• The KIPS Transactions:PartA
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• v.16A no.3
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• pp.209-216
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• 2009

The ubiquitous smart home is the home of the future that takes advantage of context information from the human and the home environment and provides an automatic home service for the human. Human location and motion are the most important contexts in the ubiquitous smart home. We present a real-time human tracker that predicts human location and motion for the ubiquitous smart home. We used four network cameras for real-time human tracking. This paper explains the real-time human tracker's architecture, and presents an algorithm with the details of two functions (prediction of human location and motion) in the real-time human tracker. The human location uses three kinds of background images (IMAGE1: empty room image, IMAGE2: image with furniture and home appliances in the home, IMAGE3: image with IMAGE2 and the human). The real-time human tracker decides whether the human is included with which furniture (or home appliance) through an analysis of three images, and predicts human motion using a support vector machine. A performance experiment of the human's location, which uses three images, took an average of 0.037 seconds. The SVM's feature of human's motion recognition is decided from pixel number by array line of the moving object. We evaluated each motion 1000 times. The average accuracy of all the motions was found to be 86.5%.

• Journal of the Korean Institute of Intelligent Systems
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• v.15 no.2
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• pp.149-162
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• 2005

This paper suggest a way to detect a specific wanted figure in public places such as subway stations and banks by comparing color face images extracted from the real time CCTV with the face images of designated specific figures. Assuming that the characteristic of the surveillance camera allows the face information in screens to change arbitrarily and to contain information on numerous faces, the accurate detection of the face area was focused. To solve this problem, the normalization work using subsampling with $20{\times}20$ pixels on arbitrary face images, which is based on the Perceptron Neural Network model suggested by R. Rosenblatt, created the effect of recogning the whole face. The optimal linear filter and the histogram shaper technique were employed to minimize the outside interference such as lightings and light. The addition operation of the egg-shaped masks was added to the pre-treatment process to minimize unnecessary work. The images finished with the pre-treatment process were divided into three reception fields and the information on the specific location of eyes, nose, and mouths was determined through the neural network. Furthermore, the precision of results was improved by constructing the three single-set network system with different initial values in a row.

• The Journal of the Institute of Internet, Broadcasting and Communication
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• v.16 no.5
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• pp.39-48
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• 2016

One of the major trends of automotive networking architecture is the introduction of automotive Ethernet. Ethernet is already used in single automotive applications (e.g. to connect high-data-rate sources as video cameras), it is expected that the ongoing standardization at IEEE (IEEE802.3bw - 100BASE-T1, respectively IEEE P802.3bp - 1000BASE-T1) will lead to a much broader adoption in future. Those applications will not be limited to simple point-to-point connections, but may affect Electric/Electronic(EE) Architectures as a whole. It is agreed that IP based traffic via Ethernet could be secured by application of well-established IP security protocols (e.g., IPSec, TLS) combined with additional components like, e.g., automotive firewall or IDS. In the case of safety and real-time related applications on resource constraint devices, the IP based communication is not the favorite option to be used with complicated and performance demanding TLS or IPSec. Those applications will be foreseeable incorporate Layer-2 based communication protocols as, e.g., currently standardized at IEEE[13]. The present paper reflects the state-of-the-art communication concepts with respect to security and identifies architectural challenges and potential solutions for future Ethernet Switch-based EE-Architectures. It also gives an overview and provide insights into the ongoing security relevant standardization activities concerning automotive Ethernet. Furthermore, the properties of non-automotive Ethernet security mechanisms as, e.g., IEEE 802.1AE aka. MACsec or 802.1X Port-based Network Access Control, will be evaluated and the applicability for automotive applications will be assessed.

• Journal of Broadcast Engineering
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• v.24 no.5
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• pp.703-712
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• 2019

Single image Super-Resolution (SISR) aims to generate a visually pleasing high-resolution image from its degraded low-resolution measurement. In recent years, deep learning - based super - resolution methods have been actively researched and have shown more reliable and high performance. A typical method is WaveletSRNet, which restores high-resolution images through wavelet coefficient learning based on feature maps of images. However, there are two disadvantages in WaveletSRNet. One is a big processing time due to the complexity of the algorithm. The other is not to utilize feature maps efficiently when extracting input image's features. To improve this problems, we propose an efficient single image super resolution method, named RDB-WaveletSRNet. The proposed method uses the residual dense block to effectively extract low-resolution feature maps to improve single image super-resolution performance. We also adjust appropriated growth rates to solve complex computational problems. In addition, wavelet packet decomposition is used to obtain the wavelet coefficients according to the possibility of large scale ratio. In the experimental result on various images, we have proven that the proposed method has faster processing time and better image quality than the conventional methods. Experimental results have shown that the proposed method has better image quality by increasing 0.1813dB of PSNR and 1.17 times faster than the conventional method.

• The Journal of the Institute of Internet, Broadcasting and Communication
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• v.22 no.6
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• pp.121-127
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• 2022

Smart mirror is an IoT device that attaches a display and an embedded computer to the mirror and provides various information to the useer along with the mirror function. This paper went beyond the form of dealing with smart mirrors only stand alone device the provide information to users, and constructed a network in which smart mirrors are connected, and proposed and implemented a CoMirror system that allows users to talk and share information with other smart mirror users. The CoMirror system has a structure in which several CoMirror clients are connected on one CoMirror server. The CoMirror client consists of Raspberry Pi, a mirror film, a touch pad, a display device, an web camera, etc. The server has functions such as face learning and recognition, user management, a relay role for exchanging messages between clients, and setting up for video call. Users can communicate with other CoMirror users via the server, such as text, image, and audio messages, as well as 1:1 video call.

• Journal of the Korean Geotechnical Society
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• v.39 no.10
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• pp.41-48
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• 2023

The presence of abnormalities in the subgrade of roads poses safety risks to users and results in significant maintenance costs. In this study, we aimed to experimentally evaluate the temperature distributions in abnormal areas of subgrade materials using infrared cameras and analyze the data with machine learning techniques. The experimental site was configured as a cubic shape measuring 50 cm in width, length, and depth, with abnormal areas designated for water and air. Concrete blocks covered the upper part of the site to simulate the pavement layer. Temperature distribution was monitored over 23 h, from 4 PM to 3 PM the following day, resulting in image data and numerical temperature values extracted from the middle of the abnormal area. The temperature difference between the maximum and minimum values measured 34.8℃ for water, 34.2℃ for air, and 28.6℃ for the original subgrade. To classify conditions in the measured images, we employed the image analysis method of a convolutional neural network (CNN), utilizing ResNet-101 and SqueezeNet networks. The classification accuracies of ResNet-101 for water, air, and the original subgrade were 70%, 50%, and 80%, respectively. SqueezeNet achieved classification accuracies of 60% for water, 30% for air, and 70% for the original subgrade. This study highlights the effectiveness of CNN algorithms in analyzing subgrade properties and predicting subsurface conditions.

• Radiation Oncology Journal
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• v.21 no.1
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• pp.100-106
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• 2003

Purpose : To develop a patients' setup verification tool (PSVT) to verify the alignment of the machine and the target isocenters, and the reproduclbility of patients' setup for three dimensional conformal radiotherapy (3DCRT) and intensity modulated radiotherapy (IMRT). The utilization of this system is evaluated through phantom and patient case studies. Materials and methods : We developed and clinically tested a new method for patients' setup verification, using digitally reconstructed radiography (DRR), simulation, porial and digital images. The PSVT system was networked to a Pentium PC for the transmission of the acquired images to the PC for analysis. To verify the alignment of the machine and target isocenters, orthogonal pairs of simulation images were used as verification images. Errors in the isocenter alignment were measured by comparing the verification images with DRR of CT Images. Orthogonal films were taken of all the patients once a week. These verification films were compared with the DRR were used for the treatment setup. By performing this procedure every treatment, using humanoid phantom and patient cases, the errors of localization can be analyzed, with adjustments made from the translation. The reproducibility of the patients' setup was verified using portal and digital images. Results : The PSVT system was developed to verify the alignment of the machine and the target isocenters, and the reproducibility of the patients' setup for 3DCRT and IMRT. The results show that the localization errors are 0.8$\pm$0.2 mm (AP) and 1.0$\pm$0.3 mm (Lateral) in the cases relating to the brain and 1.1$\pm$0.5 mm (AP) and 1.0$\pm$0.6 mm (Lateral) in the cases relating to the pelvis. The reproducibility of the patients' setup was verified by visualization, using real-time image acquisition, leading to the practical utilization of our software Conclusions : A PSVT system was developed for the verification of the alignment between machine and the target isocenters, and the reproduclbility of the patients' setup in 3DCRT and IMRT. With adjustment of the completed GUI-based algorithm, and a good quality DRR image, our software may be used for clinical applications.

• Trans-
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• v.7
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• pp.19-48
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• 2019

This study was described to examine the meaning of the media exhibition work <70mK>, which aims to capture the topography of the collective consciousness of the Korean people through large-scale interviews. <70mK> edits and organizes interview images of individual beings in mosaic-like layouts and forms, creating video exhibitions and holding exhibitions. The objects in the split frame show the continuity of differences that reveal their own thoughts and personalities. This is a synchronic and conscious collective typology in which the intrinsic nature of the individuals is embodied in a simultaneous and holistic image. Interview images reveal their own form as a actual being and convey the intrinsic nature of one's own as oral information. <70mK> constructs a new individualization by aesthetically structuring the forms and information of life individuals in the extension of a specific group. The beings in the frame are not communicating with each other and are looking straight ahead. it conveys to visitors their relationship and personality as the preindividual reality. It is the repetitive arrangement and composition of heterogeneity and difference that each individual shows, and is a chain operation that includes collective identity behind it. <70mK> constructs the direct images and sounds of individual interviewee, creating a new form of information transfer called Video Art Exhibition. This makes metaphors and perceptions of the meaning and process of transindividual relationships and the meaning of psychic individuation and collective individuation. This is an appropriate case to explain with modern technology and individualization of Gilbert Simondon thought together with the meaning of becoming and relation of individualization. The exhibition space constructed by <70mK> is an aesthetic methodology of the psychic and collective meaning and its relationship to a particular group of individuals through which they are connected. Simondon studied the meaning of the process of individualization and the meaning of becoming, and is a philosopher who positively considered the potential of modern technology. <70mK> is a new individual as structured and generated ethical reality mediated by modern technology mechanisms and network behaviors. It is an case of an aesthetic and practical methodology of how interviews function as 'transduction' in the process of individualization in which technology is cooperated. The direct images and sounds of <70mK> are systems in which the information of life individuals is carried, amplified, accumulated and transmitted. It is also a new individual as a psychic and collective landscape. It is a newly became exhibition art work through the multiple individualization, and is a representation of transindividual meanings and process. The media exhibition art of individualized metastable states leads to new relationships in which viewers perceive the same preindividual reality and feel affectivity. The exhibition space of <70mK> becomes a stage for preparing the actual possibility of the transindividual group beyond the representation of the semantic function.

• Journal of Intelligence and Information Systems
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• v.19 no.4
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• pp.147-157
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• 2013

With the advent of the digital environment that can be accessed anytime, anywhere with the introduction of high-speed network, the free distribution and use of digital content were made possible. Ironically this environment is raising a variety of copyright infringement, and product images used in the online shopping mall are pirated frequently. There are many controversial issues whether shopping mall images are creative works or not. According to Supreme Court's decision in 2001, to ad pictures taken with ham products is simply a clone of the appearance of objects to deliver nothing but the decision was not only creative expression. But for the photographer's losses recognized in the advertising photo shoot takes the typical cost was estimated damages. According to Seoul District Court precedents in 2003, if there are the photographer's personality and creativity in the selection of the subject, the composition of the set, the direction and amount of light control, set the angle of the camera, shutter speed, shutter chance, other shooting methods for capturing, developing and printing process, the works should be protected by copyright law by the Court's sentence. In order to receive copyright protection of the shopping mall images by the law, it is simply not to convey the status of the product, the photographer's personality and creativity can be recognized that it requires effort. Accordingly, the cost of making the mall image increases, and the necessity for copyright protection becomes higher. The product images of the online shopping mall have a very unique configuration unlike the general pictures such as portraits and landscape photos and, therefore, the general image watermarking technique can not satisfy the requirements of the image watermarking. Because background of product images commonly used in shopping malls is white or black, or gray scale (gradient) color, it is difficult to utilize the space to embed a watermark and the area is very sensitive even a slight change. In this paper, the characteristics of images used in shopping malls are analyzed and a watermarking technology which is suitable to the shopping mall images is proposed. The proposed image watermarking technology divide a product image into smaller blocks, and the corresponding blocks are transformed by DCT (Discrete Cosine Transform), and then the watermark information was inserted into images using quantization of DCT coefficients. Because uniform treatment of the DCT coefficients for quantization cause visual blocking artifacts, the proposed algorithm used weighted mask which quantizes finely the coefficients located block boundaries and coarsely the coefficients located center area of the block. This mask improves subjective visual quality as well as the objective quality of the images. In addition, in order to improve the safety of the algorithm, the blocks which is embedded the watermark are randomly selected and the turbo code is used to reduce the BER when extracting the watermark. The PSNR(Peak Signal to Noise Ratio) of the shopping mall image watermarked by the proposed algorithm is 40.7~48.5[dB] and BER(Bit Error Rate) after JPEG with QF = 70 is 0. This means the watermarked image is high quality and the algorithm is robust to JPEG compression that is used generally at the online shopping malls. Also, for 40% change in size and 40 degrees of rotation, the BER is 0. In general, the shopping malls are used compressed images with QF which is higher than 90. Because the pirated image is used to replicate from original image, the proposed algorithm can identify the copyright infringement in the most cases. As shown the experimental results, the proposed algorithm is suitable to the shopping mall images with simple background. However, the future study should be carried out to enhance the robustness of the proposed algorithm because the robustness loss is occurred after mask process.