• Fire Science and Engineering
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• v.26 no.5
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• pp.1-7
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• 2012

We have studied on equivalent length tables which are used to calculate the friction loss of pipe fittings and valves of water-based fire systems in Korea. Three kinds of equivalent length tables are mainly used and unfortunately, the most extensively used table is not ascertained the reliable source. When the three tables are compared, each table has different equivalent length up to 2.4 times in same item. We should use unified equivalent length table which is scientifically reasonable in order to act up to globalization as performing lots of over-sea projects. Therefore, we propose the reasonable equivalent length tables.

• Journal of Korea Multimedia Society
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• v.19 no.11
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• pp.1837-1851
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• 2016

Newspaper reader mobile applications using text-to-speech (TTS) function enable blind people to read newspaper contents. But, tables cannot be easily read by the reader program because most of the tables are stored as images in the contents. Even though we try to use OCR (Optical character reader) programs to recognize letters from the table images, it cannot be simply applied to the table reading function because the table structure is unknown to the readers. Therefore, identification of exact location of each table cell that contains the text of the table is required beforehand. In this paper, we propose an efficient image processing algorithm to recognize all the cells in tables by identifying columns and rows in table images. From the cell location data provided by the table column and row identification algorithm, we can generate table structure information and table reading scenarios. Our experimental results with table images found commonly in newspapers show that our cell identification approach has 100% accuracy for simple black and white table images and about 99.7% accuracy for colored and complicated tables.

• Journal of the Korean Society of Industry Convergence
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• v.5 no.2
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• pp.103-110
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• 2002

An artificial neural network is applied to the prediction of compressive strength, slump value of concrete. Standard mixed tables arc trained and estimated, and the results are compared with those of experiments. To consider the varieties of material properties, the standard mixed tables of two companies of Ready Mixed Concrete are used. And they are trained with the neural network. In this paper, standard back propagation network is used. For the arrangement on the approval of prediction of compressive strength and slump value, the standard compressive strength of 210, $240kgf/cm^2$ and target slump value of 12, 15cm are used because the amount of production of that range arc the most at ordinary companies. In results, in the prediction of compressive strength and slump value, the predicted values are converged well to those of standard mixed tables at the target error of 0.10, 0.05, 0.001 regardless of two companies.

• Proceedings of the Korean Society for Noise and Vibration Engineering Conference
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• 2012.04a
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• pp.324-329
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• 2012

Isolation tables are widely used for precision equipments and their isolation performances have been usually expressed and evaluated by transsmissibility. However, transmissibility is a concept for 1-degree of freedom(DOF) system. In practice, isolation tables are supproted by more than 4 springs. Each spring is subjected to vertical and horizontal ground vibrations, and also the table has more than 1-DOF. Therefore, isolation tables should be treated as multi-input/multi-output(MIMO) system of which isolation performance is expressed by transmissibility matrix. However, the matrix is too complicated to be an index for a system. In this paper, maximum singular value of transmissibility matrx is suggested as a simple performance index of a MIMO isolation system. Physical meaning of singular value is explained using a simple a 2-DOF isolation table. Furthermore, maximum singular values of passive, 3-DOF active and 6-DOF active isolation tables are obtained through experiments, and their meaning are explained and compared with each other.

• Proceedings of the Korea Information Processing Society Conference
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• 2005.05a
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• pp.55-58
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• 2005

In multi-level storage system with snapshot data, some snapshots which are from selection portions of the base tables are kept in main memory. So how to efficiently refresh snapshots in response to changes on their base tables for preserving consistency which requires snapshots reflect the current state of the base tables referenced by the snapshot query is a very import research issue. In this paper, a method for efficiently refreshing snapshots is proposed. In this method, it uses a data structure to store metadata which contains some necessary information of every snapshot and an updating log that records the history of changes on its base tables. Synchronization process scans the metadata and refreshing process is executed using appropriate logs after it finds anyone of the snapshot need to be refreshed.

• Smart Structures and Systems
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• v.32 no.6
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• pp.359-369
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• 2023

Servo-motor driven uniaxial shake tables have been widely used for education and research purposes in earthquake engineering. These shake tables are mostly displacement-controlled by a digital proportional-integral-derivative (PID) controller; however, accurate reproduction of acceleration time histories is not guaranteed. In this study, a control strategy is proposed and verified for uniaxial shake tables driven by a servo-motor. This strategy incorporates a deep-learning algorithm named Long Short-Term Memory (LSTM) network into a displacement PID feedback controller. The LSTM controller is trained by using a large number of experimental data of a self-made servo-motor driven uniaxial shake table. After the training is completed, the LSTM controller is implemented for directly generating the command voltage for the servo motor to drive the shake table. Meanwhile, a displacement PID controller is tuned and implemented close to the LSTM controller to prevent the shake table from permanent drift. The control strategy is named the LSTM-PID control scheme. Experimental results demonstrate that the proposed LSTM-PID improves the acceleration tracking performance of the uniaxial shake table for both bare condition and loaded condition with a slender specimen.

• Journal of Forest and Environmental Science
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• v.28 no.4
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• pp.205-211
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• 2012

Yield tables are a frequently used data base for regional timber resource forecasting. A normal yield table is based on two independent variables, age and site (species constant), and applies to fully stocked (or normal) stands while empirical yield tables are based on average rather than fully stocked stands. Normal and empirical yield tables essentially have many limitations. The limitations of normal and empirical yield tables led to the development of variable density yield tables. Mathematical models for estimating timber yields are usually developed by fitting a suitable equation to observed data. The model is then used to predict yields for conditions resembling those of the original data set. It may be accurate for the specific conditions, but of unproven accuracy or even entirely useless in other circumstances. Thus, these models tend to be specific rather than general and require validation before applying to other areas. Dalbergia sissoo forms a major portion of irrigated plantations in the hot desert of India and is an important timber tree species where stem wood is primarily used as timber. Variable density yield model is not available for this species which is very crucial in long-term planning for managing the plantations on a sustained basis. Thus, the objective of this study was to develop variable density yield model based on the data collected from 30 sample plots of D. sissoo laid out in IGNP area of Rajasthan State (India) and measured annually for 5 years. The best approximating model was selected based on the fit statistics among the models tested in the study. The model develop was evaluated based on quantitative and qualitative statistical criteria which showed that the model is statistically sound in prediction. The model can be safely applied on D. sissooo plantations in the study area or areas having similar conditions.

• Journal of Korean Library and Information Science Society
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• v.33 no.2
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• pp.167-187
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• 2002

This study suggests a plan of tables of deference for Korean Decimal Classification, 4th edition, based on the study on those in Dewey Decimal Classification, 21st edition. It suggests two tables for the Auxiliary Tables, one for standard subdivisions and one for subdivisions for literature. Twenty-two tables are suggested for the Schedule of ten main classes.

• The Journal of the Korea Contents Association
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• v.6 no.10
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• pp.25-33
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• 2006

For semantic retrieval in semantic web environment, it is an important factor to manage and manipulate distributed resources. Ontology is essential for efficient search in distributed resources, but it is almost impossible to construct an unified ontology for all distributed resources in the web. In this paper, we assumed that most information in the web environment exist in the form of RDBMS, and propose a matching method between domain ontology and the existing RDBMS tables for semantic retrieval. Most previous studies about matching between RDBMS tables and domain ontology have extracted a local ontology from RDBMS tables at first, and conducted the matching between the local ontology and domain ontology. However in the processing of extracting a local ontology, some problems such as losing domain information can be occurred since its correlation with domain ontology has not been considered at all. In this paper, we propose a methods to prevent the loss of domain information through the similarity measure between instances of RDBMS tables and instances of ontology. And using the relational information between RDBMS tables and the relational information between classes in domain ontology, more efficient instance-based matching becomes possible.

• Journal of Korea Multimedia Society
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• v.9 no.9
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• pp.1231-1246
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• 2006

HTML is a format for rendering Web documents visually and uses tables to present a relational information. Since HTML has limits in terms of information processing and management by a computer, it is important to transform HTML tables into XML documents, which is able to represent logical structure information. As a prerequisite for extracting information from the Web, this paper presents an efficient method for extracting logical structures from HTML tables and transforming them into XML documents. The proposed method consists of two phases: Area segmentation and structure analysis. The area segmentation step removes noisy areas and extracts attribute and value areas through visual and semantic coherency checkup. The hierarchical structure between attribute and value areas are analyzed and transformed into XML representations using a proposed table model. Experimental results with 1,180 HTML tables show that the proposed method performs better than the conventional method, resulting in an average precision of 86.7%.