• Annual Conference of KIPS
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• 2008.05a
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• pp.1080-1083
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• 2008

유비쿼터스 사회에는 도서관, 커피숍과 같은 공공장소와 자동차, 전철, 비행기등과 같은 대중교통에도 인터넷에 접근할 수 있게 될 것이다. 또한 모든 통신은 끊임없는 인터넷이 지원되어야 하고, 세션이 유지되어야 하며, 이동 중에 통신이 끊어지지 않고, 라우팅이 효율적으로 이루어져야 한다. 이러한 요구를 반영할 수 있는 네트워크 이동성 기술은 이동 IPv6이 가지고 있는 근본적이고, 비효율적인 삼각 라우팅 문제와 중첩된 환경에서 삼각라우팅 문제가 반복되는 핀볼 라우팅 문제를 가지고 있다. 본 논문은 중첩환경의 라우팅 문제를 조사하고, 해결하기 위해 이미 제안된 내용들을 분석하고, 효율성과 안전성을 만족할 수 있는 프로토콜을 제안한다.

• ETRI Journal
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• v.46 no.2
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• pp.175-183
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• 2024

Recently, polar code has attracted the attention of many scholars and has been developed as a code technology in coded-cooperative communication. We propose a polar code scheme based on Plotkin structure and quasi-uniform punching (PC-QUP). Then we apply the PC-QUP to coded-cooperative scenario and built to a new coded-cooperative scheme, which is called PCC-QUP scheme. The coded-cooperative scheme based on polar code is studied on the aspects of codeword construction and performance optimization. Further, we apply the proposed schemes to space-time block coding (STBC) to explore the performance of the scheme. Monte Carlo simulation results show that the proposed cooperative PCC-QUP-STBC scheme can obtain a lower bit error ratio (BER) than its corresponding noncooperative scheme.

• International journal of advanced smart convergence
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• v.13 no.2
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• pp.80-87
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• 2024

This paper focuses on improving accuracy in constrained computing settings by employing the ReLU (Rectified Linear Unit) activation function. The research conducted involves modifying parameters of the ReLU function and comparing performance in terms of accuracy and computational time. This paper specifically focuses on optimizing ReLU in the context of a Multilayer Perceptron (MLP) by determining the ideal values for features such as the dimensions of the linear layers and the learning rate (Ir). In order to optimize performance, the paper experiments with adjusting parameters like the size dimensions of linear layers and Ir values to induce the best performance outcomes. The experimental results show that using ReLU alone yielded the highest accuracy of 96.7% when the dimension sizes were 30 - 10 and the Ir value was 1. When combining ReLU with the Adam optimizer, the optimal model configuration had dimension sizes of 60 - 40 - 10, and an Ir value of 0.001, which resulted in the highest accuracy of 97.07%.

• International journal of advanced smart convergence
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• v.13 no.1
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• pp.1-11
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• 2024

Cognitive small cell networks, consisting of macro-cells and small cells, are foreseen as a promising candidate solution to address 5G spectrum scarcity. Recently, many technological issues (such as spectrum sensing, spectrum sharing) related to cognitive small cell networks have been studied, but the common control channel (CCC) establishment problem has been ignored. CCC is an indispensable medium for control message exchange that could have a huge significant on transmitter-receiver handshake, channel access negotiation, topology change, and routing information updates, etc. Therefore, establishing CCC in cognitive small cell networks is a challenging problem. In this paper, we propose a potential game theory-based approach for CCC establishment in cognitive radio networks. We design a utility function and demonstrate that it is an exact potential game with a pure Nash equilibrium. To maintain the common control channel list (CCL), we develop a CCC update algorithm. The simulation results demonstrate that the proposed approach has good convergence. On the other hand, it exhibits good delay and overhead of all networks.

• Annual Conference of KIPS
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• 2007.05a
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• pp.1276-1278
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• 2007

무선 네트워크 기술의 발전과 이동성 지원에 대한 사용자의 요구가 증대됨에 따라 모바일 IPv6와 이를 확장한 NEMO (NEtwork Mobility) Basic Support 프로토콜이 등장하였다. 이동네트워크들이 중첩되어 구성될 경우 NBS (NEMO Basic Support) 프로토콜을 사용하는 네트워크에서는 패킷이 네트워크를 구성하는 이동라우터(MR, Mobile Router)의 홈에이전트(HA, Home Agent)를 모두 거치면서 중첩 터널링이 수행되는 핀볼라우팅 문제가 발생한다. 본 논문에서는 이러한 문제점을 해결하기 위해 중첩된 이동네트워크에서 새로운 라우팅 헤더를 사용한 경로최적화 기법을 제안한다. 제안하는 기법은 새로운 IPv6 라우팅 헤더 DH (Destination-information Header)를 정의하고 이를 라우팅 헤더 타입 2를 대신하여 사용함으로써 중첩된 이동네트워크에서의 경로최적화를 구현한다. 이 기법은 기존 기법에 비하여 최적화된 경로로 통신하여 최소 32% 뛰어난 성능향상을 확인할 수 있다.

• The Journal of Korean Institute of Electromagnetic Engineering and Science
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• v.29 no.5
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• pp.353-358
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• 2018

We herein analyze the service traffic characteristics and spectrum of the 5G mobile communication and suggest the effective 5G network deployment method for 5G mobile communication services. The data rates of the 5G mobile communication are from several kbps (voice and IoT) up to 1 Gbps (hologram, among others). The 5G mobile communication services show the diverse cell coverage environments owing to the use of diverse service data rates and multiple spectrum bands. To effectively support the 5G mobile communication services, the network deployment requires the optimization of the service coverages for new service environments and multiple spectrum bands. Considering the 5G spectrum bandwidth debated at present, if the 5G services of 100 Mbps can be supported in the 200 m cell edge using the 3.5 GHz spectrum bands, the 5G services of the 1 Gbps hologram and 500-Mbps 4k UHD can be supported in the cell edges of 50 m and 100 m using the 28 GHz spectrum bands. Therefore, the 5G services can be supported effectively by the 5G network deployment using spectrum portfolio configurations to match the diverse 5G services and multiple bands.

• Journal of Korean Society of Steel Construction
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• v.19 no.6
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• pp.695-702
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• 2007

The Thermal Prestressing Method for continuous composite girder bridges is a new design and construction method developed to induce initial composite stresses in the concrete slab at negative bending regions. Due to the induced initial stresses, prevention of tensile cracks at the concrete slab, reduction of steel girder section, and reduction of reinforcing bars are possible. Thus, the construction efficiency can be improved and the construction can be made more economical. The method for determining the optimum heating region of the thermal prestressing method has not been established although such method is essential for improving the efficiency of the design process. The trial-and-error method used in previous studies is far from efficient, and a more rational method for computing optimal heating region is required. In this study, an efficient method for determining the optimum heating region in using the thermal prestressing method was developed based on the neural network algorithm, which is widely adopted to pattern recognition, optimization, diagnosis, and estimation problems in various fields. Back-propagation algorithm, commonly used as a learning algorithm in neural network problems, was used for the training of the neural network. Through case studies of two-span and three-span continuous composite girder bridges using the developed procedure, the optimal heating regions were obtained.

• Journal of the Korea Academia-Industrial cooperation Society
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• v.19 no.6
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• pp.600-613
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• 2018

The purpose of this research was to introduce a network analysis method for analyzing the recent trend of the flexible solar cell using a scholarly database. Based on the five years from 2013 to 2017, we used centrality analysis of research papers via measurement of degree centrality, closeness centrality, and betweenness centrality. The results of network analysis show that cell has a centrality value above 0.8, which means that cell is connected with 80% of the total keywords, so it is recognized as the center of flexible solar cell research. The analysis results also indicate that perovskite and copper indium gallium diselenide (CuInGaSe2, or CIGS) are the center of the subgroup for cell. We recognize that the result refers to recent new technology called the CIGS/perovskite tandem solar cell. We hope that the network analysis method will be the appropriate and precise tool for technology and research planning via elaboration and optimization.

• Journal of Korean Society of Transportation
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• v.23 no.3 s.81
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• pp.35-47
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• 2005

This paper is to review a literature concerning Bus Transit Route Network Design(BTRNDP), to describe a future study direction for a systematic application for the BTRNDP. Since a bus transit uses a fixed route, schedule, stop, therefore an approach methodology is different from that of auto network design problem. An approach methodology for BTRNDP is classified by 8 categories: manual & guideline, market analysis, system analytic model. heuristic model. hybrid model. experienced-based model. simulation-based model. mathematical optimization model. In most previous BTRNDP, objective function is to minimize user and operator costs, and constraints on the total operator cost, fleet size and service frequency are common to several previous approach. Transit trip assignment mostly use multi-path trip assignment. Since the search for optimal solution from a large search space of BTRNDP made up by all possible solutions, the mixed combinatorial problem are usually NP-hard. Therefore, previous researches for the BTRNDP use a sequential design process, which is composed of several design steps as follows: the generation of a candidate route set, the route analysis and evaluation process, the selection process of a optimal route set Future study will focus on a development of detailed OD trip table based on bus stop, systematic transit route network evaluation model. updated transit trip assignment technique and advanced solution search algorithm for BTRNDP.

• Journal of the Korea Society of Computer and Information
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• v.27 no.12
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• pp.59-68
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• 2022

This paper presents a method for 1:1 verification by comparing the similarity between the given real product image and the drawing image. The proposed method combines two existing CNN-based deep learning models to construct a Siamese Network. After extracting the feature vector of the image through the FC (Fully Connected) Layer of each network and comparing the similarity, if the real product image and the drawing image (front view, left and right side view, top view, etc) are the same product, the similarity is set to 1 for learning and, if it is a different product, the similarity is set to 0. The test (inference) model is a deep learning model that queries the real product image and the drawing image in pairs to determine whether the pair is the same product or not. In the proposed model, through a comparison of the similarity between the real product image and the drawing image, if the similarity is greater than or equal to a threshold value (Threshold: 0.5), it is determined that the product is the same, and if it is less than or equal to, it is determined that the product is a different product. The proposed model showed an accuracy of about 71.8% for a query to a product (positive: positive) with the same drawing as the real product, and an accuracy of about 83.1% for a query to a different product (positive: negative). In the future, we plan to conduct a study to improve the matching accuracy between the real product image and the drawing image by combining the parameter optimization study with the proposed model and adding processes such as data purification.