• Structural Engineering and Mechanics
• /
• v.31 no.1
• /
• pp.57-74
• /
• 2009

Power signals resulting from spindle and feed motor, present a rich content of physical information, the appropriate analysis of which can lead to the clear identification of the nature of the tool wear. The partial least-squares regression (PLSR) method has been established as the tool wear analysis method for this purpose. Firstly, the results of the application of widely used techniques are given and their limitations of prior methods are delineated. Secondly, the application of PLSR is proposed. The singular value theory is used to noise reduction. According to grey relational degree analysis, sample variable is filtered as part sample variable and all sample variables as independent variables for modelling, and the tool wear is taken as dependent variable, thus PLSR model is built up through adapting to several experimental data of tool wear in different milling process. Finally, the prediction value of tool wear is compare with actual value, in order to test whether the model of the tool wear can adopt to new measuring data on the independent variable. In the new different cutting process, milling tool wear was predicted by the methods of PLSR and MLR (Multivariate Linear Regression) as well as BPNN (BP Neural Network) at the same time. Experimental results show that the methods can meet the needs of the engineering and PLSR is more suitable for monitoring tool wear.

• Journal of Computing Science and Engineering
• /
• v.7 no.1
• /
• pp.1-20
• /
• 2013

Over the past generation, data warehousing and online analytical processing (OLAP) applications have become the cornerstone of contemporary decision support environments. Typically, OLAP servers are implemented on top of either proprietary array-based storage engines (MOLAP) or as extensions to conventional relational DBMSs (ROLAP). While MOLAP systems do indeed provide impressive performance on common analytics queries, they tend to have limited scalability. Conversely, ROLAP's table oriented model scales quite nicely, but offers mediocre performance at best relative to the MOLAP systems. In this paper, we describe a storage and indexing framework that aims to provide both MOLAP like performance and ROLAP like scalability by essentially combining some of the best features from both. Based upon a combination of R-trees and bitmap indexes, the storage engine has been integrated with a robust OLAP query engine prototype that is able to fully exploit the efficiency of the proposed storage model. Specifically, it utilizes an OLAP algebra coupled with a domain specific query optimizer, to map user queries directly to the storage and indexing framework. Experimental results demonstrate that not only does the design improve upon more naive approaches, but that it does indeed offer the potential to optimize both query performance and scalability.

• Journal of the Society of Disaster Information
• /
• v.13 no.3
• /
• pp.322-331
• /
• 2017

This study proposed subway construction information classification system based on civil engineering information classification system proposed by Korea Institute of Construction Technology. Also, Based on this criterion, This study established data modeling for NAS operating system Composed of construction information classification system - network - operation and presented an relational database integrated model. The data modeling method proposed in this study can be applied to other civil engineering facilities, so it can be operated as scientific NAS.

• Journal of Computing Science and Engineering
• /
• v.3 no.1
• /
• pp.27-58
• /
• 2009

Aggregation join queries are an important class of queries over data streams. These queries involve both join and aggregation operations, with window-based joins followed by an aggregation on the join output. All existing research address join query optimization and aggregation query optimization as separate problems. We observe that, by putting them within the same scope of query optimization, more efficient query execution plans are possible through more versatile query transformations. The enabling idea is to perform aggregation before join so that the join execution time may be reduced. There has been some research done on such query transformations in relational databases, but none has been done in data streams. Doing it in data streams brings new challenges due to the incremental and continuous arrival of tuples. These challenges are addressed in this paper. Specifically, we first present a query processing model geared to facilitate query transformations and propose a query transformation rule specialized to work with streams. The rule is simple and yet covers all possible cases of transformation. Then we present a generic query processing algorithm that works with all alternative query execution plans possible with the transformation, and develop the cost formulas of the query execution plans. Based on the processing algorithm, we validate the rule theoretically by proving the equivalence of query execution plans. Finally, through extensive experiments, we validate the cost formulas and study the performances of alternative query execution plans.

• Journal of the Society of Naval Architects of Korea
• /
• v.30 no.3
• /
• pp.90-99
• /
• 1993

As the finite element method has become a considerable and effective design tool in ship structural analysis, modeling of three dimensional finite element mesh is more necessary than before. However, the unique style and complexity of a ship usually make the modeling be hard and costly. Although most pre-processor of FEM software and geometric modeler provides modeling function, the capability is quite limited for complicated structure. In order to perform FEM modeling quickly, it is necessary to extract, rearrange, and formalize data from ship design database for partially automatic mesh generation. In this paper, the process of designing relational data tables from design data is shown as a part of analysis automation with the application of engineering database concept.

• Journal of Convergence for Information Technology
• /
• v.11 no.10
• /
• pp.302-313
• /
• 2021

As the domestic consulting industry matured, consultants were required to have insight into customer's business and consulting business. Gaining these insights requires deep understanding of the business domains and high degree of competencies. This study empirically analyzed the data collected through the survey in order to apply the ICMCI competence model to domestic consultants. As a result of the study, it was found that business competency and technical competency had a positive effect on project performance, but values & behavior competency were not statistically significant. On the other hand, it was found that only technical competency, values & behavior competency had a positive effect on social-relational competency. Through this study, it was confirmed that a deep understanding and perception of the consulting business is necessary to grow into a professional consultant, but there is a limit to generalizing the research results because the characteristics of the population cannot be sufficiently reflected with a small sample.

• The Journal of Asian Finance, Economics and Business
• /
• v.7 no.12
• /
• pp.1005-1015
• /
• 2020

This paper aims to propose a Comprehensive Decision Support Model to evaluate retail companies' financial performance traded on the Vietnam Stock Exchange Market. The financial performance has been examined in terms of the valuations ratios, profitability ratios, growth rates, liquidity ratios, efficiency ratios, and leverage ratios. The data of twelve companies from the first quarter to the fourth quarter of 2019 and the first quarter of 2020 were employed. The weights of 18 chosen financial ratios are calculated by using the Standard Deviation method (SD). Grey Relational Analysis technique was applied to obtain the final ranking of each company in each quarter. The results showed that leverage ratios have the most significant impact on the retail companies' financial performance and gives some long-term investment recommendations for stakeholders and indicated that the Taseco Air Services Joint Stock Company (AST), Mobile World Investment Corporation (MWG), and Cam Ranh International Airport Services Joint Stock Company (CIA) are three of the top efficient companies. The three of the worst companies are Viglacera Corporation (VGC), Saigon General Service Corporation (SVC), and HocMon Trade Joint Stock Company (HTC). Furthermore, this study suggests that the GRA model could be implemented effectively to ranking companies of other industries in the future research.

• The Journal of Information Technology and Database
• /
• v.6 no.1
• /
• pp.1-13
• /
• 1999

The modeling components in the object-oriented paradigm are based on the object, not the structured function or procedure. That is, in the past, when one wanted to solve problems, he would describe the solution procedure. However, the object-oriented paradigm includes the concepts that solve problems through interaction between objects. The object-oriented model is constructed by describing the relationship between object to represent the real world. As in object-oriented model the relationships between objects increase, the control of objects caused by their insertions, deletions, and modifications comes to be very complex and difficult. Because the loss of the referential integrity happens and the object reusability is reduced. For these reasons, the necessity of the control of objects and the visualization of the relationships between them is required. In order that we design a database necessary to implement Object Browser that has functionalities to visualize Java objects and to perform the query processing in Java object modeling, in this paper we show the processes for EER modeling on Java object and its transformation into relational database schema. In addition we implement Java Object Parser that parses Java object and inserts the parsed results into the implemented database.

• The Journal of Asian Finance, Economics and Business
• /
• v.8 no.11
• /
• pp.133-143
• /
• 2021

This study investigates the relationship between social capital and enterprise performance with knowledge sharing as the mediator. By employing the data of 677 respondents collected from delivering questionnaires to small and medium-size firms in Vietnam in 2020, this study suggests a two-step approach that combines exploration factor analysis (EFA), confirmatory factor analysis (CFA), and path analysis (SEM). The empirical findings significantly support our proposed model by demonstrating that knowledge sharing mediates the connection between all three elements of social capital and enterprise performance. At the same time, the results emphasize the importance of knowledge sharing as a major benefit of social capital and a substantial driving element of both operational and financial performance. The results show that all three social capital qualities (structural, relational, and cognitive) significantly impact both tacit and explicit knowledge sharing, while knowledge is one of the main routes connecting social capital to enterprise performance. Hence, our research model may be used in future studies to evaluate social capital, knowledge sharing, and firm performance as a new theoretical model. Our results offer a plausible explanation for how social capital improves knowledge sharing and enterprise performance.

• Journal of the Korean BIBLIA Society for library and Information Science
• /
• v.35 no.3
• /
• pp.187-207
• /
• 2024

This study addresses the limitations of the rigid and simplistic relational structure of the KDC 6th edition's relative index by systematically analyzing the relationships between index terms. Based on this analysis, a flexible and detailed model for structuring the relationships within the relative index is proposed. The study categorizes these relationships into hierarchical, associative, and equivalence relationships, further subdividing them to capture the complexity of the interactions. The proposed model is implemented using RDF syntax, suggesting the potential for extending the relative index into linked data. This model not only clarifies the complex relationships between KDC index terms but also contributes to the development of a dynamic and adaptable classification system capable of effectively incorporating new information.