检索结果-内蒙古大学图书馆

A hybrid Improved Fully Homomorphic Encryption with AES to provide high security in Cloud computing

A hybrid Improved Fully Homomorphic Encryption with AES to p...

2023 International Conference on Innovative computing, Intelligent Communication and Smart Electrical Systems, ICSES 2023

作者： Ravindran, K. Prabhu, S. Nagendra Easwari Engineering College SRM Institute of Science and Technology Department of Information Technology Chennai India SRM Institute of Science and Technology Department of Computational Intelligence School of Computing India

ISBN: (纸本)9798350319200

Since this information may be accessible by a third party and could compromise the client's information's confidentiality, there is a barrier between the customer and the true location of his information. The most often used approach to bridging this security gap has been to first encrypt online data using traditional methods before sending it to the cloud service provider. But to decrypt the information and complete the calculations that are required, the customer must give the server a secret key. Using homomorphic encryption, mathematical calculations can be made on encrypted information without having to first decode it. The electrocardiogram (ECG) measures and finds arrhythmias in the circulatory system. It differ from individual to individual, these characteristics are now employed for identification. So it's crucial to secure an ECG signal. A safety method known as Homomorphic Encryption (HE) handles encrypted information without the need for *** identical initial information findings are provided by HE. In this research, an Improved Fully Homomorphic Encryption (IFHE) technique using Advanced Encryption Standard (AES) is proposed for encoding the ECG measures to enhance safety while safeguarding the confidentiality of information while removing sharing key limitations. The information of the customer is encrypted in the cloud server discussed in this work, so required computations can be performed on the encrypted information. To do this, it is proposed that the method of assessment be added as a further layer of security to the AES technique, which then executes several homomorphic mathematical computations on the encrypted information in place of the initial information. To increase safety, a linear polynomial equation with changeable values is proposed for the assessment ***, the IFHEAES method has a 100% success rate in decryption (recovering the original signal) and 95.8% efficiency in categorization. Its decryption and enc

关键词： Advanced Encryption Standard Cloud computing Improved Fully Homomorphic Encryption Performance Measures Security

来源：评论

学校读者我要写书评

暂无评论

Machine Learning Approach for Handling Imbalanced Students' Performance Data 15

Machine Learning Approach for Handling Imbalanced Students' ...

引用

15th International Conference on Advances in computing, Control, and Telecommunication Technologies, ACT 2024

作者： Sujatha, E. Divya, S. Sakthivelan, R.G. Gopirajan, P.V. Thandalam Chennai India Chennai India Department of Computer Science and Engineering Gopalan College of Engineering and Management Bengaluru India Department of Computational Intelligence School of Computing SRM Institute of Science and Technology Kattankulathur campus Chennai India

ISBN: (纸本)9798331300579

Imbalanced student performance data in educational institutions is crucial for any machine learning prediction model. It affects the efficiency of classifiers and challenges the sampling methods for having a more significant number of features. The proposed model was designed to predict the student's performance by comparing the results with popular similar models. The Kaggle dataset having 386 rows and 33 columns of student data, was used in this study. In addition, the Portugal database was considered for experimental analysis, containing 394 students and 19 attributes. It proves that the Random Forest classifier yields the highest accuracy at 84.15% in handling imbalanced datasets. The results show that the SVM-SMOTE is higher accuracy as, 94.76%, than the other sampling methods in predicting the student's performance with various features. © Grenze Scientific Society, 2024.

关键词： Adversarial machine learning

来源：评论

学校读者我要写书评

暂无评论

Machine Learning-Based Dynamic Signal Switching: A Promising Solution to Traffic Congestion

Machine Learning-Based Dynamic Signal Switching: A Promising...

引用

2023 International Conference on Innovative computing, Intelligent Communication and Smart Electrical Systems, ICSES 2023

作者： Kanchana, M. Gopirajan, P.V. Mahalakshmi, B. Vijaya Nirmala, B. SRM Institute of Science and Technology School of Computing Department of Computing Technologies Katankulathur Tamil Nadu Chennai603203 India SRM Institute of Science and Technology School of Computing Department of Computational Intelligence Katankulathurx Tamil Nadu Chennai603203 India AMC Engineering College Department of Computer Science and Engineering Bangalore India

ISBN: (纸本)9798350319200

Today's growing urban population means increased revenue for individuals, translating into growing vehicles on the road. Nowadays, people use their private vehicles instead of public transportation, which results in a considerable number of personal vehicles that lead totraffic congestion everywhere. The ever-increasing number of vehicles and complex congestion leads to frequent traffic jams in major cities. In today's scenario, traditional traffic management methods have become redundant as the traffic volume has grown exponentially. The primary goal of this proposed work is to develop an algorithm that uses machine learning to control traffic effectively and ensure efficient traffic flow in the event of unforeseen events like accidents. The existing algorithm focuses on predicting shortterm traffic flow but ignores that traffic congestion may also occur due to accidents and emergencies. Our proposed model will consider all the above factors and use dynamic signal switching among lanes to predict the best and most efficient solution to reducing waiting time for vehicles and congestion on the road. To create an effective traffic flow management model with the least amount of road mayhem, our suggested model needs traffic data as input, which was then trained using various Machine Learning (ML) models. © 2023 IEEE.

关键词： IDD Image processing Machine Learning Neural Network RCNN Traffic Management YOLO

来源：评论

学校读者我要写书评

暂无评论

Electronic structures and strengthening mechanisms of superhard high-entropy diborides

引用

Rare Metals 2023年第2期42卷 614-628页

作者： Gang Yao William-Yi Wang Pei-Xuan Li Ke Ren Jia-Qi Lu Xing-Yu Gao De-Ye Lin Jun Wang Yi-Guang Wang Hai-Feng Song Zi-Kui Liu Jin-Shan Li State Key Laboratory of Solidification Processing Northwestern Polytechnical UniversityXi’an710072China Innovation Center NPU ChongqingChongqing401135China Laboratory of Computational Physics Institute of Applied Physics and Computational MathematicsBeijing100088China Institute of Advanced Structure Technology Beijing Institute of TechnologyBeijing100081China Department of Materials Science and Engineering The Pennsylvania State UniversityUniversity ParkPA16802USA

High-entropy diborides(HEBs)have attracted extensive research due to their potential ultra-high *** the present work,the effects of transition metals(TM)on lattice parameters,electron work function(EWF),bonding charge density,and hardness of HEBs are comprehensively investigated by the first-principles calculations,including(TiZrHfNbTa)B_(2),(TiZrHfNbMo)B_(2),(TiZrHfTaMo)B_(2),(TiZrNbTaMo)B_(2),and(TiHfNbTaMo)B_(2).It is revealed that the disordered TM atoms result in a severe local lattice distortion and the formation of weak *** view of bonding charge density,it is understood that the degree of electron contribution of TM atoms directly affects the bonding strength of the metallic layer,contributing to the optimized hardness of ***,the proposed power-law-scaled relationship integrating the EWF and the grain size yields an excellent agreement between our predicted results and those reported experimental *** is found that the HEBs exhibit relatively high hardness which is higher than those of single transition metal *** particular,the hardness of(TiZrNbTaMo)B_(2)and(TiHfNbTaMo)B_(2)can be as high as29.15 and 28.02 GPa,*** work provides a rapid strategy to discover/design advanced HEBs efficiently,supported by the coupling hardening mechanisms of solid solution and grain refinement based on the atomic and electronic interactions.

关键词： High-entropy diborides(HEBs) Hardness Electronic structure Lattice distortion Power-law

来源：评论

学校读者我要写书评

暂无评论

Android Malware Detection System using Machine Learning 2024

Android Malware Detection System using Machine Learning

引用

16th International Conference on Contemporary computing, IC3 2024

作者： Kaur, Amanpreet Lal, Sangeeta Goel, Shruti Pandey, Mrinal Agarwal, Astha Department of Computer Science and Engineering & IT Jaypee Institute of Information Technology India School of computing and mathematics Keele University Newcastle-under-Lyme United Kingdom

ISBN: (纸本)9798400709722

Detecting Android malware is imperative for safeguarding user privacy, securing data, and preserving device performance. Consequently, numerous studies have underscored the complexities associated with Android malware detection, prompting a multidimensional approach to tackle these challenges effectively. This research leverages machine learning techniques, emphasizing feature extraction, classification algorithms, and both supervised and unsupervised learning methodologies. The exploration begins with in-depth Exploratory Data Analysis (EDA) to gain insights into the dataset, paving the way for informed decision-making. Principal Component Analysis (PCA) is employed for dimensionality reduction, a pivotal step in handling the multivariate nature of the data. The integration of API calls, clustering, and anomaly detection further enriches the model's capability to discern between benign and malicious applications. Crucially, the study delves into the intricacies of sampling, evaluation, and the Confusion Matrix to quantify the model's performance accurately. The utilization of diverse classification algorithms, including Support Vector Machines (SVM), Multi-Layer Perceptrons (MLP), Random Forest, GaussianNB, Decision Tree, and Logistic Regression, underscores the comprehensive nature of the approach. These algorithms collectively contribute to a robust and versatile Android malware detection model capable of adapting to varying threat scenarios. The dataset employed for training and evaluation is sourced from Kaggle, encompassing 29,999 Android applications categorized as benign or malicious based on permissions sought. Current detection methods, deemed resource-intensive and exhaustive, face the challenge of keeping pace with the relentless evolution of new malware strains. This research seeks to address this gap by proposing a sophisticated, machine learning-driven model that not only enhances accuracy but also demonstrates efficiency and adaptability in the face

关键词： Android malware

来源：评论

学校读者我要写书评

暂无评论

Projected gradient descent algorithm for ab initio crystal structure relaxation under a fixed unit cell volume

引用

Physical Review B 2024年第22期109卷 224108-224108页

作者： Yukuan Hu Junlei Yin Xingyu Gao Xin Liu Haifeng Song Institute of Computational Mathematics and Scientific/Engineering Computing Academy of Mathematics and Systems Science Chinese Academy of Sciences Beijing 100190 China School of Mathematical Sciences Innovation Center NPU Chongqing Chongqing 401135 China National Key Laboratory of Computational Physics

This paper is concerned with ab initio crystal structure relaxation under a fixed unit cell volume, which is a step in calculating the static equations of state and forms the basis of thermodynamic property calculations for materials. The task can be formulated as an energy minimization with a determinant constraint. Widely used line minimization-based methods (e.g., conjugate gradient method) lack both efficiency and convergence guarantees due to the nonconvex nature of the determinant constraint as well as the significant differences in the curvatures of the potential energy surface with respect to atomic and lattice components. To this end, we propose a projected gradient descent algorithm named PANBB. It is equipped with (i) search direction projections for lattice vectors, (ii) distinct curvature-aware initial trial step sizes for atomic and lattice updates, and (iii) a nonrestrictive line minimization criterion as the stopping rule for the inner loop. It can be proved that PANBB favors theoretical convergence to equilibrium states. Across a benchmark set containing 223 structures from various categories, PANBB achieves average speedup factors of approximately 1.41 and 1.45 over the conjugate gradient method and direct inversion in the iterative subspace implemented in off-the-shelf simulation software, respectively. Moreover, it normally converges on all the systems, manifesting its robustness. As an application, we calculate the static equations of state for the high-entropy alloy AlCoCrFeNi, which remains elusive owing to 160 atoms representing both chemical and magnetic disorder and the strong local lattice distortion. The results are consistent with the previous calculations and are further validated by experimental thermodynamic data.

关键词： Crystal structure Structural properties Density functional theory

来源：评论

学校读者我要写书评

暂无评论

Design of Approximate Multiplier using Highly Compressed 5_2 Counter 6

Design of Approximate Multiplier using Highly Compressed 5_2...

引用

6th International Conference on Mobile computing and Sustainable Informatics, ICMCSI 2025

作者： Nelmin, Bathlin N. Shaji, R.S. Hariprasad, S. Shettygari, Sudeshna Vasan, J.K. Vijayan, V. Department of Electronics and Communication Engineering University College of Engineering Nagercoil India Department of Computer Science and Engineering St. Xavier’s Catholic College of Engineering Nagercoil India Department of Computational Intelligence School of Computing SRM Institute of Science and Technology Kattankulathur Chennai India Department of Electronics and Communication Engineering SRM Institute of Science and Technology Kattankulathur Chennai India

ISBN: (纸本)9798331522667

Approximate computing effectively impacts low-power VLSI circuits by reducing circuit overhead. It introduces minimal error in the output, which does not significantly affect the application. This paper proposes an approximate multiplier constructed using 5_3 and 5_2 counters. The proposed 5_2 counter delivers two outputs instead of three, thereby achieving 60% compression. The overhead of the 5_2 counter circuit is reduced, achieving a power delay product (PDP) improvement of 18%. This reduction comes with an addition of an 6% error rate. The newly designed multiplier has less delay, where the Mean error distance (MED) is kept as low as possible. The complexity of the 5_2 counter is also reduced since the counter uses only a full adder and three gates. This is achieved by applying various error optimization mechanisms. The error parameters, (i) Error Distance (ED), and (ii) Mean Error Distance (MED) are analyzed and compared with existing works. The proposed multipliers are involved in image contrast application with better Peak Signal to Noise Ratio (PSNR) value. © 2025 IEEE.

关键词： Delay circuits

来源：评论

学校读者我要写书评

暂无评论

Empowering Collaborative Filtering Using Probabilistic Diffusion Models

Empowering Collaborative Filtering Using Probabilistic Diffu...

引用

International Conference on Information and Communication Technology Convergence (ICTC)

作者： Yu Hou Won-Yong Shin School of Mathematics and Computing (Computational Science and Engineering) Yonsei University Seoul Republic of Korea

ISBN: (数字)9798350364637

ISBN: (纸本)9798350364644

Probabilistic diffusion models, a type of deep gen-erative models, have become one of emerging topics thanks to their state-of-the-art performance in computer vision and natural language processing (NLP) domains. Due to their denoising nature, diffusion models align well with recommender systems, where noisy user-item historical interactions are given. Diffusion models can effectively recover the original interactions from corrupted ones. Nevertheless, there are various challenges in applying diffusion models to recommender systems. To under-stand the challenges and solutions, there should be a reference for researchers and practitioners working on diffusion-based recommender systems. To this end, we first provide a comprehen-sive overview of diffusion-based collaborative filtering techniques, covering both 1) standard (non-sequential) recommendation and 2) sequential recommendation. We first explain the fundamental concepts of collaborative filtering and probabilistic diffusion models, and then summarize their applications to both standard and sequential recommendation settings.

关键词： Reviews Collaborative filtering Noise reduction Diffusion models Probabilistic logic Information filters Natural language processing Noise measurement Recommender systems Standards

来源：评论

学校读者我要写书评

暂无评论

TWO-GRID ALGORITHM OF H^(1)-GALERKIN MIXED FINITE ELEMENT METHODS FOR SEMILINEAR PARABOLIC INTEGRO-DIFFERENTIAL EQUATIONS

引用

Journal of computational mathematics 2022年第5期40卷 667-685页

作者： Tianliang Hou Chunmei Liu Chunlei Dai Luoping Chen Yin Yang School of Mathematics and Statistics Beihua UniversityJilin 132013China College of Science Hunan University of Science and EngineeringYongzhou 425199China School of Mathematics Southwest Jiaotong UniversityChengdu 611756China Hunan Key Laboratory for Computation and Simulation in Science and Engineering Key Laboratory of Intelligent Computing&Information Processing of Ministry of EducationSchool of Mathematics and Computational ScienceXiangtan UniversityXiangtan 411105China

In this paper,we present a two-grid discretization scheme for semilinear parabolic integro-differential equations by H1-Galerkin mixed finite element *** use the lowest order Raviart-Thomas mixed finite elements and continuous linear finite element for spatial discretization,and backward Euler scheme for temporal ***,a priori error estimates and some superclose properties are ***,a two-grid scheme is presented and its convergence is *** the proposed two-grid scheme,the solution of the nonlinear system on a fine grid is reduced to the solution of the nonlinear system on a much coarser grid and the solution of two symmetric and positive definite linear algebraic equations on the fine grid and the resulting solution still maintains optimal ***,a numerical experiment is implemented to verify theoretical results of the proposed *** theoretical and numerical results show that the two-grid method achieves the same convergence property as the one-grid method with the choice h=H^(2).

关键词： Semilinear parabolic integro-differential equations H^(1)-Galerkin mixed finite element method A priori error estimates Two-grid Superclose.

来源：评论

学校读者我要写书评

暂无评论

Multi-Scale Time Series Segmentation Network Based on Eddy Current Testing for Detecting Surface Metal Defects

引用

IEEE/CAA Journal of Automatica Sinica 2025年第3期12卷 528-538页

作者： Xiaorui Li Xiaojuan Ban Haoran Qiao Zhaolin Yuan Hong-Ning Dai Chao Yao Yu Guo Mohammad S.Obaidat George Q.Huang the School of Intelligence Science and Technology University of Science and Technology Beijing the Beijing Advanced Innovation Center for Materials Genome Engineering the Key Laboratory of Intelligent Bionic Unmanned Systems and the Institute of Materials Intelligent Technology Liaoning Academy of Materials IEEE the Department of Computer Science Hong Kong Baptist University the School of Computer and Communication Engineering Key Laboratory of Advanced Materials and Devices for Post-Moore Chips Ministry of Education University of Science and Technology Beijing the Beijing Advanced Innovation Center for Materials Genome Engineering University of Science and Technology Beijing the School of Computer and Communication Engineering University of Science and Technology Beijing the King Abdullah Ⅱ School of Information Technology The University of Jordan the Department of Computational Intelligence the School of Computing SRM University the School of Engineering The Amity University The Hong Kong Polytechnic University

In high-risk industrial environments like nuclear power plants, precise defect identification and localization are essential for maintaining production stability and safety. However, the complexity of such a harsh environment leads to significant variations in the shape and size of the defects. To address this challenge, we propose the multivariate time series segmentation network(MSSN), which adopts a multiscale convolutional network with multi-stage and depth-separable convolutions for efficient feature extraction through variable-length templates. To tackle the classification difficulty caused by structural signal variance, MSSN employs logarithmic normalization to adjust instance distributions. Furthermore, it integrates classification with smoothing loss functions to accurately identify defect segments amid similar structural and defect signal subsequences. Our algorithm evaluated on both the Mackey-Glass dataset and industrial dataset achieves over 95% localization and demonstrates the capture capability on the synthetic dataset. In a nuclear plant's heat transfer tube dataset, it captures 90% of defect instances with75% middle localization F1 score.

关键词： Eddy current testing nondestructive testing semantic segmentation time series analysis

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：