• Journal of the Institute of Electronics and Information Engineers
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• v.53 no.2
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• pp.3-9
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• 2016

In this paper, we propose a Radio over Fiber system for small cell applications and for mobile fronthaul networks supporting cloud-radio access networks(RAN). We built a system with a downlink employing orthogonal frequency division multiplexing (OFDM) techniques and an uplink using single carrier-frequency multiple access(SC-FDMA). System parameters are evaluated for various subcarrier modulations and the results of link performance measurements are analyzed.

• Proceedings of the Korean Institute of Information and Commucation Sciences Conference
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• 2014.05a
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• pp.631-634
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• 2014

When to build a Web and Cloud Computing environment, it is essential to used a database system. Database systems includes commercial programs, such as Oracle and MS-SQL, but also similar to the performance of commercial applications, there are many free programs. In particular, PostgreSQL, MySQL, MariaDB are no costs, but the source is open to the public can be applied to a variety of environments. This paper presents an open source relational database management system, the trends are examined.

• Journal of Korea Multimedia Society
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• v.25 no.2
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• pp.325-334
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• 2022

Digital twin has the advantages of quality improvement and cost reduction, so it is widely applied to various industries. In this paper, a method to implement the major technologies of digital twin easily and quickly is presented. These include data management and relay servers, real-time monitoring applications including remote control interfaces, and direct connection protocols for video streaming. In addition, an algorithm for controlling a two-wheeled vehicle with a 2D interface is also proposed. The implemented system performs near real-time synchronization between the real environment and the virtual space. The delay time that occurs in remote control of the vehicle in the real environment was compared with the results of applying the proposed delay time reduction method. In addition, in the case of 2D interface-based control, an algorithm that can guarantee the user experience was implemented and applied to the actual environment and verified through experiments.

• The Journal of Korea Robotics Society
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• v.18 no.2
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• pp.135-142
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• 2023

Light detection and ranging (LiDAR) sensors have been most widely used in terrestrial robotic applications because they can provide dense and precise measurements of the surrounding environments. However, the reliability of LiDAR measurements can considerably vary due to the different reflectivities of laser beams to the reflecting surface materials. This study presents a robust LiDAR-based mapping method for the varying laser reflectivities in indoor environments using the framework of simultaneous localization and mapping (SLAM). The proposed method can minimize the performance degradations in the SLAM accuracy by checking and discarding potentially unreliable LiDAR measurements in the SLAM front-end process. The gaps in point-cloud maps created by the proposed approach are filled by a Gaussian process regression method. Experimental results with a mobile robot platform in an indoor environment are presented to validate the effectiveness of the proposed methodology.

• Annual Conference of KIPS
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• 2023.05a
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• pp.58-59
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• 2023

클라우드 애플리케이션의 성능 모니터링 방법에는 클라우드 소프트웨어 스택의 인프라, 플랫폼 및 애플리케이션 계층에서 수집한 시계열 데이터 분석이라는 방법이 존재한다. 클라우드 컴퓨팅 환경에서 운영되는 서비스 간의 런타임 종속성을 분석하는 것은 클라우드 리소스 관리를 수행하기 위해 필요한 단계이다. 본 논문에서는 Bi-LSTM 기법을 활용해 클라우드 애플리케이션의 관계를 분석하고 종속성을 찾아 모니터링 성능을 향상시키는 시스템을 제안한다. 제안하는 시스템은 클라우드 스택의 모든 계층으로부터 시계열 데이터를 수집하여 인공지능 모델을 훈련, 재훈련 및 업데이트 과정을 진행한다. 본 논문에서는 Bi-LSTM 모델을 활용하여 훈련 중에 학습된 성능 메트릭 간의 종속성을 발견한다.

• International Journal of Internet, Broadcasting and Communication
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• v.16 no.2
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• pp.193-202
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• 2024

As companies specialize, they use more modern applications, but they still rely on legacy systems and data access is limited by data silos. In this paper, we propose the Fabricator system, a design system for metadata based on Data Fabric that plays a key role in the data orchestration layer consisting of three layers: Sources Engine, Workload Builder, and Data Fabric Ingestion, thereby achieving meaningful integration of data and information. Provides useful insights to users through conversion. This allows businesses to efficiently access and utilize data, overcoming the limitations of legacy systems.

• Electronics and Telecommunications Trends
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• v.39 no.5
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• pp.12-20
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• 2024

As more devices are used across various industries and their performance improves, artificial intelligence applications are being increasingly adopted. Hence, the rapid development of neural networks suitable for diverse devices can determine the competitiveness of companies. Machine learning operations (MLOps), which constitute a framework that supports neural network generation and its immediate application to devices, have become necessary for the development of artificial intelligence. Currently, most MLOps are provided by major companies such as Google, Amazon, and Microsoft, which provide cloud services supported by large-scale computing power. In addition, various services are provided by the open-source project Kubeflow. We examine basic concepts and technology trends in MLOps and unveil additional functions required in industry.

• Current Optics and Photonics
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• v.8 no.5
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• pp.508-514
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• 2024

This paper presents a deep learning-based weight sensor, using optical speckle patterns of multimode fiber, designed for real-time intrusion detection. The weight sensor has been trained to identify 11 distinct speckle patterns, ranging in weight from 0.0 kg to 2.0 kg, with an interval of 200 g between each pattern. The estimation for untrained weights is based on the generalization capability of deep learning. This results in an average weight error of 243.8 g. Although this margin of error precludes accurate weight measurement, the system's ability to detect abrupt weight changes makes it a suitable choice for intrusion detection applications. The weight sensor is integrated with the Google Teachable Machine, and real-time intrusion notifications are facilitated by the ThingSpeak^TM cloud platform, an open-source Internet of Things (IoT) application developed by MathWorks.

• Journal of Broadcast Engineering
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• v.22 no.1
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• pp.107-117
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• 2017

Recently, IoT applications are being deployed in Smart TVs, and these IoT applications are using smart TVs as application platforms rather than broadcast platforms. With the advent of Hybrid broadcast technologies, now it becomes available to develop IoT applications which are coupled to the broadcast information. However, the existing IoT services are not suitable for Hybrid broadcast application since they are built on cloud and require various protocol implementations. In this paper, a Fog Computing-based architecture for hybrid broadcast application is proposed. Instead of accessing IoT services from hybrid broadcast app directly, the proposed architecture places Fog Applet Server between them and distribute loads of hybrid broadcast app to the Fog Applet. The proposed architecture is implemented as a service to control IoT device with hybrid application.

• Communications of Mathematical Education
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• v.34 no.4
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• pp.545-561
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• 2020

The purpose of this study is to investigate the applications and possibilities of major programs that provide services using artificial intelligence in mathematics education. For this study, related papers, reports, and materials were collected and analyzed, focusing on materials mostly published within the last five years. The researcher searched the keywords of "artificial intelligence", "artificial intelligence", "AI" and "mathematics education" independently or in combination. As a result of the study, artificial intelligence for mathematics education was mostly supporting learners' personalized mathematics learning, defining it as an auxiliary role to support human mathematics teachers, and upgrading the technology of not only cognitive aspects but also affective aspects. As suggestions, the researcher argued that followings are necessary: Research for the establishment of an elaborate artificial intelligence mathematical system, discovery of artificial intelligence technology for appropriate use to support mathematics education, development of high quality of mathematics contents for artificial intelligence, and the establishment and operation of a cloud-based comprehensive system for mathematics education. The researcher proposed that continuous research to effectively help students study mathematics using artificial intelligence including students' emotional or empathetic abilities, and collaborative learning, which is only possible in offline environments. Also, the researcher suggested that more sophisticated materials should be developed for designing mathematics teaching and learning by using artificial intelligence.