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

30,380 篇 会议
4,648 篇 期刊文献
239 册 图书

馆藏范围

35,267 篇 电子文献
0 种 纸本馆藏

日期分布

学科分类号

21,799 篇 工学
- 15,762 篇 计算机科学与技术...
- 13,251 篇 软件工程
- 5,816 篇 信息与通信工程
- 3,436 篇 控制科学与工程
- 2,683 篇 电子科学与技术（可...
- 2,620 篇 电气工程
- 2,351 篇 生物工程
- 1,891 篇 生物医学工程（可授...
- 1,538 篇 光学工程
- 1,346 篇 机械工程
- 1,217 篇 动力工程及工程热...
- 1,204 篇 仪器科学与技术
- 1,016 篇 化学工程与技术
- 855 篇 安全科学与工程
- 721 篇 交通运输工程
11,171 篇 理学
- 6,041 篇 数学
- 3,059 篇 物理学
- 2,570 篇 生物学
- 1,996 篇 统计学（可授理学、...
- 1,336 篇 系统科学
- 1,088 篇 化学
5,627 篇 管理学
- 3,282 篇 管理科学与工程(可...
- 2,624 篇 图书情报与档案管...
- 1,825 篇 工商管理
1,600 篇 医学
- 1,389 篇 临床医学
- 1,299 篇 基础医学(可授医学...
- 851 篇 药学(可授医学、理...
- 677 篇 公共卫生与预防医...
1,028 篇 法学
- 822 篇 社会学
644 篇 经济学
- 644 篇 应用经济学
490 篇 农学
430 篇 教育学
156 篇 文学
77 篇 军事学
39 篇 艺术学
1 篇 哲学

主题

1,120 篇 accuracy
871 篇 feature extracti...
856 篇 computational mo...
741 篇 deep learning
683 篇 training
679 篇 computer science
537 篇 real-time system...
523 篇 support vector m...
499 篇 machine learning
461 篇 predictive model...
426 篇 internet of thin...
373 篇 convolutional ne...
364 篇 data models
354 篇 computer archite...
334 篇 reliability
309 篇 optimization
291 篇 data mining
281 篇 routing
263 篇 wireless sensor ...
255 篇 conferences

机构

83 篇 institut univers...
82 篇 north-west unive...
81 篇 national centre ...
79 篇 infn sezione di ...
77 篇 institute of inf...
76 篇 infn sezione di ...
76 篇 tno technical sc...
67 篇 université de st...
67 篇 dept. of informa...
66 篇 università di ca...
64 篇 nikhef national ...
58 篇 dept. of informa...
57 篇 dept. of compute...
56 篇 dept. of compute...
53 篇 leiden universit...
52 篇 school of automa...
52 篇 dept. of compute...
49 篇 dept. of compute...
47 篇 university würzb...
45 篇 dept. of electri...

作者

85 篇 ferrara g.
85 篇 ardid m.
85 篇 gal t.
85 篇 bozza c.
84 篇 calvo d.
82 篇 kalekin o.
81 篇 chen a.
80 篇 díaz a.f.
80 篇 boumaaza j.
78 篇 coleiro a.
77 篇 gozzini s.r.
70 篇 huang f.
70 篇 dallier r.
60 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

31,526 篇 英文
3,344 篇 其他
301 篇 中文
54 篇 日文
45 篇 朝鲜文
2 篇 德文
2 篇 斯洛文尼亚文
1 篇 法文
1 篇 葡萄牙文

检索条件"机构=Computer Applications in Science and Engineering dept."

共 35267 条记录，以下是1281-1290 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：

Anylogic and Python-Based Gunshot Detection System Using CNN and Trilateration

Anylogic and Python-Based Gunshot Detection System Using CNN...

引用

2024 IEEE International Conference on Information Technology, Electronics and Intelligent Communication Systems, ICITEICS 2024

作者： Shendre, Sanjivani P. Priya, M.Yagnasri Sridhar, Swetha Kamble, Samrudhi S. Khanna, Manju Amrita School of Computing Amrita Vishwa Vidyapeetham Dept. of Computer Science and Engineering Bengaluru India

ISBN: (纸本)9798350382693

Gunshot detection has been applied in fields such as defense and forensic sciences. This plays a very critical role in law enforcement and public safety. Detecting a gunshot begins with automatic detection of the presence of an audio event. These rare events can be analyzed and prevented by using a system that detects the audio and location of gunshots. The success of this system relies ultimately on its accuracy. In this paper, audio data has been collected and a machine learning(ML) model using a Convolution Neural Network (CNN) has been trained that classifies the audio and detects a gunshot acoustic. The prediction of the gunshot location has been implemented using the trilateration method with the use of AI agents as sensors. The model has been trained in Python programming language. This simulation has been implemented in the Java programming language with AnyLogic software as the user interface. © 2024 IEEE.

关键词： Java programming language

来源：评论

学校读者我要写书评

暂无评论

Development of a Predictive Model for Heart Disease Using Clinical Data: A Focus on Feature Selection & Algorithm Optimization 1

Development of a Predictive Model for Heart Disease Using Cl...

引用

1st IEEE International Conference on Advances in Computing, Communication and Networking, ICAC2N 2024

作者： Kaushik, Priyanka Trivedi, Vishal Sharma, Bhavik Sharma, Shubham Kumar, Pradeep Ramya, R. Chandigarh University Dept. of Computer Science Engineering Chandigarh India Madhav University Dept. of Pharmacy Pindwara India Mangalayatan University Dept. of Pharmacy Beswan India J.S. University Dept. of Computer Science Shikohabad India Dhanalakshmi Srinivasan University Dept. of CSE Coimbatore India

ISBN: (纸本)9798350356816

Heartdisease is increasingly common among individuals, including students & working professionals, with heart stroke being the most prevalent condition. Diagnosing heart-related problems requires a combination of pathological & clinical data to ensure accuracy. Predicting these diseases accurately is crucial for researchers. This paper introduces a model for predicting heart disease aimed at assisting medical professionals in identifying potential issues based on clinical data. The approach involves selecting key clinical features such as age, body pain, blood pressure, & blood sugar levels. An algorithm is developed using this data to achieve high accuracy & precision. Ultimately, a user-friendly Heart Disease Prediction Model (HDPM) is created to display prediction graphs, performance metrics (execution time, accuracy, specificity), & predicted results, facilitating the classification of heart disease. © 2024 IEEE.

关键词： Prediction models

来源：评论

学校读者我要写书评

暂无评论

Analysis of EEG Signals for Predicting Neurological Recovery in Post-Cardiac Arrest Comatose Patients 1

Analysis of EEG Signals for Predicting Neurological Recovery...

引用

1st IEEE International Conference on Artificial Intelligence for Medicine, Health and Care, AIMHC 2024

作者： Guntunur, Shria Varma, Shreya Saxena, Shubangi Sagere, Supreeta Srinivasa, Gowri PES Center for Pattern Recognition Dept. Computer Science Engineering PES University Bengaluru India

ISBN: (纸本)9798350371987

Prognostic decisions made in the early days following cardiac arrest can significantly impact patient outcomes. This work leverages continuous electroencephalography (EEG) to predict neurological outcomes in patients who have become comatose after a cardiac arrest. We propose a two-stage stacked classifier (TSSC), combining an RNN model and an SVM model with a non-linear kernel, with KNN serving as the meta-classifier. This approach involves an analysis of EEG features extracted using Welch’s power spectral density, resulting in a reduced feature subset and a subsequent enhancement in accuracy. Experimental results demonstrate an impressive predictive accuracy of 95.1% with this approach. We also discuss the implications of our findings for clinical practice. © 2024 IEEE.

关键词： Electroencephalography

来源：评论

学校读者我要写书评

暂无评论

Bi-directional GRU-Based Approach for Multi-Class Text Error Identification System 9

Bi-directional GRU-Based Approach for Multi-Class Text Error...

引用

9th IEEE International Conference for Convergence in Technology, I2CT 2024

作者： Reeha, Shaik Nikith, Boda Venkata Mani Prakash Reddy, G. Pati, Peeta Basa Amrita School of Computing Amrita Vishwa Vidyapeetham Dept. of Computer Science And Engineering Bengaluru India

ISBN: (纸本)9798350394474

In today's highly competitive academic and research landscape, the impression authors leave on readers is paramount to their reputation and success. Spelling errors can significantly undermine an author's credibility and negatively impact their standing within the scholarly community. To mitigate this risk, it is imperative that authors thoroughly proofread their content before submitting it to prestigious conference journals or sharing it with fellow researchers. This paper introduces a novel solution to streamline the error-checking process and empower authors to focus on other critical aspects of their projects. We propose a sophisticated text classification model, leveraging the vast capabilities of the Recurrent Neural Network (RNN) architecture, which was trained on the extensive C4 dataset sourced from the TensorFlow Library. This model exhibits exceptional proficiency in rectifying spelling mistakes across a wide range of contexts, thereby bolstering the overall quality and clarity of written work. Notably, our text classification model trained with Bi-Directional GRU method showcases a remarkable accuracy of 67% in classifying errors into four distinct categories, providing insightful feedback to authors for further improvement. © 2024 IEEE.

关键词： Recurrent neural networks

来源：评论

学校读者我要写书评

暂无评论

Optimizing Content Delivery Networks for Enhanced Performance and Energy Efficiency 15

Optimizing Content Delivery Networks for Enhanced Performanc...

引用

15th International Conference on Computing Communication and Networking Technologies, ICCCNT 2024

作者： Jahnave, Poluru Reddy Karna, Siwani Santhoshi Haneesha, Samudrala Sai Bhaskaran, Sreebha Dept. of Computer Science and Engineering Amrita School of Computing Bengaluru Amrita Vishwa Vidyapeetham India

ISBN: (纸本)9798350370249

Content Delivery Networks (CDNs) are fundamental to modern Internet content distribution, enabling high-speed delivery of web pages, videos, and other online resources. Optimizing caching strategies within CDNs is crucial for improving network efficiency and ensuring a seamless user experience. This research explores the efficacy of traditional caching algorithms such as LFU, LRU, RAND, and FIFO, in comparison to machine learning algorithms including Linear Regression (LR), Gradient Boosting (GB), K-Nearest Neighbours (kNN), Decision Tree (DT), AdaBoost, Random Forest (RF), LightGBM, and XGBoost. The findings demonstrate that machine learning techniques can significantly enhance CDN performance by identifying optimal caching locations and adapting to traffic patterns. Notably, the XGBoost model achieved a cache hit rate of 76.31%, a latency of 0.98 seconds, and a throughput of 18,796.16 requests per second, surpassing traditional methods in hit rate and overall efficiency. The study underscores the need for predictive and adaptive caching approaches in modern traffic management, highlighting the benefits of improved caching on user experience, operational costs, and environmental impact. ©2024 IEEE.

关键词： Random forests

来源：评论

学校读者我要写书评

暂无评论

Bridging the Language Gap: Enhancing English-to-Telugu Translation using NMT and Encoding Decoding Techniques 15

Bridging the Language Gap: Enhancing English-to-Telugu Trans...

引用

15th International Conference on Computing Communication and Networking Technologies, ICCCNT 2024

作者： Asmitha, M. Kavitha, C.R. Amrita Vishwa Vidyapeetham Amrita School of Computing Dept. of Computer Science and Engineering Bengaluru India

ISBN: (纸本)9798350370249

Language translation, particularly in the context of natural language processing, involves converting text or speech from one language into another while preserving its meaning, context, and cultural nuances. This task is critical for enabling communication across different languages and is a significant area of research and development in artificial intelligence. Machine translation has a wide range of real-time applications that have significantly impacted various fields by bridging language barriers. Some of the real time application includes Google Translate, Microsoft Translator, Skype Translator. NMT has revolutionized language translation with models like Google's Transformer, OpenAI's GPT, Facebook's BART, and Google's T5. Development of a machine translation system to translate English sentences into Telugu. The system utilizes a neural network model based on an encoder-decoder architecture with attention mechanism. Preprocessing techniques are applied to the dataset, including lowercasing, removal of special characters, and tokenization. The sparse categorical cross-entropy loss function and Adam optimizer are used to train the model. The actual vs. projected output is used to evaluate performance. Pre-trained GloVe word embeddings are used in the implementation to improve the model's capacity to extract semantic information. © 2024 IEEE.

关键词： Attention mechanism Encoder-Decoder GloVe word embeddings Machine translation Neural network Pre-processing

来源：评论

学校读者我要写书评

暂无评论

Analyzing Urban Transportation Services using RideShare Data Insights 9

Analyzing Urban Transportation Services using RideShare Data...

引用

9th IEEE International Conference for Convergence in Technology, I2CT 2024

作者： Jashwanth, Kandukuri Sai Praneeth Reddy, Koti Leela Sai Snehitha, Munaga Sampath, Nalini Nair, Priyanka C. Amrita Vishwa Vidyapeetham Amrita School of Computing Dept. of Computer Science And Engineering Bengaluru India

ISBN: (纸本)9798350394474

In this fast-growing world, the need for choosing or booking a ride is increasing. Since the fare displayed on booking apps such as Uber, Rapido, etc., and the fare after the ride is completed differ, it is imperative to predict the fare. There is a large difference in those prices. To address these issues, an optimized model for ride fare prediction should be there. These rideshare services brought a large change in the transportation system but predicting the fare system has to change. The study presents various machine-learning models of regression such as the Selection Operator regressor, Elastic-Net regressor, Ridge regressor, Random Forest regressor, Least Absolute Shrinkage, and XGBoost regressor. The XGBoost regressor outperformed its counterparts with an R2 value of 0.9734. After the regression models are applied the label values are classified into three categories: high, medium, and low. The obtained ordinal label values are given into classification algorithms like Naive Bayes, Extra Trees classifier, Support Vector Machine, and Multi-layer Perceptron are applied. A comparative analysis is done and SVM performed the best in classification algorithms with an F1 score of 99.53. © 2024 IEEE.

关键词： Forecasting

来源：评论

学校读者我要写书评

暂无评论

RT-MDM: Real-Time Scheduling Framework for Multi-DNN on MCU Using External Memory 24

RT-MDM: Real-Time Scheduling Framework for Multi-DNN on MCU ...

引用

61st ACM/IEEE Design Automation Conference, DAC 2024

作者： Kang, Sukmin Lee, Seongtae Koo, Hyunwoo Chwa, Hoon Sung Lee, Jinkyu Dept. of Semiconductor and Display Engineering Sungkyunkwan University Korea Republic of Samsung Electronics Co. Ltd. Korea Republic of Dept. of Computer Science and Engineering Sungkyunkwan University Korea Republic of School of Electronic and Electrical Engineering Sungkyunkwan University Korea Republic of Dept. of Electrical Engineering and Computer Science Dgist Korea Republic of

ISBN: (纸本)9798400706011

As the application scope of DNNs executed on microcontroller units (MCUs) extends to time-critical systems, it becomes important to ensure timing guarantees for increasing demand of DNN inferences. To this end, this paper proposes RT-MDM, the first RealTime scheduling framework for Multiple DNN tasks executed on an MCU using external memory. Identifying execution-order dependencies among segmented DNN models and memory requirements for parallel execution subject to the dependencies, we propose (i) a segment-group-based memory management policy that achieves isolated memory usage within a segment group and sharded memory usage across different segment groups, and (ii) an intra-task scheduler specialized for the proposed policy. Implementing RT-MDM on an actual system and optimizing its parameters for DNN segmentation and segment-group mapping, we demonstrate the effectiveness of RT-MDM in accommodating more DNN tasks while providing their timing guarantees. © 2024 Copyright is held by the owner/author(s). Publication rights licensed to ACM.

关键词： Memory management

来源：评论

学校读者我要写书评

暂无评论

Enhancing Healthcare Image Record Security via CNN-based Tamper Detection, Watermarking, and Digital Signatures 2

Enhancing Healthcare Image Record Security via CNN-based Tam...

引用

2nd International Conference on Self Sustainable Artificial Intelligence Systems, ICSSAS 2024

作者： Kumaran, U. Gurupriya, M. Thodathara, Harshitha Reddy Aryagopal Vijjapu, Aditya Harish, Gattamaneni Amrita Vishwa Vidyapeetham Amrita School of Computing Dept. of Computer Science and Engineering Bengaluru India

ISBN: (纸本)9798350368413

computers have been seamlessly integrated into every domain including health care where one of its applications is in the storage of health care records such as medical images. Electronic healtheare records contain a lot of sensitive information about patients, such as the diseases, diagnosis, treatment plans, drugs administered or medicines prescribed and hence this vital information must not be disclosed at any cost as it can have huge repercussions. As each day passes, more vulnerabilities and threats surface and it is important to come up with secure systems and apt security measures to counter these threats and keep the attackers at bay. This study provides a holistic approach to secure and safeguard medical image records by addressing two problems, the first is image tamper detection using medical image deepfake detection to decipher whether the image has been modified or not, and the second is to employ various cryptographic techniques such as hashing, watermarking and digital signatures to protect the images from getting tampered itself. © 2024 IEEE.

关键词： Electronic health record

来源：评论

学校读者我要写书评

暂无评论

Hybrid Cryptography Techniques for Data Security in Cloud Computing 5

Hybrid Cryptography Techniques for Data Security in Cloud Co...

引用

5th IEEE International Conference on Computing, Power, and Communication Technologies, IC2PCT 2024

作者： Reddy, Kethamreddy Karthikeya Chadha, Angela Raj Nikhil, Perla Sai Sountharrajan, S. Amrita School of Computing Amrita Vishwa Vidyapeetham Dept. of Computer Science & Engineering Chennai India

ISBN: (纸本)9798350383522

The Prime objective of cloud computing is that to the centralize processing and storage capabilities. Since cloud computing elevates performance requirements to greater heights, it is possible to process extremely huge amounts of data with minimal effort. This research work suggests a two-tier cryptography-based security system for cloud computing. This particular model combines symmetric and asymmetric key cryptography methods. In this case, the most used Data Encryption Standard (DES) and the Advanced Encryption Standard (AES) are used to enable layered encryption and decryption, enhancing the security of cloud storage. It generates the secret key using Elliptic Curve Cryptography, which is utilized in the DES and AES algorithms to promote adaptability, scalability, and dependability. © 2024 IEEE.

关键词： AES Cloud cryptography DES and ECC RSA Two layered architecture

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 << < 125 126 127 128 129 130 131 132 133 134 > >>

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：