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Advancing biological fluorescence microscopy with deep learning:a bibliometric perspective

Medical Data Mining 2022年第4期5卷 42-55页

作者： Li Fu Cheng-Liang Yin Jia-Lei Wang Xiao-Zhu Liu College of Materials and Environmental Engineering Hangzhou Dianzi UniversityHangzhou 310018China Medical Big Data Research Center Medical Innovation Research Division of PLA General HospitalBeijing 100853China National Engineering Laboratory for Medical Big Data Application Technology Chinese PLA General HospitalBeijing 100853China Department of Algorithm Shining3D Technology Company LimitidHangzhou 311258China Department of Cardiology The Second Affiliated Hospital of Chongqing Medical UniversityChongqing 400010China

Background:Fluorescence microscopy has increasingly promising applications in life *** bibliometrics-based review focuses on deep learning assisted fluorescence microscopy imaging ***:Papers on this topic retrieved by Core Collection on Web of Science between 2017 and July 2022 were used for the *** addition to presenting the representative papers that have received the most attention,the process of development of the topic,the structure of authors and institutions,the selection of journals,and the keywords are analyzed in detail in this ***:The analysis found that this topic gained immediate popularity among scholars from its emergence in 2017,gaining explosive growth within three *** phenomenon is because deep learning techniques that have been well established in other fields can be migrated to the analysis of fluorescence *** 2020 onwards,this topic tapers off but has attracted a few stable research groups to tackle the remaining *** this topic has been very popular,it has not attracted scientists from all over the *** USA,China,Germany,and the UK are the key players in this *** analysis and clustering are applied to understand the different focuses on this ***:Based on the bibliometric analysis,the current state of this topic to date and future perspectives are summarized at the end.

关键词： deep learning fluorescence microscopy signal-to-noise ratio convolutional neural network cell segmentation

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User-Centric Joint Access-Backhaul Design for Full-Duplex Self-Backhauled Wireless Networks

arXiv

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arXiv 2018年

作者： Chen, Erkai Tao, Meixia Zhang, Nan Department of Electronic Engineering Shanghai Jiao Tong University Shanghai200240 China Wireless Algorithm Department Product Research and Development System ZTE Corporation Shanghai201203 China

Full-duplex self-backhauling is promising to provide cost-effective and flexible backhaul connectivity for ultra-dense wireless networks, but also poses a great challenge to resource management between the access and backhaul links. In this paper, we propose a user-centric joint access-backhaul transmission framework for full-duplex self-backhauled wireless networks. In the access link, user-centric clustering is adopted so that each user is cooperatively served by multiple small base stations (SBSs). In the backhaul link, user-centric multicast transmission is proposed so that each user’s message is treated as a common message and multicast to its serving SBS cluster. We first formulate an optimization problem to maximize the network weighted sum rate through joint access-backhaul beamforming and SBS clustering when global channel state information (CSI) is available. This problem is efficiently solved via the successive lower-bound maximization approach with a novel approximate objective function and the iterative link removal technique. We then extend the study to the stochastic joint access-backhaul beamforming optimization with partial CSI. Simulation results demonstrate the effectiveness of the proposed algorithms for both full CSI and partial CSI scenarios. They also show that the transmission design with partial CSI can greatly reduce the CSI overhead with little performance degradation. Copyright © 2018, The Authors. All rights reserved.

关键词： Channel state information

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Stroke in the Arab World: A bibliometric analysis of research activity (2002–2016)

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eNeurologicalSci 2018年 13卷 40-45页

作者： Salhab, Hamza A. Salameh, Pascale Hajj, Hind Hosseini, Hassan Faculty of Medicine American University of Beirut Lebanon Neuroscience Research Center Faculty of Medical Sciences Lebanese University Beirut Lebanon Faculty of Medical Sciences Lebanese University Beirut Lebanon Algorithm SAL Zouk Mosbeh Beirut 11 962 Lebanon Department of Neurology Henri-Mondor Hospital UPEC Assistance Publique-Hopitaux de Paris Creteil France

Background: The Arab world has an increasing prevalence of strokes, a leading cause of death in this part of the world. Aims: The aim of this article is to quantify the stroke research activity in the Arab countries over the past 15 years taking into consideration the population, GDP, and DALY of each country. Methods: A PubMed search was conducted to find stroke research articles published from the Arab countries between 2002 and 2016 (inclusive). Medical subject headings related to strokes and author origin/affiliation were used for this purpose. Results: The Arab world only produced 0.51% of all the stroke-related publications on PubMed even though the stroke-related DALY percentage in this region was greater than 2.88% during the period we studied. In general, the number of publications increased in the last few years. Somalia came first regarding the percentage of stroke to non-stroke publications released. Lebanon had the highest number of publications per GDP (in US Billion Dollars), Qatar had the highest number of publications per million persons (PPMP), while Saudi Arabia had the highest number of publications per 1% of stroke DALY. In addition, a strong positive correlation was found between the number of stroke publications and GDP;however, the correlation between the number of stroke publication and either population size or DALY was a weak positive one. Conclusions: A general increase in publications is noticed, but stroke research activity in the Arab world is still poor compared to other parts of the world. © 2018 The Authors

关键词： Arab world Bibliometric DALY GDP Population Stroke

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Joint uplink and downlink transmission design for URLLC using finite blocklength codes 15

Joint uplink and downlink transmission design for URLLC usin...

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15th International Symposium on Wireless Communication Systems, ISWCS 2018

作者： Shen, Chao Chang, Tsung-Hui Xu, Hanqing Zhao, Yajun State Key Lab of Rail Traffic Control and Safety Beijing Jiaotong University Beijing China School of Science and Engineering Chinese University of Hong Kong Shenzhen China Shenzhen Research Institute of Big Data Shenzhen China Algorithm Department Wireless Product R and D Institute ZTE Corporation Shenzhen China

ISBN: (纸本)9781538650059

This paper considers a joint uplink (UL) and downlink (DL) transmission design problem for achieving ultrareliable and low-latency communications (URLLC) in a two-hop wireless network. Specifically, we assume that a sensor node sends information signals to a base station (BS) and then the BS sends some processed signals to some mobile terminals (MTs). The objective is to minimize the total over-the-air transmission latency under stringent UL-DL reliability constraints and power limit. The achievable rate formula of finite blocklength codes is used to explicitly model the relation between the transmission rate, latency and reliability. While the formulated problem is difficult to solve, we explore the problem structure by analyzing monotonicity and convexity of the objective function with respect to system variables. Then we develop an efficient alternating optimization (AO) algorithm to solve the considered problem. Simulation results demonstrate interesting trade off between various system parameters and show that the proposed AO algorithm yields near-optimal solutions. © 2018 IEEE.

关键词： Sensor nodes

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Field Trial of a New Metropolitan WDM Architecture and Flexible Scheduling Based on Optical Layer OAM

Field Trial of a New Metropolitan WDM Architecture and Flexi...

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Asia Communications and Photonics Conference and Exhibition (ACP)

作者： Yang Zhao Yucong Liu Xiang Li Dong Wang Changbin Hu Dechao Zhang Department of Fundamental Network Technology China Mobile Research Institute Beijing China Optical System & Algorithm Development Department Huawei Technologies Co. Ltd. Wuhan China

A novel wavelength pooling technology and a flexible scheduling method based on optical layer OAM (O-OAM) are proposed. Costs of network construction and maintenance are reduced significantly, and service latency is r... 详细信息

ISBN: (数字)9798350379266

ISBN: (纸本)9798350379273

关键词： Costs Asia Optical fiber networks Wavelength division multiplexing Maintenance Monitoring Photonics

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A REGULARIZATION NEWTON METHOD FOR MIXED COMPLEMENTARITY PROBLEMS

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Acta Mathematica Scientia 2004年第3期24卷 376-384页

作者：王宜举周厚春王长钰 Institute of Operations Research Qufu Normal University Rizhao 276800 China School of Mathematics and Computer Science Nanjing Normal University Nanjing 210091 China School of Mathematics and Computer Science Nanjing Normal University Nanjing 210097 China Department of Mathematics Linyi Teachers College Linyi 276005 China is proposed. Its global convergence is proved under the assumption that F is a P0-function. The main feature of our algorithm is that a priori of the existence of an accumulation point for convergence need not to be assumed.

In this paper, a regularization Newton method for mixed complementarity problem(MCP) based on the reformulation of MCP in [1] is proposed. Its global convergence is proved under the assumption that F is a P0-function. The main feature of our algorithm is that a priori of the existence of an accumulation point for convergence need not to be assumed.

关键词： regularization Newton method global convergence super-linear convergence

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Tightly-Coupled Lidar-Based Lifelong Mapping using Wheels and a MEMS Gyroscope for Mobile Robots in Dynamic Environment 24

Tightly-Coupled Lidar-Based Lifelong Mapping using Wheels an...

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3rd International Symposium on Robotics, Artificial Intelligence and Information Engineering, RAIIE 2024

作者： Hu, Lizhi Chen, Huilin Li, Xiang Lu, Wei Zhao, Yifan Hu, Songyu Navigation and Localization Algorithm Department Zhejiang HuaRay Technology Co. Lt. Hangzhou China Software Research and Development Center Zhejiang HuaRay Technology Co. Lt. Hangzhou China State Key Laboratory of Fluid Power and Mechatronic Systems College of Mechanical Engineering Zhejiang University Hangzhou China

ISBN: (纸本)9798400718311

Localization and mapping technology of mobile robots is important in production and warehousing. The changing warehousing environment always result in poor accuracy and robustness of the mobile robot's localization. It is necessary to detect the degree of environmental changes and update the map. This paper proposes a novel lifelong mapping method fusing measurements from the lidar, wheels and a MEMS gyroscope, which can create a reliable map corresponding to the current working environment. Firstly, we use the wheels and gyroscopes measures for pre-integration to provide relative motion constraints, while integrating wheels and gyroscopes to provide initial pose for lidar matching. We also establish lidar odometry by submaps to provide another type of relative motion constraints. The absolute constraints are obtained by matching the lidar measurements with prior map. These three types of constraints are optimized in a factor graph. At the same time, during the process of updating the map, detect newly added artificial markers such as reflective columns or strips, and update them into the map timely. Then, in order to delete redundant lidar data keyframes for building map, we propose a determine redundancy method based on submaps. Finally, we propose a method for calculating the degree of map changes, which can update the map timely. Experimental results prove that our method can establish higher quality maps, optimize lidar external parameters timely during the mapping process, delete redundant lidar keyframes more efficiently, and update the current environmental map more accurately and timely. © 2024 Copyright held by the owner/author(s). Publication rights licensed to ACM.

关键词： Gyroscopes

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Discriminating proteins using a novel ensemble algorithm

Discriminating proteins using a novel ensemble algorithm

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Conference on Information and Knowledge Technology

作者： Elham Nikookar Kambiz Badie Mehdi Sadeghi Ebrahim Naderi Department of algorithm and computaion University of Tehran Tehran Iran NIGEB Tehran Iran Research Institute for ICT Tehran Iran Shahid Chamran University of Ahvaz Ahwaz Iran

Decisions of multiple hypotheses are combined in ensemble learning to produce more accurate and less risky results. In this article, we present a novel ensemble machine learning approach for the development of robust thermo stable protein discrimination. But unlike widely used ensemble approaches in which bootstrapped training data are used, we keep the original data unchanged. Instead, we build an ensemble of base classifiers that each of them uses a division of features (called feature group) to predict the class label of each sample. Then, we try to learn the base classifiers' outputs (behavior) for different samples. By testing the proposed method on a well-known dataset, we show that our ensemble method is comparable in precision, recall and f-measure to the state of the art classifiers.

关键词： Proteins Feature extraction Amino acids Bioinformatics Boosting Support vector machines Decision trees

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A GLOBALLY CONVERGENT algorithm FOR THE EUCLIDEAN MULTIPLICITY LOCATION PROBLEM

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Acta Mathematicae Applicatae Sinica 1992年第4期8卷 357-366页

作者： J.B.ROSEN 薛国良 Computer Science Department University of MinnesotaMinneapolisMN 55455USA Institute of Operations Research Qufu Normal University Qufu 278165 Chinahe Euclidean single facility location problem (ESFL) and the Euclidean multiplicity lo-cation problem (EMFL) are two special nonsmooth convex programming problems which haveattracted a largr literature. For the ESFL problem. there are algorithms which converge bothglobally and quadratically For the EMFL problem there are some quadratically convergentalgorithms. but for global convergencel they all need nontrivial assumptions on the problem.In this paper we present an algorithm for EMFL. With no assumption on the problem it isproved that from any initial point this algorithm generates a sequence of points which convergesto the closed convex set of optimal solutions of EMFL.

The Euclidean single facility location problem (ESFL) and the Euclidean multiplicity lo-cation problem (EMFL) are two special nonsmooth convex programming problems which haveattracted a largr literature. For the ESFL problem. there are algorithms which converge bothglobally and quadratically For the EMFL problem, there are some quadratically convergentalgorithms. but for global convergencel they all need nontrivial assumptions on the *** this paper, we present an algorithm for EMFL. With no assumption on the problem, it isproved that from any initial point, this algorithm generates a sequence of points which convergesto the closed convex set of optimal solutions of EMFL.

关键词： A GLOBALLY CONVERGENT algorithm FOR THE EUCLIDEAN MULTIPLICITY LOCATION PROBLEM

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Zeta Hull pursuits: learning nonconvex data hulls 14

Zeta Hull pursuits: learning nonconvex data hulls

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Proceedings of the 27th International Conference on Neural Information Processing Systems - Volume 1

作者： Yuanjun Xiong Wei Liu Deli Zhao Xiaoou Tang Information Engineering Department The Chinese University of Hong Kong Hong Kong IBM T. J. Watson Research Center Yorktown Heights New York Advanced Algorithm Research Group HTC Beijing China

Selecting a small informative subset from a given dataset, also called column sampling, has drawn much attention in machine learning. For incorporating structured data information into column sampling, research efforts were devoted to the cases where data points are fitted with clusters, simplices, or general convex hulls. This paper aims to study nonconvex hull learning which has rarely been investigated in the literature. In order to learn data-adaptive nonconvex hulls, a novel approach is proposed based on a graph-theoretic measure that leverages graph cycles to characterize the structural complexities of input data points. Employing this measure, we present a greedy algorithmic framework, dubbed Zeta Hulls, to perform structured column sampling. The process of pursuing a Zeta hull involves the computation of matrix inverse. To accelerate the matrix inversion computation and reduce its space complexity as well, we exploit a low-rank approximation to the graph adjacency matrix by using an efficient anchor graph technique. Extensive experimental results show that data representation learned by Zeta Hulls can achieve state-of-the-art accuracy in text and image classification tasks.

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