• Journal of Korea Multimedia Society
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• v.9 no.2
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• pp.172-188
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• 2006

Sensor localization is one of the fundamental problems in wireless sensor networks. Previous localization algorithms can be classified into two categories, the GGB (Global Geometry-Based) approaches and the LGB (Local Geometry-Based). In the GGB approaches, there are a fixed set of reference nodes of which the coordinates are pre-determined. Other nodes determine their positions based on the distances from the fixed reference nodes. In the LGB approaches, meanwhile, the reference node set is not fixed, but grows up dynamically. Most GGB algorithms assume that the nodes are deployed in a convex shape area. They fail if either nodes are in a concave shape area or there are obstacles that block the communications between nodes. Meanwhile, the LGB approach is vulnerable to the errors in the distance estimations. In this paper, we propose new localization algorithms to cope with those two limits. The key technique employed in our algorithms is to determine, in a fully distributed fashion, if a node is in the line-of-sight from another. Based on the technique, we present two localization algorithms, one for anchor-based, another for anchor-free localization, and compare them with the previous algorithms.

• Journal of KIISE:Software and Applications
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• v.26 no.10
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• pp.1143-1155
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• 1999

셀룰러 방식의 이동통신 시스템에서 전파의 유효신호 도달범위를 예측하기 위해서는 전파전파 모델을 이용한 예측기법이 주로 사용된다. 그러나, 전파과정에서 주변 지형지물에 의해 발생하는 전파손실은 매우 복잡한 비선형적인 특성을 가지며 수식으로는 정확한 표현이 불가능하다. 본 논문에서는 신경회로망의 함수 근사화 능력을 이용하여 전파손실 예측모델을 생성하는 방법을 제안한다. 즉, 전파손실을 송수신 안테나간의 거리, 송신안테나의 특성, 장애물 투과영향, 회절특성, 도로, 수면에 의한 영향 등과 같은 전파환경 변수들의 함수로 가정하고, 신경회로망 학습을 통하여 함수를 근사화한다. 전파환경 변수들이 신경회로망 입력으로 사용되기 위해서는 3차원 지형도와 벡터지도를 이용하여 전파의 반사, 회절, 산란 등의 물리적인 특성이 고려된 특징 추출을 통해 정량적인 수치들을 계산한다. 이와 같이 얻어진 훈련데이타를 이용한 신경회로망 학습을 통해 전파손실 모델을 완성한다. 이 모델을 이용하여 서울 도심 지역의 실제 서비스 환경에 대한 타 모델과의 비교실험결과를 통해 제안하는 모델의 우수성을 보인다.Abstract In cellular mobile communication systems, wave propagation models are used in most cases to predict cell coverage. The amount of propagation loss induced by the obstacles in the propagation path, however, is a highly non-linear function, which cannot be easily represented mathematically. In this paper, we introduce the method of producing propagation loss prediction models by function approximation using neural networks. In this method, we assume the propagation loss is a function of the relevant parameters such as the distance from the base station antenna, the specification of the transmitter antenna, obstacle profile, diffraction effect, road, and water effect. The values of these parameters are produced from the field measurement data, 3D digital terrain maps, and vector maps as its inputs by a feature extraction process, which takes into account the physical characteristics of electromagnetic waves such as reflection, diffraction and scattering. The values produced are used as the input to the neural network, which are then trained to become the propagation loss prediction model. In the experimental study, we obtain a considerable amount of improvement over COST-231 model in the prediction accuracy using this model.

• Journal of the Institute of Convergence Signal Processing
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• v.10 no.3
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• pp.198-206
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• 2009

This paper presents the reduction of the positional uncertainty of an ultrasonic sensor ring with overlapped beam pattern for the efficient obstacle detection of a mobile robot. Basically, it is assumed that a relatively small number of inexpensive low directivity ultrasonic sensors are installed at regular spacings along the side of a circular mobile robot with their beams overlapped. First, for both single and double obstacles, we show that the positional uncertainty inherent to an ultrasonic sensor can be reduced using the overlapped beam pattern, and also quantify the relative improvement in positional uncertainty. Second, given measured distance data from one or two ultrasonic sensors, we devise the geometric method to determine the position of an obstacle with respect to the center of a mobile robot. Third, we examine and compare existing ultrasonic sensor models, including Gaussian distribution, parabolic distribution, uniform distribution, and impulse, and then build the sensor model of overlapped ultrasonic sensors, adequate for obstacle detection in terms of positional uncertainty and computational requirement. Finally, through experiments using our prototype ultrasonic sensor ring, the validity of overlapped beam pattern for reduced positional uncertainty and efficient obstacle detection is demonstrated.

• Journal of the Korea Convergence Society
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• v.10 no.4
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• pp.153-163
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• 2019

The importance and necessity of convergence research to solve complexity and diversity of research problems is more increasing. For successful convergence research, connectivity beyond the boundary and distance between disciplines is a key factor. To understand the current status and characteristics of connectivity among researchers, we investigated the interdisciplinary relationships among 487 researchers' disciplines in a university by using network anaylsis. The results showed that (1) connectivity between similar disciplines were higher than different disciplines, (2) the density and cohesion level of connectivity within the same campuses were higher, and (3) network centrality was concentrated in engineering and medicine. Based on these results, the necessity of overcoming boundaries and distances as obstacles to convergence research and the necessity of diversification of centrality were proposed. While previous studies mainly analyzed the research outcomes, this study is meaningful because it analyzed researchers' connectivity and collaborative structures in the actual convergence research procedures.

• KSII Transactions on Internet and Information Systems (TIIS)
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• v.18 no.5
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• pp.1317-1340
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• 2024

With the rapid development of information technology, people's demands on precise indoor positioning are increasing. Wireless sensor network, as the most commonly used indoor positioning sensor, performs a vital part for precise indoor positioning. However, in indoor positioning, obstacles and other uncontrollable factors make the localization precision not very accurate. Ultra-wide band (UWB) can achieve high precision centimeter-level positioning capability. Inertial navigation system (INS), which is a totally independent system of guidance, has high positioning accuracy. The combination of UWB and INS can not only decrease the impact of non-line-of-sight (NLOS) on localization, but also solve the accumulated error problem of inertial navigation system. In the paper, a fused UWB and INS positioning method is presented. The UWB data is firstly clustered using the Fuzzy C-means (FCM). And the Z hypothesis testing is proposed to determine whether there is a NLOS distance on a link where a beacon node is located. If there is, then the beacon node is removed, and conversely used to localize the mobile node using Least Squares localization. When the number of remaining beacon nodes is less than three, a robust extended Kalman filter with M-estimation would be utilized for localizing mobile nodes. The UWB is merged with the INS data by using the extended Kalman filter to acquire the final location estimate. Simulation and experimental results indicate that the proposed method has superior localization precision in comparison with the current algorithms.

• Journal of Platform Technology
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• v.11 no.2
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• pp.26-38
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• 2023

This paper is a study on a transport robot capable of autonomously driving to a destination using a QR code in an indoor environment. The transport robot was designed and manufactured by attaching a lidar sensor so that the robot can maintain a certain distance during movement by detecting the distance between the camera for recognizing the QR code and the left and right walls. For the location information of the delivery robot, the QR code image was enlarged with Lanczos resampling interpolation, then binarized with Otsu Algorithm, and detection and analysis were performed using the Zbar library. The QR code recognition experiment was performed while changing the size of the QR code and the traveling speed of the transport robot while the camera position of the transport robot and the height of the QR code were fixed at 192cm. When the QR code size was 9cm × 9cm The recognition rate was 99.7% and almost 100% when the traveling speed of the transport robot was less than about 0.5m/s. Based on the QR code recognition rate, an experiment was conducted on the case where the destination is only going straight and the destination is going straight and turning in the absence of obstacles for autonomous driving to the destination. When the destination was only going straight, it was possible to reach the destination quickly because there was little need for position correction. However, when the destination included a turn, the time to arrive at the destination was relatively delayed due to the need for position correction. As a result of the experiment, it was found that the delivery robot arrived at the destination relatively accurately, although a slight positional error occurred while driving, and the applicability of the QR code-based destination self-driving delivery robot was confirmed.

• Fire Science and Engineering
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• v.33 no.6
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• pp.173-180
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• 2019

Oil tank fires need to be suppressed differently from other oil-related fires, due to the high-temperature flames and hot updraft above the tank, in the former case, that cause the destruction of large amounts of foam. We studied high-capacity foam discharge systems based on the standards of the American Petroleum Institute (API), National Fire Protection Association (NFPA), British Standard European Norm (BS EN), and the laws of Japan. The performance of a high-capacity foam discharge system was measured by conducting real fire experiments with model oil tanks. We concluded that lightweight and easily movable high-capacity foam discharge systems should be urgently introduced in domestic operations. Additionally, the obstacles faced by major tanks, such as long-distance installation of large-diameter fire hoses and narrowing of firefighting spaces, should be resolved depending on the conditions of the site.

• Journal of the Korea Institute of Information and Communication Engineering
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• v.20 no.7
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• pp.1243-1248
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• 2016

This paper investigated the channel link budget for Wireless Avionics Intra-Communication (WAIC) in 4.4GHz. The band 4.2~4.2GHz was allocated for the communication service among aeronautical applications in world radiocommunication conference (WRC). Wireless channels in aircraft was modelled by the combination of path loss, shadowing effect caused by obstacles, and fading caused by multipath signals. In addition, wireless channels in aircraft are categorized into 6 groups according to various locations of transmitter and receiver. We analyzed the channel link budget for the 6 channel groups in terms of maximum transmission distance and outage probability. Our analysis and intensive computer simulation results show that the propagation characteristics of group A, B, and F is superior to group C, D, E, and the propagation of group E is the most vulnerable. Also, these results can be utilized as basic reference for the channel analysis of intra-aircraft or similar environment.

• Journal of the Institute of Electronics Engineers of Korea TC
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• v.43 no.9 s.351
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• pp.60-68
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• 2006

Using the wireless communication among unacquainted vehicles, an intelligent vehicle safety system can be constructed to exchange vehicle safety-related information, such as urgency stop, traffic accident and road obstacles. In the majority of vehicle safety applications, vehicle safety messages are propagated in the form of broadcast. However, this approach causes some effectiveness and performance problems with massive radio collision, multi-hop propagation. This paper presents a priority based relay node selection method for propagating vehicle safety messages of traffic accident protection system. With this method, vehicle safety messages are relayed by a node that locates in proper distance out of the nodes that are included in the radio transmission range. By decreasing the number of duplicated messages, the packet overhead is lessened while the communication performance is raised. The proposed method was proven to be better than other schemes through network simulations.

• Journal of the Korean Institute of Intelligent Systems
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• v.19 no.4
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• pp.470-477
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• 2009

Modular reconfigurable robots with physical docking capability easily adapt to a new environment and many studies are necessary for the modular robots. In this paper, we propose a vision-based fuzzy autonomous docking controller for the modular docking robots. A modular docking robot platform which performs real-time image processing is designed and color-based object recognition method is implemented on the embedded system. The docking robot can navigate to a subgoal near a target robot while avoiding obstacles. Both a fuzzy obstacle avoidance controller and a fuzzy navigation controller for subgoal tracking are designed. We propose an autonomous docking controller using the fuzzy obstacle avoidance and navigation controllers, absolute distance information and direction informations of robots from PSD sensors and a compass sensor. We verify the proposed docking control method by docking experiments of the developed modular robots in the various environments with different distances and directions between robots.