up to now, process design for this $CO_2$ marine geological storage has been carried out mainly on pure $CO_2$. Unfortunately the $CO_2$ mixture captured from the power plants and steel making plants contains many impurities such as $N_2$, $O_2$, Ar, $H_2O$, $SO_2$, $H_2S$. A small amount of impurities can change the thermodynamic properties and then significantly affect the compression, purification, transport and injection processes. In order to design a reliable $CO_2$ marine geological storage system, it is necessary to analyze the impact of these impurities on the whole CCS process at initial design stage. The purpose of the present paper is to compare and analyse the relevant physical property models including BWRS, PR, PRBM, RKS and SRK equations of state, and NRTL-RK model which are crucial numerical process simulation tools. To evaluate the predictive accuracy of the equation of the state for $CO_2-SO_2$ mixture, we compared numerical calculation results with reference experimental data. In addition, optimum binary parameter to consider the interaction of $CO_2$ and $SO_2$ molecules was suggested based on the mean absolute percent error. In conclusion, we suggest the most reliable physical property model with optimized binary parameter in designing the $CO_2-SO_2$ mixture marine geological storage process.

• Food Science of Animal Resources
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• v.40 no.4
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• pp.497-511
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• 2020

This study aimed at comparing the storage stability, fatty acids profile, volatile flavor compounds and eating quality of Hanwoo beef longissimus thoracis (LT) muscles between two marbling morphological groups (fineness and coarseness). The 1⁺ grade Hanwoo LT muscles were measured for marbling fleck morphology at the 13^th thoracic vertebrae location by using computerized image analysis. Results reveal that both marbling groups had similar proximate composition (protein, fat, moisture and collagen), color and technological quality traits (p>0.05). However, the coarse marbling group presented greater C18:2n6 and polyunsaturated fatty acids contents compared to the fine marbling group (p<0.05). Furthermore, the fine marbling group presented lower volatile basic nitrogen (VBN) and 2-thiobarbituric acid reactive substance (TBARS) contents compared to the coarse marbling group after 14 d storage (p<0.05). Also, higher amounts of C18:2n6 oxidation-derived volatile compounds such as hexanal and 3-ethyl-2-methyl-1,3-hexadiene, were found in the coarse marbling group. In term of sensory aspects, the finely-marbled group received higher scores of flavor and taste compared to the coarse marbling group (p<0.05). Overall, the marbling flecks morphology partially showed its effects on the storage stability, fatty acids profile and eating quality of the 1⁺ grade Hanwoo beef LT muscle.

• KSCE Journal of Civil and Environmental Engineering Research
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• v.3 no.1
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• pp.1-12
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• 1983

The wave and hydrologic climate at a beach location are everchanging and coastal engineers have always been interested in the deformation of the natural beach caused by wave action over short or long interval of time. The drift of sand on a beach particulary manifests itself when blocked construction of seawalls, jetties, breakerwaters and groins etc.${\cdots}$ For this reason, the understanding and evaluation of littoral drift has been especially important to the coastal engineers. The resulting of the sand drift movement, such as the type of beach profile, width of beach, storage volume of the littoral sand over the profile are rapid everchange. We have studied the geological changes due to the littoral drift on a beach with field investigation and model tests in laboratory. But, it is impossible to make quantative correct analysis because of the factors are everchange and complicate. And then, most of study are incline to qualitative analysis. In this paper, authors studied mainly on the transition of beach profile and sediment storage on the profile using statistical field data as qualitative analytical method. The used theoretical beach transition model by Sonu and Beek have developed to obtain the change of HAEUNDAE beach backed with seawall. Results of this study indicate that the transition model are useful in the analysis of beach profile changement and the littoral drift movement on the beach. Qualitative analysises for HAEUNDAE beach are as follows. 1) Transition sequence of profile has 4 major transition for one cycle. 2) Storage sediment model of beach profile by Sonu and Beek well coincided with HAEUNDAE beach. 3) Seasonal cycle has ill-balanced process for the 5-yr. investigation.

• The Journal of Korean Institute of Communications and Information Sciences
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• v.35 no.9B
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• pp.1350-1359
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• 2010

Recently many researchers have been proved that general RFID system for proximity authentication is vulnerable to various location-based relay attacks such as distance fraud, mafia fraud and terrorist fraud attacks. The distance-bounding protocol is used to prevent the relay attacks by measuring the round trip time of single challenge-response bit. In 2008, Munilla and Peinado proposed an improved distance-bounding protocol applying void-challenge technique based on Hancke-Kuhn's protocol. Compare with Hancke-Kuhn's protocol, Munilla and Peinado's protocol is more secure because the success probability of an adversary has (5/8)n. However, Munilla and Peinado's protocol is inefficient for low-cost passive RFID tags because it requires large storage space and many hash function computations. Thus, this paper proposes a new RFID distance-bounding protocol for low-cost passive RFID tags that can be reduced the storage space and hash function computations. As a result, the proposed distance-bounding protocol not only can provide both storage space efficiency and computational efficiency, but also can provide strong security against the relay attacks because the adversary's success probability can be reduced by $(5/8)^n$.

• Journal of KIISE:Information Networking
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• v.29 no.4
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• pp.412-427
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• 2002

This paper proposes a restoration scheme based on mobility learning and prediction in the presence of the failure of mobility databases in mobile communication systems. In mobile communication systems, mobility databases must maintain the current location information of users to provide a fast connection for them. However, the failure of mobility databases may cause some location information to be lost. As a result, without an explicit restoration procedure, incoming calls to users may be rejected. Therefore, an explicit restoration scheme against the failure of mobility databases is needed to guarantee continuous service availability to users. Introducing mobility learning and prediction into the restoration process allows systems to locate users after a failure of mobility databases. In failure-free operations, the movement patterns of users are learned by a Neuro-Fuzzy Inference System (NFIS). After a failure, an inference process of the NFIS is initiated and the users' future location is predicted. This is used to locate lost users after a failure. This proposal differs from previous approaches using checkpoint because it does not need a backup process nor additional storage space to store checkpoint information. In addition, simulations show that our proposal can reduce the cost needed to restore the location records of lost users after a failure when compared to the checkpointing scheme