• The Journal of Korean Institute of Communications and Information Sciences
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• v.41 no.9
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• pp.1141-1145
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• 2016

In general, a variable forgetting factor is applied to the RLS algorithm for the time-varying parameter estimation in the non-stationary environments. The introduction of a variable forgetting factor to RLS needs heavy additional calculation complexity. We propose a new Gauss Newton variable forgetting factor RLS algorithm which needs small amount of calculation as well as estimates the better parameters in time-varying nonstationary environment. The algorithm performs as good as the conventional Gauss Newton variable forgetting factor RLS and the required additional calculation complexity reduces from $O(N^2)$ to O(N).

• Journal of Multimedia Information System
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• v.8 no.3
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• pp.147-158
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• 2021

Versatile Video Coding (VVC) is the latest video coding standard developed by Joint Video Exploration Team (JVET). In VVC, the quadtree plus multi-type tree (QT+MTT) structure of coding unit (CU) partition is adopted, and its computational complexity is considerably high due to the brute-force search for recursive rate-distortion (RD) optimization. In this paper, we aim to reduce the time complexity of inter-picture prediction mode since the inter prediction accounts for a large portion of the total encoding time. The problem can be defined as classifying the split mode of each CU. To classify the split mode effectively, a novel convolutional neural network (CNN) called multi-level tree (MLT-CNN) architecture is introduced. For boosting classification performance, we utilize additional information including inter-picture information while training the CNN. The overall algorithm including the MLT-CNN inference process is implemented on VVC Test Model (VTM) 11.0. The CUs of size 128×128 can be the inputs of the CNN. The sequences are encoded at the random access (RA) configuration with five QP values {22, 27, 32, 37, 42}. The experimental results show that the proposed algorithm can reduce the computational complexity by 11.53% on average, and 26.14% for the maximum with an average 1.01% of the increase in Bjøntegaard delta bit rate (BDBR). Especially, the proposed method shows higher performance on the sequences of the A and B classes, reducing 9.81%~26.14% of encoding time with 0.95%~3.28% of the BDBR increase.

• The Journal of the Institute of Internet, Broadcasting and Communication
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• v.21 no.4
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• pp.177-182
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• 2021

Generally, the linear programming (LP) with O(n⁴) time complexity is applied to mixture optimization problem that can be produce the given ingredients grade product with minimum cost from mixture of various raw materials. This paper suggests heuristic algorithm with O(n log n) time complexity to obtain the solution of this problem. The proposed algorithm meets the content range of the components required by the alloy steel plate while obtaining the minimum raw material cost, decides the quantity of raw material that is satisfied with ingredients grade for ascending order of unit cost. Although the proposed algorithm applies simple decision technique with O(n log n) time complexity, it can be obtains same solution as or more than optimization technique of linear programing.

• Journal of the Korea Computer Industry Society
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• v.7 no.5
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• pp.513-520
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• 2006

In this paper, we propose a novel real-time frame-layer rate control algorithm using sliding window method for low bit rate video coding. The proposed rate control method performs bit allocation at the frame level to minimize the average distortion over an entire sequence as well as variations in distortion between frames. A new frame-layer rate-distortion model is derived, and a non-iterative optimization method is used for low computational complexity. In order to reduce the quality fluctuation, we use a sliding window scheme which does not require the pre-analysis process. Therefore, the proposed algorithm does not produce time delay from encoding, and is suitable for real-time low-complexity video encoder. Experimental results indicate that the proposed control method provides better visual and PSNR performance than the existing TMN8 rate control method.

• Journal of the military operations research society of Korea
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• v.17 no.2
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• pp.113-122
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• 1991

This paper presents the Allocation Priority Scheme (APS) for multiprocessor system. The objective of APS is to reduce the time-complexity on a Physical Mapping Scheme(PMS). The PMS is to allocate the nodes of the Data Dependency Graph (DDG) to the multprocessors efficiently and effectively. The APS provides the priority to each node (vertex) in the DDG. In other words, the goal of the APS is to find a request resource mapping such that the total cost (time-complexity) is minimized. The special case in which all requests have equal priorities and all resoruces have equal precedences, and the comparisons between our APS and other schems are discussed in the paper. The APS provides the heuristic rules which are based on maximum height (MH), number of children nodes ($N_c$), number of father nodes ($N_f$), and computation time ($T_c$). The estimation moth of the computaion time is in the paper.

• Journal of Korea Multimedia Society
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• v.10 no.12
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• pp.1612-1621
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• 2007

In this paper, we introduced our designed TDMA (Time Division Multiple Access) based MAC (Medium Access Control) protocol for Home Networks called HomeTDMA. We have implemented and tested it in a test bed using crossbow motes and TinyOS. We also have compared HomeTDMA and CSMA (Carrier Sense Multiple Access) in terms of space and time complexity, channel access time, delivery success ratio, and throughput. Based on our results, HomeTDMA has an advantage over CSMA on channel access time, throughput and delivery success ratioIn the case of complexity, HomeTDMA is more complex compared to CSMA. Thus, CSMA is more appropriate in wireless sensor networks (WSNs) where memory, energy, and throughput are important parameters to be considered. However, HomeTDMA has a natural advantage of collision free medium access and is very promising for home networks where a reliable transmission or data transfer and congestion control is highly preferred.

• Journal of the Institute of Electronics Engineers of Korea TC
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• v.46 no.3
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• pp.15-18
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• 2009

In this paper, we propose ST-MWSK (space-time M-ary orthogonal Walsh sequence keying) employing MWSK which does not require channel estimation at the receiver. The computational complexity for the noncoherent ML (maximum-likelihood) detector of ST-MWSK is significantly reduced compared to that of ST-FSK (ST frequency-shift keying). Also, the performance of ST-MWSK is virtually identical to that of ST-FSK.

• Journal of Korea Multimedia Society
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• v.16 no.4
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• pp.444-452
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• 2013

Operation time of a function or procedure is a thing that always needs to be optimized. Parallelizing the operation is the general method to reduce the operation time of the function. One of the most powerful parallelizing methods is using GPU. In image processing field, one of the most commonly used operations is morphology operation. Three types of morphology operations kernel, na$\ddot{i}$ve, global and shared, are presented in this paper. All kernels are made using CUDA and work parallel on GPU. Four morphology operations (erosion, dilation, opening, and closing) using square structuring element are tested on MRI images with different size to measure the speedup of the GPU implementation over CPU implementation. The results show that the speedup of dilation is similar for all kernels. However, on erosion, opening, and closing, shared kernel works faster than other kernels.

• Proceedings of the Korean Institute of Information and Commucation Sciences Conference
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• 2022.10a
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• pp.93-96
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• 2022

DTW can eliminate gaps between sequences of different lengths and find out the similarity of patterns, but due to the time and space complexity, it requires a high computational cost on large datasets. In this paper, we propose a DDTW algorithm that not only reduces computational costs but also has no error in the results. In addition, the algorithm complexity of DTW and DDTW is compared by measuring the computational time according to the length of the sequence. Simulation results show a noticeable reduction in computational time in DDTW compared to DTW.

• Journal of the Korean Operations Research and Management Science Society
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• v.41 no.1
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• pp.87-98
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• 2016

A single machine scheduling problem for jobs with stochastic processing time is considered in this study. Shortest processing time (SPT) sequencing according to the expected processing times of jobs is optimal for schedules with minimal expected mean flow time when all the jobs arrive to be scheduled and their expected processing times are known. However, SPT sequencing according to the expected processing time may not be optimal for the minimization of the mean flow time when the actual processing times of jobs are known. This study evaluates the complexity of SPT sequencing through a comparison of the mean flow times of schedules based on the expected processing times and actual processing times of randomly generated jobs. Evaluation results show that SPT sequencing according to the expected flow time exhibits chaotic variation to the optimal mean flow time. The relative deviation from the optimal mean flow time increases as the number of jobs, processing time, or coefficient of variation increases.