• Nuclear Engineering and Technology
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• v.49 no.7
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• pp.1423-1430
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• 2017

Detonation cell width is an important parameter in hydrogen explosion assessments. The experimental data on gas detonation are statistically analyzed to establish a universal method to numerically predict detonation cell widths. It is commonly understood that detonation cell width, ${\lambda}$, is highly correlated with the characteristic reaction zone width, ${\delta}$. Classical parametric regression methods were widely applied in earlier research to build an explicit semiempirical correlation for the ratio of ${\lambda}/{\delta}$. The obtained correlations formulate the dependency of the ratio ${\lambda}/{\delta}$ on a dimensionless effective chemical activation energy and a dimensionless temperature of the gas mixture. In this paper, support vector regression (SVR), which is based on nonparametric machine learning, is applied to achieve functions with better fitness to experimental data and more accurate predictions. Furthermore, a third parameter, dimensionless pressure, is considered as an additional independent variable. It is found that three-parameter SVR can significantly improve the performance of the fitting function. Meanwhile, SVR also provides better adaptability and the model functions can be easily renewed when experimental database is updated or new regression parameters are considered.

• Transactions of Materials Processing
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• v.14 no.6 s.78
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• pp.514-519
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• 2005

A tube hydroformability testing system was designed and fabricated enabling to apply the forming condition along arbitrarily pre-programmed internal pressure-axial feed path. The free-bulging and T-forming tests were carried out on the extruded aluminum (A6063) tube specimens with 40.6 mm outer diameter and 2.25 mm thickness. Nine different combinations of internal pressure and axial feed, yielding different strain paths from one another, were taken into consideration in order to induce bursting at various deformation modes. Major and minor strains were automatically measured from deformed grids around the fracture using a stereo-vision-based surface strain measurement system, named ASIAS. The forming limit diagram of the A6063 tube material was successfully obtained. Most of the data points acquired from free bulging and T-forming tests appeared in the range of negative minor strain on the FLD and are mostly located near the strain paths calculated from explicit finite element simulations. The forming limit obtained from tests after pre-tension was considerably lower than that from tests without pre-tension, which showed the strain path-dependency of the forming limit as well known in the sheet forming fold.

• Journal of Korean Society of Industrial and Systems Engineering
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• v.46 no.4
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• pp.142-151
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• 2023

Sentiment analysis is a method used to comprehend feelings, opinions, and attitudes in text, and it is essential for evaluating consumer feedback and social media posts. However, creating sentiment dictionaries, which are necessary for this analysis, is complex and time-consuming because people express their emotions differently depending on the context and domain. In this study, we propose a new method for simplifying this procedure. We utilize syntax analysis of the Korean language to identify and extract sentiment words based on the Reason-Sentiment Pattern, which distinguishes between words expressing feelings and words explaining why those feelings are expressed, making it applicable in various contexts and domains. We also define sentiment words as those with clear polarity, even when used independently and exclude words whose polarity varies with context and domain. This approach enables the extraction of explicit sentiment expressions, enhancing the accuracy of sentiment analysis at the attribute level. Our methodology, validated using Korean cosmetics review datasets from Korean online shopping malls, demonstrates how a sentiment dictionary focused solely on clear polarity words can provide valuable insights for product planners. Understanding the polarity and reasons behind specific attributes enables improvement of product weaknesses and emphasis on strengths. This approach not only reduces dependency on extensive sentiment dictionaries but also offers high accuracy and applicability across various domains.

• KIPS Transactions on Software and Data Engineering
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• v.2 no.10
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• pp.651-660
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• 2013

Object oriented design brought up improvement of productivity and software quality by adopting some concepts such as inheritance and encapsulation. However, both the number of software's classes and object couplings are increasing as the software volume is becoming larger. The object coupling between classes is closely related with software complexity, and high complexity causes decreasing software quality. In order to solve the object coupling issue, IT-field researchers adopt a component based development and software quality metrics. The component based development requires explicit representation of dependencies between classes and the software quality metrics evaluates quality of software. As part of the research, we intend to gain a basic data that will be used on decomposing software. We focused on properties of the linkage between classes rather than previous studies evaluated and accumulated the qualities of individual classes. Our method exploits machine learning technique to analyze the properties of linkage and predict the strength of dependency between classes, as a new perspective on analyzing software property.

• Journal of KIISE:Computing Practices and Letters
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• v.13 no.7
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• pp.462-475
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• 2007

The Embedded system provides human-centric services in many fields of education, information, industry and service, and monitoring programs have been variously developed for managing, controlling and testing for these embedded systems. Currently, many kernel trace toolkits are being used for monitoring. These trace toolkits are so complicate that we present $ETT^{plus}$, our simple and explicit embedded kernel trace toolkit, for embedded systems and describe the transmission method for trace data between the embedded target system and the host system. $ETT^{plus}$ provides the solution to solve the problems such as the difficult kernel patch and file system dependency in existing kernel trace toolkits like LTT. Furthermore, we present the experimental results about embedded system performance evaluations such as system call execute time or network data transmission time by using $ETT^{plus}$.

• Journal of Computing Science and Engineering
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• v.9 no.4
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• pp.204-213
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• 2015

Under the conditional independence assumption among local features, the Naive Bayes Nearest Neighbor (NBNN) classifier has been recently proposed and performs classification without any training or quantization phases. While the original NBNN shows high classification accuracy without adopting an explicit training phase, the conditional independence among local features is against the compositionality of objects indicating that different, but related parts of an object appear together. As a result, the assumption of the conditional independence weakens the accuracy of classification techniques based on NBNN. In this work, we look into this issue, and propose a novel Bayesian network for an NBNN based classification to consider the conditional dependence among features. To achieve our goal, we extract a high-level feature and its corresponding, multiple low-level features for each image patch. We then represent them based on a simple, two-level layered Bayesian network, and design its classification function considering our Bayesian network. To achieve low memory requirement and fast query-time performance, we further optimize our representation and classification function, named relation-based Bayesian network, by considering and representing the relationship between a high-level feature and its low-level features into a compact relation vector, whose dimensionality is the same as the number of low-level features, e.g., four elements in our tests. We have demonstrated the benefits of our method over the original NBNN and its recent improvement, and local NBNN in two different benchmarks. Our method shows improved accuracy, up to 27% against the tested methods. This high accuracy is mainly due to consideration of the conditional dependences between high-level and its corresponding low-level features.

• Structural Engineering and Mechanics
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• v.32 no.2
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• pp.193-212
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• 2009

The resilience of a city confronted with a terrorist bomb attack is the background of the paper. The resilience strongly depends on vital infrastructure and the physical protection of people. The protection buildings provide in case of an external explosion is one of the important elements in safety assessment. Besides the aspect of protection, buildings facilitate and enable many functions, e.g., offices, data storage, -handling and -transfer, energy supply, banks, shopping malls etc. When a building is damaged, the loss of functions is directly related to the location, amount of damage and the damage level. At TNO Defence, Security and Safety methods are developed to quantify the resilience of city infrastructure systems (Weerheijm et al. 2007b). In this framework, the dynamic response, damage levels and residual bearing capacity of multi-storey RC buildings is studied. The current paper addresses the aspects of dynamic response and progressive collapse, as well as the proposed method to relate the structural damage to a volume-damage parameter, which can be linked to the loss of functionality. After a general introduction to the research programme and progressive collapse, the study of the dynamic response and damage due to blast loading for a single RC element is described. Shock tube experiments on plates are used as a reference to study the possibilities of engineering methods and an explicit finite element code to quantify the response and residual bearing capacity. Next the dynamic response and progressive collapse of a multi storey RC building is studied numerically, using a number of models. Conclusions are drawn on the ability to predict initial blast damage and progressive collapse. Finally the link between the structural damage of a building and its loss of functionality is described, which is essential input for the envisaged method to quantify the resilience of city infrastructure.

• Journal of the Korean Society for Library and Information Science
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• v.15
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• pp.225-266
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• 1988

Various theories and techniques for the subject catalog have been developed since Charles Ammi Cutter first tried to formulate rules for the construction of subject headings in 1876. However, they do not seem to be appropriate to Korean language because the syntax and semantics of Korean language are different from those of English and other European languages. This study therefore attempts to develop a new Korean subject indexing system, namely Korean String Indexing System(KOSIS), in order to increase the use of subject catalogs. For this purpose, advantages and disadvantages between the classed subject catalog nd the alphabetical subject catalog, which are typical subject ca-alogs in libraries, are investigated, and most of remarkable subject indexing systems, in particular the PRECIS developed by the British National Bibliography, are reviewed and analysed. KOSIS is a string indexing based on purely the syntax and semantics of Korean language, even though considerable principles of PRECIS are applied to it. The outlines of KOSIS are as follows: 1) KOSIS is based on the fundamentals of natural language and an ingenious conjunction of human indexing skills and computer capabilities. 2) KOSIS is. 3 string indexing based on the 'principle of context-dependency.' A string of terms organized accoding to his principle shows remarkable affinity with certain patterns of words in ordinary discourse. From that point onward, natural language rather than classificatory terms become the basic model for indexing schemes. 3) KOSIS uses 24 role operators. One or more operators should be allocated to the index string, which is organized manually by the indexer's intellectual work, in order to establish the most explicit syntactic relationship of index terms. 4) Traditionally, a single -line entry format is used in which a subject heading or index entry is presented as a single sequence of words, consisting of the entry terms, plus, in some cases, an extra qualifying term or phrase. But KOSIS employs a two-line entry format which contains three basic positions for the production of index entries. The 'lead' serves as the user's access point, the 'display' contains those terms which are themselves context dependent on the lead, 'qualifier' sets the lead term into its wider context. 5) Each of the KOSIS entries is co-extensive with the initial subject statement prepared by the indexer, since it displays all the subject specificities. Compound terms are always presented in their natural language order. Inverted headings are not produced in KOSIS. Consequently, the precision ratio of information retrieval can be increased. 6) KOSIS uses 5 relational codes for the system of references among semantically related terms. Semantically related terms are handled by a different set of routines, leading to the production of 'See' and 'See also' references. 7) KOSIS was riginally developed for a classified catalog system which requires a subject index, that is an index -which 'trans-lates' subject index, that is, an index which 'translates' subjects expressed in natural language into the appropriate classification numbers. However, KOSIS can also be us d for a dictionary catalog system. Accordingly, KOSIS strings can be manipulated to produce either appropriate subject indexes for a classified catalog system, or acceptable subject headings for a dictionary catalog system. 8) KOSIS is able to maintain a constistency of index entries and cross references by means of a routine identification of the established index strings and reference system. For this purpose, an individual Subject Indicator Number and Reference Indicator Number is allocated to each new index strings and new index terms, respectively. can produce all the index entries, cross references, and authority cards by means of either manual or mechanical methods. Thus, detailed algorithms for the machine-production of various outputs are provided for the institutions which can use computer facilities.