• The Korean Journal of Physiology and Pharmacology
• /
• v.24 no.1
• /
• pp.89-99
• /
• 2020

Although microscopic analysis of tissue slides has been the basis for disease diagnosis for decades, intra- and inter-observer variabilities remain issues to be resolved. The recent introduction of digital scanners has allowed for using deep learning in the analysis of tissue images because many whole slide images (WSIs) are accessible to researchers. In the present study, we investigated the possibility of a deep learning-based, fully automated, computer-aided diagnosis system with WSIs from a stomach adenocarcinoma dataset. Three different convolutional neural network architectures were tested to determine the better architecture for tissue classifier. Each network was trained to classify small tissue patches into normal or tumor. Based on the patch-level classification, tumor probability heatmaps can be overlaid on tissue images. We observed three different tissue patterns, including clear normal, clear tumor and ambiguous cases. We suggest that longer inspection time can be assigned to ambiguous cases compared to clear normal cases, increasing the accuracy and efficiency of histopathologic diagnosis by pre-evaluating the status of the WSIs. When the classifier was tested with completely different WSI dataset, the performance was not optimal because of the different tissue preparation quality. By including a small amount of data from the new dataset for training, the performance for the new dataset was much enhanced. These results indicated that WSI dataset should include tissues prepared from many different preparation conditions to construct a generalized tissue classifier. Thus, multi-national/multi-center dataset should be built for the application of deep learning in the real world medical practice.

• KIEAE Journal
• /
• v.16 no.4
• /
• pp.71-77
• /
• 2016

Purpose : The energy saving in a residential building (apartment) sector is known as one of the effective solution of energy reduction. In South Korea, the government has recently reinforced regulations associated with the energy performance of buildings. However, there is a lack of research on the methods for the energy performance diagnosis that is used to analyze the wall thermal performance of the existing apartments. Because a reliable diagnosis is necessary to save the building energy, this study analyzed wall thermal performance of an existing apartment in Seoul. Method : This paper applied two methods for analysis of the thermal insulation performance; HFM(Heat Flow Meter) method and ASTR(Air-Surface Temperature Ratio) method. The HFM method is suggested by ISO9869-1 code to measure the thermal performance. The ASTR method is proposed by this study for the simplified In-situ measurement and it uses three temperature data (interior wall surface, interior and exterior air) and the overall heat transfer coefficient. This study conducted the experiment of an existing apartment in Seoul using these methods and analyzed the results. Furthermore, the energy simulation tool of the building was used to suggest retrofit of the building based on the results of measurements. Result : The error rate of HFM method and ASTR method was analyzed in about 17 to 20%. As the results of comparison between the initial design values of the wall and the measured values, the 26% degradation of insulation thermal performance was measured. Lastly, the energy simulation tool of the building shows 10.8% energy savings in accordance with the construction of suggested retrofit.

• Journal of the Korea institute for structural maintenance and inspection
• /
• v.23 no.7
• /
• pp.129-136
• /
• 2019

In this study, the magnetic flux leakage technique was applied to diagnose steel plate damage, imaging technique was applied through those signals. Steel plate specimens with different thicknesses were prepared for the imaging the magnetic flux leakage signal, and 6 different depths of damage were artificially processed at the same locations on each specimen. The sensor head consist hall sensor and magnetization yoke was fabricated to magnetize the steel plate specimen and measure the magnetic flux leakage signal. In order to remove the noise and increase the resolution of the image in the signal collected from the hall sensor, various of signal processing was performed. P-P value was analyzed for each channel to analyze the magnetic flux leakage signals measured from each damaged part. Based on the above processed signals and analysis, it was converted into heatmap image. Through this, it was possible to identify the damage on the steel plate at glance by imaging magnetic flux leakage signal.

• Journal of the Korean Society of Environmental Restoration Technology
• /
• v.15 no.3
• /
• pp.55-66
• /
• 2012

This study was carried out to investigate vegetation of Rhododendron mucronulatum habitat in Mt. Biseul to recommend basic information for synecological characteristics and management methods. The survey was carried out from May to July, 2011 and totally 46 vegetation data including 42 families 93 genera 108 species 16 varieties and 5 forma were collected and analyzed. Among the investigated 129 taxa, the numbers of rare plant resources were summarized as 19 taxa; The rare plants designated by Korea Forest Service, the specific plants by floristic region and the endemic plants were listed as 3 taxa, 15 taxa and 4 taxa, respectively. Rhododendron mucronulatum habitat of Mt. Biseul was classified into 3 plant communities (Carex lanceolata-Rhododendron mucronulatum community, Potentilla dickinsii-Selaginella rossii community, Carex lanceolata-Quercus mongolica community). Carex lanceolata-Rhododendron mucronulatum community was subdivided into Tripterygium regelii subunit and Miscanthus sinensis for. purpurascens subunit by human interference degree. And synecology, syndynamics, synchorology of these plant communities were identified, and Site-species ordination analysis by Principal Coordinate Analysis (PCoA) reflected that human impact, soil moisture condition were main ecological factors determining the distribution pattern of classified plant communities. Therefore these plant communities correspond to quite distinctive 4 habitat types : unstable-dry type=Miscanthus sinensis for. purpurascens subunit, unstable-moderate type=Tripterygium regelii subunit, stable-dry type=Potentilla dickinsii-Selaginella rossii community, stable-moderate type=Carex lanceolata-Quercus mongolica community. Finally, through the vegetational diagnosis, proper management methods such as a limit on the access of visitors, planting of native woody plants after removing unwanted vines or grass were suggested.

• Journal of the Korean Institute of Rural Architecture
• /
• v.22 no.2
• /
• pp.9-17
• /
• 2020

The ratio of the deterioration housing in rural area was 29.6%, but it was 18.3% in urban area based on a 2018 survey. In consideration of the point, this study aims to analyze the actual condition of indoor air quality in rural houses to provide basic data for improving the indoor air environment. It was investigated 15housings of Hongseong-gun, Chungchengnam-do. To investigate the correlation between indoor air quality and housing type, both the field survey of housing type and precision diagnosis of concentration of indoor air pollutants such as HCHO, TVOC, Fine dust(PM-10, PM-2.5), CO₂, Radon. The results of this study are as follows. First, according to the average value of each element of rural old housing, the construction year was distributed in 1939~2004, and 12households(80%) living in houses older than 30years have passed for about 46years. As for the housing area, more than 12houses(80%) of 60㎡ or more and 3 houses (20%) of less than 60㎡ were often living in relatively small-scale housing. Second, as a result of measuring indoor air pollutants in rural houses, substances exceeding the standard values were found in HCHO, TVOC, CO₂. Third, in the case of Fine dust and Radon, none of such factors were exceeded the standard. Fourth, there was no significant difference in indoor air quality depending on housing type in rural houses. This paper is expected to contribute to the regional development projects and effective implementation of rural policies.

• Journal of KIISE:Computing Practices and Letters
• /
• v.6 no.1
• /
• pp.82-92
• /
• 2000

This paper introduces an implementation of the diagnosis software for CC-NUMA systems. The CC-NUMA architecture is composed of two or more SMP nodes installed with the specialized hardware to provide cache-coherent operation and the high-speed interconnection network to connect each node, it enables both the high performance and the high scalability. While the CC-NUMA system provides the single system image in the operating system aspect, it should be considered the multiple systems by the diagnostic software. Thus it is difficult to diagnose and manage CC-NUMA system using commercial administration software due to characteristics of the complicated architecture. The remote diagnosis and management are also required with a view to reduce Total Cost of Ownership. In this paper, we design diagnostic software to manage CC-NUMA server system, and propose its mechanism in client-server manner to support remote administration. Additionally, we use the Java-based user interface to enlarge an administrator's accessibility.

• Journal of The Korea Institute of Healthcare Architecture
• /
• v.27 no.2
• /
• pp.39-48
• /
• 2021

Purpose: The study aims to demonstrate regional diagnosis methods and results combined with geographical information to expand the physical infrastructure related to community care services. To this end, the physical infrastructure for the core elements of community care was analyzed in terms of the fulfilment and access of facilities to derive the underserved elements and regions. Methods: Utilizes GIS network analysis techniques that can derive physical infrastructure service areas. Underserved elements are derived by comparing and analyzing the service area for each core element. Next, the underserved regions for each core element are derived through the overlapping of the set service area and the diagnosis population. Results: Among the physical infrastructure by core elements for community care, the housing support element was considerably weak, and the nursing care facility compared to health care was also analyzed to be weak. In addition, underserved regions by dong in Mapo-gu were deduced and presented for each diagnosed population. Implications: The discovery of underserved elements and underserved regions is meaningful as a diagnostic process that can derive the physical infrastructure that needs to be expanded urgently for the realization of community care and determine the priority projects and targets of the projects.

• Journal of Ocean Engineering and Technology
• /
• v.35 no.4
• /
• pp.287-295
• /
• 2021

This paper describes a recurrent neural network (RNN) for the fault classification of a blade pitch system of a spar-type floating wind turbine. An artificial neural network (ANN) can effectively recognize multiple faults of a system and build a training model with training data for decision-making. The ANN comprises an encoder and a decoder. The encoder uses a gated recurrent unit, which is a recurrent neural network, for dimensionality reduction of the input data. The decoder uses a multilayer perceptron (MLP) for diagnosis decision-making. To create data, we use a wind turbine simulator that enables fully coupled nonlinear time-domain numerical simulations of offshore wind turbines considering six fault types including biases and fixed outputs in pitch sensors and excessive friction, slit lock, incorrect voltage, and short circuits in actuators. The input data are time-series data collected by two sensors and two control inputs under the condition that of one fault of the six types occurs. A gated recurrent unit (GRU) that is one of the RNNs classifies the suggested faults of the blade pitch system. The performance of fault classification based on the gate recurrent unit is evaluated by a test procedure, and the results indicate that the proposed scheme works effectively. The proposed ANN shows a 1.4% improvement in its performance compared to an MLP-based approach.

• Journal of the Korean Institute of Rural Architecture
• /
• v.24 no.3
• /
• pp.39-46
• /
• 2022

This study aims to derive basic living service facility items in rural areas and construct related spatial data. To do this, a literature review on the laws and systems related to the residential environment and services in rural areas, rural spatial planning, and the 'Rural Convention' strategic plan reports for the Jeolla and Gyeongsang Region in 2021 was conducted. Primary data collection and review on the list of basic living service items in rural areas derived from the analysis were conducted. After data collection, 12 sectors and 44 types of rural basic living service items were derived; the data selection was carried out based on the clarity of the subject of data management, whether it was established nationwide, whether it was disclosed and provided, whether it was periodically updated, and whether it was an underlying law. Afterwards, data on the derived rural basic living service items were constructed. Afterwards, spatial data on the derived rural basic living service items were constructed. Because open data provided through various institutions were employed, data structure unification such as data attribute values and code names was needed, and abnormal data such as address errors and omissions were refined. After that, the data provided in text form was converted into spatial data through geocoding, and through comparative review of the distribution status of the converted data and the provided address, spatial data related to rural basic living services were finally constructed for about 540,000 cases. Finally, implications for data construction for diagnosing rural living areas were derived through the data collection and construction process. The derived implications include data unification, data update system establishment, the establishment of attribute values necessary for rural living area diagnosis and spatial planning, data establishment plan for facilities that provide various services, rural living area analysis method, and diagnostic index development. This study is meaningful in that it laid the foundation for data-based rural area diagnosis and rural planning, by selecting the basic rural living service items, and constructing spatial data on the selected items.

• Journal of the Society of Disaster Information
• /
• v.17 no.2
• /
• pp.319-328
• /
• 2021

Purpose: Recently, a large social disaster has called for the need to diagnose social disaster safety, and the Ministry of Public Administration and Security calculates and publishes regional safety ratings such as regional safety index and national safety diagnosis every year. The existing safety diagnosis system uses equal intervals or normal distribution to grade risk maps in a uniform manner. Method: However, the equidistant technique can objectively analyze risk ratings, but there is a limit to classifying risk ratings when the distribution is skewed to one side, and the z-score technique has a problem of losing credibility if the population does not follow a normal distribution. Because the distribution of statistical data varies from indicator to indicator, the most appropriate rating should be applied for each data distribution. Result: Therefore, in this paper, we analyze the data of disaster indicators and present a comparison and suitable method for traditional equidistant and natural brake techniques to proceed with optimized grading for each indicator. Conclusion: As a result, three of the six new indicators were applied differently from conventional grading techniques