• Transactions of the Korean Society of Automotive Engineers
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• v.10 no.3
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• pp.151-158
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• 2002

Automotive engineers involved in a new car project use various CAD systems that are chosen based on work requirements. For example, engineers in Hyundai Motors are using Pro/Designer and Alias fur the style design, but they use CATIA to design parts and assemblies, ANSYS for FEM analysis, and Pro/Engineer to design engines. Because they use different CAD systems, they have difficulties in collaborative design. Data, which contains errors, is transferred between CAD systems. It is difficult to find out such errors in a large CAD model. An evaluation method for CAD models has been developed in this study. This diagnosis tool analyses a STEP or an IGES file generated from a CAD system, and produces a quantitative error report. The tool has been tested with actual data sets. This paper proposes an algorithm that produces mathematical error values of entities of IGES models that have geometrical data, and entities of STEP models that have topological data, and inspects every part off model. To develop this system, we have used the OpenCASCADE kernel, which is an open source kernel developed by Matra Datavision of France.

• Journal of Institute of Control, Robotics and Systems
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• v.3 no.5
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• pp.520-525
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• 1997

This paper presents a fault detection and diagnosis methodology based on weighted symptom model and pattern matching between the coming fault propagation trend and the simulated one. In the first step, backward chaining is used to find the possible cause candidates for the faults. The weighted symptom model is used to generate those candidates. The weight is determined from dynamic simulation. Using WSM, the methodology can generate the cause candidates and rank them according to the probability. Second, the fault propagation trends identified from the partial or complete sequence of measurements are compared with the standard fault propagation trends stored a priori. A pattern matching algorithm based on a number of triangular episodes is used to effectively match those trends. The standard trends have been generated using dynamic simulation and stored a priori. The proposed methodology has been illustrated using two case studies, and the results showed satisfactory diagnostic resolution.

• Asian Pacific Journal of Cancer Prevention
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• v.15 no.18
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• pp.7935-7940
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• 2014

This research was planned to reveal society's attitude towards cancer and early diagnosis using the health belief model. This study was planned as descriptive research in Isparta. A random sample of n=256 individuals of both genders was recruited at the largest shopping center. As a means of collection tool, a survey consisted of two forms, the first designed for sociodemographic information and the second covering 29 questions suitable for the content of Health Belief Model. Of the participants, 66.8% were female and 33.2% were male, and the average age was $33.3{\pm}11.0$ years. Some 46.1% partly thought that they may develop cancer, and 49.6% were afraid of this possibility. As many as 50% indicated that cancer is an issue that comes from Allah. A significant difference was found between not going for control unless feeling bad, and blood analysis for cancer screening (${\chi}^2=3.780$ p= 0.03). It was seen that in an area with a high rate of cancer, people's awareness of cancer prevention and early diagnosis and attitudes towards these are insufficient.

• Transactions of the Korean Society for Noise and Vibration Engineering
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• v.25 no.9
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• pp.637-643
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• 2015

In recent years, pattern recognition methods have been widely used by many researchers for fault diagnoses of mechanical systems. The soundness of a mechanical system can be checked by analyzing the variation of the system vibration characteristic along with a pattern recognition method. Recently, the hidden Markov model has been widely used as a pattern recognition method in various fields. In this paper, the hidden Markov model is employed for the fault diagnosis of the mass unbalance of a rotating system. Mass unbalance is one of the critical faults in the rotating system. A procedure to identity the location and size of the mass unbalance is proposed and the accuracy of the procedure is validated through experiment.

• International Journal of Computer Science & Network Security
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• v.21 no.3
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• pp.83-93
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• 2021

COVID-19 poses a major risk to global health, highlighting the importance of faster and proper diagnosis. To handle the rise in the number of patients and eliminate redundant tests, healthcare information exchange and medical data are transmitted between healthcare centres. Medical data sharing helps speed up patient treatment; consequently, exchanging healthcare data is the requirement of the present era. Since healthcare professionals share data through the internet, security remains a critical challenge, which needs to be addressed. During the COVID-19 pandemic, computed tomography (CT) and X-ray images play a vital part in the diagnosis process, constituting information that needs to be shared among hospitals. Encryption and image steganography techniques can be employed to achieve secure data transmission of COVID-19 images. This study presents a new encryption with the image steganography model for secure data transmission (EIS-SDT) for COVID-19 diagnosis. The EIS-SDT model uses a multilevel discrete wavelet transform for image decomposition and Manta Ray Foraging Optimization algorithm for optimal pixel selection. The EIS-SDT method uses a double logistic chaotic map (DLCM) is employed for secret image encryption. The application of the DLCM-based encryption procedure provides an additional level of security to the image steganography technique. An extensive simulation results analysis ensures the effective performance of the EIS-SDT model and the results are investigated under several evaluation parameters. The outcome indicates that the EIS-SDT model has outperformed the existing methods considerably.

• Journal of IKEEE
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• v.25 no.3
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• pp.548-555
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• 2021

This paper outlines the basic concepts, approaches and research trends of fault diagnosis and fault tolerant control applied to industrial processes, facilities, and motor drives. The main role of fault diagnosis for industrial processes is to create effective indicators to determine the defect status of the process and then take appropriate measures against failures or hazadous accidents. The technologies of fault detection and diagnosis have been developed to determine whether a process has a trend or pattern, or whether a particular process variable is functioning normally. Firstly, data-driven based and model-based techniques were described. Secondly, fault detection and diagnosis techniques for industrial processes are described. Thirdly, passive and active fault tolerant control techniques are considered. Finally, major faults occurring in AC motor drives were listed, described their characteristics and fault diagnosis and fault tolerant control techniques are outlined for this purpose.

• Transactions of the Korean Society for Noise and Vibration Engineering
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• v.13 no.1
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• pp.48-55
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• 2003

Hidden Markov Model(HMM) has a doubly embedded stochastic process with an underlying stochastic process that can be observed through another set of stochastic processes. This structure of HMM is useful for modeling vector sequence that doesn't look like a stochastic process but has a hidden stochastic process. So, HMM approach has become popular in various areas in last decade. The increasing popularity of HMM is based on two facts : rich mathematical structure and proven accuracy on critical application. In this paper, we applied continuous HMM (CHMM) approach with AR coefficient to detect and predict the chatter of lathe bite and to diagnose the wear of oil Journal bearing using rotor shaft displacement. Our examples show that CHMM approach is very efficient method for machine health monitoring and prediction.

• Asian Pacific Journal of Cancer Prevention
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• v.17 no.sup3
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• pp.5-10
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• 2016

Breast cancer, the second cause of cancer-related death after lung cancer and the most common cancer in women after skin cancer, is curable if detected in early stages of clinical presentation. Knowledge as to any age cut-off points which might have significance for prognostic groups is important in screening and treatment planning. Therefore, determining a change-point could improve resource allocation. This study aimed to determine if a change point for survival might exist in the age of breast cancer diagnosis. This study included 568 cases of breast cancer that were registered in Breast Cancer Research Center, Tehran, Iran, during the period 1986-2006 and were followed up to 2012. In the presence of curable cases of breast cancer, a change point in the age of breast cancer diagnosis was estimated using a mixture survival cure model. The data were analyzed using SPSS (versions 20) and R (version 2.15.0) software. The results revealed that a change point in the age of breast cancer diagnosis was at 50 years age. Based on our estimation, 35% of the patients diagnosed with breast cancer at age less than or equal to 50 years of age were cured while the figure was 57% for those diagnosed after 50 years of age. Those in the older age group had better survival compared to their younger counterparts during 12 years of follow up. Our results suggest that it is better to estimate change points in age for cancers which are curable in early stages using survival cure models, and that the cure rate would increase with timely screening for breast cancer.

• Proceedings of the Korean Society of Broadcast Engineers Conference
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• 1997.06a
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• pp.61-66
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• 1997

For constructing an intelligent multimedia database system for medical diagnosis, we are focusing on two technological points. One is a retrieval algorithm of databases, and the other is a coding algorithm of multimedia contents. For the first, previously we proposed a front-end database preprocessor called“keyword-network”, and in this paper we present its extended model providing an intelligent logical AND searching function especially for medical differential diagnosis. For the second, we present examples of multimedia intellectual coding methods for cardiovascular examination records.

• Proceedings of the KIEE Conference
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• summer
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• pp.1278-1280
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• 2004

In this paper, we propose a new diagnosis method of DC/DC converter aging. The method is based on the variations of parasitic resistor for the aging process. We apply an on-line diagnosis of DC/DC converter because the observation is not a device, but a system. This study proposes a method of DC/DC converter diagnosis by analyzing the variations of model on the variations of parasitic resistor.