• The Journal of the Convergence on Culture Technology
• /
• v.4 no.2
• /
• pp.197-204
• /
• 2018

One of the hottest issues in our 21st century is AI. Just as the automation of manual labor has been achieved through the Industrial Revolution in the agricultural society, the intelligence information society has come through the SW Revolution in the information society. With the advent of Google 'Alpha Go', the computer has learned and predicted its own machine learning, and now the time has come for the computer to surpass the human, even to the world of Baduk, in other words, the computer. Machine learning ML (machine learning) is a field of artificial intelligence. Machine learning ML (machine learning) is a field of artificial intelligence, which means that AI technology is developed to allow the computer to learn by itself. The time has come when computers are beyond human beings. Many companies use machine learning, for example, to keep learning images on Facebook, and then telling them who they are. We also used a neural network to build an efficient energy usage model for Google's data center optimization. As another example, Microsoft's real-time interpretation model is a more sophisticated translation model as the language-related input data increases through translation learning. As machine learning has been increasingly used in many fields, we have to jump into the AI industry to move forward in our 21st century society.

• Proceedings of the Korean Institute of Navigation and Port Research Conference
• /
• 2010.04a
• /
• pp.135-138
• /
• 2010

IMO adopt the revision of SOLAS convention on requirement systems for ECDIS and considered an ECDIS as the major system for E-Navigation strategy on marine transportation safety and environment protection. ENC(Electronic Navigational Chart) as base map of ECDIS is considered as a principal information infrastructure that is essential for navigation tasks. But ENCs are not easy to utilize because they are encoded according to ISO/IEC 8211 file format, and ENCs is required to utilize in parts of Marine GIS and various marine application because they are used for navigational purpose mainly. Meanwhile Google earth is satellite map that Google company service, is utilized in all kinds of industry generally providing local information including satellite image, map, topography, 3D building information, etc. In this paper, we developed KML conversion technology for ENC application. details of development contents consist of ENC loading module and KML conversion module. Also, we applied this conversion technology to Korea ENC and evaluated the results.

• Asian Pacific Journal of Cancer Prevention
• /
• v.17 no.2
• /
• pp.719-722
• /
• 2016

Background: Cholangiocarcinoma (CCA) is a serious health problem in Thailand, particularly in northeastern and northern regions, but epidemiological studies are scarce and the spatial distribution of CCA remains to be determined. A database for the population at risk is required for monitoring, surveillance and organization of home health care. This study aim was to geo-visually display the distribution of CCA in northeast Thailand, using a geographic information system and Google Earth. Materials and Methods: A cross-sectional survey was carried out in 9 sub-districts and 133 villages in Chum Phuang district, Nakhon Ratchasima province during June and October 2015. Data on demography, and the population at risk for CCA were combined with the points of villages, sub-district boundaries, district boundaries, and points of hospitals in districts, then fed into a geographical information system. After the conversion, all of the data were imported into Google Earth for geo-visualization. Results: A total of 11,960 from 83,096 population were included in this study. Females and male were 52.5%, and 47.8%, the age group 41-50 years old 33.3%. Individual risk for CCA was identifed and classified by using the Korat CCA verbal screening test as low (92.8%), followed by high risk (6.74%), and no (0.49%), respectively. Gender ($X^2$-test=1143.63, p-value= 0.001), age group ($X^2$-test==211.36, p-value=0.0001), and sub-district ($X^2$-test=1471.858, p-value=0.0001) were significantly associated with CCA risk. Spatial distribution of the population at risk for CCA in Chum Phuang district was viewed with Google Earth. Geo-visual display followed Layer 1: District, Layer 2: Sub-district, Layer 3: Number of low risk in village, Layer 4: Number of high risk in village, and Layer 5: Hospital in Chum Phuang District and their related catchment areas. Conclusions: We present the first risk geo-visual display of CCA in this rural community, which is important for spatial targeting of control efforts. Risk appears to be strongly associated with gender, age group, and sub-district. Therefor, spatial distribution is suitable for the use in the further monitoring, surveillance, and home health care for CCA.

• Asian Pacific Journal of Cancer Prevention
• /
• v.17 no.3
• /
• pp.1433-1436
• /
• 2016

Background: Cholangiocarcinoma (CCA), a major problem of health in Thailand, particularly in Northeastern and Northern regions, is generally incurable and rapidly lethal because of presentation in stage 3 or 4. Early diagnosis of stage 1 and 2 could allow better survival. Therefore, this study aimed to provide a distribution map of populations at risk for CCA in BuaYai district of Nakhon Ratchasima province, Northeast Thailand. Materials and Methods: A cross-sectional survey was carried out in 10 sub-districts and 122 villages, during June and November 2015. The populations at risk for CCA were screened using the Korat CCA verbal screening test (KCVST) and then risk areas were displayed by using Google map (GM). Results: A total of 11,435 individuals from a 26,198 population completed the KCVST. The majority had a low score of risk for CCA (1-4 points; 93.3%). High scores with 6, 7 and 8 points accounted for 1.20%, 0.13% and 0.02%. The population at risk was found frequently in sub-district municipalities, followed by sub-district administrative organization and town municipalities, (F=396.220, P-value=0.000). Distribution mapping comprised 11 layers: 1, district; 2, local administrative organization; 3, hospital; 4, KCVST opisthorchiasis; 5, KCVST praziquantel used; 6, KCVST cholelithiasis; 7, KCVST raw fish consumption; 8, KCVST alcohol consumption; 9, KCVST pesticide used; 10, KCVST relative family with CCA; and 11, KCVST naive northeastern people. Geovisual display is now available online. Conclusions: This study indicated that the population at high risk of CCA in Bua Yai district is low, therefore setting a zero model project is possible. Key success factors for disease prevention and control need further study. GM production is suitable for further CCA surveillance and monitoring of the population with a high risk score in this area.

• Ecology and Resilient Infrastructure
• /
• v.7 no.3
• /
• pp.171-180
• /
• 2020

With the increase in industrialization and urbanization, scarcity of space for leisure life has become an important issue. Opportunities such as natural scenery and ecological experiences provided by waterfront spaces around streams are fundamental factors in the development of the community and creation of a hydrophilic park. In the past, on-site surveys have been conducted using human resources to quantify the number of river visitors, but the accuracy of the results was not sufficient owing to limitations in expenses, manpower, space, and time. In this study, to overcome this problem, we estimated the number of visitors using the location information related to hydrophilic parks. The study areas were Samrak Ecological Park and Daejeo Ecological Park located downstream of the Nakdong River. We compared and analyzed the pattern of the visitors by using the large communication data and the visiting pattern based on GPS location information. The GPS location information is based on Google Popular Times and Kakao visitor data. When the GPS location data were used, the pattern for weekday and weekend visitors was clearer than when the large communication data were used. Therefore, it is expected to be similar to the result of GPS location information if the number of visitors is extracted under the condition of precision of pCELL size and residence time of 30 minutes or more when using future communication big data. In addition, if revisions such as the Personal Information Protection Act are made to extract more accurate data, by estimating the number of visitors based on GPS data, more accurate indicators of the number of visitors can be derived.

• Journal of Korean Society of Transportation
• /
• v.33 no.1
• /
• pp.14-28
• /
• 2015

Numerous research has been conducted using internet search data since the mid-2000s. For example, Google Inc. developed a service predicting influenza patterns using the internet search data. The main objective of this study is to prove the hypothesis that highway traffic indices are similar to the internet search patterns. In order to achieve this objective, a model to predict the number of vehicles entering the expressway and space-mean speed was developed and the goodness-of-fit of the model was assessed. The results revealed several findings. First, it was shown that the Google search traffic was a good predictor for the TCS entering traffic volume model at sites with frequent commute trips, and it had a negative correlation with the TCS entering traffic volume. Second, the Naver search traffic was utilized for the TCS entering traffic volume model at sites with numerous recreational trips, and it was positively correlated with the TCS entering traffic volume. Third, it was uncovered that the VDS speed had a negative relationship with the search traffic on the time series diagram. Lastly, it was concluded that the transfer function noise time series model showed the better goodness-of-fit compared to the other time series model. It is expected that "Big Data" from the internet search data can be extensively applied in the transportation field if the sources of search traffic, time difference and aggregation units are explored in the follow-up studies.

• Journal of Internet Computing and Services
• /
• v.12 no.5
• /
• pp.171-179
• /
• 2011

In this paper it is hypothesized that word stimuli that are presented by Google’s search word, would improve the quality of the design solution, so this research examines the effect of related search word stimuli in concept generation and analyzes the results through the processes of creative cognition. In the process of concept generation, words are given as stimuli which are generated through Google's related search and these search words are given by 5 levels. Google search is based on the collaboration philosophy. People's participation and contribution recreate knowledge and information, so these renewed and related search words update in real time by people are used as stimuli. Two problems are provided with related search words. After the design concept generation the results are analyzed by 3 bases: the usage of related search words and those of frequency, creativity, and Finke's 12 Geneplore model. These are the results of the research. Many levels of related search words are used in design concept generation but especially higher levels which are more related to search words are more used than lower levels. The usage of multi words and conjunction with higher levels and lower levels words are observed in creative results. On the creative cognitive processes, it is more creative when using association and mental transformation with the related search words than using the related search words simply. Creative outputs also use conceptual interpretation, functional inference, and contextual shifting of creative cognitive processes of Finke's 12 Geneplore model.

• Journal of Korean Society for Geospatial Information Science
• /
• v.17 no.3
• /
• pp.71-79
• /
• 2009

We expanded the 3D building information extraction method using shadow and vertical line from single high resolution image with meta information into the method for single high resolution image without meta information. Our method guesses an azimuth angle and an elevation angle of the sensor and the sun using reference building, selected by user, on an image. For test, we used an IKONOS image and an image extracted from the Google Earth. We calculated the Root Mean Square (RMS) error of heights extracted by our method using the building height extracted from stereo IKONOS image as reference, and the RMS error from the IKONOS image and the Google Earth image was under than 3 m. We also calculated the RMS error of horizontality position by comparison between building position extracted from only the IKONOS image and it from 1:1,000 digital map, and the result was under than 3 m. This test results showed that the height pattern of building models by our method was similar with it by the method using meta information.

• Cartoon and Animation Studies
• /
• s.36
• /
• pp.553-572
• /
• 2014

In this paper, for the evaluation of the ease of a particular Web site (www.appbelt.net), insert the log tracking code for Google Analytics in a page of the Web site to collect behavioral data of visitor and has studied the improvement measures for the problems of the Web site, after the evaluation of the overall quality of the Web site through the evaluation of Coolcheck. These findings set the target value of the company's priority (importance) companies want to influence the direction of the business judgment are set up correctly, and the user's needs and behavior will be appropriate for the service seems to help improvement.

• Journal of the Korea Institute of Information and Communication Engineering
• /
• v.18 no.2
• /
• pp.357-363
• /
• 2014

The development of information technology grows the society and allows the user to generate more information and the requirements. According to recent growing interest in digital convergence technologies, digital convergence can be utilized by a variety of methods as a new study. Electronic culture atlas would be digitized cultural information that represents a particular area on the map. In detail, spatial data like as point, line, and area can be used to represent the culture information. Using electronic culture atlas, also, it is possible to provide and utilize information which is associated with time, space(map) and subject(culture). Thus, electronic culture atlas could be used as a method for the humanities or area studies and spread research results by displaying on the culture atlas. In general, existing electronic culture atlas used bitmap image mostly as a base map. Using bitmap image, it is difficult to represent to provide three-dimensional information of specific area. Also, it happens problem such as breakage occurs during zoom-in operation. To solve this problems, we design and implement electronic culture atlas based on Google Earth which is three-dimensional map service.