• Proceedings of the Korean Institute of Information and Commucation Sciences Conference
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• 2021.10a
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• pp.609-612
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• 2021

Government agencies and companies are establishing and promoting digital transformation strategies in various industrial fields, and are leading the era of the 4th industrial revolution through successful technological innovation. In this time of change, we can see many stories of global companies Nike and Starbucks as successful examples of digital transformation. These two companies are showing successful results through digital transformation. Domestic companies are also conducting digital innovation based on mobile, cloud, IoT, artificial intelligence, and AR/VR technologies, and are establishing RPA (Robotic Process Automation) processes for high efficiency and high productivity. In this paper, we introduce the 3D digital twin space construction automation process technique using data from the entire construction cycle of design, construction, and maintenance of the construction industry, and look into the digital transformation strategy of the construction industry in the future.

• Proceedings of the Korean Institute of Information and Commucation Sciences Conference
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• 2022.10a
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• pp.250-252
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• 2022

Recently, with the development of IoT technology and AI, unmanned and automated systems are progressing in various fields, and various application technologies are being studied in systems using algorithms such as object detection, recognition, and tracking. In the case of a system operating based on an image, noise removal is performed as a pre-processing process, and precise noise removal is sometimes required depending on the environment of the system. In this paper, we propose a modified central weight filter algorithm using pixel division of local regions to minimize the blurring that tends to occur in the filtering process and to emphasize the details of the resulting image. In the proposed algorithm, when a pixel of a local area is divided into two areas, the center of the dominant area among the divided areas is set as a criterion for the weight filter algorithm. The resulting image is calculated by convolving the transformed center weight with the pixel value inside the filtering mask.

• Journal of the Society of Disaster Information
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• v.20 no.2
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• pp.315-328
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• 2024

Purpose: The purpose of this paper is to present a service construction plan using multiple complex sensor information to detect abnormal situations in urban life safety that are difficult to identify on CCTV. Method: This study selected service scenarios based on actual testbed data and analyzed service importance for local government control center operators, which are main users. Result: Service scenarios were selected as detection of day and night dynamic object, Detection of sudden temperature changes, and Detection of time-series temperature changes. As a result of AHP analysis, walking and mobility collision risk situation services and fire foreshadowing detection services leading to immediate major disasters were highly evaluated. Conclusion: This study is significant in proposing a plan to build an anomaly detection service that can be used in local governments based on real data. This study is significant in proposing a plan to build an anomaly detection service that can be used by local governments based on testbed data.

• The Journal of the Korea institute of electronic communication sciences
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• v.19 no.5
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• pp.903-910
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• 2024

Complex semantic segmentation tasks are primarily performed in server environments equipped with high-performance graphics hardware such as GPUs and TPUs. This cloud-based AI inference method operates by transmitting processed results to the client. However, this approach is dependent on network communication and raises concerns about privacy infringement during the process of transmitting user data to servers. Therefore, this paper proposes a Generalized On-Device Framework for Semantic Segmentation that can operate in mobile environments with high accessibility to people. This framework supports various semantic segmentation models and enables direct inference in mobile environments through model conversion and efficient memory management techniques. It is expected that this research approach will enable effective execution of semantic segmentation algorithms even in resource-constrained situations such as IoT devices, autonomous vehicles, and industrial robots, which are not cloud computing environments. This is expected to contribute to the advancement of real-time image processing, privacy protection, and network-independent AI application fields.

• Journal of Convergence for Information Technology
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• v.11 no.2
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• pp.10-15
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• 2021

In this paper, we formed perovskite (CH3NH3PbI3) thin films on glass with wet coating methods, and used various analytical techniques to discuss film thickness, surface roughness, crystallinity, composition, and optical property. The coated semiconductor material has no defects and is uniform, the surface roughness value is very small, and a high absorption rate has been observed in the visible light area. Next, in order to implement the hole shape in the organic-inorganic layer, Samples in the order of a metal mask with holes at regular intervals, a glass coated with a perovskite material, and a magnet were etched with atmospheric pressure plasma equipment. The shape of the hole formed in the perovskite material was analyzed by changing the time. It can be seen that more etching is performed as the time increases. The sample with the longest processing time was examined in more detail, and it was classified into 7 regions by the difference according to the location of the plasma.

• Journal of the Korea Institute of Information and Communication Engineering
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• v.18 no.7
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• pp.1540-1546
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• 2014

In order to resolve coverage hole problems caused by indoor-BS (IBS) faults, we propose a new frame structure and practical algorithm based on optimization technique. Our main contributions can be described as follows: 1) a frame structure with healing channels for solving abnormal IBS faults; and 2) an efficient heuristic resource allocation algorithm with fixed IBS selection to reduce the complexity for the optimization problem. Through intensive simulations, we evaluate the performance excellency of our proposed algorithm with respect to average cell capacity and user fairness compared with conventional algorithms.

• Journal of the Korea Institute of Information and Communication Engineering
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• v.18 no.10
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• pp.2382-2388
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• 2014

To provide network reliability in indoor wireless communication systems, we should resolve the problem of unexpected network failure rapidly. In this paper, we propose an adaptive resource management (ARM) scheme to support seamless connectivity to users. In consideration of system throughput and user fairness simultaneously, the ARM scheme adaptively determines the set of healing channels, and performs scheduling and power allocation iteratively based on a constrained non-convex optimization technique. Through intensive simulations, we demonstrate the superior performance results of the proposed ARM scheme in terms of the average cell capacity and user fairness.

• KIISE Transactions on Computing Practices
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• v.22 no.2
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• pp.69-76
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• 2016

With the recent increase of the interest in IoT in almost all areas of industry, computing technologies have been increasingly applied in human environments such as houses, buildings, cars, and streets; in these IoT environments, speech recognition is being widely accepted as a means of HCI. The existing server-based speech recognition techniques are typically fast and show quite high recognition rates; however, an internet connection is necessary, and complicated server computing is required because a voice is recognized by units of words that are stored in server databases. This paper, as a successive research results of speech recognition algorithms for the Korean phonemic vowel 'ㅏ', 'ㅓ', suggests an implementation of speech recognition algorithms for the Korean phonemic vowel 'ㅣ'. We observed that almost all of the vocal waveform patterns for 'ㅣ' are unique and different when compared with the patterns of the 'ㅏ' and 'ㅓ' waveforms. In this paper we propose specific waveform patterns for the Korean vowel 'ㅣ' and the corresponding recognition algorithms. We also presents experiment results showing that, by adding neural-network learning to our algorithm, the voice recognition success rate for the vowel 'ㅣ' can be increased. As a result we observed that 90% or more of the vocal expressions of the vowel 'ㅣ' can be successfully recognized when our algorithms are used.

• Journal of Convergence for Information Technology
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• v.11 no.4
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• pp.83-101
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• 2021

This study is to investigate, using AHP, what technologies should be applied first to Korean SMEs in order to respond to the 4th industrial revolution and change to a smart enterprise. To this end, technologies related to the 4th industrial revolution and smart factory are synthesized, and the classification criteria of Dae-Hoon Kim et al. (2019) are applied, but additional opinions of experts are collected and related technologies are converted to artificial intelligence (AI), Big Data, and Cloud Computing. As a base technology, mobile, Internet of Things (IoT), block chain as hyper-connected technology, unmanned transportation (autonomous driving), robot, 3D printing, drone as a convergence technology, smart manufacturing and logistics, smart healthcare, smart transportation and smart finance were classified as smart industrial technologies. As a result of confirming the priorities for technical use by AHP analysis and calculating the total weight, manufacturing companies have a high ranking in mobile, artificial intelligence (AI), big data, and robots, while service companies are in big data and robots, artificial intelligence (AI), and smart healthcare are ranked high, and in all companies, it is in the order of big data, artificial intelligence (AI), robot, and mobile. Through this study, it was clearly identified which technologies should be applied first in order to respond to the 4th industrial revolution and change to a smart company.

• Annual Conference of KIPS
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• 2017.11a
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• pp.1179-1182
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• 2017

본 논문에서는 미세먼지를 포함하여 공기의 오염도를 측정하기 위해 폭넓게 활용되고 있는 광 산란 방식 센서의 정확도를 향상시키기 위하여, 초기 측정값에 적절한 보정 값을 추가하여 최종 결과를 구하는 방법을 제안한다. 기존 광 산란 방식의 센서는 휴대가 가능하고, 실시간으로 공기의 오염도를 측정할 수 있는 장점을 가지고 있으나, 그 정확도가 다소 낮다는 단점을 가지고 있었다. 제안시스템은 측정 범위를 확장할 수 있는 보정 값을 최종 측정값에 반영하고, 하드웨어적으로도 불필요한 외부 빛의 유입을 차단하는 설계를 적용하여 그 정확도를 높이고자 하였다. 또한, 측정된 결과를 사용자가 모바일 애플리케이션을 이용하여 손쉽게 확인할 수 있는 전체적인 시스템 구조를 설계하였다. 우리는 제안시스템의 평가를 위하여 프로토타입을 구현하여 주변 공기 오염도를 측정하였으며, 제안 방법의 적용 이전과 이후의 결과 비교를 통하여 시스템의 유효성을 확인하였다. 누구나 휴대할 수 있는 형태의 제품에 적용할 수 있는 기술이라는 점에서 앞으로 시스템의 활용범위는 무궁무진할 것으로 기대된다.