• The Journal of Korean Institute of Communications and Information Sciences
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• v.38C no.4
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• pp.335-343
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• 2013

If the SW weaknesses, which are the main cause of cyber breaches, are analyzed and removed in the SW development stages, the cyber breaches can be prevented effectively. In case of Domestic, removing SW weaknesses by applying Secure SDLC(SW Development Life Cycle) has become mandatory. In order to analyze and remove the SW weaknesses effectively, reliable SW weakness diagnostic tools are required. Therefore, we propose the functional requirements of diagnostic tool which is suitable for the domestic environment and the evaluation methodology which can assure the reliability of the diagnostic tools. Then, to analyze the effectiveness of the proposed evaluation framework, both demonstration results and process are presented.

• The korean journal of orthodontics
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• v.22 no.4 s.39
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• pp.755-778
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• 1992

It is prerequisite of orthodontists to diagnose malocclusion correctly and make treatment plans accurately for treating maloccluded patients efficiently and earning more stable and better results. Recently computers were introduced in orthodontic diagnosis steps, which enabled orthodontists to get more precise diagnosis, to make more accurate treatment planning and to provide better orthodontic cares for more patients. The authors studied on the diagnostic analysis methods which have been used frequently in Korea and made a diagnostic computer program including the horizontal and/or vertical measurement of length, degrees and proportions in lateral cephalometric radiographs, the analysis of the skeletal and soft-tissue features and the evaluation of the treatment results. We also made a scheduling program for arrangement and management of patients. 40 skeletal and 24 soft-tissue landmarks were selected in a lateral cephalometric radiographs. The available analysis methods in this program are Angular analysis, Linear analysis, Ricketts analysis, Profilogram , Steiner analysis, Tweed analysis, MacNamara analysis, Open bite analysis, Kim's diagnosis, Skeleto-dental cephalometric analysis and Height & weight analysis. We suggested that this diagnostic computer program make it possible for orthodontists to get more rapid and accurate diagnostic analysis and treatment planning and for patient to earn better and more efficient orthodontic service.

• Biomedical Science Letters
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• v.18 no.4
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• pp.399-405
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• 2012

The brain is the body's most organized and controlled organ, and it governs various psychological and mental functions. A brain abnormality could greatly affect one's physical and mental abilities, and consequently one's social life. Brain disorders can be broadly categorized into three main afflictions: stroke, brain tumor, and dementia. Among these, stroke is a common disease that occurs owing to a disorder in blood flow, and it is accompanied by a sudden loss of consciousness and motor paralysis. The main types of strokes are infarction and hemorrhage. The exact diagnosis and early treatment of an infarction are very important for the patient's prognosis and for the determination of the treatment direction. In this study, texture features were analyzed in order to develop a prototype auto-diagnostic system for infarction using computer auto-diagnostic software. The analysis results indicate that of the six parameters measured, the average brightness, average contrast, flatness, and uniformity show a high cognition rate whereas the degree of skewness and entropy show a low cognition rate. On the basis of these results, it was suggested that a digital CT image obtained using the computer auto-diagnostic software can be used to provide valuable information for general CT image auto-detection and diagnosis for pre-reading. This system is highly advantageous because it can achieve early diagnosis of the disease and it can be used as supplementary data in image reading. Further, it is expected to enable accurate medical image detection and reduced diagnostic time in final-reading.

• Journal of Biomedical Engineering Research
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• v.13 no.1
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• pp.69-78
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• 1992

This Paper describes implementation of a remote ECG diagnostic system using telephone line. The overall system includes ECG data acquisition system, ECG terminal, system control software, automatic diagnosis system, and transmission system.'The proposed system provides various functions, which are ECG data acquisition, transmission, receiving, diagnosis and dialogue between patients and medical doctors. Thls system is very simple and convienient to use. We evaluate the performance of modem and the accuracy of automatic diagnosis algorithm. The obtained results suggest the Possibilities of a remote ECG diagnostic system using the only existed telephone line.

• International Journal of Fuzzy Logic and Intelligent Systems
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• v.9 no.4
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• pp.301-308
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• 2009

In the modern life, machines are used for various areas in industries as the advance of science and industrial development has proceeded. In many machines, the rotating machines play an important role in many processes. Therefore, the development of fault diagnosis and monitoring system for rotating machines is required. An ubiquitous sensor network (USN) is a combination of the key computer science and engineering area technology including the wireless network, embedded system hardware and software, communication, real-time system, etc. It collects environmental information to realize a variety of functions. In this work, a data reduction algorithm for USN based remote fault diagnostic system which can be easily applied to previously built factories is proposed. To verify the feasibility of the proposed scheme, some simulations and experiments are executed.

• Journal of information and communication convergence engineering
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• v.17 no.2
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• pp.128-134
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• 2019

Based on the concept of Industry 4.0, various sensors are attached to facilities and equipment to collect data in real time and diagnose faults using analyzing techniques. Diagnostic technology continuously monitors faults or performance degradation of facilities and equipment in operation and diagnoses abnormal symptoms to ensure safety and availability through maintenance before failure occurs. In this paper, we propose a model to analyze the data and diagnose the state or failure using machine learning. The diagnosis model is based on a support vector machine (SVM)-based diagnosis model and a self-learning one-class SVM-based diagnostic model. In the future, it is expected that this model can be applied to facilities used in the entire industry by applying the actual data to the diagnostic model proposed in this paper, conducting the experiment, and verifying it through the model performance evaluation index.

• Journal of KIISE:Computing Practices and Letters
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• v.6 no.1
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• pp.82-92
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• 2000

This paper introduces an implementation of the diagnosis software for CC-NUMA systems. The CC-NUMA architecture is composed of two or more SMP nodes installed with the specialized hardware to provide cache-coherent operation and the high-speed interconnection network to connect each node, it enables both the high performance and the high scalability. While the CC-NUMA system provides the single system image in the operating system aspect, it should be considered the multiple systems by the diagnostic software. Thus it is difficult to diagnose and manage CC-NUMA system using commercial administration software due to characteristics of the complicated architecture. The remote diagnosis and management are also required with a view to reduce Total Cost of Ownership. In this paper, we design diagnostic software to manage CC-NUMA server system, and propose its mechanism in client-server manner to support remote administration. Additionally, we use the Java-based user interface to enlarge an administrator's accessibility.

• Journal of the Institute of Electronics Engineers of Korea SC
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• v.41 no.2
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• pp.53-60
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• 2004

This paper is the study for the automatic pulse-power diagnostic system to discriminate the four constitutions with the piezo-sensor module and digital signal processing hardware attached on the patient arm-neck and the statistical decision software instead of the fingers and intelligence of a traditional korean doctor. This system can be used as a important medical equipment because this automatically diagnostic system has shown the excellent performance of the 65∼76% correctness against the 50∼66% correctness which the general korean doctors with knowledge and experiences have shown. Additionally, this paper has discussed the excellent characteristics of the automatic discrimination algorithm of the four constitutions.

• Journal of the Korean Society for Railway
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• v.3 no.3
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• pp.147-153
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• 2000

The train control and monitoring system (TCMS) is an on board computer system in railway vehicles performing the control, supervisory and diagnostic functions of the complete train system. This system replaces a lot of hard-wired relays and minimizes the necessary vehicle wiring thus increasing the reliability of the train. It is also one of more important equipment on vehicle to implement much higher safety and reliability train system. We studied a software design technique of TCMS using a CASE tool that is a kind of safety critical software engineering tool (SCADE). This tool has mainly four functions such as the graphical editor, the document maker, tile automatically code generator, and the test simulator. The several functions of TCMS are implemented in this software easily programmed using a functional block diagram and a graphic programming language. We applied to automatically generated TCMS modules on the SCADE each functional block for the Standard type EMU in Korea. We performed the combination test using TCMS simulator and the running test in Seoul subway 7 Line. We proved that this technique is more useful for the software design of TCMS in urban transit

• Journal of Electrical Engineering and Technology
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• v.10 no.6
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• pp.2277-2287
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• 2015

In recent times, multilevel inverters are given high priority in many large industrial drive applications. However, the reliability of multilevel inverters are mainly affected by the failure of power electronic switches. In this paper, open-switch and short-switch failure of multilevel inverters and its identification using a high performance diagnostic system is discussed. Experimental and simulation studies were carried out on five level cascaded H-Bridge multilevel inverter and its output voltage waveforms were analyzed at different switch fault cases and at different modulation index values. Salient frequency domain features of the output voltage signal were extracted using the discrete wavelet transform multi resolution signal decomposition technique. Real time application of the proposed fault diagnostic system was implemented through the LabVIEW software. Artificial neural network was trained offline using the Matlab software and the resultant network parameters were transferred to LabVIEW real time system. In the proposed system, it is possible to precisely identify the individual faulty switch (may be due to open-switch (or) short-switch failure) of multilevel inverters.