• Journal of Fashion Business
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• v.6 no.3
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• pp.94-109
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• 2002

The advent of the information age, advancement of the multi-media, and proliferation of internet are all ushering-in a new era of a cyber world. The artistic expression is unfolding into a new genre of a new era.. In the modern art, the boundary between the fine art and the applied art is becoming blurred, and further, distinction of fine art from popular art is also becoming meaningless. The advancement of science and technology, by offering new materials and visual forms, is contributing to the expansion of the morden art's horizon. As fashion illustration is gaining recognition as a form of art which mirrors today's realities, it has also become increasingly necessary to add variety and newness. Fashion illustration is thus becoming the visual language of the modern world, capable of conveying artistic emotion, and at the same time able to effectively communicate the image of fashion to the masses. The increasing awareness of artistic talent and ingenuity as essential components of fashion illustration is yielding greater fusion between fashion illustration and art & technology. This has resulted in the use of the advanced computer technology as a tool for crafting artistic expressions, such as fashion illustration, and this new tool has opened-up new possibilities for expressing images and colors. Further, the computer-aided fashion illustration is emerging as a new technique for expression. The concept of fashion illustration, history of fashion illustration from its incepton to modern date is reviewed and the simplicity has been researched throughout past studies published in Korean and overseas Journals.

• The Journal of Asian Finance, Economics and Business
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• v.6 no.2
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• pp.239-246
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• 2019

Teenagers in multicultural families are more prone to depression and problem behaviors caused by violence such as bullying in schools due to their appearance, language presentation skills, and poor learning abilities compared to teenagers in general families. This study is meaningful in that it provides basic information for prevention measures in intervening with damage caused by school violence such as depression, anxiety, suicidal impulses and emotional and social. For this purpose, a survey of 300 elementary school students from 4 to 6 grade, junior high school, and high school students was conducted. A total of 400 questionnaires were distributed and of thos e 385 were used for the final analysis. The results of the study are as follows. First, the psychological factors of suicidal ideation were higher in the victimized group than school violence. Second, there was a significant difference in the relationship between emotional - social isolation and school violence experience. Third, there was a significant difference in the relationship between experience of suicide ideation and depression as well as anxiety of emotional - social isolation with psychological maladjustment. In conclusion, we plan to find ways to stabilize the multicultural society by providing prevention and protection measures against school violence.

• Journal of The Korean Society of Integrative Medicine
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• v.6 no.4
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• pp.191-206
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• 2018

Purpose : This study investigated the correlation between speech intelligibility and acoustic measurements of speech sounds produced by the children with speech sound disorders and children without any diagnosed speech sound disorder. Methods : A total of 60 children with and without speech sound disorders were the subjects of this study. Speech samples were obtained by having the subjects? speak meaningful words. Acoustic measurements were analyzed on a spectrogram using the Multi-speech 3700 program. Speech intelligibility was determined according to a listener's perceptual judgment. Results : Children with speech sound disorders had significantly lower speech intelligibility than those without speech sound disorders. The intensity of the vowel /u/, the duration of the vowel /${\omega}$/, and the second formant of the vowel /${\omega}$/ were significantly different between both groups. There was no difference in voice onset time between the groups. There was a correlation between acoustic measurements and speech intelligibility. Conclusion : The results of this study showed that the speech intelligibility of children with speech sound disorders was affected by intensity, word duration, and formant frequency. It is necessary to complement clinical setting results using acoustic measurements in addition to evaluation of speech intelligibility.

• Cross-Cultural Studies
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• v.21
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• pp.139-164
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• 2010

Sung Yung Shin was adopted as a Korean infant to an American family. She is now one of the most important writers in Asian American literary field. This paper analyzes the characteristics of her literature, focusing on Skirt full of Black (poetry)and Cooper's Lesson(children's book). Sun Yung Shin uses collage in Skirt full of Black as an effective rhetorical device because it can express her experience as an adopted other in the multicultural American society. She rewrites the fairy tale of Swan Prince in the viewpoint of silence. For a yellow Asian adopted woman, speaking is suppressed. In the end, the attempt to escape from silence is the writer's resisting activity, and the rewriting of the tale is her questioning in place of the princess. I analyses Cooper's Lesson in the viewpoint of transcultural assimilation. Cooper's lesson is accomplished not by his white father but by a Korean settler, Mr. Lee. Cooper's family is a hybrid composed of white American father, Korean mother, and their half son. So this family has many complicated difficulties, though it's small. Mr. Lee who accepted a new language to establish a new identity teaches Cooper the importance of cultural assimilation, which is not a one-sided integration to dominant culture but an intercultural communion while sustaining each culture's singularity. Cooper learns that he should live in an harmonious and balanced life in a multi-cultural society while keeping his own subjective point of view.

• Cross-Cultural Studies
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• v.36
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• pp.241-270
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• 2014

The aim of this article is to review the traditional methodologies of teaching translation that concentrate on text-typologies and, as an alternative, to propose an eclectic multi-componential approach that involves a set of interdisciplinary skills with a view to improving the trainee translators' competences and skills. To this end, three approaches, namely a minimalist approach, a pre-transferring adjustment approach and a revision vs. editing approach are proposed to shift the focus of attention from teacher-centred approaches towards student-centred approaches. It has been shown that translator training programmes need to focus on improving the trainee translators' competences and skills, such as training them how to produce and select among the different versions they produce by themselves with justified confidence as quickly as they can (minimalist approach), adjust the original text semantically, syntactically and/or textually in a way that the source text supplely accommodates itself in the linguistic system of the target language (pre-transferring adjustment), and revise and edit others' translations. As the validity of the approach proposed relies partially on instructors' competences and skills in teaching translation, universities, particularly in the Arab world, need to invest in recruiting expert practitioners instead of depending mainly on bilingual teachers to teach translation.

• KSII Transactions on Internet and Information Systems (TIIS)
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• v.15 no.4
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• pp.1275-1292
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• 2021

As a fine-grained classification problem, aspect-level sentiment classification predicts the sentiment polarity for different aspects in context. To address this issue, researchers have widely used attention mechanisms to abstract the relationship between context and aspects. Still, it is difficult to effectively obtain a more profound semantic representation, and the strong correlation between local context features and the aspect-based sentiment is rarely considered. In this paper, a hybrid attention capsule network for aspect-level sentiment classification (ABASCap) was proposed. In this model, the multi-head self-attention was improved, and a context mask mechanism based on adjustable context window was proposed, so as to effectively obtain the internal association between aspects and context. Moreover, the dynamic routing algorithm and activation function in capsule network were optimized to meet the task requirements. Finally, sufficient experiments were conducted on three benchmark datasets in different domains. Compared with other baseline models, ABASCap achieved better classification results, and outperformed the state-of-the-art methods in this task after incorporating pre-training BERT.

• International Journal of Computer Science & Network Security
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• v.21 no.11
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• pp.135-142
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• 2021

The article reveals the essence of cybercrime, approaches to understanding this concept, classification of cybercrime, and other illegal acts in this area. The concept of cybercrime has multi-discourse nature and a certain legal uncertainty. Cybercrimes, their forms and types are analyzed in the economic context. The research vocabulary of the economic industry is defined. The scope and content of concepts denoted by the terms of the sphere covered by cybercrime are studied, and its types and forms are analyzed. The article studies problems, achievements, and prospects of resisting and combating cybercrime during the development of the civil information society and Ukraine's entry into the global information space. The study focuses on the economic motivation of most cybercrimes since some material benefit from the fact of cyber offenses is assumed directly or indirectly.

• International Journal of Computer Science & Network Security
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• v.22 no.8
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• pp.242-248
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• 2022

The article presents the analysis of modern methods of automatic comparison of original and unoriginal text to detect textual plagiarism. The study covers two types of plagiarism - literal, when plagiarists directly make exact copying of the text without changing anything, and intelligent, using more sophisticated techniques, which are harder to detect due to the text manipulation, like words and signs replacement. Standard techniques related to extrinsic detection are string-based, vector space and semantic-based. The first, most common and most successful target models for detecting literal plagiarism - N-gram and Vector Space are analyzed, and their advantages and disadvantages are evaluated. The most effective target models that allow detecting intelligent plagiarism, particularly identifying paraphrases by measuring the semantic similarity of short components of the text, are investigated. Models using neural network architecture and based on natural language sentence matching approaches such as Densely Interactive Inference Network (DIIN), Bilateral Multi-Perspective Matching (BiMPM) and Bidirectional Encoder Representations from Transformers (BERT) and its family of models are considered. The progress in improving plagiarism detection systems, techniques and related models is summarized. Relevant and urgent problems that remain unresolved in detecting intelligent plagiarism - effective recognition of unoriginal ideas and qualitatively paraphrased text - are outlined.

• Journal of Ocean Engineering and Technology
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• v.36 no.1
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• pp.41-49
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• 2022

With the advancement of intelligent vehicles and unmanned systems, there is a growing interest in underwater surveys using autonomous marine vehicles (AMVs). This study presents an automated planning strategy for a long-term survey mission using a fleet of AMVs consisting of autonomous surface vehicles and autonomous underwater vehicles. Due to the complex nature of the mission, the actions of the vehicle must be of high-level abstraction, which means that the actions indicate not only motion of the vehicle but also symbols and semantics, such as those corresponding to deploy, charge, and survey. For automated planning, the planning domain definition language (PDDL) was employed to construct a mission planner for realizing a powerful and flexible planning system. Despite being able to handle abstract actions, such high-level planners have difficulty in efficiently optimizing numerical objectives such as obtaining the shortest route given multiple destinations. To alleviate this issue, a widely known technique in operations research was additionally employed, which limited the solution space so that the high-level planner could devise efficient plans. For a comprehensive evaluation of the proposed method, various PDDL-based planners with different parameter settings were implemented, and their performances were compared through simulation. The simulation result shows that the proposed method outperformed the baseline solutions by yielding plans that completed the missions more quickly, thereby demonstrating the efficacy of the proposed methodology.

• Proceedings of the Korea Information Processing Society Conference
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• 2023.05a
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• pp.647-649
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• 2023

Sentiment analysis as part of natural language processing (NLP) has received much attention following the demand to understand people's opinions. Aspect-based sentiment analysis (ABSA) is a fine-grained subtask from sentiment analysis that aims to classify sentiment at the aspect level. Throughout the years, researchers have formulated ABSA into various tasks for different scenarios. Unlike the early works, the current ABSA utilizes many elements to improve performance and provide more details to produce informative results. These ABSA formulations have provided greater challenges for researchers. However, it is difficult to explore ABSA's works due to the many different formulations, terms, and results. In this paper, we conduct a comparative analysis of recent studies on ABSA. We mention some key elements, problem formulations, and datasets currently utilized by most ABSA communities. Also, we conduct a short review of the latest papers to find the current state-of-the-art model. From our observations, we found that span-level representation is an important feature in solving the ABSA problem, while multi-task learning and generative approach look promising. Finally, we review some open challenges and further directions for ABSA research in the future.