• Journal of Digital Convergence
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• v.17 no.9
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• pp.193-198
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• 2019

In smart cities around the world, urban environments have become more convenient due to information and communication technology(ICT). However, extant studies reveal that the level of life satisfaction of citizens has not improved compared to that of the pre-smart city and citizens are skeptical about the role of the smart city. This is largely because local culture and needs were neglected during the planing and development of the smart city. The research was conducted on Cambodia as a pilot site and our findings indicate that middle age group's population is significantly small and the society is at risk of losing its culture. Therefore, this paper opens up various ways of embedding cultural programs using technology in order to pass down cultural heritage to young generation, provide an emotional attachment to the inhabitants and further build up a new phase of cultural legacy. This will engender cultural uniqueness to the city and intrigue tourists around the world resulting in the growth of the tourist industry. This research will contribute locally by providing a sense of community to the public and globally by suggesting applicable methodology to other cities that are under the similar context.

• Journal of the Korea Institute of Information and Communication Engineering
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• v.25 no.4
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• pp.595-602
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• 2021

Marine accidents are mostly caused by medium and small ships, and are continuously increasing. In this paper, we propose an architecture of the speech synthesis based automatic safety navigation support service providing system for small ships that equiped onboard systems compared with vessels. The main purpose of the system is to prevent marine accidents by providing synthesized voice safety messages to nearby ships. The safety navigation support service is operated by connecting GPS and AIS to synthesize voice safety messages, automatically broadcast through VHF. Therefore, we developed a data processing module, a staged risk analysis module, a voice synthesis safety message generation module, and a VHF broadcasting equipment control module, which are components of the system. In addition, we conducted laboratory-level and sea-trial demonstration tests using the developed the system, which verified usefulness of the proposed service.

• KSII Transactions on Internet and Information Systems (TIIS)
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• v.17 no.5
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• pp.1396-1412
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• 2023

Conversation modeling is an important and challenging task in the field of natural language processing because it is a key component promoting the development of automated humanmachine conversation. Most recent research concerning conversation modeling focuses only on the current utterance (considered as the current question) to generate a response, and thus fails to capture the conversation's logic from its beginning. Some studies concatenate the current question with previous conversation sentences and use it as input for response generation. Another approach is to use an encoder to store all previous utterances. Each time a new question is encountered, the encoder is updated and used to generate the response. Our approach in this paper differs from previous studies in that we explicitly separate the encoding of the question from the encoding of its context. This results in different encoding models for the question and the context, capturing the specificity of each. In this way, we have access to the entire context when generating the response. To this end, we propose a deep neural network-based model, called the Context Model, to encode previous utterances' information and combine it with the current question. This approach satisfies the need for context information while keeping the different roles of the current question and its context separate while generating a response. We investigate two approaches for representing the context: Long short-term memory and Convolutional neural network. Experiments show that our Context Model outperforms a baseline model on both ConvAI2 Dataset and a collected dataset of conversational English.

• Proceedings of the Korean Institute of Information and Commucation Sciences Conference
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• 2021.10a
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• pp.357-359
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• 2021

Railway system as a mass transportation is under progress to smart railway system beyond high speed and automation era. Communication network technology including 5G-R(5th Generation - Railway) mobile communication technology and information convergence technology of Big Data, Deep Learnig, AI(Artificial Intelliegnce) and Block Chain have to be used for implementation and operation of this smart railway system. In this paper, a communication network structure is suggested for this smart railway system. This suggested smart railway commnuication network structure is composed with layered structure of plane unit for safety operation of high speed railway, railway system management and customer services, and also have some complexed function of each plane. Results of this study can be used for smart railway communication network implementation, operation and managements, development of railway communication standards.

• The Journal of Bigdata
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• v.6 no.1
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• pp.63-81
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• 2021

The performance of natural language processing is rapidly improving due to the recent development and application of machine learning and deep learning technologies, and as a result, the field of application is expanding. In particular, as the demand for analysis on unstructured text data increases, interest in NLP(Natural Language Processing) is also increasing. However, due to the complexity and difficulty of the natural language preprocessing process and machine learning and deep learning theories, there are still high barriers to the use of natural language processing. In this paper, for an overall understanding of NLP, by examining the main fields of NLP that are currently being actively researched and the current state of major technologies centered on machine learning and deep learning, We want to provide a foundation to understand and utilize NLP more easily. Therefore, we investigated the change of NLP in AI(artificial intelligence) through the changes of the taxonomy of AI technology. The main areas of NLP which consists of language model, text classification, text generation, document summarization, question answering and machine translation were explained with state of the art deep learning models. In addition, major deep learning models utilized in NLP were explained, and data sets and evaluation measures for performance evaluation were summarized. We hope researchers who want to utilize NLP for various purposes in their field be able to understand the overall technical status and the main technologies of NLP through this paper.

• The Journal of the Institute of Internet, Broadcasting and Communication
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• v.21 no.1
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• pp.7-18
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• 2021

Recently, various connected industrial parks (CIPs) architectures using new technologies such as cloud computing, CPS, big data, fifth-generation mobile communication 5G, IIoT, VR-AR, and ventilation transportation AI algorithms have been proposed in Korea. Korea's small and medium-sized enterprises do not have the upper hand in technological competitiveness than overseas advanced countries such as the United States, Europe and Japan. For this reason, Korea's small and medium-sized enterprises have to invest a lot of money in technology research and development. As a latecomer, Korean SMEs need to improve their profitability in order to find sustainable growth potential. Financially, it is most efficient for small and medium-sized Korean companies to cut costs to increase their profitability. This paper made profitability improvement by reducing costs for small and medium-sized enterprises located in CIPs in Korea a major task. VJP (Vehicle Action Program) was noted as a way to reduce costs for small and medium-sized enterprises located in CIPs in Korea. The method of achieving minimum logistics costs for small businesses through the Korean CIPs payment system was analyzed. The details of the new Korean CIPs payment system were largely divided into four types: "Business", "Data", "Technique", and "Finance". Cost Benefit Analysis (CBA) was used as a performance analysis method for CIPs payment systems.

• The Research Journal of the Costume Culture
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• v.27 no.5
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• pp.449-460
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• 2019

Today, the fashion business environment of the 4.0 generation is changing based on fashion technology combined with advanced digital technologies such as AI (Artificial Intelligence), big data and IoT (Internet of Things). "Digital Transformation" means a fundamental change and innovation in a digital paradigm including corporate strategy, organization, communication, and business model, based on the utilization of digital technology. Thus, this study examines digital transformation strategies through the fashion brand Burberry. The study contents are as follows. First, it examines the theoretical concept of digital transformation and its utilization status. Second, it analyzes the characteristics of Burberry's digital transformation based on its strategies. For the research methodology, a literature review was performed on books and papers, aligning with case studies through websites, social media, and news articles. The result showed that first, Burberry has reset their main target to Millennials who actively use mobile and social media, and continues to communicate with them by utilizing digital strategy in the entire management. Second, Burberry is quickly delivering consistent brand identity to consumers by internally creating and providing social media-friendly content. Third, they have started real-time product sales and services by using IT to enhance access to brands and to lead consumers towards more active participation. In this study, Burberry's case shows that digital transformation can contribute to increased brand value and sales, keeping up with the changes in the digital paradigm. Therefore, the study suggests that digital transformation will serve as an important business strategy for fashion brands in the future.

• The Journal of the Convergence on Culture Technology
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• v.8 no.5
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• pp.613-618
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• 2022

Research on artificial intelligence based on SNN (Spiking Neural Networks) is drawing attention as a next-generation artificial intelligence that can overcome the limitations of artificial intelligence based on DNN (Deep Neural Networks) that is currently popular. In this paper, we describe the structure of the SNN compiler, a system SW that generate code from SNN description for neuromorphic computing systems. We also introduce the algorithms used for compiler implementation and present experimental results on how the execution time varies in neuromorphic computing systems depending on the the mapping algorithm. The mapping algorithm proposed in the text showed a performance improvement of up to 3.96 times over a random mapping. The results of this study will allow SNNs to be applied in various neuromorphic hardware.

• Journal of the Korean Institute of Electrical and Electronic Material Engineers
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• v.37 no.4
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• pp.420-426
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• 2024

This study proposes an innovative methodology for developing flexible printed circuit boards (FPCBs) capable of conforming to three-dimensional shapes, meeting the increasing demand for electronic circuits in diverse and complex product designs. By integrating a traditional flat plate-based fabrication process with a subsequent three-dimensional thermal deformation technique, we have successfully demonstrated an FPCB that maintains stable electrical characteristics despite significant shape deformations. Using a modified polyimide substrate along with Ag flake-based conductive ink, we identified optimized process variables that enable substrate thermal deformation at lower temperatures (~130℃) and enhance the stretchability of the conductive ink (ε ~30%). The application of this novel FPCB in a prototype 3D-shaped sensor device, incorporating photosensors and temperature sensors, illustrates its potential for creating multifunctional, shape-adaptable electronic devices. The sensor can detect external light sources and measure ambient temperature, demonstrating stable operation even after transitioning from a planar to a three-dimensional configuration. This research lays the foundation for next-generation FPCBs that can be seamlessly integrated into various products, ushering in a new era of electronic device design and functionality.

• Journal of Embryo Transfer
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• v.33 no.4
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• pp.265-270
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• 2018

Up-to-date artificial insemination (AI) using frozen sperm consider as the most widely using technology for improvement of Korean Native Cow (Hanwoo) embryo production. However, it is time consuming, required at least 15~20 years to make more than 6 generations, and their offspring number is limited. To overcome such limitations, superovulation and in vitro fertilization have been developed. For superovulation, the number of produced embryos are not enough for commercialization and donor cows need rest period. This led to use of slaughterhouse ovary for in vitro fertilization, but it is impossible to repeat the collection from the same individual and it only can improve the genetic merits of offspring for one generation. Production of embryos using Ovum Pick-Up (OPU) technique, where oocytes can be repeatedly collected from living elite donor, might overcome these limitations. In this study, we investigated the possibility of using OPU technique from donors at different age and different session periods for mass-embryo-production. Oocytes were collected from 26 donor cows twice per week, 3 - 4 months per year, between 2013 and 2016. Results showed that, the average number of embryo produced in first year used donor was significantly higher than that in second year used donor ($3.89{\pm}2.85$ vs $3.29{\pm}2.70$), however, there was no significant difference between third year used donor ($3.51{\pm}3.32$) and other groups. Taken together, our data showed that repeated using of donor up to three years is possible for in vitro embryo mass-production. Moreover, OPU can be used as suitable embryo producing technique for livestock breed improvement.