• Journal of Korean Elementary Science Education
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• v.42 no.4
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• pp.591-604
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• 2023

This study investigated the impact of elementary science classes using metaverse on the academic achievement, positive experience in science, and digital literacy of elementary school students. In addition, we examined their perceptions. The respondents were derived from two classes in the sixth grade at an elementary school in Gyeonggi-do, who were selected designated as the experimental (n=29 students) and comparative (n=29) groups, respectively. Across five lessons under the "Plant Structure and Function" unit, the experimental group conducted science classes using the metaverse, whereas the comparative group conducted general textbook-based classes. To investigate instructional effects, the study performed ANCOVA using the pre-test score as a covariate, a survey on the perception of students about science classes using metaverse, and conducted interviews with a number of subjects. The result demonstrated that science classes using metaverse exerted no significant effect on scientific academic achievement and digital literacy. However, the study observed a statistically significant effect on science learning emotion which is a sub-element of positive experiences in science. The students were positively aware of science classes using metaverse in terms of interesting and diverse activities, and free expression of inquiry results and perceived the instability of smart devices and network connections as regrettable. Finally, the study posed the implications of the use of metaverse in science classes.

• Journal of Internet Computing and Services
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• v.15 no.3
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• pp.45-52
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• 2014

The Ubiquitous-City (U-City) is a smart or intelligent city to satisfy human beings' desire to enjoy IT services with any device, anytime, anywhere. It is a future city model based on Internet of everything or things (IoE or IoT). It includes a lot of video cameras which are networked together. The networked video cameras support a lot of U-City services as one of the main input data together with sensors. They generate huge amount of video information, real big data for the U-City all the time. It is usually required that the U-City manipulates the big data in real-time. And it is not easy at all. Also, many times, it is required that the accumulated video data are analyzed to detect an event or find a figure among them. It requires a lot of computational power and usually takes a lot of time. Currently we can find researches which try to reduce the processing time of the big video data. Cloud computing can be a good solution to address this matter. There are many cloud computing methodologies which can be used to address the matter. MapReduce is an interesting and attractive methodology for it. It has many advantages and is getting popularity in many areas. Video cameras evolve day by day so that the resolution improves sharply. It leads to the exponential growth of the produced data by the networked video cameras. We are coping with real big data when we have to deal with video image data which are produced by the good quality video cameras. A video surveillance system was not useful until we find the cloud computing. But it is now being widely spread in U-Cities since we find some useful methodologies. Video data are unstructured data thus it is not easy to find a good research result of analyzing the data with MapReduce. This paper presents an analyzing system for the video surveillance system, which is a cloud-computing based video data management system. It is easy to deploy, flexible and reliable. It consists of the video manager, the video monitors, the storage for the video images, the storage client and streaming IN component. The "video monitor" for the video images consists of "video translater" and "protocol manager". The "storage" contains MapReduce analyzer. All components were designed according to the functional requirement of video surveillance system. The "streaming IN" component receives the video data from the networked video cameras and delivers them to the "storage client". It also manages the bottleneck of the network to smooth the data stream. The "storage client" receives the video data from the "streaming IN" component and stores them to the storage. It also helps other components to access the storage. The "video monitor" component transfers the video data by smoothly streaming and manages the protocol. The "video translator" sub-component enables users to manage the resolution, the codec and the frame rate of the video image. The "protocol" sub-component manages the Real Time Streaming Protocol (RTSP) and Real Time Messaging Protocol (RTMP). We use Hadoop Distributed File System(HDFS) for the storage of cloud computing. Hadoop stores the data in HDFS and provides the platform that can process data with simple MapReduce programming model. We suggest our own methodology to analyze the video images using MapReduce in this paper. That is, the workflow of video analysis is presented and detailed explanation is given in this paper. The performance evaluation was experiment and we found that our proposed system worked well. The performance evaluation results are presented in this paper with analysis. With our cluster system, we used compressed $1920{\times}1080(FHD)$ resolution video data, H.264 codec and HDFS as video storage. We measured the processing time according to the number of frame per mapper. Tracing the optimal splitting size of input data and the processing time according to the number of node, we found the linearity of the system performance.

• Journal of Intelligence and Information Systems
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• v.17 no.2
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• pp.61-75
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• 2011

A Geographic Information System(GIS) is a system that captures, stores, analyzes, manages and presents data with reference to geographic location data. In the later 1990s and earlier 2000s it was limitedly used in government sectors such as public utility management, urban planning, landscape architecture, and environmental contamination control. However, a growing number of open-source packages running on a range of operating systems enabled many private enterprises to explore the concept of viewing GIS-based sales and customer data over their own computer monitors. K telecommunication company has dominated the Korean telecommunication market by providing diverse services, such as high-speed internet, PSTN(Public Switched Telephone Network), VOLP (Voice Over Internet Protocol), and IPTV(Internet Protocol Television). Even though the telecommunication market in Korea is huge, the competition between major services providers is growing more fierce than ever before. Service providers struggled to acquire as many new customers as possible, attempted to cross sell more products to their regular customers, and made more efforts on retaining the best customers by offering unprecedented benefits. Most service providers including K telecommunication company tried to adopt the concept of customer relationship management(CRM), and analyze customer's demographic and transactional data statistically in order to understand their customer's behavior. However, managing customer information has still remained at the basic level, and the quality and the quantity of customer data were not enough not only to understand the customers but also to design a strategy for marketing and sales. For example, the currently used 3,074 legal regional divisions, which are originally defined by the government, were too broad to calculate sub-regional customer's service subscription and cancellation ratio. Additional external data such as house size, house price, and household demographics are also needed to measure sales potential. Furthermore, making tables and reports were time consuming and they were insufficient to make a clear judgment about the market situation. In 2009, this company needed a dramatic shift in the way marketing and sales activities, and finally developed a dedicated GIS_based market analysis and sales management system. This system made huge improvement in the efficiency with which the company was able to manage and organize all customer and sales related information, and access to those information easily and visually. After the GIS information system was developed, and applied to marketing and sales activities at the corporate level, the company was reported to increase sales and market share substantially. This was due to the fact that by analyzing past market and sales initiatives, creating sales potential, and targeting key markets, the system could make suggestions and enable the company to focus its resources on the demographics most likely to respond to the promotion. This paper reviews subjective and unclear marketing and sales activities that K telecommunication company operated, and introduces the whole process of developing the GIS information system. The process consists of the following 5 modules : (1) Customer profile cleansing and standardization, (2) Internal/External DB enrichment, (3) Segmentation of 3,074 legal regions into 46,590 sub_regions called blocks, (4) GIS data mart design, and (5) GIS system construction. The objective of this case study is to emphasize the need of GIS system and how it works in the private enterprises by reviewing the development process of the K company's market analysis and sales management system. We hope that this paper suggest valuable guideline to companies that consider introducing or constructing a GIS information system.

• Journal of the Korean Institute of Landscape Architecture
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• v.36 no.6
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• pp.43-54
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• 2009

This study attempted to develop a model for selecting sites for ecologically effective, multi-functional wetlands during the environmental and ecological planning stage, prior to land use Planning. This model was developed with an emphasis upon the creation of a water circulation system for a newly-created city, dispersing and retaining the run-off that is increased due to urbanization and securing spaces to create wetlands that can promote urban biodiversity. A series of Precesses for selecting sites for wetland restoration and creation - watershed analysis, selection of evaluation items, calculation of weights, reparation of thematic maps and synthesis - were incorporated into the model. Its potentials and limitations were examined by applying it to the recently-planned WiRae New Community Development Area, which is located in the Seoul metropolitan region. At the watershed analysis stage, the site was divided into 13 sub-catchment areas. Inflow to watersheds including the area was $3,020,765m^3$ Run-off before and after development is estimated as $1,901,969m^3$ and $1,970,735{\sim}2,039,502m^3$, respectively. The total storage capacity required in the development area amounts to $68,766{\sim}137,533m^3$. When thematic maps were overlapped during the selection stage for wetland sites, 13 sub-catchment areas were prioritized for wetland restoration and creation. The locations and areas for retaining run-off showed that various types of wetlands, including retaining wetlands (area wetlands), riverine wetlands (linear wetlands) and pond wetlands (point wetlands), can be created and that they can be systematically connected. By providing a basic framework for the water circulation system plan of an entire city, it may be used effectively in the space planning stage, such as planning an urban eco-network through integration with greet areas. In order to estimate reasonable run-off and create an adequate water circulation system however, a feedback process following land use planning is required. This study strived to promote urban changes in a positive direction while minimizing urban changes in negative forms.

• Korean Journal of Agricultural and Forest Meteorology
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• v.5 no.2
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• pp.70-80
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• 2003

We report the first direct measurement of $CO_2$ flux over Kwangneung broadleaf deciduous forest, one of the tower flux sites in KoFlux network. Eddy covariance system was installed on a 30 m tower along with other meteorological instruments from June to August in 2002. Although the study site was non-ideal (with valley-like terrain), turbulence characteristics from limited wind directions (i.e., 90$\pm$45$^{\circ}$) was not significantly different from those obtained at simple, homogeneous terrains with an ideal fetch. Despite very low rate of data retrieval, preliminary results from our analysis are encouraging and worthy of further investigation. Ignoring the role of advection terms, the averaged net ecosystem exchange (NEE) of $CO_2$ ranged from -1.2 to 0.7 mg m$^{-2}$ s$^{-1}$ from June to August in 2002. The effect of weak turbulence on nocturnal NEE was examined in terms of friction velocity (u*) along with the estimation of storage term. The effect of low uf u* NEE was obvious with a threshold value of about 0.2 m s$^{-1}$ . The contribution of storage term to nocturnal NEE was insignificant; suggesting that the $CO_2$ stored within the forest canopy at night was probably removed by the drainage flow along the hilly terrain. This could be also an artifact of uncertainty in calculations of storage term based on a single-level concentration. The hyperbolic light response curves explained ＞80% of variation in the observed NEE, indicating that $CO_2$ exchange at the site was notably light-dependent. Such a relationship can be used effectively in filling up the missing gaps in NEE data through the season. Finally, a simple scaling analysis based on a linear flow model suggested that advection might play a significant role in NEE evaluation at this site.

• Journal of the Korean Geographical Society
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• v.31 no.2
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• pp.160-197
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• 1996

The purpose of this study is to review research trends and issues of economic geography in Korea for the last fifty years by sub-fields of agricultural geography, industrial geography, commercial and service geography, and transportation geography. Research in Korean economic geography has progressed significantly in terms of the scope and the number of papers published during the last a half a century. Agricultural geography was a leading field of economic geography in Korea before mid-1970s. Since the mid-1970s, however, agricultural geography has turned over the leading role in economic geography to industrial geography. Classification and structure of agricultural region has been the most popular research theme in Korea, even though diverse topics has been dealt in the research of agricultulal geography in Korea during the last fifty years. In recent years, emphasis is given to study on the dynamics of agricultural region and regional differentiation of part-time farming. It is suggested that the future issues of research in agricultural geography in Korea are agricultural restructuring and changes in agricultural space under the WTO system, changes in rural area and agricultural region with the progress of informatization, changes in agricultural structures and rural society by the increase of part-time farming, governments agricultulal policy and its impacts, competitive advantages of Korean agricultulal products, and environmental impacts of agricultural restructuring. Research in industrial geography has remarkably progressed since the 1980s. Locational changes, regional industrial structure and formation of industrial region were the major topics of interest in the research of industrial geography in Korea before 1980. Since the early 1980s, in addition to the topics which were interested in before 1980, changes of industrial organization and industrial location, changes of production systems and industrial space development of high technology industries and science parks, industrial restructuring and regional economy, foreign direct investments, industrial linkages and industrial districts, and industrial policy and regional development have been the major research themes of industrial geography in Korea. Considerable number of papers has been published both in Korean journals and in foreign journals during this period. Considering global changes in the organization of industrial space, future research should be more focused on firms strategy for regaining competitive advantages, local and global perspectives of industry, industry and environmental changes, in addition to the topics which have been dealt in recent years. Research in commercial and service geography and transportation geography was negligible in Korea before the late 1970s. These two sub-fields in economic geography have begun to develop since 1980s. Periodic markets, structure of commercial area, and distribution of products were the major topics of interest in the 1980s in the commercial and service geography in Korea. In the 1990s, however reserch in producer services has been active with growth of producer services in Korean economy. It is suggested that regional changes with progress of informatization and technology, changes of international trade and regional changes, development of efficient distribution system, role of producer services in regional development, and network of producer services are the major issues to be studied in the future in the field of commercial and service geography in Korea. Commuting, distribution of products, and transportation networks have been the major topics of research in transportation geography in Korea. Diverse quantitative techniques have been applied in the most of the researches in transportation geography. It is required that future studies in transportation geography should also focus on societal and behavioral issues, policy issues regional impacts of new transportation facilities, an analysis of transportation system at the global or international level. Since the 1980s economic geography in Korea has considerably progressed with publication of papers and books. The progress can be regarded as successful in quantitative aspect, but not in quantitative aspects. For the development of Korean economic geography in both quantitative and qualitative aspects, it is necessary to promote international collaborative researches and interdisciplinary cooperations. Attention should also be given to the research on changes in competitive advantages and economic restructuring, changes of economic space with the development of high technology and the progress of informatization. economic development and culture. and foreign regional studies.

• Journal of Intelligence and Information Systems
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• v.27 no.1
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• pp.103-128
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• 2021

Recently, investors' interest and the influence of stock-related information dissemination are being considered as significant factors that explain stock returns and volume. Besides, companies that develop, distribute, or utilize innovative new technologies such as artificial intelligence have a problem that it is difficult to accurately predict a company's future stock returns and volatility due to macro-environment and market uncertainty. Market uncertainty is recognized as an obstacle to the activation and spread of artificial intelligence technology, so research is needed to mitigate this. Hence, the purpose of this study is to propose a machine learning model that predicts the volatility of a company's stock price by using the internet search volume of artificial intelligence-related technology keywords as a measure of the interest of investors. To this end, for predicting the stock market, we using the VAR(Vector Auto Regression) and deep neural network LSTM (Long Short-Term Memory). And the stock price prediction performance using keyword search volume is compared according to the technology's social acceptance stage. In addition, we also conduct the analysis of sub-technology of artificial intelligence technology to examine the change in the search volume of detailed technology keywords according to the technology acceptance stage and the effect of interest in specific technology on the stock market forecast. To this end, in this study, the words artificial intelligence, deep learning, machine learning were selected as keywords. Next, we investigated how many keywords each week appeared in online documents for five years from January 1, 2015, to December 31, 2019. The stock price and transaction volume data of KOSDAQ listed companies were also collected and used for analysis. As a result, we found that the keyword search volume for artificial intelligence technology increased as the social acceptance of artificial intelligence technology increased. In particular, starting from AlphaGo Shock, the keyword search volume for artificial intelligence itself and detailed technologies such as machine learning and deep learning appeared to increase. Also, the keyword search volume for artificial intelligence technology increases as the social acceptance stage progresses. It showed high accuracy, and it was confirmed that the acceptance stages showing the best prediction performance were different for each keyword. As a result of stock price prediction based on keyword search volume for each social acceptance stage of artificial intelligence technologies classified in this study, the awareness stage's prediction accuracy was found to be the highest. The prediction accuracy was different according to the keywords used in the stock price prediction model for each social acceptance stage. Therefore, when constructing a stock price prediction model using technology keywords, it is necessary to consider social acceptance of the technology and sub-technology classification. The results of this study provide the following implications. First, to predict the return on investment for companies based on innovative technology, it is most important to capture the recognition stage in which public interest rapidly increases in social acceptance of the technology. Second, the change in keyword search volume and the accuracy of the prediction model varies according to the social acceptance of technology should be considered in developing a Decision Support System for investment such as the big data-based Robo-advisor recently introduced by the financial sector.

• Journal of The Korean Association For Science Education
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• v.36 no.4
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• pp.705-715
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• 2016

The purpose of this research is to analyze elementary students' attention characteristics through attention test and eye tracking on real science classes. The SMI's ETG(eye tracker glasses) mobile eye tracker was used to analyze the attention process of elementary students'. The sampling rate of the ETG is 30Hz. The participants of attention test were elementary 155 6th-grade elementary students and the participants for the eye-tracker were six 6th-grade male students. The eye movements were analyzed using the 'BeGaze Mobile Video Analysis Package' program. The results of this research are as follows. First, the attention test results of elementary students showed high correlation between selective attention and sustained attention (.85) and low correlation between selective attention and self-regulation (.32). Second, the attention types of elementary students were divided into four; attention, inattention, easygoing and hasty. Third, elementary students' attention were divided into top-down, bottom-up, default mode network through analysis of elementary students′ eye-movements during real science classes. Also their attention shift occurred frequently due to various reasons in real class situation. There were three reasons that made elementary students fail to handle knowledge-dependent top-down attention; 1) the cognitive failure of target caused by failing to focus attention, 2) the absence of prior knowledge on target object, 3) the analogical failure of prior knowledge. Finally, elementary students' attention process were schematized based on the analysis of students' eye movements and attention test. This research is expected to be utilized as basic data for developing effective teaching strategies, teaching-learning models and instructional materials.

• Journal of Intelligence and Information Systems
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• v.16 no.3
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• pp.147-161
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• 2010

As broadcasting and communication are converged recently, communication is jointed to TV. TV viewing has brought about many changes. The IPTV (Internet Protocol Television) provides information service, movie contents, broadcast, etc. through internet with live programs + VOD (Video on demand) jointed. Using communication network, it becomes an issue of new business. In addition, new technical issues have been created by imaging technology for the service, networking technology without video cuts, security technologies to protect copyright, etc. Through this IPTV network, users can watch their desired programs when they want. However, IPTV has difficulties in search approach, menu approach, or finding programs. Menu approach spends a lot of time in approaching programs desired. Search approach can't be found when title, genre, name of actors, etc. are not known. In addition, inserting letters through remote control have problems. However, the bigger problem is that many times users are not usually ware of the services they use. Thus, to resolve difficulties when selecting VOD service in IPTV, a personalized service is recommended, which enhance users' satisfaction and use your time, efficiently. This paper provides appropriate programs which are fit to individuals not to save time in order to solve IPTV's shortcomings through filtering and recommendation-related system. The proposed recommendation system collects TV program information, the user's preferred program genres and detailed genre, channel, watching program, and information on viewing time based on individual records of watching IPTV. To look for these kinds of similarities, similarities can be compared by using ontology for TV programs. The reason to use these is because the distance of program can be measured by the similarity comparison. TV program ontology we are using is one extracted from TV-Anytime metadata which represents semantic nature. Also, ontology expresses the contents and features in figures. Through world net, vocabulary similarity is determined. All the words described on the programs are expanded into upper and lower classes for word similarity decision. The average of described key words was measured. The criterion of distance calculated ties similar programs through K-medoids dividing method. K-medoids dividing method is a dividing way to divide classified groups into ones with similar characteristics. This K-medoids method sets K-unit representative objects. Here, distance from representative object sets temporary distance and colonize it. Through algorithm, when the initial n-unit objects are tried to be divided into K-units. The optimal object must be found through repeated trials after selecting representative object temporarily. Through this course, similar programs must be colonized. Selecting programs through group analysis, weight should be given to the recommendation. The way to provide weight with recommendation is as the follows. When each group recommends programs, similar programs near representative objects will be recommended to users. The formula to calculate the distance is same as measure similar distance. It will be a basic figure which determines the rankings of recommended programs. Weight is used to calculate the number of watching lists. As the more programs are, the higher weight will be loaded. This is defined as cluster weight. Through this, sub-TV programs which are representative of the groups must be selected. The final TV programs ranks must be determined. However, the group-representative TV programs include errors. Therefore, weights must be added to TV program viewing preference. They must determine the finalranks.Based on this, our customers prefer proposed to recommend contents. So, based on the proposed method this paper suggested, experiment was carried out in controlled environment. Through experiment, the superiority of the proposed method is shown, compared to existing ways.

• Journal of Internet Computing and Services
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• v.16 no.5
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• pp.29-38
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• 2015

The Energy Storage System stores electricity for later use. This system can store electricity from legacy electric power systems or renewable energy systems into a battery device when demand is low. When there is high electricity demand, it uses the electricity previously stored and enables efficient energy usage and stable operation of the electric power system. It increases the energy usage efficiency, stabilizes the power supply system, and increases the utilization of renewable energy. The recent increase in the global interest for efficient energy consumption has increased the need for an energy storage system that can satisfy both the consumers' demand for stable power supply and the suppliers' demand for power demand normalization. In general, an energy storage system consists of a Power Conditioning System, a Battery Management System, a battery cell and peripheral devices. The specifications of the subsystems that form the energy storage system are manufacturer dependent. Since the core component interfaces are not standardized, there are difficulties in forming and operating the energy storage system. In this paper, the design of the profile structure for energy storage system and realization of private profiling system for energy storage system is presented. The profiling system accommodates diverse component settings that are manufacturer dependent and information needed for effective operation. The settings and operation information of various PCSs, BMSs, battery cells, and other peripheral device are analyzed to define profile specification and structure. A profile adapter software that can be applied to energy storage system is designed and implemented. The profiles for energy storage system generated by the profile authoring tool consist of a settings profile and operation profile. Setting profile consists of configuration information for energy device what composes energy saving system. To be more specific, setting profile has three parts of category as information for electric control module, sub system, and interface for communication between electric devices. Operation profile includes information in relation to the method in which controls Energy Storage system. The profiles are based on standard XML specification to accommodate future extensions. The profile system has been verified by applying it to an energy storage system and testing charge and discharge operations.