• 전기전자학회논문지
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• 제22권3호
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• pp.558-564
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• 2018

In distributed estimation where each node can collect only partial information on the parameter of interest without communication between nodes and quantize it before transmission to a fusion node which conducts estimation of the parameter, we consider a novel quantization technique employed at local nodes. It should be noted that the performance can be greatly improved if each node can transmit its measurement to one designated node (namely, head node) which can quantize its estimate using the total rate available in the system. For this case, the best strategy at the head node would be simply to partition the parameter space using the generalized Lloyd algorithm, producing the global codewords, one of which is closest to the estimate is transmitted to a fusion node. In this paper, we propose an iterative design algorithm that seeks to efficiently assign the codewords into each of quantization partitions at nodes so as to achieve the performance close to that of the system with the head node. We show through extensive experiments that the proposed algorithm offers a performance improvement in rate-distortion perspective as compared with previous novel techniques.

• 한국진공학회지
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• 제16권4호
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• pp.235-243
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• 2007

지금 국내에서는 토카막 핵융합실험장치, 대전류 중성입자빔 실험장치 및 우주 모의실험실 같은 거대시설의 건설과 운용이 활발하다. 이런 시설의 핵심설비인 대형 진공용기는 중소형 용기에 비해 누설 가능성은 높은 반면 기체누설을 검사하는 것은 까다롭다. 중소형 용기에서 널리 사용되는 헬륨누설검사 방법을 어떻게 효율적으로 이런 대형 용기에 적용할 수 있는가 알아보기 위해, 다양한 가상적인 누설검사 시스템들을 구성하고 압력분포 및 헬륨 분압을 계산하여 주어진 장치조건에서 적절한 검사 시스템을 찾는 방법에 대해 논한다.

• 한국기계가공학회지
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• 제16권5호
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• pp.31-39
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• 2017

Research in the machine tool industry has focused on ICT-based smart machines rather than hardware technologies related to machine tools. Real-time tool-status monitoring is representative of this type of technology and has become important for measuring sensors during cutting processes. In this paper, we studied several research areas and used a round bar to conduct fundamental research into the axial displacement of the main spindle of a tool when it was subjected to a machining load. We were able to use the gap sensor to detect the axial displacement indirectly by using grooves with various shapes on the round bar and sensing the gaps between the grooves. We then determined the optimal groove shape for monitoring the tool state.

• 한국항해항만학회:학술대회논문집
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• 한국항해항만학회 2006년도 International Symposium on GPS/GNSS Vol.1
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• pp.465-469
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• 2006

In recent years there has been considerable interest in the construction of super high-rise buildings. From the prior art, various procedures and devices for surveys during and after the phase of erection of a high-rise building are known. High-rise buildings are subject to strong external tilt effects caused, for instance, by wind pressures, unilateral thermal effects by exposure to sunlight, and unilateral loads. Such effects are a particular challenge in the phase of construction of a high-rise building, in as much as the high-rise building under construction is also subject to tilt effects, and will at least temporarily lose its - as a rule exactly vertical - alignment. Yet construction should progress in such a way that the building is aligned as planned, and particularly so in the vertical, when returning into an un-tilted basic state.It is essential that a straight element be constructed that theoretically, even when moving around its design centre point due to varying loads, would have an exactly vertical alignment when all biasing conditions are neutralised. Because of differential raft settlement, differential concrete shortening, and construction tolerances, this ideal situation will rarely be achieved. This paper describes a procedure developed by the authors using GPS observations combined with a network of precision inclination sensor to provide reliable coordinated points at the top of the worldwide highest-rise building under construction in Dubai.

• Journal of Communications and Networks
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• 제14권5호
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• pp.471-480
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• 2012

Reliable detection of primary user activity increases the opportunity to access temporarily unused bands and prevents harmful interference to the primary system. By extracting a global decision from local sensing results, cooperative sensing achieves high reliability against multipath fading. For the effective combining of sensing results, which is generalized by a likelihood ratio test, the fusion center should learn some parameters, such as the probabilities of primary transmission, false alarm, and detection at the local sensors. During the training period in supervised learning, the on/off log of primary transmission serves as the output label of decision statistics from the local sensor. In this paper, we extend unsupervised learning techniques with an expectation maximization algorithm for cooperative spectrum sensing, which does not require an external primary transmission log. Local sensors report binary hard decisions to the fusion center and adjust their operating points to enhance learning performance. Increasing the number of sensors, the joint-expectation step makes a confident classification on the primary transmission as in the supervised learning. Thereby, the proposed scheme provides accurate parameter estimates and a fast convergence rate even in low signal-to-noise ratio regimes, where the primary signal is dominated by the noise at the local sensors.

• 한국표면공학회지
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• 제50권2호
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• pp.119-124
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• 2017

Due to the high saturation magnetization (~2.4 T), $Fe_{16}N_2$ is interesting for the thin film application such as an actuator, data record storage and sensor etc. In this study, Fe-N thin films were deposited on Si(001) substrate with various power and deposition time by DC magnetron sputtering, in order to get high portion of $Fe_{16}N_2$ phase. Surface morphology, phase formation and magnetic properties were measured. As a result, Saturation magnetization and Remanence magnetization reach to ~2.45 T and 1.41T. But, Coercivity was not enough in this experiments. Its value lower than 100 Oe. Which is very close to theoretical value.

• 한국군사과학기술학회지
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• 제17권1호
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• pp.96-107
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• 2014

Tracking the tactical object is a fundamental affair in network-equipped modern warfare. Geodetic coordinate system based on longitude, latitude, and height is suitable to represent the location of tactical objects considering multi platform data fusion. The motion of tactical object described as a dynamic model requires an appropriate filtering to overcome the system and measurement noise in acquiring information from multiple sensors. This paper introduces the filter suitable for multi-sensor data fusion and tactical object tracking, particularly the unscented transform(UT) and its detail. The UT in Unscented Kalman Filter(UKF) uses a few samples to estimate nonlinear-propagated statistic parameters, and UT has better performance and complexity than the conventional linearization method. We show the effects of UT-based filtering via simulation considering practical tactical object tracking scenario.

• 대한교통학회지
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• 제19권6호
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• pp.171-182
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• 2001

본 연구는 지점검지체계와 구간검지체계와의 자료합성을 통하여 도심 간선도로 및 지방도로 구간별 효과척도를 산정할 뿐만 아니라 유고검지 및 통행패턴 예측, 네트워크 기종점에 대한 최적/최단 경로를 탐색하는데 기초가 되는 구간 통행시간 추정을 수행한다. 개개 수집원의 자료합성을 위해 퍼지이론과 인공신경 망의 합성모형인 FALEM(Fuzzy Adaptive Learning Estimator for travel time from Multi-information sources)을 개발, 개발된 모형 FALEM에 의해 개개구간의 통행시간을 산출하고 동일시간, 동일구간에서 조사된 실측데이터와의 오차율 비교를 통해 추정된 통행시간을 검증하였다. 테스트 환경은 개발모형에 의해 추정된 구간 통행시간의 적용성을 고려하여 실시간 운영하에서 수행되었다.

• International Journal of Internet, Broadcasting and Communication
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• 제11권1호
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• pp.27-38
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• 2019

Sensors collect information for Internet of Things (IoT)-based services. However, indoor construction sites have a poor communication environment and many interfering elements that make it difficult to collect sensor information. In this study, a network was constructed between a Bluetooth Low Energy (BLE)-based IoT device based on a serverless IoT framework and a router. This experimental environment was applied to large- and small-scale indoor construction sites. Experiments were performed to test the communication performance of BLE-based IoT devices and routers at indoor construction sites. An analysis of the received signal strength indication (RSSI) graph patterns collected from the communication between the BLE-based IoT devices and routers for different testbed site situation revealed areas with good communication performance and poor communication performance due to interfering factors. The results confirmed that structural components of the building as well as the materials, equipment, and temporary facilities used in indoor construction interfere with the communication performance. Construction project managers will require improved technical knowledge of IoT, such as optimizing the router placement and matching communication between the router and workers, to improve the communication performance for large-scale indoor construction.

• International journal of advanced smart convergence
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• 제11권2호
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• pp.7-12
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• 2022

Safety and security are the topmost priority in every environment. With the aid of Artificial Intelligence (AI), many objects are becoming more intelligent, conscious, and curious of their surroundings. The recent scientific breakthroughs in autonomous vehicular designs and development; powered by AI, network of sensors and the rapid increase of Internet of Things (IoTs) could be utilized in maintaining safety and security in our environments. AI based on deep learning architectures and models, such as Deep Neural Networks (DNNs), is being applied worldwide in the automotive design fields like computer vision, natural language processing, sensor fusion, object recognition and autonomous driving projects. These features are well known for their identification, detective and tracking abilities. With the embedment of sensors, cameras, GPS, RADAR, LIDAR, and on-board computers in many of these autonomous vehicles being developed, these vehicles can properly map their positions and proximity to everything around them. In this paper, we explored in detail several ways in which these enormous features embedded in these autonomous vehicles, such as the network of sensors fusion, computer vision and natural image processing, natural language processing, and activity aware capabilities of these automobiles, could be tapped and utilized in safeguarding our lives and environment.