• Journal of the Korean Data and Information Science Society
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• v.18 no.3
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• pp.619-628
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• 2007

This study is devoted to suggesting the norm of detection abnormal users who are inferior to the other users in the recommender system compared with estimation accuracy. To select the abnormal users, we propose the pre-filtering method by using the preference ratings to the item rated by users. In this study, the experimental result shows the possibility of detecting the abnormal users before the process of preference estimation through the prediction algorithm. And It will be possible to improve the performance of the recommender system by using this detecting norm.

• Proceedings of the IEEK Conference
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• 2002.06e
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• pp.211-214
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• 2002

Under a continuous manufacturing process, two dimension inspection system causes problems as blurring effect and low resolution and requires position calibration between frames. One dimension inspection system is, therefore, being researched as a substitution. In this paper, we implement mechanism of switching memory and processing data for reasonable one dimension inspection system. Redundant weft image and noise was suggested to be reduced by new method using modified morphological process and masked erosion process. From resulting image, line data and possible error information were obtained and constructed as a structure. Finally, error detecting algorithm was performed with this data structure. Processing time of error detecting was 0.625ms per line in applied system and experiment showed 94.7% of error detecting ability. This method is 20% faster in speed and 2.7% higher in error detecting ability comparing with the present method.

• The Transactions of The Korean Institute of Electrical Engineers
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• v.60 no.7
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• pp.1410-1416
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• 2011

A corrosion detecting system for 22.9 kV distribution power line insulation cable, which can travel autonomously along the live line, is proposed. Eddy current test method is employed to detect the corrosion, and the system developed here is capable of detecting internal corrosion of a ACSR-OC. Somewhat details of the electrical and mechanical mechanism of the system and traveling algorithm are introduced. Experimental results applied to the sample cables having artificial corrosion and the operating distribution lines are provided. From the result, we confirmed that the system is useful for detecting internal corrosion of a ACSR, and is expected to be a new non-destructive testing equipment in the area of diagnosis for the distribution power line.

• The Transactions of the Korea Information Processing Society
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• v.6 no.5
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• pp.1332-1341
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• 1999

Rapid expansion of network and increment of computer system access cause computer security to be an important issue. Hence, the researches in intrusion detection system(IDS)are active to reduce the risk from hackers. Considering IDS, we propose a new IDS model(DABIDS : Distributed Agent Based Intelligent intrusion Detection System) based on distributed intrusion detecting agents. The DABIDS dynamically collects intrusion behavior knowledge from each agents when some doubtable behaviors of users are detected and make new agents codes using intrusion scenario data base, and broadcast the detector codes to the distributed intrusion detecting agent of all node. This DABIDS can efficiently solve the problem to reduce the overhead for training detecting agent for intrusion behavior patterns.

• Journal of Korea Society of Digital Industry and Information Management
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• v.16 no.1
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• pp.67-78
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• 2020

Typical security solutions such as intrusion detection system are not suitable for detecting advanced persistent attack(APT), because they cannot draw the big picture from trivial events of security solutions. Researches on techniques for detecting multiple stage attacks by analyzing the correlations between security events or alerts are being actively conducted in academic field. However, these studies still use events from existing security system, and there is insufficient research on the structure of the entire security system suitable for advanced persistent attacks. In this paper, we propose an attack path and intention recognition system suitable for multiple stage attacks like advanced persistent attack detection. The proposed system defines the trace format and overall structure of the system that detects APT attacks based on the correlation and behavior analysis, and is designed with a structure of detection system using deep learning and big data technology, etc.

• Journal of the Korean Institute of Intelligent Systems
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• v.17 no.4
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• pp.534-539
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• 2007

In this paper, we present the development of an intelligent diagnosis system for detecting faults of the low voltage wires. The wire detecting system based on the Time-Frequency Domain Reflectometry (TFDR) algorithm shows the condition of the wires. We analyze the reflected signal which is sent from the wire detecting system and classify the fault type of the wires by using the intelligent diagnosis system. Through the TFDR, generally, the conditions of the wires are classified into the three types - damage, open and short. In order to classify the fault type efficiently, we use the fuzzy classifier which is represented as IF-THEN rules. Finally, we show the utility of the proposed algorithm by performing the simulation which is based on the data of the coaxial cable.

• Journal of the Korean Institute of Intelligent Systems
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• v.18 no.4
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• pp.518-523
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• 2008

In this paper, we present the development of an intelligent diagnosis system for detecting faults of the transmission line. Based on the TFDR (Time-Frequency Domain Reflectometry), the fault detecting performs to measure the location of fault line. We analyze the reflected signal which is sent from the wire detecting system and classify the fault type of the wires by using intelligent diagnosis system. In order to analyze effectively, we construct the intelligent diagnosis system which is based on the fuzzy-bayesian algorithm. Finally, we provide the simulation results which are performed at transmission line to evaluate the feasibility and generality of the proposed method in this paper.

• International Journal of Internet, Broadcasting and Communication
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• v.14 no.4
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• pp.88-95
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• 2022

Detecting anomalies in human movement is an important task in industrial applications, such as monitoring industrial disasters or accidents and recognizing unauthorized factory intruders. In this paper, we propose an abnormal worker movement detection system based on data stream processing and hierarchical clustering. In the proposed system, Apache Spark is used for streaming the location data of people. A hierarchical clustering-based anomalous trajectory detection algorithm is designed for detecting anomalies in human movement. The algorithm is integrated into Apache Spark for detecting anomalies from location data. Specifically, the location information is streamed to Apache Spark using the message queuing telemetry transport protocol. Then, Apache Spark processes and stores location data in a data frame. When there is a request from a client, the processed data in the data frame is taken and put into the proposed algorithm for detecting anomalies. A real mobility trace of people is used to evaluate the proposed system. The obtained results show that the system has high performance and can be used for a wide range of industrial applications.

• Journal of the Korean Society for Precision Engineering
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• v.31 no.6
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• pp.527-534
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• 2014

The control system of human torso model and driving system of stethoscope for physical assessment trainer are developed. The detecting characteristics of circular pickup coil which is driven by square wave voltage signal with resonance frequency of LC circuits are investigated and it is confirmed that the pickup coil can detect the existence of chestpiece near the coil region. The control system of human torso model is composed of 8 channel pickup coils, Mp3 and Bluetooth module. The driving system of stethoscope is composed of chestpiece with contact switch and Bluetooth headset. The chestpiece detecting algorithm check the contact of chestpiece with human body model first and excite the pickup coil sequentially to find the location. The proposed system can be applied the physical assessment trainer.

• Journal of electromagnetic engineering and science
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• v.3 no.1
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• pp.45-49
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• 2003

Wireless life signal detecting system is implemented with using the mechanism of Doppler Effect. This system can measure the respiration and heart rates with the periodic movement of skin and muscle near the heart. The system is consisted of antenna, RF transmitter, receiver, and display part. We did use two operating frequencies at 1.9 ㎓ and 10 ㎓. Firstly, the link budget about detecting system is analyzed and the signal detected from the system is compared with electrocardiogram(ECG) of monitor which is using for patient monitoring in hospital. Secondly, the detection of vital sign is also performed according to the different distances, and including behind the wall.