• KSII Transactions on Internet and Information Systems (TIIS)
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• v.11 no.6
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• pp.3166-3187
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• 2017

For "generic" multivariate public key cryptography (MPKC) systems, experts believe that the Unbalanced Oil-Vinegar (UOV) scheme is a feasible signature scheme with good efficiency and acceptable security. In this paper, we address two problems that are to find inversion solution of quadratic multivariate equations and find another structure with some random Oil-Oil terms for UOV, then propose a novel signature scheme based on hyper-sphere (HS-Sign for short) which directly answers these two problems. HS-Sign is characterized by its adding Oil-Oil terms and more advantages compared to UOV. On the one side, HS-Sign is based on a new inversion algorithm from hyper-sphere over finite field, and is shown to be a more secure UOV-like scheme. More precisely, according to the security analysis, HS-Sign achieves higher security level, so that it has larger security parameters choice ranges. On the other side, HS-Sign is beneficial from both the key side and computing complexity under the same security level compared to many baseline schemes. To further support our view, we have implemented 5 different attack experiments for the security analysis and we make comparison of our new scheme and the baseline schemes with simulation programs so as to show the efficiencies. The results show that HS-Sign has exponential attack complexity and HS-Sign is competitive with other signature schemes in terms of the length of the message, length of the signature, size of the public key, size of the secret key, signing time and verification time.

• Journal of Ecology and Environment
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• v.43 no.2
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• pp.246-253
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• 2019

Background: Water use efficiency (WUE) is an indicator of the trade-off between carbon uptake and water loss to the atmosphere at the plant or ecosystem level. Understanding temporal dynamics and the response of WUE to climatic variability is an essential part of land degradation assessments in water-limited dryland regions. Alternative definitions of and/or alternative methodologies used to measure WUE, however, have hampered intercomparisons among previous studies of different biomes and regions. The present study aims to clarify semantic differences among WUE parameters applied in previous studies and summarize these parameters in terms of their definition and methodology. Additionally, the consistency of the responses of alternative WUE parameters to interannual changes in moisture levels in Northeast Asia dryland regions (NADRs) was tested. Results: The literature review identified more than five different WUE parameters defined at leaf and ecosystem levels and indicates that major conclusions regarding the WUE response to climatic variability were partly inconsistent depending on the parameters used. Our demonstration of WUE in NADR again confirmed regional inconsistencies and further showed that inconsistencies were more distinct in hyper- and semi-arid climates than in arid climates, which might reflect the different relative roles of physical and biological processes in the coupled carbon-water process. Conclusions: The responses of alternative WUE parameters to drying and wetting may be different in different regions, and regionally different response seems to be related to aridity, which determines vegetation coverage.

• Journal of Broadcast Engineering
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• v.28 no.2
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• pp.213-229
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• 2023

In this paper, we introduce a spatial sound rendering system that provides 6DoF spatial sound in real time in response to the movement of a listener located in a virtual environment. This system was implemented using MPEG-I AEP as a development environment for the CfP response of MPEG-I Immersive Audio and consists of an encoder and a renderer including a decoder. The encoder serves to offline encode metadata such as the spatial audio parameters of the virtual space scene included in EIF and the directivity information of the sound source provided in the SOFA file and deliver them to the bitstream. The renderer receives the transmitted bitstream and performs 6DoF spatial sound rendering in real time according to the position of the listener. The main spatial sound processing technologies applied to the rendering system include sound source effect and obstacle effect, and other ones for the system processing include Doppler effect, sound field effect and etc. The results of self-subjective evaluation of the developed system are introduced.

• Journal of the Korean Data and Information Science Society
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• v.20 no.4
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• pp.749-755
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• 2009

Support vector classification (SVC) provides more complete description of the lin-ear and nonlinear relationships between input vectors and classifiers. In this paper. we propose the sparse kernel classifier to solve the optimization problem of classification with a modified hinge loss function and absolute loss function, which provides the efficient computation and the sparsity. We also introduce the generalized cross validation function to select the hyper-parameters which affects the classification performance of the proposed method. Experimental results are then presented which illustrate the performance of the proposed procedure for classification.

• Journal of the Korean Statistical Society
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• v.32 no.2
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• pp.175-191
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• 2003

An empirical Bayesian approach is discussed for estimation of characteristics from the two-way balanced rotation sampling design which includes U.S. Current Population Survey and Canadian Labor Force Survey as special cases. An empirical Bayesian estimator is derived for monthly effect under presence of two types of biases and correlations It is shown that the marginal distribution of observation provides more general correlation structure than that frequentist has assumed. Consistent estimators are derived for hyper-parameters in Normal priors.

• Journal of the Korean Data and Information Science Society
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• v.26 no.2
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• pp.517-524
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• 2015

Unlabeled examples are easier and less expensive to be obtained than labeled examples. In this paper semisupervised approach is used to utilize such examples in an effort to enhance the predictive performance of nonlinear quantile regression problems. We propose a semisupervised quantile regression method named semisupervised support vector quantile regression, which is based on support vector machine. A generalized approximate cross validation method is used to choose the hyper-parameters that affect the performance of estimator. The experimental results confirm the successful performance of the proposed S2SVQR.

• Journal of the Korean Data and Information Science Society
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• v.25 no.6
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• pp.1539-1547
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• 2014

In this paper we apply the autoregressive process to the nonlinear quantile regression in order to infer nonlinear quantile regression models for the autocorrelated data. We propose a kernel method for the autoregressive data which estimates the nonlinear quantile regression function by kernel machines. Artificial and real examples are provided to indicate the usefulness of the proposed method for the estimation of quantile regression function in the presence of autocorrelation between data.

• Journal of Welding and Joining
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• v.35 no.2
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• pp.58-62
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• 2017

A319 aluminum alloy containing 6.5% Si and 3.5% Cu as major alloying elements has been widely used in machinery parts because of its excellent castability and crack resistance. However it needs more wear resistance to extend its usage to the severe wear environments. It has been known that hyper-eutectic Al-Si alloy having more than 12.6% Si contains pro-eutectic Si particles, which give better wear resistance and lubrication characteristics than hypo-eutectic Al-Si alloy like A319 alloy. In this study, it was tried to clad hyper-eutectic Al-Si alloy on the surface of A319 alloy. In the experiments, Al-36%Si alloy powder was mixed with organic binder to make a fluidic paste. The paste was screen-printed on the A319 alloy surface, melted by pulsed Nd:YAG laser and alloyed with the A319 base alloy. As experimental parameters, the average laser power was changed to 111 W, 202 W and 280 W. With increasing the average laser power, the melting depth was changed to $142{\mu}m$, $205{\mu}m$ and $245{\mu}m$, and the dilution rate to 67.2 %, 72.4 % and 75.7 %, and the Si content in the cladding layer to 16.2 %, 14.6 % and 13.7 %, respectively. The cross-section of the cladding layer showed very fine eutectic microstructure even though it was hyper-eutectic Al-Si alloy. This seems to be due to the rapid solidification of the melted spot by single laser pulse. The average hardness for the three cladding layers was HV175, which was much higher than HV96 of A319 base alloy. From the block-on-roll wear tests, A319 alloy had a wear loss of 5.8 mg, but the three cladding layers had an average wear loss of 3.5 mg, which meant that an increase of 40 % in wear resistance was obtained by laser cladding.

• Journal of Information Technology Services
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• v.19 no.5
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• pp.83-91
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• 2020

Language Models such as BERT has been an important factor of deep learning-based natural language processing. Pre-training the transformer-based language models would be computationally expensive since they are consist of deep and broad architecture and layers using an attention mechanism and also require huge amount of data to train. Hence, it became mandatory to do fine-tuning large pre-trained language models which are trained by Google or some companies can afford the resources and cost. There are various techniques for fine tuning the language models and this paper examines three techniques, which are data augmentation, tuning the hyper paramters and partly re-constructing the neural networks. For data augmentation, we use no-answer augmentation and back-translation method. Also, some useful combinations of hyper parameters are observed by conducting a number of experiments. Finally, we have GRU, LSTM networks to boost our model performance with adding those networks to BERT pre-trained model. We do fine-tuning the pre-trained korean-based language model through the methods mentioned above and push the F1 score from baseline up to 89.66. Moreover, some failure attempts give us important lessons and tell us the further direction in a good way.

• Transactions of Materials Processing
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• v.22 no.8
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• pp.470-476
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• 2013

The aim of the current study was to predict shape recovery behavior of Ni-Ti shape memory alloy (SMA) wire after loading-unloading and after wire drawing. The superelasticity of SMA was analyzed by a hyper-elastic model for the Mullins effect using ABAQUS. Firstly, tensile tests and loading-unloading tests of the Ni-Ti SMA wire with a diameter 1.0 mm were performed using an MTS servo-hydraulic tester. The parameters for the Mullins effect were computed by ABAQUS based on curve-fitting of the loading-unloading test data. The proposed FE-model predicted the shape recovery of Ni-Ti SMA after wire drawing. Finally, the effectiveness of the model was verified by drawing experiments. The wire drawing experiments using the Ni-Ti SMA were conducted on a drawing machine(1ton, 50mm/s). In order to evaluate the shape recovery of Ni-Ti SMA, the drawn wires are annealed for 30min at $450^{\circ}C$.