• Journal of the Institute of Electronics Engineers of Korea TC
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• v.48 no.10
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• pp.43-52
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• 2011

In this paper, we propose the architecture of the policy-based emergency bio data transmission for the smart healthcare service. the medical staff can quickly and accurately monitor the emergency bio data of the remote patient through the proposed architecture. The proposed system consists of three parts: IEEE 11073-based agents and managers performing the aggregation function and transmission function of the bio data; the emergency management server performing the converting function between IEEE 11073 and HL7 and auto-diagnosis function of the policy-based; HL7 medical system based on HL7. Finally, by implementing the proposed system, we shows that the aggregation of the bio data and management of the emergency bio data in the smart healthcare service are possible.

• Journal of Biomedical Engineering Research
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• v.41 no.1
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• pp.48-54
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• 2020

In this paper, we deal with a liver fibrosis classification problem using ultrasound B-mode images. Commonly representative methods for classifying the stages of liver fibrosis include liver biopsy and diagnosis based on ultrasound images. The overall liver shape and the smoothness and roughness of speckle pattern represented in ultrasound images are used for determining the fibrosis stages. Although the ultrasound image based classification is used frequently as an alternative or complementary method of the invasive biopsy, it also has the limitations that liver fibrosis stage decision depends on the image quality and the doctor's experience. With the rapid development of deep learning algorithms, several studies using deep learning methods have been carried out for automated liver fibrosis classification and showed superior performance of high accuracy. The performance of those deep learning methods depends closely on the amount of datasets. We propose an enhanced U-net architecture to maximize the classification accuracy with limited small amount of image datasets. U-net is well known as a neural network for fast and precise segmentation of medical images. We design it newly for the purpose of classifying liver fibrosis stages. In order to assess the performance of the proposed architecture, numerical experiments are conducted on a total of 118 ultrasound B-mode images acquired from 78 patients with liver fibrosis symptoms of F0~F4 stages. The experimental results support that the performance of the proposed architecture is much better compared to the transfer learning using the pre-trained model of VGGNet.

• Journal of The Korea Institute of Healthcare Architecture
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• v.25 no.1
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• pp.17-27
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• 2019

Purpose: Clinical laboratory in hospital has taken a great role in protection of chronic disease. as well as diagnosis and treatment, And laboratory layout has been considered by the management and laboratory section more than the function and workflow. Methods: So this study figures out the workflows of laboratory sections in the recently upgraded Laboratory Medicine, and searches the functional relationships and spatial block diagram between each disciplines as follows. Literature review and expert adviser has been conducted. Results: 1) Laboratory type of Laboratory Medicine is divided into routine and specialized laboratory according to the workflow by automated or specialized test. 2) The general workflow consists of specimen collection, specimen classification, test by discipline, test report, and specimen disposal. 3) Though the function of each laboratory section is very complicated and specific, the characteristics and the workflow can be shown in detail by each lab through [Figure 4], [Figure 5], [Figure 6], [Figure 7], and [Figure 8]. 4) Functional relationship diagram can be displayed to the adjacency and relation between each laboratory and support spaces. 5) The spatial block diagram could be presented as shown in [Figure 10], in which the emergency lab lay in front side, routine lab in the central open area, and specialized lab in the behind side. Implications: This study can be used as a useful data in planning and designing a Laboratory Medicine Department.

• KSII Transactions on Internet and Information Systems (TIIS)
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• v.16 no.7
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• pp.2209-2224
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• 2022

The Internet of Things (IoT) is being used in a wide variety of fields due to the recent 4th industrial revolution. In particular, research is being conducted that combines IoT with the medical field such as telemedicine. Among them, the field of shock detection is a big issue in the medical field because the causes of shock are diverse, treatments are very complex, and require a high level of medical knowledge and experience. The transmission of infectious diseases is common when treating critically ill patients, especially patients with shock. Thus, to effectively care for shock patients, we propose an architecture that continuously monitors the patient's condition, and automatically recommends a drug injection treatment according to the patient's shock condition. The patient's hemodynamic information is continuously monitored, and the patient's shock generation information is recorded periodically. With the recorded patient information, the patient's condition is determined and automatically injected with necessary medication. The medical team can find out whether the patient's condition has improved by checking the recorded information through web applications. The study can help relieve the shortage of medical personnel and help prevent transmission of infectious disease in medical staff. We look forward to playing a role in helping medical staff by making recommendations for the diagnosis and treatment of complex and difficult shocks.

• Proceedings of the Korean Institute of Navigation and Port Research Conference
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• 2022.06a
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• pp.110-110
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• 2022

본 연구는 자율운항 선박의 원격 고장 진단 기법 개발의 일부로 수행되었다. 특히, 엔진 연료 계통 장비로부터 계측된 시계열 데이터로부터 상태 진단을 위한 알고리즘 구현 결과를 제시하였다. 엔진 연료 펌프와 청정기를 가진 육상 실험 장비로부터 진동 시계열 데이터 계측하였으며, 이상 감지, 고장 분류 및 고장 예측이 가능한 심층 학습(Deep Learning) 및 기계 학습(Machine Learning) 알고리즘을 구현하였다. 육상 실험 장비에 고장 유형 별로 인위적인 고장을 발생시켜 특징적인 진동 신호를 계측하여, 인공 지능 학습에 이용하였다. 계측된 신호 데이터는 선행 발생한 사건의 신호가 후행 사건에 영향을 미치는 특성을 가지고 있으므로, 시계열에 내포된 고장 상태는 시간 간의 선후 종속성을 반영할 수 있는 학습 알고리즘을 제시하였다. 고장 사건의 시간 종속성을 반영할 수 있도록 순환(Recurrent) 계열의 RNN(Recurrent Neural Networks), LSTM(Long Short-Term Memory models)의 모델과 합성곱 연산 (Convolution Neural Network)을 기반으로 하는 Conv1D 모델을 적용하여 예측 정확성을 비교하였다. 특히, 합성곱 계열의 RNN LSTM 모델이 고차원의 순차적 자연어 언어 처리에 장점을 보이는 모델임을 착안하여, 신호의 시간 종속성을 학습에 반영할 수 있는 합성곱 계열의 Conv1 알고리즘을 고장 예측에 사용하였다. 또한 기계 학습 모델의 효율성을 감안하여 XGBoost를 추가로 적용하여 고장 예측을 시도하였다. 최종적으로 연료 펌프와 청정기의 진동 신호로부터 Conv1D 모델과 XGBoost 모델의 고장 예측 성능 결과를 비교하였다

• Journal of the Korean Institute of Landscape Architecture
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• v.41 no.1
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• pp.44-50
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• 2013

The persons in charge of management request diagnosis and prescription to tree hospitals in order to get consultation about the problems like blight that occur in landscape tree management. This study aims to analyze what the main problems and questions raised by landscape gardeners are and those concerned in landscape tree management. This is done by investigating landscape tree-related questions and answers uploaded on the online consultation boards of the plant diagnostic centers approved in Korea including the Seoul National University Plant Clinic, the Chungbuk National University Plant Hospital, and the Kangwon Diagnostic Center. As a result, those concerned in landscape occupied the most as 81.4% among the questioners. However, only 11.5% did explain the plant management history or surrounding environment, which is essential for landscape tree diagnosis when asking questions. This shows that those concerned in landscape lack basic knowledge or interest about plant diagnosis. Among 263 questions about landscape trees, questions about physiological damage included 94 cases that were the most taking up 35.8%. Moreover, the next were damage by insects and damage by disease in order. It is thought that due to the characteristics of physiological problems that occur by various sorts of stress and with no signs, they tend to request diagnosis or prescription the most. The most frequent reasons for physiological damage are water stress and temperature stress. About damage by disease, there exist many types of diseases, and there are many complex damages accompanied by physiological causes. About damage by insects, the most common include damage by moths. In consideration of this result, universities or technician training centers should provide education for landscape tree management so that landscape technicians and students can acquire essential knowledge and information about landscape tree management and increase their interest in it. In particular, it is necessary to provide profound learning opportunities for plant physiology, and the technicians should make efforts themselves. In addition, it is needed to build organizations to which they can ask technical questions about landscape planting and management in order to understand landscape industry in general and the actual status of landscape planting technique and the actual field. Moreover, to elevate systemicity and expertise in the area of landscape tree management not yet equipped with the foundation, it is needed to cultivate the technicians intensively and conduct research by those concerned both in academic and industrial circles.

• Journal of the Korean Institute of Traditional Landscape Architecture
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• v.32 no.4
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• pp.94-104
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• 2014

This contribution studied knowledges, informations and main project issues for systematic conservation management utilize of Joseon Royal Tombs guaranteeing their Outstanding Universal Value, Authenticity and Integrity, and the outcomes are as follows. The first, regarding the tomb's system, it should be planned to enhance authenticity and integrity of Joseon Royal Tombs through historical facts, measurement, diagnosis and intervention according to international and national charters, statements and general standards. The second, regarding prevention against disasters, the anti-fire system including construction of GIS materials and the Risk Map following investigation the present condition, premising improvement of relevant laws and regulations, should be planned. The third, we should consider, regarding utilize, educational application by the each tomb's story and royal ancestral rite, tourism by the local area of each tomb and industrial application by science and IT technologies.

• ETRI Journal
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• v.35 no.5
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• pp.808-818
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• 2013

Programmable memory built-in self-test (PMBIST) is an attractive approach for testing embedded memory. However, the main difficulties of the previous works are the large area overhead and low flexibility. To overcome these problems, a new flexible PMBIST (FPMBIST) architecture that can test both single-port memory and dual-port memory using various test algorithms is proposed. In the FPMBIST, a new instruction set is developed to minimize the FPMBIST area overhead and to maximize the flexibility. In addition, FPMBIST includes a diagnostic scheme that can improve the yield by supporting three types of diagnostic methods for repair and diagnosis. The experiment results show that the proposed FPMBIST has small area overhead despite the fact that it supports various test algorithms, thus having high flexibility.

• Journal of Korea Society of Industrial Information Systems
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• v.19 no.3
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• pp.9-15
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• 2014

In the ubiquitous computing environment, a ubiquitous vehicle will be a communication node in the vehicular network as well as the means of ground transportation. It will make humans and vehicles seamlessly and remotely connected. Especially, one of the prominent services in the ubiquitous vehicle is the vehicle remote operation. However, mutual-collaboration with the in-vehicle communication network, the vehicle-to-vehicle communication network and the vehicle-to-roadside communication network is required to provide vehicle remote operation services. In this paper, an Internet-based human-vehicle interfaces and a network architecture is presented to provide remote vehicle control and diagnosis services. The performance of the proposed system is evaluated through a design and implementation in terms of the round trip time taken to get a vehicle remote operation service.

• Investigative Magnetic Resonance Imaging
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• v.12 no.1
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• pp.55-59
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• 2008

We present a case of a 37-year-old woman who had Kimura's disease involving the lower extremity mimicking malignant soft tissue mass. The diagnosis of Kimura's disease would be considered if there is a subcutaneous solid mass showing the preservation of the nodal architecture with perinodal infiltrations and the laboratory examinations for peripheral eosinophilia and serum IgE level should be recommended although it occurs at the lower extremity.