检索结果-内蒙古大学图书馆

41st International Conference on Machine Learning, ICML 2024

作者： Gangrade, Aditya Gopalan, Aditya Saligrama, Venkatesh Scott, Clayton Department of Electrical Computer Engineering Boston University United States Department of Electrical Engineering and Computer Science University of Michigan United States Department of Electrical Communication Engineering Indian Institute of Science India

While the recent literature has seen a surge in the study of constrained bandit problems, all existing methods for these begin by assuming the feasibility of the underlying problem. We initiate the study of testing such feasibility assumptions, and in particular address the problem in the linear bandit setting, thus characterising the costs of feasibility testing for an unknown linear program using bandit feedback. Concretely, we test if ∃x : Ax ≥ 0 for an unknown A ∈ m×d, by playing a sequence of actions xt ∈ d, and observing Axt + noise in response. By identifying the hypothesis as determining the sign of the value of a minimax game, we construct a novel test based on low-regret algorithms and a nonasymptotic law of iterated logarithms. We prove that this test is reliable, and adapts to the 'signal level,' Γ, of any instance, with mean sample costs scaling as Õ(d2/Γ2). We complement this by a minimax lower bound of Ω(d/Γ2) for sample costs of reliable tests, dominating prior asymptotic lower bounds by capturing the dependence on d, and thus elucidating a basic insight missing in the extant literature on such problems. Copyright 2024 by the author(s)

关键词： Software testing

来源：评论

学校读者我要写书评

暂无评论

A machine learning approach for accelerated design of magnesium alloys. Part A:Alloy data and property space

引用

Journal of Magnesium and Alloys 2023年第11期11卷 3620-3633页

作者： M.Ghorbani M.Boley P.N.H.Nakashima N.Birbilis Department of Materials Science and Engineering Monash UniversityVIC3800Australia Faculty of Information Technology Monash UniversityVIC3800Australia College of Engineering and Computer Science Australian National UniversityACT2601Australia Faculty of Engineering Science and the Built EnvironmentDeakin UniversityVIC3125Australia

Typically, magnesium alloys have been designed using a so-called hill-climbing approach, with rather incremental advances over the past century. Iterative and incremental alloy design is slow and expensive, but more importantly it does not harness all the data that exists in the field. In this work, a new approach is proposed that utilises data science and provides a detailed understanding of the data that exists in the field of Mg-alloy design to date. In this approach, first a consolidated alloy database that incorporates 916 datapoints was developed from the literature and experimental work. To analyse the characteristics of the database, alloying and thermomechanical processing effects on mechanical properties were explored via composition-process-property matrices. An unsupervised machine learning(ML) method of clustering was also implemented, using unlabelled data, with the aim of revealing potentially useful information for an alloy representation space of low dimensionality. In addition, the alloy database was correlated to thermodynamically stable secondary phases to further understand the relationships between microstructure and mechanical properties. This work not only introduces an invaluable open-source database, but it also provides, for the first-time data, insights that enable future accelerated digital Mg-alloy design.

关键词： Magnesium Alloy design Mg-alloy database Data analysis Data visualisation Unsupervised machine learning

来源：评论

学校读者我要写书评

暂无评论

Impact of atmospheric propagation impairments on submillimetre airborne radar performance

引用

International Journal of Simulation and Process Modelling 2024年第4期21卷 305-320页

作者： Teka, Bedilu Ababu Gelmecha, Demissie Jobir Singh, Ram Sewak Shakya, Rajeev Kumar Paikaray, Bijay Kumar Mishra, Satyasis Department of Electronics and Communication Engineering Adama Science and Technology University Adama Ethiopia Centre for Data Science Department of Computer Science and Engineering Siksha ‘O’ Anusandhan (Deemed to be) University Odisha India Department of Electronics and Communication Engineering Centurion University of Technology and Management Odisha India

This research presents the performance of submillimetre airborne radar systems in the presence of various atmospheric propagation impairments. The study aims to assess the effects of environmental factors such as rain, fog, clouds, atmospheric turbulence, and atmospheric attenuation on radar performance using computational methods such as Friis-transmission, ecological factors and radiation model. The simulated results have shown that the free space path loss significantly increases with distance and frequency and highlights the importance of accounting for phase differences in radar performance. The rise in the Earth’s potential leads to greater angles of incidence and refraction, lowers reflection coefficients, and enhances the output signal-to-noise ratio. This underscores the critical need to optimise transmit power. This research has been provided to extract valuable insights into the performance dynamics of submillimetre airborne radar systems amidst atmospheric propagation impairments, providing essential considerations for radar system design and operation in critical environments. Copyright © 2024 Inderscience Enterprises Ltd.

关键词： airborne radar systems atmospheric attenuation atmospheric propagation impairments atmospheric turbulence environmental factors

来源：评论

学校读者我要写书评

暂无评论

Identifying Hoaxes in Fake Spotter using XG Boost Machine Learning based Classification Method 4

Identifying Hoaxes in Fake Spotter using XG Boost Machine Le...

引用

4th International Conference on Ubiquitous Computing and Intelligent Information Systems, ICUIS 2024

作者： Chitti, Sridevi Rinku, Dhruva R. Juluru, Tarun Kumar Rao, P. Ramchandar Gouthami, Shiramshetty Kakatiya Institute of Technology and Science Department of Electronics and Communication Engineering Warangal India Cvr College of Engineering Department of Electronics and Communication Engineering Hyderabad India Jayamukhi Institute of Technological Sciences Department of Computer Science Engineering Warangal India

ISBN: (纸本)9798331529635

Social media has greatly streamlined communication in recent years which uses network, shares information, and keep up with current events. Many posts on social media are questionable and meant to deceive. There is a lot of fake news everywhere and online fake news could cause serious societal issues. It is crucial for us to identify false and misleading internet content. Technically, it is hard for us to differentiate between real and fake information. The development and sharing of content have been made easier by social media platforms, leading to a significant amount that must be examined. Information on the internet is diverse making this process difficult. In order to assess the reliability and purpose of statements, humans and machines must work together. Manually identifying fake news is challenging, and it can only be done when the individual doing the identification has extensive understanding of news. Therefore, there is a need for machine learning classifiers that can identify the false news automatically. The main goal is to measure the accuracy of deceptive detection utilizing various machine learning algorithms. Several machine learning (ML) techniques, such as Decision Trees (DT), Random Forest (RF), Logistic Regression (LR), Passive Aggressive Classifier (PAC), Extra Trees Classifier (ETC) and boosting algorithms were employed on datasets to determine if the content is authentic or untrue in order to identify hoaxes on different platforms for online networking sites. © 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

Design, Implementation and Analysis of HIBRI Cipher on IoT Platforms

引用

Journal of The Institution of Engineers (India): Series B 2024年第6期105卷 1-13页

作者： Nagesh, H.R. Poojari, Asmita Kumar, V. G. Kiran Canara Engineering College Benjanapadavu Bantwal Taluk Karnataka Mangaluru574219 India Department of Computer Science and Engineering NMAM Institute of Technology Karnataka Nitte 574110 India Department of Electronics and Communication Engineering A J Institute Engineering and Technology Karnataka Mangaluru575006 India

With the exponential growth of the Internet of Things through time there has been an enormous increase in the usage of tiny devices and information being exchanged, between low resource devices like sensors, PDA’s and the high-end devices like servers or clouds. This opens up several challenges in securing the information being exchanged. Consequently, there is a greater demand for designing encryption algorithms, particularly for devices with limited resources. This paper introduces the HIBRI cipher, a combination of the HIGHT and the BRIGHT cipher implemented in software as well as hardware. The proposed cipher is evaluated for randomness test, strict avalanche criteria, key sensitivity tests to assess the cipher’s security while memory utilization, energy consumption, execution time and throughput are analyzed by implementing in Arduino Nano based on the Atmega328 microcontroller. The NIST tests for key generation yielded P ≥ 0.01 which proves that the proposed key generation scheme generated truly random numbers while the hardware implementation shows that the comparison results for code size, RAM and execution size yielded better results than the implementations that are cutting-edge. © The Institution of Engineers (India) 2024. Springer Nature or its licensor (e.g. a society or other partner) holds exclusive rights to this article under a publishing agreement with the author(s) or other rightsholder(s);author self-archiving of the accepted manuscript version of this article is solely governed by the terms of such publishing agreement and applicable law.

关键词： Random access storage

来源：评论

学校读者我要写书评

暂无评论

Highly efficient ternary organic solar cells with excellent open-circuit voltage and fill factor via precisely tuning molecular stacking and morphology

引用

science China Chemistry 2024年第3期67卷 963-972页

作者： Dinghong Sun Zhenyu Chen Jianfeng Zhang Wei Song Jingyu Shi Jintao Zhu Yuanyuan Meng Fei Jin Shuncheng Yang Ziyi Ge Faculty of Electrical Engineering and Computer Science Ningbo UniversityNingbo 315211China Faculty of Material Science and Chemical Engineering Ningbo UniversityNingbo 315211China Zhejiang Provincial Engineering Research Center of Energy Optoelectronic Materials and Devices Ningbo Institute of Materials Technology&EngineeringChinese Academy of SciencesNingbo 315201China Center of Materials Science and Optoelectronics Engineering University of Chinese Academy of Sciences Beijing 100049China Department of Chemical and Environmental Engineering University of Nottingham NingboNingbo 315100China

The micro-morphology and molecular stacking play a key role in determining the charge transport process and nonradiative energy loss, thus impacting the performances of organic solar cells(OSCs). To address this issue, a non-fullerene acceptor PhC6-IC-F with alkylbenzene side-chain, possessing optimized molecular stacking, complementary absorption spectra and forming a cascade energy level alignment in the PM6:BTP-eC9 blend, is introduced as guest acceptor to improve efficiency of ternary OSCs. The bulky phenyl in the side-chain can regulate crystallinity and optimizing phase separation between receptors in ternary blend films, resulting in the optimal phase separations in the ternary films. As a result, high efficiencies of 18.33% as photovoltaic layer are obtained for PhC6-IC-F-based ternary devices with excellent fill factor(FF) of 78.92%. Impressively, the ternary system produces a significantly improved open circuit voltage(V_(oc)) of 0.857 V compared with the binary device,contributing to the reduced density of trap states and suppressed non-radiative recombination result in lower energy loss. This work demonstrates an effective approach for adjusting the aggregation, molecular packing and fine phase separation morphology to increase V_(oc) and FF, paving the way toward high-efficiency OSCs.

关键词： alkylbenzene side-chain morphology regulation ternary blends organic solar cells

来源：评论

学校读者我要写书评

暂无评论

A Comparative Study of Random Forest, SVM, and Naive Bayes for Sentiment Analysis Optimization 2

A Comparative Study of Random Forest, SVM, and Naive Bayes f...

引用

2nd IEEE International Conference on Innovations in High-Speed communication and Signal Processing, IHCSP 2024

作者： Pandey, Ranu Patidar, Praveen Kumar Verma, Pushpalata Khan, Gousia Hazra Anjum Harne, Sachin Tiwari, Rovin Shri Rawatpura Sarkar University Department of Computer Science and Engineering Raipur India Parul University Parul Institute of Technology Department of Computer Science and Engineering Vadodara India Bhilai Institute of Technology Department of Computer Science & Engineering Raipur India Government Engineering College Department of Computer Science and Engineering Raipur India Gh Raisoni College of Engineering Department of Computer Science and Engineering Nagpur India Rgpv Department of Electronics and Communication Engineering Bhopal India

ISBN: (纸本)9798350368949

This study presents an in-depth evaluation of sentiment analysis models applied to a US Twitter dataset. The performance of machine learning models considered in this study are Random Forest, Support Vector Machine (SVM) in both optimized and non-optimized forms, Multinomial Naive Bayes, AdaBoost, and Gaussian Naive Bayes. In this work TFIDF is utilized for vectoize text. For machine learning algorithms the Random Forest and SVM achieve training accuracies of around 99%, but showing the lower test accuracies which denotes the overfitting condition. Other models such as multinomial Naive Bayes and AdaBoost showed consistent performance across both training and testing data. Gaussian Naive Bayes' underperforms in the test data due to the models sensitivity to the data properties. Highest accuracy is achieved using the optimized support vector machine that represents the importance of hyperparameter tuning on model generalization. © 2024 IEEE.

关键词： Emotion Recognition

来源：评论

学校读者我要写书评

暂无评论

Game-Theoretic Approach for Integrated Sensing and Computation Offloading in Vehicular Edge Networks: A Utility Maximization Design

引用

IEEE Internet of Things Journal 2025年第13期12卷 23694-23708页

作者： Wang, Lina Wu, Weihong Dai, Minghui Zh, Haijun University of Science and Technology Beijing department of Communication Engineering China Donghua University School of Computer Science and Technology Shanghai China Beijing Engineering and Technology Research Center for Convergence Networks and Ubiquitous Services University of Science and Technology Beijing Beijing China

In recent years, with the rapid development of the Internet of Vehicles (IoVs) and the widespread application of integrated sensing and communication (ISAC) in the IoVs, the integrated sensing and computation offloading in vehicular edge networks has attracted widespread attention from academia and industry. Due to the generation of a large number of latencysensitive tasks from vehicles’ real-time sensing of road conditions, coupled with the rise of other computing-intensive vehicle applications, the current computing capabilities of the onboard devices cannot meet the diverse demands of vehicular users. Therefore, it is necessary to combine the computing resources around the vehicle to complete computing tasks. With the goal of maximizing the difference between gain and consumption, this paper studies the integrated sensing and computation offloading involving roadside units (RSUs) and vehicle platoon in vehicular edge networks. Specifically, we first consider that mobile vehicles can simultaneously offload computing tasks to RSU and vehicle platoon via non-orthogonal multiple access (NOMA) technology, and construct a multi-objective optimization problem with the goal of maximizing the utility of the three parties. Then, we construct a game model among ISAC vehicle, RSU, and vehicle platoon based on the Stackelberg game. By seeking the equilibrium of the game, the optimal offloading and pricing strategy are derived, while the utility of the three parties is maximized. Finally, the simulation results show that the proposed scheme is superior to other traditional schemes, and each party in the game obtains its optimal strategy. © 2014 IEEE.

关键词： Multiobjective optimization

来源：评论

学校读者我要写书评

暂无评论

Spatial Attention Integrated EfficientNet Architecture for Breast Cancer Classification with Explainable AI

引用

computers, Materials & Continua 2024年第9期80卷 5029-5045页

作者： Sannasi Chakravarthy Bharanidharan Nagarajan Surbhi Bhatia Khan Vinoth Kumar Venkatesan Mahesh Thyluru Ramakrishna Ahlam AlMusharraf Khursheed Aurungzeb Department of Electronics and Communication Engineering Bannari Amman Institute of TechnologySathyamangalam638402India School of Computer Science Engineering and Information Systems(SCORE) Vellore Institute of TechnologyVellore632014India School of Science Engineering and EnvironmentUniversity of SalfordManchesterM54WTUK Department of Computer Science&Engineering Faculty of Engineering and TechnologyJAIN(Deemed-to-be University)Bengaluru562112India Department of Management College of Business AdministrationPrincess Nourah Bint Abdulrahman UniversityP.O.Box 84428Riyadh11671Saudi Arabia Department of Computer Engineering College of Computer and Information SciencesKing Saud UniversityP.O.Box 51178Riyadh11543Saudi Arabia Adjunct Research Faculty Centre for Research Impact&OutcomeChitkara UniversityRajpura140401India

Breast cancer is a type of cancer responsible for higher mortality rates among *** cruelty of breast cancer always requires a promising approach for its earlier *** light of this,the proposed research leverages the representation ability of pretrained EfficientNet-B0 model and the classification ability of the XGBoost model for the binary classification of breast *** addition,the above transfer learning model is modified in such a way that it will focus more on tumor cells in the input ***,the work proposed an EfficientNet-B0 having a Spatial Attention Layer with XGBoost(ESA-XGBNet)for binary classification of *** this,the work is trained,tested,and validated using original and augmented mammogram images of three public datasets namely CBIS-DDSM,INbreast,and MIAS *** accuracy of 97.585%(CBISDDSM),98.255%(INbreast),and 98.91%(MIAS)is obtained using the proposed ESA-XGBNet architecture as compared with the existing ***,the decision-making of the proposed ESA-XGBNet architecture is visualized and validated using the Attention Guided GradCAM-based Explainable AI technique.

关键词： EfficientNet mammograms breast cancer Explainable AI deep-learning transfer learning

来源：评论

学校读者我要写书评

暂无评论

ML Based Intrusion Detection Scheme for various types of attacks in a WSN using C4.5 and CART classifiers

引用

Materials Today: Proceedings 2023年 80卷 3769-3776页

作者： Gite, Pratik Chouhan, Kuldeep Murali Krishna, K. Kumar Nayak, Chinmaya Soni, Mukesh Shrivastava, Amit Department of Computer Science and Engineering IPSA-IES Indore AB Road MP Indore India Department of Computer Science and Engineering I.T.S Engineering College Greater Noida India Department of Electronics and Communication Engineering Vignan's Institute of Information Technology Duvvada Andhra Pradesh Visakhapatnam India Faculty of Emerging Technology Sri Sri University Odisha751001 India Department of Computer Science & Engineering Jagran Lakecity University Bhopal India Department of Computer Science Engineering Swami Vivekanand College of Engineering Khandwa Road Near Tolnaka Vivekanand Knowledge City Indore India

A key component for preserving a WSN's integrity is designing an intrusion detection system (IDS). This article covers several sorts of security threats that may occur in a WSN. It proposes a detection of malicious nodes in a WSN. This system identifies four common assaults (i.e., black hole, wormhole, gray hole, and DDoS attacks) and is based on a Base Station machine learning (ML) algorithm (BS). The suggested ML algorithm continually analyzes data patterns from each node. Based on this technique, BS recognizes the network's harmful behavior and provides notifications to neighbor nodes to prevent attacker. First, the various assaults are examined and their characteristics are derived in terms of network parameters. Furthermore, the gathered pattern trains an ML algorithm. Then, the attacker node is effectively and properly classified within the BS. The NS2 simulator simulated the needed secure WSN. The experimental findings revealed excellent accuracy of the suggested method for attack detection. This precision can enhance network performance in terms of energy usage and packet delivery (PDR). © 2021

关键词： Base stations

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：