• The Journal of Asian Finance, Economics and Business
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• v.6 no.1
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• pp.273-280
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• 2019

Many studies have shown that job performance and leadership are important in our society. In addition, to improve the quality of work or to improve the work efficiency is still a lot of challenges for each leader. In Vietnam, there are few specific studies on the impact of leadership styles on employee engagement such as: transformational leadership styles, business leadership styles and leadership styles. In the field of higher education, the fewer studies on these issues. A study is conducted to test the impact of leadership styles on the engagement of cadres, lecturers and staff at public universities in Vietnam. Using adjustment techniques, inspecting the scales and theoretical models representing the relationship among the influential factors. The research is based on a sample of 309 cadres, lecturers and staff currently working in universities in Vietnam and used Structural Equation Modeling (SEM) to test the relationships among the variables. The study results show that the scales of the variables: transformational leadership, transactional leadership, laissez faire leadership, job satisfaction and organizational engagement attain the validity and reliability in the research. The study results also show transformational leadership, transactional leadership and laissez faire leadership are directly and indirectly affected by job satisfaction and organizational commitment.

• Journal of the Institute of Convergence Signal Processing
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• v.7 no.4
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• pp.189-194
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• 2006

In this paper, design of MUSIC algorithm, which is one of high resolution DOA (direction of arrival) estimation techniques was studied. Generally the complex-valued correlation matrix of MUSIC algorithm is transformed to unitary matrix or matrix expansion for the real hardware implementation. Using the orthogonality between the noise subspace eigenvectors and the steering vectors corresponding to signal component, we estimate DOA with the real-valued computation between steering vectors and noise subspace eigenvectors. The DOA algorithm was designed with VHDL models with considerations of 2 elements and 1 incident wave and its simulation results are derived.

• Korean Journal of Remote Sensing
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• v.24 no.5
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• pp.497-506
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• 2008

The needs for digital models of real environment such as 3D terrain or cyber city model are increasing. Most of applications related with modeling and simulation require virtual environment constructed from geospatial information of real world in order to guarantee reliability and accuracy of the simulation. The most fundamental data for building virtual environment, terrain elevation and orthogonal imagery is acquired from optical sensor of satellite or airplane. Providing interoperable and reusable digital model is important to promote practical application of high-resolution satellite imagery. This paper presents the new research regarding representation of geospatial information, especially for 3D shape and appearance of virtual terrain. and describe framework for constructing real-time 3D model of large terrain based on high-resolution satellite imagery. It provides infrastructure of 3D simulation with geographical context. Web architecture, XML language and open protocols to build a standard based 3D terrain are presented. Details of standard-based approach for providing infrastructure of real-time 3D simulation using high-resolution satellite imagery are also presented. This work would facilitate interchange and interoperability across diverse systems and be usable by governments, industry scientists and general public.

• Journal of Korea Trade
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• v.24 no.6
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• pp.61-81
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• 2020

Purpose - This paper examines how the consumer animosity of partner country influences the purchase of foreign products. We analyzed news sentiment to determine whether Chinese consumer's animosity affect the purchase of the products made in Korea around the time when the U.S. Terminal High Altitude Area Defense missile system was deployed in South Korea. Design/methodology - To measure the tone of Chinese consumer animosity more carefully, we utilized a text mining technique of the Chinese language to read the public's opinion. Using Chinese news paper's editorials of 2015.1-2018.10, we analyzed the sentiment toward Korea and regressed it with Korean export to China. Findings - Empirical results report that Chinese consumers tended to reduce their purchase of consumer goods from Korea when the animosity increased, that is, the sentiments of Chinese news editorials were negative. In contrast, the animosity did not affect the purchase of Korean intermediates or raw materials. We further analyzed the effect by dividing the animosity into three categories; politics, economics, and culture. Among these groups, political news exhibits a unique effect on Chinese purchase on consumer goods from Korea. Originality/value - Existing literature on animosity models has measured the animosity by collecting the consumers' opinions through survey at a given time point, whereas it is measured by analyzing the tone of the press release by sentiment analysis during the time period around the event occurrence in this study.

• Journal of Internet Computing and Services
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• v.20 no.2
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• pp.69-76
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• 2019

Recent Enterprise System has component driven real-time distributed architecture (RDA) and this kind of architecture should performed with satisfying strict constraints on life cycle of object and response time such as synchronization, transaction and so on. Microsoft's .NET platform supports RDA and is able to implement services including before mentioned time restriction and security service by only specifying attribute code and maximizing advantages of OMG's Model Driven Architecture (MDA). In this study, a method to automatically generate an extended model of essential elements in an enterprise-system-based RDA as well as the platform specific model (PSM) for Microsoft's .NET platform are proposed. To realize these ideas, the functionalities that should be considered in enterprise system development are specified and defined in a meta-model and an extended UML profile. In addition, after defining the UML profile for .NET specification, these are developed and applied as plug-ins of the open source MDA tool, and extended models are automatically generated using this tool. Accordingly, by using the proposed specification technology, the profile and tools can easily and quickly generate a reusable extended model even without detailed coding-level information about the functionalities considered in the .NET platform and RDA.

• Cross-Cultural Studies
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• v.25
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• pp.549-596
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• 2011

This paper aims to introduce some useful multimedia freewares, and also support Chinese instructor with discussing how to operate them for instructional design of multimedia language learning class. For this aims, this paper consists of three parts: First, instructional design. This part is focused to what kind of instructional model to be based on, for example, Dick & Carey model, ADDIE model, ASSURE model etc. This part introduces these models, and modifies ADDIE and ASSURE model to D.D.A.I.E.S and S.S.A.U.R.E.S as 'A(nalysis)' in these model may apply to the next 'D(evelopment)' on ADDIE, 'S(elect Methods, Media and Materials)' on ASSURE in the practical Chinese class. Second, Programme: What to use. This part is focused to what kind of free software we can use. In the web site online, there are huge free softwares so we usually hesitate to select and also don't know how to operate even though selected one of them. This part, accordingly, introduces ten of useful freewares and compares each other in terms of usefulness for Chinese instructors. Third, Programme: How to use. It is of no use just to know what to use but not to know how to operate, so this part describes how to use freewares like a kind of manual in detail as far as possible. In conclusion, we hope more Chinese instructors to learn and use more useful freewares for designing the better multimedia Chinese class by this paper.

• KSII Transactions on Internet and Information Systems (TIIS)
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• v.14 no.12
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• pp.4706-4724
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• 2020

With various structured data, such as the company size, loan balance, and savings accounts, the voice of customer (VOC), which is text data containing contact history and counseling details was analyzed in this study. To analyze unstructured data, the term frequency-inverse document frequency (TF-IDF) analysis, semantic network analysis, sentiment analysis, and a convolutional neural network (CNN) were implemented. A performance comparison of the models revealed that the predictive model using the CNN provided the best performance with regard to predictive power, followed by the model using the TF-IDF, and then the model using semantic network analysis. In particular, a character-level CNN and a word-level CNN were developed separately, and the character-level CNN exhibited better performance, according to an analysis for the Korean language. Moreover, a systematic selection model for optimal text mining techniques was proposed, suggesting which analytical technique is appropriate for analyzing text data depending on the context. This study also provides evidence that the results of previous studies, indicating that individual customers leave when their loyalty and switching cost are low, are also applicable to corporate customers and suggests that VOC data indicating customers' needs are very effective for predicting their behavior.

• 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.

• Korean Journal of Childcare and Education
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• v.17 no.1
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• pp.19-37
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• 2021

Objective: This study aimed to explore the effect of the national preschool curriculum on children's development in Korea, focusing on teachers' daily practice. By comparing the effect of the teachers' curriculum practice to that of quantitatively measured free play, it tried to add practical implications beyond the statistical significance. Methods: Participants were 512 three-year-old children who participated in the Panel Study of Korean Children and their teachers. National curriculum practice and free play time at the age of three was put in the hierarchical linear regression models to discover children's developmental outcomes at the age of four, in domains of language, cognitive development, and social development. Results: Results demonstrated the significant positive influence of national curriculum practice on every domain of developmental outcomes. However, no facilitative influence of free play time was observed. Conclusion/Implications: The importance of teachers' practice of the national curriculum was emphasized. It was implied that the quantity of free play time itself did not assure the sound development of children. Policy implications were discussed regarding teacher practice and education.

• Journal of Information Processing Systems
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• v.18 no.5
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• pp.614-627
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• 2022

Aspect-based sentiment analysis is to discover the sentiment polarity towards an aspect from user-generated natural language. So far, most of the methods only use the implicit position information of the aspect in the context, instead of directly utilizing the position relationship between the aspect and the sentiment terms. In fact, neighboring words of the aspect terms should be given more attention than other words in the context. This paper studies the influence of different position embedding methods on the sentimental polarities of given aspects, and proposes a position embedding interactive attention network based on a long short-term memory network. Firstly, it uses the position information of the context simultaneously in the input layer and the attention layer. Secondly, it mines the importance of different context words for the aspect with the interactive attention mechanism. Finally, it generates a valid representation of the aspect and the context for sentiment classification. The model which has been posed was evaluated on the datasets of the Semantic Evaluation 2014. Compared with other baseline models, the accuracy of our model increases by about 2% on the restaurant dataset and 1% on the laptop dataset.