• International Journal of Highway Engineering
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• v.9 no.4
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• pp.83-92
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• 2007

In 2004, the number of traffic crashes and deaths in Korea are 220,755 and 6,563, respectively. Korea Road Traffic Safety Authority reported that the number of traffic accidents occupies over 25% out of total accidents, and found that traffic crash probability is extremely high at intersections since intersections have various traffic conflict points. A Safety study using Traffic Conflict Technique is much more useful than a study using reported traffic accident data. Existing traffic conflict research hardly considered conflict severity occurring at intersections. So, the study developed new criteria considering conflict severity. Analytic methods precisely detecting crashing points using field surveying data, and applied an application of our new criteria. Opposing left-turn conflict criteria was devided by three groups(high severe conflict, middle severe conflict, and less severe conflict) based on conflict boundary by means of a standard vehicle length. After analyzing field surveying data(3hours), we found totally 41 opposing left-turn conflicts. 3 cases are high severe conflict, and another 10 cases are middle severe conflicts, and the other cases are less severe. Studies related in conflict severity are considerably important to evaluate intersection's detailed safety index, and existing studies(purely conflict counting does not consider severity) have a limitation to clearly determine the level of safety of intersections for an application.

• Journal of Korean Society of Transportation
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• v.26 no.4
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• pp.77-86
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• 2008

Firstly, this study is to compare two types of productivity changes in Seoul's urban bus industry by public transport reforms: one with considering accident costs (ML), the other without considering accident costs (M). The directional distance function (DDF), which is a form of data envelopment analysis, and the Malmquist (Luenberger) productivity index (ML, M) are used for the analysis. The results show that productivity increased regardless of accident costs over time, and the ML index is a little higher than the M index, which means that most firms experienced more of a reduction ratio of accident costs than a reduction ratio of inputs. Secondly, this paper is to analyze how reforms affect productivity changes. The results show that operational speed improvements or passenger increases most affect productivity increases, which means that the installment of median bus lanes or introduction of free transfers among public transport modes were effective in reducing both inputs and accident costs. However, operational system reforms including mid-public management were related with productivity changes but they were not as effective.

• Journal of Korean Home Economics Education Association
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• v.33 no.3
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• pp.173-187
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• 2021

The purpose of this research was to develop instructions for making upcycled clothing accessories related to the 'clothing management and recycling' unit of middle school home economics applying the design thinking technique. Teaching and learning process plans were developed according to the ADDIE model which includes the following process: analysis, design, development, implementation, and evaluation. The design thinking process includes understanding the related knowledge, sympathizing, problem identification(sharing perspectives) and idea development, making prototypes, testing, and making the actual product. Thirteen home economics teachers served as critics. Student feedbacks were collected to evaluate whether the course objectives were attained after the implementation. As a result, teaching and learning process plans, course materials, and evaluation rubrics for ten class sessions were developed. Student feedbacks confirmed the attainment of following five course objectives: improvement of ethical responsibilities through the exploration of various clothing recycling techniques, practice of creative and eco-friendly clothing culture, acquisition of the skills to use sewing tools safely, improvement of abilities to think, sympathize, and communicate, and exploration of aesthetic activities and fashion careers.

• KSCE Journal of Civil and Environmental Engineering Research
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• v.28 no.3D
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• pp.445-450
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• 2008

Recently, environmental and ecological approaches is in progress in urban stream, especially the guarantee of instream flow becomes very important. In this paper, it is suggested that water volume estimation method utilizing the topographical shape data obtained by field investigation and satellite image to manage the urban stream efficiently. The data obtained at Gap River is the study area are analysed and those results are as belows. First, surveying to investigate topographic shape characteristics of urban stream is carried out. In details, the gradient characteristics from water surface to bottom in case of sand area and in case of grass area are 0.013 and 0.065 respectively. In conclusion, the gradient characteristic of grass area is five times bigger than that of sand area. Besides, IKONOS image is classified by spectrum analysis and Minimum Distance Method and the sand area extraction method by the generalization method as Median filter is suggested to calculate water volume. Finally, mapping process on the sand area extracted from the topographical shape field data in river and satellite images is carried out by the GIS spatial analysis. And on the assumption that the water level was 1m at that time when satellite image was taken, the water volume was $225,258m^3$. It is clarified that the effect of water volume improvement was about 10.5% in comparison with water volume that had no consideration on the gradient characteristics of sand-bar.

• Fire Science and Engineering
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• v.18 no.1
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• pp.54-66
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• 2004

In this article, we are to suggest the hazard-assessing method for the underground pipelines, and find out the pipeline-maintenance schemes of high efficiency in cost. Three kinds of methods are applied in order to refer to the approaching methods of listing the hazards for the underground pipelines: the first is RBI(Risk Based Inspection), which firstly assess the effect of the neighboring population, the dimension, thickness of pipe, and working time. It enables us to estimate quantitatively the risk exposure. The second is the scoring system which is based on the environmental factors of the buried pipelines. Last we quantify the frequency of the releases using the present THOMAS' theory. In this work, as a result of assessing the hazard of it using SPC scheme, the hazard score related to how the gas pipelines erodes indicate the numbers from 30 to 70, which means that the assessing criteria define well the relative hazards of actual pipelines. Therefore. even if one pipeline region is relatively low score, it can have the high frequency of leakage due to its longer length. The acceptable limit of the release frequency of pipeline shows 2.50E-2 to 1.00E-l/yr, from which we must take the appropriate actions to have the consequence to be less than the acceptable region. The prediction of total frequency using regression analysis shows the limit operating time of pipeline is the range of 11 to 13 years, which is well consistent with that of the actual pipeline. Concludingly, the hazard-listing scheme suggested in this research will be very effectively applied to maintaining the underground pipelines.

• Journal of Food Hygiene and Safety
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• v.32 no.4
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• pp.306-313
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• 2017

This study systemically analyzed the data on the microbial levels in fresh vegetables in Korea to identify the points to control. We scanned the studies published between 2001 and 2015 in peer-reviewed research papers on the microbial levels in fresh vegetables produced in Korea. Plant products were categorized by using the US IFSAC (Interagency Food Safety Analytics Collaboration) category. The most consumed, the non-heat treated, the epidemiological foodborne diseases sources of fresh vegetable in foodservice (KCDC data) were identified by literature review. Articles were screened using National Digital Science Library (NDSL) search engine regarding to microbial hazards in plant products. Based on the total plate count number and coliforms on the 89 data cases from 26 published articles, the total plate count number was high in the order of sprouts, leaf and stem, bulbs and roots, vine-grown, solanaceous, melons, and pome. Escherichia coli was frequently detected in leaf and stem and sprouts products. Focused on the microbial data of leek, lettuce and cabbage, the levels of total plate count, coliforms and Bacillus cereus showed the levels of 4.15~7.69 log CFU/g, 1~6.99 log CFU/g, and 0.51~3.9 log CFU/g, respectively, by 33 published papers. The levels of environmental factors affecting the microbial safety of lettuce and leek before harvest were investigated. Manure, soil, hands, scale, gloves were the major potential microbial contamination points to control. In addition, GAP (good agricultural practice), microbial testing, and improvement of irrigation methods are required to provide the safer fresh produce.

• The Journal of Korea Institute of Information, Electronics, and Communication Technology
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• v.14 no.3
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• pp.201-207
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• 2021

Deep learning, a type of machine learning, performs learning while changing the weights as it progresses through each learning process. Tensor Flow and Keras provide the results of the end of the learning in graph form. Thus, If an error occurs, the result must be discarded. Consequently, existing technologies provide a function to roll back learning results, but the rollback function is limited to results up to five times. Moreover, they applied the concept of MLOps to track the deep learning process, but no rollback capability is provided. In this paper, we construct a system that manages the intermediate value of the learning process by blockchain to record the intermediate learning process and can rollback in the event of an error. To perform the functions of blockchain, the deep learning process and the rollback of learning results are designed to work by writing Smart Contracts. Performance evaluation shows that, when evaluating the rollback function of the existing deep learning method, the proposed method has a 100% recovery rate, compared to the existing technique, which reduces the recovery rate after 6 times, down to 10% when 50 times. In addition, when using Smart Contract in Ethereum blockchain, it is confirmed that 1.57 million won is continuously consumed per block creation.

• Journal of the Korean Society for information Management
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• v.39 no.3
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• pp.99-132
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• 2022

The purpose of this study is to propose AET (Augmented and Extended Topics), a novel method of synthesizing both LDA and BERTopic results, and to analyze the recently published LIS articles as an experimental approach. To achieve the purpose of this study, 55,442 abstracts from 85 LIS journals within the WoS database, which spans from January 2001 to October 2021, were analyzed. AET first constructs a WORD2VEC-based cosine similarity matrix between LDA and BERTopic results, extracts AT (Augmented Topics) by repeating the matrix reordering and segmentation procedures as long as their semantic relations are still valid, and finally determines ET (Extended Topics) by removing any LDA related residual subtopics from the matrix and ordering the rest of them by F₁ (BERTopic topic size rank, Inverse cosine similarity rank). AET, by comparing with the baseline LDA result, shows that AT has effectively concretized the original LDA topic model and ET has discovered new meaningful topics that LDA didn't. When it comes to the qualitative performance evaluation, AT performs better than LDA while ET shows similar performances except in a few cases.

• KIPS Transactions on Computer and Communication Systems
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• v.9 no.11
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• pp.273-280
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• 2020

Automatic Static Analysis Tools help developers to quickly find potential defects in source code with less effort. However, the tools reports a large number of false positive warnings which do not have to fix. In our study, we proposed an artificial neural network-based warning classification method using topic models of source code blocks. We collect revisions for fixing bugs from software change management (SCM) system and extract code blocks modified by developers. In deep learning stage, topic distribution values of the code blocks and the binary data that present the warning removal in the blocks are used as input and target data in an simple artificial neural network, respectively. In our experimental results, our warning classification model based on neural network shows very high performance to predict label of warnings such as true or false positive.

• Journal of the Korean Association of Geographic Information Studies
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• v.7 no.3
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• pp.99-107
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• 2004

This study presents an application of GIS technologies to construct the graphic user interface for 3-dimensional exhibition of the results obtained by ocean hydrodynamic model. In coastal management studies, GIS provide a receptacle for scattered data from diverse sources and an improvement of the 3D visualization of such data. Within the frame of a GIS a variety of analytical, statistical and modeling tools can be applied to transform data and make them suitable for a given application. A 3D hydrodynamic model was driven by time-dependent external forcing such as tide, wind velocity, temperature. salinity, river discharge, and solar radiation under the open boundary condition. The Jinhae bay was selected as a case study. Here, we have used GeoMania v2.5 GIS software and its 3D Analyst extension module to visualize hydrodynamic model result that were simulated around the Jinhae bay.