• Journal of IKEEE
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• v.26 no.2
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• pp.240-248
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• 2022

Floating-point images that express pixel information as real numbers are used in HDR images. There have been various researches on efficient median filter algorithms, but most of them are applicable to 8-bit depth images and there are only a few number of algorithms applicable to floating-point images, including Gil and Werman's algorithm. In this paper, we propose a median filter algorithm that works efficiently on floating-point images by improving Kim's algorithm, which improved Gil and Werman's algorithm. Experimental results show that the execution time is improved by about 10% compared to the Kim's algorithm by reducing the redundant work for the repetitively used binary search tree and applying the inverted index.

• Advances in nano research
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• v.12 no.5
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• pp.489-499
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• 2022

Nanofluids have recently triggered a substantial scientific interest as cooling media. However, their stability is challenging for successful engagement in industrial applications. Different factors, including temperature, nanoparticles and base fluids characteristics, pH, ultrasonic power and frequency, agitation time, and surfactant type and concentration, determine the nanofluid stability regime. Indeed, it is often too complicated and even impossible to accurately find the conditions resulting in a stabilized nanofluid. Furthermore, there are no empirical, semi-empirical, and even intelligent scenarios for anticipating the stability of nanofluids. Therefore, this study introduces a straightforward and reliable intelligent classifier for discriminating among the stability regimes of alumina-water nanofluids based on the Zeta potential margins. In this regard, various intelligent classifiers (i.e., deep learning and multilayer perceptron neural network, decision tree, GoogleNet, and multi-output least squares support vector regression) have been designed, and their classification accuracy was compared. This comparison approved that the multilayer perceptron neural network (MLPNN) with the SoftMax activation function trained by the Bayesian regularization algorithm is the best classifier for the considered task. This intelligent classifier accurately detects the stability regimes of more than 90% of 345 different nanofluid samples. The overall classification accuracy and misclassification percent of 90.1% and 9.9% have been achieved by this model. This research is the first try toward anticipting the stability of water-alumin nanofluids from some easily measured independent variables.

• Smart Structures and Systems
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• v.30 no.2
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• pp.195-207
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• 2022

Computational drawbacks associated with regular predictive models have motivated engineers to use hybrid techniques in dealing with complex engineering tasks like simulating the compressive strength of concrete (CSC). This study evaluates the efficiency of tree potential metaheuristic schemes, namely shuffled complex evolution (SCE), multi-verse optimizer (MVO), and beetle antennae search (BAS) for optimizing the performance of a multi-layer perceptron (MLP) system. The models are fed by the information of 1030 concrete specimens (where the amount of cement, blast furnace slag (BFS), fly ash (FA1), water, superplasticizer (SP), coarse aggregate (CA), and fine aggregate (FA2) are taken as independent factors). The results of the ensembles are compared to unreinforced MLP to examine improvements resulted from the incorporation of the SCE, MVO, and BAS. It was shown that these algorithms can considerably enhance the training and prediction accuracy of the MLP. Overall, the proposed models are capable of presenting an early, inexpensive, and reliable prediction of the CSC. Due to the higher accuracy of the BAS-based model, a predictive formula is extracted from this algorithm.

• Journal of the Institute of Electronics Engineers of Korea CI
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• v.46 no.3
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• pp.96-106
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• 2009

Extending the scale of the distributed processing in a single Ethernet cluster is physically restricted by maximum ports per switch. This paper presents an implementation of MPI-based multicluster consisting of multiple Ethernet switches for extending the scale of distributed processing, and a asymptotical analysis for communication overhead through execution-time analysis model. To determine an optimum task partitioning, we analyzed the processing time for various partitioning schemes, and AAP(accumulator array partitioning) scheme was finally chosen to minimize the overall communication overhead. The scope of data partitioned in AAP was modified to fit for incremented nodes, and suitable load balancing algorithm was implemented. We tried to alleviate the communication overhead through exploiting the pipelined broadcast and flat-tree based result gathering, and overlapping of the communication and the computation time. We used the linear pipeline broadcast to reduce the communication overhead in intercluster which is interconnected by a single link. Experimental results shows nearly linear speedup by the proposed parallel distributed GHT implemented on MPI-based Ethernet multicluster with four 100Mbps Ethernet switches and up to 128 nodes of Pentium PC.

• Journal of the Institute of Electronics and Information Engineers
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• v.53 no.11
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• pp.41-47
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• 2016

High efficiency video coding (HEVC) employs a coding tree unit (CTU) to improve the coding efficiency. A CTU consists of coding units (CU), prediction units (PU), and transform units (TU). All possible block partitions should be performed on each depth level to obtain the best combination of CUs, PUs, and TUs. To reduce the complexity of block partitioning process, this paper proposes the PU mode skip algorithm with region of interest (RoI) selection using motion vector. In addition, this paper presents the CU depth level skip algorithm using the co-located block information in the previously encoded frames. First, the RoI selection algorithm distinguishes between dynamic CTUs and static CTUs and then, asymmetric motion partitioning (AMP) blocks are skipped in the static CTUs. Second, the depth level skip algorithm predicts the most probable target depth level from average depth in one CTU. The experimental results show that the proposed fast CU decision algorithm can reduce the total encoding time up to 44.8% compared to the HEVC test model (HM) 14.0 reference software encoder. Moreover, the proposed algorithm shows only 2.5% Bjontegaard delta bit rate (BDBR) loss.

• Journal of Korean Society of Forest Science
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• v.98 no.5
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• pp.618-629
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• 2009

The objective of this study was to examine the impact of pruning (P treatment) and transplanting (T treatment) of Acer palmatum on cambial growth and compartmentalization of pruning wounds for one year after treatments. Changes of cambial electrical resistance (CER), sizes of pruning wounds, cambial growth of trunks and stems near the wounds, and total phenols at branch unions during the period were examined using a total of 49 trees. After harvesting, areas of discolored wood behind the wounds, relative proportions of extractives, holocellulose and lignin at branch unions were also determined. CER and the cambial growth of trunk at 30 cm above the ground (TGR) were inversely correlated, and differences of CER and TGR among three treatments were significant. TGRs of control, P treatment and P+T treatment after the treatments were 112.2%, 72.4% and 52.5% of the annual growth for the year before the treatments, respectively. The cambial growth rate of stem (SGR) at 1.5 cm above the branch bark ridge and the closure rate of pruning wound (WCR) for one year after treatments were positively correlated, and WCR of P treatment of 39.8% was significantly higher than that of P+T treatment of 31.8%. Wounds of P+T treatment formed greater discolored area per unit area of pruning wound (D/W Ratio) than those of P treatment significantly. Lower WCR and higher D/W Ratio of P+T treatment suggested less ability of compartmentalizing the wounds than P treatment. Total phenols at branch core of pruning wound for both treatments heightened a month after treatment, and then lowered. The contents at below core of the wound were higher than those at control ones continuously, while they became similar each other at above core. Relatively high phenol contents of the extractives at P+T treatment implied that trees with P+T treatment allocated more energy to compartmentalize their wounds. Holocellulose and lignin contents at the branch core of treated branch unions of both treatments were lower and higher, respectively, than at the same part of the union with living branch, as results of the tree reaction to protection from wounding and microbial invasion.

• Korean Journal of Environment and Ecology
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• v.24 no.6
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• pp.735-743
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• 2010

In order to inspect growth responses of Fraxinus rhynchophylla Hance, Koelreuteria paniculata Laxmann, Quercus acutissima Carruther and Ulmus parvifolia Jacquin to NaCl treatment, NaCl solution was treated for four months with 0, 25, 50, 100 and 200 mM concentrations, then survival rate, change of relative growth rate, weight, dry weight and pigment content of leaf were investigated. According to NaCl treatment, pH and EC (electrical conductivity) of soil increased, and growth rates of four tree species fell apparently as treatment time became longer. U. parvifolia had the highest survival rate with 15% in the 200mM treatment, and the other three species withered in the treatment. Relative growth rate, weight and dry weight decreased when NaCl treatment time grew longer. The total chlorophyll declined after it rose to 60 days, and the total chlorophyll and carotenoid of the all species according to NaCl treatment did not change very much. With the result from anlayzing growth responses of four tree species to oxidative stress which occurs during NaCl treatment, U. parvifolia has the highest tolerance, followed by K. paniculata, F. rhynchophylla and Q. acutissima.

• Journal of KIISE
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• v.44 no.9
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• pp.954-965
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• 2017

A stable power supply is very important for the maintenance and operation of the power infrastructure. Accurate power consumption prediction is therefore needed. In particular, a university campus is an institution with one of the highest power consumptions and tends to have a wide variation of electrical load depending on time and environment. For this reason, a model that can accurately predict power consumption is required for the effective operation of the power system. The disadvantage of the existing time series prediction technique is that the prediction performance is greatly degraded because the width of the prediction interval increases as the difference between the learning time and the prediction time increases. In this paper, we first classify power data with similar time series patterns considering the date, day of the week, holiday, and semester. Next, each ARIMA model is constructed based on the classified data set and a daily power consumption forecasting method of the university campus is proposed through the time series cross-validation of the predicted time. In order to evaluate the accuracy of the prediction, we confirmed the validity of the proposed method by applying performance indicators.

• Journal of the Korea Academia-Industrial cooperation Society
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• v.12 no.3
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• pp.1051-1057
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• 2011

By the recently developed GMP(Glass Molding Press) process, aspheric glass lenses are widely used in many optical applications such as digital cameras, optical data storages and electrical devices etc. The GMP process can economically produce complex shaped glass lenses with high precision and good repeatability. This study deals the optimization of molding conditions for aspheric glass lenses in progressive GMP process through Design Of Experiment(Taguchi method). Tree main factors for molding conditions were selected based on pressure, temperature and cooling time at 1st cooling stage. From the analysis of experiments which were preformed with 3-cavity glass mold, it was revealed that the cooling time was the most sensitive parameter for form accuracy(PV) in progressive GMP process.

• The KIPS Transactions:PartC
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• v.8C no.5
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• pp.525-534
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• 2001

Generally, compression and encryption procedures are performed independently in lossless image compression and encryption. When compression is followed by encryption, the compressed-stream should have the property of randomness because its entropy is decreased during the compression. However, when full data is compressed using image compression methods and then encrypted by encryption algorithms, real-time processing is unrealistic due to the time delay involved. In this paper, we propose to combine compression and encryption to reduce the overall processing time. It is method decomposing gray-scale image by means of quadtree compression algorithms and encrypting the structural part. Moreover, the lossless compression ratio can be increased using a transform that provides an decorrelated image and homogeneous region, and the encryption security can be improved using a reconstruction of the unencrypted quadtree data at each level. We confirmed the increased compression ratio, improved encryption security, and real-time processing by using computer simulations.