检索结果-内蒙古大学图书馆

IEEE International Conference on Bioinformatics and Biomedicine (BIBM)

作者： Jing Gao Fa Zhang Kai Hu Xuefeng Cui Key Laboratory of Intelligent Computing and Information Processing of Ministry of Education Xiangtan University Xiangtan China Institute of Computing Technology Chinese Academy of Sciences Beijing China Key Laboratory of Medical Imaging and Artificial Intelligence of Hunan Province Xiangnan University Chenzhou China School of Medical Technology Beijing Institute of Technology Beijing China School of Computer Science and Technology Shandong University Qingdao China

ISBN: (数字)9781665468190

ISBN: (纸本)9781665468206

Recent advances in spatial transcriptomics have enabled the comprehensive measurement of transcriptional profiles while retaining the spatial contextual information. Identifying spatial domains is a critical step in the analysis of spatially resolved transcriptomics. Existing unsupervised methods perform poorly on this task owing to the large amount of noise and dropout events in the transcriptomic profiles. To address this problem, we first extend an unsupervised algorithm to a supervised learning method that can identify useful features and reduce noise hindrance. Second, inspired by the classical convolution in convolutional neural networks (CNNs), we designed a regular hexagonal convolution to compensate for the missing gene expression patterns from adjacent nodes. Compared with the graph convolution in graph neural networks (GNNs), our hexagonal convolution can preserve the relative spatial location information of different nodes in graph-structured data. Third, based on the hexagonal convolution, a novel hexagonal Convolutional Neural Network (hexCNN) is proposed for spatial transcriptomics classification. Finally, we compared the proposed hexCNN with existing methods on the DLPFC dataset. The results show that hexCNN achieves a classification accuracy of 87.2% and an average Rand index (ARI) of 78.2% (1.9% and 3.3% higher than those of GNNs).

关键词： Visualization Convolution Supervised learning Interference Spatial databases Graph neural networks Convolutional neural networks

来源：评论

学校读者我要写书评

暂无评论

Joint active and passive beamforming for intelligent reflecting surface-assisted massive MIMO systems

arXiv

引用

arXiv 2019年

作者： Li, Xingjian Fang, Jun Gao, Feifei Li, Hongbin National Key Laboratory of Science and Technology on Communications University of Electronic Science and Technology of China Chengdu611731 China Institute of Information Processing Department of Automation Tsinghua University Beijing100084 China Department of Electrical and Computer Engineering Stevens Institute of Technology HobokenNJ07030 United States

In this paper, we study the problem of joint active and passive beamforming for intelligent reflecting surface (IRS)assisted massive MIMO systems, where multiple IRSs equipped with a large number of passive elements are deployed to assist a base station (BS) to simultaneously serve a small number of single-antenna users in the same time-frequency resource. Our objective is to maximize the minimum signal to interference plus noise (SINR) at users by jointly optimizing the transmit precoding vector at the BS and phase shift parameters at IRSs. We show that an interesting automatic interference cancelation (AIC) property holds asymptotically as the number of passive elements approaches infinity, i.e., when an IRS is optimally tuned to serve a certain user, this IRS will become interference-free to other users. By utilizing this property, the max-min problem can be converted into an IRS-user association problem, where the objective is to determine which IRSs are assigned for each user. An exhaustive search scheme and a greedy search scheme are proposed to solve the IRS-user association problem. Our theoretical analysis reveals that our proposed solution attains an SINR that scales quadratically with the number of reflecting elements. Also, our theoretical result suggests that even with a moderate number of active antennas at the BS, a massive MIMO like gain can be achieved by increasing the number of passive reflecting elements, thus significantly reducing the energy consumption at the BS. Simulation results are provided to corroborate our theoretical results and to illustrate the effectiveness of our proposed solution. Copyright © 2019, The Authors. All rights reserved.

关键词： MIMO systems

来源：评论

学校读者我要写书评

暂无评论

Idea creation of creative computing based on embedding features and ontology 2016

Idea creation of creative computing based on embedding featu...

引用

3rd Multidisciplinary International Social Networks Conference, MISNC 2016, 5th ASE International Conference on Social Informatics, SocialInformatics 2016 and 7th ASE International Conference on Data Science, DS 2016

作者： Zhang, Fuquan Mao, Zijing Ding, Gangyi Zhang, Rui Lai, Junjiang School of software Beijing Institute of Technology Beijing100081 China Fujian Provincial Key Laboratory of Information Processing and Intelligent Control Ji Yuan Ju Yuan Jin Shan Fuzhou Fujian350121 China Department of Electrical Engineering University of Texas at San Antonio One UTSA Circle San AntonioTX78249 United States Software Building Beijing Institute of Technology 5 South Zhongguancun Street Haidian Beijing100081 China Department of Mathematics Minjiang University Fuzhou No.150 Binzhou Road Jin Shan Fuzhou Fujian350108 China

ISBN: (纸本)9781450341295

This paper used clustering to embed features and use ontology to simulate the process of idea creation from human brain. All the technologies are applied on the frame of creative computing. We are try to display the emergence, the self-organization, the self-coordination of idea creation process of human brain. By creative computing we will try to discover how the idea coming from step by step. From this paper, you will see the process in five steps from blurry motivation to clear creative idea. © 2016 ACM.

关键词： Ontology

来源：评论

学校读者我要写书评

暂无评论

A Photonics-aided MMW OFDM Joint Radar and Communication System with Velocity Accuracy Improvement

A Photonics-aided MMW OFDM Joint Radar and Communication Sys...

引用

Applied Sensing Conference (APSCON), IEEE

作者： Lanfeng Peng Dongxiang Luo Yaoqiang Xiao Fan Li School of Electronics and Information Technology Guangdong Provincial Key Laboratory of Opto-Electronic Information Processing Chips and Systems Sun Yat-Sen University Guangzhou China Institute of Semiconductors South China Normal University Guangzhou China School of Chemistry and Chemical Engineering/Huangpu Hydrogen Innovation Center Guangzhou University Guangzhou China College of Computer Science and Electronic Engineering Hunan University Changsha China

Photonics-aided millimeter wave (MMW) Orthogonal frequency division multiplexing (OFDM) system is a novel approach to realize the joint radar and communication system. The phase noise introduced by the laser will degrade the system performance. In this paper, we analyze the mechanism of phase noise acting on OFDM radar system. A method that combines chirp-Z transform (CZT) and compensation enabled by a reference signal is adopted to improve the velocity accuracy. RF pilot (RFP) and blind phase search (BPS) algorithm are adopted to improve communication performance. A simulation is demonstrated at 30 GHz with 2 GHz communication bandwidth. A twodimensional radar imaging with a range resolution of 0.075 m and velocity resolution of 0.980 m/s and a communication capacity of 6.4 Gbps are obtained in the proposed joint radar and communication system.

关键词： Phase noise Laser radar Image resolution Communication systems OFDM Bandwidth Radar imaging

来源：评论

学校读者我要写书评

暂无评论

SMGC-SBERT: A Multi-Feature Fusion Chinese Short Text Similarity Computation Model Based on Optimised SBERT

SMGC-SBERT: A Multi-Feature Fusion Chinese Short Text Simila...

引用

IEEE International Conference on Systems, Man and Cybernetics

作者： Shuo Zhao Qiliang Gu Jianqiang Zhang Gongpeng Song Qin Lu Key Laboratory of Computing Power Network and Information Security Ministry of Education Shandong Computer Science Center Qilu University of Technology (Shandong Academy of Sciences) Jinan China Shandong Engineering Research Center of Big Data Applied Technology Faculty of Computer Science and Technology Qilu University of Technology (Shandong Academy of Sciences) Jinan China Shandong Provincial Key Laboratory of Computer Networks Shandong Fundamental Research Center for Computer Science Jinan China Shandong Branch of China Mobile Communication Group Design Institute Co. Jinan China

ISBN: (数字)9781665410205

ISBN: (纸本)9781665410212

Chinese short text similarity computation stands as a pivotal task within natural language processing, garnering significant attention. However, existing models grapple with limitations in handling intricate semantic relationships, such as the challenge of discerning subtle semantic nuances in text, inadequacies in effectively integrating diverse levels of semantic information, and the struggle to capture polysemous meanings accurately. In addressing these issues, this paper introduces an innovative Chinese short text similarity computation model, SMGC-SBERT. This model addresses shortcomings of the existing models by employing a multi-module fusion strategy, thereby enabling a more precise measurement of semantic similarity between texts. Primarily, the model incorporates SAT embedding to acquire phrase-level semantic information and leverages the MS-BERT model to encode text, improving the model's comprehension of textual polysemy and obtaining richer semantic representation. Then, the fusion of module features, including multi-branch convolutional networks and mix pooling, enables the extraction of textual features from varied levels, bolstering the model's representational capacity. Additionally, to further reduce overfitting risks while improving accuracy and other performance, a multi-layer feature adjustment network is utilized for short text similarity calculation. The final resultant experimental findings showcase the superiority of the SMGC-SBERT model over other neural network models, demonstrating significant advancements across both Chinese-SNLI and CCKS2018_Task3 Chinese short text datasets.

关键词： Deep learning Computational modeling Semantics Neural networks Feature extraction Natural language processing Multilingual Convolutional neural networks Cybernetics Overfitting

来源：评论

学校读者我要写书评

暂无评论

Poisoning attack against estimating from pairwise comparisons

arXiv

引用

arXiv 2021年

作者： Ma, Ke Xu, Qianqian Zeng, Jinshan Cao, Xiaochun Huang, Qingming The School of Computer Science and Technology University of Chinese Academy of Sciences Beijing100049 China The Artificial Intelligence Research Center Peng Cheng Laboratory Shenzhen518055 China The Key Laboratory of Intelligent Information Processing Institute of Computing Technology Chinese Academy of Sciences Beijing100190 China The School of Computer and Information Engineering Jiangxi Normal University Jiangxi Nanchang330022 China Institute of Information Engineering Chinese Academy of Sciences Beijing100093 China The School of Cyber Security University of Chinese Academy of Sciences Beijing100049 China The Key Laboratory of Intelligent Information Processing Institute of Computing Technology Chinese Academy of Sciences Beijing100190 China The School of Computer Science and Technology University of Chinese Academy of Sciences Beijing100049 China The Key Laboratory of Big Data Mining and Knowledge Management The School of Economics and Management University of Chinese Academy of Sciences Beijing100049 China

As pairwise ranking becomes broadly employed for elections, sports competitions, recommendation, information retrieval and so on, attackers have strong motivation and incentives to manipulate or disrupt the ranking list. They could inject malicious comparisons into the training data to fool the target ranking algorithm. Such a technique is called "poisoning attack" in regression and classification tasks. In this paper, to the best of our knowledge, we initiate the first systematic investigation of data poisoning attack on the pairwise ranking algorithms, which can be generally formalized as the dynamic and static games between the ranker and the attacker, and can be modeled as certain kinds of integer programming problems mathematically. To break the computational hurdle of the underlying integer programming problems, we reformulate them into the distributionally robust optimization (DRO) problems, which are computational tractable. Based on such DRO formulations, we propose two efficient poisoning attack algorithms and establish the associated theoretical guarantees including the existence of Nash equilibrium and the generalization ability bounds. The effectiveness of the suggested poisoning attack strategies is demonstrated by a series of toy simulations and several real data experiments. These experimental results show that the proposed methods can significantly reduce the performance of the ranker in the sense that the correlation between the true ranking list and the aggregated results with toxic data can be decreased dramatically. © 2021, CC BY-NC-ND.

关键词： Toys

来源：评论

学校读者我要写书评

暂无评论

GK: A Graphormer Architecture Based Knowledge Graph Reasoning Model for Link Prediction

GK: A Graphormer Architecture Based Knowledge Graph Reasonin...

引用

IEEE International Conference on Big Data and Cloud Computing (BdCloud)

作者： Yueiia Wu Jian-tao Zhou Ministry of Education Inner Mongolia Engineering Laboratory for Cloud Computing and Service Software Inner Mongolia Key Laboratory of Social Computing and Data Processing College of Computer Science Inner Mongolia University National & Local Joint Engineering Research Center of Intelligent Information Processing Technology for Mongolian Engineering Research Center of Ecological Big Data Hohhot China

Knowledge Graph has become a dominant research field in graph theory, but its incompleteness and sparsity hinder its application in various fields. Knowledge Graph Reasoning aims to alleviate these problems by deducing new knowledge or identifying false knowledge from existing knowledge. Recently, the Graph Convolution Network (GCN) based method is one of the most advanced methods to realize knowledge graph reasoning. However, it still suffers from some problems such as incomplete neighbor information aggregation and slow training speed. This paper proposes a knowledge graph reasoning model named GK for the link prediction task, which obtains better performance than existing GCN-based methods by introducing Graphormer into knowledge reasoning. The GK first proposes that nodes and their surroundings can be regarded as a hierarchical architecture that enables the model to capture more practical reasoning information to improve prediction accuracy. In addition, to accelerate the training speed of the model on the large-scale Knowledge Graph, we present a faster shortest path-finding method F-SPF in the edge coding process. Extensive experimental results show that the GK model can obtain the state-of-the-art prediction results of current GCN-based methods and can improve the training speed.

关键词： Training Knowledge engineering Knowledge graphs Predictive models Prediction algorithms Feature extraction Cognition

来源：评论

学校读者我要写书评

暂无评论

Decoding Continuous Character-based Language from Non-invasive Brain Recordings

arXiv

引用

arXiv 2024年

作者： Zhang, Cenyuan Zheng, Xiaoqing Yin, Ruicheng Geng, Shujie Xu, Jianhan Gao, Xuan Lv, Changze Ling, Zixuan Huang, Xuanjing Cao, Miao Feng, Jianfeng School of Computer Science Fudan University Shanghai China Shanghai Key Laboratory of Intelligent Information Processing Fudan University Shanghai China 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

Deciphering natural language from brain activity through non-invasive devices remains a formidable challenge. Previous non-invasive decoders either require multiple experiments with identical stimuli to pinpoint cortical regions and enhance signal-to-noise ratios in brain activity, or they are limited to discerning basic linguistic elements such as letters and words. We propose a novel approach to decoding continuous language from single-trial non-invasive fMRI recordings, in which a three-dimensional convolutional network augmented with information bottleneck is developed to automatically identify responsive voxels to stimuli, and a character-based decoder is designed for the semantic reconstruction of continuous language characterized by inherent character structures. The resulting decoder can produce intelligible textual sequences that faithfully capture the meaning of perceived speech both within and across subjects, while existing decoders exhibit significantly inferior performance in cross-subject contexts. The ability to decode continuous language from single trials across subjects demonstrates the promising applications of non-invasive language brain-computer interfaces in both healthcare and neuroscience. Copyright © 2024, The Authors. All rights reserved.

关键词： Semantics

来源：评论

学校读者我要写书评

暂无评论

Network Parameter Generation for One-Shot Object Detection

Network Parameter Generation for One-Shot Object Detection

引用

IEEE International Conference on Unmanned Systems (ICUS)

作者： Kang Wang Jiajia Zhao Yang Wang Shuigeng Zhou Shanghai Key Lab of Intelligent Information Processing and School of Computer Science Fudan University Shanghai China Science and Technology on Complex System Control and Intelligent Agent Cooperation Laboratory Beijing Electro-Mechanical Engineer Institute Beijing China School of Information Engineering Nanchang University China

ISBN: (纸本)9781728137933

Recent object detection models have achieved satisfactory performance by deep learning with large-scale annotated datasets. However, these models often perform poorly when the training examples are not sufficient enough, especially for one-shot object detection where there is only one training example of each target class. In this paper, we propose a network parameter generation framework for effective one-shot object detection. By leveraging the semantic relationship between the source-domain and the target-domain (new classes), our framework can generate network parameters for the new classes directly. Furthermore, we develop two implementation schemes for this framework: weighting-based parameter generation and regression-based parameter generation. These two schemes use different information to construct the relationship and transfer knowledge from the source-domain to the target-domain. Experiments on the PASCAL-OSCD benchmark show that our methods can significantly boost the performance of one-shot object detection.

关键词： Object detection Detectors Head Training Feature extraction Task analysis Training data

来源：评论

学校读者我要写书评

暂无评论

An Enhanced Flower Pollination Algorithm for Solving Optimal Power Flow Problem

SSRN

引用

SSRN 2022年

作者： Zhong, keyu Xiao, Fen Gao, Xieping Key Laboratory of Computing and Stochastic Mathematics of Ministry of Education Hunan Normal University Changsha410081 China School of Mathematics and Statistics Hunan Normal University Changsha410081 China School of Computer Science Xiangtan University Hunan Xiangtan411105 China Hunan Provincial Key Laboratory of Intelligent Computing and Language Information Processing Hunan Normal University Changsha410081 China

The OPF system for renewable energy power has presented characteristics such as extremely high security constraints and more obvious multimodal properties, its solution is a challenging task and requires more efficient methods. In this paper, an enhanced flower pollination algorithm, EFPA-SF is proposed to solve the OPF problem. In EFPA-SF, there are four improvements: firstly, a random step size in the process of cross-pollination is proposed to improve the global search ability of EFPA-SF. Secondly, in the stage of self-pollination, the global optimal pollen is introduced to improve the ability of exploitation–exploration balance of the algorithm. In addition, if pollen individual crosses boundaries, boundary constraint is carried out by the previous position and boundary position of pollen, which is instrumental to escape from local optimum. Finally, the superiority of feasible solutions (SF) constraints handling method is integrated into the algorithm to satisfy the feasibility of the solutions. To verify the effectiveness of the proposed algorithm, the optimization capability of EFPA is first investigated and analyzed by using the most recent IEEE CEC2021 benchmark functions. Then, EFPA-SF is used to solve three engineering design problems and the performance is compared with the state-of-the-art algorithms, the validation results reveal that the proposed algorithm outperforms state-of-the-art algorithms, and demonstrate that it can be used for constrained optimization as well as for unconstrained optimization problems with good generality. Finally, EFA-SF is applied to the OPF problem on a modified IEEE-30 bus system that incorporates stochastic wind, solar, and small hydro power in addition to conventional thermal power generation. The comprehensive investigation reveals that EFA-SF can provide competitive solutions to the OPF problem compared to popular algorithms. © 2022, The Authors. All rights reserved.

关键词： Constraint handling

来源：评论

学校读者我要写书评

暂无评论

建议与咨询留下您的常用邮箱和电话号码，以便我们向您反馈解决方案和替代方法

时间限定

文献类型

馆藏选择

核心期刊

语言

文献类型

帮助

文字说明：

检索规则说明：

检索范例：

分类表

所选分类

限定检索结果

文献类型

馆藏范围

日期分布

学科分类号

主题

机构

作者

语言

请选择保存的检索档案：

请选择收藏分类：

通借通还

建议与咨询 留下您的常用邮箱和电话号码，以便我们向您反馈解决方案和替代方法

时间限定

文献类型

馆藏选择

核心期刊

语言

文献类型

帮助

文字说明：

检索规则说明：

检索范例：

分类表

所选分类

限定检索结果

文献类型

馆藏范围

日期分布

学科分类号

主题

机构

作者

语言

请选择保存的检索档案： 新增检索档案 确定 取消

请选择收藏分类： 新增自定义分类 确定 取消

通借通还

建议与咨询留下您的常用邮箱和电话号码，以便我们向您反馈解决方案和替代方法

请选择保存的检索档案：

请选择收藏分类：