• Journal of the Institute of Electronics and Information Engineers
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• v.49 no.11
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• pp.86-94
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• 2012

In this paper we propose a hardware architecture of high-speed CGH (computer generated hologram) generation processor, which particularly reduces the number of memory access times to avoid the bottle-neck in the memory access operation. For this, we use three main schemes. The first is pixel-by-pixel calculation rather than light source-by-source calculation. The second is parallel calculation scheme extracted by modifying the previous recursive calculation scheme. The last one is a fully pipelined calculation scheme and exactly structured timing scheduling by adjusting the hardware. The proposed hardware is structured to calculate a row of a CGH in parallel and each hologram pixel in a row is calculated independently. It consists of input interface, initial parameter calculator, hologram pixel calculators, line buffer, and memory controller. The implemented hardware to calculate a row of a $1,920{\times}1,080$ CGH in parallel uses 168,960 LUTs, 153,944 registers, and 19,212 DSP blocks in an Altera FPGA environment. It can stably operate at 198MHz. Because of the three schemes, the time to access the external memory is reduced to about 1/20,000 of the previous ones at the same calculation speed.

• Journal of KIISE:Information Networking
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• v.29 no.3
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• pp.299-313
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• 2002

Recently, the demand for mobile communications and multimedia services has rapidly increased so that conventional cellular system cannot fulfill the requirement of users (capacity and QoS) any more. Therefore, the hierarchical cellular system has been suggested in order to guarantee the QoS and to admit large population of users. IMT-2000 adopts the hierarchical cellular structure, which requires a call control algorithm capable of manipulating and utilizing the complicated structure of hierarchical cellular structure with handiness and efficiency. In this thesis, as an improvement of conventional combined algorithm, a new call control algorithm considering the moving speed of terminal and bandwidth is suggested. This algorithm employs buffers and guard channels to reduce the failure rate. Also, this algorithm considers the moving speed of terminal and bandwidth to elevate the efficiency. Furthermore, calls are handled separately according to the moving speeds of terminal and bandwidths to improve the QoS and reduce the handover rate. As an evaluation of the suggested algorithm, a model hierarchical cellular system is constructed and simulations are conducted with various types of traffic. As the result of the simulations, such indices as block rate, drop rate, channel utilization, and the number of inter layer handovers are examined to demonstrate the excellency fo the suggested algorithm.

• The Journal of the Acoustical Society of Korea
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• v.39 no.5
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• pp.414-423
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• 2020

In this paper, we propose a Dilated Convolution Gate Linear Unit (DCGLU) to mitigate the lack of sparsity and small receptive field problems caused by the segmentation map extraction process in sound event detection with weak labels. In the advent of deep learning framework, segmentation map extraction approaches have shown improved performance in noisy environments. However, these methods are forced to maintain the size of the feature map to extract the segmentation map as the model would be constructed without a pooling operation. As a result, the performance of these methods is deteriorated with a lack of sparsity and a small receptive field. To mitigate these problems, we utilize GLU to control the flow of information and Dilated Convolutional Neural Networks (DCNNs) to increase the receptive field without additional learning parameters. For the performance evaluation, we employ a URBAN-SED and self-organized bird sound dataset. The relevant experiments show that our proposed DCGLU model outperforms over other baselines. In particular, our method is shown to exhibit robustness against nature sound noises with three Signal to Noise Ratio (SNR) levels (20 dB, 10 dB and 0 dB).

• Journal of the Korea Society of Computer and Information
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• v.20 no.5
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• pp.53-63
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• 2015

Singing voice synthesis is the generation of a song using a computer given its lyrics and musical notes. Hidden Markov models (HMM) have been proved to be the models of choice for text to speech synthesis. HMMs have also been used for singing voice synthesis research, however, a huge database is needed for the training of HMMs for singing voice synthesis. And commercially available singing voice synthesis systems which use the piano roll music notation, needs to adopt the easy to read standard music notation which make it suitable for singing learning applications. To overcome this problem, we use a speech database for training context dependent HMMs, to be used for singing voice synthesis. Pitch and duration control methods have been devised to modify the parameters of the HMMs trained on speech, to be used as the synthesis units for the singing voice. This work describes a singing voice synthesis system which uses a MusicXML based music score editor as the front-end interface for entry of the notes and lyrics to be synthesized and a hidden Markov model based text to speech synthesis system as the back-end synthesizer. A perceptual test shows the feasibility of our proposed system.

• Journal of the Institute of Electronics Engineers of Korea CI
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• v.48 no.5
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• pp.88-98
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• 2011

Recently, according as the importance of GIS(geography information system) database security is embossed, much researches had been achieved about GIS network security. But most such researches are weak against sourceful illegal reproductions and distributions of GIS vector data map. In this paper, we proposed an efficient layer unit contents based partial encryption technique in the vector map compression domain to prevent illegal distributions and unauthorized accesses. This method achieves a partial encryption about each central coordinate and directional parameters of a MCA(minimum coding attribute) that is created at the vector map compression processing in the vector space. First, the position encryption is applied as permutating randomly the center coordinate of each record that is minimum unit of vector map shape. And second, the direction encryption that changing shapes of vector map topography is applied as encrypting the direction of vertices's coordinates of each record. In experimental results, we confirmed that our proposed method can encipher the large volumed vector map data effectively in low computational complexity. Also, we could minimize the decline of compression efficiency that occurred by conventional contents based encryption schemes using AES or DES algorithms.

• The Journal of The Korea Institute of Intelligent Transport Systems
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• v.19 no.2
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• pp.89-103
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• 2020

As we face an aging society, the demand for personal mobility for disabled and aged people is increasing. In fact, as of 2017, the number of electric wheelchair in the country continues to increase to 90,000. However, people with disabilities and seniors are more likely to have accidents while driving, because their judgment and coordination are inferior to normal people. One of the causes of the accident is the interference of personal vehicle steering control due to unbalanced road surface conditions. In this paper, we introduce a encoder type semantic segmentation algorithm that can recognize road conditions at high speed to prevent such accidents. To this end, more than 1,500 training data and 150 test data including road surface damage were newly secured. With the data, we proposed a deep neural network composed of encoder stages, unlike the Auto-encoding type consisting of encoder and decoder stages. Compared to the conventional method, this deep neural network has a 4.45% increase in mean accuracy, a 59.2% decrease in parameters, and an 11.9% increase in computation speed. It is expected that safe personal transportation will be come soon by utilizing such high speed algorithm.

• Journal of the Korea Institute of Information and Communication Engineering
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• v.18 no.11
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• pp.2709-2714
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• 2014

This paper has analyzed the change of threshold voltage and conduction path for the ratio of top and bottom gate oxide thickness of asymmetric double gate MOSFET. The asymmetric double gate MOSFET has the advantage that the factor to be able to control the current in the subthreshold region increases. The analytical potential distribution is derived from Poisson's equation to analyze the threshold voltage and conduction path for the ratio of top and bottom gate oxide thickness. The Gaussian distribution function is used as charge distribution. This analytical potential distribution is used to derive off-current and subthreshold swing. By observing the results of threshold voltage and conduction path with parameters of bottom gate voltage, channel length and thickness, projected range and standard projected deviation, the threshold voltage greatly changed for the ratio of top and bottom gate oxide thickness. The threshold voltage changed for the ratio of channel length and thickness, not the absolute values of those, and it increased when conduction path moved toward top gate. The threshold voltage and conduction path changed more greatly for projected range than standard projected deviation.

• Korean Chemical Engineering Research
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• v.57 no.2
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• pp.274-282
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• 2019

In recent years, big data analysis has been expanded to include automatic control through reinforcement learning as well as prediction through modeling. Research on the utilization of image data is actively carried out in various industrial fields such as chemical, manufacturing, agriculture, and bio-industry. In this paper, we applied NASNet, which is an AutoML reinforced learning algorithm, to DeepU-Net neural network that modified U-Net to improve image semantic segmentation performance. We used BRATS2015 MRI data for performance verification. Simulation results show that DeepU-Net has more performance than the U-Net neural network. In order to improve the image segmentation performance, remove dropouts that are typically applied to neural networks, when the number of kernels and filters obtained through reinforcement learning in DeepU-Net was selected as a hyperparameter of neural network. The results show that the training accuracy is 0.5% and the verification accuracy is 0.3% better than DeepU-Net. The results of this study can be applied to various fields such as MRI brain imaging diagnosis, thermal imaging camera abnormality diagnosis, Nondestructive inspection diagnosis, chemical leakage monitoring, and monitoring forest fire through CCTV.

• KSCE Journal of Civil and Environmental Engineering Research
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• v.42 no.5
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• pp.689-699
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• 2022

Recently, high productivity capabilities have been improved due to the application of advanced technologies in various industries, but in the construction industry, productivity improvements have been relatively low. Research on advanced technology for the construction industry is being conducted quickly to overcome the current low productivity. Among advanced technologies, 3D scan technology is widely used for creating 3D digital terrain models at construction sites. In particular, the 3D digital terrain model provides basic data for construction automation processes, such as earthwork machine guidance and control. The quality of the 3D digital terrain model has a lot of influence not only on the performance and acquisition environment of the 3D scanner, but also on the denoising, registration and merging process, which is a preprocessing process for creating a 3D digital terrain model after acquiring terrain scan data. Therefore, it is necessary to improve the terrain scan data processing performance. This study seeks to solve the problem of density inhomogeneity in terrain scan data that arises during the pre-processing step. The study suggests a 'pixel-based point cloud comparison algorithm' and verifies the performance of the algorithm using terrain scan data obtained at an actual earthwork site.

• Journal of the Microelectronics and Packaging Society
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• v.30 no.4
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• pp.86-90
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• 2023

The packaging of electronic devices performs a protective function to ensure that their durability and reliability are not affected by changes in the operating environment caused by external factors. Recent advances in materials have led to ongoing research into bonded packaging of heterogeneous materials such as polymers and inorganic materials in electronic devices. In this packaging process, it is important to have a binding that joins the materials and ensures the operating environment, which includes adhesion to the substrate, corrosion and oxidation resistance through moisture removal, and durability. In this study, the hygroscopicity of the coating layer by modifying the polymer surface based on PVA was evaluated by controlling and measuring the contact angle, and the adhesion was confirmed by applying water-based ink and testing according to ASTM_D3363. For the durability of the polymer surface, the IPL post-treatment process was used to improve the hardness and toughness against applied voltage, and the pencil hardness test and nanoindentation test were conducted. Through this, we analyzed and proposed solutions to ensure the reliability and durability of polymer devices in polymer microfabrication against environmental factors such as moisture, temperature fluctuations and adhesion, and surface abrasion.