• KEPCO Journal on Electric Power and Energy
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• v.5 no.3
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• pp.157-163
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• 2019

K-BEMS System was introduced to reduce peak load and to save total energy of the 120 buildings that KEPCO headquarter and branch offices use. K-BEMS system is composed of PV, battery, and hybrid PCS. In this system, ESS, PV, lighting is used to save building energy based on demand prediction. Currently, neural network technique for short past data is applied to demand prediction, and fixed scheduling method by operator for ESS charging/discharging is used. To enhance this system, KEPCO research institute has carried out this K-BEMS research project for 3 years since January 2016. As the result of this project, we developed new real-time highly reliable building demand prediction technique with error free and optimized automatic ESS charging/discharging technique. Through several field test, we can certify the developed algorithm performance successfully. So we will describe the details in this paper.

• The Journal of Sustainable Design and Educational Environment Research
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• v.18 no.3
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• pp.28-38
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• 2019

For students and staff members who spend long periods of time in school, schools must meet a variety of needs such as learning, rest, experience, exchange, play, culture, meeting, and meals. The purpose of this study is to provide basic data aim at improving the school environment by investigating and analyzing the characteristics of middle school students'. For this purpose, the theoretical data collection : case studies and questionnaires, were conducted to analyze the correlation between student's activities and the space utilization of the school. First of all, a questionnaire survey was conducted on 301 middle school students in Ulsan. The t-test and ANOVA analysis were conducted on the questionnaire results to examine whether there was any difference in the perception of school space. The analysis showed significant correlation between interaction with school space according to the characteristics of students' activities. However, there are problems such as the use of space for various.

• Journal of The Korean Association For Science Education
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• v.41 no.5
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• pp.359-370
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• 2021

This study aims to identify the characteristics of the program that integrates maker education with science subjects and to explore the maker's competency expressed in students. To this study, a maker activity program based on scientific concepts was developed and applied to 20 first-year students at H University in a general chemistry experiment course, and activity data were analyzed. The analysis results of maker activities based on scientific concepts are as follows. First, students performed activities through the process of 'presentation of ideas,' 'selection and planning of ideas,' and 'prototyping'. In particular, it was confirmed that prototyping was divided into stages of "partial prototyping" and "full prototyping". Second, as characteristics of the activity, 'use of scientific concepts as logic for coding in the process of maker activities', 'in-depth understanding of scientific concepts', and 'inducing high achievement and interest through transfer of initiative in learning' were confirmed. Third, collaboration competency and making performance competency were frequently expressed in the process of activities, but human-centered competency were rarely expressed.

• International Journal of Computer Science & Network Security
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• v.21 no.8
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• pp.353-359
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• 2021

Information technology and the need for timely and effective communication during the Covid-19 have made most governments adopt technological approaches to provide their services. E-government services have been adopted by most governments especially in developed countries to quickly and effectively share information. This study discusses the reasons why governments in the Gulf region should develop a new model for information technology knowledge management practices. To achieve this, the author identified possible benefits of adopting information technology knowledge management practices and why most governments in the Gulf find it hard to adopt them. Knowledge management allows for learning, transfer as well as sharing of information between government organizations and citizens and with the development of technology, the effectiveness of electronic services can easily be achieved. Also, effective adoption of information technology can improve knowledge management with the help of techniques that enhance capture, storage, retrieval as well as sharing of information. The author used systematic literature review to select 28 journals and articles published post 2019. IEEE, Google Scholar and Science Direct were used to select potential studies from which 722 journals and articles were selected. Through screening and eligibility assessment, 21 articles were retained while the back and forward search had 7 more articles which were also included in the study. Using information gathered from these articles and journals a new conceptual model was developed to help improve information technology knowledge management for governments in the Gulf region to effectively deliver e-services during Covid-19. This model was developed based on the process of KM, Theory of Planned Behavior and Unified Theory of Acceptance and Use of Technology. Based on the developed model. From UTAUT model, performance expectancy, effort expectancy as well as social influence had a great impact.

• Journal of the Korean Society for Library and Information Science
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• v.53 no.3
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• pp.215-245
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• 2019

The purpose of this study is to derive evaluation elements on teen space in public libraries in Korea and to study current status and implications for teen space in public libraries. To this end, six items of space evaluation factors; Convenience, Accessibility, Safety, Diversity, Comfort and Emotionality - were derived based on the teen space guidelines by the Young Adult Library Service Association and previous studies. The research also conducted a case study on teen spaces of five public libraries in Seoul. As a result, teen space in libraries requires use guidance and convenience facilities, access to information resources, maintenance of user guidelines, various spaces for teens, pleasant library environment and learning motivation promotion, and provision space to support all necessary resources of teens.

• Journal of the Korea Institute of Information and Communication Engineering
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• v.23 no.5
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• pp.547-554
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• 2019

With the curriculum revision in 2015, informatics for secondary high schools was designated as mandatory. As a result, there is an increasing interest in programming in elementary and junior high schools as well as in universities. Arduino is one of the famous tools for programming education, and the usefulness of it has been proven through various case studies. However, existing Arduino-based kits have hardware-dependent drawbacks such as complicated wiring, poor scalability, etc. To overcome these problems, we proposed a kit design, which has a module-based structure, can be extended through one common interface, and can be used for learning at various levels. In this paper, we describe the implementation details of FRUTO kit and a software to use it, which satisfies the proposed design criteria. FRUTO kit has been determined in its current form through several design changes, and is under pre-test before launching.

• The Journal of the Institute of Internet, Broadcasting and Communication
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• v.21 no.2
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• pp.117-124
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• 2021

This study is a study to recognize hand movements using a neural network for wrist rehabilitation. The rehabilitation of the hand aims to restore the function of the injured hand to the maximum and enable daily life, occupation, and hobby. It is common for a physical therapist, an occupational therapist, and a security tool maker to form a team and approach a doctor for a hand rehabilitation. However, it is very inefficient economically and temporally to find a place for treatment. In order to solve this problem, in this study, patients directly use smart devices to perform rehabilitation treatment. Using this will be very helpful in terms of cost and time. In this study, a wrist rehabilitation dataset was created by collecting data on 4 types of rehabilitation exercises from 10 persons. Hand gesture recognition was constructed using a neural network. As a result, the accuracy of 93% was obtained, and the usefulness of this system was verified.

• Journal of the Korea Institute of Information and Communication Engineering
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• v.24 no.3
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• pp.384-390
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• 2020

The reverberation effect on the sound when producing movies or VR contents is a very important factor in the realism and liveliness. The reverberation time depending the space is recommended in a standard called RT60(Reverberation Time 60 dB). In this paper, we propose a scene recognition technique for automatic reverberation editing. To this end, we devised a classification model that independently trains color images and predicted depth images in the same model. Indoor scene classification is limited only by training color information because of the similarity of internal structure. Deep learning based depth information extraction technology is used to use spatial depth information. Based on RT60, 10 scene classes were constructed and model training and evaluation were conducted. Finally, the proposed SCR + DNet (Scene Classification for Reverb + Depth Net) classifier achieves higher performance than conventional CNN classifiers with 92.4% accuracy.

• Journal of Convergence for Information Technology
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• v.11 no.7
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• pp.14-20
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• 2021

Most accidents caused by road icing in winter lead to major accidents. Because it is difficult for the driver to detect the road icing in advance. In this work, we study how to accurately detect road traffic emerging risk using AutoML and CNN's ensemble model that use both structured and unstructured data. We train CNN-based road traffic emerging risk classification model using images that are unstructured data and AutoML-based road traffic emerging risk classification model using weather data that is structured data, respectively. After that the ensemble model is designed to complement the CNN-based classification model by inputting probability values derived from of each models. Through this, improves road traffic emerging risk classification performance and alerts drivers more accurately and quickly to enable safe driving.

• Journal of the Korea Institute of Information and Communication Engineering
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• v.24 no.1
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• pp.22-27
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• 2020

Recently, as the number of households raising pets increases due to the increase of single households, there is a need for a system for monitoring the status or behavior of pets. There are regional limitations in the monitoring of pets using domestic CCTVs, which requires a large number of CCTVs or restricts the behavior of pets. In this paper, we propose a mobile system for detecting and tracking cats using deep learning to solve the regional limitations of pet monitoring. We use YOLO (You Look Only Once), an object detection neural network model, to learn the characteristics of pets and apply them to Raspberry Pi to track objects detected in an image. We have designed a mobile monitoring system that connects Raspberry Pi and a laptop via wireless LAN and can check the movement and condition of cats in real time.