检索结果-内蒙古大学图书馆

您好，读者！请登录

内蒙古大学图书馆

首页
概况
党建
资源
服务
科研支持
- 论文收录引用证明
- 科技查新
知识产权
档案馆
帮助

咨询与建议

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

您的常用邮箱：*

您的手机号码：*

问题描述：

当前已输入0个字，您还可以输入200个字

全部搜索
期刊论文
图书
学位论文
标准
纸本馆藏
外文资源发现
数据库导航
超星发现

高级检索

时间限定

出版年份：

文献类型

图书期刊文献学位论文多媒体

馆藏选择

电子馆藏纸本馆藏

核心期刊

全部期刊 SCI 收录期刊 SSCI 收录期刊 EI 收录期刊 CSCD 收录期刊 CSSCI 收录期刊

语言

中文英文

文献类型

期刊文献图书学位论文标准纸本馆藏

帮助

文字说明：

T=题名（书名、题名），A=作者（责任者），K=主题词，P=出版物名称，PU=出版社名称，O=机构（作者单位、学位授予单位、专利申请人），L=中图分类号，C=学科分类号，U=全部字段，Y=年（出版发行年、学位年度、标准发布年）

检索规则说明：

AND代表“并且”；OR代表“或者”；NOT代表“不包含”；(注意必须大写,运算符两边需空一格)

检索范例：

范例一：(K=图书馆学 OR K=情报学) AND A=范并思 AND Y=1982-2016
范例二：P=计算机应用与软件 AND (U=C++ OR U=Basic) NOT K=Visual AND Y=2011-2016

分类表

所选分类

>> <<

限定检索结果

文献类型

7,956 篇 会议
81 篇 期刊文献
77 册 图书

馆藏范围

8,114 篇 电子文献
0 种 纸本馆藏

日期分布

学科分类号

5,054 篇 工学
- 3,914 篇 计算机科学与技术...
- 2,388 篇 信息与通信工程
- 1,802 篇 软件工程
- 1,358 篇 电气工程
- 633 篇 控制科学与工程
- 418 篇 动力工程及工程热...
- 372 篇 电子科学与技术（可...
- 314 篇 生物工程
- 222 篇 生物医学工程（可授...
- 209 篇 仪器科学与技术
- 205 篇 机械工程
- 173 篇 测绘科学与技术
- 167 篇 光学工程
- 126 篇 化学工程与技术
- 120 篇 材料科学与工程（可...
- 95 篇 建筑学
- 88 篇 土木工程
- 85 篇 石油与天然气工程
- 85 篇 安全科学与工程
1,380 篇 理学
- 634 篇 数学
- 413 篇 物理学
- 360 篇 生物学
- 213 篇 统计学（可授理学、...
- 138 篇 化学
- 121 篇 系统科学
686 篇 管理学
- 395 篇 管理科学与工程(可...
- 307 篇 图书情报与档案管...
- 149 篇 工商管理
239 篇 医学
- 210 篇 临床医学
- 132 篇 基础医学(可授医学...
84 篇 法学
82 篇 农学
57 篇 经济学
23 篇 军事学
22 篇 教育学
15 篇 文学
1 篇 哲学

主题

1,596 篇 wireless sensor ...
501 篇 neural networks
328 篇 wireless communi...
303 篇 convolutional ne...
254 篇 deep learning
238 篇 sensor nodes
222 篇 routing
217 篇 feature extracti...
185 篇 monitoring
179 篇 image processing
178 篇 signal processin...
172 篇 wireless sensor ...
168 篇 energy consumpti...
166 篇 sensor networks
163 篇 sensors
158 篇 accuracy
149 篇 sensor systems
147 篇 real-time system...
142 篇 protocols
139 篇 routing protocol...

机构

15 篇 chitkara univers...
10 篇 univ chinese aca...
10 篇 school of inform...
10 篇 beijing universi...
10 篇 gla university m...
9 篇 south china univ...
9 篇 university of ch...
9 篇 beijing institut...
8 篇 department of co...
8 篇 department of el...
7 篇 school of inform...
7 篇 chinese academy ...
6 篇 univ wisconsin d...
6 篇 karnataka bangal...
6 篇 computer network...
6 篇 shanghai jiao to...
6 篇 school of comput...
6 篇 school of electr...
6 篇 amrita vishwa vi...
6 篇 shihezi universi...

作者

12 篇 wang wei
11 篇 chen chen
9 篇 liu yang
9 篇 li qiang
8 篇 zhang tao
8 篇 wang lei
7 篇 wei liu
7 篇 liu wei
7 篇 cao jiannong
6 篇 badache nadjib
6 篇 jiao licheng
6 篇 wei wang
5 篇 zhou jie
5 篇 li xin
5 篇 hui wang
5 篇 pitchaimanickam ...
5 篇 soman k. p.
5 篇 liu ying
5 篇 zhang sheng
5 篇 qiang li

语言

7,951 篇 英文
153 篇 其他
18 篇 中文
1 篇 俄文

检索条件"任意字段=5th International Conference on Informational Processing in Sensor Networks"

共 8114 条记录，以下是211-220 订阅

全选清除本页清除全部题录导出标记到"检索档案"

详细简洁

排序：

High-Performance Computing for Efficient Transaction processing: A Comparative Study of Parallel and Sequential Execution using SQLite 5

High-Performance Computing for Efficient Transaction Process...

引用

5th international conference on IoT Based Control networks and Intelligent Systems, ICICNIS 2024

作者： Balaji, C.V.Roshan Shaman, K.R. Pritham Raj, V. Kumar, N.Nithish Kumaran, K. School of Computer Science and Engineering Vellore Institute of Technology Chennai campus India

ISBN: (纸本)9798331518097

High-performance computing (HPC) has become an essential tool for improving the efficiency and scalability of transaction processing systems, especially as data volumes continue to grow in fields like finance, e-commerce, and blockchain. this paper presents a comparative study of parallel and sequential transaction processing methods using an SQLite database. Specifically, the research investigates the impact of HPC techniques on transaction throughput, processing speed, and efficiency by simulating 1,000 user transactions. the study employs Python's multiprocessing module to simulate parallel execution, contrasting it with traditional sequential execution. Key performance indicators, including execution time, transaction success rate, and system efficiency, were analyzed to determine the advantages of parallel processing in a transaction-heavy environment. Our results reveal that parallel execution significantly reduces processing time, boosts throughput, and increases overall system efficiency compared to sequential processing. Additionally, the study discusses how parallel processing techniques can address common bottlenecks in transaction-heavy applications and provide solutions for improving the performance of large-scale, data-intensive systems. the findings demonstrate the potential for using HPC to optimize database operations, particularly in systems where high-volume transaction processing is a critical requirement. Future work will explore advanced parallelization strategies, fault tolerance mechanisms, and integrations with distributed databases and blockchain systems. this research contributes to the growing body of knowledge on optimizing transaction processing in high-performance computing environments, with potential applications across various sectors, including financial services, e-commerce, and blockchain technology. © 2024 IEEE.

关键词： Blockchain

来源：评论

学校读者我要写书评

暂无评论

Beyond Depth: Evaluating ResNet-50 and ResNet-152 Performance on Cifar-10 Dataset 5

Beyond Depth: Evaluating ResNet-50 and ResNet-152 Performanc...

引用

5th international conference on Sustainable Communication networks and Application, ICSCNA 2024

作者： Krithika, M. Gayathri, A. Revathy, G. Senthilvadivu, S. Venkateswaran, S. SASTRA Deemed University Srinivasa Ramanujan Centre Department of CSE Kumbakonam Thanjavur India Saveetha University Department of CSE Chennai India Veltech Rangarajan Dr Sagunthala R&D Institute of science and Technology Chennai India

ISBN: (纸本)9798331530013

Deep learning techniques have transformed the area of computer vision, with Residual networks (ResNets) particularly notable for their capacity to effectively train very deep neural networks. the work conducts a thorough analysis of the use of two popular ResNet architectures-ResNet-50 and ResNet-152-for image classification tasks using the CIFAR-10 dataset. On investigating the delicate relationship between model depth, computational complexity, and classification performance. Providing a thorough investigation of training dynamics, convergence rates, and final model performance. Our findings show that ResNet-152 delivers somewhat greater accuracy, notably on the more complicated CIFAR -10 dataset, but at a substantial expense in terms of processing resources and training time. Quantifying the trade-offs between model depth and efficiency, and provide empirical data to help practitioners choose suitable architectures for comparable picture categorization tasks. Furthermore, investigation ways for optimizing training processes, such as learning rate scheduling and data augmentation strategies, in order to maximize the potential of each design. © 2024 IEEE.

关键词： Convolutional neural networks

来源：评论

学校读者我要写书评

暂无评论

Systematic Review of Sentiment Analysis: Insights through CNN-LSTM networks 5

Systematic Review of Sentiment Analysis: Insights Through CN...

引用

5th international conference on Industrial Engineering and Artificial Intelligence, IEAI 2024

作者： Feisheng, Liu Guangzhou Sontan Polytechnic College School of Information Engineering Guangzhou China

ISBN: (纸本)9798350386363

Sentiment analysis, leveraging advancements in Natural Language processing (NLP) and Machine Learning (ML), has become a pivotal tool for interpreting public opinion in various sectors. this systematic review delves into the innovative integration of Convolutional Neural networks (CNN) and Long Short-Term Memory (LSTM) networks within this field, with a particular focus on customer evaluations in the digital age. While traditional sentiment analysis primarily utilized classical ML and lexicon-based methods, the incorporation of deep learning (DL) techniques has marked a transformative phase, especially in analyzing extensive social network data. Our review guides readers through the DL landscape in sentiment analysis, highlighting the combined strengths of CNN and LSTM models. It offers an in-depth examination of various sentiment analysis methodologies, underscoring the profound impact of CNN-LSTM networks. this paper discusses diverse sentiment analysis approaches, their practical applications, and addresses the challenges faced. Notably, the synergy of CNN and LSTM has led to significant advancements in interpreting complex sentiment data, opening new avenues in marketing, brand management, and public opinion analysis. the goal of this review is to provide an extensive understanding of DL in sentiment analysis, shedding light on its contemporary applications and potential future developments. © 2024 IEEE.

关键词： Convolutional neural networks

来源：评论

学校读者我要写书评

暂无评论

Effects on Selective Removal of Adversarial Examples for Noisy X-ray Images 5

Effects on Selective Removal of Adversarial Examples for Noi...

引用

5th international conference on Intelligent Medicine and Image processing, IMIP 2023

作者： Namura, Haruto Itasaka, Tatsuki Okuda, Masahiro Doshisha University Graduate School of Science and Engineering Kyoto Japan

ISBN: (纸本)9798350337396

Preprocessing the input images of the deep neural networks (DNN) is a way to prevent adversarial attacks without compromising the classification performance of the targeted model. Especially, considering the perturbation as noise, then applying denoising as the preprocessing method is known to be effective in removing perturbations caused by adversarial attacks. However, perturbation removal can result in excessive image smoothing and finer details of the image can be lost in the denoising process. Here, we experimentally confirm the effectiveness of selectively removing perturbations to maintain image quality after perturbation removal and propose an image reconstructing model based on Res-Unet. © 2023 IEEE.

关键词： Deep neural networks

来源：评论

学校读者我要写书评

暂无评论

Revolutionizing Data Transmission - A Comprehensive Review of Deep Learning-Based Routing Mechanism for 5G Wireless sensor networks 10

Revolutionizing Data Transmission - A Comprehensive Review o...

引用

10th international conference on Communication and Signal processing, ICCSP 2024

作者： Vijayakumar, K. thirumaraiselvan, P. Sivakumar, B. Seenuvasan, P. Adhiparasakthi Engineering College Department of It Tamilnadu India Adhiparasakthi Engineering College Department of ECE Tamilnadu India Srm Institute of Science and Technology Department of Computing Technologies Tamilnadu India University College of Engineering Department of It Villupuram India

ISBN: (纸本)9798350353068

the convergence of 5G technology and Wireless sensor networks (WSNs) has lead in a transformative era in wireless communication, demanding intelligent and adaptive routing protocols. this review explores into the monarchy of deep learning-based routing protocols, dissecting their potential applications, challenges, and impact on the efficiency of 5G-enabled WSNs. Lack of understanding and variance, two crucial factors in the details of deep learning-based routing. the review scrutinizes the complexity of routing decisions and explores how deep learning algorithms introduce a layer of adaptability significant of human perception. As we examine the landscape of 5G WSNs, the benefits and challenges of incorporating deep learning into routing practices come to light. Adaptive decision-making, energy efficiency, resilience to dynamic environments, and enhanced data accuracy emerge as promising outcomes. However, the review also sheds light on the computational complexities and potential biases in training data that necessitate careful consideration. this review serves as a compass, navigating through the terrain of deep learning-based routing protocols for 5G WSNs. By sorting out the hints of incomprehension and variance within this context, we aim to provide a comprehensive understanding of the evolving landscape of intelligent routing. As 5G technology continues to redefine connectivity standards, this review contributes to the foundation of knowledge guiding the development and implementation of effective and adaptive routing protocols in the era of wireless sensor networks. © 2024 IEEE.

关键词： Wireless sensor networks

来源：评论

学校读者我要写书评

暂无评论

Design Guidelines for Voltage Doubler Circuits with Transmission Line Impedance Matching networks for RFEH Applications 5

Design Guidelines for Voltage Doubler Circuits with Transmis...

引用

5th IEEE international conference on Advances in Electrical, Computing, Communication and Sustainable Technologies, ICAECT 2025

作者： Rosaline, Imaculate Shastry, Prasad Ramaiah Institute of Technology Department of Ece Bangalore India Bradley University Department of Electrical and Computer Engg PeoriaIL United States

ISBN: (纸本)9798350356236

RF Energy Harvesting (RFEH) is the ideal substitute for traditional batteries for continuously powering the sensor networks situated in remote locations. An appropriate Voltage Doubler circuit (full-wave rectifier circuit) with high Power Conversion Efficiency (PCE) is required for this purpose. this paper gives guidelines for the design of voltage doubler circuits (rectifiers) utilizing two different transmission line (Tline) impedance-matching networks. Schottky diodes were used for rectification and two impedance-matching networks (IMN) were designed using the transmission lines. the two IMNs differ in their topologies and hence are termed Pi-section and T-section networks. the T-section network was found to give a much higher return loss. the proposed rectifiers operate at 900 MHz over a wide range of RF input power levels varying from -20 dBm to 30 dBm. With the T-section IMN, the voltage doubler offered a maximum PCE of 53% at an input power level of 20 dBm and a load resistance of 1 M Ohm. the DC output voltage was found to be 2.53 V. © 2025 IEEE.

关键词： Impedance matching (electric)

来源：评论

学校读者我要写书评

暂无评论

TsCDD-GAN: A Conditional Dual-Discriminator Generative Adversarial Network for Incomplete Time Series Data Imputation and Clustering 5

TsCDD-GAN: A Conditional Dual-Discriminator Generative Adver...

引用

5th international conference on Computer Vision, Image and Deep Learning, CVIDL 2024

作者： Peng, Bo Dong, Chen Tianjin University of Technology School of Computer Science and Engineering Tianjin China

ISBN: (纸本)9798350373820

Time series clustering is a complex unsupervised data mining and analysis technique that can be applied to various fields such as signal processing, financial analysis, and more. However, time series data often contain missing values due to reasons such as sensor failures, data corruption, or intentional omissions in the real world. Traditional generative imputation methods operate independently from subsequent clustering tasks, and their performance relies on the combination with the clustering method, lacking a deeper connection. Efficiently integrating imputation and clustering tasks into a unified framework remains a formidable challenge. this paper presents a novel model that harmonizes the imputation and clustering processes, referred to as the Conditional Dual-Discriminator Generative Adversarial Network for Incomplete Time Series Data Imputation and Clustering (TsCDD-GAN). the TsCDD-GAN model leverages advanced bi-directional Recurrent Units (Bidirectional RNN) as the generator to learn and impute missing data, integrating two discriminators. the first discriminator assists the generator in producing more authentic values, while the second, a conditional discriminator, extracts clustering information from the latent representations of the data. this enables the generator to not only generate more realistic values but also ensure that the imputed data exhibit cluster-friendly characteristics. through experiments conducted on the UCR time series dataset, our model has demonstrated better performance in terms of imputation accuracy on incomplete datasets. © 2024 IEEE.

关键词： Generative adversarial networks

来源：评论

学校读者我要写书评

暂无评论

Energy-Efficient Autism Spectrum Disorder Data Collection Mechanism using Wireless sensor networks and Internet-of-things 5

Energy-Efficient Autism Spectrum Disorder Data Collection Me...

引用

5th IEEE international conference on Advances in Electrical, Computing, Communication and Sustainable Technologies, ICAECT 2025

作者： Vijaya Shetty, S. Srujana, S.N. Naidu, P. Ramesh Neeli, Jyoti Sarojadevi, H. Prakash, Ramya Nitte Meenakshi Institute of Technology Department of Computer Science and Engineering Karnataka Bengaluru India

ISBN: (纸本)9798350356236

A patient's cognitive health may be better assessed using smart monitoring and assisted living technologies. Social skills, repetitive habits, verbal and nonverbal communication, and adjusting to new environments are among the challenges children on the autism spectrum face. Because of their reduced cognitive capacities, children with autism spectrum disorder (ASD) present a significant public health challenge because it is difficult to comprehend their feelings. the main purpose of this research is to assist autistic newborns in adapting to their environment via Internet-of-things (IoT) technologies and wireless sensor networks. the study indicates an Internet of things (IoT)-WSNs system for data collection, using an energy-efficient cluster-based routing optimization (EECRO) method that sends data to an IoT gateway server as quickly as possible, allowing the guardian to access the data in real-time. the simulation outcome indicates the EECRO can significantly reduce energy consumption to deliver messages from autistic children to their guardians. © 2025 IEEE.

关键词： Assisted living

来源：评论

学校读者我要写书评

暂无评论

5G Application for Methodologies for Big Data Application 5

5G Application for Methodologies for Big Data Application

引用

5th IEEE international conference on Computing, Power, and Communication Technologies, IC2PCT 2024

作者： Singh, Amanveer Chitkara University Institute of Engineering and Technology Chitkara University Centre for Interdisciplinary Research in Business and Technology Punjab India

ISBN: (纸本)9798350383522

the advantages and benefits of big data and cellular networks are discussed in this essay. First, a summary of their interactions, together with big data-driven and big data-assisted communication networks, is given. the erstwhile caters for big data characteristics like number, pace, and variation by utilizing diverse means such as transmission, storage, and processing in cellular networks in order to accommodate big data apps and services. In order to gather wireless big data and gain detailed information about the networks and users for better network management and scheduling, the latter makes use of big data methods. Two examples that focus on channel data collection and big data-aided peripheral information storage are offered that will further highlight the reciprocal advantages. the discussion concludes with a few intriguing open study questions. © 2024 IEEE.

关键词： 5G Convergence Big Data Cellular networks Cloud Computing Data Analytics Data Collection Data processing Data Storage and Data Security Data Transmission Edge Computing Network Infrastructure Network Management Resource Allocation Wireless Communications

来源：评论

学校读者我要写书评

暂无评论

Disease Classification Model using Capsule networks based on White Blood Cells 5

Disease Classification Model using Capsule Networks based on...

引用

5th IEEE international conference for Emerging Technology, INCET 2024

作者： Gaikwad, Prajwal S. Deshmukh, Rakesh K. Pise, Priya Bhopale, Shrikant D. Kalinga University Raipur India Dept. of Computer Engineering AISSMS's Institute of Information Technology Pune India Kalinga University Raipur India Indira College of Engineering and Management Pune India Dr.D.Y.Patil Pratisthan's Colleg of Engineering Salokhenagar Kolhapur India

ISBN: (纸本)9798350361155

As a substitute for recurrent neural networks (RNNs), Deep Learning (DLs) has shown promise in text processing in the last several years. In this study, we looked at the recently announced capsule networks (CapsNets), which are gaining a lot of interest since they outperform Deep Learning (DLs) in image analysis, and we found that they function well for language categorization and sentiment analysis in some instances. Our experimental findings demonstrate that the suggested well-tuned CapsNets model may serve as a suitable (and, in some cases, superior and more cost-effective) alternative to sentence categorization models based on RNNs and DLs. We ran a battery of tests with randomly shuffled test data to see whether CapsNets could learn the sequence of words sequentially. Overall, our CapsNets model outperforms DL and RNN models in terms of classification performance and resilience to adversarial assaults. © 2024 IEEE.

关键词： Cost effectiveness

来源：评论

学校读者我要写书评

暂无评论

没有更多数据了...

全选清除本页清除全部题录导出标记到“检索档案”

共500页 << < 18 19 20 21 22 23 24 25 26 27 > >>

检索报告对象比较合并检索0

隐藏清空

合并搜索

回到顶部

执行限定条件

内容：

评分：

请选择保存的检索档案：

请选择收藏分类：

订阅名称：

通借通还

温馨提示：

图书名称：

借书校区：

取书校区：

手机号码：

邮箱地址：

一卡通帐号：

电话和邮箱必须正确填写，我们会与您联系确认。

联系人：

所在院系：

联系邮箱：

联系电话：

内蒙古自治区呼和浩特市赛罕区大学西街235号邮编: 010021

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：