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A Time-Aware Dynamic Service Quality Prediction Approach for Services

Tsinghua Science and Technology 2020年第2期25卷 227-238页

作者： Ying Jin Weiguang Guo Yiwen Zhang Department of Management Hefei UniversityHefei 230601China School of Computer Science and Technology and also with the Key Laboratory of Intelligent Computing and Signal ProcessingMinistry of EducationAnhui UniversityHefei 230601China

Dynamic Quality of Service(QoS)prediction for services is currently a hot topic and a challenge for research in the fields of service recommendation and *** paper addresses the problem with a Time-aWare service Quality Prediction method(named TWQP),a two-phase approach with one phase based on historical time slices and one on the current time *** the first phase,if the user had invoked the service in a previous time slice,the QoS value for the user calling the service on the next time slice is predicted on the basis of the historical QoS data;if the user had not invoked the service in a previous time slice,then the Covering Algorithm(CA)is applied to predict the missing *** the second phase,we predict the missing values for the current time slice according to the results of the previous phase.A large number of experiments on a real-world dataset,WS-Dream,show that,when compared with the classical QoS prediction algorithms,our proposed method greatly improves the prediction accuracy.

关键词： dynamic Quality of Service(QoS)prediction time-aware service recommendation

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HRTransNet: HRFormer-Driven Two-Modality Salient Object Detection

arXiv

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arXiv 2023年

作者： Tang, Bin Liu, Zhengyi Tan, Yacheng He, Qian School of Artificial Intelligence and Big Data Hefei University Hefei China Key Laboratory of Intelligent Computing and Signal Processing of Ministry of Education School of Computer Science and Technology Anhui University Hefei China

The High-Resolution Transformer (HRFormer) can maintain high-resolution representation and share global receptive fields. It is friendly towards salient object detection (SOD) in which the input and output have the same resolution. However, two critical problems need to be solved for two-modality SOD. One problem is two-modality fusion. The other problem is the HRFormer output’s fusion. To address the first problem, a supplementary modality is injected into the primary modality by using global optimization and an attention mechanism to select and purify the modality at the input level. To solve the second problem, a dual-direction short connection fusion module is used to optimize the output features of HRFormer, thereby enhancing the detailed representation of objects at the output level. The proposed model, named HRTransNet, first introduces an auxiliary stream for feature extraction of supplementary modality. Then, features are injected into the primary modality at the beginning of each multi-resolution branch. Next, HRFormer is applied to achieve forwarding propagation. Finally, all the output features with different resolutions are aggregated by intra-feature and inter-feature interactive transformers. Application of the proposed model results in impressive improvement for driving two-modality SOD tasks, e.g., RGB-D, RGB-T, and light field ***://***/liuzywen/HRTransNet Copyright © 2023, The Authors. All rights reserved.

关键词： Global optimization

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Broadband High Gain Composite VHF Monopole Antenna Design

Broadband High Gain Composite VHF Monopole Antenna Design

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IEEE International Conference on Electronic Information and Communication Technology (ICEICT)

作者： Lihua Wang Baofeng Cao Peng Li Zongxiang Li Yingsong Li College of Information and Communication Engineering Harbin Engineering University Harbin China State Key Laboratory of Nuclear and Biochemical Calamity Protection for Civilian Beijing China Key Laboratory of Intelligent Computing and Signal Processing Ministry of Education Anhui University Hefei China

A novel wideband miniaturized composite monopole antenna is proposed, analysed and investigated in detail, where the antenna consists of a conical monopole structure with a loaded capacitive disc. The antenna is composed of multiple nested section, aiming to reduce the profile of the antenna. The loading disc at its top is equivalent to a capacitive structure to improve the antenna matching and the stability of the pattern. According to the simulation results, the impedance bandwidth $(\mathbf{S}_{\mathbf{11}} < -\mathbf{10})$ is 132.9% $(\mathbf{60.45}\sim \mathbf{300}\ \mathbf{MHz})$ , or even wider. The gain at the entire frequency averages 3 dBi. The performance of the antenna is very suitable for remote wireless communication.

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Performer: A High-Performance Global-Local Model-Augmented with Dual Network Interaction Mechanism

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IEEE Transactions on Cognitive and Developmental Systems 2024年

作者： Tan, Dayu Hao, Rui Hua, Linfeng Xu, Qi Su, Yansen Zheng, Chunhou Zhong, Weimin Anhui University Key Laboratory of Intelligent Computing and Signal Processing Ministry of Education Institutes of Physical Science and Information Technology Hefei230601 China East China University of Science and Technology Key Laboratory of Smart Manufacturing in Energy Chemical Process Ministry of Education Shanghai200237 China Dalian University of Technology School of Computer Science and Technology Dalian116024 China

In deep learning, Convolutional Neural Networks (CNNs) focus on local information through convolutional kernels, while transformers attend to global information using self-attention mechanisms. The union of these distinct approaches enables a more comprehensive extraction of image features. However, the feature map dimensions of CNN and Transformer differ, leading to dimension mismatch issues when combining these architectures. Additionally, the parameter size of the hybrid model integrating both architectures remains large, making it difficult to train. To further augmenting the interpretation of complex image patterns, we present Performer, a dual-network architecture that seamlessly combines CNNs and transformers, resulting in a novel and efficient representation learning model. In the Performer model, we innovate by devising a unique interaction methodology for CNN and transformer architectures to enhance the image feature extraction capabilities mutually. To counteract issue of dimensionality mismatch, we also introduce a refined transformer block, a advancement over the transformer block of ViT. To validate the effectiveness of Performer, we conduct extensive experiments on both classification and segmentation tasks. Performer achieve an accuracy of 83.37% on the ImageNet-200 dataset. For semantic segmentation, Performer excels on the CamVid and Hippocampus datasets. On CamVid, our model achieves a mean Intersection over Union (mIoU) of 63.27% and Pixel Accuracy of 92.11%, demonstrating superior performance in capturing fine details and handling complex scenes effectively. The code is available at https://***/hlfthh/ Performer. © 2016 IEEE.

关键词： Semantic Segmentation

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MSCA-UNet: Multi-Scale Channel Adaptive Sensing Module for Medical Image Segmentation

MSCA-UNet: Multi-Scale Channel Adaptive Sensing Module for M...

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New Trends in Computational Intelligence (NTCI), International Conference on

作者： Liangjin Diao Longfeng Shen Jiacong Chen Fangzhen Ge Mengwen Li Anhui Engineering Research Center for Intelligent Computing and Application on Cognitive Behavior (ICACB) College of Computer Science and Technology Huaibei Normal University Huaibei Anhui China Institute of Artificial Intelligence Hefei Comprehensive National Science Center Hefei China Key Laboratory of Intelligent Computing & Signal Processing Ministry of Education Anhui University Hefei Anhui China

ISBN: (数字)9798331517021

ISBN: (纸本)9798331517038

Recent advancements in CNNs for medical image segmentation have focused on the combination of CNN and Transformer architectures to capture both local and global features. However, challenges remain, such as effectively utilizing fused features at the encoder-decoder bottleneck and addressing blurred object edges in datasets. To tackle these issues, we introduce a multi-scale channel adaptive sensing module, enhancing the model's representational and perceptual capabilities by integrating multi-scale and channel-specific information. Additionally, we propose a cross-perception module and multi-scale segmentation head to improve global coordination and multi-scale information gathering. Experiments on the ACDC and Synapse datasets demonstrate our model's superiority.

关键词： Image segmentation Adaptation models Head Image edge detection Computer architecture Transformers Market research Sensors Synapses Biomedical imaging

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A dual-band antenna designed for 5G communication based on a self-decoupled antenna

A dual-band antenna designed for 5G communication based on a...

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International Applied Computational Electromagnetics Society Symposium (ACES)

作者： Rongzhen Fang Xianliang Wu Zhipeng Chen Mengying Dong Yunfeng Hu Yuanyuan Li Key Laboratory of Intelligent Computing and Signal Processing Anhui University Hefei China Department of Education of Anhui Province Anhui University Hefei China

In this paper, a dual-band antenna for 5G communication based on an antenna design with self-decoupling properties is *** antenna is composed of a self-decoupled antenna unit vertically placed on an 30×80 mm 2 ground plane and printed on 0.8 mm thick FR-4(εr = 4.4, tanδ = 0.02) substrate,and then added a pair of L-shaped coupling feeder structures on this *** shows that the antenna has two operating frequency bands of 3.3-4.2GHz and 4.8-5GHz, and has good transmission and isolation in the above two operating frequency ***,it also has the advantages of small size, self-decoupling,high isolation,simple structure and easy *** antenna can be used as 5G mobile phone communication antenna unit.

关键词： Couplings 5G mobile communication Transmitting antennas Dual band Mobile antennas Antenna feeds Computational electromagnetics

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Electromagnetic scattering of two-dimensional rough cylinder based on statistical integral equation 2

Electromagnetic scattering of two-dimensional rough cylinder...

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2020 2nd International Conference on Artificial Intelligence Technologies and Application, ICAITA 2020

作者： Zhu, Mengnan Wang, Anqi Huang, Zhixiang Key Laboratory of Intelligent Computing and Signal Processing Ministry of Education Anhui University Hefei China

The study of electromagnetic scattering from Gaussian rough surface is of great significance in radar reconnaissance, target tracking and ocean remote sensing. The moment method (MOM) is a commonly used method with high accuracy. However, in the past research, Monte Carlo method is used to simulate the Gaussian rough surface. In this method, a large number of random simulation operations are carried out, and then a statistical convergence result is obtained by counting the results of all operations. In this paper, the stochastic integral equation method SIEM(Stochastic Integral Equation Method) is proposed to calculate the electromagnetic scattering of Gaussian rough surface. SIEM avoids the difficulty of high difficulty precise modeling and repeated calculation many times, and only single modeling and calculation are carried out for the target problem. In this paper, the electromagnetic scattering of two-dimensional cylinder with Gaussian rough surface is solved, and the effectiveness of SIEM is proved by comparing with mom. © 2020 Published under licence by IOP Publishing Ltd.

关键词： Method of moments

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A RIS-Assisted Multiuser MIMO Communication Method Based on Deep Reinforcement Learning

A RIS-Assisted Multiuser MIMO Communication Method Based on ...

引用

IEEE International Conference on Communication and Information Systems (ICCIS)

作者： Changlin Tian Hui Zhi Kui Tie Key Laboratory of Intelligent Computing and Signal Processing of Ministry of Education Anhui University School of Electronic and Information Engineering Anhui University Hefei China Ceyear Technologies (AnHui) CO. LTD Bengbu China

In this paper, a RIS-assisted multiuser MIMO communication method based on deep reinforcement learning (RMMC-DRL) is proposed for multiuser scenarios. Our objective is to find the optimal transmit beamforming matrix of BS and optimal phase shift matrix of reflective intelligent surface (RIS) to maximize the sum rate of multiuser, this problem is reduced into a constrained optimization problem. It is a non-convex optimization problem, so we solve it through deep reinforcement learning (DRL) and then use the results for communication. In the DRL, a deep deterministic policy gradient (DDPG) framework that can handle continuous states and actions is designed, reward is set as optimization goal, and the transmit beamforming matrix and the phase shift matrix of RIS are obtained through the interaction with environment. Unlike the alternating optimization (AO) method, which solve the transmit beamforming matrix and the RIS phase shift matrix alternatively, the RMMC-DRL can obtain both transmit beamforming matrix and RIS phase shift matrix simultaneously as the output of DRL. Simulation results show that RMMC-DRL can learn and improve its behavior by interacting with the environment. Compared with AO method, RMMC-DRL can obtain higher sum rate and lower computational complexity.

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A 0.33–2.61-GHz Rectifier with Expanded Dynamic Input Power Range Using Microstrip Impedance Compression Circuit

TechRxiv

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TechRxiv 2023年

作者： Li, Yingsong Liu, Xin Zhang, Dawei Wu, Xiaohu Liu, Xiaoguang Huang, Zhixiang The College of Information and Communication Engineering Harbin Engineering University Harbin150001 China The Key Laboratory of Intelligent Computing and Signal Processing Ministry of Education Anhui University Anhui Hefei China Shenzhen518055 China

In this letter, an ultra-broadband rectifier with expanded dynamic input power range (IPR) for both wireless power transfer (WPT) and radio frequency energy-harvesting (RFEH) is proposed and analyzed. Expanded dynamic IPR and broadband impedance matching are realized by utilizing a microstrip transmission line impedance compression circuit (MTLICC) with the topology of the paralleled voltage doubler. A proof-of-concept prototype shows a dynamic IPR of 8.5–23.5 dBm, a frequency range of 0.33–2.61 GHz (fractional bandwidth of 155%), PCE is greater than 50%, and a peak PEC of 79.7% (achieved at an input-power level of 19 dBm). The measurement results are in good agreement with the simulation. Covering most 3G/4G/5G/ISM frequency bands, this design is promising for RF power transmission and energy harvesting in the age of the Internet of Things systems. © 2023, CC BY.

关键词： Timing circuits

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A Unified Affine-Projection-Like Adaptive Algorithm for System Identification

TechRxiv

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TechRxiv 2023年

作者： Li, Yingsong Fu, Yonglin Miao, Yongchun Huang, Zhixiang Diniz, Paulo S.R. The Key Laboratory of Intelligent Computing and Signal Processing Ministry of Education Anhui University Anhui Hefei230601 China The Universidade Federal do Rio de Janeiro Rio de Janeiro21941-972 Brazil

A unified affine-projection-like adaptive (UAPLA) algorithm is deivised and verified for system identification. The UAPLA algorithm uses a generalized cost function encompassing some data-reusing methods to cope with colored input signals. Furthermore, the UAPLA algorithm is derived based on the new cost function to generalize multiple affine-projection algorithms. As a result, the proposed UAPLA algorithm includes some classical adaptive filters as exceptional cases while allowing flexibility to achieve low estimation errors under impulsive noises. The obtained results conducted by simulations help to corroborate the superiority of the proposed UAPLA algorithm over other popular AP algorithms. © 2023, CC BY.

关键词： Adaptive filters

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