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

30,629 篇 会议
4,958 篇 期刊文献
249 册 图书

馆藏范围

35,836 篇 电子文献
0 种 纸本馆藏

日期分布

学科分类号

22,252 篇 工学
- 15,838 篇 计算机科学与技术...
- 13,328 篇 软件工程
- 5,847 篇 信息与通信工程
- 3,722 篇 控制科学与工程
- 2,762 篇 电子科学与技术（可...
- 2,760 篇 电气工程
- 2,344 篇 生物工程
- 1,887 篇 生物医学工程（可授...
- 1,540 篇 光学工程
- 1,447 篇 机械工程
- 1,271 篇 动力工程及工程热...
- 1,250 篇 仪器科学与技术
- 1,049 篇 化学工程与技术
- 859 篇 安全科学与工程
- 748 篇 交通运输工程
11,425 篇 理学
- 6,205 篇 数学
- 3,137 篇 物理学
- 2,565 篇 生物学
- 2,047 篇 统计学（可授理学、...
- 1,408 篇 系统科学
- 1,110 篇 化学
5,668 篇 管理学
- 3,349 篇 管理科学与工程(可...
- 2,596 篇 图书情报与档案管...
- 1,822 篇 工商管理
1,587 篇 医学
- 1,374 篇 临床医学
- 1,281 篇 基础医学(可授医学...
- 850 篇 药学(可授医学、理...
- 656 篇 公共卫生与预防医...
1,025 篇 法学
- 826 篇 社会学
646 篇 经济学
- 646 篇 应用经济学
497 篇 农学
433 篇 教育学
155 篇 文学
81 篇 军事学
39 篇 艺术学
1 篇 哲学

主题

1,041 篇 accuracy
844 篇 feature extracti...
814 篇 computational mo...
689 篇 deep learning
681 篇 computer science
672 篇 training
511 篇 support vector m...
504 篇 real-time system...
499 篇 machine learning
443 篇 predictive model...
404 篇 internet of thin...
348 篇 computer archite...
344 篇 data models
331 篇 convolutional ne...
321 篇 reliability
313 篇 optimization
290 篇 data mining
278 篇 routing
260 篇 wireless sensor ...
247 篇 conferences

机构

82 篇 north-west unive...
82 篇 institut univers...
80 篇 national centre ...
79 篇 infn sezione di ...
76 篇 infn sezione di ...
76 篇 institute of inf...
75 篇 tno technical sc...
66 篇 università di ca...
65 篇 université de st...
65 篇 dept. of informa...
60 篇 nikhef national ...
58 篇 dept. of informa...
56 篇 dept. of compute...
56 篇 dept. of compute...
54 篇 school of automa...
52 篇 leiden universit...
49 篇 dept. of compute...
49 篇 dept. of compute...
45 篇 dept. of electri...
44 篇 university würzb...

作者

85 篇 ferrara g.
85 篇 ardid m.
84 篇 calvo d.
84 篇 gal t.
84 篇 bozza c.
81 篇 chen a.
80 篇 kalekin o.
79 篇 díaz a.f.
79 篇 boumaaza j.
78 篇 coleiro a.
77 篇 gozzini s.r.
68 篇 huang f.
68 篇 dallier r.
62 篇 anguita m.
52 篇 kulikovskiy v.
44 篇 del burgo r.
41 篇 benoit d.m.
41 篇 eddymaoui a.
40 篇 gagliardini s.
40 篇 labalme m.

语言

34,558 篇 英文
819 篇 其他
349 篇 中文
57 篇 日文
51 篇 朝鲜文
2 篇 德文
1 篇 法文
1 篇 葡萄牙文
1 篇 斯洛文尼亚文

检索条件"机构=Dept. of Control Engineering and Computer Science"

共 35836 条记录，以下是4901-4910 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：

Detection of Specific Language Impairment Using XGBoost Model

Detection of Specific Language Impairment Using XGBoost Mode...

引用

International Conference on Computing and Networking Technology (ICCNT)

作者： Rajnish Rai Veena Thenkanidiyoor Dept. of Computer Science and Engineering National Institute of Technology Goa Goa India

ISBN: (数字)9798350370249

ISBN: (纸本)9798350370270

Specific Language Impairment (SLI) in children, a neurodevelopmental disorder presenting significant hurdles in language acquisition. Motivated by the prevalence and complexity of SLI diagnosis, this article introduces an methodology using Mel-Frequency Cepstral Coefficients (MFCC) and chroma features combined with the XGBoost algorithm for classification. By analyzing a diverse dataset encompassing both SLI-diagnosed and non SLI children, the proposed model achieves efficiency of $\mathbf{9 9. 3 \%}$ accuracy on unseen data. Notably, the model’s strategic feature selection and utilization of XGBoost demonstrate superior performance compared to existing methods, highlighting its importance in SLI diagnosis and intervention planning. This work significantly advances machine learning-based diagnostic tools and holds promise for improving the quality of life for individuals impacted by SLI.

关键词： Training Accuracy Machine learning algorithms Computational modeling Medical treatment User interfaces Classification algorithms Planning Mel frequency cepstral coefficient Monitoring

来源：评论

学校读者我要写书评

暂无评论

Time Series Forecasting in Financial Market: Long Short-Term Memory (LSTM) Approach for Stock Price Prediction

Time Series Forecasting in Financial Market: Long Short-Term...

引用

IEEE Region 10 Symposium

作者： Ajaykumar Patel Vijay Ukani Priyank Thakkar Computer Science & Engineering Dept. Institute of Technology Nirma University Ahmedabad India

ISBN: (数字)9798350364866

ISBN: (纸本)9798350364873

Stock market nature is nonlinear, and research on it has become increasingly important in recent years. The influence of numerous factors on stock prices renders stock forecasting an intricate and demanding task. Possible stock market price forecast increases people's gains while minimizing their risks. Ma-chine learning and deep learning techniques play an important role in forecasting stock prices in today's scenario, considering technical indicators. The choice of deep learning technique and tweaking its hyper-parameters are crucial components of stock price prediction. Several model architectures are suggested here, taking into account LSTM deep learning techniques and hyper-parameters like the batch size, number of hidden layers and number of epochs. Hyper-parameters such as the number of years data, the number of preceding days considered, and database spitting are examined and discussed here, in addition to hyper-parameters relating to LSTM networks. The model with 11 years of historical data, 60 or 100 previous days consideration, and 70:10:20 database split outperforms as compared to other model architectures suggested in the paper.

关键词： Deep learning Databases Time series analysis Data models Stock markets Forecasting Long short term memory Tuning IEEE Regions

来源：评论

学校读者我要写书评

暂无评论

Transfer Learning Based Hybrid Quantum Neural Network Model for Surface Anomaly Detection

Transfer Learning Based Hybrid Quantum Neural Network Model ...

引用

IEEE computer Society Annual Symposium on VLSI

作者： Sounak Bhowmik Himanshu Thapliyal Dept. of Electrical Engineering and Computer Science University of Tennessee Knoxville Tennessee USA

ISBN: (数字)9798350354119

ISBN: (纸本)9798350354126

The rapid increase in the volume of data increased the size and complexity of the deep learning models. These models are now more resource-intensive and time-consuming for training than ever. This paper presents a quantum transfer learning (QTL) based approach to significantly reduce the number of parameters of the classical models without compromising their performance, sometimes even improving it. Reducing the number of parameters reduces overfitting problems and training time and increases the models' flexibility and speed of response. For illustration, we have selected a surface anomaly detection problem to show that we can replace the resource-intensive and less flexible anomaly detection system (ADS) with a quantum transfer learning-based hybrid model to address the frequent emergence of new anomalies better. We showed that we could reduce the total number of trainable parameters up to 90 % of the initial model without any drop in performance.

关键词： Training Computational modeling Transfer learning Very large scale integration Feature extraction Complexity theory Integrated circuit modeling

来源：评论

学校读者我要写书评

暂无评论

Generating High-Quality Distributed Representations of Words Using Wiktionary and Sentence-BERT

Generating High-Quality Distributed Representations of Words...

引用

IIAI International Conference on Advanced Applied Informatics (IIAIAAI)

作者： Ryota Nishiura Seiji Tsuchiya Hirokazu Watabe Dept. of Information and Computer Science Graduate School of Science and Engineering Doshisha University Kyotanabe Kyoto Japan Dept. of Intelligent Information Engineering and Science Faculty of Science and Engineering Doshisha University Kyotanabe Kyoto Japan

ISBN: (数字)9798350377903

ISBN: (纸本)9798350377910

We propose an improved method to generate high-quality distributed representations of words. In our previous paper, we introduced a novel method to obtain distributed representations of words with BERT using Wiktionary as semantic sources of words. The previous method outperformed a Wrd2Vec model in a word similarity task, while there still had to be some room to improve in term of semantic accuracy. In this paper, our new method introduces one of Sentence-BERT models to text-embed the semantic sources instead of the original BERT model. We demonstrate that our proposed method outperforms both our previous method and the Word2Vec model in the tasks.

关键词： Vocabulary Accuracy Semantics Encyclopedias Internet Online services Informatics

来源：评论

学校读者我要写书评

暂无评论

Pushing the Limits of Machine Translation with GPT-4 and Marian NMT in Multilingual Communication

Pushing the Limits of Machine Translation with GPT-4 and Mar...

引用

2024 IEEE International Conference on Intelligent Systems and Advanced Applications, ICISAA 2024

作者： Jain, Sourabh Sadim, Mohd Amhia, Hemant Kumar, N. Krishna Choudhury, Shibanjali Rajlakshmi, P.V. GGITS Dept of Computer Science & Engineering M.P. Jabalpur India IES Institute of Technology and Management IES University Department of Computer Science & Engineering M.P. Bhopal462044 India Jabalpur Engineering College Electrical Engineering department MP Jabalpur India Guru Nanak Institutions Technical Campus Dept.of CSE Ibrahimpatam Telangana Hyderabad India Techno College of Engineering Dept. of CSE Tripura Agartala India Kongu Engineering College Department of English TN Erode India

ISBN: (纸本)9798331539948

Machine translation (MT) plays a crucial role in enabling linguistic diversity in online interactions. In this research, we provide a unique method for expanding the capabilities of MT inside a multilingual communication framework by combining GPT-4 with Marian Neural Machine Translation (NMT). We present a complete technique comprising translation quality evaluation, contextual coherence augmentation, and translation delay optimization. The results show that our method is successful in enhancing translation quality, preserving contextual coherence, and decreasing delay. Three algorithms are used in the suggested technique. 1) Contextual Coherence Enhancement, 2) Translation Latency Optimization, and 3) Translation Quality Assessment using BLEU and METEOR ratings. The first method uses BLEU and METEOR scores to quantitatively measure translation quality, guaranteeing linguistic precision. The second method improves conversational fluency by increasing contextual coherence. The third method minimizes the time it takes to translate a sentence, facilitating simultaneous translation and conversation. We evaluated our approach by comparing it to six established MT techniques. According to the outcomes, our strategy is superior to the status quo in many respects. In particular, our approach enhanced translation quality as measured by BLEU and METEOR ratings. It also had a far greater Contextual Coherence Enhancement Factor (CEF) and Coherence Improvement Percentage, indicating that it successfully preserved the rational progressions of conversations. Furthermore, significant improvements in translation latency were also highlighted by the Latency Optimization Ratio (LOR). © 2024 IEEE.

关键词： computer aided language translation

来源：评论

学校读者我要写书评

暂无评论

Letting 3D Guide the Way: 3D Guided 2D Few-Shot Image Classification

Letting 3D Guide the Way: 3D Guided 2D Few-Shot Image Classi...

引用

IEEE Workshop on Applications of computer Vision (WACV)

作者： Jiajing Chen Minmin Yang Senem Velipasalar Electrical Engineering and Computer Science Dept. Syracuse University Syracuse NY USA

Existing few-shot image classification networks aim to perform prediction on images belonging to classes that were not seen during training, with only a few labeled images, which are randomly picked from the same image pool as the support set. However, this traditional approach has two main issues: (i) in real-world applications, since support images are randomly picked, the angle they were captured from can be very different from that of the query image, causing the images to look very different and making it hard to match them; (ii) since support and query images, for both training and testing, are sampled from the same image pool, models can overfit the dataset, especially if the image pool contains images with similar color, texture or view angle. Thus, good performance on a dataset does not reflect a model’s real ability. To address these issues, we propose a novel few-shot learning approach referred to as the 3D guided 2D (3DG2D) few-shot image classification. In our proposed approach, the queries are 2D images, and the support set is composed of 3D mesh data, providing different views of an object, in contrast to randomly picked images providing a single view. From each 3D mesh, 14 projection images are generated from different angles. Thus, these projections have significant variance among themselves. To address this challenge, we also propose the Angle Inference Module (AIM), which is used to infer the view angle of a query image so that more attention is given to projection images corresponding to the same view angle as the query image to achieve better prediction performance. We perform experiments on ModelNet40, Toys4K and ShapeNet datasets with 4-fold cross validation, and show that our 3DG2D few-shot classification approach consistently outperforms the state-of-the-art baselines.

关键词：

来源：评论

学校读者我要写书评

暂无评论

ZCube: A Zero-Trust, Zero-Knowledge, and Zero-Memory Platform for Privacy and yet Secured Access

ZCube: A Zero-Trust, Zero-Knowledge, and Zero-Memory Platfor...

引用

IEEE International Conference on Trust, Privacy and Security in Intelligent Systems and Applications (TPS-ISA)

作者： Vinh Quach Ram Dantu Sirisha Talapuru Shakila Zaman Apurba Pokharel Dept. of Computer Science and Engineering University of North Texas Denton TX USA

ISBN: (数字)9798350386745

ISBN: (纸本)9798350386752

As concerns over privacy and trust escalate among individuals and corporations, traditional memory-based trust systems are increasingly seen as inadequate and undesirable. The rise of microservice architecture complicates this by making data paths harder to track. Given these concerns, the critical question arises: How can we establish trust or verify an entity’s credibility without collecting private information or relying on comparisons with pre-existing data, while knowing the exact data path of each request? To address this challenge, we introduce a lightweight, scalable, ZCube platform that employs nested Zero Knowledge Proofs (ZKPs), eliminating reliance on memory or evaluations based on past actions. This platform verifies and maintains trust in real-time without centralizing trust in any specific part of the system. It anticipates intentions and rigorously monitors them, ensuring operational integrity while preserving privacy. Distinctive for its ZKP trustless setup incorporating blockchain, each request begins anew and is rigorously monitored bidirectionally during execution. Our tests on the realistic example of a microservice-based distributed system, OpenTelemetry Demo, confirm that our novel approach— combining proof segmentation with plan adherence— exhibits fast response times of less than 200ms on average for most test cases. This ZCube platform surpasses traditional methods in efficiency and security. Our analysis shows comprehensive security and enhanced performance while effectively maintaining bidirectional trustlessness.

关键词： Privacy Microservice architectures Trustless services Real-time systems Security Time factors Proposals Zero knowledge proof Monitoring Stress

来源：评论

学校读者我要写书评

暂无评论

Challenges in Certificate Management Over Open RAN Fronthaul Interface

Challenges in Certificate Management Over Open RAN Fronthaul...

引用

International Conference on Information and Communication Technology Convergence (ICTC)

作者： Jungbum Lee Hyunsoo Kim Chang-Gun Lee Ted “Taekyoung” Kwon Dept. of Computer Science and Engineering Seoul National University Seoul South Korea

ISBN: (数字)9798350364637

ISBN: (纸本)9798350364644

Open RAN is transforming mobile networks into open and flexible environments through the integration of modern software and artificial intelligence. However, the existing standardization documents provide insufficient guidelines on the issuance and revocation of certificates, posing potential risks for the system. As an initial effort to overcome this limitation, we study the challenges related to the certificate management framework over the Open RAN fronthaul interface, with a particular focus on the mutual authentication and the coordination of security policies across different vendors.

关键词： Authentication Open RAN Network architecture Software Information and communication technology Security Artificial intelligence Guidelines Convergence

来源：评论

学校读者我要写书评

暂无评论

Sales Prediction for Imported Fruits using a Linear Regression Model

Sales Prediction for Imported Fruits using a Linear Regressi...

引用

International Conference on Computational Intelligence and Communication Networks (CICN)

作者： Jayasravani Bhumireddy Ankita Bose Dept. of Computer Science and Engineering GITAM Deemed University Bengaluru Karnataka India

ISBN: (数字)9798331505264

ISBN: (纸本)9798331505271

Forecasting fruit sales is vital for the retail sector to establish an efficient supply chain, control inventory levels effectively, and satisfy customer needs. This research employs a machine learning algorithm to predict upcoming fruit sales by analyzing past data. We aim to create a dependable prediction system by examining various data elements like past month's sales, seasonal patterns, promotions, holidays, and weather conditions. Linear regression, decision trees, and neural networks are being evaluated for their ability to forecast sales volumes. The model is created and coached with sales data, then evaluated for accuracy using different performance measures. Our findings in the fruit retail industry demonstrate that employing advanced forecasting methods decreases wastage and improves decision-making (resulting in increased profits). This research demonstrates that implementing data-driven sales forecasting within the fresh produce industry may result in more effective and environmentally friendly business operations.

关键词： Industries Machine learning algorithms Linear regression Decision making Supply chains Neural networks Weather forecasting Predictive models Forecasting Business

来源：评论

学校读者我要写书评

暂无评论

Enhanced Machine Learning Approach for Detecting Spammers in Industrial Mobile Cloud Computing Environment

Enhanced Machine Learning Approach for Detecting Spammers in...

引用

IoT Based control Networks and Intelligent Systems (ICICNIS), International Conference on

作者： K. Sai Bhavana B. Abhinandu P. Sai Sriyesh K. Rama S. Satheesh Kumar Dept. Computer Science & Information Technology Institute of Aeronautical Engineering Hyderabad India

ISBN: (数字)9798331518097

ISBN: (纸本)9798331518103

This research study proposes an innovative machine learning algorithm, Spammer Identification Novel K-Means Extension (SINKEX), to fortify IoT mobile networks against commands and potential disruptions in industrial production. Utilizing an industrial mobile cloud dataset, the algorithm employs basic, content, and network features, including follower count, post frequency, message content, and hyperlink usage, for spam detection. After employing Pearson Correlation and Euclidean Distance to eliminate dissimilar records, Principal Component Analysis (PCA) is applied to remove irrelevant features. The SINKEX algorithm then labels unclassified records, designating an account as a SPAMMER or NON-SPAMMER based on features like follower count and post frequency. Comparisons with a hybrid fuzzy c-means clustering algorithm demonstrate SINKEX's superior performance, achieving higher accuracy, precision, and recall. The results are presented through an intuitive graphical user interface, showcasing the algorithm's effectiveness in securing industrial IoT networks against malicious activities.

关键词： Cloud computing Machine learning algorithms Clustering algorithms Production Machine learning Intelligent systems Hypertext systems Principal component analysis Industrial Internet of Things Graphical user interfaces

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 << < 487 488 489 490 491 492 493 494 495 496 > >>

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：