• The Journal of Korean Institute of Communications and Information Sciences
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• v.34 no.9B
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• pp.939-946
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• 2009

In this paper, we propose a new network ASIP(Application Specific Instruction-set Processor) which was designed for simulation models by a machine descriptions language LISA(Language for Instruction Set Architecture). This network ASIP is aimed for an exclusive engine undertaking packet processing in a router. To achieve the purpose, we added a new necessary instruction set for processing a general ASIP based on MIPS(Microprocessor without Interlock Pipeline Stages) architecture in high speed. The new instructions can be divided into two groups: a classification instruction group and a modification instruction group, and each group is to be processed by its own functional unit in an execution stage. The functional unit was optimized for area and speed through Verilog HDL, and the result after synthesis was compared with the area and operation delay time. Moreownr, it was allocated to the Macro function ana low-level standardized programming language C using CKF(Compiler Known Function). Consequently, we verified performance improvement achieved by analysis and comparison of execution cycles of application programs.

• International Journal of Computer Science & Network Security
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• v.21 no.8
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• pp.369-376
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• 2021

One of the most active areas of research in the field of affective computing and signal processing is emotion recognition. This paper proposes emotion recognition of low-resource (Sindhi) language. This work's uniqueness is that it examines the emotions of languages for which there is currently no publicly accessible dataset. The proposed effort has provided a dataset named MAVDESS (Mehran Audio-Visual Dataset Mehran Audio-Visual Database of Emotional Speech in Sindhi) for the academic community of a significant Sindhi language that is mainly spoken in Pakistan; however, no generic data for such languages is accessible in machine learning except few. Furthermore, the analysis of various emotions of Sindhi language in MAVDESS has been carried out to annotate the emotions using line features such as pitch, volume, and base, as well as toolkits such as OpenSmile, Scikit-Learn, and some important classification schemes such as LR, SVC, DT, and KNN, which will be further classified and computed to the machine via Python language for training a machine. Meanwhile, the dataset can be accessed in future via https://doi.org/10.5281/zenodo.5213073.

• Ocean policy research
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• v.33 no.2
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• pp.123-145
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• 2018

Maritime tourism destinations need to improve image as well as enhance competitiveness through development of new marine tourism attraction due to the decrease of the number of passengers. The maritime city is trying to combine dynamic marine leisure activities as an alternative. For this purpose, it is possible to realize clear marine tourism activation policy and improve the identity of local community through the accurate analysis of the interest of the stakeholder groups of local residents in Songjeong beach in Busan. In this study, we first analyzed the language network based on the expression language related to the conflict between the stakeholders of Songjeong beach. Second, we analyzed the individual characteristics of the structure of conflict frames of stakeholders and suggested solutions by comparing the differences and similarities between perception frames of conflict parties. Third, we distinguish and compare differences of perception among the conflict parties through the detailed frame type. Based on the relationship structure between the detailed frame types of the conflict parties, we suggested an alternative for conflict resolution by restructuring the conflicts and negative perceptions among the stakeholders.

• International Journal of Computer Science & Network Security
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• v.21 no.3
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• pp.206-211
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• 2021

Internet users are increasingly invited to express their opinions on various subjects in social networks, e-commerce sites, news sites, forums, etc. Much of this information, which describes feelings, becomes the subject of study in several areas of research such as: "Sensing opinions and analyzing feelings". It is the process of identifying the polarity of the feelings held in the opinions found in the interactions of Internet users on the web and classifying them as positive, negative, or neutral. In this article, we suggest the implementation of a sentiment analysis tool that has the role of detecting the polarity of opinions from people about COVID-19 extracted from social media (tweeter) in the Arabic language and to know the impact of the pre-processing phase on the opinions classification. The results show gaps in this area of research, first of all, the lack of resources when collecting data. Second, Arabic language is more complexes in pre-processing step, especially the dialects in the pre-treatment phase. But ultimately the results obtained are promising.

• International Journal of Computer Science & Network Security
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• v.23 no.9
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• pp.91-94
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• 2023

This study aims to evaluate the Higher Diploma in English for the Primary Stage from the diploma students' perspectives. A questionnaire was designed consisting of 25 items distributed in two areas: cognitive/academic preparation and professional/skill preparation. The following statistical analyses were used: means, standard deviations, t-test, and one-way analysis of variance (ANOVA). The study results showed that the level of evaluation of the two domains in the program was low. The study also showed no statistically significant differences between the means of educational diploma students when evaluating the Higher Diploma in English for the Primary Stage due to their academic specialization (Arabic language, social sciences, and Islamic studies). In conclusion, the researcher suggested a developmental mechanism derived from the study results to improve the higher Diploma in English for the Primary Stage.

• ETRI Journal
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• v.45 no.1
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• pp.93-104
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• 2023

Coreference resolution is a task in discourse analysis that links several headwords used in any document object. We suggest pointer networks-based coreference resolution for Korean using multi-task learning (MTL) with an attention mechanism for a hierarchical structure. As Korean is a head-final language, the head can easily be found. Our model learns the distribution by referring to the same entity position and utilizes a pointer network to conduct coreference resolution depending on the input headword. As the input is a document, the input sequence is very long. Thus, the core idea is to learn the word- and sentence-level distributions in parallel with MTL, while using a shared representation to address the long sequence problem. The suggested technique is used to generate word representations for Korean based on contextual information using pre-trained language models for Korean. In the same experimental conditions, our model performed roughly 1.8% better on CoNLL F1 than previous research without hierarchical structure.

• International Journal of Computer Science & Network Security
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• v.24 no.3
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• pp.160-172
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• 2024

The characteristic aspects of learning a foreign language require special resources and tools for online learning. Criteria for choosing educational platforms depend on key elements of an academic subject area. Microsoft Teams (hereafter, MT) educational platform is competitive one because it meets most of the needs that arise during the formation of a secondary linguistic persona. Due to the large number of corporate programs, there are a successful acquisition of language skills and the implementation of all types of oral activities of students. A significant MT advantage is the constant analysis and monitoring of the platform of participants' needs in the educational process by developers. The article highlights MT advantages and disadvantages. The attention is drawn to individual programs, which, in the authors' opinion, are the most successful to learn writing, reading, speaking, listening, as well as organize classes that meet needs of modern foreign students.

• Journal of Korea Society of Digital Industry and Information Management
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• v.19 no.4
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• pp.87-96
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• 2023

ChatGPT, a leader in generative AI, can use natural expressions like humans based on large-scale language models (LLM). The ability to grasp the context of the language and provide more specific answers by algorithms is excellent. It also has high-quality conversation capabilities that have significantly developed from past Chatbot services to the level of human conversation. In addition, it is expected to change the operation method of the tourism industry and improve the service by utilizing ChatGPT, a generative AI in the tourism sector. This study was conducted to explore ChatGPT trends and paradigms in tourism. The results of the study are as follows. First, keywords such as tourism, utilization, creation, technology, service, travel, holding, education, development, news, digital, future, and chatbot were widespread. Second, unlike other keywords, service, education, and Mokpo City data confirmed the results of a high degree of centrality. Third, due to CONCOR analysis, eight keyword clusters highly relevant to ChatGPT in the tourism sector emerged.

• Journal of Korean Library and Information Science Society
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• v.53 no.1
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• pp.191-210
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• 2022

Niklas Luhmann is a sociologist who has had a strong influence on other disciplines. Therefore, it is necessary to examine what Luhmann's theory has influenced on his subsequent researchers. This study analyzed the knowledge network of studies on Niklas Luhmann's theory by follow-up researchers. Bibliographic coupling and co-citation were used as the analysis method of knowledge network. The main results are as follows. First, the language clusters were divided into Latin American / Spanish-speaking regions, Western Europe / Anglo-American regions, Eastern / Northern Europe and other language regions through bibliographic coupling analysis. Second, from the node analysis of bibliographic coupling, It was divided into 2 main cases: where Luhmann's major works were cited; where Luhmann's minor works were cited. Third, it was found that there are the core work groups that are repeatedly cited among Luhmann's works. Fourth, 12 core works were derived from the node analysis of the co-citation network, and appeared in four groups according to themes.

• The Journal of Information Systems
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• v.25 no.4
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• pp.121-139
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• 2016

Purpose In this study, we propose the special purposed R package named ""new_Noun()" to process nonstandard texts appeared in various social networks. As the Big data is getting interested, R - analysis tool and open source software is also getting more attention in many fields. Design/methodology/approach With more than 9,000 R packages, R provides a user-friendly functions of a variety of data mining, social network analysis and simulation functions such as statistical analysis, classification, prediction, clustering and association analysis. Especially, "KoNLP" - natural language processing package for Korean language - has reduced the time and effort of many researchers. However, as the social data increases, the informal expressions of Hangeul (Korean character) such as emoticons, informal terms and symbols make the difficulties increase in natural language processing. Findings In this study, to solve the these difficulties, special algorithms that upgrade existing open source natural language processing package have been researched. By utilizing the "KoNLP" package and analyzing the main functions in noun extracting command, we developed a new integrated noun processing package "new_Noun()" function to extract nouns which improves more than 29.1% compared with existing package.