• Radiation Oncology Journal
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• v.16 no.4
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• pp.497-504
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• 1998

Purpose : To evaluate the usefulness of electronic portal imaging device through objective compare of the images acquired using an EPID and a conventional port film Materials and Methods : From Apr. to Oct. 1997, a total of 150 sets of images from 20 patients who received radiation therapy in the pelvis area were evaluated in the Inha University Hospital and Severance Hospital. A dual image recording technique was devised to obtain both electronic portal images and port film images simultaneously with one treatment course. We did not perform double exposure five to ten images were acquired from each patient. All images were acquired from posteroanterior (PA) view except images from two patients. A dose rate of 100-300 Mu/min and a 10-MV X-ray beam were used and 2-10 MUs were required to produce a verification image during treatment. Kodak diagnostic film with metal/film imaging cassette which was located on the top of the EPID detector was used for the port film. The source to detector distance was 140 cm. Eight anatomical landmarks (pelvic brim, sacrum, acetabulum. iliopectineal line, symphysis, ischium, obturator foramen, sacroiliac joint) were assessed. Four radiation oncologist joined to evaluate each image. The individual landmarks in the port film or in the EPID were rated - very clear (1), clear (2), visible (3), not clear (4), not visible (5). Results : Using an video camera based EPID system. there was no difference of image quality between no enhanced EPID images and port film images. However, when we provided some change with window level for the portal image, the visibility of the sacrum and obturator foramen was improved in the portal images than in the port film images. All anatomical landmarks were more visible in the portal images than in the port film when we applied the CLAHE mode enhancement. The images acquired using an matrix ion chamber type EPID were also improved image qualify after window level adjustment. Conclusion : The quality of image acquired using an electronic portal imaging device was comparable to that of the port film. When we used the enhance mode or window level adjustment. the image quality of the EPID was superior to that of the port film. EPID may replace the port film.

• The Korean Society of Law and Medicine
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• v.16 no.2
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• pp.159-193
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• 2015

Owing to causes such as population aging, increased use of various medical devices, long-term hospitalization of various patients with reduced immune function such as cancer, diabetes, and organ transplant patients, and the growing size of hospitals, hospital infections are continuing to increase. As seen in the MERS crisis of 2015, hospital infections have become a social and national problem. In order to prevent damage due to such hospital infections, it is necessary to first strictly implement measures to prevent hospital infections, while, on the other hand, providing proper relief of damage suffered due to hospital infections. However, the mainstream attitude of judicial precedents relating to hospital infection cases has been judged to in fact shift responsibility over damages due to hospital infections on the patient. In light of the philosophy of the damage compensation system, whose guiding principle if the fair and proper apportionment of damages, there is a need to seek means of drastically relaxing the burden of proof on the patient's side relative to conventional legal principles for relaxing the burden of proof, or the theory of de facto estimation. In relation to such need, the German civil code (Burgerliches Gesetzbuch), which defines contracts of medical treatment as typical contracts under the civil code, and has presumption of negligence provisions stipulating that, in cases such as hospital infections which were completely under the control of the medical care providers, if risks in general medical treatment have been realized which cause violations of the life, body, or health of patients, error on the part of the person providing medical care is presumed, was examined. Contracts of medical treatment are entered into very frequently and broadly in the everyday lives of the general public, with various disputes owing thereto arising. Therefore, it is necessary to, by defining contracts of medical treatment as typical contracts under the civil code, regulate the content of said contracts, as well as the proof of burden when disputes arise. If stipulations in the civil code are premature as of yet, an option may be to regulate through a special act, as is the case with France. In the case of hospital infection cases, it is thought that 'legal presumption of negligence' relating to 'negligence in the occurrence of hospital infections,' which will create a state close to equality of arms, will aid the resolution of the realistic issue of the de facto impossibility of remedying damages occurring due to negligence in the process of occurrence of hospital infections. Also, even if negligence is presumed by law, as the patient side is burdened with proving the causal relationships, such drastic confusion as would occur if the medical care provider side is found fully liable if a hospital infection occurs may be avoided. It is thought that, alongside such efforts, social insurance policy must be improved so as to cover the expenses of medical institutions having strictly implemented efforts to prevent hospital infections in the event that they have suffered damages due to a hospital infection accident, and that close future research and examination into this matter will be required.

• The Korean Journal of Nuclear Medicine
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• v.36 no.6
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• pp.344-356
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• 2002

Purpose: RBC blood pool SPECT has been used to diagnose focal liver lesion such as hemangioma owing to its high specificity. However, low spatial resolution is a major limitation of this modality. Recently, ordered subset expectation maximization (OSEM) has been introduced to obtain tomographic images for clinical application. We compared this new modified iterative reconstruction method, OSEM with conventional filtered back projection (FBP) in imaging of liver hemangioma. Materials and Methods: Sixty four projection data were acquired using dual head gamma camera in 28 lesions of 24 patients with cavernous hemangioma of liver and these raw data were transferred to LINUX based personal computer. After the replacement of header file as interfile, OSEM was performed under various conditions of subsets (1,2,4,8,16, and 32) and iteration numbers (1,2,4,8, and 16) to obtain the best setting for liver imaging. The best condition for imaging in our investigation was considered to be 4 iterations and 16 subsets. After then, all the images were processed by both FBP and OSEM. Three experts reviewed these images without any information. Results: According to blind review of 28 lesions, OSEM images revealed at least same or better image quality than those of FBP in nearly all cases. Although there showed no significant difference in detection of large lesions more than 3 cm, 5 lesions with 1.5 to 3 cm in diameter were detected by OSEM only. However, both techniques failed to depict 4 cases of small lesions less than 1.5 cm. Conclusion: OSEM revealed better contrast and define in depiction of liver hemangioma as well as higher sensitivity in detection of small lesions. Furthermore this reconstruction method dose not require high performance computer system or long reconstruction time, therefore OSEM is supposed to be good method that can be applied to RBC blood pool SPECT for the diagnosis of liver hemangioma.

• Journal of Intelligence and Information Systems
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• v.22 no.2
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• pp.33-56
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• 2016

Many researchers have focused on developing bankruptcy prediction models using modeling techniques, such as statistical methods including multiple discriminant analysis (MDA) and logit analysis or artificial intelligence techniques containing artificial neural networks (ANN), decision trees, and support vector machines (SVM), to secure enhanced performance. Most of the bankruptcy prediction models in academic studies have used financial ratios as main input variables. The bankruptcy of firms is associated with firm's financial states and the external economic situation. However, the inclusion of qualitative information, such as the economic atmosphere, has not been actively discussed despite the fact that exploiting only financial ratios has some drawbacks. Accounting information, such as financial ratios, is based on past data, and it is usually determined one year before bankruptcy. Thus, a time lag exists between the point of closing financial statements and the point of credit evaluation. In addition, financial ratios do not contain environmental factors, such as external economic situations. Therefore, using only financial ratios may be insufficient in constructing a bankruptcy prediction model, because they essentially reflect past corporate internal accounting information while neglecting recent information. Thus, qualitative information must be added to the conventional bankruptcy prediction model to supplement accounting information. Due to the lack of an analytic mechanism for obtaining and processing qualitative information from various information sources, previous studies have only used qualitative information. However, recently, big data analytics, such as text mining techniques, have been drawing much attention in academia and industry, with an increasing amount of unstructured text data available on the web. A few previous studies have sought to adopt big data analytics in business prediction modeling. Nevertheless, the use of qualitative information on the web for business prediction modeling is still deemed to be in the primary stage, restricted to limited applications, such as stock prediction and movie revenue prediction applications. Thus, it is necessary to apply big data analytics techniques, such as text mining, to various business prediction problems, including credit risk evaluation. Analytic methods are required for processing qualitative information represented in unstructured text form due to the complexity of managing and processing unstructured text data. This study proposes a bankruptcy prediction model for Korean small- and medium-sized construction firms using both quantitative information, such as financial ratios, and qualitative information acquired from economic news articles. The performance of the proposed method depends on how well information types are transformed from qualitative into quantitative information that is suitable for incorporating into the bankruptcy prediction model. We employ big data analytics techniques, especially text mining, as a mechanism for processing qualitative information. The sentiment index is provided at the industry level by extracting from a large amount of text data to quantify the external economic atmosphere represented in the media. The proposed method involves keyword-based sentiment analysis using a domain-specific sentiment lexicon to extract sentiment from economic news articles. The generated sentiment lexicon is designed to represent sentiment for the construction business by considering the relationship between the occurring term and the actual situation with respect to the economic condition of the industry rather than the inherent semantics of the term. The experimental results proved that incorporating qualitative information based on big data analytics into the traditional bankruptcy prediction model based on accounting information is effective for enhancing the predictive performance. The sentiment variable extracted from economic news articles had an impact on corporate bankruptcy. In particular, a negative sentiment variable improved the accuracy of corporate bankruptcy prediction because the corporate bankruptcy of construction firms is sensitive to poor economic conditions. The bankruptcy prediction model using qualitative information based on big data analytics contributes to the field, in that it reflects not only relatively recent information but also environmental factors, such as external economic conditions.

• Proceedings of the Korean Society of Propulsion Engineers Conference
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• 2011.04a
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• pp.1-2
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• 2011

Hybrid rockets have lately attracted attention as a strong candidate of small, low cost, safe and reliable launch vehicles. A significant topic is that the first commercially sponsored space ship, SpaceShipOne vehicle chose a hybrid rocket. The main factors for the choice were safety of operation, system cost, quick turnaround, and thrust termination. In Japan, five universities including Hokkaido University and three private companies organized "Hybrid Rocket Research Group" from 1998 to 2002. Their main purpose was to downsize the cost and scale of rocket experiments. In 2002, UNISEC (University Space Engineering Consortium) and HASTIC (Hokkaido Aerospace Science and Technology Incubation Center) took over the educational and R&D rocket activities respectively and the research group dissolved. In 2008, JAXA/ISAS and eleven universities formed "Hybrid Rocket Research Working Group" as a subcommittee of the Steering Committee for Space Engineering in ISAS. Their goal is to demonstrate technical feasibility of lowcost and high frequency launches of nano/micro satellites into sun-synchronous orbits. Hybrid rockets use a combination of solid and liquid propellants. Usually the fuel is in a solid phase. A serious problem of hybrid rockets is the low regression rate of the solid fuel. In single port hybrids the low regression rate below 1 mm/s causes large L/D exceeding a hundred and small fuel loading ratio falling below 0.3. Multi-port hybrids are a typical solution to solve this problem. However, this solution is not the mainstream in Japan. Another approach is to use high regression rate fuels. For example, a fuel regression rate of 4 mm/s decreases L/D to around 10 and increases the loading ratio to around 0.75. Liquefying fuels such as paraffins are strong candidates for high regression fuels and subject of active research in Japan too. Nakagawa et al. in Tokai University employed EVA (Ethylene Vinyl Acetate) to modify viscosity of paraffin based fuels and investigated the effect of viscosity on regression rates. Wada et al. in Akita University employed LTP (Low melting ThermoPlastic) as another candidate of liquefying fuels and demonstrated high regression rates comparable to paraffin fuels. Hori et al. in JAXA/ISAS employed glycidylazide-poly(ethylene glycol) (GAP-PEG) copolymers as high regression rate fuels and modified the combustion characteristics by changing the PEG mixing ratio. Regression rate improvement by changing internal ballistics is another stream of research. The author proposed a new fuel configuration named "CAMUI" in 1998. CAMUI comes from an abbreviation of "cascaded multistage impinging-jet" meaning the distinctive flow field. A CAMUI type fuel grain consists of several cylindrical fuel blocks with two ports in axial direction. The port alignment shifts 90 degrees with each other to make jets out of ports impinge on the upstream end face of the downstream fuel block, resulting in intense heat transfer to the fuel. Yuasa et al. in Tokyo Metropolitan University employed swirling injection method and improved regression rates more than three times higher. However, regression rate distribution along the axis is not uniform due to the decay of the swirl strength. Aso et al. in Kyushu University employed multi-swirl injection to solve this problem. Combinations of swirling injection and paraffin based fuel have been tried and some results show very high regression rates exceeding ten times of conventional one. High fuel regression rates by new fuel, new internal ballistics, or combination of them require faster fuel-oxidizer mixing to maintain combustion efficiency. Nakagawa et al. succeeded to improve combustion efficiency of a paraffin-based fuel from 77% to 96% by a baffle plate. Another effective approach some researchers are trying is to use an aft-chamber to increase residence time. Better understanding of the new flow fields is necessary to reveal basic mechanisms of regression enhancement. Yuasa et al. visualized the combustion field in a swirling injection type motor. Nakagawa et al. observed boundary layer combustion of wax-based fuels. To understand detailed flow structures in swirling flow type hybrids, Sawada et al. (Tohoku Univ.), Teramoto et al. (Univ. of Tokyo), Shimada et al. (ISAS), and Tsuboi et al. (Kyushu Inst. Tech.) are trying to simulate the flow field numerically. Main challenges are turbulent reaction, stiffness due to low Mach number flow, fuel regression model, and other non-steady phenomena. Oshima et al. in Hokkaido University simulated CAMUI type flow fields and discussed correspondence relation between regression distribution of a burning surface and the vortex structure over the surface.

• Journal of Intelligence and Information Systems
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• v.25 no.3
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• pp.43-62
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• 2019

At one time, the anomaly detection sector dominated the method of determining whether there was an abnormality based on the statistics derived from specific data. This methodology was possible because the dimension of the data was simple in the past, so the classical statistical method could work effectively. However, as the characteristics of data have changed complexly in the era of big data, it has become more difficult to accurately analyze and predict the data that occurs throughout the industry in the conventional way. Therefore, SVM and Decision Tree based supervised learning algorithms were used. However, there is peculiarity that supervised learning based model can only accurately predict the test data, when the number of classes is equal to the number of normal classes and most of the data generated in the industry has unbalanced data class. Therefore, the predicted results are not always valid when supervised learning model is applied. In order to overcome these drawbacks, many studies now use the unsupervised learning-based model that is not influenced by class distribution, such as autoencoder or generative adversarial networks. In this paper, we propose a method to detect anomalies using generative adversarial networks. AnoGAN, introduced in the study of Thomas et al (2017), is a classification model that performs abnormal detection of medical images. It was composed of a Convolution Neural Net and was used in the field of detection. On the other hand, sequencing data abnormality detection using generative adversarial network is a lack of research papers compared to image data. Of course, in Li et al (2018), a study by Li et al (LSTM), a type of recurrent neural network, has proposed a model to classify the abnormities of numerical sequence data, but it has not been used for categorical sequence data, as well as feature matching method applied by salans et al.(2016). So it suggests that there are a number of studies to be tried on in the ideal classification of sequence data through a generative adversarial Network. In order to learn the sequence data, the structure of the generative adversarial networks is composed of LSTM, and the 2 stacked-LSTM of the generator is composed of 32-dim hidden unit layers and 64-dim hidden unit layers. The LSTM of the discriminator consists of 64-dim hidden unit layer were used. In the process of deriving abnormal scores from existing paper of Anomaly Detection for Sequence data, entropy values of probability of actual data are used in the process of deriving abnormal scores. but in this paper, as mentioned earlier, abnormal scores have been derived by using feature matching techniques. In addition, the process of optimizing latent variables was designed with LSTM to improve model performance. The modified form of generative adversarial model was more accurate in all experiments than the autoencoder in terms of precision and was approximately 7% higher in accuracy. In terms of Robustness, Generative adversarial networks also performed better than autoencoder. Because generative adversarial networks can learn data distribution from real categorical sequence data, Unaffected by a single normal data. But autoencoder is not. Result of Robustness test showed that he accuracy of the autocoder was 92%, the accuracy of the hostile neural network was 96%, and in terms of sensitivity, the autocoder was 40% and the hostile neural network was 51%. In this paper, experiments have also been conducted to show how much performance changes due to differences in the optimization structure of potential variables. As a result, the level of 1% was improved in terms of sensitivity. These results suggest that it presented a new perspective on optimizing latent variable that were relatively insignificant.

• Journal of the Korean Institute of Landscape Architecture
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• v.47 no.3
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• pp.39-48
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• 2019

This research is based on the analysis of in-depth interviews of designers who participated in the design of the Yeonnam-dong section, which was completed in 2016. The case study site has received many domestic and foreign awards and is receiving very positive reviews from actual users. 53 concepts were derived from the open coding of the ground theory methodology. Thirty-four higher categories incorporated the concepts and 18 higher categories that reintegrated them. Later, the six categories of the ground theory were interpreted as the paradigm, and it was determined that the aspects of 'will of client' and 'work efficiency', 'site resources' and 'field manager's specialty' were the categories that had the greatest positive impact on the park construction. The key category of this park's construction was interpreted as "a park-construction model with active empathy and communication." The results of the study and are linked to the following research proposals. First, the need to improve the trust between the client and the landscape designer and the need to improve the customary administrative procedures; second, the importance of the input of landscape experts into the park construction process; third, the importance of all efforts to develop the design; fourth, the importance of on-site circular resources and landscape preservation; and fifth active social participation to increase the opportunity. This study, which seeks to grasp the facts that existed behind the park's construction, which received excellent internal and external evaluations, and has a qualitative, objective and structural interpretation of the social network related to the park's construction, in contrast to the conventional quantitative post-evaluation. It is expected that the administration and system improvements related to landscaping will be further improved through the continuation of in-depth post-evaluation studies.

• Journal of the Korean Institute of Landscape Architecture
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• v.48 no.6
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• pp.25-38
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• 2020

The objective of this study is to propose a direction for creating a memorial park for the 250 students victims of the Sewol ferry disaster. To this end, this study first attempted to understand the matters discussed at various levels to create a memorial park and find a way that the park can be built by gathering opinions from the bereaved families and the victims themselves, as well as local residents, and experts. Workshops, competitions, special lectures, and websites, etc, were analyzed. A social discourse analysis methodology was used for systematic analysis, and the analyzed discourse was categorized into 4 types for assessment, and the functions and roles were subdivided into 15 types. To assess the priorities and the adequacy of the discourse, an analytic hierarchy process (AHP) was used among 30 activists, public servants, and experts. Then, a survey was conducted to analyze the perception of the residents (467 participants including the bereaved families) about the memorial park. Based on the results of the analysis, two directions were set for the memorial park. First, is a memorial park to remember the victims in everyday life. It must be a park with various cultural contents instead of a conventional memorial park that is solemn and grave sharing anguish and sorrow. The memorial park for the Sewol ferry disaster must become a space where visitors can naturally encounter and remember the victims. Second, is a park that serves as a catalyst that brings change and innovation to the community. It must be able to bring change to the community with direct and indirect influence. It must serve as an impetus to bring change and innovation to the community in the mid-to-long-term. Having many visitors may also lead to an economic effect. These visitors may not just stay in the park, but even contribute to revitalizing the local businesses. The purpose of this study is to apply the research findings to guide the International Design Competition scheduled for 2020 and serve to establish guidelines for a continuous park management system.

• Journal of the Korea Organic Resources Recycling Association
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• v.29 no.1
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• pp.19-27
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• 2021

Hydroponic farming is a method to grow a plant without soil. Plants can be grown on water or hydroponic growing media, and they are fed with mineral nutrient solutions, which are fertilizers dissolved into water. Hydroponic farming has the advantage of increasing plant productivity over conventional greenhouse farming. Previous studies of hydroponic nutrient wastewater from acyclic hydroponic farms pointed out that hydroponic nutrient wastewater contained residual nutrients, and they were drained to a nearby river bank which causes several environmental issues. Also, previous studies suggest that excessive use of the nutrient solution and disposal of used hydroponic growing media and crop wastes in hydroponic farms are major problems to hydroponic farming. This study was conducted to determine the impact of hydroponic nutrient wastewater, used hydroponic growing media, and crop wastes from acyclic hydroponic farms on the surrounding environment by analyzing water quality and soil analysis of the above three factors. Three soil cultivation farms and several hydroponic farms in the Gangwon C region were selected for this study. Samples of water and soils were collected from both inside and outside of each farm. Also, a sample of soil and leachate from crop waste piles stacked near the farm was collected for analysis. Hydroponic nutrient wastewater from acyclic hydroponic farm contained an average of 402 mg/L of total nitrogen (TN) concentration, and 77.4 mg/L of total phosphate (TP) concentration. The result of TP in hydroponic nutrient wastewater exceeds the living environmental standard of the river in enforcement decree of the framework act on environmental policy by 993.7 times. Also, it exceeds the standard of industrial wastewater discharge standards under the water environment conservation act by 6~19 times in TN, and 2~27 times in TP. Leachate from crop waste piles contained 11,828 times higher COD and 395~2662 times higher TP than the standard set by the living environmental standard of the river in enforcement decree of the framework act on environmental policy and exceeds 778 times higher TN and 5 times higher TP than the standard of industrial wastewater discharge standards under the water environment conservation act. For more precise studies of the impact of hydroponic nutrient wastewater, used hydroponic growing media, and crop wastes from acyclic hydroponic farms on the surrounding environment, additional information regarding a number of hydroponic farms, arable area(ha), hydroponic farming area, seasonal, weather, climate factor around the river, and the property of the area and farm is needed. Analysis of these factors and additional water and soil samples are needed for future studies.

• Journal of Korea Water Resources Association
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• v.55 no.8
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• pp.623-634
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• 2022

Due to river maintenance projects such as the creation of hydrophilic areas around rivers and the Four Rivers Project, the flow characteristics of rivers are continuously changing, and the risk of water quality accidents due to the inflow of various pollutants is increasing. In the event of a water quality accident, it is necessary to minimize the effect on the downstream side by predicting the concentration and arrival time of pollutants in consideration of the flow characteristics of the river. In order to track the behavior of these pollutants, it is necessary to calculate the diffusion coefficient and dispersion coefficient for each section of the river. Among them, the dispersion coefficient is used to analyze the diffusion range of soluble pollutants. Existing experimental research cases for tracking the behavior of pollutants require a lot of manpower and cost, and it is difficult to obtain spatially high-resolution data due to limited equipment operation. Recently, research on tracking contaminants using RGB drones has been conducted, but RGB images also have a limitation in that spectral information is limitedly collected. In this study, to supplement the limitations of existing studies, a hyperspectral sensor was mounted on a remote sensing platform using a drone to collect temporally and spatially higher-resolution data than conventional contact measurement. Using the collected spatio-temporal hyperspectral images, the tracer concentration was calculated and the transverse dispersion coefficient was derived. It is expected that by overcoming the limitations of the drone platform through future research and upgrading the dispersion coefficient calculation technology, it will be possible to detect various pollutants leaking into the water system, and to detect changes in various water quality items and river factors.