• The Journal of Pediatrics of Korean Medicine
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• v.20 no.2
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• pp.147-175
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• 2006

Objective : This study is to investigate the method for assesment and diagnosis of ADHD, especially focusing on behavior rating scales. Methods : We searched the recent date of the publication and paper in ADHD. Results : For Assesment and Diagnosis of ADHD, various method such as interview with parents, child and teacher, behavior observation, behavior rating scales and neuropsychological test are used. The structured interview consists of the restrictive questions and response, and then have diagnostic algorithm, consequently can be used by untrained clinicians. Of the structured interview, standardization of K-SADS in Korean version is finished. Behavior rating scales, the form of parent, teacher and self-report questionnaires, are used as diagnosis and treatment evaluation of ADHD. Behavior rating scales consist of both ADHD-specific scales and broad-band scales designed to screen for various symptoms (including ADHD symptoms). ADHD-specific scales are useful in differential diagnosis, discrimination of subtype, treatment evaluation, However, broad-band scales are useful in preliminary examination. The neuropsychological tests can evaluate attention deficit and effect of attention deficit on cognitive function and academic performance. The neuropsychological tests also used in diagnosis and treatment evaluation of ADHD. Conclusion : For Assesment and Diagnosis of ADHD, various method are used, especially behavior rating scales are both useful and simple tool for diagnosis and treatment evaluation.

• The Journal of the Korea Contents Association
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• v.14 no.8
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• pp.150-155
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• 2014

This study explored the police organizational health diagnosis index development. and the ultimate purpose of this study is to suggest the ways for the police to develop the police organizational health diagnosis index and then to raise the organizational effectiveness. A police organizational health diagnosis index comprises three categories; Organizational Behavior, Group Behavior, and Individual Behavior. A Organizational Behavior questionnaire comprises five categories; Organizational Structure, Organizational atmosphere, Environmental Compliance, Transformational Leadership, and Communication & decision-making. Secondly, A Group Behavior questionnaire comprises five categories; How to manage the personnel, Conflict management style, Group cohesion, Vision and Strategy, and Community-oriented & shared responsibility. Thirdly, An Individual Behavior questionnaire comprises five categories; Job Motivation, work-related factors, Trust, Vitality, and Organizational Cynicism. This author expects this study to contribute to the development of an adequate measuring instrument of the police organizational health diagnosis index.

• Journal of Institute of Control, Robotics and Systems
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• v.10 no.5
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• pp.450-457
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• 2004

In this research, the automatic synthesis of knowledge models is proposed. which are the basis of the methods using qualitative models adapted widely in fault diagnosis and hazard evaluation of chemical processes. To provide an easy and fast way to construct accurate causal model of the target process, the Role-Behavior modeling method is developed to represent the knowledge of modularized process units. In this modeling method, Fault-Behavior model and Structure-Role model present the relationship of the internal behaviors and faults in the process units and the relationship between process units respectively. Through the multiple modeling techniques, the knowledge is separated into what is independent of process and dependent on process to provide the extensibility and portability in model building, and possibility in the automatic synthesis. By taking advantage of the Role-Behavior Model, an algorithm is proposed to synthesize the plant-wide causal model, Fault-Causality Graph (FCG) from specific Fault-Behavior models of the each unit process, which are derived from generic Fault-Behavior models and Structure-Role model. To validate the proposed modeling method and algorithm, a system for building FCG model is developed on G2, an expert system development tool. Case study such as CSTR with recycle using the developed system showed that the proposed method and algorithm were remarkably effective in synthesizing the causal knowledge models for diagnosis of chemical processes.

• Structural Engineering and Mechanics
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• v.57 no.3
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• pp.529-541
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• 2016

Under the interaction between dam body, dam foundation and external environment, the dam structural behavior presents the time-varying nonlinear characteristics. According to the prototypical observations, the correct identification on above nonlinear characteristics is very important for dam safety control. It is difficult to implement the description, analysis and diagnosis for dam structural behavior by use of any linear method. Based on the rescaled range analysis approach, the algorithm is proposed to identify and extract the fractal feature on observed dam structural behavior. The displacement behavior of one actual dam is taken as an example. The fractal long-range correlation for observed displacement behavior is analyzed and revealed. The feasibility and validity of the proposed method is verified. It is indicated that the mechanism evidence can be provided for the prediction and diagnosis of dam structural behavior by using the fractal identification method. The proposed approach has a high potential for other similar applications.

• Journal of the Korean Academy of Child and Adolescent Psychiatry
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• v.22 no.2
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• pp.95-102
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• 2011

Objectives : This present study examined the power of the Korean Child Behavior Checklist (K-CBCL) subscales to predict a DSM-IV diagnosis of oppositional defiant disorder (ODD). Methods : The sample included 37 children and adolescents with ODD and 46 normal controls. The participants and their parents were interviewed for clinical diagnosis using the Kiddie-Schedule for Affective Disorders and Schizophrenia-Present and Lifetime Version (K-SADS-PL) and the parents completed the K-CBCL. Logistic regression analysis was used to predict the diagnosis of ODD. Results : Among the CBCL subscales, Delinquent and Aggressive Behavior scales significantly predicted ODD diagnosis. The means of these CBCL subscales were significantly higher in the ODD group when compared to the controls. Conclusion:Two CBCL subscales (Deliquent and Aggressive Behavior) displayed good diagnostic efficiency for assessing ODD in children and adolescents. Through combining information from the CBCL, an empirical-quantitative approach to psychopathology in children and the DSM-IV diagnostic criteria, the results demonstrated that a clinical diagnostic approach is an effective diagnostic paradigm for children with ODD.

• Journal of the Institute of Electronics and Information Engineers
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• v.51 no.6
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• pp.175-182
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• 2014

Development of an objective diagnosis index for diagnosing a the beginning nature of a disease is the most one of tongue diagnosis in the oriental medicine. However, previous systems have a difficult problem in the creation of objective diagnosis index, and focused on the expert system that can diagnose automatically without an oriental doctor behavior. Therefore, computerized assistant diagnosis software for calculating an optimized diagnosis index is proposed in this paper. This software is operated by the diagnosing behavior of oriental doctor. As developed software is a semi-automatic system, manual method is used to segment a tongue body. Futhermore, numerical diagnosis indices including the color information of non-tongue coating and tongue coating, WTCI are provided to oriental doctor automatically and real-timely. Also, probability estimation value for classifying no coating, thin coating, and thick coating is presented by using the tongue coating area ratio, and EMR chart can use for convenience of diagnosis. In order to evaluate the effectiveness of the our developed software, after building a various tongue image from 60 subjects, we experimented on diagnosis image with our software. As a result, the developed software showed the 95% use-effectiveness of subjects.

• Asian Pacific Journal of Cancer Prevention
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• v.14 no.7
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• pp.4373-4377
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• 2013

Background: The majority of cervical cancers, the most prevalent cancer among Nepali women, are diagnosed in advanced stage leading to high mortality in Nepal. The present study explored factors associated with late diagnosis. Materials and Methods: A cross-sectional study was carried out in two specialized cancer hospitals of Nepal from August 12 to October 12, 2012. Randomly selected 110 cervical cancer patients were interviewed and their medical records were reviewed. Multivariate logistic regression analysis was performed to predict associations. Results: Mean age of patients was 52.7years (SD=10.6), 66% were illiterate and 77% were rural inhabitants. Medical shops (33.6%) and private hospitals (31%) were major first contact points of patients with health care providers (HCP). There was no cervical/per-speculum examination (78.2%) and symptoms misinterpretation (90%) of patients occurred in initial consultation with HCP. Four in every five cases (80.9%) of cervical cancer had late diagnosis. Literate women (adjusted OR=0.121, CI: 0.030-0.482) and women having abnormal vaginal bleeding as early symptom (adjusted OR=0.160, CI: 0.035-0.741) were less likely to suffer late diagnosis. Women who shared their symptoms late (adjusted OR=4.272, CI: 1.110-16.440) and did so with people other than their husband (adjusted OR=12.701, CI: 1.132-142.55) were more likely for late diagnosis. Conclusions: High level of illiteracy among women and their problematic health seeking behavior for gynecological symptoms are responsible for late diagnosis of cervical cancer in Nepal. In the absence of a routine screening program, prevention interventions should be focused on raising awareness of gynecological symptoms and improving health seeking behavior of women for such symptoms.

• 제어로봇시스템학회:학술대회논문집
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• 1997.10a
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• pp.1428-1431
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• 1997

This paper presents an efficient fault diagnosis methodology for lare chemical processes. The methodology is based on a two-tier strategy, When a falt occurs in a process, a top tier identifies the sector (process part or unit) that may contain the fault(s). Afterwards, a bottom tier or lower level evaluates the suspicious sector. The process modeling methodology based on functionality-behavior relations of process units, is proposed and utilized in the top-tier. This methodology models a target process as sequences of functions and variables and their relations. In the bottom tier, each sector has a dedicated diagostic module, which is tailored to the available information or models of the sector. For the sectors selected in the top-tier diagnosis, each diagnostic module is executed to identify the actual faults within the sector. Teh utility of the methodology is illustrated in the diagnosis of the CSTR with heat exchanger.

• Journal of information and communication convergence engineering
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• v.19 no.1
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• pp.29-35
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• 2021

While the population of pet dogs and pet-related markets are increasing, there is no convenient and reliable tool for pet health monitoring for pet owners/caregivers. In this paper, we propose a mobile platform-based pre-diagnosis system that pet owners can use for pre-diagnosis and obtaining information on coping strategies based on their observations of the pet dog's abnormal behavior. The proposed system constructs symptom-disease association databases for 100 frequently observed diseases under veterinarian guidance. Then, we apply the possibilistic fuzzy C-means algorithm to form the "probable disease" set and the "doubtable disease" set from the database. In the experiment, we found that the proposed system found almost all diseases correctly, with an average of 4.5 input symptoms and outputs 1.5 probable and one doubtable disease on average. The utility of this system is to alert the owner's attention to the pet dog's abnormal behavior and obtain an appropriate coping strategy before consult a veterinarian.

• Asian Pacific Journal of Cancer Prevention
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• v.14 no.10
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• pp.5769-5773
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• 2013

Background: This is a descriptive study to determine whether coursework that is focused on early diagnosis in cancer makes a difference in self-reported health promoting lifestyle behavior of students who study health management. Materials and Methods: The population of the study consisted of a sample of 104 students enrolled in the Department of Health Management at the Faculty of Health in Kirikkale University in Turkey. Forty-eight students enrolled in a course called "Early Diagnosis of Cancer" and fifty-six did not take this course. Demographic information was collected and the "Health Promotion Life-Style Profile (HPLP)" was used to collect health promotion data. Frequency and descriptive statistics including one-way ANOVA, Mann-Whitney U test, Kruskal Wallis tests were used to evaluate data. Results: The HPLP mean score of the students was found to be $127.5{\pm}17.45$. The highest mean score was observed for self-fulfillment and health responsibility, while the lowest was for diet and exercise sub-scales. It was found that certain variables were effective in developing health promoting lifestyle behaviors such as choosing this job voluntarily, working status of father and participation in social activity (p<0.05). In conclusion, it was found that the students had moderate levels of health promoting lifestyle behavior and they should be supported in terms of diet and exercise.