• The Journal of the Korea Contents Association
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• v.20 no.8
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• pp.34-41
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• 2020

An era of stabilizing IoT markets and rapid expansion is coming. In an IoT environment, communication environments where objects take the lead in communication can occur depending on the situation, and communication with unspecified IoT environments has increased the need for thorough management of personal sensitive information. Although there are benefits that can be gained by changing environment due to IoT, there are problems where personal sensitive information is transmitted in the name of big data without even knowing it. For the safe management of personal sensitive information transmitted through sensors in IoT environment, the government plans to propose measures to enhance information protection in IoT environment as the use of non-identifiable personal information in IoT environment is expected to be activated in earnest through the amendment of the Data 3 Act and the initial collection method.

• KIISE Transactions on Computing Practices
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• v.22 no.10
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• pp.537-545
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• 2016

Demand for text arranged in a circular shape is increasing as devices with round display such as smart watches are now being actively released. Data visualization field is receiving a lot of attention as the era of big data evolves. However, current web standard does not support the drawing of circular text. Therefore, the objective of this study was to extend CSS3 specifications to have circular text layout in web documents. In addition, we implemented a preprocessor so that contents made with CSS3 extensions could be shown in existing browsers. To confirm the wide expression range of CSS3 extension, we prepared some sample contents and analyzed them.

• The Journal of The Korea Institute of Intelligent Transport Systems
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• v.17 no.4
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• pp.14-25
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• 2018

In recent years, it has become technically easier to explain factors related with traffic accidents in the Big Data era. Therefore, it is necessary to apply the latest analysis techniques to analyze the traffic accident data and to seek for new findings. The purpose of this study is to compare the predictive performance of the negative binomial regression model and the deep learning method developed in this study to predict the frequency of traffic accidents in expressways. As a result, the MOEs of the deep learning model are somewhat superior to those of the negative binomial regression model in terms of prediction performance. However, using a deep learning model could increase the predictive reliability. However, it is easy to add other independent variables when using deep learning, and it can be expected to increase the predictive reliability even if the model structure is changed.

• Journal of the Korea Institute of Information and Communication Engineering
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• v.21 no.1
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• pp.90-98
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• 2017

Since 2010, SNS was holding the explosive spread of smartphones has created a place of public advertising platform, and it entered the Internet of Things (IoT) is born gradually countdown of the era came to us already. In utilizing a variety of location-based services IoT services (beacon, O2O) The focus of this paper to analyze the differences in satisfaction with the oil layer by experienced users of what is being used. We consider the type and overall utilization of the concepts typical IoT service in the current service is made to expand the contents of the paper. Hypothesis was reconstructed ease, attractiveness, a survey reliability, value four kinds of models, called Honeycomb UX, User Experience Honeycomp Peter Mobil. Company that provides the service IoT in this study are expected to be used as basic data to help provide a more accurate personalized service according to the user's satisfaction difference.

• Journal of Convergence for Information Technology
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• v.10 no.6
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• pp.8-13
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• 2020

In this paper, we study smart healthcare devices that enable active health care by building health care system with acquaintances or family members rather than single health care. The company develops health care services for families regardless of age and gender through intuitive UI design as a target for young users who serve elderly parents. Automated collection of health information and real-time feedback are available, and data can be aggregated and analyzed through repeaters. It can also utilize structured databases in the form of big data. The services offered can be used to prevent diseases and reduce medical expenses through health care, while automatic management can maximize users' convenience and increase demand. By reducing the development period of products that are based on this technology, reducing the development period of products and strengthening competitiveness, the company has the advantage of inducing generation-to-generation communication in an era when it is becoming a nuclear family.

• Journal of Digital Convergence
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• v.14 no.12
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• pp.1-12
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• 2016

Today, with the popularity of smart phones and the proliferation of SNS, anyone is exposed to the risk of personal information leakage. Unlike the prior studies of privacy, this research aims to identify the privacy factors affecting the provision intention of individual information from the SNS Users. This study also analyses how the perceived privacy risks and corporate trust affect the provision intention of individual information. The analysis results of empirical data show that despite experiencing the privacy leakage such as direct hacking and being aware of the risk, people are providing firms with personal information. The most influential variables to perceived privacy risk are information privacy policy, information privacy concern, previous privacy experience and information privacy awareness in the decreasing order of importance. Those to the corporate trust are information privacy policy, information privacy awareness, previous privacy concern and information privacy experience. Besides, the corporate trust and the perceived privacy risk also affect the provision intention of personal information. Finally, this study proposes the implications for personal information privacy.

• Journal of Convergence for Information Technology
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• v.11 no.12
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• pp.22-29
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• 2021

COVID-19, which has spread around the world, is also affecting local economic industries such as the domestic tourism industry and the service industry. In particular, the quality of life is threatened as safety prevention rules related to infectious diseases such as social distancing have been regularized. The purpose of this study is to analyze the impact on safety quarantine on users of the summer festival at Songho Beach in Haenam, a summer resort. In addition, it protrudes through big data surveys, demographic analysis, and technology analysis on the management of users who have changed in the COVID-19 era. It is expected to be a reference material by utilizing practical data on users in the future. In addition, this study is significant that it has been reviewed for safety and satisfaction for tourists using the summer beach festival through quarantine management using ICT technology in the COVID-19 situation, and needs to be used as good guidelines and examples for this study in the future.

• Journal of the Korea Institute of Information and Communication Engineering
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• v.25 no.10
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• pp.1435-1440
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• 2021

With the advent of the low interest rate era, many investors are flocking to the stock market. In the past stock market, people invested in stocks labor-intensively through company analysis and their own investment techniques. However, in recent years, stock investment using artificial intelligence and data has been widely used. The success rate of stock prediction through artificial intelligence is currently not high, so various artificial intelligence models are trying to increase the stock prediction rate. In this study, we will look at various artificial intelligence models and examine the pros and cons and prediction rates between each model. This study investigated as stock prediction programs using artificial intelligence artificial neural network (ANN), deep learning or hierarchical learning (DNN), k-nearest neighbor algorithm(k-NN), convolutional neural network (CNN), recurrent neural network (RNN), and LSTMs.

• Journal of the Korea Safety Management & Science
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• v.22 no.4
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• pp.75-86
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• 2020

With the advent of the 4.0 era of logistics due to the Fourth Industrial Revolution, infrastructures have been built to receive the same services online and offline. Logistics services affected by logistics 4.0 and IT technology are rapidly changing. Logistics services are developing using technologies such as big data, artificial intelligence, blockchain, Internet of things, and augmented reality. The convergence of logistics services and various IT new technologies is accelerating, and the development of data management solution technology has led to the emergence of electronic cargo waybill to replace paper cargo waybill. The electronic waybill was developed to supplement paper waybill that lack economical and safety. However, the electronic waybill that appeared to complement the paper waybill are also in need of complementation in terms of efficiency and reliability. New research is needed to ensure that electronic cargo waybill gain the trust of users and are actively utilized. To solve this problem, electronic cargo waybill that combine blockchain technology are being developed. This study aims to improve the reliability, operational efficiency and safety of blockchain electronic cargo waybill. The purpose of this study is to analyze the blockchain-based electronic cargo waybill system and to derive evaluation indicators for system supplementation.

• The Journal of the Korea Contents Association
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• v.21 no.6
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• pp.51-61
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• 2021

In the era of the 4th industrial revolution symbolized by the Internet of Things, big data and artificial intelligence, various embedded devices are increasing exponentially. These devices have communication functions despite their low specifications, so the possibility of personal information leakage is increasing, and security threats are also increasing. Embedded devices can have security issues at most levels, from hardware to services over the network. In addition, it is difficult to apply general security techniques because it has characteristics of resource constraints such as low specifications and low power, and the related technology has not been standardized. In this study, we present vulnerabilities and possible problems and considerations in applying SDN to embedded devices in consideration of structural characteristics and real-world discovered cases. This study presents vulnerabilities and possible problems and considerations when applying SDN to embedded devices. From a hardware perspective, we consider the problems of Wi-Fi chips and Bluetooth, the problems of open flow implementation, SDN controllers, and examples of structural properties. SDN separates the data plane and the control plane, and provides a standardized interface between the two, enabling efficient communication control. It can respond to the security limitations of existing network technologies that are difficult to respond to rapid changes.