• Journal of the Korean Institute of Intelligent Systems
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• v.18 no.5
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• pp.624-631
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• 2008

This paper presents a method for a mobile robot to follow a moving object in real time. The robot follows a target object keeping the facing angle toward the target and the distance to the target to given value. The method consists of two procedures: first, the detection of target position in the robot coordinate system, and the second, the calculation of translational velocity and rotational velocity to follow the object:. To detect the target location, range sensor data is represented in histogram. Based on the real time calculation of the location of the target relative to the robot, translational velocity and rotational velocity to follow the target are calculated. The velocities make the heading angle and the distance to target converge toward the desired ones. The performance of the method is tested through simulation. In the simulation, the target moves with three different trajectories, straight line trajectory, rectangular trajectory, and circular trajectory. As shown in the results, it is inevitable to lose track temporarily of the target when the target suddenly changes its motion direction. Nevertheless, the robot speeds up to catch up and finally succeeds to follow the target as soon as possible even in this case. The proposed method can also be utilized to coordinate the motion of multiple robots to keep their formation as well as to follow a target.

• The Journal of the Acoustical Society of Korea
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• v.36 no.5
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• pp.293-299
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• 2017

Small unmanned platforms maneuvering underwater are the key naval future forces, utilized as the asymmetric power in war. As a method of detecting and identifying such platforms, we introduce a property estimation technique based on an iterative numerical analysis. The property estimation technique can estimate not only the position of a target but also its physical properties. Moreover, it will have a potential in detecting and classifying still target or multiple targets. In this study, we have conducted the property estimation of an small underwater target using the data acquired from the lake experiment. As a result, it shows that the properties of a small platform may be roughly estimated from the in site data even using one channel.

• Parasites, Hosts and Diseases
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• v.56 no.5
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• pp.419-427
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• 2018

This study aimed to develop a new multiplex real-time PCR detection method for 3 species of waterborne protozoan parasites (Cryptosporidium parvum, Giardia lamblia, and Cyclospora cayetanensis) identified as major causes of traveler's diarrhea. Three target genes were specifically and simultaneously detected by the TaqMan probe method for multiple parasitic infection cases, including Cryptosporidium oocyst wall protein for C. parvum, glutamate dehydrogenase for G. lamblia, and internal transcribed spacer 1 for C. cayetanensis. Gene product 21 for bacteriophage T4 was used as an internal control DNA target for monitoring human stool DNA amplification. TaqMan probes were prepared using 4 fluorescent dyes, $FAM^{TM}$, $HEX^{TM}$, $Cy5^{TM}$, and CAL Fluor $Red^{(R)}$ 610 on C. parvum, G. lamblia, C. cayetanensis, and bacteriophage T4, respectively. We developed a novel primer-probe set for each parasite, a primer-probe cocktail (a mixture of primers and probes for the parasites and the internal control) for multiplex real-time PCR analysis, and a protocol for this detection method. Multiplex real-time PCR with the primer-probe cocktail successfully and specifically detected the target genes of C. parvum, G. lamblia, and C. cayetanensis in the mixed spiked human stool sample. The limit of detection for our assay was $2{\times}10$ copies for C. parvum and for C. cayetanensis, while it was $2{\times}10^3$ copies for G. lamblia. We propose that the multiplex real-time PCR detection method developed here is a useful method for simultaneously diagnosing the most common causative protozoa in traveler's diarrhea.

• Korean Journal of Remote Sensing
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• v.34 no.2_2
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• pp.313-326
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• 2018

This paper introduces core techniques on ship detection and tracking based on a compact HF radar platform which is necessary to establish a wide-area surveillance network. Currently, most HF radar sites are primarily optimized for observing sea surface radial velocities and bearings. Therefore, many ship detection systems are vulnerable to error sources such as environmental noise and clutter when they are applied to these practical surface current observation purpose systems. In addition, due to Korea's geographical features, only compact HF radars which generates non-uniform antenna response and has no information on target information are applicable. The ship detection and tracking techniques discussed in this paper considers these practical conditions and were evaluated by real data collected from the Yellow Sea, Korea. The proposed method is composed of two parts. In the first part, ship detection, a constant false alarm rate based detector was applied and was enhanced by a PCA subspace decomposition method which reduces noise. To merge multiple detections originated from a single target due to the Doppler effect during long CPIs, a clustering method was applied. Finally, data association framework eliminates false detections by considering ship maneuvering over time. According to evaluation results, it is claimed that the proposed method produces satisfactory results within certain ranges.

• Investigative Magnetic Resonance Imaging
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• v.13 no.2
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• pp.117-126
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• 2009

Purpose : A numerical method of designing a multiple quantum filter (MQF) is presented for the optimum detection of myo-inositol (mI), an important brain metabolite, by using in vivo proton nuclear magnetic resonance spectroscopy ($^1$-HMRS). Materials and Methods : Starting from the characterization of the metabolite, the filter design includes the optimization of the sequence parameters such as the two echo times (TEs), the mixing time (TM), and the flip angle and offset frequency of the 3rd $90^{\circ}$ pulse which converts multiple quantum coherences (MQCs) back into single quantum coherences (SQCs). The optimized filter was then tested both in phantom and in human brains. Results : The results demonstrate that the proposed MQF can improve the signal-to-background ratio of the target metabolite by a factor of more than three by effectively suppressing the signal from the background metabolites. Conclusion : By incorporating a numerical method into the design of MQFs in $^1$-HMRS the spectral integrity of a target metabolite, in particular, with a complicated spin system can be substantially enhanced.

• The Plant Pathology Journal
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• v.20 no.4
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• pp.302-307
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• 2004

Three pairs of specific primers were developed for rapid and precise RT-PCR detection of three seed-transmissible viruses, namely Peanut clump virus (PCV, Pecluvirus), White clover mosaic virus (WCIMV, Potexvirus) and Carrot red leaf virus (CaRLV, Luteovirus). Each primer set was found in conserved region through multiple sequence alignment in the DNAMAN. Total nucleic acids extracted from PCV-, WCMV-, and CaRLV-infected seeds and healthy plants were used for RT-PCR detection using each virus-specific primer, Sizes of PCV, WCIMV, and CaRLV PCR products were 617bp (PCV-uni5 and PCV-uni3 primers), 561bp (WCMV-CP5 and WCMV-CP3 primers), and 626bp (CL1-UP and CL2-DN primers); which corresponded to the target sizes. Nucleotides sequences of each amplified cDNA were confirmed which belonged to the original virus. This study suggests that these virus-specific primer sets can specifically amplify viral sequences in infected seeds. Thus, they can be used for specific detection of three viruses (PCV, WCMV and CaRLV) from imported seed samples for plant quarantine service.

• Journal of the HCI Society of Korea
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• v.1 no.1
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• pp.45-52
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• 2006

This paper presents an image-space algorithm to real-time collision detection, which is run completely by GPU. For a single object or for multiple objects with no collision, the front and back faces appear alternately along the view direction. However, such alternation is violated when objects collide. Based on these observations, the algorithm propose the depth peeling method which renders the minimal surface of objects, not whole surface, to find colliding. The Depth peeling method utilizes the state-of-the-art functionalities of GPU such as framebuffer object, vertexbuffer object, and occlusion query. Combining these functions, multi-pass rendering and context switch can be done with low overhead. Therefore proposed approach has less rendering times and rendering overhead than previous image-space collision detection. The algorithm can handle deformable objects and complex objects, and its precision is governed by the resolution of the render-target-texture. The experimental results show the feasibility of GPU-based collision detection and its performance gain in real-time applications such as 3D games.

• The Journal of the Acoustical Society of Korea
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• v.20 no.3
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• pp.3-7
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• 2001

In active sonar system using CW signal, when the noise included reverberation has not the white characteristics, the CFAR detector estimates high threshold. Because of this reason it cannot detect targets and not resolve the closely spaced multiple targets. In order to solve these problems, we propose an adaptive reverberation rejection filter The proposed filter is composed of an adaptive filter and a fixed filter with its coefficients. To study the performance of the proposed adaptive reverberation rejection filter, various experiments have been performed under In moving active sonar environments. As a results, the proposed method has the improved performance than the previous methods.

• Journal of the Korean Society for Aeronautical & Space Sciences
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• v.48 no.6
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• pp.419-429
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• 2020

In conducting a mission to explore and track targets using a number of unmanned aerial vehicles(UAVs), performance for that mission may vary significantly depending on the operating conditions of the UAVs such as the number of operations, the altitude, and what future flight paths each aircraft decides based on its current position. However, studies on the number of operations, operating conditions, and flight patterns of unmanned aircraft in these surveillance missions are insufficient. In this study, several types of flight simulations were conducted to detect and determine targets while multiple UAVs were involved in the avoidance of collisions according to various autonomous flight algorithms based by flocking theory, and the results were presented to suggest a more efficient/effective way to control a number of UAVs in target detection missions.

• The Bulletin of The Korean Astronomical Society
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• v.41 no.2
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• pp.48.3-49
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• 2016

We have five different types of observation modes with regard to the Deep Ecliptic Patrol of the Southern Sky (DEEP-South); Opposition Census (OC) for targeted photometry, Sweet Spot Survey (S1) for discovery and orbit characterization of Atens and Atiras, Ecliptic Survey (S2) for asteroid family studies and comet census, NEOWISE follow-up (NW) for near simultaneous albedo measurements in the visible bands, and Target of Opportunity (TO) observation for follow-up either for unpredictable events or targets of special interests. Different exposures with such different modes result in a wide range of background noise level, the number of background stars and the mover's projected speed in each image. The Moving Object Detection Program (MODP) utilizes multiple mosaic images being taken for the same target fields at different epochs at the three KMTNet sites. MODP employs existing software packages such as SExtractor (Source-Extractor) and SCAMP (Software for Calibrating Astrometry and Photometry); SExtractor generates object catalogs, while SCAMP conducts precision astrometric calibration, then MODP determines if a point source is moving. This package creates animated stamp images for visual inspection with MPC reports, the latter for checking whether an object is known or unknown. We evaluate the astrometric accuracy and efficiency of MODP using the year one dataset obtained from DEEP-South operations.