• Journal of Intelligence and Information Systems
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• v.26 no.3
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• pp.109-125
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• 2020

The Ministry of National Defense is pushing for the Defense Acquisition Program to build strong defense capabilities, and it spends more than 10 trillion won annually on defense improvement. As the Defense Acquisition Program is directly related to the security of the nation as well as the lives and property of the people, it must be carried out very transparently and efficiently by experts. However, the excessive diversification of laws and regulations related to the Defense Acquisition Program has made it challenging for many working-level officials to carry out the Defense Acquisition Program smoothly. It is even known that many people realize that there are related regulations that they were unaware of until they push ahead with their work. In addition, the statutory statements related to the Defense Acquisition Program have the tendency to cause serious issues even if only a single expression is wrong within the sentence. Despite this, efforts to establish a sentence comparison system to correct this issue in real time have been minimal. Therefore, this paper tries to propose a "Comparison System between the Statement of Military Reports and Related Laws" implementation plan that uses the Siamese Network-based artificial neural network, a model in the field of natural language processing (NLP), to observe the similarity between sentences that are likely to appear in the Defense Acquisition Program related documents and those from related statutory provisions to determine and classify the risk of illegality and to make users aware of the consequences. Various artificial neural network models (Bi-LSTM, Self-Attention, D_Bi-LSTM) were studied using 3,442 pairs of "Original Sentence"(described in actual statutes) and "Edited Sentence"(edited sentences derived from "Original Sentence"). Among many Defense Acquisition Program related statutes, DEFENSE ACQUISITION PROGRAM ACT, ENFORCEMENT RULE OF THE DEFENSE ACQUISITION PROGRAM ACT, and ENFORCEMENT DECREE OF THE DEFENSE ACQUISITION PROGRAM ACT were selected. Furthermore, "Original Sentence" has the 83 provisions that actually appear in the Act. "Original Sentence" has the main 83 clauses most accessible to working-level officials in their work. "Edited Sentence" is comprised of 30 to 50 similar sentences that are likely to appear modified in the county report for each clause("Original Sentence"). During the creation of the edited sentences, the original sentences were modified using 12 certain rules, and these sentences were produced in proportion to the number of such rules, as it was the case for the original sentences. After conducting 1 : 1 sentence similarity performance evaluation experiments, it was possible to classify each "Edited Sentence" as legal or illegal with considerable accuracy. In addition, the "Edited Sentence" dataset used to train the neural network models contains a variety of actual statutory statements("Original Sentence"), which are characterized by the 12 rules. On the other hand, the models are not able to effectively classify other sentences, which appear in actual military reports, when only the "Original Sentence" and "Edited Sentence" dataset have been fed to them. The dataset is not ample enough for the model to recognize other incoming new sentences. Hence, the performance of the model was reassessed by writing an additional 120 new sentences that have better resemblance to those in the actual military report and still have association with the original sentences. Thereafter, we were able to check that the models' performances surpassed a certain level even when they were trained merely with "Original Sentence" and "Edited Sentence" data. If sufficient model learning is achieved through the improvement and expansion of the full set of learning data with the addition of the actual report appearance sentences, the models will be able to better classify other sentences coming from military reports as legal or illegal. Based on the experimental results, this study confirms the possibility and value of building "Real-Time Automated Comparison System Between Military Documents and Related Laws". The research conducted in this experiment can verify which specific clause, of several that appear in related law clause is most similar to the sentence that appears in the Defense Acquisition Program-related military reports. This helps determine whether the contents in the military report sentences are at the risk of illegality when they are compared with those in the law clauses.

• Journal of Korean Society for Atmospheric Environment
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• v.28 no.3
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• pp.233-248
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• 2012

The national emission from energy sector accounted for 84.7% of all domestic emissions in 2007. Of the energy-use emissions, the emission from mobile source as one of key categories accounted for 19.4% and further the road transport emission occupied the most dominant portion in the category. The road transport emissions can be estimated on the basis of either the fuel consumed (Tier 1) or the distance travelled by the vehicle types and road types (higher Tiers). The latter approach must be suitable for simultaneously estimating $CO_2$, $CH_4$, and $N_2O$ emissions in local administrative districts. The objective of this study was to estimate 31 municipal GHG emissions from road transportation in Gyeonggi Province, Korea. In 2008, the municipalities were consisted of 2,014 towns expressed as Dong and Ri, the smallest administrative district unit. Since mobile sources are moving across other city and province borders, the emission estimated by fuel sold is in fact impossible to ensure consistency between neighbouring cities and provinces. On the other hand, the emission estimated by distance travelled is also impossible to acquire key activity data such as traffic volume, vehicle type and model, and road type in small towns. To solve the problem, we applied a hierarchical cluster analysis to separate town-by-town road patterns (clusters) based on a priori activity information including traffic volume, population, area, and branch road length obtained from small 151 towns. After identifying 10 road patterns, a rule building expert system was developed by visual basic application (VBA) to assort various unknown road patterns into one of 10 known patterns. The expert system was self-verified with original reference information and then objects in each homogeneous pattern were used to regress traffic volume based on the variables of population, area, and branch road length. The program was then applied to assign all the unknown towns into a known pattern and to automatically estimate traffic volumes by regression equations for each town. Further VKT (vehicle kilometer travelled) for each vehicle type in each town was calculated to be mapped by GIS (geological information system) and road transport emission on the corresponding road section was estimated by multiplying emission factors for each vehicle type. Finally all emissions from local branch roads in Gyeonggi Province could be estimated by summing up emissions from 1,902 towns where road information was registered. As a result of the study, the GHG average emission rate by the branch road transport was 6,101 kilotons of $CO_2$ equivalent per year (kt-$CO_2$ Eq/yr) and the total emissions from both main and branch roads was 24,152 kt-$CO_2$ Eq/yr in Gyeonggi Province. The ratio of branch roads emission to the total was 0.28 in 2008.

• Journal of the Korean Association of Geographic Information Studies
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• v.22 no.1
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• pp.1-18
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• 2019

This research measured and visualized the spatial dependency and the spatial heterogeneity of the small business in Cheonan-si, Asan-si with $100m{\times}100m$ grids based on global and local spatial autocorrelation. First, we confirmed positive spatial autocorrelation of small business in the research area using Moran's I Index, which is ESDA(Exploratory Spatial Data Analysis). And then, through Getis-Ord $GI{\ast}$, one kind of LISA(Local Indicators of Spatial Association), local patterns of spatial autocorrelation were visualized. These verified that Spatial Regression Model is valid for the location factor analysis on small business commercial buildings. Next, GWR(Geographically Weighted Regression) was used to analyze the spatial relations between the distribution of small business, hourly mobile traffic-based floating population, land use attributes index, residence, commercial building, road networks, and the node of traffic networks. Final six variables were applied and the accessibility to bus stops, afternoon time floating population, and evening time floating population were excluded due to multicollinearity. By this, we demonstrated that GWR is statistically improved compared to OLS. We visualized the spatial influence of the individual variables using the regression coefficients and local coefficients of determinant of the six variables. This research applied the measured population information in a practical way. Reflecting the dynamic information of the urban people using the commercial area. It is different from other studies that performed commercial analysis. Finally, this research has a differentiated advantage over the existing commercial area analysis in that it employed hourly changing commercial service population data and it applied spatial statistical models to micro spatial units. This research proposed new framework for the commercial analysis area analysis.

• 대한공업교육학회지
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• v.40 no.1
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• pp.142-162
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• 2015

The purpose of this study are to provide the basic data materials and implementations for successful performance of electric-work field representatives of South Korean firms by identifying their roles and competency and examining their educational need. For this research purposes, three phased analysis was followed on: (1) the roles of electric-work field representatives, (2) competency of electric-work field representatives and (3) educational need for their competency. This research method was to conduct a focus group interview for 10 expert field representatives along with survey. The collected data materials were processed by MS Excel and SPSS 21.0 for statistical analysis including average, standard deviation and other basic statistics; the gap in awareness of field representatives; and need values. For the needs analysis, the difference between significance of field representatives' competency and current status was examined by t test. And the awareness gap between competency importance and current status was identified based on the Borich equation. The Locus for Focus model was employed herein to identify the kinds of competency with high importance and high inconsistency to prioritize. As a result, this research has found as follows: first, the roles of field representatives were found to be in 13 different kinds of roles. Second, electric-work field representatives were found to need to have 16 different skills. Third, regarding the 16 abilities, the gap between current status and significance was analyzed herein. The results showed statistically significant differences in all cases. The Borich needs analysis found the first required ability was communication ability followed by power of execution, conflict management ability, analytical thinking and time management ability. Also, the results of Locus for Focus model analysis displayed that the first quadrant(HH) included 7 highly-demanded abilities of communication ability, analytical thinking, decision making ability, specialty, time management ability, power of execution and drive for work implementation. The top-priority group was found to have 5 items of communication ability, analytical thinking, time management ability, power of execution and drive for work implementation which were commonly seen in the Locus for Focus model outcomes. Based on these findings, this research could identify the roles and competency of electric-work field representatives and provide the basic data materials applicable to future personal management of electricity companies including recruitment, division of work, job description, evaluation, etc. Also this research offered guidelines on demanded abilities in the field and where to place priority. The kinds of abilities with high educational demand as found in this research must be considered in designing educational programs for the competency building of field representatives. This research is expected to provide useful information in developing such educational programs for field representatives.

• Korean Journal of Environmental Agriculture
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• v.27 no.2
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• pp.120-132
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• 2008

Remotely sensed images from a satellite can be applied for detecting and quantifying spatial and temporal variations in terms of landuse & landcover, crop growth, and disaster for agricultural applications. The purposes of this study were to analyze topography using DEM(digital elevation model) and classify landuse & landcover into 10 classes-paddy field, dry field, forest, bare land, grass & bush, water body, reclaimed land, salt farm, residence & building, and others-using Landsat TM images in North Korea. Elevation was greater than 1,000 meters in the eastern part of North Korea around Ranggang-do where Kaemagowon was located. Pyeongnam and Hwangnam in the western part of North Korea were low in elevation. Topography of North Korea showed typical 'east-high and west-low' landform characteristics. Landcover classification of North Korea using spectral reflectance of multi-temporal Landsat TM images was performed and the statistics of each landcover by administrative district, slope, and agroclimatic zone were calculated in terms of area. Forest areas accounted for 69.6 percent of the whole area while the areas of dry fields and paddy fields were 15.7 percent and 4.2 percent, respectively. Bare land and water body occupied 6.6 percent and 1.6 percent, respectively. Residence & building reached less than 1 percent of the country. Paddy field areas concentrated in the A slope ranged from 0 to 2 percent(greater than 80 percent). The dry field areas were shown in the A slope the most, followed by D, E, C, B, and F slopes. According to the statistics by agroclimatic zone, paddy and dry fields were mainly distributed in the North plain region(N-6) and North western coastal region(N-7). Forest areas were evenly distributed all over the agroclimatic regions. Periodic landcover analysis of North Korea based on remote sensing technique using satellite imagery can produce spatial and temporal statistics information for future landuse management and planning of North Korea.

• Journal of Energy Engineering
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• v.25 no.4
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• pp.93-102
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• 2016

Vehicle-to-Grid (V2G) system, bi-direction power trading technology, enables drivers possessing electric vehicle to sell the spare electricity charged in the vehicle to power distribution company. The drivers gain profit by charging electricity in the day time of high electricity rate. In this regard, the government is preparing the policies of building and supporting V2G infrastructure and demanding the potential consumers' preference for the V2G system. This paper attempts to analyze the consumers' preference using the data from obtained a survey of randomly selected 1,000 individuals. To this end, choice experiment, an economic technique, is employed here. The attributes considered in the study are residual amount of electricity, electricity trading hours, required plug-in time, and price measured as an amount additional to current gasoline vehicle price. The multinomial logit model, which requires the assumption of 'independence of irrelevant alternatives', is applied but the assumption could not be satisfied in our data. Thus, we finally utilized nested logit model which does not require the assumption. All the parameter estimates in the utility function are statistically significant at the 10% level. The estimation results show that the marginal willingness to pay (MWTP) for one hour increase in electricity trading hours is estimated to be KRW 1,601,057. On the other hand, a one percent reduction in residual amount of electricity and one hour reduction in required plug-in time in V2G system are computed to be KRW -91,911 and -470,619, respectively. The findings can provide policy makers with useful information for decision-making about introducing and managing V2G system.

• Journal of Life Science
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• v.31 no.9
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• pp.840-848
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• 2021

This study was conducted to estimate annual trends and the environmental effects in the racing records of Jeju horses. The Korean Racing Authority (KRA) collected 48,645 observations for 2,167 Jeju horses from 2002 to 2019. Racing records were preprocessed to eliminate errors that occur during the data collection. Racing times were adjusted for comparison between race distances. A stepwise Akaike information criterion (AIC) variable selection method was applied to select appropriate environment variables affecting racing records. The annual improvement of the race time was -0.242 seconds. The model with the lowest AIC value was established when variables were selected in the following order: year, budam classification, jockey ranking, trainer ranking, track condition, weather, age, and gender. The most suitable model was constructed when the jockey ranking and age variables were considered as random effects. Our findings have potential for application as basic data when building models for evaluating genetic abilities of Jeju horses.

• Korean Journal of Heritage: History & Science
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• v.55 no.1
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• pp.175-198
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• 2022

With the development of technology, the methods of digitally converting various forms of analog information have become common. As a result, the concept of recording, building, and reproducing data in a virtual space, such as digital heritage and digital reconstruction, has been actively used in the preservation and research of various cultural heritages. However, there are few existing research results that suggest optimal scanners for small and medium-sized relics. In addition, scanner prices are not cheap for researchers to use, so there are not many related studies. The 3D scanner specifications have a great influence on the quality of the 3D model. In particular, since the state of light reflected on the surface of the object varies depending on the type of light source used in the scanner, using a scanner suitable for the characteristics of the object is the way to increase the efficiency of the work. Therefore, this paper conducted a study on nine small and medium-sized buried cultural properties of various materials, including earthenware and porcelain, by period, to examine the differences in quality of the four types of 3D scanners. As a result of the study, optical scanners and small and medium-sized object scanners were the most suitable digital records of the small and medium-sized relics. Optical scanners are excellent in both mesh and texture but have the disadvantage of being very expensive and not portable. The handheld method had the advantage of excellent portability and speed. When considering the results compared to the price, the small and medium-sized object scanner was the best. It was the photo room measurement that was able to obtain the 3D model at the lowest cost. 3D scanning technology can be largely used to produce digital drawings of relics, restore and duplicate cultural properties, and build databases. This study is meaningful in that it contributed to the use of scanners most suitable for buried cultural properties by material and period for the active use of 3D scanning technology in cultural heritage.

• Management & Information Systems Review
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• v.37 no.3
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• pp.27-47
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• 2018

In this study, we examine how land use zoning affects the land price controlling other variables such as road-facing condition of the land, land form, land age after its development and land size. We employ geographically weighted regression analysis which reflects spatial dependency as methodology with a data sample of land transaction price data of Jangyu, a new town, in Korea. The results of our empirical analysis show that the respective coefficients of traditional regression and geographically weighted regression are not significantly different. However, after calculating Moran's Index with residuals of both OLS and GWR models, we find that Moran's Index of GWR decreases around 26% compared to that of OLS model, thus improving the problem of spatial autoregression of residuals considerably. Unlike our expectation, though, in both traditional regression and geographically weighted regression where residential exclusive area is used as a reference variable, the dummy variable of the residential land for both housing and shops shows a negative sign. This may be because the residential land for both housing and shops is usually located in the level area while the residential exclusive area is located at the foot of a mountain or on a gentle hill where the residents can have good quality air and scenery. Although the utility of the residential land for both housing and shops is higher than its counterpart's since it has higher floor area ratio, amenity which can be explained as high quality of air and scenery in this study seems to have higher impact in purchase of land for housing. On the other hand, land for neighbourhood living facility seems to be valued higher than any other land zonings used in this research since it has much higher floor area ratio than the two land zonings above and can have a building with up to 5 stories constructed on it. With regard to road-facing condition, land buyers seem to prefer land which faces a medium-width road as expected. Land facing a wide-width road may have some disadvantage in that it can be exposed to noise and exhaust gas from cars and that entrance may not be easy due to the high speed traffic of the road. In contrast, land facing a narrow road can be free of noise or fume from cars and have privacy protected while it has some inconvenience in that entrance may be blocked by cars parked in both sides of the narrow road. Finally, land age variable shows a negative sign, which means that the price of land declines over time. This may be because decline of the land price of Jangyu was bigger than that of other regions in Gimhae where Jangyu, a new town, also belong, during the global financial crisis of 2008.

• Journal of Intelligence and Information Systems
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• v.22 no.4
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• pp.69-85
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• 2016

Successful relationship with loving partners is one of the most important factors in life. In psychology, there have been some previous researches studying the factors influencing romantic relationships. However, most of these researches were performed based on statistical analysis; thus they have limitations in analyzing complex non-linear relationships or rules based reasoning. This research analyzes commitment and persistence in heterosexual involvement according to styles of loving using a datamining technique as well as statistical methods. In this research, we consider six different styles of loving - 'eros', 'ludus', 'stroge', 'pragma', 'mania' and 'agape' which influence romantic relationships between lovers, besides the factors suggested by the previous researches. These six types of love are defined by Lee (1977) as follows: 'eros' is romantic, passionate love; 'ludus' is a game-playing or uncommitted love; 'storge' is a slow developing, friendship-based love; 'pragma' is a pragmatic, practical, mutually beneficial relationship; 'mania' is an obsessive or possessive love and, lastly, 'agape' is a gentle, caring, giving type of love, brotherly love, not concerned with the self. In order to do this research, data from 105 heterosexual couples were collected. Using the data, a linear regression method was first performed to find out the important factors associated with a commitment to partners. The result shows that 'satisfaction', 'eros' and 'agape' are significant factors associated with the commitment level for both male and female. Interestingly, in male cases, 'agape' has a greater effect on commitment than 'eros'. On the other hand, in female cases, 'eros' is a more significant factor than 'agape' to commitment. In addition to that, 'investment' of the male is also crucial factor for male commitment. Next, decision tree analysis was performed to find out the characteristics of high commitment couples and low commitment couples. In order to build decision tree models in this experiment, 'decision tree' operator in the datamining tool, Rapid Miner was used. The experimental result shows that males having a high satisfaction level in relationship show a high commitment level. However, even though a male may not have a high satisfaction level, if he has made a lot of financial or mental investment in relationship, and his partner shows him a certain amount of 'agape', then he also shows a high commitment level to the female. In the case of female, a women having a high 'eros' and 'satisfaction' level shows a high commitment level. Otherwise, even though a female may not have a high satisfaction level, if her partner shows a certain amount of 'mania' then the female also shows a high commitment level. Finally, this research built a prediction model to establish whether the relationship will persist or break up using a decision tree. The result shows that the most important factor influencing to the break up is a 'narcissistic tendency' of the male. In addition to that, 'satisfaction', 'investment' and 'mania' of both male and female also affect a break up. Interestingly, while the 'mania' level of a male works positively to maintain the relationship, that of a female has a negative influence. The contribution of this research is adopting a new technique of analysis using a datamining method for psychology. In addition, the results of this research can provide useful advice to couples for building a harmonious relationship with each other. This research has several limitations. First, the experimental data was sampled based on oversampling technique to balance the size of each classes. Thus, it has a limitation of evaluating performances of the predictive models objectively. Second, the result data, whether the relationship persists of not, was collected relatively in short periods - 6 months after the initial data collection. Lastly, most of the respondents of the survey is in their 20's. In order to get more general results, we would like to extend this research to general populations.