• Journal of the Architectural Institute of Korea Planning & Design
• /
• v.35 no.8
• /
• pp.23-34
• /
• 2019

The façade, a fundamental function as a skin that protects human life from external environment such as cold and hot weather, snow, rain, and wind, etc, has served as a media for communication between indoor space of the building and outside space. From the media for communication point of view, the approach to envelope design, in which environmental elements are transmitted internally through the filtering of external environments, has been evolving in various ways from the past to the present. Today, modern architecture technologies including curtain wall systems and user-friendly computer programming and environmental analysis programs demonstrate a differentiated approach to envelope design related to the indoor environment. For this reason, it is worth noting that the envelope design factors and trends that appear variously in the UNStudio's projects before and after the 2000s. The factors reflected in the envelop design in conjunction with the indoor environment obtained through the case study of the UNStudio's office projects were daylight environment, thermal environment, ventilation, noise, privacy and view, and consideration for daylight environment and thermal environment was reflected in many cases through the case study. Looking at the changes in the diagrams in order of year, it can be seen that the envelope design using the environmental analysis tool has been performed since 2006. This is a clue to show the envelop design changes from the conceptual method to the data-based one. The diagrams and analysis results related to the envelop design showed that the thermal environment related to solar radiation was the most, and no diagrams and analysis related to the indoor illumination were found. Since 2010, PV panel installation has been shown in the envelope design, which can be found in the increased efficiency of PV panels due to the technological advances and the decrease in production cost.

• Journal of the Korea Institute of Information and Communication Engineering
• /
• v.24 no.11
• /
• pp.1463-1469
• /
• 2020

Multimedia information, including video and voice, is highly utilized in that it is easily understood by people. For this reason, applications have been studied which store multimedia information in IoT devices and transmit information in conjunction with smartphones. The problem is that the size of information can be larger than the capacity of IoT devices due to video and image. In this paper, the multimedia content design technique, which takes into account the limitations of storage capacity, was studied when there is a limit of storage capacity. Considering that the video has a higher understanding of information than text, while the capacity is larger, the solution between information comprehension and capacity is sought. The size of static and dynamic media is a variable and the harm is solved in accordance with the linear planning method. Case studies have shown that the design techniques of this paper are useful.

• KSII Transactions on Internet and Information Systems (TIIS)
• /
• v.15 no.7
• /
• pp.2496-2512
• /
• 2021

The requirements for powerful computing capability, high capacity, low latency and low energy consumption of emerging services, pose severe challenges to the fifth-generation (5G) network. As a promising paradigm, mobile edge networks can provide services in proximity to users by deploying computing components and cache at the edge, which can effectively decrease service delay. However, the coexistence of heterogeneous services and the sharing of limited resources lead to the competition between various services for multiple resources. This paper considers two typical heterogeneous services: computing services and content delivery services, in order to properly configure resources, it is crucial to develop an effective offloading and caching strategies. Considering the high energy consumption of 5G base stations, this paper considers the hybrid energy supply model of traditional power grid and green energy. Therefore, it is necessary to design a reasonable association mechanism which can allocate more service load to base stations rich in green energy to improve the utilization of green energy. This paper formed the joint optimization problem of computing offloading, caching and resource allocation for heterogeneous services with the objective of minimizing the on-grid power consumption under the constraints of limited resources and QoS guarantee. Since the joint optimization problem is a mixed integer nonlinear programming problem that is impossible to solve, this paper uses deep reinforcement learning method to learn the optimal strategy through a lot of training. Extensive simulation experiments show that compared with other schemes, the proposed scheme can allocate resources to heterogeneous service according to the green energy distribution which can effectively reduce the traditional energy consumption.

• International Journal of Computer Science & Network Security
• /
• v.21 no.2
• /
• pp.212-220
• /
• 2021

The objectives of this research were to identify the digital competencies required for information science specialists at Saudi universities and to examine whether there existed conspicuous differences in the standpoint of these specialists due to years of work experience with regard to the importance of these competencies. A descriptive analytical method was used to accomplish these objectives while extracting the required digital competency list and ascertaining its importance. The research sample comprised 24 experts in the field of information science from several universities in the Kingdom of Saudi Arabia. The participants in the sample were asked to complete a questionnaire prepared to acquire the pertinent data in the period between January 5, 2021 and January 20, 2021. The results reveal that the digital competencies required for information science specialists at Saudi universities encompass general features such as the ability to use computer, Internet, Web2, Web3, and smartphone applications, digital learning resource development, data processing (big data) and its sharing via the Internet, system analysis, dealing with multiple electronic indexing applications and learning management systems and its features, using electronic bibliographic control tools, artificial intelligence tools, cybersecurity system maintenance, ability to comprehend and use different programming languages, simulation, and augmented reality applications, and knowledge and skills for 3D printing. Furthermore, no statistically significant differences were observed between the mean ranks of scores of specialists with less than 10 years of practical experience and those with practical experience of 10 years or more with regard to conferring importance to digital competencies.

• Journal of the Korea Institute of Information Security & Cryptology
• /
• v.30 no.6
• /
• pp.1053-1065
• /
• 2020

With the recent development of hardware performance and artificial intelligence technology, sophisticated fake videos that are difficult to distinguish with the human's eye are increasing. Face synthesis technology using artificial intelligence is called Deepfake, and anyone with a little programming skill and deep learning knowledge can produce sophisticated fake videos using Deepfake. A number of indiscriminate fake videos has been increased significantly, which may lead to problems such as privacy violations, fake news and fraud. Therefore, it is necessary to detect fake video clips that cannot be discriminated by a human eyes. Thus, in this paper, we propose a deep-fake detection model applied with Bidirectional Convolution LSTM and Attention Module. Unlike LSTM, which considers only the forward sequential procedure, the model proposed in this paper uses the reverse order procedure. The Attention Module is used with a Convolutional neural network model to use the characteristics of each frame for extraction. Experiments have shown that the model proposed has 93.5% accuracy and AUC is up to 50% higher than the results of pre-existing studies.

• Journal of the Korea Institute of Information and Communication Engineering
• /
• v.23 no.12
• /
• pp.1588-1595
• /
• 2019

This paper presents the technique on structuring information of the diagram repository for UML diagrams. Because object interactions are the body of object-oriented programming, this paper handles especially the sequence diagrams and class diagrams among UML diagrams. Based on class diagrams, sequence diagrams represent the procedure of object interactions in run-time and then the corresponding codes are generated from the contents of those sequence diagrams. To do this work, this paper presents a method to construct the information repository for generating code from the contents of sequence diagrams. This paper classifies the five message types of sequence diagrams and then extracts the needed information including items and values on the corresponding message types for constructing message repositories. Because sequence diagram is composed of messages included, the final repository is constructed by collecting each of structured repositories on messages sequentially.

• Journal of the Korea Society of Computer and Information
• /
• v.25 no.12
• /
• pp.165-172
• /
• 2020

Recently, due to exponential growth of access information on the web, the importance of predicting a user's next web page use has been increasing. One of the methods that can be used for predicting user's next web page is deep learning. To predict next web page, web logs are analyzed by data preprocessing and then a user's next web page is predicted on the output of the analyzed web logs using a deep learning algorithm. In this paper, we propose a framework for web page prediction that includes methods for web log preprocessing followed by deep learning techniques for web prediction. To increase the speed of preprocessing of large web log, a Hadoop based MapReduce programming model is used. In addition, we present a web prediction system that uses an efficient deep learning technique on the output of web log preprocessing for training and prediction. Through experiment, we show the performance improvement of our proposed method over traditional methods. We also show the accuracy of our prediction.

• Nutrition Research and Practice
• /
• v.15 no.2
• /
• pp.160-172
• /
• 2021

BACKGROUND/OBJECTIVES: Nutritional status and food intake during pregnancy and lactation can affect fetal programming. In the current metabolic syndrome epidemic, high-fructose diets have been strongly implicated. This study investigated the effect of maternal high-fructose intake during pregnancy and lactation on the development of metabolic syndrome in adult offspring. SUBJECTS/METHODS: Drinking water with or without 20% fructose was administered to female C57BL/6J mice over the course of their pregnancy and lactation periods. After weaning, pups ate regular chow. Accu-Chek Performa was used to measure glucose levels, and a tail-cuff method was used to examine systolic blood pressure. Animals were sacrificed at 7 months, their livers were excised, and sections were stained with Oil Red O and hematoxylin and eosin (H&E) staining. Kidneys were collected for gene expression analysis using quantitative real-time Polymerase chain reaction. RESULTS: Adult offspring exposed to maternal high-fructose intake during pregnancy and lactation presented with heavier body weights, fattier livers, and broader areas under the curve in glucose tolerance test values than control offspring. Serum levels of alanine aminotransferase, aspartate aminotransferase, glucose, triglycerides, and total cholesterol and systolic blood pressure in the maternal high-fructose group were higher than that in controls. However, there were no significant differences in mRNA expressions of renin-angiotensin-aldosterone system genes and sodium transporter genes. CONCLUSIONS: These results suggest that maternal high-fructose intake during pregnancy and lactation induces metabolic syndrome with hyperglycemia, hypertension, and dyslipidemia in adult offspring.

• Journal of the Society of Disaster Information
• /
• v.18 no.2
• /
• pp.418-431
• /
• 2022

Purpose: We propose a new scheme for predicting promise technology and it improves the conventional scheme that misses important lists of patent because of insufficient search formula, and cannot reflect new trend of technology due to the unreleased period of patents. Method: In this paper, we propose a new search formula exploiting TF and TF-IDF with R programming as well as related keywords, and LDA topic modeling scheme is used for analyzing recently published papers in Satellite·Terrestrial Information Convergence Disaster Response. Result: By comparing both schemes with commercial DB, the proposed scheme can find more important patents, and can reflect new trend of technology, compared to the conventional scheme. Conclusion: The proposed scheme can be used to predict promise technologies in the field of Satellite·Terrestrial Information Convergence Disaster Response.

• Journal of Digital Convergence
• /
• v.19 no.7
• /
• pp.51-56
• /
• 2021

This paper studies VPBL(Various PBL) models, applies them to classes, and analyzes results so that students of various majors can design and implement problems according to the characteristics of their majors in order to improve problem solving in education. VPBL performs the process of designing and implementing problems that reflect the characteristics of the major by applying constraints to the professor's programming language. The professor performs mini_class in the process of solving the designed problem and then shares it throughout. VPBL model apply results, The traditional teaching method was 3.51 points and the application of the VPBL model was 4.52 points, and "interaction, understanding of learning contents, and acquiring knowledge related to curriculum" were improved. In addition, VPBL has the advantage of expanding the learning range in the solving process as it is based on various problem solving, which has the effect of expanding the learning range compared to existing class models. Research on the expanded application of various SW liberal education in the future is required.