• Journal of Korea Society of Industrial Information Systems
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• v.11 no.5
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• pp.37-52
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• 2006

XML architecture is important to wireless or wired presentation. It is also important for data exchange between businesses. XML forces the separation of content from style and gives wired or wireless devices flexibility for interpretation. Separation of content, style, and logic is key to advanced architecture. XML can be exchanged among databases on multiple systems with presentation on wired or wireless devices. An XML schema might need to be defined, or an established DTD might need to be transformed to access a relational database on the server. The purpose of this study is to generate XML documents such as DTD, XML schema, RDB mapping using Tagfree's XML developer tools in order to experience whole processes mentioned above. Overall understanding of data structures of and database processing with XML documents, which is essential to XML programming and database processing, can be accomplished with this study without much endeavor to learn complex XML syntax. The future study can be extended on the subject of web programming with DOM or SAX API.

• KIPS Transactions on Software and Data Engineering
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• v.10 no.12
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• pp.579-586
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• 2021

Time series forecasting refers to predicting future time information based on past time information. Accurately predicting future information is crucial because it is used for establishing strategies or making policy decisions in various fields. Recently, a transformer model has been mainly studied for a time series prediction model. However, the existing transformer model has a limitation in that it has an auto-regressive structure in which the output result is input again when the prediction sequence is output. This limitation causes a problem in that accuracy is lowered when predicting a distant time point. This paper proposes a sequential decoding model focusing on the style transformation technique to handle these problems and make more precise time series forecasting. The proposed model has a structure in which the contents of past data are extracted from the transformer-encoder and reflected in the style-based decoder to generate the predictive sequence. Unlike the decoder structure of the conventional auto-regressive transformer, this structure has the advantage of being able to more accurately predict information from a distant view because the prediction sequence is output all at once. As a result of conducting a prediction experiment with various time series datasets with different data characteristics, it was shown that the model presented in this paper has better prediction accuracy than other existing time series prediction models.

• The Journal of Korean Association of Computer Education
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• v.14 no.1
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• pp.1-12
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• 2011

Educational Programming Language has been reported to expand thinking ability and to give help in creative problem solving ability by numerous researches. Researchers are verifying the educational effects of EPL by applying it to various area, but researches in effective application of EPL is yet incomplete. Thus, for effective application of EPL, this research has verified the project completing ability depending on studying style targeted to college senior students. As results of verification, first, the results showed significant differences in project completing abilities depending on information processing methods, and learners who preferred self-reflecting introspection showed high scores. Second, in learning style the divergers showed the highest scores. This research suggested the necessity of guidance and detailed planning of self-reflecting introspective activity in ideas that would be realized by learners through searching for factors that could enhance the degree of project completion in programming learning using EPL.

• Information Systems Review
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• v.25 no.4
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• pp.265-290
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• 2023

Even though crowdfunding has become popular as a novel means of raising capital for early-stage ventures and startups through an Internet-based platform, it is unclear how a funder's characteristics, such as motivation and ability, influence their information processing and pledging decision. This study aims to propose and test a research model for determining the relationships between a funder's personal attributes, information processing style, and funding intention. To test the research model, we collected data from 139 Amazon Mechanical Turk participants through an online questionnaire survey. The findings indicate that a funder's self-efficacy has a positive effect on heuristic processing but has no significant effect on systematic processing. By contrast, a funder's personal relevance positively influences both systematic and heuristic processing. Furthermore, heuristic processing, as well as perceived value and perceived risk, influence pledging intentions positively. Our findings potentially contribute to improving the design of crowdfunding platforms to better support a funder's information needs. Based on our findings, we discuss the implications of our study as well as the directions for future research.

• KIPS Transactions on Software and Data Engineering
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• v.12 no.8
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• pp.341-354
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• 2023

The title of a document is the brief summarization of the document. Readers can easily understand a document if we provide them with its title in their preferred styles and the languages. In this research, we propose a cross-lingual and style-based title generation model using multiple adapters. To train the model, we need a parallel corpus in several languages with different styles. It is quite difficult to construct this kind of parallel corpus; however, a monolingual title generation corpus of the same style can be built easily. Therefore, we apply a zero-shot strategy to generate a title in a different language and with a different style for an input document. A baseline model is Transformer consisting of an encoder and a decoder, pre-trained by several languages. The model is then equipped with multiple adapters for translation, languages, and styles. After the model learns a translation task from parallel corpus, it learns a title generation task from monolingual title generation corpus. When training the model with a task, we only activate an adapter that corresponds to the task. When generating a cross-lingual and style-based title, we only activate adapters that correspond to a target language and a target style. An experimental result shows that our proposed model is only as good as a pipeline model that first translates into a target language and then generates a title. There have been significant changes in natural language generation due to the emergence of large-scale language models. However, research to improve the performance of natural language generation using limited resources and limited data needs to continue. In this regard, this study seeks to explore the significance of such research.

• The Transactions of the Korea Information Processing Society
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• v.7 no.12
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• pp.3995-4003
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• 2000

This paper describes a method that extracts the region of car-licence plates in color images of private and commercial cars. To extract car-licence plates, we use the feature that car-licence plate regions have regular colors according to the kinds of cars. In this paper, we propose the method that combines H component of HSI color model and Q component of YIQ color model. To improve efficiency of the process, we cxplore lines ill a car image by a regular interval in a bottom-up style. As a result, the extraction rates by only H-component. only by Q- component. and by combined Hand Q, are 53.6%, 82.1%, and 94.6% respectively.

• Proceedings of the Korea Information Processing Society Conference
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• 2011.11a
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• pp.62-65
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• 2011

FPGA는 대용량의 게이트를 지원하는 하드웨어를 프로그램 할 수 있는 디바이스이다. ASIC을 위해 설계된 로직은 칩으로 제조되기 전에 검증 과정을 거친다. 이 검증 과정에서 시뮬레이션의 한계를 극복하기 위해 FPGA를 사용한 에뮬레이션 방법을 많이 채택한다. 에뮬레이션 과정에서 ASIC의 동작 속도로 검증하는 것이 바람직하지만 FPGA의 특성상 ASIC과 같은 속도로 동작하기는 쉽지 않은 것이 현실이다. 본 논문에서는 HDL 코딩 방법에 따른 FPGA의 성능 민감도를 실험하였다. 실험 및 평가를 위해 다양한 알고리즘을 가진 가산기를 이용하였고 각 가산기 종류와 비트수에 따라 Verilog-HDL을 이용하여 코딩하였으며 대표적인 FPGA 제조사(Altera와 Xilinx)별, 디바이스별로 동작 속도와 자원 사용량을 측정하였다. 실험 결과 FPGA 제조사별로 다른 경향을 보임을 확인하였다. 성능 면에서는 비트별로 다소 차이는 있지만 Altera 디바이스에서는 Ripple Carry, Carry Lookahead 가산기보다 Prefix 가산기의 성능이 우수하게 나왔다. Xilinx 디바이스에서는 예상과 달리 가산기들 사이의 성능 차이가 크게 나지 않았으며 Ripple Carry, Carry Lookahead 가산기가 Prefix 가산기보다 높은 성능을 보이는 경우도 있었다. 비용 면에서는 디바이스별로 큰 차이가 나지 않았으며 ASIC과 비슷한 성능 민감도를 보였다. 그리고 각 제조사에서 제공하는 IP(Intellectual Property) Core를 사용했을 경우는 대부분의 디바이스에서 우수한 성능을 보여 주었다. TSMC 90nm 공정 기술로 제작한 ASIC과 IP Core를 비교했을 때는 ASIC의 성능이 4배 정도 우수한 것으로 나타났다.

• Journal of Smart Tourism
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• v.3 no.1
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• pp.41-47
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• 2023

Tourism and hospitality have encountered significant changes in recent years as a result of the rapid development of information technology (IT). Customers now expect more expedient services and customized travel experiences, which has intensified competition among service providers. To meet these demands, businesses have adopted sophisticated IT applications such as ChatGPT, which enables real-time interaction with consumers and provides recommendations based on their preferences. This paper focuses on the AI support-prompt middleware system, which functions as a mediator between generative AI and human users, and discusses two operational rules associated with it. The first rule is the Information Processing Rule, which requires the middleware system to determine appropriate responses based on the context of the conversation using techniques for natural language processing. The second rule is the Information Presentation Rule, which requires the middleware system to choose an appropriate language style and conversational attitude based on the gravity of the topic or the conversational context. These rules are essential for guaranteeing that the middleware system can fathom user intent and respond appropriately in various conversational contexts. This study contributes to the planning and analysis of service design by deriving design rules for middleware systems to incorporate artificial intelligence into tourism services. By comprehending the operation of AI support-prompt middleware systems, service providers can design more effective and efficient AI-driven tourism services, thereby improving the customer experience and obtaining a market advantage.

• Proceedings of the IEEK Conference
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• 2003.07a
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• pp.557-560
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• 2003

The increase of vehicles stagnations leads to the increasing attention to the way customers pay and a large number of projects on electronic cash system. Tranport system is comprised of a number of advanced technologies, including information processing, communications, control, and electronics. Recently many research on a system which provides contact in order to protect driver's vehicle passage have been carried out. And some potential problems from that system are being reviewed by electronic cash system. In this papers, we suggest RF protocol developing technology using the concept of electronic cash. ATM electronic cash developing is consist of component of pre-developed coin throw, integration of component using its, and production of more requirement-satisfactory ITS solution. Result increase 15~40% pre-type vehicles stagnations. Especially, we expect this proposed concept would be well adapted to our national environments.

• KIPS Transactions on Software and Data Engineering
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• v.5 no.9
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• pp.411-418
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• 2016

Learning analytic has been utilized to helps us to successfully complete the course by using the interaction of the teacher and the learner data generated from the teaching and learning support system. In other words, Learning analytic is a method in order to understand the activities of learners. In the learning analytic, the data model is needed in order to utilize the more useful for teaching and learning activities data. Therefore, in this study, we propose a user centric data model of learning styles and learning objects. This model is expressed by aggregating of user learning style, learning objects, and learning activities. The proposed model is significant that laid the foundation for analyzing the activities of the learners in course units.