• Journal of Computing Science and Engineering
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• v.1 no.2
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• pp.177-194
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• 2007

Index selection is one of the most important decisions to take in the physical design of relational data warehouses. Indices reduce significantly the cost of processing complex OLAP queries, but require storage cost and induce maintenance overhead. Two main types of indices are available: mono-attribute indices (e.g., B-tree, bitmap, hash, etc.) and multi-attribute indices (join indices, bitmap join indices). To optimize star join queries characterized by joins between a large fact table and multiple dimension tables and selections on dimension tables, bitmap join indices are well adapted. They require less storage cost due to their binary representation. However, selecting these indices is a difficult task due to the exponential number of candidate attributes to be indexed. Most of approaches for index selection follow two main steps: (1) pruning the search space (i.e., reducing the number of candidate attributes) and (2) selecting indices using the pruned search space. In this paper, we first propose a data mining driven approach to prune the search space of bitmap join index selection problem. As opposed to an existing our technique that only uses frequency of attributes in queries as a pruning metric, our technique uses not only frequencies, but also other parameters such as the size of dimension tables involved in the indexing process, size of each dimension tuple, and page size on disk. We then define a greedy algorithm to select bitmap join indices that minimize processing cost and verify storage constraint. Finally, in order to evaluate the efficiency of our approach, we compare it with some existing techniques.

• Journal of KIISE:Databases
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• v.36 no.2
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• pp.84-98
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• 2009

Various algorithms and architectures for IP address lookup have been studied to improve forwarding performance in the Internet routers. Previous IP address lookup architecture using Bloom filter requires a separate Bloom filter as well as a separate hash table in each prefix length, and hence it is not efficient in implementation complexity. To reduce the number of hash tables, it applies controlled prefix expansion, but prefix duplication is inevitable in the controlled prefix expansion. Previous parallel multiple-hashing architecture shows very good search performance since it performs parallel search on tables constructed in each prefix length. However, it also has high implementation complexity because of the parallel search structure. In this paper, we propose a new IP address lookup architecture using all-length Bloom filter and all-length multiple hash table, in which various length prefixes are accomodated in a single Bloom filter and a single multiple hash table. Hence the proposed architecture is very good in terms of implementation complexity as well as search performance. Simulation results using actual backbone routing tables which have $15000{\sim}220000$ prefixes show that the proposed architecture requires 1.04-1.17 memory accesses in average for an IP address lookup.

• The Korean Journal of Archival Studies
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• no.67
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• pp.139-203
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• 2021

The study aims to analyze the records management reference tables currently being utilized and to provide directions on how should be redesigned in the future to operate as a appraisal tool for national archives. From the perspective of "what records should be the national archives", it was intended to analyze the records management reference tables, particularly in the environmental public authorities, and to propose future improvements. The main focus of the analysis is on appraising records that need to be preserved as national archives, and therefore, prior to analysis of the tables, it examines whether the archival selection criteria are clearly presented. Subsequently, the study is conducted how to implement this criteria through the records management reference table of each agency and how its implementation system will be constructed. The analysis will be focused on Ministry of Environment's records management reference table and records schedules or appraisal/selection tools of the central and federal institutions that perform environmental functions in U.S., Australia, and UK.

• International journal of advanced smart convergence
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• v.10 no.1
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• pp.1-11
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• 2021

Document page segmentation is an important step in building a quality optical character recognition module. The study examined already existing work on the topic of page segmentation and focused on the development of a segmentation model that has greater functional significance for application in an organization, as well as broad capabilities for managing the quality of the model. The main problems of document segmentation were highlighted, which include a complex background of intersecting objects. As classes for detection, not only classic text, table and figure were selected, but also additional types, such as signature, logo and table without borders (or with partially missing borders). This made it possible to pose a non-trivial task of detecting non-standard document elements. The authors compared existing neural network architectures for object detection based on published research data. The most suitable architecture was RetinaNet. To ensure the possibility of quality control of the model, a method based on neural network modeling using the RetinaNet architecture is proposed. During the study, several models were built, the quality of which was assessed on the test sample using the Mean average Precision metric. The best result among the constructed algorithms was shown by a model that includes four neural networks: the focus of the first neural network on detecting tables and tables without borders, the second - seals and signatures, the third - pictures and logos, and the fourth - text. As a result of the analysis, it was revealed that the approach based on four neural networks showed the best results in accordance with the objectives of the study on the test sample in the context of most classes of detection. The method proposed in the article can be used to recognize other objects. A promising direction in which the analysis can be continued is the segmentation of tables; the areas of the table that differ in function will act as classes: heading, cell with a name, cell with data, empty cell.

• Archives of design research
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• v.16 no.3
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• pp.319-328
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• 2003

The purpose of this study was to investigate the actual size of tables and chairs in small restaurants. The examined objets were 48 restaurants serving flour-based, korean style and japanese style meals. Those restaurants are currently being operated at six universities in Seoul, and their sizes are limited under $66m^2$. The results of this study were as follows ; 1 . In small restaurants, the size of the seat for one person is $0.346m^2$on the average. The range of the size starts from $0.285m^2$to $0.403m^2$, showing a great difference. 2. The most common size of tables in small restaurants is the oblong style of $600{\times}900$ for four people. The smallest size is $440{\times}710$, while the biggest one is $700{\times}1000$, showing a great number of variation. If the most common size of tables is set to be the general size of tables in small restaurants, it will be $600{\times}900$. 3. The sizes of the seats for chairs used in small restaurants start from $270{\times}270$ to $430{\times}430$. The most common size of the seats for chairs is $400{\times}400$, only showing a small number. For the cases of tables with the most common size of $600{\times}900$, the width of the seats for chairs should be under 400. 4. For the height between the table and the seats of the chair, the distance from 270 to 300 is relevant. However, according to the results of the investigation, it seems that there are more cases of the distance from 250 to 260 than that from 270 to 300.

• Journal of The Korean Association For Science Education
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• v.4 no.1
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• pp.15-25
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• 1984

The purpose of this study is to develop a practical and ideal model of science laboratory enrolled 48-60 students by studying optimal facilities such as laboratory tables and chairs proper to elementary school settings. The science laboratory model was figured out in terms of the following six procedures; (1) Current status as well as problems of science laboratory and its facilities was identified by means of the questionnaires conducted to 201 elementary schools, using stratified cluster sampling tehnique, under the consideration of the school size and the regional characteristics across the country. (2) Collected were the anthropometric data with respect to sitting height, popliteal height, buttock popliteal length, elbow rest height, and back width from the 747 students, 4th-6th grade, in Seoul area. (3) It was measured the work apace necessary for individual student to perform his experiment. (4) Using the data of the process (2), we determined the optimal sizes of laboratory tables and chairs fitted for Korean elementary school students. (5) The optimal area of science laboratory for 48-60 students is determined in terms of the data obtained in (3) for individual work space in addition to the appropriate table size figured out by (4). (6) A practical and ideal model for a science laboratory in elementary school was designed according to the above procedures. For the optimal model of science laboratory, the results of this study can be summarized as follows: The sizes of chair and table are categorized into three groups such as small, medium, and large depending on students' physical outfit. The small size base on the 12.5th percentile point of students' sitting height is used for students of the 0-25th percentile ranks. The medium size base on the 50th percentile point of students' sitting height is used for students of the 26-75th percentile ranks. The large size base on the 87.5th percentile point of students' sitting height is used for students of the 76-100th percentile ranks. (1) Sizes of chairs: The small size is 28cm in width and 33cm in height. The medium size is 31cm in width and 36cm in height. The large size is 35cm in width and 38cm in height. (2) Sizes of laboratory tables: The small size is 120cm in length, 86cm in width, and 60cm in height. The large size is 120cm in length, 86cm in width, and 60cm in height. The large size is 120cm in length, 86cm in width, and 65cm in height. (3) Size of science laboratory: The optimal science laboratory for 48-60 elementary school students, which can install the 12 laboratory tables, is 12m in length and 10m in width.

• Journal of the Institute of Electronics Engineers of Korea CI
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• v.46 no.4
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• pp.94-101
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• 2009

In this paper, we propose design of hardware based on a high speed digital signal processor (DSP) and a field programmable gate array (FPGA) for real-time suppression of fixed pattern noise (FPN) using hardware neural networks (HNN) in cooled infrared focal plane array (IRFPA) imaging system FPN appears a limited operation by temperature in observable images which applies to non-uniformity correction for infrared detector. These have very important problems because it happen serious problem for other applications as well as degradation for image quality in our system Signal processing architecture for our system operates reference gain and offset values using three tables for low, normal, and high temperatures. Proposed method creates virtual tables to separate for overlapping region in three offset tables. We also choose an optimum tenn of temperature which controls weighted values of HNN using mean values of pixels in three regions. This operates gain and offset tables for low, normal, and high temperatures from mean values of pixels and it recursively don't have to do an offset compensation in operation of our system Based on experimental results, proposed method showed improved quality of image which suppressed FPN by change of temperature distribution from an observational image in real-time system.

• Journal of the Korean Society of Fisheries and Ocean Technology
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• v.20 no.2
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• pp.112-121
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• 1984

This paper is compared the simulation tables by the general propagation velocity and the calculated propagation velocities with distances and times to take to be transmitted Loran C wave from master station to slave stations, with Loran C tables, and compared the accuracy of position fixes by the simulation to them by Loran C table with the time differences of 9970 chain to be measured in the south coast of Korea, and by the simulation with the time differences of 5970 chain to be measured at definite position to them. The results obtained are as follows; 1. the simulation tables by the calculated propagation velocities is nearer to Loran C tables than it by the general propagation velocity. 2. The ranges of total errors of the simulation positions by the general propagation velocity and the calculated propagation velocities to the position fixies of Loran C table with the time differences of 9970 chain to be measured in the south coast of Korea are 0.2-0.7 miles, 0.01-0.1 miles, and the mean values of them are 0.46 miles and standard deviations of time are 0.1 miles, 0.03 miles respectively. 3. Mean value of total errors of the simulation position by the calculated propagation velocities to the definite position with the time difference of 5970 chain is 0.2miles and is reduced 0.1-0.2 miles than it by the general propagation velocity.

• The Korean Journal of Food And Nutrition
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• v.26 no.4
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• pp.886-894
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• 2013

The National Standard Food Composition Table published by the Rural Development Administration (RDA) provides the foundations in research, nutrition monitoring, policy and dietary practices in Korea. This databases consists of several sets of data including food descriptions, nutrients, portion weights, and source of data. The National Standard Food Composition Table have been published since 1970 and, recently, new version (8th edition) of Food Composition Table which has quantitative and qualitative nutrient data is released in 2011. In addition, the User-friendly Food Composition Table is divided into adult, children, and elderly categories depending on the subjects because we need different nutrients according to various ages. The Tables of Food Functional Composition is firstly edited in 2009. RDA published the minerals and fatty acids composition table, tables of amino acid, fat-soluble vitamin composition table, and the cholesterol table. The resulting database will be widely used. The users of the databases are from diverse fields, includeing federal agencies, the food industry, health professionals, restaurants, software application developers, academia and research organizations, international organizations, and foreign governments ect. Therefore, consistent improvements of the database is important, so that people can better address such health challenges by providing reliable and accurate data.

• The KIPS Transactions:PartD
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• v.19D no.1
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• pp.1-14
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• 2012

As the size of the data warehouse is large, the selection of indices on the data warehouse affects the efficiency of the query processing of the data warehouse. Indices induce the lower query processing cost, but they occupy the large storage areas and induce the index maintenance cost which are accompanied by database updates. The bitmap join indices are well applied when we optimize the star join queries which join a fact table and many dimension tables and the selection on dimension tables in data warehouses. Though the bitmap join indices with the binary representations induce the lower storage cost, the task to select the indexing attributes among the huge candidate attributes which are generated is difficult. The processes of index selection are to reduce the number of candidate attributes to be indexed and then select the indexing attributes. In this paper on bitmap join index selection problem we reduce the number of candidate attributes by the data mining techniques. Compared to the existing techniques which reduce the number of candidate attributes by the frequencies of attributes we consider the frequencies of attributes and the size of dimension tables and the size of the tuples of the dimension tables and the page size of disk. We use the mining of the frequent itemsets as mining techniques and reduce the great number of candidate attributes. We make the bitmap join indices which have the least costs and the least storage area adapted to storage constraints by using the cost functions applied to the bitmap join indices of the candidate attributes. We compare the existing techniques and ours and analyze them in order to evaluate the efficiencies of ours.