• Tribology and Lubricants
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• v.16 no.6
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• pp.461-468
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• 2000

In this study, a neural network based diagnostic system of a rotating spindle system supported by ball bearings was introduced. In order to create actual failure situations, two exemplary abnormal status were made. Out of several possible data source locations, ten measurement spots were chosen. In order to discriminate multiple abnormal status, a neural network system was introduced using back propagation algorithm updating connecting weight between each nodes. In order to find the optimal structure of the neural network system reducing the information sources, magnitude of the weight of the network was referred. Hinton diagram was used to visually inspect the least sensitive weight connecting between input and hidden layers. Number of input node was reduced from 10 to 7 and prediction rate was increased to 100%.

• Proceedings of the KSR Conference
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• 2004.06a
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• pp.1422-1424
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• 2004

Various deterioration diagnostic techniques and devices are suggested, and most of which measure leakage current components as an indicator of arrester ageing. However, the techniques based on the magnitude of leakage current measure simply RMS or peak value of leakage current components and do not provide detailed information needed in the diagnosis. In this study, we found that the phase vs. wave height of total leakage current is changed or a new wave height is produced with arrester ageing. To complete the new technique, we designed an arrester diagnostic device which is composed of a current detection circuit, an optical transmission circuit, and an analysis program. After measurement of the total leakage current, magnitudes, phase vs. wave height, and harmonics of the leakage current components are analyzed by the microprocessor based device. From the experimental results, we confirmed that the device can measure most parameters needed for the arrester diagnostics and analyze an initial deterioration state.

• Journal of Korean Society of Industrial and Systems Engineering
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• v.26 no.2
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• pp.23-28
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• 2003

This research explains visualization of diagnostic system of 3D CAD data, IGES (Initial Graphics Exchange Specification), by using JNI(Java Native Interface) to connect between C++ and Java programming. The diagnostic system is to analyze IGES clearly by identifying errors and anomalies with respect to the diagnosis of geometry and topology of entities. The output of the system is IGES file including . error information which can be visualized with different colors by several commercial visualization systems. The paper focuses on the visualization of the result IGES which can be extended to web based application over internet.

• 전자공학회논문지 IE
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• v.46 no.3
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• pp.62-67
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• 2009

In this paper, ROC curves were designed by using Fuzzy Logic Systems. ROC curve is used for diagnostic evaluation and the person evaluating ROC curve is chosen as a first-level diagnostician. For rating diagnostic capability on ROC curve through learning, the chest X-ray image is used. The images used for making a diagnosis are X-ray film being both noise and signal. The result over diagnostic capability difference between the male and the female represented a man had better than a woman but that difference can be ignored.

• Clinical and Experimental Pediatrics
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• v.50 no.2
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• pp.127-131
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• 2007

Fever of unknown origin (FUO) has been a convenient term used to classify patients who warrant a particular systemic approach to diagnostic evaluation and management. The greatest clinical concern in evaluating FUO is identifying patients whose fever has a serious or life-threatening cause when a delay in diagnosis could jeopardize successful intervention. Thorough history and complete physical examination are critical to uncover the etiologic diagnosis. Most cases of FUO in children are caused by atypical presentations of common diseases rather than by typical manifestations of rare disorders. Selection of diagnostic tests and speed of investigation should be guided by a knowledge of the disease severity, patient age, epidemiologic and geographic information, and any positive findings from a detailed history and physical examination. The three most common causes of FUO in children are infectious diseases, connective tissue diseases, and malignancy. In general, the prognosis of FUO in children is better than that of adults. Although the outcome is dependent on the primary disease process, fever abates spontaneously in most cases in whom the cause of fever remains unclear.

• Proceedings of the Korean Society for Noise and Vibration Engineering Conference
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• 2002.05a
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• pp.387-392
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• 2002

A portable mould oscillation analyzer with an integrated computer, developed by POSCO, records the movement of the mould in every spatial direction. The system uses the gap sensors to measure the mould movement (displacement) in two horizontal directions according to the mould narrow and broad faces and the vertical strokes in the four corners of mould. The gap sensor is a non-contacting minute displacement-measuring device using the principle of high frequency eddy current loss. The mould oscillation diagnostic system integrates the gap sensors, their converters and the industrial portable computer with plug-in data acquisition boards. In an own expert module, which is included in the diagnosis program, one can obtain much information about the mould oscillation equipment.

• Journal of radiological science and technology
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• v.14 no.2
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• pp.27-31
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• 1991

• Journal of the Korean Institute of Telematics and Electronics
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• v.27 no.9
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• pp.1351-1363
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• 1990

In this paper, a reliable control system structured with dual CPU modules and dual I/O modules is implemented as a means of achieving a highly reliable fault tolerant control system. For this, faults in the system modules are first examined, and a fault detection technique consisting of self diagnostic, comparison process, and exception processing is applied. Self diagnostic is used to locate which components in the modules have been failed, while comparison process is to cmpare control outputs computed by both CPU modules and protect the plant from malfunction by blocking failed control outputsin advance. Finally exception processing is used to determine the faults that are not detected immediately by the self diagnostic and comparison process, e.g. bus error processing when acknowledge signal for data transfer is not activeted in the I/O modules. Also reliability analysis is conducted for the discrete time Markov model with dual structure. It is shown quantitatively that the reliability is improved in the control system with dual structure in comparison with a system with single module structure.

• Journal of Korea Multimedia Society
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• v.25 no.10
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• pp.1512-1523
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• 2022

Artificial intelligence application in digital health care has been increasing with its development of artificial intelligence. The convergence of the healthcare industry and information and communication technology makes the diagnosis of diseases more simple and comprehensible. From the perspective of medical services, its practice as an initial test and a reference indicator may become widely applicable. Therefore, analyzing the factors that are the basis for existing diagnosis protocols also helps suggest directions using artificial intelligence beyond previous regression and statistical analyses. This paper conducts essential diagnostic prediction learning based on the analysis of blood cancer factors reported previously. Blood cancer diagnosis predictions based on artificial intelligence contribute to successfully achieve more than 90% accuracy and validation of blood cancer factors as an alternative auxiliary approach.

• Journal of the Korean Society of Food Culture
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• v.28 no.3
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• pp.282-292
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• 2013

The purpose of this study is to identify a suitable organizational diagnostic model for analyzing the management efficiency of food service firms. We used the three-iteration Delphi technique on a panel of 19 business employees, 7 industry experts, and 4 employees in the food service industry. A total of 36 assessment indicators were developed through this panel, with numerous major findings. First, it is important to evaluate the leadership qualities of employees in terms of their motivation and competency. Second, it is important to evaluate the ability of employees to interface well with other employees. Third, it is important to evaluate and manage the brand image recognized by customers. Fourth, it is important to evaluate the fairness and regularity of the rewards given for an excellent job performance. Fifth, it is important to evaluate the level of communication and information distribution in the organizational culture. Last, but not least, it is important to evaluate the transparency and fairness of an organization in its human resource management (HRM) and the efficiency of its organizational structure. In conclusion, this study empirically shows how food service firms can develop an organizational diagnostic model to increase their managerial efficiency.