• Structural Engineering and Mechanics
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• 제41권4호
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• pp.539-558
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• 2012

The diagnosis of bridge serviceability is carried out by a combination of in-situ visual inspection, static and dynamic loading tests and analyses. Structural health monitoring (SHM) using information technology and sensors is increasingly being used for providing a better estimate of structural performance characteristics rather than above traditional methods. Because the mechanical behavior of bridges with various kinds of damage can not be made clear, it is very difficult to estimate both the damage mode and degree of damage of existing bridges. In this paper, the sensitivity of both static and dynamic behaviors of bridges are studied as a measure of damage assessment through experiments on model bridges induced with some specified artificial damages. And, a method of damage assessment of bridges based on those behaviors is discussed in detail. Finally, based on the results, a possible application for structural health monitoring systems for existing bridges is also discussed.

• 대한인간공학회지
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• 제6권1호
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• pp.9-24
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• 1987

The design and philosophy are presented for an intelligent aid for a hyman operator who must diagnose a novel fault in a physical system. A novel fault is defined as one that the operator has not experienced in either real system operation or training. When the operator must diagnose a novel fault, deep reasoning about the behavior of the system components is required. To aid the human operator in this situation, four aiding approaches which provide useful information are proposed. The aiding information is generated by a qualitative, component-level model of the physical system. Both the aid and the human are able to reason causally about the system in a cooperative search for a diagnosis. The aiding features were designed to help the hyman's use of his/her mental model in predicting the normal system behavior, integrating the observations into the actual system behavior, or finding discrepancies between the two. The aid can also have direct access to the operator's hypotheses and run a hypothetical system model. The different aiding approaches will be evaluated by a series of experiments.

• Journal of the Korean Academy of Child and Adolescent Psychiatry
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• 제30권1호
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• pp.9-16
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• 2019

Objectives: The purpose of this study was to analyze the discriminant validity and the clinical cut off scores of the Child Behavior Checklist 1.5-5 (CBCL 1.5-5) in the diagnosis of autism spectrum disorder (ASD) and non-ASD. Methods: In total, 104 ASD and 441 non-ASD infants were included in the study. T-test, discriminant analysis, receiver operating characteristic (ROC) curve analysis, and odds ratio analysis were performed on the data. Results: The discriminant validity was confirmed by mean differences and discriminant analysis on the subscales of Emotionally reactive, Somatic complaints, Withdrawn, Sleep problems, Attention problems, Aggressive behavior, Internalizing problems, Externalizing problems, and Total problems, along with the Diagnostic and Statistical Manual of Mental Disorders (DSM)-oriented scales between the two groups. ROC analysis showed that the following subscales significantly separated ASD from normal infants: Emotionally reactive, Somatic complaints, Withdrawn, Sleep problems, Attention problems, Aggressive behavior, Internalizing problems, Externalizing problems, Total problems, and DSM pervasive developmental problems. Moreover, the clinical cut off score criteria adopted in the Korean-CBCL 1.5-5 were shown to be valid for the subscales Withdrawn, Internalizing problems, Externalizing problems, Total problems, and DSM pervasive developmental problems. Conclusion: The subscales of Withdrawn, Internalizing problems, Externalizing problems, Total problems, and DSM pervasive developmental problems significantly discriminated infants with ASD.

• 한국정밀공학회:학술대회논문집
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• 한국정밀공학회 1994년도 추계학술대회 논문집
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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.

• Journal of the Korean Academy of Child and Adolescent Psychiatry
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• 제18권2호
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• pp.97-108
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• 2007

Multiple areas of development are affected in pervasive developmental disorders(PDD), and assessments of various aspects of behavior and development are essential for diagnosis. The object of this review is to provide the practical guidelines for the assessment of core features of PDD, including abnormalities in communication, social interaction, and repetitive and stereotyped behavior. It covers the issues of differential diagnosis within and outside the PDD category, standardized diagnostic tools, assessment of intellectual and language functions, and the early diagnosis of PDD in infancy. This guideline also stresses the process of medical and neurological evaluation for proper diagnosis of PDD.

• 대한불안의학회지
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• 제5권2호
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• pp.96-102
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• 2009

Objective : We investigated that ADHD categorical diagnosis and the dimensional tools for the evaluation of ADHD, widely used in the clinical field, such as the child behavior check list- Korean version (K-CBCL), Korean personality inventory for children (KPI-C), computerized Attention Diagnostic System (ADS). Method : The DSM-IV clinical diagnosis applied by child psychiatrist. K-CBCL, KPI-C, ADS are used. Ultimately, totally 161 ADHD children and 161 controls were evaluated. Subject group are consist of 202 boys (62.7%) and 120 girls (37.3%), and the mean age was $9.5{\pm}2.0$ years old. Results and Conclusion : Social problem, and attention problem in the K-CBCL, correct response time standard deviation in the computerized ADS were statistically significant different and attention problem in the K-CBCL, hyperactivity subscale in the KPI-C were significant trait, between subject group and control group. The ROC value of attention problem in the K-CBCL, hyperactivity subscale in the KPI-C, and ADS were .78, .93, .86. Finally, we found that K-CBCL, KPI-C, ADS were significant corelation with the ADHD categorical diagnosis.

• 한국소음진동공학회논문집
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• 제16권5호
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• pp.495-502
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• 2006

A fault diagnosis method is developed in this study using automaton through quantization of vibration signals for normal and faulty conditions, respectively. Automaton is a kind of qualitative model which describes the system behaviour at the level of abstraction. The system behavior was extracted from the probability of the output sequence of vibration signals. The sequence was made as vibration levels by reconstructing the originally measured vibration signals. As an example, a fault diagnosis for the bearing of ATM machine was done, which detected the bearing fault with confident level compared to any other existing methods of kurtosis or spectrum analysis.

• 한국시스템다이내믹스연구
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• 제17권3호
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• pp.145-173
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• 2016

This study aims to develop strategic diagnosis framework of performance by identifying and analysing the dynamics of the technology commercialization ecosystem in innovative region. To achieve the purpose of this study, the systems thinking approach is used. The systems thinking approach connects feedback structure and behavior more explicitly to diagnosis vicious feedback loop in the regional technology commercialization ecosystem. In terms of an ecological point of view, it will be possible to explore dominant feedback structure and find leverages to overcome the limitations of regional technology commercialization performance. The diagnosis of reenforcing and balancing feedback structure is based on the statistical analysis of the survey data which has been collected in a cluster random sampling method, targeting on the 200 firm located in the Pangyo and Daeduk region. The results from this research showed that the regional technology commercialization ecosystem was immature and faced limit to the growth. An important finding of this study was that regional technology commercialization ecosystem need to activation of startups and reinforcement of virtuous feedback structures of technology commercialization market systems.

• Journal of Oral Medicine and Pain
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• 제47권2호
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• pp.107-108
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• 2022

Artificial intelligence (AI) refers to the use of machines to mimic intelligent human behavior. It involves interactions with humans in clinical settings, and augmented intelligence is considered as a cognitive extension of AI. The importance of AI in healthcare and medicine has been emphasized in recent studies. Machine learning models, such as genetic algorithms, artificial neural networks (ANNs), and fuzzy logic, can learn and examine data to execute various functions. Among them, ANN is the most popular model for diagnosis based on image data. AI is rapidly becoming an adjunct to healthcare professionals and is expected to be human-independent in the near future. The introduction of AI to the diagnosis and treatment of oral diseases worldwide remains in the preliminary stage. AI-based or assisted diagnosis and decision-making will increase the accuracy of the diagnosis and render treatment more precise and personalized. Therefore, dental professionals must actively initiate and lead the development of AI, even if they are unfamiliar with it.

• Asian Pacific Journal of Cancer Prevention
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• 제14권10호
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• pp.5693-5697
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• 2013

Background: Changes in the attitudes and behavior of relatives of breast cancer patients concerning cancer prevention and screening after diagnosis in a loved one were evaluated. Materials and Methods: Forty-three questions were used to collect data from the relatives of the breast cancer patients who had been living with their relatives for at least one year. Results: The study group was composed of 171 female relatives (median age: 43, range: 17-82 yr). After the patients were diagnosed with breast cancer, changes in the attitudes and behavior of their relatives toward the prevention and screening of cancer were evident in 78 (45.6%) of the study participants (e.g. eating habits, quit or reduced smoking, exercise habits). In addition, it was noted that some characteristics of the relatives had different effects on different attitudes and behavior. Conclusions: Awareness on breast cancer among the relatives of breast cancer patients is useful for the management of health and social problems that can be seen in these individuals. At the same time, this information could help countries determine whether their actual level of healthcare for early cancer diagnosis, prevention, and screening are adequate.