检索结果-内蒙古大学图书馆

2nd International Conference on Cyber Resilience, ICCR 2024

作者： Mustafa, Hossam M. J. Al-Zyod, Mohammad H. University Of Petra Faculty Of Information Technology Department Of Data Science And Artificial Intelligence Amman Jordan Al-Balqa Applied University Computer Science Department Salt Jordan

ISBN: (纸本)9798350394962

The majority of information technology organizations nowadays prefer cloud computing as their main choice due to improvements in information technology. However, as a result of cloud computing's vast and open architecture, which makes it vulnerable to hacker attacks, the security of data remains an important concern. As a consequence, ensuring the security and integrity of data has become crucial while constructing an abnormal intrusion detection system utilizing machine learning algorithms represents a method to potentially detect intrusions. Recurring clouding as well as prevention. Using machine learning algorithms and revised intrusion datasets is necessary to overcome the challenge of finding effective and optimal network intrusion detection systems. The White Shark Optimization approach works along with Support Vector Machines (SVM). The suggested algorithm's effectiveness is assessed using metrics including accuracy and recall. When results of previous research employing both of the two datasets (NSL-KDD and Kyoto) for predicting the detection of abnormal infiltration are compared to the proposed algorithm based on SVM, it is determined that the white shark optimization algorithm produced the best accuracy, at 99.8%. © 2024 IEEE.

关键词： Support vector machines

来源：评论

学校读者我要写书评

暂无评论

Predicting Flight Delays and Error Calculation Using Machine Learning Classifiers 5

Predicting Flight Delays and Error Calculation Using Machine...

引用

5th International Conference on Electronics and Sustainable Communication Systems, ICESC 2024

作者： Rajeshkumar, G. Vijaya, K. Sadesh, S. Arunkumar, P.M. Manoj Praveen, V. Kumar, M. Senthil Bannari Amman Institute of Technology Dept of Cse Sathyamangalam India Kongu Engineering College Department of Csd Perunduarai Erode India Velalar College of Engineering and Technology Department of Artificial Intelligence and Data Science Erode India Karpagam College of Engineering Department of Computer Science and Engineering Coimbatore641032 India Erode Sengunthar Engineering Collge Department of Artificial Intelligence and Data Science Perundurai India

ISBN: (纸本)9798350379945

Flight delays are a significant concern in the aviation industry, causing inconvenience for passengers and financial losses for airlines. Predicting flight delays accurately can help mitigate these issues by allowing both airlines and passengers to proactively manage schedules and resources. The delay might depend on weather, crew management, and resource planning. Existing prediction methods often lack accuracy or rely on historical data and statistical models, which may not capture the complex interactions and patterns present in flight operations to predict delays. This study proposes a novel approach for flight delay prediction using advanced machine learning techniques and tools. Specifically, machine-learning classifiers, such as Support Vector Machines (SVM) and Decision Tress, are employed to analyze a comprehensive live streaming dataset comprising various incorporated factors like flight operations, weather conditions, air traffic congestion, and aircraft performance. Proposed model is trained on a large dataset encompassing diverse routes and airlines and has achieved an accuracy of 95% in predicting delays by outperforming existing methods. © 2024 IEEE.

关键词： Traffic congestion

来源：评论

学校读者我要写书评

暂无评论

Machine Learning Diagnosis of Lumpy Skin Disease in Cattle Herds 3

Machine Learning Diagnosis of Lumpy Skin Disease in Cattle H...

引用

3rd International Conference on Applied artificial intelligence and Computing, ICAAIC 2024

作者： Krishna, Nimmagadda Kumar Benjamin, Ruth Moly Tejaswi, Nimmagadda Institute of Technology and Sciences Division of Computer Science and Engineering Karunya Coimbatore India Shri Vishnu Engineering College for Women Division of Artificial Intelligence and Data Science Bhimavaram India

ISBN: (纸本)9798350375190

In order to diagnose lumpy skin disease in cattle herds, machine learning techniques such as Support Vector Machine (SVM), Gradient Boosting, and Random Forest algorithms were used in this research work. The objective of the study is to create a diagnostic tool that would be both accurate and effective to identify and treat this infectious disease early on. The algorithms were trained to classify cases with high accuracy using a dataset that included different clinical and demographic characteristics related with the presence or absence of Lumpy Skin Disease. SVM is used because of its capacity to manage intricate and non-linear correlations in the data, and Random Forest and Gradient Boosting algorithms were chosen due to their predictive performance. © 2024 IEEE.

关键词： Support vector machines

来源：评论

学校读者我要写书评

暂无评论

The Impact of Generative artificial intelligence on Learning: A Case Study at the University of Petra 2

The Impact of Generative Artificial Intelligence on Learning...

引用

2nd International Conference on Cyber Resilience, ICCR 2024

作者： El-Khalili, Nuha Al-Nashashibi, May Al-E'mari, Salam University Of Petra Faculty Of Information Technology Software Engineering Department Amman Jordan University Of Petra Faculty Of Information Technology Data Science & Artificial Intelligence Department Amman Jordan University Of Petra Faculty Of Information Technology Information Security Department Amman Jordan

ISBN: (纸本)9798350394962

Recently, a noticeable trend of using Generative artificial intelligence (GAI) within the educational field has raised interest to study the shape and impact of this utilization. This study investigates the opinions of Information technology (IT) undergraduate students about the utilization of GAI during the learning process, focusing on their perception of the quality of produced information, challenges and concerns while using it, how they utilize it during learning, and long-term impact of using GAI. An electronic survey was distributed as a Google from to undergraduate students from five IT programs at the University of Petra. The results of 122 students revealed that 82% use GAI while learning. The main use of GAI (80% of respondents) was for solving programming problems, while 66% of respondents use GAI to write reports and express their ideas. The majority 86% of participants evaluate the presented information from GAI before using them, since they believe that sometimes the information is incorrect. 89% of respondents believe that they can learn from GAI tools, however, 95% of them feel it is necessary to train them on the proper utilization of GAI in education, and, 76% think that regulations must be released about the acceptable use of GAI. © 2024 IEEE.

关键词： artificial intelligence

来源：评论

学校读者我要写书评

暂无评论

Exploiting comments information to improve legal public opinion news abstractive summarization

引用

Frontiers of Computer science 2022年第6期16卷 31-40页

作者： Yuxin HUANG Zhengtao YU Yan XIANG Zhiqiang YU Junjun GUO Faculty of Information Engineering and Automation Kunming University of Science and TechnologyKunming650500China Yunnan Key Laboratory of Artificial Intelligence Kunming University of Science and TechnologyKunming650500China

Automatically generating a brief summary for legal-related public opinion news(LPO-news,which contains legal words or phrases)plays an important role in rapid and effective public opinion *** LPO-news,the critical case elements which are significant parts of the summary may be mentioned several times in the reader ***,we investigate the task of comment-aware abstractive text summarization for LPO-news,which can generate salient summary by learning pivotal case elements from the reader *** this paper,we present a hierarchical comment-aware encoder(HCAE),which contains four components:1)a traditional sequenceto-sequence framework as our baseline;2)a selective denoising module to filter the noisy of comments and distinguish the case elements;3)a merge module by coupling the source article and comments to yield comment-aware context representation;4)a recoding module to capture the interaction among the source article words conditioned on the *** experiments are conducted on a large dataset of legal public opinion news collected from micro-blog,and results show that the proposed model outperforms several existing state-of-the-art baseline models under the ROUGE metrics.

关键词： legal public opinion news abstractive summarization comment comment-aware context case elements bidirectional attention

来源：评论

学校读者我要写书评

暂无评论

Kolmogorov Arnold Network for Hyperspectral Image Classification: A Detailed Explanation 2

Kolmogorov Arnold Network for Hyperspectral Image Classifica...

引用

2nd DMIHER International Conference on artificial intelligence in Healthcare, Education and Industry, IDICAIEI 2024

作者： Suman, Saurabh Pacharaney, Utkarsha Choudhary, Vishal Kumar Raushan, Rahul Kumar, Abhishek Kumar, Gulshan Faculty of Engineering and Technology Department of Computer Science and Design Maharashtra Wardha India Faculty of Engineering and Technology Department of Artificial Intelligence and Machine Learning Maharashtra Wardha India Faculty of Engineering and Technology Department of Computer Science and Medical Engineering Maharashtra Wardha India

ISBN: (纸本)9798331528713

Hyperspectral imaging (HSI) has been proved to be useful in numerous fields because of its ability to acquire the spectral information across the hundreds of contiguous bands. Nevertheless, the vast dimensionality of the hyperspectral data presents a great problem especially during data processing as well as during classification. Recently, one of the techniques that have attracted most interest for the classification of hyperspectral images is Kolmogorov Arnold Network (KAN), which is efficient with regard to those high-dimensional non- linear data sets found in hyperspectral imagery. This study focuses on how KAN can be utilized for classifying hyperspectral images, how B-spline curves can be used for augmenting the performance of the model, and what experimentation was done with the state-of-the-art hyperspectral data set. From these results, it was established that KAN plus B-spline curves was a good strategy for hyperspectral images classification compared to existing systems in both accuracy and speed. © 2024 IEEE.

关键词： Splines

来源：评论

学校读者我要写书评

暂无评论

A Review on Implementation of Wearable Devices in Healthcare 7

A Review on Implementation of Wearable Devices in Healthcare

引用

7th International Conference on Inventive Computation Technologies, ICICT 2024

作者： Suman, Saurabh Choudhary, Vishal Kumar Pacharaney, Utkarsha Kumar, Abhishek Kumar, Dhiraj Raushan, Rahul Faculty of Engineering And Technology Department of Computer Science And Design Maharashtra Wardha India Faculty of Engineering And Technology Department of Computer Science And Medical Engineering Maharashtra Wardha India Faculty of Engineering And Technology Department of Artificial Intelligence And Machine Learning Maharashtra Wardha India

ISBN: (纸本)9798350359299

The capacity to get additional patient data, including clinical, behavioral, and self-monitored data, has enhanced by the expanding usage of wearable technology. Large volumes of previously unobtainable data are now available, providing a chance to create new instruments with sophisticated analysis and decision support systems for application in clinical settings. Additionally, it gives patients additional options by arming them with personalized decision-support resources and information, enabling them to take charge of their own health care while maintaining their sense of autonomy. Especially well-suited for miniaturization and integration into microfluidic devices are biosensors with electrochemical sensors. Applications cover activities in the domains of diagnostics, food and environmental control, and the identification of complete cells, the parts of cells, proteins, and tiny compounds. Microfluidic technologies can be as basic as sample transport tubes or as sophisticated as platforms with extra components for sample preparation and sensing electrode integration. The kind of detection, application, and sample material all influence the microfluidics design. The next issue for the healthcare industry will be how to use newly acquired information in a way that benefits patients, healthcare organizations, and professionals all while reducing costs and workloads. Given the current limitations, the challenge for wearable technology designers is to provide solutions that healthcare practitioners can readily integrate and use. © 2024 IEEE.

关键词： Biosensors

来源：评论

学校读者我要写书评

暂无评论

Analysis of Prediction of Pneumonia from Chest X-ray images using CNN and Transfer Learning 5

Analysis of Prediction of Pneumonia from Chest X-ray images ...

引用

5th IEEE International Conference for Emerging technology, INCET 2024

作者： Vinay, K. Shashanka Kodipalli, Ashwini Swetha, P. Kumaraswamy, S. Dept. of Computer Science and Engineering Global Academy of Technology Karnataka Bengaluru India Dept of Artificial Intelligence and Data Science Global Academy of Technology Karnataka Bengaluru India

ISBN: (纸本)9798350361155

A good design for image classification problems is the CNN architecture you presented, which consists of 5 convolution blocks followed by 4 fully connected layers. From the input X-ray images, the convolutional blocks extract pertinent features, and the fully connected layers assist in determining the final classification based on those learned features. You have integrated various approaches to improve the performance of your model. The inputs to each layer are normalized through batch normalization, which can speed up training and enhance generalization. By removing certain neurons at random during training, dynamic dropout helps avoid overfitting. L2 regularization weight decay and learning rate decay are two efficient strategies for preventing overfitting and enhancing the model's capacity to expand to new data. Popular optimization algorithm Adam optimizer effectively neural network training. For binary classification problems like the diagnosis of pneumonia, the loss function for binary Cross-Entropy is the best option. To determine your model's efficacy, you must validate it using benchmark datasets that are available to the general public. You can evaluate your model's effectiveness by comparing its performance to that of current methods by conducting experimental investigations on these datasets. Your model performs well as evidenced by accuracy scores of 90.93%, 89.17% for multi-class classification and binary classification. tasks. Automated methods, such as the one you suggested, might help medical practitioners recognize pneumonia and spot diseased spots in chest X-ray pictures. However, it's crucial to remember that automated systems shouldn't take the place of professional radiologists' and doctors' skills and judgment;rather, they should be used as supportive tools. Medical To ensure accurate diagnosis and suitable patient care, specialists should always review and interpret the system's data. It's also crucial to take into account potential drawback

关键词： Convolutional neural networks

来源：评论

学校读者我要写书评

暂无评论

Transverse Velocity Field Measurements in High-resolution Solar Images Based on Deep Learning

引用

Research in Astronomy and Astrophysics 2023年第6期23卷 86-97页

作者： Zhen-Hong Shang Si-Yu Mu Kai-Fan Ji Zhen-Ping Qiang Faculty of Information Engineering and Automation Kunming University of Science and TechnologyKunming 650500China Yunnan Key Laboratory of Artificial Intelligence Kunming University of Science and TechnologyKunming 650500China Yunnan Observatories Chinese Academy of SciencesKunming 650216China College of Big Data and Intelligent Engineering Southwest Forestry UniversityKunming 650224China

To address the problem of the low accuracy of transverse velocity field measurements for small targets in highresolution solar images,we proposed a novel velocity field measurement method for high-resolution solar images based on *** method transforms the transverse velocity field measurements into an optical flow field prediction *** evaluated the performance of the proposed method using the Hαand TiO data sets obtained from New Vacuum Solar Telescope *** experimental results show that our method effectively predicts the optical flow of small targets in images compared with several typical machine-and deeplearning *** the Hαdata set,the proposed method improves the image structure similarity from 0.9182 to0.9587 and reduces the mean of residuals from 24.9931 to 15.2818;on the TiO data set,the proposed method improves the image structure similarity from 0.9289 to 0.9628 and reduces the mean of residuals from 25.9908 *** optical flow predicted using the proposed method can provide accurate data for the atmospheric motion information of solar *** code implementing the proposed method is available on https://***/lygmsy123/transverse-velocity-field-measurement.

关键词： methods:data analysis techniques:image processing Sun:fundamental parameters

来源：评论

学校读者我要写书评

暂无评论

Hybrid- Blowfish Security Strengths Using Side Channel Countermeasures

Hybrid- Blowfish Security Strengths Using Side Channel Count...

引用

2023 International Telecommunications Conference, ITC-Egypt 2023

作者： Souror, Walid W. Fouad, Mohamed Takieldeen, Ali E. Zagazig University Electronics and Communication Department Faculty of Engineering Egypt Delta University for Science and Technology Artificial Intelligence Department Faculty of Artificial Intelligence Gamasa35712 Egypt

ISBN: (纸本)9798350326062

in today's digital age, the need for secure communication has become increasingly crucial. Cryptography has become an essential aspect of modern-day communication, where transmitting and storing sensitive information securely is paramount. By using encryption techniques, cryptography protects sensitive information stored in computer systems, transmitted through networks and exchanged among individuals. It is vital for organizations to implement robust cryptography practices in order to safeguard their critical data and protect themselves from cyber-attacks. The misuse or breach of sensitive information can result in serious consequences such as financial loss, reputational damage and data theft. Overall, We introduce new algorithm Hybrid-Blowfish by combination between blowfish and counter-measure of SCA using Masking string, we compared DES, 3DES, AES, blowfish, RSA and Hybrid-Blowfish across the tests like frequency test, serial test, encryption time, decryption time, memory used, avalanche effect, entropy and no of bits required for encoding optimally and the result demonstrate the effectiveness and superiority of Hybrid-Blowfish compared to traditional Blowfish and increase the cyber-security strength by approximately 25% © 2023 IEEE.

关键词： Losses

来源：评论

学校读者我要写书评

暂无评论

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：

请选择收藏分类：

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

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：