• Proceedings of the Korean Institute of Information and Commucation Sciences Conference
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• 2016.10a
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• pp.256-259
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• 2016

The growth of mobile devices in Internet of Things (IoT) leads to a number of intelligent buildings related IoT applications. For instance, home automation controlling system uses client system such web apps on smartphone or web service to access the home server by sending control commands. The home server receives the command, then controls for instance the light system. The gateway based RESTful technology responsible for handling clients' requests attests an internet latency in case a large number of clients' requests submit toward the gateway increases. In this paper, we propose the design tasks of the IoT gateway for handling concurrency events. In the procedure of designing tasks, concurrency is best understood by employing multiple levels of abstraction. The way that is eminently to accomplish concurrency is to build an object-oriented environment with support for messages passing between concurrent objects. We also investigate the performance of event-driven architecture for building IoT gateway using node.js on one side and communication protocol based message-oriented middleware known as XMPP to handle communications of intelligent building control devices connected to the gateway through a centralized hub. The Node.JS is 40% faster than the traditional web server side features thread-based approach. The use of Node.js server-side handles a large number of clients' requests, then therefore, reduces delay in performing predefined actions automatically in intelligent building IoT environment.

• Science of Emotion and Sensibility
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• v.22 no.2
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• pp.17-28
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• 2019

The touchscreen device is now commonly found in the form of mobile phones, tablet PCs, and other devices. Varied physical and visual experiences can be experienced through touchscreens. This study intended to explore how the physical and visual experiences provided by the touchscreen would affect people through their existing associations of behavior-attitude. Previous studies have found that certain behaviors affect attitudes. In particular, the approach-avoidance behavior has been noted to influence both social and personal attitudes. It was thus deemed necessary to ascertain the approach-avoidance effect exerted by touchscreens on the attitudes of users as the technology is widely used today. Experiment 1 provided an approach-avoidance experience via a touchscreen and demonstrated that touchscreen-based approach-avoidance dragging behavior on the touchscreen can affect a user's preference and purchase intent. It was found that a product that had been approached showed both higher preference and higher purchase intent than a product that had been avoided. Experiment 2 investigated whether a similar effect would occur when only the visual experience of approach-avoidance was provided. The outcome proved that products that had been visually approached had higher scores than products that had been avoided, both in terms of preference and purchase intent. The movement of the arm on the touchscreen (Experiment 1) and the visual perception of the approach-avoidance experience (Experiment 2) were both shown to influence participants' attitudes toward products. The results of this study suggest that the behavior and perception of users may be an important factor in designing touchscreen interfaces for online shopping.

• Science of Emotion and Sensibility
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• v.22 no.2
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• pp.49-58
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• 2019

In the era of the 4th Industrial Revolution, artificial intelligence (AI) has become one of the core technologies in terms of the business strategy among information technology companies. Both international and domestic major portal companies are launching AI search services. These AI search services utilize voice, images, and other unstructured data to provide different experiences from existing text-based search services. An unfamiliar experience is a factor that can hinder the usability of the service. Therefore, the usability testing of the AI search services is necessary. This study examines the usability of the AI search service on the Naver App 8.9.3 beta version by comparing it with the search services of the current Naver App and targets 30 people in their 20s and 30s, who have experience using Naver apps. The usability of Smart Lens, Smart Voice, Smart Around, and AiRS, which are the Naver App beta versions of their artificial intelligence search service, is evaluated and statistically significant usability changes are revealed. Smart Lens, Smart Voice, and Smart Around exhibited positive changes, whereas AiRS exhibited negative changes in terms of usability. This study evaluates the change in usability according to the application of the artificial intelligence search services and investigates the correlation between the evaluation factors. The obtained data are expected to be useful for the usability evaluation of services that use AI.

• Journal of Convergence for Information Technology
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• v.9 no.6
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• pp.153-163
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• 2019

The purpose of this study is to research the effect of life satisfaction on young people at an early age and the impact of media on behavioral aggressiveness during this process. To this end, a group of primary schools located in Jiangnan and Jiangbei in the Seoul area and the Nanjing Road in the city were selected and 290 early youths from grades 4-6 of elementary school were chosen as specimens of structural equations. The results indicate that firstly, the personal causes of early youth have a positive (+) effect on the self-esteem life satisfaction and negative (-) impact on liquidity aggressiveness. Secondly, depression has a negative impact on life satisfaction, while action aggressiveness has no effect. Thirdly, the mobility aggression of early youth has a negative impact on life satisfaction (-), and there is a partial media relationship between self-esteem and life satisfaction. However, there is no media relationship between depression and life satisfaction. Based on the above research results, the project of improving youth early life satisfaction and reducing mobile aggression was proposed.

• Journal of Convergence for Information Technology
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• v.11 no.4
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• pp.26-34
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• 2021

In the era of the Fourth Industrial Revolution, the future battlefield will carry out multi-area operations with hyper-connected, high-speed and mobile systems. In order to prepare for changes in the future, the Korean military intends to develop various weapons systems and form a multi-layer tactical network to support On The Move communication. However, current tactical networks are limited in support of On The Move communications. In other words, the operation of multi-beam antennas is necessary to efficiently construct a multi-layer tactical network in future warfare. Therefore, in this paper, we look at the need for multi-beam antennas through the operational scenario of a multi-layer tactical network. In addition, based on development consideration factors, features of rotary-wing and fixed-wing aircraft, we present the location and operation of airborne relay drone installations of multi-beam antennas.

• Journal of Digital Convergence
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• v.19 no.2
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• pp.245-251
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• 2021

As the trend of steadily increasing the number of single or double household, there is a growing demand to see who is the outsider visiting the home during the free time. Various models of face recognition technology have been proposed through many studies, and Harr Cascade of OpenCV and Hog of Dlib are representative open source models. Among the two modes, Dlib's Hog has strengths in front of the indoor and at a limited distance, which is the focus of this study. In this paper, a face recognition visitor access system based on Dlib was designed and implemented. The whole system consists of a front module, a server module, and a mobile module, and in detail, it includes face registration, face recognition, real-time visitor verification and remote control, and video storage functions. The Precision, Specificity, and Accuracy according to the change of the distance threshold value were calculated using the error matrix with the photos published on the Internet, and compared with the results of previous studies. As a result of the experiment, it was confirmed that the implemented system was operating normally, and the result was confirmed to be similar to that reported by Dlib.

• Journal of the Korea Academia-Industrial cooperation Society
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• v.22 no.6
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• pp.573-582
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• 2021

In this study, a series of processes for evaluating the effective protection against barriers that should be equipped in institutions that perform reliability tests on high-risk ammunition, such as high-explosive ammunition, were introduced. The impact that high-explosive bombs can have on personnel includes damage to the eardrum and lungs caused by explosion overpressure and penetrating wounds that can be received by fragments generated simultaneously with the explosion. Therefore, a high-explosive with COMP B explosives as its contents were set up, and an explosion protection theory investigation to calculate the degree of damage, numerical calculations and simulations were performed to verify the protection power. A numerical calculation revealed the maximum explosion overpressure on the protective wall when the high-explosive exploded and the penetration force of the fragment against a 50 mm-thick protective wall to be 77.74 kPa and 41.34 mm, respectively. In the simulation verification using AUTODYN, the maximum explosion overpressures affecting the firewall and personnel were 56.68 kPa and 18.175 kPa, respectively, and the penetration of fragments was 35.56 mm. This figure is lower than the human damage limit, and it was judged that the protective power of the barrier would be effective.

• Journal of the Korea Convergence Society
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• v.12 no.6
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• pp.233-239
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• 2021

Recently, the COVID-19 virus has caused people to stay indoors longer without going out. As a result of this, people's activity decreased sharply, and their weight gained. So people became more interested in health. Home training can be an alternative method to solve this problem. Accordingly, To find out the trends of home training, we collected articles from December 1, 2019, to November 30, 2020, using the news provided by BIG KINDS, a news analysis system. We analyzed frequency analysis, relational analysis according to weighting, and related word analysis with the program using the algorithm developed by BIG KINDS. In conclusion, first, it was found that home training is led by technology and the emergence of artificial intelligence. Second, it can be assumed that people mainly do home training using content and video services related to mobile carriers. Third, people had a high preference for Pilates in the sports category. It can be seen that the number of patent applications increased as the demand for exercise products related to Pilates increased. In the next study, we expect that this study will be used as primary data for various big data studies by supplementing the research methodology and conducting various analyses.

• KIPS Transactions on Software and Data Engineering
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• v.11 no.3
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• pp.141-148
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• 2022

Recently, reinforcement learning combined with deep neural network technology has achieved remarkable success in various fields such as board games such as Go and chess, computer games such as Atari and StartCraft, and robot object manipulation tasks. However, such deep reinforcement learning describes states, actions, and policies in vector representation. Therefore, the existing deep reinforcement learning has some limitations in generality and interpretability of the learned policy, and it is difficult to effectively incorporate domain knowledge into policy learning. On the other hand, dNL-RRL, a new relational reinforcement learning framework proposed to solve these problems, uses a kind of vector representation for sensor input data and lower-level motion control as in the existing deep reinforcement learning. However, for states, actions, and learned policies, It uses a relational representation with logic predicates and rules. In this paper, we present dNL-RRL-based policy learning for transportation mobile robots in a manufacturing environment. In particular, this study proposes a effective method to utilize the prior domain knowledge of human experts to improve the efficiency of relational reinforcement learning. Through various experiments, we demonstrate the performance improvement of the relational reinforcement learning by using domain knowledge as proposed in this paper.

• The Journal of the Korea Contents Association
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• v.22 no.4
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• pp.222-230
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• 2022

Recently, Korea's cultural content industry is developing, and behind the growing recognition around the world is the real-time sharing service of global network users due to the development of science and technology. In particular, in the case of YouTube, its propagation power is fast and powerful in that everyone, not limited users, can become potential video providers. As more than 80% of mobile phone users are using YouTube in Korea, YouTube's information means that psychological factors of users are reflected. For example, information such as the number of video views, likes, and comments of a channel with a specific personality shows a measure of the channel's personality interest. This is highly related to the fact that information such as the frequency of keyword search on portal sites is closely related to the stock market economically and psychologically. Therefore, in this study, YouTube information from a representative entertainment company is collected through a crawling algorithm and analyzed for the causal relationship with major variables related to stock prices. This study is considered meaningful in that it conducted research by combining cultural content, IT, and financial fields in accordance with the era of the fourth industry.