• Spatial Information Research
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• v.9 no.2
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• pp.291-307
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• 2001

In today's environmental engineering practice, many technologies such as GIS have been adopted to analyze chemical and biological process in water bodies and pollutants movements on the land surface. However, the linkage between spatially represented land surface pollutants and the in-stream processes has been relatively weak. This lack of continuity needs to develop a method in order to link the spatially-based pollutant source characterization with the water quality modeling. The objective of this thesis was to develop a two-way(forward and backward) link between ArcView GIS software and the USEPA water quality model, WASP5. This thesis includes a literature review, the determination of the point source and non-point source loadings from WASP5 modeling, and the linkage of a GIS with WASP5 model. The GIS and model linkage includes pre-processing of the input data within a GIS to provide necessary information for running a model in the forms of external input files. The model results has been post-processed and stored in the GIS database to be reviewed in a user defined form such as a chart, or a table. The interface developed from this study would provide efficient environment to support the easier decision making form water quality management.

• Journal of the Computational Structural Engineering Institute of Korea
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• v.32 no.6
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• pp.383-390
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• 2019

A helideck is one of the essential structures in offshore platforms for the transportation of goods and operating personnel between land and offshore sites. As such, it should be carefully designed and installed for the safety of the offshore platform. In this study, a structural design optimization method for a lightweight offshore helideck is developed based on a genetic algorithm and an attainable design set concept. A helideck consists of several types of structural members such as plates, girders, stiffeners, trusses, and support elements, and the dimensions of these members are typically pre-defined by manufacturers. Therefore, design sets are defined by collecting the standard section data for these members from the American Institute of Steel Construction (AISC), and integer section labels are assigned as design variables in the genetic algorithm. The objective is to minimize the total weight of the offshore helideck while satisfying the maximum allowable stress criterion under various loading conditions including self-weight, wind direction, landing position, and landing condition. In addition, the unity check process is also utilized for additional verification of structural safety against buckling failure of the helideck.

• Journal of radiological science and technology
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• v.35 no.2
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• pp.133-139
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• 2012

For the examination of nuclear medicine, myocardial scan is a good method to evaluate a hemodynamic importance of coronary heart disease. but, the automatized qualitative measurement is additionally necessary to improve the decoding efficiency. we suggests the creation of cardiac three-dimensional model and model of three-dimensional cardiac thickness as a new measurement. For the experiment, cardiac reduced cross section was obtained from SPECT. Next, the pre-process was performed and image segmentation was fulfilled by level set. for the modeling of left cardiac thickness, it was realized by applying difference equation of two-dimensional laplace equation. As the result of experiment, it was successful to measure internal wall and external wall and three-dimensional modeling was realized by coordinate. and, with laplace formula, it was successful to develop the thickness of cardiac wall. through the three-dimensional model, defects were observed easily and position of lesion was grasped rapidly by the revolution of model. The model which was developed as the support index of decoding will provide decoding information to doctor additionally and reduce the rate of false diagnosis as well as play a great role for diagnosing IHD early.

• The Korean Journal of Archival Studies
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• no.37
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• pp.273-305
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• 2013

In order to actively use of records and information in current digital record management systems, we have to check whether a system is designed to fully support the user of records and whether the good use of the system is being. This study analyzed the status of the use of the search function of Records Management System(RMS) for public agencies, and evaluated them. In order to investigate the status of the use of the search function, it surveyed records managers of public agencies using the RMS. The result showed that records managers unsatisfied with the usability and the search performance of the RMS. To evaluate the search function, it identified the functional requirement of the system and develops a checklist that can be used for evaluation. Two assessments were conducted. Firstly, as pre-evaluation, it assessed the degree of implementation of the current RMS according to the checklist as an inspection chart using document examination method. Secondly, it assessed the degree of implementation using a survey of records managers of public agencies that use the RMS. Assessment results show the improvement of the basic features that are essential to the system is required. In particular, the search function is required to improve user-friendliness for the user. For the advance of RMS, this study discusses the necessity for improvement of the search functions, the build of continuous maintenance and management system, and the user education.

• International Journal of Computer Science & Network Security
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• v.23 no.1
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• pp.112-119
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• 2023

Traditionally used for networking computers and communications, the Internet has been evolving from the beginning. Internet is the backbone for many things on the web including social media. The concept of social networking which started in the early 1990s has also been growing with the internet. Social Networking Sites (SNSs) sprung and stayed back to an important element of internet usage mainly due to the services or provisions they allow on the web. Twitter and Facebook have become the primary means by which most individuals keep in touch with others and carry on substantive conversations. These sites allow the posting of photos, videos and support audio and video storage on the sites which can be shared amongst users. Although an attractive option, these provisions have also culminated in issues for these sites like posting offensive material. Though not always, users of SNSs have their share in promoting hate by their words or speeches which is difficult to be curtailed after being uploaded in the media. Hence, this article outlines a process for extracting user reviews from the Twitter corpus in order to identify instances of hate speech. Through the use of MPCA (Modified Principal Component Analysis) and ECNN, we are able to identify instances of hate speech in the text (Enhanced Convolutional Neural Network). With the use of NLP, a fully autonomous system for assessing syntax and meaning can be established (NLP). There is a strong emphasis on pre-processing, feature extraction, and classification. Cleansing the text by removing extra spaces, punctuation, and stop words is what normalization is all about. In the process of extracting features, these features that have already been processed are used. During the feature extraction process, the MPCA algorithm is used. It takes a set of related features and pulls out the ones that tell us the most about the dataset we give itThe proposed categorization method is then put forth as a means of detecting instances of hate speech or abusive language. It is argued that ECNN is superior to other methods for identifying hateful content online. It can take in massive amounts of data and quickly return accurate results, especially for larger datasets. As a result, the proposed MPCA+ECNN algorithm improves not only the F-measure values, but also the accuracy, precision, and recall.

• Journal of Korea Water Resources Association
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• v.57 no.3
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• pp.181-193
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• 2024

The increasing atmospheric imbalance caused by climate change leads to an elevation in precipitation, resulting in a heightened frequency of flooding. Consequently, there is a growing need for technology to detect and monitor these occurrences, especially as the frequency of flooding events rises. To minimize flood damage, continuous monitoring is essential, and flood areas can be detected by the Synthetic Aperture Radar (SAR) imagery, which is not affected by climate conditions. The observed data undergoes a preprocessing step, utilizing a median filter to reduce noise. Classification techniques were employed to classify water bodies and non-water bodies, with the aim of evaluating the effectiveness of each method in flood detection. In this study, the Otsu method and Support Vector Machine (SVM) technique were utilized for the classification of water bodies and non-water bodies. The overall performance of the models was assessed using a Confusion Matrix. The suitability of flood detection was evaluated by comparing the Otsu method, an optimal threshold-based classifier, with SVM, a machine learning technique that minimizes misclassifications through training. The Otsu method demonstrated suitability in delineating boundaries between water and non-water bodies but exhibited a higher rate of misclassifications due to the influence of mixed substances. Conversely, the use of SVM resulted in a lower false positive rate and proved less sensitive to mixed substances. Consequently, SVM exhibited higher accuracy under conditions excluding flooding. While the Otsu method showed slightly higher accuracy in flood conditions compared to SVM, the difference in accuracy was less than 5% (Otsu: 0.93, SVM: 0.90). However, in pre-flooding and post-flooding conditions, the accuracy difference was more than 15%, indicating that SVM is more suitable for water body and flood detection (Otsu: 0.77, SVM: 0.92). Based on the findings of this study, it is anticipated that more accurate detection of water bodies and floods could contribute to minimizing flood-related damages and losses.

• Journal of Intelligence and Information Systems
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• v.16 no.3
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• pp.163-179
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• 2010

Recentlythe concept of fast fashion is drawing attention as customer needs are diversified and supply lead time is getting shorter in fashion industry. It is emphasized as one of the critical success factors in the fashion industry how quickly and efficiently to satisfy the customer needs as the competition has intensified. Because the fast fashion is inherently susceptible to trend, it is very important for fashion retailers to make quick decisions regarding items to launch, quantity based on demand prediction, and the time to respond. Also the planning decisions must be executed through the business processes of procurement, production, and logistics in real time. In order to adapt to this trend, the fashion industry urgently needs supports from intelligent quick response(QR) system. However, the traditional functions of QR systems have not been able to completely satisfy such demands of the fast fashion industry. This paper proposes an intelligent quick response system for the fast fashion(IQRS-FF). Presented are models for QR process, QR principles and execution, and QR quantity and timing computation. IQRS-FF models support the decision makers by providing useful information with automated and rule-based algorithms. If the predefined conditions of a rule are satisfied, the actions defined in the rule are automatically taken or informed to the decision makers. In IQRS-FF, QRdecisions are made in two stages: pre-season and in-season. In pre-season, firstly master demand prediction is performed based on the macro level analysis such as local and global economy, fashion trends and competitors. The prediction proceeds to the master production and procurement planning. Checking availability and delivery of materials for production, decision makers must make reservations or request procurements. For the outsourcing materials, they must check the availability and capacity of partners. By the master plans, the performance of the QR during the in-season is greatly enhanced and the decision to select the QR items is made fully considering the availability of materials in warehouse as well as partners' capacity. During in-season, the decision makers must find the right time to QR as the actual sales occur in stores. Then they are to decide items to QRbased not only on the qualitative criteria such as opinions from sales persons but also on the quantitative criteria such as sales volume, the recent sales trend, inventory level, the remaining period, the forecast for the remaining period, and competitors' performance. To calculate QR quantity in IQRS-FF, two calculation methods are designed: QR Index based calculation and attribute similarity based calculation using demographic cluster. In the early period of a new season, the attribute similarity based QR amount calculation is better used because there are not enough historical sales data. By analyzing sales trends of the categories or items that have similar attributes, QR quantity can be computed. On the other hand, in case of having enough information to analyze the sales trends or forecasting, the QR Index based calculation method can be used. Having defined the models for decision making for QR, we design KPIs(Key Performance Indicators) to test the reliability of the models in critical decision makings: the difference of sales volumebetween QR items and non-QR items; the accuracy rate of QR the lead-time spent on QR decision-making. To verify the effectiveness and practicality of the proposed models, a case study has been performed for a representative fashion company which recently developed and launched the IQRS-FF. The case study shows that the average sales rateof QR items increased by 15%, the differences in sales rate between QR items and non-QR items increased by 10%, the QR accuracy was 70%, the lead time for QR dramatically decreased from 120 hours to 8 hours.

• KIPS Transactions on Computer and Communication Systems
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• v.10 no.10
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• pp.261-268
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• 2021

Cloud computing is a computing paradigm in which users can utilize computing resources in a pay-as-you-go manner. In a cloud system, resources can be dynamically scaled up and down to the user's on-demand so that the total cost of ownership can be reduced. The Modeling and Simulation (M&S) technology is a renowned simulation-based method to obtain engineering analysis and results through CAE software without actual experimental action. In general, M&S technology is utilized in Finite Element Analysis (FEA), Computational Fluid Dynamics (CFD), Multibody dynamics (MBD), and optimization fields. The work procedure through M&S is divided into pre-processing, analysis, and post-processing steps. The pre/post-processing are GPU-intensive job that consists of 3D modeling jobs via CAE software, whereas analysis is CPU or GPU intensive. Because a general-purpose desktop needs plenty of time to analyze complicated 3D models, CAE software requires a high-end CPU and GPU-based workstation that can work fluently. In other words, for executing M&S, it is absolutely required to utilize high-performance computing resources. To mitigate the cost issue from equipping such tremendous computing resources, we propose HEMOS-Cloud service, an integrated cloud and cluster computing environment. The HEMOS-Cloud service provides CAE software and computing resources to users who want to experience M&S in business sectors or academics. In this paper, the economic ripple effect of HEMOS-Cloud service was analyzed by using industry-related analysis. The estimated results of using the experts-guided coefficients are the production inducement effect of KRW 7.4 billion, the value-added effect of KRW 4.1 billion, and the employment-inducing effect of 50 persons per KRW 1 billion.

• Journal of Korean Academy of Fundamentals of Nursing
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• v.6 no.3
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• pp.532-543
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• 1999

This study was conducted to provide the basic data necessary for the improvement of the teaching method for basic nursing practice as well as the effectiveness of the practice by examining the students' competency in cleansing enema after doing the self study instead of the traditional education. To examine the competency in cleansing enema after the self study, this study is an one group pretest-posttest design that subjects did the enema practice through the self study. The subjects were 89 sophomore students at Y University. College of Nursing. In basic nursing lab practice class, cleansing enema self study module was given to the students which was developed by the researcher based on the literature review and asked them to finish doing the pre study and checking the self study evaluation criteria after reading the goal, learning activities and theoretical guideline. After watching the video tape, students practiced the process in the module by themselves. For the competency in cleansing enema. repeated autonomous practices were done during the open lab other than the regular class. Whenever the practice was done, the frequency and time were measure and documented. When the student felt confident through repeated practices, the competency was evaluated by the researcher and two assistants based on the evaluation criteria. And the process was repeated till the student could perform all the items on evaluation criteria completely. The data were collected for 42 days from Oct. 15 to Nov. 26 in 1996. Collected data were analyzed by frequency, percentage, Pearson correlation coefficient and variance analysis. The results are summarized as follows : 1. 43.2% of the students were favorable to nursing and 63.6% like lecture, but 71.6% like practice. So they were more interested in practice than in lecture. 2. 62.3% of the students scored high in written test, 97.8% scored high in practice. So the practice score was better. 3. The frequency of repeated practice to pass the test ranged from 1 to 4 and the average is 2.2. 4. The average time needed in preparation and the performance was nearly the same regardless of the frequency. It took 5 to 38 minutes for those who passed the test after practicing once and the average was 16 minutes. 5 to 60 minutes were taken for those who practiced twice to pass the test and the average was 21 minutes. Those who passed the test after three practices needed 8 to 30 minutes and the average was 15 minutes, which was similar to the time that the students who passed the test for the first trial. Only one student passed the test after 4 practices and it took 10 minutes. 5. 64% of the students agreed that the context and the content of the module were appropriate for the self study and 68.2% were satisfied. And 71.9% said that the module helped them to practice the enema self study 6. Though only 42% of the students were satisfied with the video. 50.6% said that it was helpful for the self study. 7. 52.3% of the students were satisfied with the self study method, and 86.6% obtained self-confidence when performing the enema. 8. The lower the student's practice score was, the more practices were needed for them to pass the test(r=-.213, P<.05). As a result, for performing the enema practice competently, two or more practice opportunities were needed to be given. And it is possible to obtain the less complex nursing skills through the self study, when enough learning resources and assistance such as learning guidance or video tapes are provided. Based on this study. I want to suggest that. 1. There must be college policy that can support the new method instead of the traditional learning method for the students to attain the proficiency in basic nursing skills. 2. The assistant materials should be developed as soon as possible to promote the self study of basic nursing skills.

• Korean Journal of Animal Reproduction
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• v.26 no.3
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• pp.245-252
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• 2002

This study was to evaluate the in vitro survival of bovine enucleated MII (eMII) oocytes according to minimum volume cooling (MVC) freezing method and activation timing, and their in vitro development after somatic cell nuclear transfer (SONT). in vitro matured bovine oocytes for 20 h were stained with 5 $\mu\textrm{g}$/$m\ell$ Hoechst, and their 1st polar body and MII plate were removed by enucleation micropipette under UV filter. Also, eMII oocytes were subjected to activation after (group II) and before (group III) vitrification in 5 ${\mu}{\textrm}{m}$ ionomycin added CRlaa medium for 5 min. For vitrification, eMll oocytes were pretreated with EG10 for 5 min, exposed to EG30 for 30 sec and then directly plunged into L$N_2$. Thawing was taken by 4-step procedures at 37$^{\circ}C$. Survived eMII oocytes were subjected to SONT with cultured adult bovine ear cells. Reconstructed oocytes were cultured in 10 $\mu\textrm{g}$/$m\ell$ of cycloheximide and 2.5 $\mu\textrm{g}$/$m\ell$ of cytochalasin D added CRlaa medium for 1 h, and then in 10 $\mu\textrm{g}$/$m\ell$ of cycloheximide added CRlaa medium for 4 h. Subsequently, the reconstructed oocytes were incubated for 2 days and cleaved embryos were further cultured on cumulus-cell monolayer drop in CRlaa medium for 6 days. Survival rates of bovine vitrified-thawed eMII oocytes in group II (activation after vitrification and thawing) and III (activation before vitrification) were 81.0% and 84.9%, respectively. Fusion rates of cytoplasts and oocytes in group II and III were 69.0% and 70.0%, respectively, and their results were not different with non-frozen NT group (control, 75.2%). Although their cleaved rates (53.4% and 58.4%) were not different, cytoplasmic fragment rate in group II (32.8%) was significantly higher than that in group III (15.6%)(P<0.05). Also, subsequent development rate into >morula in group II (8.6%) was low than that in group III(15.6%). However, in vitro development rate in group III was not different with that in control (24.8%). This result suggested that MVC method was appropriate freezing method for the bovine eMII oocytes and vitrified eMII oocytes after pre-activation could support in vitro embryonic development after SONT as equally well as fresh oocytes.