• Journal of Intelligence and Information Systems
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• v.18 no.1
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• pp.1-21
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• 2012

In recent years, mobile phone has experienced an extremely fast evolution. It is equipped with high-quality color displays, high resolution cameras, and real-time accelerated 3D graphics. In addition, some other features are includes GPS sensor and Digital Compass, etc. This evolution advent significantly helps the application developers to use the power of smart-phones, to create a rich environment that offers a wide range of services and exciting possibilities. To date mobile AR in outdoor research there are many popular location-based AR services, such Layar and Wikitude. These systems have big limitation the AR contents hardly overlaid on the real target. Another research is context-based AR services using image recognition and tracking. The AR contents are precisely overlaid on the real target. But the real-time performance is restricted by the retrieval time and hardly implement in large scale area. In our work, we exploit to combine advantages of location-based AR with context-based AR. The system can easily find out surrounding landmarks first and then do the recognition and tracking with them. The proposed system mainly consists of two major parts-landmark browsing module and annotation module. In landmark browsing module, user can view an augmented virtual information (information media), such as text, picture and video on their smart-phone viewfinder, when they pointing out their smart-phone to a certain building or landmark. For this, landmark recognition technique is applied in this work. SURF point-based features are used in the matching process due to their robustness. To ensure the image retrieval and matching processes is fast enough for real time tracking, we exploit the contextual device (GPS and digital compass) information. This is necessary to select the nearest and pointed orientation landmarks from the database. The queried image is only matched with this selected data. Therefore, the speed for matching will be significantly increased. Secondly is the annotation module. Instead of viewing only the augmented information media, user can create virtual annotation based on linked data. Having to know a full knowledge about the landmark, are not necessary required. They can simply look for the appropriate topic by searching it with a keyword in linked data. With this, it helps the system to find out target URI in order to generate correct AR contents. On the other hand, in order to recognize target landmarks, images of selected building or landmark are captured from different angle and distance. This procedure looks like a similar processing of building a connection between the real building and the virtual information existed in the Linked Open Data. In our experiments, search range in the database is reduced by clustering images into groups according to their coordinates. A Grid-base clustering method and user location information are used to restrict the retrieval range. Comparing the existed research using cluster and GPS information the retrieval time is around 70~80ms. Experiment results show our approach the retrieval time reduces to around 18~20ms in average. Therefore the totally processing time is reduced from 490~540ms to 438~480ms. The performance improvement will be more obvious when the database growing. It demonstrates the proposed system is efficient and robust in many cases.

• Journal of Intelligence and Information Systems
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• v.19 no.4
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• pp.21-37
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• 2013

Recently, as the advent of the knowledge-based society, there are more people getting interested in the intellectual property. Especially, the ICT companies leading the high-tech industry are working hard to strive for systematic management of intellectual property. As we know, the patent information represents the intellectual capital of the company. Also now the quantitative analysis on the continuously accumulated patent information becomes possible. The analysis at various levels becomes also possible by utilizing the patent information, ranging from the patent level to the enterprise level, industrial level and country level. Through the patent information, we can identify the technology status and analyze the impact of the performance. We are also able to find out the flow of the knowledge through the network analysis. By that, we can not only identify the changes in technology, but also predict the direction of the future research. In the field using the network analysis there are two important analyses which utilize the patent citation information; citation indicator analysis utilizing the frequency of the citation and network analysis based on the citation relationships. Furthermore, this study analyzes whether there are any impacts between the size of the company and patent citation relationships. 74 S&P 500 registered companies that provide IT and communication services are selected for this study. In order to determine the relationship of patent citation between the companies, the patent citation in 2009 and 2010 is collected and sociomatrices which show the patent citation relationship between the companies are created. In addition, the companies' total assets are collected as an index of company size. The distance between companies is defined as the absolute value of the difference between the total assets. And simple differences are considered to be described as the hierarchy of the company. The QAP Correlation analysis and MR-QAP analysis is carried out by using the distance and hierarchy between companies, and also the sociomatrices that shows the patent citation in 2009 and 2010. Through the result of QAP Correlation analysis, the patent citation relationship between companies in the 2009's company's patent citation network and the 2010's company's patent citation network shows the highest correlation. In addition, positive correlation is shown in the patent citation relationships between companies and the distance between companies. This is because the patent citation relationship is increased when there is a difference of size between companies. Not only that, negative correlation is found through the analysis using the patent citation relationship between companies and the hierarchy between companies. Relatively it is indicated that there is a high evaluation about the patent of the higher tier companies influenced toward the lower tier companies. MR-QAP analysis is carried out as follow. The sociomatrix that is generated by using the year 2010 patent citation relationship is used as the dependent variable. Additionally the 2009's company's patent citation network and the distance and hierarchy networks between the companies are used as the independent variables. This study performed MR-QAP analysis to find the main factors influencing the patent citation relationship between the companies in 2010. The analysis results show that all independent variables have positively influenced the 2010's patent citation relationship between the companies. In particular, the 2009's patent citation relationship between the companies has the most significant impact on the 2010's, which means that there is consecutiveness regarding the patent citation relationships. Through the result of QAP correlation analysis and MR-QAP analysis, the patent citation relationship between companies is affected by the size of the companies. But the most significant impact is the patent citation relationships that had been done in the past. The reason why we need to maintain the patent citation relationship between companies is it might be important in the use of strategic aspect of the companies to look into relationships to share intellectual property between each other, also seen as an important auxiliary of the partner companies to cooperate with.

• Journal of Intelligence and Information Systems
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• v.21 no.1
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• pp.1-13
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• 2015

As opinion mining in big data applications has been highlighted, a lot of research on unstructured data has made. Lots of social media on the Internet generate unstructured or semi-structured data every second and they are often made by natural or human languages we use in daily life. Many words in human languages have multiple meanings or senses. In this result, it is very difficult for computers to extract useful information from these datasets. Traditional web search engines are usually based on keyword search, resulting in incorrect search results which are far from users' intentions. Even though a lot of progress in enhancing the performance of search engines has made over the last years in order to provide users with appropriate results, there is still so much to improve it. Word sense disambiguation can play a very important role in dealing with natural language processing and is considered as one of the most difficult problems in this area. Major approaches to word sense disambiguation can be classified as knowledge-base, supervised corpus-based, and unsupervised corpus-based approaches. This paper presents a method which automatically generates a corpus for word sense disambiguation by taking advantage of examples in existing dictionaries and avoids expensive sense tagging processes. It experiments the effectiveness of the method based on Naïve Bayes Model, which is one of supervised learning algorithms, by using Korean standard unabridged dictionary and Sejong Corpus. Korean standard unabridged dictionary has approximately 57,000 sentences. Sejong Corpus has about 790,000 sentences tagged with part-of-speech and senses all together. For the experiment of this study, Korean standard unabridged dictionary and Sejong Corpus were experimented as a combination and separate entities using cross validation. Only nouns, target subjects in word sense disambiguation, were selected. 93,522 word senses among 265,655 nouns and 56,914 sentences from related proverbs and examples were additionally combined in the corpus. Sejong Corpus was easily merged with Korean standard unabridged dictionary because Sejong Corpus was tagged based on sense indices defined by Korean standard unabridged dictionary. Sense vectors were formed after the merged corpus was created. Terms used in creating sense vectors were added in the named entity dictionary of Korean morphological analyzer. By using the extended named entity dictionary, term vectors were extracted from the input sentences and then term vectors for the sentences were created. Given the extracted term vector and the sense vector model made during the pre-processing stage, the sense-tagged terms were determined by the vector space model based word sense disambiguation. In addition, this study shows the effectiveness of merged corpus from examples in Korean standard unabridged dictionary and Sejong Corpus. The experiment shows the better results in precision and recall are found with the merged corpus. This study suggests it can practically enhance the performance of internet search engines and help us to understand more accurate meaning of a sentence in natural language processing pertinent to search engines, opinion mining, and text mining. Naïve Bayes classifier used in this study represents a supervised learning algorithm and uses Bayes theorem. Naïve Bayes classifier has an assumption that all senses are independent. Even though the assumption of Naïve Bayes classifier is not realistic and ignores the correlation between attributes, Naïve Bayes classifier is widely used because of its simplicity and in practice it is known to be very effective in many applications such as text classification and medical diagnosis. However, further research need to be carried out to consider all possible combinations and/or partial combinations of all senses in a sentence. Also, the effectiveness of word sense disambiguation may be improved if rhetorical structures or morphological dependencies between words are analyzed through syntactic analysis.

• Journal of Intelligence and Information Systems
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• v.19 no.2
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• pp.73-85
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• 2013

Nowadays, in today's information society, the importance of the knowledge service using the information to creative value is getting higher day by day. In addition, depending on the development of IT technology, it is ease to collect and use information. Also, many companies actively use customer information to marketing in a variety of industries. Into the 21st century, companies have been actively using the culture arts to manage corporate image and marketing closely linked to their commercial interests. But, it is difficult that companies attract or maintain consumer's interest through their technology. For that reason, it is trend to perform cultural activities for tool of differentiation over many firms. Many firms used the customer's experience to new marketing strategy in order to effectively respond to competitive market. Accordingly, it is emerging rapidly that the necessity of personalized service to provide a new experience for people based on the personal profile information that contains the characteristics of the individual. Like this, personalized service using customer's individual profile information such as language, symbols, behavior, and emotions is very important today. Through this, we will be able to judge interaction between people and content and to maximize customer's experience and satisfaction. There are various relative works provide customer-centered service. Specially, emotion recognition research is emerging recently. Existing researches experienced emotion recognition using mostly bio-signal. Most of researches are voice and face studies that have great emotional changes. However, there are several difficulties to predict people's emotion caused by limitation of equipment and service environments. So, in this paper, we develop emotion prediction model based on vision-based interface to overcome existing limitations. Emotion recognition research based on people's gesture and posture has been processed by several researchers. This paper developed a model that recognizes people's emotional states through body gesture and posture using difference image method. And we found optimization validation model for four kinds of emotions' prediction. A proposed model purposed to automatically determine and predict 4 human emotions (Sadness, Surprise, Joy, and Disgust). To build up the model, event booth was installed in the KOCCA's lobby and we provided some proper stimulative movie to collect their body gesture and posture as the change of emotions. And then, we extracted body movements using difference image method. And we revised people data to build proposed model through neural network. The proposed model for emotion prediction used 3 type time-frame sets (20 frames, 30 frames, and 40 frames). And then, we adopted the model which has best performance compared with other models.' Before build three kinds of models, the entire 97 data set were divided into three data sets of learning, test, and validation set. The proposed model for emotion prediction was constructed using artificial neural network. In this paper, we used the back-propagation algorithm as a learning method, and set learning rate to 10%, momentum rate to 10%. The sigmoid function was used as the transform function. And we designed a three-layer perceptron neural network with one hidden layer and four output nodes. Based on the test data set, the learning for this research model was stopped when it reaches 50000 after reaching the minimum error in order to explore the point of learning. We finally processed each model's accuracy and found best model to predict each emotions. The result showed prediction accuracy 100% from sadness, and 96% from joy prediction in 20 frames set model. And 88% from surprise, and 98% from disgust in 30 frames set model. The findings of our research are expected to be useful to provide effective algorithm for personalized service in various industries such as advertisement, exhibition, performance, etc.

• KOREAN JOURNAL OF CROP SCIENCE
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• v.27 no.4
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• pp.361-370
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• 1982

The effects of climatic factors on organisms lire variable and complex, and it, however, can be interpreted in terms of those on the distribution and those on the population densities. The distribution of an organism may largely be determined by the temperatures, except some temporal organisms which are depended on the air mass movements. Population density of an organism is determined by various climatic factors, such as previous winter temperature, temperature of growing season and rainfall. The start of growing season of the rice plants has been shifted to earlier since last decade in Korea. This may mean that the overall climatic condition during the growing season might be considerably different from those in past years, and such a difference in climatic conditions might have close relation with the recent status of the diseases and insect pests through direct effects on the physiology and population dynamics of the organisms, as well as through on the biotic associations of the pest organisms. The white back planthopper and brown planthopper have become the key insect pests in Korea in recent years. They are migratory and have high reproductive pontentials and more generations than average residential insects. The synchronization of the migrants and physiological condition of the rice plants seems to be the important factors in relation to the recent outbreaks of these insects; the high reproductive rate can be obtained with the growth stage of rice being 30-50 days after transplanting. The modication of the microclimate associated with high plant density and some other introduced new cultural techniques also have some relation with the outbreak. The key diseases of the rice are the blast disease, sheath blight and the bacterial leaf blight. For the rice blast, the seedling blast and leaf blast during the early growing season and the neck blast, have become more serious, the former may be related to hotbed nursery and the later may be related to the high humidity in early August, and synchronization of the heading time which has been shifted to early part from middle or late part of August. In general, for the rice diseases, the development of the new races have been the most serious which are largely resulted from the introduction of the new varieties, but it also seems to be related with the prolonged periods of the favorable condition associated with the shifted growing seasons. In general, the diseases and insect pest problems have become much more variable and complex, and control measures should be based on the thorough knowledge of the ecology of the pest organisms, that is, effects of various environmental factors on the disease cycle; spore release, spore deposition, infection, colonization and sporulation of the disease organisms, and those on the development, reproductive potentials, dispersal, age specific responses of the insects. The well organized real-time pest management systems, such as alfalfa weevil management system developed at the Purdue University in U.S., is the prime importance for the implementation of the pest management principles.

• Journal of Korea Multimedia Society
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• v.8 no.4
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• pp.439-449
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• 2005

Distributed main memory database management systems (DMM-DBMSs) store the database in main memories of the participating sites. They provide high performance through fast access to the local databases and high speed communication among the sites. Recently, a lot of research results on DMM- DBMSs has been reported. However, to the best of our knowledge, there is no known research result on the performance of the catalog management schemes for DMM-DBMSs. In this work, we evaluated the performance of the partitioned catalog management schemes through experimental analysis. First, we classified the partitioned catalog management schemes into three categories : Partitioned Catalogs Without Caching (PCWC), Partitioned Catalogs With Incremental Caching (PCWIC), and Partitioned Catalogs With Full Caching (PCWFC). Experiments were conducted by varying the number of sites, the number of terminals per site, buffer size, write query ratio, and local query ratio. Experiments show that PCWFC outperforms the other two schemes in all cases. It also means that the performance of PCWIC gradually increases as time goes by. It should be noted that PCWFC does not guarantee high performance for disk-based distributed DBMSs in cases when the workload of individual site is high, catalog write ratio is high, or remote data objects are accessed very frequently. Main reason that PCWFC outperforms for DMM-DBMSs is that query compilation and remote catalog access can be done in a very high speed, even when the catalogs of the remote data objects are frequently updated.

• Journal of Science Education
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• v.44 no.1
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• pp.1-14
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• 2020

In this study, we analyzed the written and drawn explanations of thirty elementary school pre-service teachers in order to examine their perception on the seasonal length of day and night. The main findings are as follows: First, pre-service teachers used the most common term in the description of the texts, such as meridian altitude, axis of rotation, and revolution, and there were more misconceptions in the drawn explanation than in the written explanation. Second, by analyzing the pre-service teachers' perceptions by combining written and drawn explanations, it is possible to detect scientific errors that the distance between the Earth and the Sun is closer when the axis of rotation is tilted in relation to the revolution and seasonal changes due to changes in the orbital radius of the Earth. In addition, there have been types of explanations such as seasonally changing meridian altitudes related to the rotation of the Earth but no change in the location of the Sun. Based on the results of the analysis, we discussed the lack of experience in constructing an explanatory system of specific phenomena using scientific knowledge, lack of observational experiences about natural phenomena, and lack of exposure to other explanatory systems that cause cognitive conflicts. We hope that it will be concrete and practical help to improve the understanding of pre-service teachers in the science domain of primary teacher training program.

• Proceedings of the Korean Society of Grassland Science Conference
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• 2002.09b
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• pp.131-156
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• 2002

Although economically viable, the livestock industry is currently facing a number of challenging environmental problems and highly complex social issues, many of which are related to its size and geographically concentrated nature. Increased emphasis on environmental quality has also placed new demands on livestock producers to ensure that their production practices are in harmony with natural environment. In terms of sustainable agricultural systems, ruminants have served and will continue to serve a valuable role. They are particularly useful in converting vast renewable resources from rangeland, pasture, and crop residues or other by-product into food edible for human. With ruminants, land that is too poor or too erodable to cultivate becomes productive. Also, nutrients in by-products are utilized and do not become a waste-disposal problem. In Korea, however, native and dairy cattle production is not consistent with the advantageous roles of ruminant livestock in sustainable agricultural system because imported feed grains become the main basis for cattle raising. At present the ruminant livestock producers are heavily concentrated in and around the urban areas. About 75% of all the nation's cattle herds are kept on the outskirts of urban areas. As a result, the amount of pasture and forage land available per head of cattle is generally small. Furthermore, animals are raised in a cattle shed with high density. This situation is rather unfavorable for the national economic and environmental points of view As nation income increased, the demand for livestock products grew at an unforeseeable pace. But the pasture area involving in current utilization is tended to decrease during recent years. Based on the above figures more than 250,000 ha of pasture ought to be available for the present herd of cattle. It is obvious that these needs can scarcely be met with arable lands. Lands area for the establishment of new grassland have to be found in the hills and mountains which have not yet been used for crop framing or livestock. The development of extensive grasslands in the hill and woodland areas is now a declared aim. The starting point of the present work is the lack of knowledge of forage production and utilization in hill pasture and woodland in spite of indispensable necessity for livestock production in Korea. The importance of pastoral system in hill region and woodland is particularly emphasized in a standpoint of sustainable livestock production. Main chapter comprises the principle and techniques applicable for improving the utilization of hill pasture and woodland. We finally discussed the problems to solve and future works for a successful livestock production in hill and mountainous area in Korea.

• Journal of KIISE:Software and Applications
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• v.41 no.7
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• pp.481-491
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• 2014

The power production using renewable energy is more important because of a limited amount of fossil fuel and the problem of global warming. A concentrative photovoltaic system comes into the spotlight with high energy production, since the rate of power production using solar energy is proliferated. These systems, however, need to sophisticated tracking methods to give the high power production. In this paper, we propose a hierarchical tracking system using modular Bayesian networks and a naive Bayes classifier. The Bayesian networks can respond flexibly in uncertain situations and can be designed by domain knowledge even when the data are not enough. Bayesian network modules infer the weather states which are classified into nine classes. Then, naive Bayes classifier selects the most effective method considering inferred weather states and the system makes a decision using the rules. We collected real weather data for the experiments and the average accuracy of the proposed method is 93.9%. In addition, comparing the photovoltaic efficiency with the pinhole camera system results in improved performance of about 16.58%.

• Korean Medical Education Review
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• v.17 no.1
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• pp.33-38
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• 2015

During the education reform in 2009, the Catholic University of Korea College of Medicine (CUMC) adopted body systems as the basis for structuring basic medical education. After running the new program for 5 years, we need to evaluate the program by comparing it with nationwide standards. This study was designed to evaluate the coverage of our basic medical education program by comparing it with the assessment items of the medical licensing examination for physicians in the Republic of Korea. We built a relational database populated with 3,017 learning outcomes from all the courses on basic medical education. We tagged each learning outcome according to 2 criteria: 206 physician encounters and 9 outcome domains. A majority of the learning outcomes were in the domains of 'knowledge' and 'critical thinking'. In addition, we repeated the categorization process with 584 assessment items of the medical licensing examination in the Republic of Korea and compared them with the categorization results of the learning outcomes. Among the 206 physician encounters, we found that outcomes on family violence and sexual violence were missing in the learning outcomes of CUMC. Eighty-two physician encounters were associated with more than one outcome domain, and 96 physician encounters were covered in more than one course. Twenty-one physician encounters were repeated in 5 or more courses and 34 physician encounters had outcomes categorized into 3 or more domains. Thus, we showed that the 2-way categorization could be applied to the comparison and evaluation of two different education formats.