检索结果-内蒙古大学图书馆

Chinese Materials Conference, 2018

作者： Wang, Yuehua Ma, Liwen Zhang, Yunhe Huang, Zhaojie Xi, Xiaoli College of Materials Science and Engineering Beijing University of Technology Beijing100124 China National Engineering Laboratory for Industrial Big-data Application Technology Beijing University of Technology Beijing100124 China

ISBN: (纸本)9783035713848

With the development of new energy vehicles, urgent issues have attracted considerable attention. Some power batteries have entered the scrapping period with the imperative recycling of used power batteries. Some studies have predicted that by 2020 the amount of power lithium battery scrap will reach 32.2 GWh, corresponding to ~500,000 tons, and by 2023 the scrap will reach 101 GWh, corresponding to ~1.16 million tons. In this study, nickel-cobalt-lithium LiNi0.7 Co0.3 O2 cathode materials are regenerated from spent lithium-ion battery cathode materials as the raw material, which not only aids in the reduction of pressure on the environment but also leads to the recycling of resources. First, the extraction was employed using extracting agent p204 to remove aluminum ions from an acid leaching solution. The extraction conditions for aluminum ions were: including a phase ratio of 1:2, a pH of 3, an extractant concentration of 30%, and a saponification rate of 70%. Next, the precursor was prepared by co-precipitation using sodium hydroxide and ammonia water as the precipitant and complexion agents, respectively;hence, the cathode material can be uniformly mixed at the atomic level. The precursor and lithium hydroxide were subjected to calcination at high temperature using a high-temperature solid-phase method. The Calcination conditions included an air atmosphere;a calcination temperature of 800 °C;a calcination time of 15 h, an n (precursor): n (lithium hydroxide) ratio of 1:1.1. The thermogravimetric analysis revealed that the synthesis temperature should not exceed 850 °C. X-ray diffraction analysis, scanning electron microscopy, and energy spectrum analysis of the cathode material revealed a composition comprising Li, Ni, and Co oxides. After analysis, the material obtained is lithium nickel-cobalt-oxide, LiNi0.7 Co0.3 O2, which is a positive electrode material with good crystallinity and a regular layered structure. © 2019 Trans Tech Publications, Switzerland.

关键词： Coprecipitation

来源：评论

学校读者我要写书评

暂无评论

Capacity analysis of ship-tugging operations in a large container port

引用

Asian Transport Studies 2020年 6卷

作者： Kang, Liujiang Gao, Song Meng, Qiang Key Laboratory of Transport Industry of Big Data Application Technologies for Comprehensive Transport Ministry of Transport Beijing Jiaotong University 100044 China Intelligent Transportation Systems Research Center Wuhan University of Technology Wuhan 430063 China Department of Civil and Environmental Engineering National University of Singapore Singapore 117576 Singapore

In this study, we deal with the simulation problem of ship-tugging operations in a large container port. First, we build a tugboat-service network using a directed graph, where the nodes consist of tugboat bases, anchorages, and berths while the arcs represent the directed links between nodes. Second, we develop a marine traffic simulation system, which can simulate maritime traffic conditions in restricted waters, such as large container ports and busy straits. The marine traffic simulation system is a customized system. Users are allowed to set their study areas and virtual traffic environment (such as traffic demand and network structure) at will. Finally, we conduct various simulations for a real tugboat-service network of Singapore Port, which includes one anchorage, one tugboat base, two berths, and two channels between the anchorage and berths. A detailed analysis of the tugging capacity is provided based on simulation results. © 2020 The Authors

关键词： Capacity estimation Container ports Simulation system development Tugging operations

来源：评论

学校读者我要写书评

暂无评论

Finding robust and consistent space-time delivery paths for multi-day vehicle routing problem

Finding robust and consistent space-time delivery paths for ...

引用

2019 IEEE Intelligent Transportation Systems Conference, ITSC 2019

作者： Zhuge, Lijuan Tong, Lu Carol Wu, Hailong Chen, Yiheng Zhou, Xuesong Beijing Jiaotong University School of Traffic and Transportation Haidian Beijing100044 China Beihang University School of Electronic and Information Engineering Beijing100091 China National Engineering Laboratory for Comprehensive Transportation Big Data Application Technology Beijing100091 China Beijing Jingdong Zhenshi Information Technology Co. Ltd. Logistics RandD Department China Arizona State University School of Sustainable Engineering and the Built Environment TempeAZ85281 United States

ISBN: (纸本)9781538670248

Facing uncertain and dynamic demands over different days, logistics companies need to adopt adaptive solutions for the last-mile delivery. Meanwhile, one of the major barriers for implementing vehicle routing problem (VRP) algorithms in real world dispatching systems is the stability of delivery driver's routes and schedules. To establish a theoretically sound and practically useful solution framework, this paper aims to optimize robust and consistent space-time paths for the multi-day VRP by providing daily schedules with limited variations from the master schedule. A multi-commodity network flow-based optimization model is proposed to minimize generalized transportation costs and the daily deviation of day-dependent space-time paths among demand analysis zones. Lagrange relaxation (LR) methods and alternating direction method of multipliers (ADMM) are used to handle complex side constraints. Experiments on illustrative networks and Beijing delivery network are developed to demonstrate the effectiveness of the proposed method. © 2019 IEEE.

关键词： Vehicle routing

来源：评论

学校读者我要写书评

暂无评论

Medical Image Segmentation Using Deep Learning: A Survey

arXiv

引用

arXiv 2020年

作者： Wang, Risheng Lei, Tao Cui, Ruixia Zhang, Bingtao Meng, Hongying Nandi, Asoke K. The School of Electronic Information and Artificial Intelligence The Shaanxi Joint Laboratory of Artificial Intelligence Shaanxi University of Science and Technology Xi'An710021 China The 'Laboratory of Hepatobiliary Surgery First Affiliated Hospital' 'National Engineering Laboratory of Big Data Algorithm and Analysis Technology Research' Xi'an Jiaotong University Xi'An710049 China The School of Electronic and Information Engineering Lanzhou Jiaotong University Lanzhou730070 China The Department of Electronic and Electrical Engineering Brunel University London UxbridgeUB8 3PH United Kingdom

Deep learning has been widely used for medical image segmentation and a large number of papers has been presented recording the success of deep learning in the field. In this paper, we present a comprehensive thematic survey on medical image segmentation using deep learning techniques. This paper makes two original contributions. Firstly, compared to traditional surveys that directly divide literatures of deep learning on medical image segmentation into many groups and introduce literatures in detail for each group, we classify currently popular literatures according to a multi-level structure from coarse to fine. Secondly, this paper focuses on supervised and weakly supervised learning approaches, without including unsupervised approaches since they have been introduced in many old surveys and they are not popular currently. For supervised learning approaches, we analyze literatures in three aspects: the selection of backbone networks, the design of network blocks, and the improvement of loss functions. For weakly supervised learning approaches, we investigate literature according to data augmentation, transfer learning, and interactive segmentation, separately. Compared to existing surveys, this survey classifies the literatures very differently from before and is more convenient for readers to understand the relevant rationale and will guide them to think of appropriate improvements in medical image segmentation based on deep learning approaches. Copyright © 2020, The Authors. All rights reserved.

关键词： Surveys

来源：评论

学校读者我要写书评

暂无评论

Natural image classification based on multi-parameter optimization in deep convolutional neural network

引用

International Journal of Performability engineering 2019年第9期15卷 2515-2521页

作者： Wang, Lei Zhang, Yanning Xi, Runping Ling, Lu School of Computer Northwestern Polytechnical University Xi'an710072 China National Engineering Laboratory for Integrated Aero-Space-Ground-Ocean Big Data Application Technology Xi'an710072 China Jiangxi Engineering Technology Research Center of Nuclear Geoscience Data Science and System East China University of Technology Nanchang330013 China

Traditional machine learning algorithms cannot adequately train the parameters of networks using massive data. A deep convolutional neural network based on multi-parameter optimization by the TensorFlow deep learning framework is designed in this paper. In order to improve the training speed and prevent over-fitting, we improve and optimize the multi-parameters, including the batch value, dropout, and momentum in the network structure. The experiment involves training and testing on the standard natural image data sets in cifar-10 and cifar-100. The experimental results show that the method achieve better classification accuracy in less time compared with other algorithms, such as Conv-KN, ImageNet-2010, SVM, LR, and Boosting. © 2019 Totem Publisher, Inc. All rights reserved.

关键词： Image classification

来源：评论

学校读者我要写书评

暂无评论

Ball k-means

arXiv

引用

arXiv 2020年

作者： Xia, Shuyin Peng, Daowan Meng, Deyu Zhang, Changqing Wang, Guoyin Chen, Zizhong Wei, Wei Department of Chongqing Key Laboratory of Computational Intelligence Chongqing University of Posts and Telecommunications Chongqing400065 China National Engineering Laboratory for Algorithm and Analysis Technologiy on Big Data Xian Jiaotong University Xi'an710049 China College of Intelligence and Computing Tianjin University 300072 China Department of Computer Science and Engineering University of California Riverside 900 University Avenue RiversideCA92521 United States School of Computer Science and Engineering Xi'an University of Technology Xi'an710048 China

This paper presents a novel accelerated exact k-means algorithm called the Ball k-means algorithm, which uses a ball to describe a cluster, focusing on reducing the point-centroid distance computation. The Ball k-means can accurately find the neighbor clusters for each cluster resulting distance computations only between a point and its neighbor clusters centroids instead of all centroids. Moreover, each cluster can be divided into a stable area and an active area, and the later one can be further divided into annulus areas. The assigned cluster of the points in the stable area is not changed in the current iteration while the points in the annulus area will be adjusted within a few neighbor clusters in the current iteration. Also, there are no upper or lower bounds in the proposed Ball k-means. Furthermore, reducing centroid-centroid distance computation between iterations makes it efficient for large k clustering. The fast speed, no extra parameters and simple design of the Ball k-means make it an all-around replacement of the naive k-means algorithm. Copyright © 2020, The Authors. All rights reserved.

关键词： K-means clustering

来源：评论

学校读者我要写书评

暂无评论

Towards end-to-end text spotting in natural scenes

arXiv

引用

arXiv 2019年

作者： Wang, Peng Li, Hui Shen, Chunhua School of Computer Science Northwestern Polytechnical University China National Engineering Laboratory for Integrated AeroSpace-Ground-Ocean Big Data Application Technology China Samsung Research Monash University Australia

Text spotting in natural scene images is of great importance for many image understanding tasks. It includes two sub-tasks: text detection and recognition. In this work, we propose a unified network that simultaneously localizes and recognizes text with a single forward pass, avoiding intermediate processes such as image cropping and feature re-calculation, word separation, and character grouping. The overall framework is trained end-to-end and is able to spot text of arbitrary shapes. The convolutional features are calculated only once and shared by both the detection and recognition modules. Through multi-task training, the learned features become more discriminative and improve the overall performance. By employing a 2D attention model in word recognition, the issue of text irregularity is robustly addressed. The attention model provides the spatial location for each character, which not only helps local feature extraction in word recognition, but also indicates an orientation angle to refine text localization. Experiments demonstrate that our proposed method can achieve state-of-the-art performance on several widely-used text spotting benchmarks, including both regular and irregular datasets. © 2019, CC BY-NC-SA.

关键词： Deep neural networks

来源：评论

学校读者我要写书评

暂无评论

User Identity Authentication and Identification Based on Multi-Factor Behavior Features

User Identity Authentication and Identification Based on Mul...

引用

IEEE Globecom Workshops

作者： Xing Ding Changgen Peng Hongfa Ding Maoni Wang Hui Yang Qinyong Yu College of Computer Science & Technology State Key Laboratory of Public Big Data Guizhou University Guiyang China College of Information Guizhou University of Financial and Economics Guiyang China National Engineering Laboratory Big Data Application on Improving Government Governance Capabilities Guiyang China CETC Big Data Research Institute Co. Ltd Guiyang China

ISBN: (数字)9781728109602

ISBN: (纸本)9781728109619

Behavior-based identity authentication has been of research interests due to its low cost and the fact that such authentication factors cannot easily copied nor stolen. However, single behavior feature authentication usuall cannot gaurantee sufficient accuracy. In this paper, a multi-factor behavior features identity authentication method is proposed by combining factors of mouse, keystroke and address. We apply support vector machine by using the information divergence of features as the weight of the linear kernel function to solve quantification's problem of features influence degree on authentication. The tailored support vector machine is applied to multi-factor behavior features to identity authentication. Our experimental results show that the improved support vector machine is better than both the linear and Gaussian kernel support vector machines for identity authentication in accuracy. The proppsed method can be applied to large volume users' identity authentication cases where their behavior features are likely to be similar.

关键词： Authentication Mice IP networks Feature extraction Support vector machines Hidden Markov models Presses

来源：评论

学校读者我要写书评

暂无评论

Award for Outstanding Comprehensive Mini-Challenge 2 Solution - RadiationMonitor: An Interactive System for Visualizing and Exploring Spatial-Temporal data

Award for Outstanding Comprehensive Mini-Challenge 2 Solutio...

引用

IEEE Symposium on Visual Analytics Science and technology (VAST)

作者： Datong Wei Hanning Shao Zijing Tan Chenlu Li Zhixian Lin Xiaoju Dong Xiaoru Yuan Key Laboratory of Machine Perception Ministry of Education School of EECS Peking University Weinberg College of Arts and Sciences Northwestern University School of Electronic Information and Electrical Engineering Shanghai Jiao Tong University National Engineering Laboratory for Big Data Analysis and Application Peking University

In this paper, we proposed RadiationMonitor, an interactive system for visualizing and exploring spatial-temporal data from static and mobile sensors. We use pixel-based time-series visualization for event presentation, and the trajectories of mobile sensors are discretized to display the spatial distribution of sensor readings. Our system provides cross-filtering and detail-on-demand interactions, which allow users to investigate data from both spatial and temporal aspects.

关键词： Sensor systems Pollution measurement data visualization Uncertainty Image color analysis Measurement uncertainty Awards

来源：评论

学校读者我要写书评

暂无评论

Smartphone-based Public Transport Guidance: An Investigation of Potential Benefits

Smartphone-based Public Transport Guidance: An Investigation...

引用

2019 IEEE Intelligent Transportation Systems Conference, ITSC 2019

作者： Liu, Tao Jiang, Yu Ceder, Avishai Avi Gasson, Rachel Cheyne, Lorraine Southwest Jiaotong University School of Transportation and Logistics Chengdu611756 China National United Engineering Laboratory of Integrated and Intelligent Transportation Chengdu610031 China National Engineering Laboratory of Integrated Transportation Big Data Application Technology Chengdu611756 China Transport Division Bygningstorvet 116B LyngbyDK-2800Kgs Denmark Technion-Israel Institute of Technology Transportation Research Institute Haifa32000 Israel Transportation Research Center Faculty of Engineering University of Auckland Department of Civil and Environmental Engineering 20 Symonds Street New Zealand Auckland New Zealand

ISBN: (纸本)9781538670248

With the rapid development of smartphone applications, real-time and readily available journey planning information is becoming an integral part of a public transport (PT) system. Smartphones and other mobile devices are information sources capable of contributing to "big-data", and while each traveler has specific preference when undertaking a trip. The objective of this study is to look at how readily available smartphone-based information containing elements that might influence the decisions of which trip to select, can be personalized. The potential effect of personalized data availability for PT users has been investigated by considering five key weighted factors: waiting time, travel time, fare cost, walking time, and number of transfers. The methodology is based on finding the K-shortest path for travelers where the value of each link comprises the cost of the five weighted factors based on users' preferences. By incorporating weighted factors, users may lean toward the 2nd, or 3rd, etc., shortest path. A case study was conducted to look at five parallel PT routes with different journey attributes in the city center of Auckland, New Zealand. The results show that the satisfaction of the users improves as they achieve their desired trip under optimized conditions based on their preferences. © 2019 IEEE.

关键词： Smartphones

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：