• Journal of Digital Convergence
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• v.19 no.8
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• pp.319-325
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• 2021

With the advancement of wireless technology and the rapid growth of the infrastructure of mobile communication technology, systems applying AI-based platforms are drawing attention from users. In particular, the system that understands users' tastes and interests and recommends preferred items is applied to advanced e-commerce customized services and smart homes. However, there is a problem that these recommendation systems are difficult to reflect in real time the preferences of various users for tastes and interests. In this research, we propose a Fuzzy-AHP-based movies recommendation system using the Gated Recurrent Unit (GRU) language model to address a problem. In this system, we apply Fuzzy-AHP to reflect users' tastes or interests in real time. We also apply GRU language model-based models to analyze the public interest and the content of the film to recommend movies similar to the user's preferred factors. To validate the performance of this recommendation system, we measured the suitability of the learning model using scraping data used in the learning module, and measured the rate of learning performance by comparing the Long Short-Term Memory (LSTM) language model with the learning time per epoch. The results show that the average cross-validation index of the learning model in this work is suitable at 94.8% and that the learning performance rate outperforms the LSTM language model.

• Korean Association of Arts Management
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• no.59
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• pp.73-99
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• 2021

Free admission policies have been gradually extended for the public to use cultural facilities free of charge, which lowered the barriers to use those facilities and has a great effect on increasing visitor demands. However, the annual number of visitors which is open to the public isn't quite accurate and varies from institution to institution, which means just a head count. Especially people counter overestimates the number of visitors because it counts visitors in duplicate. Therefore, the purpose of this study is to prepare effective way of grasping the number of visitors using cultural infrastructure. First, comparable number of visitors should be measured by defining the notion of visitor clearly, which has been measured vaguely. Secondly, the problem of duplicate count, which is considered the most problematic, should be solved. Thirdly, the various analysis of visitor behavior should be conducted to provide a high-quality service. To work out the problems above, new measurement will be presented here. This study suggests a state-of-the-art wireless signal-based measurement that could eliminate the duplicate data by collecting MAC address -smart device's distinct signal value. And it also could analyze diverse visitor behaviors by understanding a flow of visitor traffic, duration of stay and revisitation. I would like to examine the possibility and effectiveness of this new measurement by testing it.

• Journal of the Korea Society of Computer and Information
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• v.27 no.2
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• pp.171-177
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• 2022

In this paper, we propose a service method that can provide insight into multi-source agricultural data, way to cluster environmental factor which supports data analysis according to time flow, and curate crop environmental factors. The proposed curation service consists of four steps: collection, preprocessing, storage, and analysis. First, in the collection step, the service system collects and organizes multi-source agricultural data by using an OpenAPI-based web crawler. Second, in the preprocessing step, the system performs data smoothing to reduce the data measurement errors. Here, we adopt the smoothing method for each type of facility in consideration of the error rate according to facility characteristics such as greenhouses and open fields. Third, in the storage step, an agricultural data integration schema and Hadoop HDFS-based storage structure are proposed for large-scale agricultural data. Finally, in the analysis step, the service system performs DTW-based time series classification in consideration of the characteristics of agricultural digital data. Through the DTW-based classification, the accuracy of prediction results is improved by reflecting the characteristics of time series data without any loss. As a future work, we plan to implement the proposed service method and apply it to the smart farm greenhouse for testing and verification.

• Journal of Korean Elementary Science Education
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• v.40 no.4
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• pp.443-459
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• 2021

In this study, a TPACK-based STEAM program was developed and applied under the theme of excretory organs in the 'Structure and Function of Our Body' of the elementary science curriculum. The program was produced and conducted through curriculum analysis and learning goal detailing, learning environment analysis, teaching·learning method and technology selection, TPACK elements arrangement and teaching·learning material development, application and effectiveness verification. Teacher's TPACK considered in STEAM program design process is content knowledge (appearance and work of excretory organs), pedagogical knowledge (STEAM, problem-based learning, research learning, discussion learning, cooperative learning, scientific writing) and technology knowledge (3D printer and smart device application technology). The program consisted of a total of 8 hours of project learning activities and was applied to 29 students in the fifth grade as an experimental group. A program of the same theme developed mainly from textbooks was applied to 27 students in the fifth grade of a comparison group. As a result of the application of the program, the experimental group showed significant improvement in creative problem-solving ability and scientific attitude compared to the comparison group, and the class satisfaction with the STEAM program was also high. However, there was no significant difference in academic achievement ability.

• Journal of the Korea Convergence Society
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• v.12 no.11
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• pp.193-206
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• 2021

Artificial Intelligence (AI) has been inserted into people's lives through Intelligent Virtual Assistants (IVA), like Alexa. Moreover, intelligent systems have expanded to design studios. This research delves into designers' perspectives on developing AI-based practices and examines the challenges of adopting future intelligent design assistants. We surveyed UX/UI professionals in Brazil to understand how they use IVAs and AI design tools. We also explored a scenario featuring the use of Alexa Sensei, a hypothetical voice-controlled AI-based design assistant mixing Alexa and Adobe Sensei characteristics. The findings indicate respondents have had limited opportunities to work with AI, but they expect intelligent systems to improve the efficiency of the design process. Further, majority of the respondents predicted that they would be able to collaborate creatively with AI design systems. Although designers anticipated challenges in natural language interaction, those who already adopted IVAs were less resistant to the idea of working with Alexa Sensei as an AI design assistant.

• 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.

• Journal of the Korea Institute of Building Construction
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• v.23 no.2
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• pp.175-185
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• 2023

Upon analyzing labor productivity in the construction industry across OECD countries, it was found that in 2019, labor productivity per employee in the South Korean construction industry was lower than that of major developed countries when adjusted for purchasing power parity(PPP). Specifically, when benchmarked against other countries at a base of 100, South Korea scored 76.9 in the United States, 88.4 in Japan, and 85.1 in the OECD average. Notably, South Korea ranked 25th in labor productivity per employee in the construction industry among 35 OECD countries in 2019, indicating a low standing. A comparative analysis of the construction market size and labor productivity in the construction industry across OECD countries revealed that larger construction markets did not necessarily correlate with higher labor productivity. To enhance labor productivity in the construction industry, this study proposed the active implementation of smart construction technology at construction sites and the promotion of on-site assembly work using off-site construction(OSC) technology, rather than traditional on-site labor. Moreover, it was recommended that the development of modular construction methods and technologies be expanded. In the future, if off-site production methods and modules are further developed through advanced robotics and factory automation, labor productivity is anticipated to increase due to the restructuring of production methods, such as manufacturing.

• Journal of the Korea Institute of Building Construction
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• v.23 no.3
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• pp.305-313
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• 2023

With an increasing interest in the commercialization of research results in the present societal climate, especially in the construction industry, preliminary product analysis plays a critical role when introducing a new product to the market. It significantly influences the product's success or failure. In this context, this study aims to investigate the utility of Importance-Performance Analysis (IPA) as a management strategy tool for preliminary analysis in the commercialization of new architectural technologies. The study specifically assesses a smart ball product engineered for pipeline inspection. The evaluation is carried out based on product quality, convenience, and usability categories. Seventeen factors are recognized as sub-items, and a survey is conducted among relevant experts and consumer groups. From the survey, four key items are chosen: "Keep up the good work," "Concentrate here," "Low priority," and "Possible overkill." Suitable strategic measures are derived for each item. By conducting a correlation analysis between product importance and performance, this study offers a method to establish priority directions for future development. This analysis assists in identifying areas that necessitate improvement or additional focus to increase the product's commercial potential. On the whole, this study contributes to understanding and applying Importance-Performance Analysis as a valuable tool in the preliminary analysis and commercialization of novel technologies in the field of architecture.

• SUVANNABHUMI
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• v.10 no.2
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• pp.181-213
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• 2018

How to study Southeast Asia (SEA)? The need to explore and identify methodologies for studying SEA are inherent in its multifaceted subject matter. At a minimum, the region's rich cultural diversity inhibits both the articulation of decisive defining characteristics and the training of scholars who can write with confidence beyond their specialisms. Consequently, the challenges of understanding the region remain and a consensus regarding the most effective approaches to studying its history, identity and future seem quite unlikely. Furthermore, "Area Studies" more generally, has proved to be a less attractive frame of reference for burgeoning scholarly trends. This paper will propose a new tool to help address these challenges. Even though the science of artificial intelligence (AI) is in its infancy, it has already yielded new approaches to many commercial, scientific and humanistic questions. At this point, AI has been used to produce news, generate better smart phones, deliver more entertainment choices, analyze earthquakes and write fiction. The time has come to explore the possibility that AI can be put at the service of the study of SEA. The paper intends to lay out what would be required to develop SEABOT. This instrument might exist as a robot on the web which might be called upon to make the study of SEA both broader and more comprehensive. The discussion will explore the financial resources, ownership and timeline needed to make SEABOT go from an idea to a reality. SEABOT would draw upon artificial neural networks (ANNs) to mine the region's "Big Data", while synthesizing the information to form new and useful perspectives on SEA. Overcoming significant language issues, applying multidisciplinary methods and drawing upon new yields of information should produce new questions and ways to conceptualize SEA. SEABOT could lead to findings which might not otherwise be achieved. SEABOT's work might well produce outcomes which could open up solutions to immediate regional problems, provide ASEAN planners with new resources and make it possible to eventually define and capitalize on SEA's "soft power". That is, new findings should provide the basis for ASEAN diplomats and policy-makers to develop new modalities of cultural diplomacy and improved governance. Last, SEABOT might also open up avenues to tell the SEA story in new distinctive ways. SEABOT is seen as a heuristic device to explore the results which this instrument might yield. More important the discussion will also raise the possibility that an AI-driven perspective on SEA may prove to be even more problematic than it is beneficial.

• Design Convergence Study
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• v.16 no.5
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• pp.1-20
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• 2017

Cardio-cerebrovascular disease is one of the chronic diseases that often attack people in Korea, and in fact, it ranks second in terms of death rate. This disease can be prevented by improving lifestyle, usual health care is important. But, in Korea most of the prevention or management programs adopt passive methods like using guide books or giving lectures, so it is not very effective in preventing the disease. Presently, the smart health care market is being developed in Korea and overseas. As an example, quantified self is being spread through wearable devices which are intended to measure each individual's health conditions and quantify body data into numbers for bettering habits. Accordingly, this author will explore and discuss wearable health care devices so as to prevent and manage cardio-cerebrovascular disease in a more active way. First, this study has classified wearable health care devices presently commercialized or related with cardio-cerebrovascular disease into wrist, clothes, or attaching types by the way of their attachment and analyzed them. After that, summing that up, this author performed cross-tabulations with other ways of preventing cardio-cerebrovascular disease. This will contribute to improving one's health care behavior about disease more actively and also work as an active interdisciplinary mechanism in research dealing with how to prevent disease afterwards.