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Combined Effect of Concept Drift and Class Imbalance on Model Performance During Stream Classification

Computers, Materials & Continua 2023年第4期75卷 1827-1845页

作者： Abdul Sattar Palli Jafreezal Jaafar Manzoor Ahmed Hashmani Heitor Murilo Gomes Aeshah Alsughayyir Abdul Rehman Gilal Department of Computer and Information Sciences Universiti Teknologi PETRONAS(UTP)Seri Iskandar32610Malaysia Centre for Research in Data Science UTPPerak32610Malaysia High Performance Cloud Computing Centre(HPC3) UTPPerak32610Malaysia School of Engineering and Computer Science Victoria University of WellingtonWellington6012New Zealand AI Institute University of Waikato WellingtonHamilton3240New Zealand Anti-Narcotics Force Ministry of Narcotics ControlIslamabad46000Pakistan College of Computer Science and Engineering Taibah UniversityMadinah42353Saudi Arabia

Every application in a smart city environment like the smart grid,health monitoring, security, and surveillance generates non-stationary datastreams. Due to such nature, the statistical properties of data changes overtime, leading to class imbalance and concept drift issues. Both these issuescause model performance degradation. Most of the current work has beenfocused on developing an ensemble strategy by training a new classifier on thelatest data to resolve the issue. These techniques suffer while training the newclassifier if the data is imbalanced. Also, the class imbalance ratio may changegreatly from one input stream to another, making the problem more *** existing solutions proposed for addressing the combined issue of classimbalance and concept drift are lacking in understating of correlation of oneproblem with the other. This work studies the association between conceptdrift and class imbalance ratio and then demonstrates how changes in classimbalance ratio along with concept drift affect the classifier’s *** analyzed the effect of both the issues on minority and majority classesindividually. To do this, we conducted experiments on benchmark datasetsusing state-of-the-art classifiers especially designed for data stream ***, recall, F1 score, and geometric mean were used to measure theperformance. Our findings show that when both class imbalance and conceptdrift problems occur together the performance can decrease up to 15%. Ourresults also show that the increase in the imbalance ratio can cause a 10% to15% decrease in the precision scores of both minority and majority *** study findings may help in designing intelligent and adaptive solutionsthat can cope with the challenges of non-stationary data streams like conceptdrift and class imbalance.

关键词： Classification data streams class imbalance concept drift class imbalance ratio

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Fully Dynamic Online Selection through Online Contention Resolution Schemes

arXiv

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arXiv 2023年

作者： Avadhanula, Vashist Celli, Andrea Colini-Baldeschi, Riccardo Leonardi, Stefano Russo, Matteo Department of Computing Sciences Bocconi University Milan Italy Core Data Science Meta London United Kingdom Department of Computer Control and Management Engineering Sapienza University Rome Italy

We study fully dynamic online selection problems in an adversarial/stochastic setting that includes Bayesian online selection, prophet inequalities, posted price mechanisms, and stochastic probing problems subject to combinatorial constraints. In the classical "incremental" version of the problem, selected elements remain active until the end of the input sequence. On the other hand, in the fully dynamic version of the problem, elements stay active for a limited time interval, and then leave. This models, for example, the online matching of tasks to workers with task/worker-dependent working times, and sequential posted pricing of perishable goods. A successful approach to online selection problems in the adversarial setting is given by the notion of Online Contention Resolution Scheme (OCRS), that uses a priori information to formulate a linear relaxation of the underlying optimization problem, whose optimal fractional solution is rounded online for any adversarial order of the input sequence. Our main contribution is providing a general method for constructing an OCRS for fully dynamic online selection problems. Then, we show how to employ such OCRS to construct no-regret algorithms in a partial information model with semi-bandit feedback and adversarial inputs. Copyright © 2023, The Authors. All rights reserved.

关键词： Stochastic systems

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Integrated Energy-Efficient Distributed Link Stability Algorithm for UAV Networks

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Computers, Materials & Continua 2024年第11期81卷 2357-2394页

作者： Altaf Hussain Shuaiyong Li Tariq Hussain Razaz Waheeb Attar Farman Ali Ahmed Alhomoud Babar Shah School of Computer Science and Technology Chongqing University of Posts and TelecommunicationsChongqing400065China Key Laboratory of Industrial Internet of Things and Networked Control Ministry of EducationChongqing University of Posts and TelecommunicationsChongqing400065China School of Computer Science and Information Engineering Zhejiang Gongshang UniversityHangzhou310018China Management Department College of Business AdministrationPrincess Nourah bint Abdulrahman UniversityRiyadh11671Saudi Arabia Department of Applied AI School of ConvergenceCollege of Computing and InformaticsSungkyunkwan UniversitySeoul03063Republic of Korea Department of Computer Science College of ScienceNorthern Border UniversityArar91431Saudi Arabia College of Technological Innovation Zayed UniversityDubai19282United Arab Emirates

Ad hoc networks offer promising applications due to their ease of use,installation,and deployment,as they do not require a centralized control *** these networks,nodes function as senders,receivers,and *** such network is the Flying Ad hoc Network(FANET),where nodes operate in three dimensions(3D)using Unmanned Aerial Vehicles(UAVs)that are remotely *** the integration of the Internet of Things(IoT),these nodes form an IoT-enabled network called the Internet of UAVs(IoU).However,the airborne nodes in FANET consume high energy due to their payloads and low-power *** optimal routing approach for communication is essential to address the problem of energy consumption and ensure energy-efficient data transmission in *** paper proposes a novel energy-efficient routing protocol named the Integrated Energy-Efficient Distributed Link Stability Algorithm(IEE-DLSA),featuring a relay mechanism to provide optimal routing with energy efficiency in *** energy efficiency of IEE-DLSA is enhanced using the Red-Black(R-B)tree to ensure the fairness of advanced energy-efficient *** link stability,transmission loss avoidance,delay awareness with defined threshold metrics,and improving the overall performance of the proposed protocol are the core functionalities of *** simulations demonstrate that the proposed protocol performs well compared to traditional FANET routing *** evaluation metrics considered in this study include network delay,packet delivery ratio,network throughput,transmission loss,network stability,and energy consumption.

关键词： FANET UAV internet of UAVs relay mechanism energy consumption routing IEE-DLSA

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WiWm-EP: Wi-Fi CSI-based Wheat Moisture Detection Using Equivalent Permittivity

WiWm-EP: Wi-Fi CSI-based Wheat Moisture Detection Using Equi...

引用

2023 IEEE INFOCOM Conference on Computer Communications Workshops, INFOCOM WKSHPS 2023

作者： Hu, Pengming Yang, Weidong Wang, Xuyu Mao, Shiwen Shen, Erbo Henan University of Technology Henan Key Laboratory of Grain Photoelectric Detection and Control Zhengzhou450001 China College of Information Science and Engineering Henan University of Technology Zhengzhou450001 China Knight Foundation School of Computing and Information Sciences Florida International University FL33199 United States Auburn University Department of Electrical and Computer Engineering AuburnAL36849-5201 United States

ISBN: (纸本)9781665494274

Moisture content is one of the important indexes of food storage security. The existing detection methods are time-consuming and high cost such that it is difficult to realize online moisture detection. In this paper, according to the dielectric properties of wheat, we propose a wheat moisture content detection system with commercial Wi-Fi devices, termed WiWm-EP. First, we introduce the relationship between the moisture content of wheat and its dielectric constant. Then, we establish an equivalent permittivity (EP) model to characterize wheat moisture content, where the EP can be calculated from channel state information (CSI) of the dual antenna model. Besides, we build the fitting function between the EP and the moisture content as the wheat moisture detection model. Finally, we evaluate the performance of the system through different experiments. The average relative error of the detection results of five wheat samples with different moisture contents is less than 3%. © 2023 IEEE.

关键词： Permittivity

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Neighbor Patches Merging Reduces Spatial Redundancy to Accelerate Vision Transformer

SSRN

引用

SSRN 2024年

作者： Jiang, Kai Peng, Peng Lian, Youzao Shao, Weihui Xu, Weisheng Department of Control Science and Engineering College of Electronic and Information Engineering Tongji University No. 4800 Caoan Highway Shanghai201804 China Education Technology and Computing Center Tongji University No. 1239 Siping Road Shanghai200092 China

Vision Transformer models, despite their excellent performance, often suffer from significant computational requirements. The computational complexity of these models is closely tied to the number of tokens processed, and pruning redundant or similar tokens can effectively speed up model inference. In this study, we propose a novel method that focuses on spatial redundancy within images. By evaluating the similarity between patches in pixel spaces, we prune redundant patches prior to inputting them into the Vision Transformer. Notably, our approach does not require any fine-tuning and can significantly enhance the efficiency of Vision Transformer models. Specifically, we demonstrate that our method can accelerate the inference speed of the vit-base-patch16-384 model by 25% while incurring only a minimal accuracy loss of 0.07%. Furthermore, when applied to VideoMAE, our method doubles the throughput with only a 0.29% accuracy loss. These results highlight the effectiveness of our approach in reducing computational requirements while preserving model performance. © 2024, The Authors. All rights reserved.

关键词： Merging

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Path Planning and Information Protection of Mobile Robots Based on Deceptive Reinforcement Learning 23rd

Path Planning and Information Protection of Mobile Robots Ba...

引用

23rd IFToMM China International Conference on Mechanism and Machine Science and engineering, IFToMM CCMMS 2022

作者： Xu, Qingfeng Shi, Yingnan Wang, Junchao Miller, Tim Xu, Hangding Wang, Tianmu Lin, Hongbin Liu, Xin-Jun Nie, Zhenguo Ths State Key Laboratory of Tribology Department of Mechanical Engineering Tsinghua University Beijing100084 China Beijing Key Laboratory of Precision/Ultra-Precision Manufacturing Equipments and Control Tsinghua University Beijing100084 China School of Computing and Information Systems Melbourne School of Engineering University of Melbourne Melbourne3000 Australia School of Mathematics and Information Science Guangzhou University Guangzhou510006 China

ISBN: (纸本)9789811993978

Mobile robots have been widely used in military and other fields. By observing the path of the mobile robot, it is easy to infer the destination of its path. However, in some special situations, the user of the mobile robot does not want to reveal its purpose information, such as carrying out military attacks, sneak reconnaissance missions, etc. In order to protect the mobile robot's path information from being leaked, we combine the reinforcement learning path planning method to propose a computationally efficient deceptive reinforcement learning mobile robot path planning method. The path planned by this method balances the path cost and the target deception weight, making it difficult for observers observing the mobile robot path to predict the real target of the mobile robot, while ensuring a lower path cost for the mobile robot. © 2023, The Author(s), under exclusive license to Springer Nature Singapore Pte Ltd.

关键词： Mobile robots

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Meta-heuristics for Feature Selection and Classification in Diagnostic Breast Cancer

引用

Computers, Materials & Continua 2022年第10期73卷 749-765页

作者： Doaa Sami Khafaga Amel Ali Alhussan El-Sayed M.El-kenawy Ali E.Takieldeen Tarek M.Hassan Ehab A.Hegazy Elsayed Abdel Fattah Eid Abdelhameed Ibrahim Abdelaziz A.Abdelhamid Department of Computer Sciences College of Computer and Information SciencesPrincess Nourah Bint Abdulrahman UniversityRiyadh11671Saudi Arabia Department of Communications and Electronics Delta Higher Institute of Engineering and TechnologyMansoura35111Egypt Faculty of Artificial Intelligence Delta University for Science and TechnologyMansoura35712Egypt Communications and Computers Engineering Department Faculty of EngineeringDelta University for Science and TechnologyInternational Coastal RoadGamasa CityDakhliyaEgypt Faculty of Applied Health Science Technology Delta University for Science and TechnologyMansoura35712Egypt Faculty of Medicine Head of Internal Medicine DepartmentDelta University for Science and TechnologyMansouraEgypt Computer Engineering and Control Systems Department Faculty of EngineeringMansoura University35516MansouraEgypt Department of Computer Science Faculty of Computer and Information SciencesAin Shams University11566CairoEgypt Department of Computer Science College of Computing and Information TechnologyShaqra University11961Saudi Arabia

One of the most common kinds of cancer is breast *** early detection of it may help lower its overall rates of *** this paper,we robustly propose a novel approach for detecting and classifying breast cancer regions in thermal *** proposed approach starts with data preprocessing the input images and segmenting the significant regions of *** addition,to properly train the machine learning models,data augmentation is applied to increase the number of segmented regions using various scaling *** the other hand,to extract the relevant features from the breast cancer cases,a set of deep neural networks(VGGNet,ResNet-50,AlexNet,and GoogLeNet)are *** resulting set of features is processed using the binary dipper throated algorithm to select the most effective features that can realize high classification *** selected features are used to train a neural network to finally classify the thermal images of breast *** achieve accurate classification,the parameters of the employed neural network are optimized using the continuous dipper throated optimization *** results show the effectiveness of the proposed approach in classifying the breast cancer cases when compared to other recent approaches in the ***,several experiments were conducted to compare the performance of the proposed approach with the other *** results of these experiments emphasized the superiority of the proposed approach.

关键词： Breast cancer image segmentation dipper throated optimization feature selection meta-heuristics

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Differentially Private Average Consensus with Improved Accuracy-Privacy Trade-off

arXiv

引用

arXiv 2023年

作者： Wang, Lei Liu, Weijia Guo, Fanghong Qiao, Zixin Wu, Zhengguang College of Control Science and Engineering Zhejiang University Hangzhou China Department of Automation Zhejiang University of Technology Hangzhou China Shanghai Institute of Computing Technology Shanghai China

This paper studies the average consensus problem with differential privacy of initial states, for which it is widely recognized that there is a trade-off between the mean-square computation accuracy and privacy level. Considering the trade-off gap between the average consensus algorithm and the centralized averaging approach with differential privacy, we propose a distributed shuffling mechanism based on the Paillier cryptosystem to generate correlated zero-sum randomness. By randomizing each local privacy-sensitive initial state with an i.i.d. Gaussian noise and the output of the mechanism using Gaussian noises, it is shown that the resulting average consensus algorithm can eliminate the gap in the sense that the accuracy-privacy trade-off of the centralized averaging approach with differential privacy can be almost recovered by appropriately designing the variances of the added noises. We also extend such a design framework with Gaussian noises to the one using Laplace noises, and show that the improved privacy-accuracy trade-off is preserved. © 2023, CC BY-NC-SA.

关键词： Cryptography

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Discrete-Time Stress Matrix-Based Formation control of General Linear Multi-Agent Systems

arXiv

引用

arXiv 2024年

作者： Onuoha, Okechi Kurawa, Suleiman Tang, Zezhi Dong, Yi School of Computing Engineering and Intelligent Systems Ulster University United Kingdom School of Electrical and Electronic Engineering The University of Manchester United Kingdom Department of Automatic Control and Systems Engineering University of Sheffield United Kingdom School of Electronics & Computer Science University of Southampton United Kingdom

This paper considers the distributed leader-follower stress-matrix-based affine formation control problem of discrete-time linear multi-agent systems with static and dynamic leaders. In leader-follower multi-agent formation control, the aim is to drive a set of agents comprising leaders and followers to form any desired geometric pattern and simultaneously execute any required manoeuvre by controlling only a few agents denoted as leaders. Existing works in literature are mostly limited to the cases where the agents’ inter-agent communications are either in the continuous-time settings or the sampled-data cases where the leaders are constrained to constant (or zero) velocities or accelerations. Here, we relax these constraints and study the discrete-time cases where the leaders can have stationary or time-varying velocities. We propose control laws in the study of different situations and provide some sufficient conditions to guarantee the overall system stability. Simulation study is used to demonstrate the efficacy of our proposed control laws. © 2024, CC BY.

关键词： Linear systems

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INTELLIGENT TRACKING AND NAVIGATING MOVING OBJECTS IN A SMART ENVIRONMENT USING IOT NETWORK 1

INTELLIGENT TRACKING AND NAVIGATING MOVING OBJECTS IN A SMAR...

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1st International Conference on Technologies for Smart Green Connected Society 2021, ICTSGS 2021

作者： Parvathi, R. Kumar, T.Ch. Anil Nandhakumar, A. Arshad, Haqqani Singh, Ajith B. Department of Information Technology School of Computing Science Hindustan Institute of Technology and Science Padur Chennai India Department of Mechanical Engineering Vignan's Foundation for Science Technology and Research Vadlamudi Dt. Andhra Pradesh Guntur India Department of Electronics and Communication Engineering Dhaanish Ahmed Institute of Technology Chennai India Department of Mechanical Engineering Yanbu Industrial Collge Yanbu Western Region Saudi Arabia Department- Instrumentation and Control Engineering Sri Krishna College of Technology Coimbatore India

ISBN: (纸本)9781607685395

Internet of things (IoT) constitutes the combinations of sensors, controllers, actuators, connectivity. Tracking and navigating moving objects are crucial tasks for security as well as a secure and smart environment. By using the sensory data, location of objects can be identified then that sensory data will be transferred to controllers for the further processes. One pivot role of the system is to identify the trajectory and location of the object using the speed, velocity, acceleration, maps etc and this can be done by machine learning programs. Analyzing service required, prediction of the trajectory and real-world knowledge of maps or locations, To avoid the loop-carry dependency, service request parameters are dynamically changed to locate relevant virtual objects. In order to track moving items, this study provides an architecture based on IoT self-aware environment technology that facilitates the tracking and allocation of relevant virtual objects. © The Electrochemical Society

关键词： IoT loop-carry dependency machine learning object identification self-aware environment sensory data

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