• The Journal of Bigdata
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• v.8 no.1
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• pp.73-82
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• 2023

Marine debris not only affects the survival of marine life, water pollution, and scenery but also has secondary effects on economic loss and human health. While research on underwater and surface debris is actively ongoing, solutions to marine debris in hard-to-reach blind spots are being developed slowly. To address this problem, we utilize drones to detect and track marine debris in blind spots such as tetrapods. The detected debris is then visualized by calculating its location coordinates using the drone's GPS, altitude, and heading values. The proposed method of using drones for detecting marine debris and matching it with longitude and latitude coordinates provides an effective solution to the problem of marine debris in blind spots.

• Korean Journal of Microbiology
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• v.50 no.2
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• pp.114-118
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• 2014

A total of 122 ESBL-producing intestinal bacteria were collected from regional hospitals in the Chungcheong area. Combination disk test (CDT) was performed for antimaicrobial susceptability using cefotaxime and cefotaxime/clavulanate according to Clinical Laboratory Standard Institute (CLSI). Mutiplex PCR using specific primers was performed for a detection of ESBL-genotypes and enterobacterial repetitive intergenic consensus (ERIC)-PCR was carried out for the tracking of molecular epidemiology. In the confirmation test using CDT, 73 out of 76 (96.1%) ESBL-producing Escherichia coli and 43 out of 46 (93.4%) ESBL-producing Klebsiella pnemoniae were positive. In the multiplex PCR, 60.5% of E. coil were positive for CTX-M-2 type gene and 56.5% of K. pneumoniae were positive for VEB -1 type gene. In the ERIC-PCR, E. coil isolates formed 5 clusters and K. pneumoniae isolates were grouped into 4 clusters depending on region. Genotypes of clinical isolates are useful for detection and differentiation of ESBL producing intestinal bacteria. The ERIC-PCR method is thought to be helpful for establishing a regional surveillance system for infection due to its formation of different clusters depending on region.

• Journal of Internet Computing and Services
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• v.25 no.1
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• pp.29-37
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• 2024

In this paper, we propose an efficient image processing system to detect and track the movement of specific objects such as patients. The proposed system extracts the outline area of an object from a binarized difference image by applying a thinning algorithm that enables more precise detection compared to previous algorithms and is advantageous for mixed-mode design. The binarization and thinning steps, which require a lot of computation, are designed based on RTL (Register Transfer Level) and replaced with optimized hardware blocks through logic circuit synthesis. The designed binarization and thinning block was synthesized into a logic circuit using the standard 180n CMOS library and its operation was verified through simulation. To compare software-based performance, performance analysis of binary and thinning operations was also performed by applying sample images with 640 × 360 resolution in a 32-bit FPGA embedded system environment. As a result of verification, it was confirmed that the mixed-mode design can improve the processing speed by 93.8% in the binary and thinning stages compared to the previous software-only processing speed. The proposed mixed-mode system for object recognition is expected to be able to efficiently monitor patient movements even in an edge computing environment where artificial intelligence networks are not applied.

• Journal of the Korean Institute of Illuminating and Electrical Installation Engineers
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• v.21 no.8
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• pp.87-95
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• 2007

In this paper, we analyzed the mr detection and the stability of the object tracking system by an adaptive stereo object hacking using region-based MAD(Mean Absolute Difference) algorithm and the modified PID(Proportional Integral Derivative)-based pan/tilt controller. That is, in the proposed system, the location coordinates of the target object in the right and left images are extracted from the sequential stereo input image by applying a region-based MAD algorithm and the configuration parameter of the stereo camera, and then these values could effectively control to pan/tilt of the stereo camera under the noisy circumstances through the modified PID controller. Accordingly, an adaptive control effect of a moving object can be analyzed through the advanced system with the proposed 3D robot vision, in which the possibility of real-time implementation of the robot vision system is also confirmed.

• Journal of Institute of Control, Robotics and Systems
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• v.12 no.5
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• pp.431-437
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• 2006

In this paper vector code correlation(VCC) method and an algorithm to promote the image-processing performance in building an effective measurement system using cameras are described far automatically berthing and controlling the ship equipped with side-thrusters. In order to realize automatic ship berthing, it is indispensable that the berthing assistant system on the ship should continuously trace a target in the berth to measure the distance to the target and the ship attitude, such that we can make the ship move to the specified location. The considered system is made up of 4 apparatuses compounded from a CCD camera, a camera direction controller, a popular PC with a built-in image processing board and a signal conversion unit connected to parallel port of the PC. The object of this paper is to reduce the image-processing time so that the berthing system is able to ensure the safety schedule against risks during approaching to the berth. It could be achieved by composing the vector code image to utilize the gradient of an approximated plane found with the brightness of pixels forming a certain region in an image and verifying the effectiveness on a commonly used PC. From experimental results, it is clear that the proposed method can be applied to the measurement system for automatic ship berthing and has the image-processing time of fourfold as compared with the typical template matching method.

• The Journal of Korean Institute of Communications and Information Sciences
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• v.31 no.3A
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• pp.274-281
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• 2006

Sensor network applications need synchronized time extremely such as object tracking, consistent state updates, duplicate detection, and temporal order delivery. This paper describes reliable time synchronization protocol (RTSP) for wireless sensor networks. In the proposed method, synchronization error is decreased by creating hierarchical tree with lower depth and reliability is improved by maintaining and updating information of candidate parent nodes. The RTSP reduces recovery time and communication overheads comparing to TPSN when there are topology changes owing to moving of nodes, running out of energy and physical crashes. Simulation results show that RTSP has about 20% better performance than TPSN in synchronization accuracy. And the number of message in the RTSP is $20%{\sim}60%$ lower than that in the TPSN when nodes are failed in the network. In case of different transmission range of nodes, the communication overhead in the RTSP is reduced up to 40% than that in the TPSN at the maximum.

• The Journal of Korean Institute of Electromagnetic Engineering and Science
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• v.27 no.10
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• pp.926-934
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• 2016

In this paper, we designed a compact frequency synthesizer with multi-function for Ka-band seeker. DDS(Direct Digital Synthesizer) is applied to generate various waveform and to cover high-speed frequency sweep. In order to reduce size, waveform generator and frequency up-converter are integrated in one module. Proposed frequency synthesizer provides precise detection and tracking waveform for low and high speed targets. It is observed that fabricated synthesizer performs $0.45{\mu}sec$ frequency switching time and -93.69 dBc/Hz phase noise at offset 1 kHz. The size of the synthesizer is kept within 120 mm width, 120 mm length and 22 mm height.

• The Journal of the Institute of Internet, Broadcasting and Communication
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• v.21 no.5
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• pp.203-208
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• 2021

At the manufacturing site, workers have been operating by inputting materials into the manufacturing process and leaving input records according to the work instructions, but product LOT tracking has been not possible due to many omissions. Recently, it is being carried out as a system to automatically input materials using RFID-Tag. In particular, the initial automatic recognition rate was good at 97 percent by automatically generating input information through RACK (TAG) ID and RACK input time analysis, but the automatic recognition rate continues to decrease due to multi-material RACK, TAG loss, and new product input issues. It is expected that it will contribute to increasing speed and yield (normal product ratio) in the overall production process by improving automatic recognition rate and real-time monitoring through the establishment of artificial intelligent smart factory datasets.

• Proceedings of the Korean Institute of Information and Commucation Sciences Conference
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• 2022.10a
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• pp.250-252
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• 2022

Recently, with the development of IoT technology and AI, unmanned and automated systems are progressing in various fields, and various application technologies are being studied in systems using algorithms such as object detection, recognition, and tracking. In the case of a system operating based on an image, noise removal is performed as a pre-processing process, and precise noise removal is sometimes required depending on the environment of the system. In this paper, we propose a modified central weight filter algorithm using pixel division of local regions to minimize the blurring that tends to occur in the filtering process and to emphasize the details of the resulting image. In the proposed algorithm, when a pixel of a local area is divided into two areas, the center of the dominant area among the divided areas is set as a criterion for the weight filter algorithm. The resulting image is calculated by convolving the transformed center weight with the pixel value inside the filtering mask.

• Journal of Korean Society of Transportation
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• v.23 no.4 s.82
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• pp.17-28
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• 2005

About 91.1% of Railway-Highway Crossings (RHC) in Korea use a Constant Distance Warning System(CDWS), while about 8.9% use a Constant Warning Time System(CWTS). The CDWS does not recognize speed differences of approaching trains and provides only waiting times to vehicles and pedestrians based on the highest speed of approaching trains. Under the CDWS, therefore, low speed trains provide unnecessary waiting times at crossings which often generates complains to vehicle drivers and pedestrians and may cause wrong decisions to pass the crossings. The objective of this research is to improve the safety of the RHC by developing accurate a CWTS. In this research a train speed and location detection system was developed with ultra sonic detectors. Locations of the detectors was decided based on the highest speed and the minimum warning time of Saemaul of 160 km/h. To validate the algorithms of the newly developed systems the lab tests were conducted. The results show that the train detection system provides accurate locations of trains and the maximum error between real speeds of trains and those of the system was 0.07m/s.