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2018 International Conference on Mathematics, Modeling, Simulation and Statistics Application（MMSSA2018）

作者： She Liu Shuying Yang Department of computer and Communication Engineering Tianjin University of Technology Key laboratory of Intelligence Computing and Novel Software Technology Tianjin University of Technology

ISBN: (纸本)9781510880504

Evolutionary programming algorithm is applied to the problem of image clustering. The solution of the problem is encoded by the symbol coding, and swarm intelligent model is used to search the solution of the problem. In evolutionary programming algorithm, the global search ability is effectively improved by mutation operator and selection operator. The excellent diversity of solutions is guaranteed by using Gaussian mutation operator, and the complexity of the evolutionary operation is reduced. The simulation experiments show that the proposed algorithm for image clustering is effective and correct.

关键词： evolutionary programming image clustering swarm intelligence

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Uplink Supportive Number of Users in Massive MIMO Systems 9

Uplink Supportive Number of Users in Massive MIMO Systems

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2017 9th IEEE International Conference on communication software and Networks (ICCSN 2017)

作者： Jun Zhu Chao Wang Peng Ma Chaochao Jia Kai Li Key laboratory of Intelligent Computing & Signal Processing (Anhui University) Ministry of Education Technology and Innovation Department Shanghai Research Center for Wireless Communication

ISBN: (纸本)9781509038237;9781509038220

The supportive number of users achieving the maximum sum rate is studied in uplink massive MIMO systems for zero-forcing(ZF) and maximum-ratio combining(MRC). We obtain the lower bound of the achievable rate of each user for ZF and MRC receivers with any finite number of base station(BS) antennas, respectively. By this theoretical result, this paper will focus on the supportive number of users which was constrained with the minimum achievable rate. Through analyzing the optimal problem of maximizing the overall sum rate, we obtain the expression of optimal number of users and present the user scheduling algorithm for achieving the maximized sum rate. The numerical results show that the massive MIMO systems can improve the supportive number of users, and ZF receivers can support more number of users than MRC under the same condition.

关键词： large number of antennas achievable uplink rate supportive number of users massive MIMO

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An Adaptive Spectrum Allocation Algorithm in Ultra-Dense Network

An Adaptive Spectrum Allocation Algorithm in Ultra-Dense Net...

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International Conference on communication software and Networks, ICCSN

作者： Jun Zhu Chaochao Jia Chao Wang Kai Li Key laboratory of Intelligent Computing & Signal Processing (Anhui University) Ministry of Education Hefei China Technology and Innovation Department Shanghai Research Center for Wireless Communication Shanghai China

In this paper, we propose a novel method to adaptively adjust the parameter threshold used in overlapping frequency. We verify the performance of the proposed algorithm from the system simulation. Compared with the traditional network planning scheme which needs setting parameters manually, the optimal threshold is adaptively adjusted according to the distribution of the users. The simulation results show that the algorithm can improve the signal-to-interference-plus-noise-ratio (SINR) performance of users and the cell throughput when the users are distributed in the edge of cell coverage which owns the same optimization result as traditional optimization method. So the algorithm can effectively solve the decrease problem of spectral efficiency when the threshold in frequency overlap is set unreasonable and also save a lot of labour cost on setting parameters.

关键词： Interference Signal to noise ratio Throughput Clustering algorithms Bandwidth Radio spectrum management Resource management

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Strategic priorities for transformative progress in advancing biology with proteomics and artificial intelligence

arXiv

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arXiv 2025年

作者： Sun, Yingying Jun, A. Liu, Zhiwei Sun, Rui Qian, Liujia Payne, Samuel H. Bittremieux, Wout Ralser, Markus Li, Chen Chen, Yi Dong, Zhen Perez-Riverol, Yasset Khan, Asif Sander, Chris Aebersold, Ruedi Vizcaíno, Juan Antonio Krieger, Jonathan R. Yao, Jianhua Wen, Han Zhang, Linfeng Zhu, Yunping Xuan, Yue Sun, Benjamin Boyang Qiao, Liang Hermjakob, Henning Tang, Haixu Gao, Huanhuan Deng, Yamin Zhong, Qing Chang, Cheng Bandeira, Nuno Li, Ming Weinan, E. Sun, Siqi Yang, Yuedong Omenn, Gilbert S. Zhang, Yue Xu, Ping Fu, Yan Liu, Xiaowen Overall, Christopher M. Wang, Yu Deutsch, Eric W. Chen, Luonan Cox, Jürgen Demichev, Vadim He, Fuchu Huang, Jiaxing Jin, Huilin Liu, Chao Li, Nan Luan, Zhongzhi Song, Jiangning Yu, Kaicheng Wan, Wanggen Wang, Tai Zhang, Kang Zhang, Le Bell, Peter A. Mann, Matthias Zhang, Bing Guo, Tiannan Affiliated Hangzhou First People’s Hospital State Key Laboratory of Medical Proteomics School of Medicine Westlake University Zhejiang Province Hangzhou China Westlake Center for Intelligent Proteomics Westlake Laboratory of Life Sciences and Biomedicine Zhejiang Province Hangzhou China Biology Department Brigham Young University ProvoUT84602 United States Department of Computer Science University of Antwerp Antwerp2020 Belgium Department of Biochemistry CharitéUniversitätsmedizin Berlin Berlin Germany Biomedicine Discovery Institute Department of Biochemistry and Molecular Biology Monash University MelbourneVICVIC 3800 Australia Wellcome Genome Campus Hinxton CambridgeCB10 1SD United Kingdom Harvard Medical School Ludwig Center at Harvard United States Harvard Medical School Broad Institute Ludwig Center at Harvard Dana-Farber Cancer Institute United States Department of Biology Institute of Molecular Systems Biology ETH Zürich Zürich Switzerland Bruker Ltd. MiltonONL9T 6P4 Canada AI for Life Sciences Lab Tencent Shenzhen518057 China State Key Laboratory of Medical Proteomics AI for Science Institute Beijing100080 China Beijing Institute of Lifeomics Beijing102206 China Thermo Fisher Scientific GmbH Hanna-Kunath Str. 11 Bremen28199 Germany Informatics and Predictive Sciences Research Bristol Myers Squibb United States Department of Chemistry Fudan University Songhu Road 2005 Shanghai200438 China Department of Computer Science Luddy School of Informatics Computing and Engineering Indiana University IN47408 United States ProCan® Children’s Medical Research Institute Faculty of Medicine and Health The University of Sydney WestmeadNSW Australia La Jolla CA United States Central China Institute of Artificial Intelligence University of Waterloo Canada AI for Science Institute Center for Machine Learning Research School of Mathematical Sciences Peking University China Research Institute of Intelligent Complex Systems Fudan U

Artificial intelligence (AI) is transforming scientific research, including proteomics. Advances in mass spectrometry (MS)-based proteomics data quality, diversity, and scale, combined with groundbreaking AI techniques, are unlocking new challenges and opportunities in biological discovery. Here, we highlight key areas where AI is driving innovation, from data analysis to new biological insights. These include developing an AI-friendly ecosystem for proteomics data generation, sharing, and analysis;improving peptide and protein identification and quantification;characterizing protein-protein interactions and protein complexes;advancing spatial and perturbation proteomics;integrating multi-omics data;and ultimately enabling AI-empowered virtual cells. © 2025, CC BY.

关键词： Biotic

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Recent Advances in Clonal Selection Algorithms and Applications

Recent Advances in Clonal Selection Algorithms and Applicati...

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IEEE Symposium Series on Computational Intelligence

作者： Wenjian Luo Xin Lin Anhui Province Key Laboratory of Software Engineering in Computing and Communication University of Science and Technology of China Hefei Anhui China

Clonal selection algorithms (CSAs) are a kind of Artificial Immune Algorithms (AIAs). In this paper, recent advances in clonal selection algorithms are summarized and reviewed. First, the basic framework of clonal selection algorithms is given. Second, various types of applications using clonal selection algorithms are summarized, including global optimization, constrained optimization, combinatorial optimization, multiobjective optimization, dynamic optimization and other applications. Last, a brief conclusion and some remarks about clonal selection algorithms are given.

关键词： Immune Computation Clonal Selection Algorithms Optimization

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High-contrast transparency comb of the electromagnetically-induced-transparency memory

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Physical Review A 2018年第3期98卷 033802-033802页

作者： Sheng-Jun Yang Jun Rui Han-Ning Dai Xian-Min Jin Shuai Chen Jian-Wei Pan Hefei National Laboratory for Physical Sciences at Microscale and Department of Modern Physics University of Science and Technology of China Hefei Anhui 230026 China CAS Center for Excellence and Synergetic Innovation Center in Quantum Information and Quantum Physics University of Science and Technology of China Hefei Anhui 230026 China CAS-Alibaba Quantum Computing Laboratory Shanghai 201315 China State Key Laboratory of Advanced Optical Communication Systems and Networks School of Physics and Astronomy Shanghai Jiao Tong University Shanghai 200240 China

Quantum interface of coherent optical field and atomic excitations plays an important role in quantum metrology and quantum information science. The electromagnetically-induced-transparency (EIT) technique has shown versatile and powerful capability in many applications during the last decades. By using efficient EIT-based memory, we directly observed single-photon-level Ramsey interference and also high-contrast spectral transparency comb with a visibility up to about 0.81 at around the resonant line in cold atoms. The interference fringes are mainly influenced by the pulse repetition period, the waveform overlap of the slowed and retrieved signal pulses, and the coherent lifetime of the EIT memory. All these factors have been investigated in detail. Such high-contrast interference fringe may offer us methods for precision measurement and potential applications in areas of atomic clock and magnetometry.

关键词： Atom interferometry Coherent control Cooling & trapping Light-matter interaction Quantum optics

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An Efficient and Slight Convolutional Neural Network for Vehicle Type Classification

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Journal of Physics: Conference Series 2018年第1期1069卷

作者： Haibo Zheng Naijie Gu Xiaoci Zhang Anhui Province Key Laboratory of Computing and Communication Software School of Computer and Technology University of Science and Technology of China Hefei China

With the popularity of small storage embedded devices, recent researches on deep convolutional neural networks no longer only focus on improving the classification accuracy but start to attach great importance to the size of convolutional neural networks. This paper proposes a small deep convolutional neural network for vehicle type classification, based on the Fire module and the residual module. The Fire module is applied to maintain a small number of parameters. The residual module is employed to accelerate the training process and improves the classification accuracy. Experimental results show that our model achieves 95.57% accuracy of vehicle type classification on an open source dataset BIT-Vehicle. This outperforms previous researches and some classical convolutional neural networks such as AlexNet, ResNet-32 and SqueezeNet. What is more, the size of our model is only 5.3 MB, which has 40X fewer parameters than AlexNet and has 15X fewer parameters than ResNet-32.

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A simplification method of polymorphic boolean functions

arXiv

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arXiv 2017年

作者： Luo, Wenjian Li, Zhifang Anhui Key Laboratory of Software in Computing and Communication School of Computer Science and Technology University of Science and Technology of China Hefei230027 China

Polymorphic circuits are a special kind of circuits which possess multiple build-in functions, and these functions are activated by environment parameters, like temperature, light and VDD. The behavior of a polymorphic circuit can be described by a polymorphic Boolean function. For the first time, this brief presents a simplification method of the polymorphic Boolean function. Copyright © 2017, The Authors. All rights reserved.

关键词： Boolean functions

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Design methods for polymorphic combinational logic circuits based on the Bi-Decomposition approach

arXiv

引用

arXiv 2017年

作者： Li, Zhifang Luo, Wenjian Yue, Lihua Wang, Xufa School of Computer Science and Technology University of Science and Technology of China Hefei Anhui230027 China Anhui Key Laboratory of Software in Computing and Communication University of Science and Technology of China Hefei Anhui230027 China

Polymorphic circuits are a special kind of digital logic components, which possess multiple build-in functions. In different environments, a polymorphic circuit would perform different functions. Evolutionary Algorithms, Binary Decision Diagrams (BDD) and the multiplex method have been adopted to design polymorphic circuits. However, the evolutionary methods face the scalable problem. The BDD method consumes too much gate resource. The polymorphic circuit built by the multiplex method rarely contains polymorphic gates. In this paper, based on the traditional Bi-Decomposition circuit design approach, two methods, *** Poly-Bi-Decomposition method and the TransformationBi-Decomposition method, are proposed for designing polymorphic circuits. The Poly_Bi-Decomposition method can design relatively large and gate-efficient polymorphic circuits with a higher percentage of polymorphic gates. The TransformationBi-Decomposition method can use the traditional circuit design approaches and tools, e.g. Bi-Decomposition, to design polymorphic circuits directly. The experimental results show the good performance of the proposed methods. Copyright © 2017, The Authors. All rights reserved.

关键词： Timing circuits

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A novel denoising method for infrared image based on bilateral filtering and non-local means

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Optoelectronics Letters 2017年第3期13卷 237-240页

作者：刘凤连孙梦尧蔡文娜 Key Laboratory of Computer Vision and System Ministry of Education of ChinaTianjin Key Laboratory of Intelligence Computing and Novel Software TechnologySchool of Computer and Communication EngineeringTianjin University of TechnologyTianjin 300384China

This paper presents an image denoising method based on bilateral filtering and non-local means. The non-local region texture or structure of the image has the characteristics of repetition, which can be used to effectively preserve the edge and detail of the image. And compared with classical methods, bilateral filtering method has a better performance in denosing for the reason that the weight includes the geometric closeness factor and the intensity similarity factor. We combine the geometric closeness factor with the weight of non-local means, and construct a new weight. Experimental results show that the modified algorithm can achieve better performance. And it can protect the image detail and structure information better.

关键词： bilateral filtering similarity pixel texture combine repetition neighborhood preserve noisy

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