• 농촌계획
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• 제20권2호
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• pp.81-90
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• 2014

This study was carried out to identify the limitations and problems of organization, as well as present plans to activate the organization through diagnosis on 'My Hometown Keeper' organization that was created for the purpose of growth of agricultural and fishing regions, and environment improvement. Utilizing Weisbord's Six-box Model, an organization diagnosis model useful for diagnosis of 'My Hometown Keeper' organization, 6 areas including organization's objective, structure, relationship, compensation system, leadership, subsidiary device system etc. and 14 survey questions were prepared, and a survey investigation was conducted on the staff at Korea Rural Community Corporation in charge of 'My Hometown Keeper' participating residents and administrative support. Based on the analysis results of survey investigation, the limitations and problems of organization were identified, and as plans to improve these and activate 'My Hometown Keeper' organization, 'Clear establishment of organization's objective and role', 'Preparation of compensation and incentive system', 'Growth of relationship and leadership between constituents' 'Enhancing the utilization of subsidiary device system such as education and information acquisition etc.' etc. were presented.

• 대한전기학회:학술대회논문집
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• 대한전기학회 2000년도 하계학술대회 논문집 D
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• pp.2488-2491
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• 2000

A Neural network is possible to nonlinear function mapping and parallel processing. Therefore It has been developing for a Diagnosis system of nuclear plower plant. In general Neural Networks is a static mapping but Dynamic Neural Network(DNN) is dynamic mapping. When a fault occur in system, a state of system is changed with transient state. Because of a previous state signal is considered as a information. DNN is better suited for diagnosis systems than static neural network. But a DNN has many weights, so a real time implementation of diagnosis system is in need of a rapid network architecture. This paper presents a algorithm for RCP monitoring Alarm diagnosis system using Self Dynamic Neural Network(SDNN). SDNN has considerably fewer weights than a general DNN. Since there is no interlink among the hidden layer. The effectiveness of Alarm diagnosis system using the proposed algorithm is demonstrated by applying to RCP monitoring in Nuclear power plant.

• 의료ㆍ복지 건축 : 한국의료복지건축학회 논문집
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• 제21권2호
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• pp.7-15
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• 2015

Purpose: The purpose of this study is analyze linkage and spatial and structural characteristics of outpatient department and diagnosis/treatment area of geriatric hospitals based on quantitative analysis, according to function and corridor types. Methods: To examine structural characteristics and correlation of outpatient department and diagnosis/treatment area of six geriatric hospitals according to the corridor type, were systemized according to the function and corridor type and made into a j-graph, and an index was created by using space syntax to understand spatial characteristics. Results: 1) Different functional spaces are connected by a corridor, which, therefore, can be an axis of the connectivity and linkage of functional spaces and an important element in a clear hierarchy. 2) Treatment areas were disconnected from different functional spaces and, therefore, the accessibility was low. Many hospitals had an arrangement plan for treatment and diagnosis areas, and recent hospitals have segmented treatment areas within the rehabilitation space, which resulted in deeper space. 3) In terms of the level of integration, more integrated reception area meant shallower spatial depth, and deeper space for treatment and diagnosis areas. Implications: Spatial relation of outpatient department of geriatric hospitals was analyzed based on characteristics of the elderly.

• 한국환경복원기술학회지
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• 제21권2호
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• pp.13-26
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• 2018

The restoration of the impaired stream ecosystem is an important part of river policies in Ministry of Environment (MoE). However, the diagnosing the impairment sources of stream ecosystem has been omitted on the current river projects and policies. This phenomena lead the remaining impairment sources keep influencing on negative effects on streams. Hence, it is critical to construct a diagnosis system of impairment sources in order to increase the efficiency of various river restoration projects and policies. Moreover, it is also important to understand the relative impact of socio-economic factors of the impairment of stream ecosystems so as to build a domestic diagnosis system in place. Therefore, the study aims to analyse the relative effects of socio-economic factors which are the source of the stream ecosystem impairments through implementing the Analytic Hierarchy Process (AHP). In order to achieve the goal, a list of socio-economic factors influencing the stream health has been derived. On the basis of the derived causes list, AHP questionnaire were carried out to the experts of aquatic ecology. The study results could be implemented to analysing the relative influence of socio-economic impairment causes in domestic stream environments. In addition, more case study investigation is needed to cross-check if the derived impairment causes and weights are applied in the field as well as to develop more reliable indicators.

• 한국의학물리학회지:의학물리
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• 제30권2호
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• pp.49-58
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• 2019

Purpose: Automated analytical systems have begun to emerge as a database system that enables the scanning of medical images to be performed on computers and the construction of big data. Deep-learning artificial intelligence (AI) architectures have been developed and applied to medical images, making high-precision diagnosis possible. Materials and Methods: For diagnosis, the medical images need to be labeled and standardized. After pre-processing the data and entering them into the deep-learning architecture, the final diagnosis results can be obtained quickly and accurately. To solve the problem of overfitting because of an insufficient amount of labeled data, data augmentation is performed through rotation, using left and right flips to artificially increase the amount of data. Because various deep-learning architectures have been developed and publicized over the past few years, the results of the diagnosis can be obtained by entering a medical image. Results: Classification and regression are performed by a supervised machine-learning method and clustering and generation are performed by an unsupervised machine-learning method. When the convolutional neural network (CNN) method is applied to the deep-learning layer, feature extraction can be used to classify diseases very efficiently and thus to diagnose various diseases. Conclusions: AI, using a deep-learning architecture, has expertise in medical image analysis of the nerves, retina, lungs, digital pathology, breast, heart, abdomen, and musculo-skeletal system.

• 디지털콘텐츠학회 논문지
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• 제15권1호
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• pp.121-128
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• 2014

SSE-CMM은 보안엔지니어링을 공학, 보증, 위험 프로세스의 3가지 요소로 나누고 있으며 정보보호 성숙도 평가 모델과 수준을 제시하고 있다. 정보보호 성숙도 측정은 취약점 진단, 위험분석 방법론을 실무 현장에서 사용할 수 있도록 종합적으로 결론을 제시한다. 사이버거래의 일반적인 서비스는 인터넷 뱅킹, 모바일 뱅킹, 텔레뱅킹 등이다. 사이버거래 처리구조의 한 종류인 뱅킹시스템 정보보호 성숙도 측정방법론 연구 목적은 기존의 취약점 진단, 위험분석 방법론을 실무현장에서 사용할 수 있도록 종합적 결론을 제시한다. 안전성과 편리성을 확보하여 이용자들이 사이버 거래를 편리하게 이용할 수 있는 환경을 구축하는 것이 사이버 거래 활성화의 핵심이다. 특히 업무현장에서 정보보호 성숙도 측정을 통한 사이버뱅킹시스템의 안전성을 확보한다면 현장의 실무처리 결과로 많은 효과가 나타날 것으로 기대한다.

• KSII Transactions on Internet and Information Systems (TIIS)
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• 제18권2호
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• pp.284-310
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• 2024

Identifying clinical pathways for disease diagnosis and treatment process recommendations are seriously decision-intensive tasks for health care practitioners. It requires them to rely on their expertise and experience to analyze various categories of health parameters from a health record to arrive at a decision in order to provide an accurate diagnosis and treatment recommendations to the end user (patient). Technological adaptation in the area of medical diagnosis using AI is dispensable; using expert systems to assist health care practitioners in decision-making is becoming increasingly popular. Our work architects a novel knowledge-based recommender system model, an expert system that can bring adaptability and transparency in usage, provide in-depth analysis of a patient's medical record, and prescribe diagnostic results and treatment process recommendations to them. The proposed system uses a set of parallel discrete fuzzy rule-based classifier systems, with each of them providing recommended sub-outcomes of discrete medical conditions. A novel knowledge-based combiner unit extracts significant relationships between the sub-outcomes of discrete fuzzy rule-based classifier systems to provide holistic outcomes and solutions for clinical decision support. The work establishes a model to address disease diagnosis and treatment recommendations for primary lung disease issues. In this paper, we provide some samples to demonstrate the usage of the system, and the results from the system show excellent correlation with expert assessments.

• 대한세포병리학회지
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• 제11권2호
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• pp.103-108
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• 2000

Pulmonary alveolar proteinosis(PAP) is a rare disease in which the alveolar spaces are filled with an eosinophilic, PAS-positive material, whereas the interstitial architecture of the lung usually remains unaffected. Although a definitive diagnosis is usually made by an open lung biopsy, bronchoalveolar lavage(BAL) cytology may play a decisive role in the diagnosis and therapy of these patients and may spare a patient a more invasive diagnostic procedure. The author presents a patient in whom BAL cytology specimen contained the characteristic globules of amorphous proteinaceous PAS-positive material accompanied by background of rare macrophages and inflammatory cells. Ultrastructural study using BAL specimen can confirm the diagnosis of PAP.

• 한국정밀공학회:학술대회논문집
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• 한국정밀공학회 2001년도 춘계학술대회 논문집
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• pp.430-434
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• 2001

Virtual manufacturing system is integrated computer model that represents the precise and whole structure of manufacturing system and simulates its physical and logical behavior in operation.[1] A virtual machine is computer model that represents a CNC machine tool and one of core elements of virtual manufacturing system. In this paper, it is emphasized that a virtual machine must be web-based system for serving information to all attendants in a real machine tool without the restriction of time or location, and then in the fault diagnosis, one of important modules of a virtual machine, the methods of both using the controller signal and web-based expert system are proposed.

• 대한기계학회논문집B
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• 제27권5호
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• pp.553-560
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• 2003

On-site diagnosis of chiller performance is an essential step fur energy saving business. The main purpose of the on-site diagnosis is to predict the COP of a target chiller. Many models based on thermodynamics background have been proposed for this purpose. However, they have to be modified from chiller to chiller and require deep insight into thermodynamics that most of field engineers are often lacking in. This study focuses on developing an easy-to-use diagnostic technique that is based on adaptive neuro-fuzzy inference system (ANFIS). Quality of the training data for ANFIS, sampled over June through September, is assessed by checking COP prediction errors. The architecture of the ANFIS, its error bounds, and collection of training data are described in detail.