• Journal of Sensor Science and Technology
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• v.32 no.4
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• pp.207-212
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• 2023

H₂S is a toxic and harmful gas, even at concentrations as low as hundreds of parts per million; thus, developing an H₂S sensor with excellent performance in terms of high response, good selectivity, and fast response time is important. In this study, an H₂S sensor with a high response and fast response time, consisting of a sensing material (SnO₂), an electrode, a temperature sensor, and a micro-heater, was developed using micro-electro-mechanical system technology. The developed H₂S sensor with a micro-heater (circular type) has excellent H₂S detection performance at low H₂S concentrations (0-10 ppm), with quick response time (<16 s) and recovery time (<65 s). Therefore, we expect that the developed H₂S sensor will be considered a promising candidate for protecting workers and the general population and for responding to tightened regulations.

• Current Optics and Photonics
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• v.1 no.3
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• pp.196-202
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• 2017

Corona discharge is always a sign of failure processes of high-voltage electrical apparatus, including those utilized in electric railway systems. Solar-blind ultraviolet (UV) cameras are effective tools for corona inspection. In this work, we present an automatic railway corona-discharge detection system based on solar-blind ultraviolet detection. The UV camera, mounted on top of a train, inspects the electrical apparatus, including transmission lines and insulators, along the railway during fast cruising of the train. An algorithm based on the Hough transform is proposed for distinguishing the emitting objects (corona discharge) from the noise. The detection system can report the suspected corona discharge in real time during fast cruises. An experiment was carried out during a routine inspection of railway apparatus in Xinjiang Province, China. Several corona-discharge points were found along the railway. The false-alarm rate was controlled to less than one time per hour during this inspection.

• The Journal of The Korea Institute of Intelligent Transport Systems
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• v.9 no.1
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• pp.9-18
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• 2010

Our country has so large mountain area that the tunnel construction is inevitable and the need of incident detection that provides safe management of tunnels is increasing. In this paper, we suggest a tunnel incident detection system using computer vision techniques, which can detect the incidents in a tunnel and provides the information to the tunnel administrative office in order to help safe tunnel operation. The suggested system enhances the processing speed by using simple processing algorithm such as image subtraction, and ensures the accuracy of the system by focused on the incident detection itself rather than its classification. The system is also cost effective because the video data from 4 cameras can be simultaneously analyzed in a single PC-based system. Our system can be easily extended because the PC-based analyzer can be increased according to the number of cameras in a tunnel. Also our web-based structure is useful to connect the other remotely located tunnel incident systems to obtain interoperability between tunnels. Through the experiments the system has successfully detected the incidents in real time including dropped luggage, stoped car, traffic congestion, man walker or bicycle, smoke or fire, reverse driving, etc.

• The Journal of Korean Institute of Communications and Information Sciences
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• v.41 no.9
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• pp.1120-1131
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• 2016

In this paper, we propose a smoker recognition algorithm, detecting smokers in a video sequence in order to prevent fire accidents. We use description-based method in hierarchical approaches to recognize smoker's activity, the algorithm consists of background subtraction, object detection, event search, event judgement. Background subtraction generates slow-motion and fast-motion foreground image from input image using Gaussian mixture model with two different learning-rate. Then, it extracts object locations in the slow-motion image using chain-rule based contour detection. For each object, face is detected by using Haar-like feature and smoke is detected by reflecting frequency and direction of smoke in fast-motion foreground. Hand movements are detected by motion estimation. The algorithm examines the features in a certain interval and infers that whether the object is a smoker. It robustly can detect a smoker among different objects while achieving real-time performance.

• Journal of the Korea Institute of Information and Communication Engineering
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• v.26 no.8
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• pp.1142-1147
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• 2022

The edges of image should be detected first so that the objects in the image can be identified. An hardware-implemented edge detection algorithm outperforms its software version. Sobel operation is the most suitable algorithm for an hardware implementation of edge detection. And lots of works have been done to perform Sobel operations efficiently on FPGA-based hardware. This work proposes how to implement fast edge detection circuit on FPGA, which is based on the conventional circuit for edge detection using Sobel operator. The newly proposed circuit is suitable for processing images when the images are stored in memory devices and outperforms the conventional one with little additional FPGA resources. Both the conventional circuit and the proposed circuit were implemented on an FPGA. And the result showed that the proposed circuit almost doubles the performance in processing images and needs little additional FPGA resources.

• Journal of Information Processing Systems
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• v.12 no.4
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• pp.644-660
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• 2016

The real-time detection of malware remains an open issue, since most of the existing approaches for malware categorization focus on improving the accuracy rather than the detection time. Therefore, finding a proper balance between these two characteristics is very important, especially for such sensitive systems. In this paper, we present a fast portable executable (PE) malware detection system, which is based on the analysis of the set of Application Programming Interfaces (APIs) called by a program and some technical PE features (TPFs). We used an efficient feature selection method, which first selects the most relevant APIs and TPFs using the chi-square ($KHI^2$) measure, and then the Phi (${\varphi}$) coefficient was used to classify the features in different subsets, based on their relevance. We evaluated our method using different classifiers trained on different combinations of feature subsets. We obtained very satisfying results with more than 98% accuracy. Our system is adequate for real-time detection since it is able to categorize a file (Malware or Benign) in 0.09 seconds.

• Journal of Korea Game Society
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• v.1 no.1
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• pp.42-48
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• 2001

Collision is a brief dynamic event consisting of the close approach of two or more objects or particles resulting in an abrupt change of momentum or exchange of energy because of interaction. Collisions play very important role in computer graphics, computer games and animations fields. Collisions can supply active interaction between cyberspace and real world and give much interests for making nice games so reasonable collision detection algorithms are needed. Collision detection algorithms should satisfy being fast and accuracy. In this paper, we survey the 2D collision detection algorithms between geometric models. We present several methods and system available for collision detection.

• ETRI Journal
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• v.39 no.6
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• pp.832-840
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• 2017

Recently, deep recurrent neural networks have achieved great success in various machine learning tasks, and have also been applied for sound event detection. The detection of temporally overlapping sound events in realistic environments is much more challenging than in monophonic detection problems. In this paper, we present an approach to improve the accuracy of polyphonic sound event detection in multichannel audio based on gated recurrent neural networks in combination with auditory spectral features. In the proposed method, human hearing perception-based spatial and spectral-domain noise-reduced harmonic features are extracted from multichannel audio and used as high-resolution spectral inputs to train gated recurrent neural networks. This provides a fast and stable convergence rate compared to long short-term memory recurrent neural networks. Our evaluation reveals that the proposed method outperforms the conventional approaches.

• International Journal of Oral Biology
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• v.42 no.4
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• pp.197-201
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• 2017

A novel method for the detection of hydrogen peroxide in aqueous solution was developed via reaction between $H_2O_2$, trivalent titanium ion ($Ti^{3+}$) and 4-(2-thiazolylazo) resorcinol (TAR), resulting in a ternary complex with a maximum UV absorbance at 530 nm. The CE detection of $H_2O_2$ was fast, sensitive and cost-effective without pretreatment procedures. $H_2O_2$ was detected within 15 min at 1 to $100{\mu}M$ range with the lowest detection limit at $1.0{\mu}M$. Under the optimized CE conditions, the concentration of $H_2O_2$ in coffee or tea extract was quantitatively determined. Our results show that CE detection of the ternary complex of $H_2O_2-Ti^{3+}$-TAR has potential applications for the detection of $H_2O_2$ in aqueous sources.

• Proceedings of the KSRS Conference
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• 2003.11a
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• pp.1099-1101
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• 2003

Change detection technology, which discovers the change information on the surface of the earth by comparing and analyzing multi-temporal satellite images, can be usefully applied to the various fields, such as environmental inspection, urban planning, forest policy, updating of geographical information and the military usage. In this paper, we introduce a change detection system that can extract and analyze change elements from high-resolution satellite imagery as well as low- or middle-resolution satellite imagery. The developed system provides not only 7 pixelbased methods that can be used to detect change from low- or middle-resolution satellite images but also a float window concept that can be used in manual change detection from highresolution satellite images. This system enables fast access to the very large image, because it is constituted by OGC grid coverage components. Also new change detection algorithms can be easily added into this system if once they are made into grid coverage components.