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Complex & Intelligent Systems 2025年第7期11卷 1-1页

作者： Yao, Aiting Huang, Chen Zhang, Weiqi Dong, Chengzu Lu, Meiqu Mao, Junjun Liu, Xiao Li, Xuejun Anhui Provincial International Joint Research Center for Advanced Technology in Medical Imaging School of Computer Science and Technology Anhui University Hefei China AI Techplus Pty Ltd Organization Melbourne Australia School of Information Technology Deakin University Geelong Australia School of Data Science Lingnan University Hongkong China School of Artificial Intelligence Guangxi Minzu University Nanning China Key Laboratory of Intelligent Computing and Signal Processing Ministry of Education Hefei China

Exploring cascaded write amplification in LSM-tree based key-value stores with solid-state disks 21

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Exploring cascaded write amplification in LSM-tree based key...

21st IEEE International Conference on High Performance computing and Communications, 17th IEEE International Conference on Smart City and 5th IEEE International Conference on Data Science and Systems, HPCC/SmartCity/DSS 2019

作者： Sun, Hui Dai, Shangshang Huang, Jianzhong Key Laboratory of Intelligent Computing and Signal Processing Ministry of Education School of Computer Sci. and Tech. Anhui University Hefei China Wuhan National Lab. for Optoelectronics Huazhong University of Sci. and Tech Wuhan China

ISBN: (纸本)9781728120584

Log-structured merge tree (i.e., LSM-tree) based key-value stores, which are widely used in big-data applications, provide high performance. NAND Flash-based Solid state disks (i.e., SSDs) become the popular devices that alternative to hard disk drives (i.e., HDDs) because of the high performance and low power consumption. LSM-tree KV stores with SSDs are deployed in large-scale storage systems to achieve high performance in the cloud. However, the host-side write amplification in LSM-tree KV stores and the device-side write amplification in SSDs can impair the overall system performance. The former that is attributed to compaction has a burn on I/O bandwidth between two sides. The latter, which results from garbage collection in NAND Flash memory, blocks user I/Os from the host and degrades the SSD performance. In this study, we explored cascaded write amplification in LSM-tree KV stores with SSDs. Our primary goal is to comprehensively study two-level cascaded write amplification on the host and device sides. We quantitatively analyze the impact of two-level write amplification on overall performance. This work reveals details of cascaded write amplification and helps developers in the software stacks of LSM-tree based KV stores with SSDs. © 2019 IEEE.

关键词： NAND circuits

Separable reversible data hiding based on MSB prediction for encrypted 3D mesh models?

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arXiv 2019年

作者： Xu, Na Yin, Zhaoxia Key Lab of Intelligent Computing and Signal Processing of Ministry of Education School of Computer Science and Technology Anhui University Hefei

Reversible data hiding in encrypted domain (RDH-ED) has received tremendous attention from the research community because data can be embedded into cover media without exposing it to the third party data hider and the cover media can be losslessly recovered after the extraction of the embedded data. Although, in recent years, exten- sive studies have been carried out about images based RDH-ED, little attention is paid to RDH-ED in 3D mesh models due to its complex data structure and irregular geometry. We propose a separable RDH-ED method for 3D mesh models based on MSB (most significant bit) predic- tion. Firstly, we divide all the vertices of the mesh into the "embedded" set and "reference" set according to topological information between ver- tices, and calculate the MSB prediction errors for the vertices of the "em- bedded" set. Then, bit-stream encryption is used to encrypt the mesh. Finally, data is embedded by replacing the MSB of the encrypted vertex coordinates of the "embedded" set by the additional data bits. Recipient with data hiding key can correctly extract the additional data from the marked encrypted mesh. Recipient with encryption key can recover the mesh perfectly by using MSB prediction. Experimental results show that the proposed method has higher embedding capacity and higher quality of the recovered meshes compared to the existing RDH-ED method for 3D meshes based on symmetric encryption. Copyright © 2019, The Authors. All rights reserved.

关键词： Forecasting

A Wideband Dual-Band Magneto-Electric Dipole Antenna with Modified Feed Structure 10

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A Wideband Dual-Band Magneto-Electric Dipole Antenna with Mo...

10th International Conference on Microwave and Millimeter Wave Technology, ICMMT 2018

作者： Li, Fan Sun, Yufa Zhu, Haoran Fang, Ionzvu Anhui University Ministry of Education Key Lab of Intelligent Computing and Signal Processing Hefei230601 China

ISBN: (纸本)9781538624166

In this paper, a novel wideband dual-band magneto-electric dipole antenna with modified feed structure is proposed. Double-layer patches are utilized to design a pair of folding metal. The double-layer patches dipole can generate two resonant frequencies, which are employed to form a dual-band magneto-electric dipole antenna. A stair-shaped feeding strip with a hexagonal structure is designed to modify the impedance matching. It is found from simulated results that two operation bands with bandwidths of 60% from 1.61 to 2.99 GHz and 31.9% from 4.99 to 6.89 GHz under the return loss level of 10 dB were achieved. The gain of the antenna ranged from 7.56 to 10.56 dBi. Furthermore, low cross-polarization level and low back-radiation are also obtained with the proposed antenna. © 2018 IEEE.

关键词： Natural frequencies

A wideband dual-polarized magneto-electric dipole antenna for 2G/3G/LTE/WiMAX base stations

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A wideband dual-polarized magneto-electric dipole antenna fo...

2018 IEEE MTT-S International Wireless Symposium, IWS 2018

作者： Lu, Zongzheng Sun, Yufa Zhu, Haoran Zhang, Hongwei Huang, Fei Key Lab of Intelligent Computing and Signal Processing Ministry of Education Anhui University Hefei230601 China

ISBN: (纸本)9781538663462

A wideband dual-polarized magneto-electric (ME) dipole antenna is proposed for 2G/3G/LTE/WiMAX applications. It also applies to 5G (3.3-3.6 GHz). The proposed antenna has Γ-shaped feeding strips to impart a wide impedance bandwidth for it special structure, and a rectangular box-shaped reflector to enhance its stability in radiation patterns and high gain over the operating frequencies. The simulated results show a common impedance bandwidth is 81.2% with standing-wave ratio (SWR) ≤ 1.5 from 1.58 to 3.74 GHz, port-to-port isolation is large than 25dB within the bandwidth. The simulated antenna gains vary from 8 to 10.7 dBi and from 8.2 to 10.6 dBi for port 1 and port 2, respectively. The antenna has nearly symmetrical radiation patterns with low back lobe radiation both in horizontal and vertical planes, and broadside radiation patterns with narrow beam can be also obtained. © 2018 IEEE.

关键词： Base stations

Multiple reconstruction compression framework based on PNG image

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arXiv 2019年

作者： Lu, Zhiqing Yin, Zhaoxia Luo, Bin Key Lab of Intelligent Computing and Signal Processing of Ministry of Education School of Computer Science and Technology Anhui University Hefei230601 China

It is shown that neural networks (NNs) achieve excellent performances in image compression and reconstruction. However, there are still many shortcomings in the practical application, which eventually lead to the loss of neural network image processing ability. Based on this, this paper proposes a joint framework based on neural network and zoom compression. The framework first encodes the incoming PNG or JPEG image information, and then the image is converted into binary input decoder to reconstruct the intermediate state image, next we import the intermediate state image into the zooming compressor and re-pressurize it, and reconstruct the final image. From the experimental results, this method can better process the digital image and suppress the reverse expansion problem, and the compression effect can be improved by 4 to 10 times as much as that of using RNN alone, showing better ability in application. In this paper, the method is transmitted over a digital image, the effect is far better than the existing compression method alone, the Human visual system can not feel the change of the effect. Copyright © 2019, The Authors. All rights reserved.

关键词： Image compression

Drug3D-DTI: Improved Drug-target Interaction Prediction by Incorporating Spatial Information of Small Molecules

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Drug3D-DTI: Improved Drug-target Interaction Prediction by I...

IEEE International Conference on Bioinformatics and Biomedicine (BIBM)

作者： Zhirui Liao Xiaodi Huang Hiroshi Mamitsuka Shanfeng Zhu School of Computer Science Fudan University Shanghai China Institute of Artificial Intelligence Biomedicine Nanjing University Nanjing China School of Computing Mathematics and Engineering Charles Sturt University Albury NSW Australia Bioinformatics Center Institute for Chemical Research Kyoto University Uji Kyoto Japan Institute of Science and Technology for Brain-Inspired Intelligence Fudan University Shanghai China Key Laboratory of Computational Neuroscience and Brain-Inspired Intelligence (Fudan University) Ministry of Education China MOE Frontiers Center for Brain Science Fudan University Shanghai China Zhangjiang Fudan International Innovation Center Shanghai China Shanghai Key Lab of Intelligent Information Processing Fudan University Shanghai China

ISBN: (纸本)9781665429825

A number of machine learning (ML) approaches for drug discovery have been available that rely only on sequential (1D) and planar (2D) information without effectively using the 3D information for generating features of drugs. However, 3D information of small molecules can reflect relative position of atoms more directly, which affects molecular properties. In this work, we present a new deep learning model called Drug3D-DTI for drug-target interaction prediction. Drug3D-DTI takes advantage of molecular spatial information, i.e., atom proximity in three-dimensional (3D) structures. We comprehensively evaluated the performance of Drug3D-DTI on two datasets with two tasks of regression and classification. In particular, we compared Drug3D-DTI with several existing methods including the two cutting-edge methods for compound-protein interaction prediction. From the experimental results, Drug3D-DTI clearly outperformed other methods under all settings. Further, this performance improvement was validated by ablation experiments and a case study. The implementation of Drug3D-DTI is available at (https://***/zhiruiliao/Drug3D-DTI).

关键词： Drugs Proteins Deep learning Solid modeling Three-dimensional displays Conferences Predictive models

Syntax-enhanced Pre-trained model

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arXiv 2020年

作者： Xu, Zenan Guo, Daya Tang, Duyu Su, Qinliang Shou, Linjun Gong, Ming Zhong, Wanjun Quan, Xiaojun Jiang, Daxin Duan, Nan School of Computer Science and Engineering Sun Yat-sen University Guangzhou China Microsoft Research Asia Beijing China Microsoft Search Technology Center Asia Beijing China Guangdong Key Laboratory Big Data Analysis and Processing Guangzhou China Key Lab. of Machine Intelligence and Advanced Computing Ministry of Education China

We study the problem of leveraging the syntactic structure of text to enhance pre-trained models such as BERT and RoBERTa. Existing methods utilize syntax of text either in the pre-training stage or in the fine-tuning stage, so that they suffer from discrepancy between the two stages. Such a problem would lead to the necessity of having human-annotated syntactic information, which limits the application of existing methods to broader scenarios. To address this, we present a model that utilizes the syntax of text in both pre-training and fine-tuning stages. Our model is based on Transformer with a syntax-aware attention layer that considers the dependency tree of the text. We further introduce a new pre-training task of predicting the syntactic distance among tokens in the dependency tree. We evaluate the model on three downstream tasks, including relation classification, entity typing, and question answering. Results show that our model achieves state-of-the-art performance on six public benchmark datasets. We have two major findings. First, we demonstrate that infusing automatically produced syntax of text improves pre-trained models. Second, global syntactic distances among tokens bring larger performance gains compared to local head relations between contiguous tokens. Copyright © 2020, The Authors. All rights reserved.

关键词： Syntactics

New Framework for Code-Mapping-based Reversible Data Hiding in JPEG Images

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arXiv 2020年

作者： Du, Yang Yin, Zhaoxia Key Lab of Intelligent Computing and Signal Processing of Ministry of Education School of Computer Science and Technology Anhui University Hefei230601 China Anhui Key Laboratory of Multimodal Cognitive Computation School of Computer Science and Technology Anhui University Hefei230601 China School of Communication & Electronic Engineering East China Normal University Shanghai200241 China

Code mapping (CM) is an efficient technique for reversible data hiding (RDH) in JPEG images, which embeds data by constructing a mapping relationship between the used and unused codes in the JPEG bitstream. This study presents a new framework for designing a CM-based RDH method. First, a new code mapping strategy is proposed to suppress file size expansion and improve applicability. Based on our proposed strategy, the mapped codes are redefined by creating a new Huffman table rather than selecting them from the unused codes in the original Huffman table. The critical issue of designing the CM-based RDH method, that is, constructing code mapping, is converted into a combinatorial optimization problem. This study proposes a novel CM-based RDH method that utilizes a genetic algorithm (GA). The experimental results demonstrate that the proposed method achieves a high embedding capacity with no signal distortion while suppressing file size expansion. Copyright © 2020, The Authors. All rights reserved.

关键词： Mapping

Design of Filtering Power Divider with Wide Stopband Based on QMSIW

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Journal of Physics: Conference Series 2020年第1期1651卷

作者： Yi Cheng Zhixiang Huang Zhongmiao Wang Chao Wang Xuemei Li Key Lab of Ministry of Education of Intelligent Computing & Signal Processing Anhui University Hefei Anhui 230601 China

A miniaturized filtering power divider with wide stopband based on quarter-mode substrate integrated waveguide (QMSIW) is proposed. The physical size of the QMSIW is reduced by 3/4 comparing with the traditional SIW structure, which can achieve miniaturization, and its electromagnetic field distribution has little effect. Using the metal interference column and the etched U-shaped groove to adjust the resonance frequency, so that the main mode and the first higher mode form a passband, meanwhile, suppressing the second higher mode. The simulation results show that the center frequency is 4.42 GHz with insertion loss of 0.45 dB, the 3-dB bandwidth is 4.12-4.63 GHz with a fractional bandwidths of 9.7%, and there is a great stopband up to 11 GHz with 15 dB rejection level. Besides, the return loss of passband is better than 17.5 dB. To verify the validity of this design, a prototype is fabricated and measured. The measured results demonstrate that it has a good agreement with the design simulations.

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