The National Base Map construction consists of the regular correction work of dividing the whole country into two regions and carrying out the modification Plotting by aerial photographs every two years as well as the real time updating work of correcting the major change feature within two weeks by the field survey and the As-Built Drawing. In the case of the Building Layout Drawing of Korea Real estate Administration intelligence System(KRAS) used for real time updating work of the National base map, the coordinate transformation error is included in the positional error when applied to the National Base Map based on the World Geodetic Reference System as the coordinate system based on the Regional Geodetic Reference System. In addition, National Base Map is registered based on the outline(eaves line) of the building in the Digital Topographic Map, and the Cadastral and Architecture are registered based on the building center line. Therefore, the Building Object management standard is inconsistent. In order to investigate the improvement method, the network RTK survey was conducted directly on a location of the Building Layout Drawing of Korea Real estate Administration intelligence System(KRAS) and the problems were analyzed by comparing with the plane plotting position reference in National Base Map. In the case of the general structure with the difference on the Building center line and the eaves line, beside the location information was different also the difference in the ratio of the building object was different between Building center line and the eave. In conclusion, it is necessary to provide the Base data of the double layer of the Building center line and the outline of the building(eaves line) in order to utilize the Building Layout Drawing of Korea Real estate Administration intelligence System(KRAS). In addition, it is necessary to study an organic map update process that can acquire the up-to-dateness and the accuracy at the same time.
Journal of the Korean Association of Geographic Information Studies
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v.17
no.4
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pp.69-85
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2014
Carbon stocks of NFI plots can be accurately estimated using field survey information. However, an accurate estimation of carbon stocks in other unsurveyed sites is very difficult. In order to fill this gap, various spatial information can be used as an ancillary data. In South Korea, there is the 1:5,000 forest type map that was produced by digital air-photo interpretation and field survey. Because this map contains very detailed forest information, it can be used as the high-quality spatial data for estimating carbon stocks. In this study, we compared three upscaling methods based on the 1:5,000 forest type map and 5th national forest inventory data. Map algebra(method 1), RK(Regression Kriging)(method 2), and GWR(Geographically Weighted Regression)(method 3) were applied to estimate forest carbon stock in Chungcheong-nam Do and Daejeon metropolitan city. The range of carbon stocks from method 2(1.39~138.80 tonC/ha) and method 3(1.28~149.98 tonC/ha) were more similar to that of previous method(1.56~156.40 tonC/ha) than that of method 1(0.00~93.37 tonC/ha). This result shows that RK and GWR considering spatial autocorrelation can show spatial heterogeneity of carbon stocks. We carried out paired t-test for carbon stock data using 186 sample points to assess estimation accuracy. As a result, the average carbon stocks of method 2 and field survey method were not significantly different at p=0.05 using paired t-test. And the result of method 2 showed the lowest RMSE. Therefore regression kriging method is useful to consider spatial variations of carbon stocks distribution in rugged terrain and complex forest stand.
Kim, Eui-Chan;Kim, Kye-Hyun;Lee, Chul-Yong;Park, Eun-Ji
Journal of Korea Spatial Information System Society
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v.9
no.1
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pp.105-115
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2007
Data mining extracts interesting knowledge from a large database. Among numerous data mining techniques, research work is primarily concentrated on clustering and association rules. The clustering technique of the active research topics mainly deals with analyzing spatial and attribute data. And, the technique of association rules deals with identifying frequent patterns. There was an advanced apriori algorithm using an existing bit-clustering algorithm. In an effort to identify an alternative algorithm to improve apriori, we investigated FP-Growth and discussed the possibility of adopting bit-clustering as the alternative method to solve the problems with FP-Growth. FP-Growth using bit-clustering demonstrated better performance than the existing method. We used chess data in our experiments. Chess data were used in the pattern mining evaluation. We made a creation of FP-Tree with different minimum support values. In the case of high minimum support values, similar results that the existing techniques demonstrated were obtained. In other cases, however, the performance of the technique proposed in this paper showed better results in comparison with the existing technique. As a result, the technique proposed in this paper was considered to lead to higher performance. In addition, the method to apply bit-clustering to GML data was proposed.
Official development assistance refers to assistance provided by governments and other public institutions in donor countries, aimed at promoting economic development and social welfare in developing countries. The purpose of this research is to examine the construction process of the "Myanmar Cultural Heritage Management System" that is underway as part of the ODA project to strengthen cultural and artistic capabilities and analyze the achievements and challenges of the Digital Cultural Heritage ODA. The digital cultural heritage management system is intended to achieve the permanent preservation and sustainable utilization of tangible and intangible cultural heritage materials. Cultural heritage can be stored in digital archives, newly approached using computer analysis technology, and information can be used in multiple dimensions. First, the Digital Cultural Heritage ODA was able to permanently preserve cultural heritage content that urgently needed digitalization by overcoming and documenting the "risk" associated with cultural heritage under threat of being extinguished, damaged, degraded, or distorted in Myanmar. Second, information on Myanmar's cultural heritage can be systematically managed and used in many ways through linkages between materials. Third, cultural maps can be implemented that are based on accurate geographical location information as to where cultural heritage is located or inherited. Various items of cultural heritage were collectively and intensively visualized to maximize utility and convenience for academic, policy, and practical purposes. Fourth, we were able to overcome the one-sided limitations of cultural ODA in relations between donor and recipient countries. Fifth, the capacity building program run by officials in charge of the beneficiary country, which could be the most important form of sustainable development in the cultural ODA, was operated together. Sixth, there is an implication that it is an ODA that can be relatively smooth and non-face-to-face in nature, without requiring the movement of manpower between countries during the current global pandemic. However, the following tasks remain to be solved through active discussion and deliberation in the future. First, the content of the data uploaded to the system should be verified. Second, to preserve digital cultural heritage, it must be protected from various threats. For example, it is necessary to train local experts to prepare for errors caused by computer viruses, stored data, or operating systems. Third, due to the nature of the rapidly changing environment of computer technology, measures should also be discussed to address the problems that tend to follow when new versions and programs are developed after the end of the ODA project, or when developers have not continued to manage their programs. Fourth, since the classification system criteria and decisions regarding whether the data will be disclosed or not are set according to Myanmar's political judgment, it is necessary to let the beneficiary country understand the ultimate purpose of the cultural ODA project.
This study suggested methodology of Citizen Science as a tool of ecosystem conservation and management to achieve Wetland Protected Area (WPA) Conservation Plan and examined whose applicability in 3 WPAs (Jangrok of Gwangju metropolitan city, Madongho of Goseong in South Gyeongsang Province, and Incheongang estuary of Gochang in North Jeolla Province). It consists of a) figuring out main interests and stakeholder or beneficiaries of WPA and their information demand based on conservation, utilization, and management target in the WPA Conservation Plan, b) conducting research activities to gain outcome to address stakeholder's demand, and c) returning the research outcome to citizen scientists and making diffusion to the society. Based on the suggested method and process, citizen scientists conducted ecosystem monitoring (plants including Invasive Alien Plants, terrestrial insects, traces of mammals, discovering unknown wetland). As a result, citizen scientists contributed to collecting species information of 16 plans, 43 species of terrestrial insects, 5 mammals including Lutra lutra (Endangered Species I) and Prionailurus bengalensis (Endangered Species II). The authors constructed and provided distribution map of Invasive Alien Plants, which included information of location and density which citizen scientists registered, for Environment Agencies and local governments who manage 3 WPAs to aid data-based ecosystem policy, In further studies, not only accumulating research data and outcomes acquired from citizen science to suffice the policy demands but also deliberate reviewing policy applicability and social·economic ripple effect should be processed for the suggested Citizen Science in WPA to be settled down as a tool of ecosystem conservation and management.
Kim, Kilho;Choi, Sangwoo;Chae, Moon-jung;Park, Heewoong;Lee, Jaehong;Park, Jonghun
Journal of Intelligence and Information Systems
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v.25
no.1
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pp.163-177
/
2019
As smartphones are getting widely used, human activity recognition (HAR) tasks for recognizing personal activities of smartphone users with multimodal data have been actively studied recently. The research area is expanding from the recognition of the simple body movement of an individual user to the recognition of low-level behavior and high-level behavior. However, HAR tasks for recognizing interaction behavior with other people, such as whether the user is accompanying or communicating with someone else, have gotten less attention so far. And previous research for recognizing interaction behavior has usually depended on audio, Bluetooth, and Wi-Fi sensors, which are vulnerable to privacy issues and require much time to collect enough data. Whereas physical sensors including accelerometer, magnetic field and gyroscope sensors are less vulnerable to privacy issues and can collect a large amount of data within a short time. In this paper, a method for detecting accompanying status based on deep learning model by only using multimodal physical sensor data, such as an accelerometer, magnetic field and gyroscope, was proposed. The accompanying status was defined as a redefinition of a part of the user interaction behavior, including whether the user is accompanying with an acquaintance at a close distance and the user is actively communicating with the acquaintance. A framework based on convolutional neural networks (CNN) and long short-term memory (LSTM) recurrent networks for classifying accompanying and conversation was proposed. First, a data preprocessing method which consists of time synchronization of multimodal data from different physical sensors, data normalization and sequence data generation was introduced. We applied the nearest interpolation to synchronize the time of collected data from different sensors. Normalization was performed for each x, y, z axis value of the sensor data, and the sequence data was generated according to the sliding window method. Then, the sequence data became the input for CNN, where feature maps representing local dependencies of the original sequence are extracted. The CNN consisted of 3 convolutional layers and did not have a pooling layer to maintain the temporal information of the sequence data. Next, LSTM recurrent networks received the feature maps, learned long-term dependencies from them and extracted features. The LSTM recurrent networks consisted of two layers, each with 128 cells. Finally, the extracted features were used for classification by softmax classifier. The loss function of the model was cross entropy function and the weights of the model were randomly initialized on a normal distribution with an average of 0 and a standard deviation of 0.1. The model was trained using adaptive moment estimation (ADAM) optimization algorithm and the mini batch size was set to 128. We applied dropout to input values of the LSTM recurrent networks to prevent overfitting. The initial learning rate was set to 0.001, and it decreased exponentially by 0.99 at the end of each epoch training. An Android smartphone application was developed and released to collect data. We collected smartphone data for a total of 18 subjects. Using the data, the model classified accompanying and conversation by 98.74% and 98.83% accuracy each. Both the F1 score and accuracy of the model were higher than the F1 score and accuracy of the majority vote classifier, support vector machine, and deep recurrent neural network. In the future research, we will focus on more rigorous multimodal sensor data synchronization methods that minimize the time stamp differences. In addition, we will further study transfer learning method that enables transfer of trained models tailored to the training data to the evaluation data that follows a different distribution. It is expected that a model capable of exhibiting robust recognition performance against changes in data that is not considered in the model learning stage will be obtained.
Lee, Hyong-Euk;Kim, Yong-Hwi;Lee, Tae-Youb;Park, Kwang-Hyun;Kim, Yong-Soo;Cho, Joon-Myun;Bien, Z. Zenn
Journal of the Korean Institute of Intelligent Systems
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v.17
no.2
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pp.244-251
/
2007
Intention reading technique is essential to provide personalized services toward more convenient and human-friendly services in complex ubiquitous environment such as a smart home. If a system has knowledge about an user's intention of his/her behavioral pattern, the system can provide mote qualified and satisfactory services automatically in advance to the user's explicit command. In this sense, learning capability is considered as a key function for the intention reading technique in view of knowledge discovery. In this paper, ore introduce a personalized media control method for a possible application iii a smart home. Note that data pattern such as human behavior contains lots of inconsistent data due to limitation of feature extraction and insufficiently available features, where separable data groups are intermingled with inseparable data groups. To deal with such a data pattern, we introduce an effective engineering approach with the combination of fuzzy logic and probabilistic reasoning. The proposed learning system, which is based on IFCS (Iterative Fuzzy Clustering with Supervision) algorithm, extract probabilistic fuzzy rules effectively from the given numerical training data pattern. Furthermore, an extended architectural design methodology of the learning system incorporating with the IFCS algorithm are introduced. Finally, experimental results of the media contents recommendation system are given to show the effectiveness of the proposed system.
The purpose of this study was to examine the professors, who teach the dental hygiene program in Korea, their Awareness on authors determined among research ethics. Three hundred and six full time professors and four hundred and eighty four part time professors in seventy eight universities all around Korea were surveyed. The following are the results that the collected data was carried out statistical analysis by using SPSS 12.0 program. The results was as followed. 1. The present study's author makers, 95 respondents (55.6%) experienced advising professor and 67 respondents (39.2%) experienced personally. 2. As recognition about range and order decision of the authors, they expressed the biggest recognition that person who did the interpretation of the results or gave important information doesn't always become the first author of the article($2.81{\pm}.485$). 3. Between general characteristics and authorship recognition level, they were statistically significantly different with number of articles published as the first author(p<0.05). 4. Regarding the correlation between students who helped with collection of data and references also have the right to be the author of the research article and Person who did the rough draft translation also has the right to be the co-author of the research article had a statistically significant correlation of .433 which was the highest correlation factor (p<0.01). Conclusions, rules and regulations on research ethic should be more publicized through educational institutions.
Objectives : The systematic health education to form the basic healthy lifestyle should be realized from elementary school, so oral health education at elementary school can determine the whole lifetime oral health. The elementary school health teacher's recognition and behavior who in charge of health promotion of students is important. Therefore, the study was conducted to enhance oral health education. Methods : Total 114 people among of 131 from health teacher Gwangju elementary school. Survey system is configured by referring to PRECEDE model. Results : In behavioral diagnosis the proportion of oral Health Education is less than 10%(58.8%), mostly educated in activity time (86.0%), the health teachers educate when it is needed(53.5%). In predisposing diagnosis in the eight areas of health education, the oral health education is ranked as fourth, fifth. Even in the next year project, the oral health education ratio was 21.9 percent. In enabling diagnosing every year the Oral health education training experienced rate is 13.2%, satisfaction rate is 33.3%. In reinforcing diagnosing disability element in the regular education course are the lack of oral health-related information (46.7%), lack of materials needed for education (30.6%), lack of training opportunities (21.4%). Conclusion : In further research, oral health education textbooks, materials and methods should be developed. At the foundation of there developments, the elementary oral health education program should be more fully developed and conducted and also the evaluation of its effectiveness will need.
The objective of this research is to compare and analyze regional accessibility of Korean primary school students to oral health services from the perspective of public health geography by using geographic information system in which the choropleth map has been regarded as the most popular method. Statistical proximity on the basis of calculus of 205 regions-based school oral health data is optimized to set five class intervals for five maps. These choropleth maps of oral heal programs such as oral health education, tooth-brushing method education, preventive dental care and curative dental care, demonstrate that there exist wide regional discrepancies throughout the country in terms of primary school students' accessibility to oral health services within the programs. The paper not just contributes to overcoming the existing paradigm by actively considering an interdisciplinary research among public health dentistry, dental hygiene and geography of public health, but provides clear evidence for national oral health policy in South Korea.
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