• KIPS Transactions on Software and Data Engineering
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• v.12 no.11
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• pp.471-480
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• 2023

The Korean construction order volume in South Korea grew significantly from 91.3 trillion won in public orders in 2013 to a total of 212 trillion won in 2021, particularly in the private sector. As the size of the domestic and overseas markets grew, the scale and complexity of EPC (Engineering, Procurement, Construction) projects increased, and risk management of project management and ITB (Invitation to Bid) documents became a critical issue. The time granted to actual construction companies in the bidding process following the EPC project award is not only limited, but also extremely challenging to review all the risk terms in the ITB document due to manpower and cost issues. Previous research attempted to categorize the risk terms in EPC contract documents and detect them based on AI, but there were limitations to practical use due to problems related to data, such as the limit of labeled data utilization and class imbalance. Therefore, this study aims to develop an AI model that can categorize the contract terms based on the FIDIC Yellow 2017(Federation Internationale Des Ingenieurs-Conseils Contract terms) standard in detail, rather than defining and classifying risk terms like previous research. A multi-text classification function is necessary because the contract terms that need to be reviewed in detail may vary depending on the scale and type of the project. To enhance the performance of the multi-text classification model, we developed the ELECTRA PLM (Pre-trained Language Model) capable of efficiently learning the context of text data from the pre-training stage, and conducted a four-step experiment to validate the performance of the model. As a result, the ensemble version of the self-developed ITB-ELECTRA model and Legal-BERT achieved the best performance with a weighted average F1-Score of 76% in the classification of 57 contract terms.

• Investigative Magnetic Resonance Imaging
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• v.3 no.2
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• pp.173-178
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• 1999

Purpose : To evaluate the usefulness of functional MRI (fMRI) of visual cortex in patients with ischemic infarction in the occipital lobe. Materials and Methods : Four patients with the symptoms and signs of visual cortical ischemia were included. Functional MRI was performed by 2D-FLASH technique with the parameter of 90/56msec TR/TE, $40^{\circ}$ flip angle, $240{\times}240{\;}FOV,{\;}64{\times}128$ matrix number, 8.32 seconds acquisition time, 8mm slice thickness. An axial slice including both visual cortices was selected and alternative activation and resting of the visual cortex was performed using red color photostimulator. all patients undertook visual field test, and vascular abnormality was examined by MRA (n=4) and DSA (n=2). fMRI results were compared with the results of a visual field test, conventional MRI and cerebral angiography. Results : On fMRI, decreased activity of the visual cortex was found in the occipital lobe corresponding to stenosis of the posterior cerebral artery or its branch noted on angiogram. However, 2 of 4 patients showed no abnormal findings on conventional MRI. Visual field defect was noted in 3 patients, one and of whom showed no abnormality on conventional MRI and diffusion-weighted image, but revealed decreased activity in the corresponding visual cortex on fMRI. Conclusion : fMRI may be a sensitive method for detection of the status of decreased blood flow or vascular reserve which other methods can not.

• Journal of the Korean Institute of Landscape Architecture
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• v.36 no.4
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• pp.83-99
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• 2008

Images of Seong-Nam appears different according to diverse conditions. This study was intended to analyze the differences of cognition by personal characteristics such as age, gender, location, and period when an individual evaluates an urban image. This research focused on the interpretation of the visualized results from Multidimensional Scaling (MDS) and Individual Difference Scaling (INDSCAL) with two questionnaires. This study can be summarized as follows: 1. Namhan Sansung was ranked as the first symbolic property by citizens in Seong-Nam. Next was Yuldong Park, followed by Bundang Central Park, Seohyun Station including Samsung Plaza, and, finally, Moran Market. This trend also similarly appeared in the selection of preferred places. 2. There were no statistical differences in trends of choice of symbolic landmarks and preferred places according to age, gender, and period; however, there were meaningful differences according to location. 3. The total image of Seong-Nam was positioned to be separated from images of other districts and landmarks on the image spatial plot by MDS; however, images of the old and new district were plotted close to symbolic landmarks where located around each district. 4. INDSCAL illustrated that men weighted the historical meaning while women weighted preference and city size when evaluating an urban image. On the other hand, there was no difference in cognitive trends according to age, location, and period. Until now, an individual difference in the cognition and evaluation of an urban image was a socially accepted notion. However, this study verified the difference according to personal characteristics and developed a practical tool to analyze an individual cognition trend about a city image.

• Journal of Food Hygiene and Safety
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• v.30 no.1
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• pp.43-50
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• 2015

In this study, single PCR and multiplex PCR tests were examined for identification of four types of squid species (giant squid, cuttlefish, octopus, beka squid) purchased from fish market as well as aquatic processed products in Busan. To design the specific primers against each species, the nucleotide sequences of the mitochondrial 16s rRNA gene of Architeuthis dux, Todarodes pacificus, Enteroctopus dofleini, Enteroctopus megalocyathus, Uroteuthis chinensis, Uroteuthis duvauceli, Uroteuthis edulis groups were analyzed for the identification of each species registered in the GeneBank (www.ncbi.nlm.nih.gov) and have been used for comparative analysis. In order to obtain the size variation of amplified fragments on multiplex PCR, we designed KOJ-F, OJ-F, OCT-F, HAN-F, ALLR primers for each species. The optimal PCR conditions and primers were selected for four types of squid species to determine target base sequences in its PCR products. In the case of single PCR, giant squid was only amplified by KOJ-F/ALLR primer; cuttlefish was only amplified by OJ-F/ALLR primer; octopus was only amplified by OCT-F/ALLR primer; and beka squid was only amplified by HAN-F/ALLR primer. For multiplex PCR, the mixture of four kinds of genomic DNA (giant squid, cuttlefish, octopus, beka squid) been prepared as a template and used together with the mixture of KOJ-F/OJ-F/OCT-F/HAN-F/ALLR primers in the reaction. By the multiplex PCR, it is confirmed that four samples are correspond to multiple simultaneous amplicon. Finally, we validated the established methods of multiplex PCR in the aquatic processed products. Although the mitochondrial 16s rRNA primers used in this study was useful as a marker for detection of each species among them, the study indicated that the established multiplex PCR method can be more useful tool for monitoring the processed products.

• Journal of the Korean Association of Geographic Information Studies
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• v.23 no.2
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• pp.1-20
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• 2020

The purpose of this study was to analyze the distribution characteristics of spatial and temporal PM_2.5 in urban areas of Changwon-si, and to identify the causes of PM_2.5 by comparing the characteristics of land-use, and to suggest the direction of reduction measures. As the basic data, the every hour average from September 2017 to August 2018 of Airpro data, which has measurement points in kindergartens, elementary schools, and some middle and high schools in Changwon-si was used. Also, by using IDW method among spatial interpolation methods of GIS, monthly and time-slot distribution maps were constructed, and based on this, spatial and temporal PM_2.5 distribution characteristics were confirmed. First, to verify the accuracy of the Airpro data, the correlation with AirKorea data managed by the Ministry of Environment was confirmed. As a result of the analysis, R² was 0.75~0.86, showing a very high correlation and the data was judged that it was suitable for the study. In the monthly analysis, January was the highest year, and August was the lowest. As a result of analysis by time-slot, The clock-in time at 06-09 was the highest, and the activity time at 09-18 was the lowest. By administrative district, Sangnam-dong, Happo-dong, and Myeonggok-dong were the most severe regions of PM_2.5 and Hoeseong-dong was the lowest. As a result of analyzing the land-use characteristics by administrative area, it was confirmed that the ratio of traffic area and commercial area is high in the serious area of PM_2.5. In conclusion, the results of this study will be used as basic data to grasp the characteristics of PM_2.5 distribution in Changwon-si. Also, it is thought that the severe regions and the direction of establishing reduction measures derived from this study can be used to prepare more effective policies than before.

• Journal of Intelligence and Information Systems
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• v.24 no.2
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• pp.221-241
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• 2018

Deep learning is getting attention recently. The deep learning technique which had been applied in competitions of the International Conference on Image Recognition Technology(ILSVR) and AlphaGo is Convolution Neural Network(CNN). CNN is characterized in that the input image is divided into small sections to recognize the partial features and combine them to recognize as a whole. Deep learning technologies are expected to bring a lot of changes in our lives, but until now, its applications have been limited to image recognition and natural language processing. The use of deep learning techniques for business problems is still an early research stage. If their performance is proved, they can be applied to traditional business problems such as future marketing response prediction, fraud transaction detection, bankruptcy prediction, and so on. So, it is a very meaningful experiment to diagnose the possibility of solving business problems using deep learning technologies based on the case of online shopping companies which have big data, are relatively easy to identify customer behavior and has high utilization values. Especially, in online shopping companies, the competition environment is rapidly changing and becoming more intense. Therefore, analysis of customer behavior for maximizing profit is becoming more and more important for online shopping companies. In this study, we propose 'CNN model of Heterogeneous Information Integration' using CNN as a way to improve the predictive power of customer behavior in online shopping enterprises. In order to propose a model that optimizes the performance, which is a model that learns from the convolution neural network of the multi-layer perceptron structure by combining structured and unstructured information, this model uses 'heterogeneous information integration', 'unstructured information vector conversion', 'multi-layer perceptron design', and evaluate the performance of each architecture, and confirm the proposed model based on the results. In addition, the target variables for predicting customer behavior are defined as six binary classification problems: re-purchaser, churn, frequent shopper, frequent refund shopper, high amount shopper, high discount shopper. In order to verify the usefulness of the proposed model, we conducted experiments using actual data of domestic specific online shopping company. This experiment uses actual transactions, customers, and VOC data of specific online shopping company in Korea. Data extraction criteria are defined for 47,947 customers who registered at least one VOC in January 2011 (1 month). The customer profiles of these customers, as well as a total of 19 months of trading data from September 2010 to March 2012, and VOCs posted for a month are used. The experiment of this study is divided into two stages. In the first step, we evaluate three architectures that affect the performance of the proposed model and select optimal parameters. We evaluate the performance with the proposed model. Experimental results show that the proposed model, which combines both structured and unstructured information, is superior compared to NBC(Naïve Bayes classification), SVM(Support vector machine), and ANN(Artificial neural network). Therefore, it is significant that the use of unstructured information contributes to predict customer behavior, and that CNN can be applied to solve business problems as well as image recognition and natural language processing problems. It can be confirmed through experiments that CNN is more effective in understanding and interpreting the meaning of context in text VOC data. And it is significant that the empirical research based on the actual data of the e-commerce company can extract very meaningful information from the VOC data written in the text format directly by the customer in the prediction of the customer behavior. Finally, through various experiments, it is possible to say that the proposed model provides useful information for the future research related to the parameter selection and its performance.

• Journal of Korean Society of Environmental Engineers
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• v.33 no.6
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• pp.439-446
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• 2011

In this research, enhanced land-cover classification methods using high-resolution satellite image (HRSI) and GIS in terms of practicality and accuracy was proposed. It aims for understanding non-point pollutant origin/loading, assessment the efficiency of rainfall storage/infiltration facilities and sounds water-environment management. The result of applying enhanced land-cover classification methods to the urban region verifies that roof and road area are including various vegetations such as roof garden, flower bed in the median strip and street tree. This accounts for 3% of total study area, and more importantly it was counted as impervious area by GIS alone or conventional indoor work. The feasibility of the method was assessed by applying to rainfall-runoff analysis for three weak rainfall in the range of 7.1-10.5 mm events in 2000, Chiba, Japan. A good agreement between simulated and observed runoff hydrograph was obtained. In comparison, the hydrograph simulated with land-use parameters by the detailed land-use information of 10m grid had an error between 31%~71%, while enhanced method showed 4% to 29%, and showed the improvement particularly for reproducing observed peak and recession flow rate of hydrograph in weak rainfall condition.

• The Journal of Korean society of community based occupational therapy
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• v.1 no.2
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• pp.11-20
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• 2011

Objective : The purpose of this study was to investigate the effects of the activities of daily living on time-use of the Elderly in facility. This study is also to provide basic data of the redesign time management and lifestyle as occupational therapy. Methods : The subjects were 20 elderly people (over 65 years) who live in S institution of Daejeun from August 11th, to August 22th in 2008. We used time table, interview and FIM which was to evaluate the ability to collect the general characteristics of these subjects(gender, age, moving period, education). Results : There was no significant different between the general characteristics of the subjects and activity of daily living. The more they spent time in Active BADL and IADL, the more they got higher scores in ADL performance ability(p<0.01). The more they spent time in the more they got higher score in ADL performance ability(p<0.05). Conclusion : We could know the amount of spending time of the elderly in Daejeun area facility and it related to activity of daily living. To improve the efficiency of time-use of the elderly, it is needed the role of occupational therapists. They should prepare a intervention to maintain active and positive life of the elderly.

• Journal of Wetlands Research
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• v.14 no.1
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• pp.21-33
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• 2012

The dominant land use at the Seonakdong river watershed is paddy and forest areas and the Seonakdong river stands still. Thus, the water pollution in the Seonakdong river is becoming more serious for the non-point source. In this study, SWAT(Soil and Water Assessment Tool) model was evaluated for simulation of flow and water quality behaviors in Seonakdong river. To perform the calibration and verification of the SWAT model, the measurements of discharge and water quality were performed for the period from 2006 to 2007 at 5 gauging stations in Seonakdong river. The $R^2$ value for discharge and water quality were 0.86 and 0.70 respectively for calibration after the sensitive analysis. The $R^2$ value for discharge and water quality were 0.81 and 0.51 respectively for verification. The simulation results show that BOD value in the river tends to decrease after the opening of gates and the patterns of TN and TP concentrations are similar as that of BOD. The gate operators need to determine how to supply water in drought season for effective water quality improvement. This study shows that the SWAT model, which is capable of simulating hydrologic and water quality behaviors temporarily and spatially at watershed scale, could be used to get the gate operation rule for the water quality management in Seonakdong river.

• Journal of the Korean Association of Geographic Information Studies
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• v.23 no.3
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• pp.120-131
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• 2020

Water body detection using remote sensing based on machine interpretation of satellite image is efficient for managing water resource, drought and flood monitoring. In this study, water body detection with SAR satellite image based on machine learning was performed. However, non water body area can be misclassified to water body because of shadow effect or objects that have similar scattering characteristic comparing to water body, such as roads. To decrease misclassifying, 8 combination of morphology open filtered band, DEM band, curvature band and Cosmo-SkyMed SAR satellite image band about Mokpo region were trained to semantic segmentation machine learning models, respectively. For 8 case of machine learning models, global accuracy that is final test result was computed. Furthermore, concordance rate between landcover data of Mokpo region was calculated. In conclusion, combination of SAR satellite image, morphology open filtered band, DEM band and curvature band showed best result in global accuracy and concordance rate with landcover data. In that case, global accuracy was 95.07% and concordance rate with landcover data was 89.93%.