• 한국통신학회논문지
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• 제34권9B호
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• pp.939-946
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• 2009

본 논문에선 기계 기술 언어(machine descriptions language)인 LISA(Language for Instruction Set Architecture)를 통하여 시뮬레이션 모델로 설계한 새로운 네트워크 ASIP(Application Specific Instruction-set Processor)을 제안한다. 제안한 네트워크 ASIP은 라우터(router)에서 패킷 프로세싱을 담당하는 전용엔진을 목적으로 설계되었다. 이를 위해 MIPS(Microprocessor without Interlock Pipeline Stages) 아키텍처를 기반으로 한 일반적인 ASIP에 패킷을 빠른 속도로 처리하기 위해 필요한 새로운 명령어 셋을 추가하였다. 새로 추가된 명령어 셋은 "classification" 명령어 그룹과 "modification" 명령어 그룹으로 나눌 수 있으며, 각 그룹은 실행 단계(execution stage)에 위치한 각각의 기능 유닛(function unit)에 의해서 처리된다. 그리고 각각의 기능 유닛은 Verilog HDL을 통해 면적과 속도 측면에서 최적화하였으며, 이를 합성하여 면적과 동작 지연시간을 비교하였다. 또한 CKF(Compiler Known Function)을 이용하여 C 언어 레벨의 매크로 함수에 할당하였으며, 어플리케이션 프로그램에 대한 실행 싸이클을 비교 분석하여 성능 향상을 확인하였다.

• International Journal of Computer Science & Network Security
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• 제21권8호
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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.

• 해양정책연구
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• 제33권2호
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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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• 제21권3호
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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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• 제23권9호
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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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• 제45권1호
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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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• 제24권3호
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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.

• 디지털산업정보학회논문지
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• 제19권4호
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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.

• 한국도서관정보학회지
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• 제53권1호
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• pp.191-210
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• 2022

Niklas Luhmann은 다른 학문 분야에도 막강한 영향력을 끼치고 있는 사회학자이다. 따라서 Luhmann의 이론이 후속 연구자들에게 어떤 영향력을 끼쳤는지를 검토할 필요가 있다. 이 연구는 Niklas Luhmann의 이론을 연구하는 후속연구자들의 지식 네트워크를 분석하였고, 분석 방법은 서지결합과 동시인용을 사용하였다. 주요 결과는 다음과 같다. 첫째, 서지결합분석을 통해서는 남미·스페인어권, 서유럽·영미권, 동·북유럽 및 기타 어권으로 클러스터가 나뉘었다. 둘째, 서지결합 노드 단위 분석에서는 주로 Luhmann의 핵심 저작을 인용한 경우, Luhmann의 주변 저작들을 인용한 경우로 나뉘었다. 셋째, 동시인용분석을 통해서는 Luhmann의 저작 중 반복적으로 인용되는 핵심 저작군이 있는 것으로 나타났다. 넷째, 동시인용 네트워크의 노드 단위 분석에서는 12개의 핵심 저작이 도출되었고, 핵심 저작들은 주제에 따라 4개의 저작군으로 나타났다.

• 한국정보시스템학회지:정보시스템연구
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• 제25권4호
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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.