• Journal of the Korean Academy of Child and Adolescent Psychiatry
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• v.22 no.1
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• pp.38-43
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• 2011

Chronic tic disorder or Tourette syndrome is known to be a chronic neuro-behavioral disease for which cognitive behavioral therapy (CBT) strategies have recently been introduced. Here, we report the effectiveness of CBT in a case of childhood chronic tic disorder, which is very common in clinical settings. The DSM-IV clinical diagnosis was applied by a child psychiatrist. The Yale Global Tic Severity Scale, Kovac's children's depression inventory, Spielberger State-Trait Anxiety Inventory, Abbreviated Conners' Rating Scales, and the Dupaul ADHD Rating Scales were used. This case involved a pharmacological treatment-refractory patient over the previous year. Thus, psychiatric consultation was undertaken. Subsequently, we administered five sessions of CBT for four weeks, consisting of symptom evaluation and planning, habit reversal training, and ventilation training. Following four weeks of CBT administration, there were improvements in the scores of the Yale Global Tic Severity Scale and the Clinical Global Improvement scale. Our observations indicate that CBT may be effective in the treatment of childhood tic disorder.

• Nuclear Engineering and Technology
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• v.44 no.4
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• pp.379-386
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• 2012

A symptom-based procedure with a critical safety function monitoring system has been established to reduce the operator's diagnosis and cognitive burden since the Three-Mile Island (TMI) accident. However, it has been reported that a symptom-based procedure also requires an operator's cognitive efforts to cope with off-normal events. This can be caused by mismatches between a static model, an emergency operating procedure (EOP), and a dynamic process, the nature of an ongoing situation. The purpose of this study is to share the evidence of mismatches that may result in an excessive cognitive burden in conducting EOPs. For this purpose, we analyzed simulated emergency operation records and observed some operator behaviors during the EOP operation: continuous steps, improper description, parameter check at a fixed time, decision by information previously obtained, execution complexity, operation by the operator's knowledge, notes and cautions, and a foldout page. Since observations in this study are comparable to the results of an existing study, it is expected that the operational behaviors observed in this study are generic features of operators who have to cope with a dynamic situation using a static procedure.

• Proceedings of the Korean Institute of Information and Commucation Sciences Conference
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• 2022.05a
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• pp.12-14
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• 2022

One of the most negative social changes of the last decade is population aging which leads to 19 times more patients with Mild Cognitive Disorder(MCI). It is well established that MCI is the most important state that can prevent dementia with early diagnosis and intervention. However, the social security system for patients with dementia is not working properly due to the coronavirus pandemic and the limited human power. This article proposes design principles for dementia training programs of extended reality devices. and The findings in this study provide a guide for considering the cognitive and physical and social functions of patients.

• Korean Management Science Review
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• v.15 no.2
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• pp.161-175
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• 1998

As organizations have come to be more complex and diverse, management has come to spend an increasing proportion of its time and efforts in handling organization conflict. Moreover, organizational conflict problems are often not recognized until the balance of interests is destroyed or a radical organizational change such as BPR takes place. Once an organizational conflict arises, however, it reduces corporate synergy seriously, leading to organizational ineffectiveness. Therefore, it is important to identify the cause of organizational conflict in advance and resolve it based on the proper diagnosis as early as possible lest it should undermine the organizational effectiveness. We propose a method that facilitates diagnosing potential organizational conflict and determining appropriate strategy to the conflict, based on the analysis of cognitive maps. To support the application of the method in the real world context, a computerized tool is introduced. The working procedures of the method and the features of the tool are illustrated with their application to the real case of the cable TV home shopping company.

• Proceedings of the Korean Institute of Intelligent Systems Conference
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• 1997.10a
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• pp.315-320
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• 1997

Rule minimization technique adapted from rough set theory was applied to remove redundant knowledge which is not necessary to make a knowledge base. New algorithm to diagnose fault using Improved Fuzzy Cognitive Maps(I-FCMs), and Fuzzy Associative Memory(FAM) is proposed. I-FCM[22] is superior to gathering knowledge from many experts and descries dynamic behaviors of systems very well. I-FCM is not only a knowledge base, but also a inference engine. FAM has learning capability like neural network[12]. Rule minimization and composition of I-FCM and FAM make it possible to construct compact knowledge base and breaks the border between inference engine and knowledge base.

• Journal of the Korean Society for Railway
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• v.8 no.2
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• pp.176-181
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• 2005

The purpose of this thesis is, based on the cognitive response of employees, to depict the phenomenon and the pattern of organizational culture in A Subway system, To attain this purpose, several aspects of organizational culture are surveyed through questionaire and analyzed by SPSS. The major findings are . 1) In general, the cognitive response of employees in railway-concerned firms on culture-related aspects is awfully negative. 2) Job satisfaction and involvement in A Subway is highly related to achievement factor in terms of culture. 3) According to the analysis based on four kinds of Job Groups, certain job groups such as drivers and vehicle maintenance are seen as having exceptionally negative attitude towards every aspects of their organization. So, some careful diagnosis and approaches to the symptoms, the causes, and the treatments are urgently needed.

• Sleep Medicine and Psychophysiology
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• v.1 no.2
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• pp.193-196
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• 1994

Primary depression with cognitive impairment, referred to as depressive pseudodementia, may be mistaken for a progressive degenerative dementia. Recognition of primary depression is clinically important because of its treatability. To differentiate depression from degenerative dementia, author used brain SPECT. By the result the regional cerebral blood flow(rCBF) in elderly depressed patient was decreased in the right frontal cortex. The pattern of rCBF was different from that of dementia which shows decreased rCBF in bifrontal cortex. By using brain SPECT in depressed elderly patient with cognitive impairment, the discrimination from dementia will be more effective and accurate.

• Journal of the Korean Society for Precision Engineering
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• v.32 no.1
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• pp.39-47
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• 2015

Globalization, unpredictable markets, increased products customization and frequent changes in products, production technologies and machining systems have become a complexity in today's manufacturing environment. One key strategy for coping with the evolution of this situation is to develop or apply an enable technology such as intelligent manufacturing. Intelligent manufacturing system (IMS) is characterized by decentralized, distributed, networked compositions of heterogeneous and autonomous systems. The model of IMS is inherited from the organization of the living systems in biology and nature so that the manufacturing system has the advanced characteristics inspired from biology such as self-adaptation, self-diagnosis, and selfhealing. To prove this concept, an innovative system with applying the advanced information and communication technology such as internet of things, cognitive agent are proposed to integrate, organize and allocate the machining resources. Innovative system is essential for modern machining system to flexibly and quickly adapt to new challenges of manufacturing environment.

• International Journal of Internet, Broadcasting and Communication
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• v.14 no.3
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• pp.108-114
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• 2022

Autism (ASD) is a mental disorder characterized by a pronounced deficit in personal, social, speech, and other aspects of development and communication skills. Since autism is a complex developmental disorder that requires a lot of effort to recognize, this research was conducted to develop an interactive data Acquisition System and detect the first signs of ASD in children. The proposed system presents several variants of the tasks in an entertaining form, using hand tracking. Hand tracking is used to attract children's attention and interest them more to achieve more accurate results. The creation of the system is based on such libraries as OpenCV, PyGame, TensorFlow, and Mediapipe. The ultimate goal of the paper is to obtain data on the disease of autism in children for use in further diagnosis by medical experts.

• Journal of Korea Multimedia Society
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• v.22 no.10
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• pp.1168-1177
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• 2019

In order to diagnose and prevent Alzheimer's Disease (AD), it is becoming increasingly important to develop a CAD(Computer-aided Diagnosis) system for AD diagnosis, which provides effective treatment for patients by analyzing 3D MRI images. It is essential to apply powerful deep learning algorithms in order to automatically classify stages of Alzheimer's Disease and to develop a Alzheimer's Disease support diagnosis system that has the function of detecting hippocampus and CSF(Cerebrospinal fluid) which are important biomarkers in diagnosis of Alzheimer's Disease. In this paper, for AD diagnosis, we classify a given MRI data into three categories of AD, mild cognitive impairment, and normal control according by applying 3D brain MRI image to the Faster R-CNN model and detect hippocampus and CSF in MRI image. To do this, we use the 2D MRI slice images extracted from the 3D MRI data of the Faster R-CNN, and perform the widely used majority voting algorithm on the resulting bounding box labels for classification. To verify the proposed method, we used the public ADNI data set, which is the standard brain MRI database. Experimental results show that the proposed method achieves impressive classification performance compared with other state-of-the-art methods.