• The Journal of the Korea Contents Association
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• v.10 no.6
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• pp.49-54
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• 2010

As information on gene sequences is not only diverse but also extremely huge in volume, high-performance computer and information technology techniques are required to build and analyze gene sequence databases. This has given rise to the discipline of bioinformatics, a field of research where computers are utilized to collect, to manage, to save, to evaluate, and to analyze biological data. In line with such continued development in bioinformatics, the Korea Institute of Science and Technology Information (KISTI) has built an infrastructure for the biological information, based on the information technology, and provided the information for researchers of bioscience. This paper analyzes the reference fields of Genbank, the most frequently used gene database by the global researchers among the life information databases, and proposes the interface method to NDSL which is the science and technology information integrated service provided by KISTI. For these, after collecting Genbank data from NCBI FTP site, we rebuilt the database by separating Genbank text files into the basic gene data and the reference data. So new tables are generated through extracting the paper and patent information from Genbank reference fields. Then we suggest the method of connection with the paper DB and the patent DB operated by KISTI.

• Journal of Korea Technology Innovation Society
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• v.18 no.3
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• pp.387-415
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• 2015

In this study, we have proposed an estimation model of domestic market size using the linking between standard statistical classification systems, and reviewed the practical applicability of the model. The results of the mining and manufacturing survey of Statistics Korea conducted on the basis of KSIC (Korea Standard Industrial Classification) and Korea trade statistics based on HS (The Harmonized Commodity Description and Coding System; Harmonized System) classification were linked for the model by using the correspondence tables provided by Statistics Korea and United Nations Statistics Division. The most serious problem to adopt the integrated KSIC-ISIC-HS correspondence table for the estimation of domestic market size is the complex multiple linkages among KSIC and HS codes. In this study, we have suggested the method to divide the amount of trade corresponding to the HS codes linked to more than two ISIC codes based on the ratio of shipments corresponding to the ISIC codes as the weight. Then, it is possible to analyze the domestic market size of 125 ISIC codes in the manufacturing industry and to forecast the market size in the near future by using the model. Although the model has some limitations such as the difficulty in analysis on more subdivided items than ISIC items, the impossibility of the analysis on items in industries except for manufacturing, errors in the shipment due to some missing data, this study has significance in the sense that it provided the analysis method of domestic market size by using the most objective, reliable and sustainably useful data.

• Journal of KIISE:Databases
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• v.30 no.3
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• pp.336-349
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• 2003

Histograms have been getting a lot of attention recently. Histograms are commonly utilized in commercial database systems to capture attribute value distributions for query optimization Recently, in the advent of researches on approximate query answering and stream data, the interests in histograms are widely being spread. The simplest approach assumes that the attributes in relational tables are independent by AVI(Attribute Value Independence) assumption. However, this assumption is not generally valid for real-life datasets. To alleviate the problem of approximation on multi-dimensional data with multiple one-dimensional histograms, several techniques such as wavelet, random sampling and multi-dimensional histograms are proposed. Among them, GENHIST is a multi-dimensional histogram that is designed to approximate the data distribution with real attributes. It uses overlapping buckets that allow more efficient approximation on the data distribution. In this paper, we propose a scheme, OPT that can determine the optimal frequencies of overlapped buckets that minimize the SSE(Sum Squared Error). A histogram with overlapping buckets is first generated by GENHIST and OPT can improve the histogram by calculating the optimal frequency for each bucket. Our experimental result confirms that our technique can improve the accuracy of histograms generated by GENHIST significantly.

• Journal of KIISE:Software and Applications
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• v.30 no.7_8
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• pp.672-680
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• 2003

A shopbot is a software agent whose goal is to maximize buyer´s satisfaction through automatically gathering the price and quality information of goods as well as the services from on-line sellers. In the response to shopbots´ activities, sellers on the Internet need the agents called pricebots that can help them maximize their own profits. In this paper we adopts Q-learning, one of the model-free reinforcement learning methods as a price-setting algorithm of pricebots. A Q-learned agent increases profitability and eliminates the cyclic price wars when compared with the agents using the myoptimal (myopically optimal) pricing strategy Q-teaming needs to select a sequence of state-action fairs for the convergence of Q-teaming. When the uniform random method in selecting state-action pairs is used, the number of accesses to the Q-tables to obtain the optimal Q-values is quite large. Therefore, it is not appropriate for universal on-line learning in a real world environment. This phenomenon occurs because the uniform random selection reflects the uncertainty of exploitation for the optimal policy. In this paper, we propose a Mixed Nonstationary Policy (MNP), which consists of both the auxiliary Markov process and the original Markov process. MNP tries to keep balance of exploration and exploitation in reinforcement learning. Our experiment results show that the Q-learning agent using MNP converges to the optimal Q-values about 2.6 time faster than the uniform random selection on the average.

• The Journal of the Korea Contents Association
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• v.15 no.9
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• pp.403-410
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• 2015

Since 1970, MRI has greatly been developing in terms of strength of magnetic field, the number of receipt channels, and short time of examination. With the development of digital systems and wireless network, hospitals have also acquired, saved, and managed digital images taken by various kinds of medical imaging equipment. However, domestic universities fail to provide practice training course independently thanks to expensive practice equipment and high maintenance cost, and rely on clinical training. Therefore, this study developed a MR patient diagnosis program based on Windows PC to help out students before their working in clinical filed. The designed Relational Database of MRI Simulator is made up of seven tables according to functions and data characteristics. Regarding the designed patient information, each stepwise function was classified by the patient registration method in clinical field. In addition, on the assumption of the basic information for diagnosis, each setting and content were classified. The menu by execution step was arrayed on the left side for easy view. For patient registration, a patient's name, gender, unique ID, birth date, weight, and other types of basic information were entered, and the patient's posture and diagnosis direction were set up. In addition, the body regions for diagnosis and Pulse Sequence were listed for selection. Also, Protocol name and other additional factors were allowed to be entered. The final window was designed to check diagnosis images, patient information, and diagnosis conditions. By learning how to enter patient information and change diagnosis conditions in this program, users will be able to understand more theories and terms learned in practice and thereby to shorten their learning time in actual clinical work.

• Journal of Nutrition and Health
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• v.45 no.1
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• pp.80-93
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• 2012

Recent studies have reported that the glycemic index (GI) has an effect on developing the risk for metabolic abnormalities such as diabetes, dyslipidemia, and obesity. As there are no reliable GI values for common Korean foods, only a few studies have been carried out using the dietary GI for Korean adults. The aim of this study was to establish a table of GI values for common Korean foods and evaluate dietary glycemic index (DGI) and dietary glycemic load (DGL) among the Korean adult population. International tables of GI values and other published values were used to tabulate GI values for common Korean foods. Among 653 food items, 149 (22.8%) were adapted from published data, 60 (9.2%) were imputed from similar foods, and 444 (68.0%) were assigned a zero. Data from 7,940 subjects aged 20 years and older in the 2007-2008 Korea National Health and Nutrition Examination Survey were obtained, and DGI and DGL were calculated. The average DGI was 60.0 and the average DGL was 182.5 when the reference food GI value was glucose. After adjusting for potential confounding variables, DGI and DGL increased significantly according to age group (p for trend < 0.001). The food group that contributed most to DGL was grain and its products supplying 85.3% of total DGL, whereas the mean GI value in grain and its products was 72.6. Fruits and potatoes also contributed to DGL (5.8 and 2.9%, respectively), and their GIs were high (67.7 for potatoes and 45.8 for fruits). For individual food items, white rice supplied 66.7% of total GI followed by glutinous rice (2.3%) and steamed white rice cakes (2.0%). In conclusion, a table of GI values for 653 common food items was established in which white rice was the most contributing item to DGL. Our results will be useful to examine the relationships between DGI, DGL, and metabolic abnormalities in the Korean population.

• The Journal of Korean Institute of Communications and Information Sciences
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• v.31 no.5A
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• pp.459-468
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• 2006

Current routing in sensor networks focuses on finding methods for energy-efficient route setup and reliable relaying of data from the sensors to the sink so that the lifetime of the network is maximized. The existing routing protocols do not have routing tables to determine a path when packets are transferred. A sensor network by a routing table increases a cost of maintaining and updating a path, because sensor nodes have characteristics to be mobile and constrained capacity and resources. This paper proposes a new routing algorithm by broadcasting a bitmap in order to reduce the number of messages transferred when routing paths are established. Each node has a routing table with a bitmap, which contains link information. A bitmap is formed two-dimensional array, which consists of each row and column represented with a bit. The node only updates its own bitmap if it receives a bitmap from another adjacent nodes after the broadcasting. There by, each node has a bitmap with partial links information not total links information on the network. The proposed routing algorithm reduces the number of messages for routing establishment at least 10% compared with the previous algorithms.

• Journal of the Korea Academia-Industrial cooperation Society
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• v.17 no.11
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• pp.340-347
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• 2016

Since the 1970s, manufacturing has been one of the key driving forces that has led to Korea's economic growth. However, this growth rate has been reduced significantly since the 2000s, and shows that revenues and employment are steadily decreasing. In addition, while manufacturing investment in Korea has dropped sharply, the United States, Germany, Japan, and other major countries have increased investment in manufacturing. These countries have promoted manufacturing innovation strategies that include the convergence of information and communications technologies (ICT) and manufacturing. For manufacturing innovation, it is important for time and cost savings required for product development to be achieved by changes in the production process, especially product design. Modeling and simulation (M&S) is a process that replaces physical product design, mockup making, and testing, with virtual product creation (modeling) and engineering analysis (simulation). In this paper, we analyze the economic ripple effect of supercomputing M&S using an input-output model technique based on the input-output tables published by the Bank of Korea. When we set the M&S budget (about US$16 million for the last 10 years) of the Korea Institute of Science and Technology Information (KISTI) as input coefficients, the effect on production inducement, value-added inducement, and employment inducement was analyzed to be US$24 million, US$13.4 million, and 267, respectively.

• Journal of KIISE:Computing Practices and Letters
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• v.15 no.5
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• pp.345-349
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• 2009

Social bookmarking systems are a typical web 2.0 service based on folksonomy, providing the platform for storing and sharing bookmarking information. Spammers in social bookmarking systems denote the users who abuse the system for their own interests in an improper way. They can make the entire resources in social bookmarking systems useless by posting lots of wrong information. Hence, it is important to detect spammers as early as possible and protect social bookmarking systems from their attack. In this paper, we applied a diverse set of machine learning approaches, i.e., decision tables, decision trees (ID3), $na{\ddot{i}}ve$ Bayes classifiers, TAN (tree-augment $na{\ddot{i}}ve$ Bayes) classifiers, and artificial neural networks to this task. In our experiments, $na{\ddot{i}}ve$ Bayes classifiers performed significantly better than other methods with respect to the AUC (area under the ROC curve) score as veil as the model building time. Plausible explanations for this result are as follows. First, $na{\ddot{i}}ve$> Bayes classifiers art known to usually perform better than decision trees in terms of the AUC score. Second, the spammer detection problem in our experiments is likely to be linearly separable.

• KIPS Transactions on Software and Data Engineering
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• v.7 no.9
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• pp.335-344
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• 2018

The power model is needed to handle the power consumption of mobile AMOLED display at the software level. However, the existing studies to generate the power model have required the experimental environment and equipment for the power measurement activity. In addition, the combination of RGB values used for modeling was imprudent and small, so it was difficult to reflect the mutual influence between the RGB values into the model. To solve these problems, we propose an RGB color space partitioning method, which is used to prudently sample the combinations of the RGB values based on the color or the power. We also propose a process for generating a mapping table composed of . We analyzed the characteristics of the samples generated according to the proposed partitioning methods, taking into account the color and the power, and generated the mapping table for the AMOLED display. Furthermore, we confirmed the reusability of the mapping table by utilizing one mapping table multiple times in evaluating different power models. These mapping tables are provided to researchers and can be used to generate and evaluate power models without power measurement activities.