• Journal of the Korea Institute of Information Security & Cryptology
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• v.9 no.1
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• pp.57-70
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• 1999

Since a hybrid firewall filters packets at a network layer along with providing gateway functionalities at an application layer, it has a better performance than an If filtering firewall. In addition, it provides both the various kinds of access control mechanisms and transparent services to users. However, the security policies of a network layer are different from those of an application layer. Thus, the user interfaces for managing a hybrid firewalls in a consistent manner are needed. In this paper, we implement a graphical user interface to provide access control mechanisms and management facilities for a hybrid firewall such as log analysis, a real-time monitor for network traffics, and the statisics on traffics. And we also propose a new rule script language for specifying access control rules. By using the script language, users can generate the various forma of access control rules which are adapted by the existing firewalls.

• International Journal of Computer Science & Network Security
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• v.22 no.4
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• pp.245-253
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• 2022

Commenced in 1954 by IBM, machine translation has expanded immensely, particularly in this period. Machine translation can be broken into seven main steps namely- token generation, analyzing morphology, lexeme, tagging Part of Speech, chunking, parsing, and disambiguation in words. Morphological analysis plays a major role when translating Indian languages to develop accurate parts of speech taggers and word sense. The paper presents various machine translation methods used by different researchers for Indian languages along with their performance and drawbacks. Further, the paper concentrates on parts of speech (POS) tagging in Marathi dialect using various methods such as rule-based tagging, unigram, bigram, and more. After careful study, it is concluded that for machine translation, parts of speech tagging is a major step. Also, for the Marathi language, the Hidden Markov Model gives the best results for parts of speech tagging with an accuracy of 93% which can be further improved according to the dataset.

• The Journal of the Korea institute of electronic communication sciences
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• v.10 no.3
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• pp.375-380
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• 2015

This paper is studied the Korean language to optimize the Hangul character coding for information processing in information terminal device and transmission in network. The paper analyzed Hangul character in Korean language and use frequency of each character. The paper also compared the analysis result to Hangul characters which are coded in standard in Korean character and Unicode. This study referred "Modern Korean Use Frequency Rate Survey Result" issued by The National Institute of the Korean Language. There are total 58,437 Korean words in the report. As a result of this paper, the Korean word 58,437ea are consisted of Hangul character total 1,540ea. The highest use frequency character is "다" and its use frequency to total use frequency rate is 15%. The lowest use character is "휫"and its use frequency to total use frequency rate is 0.00003%. The number of analyzed Hangul character 1,540 is less 7.2 times and 1.5 times than Korean and Unicode standard respectively.

• International Journal of Computer Science & Network Security
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• v.22 no.4
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• pp.183-192
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• 2022

The role that English currently plays is undeniable. It has become the most common means of communication among native speakers of several languages around the world. English penetrates into all areas of people's daily lives. In the field of Information Technology (IT), English has taken a dominant position, as many of the terms used on a daily basis are written in English. The purpose of the article is to analyze the linguistic features of anglicisms in the field of Information Technology. Methods. The research is based on systematic and comparative analysis, dialectical method, as well as methods of classification and generalization. Results. This study presents the results of compiling a multilingual glossary with anglicisms used in the GitHub and 3D Slicer fields. Despite the limited number of terms included in the glossary, the article provides a lot of evidence for the influence of the English language in the areas of Information Technology, GitHub and 3D Slicer under consideration. The types of anglicisms used in the 3D Slicer area seem to be more diverse than in the GitHub area. This study found that five European languages use language strategies to solve any communication problem. The multilingual glossary showed that in some cases there is a coexistence between Anglicism and the native term. In other cases, the English term is the only one used in different languages. There are cases when only the native language is used. Conclusions. This study is a useful tool that helps to improve the efficiency of communication between engineers and technicians who speak different native languages. The ultimate goal of this research will be to create a multilingual glossary that is still under development and is likely to cover other IT areas such as Python and VTK.

• The Journal of Fisheries Business Administration
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• v.50 no.3
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• pp.59-71
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• 2019

In terms of coastal and marine tourism, Busan's Haeundae had the nation's representativeness, and is pushing for many kinds of related policies to revitalize the special tourism zone. Due to a drop in the number of beach users, it is inevitable for the Haeundae Special Tourist Zone to face active responses to new trends emerging in the global tourism market. Therefore, the purpose of this study is to present a tourism strategy for making the Suyeong River as a more competitive ourist resource along the zone. First, a language network analysis is conducted through interviews to understand the ideas of interest groups for the river cruise activation project. Second, the frame structure of stakeholders is used to analyze solutions by comparing the similarities and differences in recognition frames of interest groups. Third, we intend to analyze the detailed frame types of stakeholders and present new alternatives based on the structure of relationships between types.

• International Journal of Contents
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• v.17 no.1
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• pp.1-10
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• 2021

Visual analytics is an emerging research field that combines the strength of electronic data processing and human intuition-based social background knowledge. This study demonstrates useful visual analytics with Tableau in conjunction with semantic network analysis using examples of sentiment flow and strategic communication strategies via Twitter in a blockchain domain. We comparatively investigated the sentiment flow over time and language usage patterns between companies with a good reputation and firms with a poor reputation. In addition, this study explored the relations between reputation and marketing communication strategies. We found that cryptocurrency firms more actively produced information when there was an increased public demand and increased transactions and when the coins' prices were high. Emotional language strategies on social media did not affect cryptocurrencies' reputations. The pattern in semantic representations of keywords was similar between companies with a good reputation and firms with a poor reputation. However, the reputable firms communicated on a wide range of topics and used more culturally focused strategies, and took more advantages of social media marketing by expanding their outreach to other social media networks. The visual big data analytics provides insights into business intelligence that helps informed policies.

• IEMEK Journal of Embedded Systems and Applications
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• v.9 no.2
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• pp.117-125
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• 2014

The EtherCAT protocol has become a very promising alternative for real-time industrial application due to its ability to eliminate uncertainties in the Ethernet. However, the extended markup language (XML) for the EtherCAT network system, which is required in the design, lacks systematic development to take advantage of model transformation techniques. This paper focuses on the system development procedure of the EtherCAT-based encoder system using the CANopen over EtherCAT (CoE) protocol. UML modeling is being adapted to design for XML of EtherCAT-based encoder system. To this purpose, this paper analyzes the object dictionary (OD) of a commercial encoder and CANopen over EtherCAT. A UML diagram is then designed based on the analysis, and XML is generated through the designed UML diagram. Finally, an experimental test_bed for the EtherCAT-based encoder system is implemented and its performance is compared with a commercial encoder.

• The Journal of Information Systems
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• v.15 no.4
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• pp.247-268
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• 2006

We introduce about XBRL, eXtensible Business Reporting Language, which is widely accepted as the international standard language for business financial reporting. XBRL is a language for the electronic communication of business and financial data which is revolutionizing business reporting around the world. It provides major benefits in the preparation, analysis and communication of business information. It offers cost savings, greater efficiency and improved accuracy and reliability to all those involved in supplying or using financial data. XBRL is a kind of XML application based on the open Internet technologies. We propose a framework for enterprise information supply chain using XBRL Web services. A Web service is defined as a software system based on XML and designed to support interoperable machine-to-machine interaction over a network by the W3C. Web services are frequently just application programming interfaces (API) that can be accessed over a network, such as the internet and executed on a remote system hosting the requested services. An XBRL Web service-based enterprise information supply chain enables for companies to implement seamless information supply chains from businesses to financial institutions, to supervisory authorities, and to other stake holders for real time information access. And thereby it is expected to contribute to the increase in the value of companies due to the enhanced visibility and transparency of accounting and management.

• International Journal of Computer Science & Network Security
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• v.23 no.6
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• pp.162-168
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• 2023

This article presents an examination of the major cognitive-semantic theories in linguistics (Langacker, Lakoff, Fillmore, Croft). The CST's foundations are discussed concerning the educational policy changes, which are necessary to improve the linguistic disciplines in the changing context of higher education, as well as the empowerment and development of the industry. It is relevant in the light of the linguistic specialists' quality training and the development of effective methods of language learning. Consideration of the theories content, tools, and methods of language teaching, which are an important component of quality teaching and the formation of a set of knowledge and skills of students of linguistic specialties, remains crucial. This study aims to establish the main theoretical positions and directions of cognitive-semantic theory in linguistics, determine the usefulness of teaching the basics of cognitive linguistics, the feasibility of using methods of cognitive-semantic nature in the learning process. During the research, the methods of linguistic description and observation, analysis, and synthesis were applied. The result of the study is to establish the need to study basic linguistic theories, as well as general theoretical precepts of cognitive linguistics, which remains one of the effective directions in the postmodern mainstream. It also clarifies the place of the main cognitive-semantic theories in the teaching linguistics' practice of the XXI century.

• Journal of information and communication convergence engineering
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• v.17 no.4
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• pp.239-245
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• 2019

Recently, effort to obtain various information from the vast amount of social network services (SNS) big data generated in daily life has expanded. SNS big data comprise sentences classified as unstructured data, which complicates data processing. As the amount of processing increases, a rapid processing technique is required to extract valuable information from SNS big data. We herein propose a system that can extract human sentiment information from vast amounts of SNS unstructured big data using the naïve Bayes algorithm and natural language processing (NLP). Furthermore, we analyze the effectiveness of the proposed method through various experiments. Based on sentiment accuracy analysis, experimental results showed that the machine learning method using the naïve Bayes algorithm afforded a 63.5% accuracy, which was lower than that yielded by the NLP method. However, based on data processing speed analysis, the machine learning method by the naïve Bayes algorithm demonstrated a processing performance that was approximately 5.4 times higher than that by the NLP method.