• International Journal of Knowledge Content Development & Technology
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• v.7 no.3
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• pp.67-86
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• 2017

The emergence of smart devices such as smartphones (e.g., iPhone) and tablets (e.g., iPad) may enhance e-learning by increasing communication and collaborative learning outside the classroom. These devices also facilitate the use of online technologies such as Facebook. However, the adaptation of Learning Management System (LMS) services to mobile devices took longer than social networks or online tools such as Facebook and Twitter have already been long used via smartphone. The main purposes of this study are to explore students' skill levels of LMS (Moodle) and their knowledge of online tools or technologies and then examine if there is a correlation between smartphone use and using of online tools and Moodle in learning. The study conducted among 173 students in the Department of Information Studies (DIS) in Oman, using online survey. The study found that most students demonstrated high levels of accessing course/subject materials and regularly engaging with studies of using LMSs. YouTube, Wikipedia and Facebook were clearly recorded as the most popular sites among students while LinkedIn and Academia.edu were two online tools that had never been heard of by over half of the 142 participants. Emailing and searching are recorded the most popular online learning activities among students. The study concluded that students prefer to use smartphone for accessing these tools rather than using it to access LMSs, while a positive correlation was found between the use of these tools and smartphones, but there was no correlation between smartphones and using LMSs.

• Proceedings of the Korean Institute of Information and Commucation Sciences Conference
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• 2017.10a
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• pp.146-147
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• 2017

Big data analysis is a technique for effectively analyzing unstructured data such as the Internet, social network services, web documents generated in the mobile environment, e-mail, and social data, as well as well formed structured data in a database. The most big data analysis techniques are data mining, machine learning, natural language processing, and pattern recognition, which were used in existing statistics and computer science. Global research institutes have identified analysis of big data as the most noteworthy new technology since 2011. Therefore, companies in most industries are making efforts to create new value through the application of big data. In this study, we analyzed using the Social Matrics which a big data analysis tool of Daum communications. We analyzed public perceptions of "Internet of things" keyword, one month as of october 8, 2017. The results of the big data analysis are as follows. First, the 1st related search keyword of the keyword of the "Internet of things" has been found to be technology (995). This study suggests theoretical implications based on the results.

• Proceedings of the Korean Institute of Information and Commucation Sciences Conference
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• 2017.10a
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• pp.140-141
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• 2017

Big data analysis, in the large amount of data stored as the data warehouse which it refers the process of discovering meaningful new correlations, patterns, trends and creating new values. Thus, Big data analysis is an effective analysis of various big data that exist all over the world such as social big data, machine to machine (M2M) sensor data, and corporate customer relationship management data. In the big data era, it has become more important to effectively analyze not only structured data that is well organized in the database, but also unstructured big data such as the internet, social network services, and explosively generated web documents, e-mails, and social data in mobile environments. By the way, a meta analysis refers to a statistical literature synthesis method from the quantitative results of many known empirical studies. We reviewed a total of 750 samples among 50 studies published on the topic related as IDT between 2000 and 2017 in Korea.

• Journal of the Korea Academia-Industrial cooperation Society
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• v.15 no.10
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• pp.6310-6316
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• 2014

The increase in the Internet and smart device users requires high-level network security. Network security consists of Web Firewall, Network Firewall, IPS, DDoS system, UTM (Unified Treat Management), VPN, NAC (Network Access Control), Wireless security, Mobile security, and Virtualization. Most network security solutions running on IPv4, and IPv6 network services are not sufficiently ready. Therefore, in this paper, this study designed and implemented important functions of Network Access Control (NAC), which include IPv6 host detection, isolation, blocking and domain assignment for the IPv6 network. In particular, domain assignment function makes 128 bits IPv6 address management easy. This system was implemented on a KISA IPv6 test-bed using well known devices. Finally, the test result showed that all IPv6 based wired and wireless devices were well-controlled (detection, blocking, isolation and domain assignment).

• Journal of the Korea Institute of Information and Communication Engineering
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• v.25 no.9
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• pp.1199-1205
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• 2021

In the era of big data, not only structured data well organized in databases, but also the Internet, social network services, it is very important to effectively analyze unstructured big data such as web documents, e-mails, and social data generated in real time in mobile environment. Big data analysis is the process of creating new value by discovering meaningful new correlations, patterns, and trends in big data stored in data storage. We intend to summarize and visualize the analysis results through frequency analysis of unstructured article data using R language, a big data analysis tool. The data used in this study was analyzed for total 104 papers in the Mon-May 2021 among the journals of the Korea Institute of Information and Communication Engineering. In the final analysis results, the most frequently mentioned keyword was "Data", which ranked first 1,538 times. Therefore, based on the results of the analysis, the limitations of the study and theoretical implications are suggested.

• Journal of the Korea Academia-Industrial cooperation Society
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• v.19 no.11
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• pp.730-737
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• 2018

With the increasing number of health consumers aiming for a happy quality of life, the O2O medical marketing market is activated by choosing reliable health care facilities and receiving high quality medical services based on the medical information distributed on web's blog. Because unstructured text data used on the Internet, mobile, and social networks directly or indirectly reflects authors' interests, preferences, and expectations in addition to their expertise, it is difficult to guarantee credibility of medical information. In this study, we propose a blog reading system that provides users with a higher quality medical information service by classifying medical information blogs (medical blog, ad blog) using bigdata and MLP processing. We collect and analyze many domestic medical information blogs on the Internet based on the proposed big data and machine learning technology, and develop a personalized health information recommendation system for each disease. It is expected that the user will be able to maintain his / her health condition by continuously checking his / her health problems and taking the most appropriate measures.

• Journal of Convergence for Information Technology
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• v.11 no.4
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• pp.35-45
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• 2021

The e-commerce industry using mobile or web is growing rapidly, and the emergence of various platform services is causing innovative changes in the e-commerce industry. This study aims to identify the attachment types of e-commerce users and to demonstrate the relationship between the PPerceived Usefulness, and Perceived Ease of Use by TAM. In order to empirically verify the research model of this study, a survey was conducted on ordinary people with experience using e-commerce and path analysis was conducted by using PLS to analyze its Internal consistency, Confirmatory factor analysis, Discriminant validity and Goodness-of-fit verification. As a result, a significant relationship between Perceived Stability, Perceived Usefulness, and Perceived Ease of Use was identified, could verify the association with the TAM and Acceptance Intention.

• 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.

• Journal of the Korea Institute of Information and Communication Engineering
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• v.24 no.11
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• pp.1403-1410
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• 2020

Recently, as interest in non-face-to-face experiences and services increases, the demand for web video contents that can be easily consumed using mobile devices such as smartphones or tablets is rapidly increasing. To cope with these requirements, in this paper we propose a technique to efficiently produce video contents that can provide experience of visiting famous places (i.e., stage tour) in animation or movies. To this end, an image dataset was established by collecting images of stage areas using Google Maps and Google Street View APIs. Afterwards, a deep learning-based style transfer method to apply the unique style of animation videos to the collected street view images and generate the video contents from the style-transferred images was presented. Finally, we showed that the proposed method could produce more interesting stage-tour video contents through various experiments.

• Journal of the Korea Institute of Information Security & Cryptology
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• v.31 no.1
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• pp.73-81
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• 2021

When downloading files using an app or web-based application on the user's mobile phone, the path is set to be saved in the pre-defined default directory. Many applications requiring access to storage, including file managers, require a write or read permission of storage to provide numerous functions and services. This means that the application will have direct access to the download folder where the numerous files downloaded. In this paper, to prove our feasibility of attack using the security vulnerabilities mentioned above, we developed a file hacking function disguised as an encryption function in the file management application. The file that encrypted will be sent to hackers via E-mail simultaneously on the background. The developed application was evaluated from VirusTotal, a malicious analysis engine, was not detected as a malicious application in all 74 engines. Finally, in this paper, we propose a defense technique and an algorithm based on the Trusted Execution Environment (TEE) to supplement these storage vulnerabilities.