Korea is promoting a digital new deal policy for the digital transformation and innovation accelerating of the industry. However, because of the strict existing data-related laws, there are still restrictions on the industry's use of data for the digital new deal policy. In order to solve this issue, a revised bill of the Data 3 Act has been proposed, but there is still insufficient discussion on how it will actually affect the activation of data use in the industry. Therefore, this study aims to analyze the perception of public opinion on the Data 3 Act and the implications of the revision of the Data 3 Act. To this end, the revision of the Data 3 Act and related research trends were analyzed, and the perception of the Data 3 Act was analyzed using a big data analysis technique. According to the analysis results, while promoting the vitalization of the data industry in line with the purpose of the revision, the Data 3 Act has a concern that it focuses on specific industries. The results of this study are meaningful in providing implications for future improvement plans by analyzing online perceptions of the industrial impact of the Data 3 Act in the early stages of implementation through big data analysis.
The Virtual Reality (VR) is an appealing subject which can be applied to various areas because of its merit - removal of time limits and space. Recently, as the technology of xDSL spreads widely, a concern of VR is on the on-line service of 3D model data in real time. But, the immensity of 3D model is an obstacle to achieve these endeavors. To solve these problems, the image based VR technique is applied. The proposed method in this paper is one of solutions on the immensity problem of 3D model data in the on-line services. This paper exploits the mixed technique of image based VR and surface rendering based on volume rendering. By using the proposed method, we can solve the immensity problem. Consequently, tole service user can explore virtual 2D volume model with almost equal to reality of 3D volume model. Furthermore, this paper explains a method to implement this service on general web environments. Of course, to fulfill these procedures, additional skills which reduce consuming time in data mining are also mentioned. The contribution of this paper is to provide a practical method for handling of large volume data web service in real-time. illustrative examples are presented to show the effectiveness of the proposed method.
You Jin-Sang;Song Yoonho;Seo1 Soon-Jee;Song Young-Soo
Geophysics and Geophysical Exploration
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v.4
no.2
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pp.25-33
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2001
Loop-loop electromagnetic (EM) survey in frequency domain has been carried out in order to provide basic solution to geotechnical applications. Source and receiver configuration may be horizontal co-planar (HCP) and/or vertical co-planar (VCP). Three quadrature components of mutual impedance ratio for each configuration are used to construct the subsurface image. For the purpose of obtaining the model response and validating the reasonable performance of the inversion, we obtained each responses of two-layered and three-layered earth models and two-dimensional (2-D) isolated anomalous body. The response of 2-D isolated anomalous body has been calculated using extended Born approximation for the solution of 2.5-D integral equation describing EM scattering problem. As a result of the least-squares inversion with variable Lagrangian multiplier, we could construct more resolvable image from HCP data than VCP data. Furthermore, joint inversion of HCP and VCP data made better stability and resolution of the inversion. Resistivity values, however, did not exactly match the true ones. Loop-loop EM field data was obtained with EM34-3XL system manufactured by Geonics Ltd. (Canada). Electrical resistivity survey was conducted on the same line for the comparison in advance. Since the constructed image from loop-loop EM data by 2-D inversion algorithm showed almost similar resistivity distribution to that from electrical resistivity one, we expect the developed 2.5-D loop-loop EM inversion program can be applied for the reconnaissance site survey.
As companies introduced ERP (Enterprise Resource Planning) systems since the middle of 1990s, the databases of the companies has become centralized and gigantic. The companies are now developing data-mining based applications on those centralized and gigantic databases for knowledge management. Almost of them are using $Pro^*C$/C++, a embedded SQL programming language, and it's because the $Pro^*C$/C++ is independent of platforms and also fast. However, they suffer from difficulties in development and maintenance due to the characteristics of corporate databases which have intrinsically large number of tables and fields. The purpose of this research is to design and implement a methodology which makes it easier to develop and maintain embedded SQL applications based on relational databases. Firstly, this article analyzes the syntax of $Pro^*C$/C++ and addresses the concept of repetition and duplication which causes the difficulties in development and maintenance of corporate information systems. Then, this article suggests a management architecture of source codes and databases in which a preprocessor generates $Pro^*C$/C++ source codes by referring a DB table specification, which would solve the problem of repetition and duplication. Moreover, this article also suggests another architecture of DB administration in which the preprocessor generates DB administration commands by referring the same table specification, which would solve the problem of repetition and duplication again. The preprocessor, named $PrePro^*C$, has been developed under the UNIX command-line prompt environment to preprocess $Pro^*C$/C++ source codes and SQL administration commands, and is under update to be used in another DB interface environment like ODBC and JDBC, too.
KSII Transactions on Internet and Information Systems (TIIS)
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v.13
no.8
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pp.4191-4211
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2019
Software product lines (SPLs) are complex software systems by nature due to their common reference architecture and interdependencies. Therefore, any form of evolution can lead to a more complex situation than a single system. On the other hand, software product lines are developed keeping long-term perspectives in mind, which are expected to have a considerable lifespan and a long-term investment. SPL development organizations need to consider software evolution in a systematic way due to their complexity and size. Addressing new user requirements over time is one of the most crucial factors in the successful implementation SPL. Thus, the addition of new requirements or the rapid context change is common in SPL products. To cope with rapid change several researchers have discussed the evolution of software product lines. However, for the evolution of an SPL, the literature did not present a systematic process that would define activities in such a way that would lead to the rapid evolution of software. Our study aims to provide a requirements-driven process that speeds up the requirements engineering process using social network sites in order to achieve rapid software evolution. We used classification, topic modeling, and sentiment extraction to elicit user requirements. Lastly, we conducted a case study on the smartwatch domain to validate our proposed approach. Our results show that users' opinions can contain useful information which can be used by software SPL organizations to evolve their products. Furthermore, our investigation results demonstrate that machine learning algorithms have the capacity to identify relevant information automatically.
Bernal, Alejandro Enciso;Monterrubio, Sergio Mauricio Martinez;Fuente, Javier Parra;Crespo, Ruben Gonzalez;Verdu, Elena
KSII Transactions on Internet and Information Systems (TIIS)
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v.15
no.5
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pp.1909-1928
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2021
At present, the Colombian government shares information on threats or vulnerabilities in the area of cybersecurity and cyberdefense, from other government agencies or departments, on an ad-hoc basis but not in real time, with the surveillance entities of the Government of the Republic of Colombia such as the Joint Command of Cybernetic Operations (CCOCI) and the Cybernetic Emergencies Response Team of Colombia (ColCERT). This research presents the MS-CSIRT (Management System Computer Security Incident Response Teams) methodology, that is used to unify the guidelines of a CSIRT towards a joint communication command in cybersecurity for the surveillance of Information Technology (IT), Technological Operations (TO), Internet Connection Sharing (ICS) or Internet of Things (IoT) infrastructures. This methodology evaluates the level of maturity, by means of a roadmap, to establish a CSIRT as a reference framework for government entities and as a guide for the areas of information security, IT and TO to strengthen the growth of the industry 4.0. This allows the organizations to draw a line of cybersecurity policy with scope, objectives, controls, metrics, procedures and use cases for the correct coordination between ColCERT and CCOCI, as support entities in cybersecurity, and the different companies (ICS, IoT, gas and energy, mining, maritime, agro-industrial, among others) or government agencies that use this methodology.
Friar Tuck, an Abandoned Mine Lands (AML) site, is located on the Greene-Sullivan county line in southwest Indiana. Prior to the on-going reclamation, Friar Tuck was one of the Indiana's largest and most environmentally adverse abandoned mine lands. The direct vegetation method was used to reclaim tailing ponds. Grading, capping, and revegetalon using agricultural limestone, fertilizer, mulch and seed were applied to the gob piles to abate acid mine drainage (AMD) and off-side sedimentaion. Erosion control structures such as terrace, diversion ditch, and gabion structures were also constructed to minimize erosion at slopes. A new method for treatment of AMD using apatite was tested in the laboratory and field. Apatite effectively removed iron, aluminum and sulfate while maintaining an almost constant pH. Apparently, this method can be applied to control AMD from mining refuse materials, even those containing high concentrations of iron and aluminum ions.
These days information technology and internet have made startling progress. In these developing environments, the strategy or marketing based on existing off-line is getting more difficult to accomplish the role of the improvement of business competitive power, and they are bringing out a lot of changes in information management and marketing performance method about consumers due to digital networking between companies and consumers. These developments and changes make many varieties in the way of design studying methodology. Therefore, in this study, considering the aspects of design, society and environment, after I developed the consumer response framework about products design which is argued by Bloch(1995) ; distinct relationship model among preference degree- design image adjective - design factors, we established design information abstraction solution combined with the interaction based on IT as eCRM in real time. This suggested solutions will provide product designers with good information in finding the design factors which consumers prefer.
KTX rolling stocks are a system consisting of several machines, electrical devices, and components. The maintenance of the rolling stocks requires considerable expertise and experience of maintenance workers. In the event of a rolling stock failure, the knowledge and experience of the maintainer will result in a difference in the quality of the time and work to solve the problem. So, the resulting availability of the vehicle will vary. Although problem solving is generally based on fault manuals, experienced and skilled professionals can quickly diagnose and take actions by applying personal know-how. Since this knowledge exists in a tacit form, it is difficult to pass it on completely to a successor, and there have been studies that have developed a case-based rolling stock expert system to turn it into a data-driven one. Nonetheless, research on the most commonly used KTX rolling stock on the main-line or the development of a system that extracts text meanings and searches for similar cases is still lacking. Therefore, this study proposes an intelligence supporting system that provides an action guide for emerging failures by using the know-how of these rolling stocks maintenance experts as an example of problem solving. For this purpose, the case base was constructed by collecting the rolling stocks failure data generated from 2015 to 2017, and the integrated dictionary was constructed separately through the case base to include the essential terminology and failure codes in consideration of the specialty of the railway rolling stock sector. Based on a deployed case base, a new failure was retrieved from past cases and the top three most similar failure cases were extracted to propose the actual actions of these cases as a diagnostic guide. In this study, various dimensionality reduction measures were applied to calculate similarity by taking into account the meaningful relationship of failure details in order to compensate for the limitations of the method of searching cases by keyword matching in rolling stock failure expert system studies using case-based reasoning in the precedent case-based expert system studies, and their usefulness was verified through experiments. Among the various dimensionality reduction techniques, similar cases were retrieved by applying three algorithms: Non-negative Matrix Factorization(NMF), Latent Semantic Analysis(LSA), and Doc2Vec to extract the characteristics of the failure and measure the cosine distance between the vectors. The precision, recall, and F-measure methods were used to assess the performance of the proposed actions. To compare the performance of dimensionality reduction techniques, the analysis of variance confirmed that the performance differences of the five algorithms were statistically significant, with a comparison between the algorithm that randomly extracts failure cases with identical failure codes and the algorithm that applies cosine similarity directly based on words. In addition, optimal techniques were derived for practical application by verifying differences in performance depending on the number of dimensions for dimensionality reduction. The analysis showed that the performance of the cosine similarity was higher than that of the dimension using Non-negative Matrix Factorization(NMF) and Latent Semantic Analysis(LSA) and the performance of algorithm using Doc2Vec was the highest. Furthermore, in terms of dimensionality reduction techniques, the larger the number of dimensions at the appropriate level, the better the performance was found. Through this study, we confirmed the usefulness of effective methods of extracting characteristics of data and converting unstructured data when applying case-based reasoning based on which most of the attributes are texted in the special field of KTX rolling stock. Text mining is a trend where studies are being conducted for use in many areas, but studies using such text data are still lacking in an environment where there are a number of specialized terms and limited access to data, such as the one we want to use in this study. In this regard, it is significant that the study first presented an intelligent diagnostic system that suggested action by searching for a case by applying text mining techniques to extract the characteristics of the failure to complement keyword-based case searches. It is expected that this will provide implications as basic study for developing diagnostic systems that can be used immediately on the site.
So, Kwang-Suk;Ryang, Woo-Hun;Kang, Sol-Ip;Kwon, Yi-Kyun
Journal of the Korean earth science society
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v.31
no.7
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pp.708-719
/
2010
The Gochang-gun Dongho macro-tide pocket-type beach, located on the southwestern coast of Korea, is investigated in terms of the seasonal variations of surface sediment and sedimentary environment. Surface sediments of 45 sites in four seasons (May 2006-February 2007) are sampled across three survey lines (15 sites in each survey line). The surface sediments of the Dongho Beach are mainly composed of fine to coarse sands, and the ratio of fine sand is the largest. The average of grain size is the coarsest in the summer. The spatial distribution of surface sediments shows a coast-parallel band of fine and medium sands during three seasons of spring, fall, and winter, whereas medium sands dominated in the northern part of the study area during the summer. These results suggest that a tide is more effective than a wave in the surface sediments of the Dongho Beach during the summer.
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