• Journal of Communications and Networks
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• 제17권3호
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• pp.286-295
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• 2015

Avionic databuses fulfill a critical function in the connection and communication of aircraft components and functions such as flight-control, navigation, and monitoring. Ethernet-based avionic databuses have become the mainstream for large aircraft owning to their advantages of full-duplex communication with high bandwidth, low latency, low packet-loss, and low cost. As a new generation aviation network communication standard, avionics full-duplex switched ethernet (AFDX) adopted concepts from the telecom standard, asynchronous transfer mode (ATM). In this technology, the switches are the key devices influencing the overall performance. This paper reviews the avionic databus with emphasis on the switch architecture classifications. Based on a comparison, analysis, and discussion of the different switch architectures, we propose a new avionic switch design based on a time-division switch fabric for high flexibility and scalability. This also merges the design concept of space-partition switch fabric to achieve reliability and predictability. The new switch architecture, called space partitioned shared memory switch (SPSMS), isolates the memory space for each output port. This can reduce the competition for resources and avoid conflicts, decrease the packet forwarding latency through the switch, and reduce the packet loss rate. A simulation of the architecture with optimized network engineering tools (OPNET) confirms the efficiency and significant performance improvement over a classic shared memory switch, in terms of overall packet latency, queuing delay, and queue size.

• 한국통신학회논문지
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• 제31권6A호
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• pp.556-562
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• 2006

본 논문에서는 OFDM 기반 이동 셀룰러 시스템에서 브로드캐스트 패킷 데이터 전송을 위한 매크로 다양성 부호화 기법을 제안한다. 제안한 기법은 동일한 데이터를 전송하는 셀들을 둘 이상의 셀 그룹으로 나누고, 각 셀 그룹이 송신 다양성 부호의 서로 다른 가지를 전송하는 것이다. 또한, 부호화된 패킷을 하나 이상의 부분 블록으로 나누고 각 부분 블록마다 셀 그룹이 전송해야 할 가지를 바꿈으로써 부분 블록마다 송신 심볼이 겪는 채널 특성을 다르게 한다. 따라서, 제안한 방법은 각 심볼이 겪는 송신 다양성과 채널 부호화 다양성을 증가시켜서 동일한 송신 전력으로 셀 경계 품질을 향상시키고 서비스 제공 영역을 넓힌다.

• Journal of Communications and Networks
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• 제17권2호
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• pp.133-144
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• 2015

In this paper, we introduce a system and a set of algorithms for disseminating popular content to a large group of wireless clients spread over a wide area. This area is partitioned into multiple cells and there is a base station in each cell which is able to broadcast to the clients within its radio coverage. Dissemination of information in the proposed system is hybrid in nature: Each base station broadcasts a fraction of information in the form of random linear combinations of data blocks. Then the clients cooperate by exchanging packets to obtain their desired messages while they are moving arbitrarily over the area. In this paper, fundamental trade-offs between the average information delivery completion time at the clients and different parameters of the system such as bandwidth usage by the base stations, average energy consumption by the clients and the popularity of the spread information are studied. Moreover different heuristic algorithms are proposed to control and maintain a balance over these trade-offs. Also, the more complicated case of multiple sessions where each client is interested in an arbitrary subset of sessions is considered and two variants of the basic dissemination algorithm are proposed. The performance of all the proposed algorithms is evaluated via extensive numerical experiments.

• 국제학술발표논문집
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• The 8th International Conference on Construction Engineering and Project Management
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• pp.505-509
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• 2020

Twitter is a useful medium to grasp various damage situations that have occurred in society. However, it is a laborious task to spot damage-related topics according to time in the environment where information is constantly produced. This paper proposes a methodology of constructing a knowledge structure by combining the BERT-based classifier and the community detection techniques to discover the topics underlain in the damage information. The methodology consists of two steps. In the first step, the tweets are classified into the classes that are related to human damage, infrastructure damage, and industrial activity damage by a BERT-based transfer learning approach. In the second step, networks of the words that appear in the damage-related tweets are constructed based on the co-occurrence matrix. The derived networks are partitioned by maximizing the modularity to reveal the hidden topics. Five keywords with high values of degree centrality are selected to interpret the topics. The proposed methodology is validated with the Hurricane Harvey test data.

• International Journal of Computer Science & Network Security
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• 제24권7호
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• pp.143-147
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• 2024

Image noise classification is a classical problem in the field of image processing, machine learning, deep learning and computer vision. In this paper, image noise classification is performed using deep learning. Keras deep learning library of TensorFlow is used for this purpose. 6900 images images are selected from the Kaggle database for the classification purpose. Dataset for labeled noisy images of multiple type was generated with the help of Matlab from a dataset of non-noisy images. Labeled dataset comprised of Salt & Pepper, Gaussian and Sinusoidal noise. Different training and tests sets were partitioned to train and test the model for image classification. In deep neural networks CNN (Convolutional Neural Network) is used due to its in-depth and hidden patterns and features learning in the images to be classified. This deep learning of features and patterns in images make CNN outperform the other classical methods in many classification problems.

• 한국통신학회논문지
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• 제14권6호
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• pp.675-685
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• 1989

상호접송망은 병렬처리 시스템에서 매우 중요한 부분이다. 최근 다단상호 접속망에 대한 연구가 많이 행해지고 있다. 본 논문에서는 회선스위칭 다단상호접속망의 시뮬레이션 방법을 확장하여 분할된 ADM/IADM 접속망의 성능 평가를 하였다. 시뮬레이션 데이터에 의하여, 적용된 분할 방법에 의한 접속망 성능과 접속망에서 사용된 저지처리방식에 의한 접속망 성능 간의 관계를 보였다. 분석 결과, hold 방식을 사용하는 IADM 접속망이 RST 면에서 가장 나은 접속망 동작을 보이는 것으로 나타났다.

• 대한전자공학회:학술대회논문집
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• 대한전자공학회 2004년도 ICEIC The International Conference on Electronics Informations and Communications
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• pp.57-60
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• 2004

Next generation wireless network is evolving toward IP-based network that can various provide multimedia services. A challenge in wireless mobile Internet is support of quality of service over wireless access networks. DiffServ architecture is proposed for evolving wireless mobile Internet. In this paper we propose an algorithm for optimal buffer partitioning which requires the minimal channel capacity to satisfy the QoS requirements of input traffic. We used a partitioned buffer with size B to serve a layered traffic at each DiffServ router. We consider a traffic model with a single source generates traffic having J $(J\geq2)$ quality of service (QoS) classes. QoS in this case is described by loss probability $\varepsilon_j$. for QoS class j. Traffic is admitted or rejected based on the buffer occupancy and its service class. Traffic is generated by heterogeneous Markov-modulated fluid source (MMFS).

• 전자공학회논문지CI
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• 제49권2호
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• pp.96-102
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• 2012

영상 분류를 위한 다단계 특성벡터 기반의 분류기 모델(Partitioned Feature-based Classification Model with Expertise Table: PFC-ET)의 성능을 더욱 향상시킨 진보된 형태의 분류기 통합모델 (Classifier Integration Model: CIM)이 본 논문에서 제안되었다. CIM은 PFC-ET과 같이 주어진 데이터에서 추출된 전체의 특징벡터를 연결하여 이용하지 않고, 같은 성질의 특징 벡터들끼리 모아서, 각각의 국지적 학습기를 통하여 분류에 이용한다. PFC-ET에서 분류판단 확률행렬에 의한 오류를 최소화하기위해 국지적 분류기로 사용되는 군집화 알고리즘의 멤버 비율을 사용하여 최종적인 분류의 정확도를 높이는 방안을 제안한다. 제안된 CIM의 성능을 검증하기 위하여, Caltech 데이터에 대한 일반적인 영상 분류와 6 클래스 위성 영상 분류 문제에 대한 실험을 진행하였다. 제안된 CIM은 기존의 PFC 와 PFC-ET 모델과 비교한 실험에서 분류 정확도와 후처리 문제의 복잡성 면에서 향상된 성능을 보여주었다.

• 한국정보과학회논문지:정보통신
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• 제32권4호
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• pp.525-534
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• 2005

본 논문은 무선 센서 네트워크에 있어서 궤도 기반 매취메이킹 서비스를 위한 질의 이탈 및 이의 방지에 관한 것이다. 이러한 문제는 정보 구독 궤도를 따라 전파되는 질의가 정보 발간 궤도와 기하학적으로는 겹침에도 불구하고 정보를 획득하지 못할 때 발생한다 이에 따라 질의를 재 제출하거나 새로운 구독 궤도를 시작함으로 인한 시간 지연이 초래되어 최악에는, 궤도내의 루핑이나 네트워크 전체로의 메시지 범람을 야기한다. 이 문제를 정형적으로 다루고 그 해결책을 제시한다. 먼저, 노드들이 존재하는 영역을 논리적으로 작은 그리드들로 분할하고, 그리드 기반 멀티캐스트 다음-흡 선택 알고리즘을 제안한다. 제안 알고리즘은 궤도 설정을 직선형태로 유지하도록 시도함은 물론 수신 노드들의 분포 및 틈새 없는 그리드 단위의 멀티캐스트를 고려한다 이러한 알고리즘에 의거하여 정보 발간 및 구독을 시행하는 경우 질의 이탈이 궁극적으로 방지됨을 증명한다. 제안 알고리즘이 탐욕적 송출과 같은 비 그리드 기반 알고리즘과 GAE와 같은 고정 크기의 그리드 접근법 보다 이웃 노드들의 전력을 더 적게 소모함을 알 수 있다.

• Journal of Electrical Engineering and Technology
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• 제12권6호
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• pp.2388-2398
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• 2017

In this study, we propose a robust face recognition system to pose variations based on automatic pose estimation. Radial basis function neural network is applied as one of the functional components of the overall face recognition system. The proposed system consists of preprocessing and recognition modules to provide a solution to pose variation and high-dimensional pattern recognition problems. In the preprocessing part, principal component analysis (PCA) and 2-dimensional 2-directional PCA ($(2D)^2$ PCA) are applied. These functional modules are useful in reducing dimensionality of the feature space. The proposed RBFNNs architecture consists of three functional modules such as condition, conclusion and inference phase realized in terms of fuzzy "if-then" rules. In the condition phase of fuzzy rules, the input space is partitioned with the use of fuzzy clustering realized by the Fuzzy C-Means (FCM) algorithm. In conclusion phase of rules, the connections (weights) are realized through four types of polynomials such as constant, linear, quadratic and modified quadratic. The coefficients of the RBFNNs model are obtained by fuzzy inference method constituting the inference phase of fuzzy rules. The essential design parameters (such as the number of nodes, and fuzzification coefficient) of the networks are optimized with the aid of Particle Swarm Optimization (PSO). Experimental results completed on standard face database -Honda/UCSD, Cambridge Head pose, and IC&CI databases demonstrate the effectiveness and efficiency of face recognition system compared with other studies.