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

4,310 篇 会议
3,030 篇 期刊文献
210 册 图书

馆藏范围

7,550 篇 电子文献
0 种 纸本馆藏

日期分布

学科分类号

4,230 篇 工学
- 2,831 篇 计算机科学与技术...
- 2,265 篇 软件工程
- 927 篇 信息与通信工程
- 526 篇 控制科学与工程
- 485 篇 生物工程
- 464 篇 生物医学工程（可授...
- 415 篇 电气工程
- 370 篇 电子科学与技术（可...
- 350 篇 光学工程
- 276 篇 机械工程
- 222 篇 仪器科学与技术
- 197 篇 化学工程与技术
- 168 篇 核科学与技术
- 153 篇 动力工程及工程热...
- 126 篇 材料科学与工程（可...
2,850 篇 理学
- 1,259 篇 数学
- 1,169 篇 物理学
- 589 篇 生物学
- 374 篇 统计学（可授理学、...
- 250 篇 系统科学
- 215 篇 化学
1,093 篇 管理学
- 614 篇 管理科学与工程(可...
- 517 篇 图书情报与档案管...
- 321 篇 工商管理
452 篇 医学
- 375 篇 临床医学
- 353 篇 基础医学(可授医学...
- 229 篇 药学(可授医学、理...
- 158 篇 公共卫生与预防医...
185 篇 法学
- 155 篇 社会学
133 篇 经济学
- 130 篇 应用经济学
86 篇 教育学
76 篇 农学
16 篇 文学
10 篇 艺术学
9 篇 军事学
3 篇 哲学

主题

252 篇 informatics
167 篇 artificial intel...
123 篇 machine learning
122 篇 computational mo...
118 篇 computer science
100 篇 feature extracti...
96 篇 computer archite...
96 篇 quality of servi...
90 篇 data mining
90 篇 hadron colliders
84 篇 deep learning
84 篇 wireless sensor ...
80 篇 semantics
75 篇 training
74 篇 monitoring
73 篇 protocols
72 篇 information syst...
71 篇 optimization
71 篇 computer network...
70 篇 image segmentati...

机构

412 篇 department for p...
404 篇 faculty of scien...
398 篇 department of ph...
396 篇 kirchhoff-instit...
386 篇 department of ph...
385 篇 department of ph...
366 篇 institute of phy...
365 篇 institute of phy...
364 篇 fakultät für phy...
312 篇 instituto de fís...
306 篇 department of ph...
280 篇 department of ph...
278 篇 graduate school ...
271 篇 department of ph...
269 篇 universidade fed...
264 篇 ictp trieste
257 篇 yerevan physics ...
255 篇 dipartimento di ...
254 篇 department of ph...
252 篇 department of ph...

作者

336 篇 c. alexa
334 篇 j. m. izen
332 篇 g. bella
331 篇 d. calvet
331 篇 c. amelung
329 篇 j. strandberg
326 篇 g. spigo
325 篇 f. siegert
318 篇 r. ströhmer
318 篇 m. rijssenbeek
318 篇 s. jin
318 篇 g. gaudio
317 篇 s. mohapatra
309 篇 s. guindon
302 篇 a. kaczmarska
299 篇 y. tayalati
297 篇 j. schaarschmidt
287 篇 a. d. pilkington
283 篇 m. klein
280 篇 l. chevalier

语言

7,170 篇 英文
306 篇 其他
68 篇 中文
12 篇 日文
3 篇 德文

检索条件"机构=Institute of Informatics and Computer Technology"

共 7550 条记录，以下是91-100 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：

Enabling LoRa energy awareness: A Multihop One-Hop Routing Protocol for Prolonging Network Lifetime 19

Enabling LoRa energy awareness: A Multihop One-Hop Routing P...

引用

19th Annual International Conference on Distributed Computing in Smart Systems and the Internet of Things, DCOSS-IoT 2023

作者： Katsidimas, Ioannis Manolopoulos, Alexandros-Ioannis Nikoletseas, Sotiris University of Patras Department of Computer Engineering and Informatics Patras Greece University of Athens Department of Physics National and Kapodistrian Athens Greece University of Patras and Computer Technology Institute and Press Diophantus Department of Computer Engineering and Informatics Patras Greece

ISBN: (纸本)9798350346497

IoT applications often rely on battery-powered nodes that may be challenging to recharge, making energy efficiency a crucial concern. In this context, routing protocols play a vital role as they dictate the paths data packets take between nodes, directly influencing the energy consumption of IoT networks. Energy-aware routing protocols have been proposed to address this issue, with the aim of optimizing energy consumption by selecting paths that minimize the energy required for data transmission and reception. These protocols employ various strategies, such as distance-based, traffic-based, and hybrid schemes, to achieve energy efficiency in IoT networks. LoRaWAnprotocol has been adopted for various IoT applications with requirements in low-power and extended coverage. Over the recent years attempts have been made to replace the typical star topology employed by LoRa with multihop solutions, in an effort to further increase its capabilities. In this paper, we present a multihop algorithm that is based on an energy-balanced routing scheme adopted by LoRa nodes to increase energy efficiency and network lifetime. Multiple one-hop routes are configured for critical nodes and a different route is selected in each transmission. Additionally, critical nodes adjust their Spreading Factor and Transmission Power according to the distance of intermediate nodes. Simulation testing results verify the improved performance of our algorithm over the direct link approach. © 2023 IEEE.

关键词： Energy efficiency

来源：评论

学校读者我要写书评

暂无评论

PIT Performance Measurement using NFD Pipeline Parameters in Named Data Networking (NDN) 10

PIT Performance Measurement using NFD Pipeline Parameters in...

引用

10th International Conference on Wireless and Telematics, ICWT 2024

作者： Sucipto, Adi Ahdan, Syaiful Iskandar Syambas, Nana Rachmana Bandung Institute of Technology School of Electrical Engineering and Informatics Bandung40132 Indonesia Universitas Teknokrat Indonesia Faculty of Engineering and Computer Science 35132 Indonesia

ISBN: (纸本)9798350377057

Although NDN is an entirely new architecture, its design principles are based on the success of the current Internet, they represent our knowledge of the advantages and disadvantages of the current Internet architecture, and they can be implemented gradually using the operations of the current Internet. The Pending Interest Table (PIT), the Forwarding Information Base (FIB), and the Content Store (CS) are the three data structures found inside the NDN router. Interest sent upstream to the content source is tracked by the Pending Interest Table (PIT), for data to be transmitted to requesters downstream. PIT is also used for measurement, loop detection, and the containment of recently satisfied interest. In this study, we did the simulation to measure and analyze the performance of PIT in NDN using NFD Pipeline Measurements. The NDNSim simulator was used in the research to observe PIT performance. The findings of the simulation and analysis indicated that in an NDN network, Satisfied Interest was influenced by the granularity of a prefix. At the number of interests 1000, the results showed a decrease in packets, including a decrease of around 21% in the Ininterest packet, and around 30% inSatisfiedInterest and InData. The effect of Prefix length also decreased in Ininterest ranging from 0.014-0.015%, while in inSatisfiedInterest and InData it ranged from 4.2-8.5%. The PIT's performance was influenced by the length of the prefix and the number of interest messages the customer sent. © 2024 IEEE.

关键词： Natural gas pipelines

来源：评论

学校读者我要写书评

暂无评论

EfficientNetB0-based Automated Diabetic Retinopathy Classification in Fundus Images 3

EfficientNetB0-based Automated Diabetic Retinopathy Classifi...

引用

3rd International Conference on Automation, Computing and Renewable Systems, ICACRS 2024

作者： Majaw, Ezekiel Alaric Sundar, G. Naveen Narmadha, D. Thangavel, Senthil Kumar Venkatesan Ajibesin, Adeyemi Abel Department of Computer Science and Engineering Karunya Institute of Technology and Sciences Coimbatore India Department of Computer Science and Engineering Amrita School of Computing Coimbatore India Department of Information Technology Faculty of Informatics and Design Cape Peninsula University of Technology South Africa

ISBN: (纸本)9798331532420

The most common cause of blindness among diabetics is diabetic retinopathy. This disease must be detected in its early stages as delaying treatment can result in permanent blindness. In today’s modern world with the development of technologies, automated techniques have improved the accuracy and efficiency of detecting and classifying this disease. This study suggests a deep learning model utilizing EfficientNetB0 that focuses on designing a neural network structure that requires fewer parameters and computations compared to traditional architectures. Further to help in increasing the accuracy, the image is being processed with methods like CLAHE which is an image processing algorithm that helps in enhancing the contrast while keeping the noise of the images as low as possible. Also, augmentation is being done on the images and SMOTE is applied to handle class imbalance. We collected the APTOS Blindness Detection dataset consisting of retinal fundus images. The accuracy that is being obtained from the proposed methodology is 98.78% indicating the model's effectiveness in detection and classifying between the various stages of diabetic retinopathy. © 2024 IEEE.

关键词： Contrastive Learning

来源：评论

学校读者我要写书评

暂无评论

A Machine Learning-Based Privacy-Preserving Approach to Incorporate Distributed Generators in AC Optimal Power Flow

A Machine Learning-Based Privacy-Preserving Approach to Inco...

引用

2024 IEEE PES Innovative Smart Grid Technologies Europe Conference, ISGT EUROPE 2024

作者： Dindar, Burak Saner, Can Berk Polat, Dogukan Yigit Çakmak, Huseyin Kemâl Hagenmeyer, Veit Institute for Automation and Applied Informatics Karlsruhe Institute of Technology Germany National University of Singapore Department of Electrical and Computer Engineering Singapore National University of Singapore School of Computing Singapore

ISBN: (纸本)9789531842976

In order to achieve the goal of a carbon-neutral power system, significant changes to the power grid are underway, necessitating enhanced interoperability between Transmission System Operators (TSOs) and Distribution System Operators (DSOs) for effective grid operation, particularly in light of the growing number of distributed generators (DGs). Data privacy concerns, however, complicate decision-making processes, particularly when integrating DGs into system-wide dispatch decisions. In this paper, we propose a machine-learning (ML)-based method to incorporate DGs located within the distribution system (DS) into dispatch decisions, adhering to data privacy by mitigating the exchange of sensitive data, such as system topology and demand profiles, between TSOs and DSOs. The methodology involves training three ML models to represent the behavior of the DS, thereby replacing the standard power flow model that contains sensitive information. Notably, we utilize a novel tailored neural network (NN) architecture to enhance computational efficiency in mapping the feasible region of the DS. Additionally, we employ open-source data to construct the Baden-Wü rttemberg (Germany) electricity grid, allowing to test our method not only on standard systems but also on a model that more accurately represents real-world power systems. The numerical case studies verify that the proposed method achieves results comparable to standard AC optimal power flow (AC-OPF) in both cost-optimality and computational time. © 2024 IEEE.

关键词： Differential privacy

来源：评论

学校读者我要写书评

暂无评论

Applying Dragonfly Algorithm for Feature Selection Optimizing in Machine Learning Classification 16

Applying Dragonfly Algorithm for Feature Selection Optimizin...

引用

16th International Conference on Developments in eSystems Engineering, DeSE 2023

作者： Raouf, Zaid Tariq Abd, Dhafar Hamed Informatics Institute for Postgraduate Student Baghdad Iraq University of Anbar College of Computer Science and Information Technology Ramadi Iraq

ISBN: (纸本)9798350381344

Feature selection plays a crucial role in the domain of machine learning, serving as an essential mission. Eliminating redundant and irrelevant attributes can enhance the learning process by increasing the learning rate, improving accuracy, and enhancing classifier performance. The primary objectives of feature selection encompass the creation of models that are more understandable and user-friendly, the enhancement of data mining efficiency, and the facilitation of data cleaning and organization for subsequent analysis. Metaheuristic algorithms have garnered considerable attention due to their prowess in solving many optimization problems such as feature section, in this paper using Dragonfly algorithm. The effectiveness of the proposed methodologies is evaluated on three benchmark datasets obtained from the Kaggle repository: the heart disease dataset, the Vehicle-Coupon-Recommendation dataset, and the Predict Diabetes dataset. Three machine learning classifiers - namely, Light Gradient Boosting Machine (LightGBM), AdaBoost, and Bagging - are utilized in this assessment. This approach yields an impressive accuracy rate of 85.71%. In contrast, when all features are included in the training process, the accuracy drops to a lower value of 83.51%. © 2023 IEEE.

关键词： Feature Selection

来源：评论

学校读者我要写书评

暂无评论

Gene Disease Classification from Biomedical Text via Ensemble Machine Learning 16

Gene Disease Classification from Biomedical Text via Ensembl...

引用

16th International Conference on Developments in eSystems Engineering, DeSE 2023

作者： Ghazi, Rabea F. Abd, Dhafar Hamed Informatics Institute for Postgraduate Student Baghdad Iraq University of Anbar College of Computer Science and Information Technology Ramadi Iraq

ISBN: (纸本)9798350381344

Detecting connections between genes and diseases is a vital endeavor in bioinformatics and genomics, carrying significant implications for the entire comprehension of the molecular underpinnings of various diseases. The rapid increase in the number of documents in the field of biomedicine has resulted in a significant burden and time requirement for manually curating relationships within this literature. In order to tackle this particular difficulty, the present study introduced a resilient ensemble machine-learning methodology that aimed at automating the classification of gene-disease relationships through the analysis of biomedical text. The proposed model was meant to leverage ensemble learning capabilities by integrating different base classifiers which are Decision Trees, Random Forest, AdaBoost, Bagging, CatBoost, Extra Trees and XGBoost with two feature extraction TF and TF-IDF. This ensemble architecture aimed to enhance the accuracy and dependability of gene-disease association predictions by utilizing a wide range of variables obtained from biomedical literature, including abstracts and various ensemble configurations and evaluating performance using standard metrics which are precision, recall, and F1-score, AUC, and accuracy. The study findings provided evidence supporting the efficacy of the ensemble methodology in enhancing both accuracy and resilience when compared to the performance of individual classifiers. The highest accuracy was achieved with XGBoost and TF 0.979%. © 2023 IEEE.

关键词： Genes

来源：评论

学校读者我要写书评

暂无评论

Education Tools for Teaching Classical Ciphers: Chinese and Japanese ciphers

Education Tools for Teaching Classical Ciphers: Chinese and ...

引用

2023 International Conference on Information and Digital Technologies, IDT 2023

作者： Klimo, Marek Antal, Eugen Kvassay, Miroslav Institute of Computer Science and Mathematics Slovak University of Technology Bratislava Slovakia University of Žilina Department of Informatics Žilina Slovakia

ISBN: (纸本)9798350305869

In this work, we focus on supporting online education of courses about Classical Ciphers and promoting historical cryptography to the general public. For this purpose, we designed and developed new modules in 2020 and integrated them into our ongoing HCPortal project. We developed an education module (Angular application) with which we can present a wide range of supporting applications regarding cryptography and cryptanalysis of historical ciphers and visualize their necessary parts. In addition, we also developed a special Virtual museum (using A-Frame technology) to promote public interest in ciphers using modern technologies. These modules have undergone significant change in recent years. They have been expanded with new content, and the structure of the Educational module has also changed. We have included various Chinese and Japanese historical ciphers into these modules due to the lack of availability of resources that specifically address this area of research. We are presenting the new content added to the HCPortal, focusing on these Chinese and Japanese ciphers. © 2023 IEEE.

关键词： Cryptography

来源：评论

学校读者我要写书评

暂无评论

Combining TL and KD for Object Detection Model Compression 13

Combining TL and KD for Object Detection Model Compression

引用

Joint 13th International Conference on Soft Computing and Intelligent Systems and 25th International Symposium on Advanced Intelligent Systems, SCIS and ISIS 2024

作者： Peng, Yuhan Lyu, Yan Zhao, Qiangfu The University of Aizu Computer Science and Engineering Aizuwakamatsu965-8580 Japan Muroran Institute of Technology Sciences and Informatics Muroran050a-8585 Japan

ISBN: (纸本)9798350373332

In modern society, object detection tasks have become extremely important due to their numerous applications in fields such as autonomous driving, surveillance, and healthcare. Real-time detection is particularly crucial for many applications. However, with the advancements in deep learning-based object detection methods, high performance often comes with high computational resource requirements, posing challenges for real-time monitoring, especially on resource-constrained devices. To address this issue, we study model compression using both transfer learning (TL) and knowledge distillation (KD). Specifically, we use the YOLOv5n model as a test case to show the basic idea for improving the performance of a small student model using a larger dataset for TL and a larger model for KD. As for KD, we further investigate feature-based and output-based KD. Experimental results show that the small student model can be improved significantly using TL and KD, with the mean Average Precision (mAP0.5) being increased by 13.28% compared to the baseline model. These results demonstrate the effectiveness of TL and KD in achieving high detection performance while reducing computational demands, making them suitable for various real-world applications. © 2024 IEEE.

关键词： Adversarial machine learning

来源：评论

学校读者我要写书评

暂无评论

Feature Selection for Binary Dataset using Dragonfly Algorithm 16

Feature Selection for Binary Dataset using Dragonfly Algorit...

引用

16th International Conference on Developments in eSystems Engineering, DeSE 2023

作者： Raouf, Zaid Tariq Abd, Dhafar Hamed Informatics Institute for Postgraduate Student Baghdad Iraq University of Anbar College of Computer Science and Information Technology Ramadi Iraq

ISBN: (纸本)9798350381344

In contemporary times, the proliferation of data dimensionality has introduced many challenges within the realm of machine learning. Consequently, identifying and selecting pertinent features have assumed paramount importance. Consequently, a diverse array of techniques for feature selection has been proffered. Among them, Metaheuristic techniques are particularly significant within this milieu, with a focus on the dragonfly algorithm garnering notable attention. Metaheuristic algorithms are rooted in the emulation of swarm intelligence, drawing inspiration from the collective behaviors exhibited by insects. This scholarly inquiry aims to enhance the efficacy of classification outcomes by leveraging the dragonfly algorithm to select the most salient features. In this paper, the proposed approach is rigorously evaluated across three distinct datasets, namely, 'Ansur,' 'Predict 5-Year Career Longevity for NBA Rookies,' and 'Chronic Kidney Disease,' all of which were procured from the Kaggle repository. The study used four machine learning classifiers, namely, XGBoosting, K-Nearest Neighbors (KNN), Decision Tree, and Gaussian Naive Bayes (Gaussian-NB), for classification and evaluation. The empirical findings unveiled a notable enhancement in classification performance. Notably, the accuracy metrics exhibit substantial improvements across all classifiers. For instance, within chronic kidney disease classification, both XGBoost and Decision Tree classifiers yielded a remarkable accuracy rate of 100%, thereby underscoring the efficacy of the proposed dragonfly algorithm-based feature selection technique in augmenting the predictive capabilities of machine learning models. © 2023 IEEE.

关键词： Feature Selection

来源：评论

学校读者我要写书评

暂无评论

Integrated Smart Parking System Using Internet of Things (IoT) and Digital Image Processing with Faster Region Based Convolutional Neural Network (Faster R-CNN) and Optical Character Recognition (OCR) 8

Integrated Smart Parking System Using Internet of Things (Io...

引用

8th International Conference on Electrical, Telecommunication and computer Engineering, ELTICOM 2024

作者： Lubis, Fahrurrozi Nababan, Erna Budhiarti Nainggolan, Pauzi Ibrahim Syah Putra, Mohammad Fadly Rahmat, Romi Fadillah Sulaiman, Riza Talupan Pangaribuan, Albert Lukas Universitas Sumatera Utara Faculty of Computer Science and Information Technology Medan Indonesia Institute of Visual Informatics Universiti Kebangsaan Malaysia Bangi43600 Malaysia

ISBN: (纸本)9798331531249

Parking is an integral part of driving, especially in urban areas. However, inefficient parking systems often cause drivers to spend a significant amount of time just to find a parking spot, even up to 10 hours per month in major cities like Jakarta. Besides wasting time, prolonged parking searches also increase fuel consumption and CO2 emissions. This study aims to develop smart parking application integrated with Internet of Things and computer Vision. The system uses ultrasonic sensors connected to an ESP32 microcontroller to detect real-time parking slot availability, sending status updates to Firebase. Additionally, Faster Region Based Convolutional Neural Network (Faster R-CNN) and Easy OCR technologies are used to detect and identify vehicle license plates and parking slot markers, ensuring consistency between reservations and actual parking slot usage. The research findings indicate that the sensors system has the fastest measurement time of 106.3 milliseconds and data transmission time of 73.6 milliseconds. The Faster R-CNN model shows and accuracy of 86% for detecting license plates and parking slot markers, while EasyOCR achieves 100% accuracy in recognizing the characters of license plates and parking slot markers. The average total time for inference and character extraction is 2.7 seconds. This integrated approach provides significant solution for both users and parking vendor. © 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

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 << < 6 7 8 9 10 11 12 13 14 15 > >>

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：