• Journal of Convergence for Information Technology
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• v.9 no.5
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• pp.34-39
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• 2019

One of the words frequently mentioned in our society today is the smart machine. Smart machines are machines that contain smart or intelligent functions. These smart machines have recently been applied in our home environment. These are phenomena that occur as a result of smart home. In a smart home environment, smart speakers have moved away from traditional music playback functions and are now increasingly serving as interfaces to control devices, the various components of a smart home. In this study, the technology trends of domestic and foreign smart speaker market are examined, problems of current products are analyzed, and necessary core technologies are described. In the domestic smart speaker market, SKT and KT are leading the related industries, while major IT companies such as Amazon, Google and Apple are focusing on launching related products and technology development.

• Journal of the Korea Convergence Society
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• v.10 no.5
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• pp.125-131
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• 2019

This study tries to grasp the factor that affects the acceptance of beacon as an O2O marketing tool. This study examined whether there is a difference between beacon accepter as a means of marketing communication and non-accepter in terms of related variables. As a result, there were significant differences between beacon perceiver and non-perceiver in 'smartphone usage' and 'brand consciousness'. In order to understand the predictive variables influencing beacon acceptance as a means of marketing communication, this study used 'perceiving beacon as a marketing communication media' as a dependent variable to perform logistic regression analysis. As a result of the analysis, it was found that 'smartphone usage' and 'brand consciousness' were the predictive variables affecting beacon perceiving. This study tried to analysis the results in the viewpoint of perceived usefulness and ease-of-use which were insisted by TAM.

• The Journal of the Korea institute of electronic communication sciences
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• v.16 no.5
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• pp.975-980
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• 2021

As technology utilizing low-power short-range wireless communication is applied in conjunction with medical information as a development of the fourth industrial revolution, interest in medical information is increasing. As the age group of smart devices increases and becomes more common, related research such as linking mobile devices with various objects and equipment is continuously being conducted. In addition, interest in untact (non-face-to-face) is increasing due to the prevalence of Coronavirus Disease-19 (COVID-19), including various infectious diseases. As a result, it is a state that requires distance not only in social but also in life. In this study, using a low-power near-field wireless communication technology of beacons to create an IoT device by communicating with the web server of the medical information system was studied to make it easier to receive medical treatment during visits to medical institutions.

• Food Science and Industry
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• v.52 no.4
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• pp.401-409
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• 2019

The need for win-win cooperation between small and medium-sized enterprises and large corporations is emphasized. For the sustainable growth of a healthy industry, the attractive parts of large companies and the capabilities of small and medium-sized enterprises must be harmonized and shared. It was also examined what items large companies should consider in selecting small and medium-sized enterprises as a partner. In the case of food producers, when considering safety issues, a comprehensive safety system should be established, not just a single factor. And cooperation is expected between small and medium-sized enterprises and other partners with new technologies such as AI, IoT, 3D printers and 5G technology. It is suggested that corporate development can be achieved by various models through win-win cooperation between large companies and small and medium-sized enterprises.

• Journal of the Korea Institute of Information and Communication Engineering
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• v.25 no.5
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• pp.628-636
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• 2021

This paper contains the implementation and performance evaluation results of a system that collects environmental data at the time when the wild animal intrusion occurred at farms and then predicts future wild animal intrusions through a machine learning-based Vector Autoregression(VAR) model. To collect the data for intrusion prediction, an IoT-based hardware prototype was developed, which was installed on a small farm located near the school and simulated over a long period to generate intrusion events. The intrusion prediction service based on the implemented VAR model provides the date and time when intrusion is likely to occur over the next 30 days. In addition, the proposed system includes the function of providing real-time notifications to the farmers mobile device when wild animals intrusion occurs in the farm, and performance evaluation was conducted to confirm that the average response time was 7.89 seconds.

• The Journal of the Korea institute of electronic communication sciences
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• v.18 no.5
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• pp.761-768
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• 2023

In the 4th Industrial Revolution, AI(Artificial Intelligence) and IoT(Internet of Things) technologies are being applied to across various fields, with particularly prominence in asset management, disaster management, and meteorological observation. In these fields, it is necessary to accurately determine the real-time and precise tracking of the object's location and status, and to collect various data even in situations that are difficult to detect with existing sensors. In order to address these demands, the use of GNSS(Global Navigation Satellite System) is essential, and this technology enables the efficient management of assets, disaster prevent and response, and accurate weather forecasting. In this paper, we provide the investigated results for the latest trends in the application of GNSS in the fields of asset management, disaster management, and weather observation, among various fields incorporating AI and IoT and analyze them.

• Journal of Convergence for Information Technology
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• v.11 no.5
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• pp.30-37
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• 2021

Various devices are connected to the Internet, and attacks using the Internet are occurring. Among such attacks, there are attacks that use malicious URLs to make users access to wrong phishing sites or distribute malicious viruses. Therefore, how to detect such malicious URL attacks is one of the important security issues. Among recent deep learning technologies, neural networks are showing good performance in image recognition, speech recognition, and pattern recognition. This neural network can be applied to research that analyzes and detects patterns of malicious URL characteristics. In this paper, performance analysis according to various parameters was performed on a method of detecting malicious URLs using neural networks. In this paper, malicious URL detection performance was analyzed while changing the activation function, learning rate, and neural network structure. The experimental data was crawled by Alexa top 1 million and Whois to build the data, and the machine learning library used TensorFlow. As a result of the experiment, when the number of layers is 4, the learning rate is 0.005, and the number of nodes in each layer is 100, the accuracy of 97.8% and the f1 score of 92.94% are obtained.

• The Journal of Korean Institute of Electromagnetic Engineering and Science
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• v.29 no.5
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• pp.353-358
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• 2018

We herein analyze the service traffic characteristics and spectrum of the 5G mobile communication and suggest the effective 5G network deployment method for 5G mobile communication services. The data rates of the 5G mobile communication are from several kbps (voice and IoT) up to 1 Gbps (hologram, among others). The 5G mobile communication services show the diverse cell coverage environments owing to the use of diverse service data rates and multiple spectrum bands. To effectively support the 5G mobile communication services, the network deployment requires the optimization of the service coverages for new service environments and multiple spectrum bands. Considering the 5G spectrum bandwidth debated at present, if the 5G services of 100 Mbps can be supported in the 200 m cell edge using the 3.5 GHz spectrum bands, the 5G services of the 1 Gbps hologram and 500-Mbps 4k UHD can be supported in the cell edges of 50 m and 100 m using the 28 GHz spectrum bands. Therefore, the 5G services can be supported effectively by the 5G network deployment using spectrum portfolio configurations to match the diverse 5G services and multiple bands.

• Journal of Internet of Things and Convergence
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• v.5 no.2
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• pp.47-54
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• 2019

This convergence study was conducted to identify the effect of the awareness enhancing program of the international development cooperation of college students sponsored by the Korea International Cooperation Agency (KOICA). A quasi-experimental study design was used. The participants consisted of one experimental group (n=32) who attended the awareness enhancing class of international development cooperation and the other control group (n=32) who did not participate in the class in a university in C city. The data were collected using online survey before the first class and after the last class in spring semester 2019. Collected data were analyzed by ANCOVA using SPSS WIN Version 20.0 program. The levels of global citizenship (p=.003) and career preparation behavior (p=.013) was higher in the experimental group than in the control group. However, career identity(p=.385) and cooperative efficacy(p=.488) did not show significant difference between the groups. This study proposed the direction for the awareness enhancing program of the international development cooperation of college students by showing its positive effects on the global citizenship and career preparation behavior.

• Journal of Internet of Things and Convergence
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• v.5 no.1
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• pp.13-28
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• 2019

The purpose of this study is to identify degree of the personality type, resilience, self-efficacy, and workplace bullying Experience among nurses at General Hospital, to ascertain the correlation between them and to ascertain factors that may affect workplace bullying. This study collected data from October 22, 2018 to October 26, 2018 through structured questionnaires from 260 nurses working at General Hospital in Seoul City, and the collected data were analyzed by descriptive statistics, t-test, ANOVA, Pearson's correlation coefficients, and multiple regression analysis using SPSS / WIN 21.0. Analysis of differences in general characteristics showed that workplace bullying was significantly different according to witness of bullying, workplace satisfaction. Resilience was significantly different according to marital status, religion, final education, and workplace satisfaction. And self-efficacy was found to be different according to respondents' marital status, religion. The relationship between DISC personality type, workplace bullying, resilience and self-efficacy showed that workplace bullying had a negative correlation with resilience, and resilience showed a positive correlation with self-efficacy. As a result of the multiple regression analysis in order to identify the factors that, workplace satisfaction, witness of workplace bullying and the resilience was the factor affecting workplace bullying; workplace bullying was decreased as the resilience was higher.