• Journal of Korea Multimedia Society
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• v.20 no.8
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• pp.1271-1281
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• 2017

It is essential to collect and analyze target information around the vehicle for autonomous driving of the vehicle. Based on the analysis, environmental information such as location and direction should be analyzed in real time to control the vehicle. In particular, obstruction or cutting of objects in the image must be handled to provide accurate information about the vehicle environment and to facilitate safe operation. In this paper, we propose a method to simultaneously generate 2D and 3D bounding box proposals using LiDAR Edge generated by filtering LiDAR sensor information. We classify the classes of each proposal by connecting them with Region-based Fully-Covolutional Networks (R-FCN), which is an object classifier based on Deep Learning, which uses two-dimensional images as inputs. Each 3D box is rearranged by using the class label and the subcategory information of each class to finally complete the 3D bounding box corresponding to the object. Because 3D bounding boxes are created in 3D space, object information such as space coordinates and object size can be obtained at once, and 2D bounding boxes associated with 3D boxes do not have problems such as occlusion.

• Journal of the Korean Society for Aeronautical & Space Sciences
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• v.34 no.5
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• pp.93-100
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• 2006

This paper presents a multi-sensor data simulator and a data fusion algorithm for tracking high dynamic flight target from Radar and Telemetry System. The designed simulator generates time-asynchronous multiple sensor data with different data rates and communication delays. Measurement noises are incorporated by using realistic sensor models. The proposed fusion algorithm is designed by a 21st order distributed Kalman Filter which is based on the PVA model with sensor bias states. A fault detection and correction logics are included in the algorithm for bad data and sensor faults. The designed algorithm is verified by using both simulation data and actual real data.

• Proceedings of the KIEE Conference
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• 2007.10a
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• pp.231-232
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• 2007

In this paper, a fault diagnosis and control integrated system (FDCIS) was developed to control the thermoelectric (TE) power in the SP-100 space reactor. The objectives of the proposed model predictive control were to minimize both the difference between the predicted TE power and the desired power, and the variation of control drum angle that adjusts the control reactivity. Also, the objectives were subject to maximum and minimum control drum angle and maximum drum angle variation speed. A genetic algorithm was used to optimize the model predictive controller. The model predictive controller was integrated with a fault detection and diagnostics algorithm so that the controller can work properly even under input and output measurement faults. With the presence of faults, the control law was reconfigured using online estimates of the measurements. Simulation results of the proposed controller showed that the TE generator power level controlled by the proposed controller could track the target power level effectively even under measurement faults, satisfying all control constraints.

• 한국데이터정보과학회:학술대회논문집
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• 2005.04a
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• pp.164-173
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• 2005

Data mining is the method to find useful information for large amounts of data in database. It is used to find hidden knowledge by massive data, unexpectedly pattern, relation to new rule. The methods of data mining are decision tree, association rules, clustering, neural network and so on. The decision tree approach is most useful in classification problems and to divide the search space into rectangular regions. Decision tree algorithms are used extensively for data mining in many domains such as retail target marketing, fraud detection, data reduction and variable screening, category merging, etc. We analyze waste database united with local information using decision tree techniques for environmental information. We can use these decision tree outputs for environmental preservation and improvement.

• Smart Media Journal
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• v.1 no.4
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• pp.27-34
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• 2012

In this paper, a novel text binarization is presented that can deal with some complex conditions, such as shadows, non-uniform illumination due to highlight or object projection, and messy backgrounds. To locate the target text region, a focus line is assumed to pass through a text region. Next, connected component analysis and stroke width estimation based on location information of the focus line is used to locate the bounding box of the text region, and each box of connected components. A series of classifications are applied to identify whether each CC(Connected component) is text or non-text. Also, a modified K-means clustering method based on an HCL color space is applied to reduce the color dimension. A text binarization procedure based on location of text component and seed color pixel is then used to generate the final result.

• Journal of Institute of Control, Robotics and Systems
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• v.18 no.3
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• pp.161-167
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• 2012

It is known that big brown bats can distinguish echo of a prey at various angles. In this paper, we suggest a new object localization strategy using ultrasonic echolocation. We calculate the relative energy ratio between a high frequency component of ultrasound signal and a low frequency component of ultrasound signal for a target object. We found the measure depends on bearing angle of the object in space. We also tested energy ratio of echoed FM ultrasound signals depending on frequency, based on cross-correlation. It can determine the relative angular position of objects even though the reflected signals are congested form each object.

• Bulletin of the Korean Chemical Society
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• v.31 no.8
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• pp.2293-2298
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• 2010

Focused electrospray (FES) deposition method is presented for matrix-assisted laser desorption/ionization (MALDI) mass spectrometry. FES ion optics consists of two cylindrical focusing electrodes capped with a truncated conical electrode through which an electrospray emitter passes along the cylindrical axis. A spray of charged droplets is focused onto a sample well on a MALDI target plate under atmospheric pressure. The shape and size distributions of matrix crystals are visualized by scanning electron microscope and the mass spectra are obtained by time-of-flight mass spectrometry. Angiotensin II, bradykinin, and substance P are used as test samples, while $\alpha$-cyano-4-hydroxycinnamic acid and dihydroxybenzoic acid are employed as matrices. FES of a sample/matrix mixture produces fine crystal grains on a 1-3 mm spot and reproducibly yields the mass spectra with little shot-to-shot and spot-to-spot variations. Although FES greatly stabilizes the signals, the space charge due to matrix ions limits the detection sensitivity of peptides. To avoid the space charge problem, we adopted a dual FES/FES mode, which separately deposits matrix and sample by FES in sequence. The dual FES/FES mode reaches the detection sensitivity of 0.88 amol, enabling ultrasensitive of peptides by homogeneously depositing matrix and sample under atmospheric pressure.

• Journal of The Korean Astronomical Society
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• v.52 no.1
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• pp.11-21
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• 2019

Intensive Monitoring Survey of Nearby Galaxies (IMSNG) is a high cadence observation program monitoring nearby galaxies with high probabilities of hosting supernovae (SNe). IMSNG aims to constrain the SN explosion mechanism by inferring sizes of SN progenitor systems through the detection of the shock-heated emission that lasts less than a few days after the SN explosion. To catch the signal, IMSNG utilizes a network of 0.5-m to 1-m class telescopes around the world and monitors the images of 60 nearby galaxies at distances D < 50 Mpc to a cadence as short as a few hours. The target galaxies are bright in near-ultraviolet (NUV) with $M_{NUV}$ < -18.4 AB mag and have high probabilities of hosting SNe ($0.06SN\;yr^{-1}$ per galaxy). With this strategy, we expect to detect the early light curves of 3.4 SNe per year to a depth of R ~ 19.5 mag, enabling us to detect the shock-heated emission from a progenitor star with a radius as small as $0.1R_{\odot}$. The accumulated data will be also useful for studying faint features around the target galaxies and other science projects. So far, 18 SNe have occurred in our target fields (16 in IMSNG galaxies) over 5 years, confirming our SN rate estimate of $0.06SN\;yr^{-1}$ per galaxy.

• Journal of the Korean Institute of Rural Architecture
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• v.24 no.1
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• pp.9-17
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• 2022

Rural spaces are increasingly valuable as areas for introducing renewable energy infrastructure to achieve carbon neutrality. Rural areas are the living grounds of rural residents, and the balance of conservation and development for rural areas is important for the introduction of reasonable facilities. In order to maintain a balance between development and preservation and to introduce reasonable renewable energy facilities, it is necessary to develop a current status survey and an effective survey method to utilize a space capable of introducing renewable energy facilities such as idle land and vacant houses. Therefore, this study was conducted to verify the readability using an unmanned aerial vehicle, and the main results are as follows. The detection of photovoltaic power generation facilities using unmanned aerial vehicles was effective in analyzing the location and area of photovoltaic panels located on the roofs of buildings, and it was possible to calculate the expected power generation by region through the area calculation of photovoltaic panels. The vacant house detection can be used to select an investigation target for an vacant house condition survey as it can identify damage to buildings that are expected to be empty houses, management status, and electricity supply facilities through aerial photos. It is judged that the unmanned aerial vehicle detection capability can be utilized as a method to improve the efficiency of investigation and supplement the data related to solar power generation facilities and vacant houses provided by public institutions. Although this study detected the status of solar power generation facilities and vacant houses through high-resolution aerial image analysis, as a follow-up study, automatic measurement methods using the temperature difference of solar power generation facilities and general characteristics of vacant houses that can be read from the air were investigated. If the deriving research is carried out, it is judged that it will be possible to contribute to the improvement of the accuracy of the detection result using the unmanned aerial vehicle and the expansion of the application range.

• Korean Journal of Microbiology
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• v.33 no.1
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• pp.1-6
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• 1997

5-Enolpyruvylshikimate 3-phosphate(EPSP) synthase is the sixth enzyme of the shikimate pathway that synthesizes aromatic amino acids. The enzyme is a primary target for the glyphos'lte which is a broad-spectrum and environmetally safe herbicide. As a first step toward development of glyphpsate-resistant EPSP synthase, the EPSP synthase gene(aroA) was amplified by polymerase chain reaction and cluned into pET-25b vector. In this construct. designated pET-aro, the aroA gene is expressed under control of strong T7 promoter. and the EPSP synthase is produced as a fusion protein with pelB leader at N-terminus and HSV-tag and His-tag at C-terminus. When the pET-aro clone was induced to produce the enzyme, it was found that the EPSP synthase was successfully exported to peri plasmic space. The periplasmic transport was greatly dependent on the induction temperatures. Among the induction temperatures examined($25^{\circ}C$, $30^{\circ}C$, $34^{\circ}C$ and $37^{\circ}C$). induction at $34^{\circ}C$ gave rise to maximal periplasmic transport. The recomhinant EPSP synthase could have been purified hy $Ni^{2+}$ -affinity chromatography using the His-tag. and detected hy anti-HSV -tag antibody. The recombinant EPSP synthase also hound to phosphocellulose resin and was eluted hy shikimate 3-phosphate and phosphoenolpyruvate. as expected. The recombinant EPSP synthase purified from phosphocellulose resin showed typical EPSP synthase activity.