• Journal of Satellite, Information and Communications
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• v.9 no.1
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• pp.28-32
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• 2014

In this paper, we analyzed performance of signal detection for terrestrial digital multimedia broadcasting (T-DMB) system in various channel environments that applied gaussian, Rayleigh and COST 207 environments that estimate response of real channel state. In order to detect the signal, a signal detection scheme based on energy detection is employed. We generated T-DMB signals so that estimate properly simulation result. For evaluating the signal detection performance, detection probability is derived. We consider two kinds of detection segment, which are three segments and five segments. And we compare the system performances in accordance with the detection segment. From simulation results, it is confirmed that the performance of signal detection is raised as increase the number of segments. The result of this paper can be applied to implement signal detection of broadcasting system.

• Transactions of the Korean Society of Automotive Engineers
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• v.22 no.7
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• pp.107-116
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• 2014

This paper presents camera-based road surface marking detection methods suited to sensor fusion-based positioning system that consists of low-cost GPS (Global Positioning System), INS (Inertial Navigation System), EDM (Extended Digital Map), and vision system. The proposed vision system consists of two parts: lane marking detection and RSM (Road Surface Marking) detection. The lane marking detection provides ROIs (Region of Interest) that are highly likely to contain RSM. The RSM detection generates candidates in the regions and classifies their types. The proposed system focuses on detecting RSM without false detections and performing real time operation. In order to ensure real time operation, the gating varies for lane marking detection and changes detection methods according to the FSM (Finite State Machine) about the driving situation. Also, a single template matching is used to extract features for both lane marking detection and RSM detection, and it is efficiently implemented by horizontal integral image. Further, multiple step verification is performed to minimize false detections.

• 한국지구물리탐사학회:학술대회논문집
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• 2002.09a
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• pp.179-195
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• 2002

This paper examined the applicability of geophysical prospecting for water leakage detection of the water utilization facilities. Electrical resistivity survey and spontaneous-potential survey were carried out for the water leakage detection of dike and embankment, and the applicability was confirmed from many case studies. However, in order to efficiently maintain and detection of the more accurate water points in the embankment, the efficiently maintain and detection of the more accurate water leakage points in the embankment, the requirements are as follows; 1) It is necessary to use the electrical resistivity survey jointly with the spontaneous-potential survey in order to improve the reliability of water leakage information. 2) It is important to understand physical properties of the soil which influences the electrical resistivity of embankment in order to accurately grasp the water leakage points from the result of the electrical resistivity survey. 3) It is necessary to introduce the three-dimensional prospecting in order to improve the reliability of the measured value. 4) Introductions of the monitoring measurement system are necessary in order to efficiently and economically maintain of the water utilization facilities.

• Journal of the Korea Academia-Industrial cooperation Society
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• v.12 no.1
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• pp.459-466
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• 2011

In this paper, we proposed a data mining framework for the management of alerts in order to improve the performance of the intrusion detection systems. The proposed alert data mining framework performs alert correlation analysis by using mining tasks such as axis-based association rule, axis-based frequent episodes and order-based clustering. It also provides the capability of classify false alarms in order to reduce false alarms. We also analyzed the characteristics of the proposed system through the implementation and evaluation of the proposed system. The proposed alert data mining framework performs not only the alert correlation analysis but also the false alarm classification. The alert data mining framework can find out the unknown patterns of the alerts. It also can be applied to predict attacks in progress and to understand logical steps and strategies behind series of attacks using sequences of clusters and to classify false alerts from intrusion detection system. The final rules that were generated by alert data mining framework can be used to the real time response of the intrusion detection system.

• Journal of Digital Convergence
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• v.14 no.11
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• pp.249-255
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• 2016

Since the elderly voices include a lot of noise caused by physiological changes in respiration, phonation, and resonance, the performance of the convergence health-care equipments such as speech recognition, synthesis, analysis program done by elderly voice is deteriorated. Therefore it is necessary to develop researches to operate health-care instruments with elderly voices. In this study, a voice activity detection using a symmetric higher-order differential energy function (SHODEO) was developed and was compared with auto-correlation function(ACF) and the average magnitude difference function(AMDF). It was confirmed to have a better performance than other methods in the voice interval detection. The voice activity detection will be applied to a voice interface for the elderly to improve the accessibility of the smart devices.

• The KIPS Transactions:PartB
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• v.16B no.1
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• pp.17-24
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• 2009

This paper suggests the background image and the algorism of detecting an accident at crossroads by using the sequence of traffic light at crossroads, which is installed within the crossroads, in order to detect an accident within crossroads. A method of using the existing image contains a problem that the accident-detection ratio gets lower in a situation that noise occurs loudly given using new accident model, the confused situation, or sound source. This study used the accident detection by developing a filter of using the property of histogram in the sequence of traffic light at crossroads and the background image, in order to reduce misjudgment of an accident caused by external shadow, vehicle stoppage, vehicle headlight, and externally environmental influence. As a result of experimenting by acquiring 15 actual accident images in order to examine the performance of the suggested algorism, the accident was detected in all the 15 videos. Even as for a new accident model, the accident within crossroads could be detected.

• Journal of the Institute of Electronics Engineers of Korea SP
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• v.46 no.4
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• pp.9-15
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• 2009

This paper proposes a cancellation algorithm of impulse noise using a rank-order method. The proposed method is a fast and simple algorithm that is composed of two parts. The first part involves noise detection using a fuzzy technique, where an image is divided into RGB color channels. Then every pixel in each color channel is investigated and assigned a probability indicating its chances of being a noise pixel. At this time, the rank order method using a noise-detection mask is utilized for accurate noise detection. Thereafter, the second part involves noise-cancellation, where each noise-pixel value in an image is replaced in proportion to its fuzzy probability. Through the experiments, both the conventional and proposed methods were simulated and compared. As a result, it is shown that proposed method is able to detect noisy pixels more accurately, and produce resulting images with high PSNR values.

• KIEE International Transaction on Electrical Machinery and Energy Conversion Systems
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• v.5B no.2
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• pp.103-110
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• 2005

Broken rotor bars in induction motors can be detected by monitoring any abnormality of the spectrum amplitudes at certain frequencies in the motor current spectrum. Broken rotor bar fault detection schemes should rely on multiple signatures in order to overcome or reduce the effect of any misinterpretation of the signatures that are obscured by factors such as measurement noises and different load conditions. Multiple Discriminant Analysis (MDA) and Artificial Neural Networks (ANN) provide appropriate environments to develop such fault detection schemes because of their multi-input processing capabilities. This paper describes two fault detection schemes for broken rotor bar fault detection with multiple signature processing, and demonstrates that multiple signature processing is more efficient than single signature processing.

• Journal of Korea Society of Digital Industry and Information Management
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• v.10 no.2
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• pp.75-82
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• 2014

MANET has various types of attacks. In particular, routing attacks using characteristics of movement of nodes and wireless communication is the most threatening because all nodes which configure network perform a function of router which forwards packets. Therefore, mechanisms that detect routing attacks and defense must be applied. In this paper, we proposed hierarchical structure attack detection techniques in order to improve the detection ability against routing attacks. Black hole detection is performed using PIT for monitoring about control packets within cluster and packet information management on the cluster head. Flooding attack prevention is performed using cooperation-based distributed detection technique by member nodes. For this, member node uses NTT for information management of neighbor nodes and threshold whether attack or not receives from cluster head. The performance of attack detection could be further improved by calculating at regular intervals threshold considering the total traffic within cluster in the cluster head.

• International Journal of Safety
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• v.11 no.1
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• pp.6-10
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• 2012

This paper presents a study on the analysis for reducing the number of false alarms in fire detection system. In order to intelligent algorithm fuzzy logic is adopted in developing fire detection system to reduce false alarm. The intelligent fire detection algorithm compared and analyzed the fire and non-fire signatures measured in circuits simulating flame fire and smoldering fire. The algorithm has input variables obtained by fire experiment with K-type thermocouple and optical smoke sensor. Also triangular membership function is used for inference rules. And the antecedent part of inference rules consists of temperature and smoke density, and the consequent part consists of fire probability. A fire-experiment is conducted with paper, plastic, and n-heptane to simulate actual fire situation. The results show that the intelligent fire detection algorithm suggested in this study can more effectively discriminate signatures between fire and similar fire.