• Journal of Internet of Things and Convergence
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• v.8 no.5
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• pp.93-98
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• 2022

With the development of new digital technologies, research on various learning tools is being actively conducted. These learning tools are also being developed so that they can be applied to various environments by applying the technology of artificial intelligence or using smart functions to which big data technology is applied. These smart learning tools are contributing a lot to increasing educational effectiveness and learning efficiency. Recently, various learning tools have been applied in universities, and solutions for smart learning from smart attendance are introduced to improve student learning efficiency. This study intends to propose a design for a smart learning tool that can increase the efficiency of project progress and increase the scalability of the results when conducting a company's customized project through such a university's smart learning tool. The proposed smart learning tool is expected to have the advantage of being able to easily adapt to the practical business project as the company-customized projects that can improve practical skills are smoothly used as a learning tool. The proposed project-based smart learning tool model is later built as a related LMS and applied to actual project progress to check its utility, and to revise and supplement the proposed smart learning tool model to provide a project-based smart learning function want to strengthen.

• Electronics and Telecommunications Trends
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• v.31 no.5
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• pp.1-10
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• 2016

빅데이터를 통한 학습, GPU를 활용한 고속 컴퓨팅 및 다양한 알고리즘 개발과 더불어 기계학습은 다양한 분야에서 종래에 이루어내지 못한 뛰어난 성과를 달성하고 있다. 그동안 상용화된 통신 시스템에서 기계학습이 활성화되지 못했지만, 전례없는 다양한 서비스와 단말을 아우르는 5G 통신에서는 더욱 적극적으로 활용될 것으로 예상된다. 기계학습은 링크 적응 등 무선접속기술, 다양한 망이 혼재된 이종망 기술, 트래픽 분류 등을 위한 네트워크 기술, 침입 탐지를 위한 보안 기술 등 다양한 통신기술에서 연구됐다. 또한, 최근에는 유럽의 Public Private Partnership(5G PPP) 프로젝트를 비롯하여 다양한 그룹에서 활발히 연구되고 있으며, 컬컴/노키아/에릭슨 등 통신 관련 기업들도 적극적인 투자를 하고 있다. 본고에서는 기계학습 관련 통신기술, 연구그룹 및 기업 동향을 소개하고, 이를 통해 5G 통신 적용 가능성을 짚어본다.

• Information Systems Review
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• v.14 no.2
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• pp.47-63
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• 2012

The concept of data warehousing was born in the 1970-80s at the same time when Wal-Mart's growing database gave birth to its need to view records in a more effective way. As the world's largest retail warehouse, Wal-Mart represents the world's largest data warehouse. A large portion of the discussionaround Wal-Mart's database management heretofore has only been process-centric, however, not its data per se. The study largely involves technical concepts around database and takes a deep look at Wal-Mart's chronicle of pre-implementation (preparation), implementation, and post-implementation (evaluation) of the data warehousing project. The highlight underlies how Wal-Mart acted against solving endless problems and was able to gear their data management to business contribution. By revisiting their data warehousing project case from a current point of view, we expect their lessons to be still available and applicable. With the renewed interest in (big) data and business intelligence, Wal-Mart's high respect for data and technology holds a lot more meaning than a couple of decades ago.

• Journal of Digital Convergence
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• v.13 no.12
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• pp.117-124
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• 2015

As the acceptance of statistical analysis has been increased because of Big Data, the needs for an advanced second generation of statistical analysis method like Structural Equation Model are also increasing. This study suggests how R-Program, as open software, can be utilized when Partial Least Square Model, one of the SEMs, is applied to statistical analysis. R is a free software as a part of GNU projects as well as a powerful and useful tool for statistical analysis including Big Data. The study utilized R and SmartPLS, a representative statistical package of PLS-SEM, and analyzed internal consistency reliability, convergent validity, and discriminant validity of the measurement model. The study also analyzed path coefficients and moderator effects of the structural model and compared the results, respectively. The results indicated that R showed the same results with SmartPLS on the measurement model and the structural model. Therefore, the study confirmed that R could be a powerful tool that is alternative to a commercial statistical package in the future.

• Journal of Digital Convergence
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• v.16 no.11
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• pp.137-147
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• 2018

To prepare for and implement policies for the Fourth Industrial Revolution, which is characterized by convergence, super-connectivity, and AI, this study summarized the effects and characteristics of individual technologies on our society and discussed the issues with humanity and social science perspectives. As a result, in terms of AI technology, the issues of job losses, project-type works, basic income and robot taxes, accountability of AI, and algorithm inequality were dealt with. Security, cyber hacking and privacy infringement issues were highlighted in big-data technology. In the part of block-chain and bioengineering, the society of decentralization, the concentration, digital divide, and ethical issues were discussed. On-demand economic aspects highlighted the problems of civil ethics and human commercialization. Lastly, the development of VR is discussed including side effects such as cyber-syndrom, avoidance of reality, and so on.

• KIPS Transactions on Software and Data Engineering
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• v.3 no.9
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• pp.349-354
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• 2014

Since Hadoop which is the Big-data processing platform was announced, SQL-on-Hadoop is the spotlight as the technique to analyze data using SQL on Hadoop. Tajo created by Korean programmers has recently been promoted to Top-Level-Project status by the Apache in April and has been paid attention all around world. Despite a sensible change caused by Hadoop's appearance in DW market, researches of those performance is insufficient. Thus, this study has been conducted to help choose a DW solution based on SQL-on-Hadoop as progressing the test on comparison analysis of RDBMS and Tajo. It has shown that Tajo based on Hadoop is more superior than RDBMS if it is used with accurate strategy. In addition, open-source project Tajo is expected not only to achieve improvements in technique due to active participation of many developers but also to be in charge of an important role of DW in the filed of data analysis.

• KIPS Transactions on Computer and Communication Systems
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• v.9 no.9
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• pp.207-212
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• 2020

The amount of data has increased significantly due to advances in technology, and various big data processing platforms are emerging, to handle it. Among them, the most widely used platform is Hadoop developed by the Apache Software Foundation, and Hadoop is also used in the IoT field. However, the existing Hadoop-based IoT sensor data collection and analysis environment has a problem of overloading the name node due to HDFS' Small File, which is Hadoop's core project, and it is impossible to update or delete the imported data. This paper uses Apache Kudu and Impala to design Lambda Architecture. The proposed Architecture classifies IoT sensor data into Cold-Data and Hot-Data, stores it in storage according to each personality, and uses Batch-View created through Batch and Real-time View generated through Apache Kudu and Impala to solve problems in the existing Hadoop-based IoT sensor data collection analysis environment and shorten the time users access to the analyzed data.

• Journal of Intelligence and Information Systems
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• v.21 no.1
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• pp.143-159
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• 2015

Predicting IT trends has been a long and important subject for information systems research. IT trend prediction makes it possible to acknowledge emerging eras of innovation and allocate budgets to prepare against rapidly changing technological trends. Towards the end of each year, various domestic and global organizations predict and announce IT trends for the following year. For example, Gartner Predicts 10 top IT trend during the next year, and these predictions affect IT and industry leaders and organization's basic assumptions about technology and the future of IT, but the accuracy of these reports are difficult to verify. Social media data can be useful tool to verify the accuracy. As social media services have gained in popularity, it is used in a variety of ways, from posting about personal daily life to keeping up to date with news and trends. In the recent years, rates of social media activity in Korea have reached unprecedented levels. Hundreds of millions of users now participate in online social networks and communicate with colleague and friends their opinions and thoughts. In particular, Twitter is currently the major micro blog service, it has an important function named 'tweets' which is to report their current thoughts and actions, comments on news and engage in discussions. For an analysis on IT trends, we chose Tweet data because not only it produces massive unstructured textual data in real time but also it serves as an influential channel for opinion leading on technology. Previous studies found that the tweet data provides useful information and detects the trend of society effectively, these studies also identifies that Twitter can track the issue faster than the other media, newspapers. Therefore, this study investigates how frequently the predicted IT trends for the following year announced by public organizations are mentioned on social network services like Twitter. IT trend predictions for 2013, announced near the end of 2012 from two domestic organizations, the National IT Industry Promotion Agency (NIPA) and the National Information Society Agency (NIA), were used as a basis for this research. The present study analyzes the Twitter data generated from Seoul (Korea) compared with the predictions of the two organizations to analyze the differences. Thus, Twitter data analysis requires various natural language processing techniques, including the removal of stop words, and noun extraction for processing various unrefined forms of unstructured data. To overcome these challenges, we used SAS IRS (Information Retrieval Studio) developed by SAS to capture the trend in real-time processing big stream datasets of Twitter. The system offers a framework for crawling, normalizing, analyzing, indexing and searching tweet data. As a result, we have crawled the entire Twitter sphere in Seoul area and obtained 21,589 tweets in 2013 to review how frequently the IT trend topics announced by the two organizations were mentioned by the people in Seoul. The results shows that most IT trend predicted by NIPA and NIA were all frequently mentioned in Twitter except some topics such as 'new types of security threat', 'green IT', 'next generation semiconductor' since these topics non generalized compound words so they can be mentioned in Twitter with other words. To answer whether the IT trend tweets from Korea is related to the following year's IT trends in real world, we compared Twitter's trending topics with those in Nara Market, Korea's online e-Procurement system which is a nationwide web-based procurement system, dealing with whole procurement process of all public organizations in Korea. The correlation analysis show that Tweet frequencies on IT trending topics predicted by NIPA and NIA are significantly correlated with frequencies on IT topics mentioned in project announcements by Nara market in 2012 and 2013. The main contribution of our research can be found in the following aspects: i) the IT topic predictions announced by NIPA and NIA can provide an effective guideline to IT professionals and researchers in Korea who are looking for verified IT topic trends in the following topic, ii) researchers can use Twitter to get some useful ideas to detect and predict dynamic trends of technological and social issues.

• The Journal of the Institute of Internet, Broadcasting and Communication
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• v.23 no.4
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• pp.189-196
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• 2023

As the manufacturing paradigm shifts, various collaborative robots are creating new markets. Demand for collaborative robots is increasing in all industries for the purpose of easy operation, productivity improvement, and replacement of manpower who do simple tasks compared to existing industrial robots. However, accidents frequently occur during work caused by collaborative robots in industrial sites, threatening the safety of workers. In order to construct an industrial site through robots in a human-centered environment, the safety of workers must be guaranteed, and there is a need to develop a collaborative robot guard system that provides reliable communication without the possibility of dispatch. It is necessary to double prevent accidents that occur within the working radius of cobots and reduce the risk of safety accidents through sensors and computer vision. We build a system based on OPC UA, an international protocol for communication with various industrial equipment, and propose a collaborative robot guard system through image analysis using ultrasonic sensors and CNN (Convolution Neural Network). The proposed system evaluates the possibility of robot control in an unsafe situation for a worker.

• Proceedings of the Korean Society of Computer Information Conference
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• 2021.01a
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• pp.307-308
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• 2021

2020년 7월 정부는 포스트 코로나 시대를 선언하며, 한국판 뉴딜 정책을 발표하였다. 한국판 뉴딜은 디지털인프라 구축, 비대면 산업육성, SOC 디지털화를 기본방향으로 내세웠으며 빅데이터, 인공지능(AI), 사물인터넷(IoT) 등 4차산업 핵심기술의 육성방안을 제시하였다. 최근 인천공항은 한국판 뉴딜 정부정책에 부응하기 위해 인천공항 K-뉴딜 프로젝트를 추진 중이며, 세부 전략과제로 자산관리의 디지털전환을 위한 IoT기반 스마트 자산관리시스템을 구축 중이다. IoT기반 스마트자산관리시스템은 인천공항에 위치한 실내외 이동형 자산에 대해 끊김없는 위치정보를 제공하는 시스템으로 기존 시스템(RFID) 대비 약 4억 원의 인적, 물적 자원을 절감하는 효과를 나타낼 것으로 예상된다. 본 논문에서는 IoT기반 스마트 자산관리시스템의 핵심기술인 실내외 연속측위 스마트 트래커와 네트워크의 구성, 저전력 위치정보 제공방법을 제시한다.