• Journal of The Korea Institute of Healthcare Architecture
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• v.13 no.3
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• pp.15-24
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• 2007

The concept of modern medical science has been changing from the old period which is simple treatment of diseases to the new period which is active prevention from diseases. Because preventing diseases is more effective and economical than treating diseases. This is the reason that needs to HPC at the concept of Health diagnosis. Another reason of HPC is to diagnose the stresses and to prescribe an effective exercise and to show the way of nutrition intake in order to keep up the condition of individual health. According to these reasons, I foresee the demand of remodelling HPC from existing HEC on this study. I define the common space that HEC uses duplication with HPC. I also aim to analyze them and to examine the alterable function and proper size of common space in case of remodelling.

• Journal of The Korea Institute of Healthcare Architecture
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• v.11 no.1
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• pp.33-41
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• 2005

The construction can proceed in different ways according to the acquired profitability of the hospital during the construction and to the features of departments or areas. This study is an analysis of remodeling construction processes to resolve major tasks of remodeling. The remodeling strategies gained from this study can be summed up as follows: 1) Remodeling work in hospitals involves the acquire relocation of space through extensive area renovations and then moving back to the space, and lastly working on the empty space. Thus, it is more advantageous in terms of construction work to demolish the existing buildings than to acquire the relocation space through extensions or renovations. That is, demolition after the maximum utilization of the existing buildings is the most desirable in terms of space availability. 2) The construction methods for remodeling are two: a method of carrying out construction by dividing the plane areas into several individual ones and of working on it floor by floor. In case of ward areas, and the outpatient area, the construction proceeds after securing the relocation space and partially setting construction areas in order to minimize the decrease in profitability due to the smaller number of beds and treatment rooms during construction. If the outpatient diagnosis/ treatment area and the supply area relocate together with the ward areas, there may be extra expenses. Thus, doing construction by area, while partially operating those areas or after relocating the whole areas.

• Journal of Periodontal and Implant Science
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• v.48 no.2
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• pp.114-123
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• 2018

Purpose: The aim of the current study was to develop a computer-assisted detection system based on a deep convolutional neural network (CNN) algorithm and to evaluate the potential usefulness and accuracy of this system for the diagnosis and prediction of periodontally compromised teeth (PCT). Methods: Combining pretrained deep CNN architecture and a self-trained network, periapical radiographic images were used to determine the optimal CNN algorithm and weights. The diagnostic and predictive accuracy, sensitivity, specificity, positive predictive value, negative predictive value, receiver operating characteristic (ROC) curve, area under the ROC curve, confusion matrix, and 95% confidence intervals (CIs) were calculated using our deep CNN algorithm, based on a Keras framework in Python. Results: The periapical radiographic dataset was split into training (n=1,044), validation (n=348), and test (n=348) datasets. With the deep learning algorithm, the diagnostic accuracy for PCT was 81.0% for premolars and 76.7% for molars. Using 64 premolars and 64 molars that were clinically diagnosed as severe PCT, the accuracy of predicting extraction was 82.8% (95% CI, 70.1%-91.2%) for premolars and 73.4% (95% CI, 59.9%-84.0%) for molars. Conclusions: We demonstrated that the deep CNN algorithm was useful for assessing the diagnosis and predictability of PCT. Therefore, with further optimization of the PCT dataset and improvements in the algorithm, a computer-aided detection system can be expected to become an effective and efficient method of diagnosing and predicting PCT.

• KIEAE Journal
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• v.17 no.4
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• pp.41-48
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• 2017

Purpose : Currently, 25% of the domestic energy consumption structure is used as building energy, and more than 18% of this energy is consumed in the residential. Accordingly, various efforts and policies that can save energy of the building is being performed. The various researchers are conducting research to diagnose the thermal performance of existing buildings. This study is to apply in the field of precision thermal insulation performance diagnostic method for thermal performance analysis of existing detached house in Seoul, Gangreung, Gyeongju, Pohang. And this paper is analyzed quantitatively measure the existing detached house energy performance. Method: Research methodology analyzed the thermal performance over the Heat Flow Meter method by applying the measurement process and method by applying the criteria of ISO 9869-1 & ASTR method. In this study, the surface heat transfer coefficient was calibrated by applying indoor surface heat transfer resistance with reference to ISO 6946 standard. The measurement error rate between the HFM diagnosis method and the ASTR diagnosis method was reduced and the measurement reliability was obtained through measurement method error verification. Result : As a result of the study, the thermal performance vulnerable parts of the building were quantitatively analyzed, and presented for methods which can be improved capable of efficient energy use buildings.

• Archives of Craniofacial Surgery
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• v.13 no.1
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• pp.76-79
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• 2012

Purpose: Sebaceous epithelioma (sebaceoma) is a benign tumor with sebaceous differentiation. It presents primarily as a yellowish papule or nodule on the face and scalp. It must be differentiated from basal cell carcinoma and other appendageal tumors. We report a giant sebaceous epithelioma on the scalp and describe the immunohistochemical character of the cells in sebaceous epithelioma to epithelial membrane antigen (EMA). Methods: A 55-year-old-man who presented with 5-cm-diameter 2-cm-height, round shape exophytic ulcerated tumor on his head presented for treatment. The patient had noticed the lesion 40 years prior as a small yellowish plaque and 18 months ago, the plaque started to grow progressively larger. We excised the lesion with 1 cm resection margin, considering the possibility of malignancy because this lesion grossly resembled basal cell carcinoma (BCC). The defect was repaired with the use of a splitthickness skin graft. Results: When we excised the lesion, the margin was clear. Histology showed nodules that consisted of an admixture of basaloid cells and mature adipocytes lacking an organized lobular architecture. Strong expression of EMA on mature adipose cells confirmed the differential diagnosis from BCC with sebaceous differentiation because of the absence of a nuclear palisade pattern and cleft-like spaces on the hematoxylin and eosin (H&E) section. Conclusion: We treated the giant sebaceous epithelioma on the scalp with surgical excision and a split-thickness skin graft. It is important to know that the diagnosis of sebaceous epithelioma should be made based on the histologic pattern of the H&E section. Immunohistochemistry with EMA can help to confirm the differential diagnosis between sebaceous epithelioma and BCC.

• Journal of the Korea institute for structural maintenance and inspection
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• v.24 no.1
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• pp.133-141
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• 2020

Korea Infrastructure Safety and Technology Corporation (KISTEC) specifies that the safety inspection and precise safety diagnosis of concrete structures shall be conducted in accordance with the 'Special Law on Safety Management of Infrastructure'. The detailed safety inspection and precise safety diagnosis guidelines presented by KISTEC, however, gives only the grade of members and structures, and thus it is impossible to quantify remaining service life (RSL) of the structures and to quantitatively reflect the effect of differential settlements on the RSL. Therefore, this study aims to develop a RSL evaluation model considering the differential settlements. To this end, a simple equation was proposed based on the correlations between differential settlements and angular distortion, by which the angular distortion of structures was then reflected in nominal strengths of structural members. In addition, the effects of the differential settlements on the RSL of structures were analyzed in detail by using the safety diagnosis results of actual concrete structure.

• KIPS Transactions on Computer and Communication Systems
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• v.11 no.3
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• pp.83-90
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• 2022

Diabetes is a common disease today, and there are also many cases of developing into serious complications called Diabetic Foot Ulcers(DFU). Diagnosis and prevention of DFU in advance is an important task, and this paper proposes the method. Based on existing studies introduced in the paper, it can be seen that foot pressure and temperature information are deeply correlated with DFU. Introduce the process and architecture of SmarTinsole, an IoT device that measures these indicators. Also, the paper describes the preprocessing process for AI-based diagnosis of DFU. Through the comparison of the measured pressure graph and the actual human step distribution, it presents the results that multiple information collected in real-time from SmarTinsole are more efficient and reliable than the previous study.

• Journal of the Korea institute for structural maintenance and inspection
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• v.25 no.3
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• pp.85-91
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• 2021

Type 1 and type 2 buildings must regularly conduct precise safety inspections and precise safety diagnosis for the safety and maintenance of facilities, and the safety grade of the building is determined according to the results of the implementation. In addition, the cycle of inspection and diagnosis is determined according to the safety grade of the building. In order to determine the safety grade of the building, a precise safety inspection conducts condition evaluation, and a precise safety diagnosis conducts condition evaluation and safety evaluation. Therefore, since the inspection and diagnosis cycle is determined according to the safety grade of the building, the condition evaluation and safety evaluation must be precise. However, in the case of member unit evaluation, which is the first step in evaluating the current condition, the evaluation grade is determined by using the representative value of the measurement result, and this may result in an error in the evaluation grade. To solve this problem, this study analyzed evaluation criteria for each evaluation item and presented evaluation criteria using inequalities to respond to measurement results and evaluation scores. In addition, we present a functional formula that can reflect performance scores for each evaluation item.

• 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.