• 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.

• Journal of Broadcast Engineering
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• v.27 no.1
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• pp.3-12
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• 2022

Image deblurring aims to remove image blur, which can be generated while shooting the pictures by the movement of objects, camera shake, blurring of focus, and so forth. With the rise in popularity of smartphones, it is common to carry portable digital cameras daily, so image deblurring techniques have become more significant recently. Originally, image deblurring techniques have been studied using traditional optimization techniques. Then with the recent attention on deep learning, deblurring methods based on convolutional neural networks have been actively proposed. However, most of them have been developed while focusing on better performance. Therefore, it is not easy to use in real situations due to the speed of their algorithms. To tackle this problem, we propose a novel deep learning-based deblurring algorithm that can be operated in real-time on HD resolution. In addition, we improved the training and inference process and could increase the performance of our model without any significant effect on the speed and the speed without any significant effect on the performance. As a result, our algorithm achieves real-time performance by processing 33.74 frames per second at 1280×720 resolution. Furthermore, it shows excellent performance compared to its speed with a PSNR of 29.78 and SSIM of 0.9287 with the GoPro dataset.

• Journal of Internet Computing and Services
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• v.24 no.6
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• pp.171-180
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• 2023

Hydrogen energy technology is gaining importance in the era of the Fourth Industrial Revolution, offering military advantages when applied to military vehicles due to its characteristics such as reduced greenhouse gas emissions, noise, and low vibration. Korea's military has initiated the Army Tiger 4.0 plan, focusing on hydrogen application, downsizing, and AI-based smart features. The Ministry of National Defense plans to collaborate with the Ministry of Environment to expand hydrogen charging stations nationwide, anticipating increased deployment of military hydrogen vehicles. However, considering the Jet Fire and VCE(Vapor Cloud Explosion) nature of hydrogen, ensuring safety during installation is crucial. Current military guidelines specify a minimum safety distance of 2m from adjacent buildings for charging stations. Scientific methods have been employed to quantitatively assess the accident damage range of hydrogen, proposing a minimum safety distance beyond the affected area.

• Journal of the Microelectronics and Packaging Society
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• v.30 no.2
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• pp.1-12
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• 2023

In the current era of the global mobile smart device revolution, electronic devices are required in all spaces that people interact with. The establishment of the internet of things (IoT) among smart devices has been recognized as a crucial objective to advance towards creating a comfortable and sustainable future society. In-mold electronic (IME) processes have gained significant industrial significance due to their ability to utilize conventional high-volume methods, which involve printing functional inks on 2D substrates, thermoforming them into 3D shapes, and injection-molded, manufacturing low-cost, lightweight, and functional components or devices. In this article, we provide an overview of IME and its latest advances in application. We review biomimetic nanomaterials for constructing self-supporting biosensor electronic materials on the body, energy storage devices, self-powered devices, and bio-monitoring technology from the perspective of in-mold electronic devices. We anticipate that IME device technology will play a critical role in establishing a human-machine interface (HMI) by converging with the rapidly growing flexible printed electronics technology, which is an integral component of the fourth industrial revolution.

• KIPS Transactions on Computer and Communication Systems
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• v.12 no.9
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• pp.283-290
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• 2023

With the recent steady development of IoT technology, it is widely used in medical systems and smart TV watches. 66% of software development is developed through language C, which is vulnerable to memory attacks, and acts as a threat to IoT devices using language C. A stack-smashing overflow attack inserts a value larger than the user-defined buffer size, overwriting the area where the return address is stored, preventing the program from operating normally. IoT devices with low memory capacity are vulnerable to stack smashing overflow attacks. In addition, if the existing vaccine program is applied as it is, the IoT device will not operate normally. In order to defend against stack smashing overflow attacks on IoT devices, we used canaries among several detection methods to set conditions with random values, checksum, and DSLR (random storage locations), respectively. Two canaries were placed within the buffer, one in front of the return address, which is the end of the buffer, and the other was stored in a random location in-buffer. This makes it difficult for an attacker to guess the location of a canary stored in a fixed location by storing the canary in a random location because it is easy for an attacker to predict its location. After executing the detection program, after a stack smashing overflow attack occurs, if each condition is satisfied, the program is terminated. The set conditions were combined to create a number of eight cases and tested. Through this, it was found that it is more efficient to use a detection method using DSLR than a detection method using multiple conditions for IoT devices.

• Journal of Intelligence and Information Systems
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• v.29 no.4
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• pp.1-13
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• 2023

The widespread adoption of smartphones and advancements in internet technology have notably shifted content consumption habits toward video. This research aims to dissect the nature of videos posted on YouTube, the global video-sharing platform, to understand the characteristics of both produced and preferred content. For this study, dance was chosen as a specific subject from a variety of video categories. Data on YouTube videos associated with the term "dance" was compiled over three years, from 2019 to 2021. The investigation revealed a clear distinction between the types of dance videos frequently uploaded to YouTube and those that receive a high number of views. The empirical analysis of this study indicates a viewer preference for vlogs that provide insights into the daily lives of dance students, as well as for purpose-driven videos, such as those highlighting dance exam preparations or school dance events. Notably, the vlogs that attract the most attention are typically created by dance students at the college or secondary school level, rather than by professionals. Although the study was focused on dance, its methodologies can be applied to different subjects. These insights are expected to contribute to the development of a recommendation system that aids content creators in effectively targeting their productions.

• Knowledge Management Research
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• v.24 no.4
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• pp.23-42
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• 2023

This study originated from recognition of importance of firefighters' decision-making in fire response, coupled with existing gap in research. By utilizing Q-methodology, the study aimed to categorize firefighters' subjectivity in fire response decision-making. Through this categorization, the study sought to highlight insights into the current technological and data limitations, as well as potential directions for future R&D in the field of firefighting. The findings of the study revealed that firefighters' subjectivity could be classified into three factors: "emphasis on direct information related to rescue," "emphasis on information related to the target property," and "emphasis on information related to command and coordination." The study theoretically confirmed that the subjectivity of firefighters' decision-making in fire response is partially influenced by their experiences and job. Additionally, the study's significance lay in its approach of collecting specific decision-making factors in fire response, moving beyond general theoretical models. Furthermore, from a policy perspective, the typification of decision-making factors contributed to connecting the identified data-based administrative needs from prior studies. Insights from the study emphasized the importance of leveraging on-site experience in Korea to aid decision-making, calling for the development of equipment and data collection methods that can rapidly and accurately assess on-site conditions.

• Journal of the Korea Institute of Building Construction
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• v.24 no.2
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• pp.203-213
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• 2024

This study delves into the mechanical properties of fiber-reinforced cement composites(FRCC) concerning the dispersion method of multi-walled carbon nanotubes(MWCNTs). MWCNTs find utility in industrial applications, particularly in magnetic sensing and crack detection, owing to their diverse properties including heat resistance and chemical stability. However, current research endeavors are increasingly directed towards leveraging the electrical properties of MWCNTs for self-sensing and smart sensor development. Notably, achieving uniform dispersion of MWCNTs poses a challenge due to variations in researchers' skills and equipment, with excessive dispersion potentially leading to deterioration in mechanical performance. To address these challenges, this study employs ultrasonic dispersion for a defined duration along with PCE surfactant, known for its efficacy in dispersion. Test specimens of FRCC are prepared and subjected to strength, drawing, and direct tensile tests to evaluate their mechanical properties. Additionally, the influence of MWCNT dispersion efficiency on the enhancement of FRCC mechanical performance is scrutinized across different dispersion methods.

• Journal of the Korean Recycled Construction Resources Institute
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• v.12 no.1
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• pp.63-71
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• 2024

Through the development of construction technology, various construction projects such as redevelopment projects, undergrounding of roads, expansion of subways, and metro railways are being carried out. However, this has led to an increase in the number of construction projects in existing urban centers and neighborhoods, resulting in an increase in the number of damages and disputes between neighboring buildings and residents, as well as an increase in safety accidents due to the aging of existing buildings. In this study, digital data was applied to a graphics program to objectify the progress of cracks by comparing the creation of cracks and the increase in length and width through photographic images and presenting the degree of cracks numerically. Through the application of the program, the error caused by the subjective judgment of crack change, which was mentioned as a shortcoming of the existing field survey, was solved. It is expected that the program can be used universally in the building diagnosis process by improving its reliability if supplemented and improved in the process of use. As a follow-up study, it is necessary to apply the extraction algorithm of the digital graphic data program to calculate the length and width of the crack by itself without human intervention in the preprocessing work and to check the overall change of the building.

• The Journal of the Institute of Internet, Broadcasting and Communication
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• v.24 no.1
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• pp.189-196
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• 2024

Currently, it is almost impossible to move the focus of a previously taken photo to a different location. This paper challenges a technology that can move the focus of a captured photo to another location after shooting. To achieve this goal, this paper proposed and implemented a method for taking photos with various focuses at the moment the camera took pictures and storing them in a single JPEG file to extract photos focused on the user's preferred location. In this paper, two methods are implemented: taking various photos by quickly moving the focal length of the lens from close to far away, and taking various photos focused on each object by recognizing objects in the camera viewfinder. Various photos taken are stored in a single JPEG to maintain compatibility with traditional photo viewers. At this time, this JPEG file used the All-in-JPEG format proposed in previous research to store a variety of images. This paper verified its practicality by implementing these technologies in an Android app named OnePIC.