• The Journal of the Korea Contents Association
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• v.7 no.10
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• pp.146-156
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• 2007

This study is possible because, first, "rammatology" and typography are connected by language. Second, I believe that language in typography should be comprehended in a relationship between peripheral studies such as history, philosophy, literature, and linguistics. Finally, "grammatology" is an excellent subject for experiments which attempt to rehabilitate the right of language, which is dependent on sound within the metaphysical boundary. This study is formed on the idea that the study of typography should be based on language, which is the basic foundation, and that this is possible in investigations related to peripheral studies. The main purpose of typography is an accurate delivery of meaning. However, the dynamics of creative thoughts towards advancement mainly depends on experiment, thus we cannot limit the purpose of typography as a means of communication to exchange meanings. For these reasons, I admit that interest in peripheral studies -which are not yet approached in the study on typography -take precedence.

• Smart Media Journal
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• v.7 no.1
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• pp.37-44
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• 2018

Utilizing sequence control and numerical computing, embedded devices are used in a variety of automated systems, including those at industrial sites, in accordance with their control program. Since embedded devices are used as a control system in corporate industrial complexes, nuclear power plants and public transport infrastructure nowadays, deliberate attacks on them can cause significant economic and social damages. Most attacks aimed at embedded devices are data-coded, code-modulated, and control-programmed. The control programs for industry-automated embedded devices are designed to represent circuit structures, unlike common programming languages, and most industrial automation control programs are designed with a graphical language, LAD, which is difficult to process static analysis. Because of these characteristics, the vulnerability analysis and security related studies for industry automation control programs have only progressed up to the formal verification, real-time monitoring levels. Furthermore, the static analysis of industrial automation control programs, which can detect vulnerabilities in advance and prepare for attacks, stays poorly researched. Therefore, this study suggests a method to present a discussion on an industry automation control program designed to represent the circuit structure to increase the efficiency of static analysis of embedded industrial automation programs. It also proposes a medium term translation technology exploiting LLVM IR to comprehensively analyze the industrial automation control programs of various manufacturers. By using LLVM IR, it is possible to perform integrated analysis on dynamic analysis. In this study, a prototype program that converts to a logical expression type of medium language was developed with regards to the S company's control program in order to verify our method.

• KIPS Transactions on Computer and Communication Systems
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• v.12 no.3
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• pp.103-110
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• 2023

With the spread of the Internet, anonymous communities emerged along with the activation of communities for communication between people, and many users are doing harm to others, such as posting aggressive posts and leaving comments using anonymity. In the past, administrators directly checked posts and comments, then deleted and blocked them, but as the number of community users increased, they reached a level that managers could not continue to monitor. Initially, word filtering techniques were used to prevent malicious writing from being posted in a form that could not post or comment if a specific word was included, but they avoided filtering in a bypassed form, such as using similar words. As a way to solve this problem, deep learning was used to monitor posts posted by users in real-time, but recently, the community uses words that can only be understood by the community or from a human perspective, not from a general Korean word. There are various types and forms of characters, making it difficult to learn everything in the artificial intelligence model. Therefore, in this paper, we proposes a preprocessing technique in which each character of a sentence is imaged using a CNN model that learns the consonants, vowel and spacing images of Korean word and converts characters that can only be understood from a human perspective into characters predicted by the CNN model. As a result of the experiment, it was confirmed that the performance of the LSTM, BiLSTM and CNN-BiLSTM models increased by 3.2%, 3.3%, and 4.88%, respectively, through the proposed preprocessing technique.