• Journal of Korea Multimedia Society
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• v.20 no.8
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• pp.1299-1311
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• 2017

Sounds based machine fault diagnosis recovers all the studies that aim to detect automatically faults or damages on machines using the sounds emitted by these machines. Conventional methods that use mathematical models have been found inaccurate because of the complexity of the industry machinery systems and the obvious existence of nonlinear factors such as noises. Therefore, any fault diagnosis issue can be treated as a pattern recognition problem. We present here an automatic fault diagnosis system of hand drills using discrete wavelet transform (DWT) and pattern recognition techniques such as principal component analysis (PCA) and artificial neural networks (ANN). The diagnosis system consists of three steps. Because of the presence of many noisy patterns in our signals, we first conduct a filtering analysis based on DWT. Second, the wavelet coefficients of the filtered signals are extracted as our features for the pattern recognition part. Third, PCA is performed over the wavelet coefficients in order to reduce the dimensionality of the feature vectors. Finally, the very first principal components are used as the inputs of an ANN based classifier to detect the wear on the drills. The results show that the proposed DWT-PCA-ANN method can be used for the sounds based automated diagnosis system.

• Journal of Society of Preventive Korean Medicine
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• v.15 no.1
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• pp.71-87
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• 2011

Objective : The present study is aimed at providing basic data to help oriental medical hospitals devise efficient operational plans by analyzing the medical expenses of in-patients in an oriental medical hospital and the factors affecting such expenses. Methods : PASW 18.0 was used to analyze the medical insurance program data of 929 patients who were discharged from a university oriental medical hospital(with 105 sick-beds) during the period from January 1 to December 31, 2010 after treatment under the coverage of health insurance and medical aid. Results : 1) Of all the patients hospitalized, 63.3% were females, their mean age was 52.73 years old, and 87.7% was covered by the health insurance program. The biggest number or 31.2% of the patients were treated by the department of acupuncture, 31.5% suffered mainly from the diseases of musculoskeletal system and connective tissues, and the average length of stay at the hospital was 19.49 days. 2) There were statistically significant differences in total medical expenses by age, clinical department in charge, principal diagnosis, and number of days hospitalized while daily average medical expenses differed depending on age, type of medical security, clinical department, principal diagnosis, and number of days staying at the hospital. 3) Total medical expenses were found significantly influenced by age, type of medical security, clinical department, principal diagnosis, and number of days hospitalized(explanatory power : 95.9%), whereas type of medical security, clinical department and principal diagnosis turned out to exercise significant influence on the daily average medical expenses(explanatory power : 26.9%). Conclusion : Oriental medical hospitals are suggested to make efforts to ensure geographical and economical accessibility for their main clients, the elderly and middle-aged, as well as to improve satisfaction of the clients with the medical service provided. They are also encouraged to work out systems to specialize in treatment with a focus on chronic degenerative and adult diseases. In addition, they are expected to try to enhance people's awareness of oriental medicine in an attempt to diversify the brackets of clients and increase frequency of their utilization.

• Journal of Oral Medicine and Pain
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• v.16 no.1
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• pp.33-72
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• 1991

The purpose of this study was to investigate the stress distribution and the displacement in the temporomandibular joints following the teeth loss patterns. The three dimensional finite element method was used for a mathematical model. The finite element model was composed of 1,632 elements and 2,411 nodes in the mandible with articular disc and mandibular fossa of the temporal bone. The masseter, the temporal and the internal pterygoid muscle forces were applied at each insertion site, bisecting point of gonion and antegonion, tip of the coronoid process, and gonion at the ration of 2:2:1 respectively. The directions of muscles force were obtained from frontal and lateral cephalometric tracings using bony landmarks of the skull. The results were as follows : 1. In control model, the minimum principal stresses were concentrated on the region of anterosuperior part of the condyle head and articular disc, and maximum principal stresses on the anterior part of the condyle head and posterolateral part of the articular disc. 2. In case of unilateral teeth loss, the greater principal stress appeared at the teeth loss side and the principal stresses increased at the teeth loss side as the number of the posterior teeth loss went up. 3. In case of bilateral teeth loss, the principal stresses were greater than those of the control model and as the number of the posterior teeth loss increased, the grater principal stresses on the temporomandibular joints appeared at the both side. 4. When the posterior teeth existed bilateral, the principal stress patterns were similar to those of the control model. 5. The displacement ws directed mainly upward and backward in the upper part of the temporomandibular joints and upward and forward in the largest part of the condyle head. The displacement increased as the number of the posterior teeth loss went up.

• International Journal of Safety
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• v.11 no.2
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• pp.22-25
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• 2012

This paper deals with the problem of fault diagnosis for identifying a single fault when the number of assumed faults is larger than that of predictive variables. Principal component analysis (PCA) is employed to isolate and identify a single fault. PCA is a method to extract important information as reducing the number of large dimension in a process. The patterns of all assumed faults can be recognized by PCA and these can be employed whether a new fault is one of predefined faults or not. Through PCA, empirical models for analyzing patterns can be trained. When a single fault occurs, the pattern generated by PCA can be obtained and this is used to identify a fault. The performance of the proposed approach is illustrated in the actuator benchmark problem.

• Korean Chemical Engineering Research
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• v.46 no.2
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• pp.383-388
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• 2008

The safe and efficient operation of the chemical processes has become one of the primary concerns of chemical companies, and a variety of fault diagnosis methods have been developed to diagnose faults when abnormal situations arise. Recently, many research efforts have focused on fault diagnosis methods based on quantitative history data-based methods such as statistical models. However, when the history data-based models trained with the data obtained on an operation mode are applied to another operating condition, the models can make continuous wrong diagnosis, and have limits to be applied to real chemical processes with various operation modes. In order to classify operation modes of chemical processes, this study considers three multivariate models of Euclidean distance, FDA (Fisher's Discriminant Analysis), and PCA (principal component analysis), and integrates them with process dynamics to lead dynamic Euclidean distance, dynamic FDA, and dynamic PCA. A case study of the TE (Tennessee Eastman) process having six operation modes illustrates the conclusion that dynamic PCA model shows the best classification performance.

• Smart Structures and Systems
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• v.17 no.6
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• pp.1031-1053
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• 2016

The health conditions of in-service civil infrastructures can be evaluated by employing structural health monitoring technology. A reliable health evaluation result depends heavily on the quality of the data collected from the structural monitoring sensor network. Hence, the problem of sensor fault diagnosis has gained considerable attention in recent years. In this paper, an innovative sensor fault diagnosis method that focuses on fault detection and isolation stages has been proposed. The dynamic or auto-regressive characteristic is firstly utilized to build a multivariable statistical model that measures the correlations of the currently collected structural responses and the future possible ones in combination with the canonical correlation analysis. Two different fault detection statistics are then defined based on the above multivariable statistical model for deciding whether a fault or failure occurred in the sensor network. After that, two corresponding fault isolation indices are deduced through the contribution analysis methodology to identify the faulty sensor. Case studies, using a benchmark structure developed for bridge health monitoring, are considered in the research and demonstrate the superiority of the new proposed sensor fault diagnosis method over the traditional principal component analysis-based and the dynamic principal component analysis-based methods.

• Journal of the korean veterinary medical association
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• v.13 no.3
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• pp.169-184
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• 1977

• The Journal of the Korea Contents Association
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• v.11 no.11
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• pp.185-193
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• 2011

There is no exact standard of detecting pulmonary tuberculosis(TB) in digital image of simple chest radiography. In this study, I experimented on the principal components analysis(PCA) algorithm in the past and suggested six other parameters as identification of TB lesions. The purpose of this study was to develop and test computer aided diagnosis(detection) method for the detection and measurement of pulmonary abnormalities on digital chest radiography. It showed comparatively low recognition diagnosis rate using PCA method, however, six kinds of texture features parameters algorithm showed similar or higher diagnosis rates of pulmonary disease than that of the clinical radiologists. Proposed algorithms using computer-aided of texture analysis can distinguish between areas of abnormality in the chest digital images, differentiate lesions having pulmonary disease. The method could be useful tool for classifying and measuring chest lesions, it would play a major role in radiologist's diagnosis of disease so as to help in pre-reading diagnosis and prevention of pulmonary tuberculosis.

• Health Policy and Management
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• v.7 no.1
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• pp.100-124
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• 1997

In order to suggest the strategies for participation in the PPS(Prospective Payment System), analyses were performed based on variations in utilization pattern and changes in revenues of hospitals in 10 selected KDRGs. The data was collected from the claims data of a tertiary hospital in Kyunggido from September 1, 1995 to August 31, 1996. The studies consisted of 1, 718 inpatients diagnosed for lens procedures, tonsilectomy &/or adenoidectomy, appendectomy with complicated principal diagnosis, Cesarean section, or vaginal delivery without any complications. The resources used in each KDRG were measured including average length of stay, total charges, number of orders, intensity of medical services, frequencies of medical services, the rate of non-reimbursable charges, and the rate of non-reimbursable orders. Then, the changes in hopital revenues due to the composition of medical fee schedules under the PPS were estimated as follows: 1) The variations in average lenght of stay, total charges, number of orders, the intensity of medical services, the frequency of medical services, the rate of non-reimbursable charges, and the rate of non-reimbursable orders among the 10 KDRGs were comparatively small. 2) The average lenght of stay was the longest(6.0 days) for appendectomy with complicated principal diagnosis, while it was the shortest(2.1 days) for two vaginal deliveries. Statistically differences existed in the average length of stay among physicians and among the dates of admission in several KDRGs. 3) The total charges were the highest for lens procedures(1, 716, 000 won), while the lowest charges were for two vaginal deliveries(558, 000 won). Statistically differences in the total charges were found among physicians in several KDRGs: however, there were no differences with the dates of admission. 4) The number of orders was the greatest(155) for appendectomy with complicated principal diagnosis, while it was the smallest(75) for the two vaginal deliveries. Statistical differences in the number of orders did not exist among physicians in the KDRGs. 5) Significant differences were found in the intensity of medical services, and in the frequency of medical services among physicians in the KDRGs. 6) The rate of non-reimbursable charges for each KDRG was not related to the rate of non-reimbursable orders. The rate of non-reimbursable orders was the highest(36.0%) for lens procedures, while the lowest rate(11.6%) was for appendectomy with complicated principal diagnosis. The rate of non-reimbursable charges was the highest(39.4-39.7%) for vaginal deliveries, while the lowest rate(13.1%) was for tonsillectomy &/or adenoidectomy(<17 ages). 7) If the physician's practicing style were not change under the PPS, the hospital revenuses could be increased by 10%, and the portion of patient payment could be decreased by 1.4-22.4%. However, the non-reimbursable charges for showed little change between two reimbursement systems. Based upon the above findings, this hospital could be eligible for participation in the PPS(Prospective Payment Systm). However, the process of diagnosis and treatment should be standardized, inentifying methods to reduce cost and to assure quality of medical care. Furthermore, consideration should be given to finding ways to increase patient volume.

• The Journal of Korea Institute of Information, Electronics, and Communication Technology
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• v.16 no.6
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• pp.526-532
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• 2023

Falls are fatal accidents that occur more than 420,000 times a year worldwide. Therefore, to study patients with falls, we found the association between extrinsic injury codes and principal diagnosis S-codes of patients with falls, and developed a prediction model to predict extrinsic injury codes based on the data of principal diagnosis S-codes of patients with falls. In this study, we received two years of data from 2020 and 2021 from Institution A, located in Gangneung City, Gangwon Special Self-Governing Province, and extracted only the data from W00 to W19 of the extrinsic injury codes related to falls, and developed a prediction model using W01, W10, W13, and W18 of the extrinsic injury codes of falls, which had enough principal diagnosis S-codes to develop a prediction model. 80% of the data were categorized as training data and 20% as testing data. The model was developed using MLP (Multi-Layer Perceptron) with 6 variables (gender, age, principal diagnosis S-code, surgery, hospitalization, and alcohol consumption) in the input layer, 2 hidden layers with 64 nodes, and an output layer with 4 nodes for W01, W10, W13, and W18 exogenous damage codes using the softmax activation function. As a result of the training, the first training had an accuracy of 31.2%, but the 30th training had an accuracy of 87.5%, which confirmed the association between the fall extrinsic code and the main diagnosis S code of the fall patient.