• International journal of advanced smart convergence
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• v.7 no.1
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• pp.42-47
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• 2018

Recently, as the demand for limited resources continues to rise and problems of resource depletion rise worldwide, the importance of renewable energy is gradually increasing. In order to solve these problems, various methods such as energy conservation and alternative energy development have been suggested, and biogas, which can utilize the gas produced from biomass as fuel, is also receiving attention as the next generation of innovative renewable energy. New and renewable energy using biogas is an energy production method that is expected to be possible in large scale because it can supply energy with high efficiency in compliance with energy supply method of recycling conventional resources. In order to more efficiently produce and manage these biogas, a biogas plant has emerged. In recent years, a large number of biogas plants have been installed and operated in various locations. Organic wastes corresponding to biogas production resources in a biogas plant exist in a wide variety of types, and each of the incoming raw materials is processed in different processes. Because such a process is required, the case where the biogas plant process is inefficiently operated is continuously occurring, and the economic cost consumed for the operation of the biogas production relative to the generated biogas production is further increased. In order to solve such problems, various attempts such as process analysis and feedback based on the feedstock have been continued but it is a passive method and very limited to operate a medium/large scale biogas plant. In this paper, we propose "CNN-based production yield prediction algorithm for increasing process efficiency of biogas plant" for efficient operation of biogas plant process. Based on CNN-based production yield forecasting, which is one of the deep-leaning technologies, it enables mechanical analysis of the process operation process and provides a solution for optimal process operation due to process-related accumulated data analyzed by the automated process.

• Journal of the Korea Society of Computer and Information
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• v.20 no.2
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• pp.47-54
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• 2015

Emotional reaction of audience can be decided by observing reaction of audience for content. We can use a method to analyze visual data from video camera to detect reaction of audience fast and economically. This paper proposes the method and system to observe audience reaction from visual data of audience and define via neural network. Also we propose a new method to detect automatically an area for audience reaction with face detection to improve a fixed area assignment method which has a limitation not to adapt depending on audiences. Additionally, the evaluation is implemented to show that the proposed method and system is effective. The proposed method showed the performance elevation of 10.5 % (7.75 hit ration) compared to a fixed area assignment method.

• Journal of the Korea Society of Computer and Information
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• v.16 no.3
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• pp.229-236
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• 2011

In this paper we present light weighted English-to-Korean and Korean-to-English mobile translators on smart phones. For natural translation and higher translation quality, translation engines are hybridized with Translation Memory (TM) and Rule-based translation engine. In order to maximize the usability of the system, we combined an Optical Character Recognition (OCR) engine and Text-to-Speech (TTS) engine as a Front-End and Back-end of the mobile translators. With the BLEU and NIST evaluation metrics, the experimental results show our E-K and K-E mobile translation equality reach 72.4% and 77.7% of Google translators, respectively. This shows the quality of our mobile translators almost reaches the that of server-based machine translation to show its commercial usefulness.

• The Journal of Korean Institute of Communications and Information Sciences
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• v.39A no.11
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• pp.625-636
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• 2014

In this paper, we propose a new embedded image compression scheme which uses rate-distortion optimized block coding of wavelet coefficients. Unlike to previous works in which set-partition or block-partition is performed according to the magnitude of wavelet coefficients, the proposed scheme achieves rate-distortion optimization by sorting wavelet coefficients or blocks according to their expected rate-distortion slope. At the same time, it performs the optimized block-partition coding using the expected rate-distortion slope of blocks. The proposed scheme also uses various relationship of wavelet coefficients for the entropy coding. Experimental results demonstrate that the proposed image compression scheme provides better overall performance than the existing embedded coding schemes such as SPIHT and EBCOT, in which the PSNR gains of the proposed scheme are about 0.11~1.16dB and -0.18~0.52dB, respectively.

• The Journal of the Korea institute of electronic communication sciences
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• v.13 no.4
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• pp.795-802
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• 2018

This study describes the semantic theoretic interpretation through the extensive use of semantic metaphors for intensive web interface with information and the metaphoric value of metaphors for interface design. Common factors that influence web design are empirical establishment and verification for generating web symbols and these are have important elemental perspectives that are used to assess the usefulness and key elements of the site. In addition, the structure of the screen has begun to change dynamically from the application of web technological functions, and the media functions have become important to make web standards when implementing visual structuring from the perspective of semiotic. Instead of using a technical expression approach to examine semiotic, a semiotic approach is applied to create aesthetic codes through the human-computer interface in terms of semiotic in a variety of natural and universal fields. Based on this, it is used as means of communication to convey the intended meaning to users so as to highlight the importance of the usability issues and metaphors user interface.

• Transactions of the Korean Society of Mechanical Engineers A
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• v.41 no.4
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• pp.333-336
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• 2017

A speaker diaphragm generates a divided vibration. The influence of the break-up mode is sufficient to cause a shape change in the diaphragm. In this paper, is widely used in ultra-thin multi-media devices, including smart phones is the advance guard of the IT sector, the micro-speakers and its target. Micro-speakers are different from general speakers. The plate has structural form and space constraints. In particular, they utilize a closed-type drive space. It is difficult to provide cooling for the auxiliary suspension structure because of the heat generated in the moving coil. The present study considered the relationship between the break-up mode and the heat transfer of the diaphragm. An experiment was conducted in two stages to compare the embodiment of the break-up mode and heat transfer in a certain frequency range. The changes in the heat were determined through measurements and thermal imaging of the break-up mode. The break-up mode tendency of the diaphragm could be rapidly predicted based on the imaging results using the thermal imaging camera. This will help in the optimal design of micro-speakers.

• The Journal of Korean Institute of Communications and Information Sciences
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• v.41 no.10
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• pp.1155-1166
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• 2016

In this paper, we propose a new embedded video compression scheme which uses three-dimensional rate-distortion optimization based block coder. After the proposed scheme removes temporal redundancy by applying the motion compensated temporal filtering(MCTF) on input video frames, two dimensional discrete wavelet transform is applied on video frames to remove spatial redundancy. The three-dimensional wavelet coefficients generated in this way are sorted according to their expected rate-distortion slope and encoded by using the three-dimensional block partition coding method. The proposed scheme also uses both the effective color video coding method which maintains embedded features, and the efficient bit-rate control method. Experimental results demonstrate that the proposed scheme not only produces embedded bit-streams, but also outperforms existing video compression schemes.

• The Journal of Korea Institute of Information, Electronics, and Communication Technology
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• v.11 no.5
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• pp.487-492
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• 2018

Recently, various applications for image processing have been ported to the mobile environment due to the expansion of the image shooting on the mobile device. However, in the case of extracting the image foreground, which is one of the most important functions of image synthesis, is difficult since it needs complex calculation. In this paper, we propose an video synthesis technique that can divide images captured by mobile devices into foreground / background and combine them in real time on target images. Considering the characteristics of mobile shooting, our system can extract automatically foreground of input video that contains weak motion when shooting. Using SIMD and GPGPU-based acceleration algorithms, SD-quality images can be processed on mobile in real time.

• Journal of KIISE
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• v.43 no.1
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• pp.47-53
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• 2016

While the Internet develops rapidly, a huge amount of image data collected from smart phones, digital cameras and black boxes are being shared through social media sites. Generally, social images are handled by tagging them with information. Due to the ease of sharing multimedia and the explosive increase in the amount of tag information, it may be considered too much hassle by some users to put the tags on images. Image retrieval is likely to be less accurate when tags are absent or mislabeled. In this paper, we suggest a method of extracting tags from social images by using image content. In this method, CNN(Convolutional Neural Network) is trained using ImageNet images with labels in the training set, and it extracts labels from instagram images. We use the extracted labels for automatic image tagging. The experimental results show that the accuracy is higher than that of instagram retrievals.

• The Korean Journal of Applied Statistics
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• v.29 no.4
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• pp.719-728
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• 2016

In this paper, we analyzed IoT patent data using the social network analysis of keyword community network in patents related to Internet of Things technology. To identify the difference of IoT patent trends between Korea and USA, 100 Korea patents and 100 USA patents were collected, respectively. First, we first extracted important keywords from IoT patent abstracts using the TF-IDF weight and their correlation and then constructed the keyword network based on the selected keywords. Second, we constructed a keyword community network based on the keyword community and performed social network analysis. Our experimental results showed while Korea patents focus on the core technologies of IoT (such as security, semiconductors and image process areas), USA patents focus on the applications of IoT (such as the smart home, interactive media and telecommunications).