• KSCI Review
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• v.15 no.2
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• pp.9-22
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• 2008

• International Journal of Advanced Culture Technology
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• v.6 no.4
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• pp.165-171
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• 2018

As the artificial intelligence (AI) plays a crucial role in machine translation (MT) which has loomed large as a new translation paradigm, concerns have also arisen if MT can produce a quality product as human translation (HT) can. In fact, several MT experimental studies report cases in which the MT product called post-editing (PE) as equally as HT or often superior ([1],[2],[6]). As motivated from those studies on translation quality between HT and PE, this study set up an experimental situation in which Korean literature was translated into English, comparatively, by 3 translators and 3 post-editors. Afterwards, a group of 3 other Koreans checked for accuracy of HT and PE; a group of 3 English native speakers scored for fluency of HT and PE. The findings are (1) HT took the translation time, at least, twice longer than PE. (2) Both HT and PE produced similar error types, and Mistranslation and Omission were the major errors for accuracy and Grammar for fluency. (3) HT turned to be inferior to PE for both accuracy and fluency.

• IEIE Transactions on Smart Processing and Computing
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• v.5 no.2
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• pp.94-99
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• 2016

Application layer attacks have for years posed an ever-serious threat to network security, since they always come after a technically legitimate connection has been established. In recent years, cyber criminals have turned to fully exploiting the web as a medium of communication to launch a variety of forbidden or illicit activities by spreading malicious automated software (auto-ware) such as adware, spyware, or bots. When this malicious auto-ware infects a network, it will act like a robot, mimic normal behavior of web access, and bypass the network firewall or intrusion detection system. Besides that, in a private and large network, with huge Hypertext Transfer Protocol (HTTP) traffic generated each day, communication behavior identification and classification of auto-ware is a challenge. In this paper, based on a previous study, analysis of auto-ware communication behavior, and with the addition of new features, a method for classification of HTTP auto-ware communication is proposed. For that, a Not Only Structured Query Language (NoSQL) database is applied to handle large volumes of unstructured HTTP requests captured every day. The method is tested with real HTTP traffic data collected through a proxy server of a private network, providing good results in the classification and detection of suspicious auto-ware web access.

• International Journal of Advanced Culture Technology
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• v.11 no.2
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• pp.221-228
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• 2023

The industrial revolution 4.0 in general and the trend of the digital economy in particular have affected all aspects of the economy. In the orther hand, Digital Technology has the power to impact the strategies and competitiveness of businesses in the market. It is ever evolving and creating a revolutionary stand for different professions as well. Accounting is considered to be one of the oldest and traditional professions. The rules and methodology of this profession has remained uniform for a long period of time. But due to the advent of the digital technology accounting industry is experiencing some great changes. Challenges for the accounting profession are reflected in the need for rapid adaptation and transformation of business practice and business processes. Gradually it was difficult to manage the accounting of large firms without having any machine help. This profession faced a lot of challenges and required the need to adapt technology. The requirements of finance and digital accounting, as well as the requirements of regional and international financial and accounting integration, require proactive preparation, taking full advantage of the advantages as well as limiting the impacts. disadvantage. The aim of this paper is to analyze and systematize the key challenges that digitalization brings for accounting industry and propose some solution for digital transformation of accounting industry for Small and Medium Enterprise in Vietnam