• Journal of the Korean Society for Library and Information Science
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• v.51 no.3
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• pp.189-213
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• 2017

Conducted within the framework of the Information Use Environments, this study analyzed the characteristics of students in high schools, identified the typical problems of the students and their information sources to resolve the problems, and analyzed the settings the students use daily. The survey questionnaires were distributed to 220 students in 3 different high schools located in the affluent community area of K-Ku in Seoul particularly known for high academic interests. 188 questionnaires were collected and analyzed using SPSS 24. The findings indicate that the students's attitudes toward education, going to college, and changes and innovations were positive. that they chose the internet as their most favorite information sources for problems, and that 21 problems in 7 self-categories were identified as the students' typical problems, and that the problems within emotional and cognitive self were considered the most important. It was interesting that the students use parents and siblings as information sources to resolve the problems within emotional and cognitive self, although they chose the internet as their favorite information sources in general. The settings that students use daily during weekdays were homes, schools, smart devices. academic tutoring centers, PC or laptop in order. The students' daily settings for weekends were homes, academic tutoring centers, restaurants, PC or laptop in order. These setting was statistically different according to gender and grades. The implications of this study were to suggest the further research questions and to show the application of the IUEs for understanding high school students in a specific setting. Further studies are needed to understand high school students in different contexts.

• Journal of Digital Convergence
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• v.20 no.1
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• pp.25-32
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• 2022

The purpose of this study was conducted to develop adult distance literacy education program and verify its effects. The program was developed through the examination on factors affecting online literacy education and necessary analysis and feedback. Pre- and post-tests analyzing the effects of distance literacy education measuring academic understanding factor, learner satisfaction and satisfactory levels on the academic were administered to 49 adult literacy learners before and after a distance literacy education course. Also, this paper try to explore learners who participated in distance literacy education experience, change and that meaning. The results of the content analysis on the program are summarized as follows. First, there were statistically significant differences regarding academic understanding factor, learner satisfaction and perceived learning outcome satisfaction variables since distance literacy education program which is based on ARCS model start. In addition, learners were satisfied with replaying the learning videos several times, and the improved ability to use smart devices. But they expressed regrets about not being able to go to school and the difficulty of using the devices. It means that distance literacy education based on the ARCS model draw a positive learning conclusion. On the basis of these results, suggestions for further research were discussed.

• Spatial Information Research
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• v.23 no.5
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• pp.9-19
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• 2015

The popularity of smart devices and Location Based Services (LBSes) is increasing in part due to users demand for personalized information associated with their location. These services provide intuitive and realistic information by adopting Augmented Reality (AR) technology. This technology utilizes various sensors embedded in the mobile devices. However, these services have inherent problems due to the devices small screen size and the complexity of the real world environment; overlapping content on a small screen and placing icons without considering the user's possible movement. In order to solve these problems, this paper proposes a Mobile Augmented Reality Model with the application of Street Data. The model consists of two layers: "Real Space" and "Information Space". In the model, a user creates a query by scanning the nearby street with a camera in real space and searches accessible content along the street through the use of the information space. Furthermore, the results are placed on both sides of the street to solve the issue of Overlapping. Also, the proposed model is implemented for region "Aenigol", and the efficiency and usefulness of the model are verified.

• Journal of Service Research and Studies
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• v.13 no.1
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• pp.186-200
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• 2023

This study aims to improve the usability of the white cane, which is walking equipment that most local visually impaired people use and carry when going out, and to contribute to the prevention of safety accidents and the walking rights of visually impaired people by providing improvement and resolution measures for the problems identified. Also, this study is a study on the visually impaired, primarily targeting the 1st to 2nd degree visually impaired people, who cannot go out on their own without walking equipment such as a white cane, corresponding to 20% among approximately 250,000 blind and low vision people in the Korean population. In the study process, the concept has been developed from the user's point of view in order that the white cane becomes a real help in the walking step of the visually impaired and the improvement of usability of the white cane, the main walking equipment for the visually impaired, are done by problem identification through the Double Diamond Model of Design Thinking (Empathize → Define → Ideate → Prototype → Test (verify)). As a result of the investigation in the process of Empathy, a total of five issues was synthesized, including an increase in the proportion of the visually impaired people, an insufficient workforce situation to help all the visually impaired, an improvement and advancement of assistive devices essential for the visually impaired, problems of damage, illegal occupation, demolition, maintenance about braille blocks, making braille block paradigms for the visually impaired and for everyone. In Ideate and Prototype steps, situations derived from brainstorming were grouped and the relationship were made through the KJ method, and specific situations and major causes were organized to establish the direction of the concept. The derived solutions and major functions are defined in four categories, and representative situations requiring solutions and major functions are organized into two user scenarios. Ideas were visualized by arranging the virtual Persona and Customer Journey Map according to the situation and producing a prototype through 3D modeling. Finally, in the evaluation, the final concept derived is a device such a smart cane for guidance for the visually impaired as ① a smart cane emphasizing portability + ② compatibility with other electronic devices + ③ a product with safety and convenience.

• Journal of Intelligence and Information Systems
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• v.17 no.3
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• pp.203-219
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• 2011

Previously common users just want to watch the video contents without any specific requirements or purposes. However, in today's life while watching video user attempts to know and discover more about things that appear on the video. Therefore, the requirements for finding multimedia or browsing information of objects that users want, are spreading with the increasing use of multimedia such as videos which are not only available on the internet-capable devices such as computers but also on smart TV and smart phone. In order to meet the users. requirements, labor-intensive annotation of objects in video contents is inevitable. For this reason, many researchers have actively studied about methods of annotating the object that appear on the video. In keyword-based annotation related information of the object that appeared on the video content is immediately added and annotation data including all related information about the object must be individually managed. Users will have to directly input all related information to the object. Consequently, when a user browses for information that related to the object, user can only find and get limited resources that solely exists in annotated data. Also, in order to place annotation for objects user's huge workload is required. To cope with reducing user's workload and to minimize the work involved in annotation, in existing object-based annotation automatic annotation is being attempted using computer vision techniques like object detection, recognition and tracking. By using such computer vision techniques a wide variety of objects that appears on the video content must be all detected and recognized. But until now it is still a problem facing some difficulties which have to deal with automated annotation. To overcome these difficulties, we propose a system which consists of two modules. The first module is the annotation module that enables many annotators to collaboratively annotate the objects in the video content in order to access the semantic data using Linked Data. Annotation data managed by annotation server is represented using ontology so that the information can easily be shared and extended. Since annotation data does not include all the relevant information of the object, existing objects in Linked Data and objects that appear in the video content simply connect with each other to get all the related information of the object. In other words, annotation data which contains only URI and metadata like position, time and size are stored on the annotation sever. So when user needs other related information about the object, all of that information is retrieved from Linked Data through its relevant URI. The second module enables viewers to browse interesting information about the object using annotation data which is collaboratively generated by many users while watching video. With this system, through simple user interaction the query is automatically generated and all the related information is retrieved from Linked Data and finally all the additional information of the object is offered to the user. With this study, in the future of Semantic Web environment our proposed system is expected to establish a better video content service environment by offering users relevant information about the objects that appear on the screen of any internet-capable devices such as PC, smart TV or smart phone.

• Journal of Digital Convergence
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• v.19 no.1
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• pp.77-88
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• 2021

Cloud computing is getting a lot of attention by many people and businesses due to IT environmental changes such as the proliferation of smart devices, the increase of digital data, and the cost of IT resources. More individuals use personal cloud computing services for storing and managing information and data. Therefore, this study proposed determinants that are expected to have an influence on evaluating the value of cloud computing based on the value-based adoption model, examining the relationship between the continuous use intention of cloud computing. Results of the study show that usefulness, convenience of information access, extensibility had a positive impact on perceived value while privacy concerns and costs had a negative impact on perceived value. In addition, perceived value was found to have a significant effect on the intention to continue use of cloud computing. Finally, trust was found to have a significant effect on the perceived value and the intention to continue use of cloud computing. The findings are expected to provide useful information for understanding the factors that individual users consider important in the steadily growing cloud computing market.

• Cartoon and Animation Studies
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• s.41
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• pp.337-356
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• 2015

Recently augmented reality contents are variously used in public such as advertisements or exhibits as well as children's books. Therefore, it is certain that the market, development of augmented reality contents, is gradually growing. Those who are the producer of augmented reality may be familiar with the skill where those images are used as a marker which is created by image recognition technique. In case of using image recognition technique, they usually use the augmented reality marker platform from Qualcomm since it is able to recognize self-produced images and 3-dimensional figures at no cost. This study was started when undergraduate students began to use those general techniques in their contents producing process. AR majoring students in Namseoul University applied image recognition technique to 3 AR contents exhibited in Sejong Center. Creating 3 different images, they have registered images at Image Target Manager provided by Vuforia to use as a marker. Moreover, they have modified the image producing method to raise the recognition rate by research. The higher recognition rate brings the more stable use of augmented reality contents. To achieve the satisfied rate, they have compared the elements of color contrast, pattern and etc. in the use of platform. Thus, the effective image creation method has been drawn. This study is aiming to suggest the production of stable contents by recognizing smart devices' limitation and producing educational contents. The purpose of this study is to help practically augmented reality contents developers by illustrating the application of augmented reality contents which are based on image recognition technique and also its effectiveness at the same time.

• Science of Emotion and Sensibility
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• v.23 no.2
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• pp.51-60
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• 2020

This study aimed to develop a modular smart clothing system for heart rate monitoring that reduces the inconvenience caused by battery charging and the large size of measurement devices. The heart rate monitoring system was modularized into a temporary device and a continuous device to enable heart rate monitoring depending on the requirement. The temporary device with near-field communication (NFC) and heart rate sensors was developed as a clothing attachment type that enables heart rate monitoring via smart phone tagging when required. The continuous device is based on Bluetooth Low Energy (BLE) communication and batteries and was developed to enable continuous heart rate measurement via a direct connection to the temporary device. Furthermore, the temporary device was configured to connect with a textile electrode made of a silver-based knitted fabric designed to be located below the pectoralis major muscle for heart rate measurement. Considering the user-experience factors, key functions, and the ease of use, we developed an application to automatically log through smart phone tagging to improve usability. To evaluate the accuracy of the heart rate measurement, we recorded the heart rate of 10 healthy male subjects with a modular smart clothing system and compared the results with the heart rate values measured by the Polar RS800. Consequently, the average heart rate value measured by the temporary system was 85.37, while that measured by the reference device was 87.03, corresponding to an accuracy of 96.73%. No significant difference was found in comparison with the reference device (T value = -1.892, p = .091). Similarly, the average heart rate measured by the continuous system was 86.00, while that measured by the reference device was 86.97, corresponding to an accuracy of 97.16%. No significant difference was found in terms of the heart rate value between the two signals (T value = 1.089, p = .304). The significance of this study is to develop and validate a modular clothing system that can measure heart rates according to the purpose of the user. The developed modular smart clothing system for heart rate monitoring enables dual product planning by reducing the price increase due to unnecessary functions.

• Journal of Intelligence and Information Systems
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• v.26 no.2
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• pp.131-145
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• 2020

In line with the trend of industrial innovation, IoT technology utilized in a variety of fields is emerging as a key element in creation of new business models and the provision of user-friendly services through the combination of big data. The accumulated data from devices with the Internet-of-Things (IoT) is being used in many ways to build a convenience-based smart system as it can provide customized intelligent systems through user environment and pattern analysis. Recently, it has been applied to innovation in the public domain and has been using it for smart city and smart transportation, such as solving traffic and crime problems using CCTV. In particular, it is necessary to comprehensively consider the easiness of securing real-time service data and the stability of security when planning underground services or establishing movement amount control information system to enhance citizens' or commuters' convenience in circumstances with the congestion of public transportation such as subways, urban railways, etc. However, previous studies that utilize image data have limitations in reducing the performance of object detection under private issue and abnormal conditions. The IoT device-based sensor data used in this study is free from private issue because it does not require identification for individuals, and can be effectively utilized to build intelligent public services for unspecified people. Especially, sensor data stored by the IoT device need not be identified to an individual, and can be effectively utilized for constructing intelligent public services for many and unspecified people as data free form private issue. We utilize the IoT-based infrared sensor devices for an intelligent pedestrian tracking system in metro service which many people use on a daily basis and temperature data measured by sensors are therein transmitted in real time. The experimental environment for collecting data detected in real time from sensors was established for the equally-spaced midpoints of 4×4 upper parts in the ceiling of subway entrances where the actual movement amount of passengers is high, and it measured the temperature change for objects entering and leaving the detection spots. The measured data have gone through a preprocessing in which the reference values for 16 different areas are set and the difference values between the temperatures in 16 distinct areas and their reference values per unit of time are calculated. This corresponds to the methodology that maximizes movement within the detection area. In addition, the size of the data was increased by 10 times in order to more sensitively reflect the difference in temperature by area. For example, if the temperature data collected from the sensor at a given time were 28.5℃, the data analysis was conducted by changing the value to 285. As above, the data collected from sensors have the characteristics of time series data and image data with 4×4 resolution. Reflecting the characteristics of the measured, preprocessed data, we finally propose a hybrid algorithm that combines CNN in superior performance for image classification and LSTM, especially suitable for analyzing time series data, as referred to CNN-LSTM (Convolutional Neural Network-Long Short Term Memory). In the study, the CNN-LSTM algorithm is used to predict the number of passing persons in one of 4×4 detection areas. We verified the validation of the proposed model by taking performance comparison with other artificial intelligence algorithms such as Multi-Layer Perceptron (MLP), Long Short Term Memory (LSTM) and RNN-LSTM (Recurrent Neural Network-Long Short Term Memory). As a result of the experiment, proposed CNN-LSTM hybrid model compared to MLP, LSTM and RNN-LSTM has the best predictive performance. By utilizing the proposed devices and models, it is expected various metro services will be provided with no illegal issue about the personal information such as real-time monitoring of public transport facilities and emergency situation response services on the basis of congestion. However, the data have been collected by selecting one side of the entrances as the subject of analysis, and the data collected for a short period of time have been applied to the prediction. There exists the limitation that the verification of application in other environments needs to be carried out. In the future, it is expected that more reliability will be provided for the proposed model if experimental data is sufficiently collected in various environments or if learning data is further configured by measuring data in other sensors.

• International Journal of Computer Science & Network Security
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• v.22 no.5
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• pp.103-114
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• 2022

The Internet of Things (IoT) is one of the fastest technologies that are used in various applications and fields. The concept of IoT will not only be limited to the fields of scientific and technical life but will also gradually spread to become an essential part of our daily life and routine. Before, IoT was a complex term unknown to many, but soon it will become something common. IoT is a natural and indispensable routine in which smart devices and sensors are connected wirelessly or wired over the Internet to exchange and process data. With all the benefits and advantages offered by the IoT, it does not face many security and privacy challenges because the current traditional security protocols are not suitable for IoT technologies. In this paper, we presented a comprehensive survey of the latest studies from 2018 to 2021 related to the security of the IoT and the use of machine learning (ML) and deep learning and their applications in addressing security and privacy in the IoT. A description was initially presented, followed by a comprehensive overview of the IoT and its applications and the basic important safety requirements of confidentiality, integrity, and availability and its application in the IoT. Then we reviewed the attacks and challenges facing the IoT. We also focused on ML and its applications in addressing the security problem on the IoT.