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

900 篇 期刊文献
290 篇 会议
3 册 图书

馆藏范围

1,193 篇 电子文献
0 种 纸本馆藏

日期分布

学科分类号

862 篇 理学
- 638 篇 物理学
- 127 篇 地球物理学
- 115 篇 数学
- 66 篇 化学
- 50 篇 统计学（可授理学、...
- 46 篇 生物学
- 25 篇 海洋科学
- 23 篇 天文学
- 23 篇 系统科学
657 篇 工学
- 265 篇 计算机科学与技术...
- 198 篇 软件工程
- 141 篇 核科学与技术
- 114 篇 仪器科学与技术
- 98 篇 信息与通信工程
- 96 篇 电子科学与技术（可...
- 79 篇 电气工程
- 60 篇 光学工程
- 50 篇 控制科学与工程
- 41 篇 航空宇航科学与技...
- 38 篇 动力工程及工程热...
- 35 篇 土木工程
- 34 篇 生物工程
- 33 篇 化学工程与技术
- 28 篇 机械工程
- 27 篇 生物医学工程（可授...
86 篇 管理学
- 52 篇 管理科学与工程(可...
- 35 篇 图书情报与档案管...
- 25 篇 工商管理
36 篇 医学
- 30 篇 临床医学
- 23 篇 基础医学(可授医学...
13 篇 经济学
12 篇 农学
11 篇 法学
7 篇 教育学
2 篇 军事学
1 篇 艺术学

主题

150 篇 hadron colliders
74 篇 higgs bosons
47 篇 proton-proton in...
41 篇 w & z bosons
36 篇 standard model (...
35 篇 large hadron col...
33 篇 neutrons
33 篇 top quark
29 篇 collisions (nucl...
29 篇 nuclear counters
28 篇 supersymmetric m...
28 篇 relativistic hea...
28 篇 quark & gluon je...
26 篇 quarks
20 篇 cross sections (...
20 篇 particle product...
20 篇 photons
20 篇 extensions of hi...
19 篇 hypothetical par...
19 篇 leptons (nuclear...

机构

418 篇 yerevan physics ...
289 篇 faculty of scien...
289 篇 department of ph...
288 篇 department for p...
286 篇 department of ph...
284 篇 kirchhoff-instit...
273 篇 department of ph...
272 篇 departamento de ...
271 篇 department of ph...
264 篇 institute of phy...
263 篇 fakultät für phy...
250 篇 institut für ast...
249 篇 faculté des scie...
248 篇 institute of phy...
233 篇 instituto de fís...
227 篇 department of ph...
227 篇 physics division...
225 篇 department of ph...
221 篇 department of ph...
221 篇 department of ph...

作者

273 篇 c. alexa
272 篇 j. m. izen
265 篇 g. bella
263 篇 j. strandberg
263 篇 d. calvet
262 篇 c. amelung
248 篇 h. a. gordon
243 篇 g. spigo
239 篇 m. klein
238 篇 f. siegert
237 篇 r. ströhmer
234 篇 m. rijssenbeek
232 篇 s. jin
232 篇 g. gaudio
232 篇 s. mohapatra
228 篇 s. guindon
225 篇 y. tayalati
223 篇 d. guest
223 篇 a. kaczmarska
222 篇 a. c. könig

语言

1,100 篇 英文
90 篇 其他
3 篇 中文

检索条件"机构=B.E Computer Science and Engineering"

共 1193 条记录，以下是41-50 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：

Ant Colony Optimization in MANeT for Decreasing energy Consumption with ML Approaches

Ant Colony Optimization in MANET for Decreasing Energy Consu...

引用

2023 Ieee International Conference on Integrated Circuits and Communication Systems, ICICACS 2023

作者： Suresha, P. Math, Gayatri Arvind, Siddapuram bhaskar, M. Naveen, I.G. S.E.A College of Engineering and Technology Department of Mechanical Engineering Bengaluru India HKE Society's B.V. Bhoomaraddi College of Arts Science and Commerce Degree College Department of Electronics & Communication Engg Bidar India Hyderabad Institute of Technology and Management Department of Computer Science & Engineering Telangana India K L University Vadeeshwaram Department of Computer Science & Engineering Vijayawada India Nitte Meenakshi Institute of Technology Department of Electronics and Communication Engineering Bengaluru India

ISBN: (纸本)9798350398465

To coordinate access from the active nodes, MAC protocols are used in ad hoc networks. Many media access control (MAC) protocols have b.en suggested for use in ad hoc networks, each with its own unique set of goals. The goal of many ad hoc networks is to increase the amount of time that its individual nodes, and by extension, the network, can function. Ad-hoc nodes are considered dead when their batteries run out, hence it is crucial to reduce power drain. because to the nature of MANeTs, in which nodes must depend on limited, portab.e power sources, energy efficiency is a significant barrier to their widespread implementation. In multi-hop systems, where nodes must additionally expend energy to route packets for other nodes and assure the connection of the network, energy saving is difficult. Since energy-efficient routing is a relatively new area of study, there are still many open questions that need to be investigated and no widely accepted standards in place. Several routing protocols used the shortest route as a criterion for path selection;however, this is inappropriate due to the topology's significant and unexpected variability and does not assume the most efficient use of energy. Simulation is the primary tool for testing the efficacy of several routing protocols in MANeTs, including RIP, RIPng, PS-RIP, PSLLC-RIP, PS-RIPng, PSLLC-RIPng, FLbUDTCRIP, and ANFISbUDTCRIP. exata 5.4 GUI network simulator and OPNeT tools are used to analyse the efficiency of the suggested protocols. All the simulation results show \that the suggested protocols perform better than the current RIP protocols. © 2023 Ieee.

关键词： multi-protocol label switching

来源：评论

学校读者我要写书评

暂无评论

Analyzing, Detecting and Automatic Classification of Different Stages of brain Tumor Using Region Segmentation and Support Vector Machine

Analyzing, Detecting and Automatic Classification of Differe...

引用

2020 International Conference on electronics and Sustainab.e Communication Systems, ICeSC 2020

作者： Gayathri, S. Wise, D.C. Joy Winnie Janani, V. eleaswari, M. Hema, S. Rajalakshmi Institute of Technology Department of Cse India B.E Computer Science and Engineering Rajalakshmi Institute of Technology India

ISBN: (纸本)9781728141084

The clinical researchers found that, Magnetic Resonance Imaging is applied in various computer science applications. However, for detecting the brain tumor without human involvement is taken into account has a major space of analysis. As a result of the obtained brain tumor images need to be optimized segmentation rule that must be more silent towards noise and size of the cluster sensitivity prob.em with automatic region based segmentation property detection. Region based segmentation is used to segment the over segment and under segment of the tumor region with automatic ROI detection. After the successful detection of tumor parts that are going to classify the different classes of brain tumors such as benign and malignant. The benign tumor and malignant tumor are classified as normal stage, medium stage and severe stage. For that different feature extraction and classification methods are used for identifying the above. Without human intercession the brain tumor should be detected and analyzed. The SVM algorithm is used to classify the tumor cell. The accurate classification and giving appropriate therapy to the Patient plays a vital role in Health Care Sector. © 2020 Ieee.

关键词： Support vector machines

来源：评论

学校读者我要写书评

暂无评论

brain Tumor Detection using MRI Image Processing Techniques

Brain Tumor Detection using MRI Image Processing Techniques

引用

2024 Ieee International Conference on Innovation and Novelty in engineering and Technology, INNOVA 2024

作者： Jadhav, Ambaji S. Pawar, Rashmi Hattaraki, Sunilkumar M. bagali, Shwetha Patil, Rajeshwari S. Patil, bhagyashree Department of Elecrtical and Electronics Engineering B.L.D.E. A’s V.P. Dr. P.G.H. College of Engg. and Tech. Vijayapura India Department of Electronics and Communication Engineering B.L.D.E. A’s V.P. Dr. P.G.H. College of Engg. and Tech. Vijayapura India Department of Computer Science and Engineering Sri Krishna Institute of Technology Bengaluru India

ISBN: (纸本)9798331505134

Medical image processing is highly developed and critical in the medical field, encompassing methods like X-rays, MRI, and CT scans. These techniques help to identify minute defects in the human body. brain tumors, which disrupt normal brain function, are detected through MRI using segmentation, feature extraction, and classification, processes that are time-consuming and depend on the expertise of clinical professionals. computer-aided technology addresses these challenges. This work aims to diagnose brain tumors accurately and quickly using MRI images. Image preprocessing is done using CLAHe and median filter to enhance contrast and eliminate noise. Thresholding is used for segmentation and a lightweight U-net is used for tumor segmentation, achieving high accuracy and efficiency without extensive training data. Finally, an MSD-CNN classifies the tumor, capturing both local and global features for better image recognition. Our proposed model outperforms over existing methods in terms of accuracy, robustness, and efficiency in brain tumor detection. © 2024 Ieee.

关键词： Median filters

来源：评论

学校读者我要写书评

暂无评论

battery Monitoring System with IoT Integration

Battery Monitoring System with IoT Integration

引用

Advancements in electrical, electronics, Communication, Computing and Automation (ICAeCA), International Conference on

作者： Sanjith Krishna S Premchand V H Shri Ram b Sakthi Satchidhanandan S Anitha N Hariharan S.V B.E. Electronics and Communication Engineering Kumaraguru College of Technology Coimbatore India B.E. Computer Science Engineering Kumaraguru College of Technology Coimbatore India B.E. Electrical and Electronics Engineering Kumaraguru College of Technology Coimbatore India Department of Mathematics Kumaraguru College of Technology Coimbatore India

ISBN: (数字)9798331525439

ISBN: (纸本)9798331525446

battery Monitoring Systems (bMS) have played a pivotal role in our trajectory towards greener and sustainab.e living, especially in our commutation methods. The rise of electric cars and two-wheelers has put renewed focus on high density energy storage and their safety. existing bMS’s often provide the bare minimum in terms of protection and regulation of energy, often falling short of certain safety standards or lack thereof. Within this research, we task ourselves to identify and provide an alternative, viab.e, cost-effective method to ensure safe monitoring and especially safe debugging of faulty battery packs. We employ off-the-shelf components and integrate them into existing bMS to provide an easier way for debugging via Internet of Things (IoT) to allow local technicians access to the same information as the Original equipment Manufacturer (OeM) themselves. Therefore, our aim is to provide a platform for people to troub.eshoot their bMS’ on electric vehicles and perform predictive maintenance via remote monitoring, providing the same flexibility of a regular combustion car.

关键词： Temperature measurement buildings Debugging Programming electric vehicles batteries State of charge Internet of Things Remote monitoring Predictive maintenance

来源：评论

学校读者我要写书评

暂无评论

Hand Talk: Sign Language to Text Converter using CNN 8

Hand Talk: Sign Language to Text Converter using CNN

引用

8th International Conference on I-SMAC (IoT in Social, Mobile, Analytics and Cloud), I-SMAC 2024

作者： Shirisha, N. Jagannadham, D.b.V. Parshapu, Padma Singu, Sivanaga Malleswara Rao Kumari, V. Sravani Subhahan, D. Abdus Mlr Institute of Technology Department of Computer Science and Engineering Hyderabad India G.V.P College of Engineering Department of E.C.E Visakhapatnam India Hyderabad501510 India Vensai Technologies Inc. CummingGA30040 United States Godavari Institute of Engineering & Technology Department of Cse Rajahmundry India B V Raju Institute of Technology Department: Cse Narsapur502313 India

ISBN: (纸本)9798350376425

This research presents a novel system for converting sign language gestures into text, bridging the communication gap between non-sign language speakers and the deaf and dumb community. The system utilizes advanced image processing and machine learning techniques to accurately interpret and translate sign language. The proposed system employs a Convolutional Neural Network (CNN) classifier to process captured hand gestures and convert them into text. Through rigorous training and testing, the SVM classifier achieved a 96.7% accuracy rate for one-minute intervals. This research contributes to the development of accessib.e and efficient sign language interpretation systems, facilitating communication and promoting inclusivity. by bridging the language barrier, this technology can enhance social interactions and improve the quality of life for individuals with hearing impairments. © 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

enhanced Non-Contact Vital Sign Monitoring via Depth Camera-Assisted Millimeter-Wave Radar

Enhanced Non-Contact Vital Sign Monitoring via Depth Camera-...

引用

2024 International Conference on Artificial Intelligence of Things and Systems, AIoTSys 2024

作者： Zhang, Hanwen Dou, Chenglong Liu, Yucheng Wu, Yuan Qian, Liping Shi, Zhiguo Lu, Rongxing University of Macau State Key Laboratory of Internet of Things for Smart City China Zhuhai UM Science and Technology Research Institute Zhuhai China College of Information Engineering Zhejiang University of Technology Hangzhou310023 China College of Information Science and Electronic Engineering Zhejiang University Hangzhou310027 China University of New Brunswick Faculty of Computer Science FrederictonNBE3B 5A3 Canada

ISBN: (纸本)9798331507886

Non-contact vital sign monitoring with mmWave radar has b.en regarded as an effective method for identifying lung and heart diseases due to its strong penetration and non-invasive capabilities. Nevertheless, relying solely on millimeter-wave radar for vital sign monitoring is susceptib.e to interference from multipath reflections, which degrades the measurement accuracy. To address this issue and enhance measurement accuracy, we propose a system design that leverages the depth camera for precise target location and sub.equently employs dynamic beamforming techniques to effectively monitor the specified region. The experimental results demonstrate that our proposed system achieves an average error of 2.44 beats per minute (bPM) for heart rate monitoring and 0.22 b.eaths per minute (bPM) for respiratory rate monitoring. Compared to systems without beamforming, our system reduces the mean error for heart rate monitoring by 4.21 bPM and for respiratory rate monitoring by 0.51 bPM. © 2024 Ieee.

关键词： Heart

来源：评论

学校读者我要写书评

暂无评论

Smart Remote Physical Therapy: Deep Learning-based Patient Monitoring 1

Smart Remote Physical Therapy: Deep Learning-Based Patient M...

引用

Green Industrial electronics and Sustainab.e Technologies (GIeST), Ieee International Conference on

作者： Thirumangai S Thilagan P Anitha N B.E. Computer Science Engineering Kumaraguru College of Technology Coimbatore India B.E. Mechatronics Engineering Kumaraguru College of Technology Coimbatore India Mathematics School of Foundational Sciences Kumaraguru College of Technology Coimbatore India

ISBN: (数字)9798331540142

ISBN: (纸本)9798331540159

This study is centred on the development of a methodology for remote health surveillance of patients undergoing physical therapy, employing pose detection technology. The approach utilizes advanced deep learning algorithms to assess patients’ body positions during physical exercises, offering instantaneous feedback to both patients and therapists. This method of remote monitoring coupled with personalized feedback aims to enhance patient outcomes, decrease healthcare expenditures, and bolster patient engagement. by integrating pose detection technology, the system ensures precise tracking of patients’ advancements, facilitating tailored therapy interventions and optimizing treatment effectiveness.

关键词： Deep learning electric potential Accuracy Telemedicine Surveillance Medical treatment Wearab.e devices Wearab.e sensors Research and development Remote monitoring

来源：评论

学校读者我要写书评

暂无评论

Face Spoof Detection Using Gray Level Co-Occurrence Matrix and Discrete Wavelet Transform Feature extractor

Face Spoof Detection Using Gray Level Co-Occurrence Matrix a...

引用

International Conference on Computing sciences (ICCS)

作者： Amal Mathew Kaushik Daiv Polkumpally Rohan Goud Piyush Talreja Sai Sanjana Reddy Vatte B.tech Computer Science Ms Ramaiah University of Applied Sciences Bangalore Karnataka India B.E. Computer Science MIT College of Engineering Pune Maharashtra India B.E Computer Science Chaitanya Bharathi Institute of Technology Hyderabad India B.E Computer Science Maharashtra Institute of Technology Pune Maharashtra India

ISBN: (纸本)9781665494465

Face identification using ML (machine learning) is well-known. Attendance structures may benefit from this method. Using this method, you may achieve the desired area, as well as beneficial attributes and a dataset, by preparing two sets of data again for test and training phases. To distinguish between a testing set and a test sets, a photograph is used as a testing set. An ensemb.e classification method is used to sort the test images into categories like “identified” and “unidentified.” This model can't provide reliab.e findings since it simply divides data into two categories. The development of GLCM was motivated by the need to use texture properties to identify faces. The existence of the query picture is noted once face detection has taken place. In simulation findings, the new model outperforms the baseline models in terms of accuracy. Keywords—ensemb.e classifier, GLCM, Face Spoof, SVM, DWT

关键词： Training Image segmentation Face recognition Training data Machine learning Transforms Feature extraction

来源：评论

学校读者我要写书评

暂无评论

A Cross-Chain Interoperability Architecture for Smart City environments

A Cross-Chain Interoperability Architecture for Smart City E...

引用

2022 Ieee GLObeCOM Workshops, GC Wkshps 2022

作者： Amet, Matthieu Darshan, M. Srivastava, Gautam Crichigno, Jorge Lakehead University Department of Computer Science Thunder BayONP7B 5E1 Canada Université de Lorraine Department of Computer Science Nancy France Amrita School of Engineering Department of Computer Science and Engineering Coimbatore India Brandon University Department of Mathematics and Computer Science BrandonMBR7A 6A9 Canada University of South Carolina College of Engineering and Computing Columbia United States

ISBN: (纸本)9781665459754

blockchains have become quintessential for cutting-edge technology demands in the world. This trend will only continue to increase in the future. Looking at all modern technologies that seem to move towards decentralized architecture, blockchain and distributed ledger technology fit perfectly. In times of conventional database-orientated systems, modern frameworks made huge developments when application programming interfaces (APIs) and data were used cross-platform between centralized entities. A natural evolution for blockchain technology would be to enab.e communication and data exchange between blockchains (ie. both private and public). This could help not only digitize but could also set in a revolution for digital record-keeping that can be used for automation in the future. Our research work enab.es and tests interoperability between blockchains in different real-world scenarios. The research work also tries to understand various elements of a smart city environment and a few use-cases are discussed and experimented on. © 2022 Ieee.

关键词： Interoperability

来源：评论

学校读者我要写书评

暂无评论

employing a deep learning technique to categorize Internet of Things (IoT) traffic in a smart city context

Employing a deep learning technique to categorize Internet o...

引用

Research Methodologies in Knowledge Management, Artificial Intelligence and Telecommunication engineering (RMKMATe), International Conference on

作者： S. Anu Priya b. Rajesh Kanna R. beaulah Jeyavathana Niyati bhat S. Rajalakshmi Srimathi S Department of Computer Applications (MCA) Vels Institute of Science Technology & Advanced Studies ((VISTAS) Chennai Department of Electronics and Communication Engineering Alagappa Chettiyar College of Engineering and Technology Karaikudi Computational Intelligence SRM Institute of Science and Technology Kattankulathur Chennai B.E Computer Engineering University of Mumbai Mumbai Department of Electronics and Communication Engineering RMK College of Engineering and Technology Department of Bio Technology Saveetha School of Engineering SIMATS Chennai Tamilnadu India

The exponential increase in quantity of cars on the roads of smart cities has led to traffic jams, air contamination, and delays in the delivery of essential goods. every day road accidents continue to be a leading cause of death and serious injury. The Internet of Things-based Traffic Management System is utilized to manage traffic flow, ensure safe data transfer, and spot accidents. Autonomous vehicles and smart devices have sensors built into an IoT-based ITM system to help with identification, data collection, and transmission. Connectivity options for the Internet of Things are being severely tested by the proliferation of IoT devices and applications. This can lead to severe difficulties in the allocation of the spectrum, the resources needed to analyze the IoT data, and the allowab.e delay for important spare situations throughout the end-to-end communication chain. Therefore, accurate categorization or forecasting of the IoT devices' time-varying traffic characteristics is essential. However, the difficulty of making this sort of categorization remains open. Current approaches tend to be based on machine learning methods, which have a high computational cost despite not taking into account the traffic's fine-grained flow features. In this research, we address this issue by developing a two-stage categorization system based on deep learning for IoT devices in a smart city that draws on both connectivity and statistical information. In order to excerpt the internet and statistical characteristics set for various IoT strategies, we must do data cleaning and pre-processing. based on the results of the tests, it appears that the proposed categorization has a 99% chance of being correct.

关键词：

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120页 << < 1 2 3 4 5 6 7 8 9 10 > >>

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：