• The Journal of the Acoustical Society of Korea
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• v.21 no.5
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• pp.478-484
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• 2002

Linear towed arrays (LTA) have a nonlinear shape due to tow vessel motion, ocean swells and currents. By reasons of nominally linear shape, various towed array shape estimation techniques have been developed since the perturbed shape cause the error in target detection. In this paper,, we propose the beamforming method for the perturbed LTA with simple structure. The proposed method linearizes a nonlinear phase of steering vector with position information measured by two reference sensors. It can be proved using some properties of Markov transition matrix, and iteration number of linearization process is decided by variance of cross phase difference. As a result of computer simulation in the ocean environment, beampattern of the proposed method is almost same with the ideal case in my type of array shape. In the signal-to-noise ratio (SNR) performance simlation, the DOA estimation performance of the proposed beamforming method is evaluated, and the comparison with Bartlett beamformer of the LTA shows that the proposed method can estimate. the spatial characteristic of sources more accuracy.

• Journal of Advanced Marine Engineering and Technology
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• v.41 no.1
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• pp.62-69
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• 2017

This paper presents a methodology for evaluating the performance of wall-climbing robots. In the literature on wall-climbing robots, there is little information on indices and evaluation methods for consistent and exact performance. Because various types of wall-climbing robots can be developed with regard to adherence and locomotion, a general method of measuring their performance regardless of type is needed. Therefore, we propose two major performance indices-the vertical adhering weight and vertical climbing speed-and their stepwise evaluation procedures. To verify the effectiveness of the proposed method, we applied it to a hull-climbing robot that we previously developed. The target robot was evaluated to have a vertical adhering weight of 18.5 kg through a slip measurement procedure and a vertical climbing speed of 41 cm/s with a position control system.

• Journal of Urban Science
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• v.7 no.2
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• pp.53-60
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• 2018

Digital Twin is a technology that creates a photocopy of real-world objects on a computer and analyzes the past and present operational status by fusing the structure, context, and operation of various physical systems with property information, and predicts the future society's countermeasures. In particular, 3D rendering technology (UAS, LiDAR, GNSS, etc.) is a core technology in digital twin. so, the research and application are actively performed in the industry in recent years. However, UAS (Unmanned Aerial System) and LiDAR (Light Detection And Ranging) have to be solved by compensating blind spot which is not reconstructed according to the object shape. In addition, the terrestrial LiDAR can acquire the point cloud of the object more precisely and quickly at a short distance, but a blind spot is generated at the upper part of the object, thereby imposing restrictions on the forward digital twin modeling. The UAS is capable of modeling a specific range of objects with high accuracy by using high resolution images at low altitudes, and has the advantage of generating a high density point group based on SfM (Structure-from-Motion) image analysis technology. However, It is relatively far from the target LiDAR than the terrestrial LiDAR, and it takes time to analyze the image. In particular, it is necessary to reduce the accuracy of the side part and compensate the blind spot. By re-optimizing it after fusion with UAS and Terrestrial LiDAR, the residual error of each modeling method was compensated and the mutual correction result was obtained. The accuracy of fusion-based 3D model is less than 1cm and it is expected to be useful for digital twin construction.

• The Journal of the Korea institute of electronic communication sciences
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• v.8 no.10
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• pp.1485-1490
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• 2013

The demonstration project of the electrical grid for Smart grid is progressed, the smart digital appliances AV technology, Smart home energy management technology charging the management function of complex energy for the automation management of air conditioning and heating, humidity and air, the health care technology charging the design of housing for the elderly and disabled and the measurement of individual bio information, and the Smart home security technology dealing with the biometric security and motion sensors, etc. have been studied. The power monitoring terminal which uses a variety of wired and wireless networks and protocol is the target additionally to be considered in addition to the security vulnerabilities that was occurred in the existing terminal. In this research paper, the author analyzes the cryptographic techniques corresponding to the smart meter occurred by the problems that are exposed on the outside which are vulnerable to physical attacks, and intends to propose the design of the security systems for the Smart meter terminal being able to maximize the efficiency of the terminal.

• International conference on construction engineering and project management
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• 2024.07a
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• pp.1311-1311
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• 2024

Recent advances in artificial intelligence technology have led to active research aimed at systematically managing the productivity and environmental impact of major management targets such as heavy equipment at construction sites. However, challenges arise due to phenomena like partial occlusions, resulting from the dynamic working environment of construction sites (e.g., equipment overlapping, obstruction by structures), which impose practical constraints on precisely monitoring heavy equipment. To address these challenges, this study aims to enhance automated multi-object tracking (MOT) in scenarios involving long-term occlusions across consecutive frames for heavy construction equipment. To achieve this, two methodologies are employed to address long-term occlusions at construction sites: (i) tracking-by-detection and (ii) video inpainting with generative adversarial networks (GANs). Firstly, this study proposes integrating FairMOT with a tracking-by-detection algorithm like ByteTrack or SMILEtrack, demonstrating the robustness of re-identification (Re-ID) in occlusion scenarios. This method maintains previously assigned IDs when heavy equipment is temporarily obscured and then reappears, analyzing location, appearance, or motion characteristics across consecutive frames. Secondly, adopting video inpainting with GAN algorithms such as ProPainter is proposed, demonstrating robustness in removing objects other than the target object (e.g., excavator) during the video preprocessing and filling removed areas using information from surrounding pixels or other frames. This approach addresses long-term occlusion issues by focusing on a single object rather than multiple objects. Through these proposed approaches, improvements in the efficiency and accuracy of detection, tracking, and activity recognition for multiple heavy equipment are expected, mitigating MOT challenges caused by occlusions in dynamic construction site environments. Consequently, these approaches are anticipated to play a significant role in systematically managing heavy equipment productivity, environmental impact, and worker safety through the development of advanced construction and management systems.

• 한국ITS학회:학술대회논문집
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• v.2007 no.10
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• pp.225-229
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• 2007

Recently, wireless sensor networks are deployed in various applications range from simple environment monitoring systems to complex systems, which generate large amount of information, like motion monitoring, military, and telematics systems. Although wireless sensor network nodes are operated with low-power 8bit processor to execute simple tasks like environment monitoring, the nodes in these complex systems have to execute more difficult tasks. Generally, MAC protocols for wireless sensor networks attempt to reduce the energy consumption using duty cycling mechanism which means the nodes periodically sleep and wake. However, in the duty cycling mechanism. a node should wait until the target node wakes and the sleep latency increases as the number of hops increases. This sleep latency can be serious problem in complex and sensitive systems which require high speed data transfer like military, wing of airplane, and telematics. In this paper, we propose a solution for reducing transmission latency through distributed duty cycling (DDC) in wireless sensor networks. The proposed algorithm is evaluated with real-deployment experiments using CC2420DBK and the experiment results show that the DDC algorithm reduces the transmission latency significantly and reduces also the energy consumption.

• The KIPS Transactions:PartB
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• v.17B no.5
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• pp.355-362
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• 2010

Face tracking is to estimate the motion of a non-rigid face together with a rigid head in 3D, and plays important roles in higher levels such as face/facial expression/emotion recognition. In this paper, we propose an AAM-based face tracking algorithm. AAM has been widely used to segment and track deformable objects, but there are still many difficulties. Particularly, it often tends to diverge or converge into local minima when a target object is self-occluded, partially or completely occluded. To address this problem, we utilize the scale invariant feature transform (SIFT). SIFT is an effective method for self and partial occlusion because it is able to find correspondence between feature points under partial loss. And it enables an AAM to continue to track without re-initialization in complete occlusions thanks to the good performance of global matching. We also register and use the SIFT features extracted from multi-view face images during tracking to effectively track a face across large pose changes. Our proposed algorithm is validated by comparing other algorithms under the above 3 kinds of occlusions.

• Journal of the Korean GEO-environmental Society
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• v.21 no.1
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• pp.5-12
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• 2020

Vibration propagated from seismic sources has damping according to distance and amplification and reduction characteristic in different regions according to topography and geological structure. The vibration propagated from the seismic source to the bedrock is largely affected by the damping according to the separation distance, which can be simply estimated through the damping equation. However, it is important to grasp geological information by location because vibration estimation transmitted to the surface are affected by the natural period of the soil located above the bedrock. Geotechnical investigation data are needed to estimate the seismic intensity based on geological information. If there is no Vs profile, the standard penetration tests are mainly used to determine the soil parameters. The Integrated DB Center of National Geotechnical Information manages the geotechnical survey data performed on the domestic ground, and there is the standard penetration test information of 400,000 holes. In this study, the possibility of quantitation the amplification coefficient for each region was examined to calculated the physical interactive seismic intensity based on geotechnical information. At this time, the shear wave column diagram was generated from the SPT-N value and ground response analysis was performed in the target area. The site coefficients for each zone and the seismic intensity distribution for the seismic motion present a significant difference according to the analysis method and the regional setting.

• Journal of the Institute of Electronics Engineers of Korea SP
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• v.44 no.1
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• pp.26-39
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• 2007

In recent years, rate control is an important technique in real time video communication applications using H.264/AVC. Many existing rate control algorithms employ the quadratic rate-distortion model, which is determine the target bits for each P frame. In this paper, a new rate control algorithm for transmission of H.264/AVC video bit stream through CBR(Constant Bit Rate) channel is proposed. The proposed algorithm predicts an adaptive QP(Quantization Parameter) for improving video distortion, due to high motion and abruptly scene change, which target bit rate and MAD(Mean of Absolute Difference) for current frame considering image complexity variance between previous and current frames. Additionally, it uses frame skip technique to maintain bit stream within a manageable range and protect buffer from overflow or underflow. Experimental results show that the proposed method gives a quality improvement of about 0.5dB when compared to previous rate control algorithm. Also our proposed algorithm encodes the video sequences with less frame skipping compared to the existing rate control for H.264/AVC.

• KIPS Transactions on Software and Data Engineering
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• v.7 no.3
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• pp.107-112
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• 2018

In this paper, optical flow based keypoint detection and tracking technique is proposed for the collaboration between flying drone with vision system and ground robots. There are many challenging problems in target detection research using moving vision system, so we combined the improved FAST algorithm and Lucas-Kanade method for adopting the better techniques in each feature detection and optical flow motion tracking, which results in 40% higher in processing speed than previous works. Also, proposed image binarization method which is appropriate for the given marker helped to improve the marker detection accuracy. We also studied how to optimize the embedded system which is operating complex computations for intelligent functions in a very limited resources while maintaining the drone's present weight and moving speed. In a future works, we are aiming to develop collaborating smarter robots by using the techniques of learning and recognizing targets even in a complex background.