• Proceedings of the Korean Society of Precision Engineering Conference
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• 1994.10a
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• pp.670-675
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• 1994

Yhis paper describes a fault diagnosis simulation of the Real-Time Multiple Fault Dignosis System (RTMFDS) for forcasting faults in a system and deciding current machine state from signal information. Comparing with other diagnosis system for single fault,the system developed deals with multiple fault diagnosis,comprising two main parts. One is a remotesignal generating and transimission terminal and the other is a host system for fault diagnosis. Signal generator generate the random fault signal and the image information, and send this information to host. Host consists of various modules and agents such as Signal Processing Module(SPM) for sinal preprocessing, Performence Monotoring Module(PMM) for subsystem performance monitoring, Trigger Module(TM) for multi-triggering subsystem fault diagnosis, Subsystem Fault Diagnosis Agent(SFDA) for receiving trigger signal, formulating subsystem fault D\ulcornerB and initiating diagnosis, Fault Diagnosis Module(FDM) for simulating component fault with Hierarchical Artificial Neural Network (HANN), numerical models and Hofield network,Result Agent(RA) for receiving simulation result and sending to Treatment solver and Graphic Agent(GA). Each agent represents a separate process in UNIX operating system, information exchange and cooperation between agents was doen by IPC(Inter Process Communication : message queue, semaphore, signal, pipe). Numerical models are used to deseribe structure, function and behavior of total system, subsystems and their components. Hierarchical data structure for diagnosing the fault system is implemented by HANN. Signal generation and transmittion was performed on PC. As a host, SUN workstation with X-Windows(Motif)is used for graphic representation.

• Proceedings of the Korean Society of Precision Engineering Conference
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• 2002.10a
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• pp.636-640
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• 2002

In contrast to conventional CNC, PC-NC opens a new era for machine tools to be more intelligent. For instance, machine tool with PC-NC can be a machine agent system with capability of reacting autonomously to changing operating conditions. This paper introduces a concept of intelligent machine agent system, composed of machine agent and cell manager. Machine agent performs the functions such as process monitoring, diagnosis, maintenance management, condition assessment and schedule negotiation, while cell manager coordinates the negotiation process among multiple machine agents.

• Proceedings of the Korean Institute of Electrical and Electronic Material Engineers Conference
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• 2004.07b
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• pp.1121-1124
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• 2004

Aging test to estimate life property of polymer insulator is executed through several international standard such as IEC 61109 and CEA tracking wheel test, but is not getting clear conclusion yet. There are two methods in the diagnosis method of polymer insulator such as off-line and on-line. The diagnosis methods in off-line are external condition analysis by the eye, contaminant analysis on surface, surface analysis, pollution withstand voltage test, power frequency flashover voltage test, lightning impulse flashover test, tensile fracture load test and flexural load test. The diagnosis methods in off-line most are the method for virgin and last aged sample. However, the diagnosis method in on-line is method that can be evaluate sample state as progressing continuously aging test in beginning, The diagnosis method in on-line is arranged as following: leakage current measurement, electric field, surface state investigation, thermal image, emitting light measurement and then so. In this paper, the tracking performance of polymer insulator with salt solution which is added surface active agent. The diagnosis of insulator sample has been analyzed by leakage current and visual examination.

• Journal of the Korea Society of Computer and Information
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• v.21 no.1
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• pp.9-16
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• 2016

In this paper, we present a performance evaluation agent based on fuzzy cluster analysis and validity measures. The proposed agent is consists of three modules, fuzzy cluster analyzer, performance evaluation measures, and feature ranking algorithm for feature selection step in CAD system. Feature selection is an important step commonly used to create more accurate system to help human experts. Through this agent, we get the feature ranking on the dataset of mass and calcification lesions extracted from the public real world mammogram database DDSM. Also we design a CAD system incorporating the agent and apply five different feature combinations to the system. Experimental results proposed approach has higher classification accuracy and shows the feasibility as a diagnosis supporting tool.

• The KIPS Transactions:PartC
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• v.9C no.4
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• pp.497-504
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• 2002

This paper proposes fault diagnosis and correction algorithms using agent collaboration, and a management model for managing network configuration faults. This management model is composed of three processes-fault detection, fault diagnosis and fault correction. Each process, based on RBR, operates on using rules which are consisted in Rule-based Knowledge Database. Proposed algorithm selves the complex fault problem that a system could not work out by itself, using agent collaboration. And the algorithm does efficiently diagnose and correct network configuration faults in abnormal network states.

• Journal of the Korea Society of Computer and Information
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• v.19 no.12
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• pp.11-19
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• 2014

In this paper, we design an intelligent agent system with the data mining module and information fusion module as the core components of the system and investigate the possibility for the medical expert system. In the data mining module, fuzzy neural network, OFUN-NET analyzes multi-view data and produces fuzzy cluster knowledge base. In the information fusion module and application module, they serve the diagnosis result with possibility degree and useful information for diagnosis, such as uncertainty decision status or detection of asymmetry. We also present the experiment results on the BI-RADS-based feature data set selected form DDSM benchmark database. They show higher classification accuracy than conventional methods and the feasibility of the system as a computer aided diagnosis system.

• Investigative Magnetic Resonance Imaging
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• v.19 no.1
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• pp.52-55
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• 2015

Supradiaphragmatic liver is a rare condition. Establishing an accurate preoperative diagnosis is difficult. Operative exploration is necessary to differentiate this lesion from intrathoracic masses, such as a pleural based tumor, diaphragmatic tumor and peripheral lung tumor. However, with the aid of the hepatocyte-specific magnetic resonance imaging contrast agent, gadoxetic acid (Gd-EOB-DTPA), functional hepatocytes in the lesion can be identified in the hepatobiliary phase, potentially allowing an accurate and non-invasive diagnosis. We report a case of supradiaphragmatic liver diagnosed by Gd-EOB-DTPA-enhanced magnetic resonance imaging.

• Proceedings of the KAIS Fall Conference
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• 2003.11a
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• pp.3-9
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• 2003

The task for chromosome analysis and diagnosis by experienced cytogenetists are being concerned as repetitive, time consuming job and expensive. For that reason, intelligent agent based on chromosome knowledge base has been established to be able to analyze chromosomes and obtain necessary advises from the knowledge base instead of human experts. That is to say, knowledge base by IF THEN production rule was implemented to a knowledge domain with normal and abnormal chromosomes, and then the inference results by knowledge base could enter the inference data into the database. Experimental data were composed of normal chromosomes of 2,736 patients 'cases and abnormal chromosomes of 259 patients' cases that have been obtained from GTG-banding metaphase peripheral blood and amniotic fluid samples. The completed intelligent agent for chromosome knowledge base provides variously morphological information by analysis of normal or abnormal chromosomes and it also has the advantage of being able to consult with user on chromosome analysis and diagnosis.

• Journal of Radiopharmaceuticals and Molecular Probes
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• v.1 no.2
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• pp.104-108
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• 2015

Human serum albumin (HSA) has potential for diagnosis and therapy in clinical setting. The purpose of experiments was to develop and evaluate $^{68}Ga$-HSA as a PET agent for diagnosis of acute inflammation. NOTA-HSA was synthesized by conjugating 2-(p-isothiocyanatobenzyl)-1,4,7-triazacyclononane-1,4,7-triacetic acid to HSA in 0.1 M sodium carbonate buffer (pH 9.5) and then purified using a PD-10 size-exclusion column. NOTA-HSA was labeled with $^{68}Ga$ at room temperature for 10 min, and 8.4% sodium hydrogen carbonate buffer was added for neutralization. $^{68}Ga$-NOTA-HSA was purified using alumina N plus light cartridge and $0.22{\mu}m$ syringe filter. Labeling efficiency and radiochemical purity were determined by ITLC-SG with 0.1 M citric acid. Biodistribution study was performed in a male BALB/c mice model of Carrageenan-induced acute inflammation. Animal PET study was performed in acute inflammation mice model after tail vein injection of $^{68}Ga$-HSA. This radiotracer showed high labeling efficiency (>99%) around pH 7. Biodistribution study showed higher inflamed footpad uptake than control footpad uptake. Animal PET study revealed 2 times higher uptake on inflamed footpad compared to control footpad. In these experiments, we developed $^{68}Ga$-HSA for acute inflammation PET imaging and evaluated it in a mouse disease model. The results demonstrated that $^{68}Ga$-HSA has potential as a PET imaging agent for diagnosis of acute inflammation.

• Proceedings of the Korean Society of Precision Engineering Conference
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• 1995.04b
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• pp.457-462
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• 1995

This paper describes diagnosis strategy of the Flexible Multiple Fault Diagnosis Module for forecasting faults in system and deciding current machine state form sensor information. Most studydeal with diagnosis control stategy about single fault in a system, this studies deal with multiple fault diagnosis. This strategy is consist of diagnosis control module such as backward tracking expert system shell, various neural network, numerical model to predict machine state and communication module for information exchange and cooperate between each model. This models are used to describe structure, function and behavior of subsystem, complex component and total system. Hierarchical structure is very efficient to represent structural, functional and behavioral knowledge. FT(Fault Tree). ST(Symptom Tree), FCD(Fault Consequence Diagrapy), SGM(State Graph Model) and FFM(Functional Flow Model) are used to represent hierachical structure. In this study, IA(Intelligent Agent) concept is introduced to match FT component and event symbol in diagnosed system and to transfer message between each event process. Proposed diagnosis control module is made of IPC(Inter Process Communication) method under UNIX operating system.