http://chineseinput.net/에서 pinyin(병음)방식으로 중국어를 변환할 수 있습니다.
변환된 중국어를 복사하여 사용하시면 됩니다.
JND-based Multiple Description Image Coding
( Jingxiu Zong ),( Lili Meng ),( Huaxiang Zhang ),( Wenbo Wan ) 한국인터넷정보학회 2017 KSII Transactions on Internet and Information Syst Vol.11 No.8
In this paper, a novel multiple description image coding (MDC) scheme is proposed, which is based on the characteristics of the human visual model. Due to the inherent characteristics of human vision, the human eye can only perceive the change of the specific thresholds, that is, the just noticeable difference (JND) thresholds. Therefore, JND model is applied to improve MDC syetem. This paper calculates the DCT coefficients firstly, and then they are compared with the JND thresholds. The data that is less than the JND thresholds can be neglected, which will improve the coding efficiency. Compared with other existing methods, the experimental results of the proposed method are superior.
Consensus Problems for Discrete-time Agents with Communication Delay
Zhenhua Wang,Huanshui Zhang,Xinmin Song,Huaxiang Zhang 제어·로봇·시스템학회 2017 International Journal of Control, Automation, and Vol.15 No.4
In this paper, consensus problems for first-order multi-agent systems with unstable pole are investigatedover undirected network, where the network is affected by communication delay. By jointly utilizing both thedelayed distributed state information and agent’s own historical input information in the protocol, sufficient conditionrelated to agent dynamic, network topology and communication delay is obtained for consensus, which isalso proven to be necessary in case of one step delay. Furthermore, the consensus problem is studied on conditionthat the delay is time-varying. Finally, numerical simulations are provided to demonstrate the effectiveness of theproposed theoretical results.
Convolutional auto-encoder based multiple description coding network
( Lili Meng ),( Hongfei Li ),( Jia Zhang ),( Yanyan Tan ),( Yuwei Ren ),( Huaxiang Zhang ) 한국인터넷정보학회 2020 KSII Transactions on Internet and Information Syst Vol.14 No.4
When data is transmitted over an unreliable channel, the error of the data packet may result in serious degradation. The multiple description coding (MDC) can solve this problem and save transmission costs. In this paper, we propose a deep multiple description coding network (MDCN) to realize efficient image compression. Firstly, our network framework is based on convolutional auto-encoder (CAE), which include multiple description encoder network (MDEN) and multiple description decoder network (MDDN). Secondly, in order to obtain high-quality reconstructed images at low bit rates, the encoding network and decoding network are integrated into an end-to-end compression framework. Thirdly, the multiple description decoder network includes side decoder network and central decoder network. When the decoder receives only one of the two multiple description code streams, side decoder network is used to obtain side reconstructed image of acceptable quality. When two descriptions are received, the high quality reconstructed image is obtained. In addition, instead of quantization with additive uniform noise, and SSIM loss and distance loss combine to train multiple description encoder networks to ensure that they can share structural information. Experimental results show that the proposed framework performs better than traditional multiple description coding methods.
( Liangliang Wang ),( Jiajun Wang ),( Hao Shi ),( Huaxiang Gu ),( Yu Zhang ),( Xun Li ),( Fei Wang ) 한국미생물 · 생명공학회 2016 Journal of microbiology and biotechnology Vol.26 No.6
Glycerol dehydrogenases (GlyDHs) are essential for glycerol metabolism in vivo, catalyzing its reversible reduction to 1,3-dihydroxypropranone (DHA). The gldA gene encoding a putative GlyDH was cloned from Thermoanaerobacterium thermosaccharolyticum DSM 571 (TtGlyDH) and expressed in Escherichia coli. The presence of Mn(2+) enhanced its enzymatic activity by 79.5%. Three highly conserved residues (Asp(171), His(254), and His(271)) in TtGlyDH were associated with metal ion binding. Based on an investigation of glycerol oxidation and DHA reduction, TtGlyDH showed maximum activity towards glycerol at 60°C and pH 8.0 and towards DHA at 60°C and pH 6.0. DHA reduction was the dominant reaction, with a lower Km(DHA) of 1.08 ± 0.13 mM and Vmax of 0.0053 ± 0.0001 mM/s, compared with glycerol oxidation, with a Km(glycerol) of 30.29 ± 3.42 mM and Vmax of 0.042 ± 0.002 mM/s. TtGlyDH had an apparent activation energy of 312.94 kJ/mol. The recombinant TtGlyDH was thermostable, maintaining 65% of its activity after a 2-h incubation at 60°C. Molecular modeling and site-directed mutagenesis analyses demonstrated that TtGlyDH had an atypical dinucleotide binding motif (GGG motif) and a basic residue Arg(43), both related to dinucleotide binding.
Distributed Consensus for High-order Agent Dynamics with Communication Delay
Zhenhua Wang,Yanli Zhu,Xinmin Song,Huaxiang Zhang 제어·로봇·시스템학회 2020 International Journal of Control, Automation, and Vol.18 No.8
In this paper, consensus problem for high-order multi-agent systems that are at most critically unstable is researched under directed graph. Under the assumption that the delay appears in the communication and being unknown, a distributed protocol with delayed relative state information is proposed to solve the problem, and the design of the constant control gain is not utilizing the precise information of delay. If the agent dynamics has nonzero poles on the imaginary axis, an allowable delay bound is provided to guarantee consensus by studying the joint effects of agent dynamics, network topology and communication delay; otherwise, consensus is tolerant for any large yet bounded communication delay. Especially, it is shown that the unknown delay in communication is allowed to be time-varying if the network topology is undirected, and in this case the delay bound can be enlarged by improving the synchronizability of the undirected graph. Finally, two numerical examples are presented to illustrate the effectiveness of the theoretical result.
Ultra Low Sheet Resistance on Poly Silicon Film by Excimer Laser Activation
다까시노구찌,Hyuck Lim,Do Young Kim,Hans S. Cho,Huaxiang Yin,권장연,Ji-Sim Jung,Jong-Man Kim,Kyung-Bae Park,Wenxu Xianyu,Xiaoxin Zhang 한국물리학회 2006 THE JOURNAL OF THE KOREAN PHYSICAL SOCIETY Vol.48 No.I
We found that the sheet resistance (Rs) value of phosphorus-doped poly-Si film activated by excimer laser annealing (ELA) has a strong correlation with the crystallinity in the film. At the optimum ELA condition of 10 shots and 450 mJ/cm2, we achieved a very low Rs value of 60 ohm/sq. in poly-Si films. With laser activation, we could get much lower Rs than with conventional rapid thermal annealing (RTA), for silicon layers of the same crystallinity level. The active dopant diffusion is observed from the energy which is speculated to correspond to the near-complete-melting energy regime during laser irradiation.
Adversarial Complementary Learning for Just Noticeable Difference Estimation
Dong Yu,Jian Jin,Lili Meng,Zhipeng Chen,Huaxiang Zhang 한국인터넷정보학회 2024 KSII Transactions on Internet and Information Syst Vol.18 No.2
Recently, many unsupervised learning-based models have emerged for Just Noticeable Difference (JND) estimation, demonstrating remarkable improvements in accuracy. However, these models suffer from a significant drawback is that their heavy reliance on handcrafted priors for guidance. This restricts the information for estimating JND simply extracted from regions that are highly related to handcrafted priors, while information from the rest of the regions is disregarded, thus limiting the accuracy of JND estimation. To address such issue, on the one hand, we extract the information for estimating JND in an Adversarial Complementary Learning (ACoL) way and propose an ACoL-JND network to estimate the JND by comprehensively considering the handcrafted priors-related regions and non-related regions. On the other hand, to make the handcrafted priors richer, we take two additional priors that are highly related to JND modeling into account, i.e., Patterned Masking (PM) and Contrast Masking (CM). Experimental results demonstrate that our proposed model outperforms the existing JND models and achieves state-of-the-art performance in both subjective viewing tests and objective metrics assessments.