• Journal of the Korea Academia-Industrial cooperation Society
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• v.20 no.4
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• pp.293-302
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• 2019

This study systematically analyzed computer-based driving intervention programs for seniors, to provide the academic background for driving intervention for seniors. Articles published from January 2009 till December 2018 were researched and analyzed. 'PubMed, Google Scholar, and Science Direct' were used to search articles published overseas, and 'RISS, KERIS, and KISS' searched for articles published in Korea. Based on the inclusion and exclusion criteria, totally 359 papers were retrieved, and 10 articles were finally analyzed; 8 articles (80%) were evidence level I, and 2 articles (20%) were evidence level III. Amongst the computer-based interventions, driving simulators (70%) were the most common, followed by two video image training (20%) and one Nintendo Wii program (10%). In most studies, driving simulators trained the cognitive and visual abilities of seniors and enhanced their abilities to cope with risk situations under various simulated circumstances. Other interventions were also reported to have a positive effect. For evaluating elderly drivers, the driving performance evaluation using a driving simulator was the most common; in addition, evaluations of attention, space-time ability, cognitive function, risk perception, depression and anxiety were also commonly used. We believe that it is appropriate to employ computer-based driving intervention programs for seniors to train and evaluate various domains. We expect that these interventions can be used as an effective tool for safe driving.

• The Journal of the Institute of Internet, Broadcasting and Communication
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• v.21 no.1
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• pp.141-148
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• 2021

In some intersections or busy traffic roads, there are more pedestrians in a specific period of time, and there are many traffic accidents caused by road congestion. Especially at the intersection where there are schools nearby, it is particularly important to protect the traffic safety of students in busy hours. In the past, when designing traffic lights, the safety of pedestrians was seldom taken into account, and the identification of motor vehicles and traffic optimization were mostly studied. How to keep the road smooth as far as possible under the premise of ensuring the safety of pedestrians, especially students, will be the key research direction of this paper. This paper will focus on person, motorcycle, bicycle, car and bus recognition research. Through investigation and comparison, this paper proposes to use YOLO v4 network to identify the location and quantity of objects. YOLO v4 has the characteristics of strong ability of small target recognition, high precision and fast processing speed, and sets the data acquisition object to train and test the image set. Using the statistics of the accuracy rate, error rate and omission rate of the target in the video, the network trained in this paper can accurately and effectively identify persons, motorcycles, bicycles, cars and buses in the moving images.

• Journal of the Korea Institute of Information Security & Cryptology
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• v.16 no.5
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• pp.93-106
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• 2006

With the rapid growth of the wireless Internet communication, a new generation of mobile devices have made possible the broad distribution of mobile digital contents, such as image, music, video, games and applications over the wireless Internet. Mobile devices are rapidly becoming the major means to extend communication channels without copy Protection, usage rule controlling and authentication. As a result, mobile digital contents may be illegally altered, copied and distributed among unauthorized mobile devices. In this paper, we take a look at Open Mobile Alliance (OMA) DRM v2.0 in general, its purpose and function. The OMA is uniquely the focal point for development of an open standard for mobile DRM. Next we introduces features for an active content and illustrates the difference between an active content and an inactive content. Enabling fast rendering of an active content, we propose an OMA-based DRM framework. This framework include the following: 1) Extending DCF Header for supporting an selective encryption, 2) Content encryption key management, 3) Rendering API for an active content. Experimental results show that the proposed framework is able to render an active content fast enough to satisfy Quality of Experience. %is framework has been proposed for a mobile device environment, but it is also applicable to other devices, such as portable media players, set-top boxes, or personal computer.

• Journal of Internet Computing and Services
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• v.23 no.5
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• pp.127-134
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• 2022

Steganography is a hidden technique in which secret messages are hidden in various multimedia files, and it is widely exploited for cyber crime and attacks because it is very difficult for third parties other than senders and receivers to identify the presence of hidden information in communication messages. Botnet typically consists of botmasters, bots, and C&C (Command & Control) servers, and is a botmasters-controlled network with various structures such as centralized, distributed (P2P), and hybrid. Recently, in order to enhance the concealment of botnets, research on Stego Botnet, which uses SNS platforms instead of C&C servers and performs C&C communication by applying steganography techniques, has been actively conducted, but image or video media-oriented stego botnet techniques have been studied. On the other hand, audio files such as various sound sources and recording files are also actively shared on SNS, so research on stego botnet based on audio steganography is needed. Therefore, in this study, we present the results of comparative analysis on hidden capacity by file type and tool through experiments, using a stego botnet that performs C&C hidden communication using audio files as a cover medium in Telegram Messenger.

• The Journal of the Convergence on Culture Technology
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• v.7 no.2
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• pp.85-95
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• 2021

Currently, we stand between computers as creative tools and computers as creators. A new genre of movies, which can be called a post-cinema situation, is emerging. This paper aims to diagnose the possibility of the emergence of AI cinema. To confirm the possibility of AI cinema, it was examined through a case study whether the creation of a story, narrative, image, and sound, which are necessary conditions for film creation, is possible by artificial intelligence. First, we checked the visual creation of AI painting algorithms Obvious, GAN, and CAN. Second, AI music has already entered the distribution stage in the market in cooperation with humans. Third, AI can already complete drama scripts, and automatic scenario creation programs using big data are also gaining popularity. That said, we confirmed that the filmmaking requirements could be met with AI algorithms. From the perspective of Manovich's 'AI Genre Convention', web documentaries and desktop documentaries, typical trends post-cinema, can be said to be representative genres that can be expected as AI cinemas. The conditions for AI, web documentaries and desktop documentaries to exist are the same. This article suggests a new path for the media of the 4th Industrial Revolution era through research on AI as a creator of post-cinema.

• Journal of Korea Society of Industrial Information Systems
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• v.28 no.4
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• pp.1-9
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• 2023

In this paper, we propose a method to recognize the braille blocks for embedded devices in real time through deep learning. First, a deep learning model for braille block recognition is trained on a high-performance computer, and the learning model is applied to a lightweight tool to apply to an embedded device. To recognize the walking information of the braille block, an algorithm is used to determine the path using the distance from the braille block in the image. After detecting braille blocks, bollards, and crosswalks through the YOLOv8 model in the video captured by the embedded device, the walking information is recognized through the braille block path discrimination algorithm. We apply the model lightweight tool to YOLOv8 to detect braille blocks in real time. The precision of YOLOv8 model weights is lowered from the existing 32 bits to 8 bits, and the model is optimized by applying the TensorRT optimization engine. As the result of comparing the lightweight model through the proposed method with the existing model, the path recognition accuracy is 99.05%, which is almost the same as the existing model, but the recognition speed is reduced by 59% compared to the existing model, processing about 15 frames per second.

• Journal of the Korean Society of Floral Art and Design
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• no.41
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• pp.93-114
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• 2019

The purpose of this study is to analyze the characteristics and problems of the content of flower design education videos on YouTube and to search for improvement direction. The subjects of analysis were 129 pieces of videos uploaded in the last one year including 'craftman floral design' as a search term. The result shows that contents covered were practical lectures, theory lectures, test related tips, job and character introduction, test work, educational guidance and publicity. The production format could be divided into studio lecture, classroom lecture, video feature, interview, Vlog, and television program. The hub-type programming strategy that periodically uploads the videos satisfying the target audiences' interests is mostly applied. The type of lecture covered 'practical skill test' got a good response from the users. Overall, content diversity, interaction between creators and users, and harmonious programming strategies are lacking. In order to improve this, it is necessary for emotional and expressive creators to pioneer differentiated fields and practice based on actual field. The introduction of interactive elements such as games and quizzes and the application of new media technologies such as VR and AR are worth trying. Three strategic types of 'hero', 'hub', and 'how to' should be applied complementary. As the demand for education content related to flower design is expected to expand in the future, it is required to develop content that can be used in various platforms, foster professional creators, and develop associated business models.

• Journal of the Korean Society of Floral Art and Design
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• no.41
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• pp.45-59
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• 2019

The characters that could be connected to diverse cultural contents have formed diverse platforms with the development of digital technology, and the size of the relevant industry and market is rapidly growing. Recently, the utilization of character emoticons for smartphone messenger has been rapidly increased, so that the characters are settled down as a tool for non-verbal communication, on top of drawing attention as an independent area. With the expansion of character market, the importance of design that could give interest and familiarity to consumers is more emphasized. The body proportion of characters includes the implicative and symbolic meanings that could express diverse personalities. Thus, this study examined the body proportion of the characters with the high consumers' preference, and then analyzed the characteristics of formative elements of character design in accordance with the body proportion. In the results of the analysis, the exaggerated form of SD characters in two or three-head figure, and the realistic Real characters in seven or eight-head figure were preferred. For the SD characters, the colors with a high chroma showing the cute and cheerful image were used. For the Real characters, the cubic effect was expressed through the colors with active images and the light and shade of color. Even though the SD characters have limited motions due to the omitted body parts, the facial movements of animation characters are exaggerated while the Real characters describe the realistic and dynamic motions.

• KSCE Journal of Civil and Environmental Engineering Research
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• v.29 no.5D
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• pp.611-617
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• 2009

With advanced technologies applied to transportation, realtime traffic information has been necessary for not only drivers but also agencies. In normal, traffic conditions have been represented to three levels according to congestion: "free", "slow", and "jammed". Those categories and criteria are set up for traffic management even though traffic information is provided for drivers. This study examines how drivers feel current congestion levels and delves into traffic categories and criteria which they recognize. To collect data for drivers' recognition, a survey of freeway travellers is conducted answering the question about traffic flow speed from video image on a freeway section. In the result of the survey, the surveyee preferred a 4-level traffic condition including "delayed" to 3-level traffic condition. As its criteria, 20 km/h, 50 km/h, and 75 km/h were obtained. These results are expected to contribute to building more appropriate traffic information for drivers and providing an operational guideline for Traffic Monitering Centers.

• The Journal of The Korea Institute of Intelligent Transport Systems
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• v.21 no.1
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• pp.105-122
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• 2022

According to the statistics about the fatal crashes that have occurred on the expressways for the last 5 years, those who died on the shoulders of the road has been as 3 times high as the others who died on the expressways. It suggests that the crashes on the shoulders of the road should be fatal, and that it would be important to prevent the traffic crashes by cracking down on the vehicles intruding the shoulders of the road. Therefore, this study proposed a method to detect a vehicle that violates the shoulder lane by using the Faster R-CNN. The vehicle was detected based on the Faster R-CNN, and an additional reading module was configured to determine whether there was a shoulder violation. For experiments and evaluations, GTAV, a simulation game that can reproduce situations similar to the real world, was used. 1,800 images of training data and 800 evaluation data were processed and generated, and the performance according to the change of the threshold value was measured in ZFNet and VGG16. As a result, the detection rate of ZFNet was 99.2% based on Threshold 0.8 and VGG16 93.9% based on Threshold 0.7, and the average detection speed for each model was 0.0468 seconds for ZFNet and 0.16 seconds for VGG16, so the detection rate of ZFNet was about 7% higher. The speed was also confirmed to be about 3.4 times faster. These results show that even in a relatively uncomplicated network, it is possible to detect a vehicle that violates the shoulder lane at a high speed without pre-processing the input image. It suggests that this algorithm can be used to detect violations of designated lanes if sufficient training datasets based on actual video data are obtained.