• Journal of the Institute of Electronics Engineers of Korea SP
• /
• v.46 no.2
• /
• pp.1-9
• /
• 2009

In recent years, a film restoration has gained increasing attention by many researchers, to support multimedia service of high quality. In general, an old film is degraded by dust, scratch, flick, and so on. Among these, the common factors are scratch and blotch, so that many researchers have been investigated to restore these degradations. However, the methods in literature have one major limitation: A method is working well in dealing with scratches, however it is poorly working in processing the blotches. The goal of this work is to develop a robust technique to restore images degraded by both scratches and blotches. For this, we use MRF-MAP (Markov random field - maximum a posteriori) framework, so that the restoration problem is considered as the minimization problem of the posteriori energy function. As the minimization is one of complex combinatorial problem, we use distributed genetic algorithms (DGAs) that effectively deal with combinatorial problems. To asses the validity of the proposed method, it was tested on natural old films and artificially degraded films, and the results were compared with other methods. Then, the results show that the proposed method is superior to other methods.

• Journal of Digital Convergence
• /
• v.11 no.11
• /
• pp.767-774
• /
• 2013

The electricity demand and supply could be off balance if several electric vehicles(EVs) were charged at the same time or at peak load times. Therefore, smart grids are necessary to flatten the EVs' electricity demand and to enable EVs to be used as distributed storage devices as electricity demand from EV-charging increases. There are still few quantitative studies on the impact of smart grids on managing EVs' electrical loads. In this study, we analyzed the quantitative impact of smart grids on managing EVs' electrical loads and suggested policy implications. As a result, it is identified that smart grids can manage effectively EVs' impact on electrical grids. The electricity market structure and regulatory framework should support the demonstration and commercialization of smart grid technologies.

• The Journal of Korean Institute of Communications and Information Sciences
• /
• v.28 no.4C
• /
• pp.397-405
• /
• 2003

In this paper, we propose an efficient motion estimation algorithm which can reduce computational complexity by using characteristics of wavelet coefficient in each subband while keeping about the same image quality as in using MRME(multiresolution motion estimation). In general, because of the high similarity between consecutive frames, we first decide whether the motion exists or not by just comparing MAD(mean absolute difference) between blocks with threshold in the lowest subbands of consecutive two frames. If it turns out that there is no motion in the lowest subband, we can also decide no motion exists in the higher subband. This is due to the characteristics of wavelet transform. Conversely, if we find any motion in the lowest subband, we can reduce computational complexity by estimating high subband motion vectors selectively according to the amount of computational complexity by estimating high subband motion vectors selectively according to the amount of energy in that subband. Experimental results are shown that algorithm suggested in this paper maintains about the same PSNR as MRME. However, the processing time was reduced about 30-50% compared with the MRME.

• The KIPS Transactions:PartC
• /
• v.16C no.3
• /
• pp.407-416
• /
• 2009

Recently, various application services in wireless sensor networks are more considered than before, and thus reliable and secure communication of sensor network is turning out as one of essential issues. This paper studies such communication in IEEE 802.15.4 based sensor network. We present IMHRS (IEEE 802.15.4 MAC-based Hybrid hop-by-hop Reliability Scheme) employing EHHR (Enhanced Hop-by-Hop Reliability), which uses Hop-cache and Hop-ack and ALC (Adaptive Link Control), which considers link status and packet type. Also, by selecting security suite depending on network and application type, energy efficiency is considered based on HAS (Hybrid Adaptive Security) Framework. The presented schemes are evaluated by simulations and experiments. Besides, the prototype system is developed and tested to show the potential efficiency.

• The Journal of the Institute of Internet, Broadcasting and Communication
• /
• v.19 no.3
• /
• pp.165-171
• /
• 2019

The study of the computer architecture has shown that major improvements in price-to-energy performance stems from domain-specific hardware development. This paper analyzes the tensor processing unit (TPU) ASIC which can accelerate the reasoning of the artificial neural network (NN). The core device of the TPU is a MAC matrix multiplier capable of high-speed operation and software-managed on-chip memory. The execution model of the TPU can meet the reaction time requirements of the artificial neural network better than the existing CPU and the GPU execution models, with the small area and the low power consumption even though it has many MAC and large memory. Utilizing the TPU for the tensor flow benchmark framework, it can achieve higher performance and better power efficiency than the CPU or CPU. In this paper, we analyze TPU, simulate the Python modeled OpenTPU, and synthesize the matrix multiplication unit, which is the key hardware.

• Journal of the Korea Computer Graphics Society
• /
• v.26 no.5
• /
• pp.1-13
• /
• 2020

In this paper, we propose a new method to stable simulation the directional ice shape by coupling of freezing solver and viscous water flow. The proposed ice modeling framework considers viscous fluid flow in the direction of ice growth, which is important in freezing simulation. The water simulation solution uses the method of applying a new viscous technique to the IISPH(Implicit incompressible SPH) simulation, and the ice direction and the glaze effect use the proposed anisotropic freezing solution. The condition in which water particles change state to ice particles is calculated as a function of humidity and new energy with water flow. Humidity approximates a virtual water film on the surface of the object, and fluid flow is incorporated into our anisotropic freezing solution to guide the growth direction of ice. As a result, the results of the glaze and directional freezing simulations are shown stably according to the flow direction of viscous water.

• The Journal of the Acoustical Society of Korea
• /
• v.25 no.1
• /
• pp.36-42
• /
• 2006

A Principal component analysis (PCA)-based Mel-Frequency Discrete Wavelet Coefficients (MFDWC) feature Parameters for speaker verification system is Presented in this Paper In this method, we used the 1st-eigenvector obtained from PCA to calculate the energy of each node of level that was approximated by. met-scale. This eigenvector satisfies the constraint of general weighting function that the squared sum of each component of weighting function is unity and is considered to represent speaker's characteristic closely because the 1st-eigenvector of each speaker is fairly different from the others. For verification. we used Universal Background Model (UBM) approach that compares claimed speaker s model with UBM on frame-level. We performed experiments to test the effectiveness of PCA-based parameter and found that our Proposed Parameters could obtain improved average Performance of $0.80\%$compared to MFCC. $5.14\%$ to LPCC and 6.69 to existing MFDWC.

• Membrane Journal
• /
• v.34 no.3
• /
• pp.182-191
• /
• 2024

This review addresses the pressing need for effective wastewater treatment methodologies by exploring advanced thin-film nanocomposite (TFN) nanofiltration membranes aimed at efficient dye removal from industrial effluents. Utilizing insights from recent research, the review focuses on the fabrication of TFN membranes incorporating innovative materials such as nanocarbons, silica nanospheres, metal-organic frameworks (MOFs), and MoS₂. The primary goals are to enhance dye removal efficiency, improve antifouling properties, and maintain high selectivity for dye/salt separation. By leveraging the distinct advantages of these nanomaterials-including large surface areas, mechanical robustness, and specific pollutant interaction capabilities-this review aims to overcome the limitations of current nanofiltration technologies and provide sustainable solutions for water treatment challenges.

• Journal of the Korea Academia-Industrial cooperation Society
• /
• v.21 no.11
• /
• pp.672-682
• /
• 2020

The Korea Nowadays, which is research on digital twin technology for efficient operation in various industrial/manufacturing sites, is being actively conducted, and gradual depletion of fossil fuels and environmental pollution issues require new renewable/eco-friendly power generation methods, such as wave power plants. In wave power generation, however, which generates electricity from the energy of waves, it is very important to understand and predict the amount of power generation and operational efficiency factors, such as breakdown, because these are closely related by wave energy with high variability. Therefore, it is necessary to derive a meaningful correlation between highly volatile data, such as wave height data and sensor data in an oscillating water column (OWC) chamber. Secondly, the methodological study, which can predict the desired information, should be conducted by learning the prediction situation with the extracted data based on the derived correlation. This study designed a workflow-based training model using a machine learning framework to predict the pressure of the OWC. In addition, the validity of the pressure prediction analysis was verified through a verification and evaluation dataset using an IoT sensor data to enable smart operation and maintenance with the digital twin of the wave generation system.

• The KIPS Transactions:PartA
• /
• v.16A no.6
• /
• pp.411-418
• /
• 2009

Vector quantization algorithm based on fuzzy clustering has been widely used in the field of data compression since the use of fuzzy clustering analysis in the early stages of a vector quantization process can make this process less sensitive to its initialization. However, the process of fuzzy clustering is computationally very intensive because of its complex framework for the quantitative formulation of the uncertainty involved in the training vector space. To overcome the computational burden of the process, this paper introduces an array architecture for the implementation of fuzzy vector quantization (FVQ). The arrayarchitecture, which consists of 4,096 processing elements (PEs), provides a computationally efficient solution by employing an effective vector assignment strategy during the clustering process. Experimental results indicatethat the proposed parallel implementation providessignificantly greater performance and efficiency than appropriately scaled alternative array systems. In addition, the proposed parallel implementation provides 1000x greater performance and 100x higher energy efficiency than other implementations using today's ARMand TI DSP processors in the same 130nm technology. These results demonstrate that the proposed parallel implementation shows the potential for improved performance and energy efficiency.