• KSII Transactions on Internet and Information Systems (TIIS)
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• 제12권2호
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• pp.800-816
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• 2018

In recent years, video surveillance research has been able to recognize various behaviors of pedestrians and analyze the overall situation of objects by combining image analysis technology and deep learning method. Human Activity Recognition (HAR), which is important issue in video surveillance research, is a field to detect abnormal behavior of pedestrians in CCTV environment. In order to recognize human behavior, it is necessary to detect the human in the image and to estimate the pose from the detected human. In this paper, we propose a novel approach for 2D Human Pose Estimation based on object detection using RGB-D information. By adding depth information to the RGB information that has some limitation in detecting object due to lack of topological information, we can improve the detecting accuracy. Subsequently, the rescaled region of the detected object is applied to ConVol.utional Pose Machines (CPM) which is a sequential prediction structure based on ConVol.utional Neural Network. We utilize CPM to generate belief maps to predict the positions of keypoint representing human body parts and to estimate human pose by detecting 14 key body points. From the experimental results, we can prove that the proposed method detects target objects robustly in occlusion. It is also possible to perform 2D human pose estimation by providing an accurately detected region as an input of the CPM. As for the future work, we will estimate the 3D human pose by mapping the 2D coordinate information on the body part onto the 3D space. Consequently, we can provide useful human behavior information in the research of HAR.

• 한국정보통신학회논문지
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• 제6권2호
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• pp.159-168
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• 2002

실시간 객체지향 분산 컴퓨팅은 객체 네트워크 형태에서 분산된 컴퓨터 시스템 구조와 관련 된 실시간 분산 컴퓨팅의 한가지 형태이다. 최근에 실시간 응용분야에 적합한 기존의 객체지향 시스템 구조를 확장한 몇 가지 의 구조가 제안되었다. 실시간 시뮬레이션 프로그램의 하나인 시간 및 메시지 트리거 객체지향 프로그램밍이 분산된 시간 트리거 시뮬레이션으로 설계될 수 있으며, 일반적이고 보편적인 설계 타입으로서 사용되고, 하나 의 실시간 시뮬레이션 패러다임으로 제안하였다. 실시간 객체지향 프로그램밍은 안전을 중요시하게 여기는 응용분야에 적용할 수 있으며, 실시간 운영체제 시스템 커널로서 객체지향 프로그램밍 언어인 비쥬얼 C++언어로 작성되었다. 응용 시스템에서 실시간 서비스를 보장하기 위한 설계자들의 노력을 현저하게 줄일 수 있는 장점을 가지고 있다.

• 한국인터넷방송통신학회논문지
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• 제10권2호
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• pp.1-6
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• 2010

근거리 무선 통신시스템은 사무실과 가정의 응용으로 빠르게 확장하고 있다. 무선 네트워크의 개발은 더 높은 data rate의 요구를 만족하도록 수행되었다. 이것으로 높은 주파수에서 동작하는 통신시스템 개발의 필요성이 강조된다. 따라서 근거리 무선 통신 네트워크는 테라헤르츠 주파수 쪽으로 옮겨갈 것으로 기대된다. 실내의 벽과 바닥, 천장에 의해 발생하는 전파 환경 분석은 3차원 광선방출기법을 이용하였다. 또한 테라헤르츠 주파수에서의 rough한 건물 벽면의 특성을 파악하기 위해 광학적으로 두꺼운 smooth한 건물 재질의 반사 모델로부터 접근하여 나타내었다. 전파환경 시뮬레이션 결과평균 수신 전력이 참고문헌의 결과와 유사한 결과를 얻을 수 있었다. 또한, 실내 공간의 크기가 $6m(L){\times}5m(W){\times}2.5m(H)$에서 콘크리트 벽의 경우 RMS 지연시간은 9.11 ns로 계산되었다.

• 전자공학회논문지CI
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• 제44권3호
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• pp.68-73
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• 2007

최근 무선센서 네트워크는 센서 영역 안에 수많은 센서 노드로 구성되어 있으며, 각각의 센서들은 강제적인 에너지 구속조건을 가지고 있으므로 효율적인 에너지 관리는 중요하다. WSN 응용 시스템에서 FEC(Forward error correction)는 데이터 전송의 에너지 효율성과 데이터 신뢰성을 증가시킨다. LDPC 코드는 FEC 코드중 하나로 코드워드의 길이가 커지면 다른 FEC 코드 보다 많은 부호화 작업을 필요로 하지만, 샤논의 용량 한계에 접근되어 있으며, 전송에너지의 감소와 데이터 신뢰도를 증가시키는데 사용되어진다. 본 논문에서는 WSN(Wireless Sensor Network)에서의 에너지 효율성 증가와 부호화의 복잡도를 줄이기 위하여 LDPC(Low-density parity-check) 코드의 패리티 체크 행렬의 생성에 Linear-Congruence 방법을 적용하였다. 결과적으로 본 논문에서 제안된 알고리즘은 부호화 에너지 효율성과 데이터의 신뢰도를 증가시켰다.

• 생물정신의학
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• 제22권1호
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• pp.20-27
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• 2015

Objectives It is increasingly thought that the human cerebellum plays an important role in emotion and cognition. Although recent evidence suggests that the cerebellum may also be implicated in fear learning, only a limited number of studies have investigated the cerebellar abnormalities in panic disorder. The aim of this study was to evaluate the cerebellar gray matter deficits and their clinical correlations among patients with panic disorder. Methods Using a voxel-based morphometry approach with a high-resolution spatially unbiased infratentorial template, regional cerebellar gray matter density was compared between 23 patients with panic disorder and 33 healthy individuals. Results The gray matter density in the right posterior-superior (lobule Crus I) and left posterior-inferior (lobules Crus II, VIIb, VIIIa) cerebellum was significantly reduced in the panic disorder group compared to healthy individuals (p < 0.05, false discovery rate corrected, extent threshold = 100 voxels). Additionally, the gray matter reduction in the left posterior-inferior cerebellum (lobule VIIIa) was significantly associated with greater panic symptom severity (r = -0.55, p = 0.007). Conclusions Our findings suggest that the gray matter deficits in the posterior cerebellum may be involved in the pathogenesis of panic disorder. Further studies are needed to provide a comprehensive understanding of the cerebro-cerebellar network in panic disorder.

• KSII Transactions on Internet and Information Systems (TIIS)
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• 제11권7호
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• pp.3524-3542
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• 2017

In a single-source and multi-relay amplify-forward (AF) cooperative network, the outage probability and the power allocation are two key factors to influence the performance of an entire system. In this paper, an optimized AF relay selection by an exclusive method and near optimal power allocation (NOPA) is proposed for both good outage probability and power efficiency. Given the same power at the source and the relay nodes, a threshold for selecting the relay nodes is deduced and employed to minimize the average outage probability. It mainly excludes the relay nodes with much higher thresholds over the aforementioned threshold and thus the remainders of the relay nodes participate in cooperative forwarding efficiently. So the proposed scheme can improve the utility of the resources in the cooperative multi-relay system, as well as reduce the computational complexity. In addition, based on the proposed scheme, a NOPA is also suggested to approach sub-optimal power efficiency with low complexity. Simulation results show that the proposed scheme obtains about 2.1dB and 5.8dB performance gain at outage probability of $10^{-4}$, when compared with the all-relay-forward (6 participated relays) and the single-relay-forward schemes. Furthermore, it obtains the minimum outage probability among all selective relay schemes with the same number of the relays. Meanwhile, it approaches closely to the optimal exhaustive scheme, thus reduce much complexity. Moreover, the proposed NOPA scheme achieves better outage probability than those of the equal power allocation schemes. Therefore, the proposed scheme can obtain good outage probability, low computational complexity and high power efficiency, which makes it pragmatic efficiently in the single-source and multi-relay AF based cooperative networks.

• 한국정보시스템학회지:정보시스템연구
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• 제26권3호
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• pp.63-90
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• 2017

Purpose This study proposes a novel system trading model using case-based reasoning (CBR) based on absolute similarity threshold. The proposed model is designed to optimize the absolute similarity threshold, feature selection, and instance selection of CBR by using genetic algorithm (GA). With these mechanisms, it enables us to yield higher returns from stock market trading. Design/Methodology/Approach The proposed CBR model uses the absolute similarity threshold varying from 0 to 1, which serves as a criterion for selecting appropriate neighbors in the nearest neighbor (NN) algorithm. Since it determines the nearest neighbors on an absolute basis, it fails to select the appropriate neighbors from time to time. In system trading, it is interpreted as the signal of 'hold'. That is, the system trading model proposed in this study makes trading decisions such as 'buy' or 'sell' only if the model produces a clear signal for stock market prediction. Also, in order to improve the prediction accuracy and the rate of return, the proposed model adopts optimal feature selection and instance selection, which are known to be very effective in enhancing the performance of CBR. To validate the usefulness of the proposed model, we applied it to the index trading of KOSPI200 from 2009 to 2016. Findings Experimental results showed that the proposed model with optimal feature or instance selection could yield higher returns compared to the benchmark as well as the various comparison models (including logistic regression, multiple discriminant analysis, artificial neural network, support vector machine, and traditional CBR). In particular, the proposed model with optimal instance selection showed the best rate of return among all the models. This implies that the application of CBR with the absolute similarity threshold as well as the optimal instance selection may be effective in system trading from the perspective of returns.

• Journal of Communications and Networks
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• 제16권6호
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• pp.627-638
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• 2014

In this paper, we study the joint price and power allocation in spectrum sharing macro-femtocell networks. The proposed game theoretic framework is based on bi-level Stackelberg game where macro base station (MBS) works as a leader and underlaid femto base stations (FBSs) work as followers. MBS has fixed data rate and imposes interference price on FBSs for maintaining its data rate and earns revenue while FBSs jointly adjust their power for maximizing their data rates and utility functions. Since the interference from FBSs to macro user equipment is kept under a given threshold and FBSs compete against each other for power allocation, there is a need to determine a power allocation strategy which converges to Stackelberg equilibrium. We consider two cases for MBS power allocation, i.e., fixed and dynamic power. MBS can adjust its power in case of dynamic power allocation according to its minimum data rate requirement and number of FBSs willing to share the spectrum. For both cases we consider uniform and non-uniform pricing where MBS charges same price to all FBSs for uniform pricing and different price to each FBS for non-uniform pricing according to its induced interference. We obtain unique closed form solution for each case if the co-interference at FBSs is assumed fixed. And an iterative algorithm which converges rapidly is also proposed to take into account the effect of co-tier interference on interference price and power allocation strategy. The results are explained with numerical simulation examples which validate the effectiveness of our proposed solutions.

• 한국지능시스템학회논문지
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• 제15권7호
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• pp.834-839
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• 2005

유비쿼터스 가정환경의 다양한 서비스들을 사용자에게 제공하기 위해서는, 사용자의 의도를 정확히 파악하여 적절한 서비스를 수행하는 지능형 에이전트가 필요하다. 기존에 서비스 선택을 위해 사용되던 명령어 기반 사용자 인터페이스와는 달리, 대화 시스템은 인간과 시스템 사이의 유연하고 풍부한 의사소통에 유용하지만 기존의 사용자나 시스템 주도 대화 시스템은 사용자의 배경지식이나 대화의 문맥에 기인한 다양한 표현을 다루기 어렵다. 본 논문에서는 '상호주도형' 의사소통을 위한 계층적 베이지안 네트워크를 이용하여 사용자와 에이전트 사이에 발생하는 대화의 모호성을 해결한다. 서비스 추론 시 정보가 부족할 경우에는 계층적 베이지안 네트워크를 이용하여 추가로 필요한 정보를 분석하고 사용자로부터 수집한다. 제안하는 방법을 유비쿼터스 가정환경에 적용하고 시뮬레이션 환경을 구축하여 그 유용성을 확인하였다.

• 대한원격탐사학회지
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• 제27권3호
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• pp.379-388
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• 2011

At present, GEOBIA (Geographic Object-based Image Analysis), heir of OBIA (Object-based Image Analysis), is regarded as an important methodology by object-oriented paradigm for remote sensing, dealing with geo-objects related to image segmentation and classification in the different view point of pixel-based processing. This also helps to directly link to GIS applications. Thus, GEOBIA software is on the booming. The main theme of this study is to look into the applicability of geo-spatial processing open source to GEOBIA. However, there is no few fully featured open source for GEOBIA which needs complicated schemes and algorithms, till It was carried out to implement a preliminary system for GEOBIA running an integrated and user-oriented environment. This work was performed by using various open sources such as OTB or PostgreSQL/PostGIS. Some points are different from the widely-used proprietary GEOBIA software. In this system, geo-objects are not file-based ones, but tightly linked with GIS layers in spatial database management system. The mean shift algorithm with parameters associated with spatial similarities or homogeneities is used for image segmentation. For classification process in this work, tree-based model of hierarchical network composing parent and child nodes is implemented by attribute join in the semi-automatic mode, unlike traditional image-based classification. Of course, this integrated GEOBIA system is on the progressing stage, and further works are necessary. It is expected that this approach helps to develop and to extend new applications such as urban mapping or change detection linked to GIS data sets using GEOBIA.