• ETRI Journal
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• v.45 no.3
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• pp.448-461
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• 2023

This article performs a detailed data scrutiny on a chronic kidney disease (CKD) dataset to select efficient instances and relevant features. Data relevancy is investigated using feature extraction, hybrid outlier detection, and handling of missing values. Data instances that do not influence the target are removed using data envelopment analysis to enable reduction of rows. Column reduction is achieved by ranking the attributes through feature selection methodologies, namely, extra-trees classifier, recursive feature elimination, chi-squared test, analysis of variance, and mutual information. These methodologies are ranked via Technique for Order of Preference by Similarity to Ideal Solution (TOPSIS) using weight optimization to identify the optimal features for model building from the CKD dataset to facilitate better prediction while diagnosing the severity of the disease. An efficient hybrid ensemble and novel similarity-based classifiers are built using the pruned dataset, and the results are thereafter compared with random forest, AdaBoost, naive Bayes, k-nearest neighbors, and support vector machines. The hybrid ensemble classifier yields a better prediction accuracy of 98.31% for the features selected by extra tree classifier (ETC), which is ranked as the best by TOPSIS.

• Annual Conference on Human and Language Technology
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• 2020.10a
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• pp.591-594
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• 2020

담화에서 의미를 전달하는 데 문제가 없을 경우에는 문장성분을 생략하여 표현한다. 생략된 문장성분을 무형대용어(zero anaphora)라고 한다. 무형대용어를 복원하기 위해서는 무형대용어 탐지와 무형대용어 해결이 필요하다. 무형대용어 탐지란 문장 내에서 생략된 필수성분을 찾는 것이고, 무형대용어 해결이란 무형대용어에 알맞은 문장성분을 찾아내는 것이다. 본 논문에서는 담화에서의 무형대용어 탐지 및 해결을 위한 말뭉치 생성 방법을 제안한다. 먼저 기존의 세종 구어 말뭉치에서 어휘지도를 이용하여 무형대용어를 복원한다. 이를 위해 본 논문에서는 동형이의어 부착과 어휘지도를 이용해서 무형대용어를 복원하고 복원된 무형대용어에 대한 오류를 수정하고 그 선행어(antecedent)를 수동으로 결정함으로써 무형대용어 해결 말뭉치를 생성한다. 총 58,896 문장에서 126,720개의 무형대용어를 복원하였으며, 약 90%의 정확률을 보였다. 앞으로 심층학습 등의 방법을 활용하여 성능을 개선할 계획이다.

• The Journal of the Convergence on Culture Technology
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• v.9 no.4
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• pp.617-623
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• 2023

Among the fire incidents in Korea over the past decade, building fires are the most common, and property and human casualties are the most common. However, the existing fire fighting system does not only inform the location of emergency exits and guide safe routes to help casualties evacuate smoothly. A system was proposed to help successful evacuation by distinguishing vertical and horizontal characteristics using spatial characteristics. In this study, an effective evacuation system was proposed by predicting fires using temperature detection sensors and smoke sensor values, and calculating the optimal evacuation path through the Dijkstra algorithm.

• Proceedings of the Korean Institute of Information and Commucation Sciences Conference
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• 2022.10a
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• pp.131-132
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• 2022

We generate classifications and scenarios for intrusions based on 3D LiDAR Data. Research was conducted to analyze and diversify various actual intrusion cases to establish a system that can recognize objects and identify and guard data on intrusion. By generating and simulating basic scenarios for cars, people, animals, natural objects and etc, we create a classification scheme necessary to build and evaluate systems for intrusion. Based on the finally constructed scenario, we add variables for vehicles and surrounding objects to diversify scenarios, and lay the foundation for building accurate and automated alerting systems for future intrusions.

• Journal of Microbiology and Biotechnology
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• v.33 no.10
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• pp.1257-1267
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• 2023

Although rational genetic engineering is nowadays the favored method for microbial strain improvement, building up mutant libraries based on directed evolution for improvement is still in many cases the better option. In this regard, the demand for precise and efficient screening methods for mutants with high performance has stimulated the development of biosensor-based high-throughput screening strategies. Genetically encoded biosensors provide powerful tools to couple the desired phenotype to a detectable signal, such as fluorescence and growth rate. Herein, we review recent advances in engineering several classes of biosensors and their applications in directed evolution. Furthermore, we compare and discuss the screening advantages and limitations of two-component biosensors, transcription-factor-based biosensors, and RNA-based biosensors. Engineering these biosensors has focused mainly on modifying the expression level or structure of the biosensor components to optimize the dynamic range, specificity, and detection range. Finally, the applications of biosensors in the evolution of proteins, metabolic pathways, and genome-scale metabolic networks are described. This review provides potential guidance in the design of biosensors and their applications in improving the bioproduction of microbial cell factories through directed evolution.

• Journal of the Semiconductor & Display Technology
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• v.23 no.1
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• pp.71-78
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• 2024

In indoor environments, since global positioning system (GPS) signals can be blocked by obstacles, such as building structure. the performance of GPS-based positioning methods can be degraded because of the loss of GPS signals. To solve this problem, various localization schemes using inertial measurement unit (IMU) sensors, such as gyroscope, accelerometer, and magnetometer, have been proposed to enhance the positioning accuracy in indoor environments. IMU-based positioning methods can estimate the location of the user by calculating the velocity and heading angle of the user without the help of GPS. However, low-cost MEMS IMUs may lead to drift error and large bias. In addition, positioning errors in IMU-based positioning approaches can be caused by the irrelevant motion of the pedestrian. In this study, we propose an enhanced indoor positioning method that provides more reliable localization results by using the camera, light detection and right (LiDAR), and ARKit framework on the iPhone. Through reliable positioning results and augmented reality (AR) experiences, our indoor positioning system can provide indoor space guidance services.

• Journal of Korea Water Resources Association
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• v.53 no.10
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• pp.845-859
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• 2020

Climate change and recent heat waves have drawn public attention toward other environmental issues, such as water pollution in the form of algal blooms, chemical leaks, and oil spills. Water pollution by the leakage of chemicals may severely affect human health as well as contaminate the air, water, and soil and cause discoloration or death of crops that come in contact with these chemicals. Chemicals that may spill into water streams are often colorless and water-soluble, which makes it difficult to determine whether the water is polluted using the naked eye. When a chemical spill occurs, it is usually detected through a simple contact detection device by installing sensors at locations where leakage is likely to occur. The drawback with the approach using contact detection sensors is that it relies heavily on the skill of field workers. Moreover, these sensors are installed at a limited number of locations, so spill detection is not possible in areas where they are not installed. Recently hyperspectral images have been used to identify land cover and vegetation and to determine water quality by analyzing the inherent spectral characteristics of these materials. While hyperspectral sensors can potentially be used to detect chemical substances, there is currently a lack of research on the detection of chemicals in water streams using hyperspectral sensors. Therefore, this study utilized remote sensing techniques and the latest sensor technology to overcome the limitations of contact detection technology in detecting the leakage of hazardous chemical into aquatic systems. In this study, we aimed to determine whether 18 types of hazardous chemicals could be individually classified using hyperspectral image. To this end, we obtained hyperspectral images of each chemical to establish a spectral library. We expect that future studies will expand the spectral library database for hazardous chemicals and that verification of its application in water streams will be conducted so that it can be applied to real-time monitoring to facilitate rapid detection and response when a chemical spill has occurred.

• Journal of the Korea Institute of Building Construction
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• v.17 no.6
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• pp.545-557
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• 2017

The study is about the efficient alternative to concrete surface in the field of visual inspection technology for deteriorated infrastructure. By combining industrial drones and deep learning based image analysis techniques with traditional visual inspection and research, we tried to reduce manpowers, time requirements and costs, and to overcome the height and dome structures. On board device mounted on drones is consisting of a high resolution camera for detecting cracks of more than 0.3 mm, a lidar sensor and a embeded image processor module. It was mounted on an industrial drones, took sample images of damage from the site specimen through automatic flight navigation. In addition, the damege parts of the site specimen was used to measure not only the width and length of cracks but white rust also, and tried up compare them with the final image analysis detected results. Using the image analysis techniques, the damages of 54ea sample images were analyzed by the segmentation - feature extraction - decision making process, and extracted the analysis parameters using supervised mode of the deep learning platform. The image analysis of newly added non-supervised 60ea image samples was performed based on the extracted parameters. The result presented in 90.5 % of the damage detection rate.

• Journal of the Korea Academia-Industrial cooperation Society
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• v.19 no.10
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• pp.151-157
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• 2018

Among the various sensors for measuring traffic, PVDF (polyvinylidene fluoride) piezoelectric sensors are used to classify vehicles because they can detect the axle of the vehicle. Piezoelectric sensors are embedded in road pavements and are always exposed to traffic loads and environmental loads. Therefore, the life expectancy is very short, less than 6 years. Traffic control is essential for reinstallation and data collection is interrupted during the failure period. The lifespan will increase if the sensor installation depth is increased. In this study, the sensor signal output was analyzed with a variable depth of sensor installation to verify the possibility of deeper installation. Furthermore, various parameters, such as the weight and speed, were analyzed. The wheel load is applied using APT. As a result, the MSI BL sensor output signal is higher than 100mV when installed at 3cm, which is reliable. If the location of the sensor is deeper in the pavement, the expected lifetime of the sensor is also increased. On the other hand, the MSI cable was found to be less than 100mV at the shallowest depth of 1cm, making it impossible for field applications.

• Journal of KIISE:Software and Applications
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• v.30 no.7_8
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• pp.727-743
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• 2003

This paper proposes an automatic highlight building algorithm for soccer video by using the structural characteristics of broadcasted sports video that an interesting (or important) event (such as goal or foul) in sports video has a continuous replay shot surrounded by gradual shot change effect like wipe. This shot editing rule is used in this paper to analyze the structure of broadcated soccer video and extracts shot involving the important events to build a highlight. It first uses the spatial-temporal image of video to detect wipe transition effects and zoom out/in shot changes. They are used to detect the replay shot. However, using spatial-temporal image alone to detect the wipe transition effect requires too much computational resources and need to change algorithm if the wipe pattern is changed. For solving these problems, a two-pass detection algorithm and a pixel sub-sampling technique are proposed in this paper. Furthermore, to detect the zoom out/in shot change and replay shots more precisely, the green-area-ratio and the motion energy are also computed in the proposed scheme. Finally, highlight shots composed of event and player shot are extracted by using these pre-detected replay shot and zoom out/in shot change point. Proposed algorithm will be useful for web services or broadcasting services requiring abstracted soccer video.