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9th International Conference on Scale Space and Variational Methods in computer Vision, SSVM 2023

作者： Bogensperger, Lea Chambolle, Antonin Effland, Alexander Pock, Thomas Institute of Computer Graphics and Vision Graz University of Technology Graz Austria CEREMADE CNRS & Université Paris-Dauphine PSL Paris France Institute for Applied Mathematics University of Bonn Bonn Germany

ISBN: (纸本)9783031319747

The total generalized variation extends the total variation by incorporating higher-order smoothness. Thus, it can also suffer from similar discretization issues related to isotropy. Inspired by the success of novel discretization schemes of the total variation, there has been recent work to improve the second-order total generalized variation discretization, based on the same design idea. In this work, we propose to extend this to a general discretization scheme based on interpolation filters, for which we prove variational consistency. We then describe how to learn these interpolation filters to optimize the discretization for various imaging applications. We illustrate the performance of the method on a synthetic data set as well as for natural image denoising. © 2023, The Author(s), under exclusive license to Springer Nature Switzerland AG.

关键词： Image denoising

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Inventory Model for Imperfect Deteriorating Items Under Fuzzy Environment 11

Inventory Model for Imperfect Deteriorating Items Under Fuzz...

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11th International Conference on Reliability, Infocom Technologies and Optimization, ICRITO 2024

作者： Mittal, Mandeep Pandey, Jayanti Tripathi Jain, Muskan School of Computer Science Engineering and Technology Bennett University Uttar Pradesh Greater Noida India Amity Institute of Applied Sciences Amity University Uttar Pradesh Department of Mathematics Uttar Pradesh Noida India

ISBN: (纸本)9798350350357

The aim of this study is to introduce the application of fuzzy numbers in an Economic Order Quantity (EOQ) model for defective items under deterioration. In practice, the fuzziness of parameters tends to reduce over time compared to the theoretical assumptions, which justifies the use of fuzzy numbers. The proposed model starts with crisp approach which later involves the fuzzification of inventory parameters, such as demand rate, holding cost, deterioration rate, purchase cost, screening cost, and ordering cost, to account for uncertainty and imprecision. The triangular fuzzy numbers are utilized to represent these parameters, and a fuzzy model is developed accordingly. To defuzzify the model, Yager's ranking index is adopted, and a detailed comparison is made between crisp and general fuzzy solutions. The model is validated through numerical examples and graphical illustrations, followed by a thorough sensitivity analysis to gain a deeper comprehension of how modifications in parameters affect the optimal solution. © 2024 IEEE.

关键词： Deterioration

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Cubature Kalman Fusion Filtering Under Amplify-and-Forward Relays With Randomly Varying Channel Parameters

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IEEE/CAA Journal of Automatica Sinica 2025年第2期12卷 356-368页

作者： Jiaxing Li Zidong Wang Jun Hu Hongli Dong Hongjian Liu the Department of Applied Mathematics Harbin University of Science and Technology IEEE the Department of Computer Science Brunel University London the School of Automation Harbin University of Science and Technology the Artificial Intelligence Energy Research Institute Northeast Petroleum University the Heilongjiang Provincial Key Laboratory of Networking and Intelligent Control Northeast Petroleum University the National Key Laboratory of Continental Shale Oil of China Northeast Petroleum University the Key Laboratory of Advanced Perception and Intelligent Control of High-End Equipment Ministry of Education Anhui Polytechnic University the School of Mathematics and Physics Anhui Polytechnic University

In this paper, the problem of cubature Kalman fusion filtering(CKFF) is addressed for multi-sensor systems under amplify-and-forward(AaF) relays. For the purpose of facilitating data transmission, AaF relays are utilized to regulate signal communication between sensors and filters. Here, the randomly varying channel parameters are represented by a set of stochastic variables whose occurring probabilities are permitted to exhibit bounded uncertainty. Employing the spherical-radial cubature principle, a local filter under AaF relays is initially constructed. This construction ensures and minimizes an upper bound of the filtering error covariance by designing an appropriate filter gain. Subsequently, the local filters are fused through the application of the covariance intersection fusion rule. Furthermore, the uniform boundedness of the filtering error covariance's upper bound is investigated through establishing certain sufficient conditions. The effectiveness of the proposed CKFF scheme is ultimately validated via a simulation experiment concentrating on a three-phase induction machine.

关键词： Amplify-and-forward (AaF) relays covariance intersection fusion cubature Kalman filtering multi-sensor systems uniform boundedness

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Novel Noise Filter Techniques and Dynamic Ensemble Selection for Classification

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Recent Advances in computer Science and Communications 2022年第1期15卷 48-59页

作者： Nguyen, Thi Ngoc A. Nhu, Quynh P. Solanki, Vijender K. School of Applied Mathematics and Informatics Hanoi University of Science and Technology Hanoi Viet Nam CMC Institute of Science and Technology 11 Duy Tan Cau Giay Hanoi Viet Nam Department of Computer Science and Engineering CMR Institute of Technology TS Hyderabad India

Background: Ensemble selection is one of the most researched topics for ensemble learning. Researchers have been attracted to selecting a subset of base classifiers that may perform more helpful than the whole ensemble system classifiers. Dynamic Ensemble Selection (DES) is one of the most effective techniques in classification problems. DES systems select the most appropriate classifiers from the candidate classifier pool. Ensemble models that balance diversity and accuracy in the training process improve performance than the whole classifiers. Objective: In this paper, novel techniques are proposed by combining Noise Filter (NF) and Dynamic Ensemble System (DES) to have better predictive accuracy. In other words, a noise filter and DES make the data cleaner and DES improves the performance of classification. Methods: The proposed NF-DES model, which was demonstrated on twelve datasets, especially has three credit scoring datasets and a performance measure accuracy. Results: The results show that our proposed model is better than other models. Conclusion: The novel noise filer and dynamic ensemble learning with the aim to improve the classification ability are presented. To improve the performance of classification, noise filter with dynamic ensemble learning makes the noise data toward the correct class. Then, novel dynamic ensemble learning chooses the appropriate subset classifiers in the pool of base classifiers. © 2022 Bentham Science Publishers.

关键词： Support vector machines

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Integrated dominating and hit set-inspired unequal clusteringbased data aggregation in wireless sensor networks

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International Journal of Intelligent Computing and Cybernetics 2022年第4期15卷 642-655页

作者： G.Vennira Selvi V.Muthukumaran A.C.Kaladevi S.Satheesh Kumar B.Swapna Department of Computer Science and Engineering Global Institute of Engineering and TechnologyVelloreIndia Department of Mathematics School of Applied SciencesREVA UniversityBangaloreIndia Department of Computer Science and Engineering Sona College of TechnologySalemIndia Department of Computer Science School of Applied SciencesREVA UniversityBangaloreIndia Department of Electronics and Communication Engineering Dr MGR Educational and Research InstituteChennaiIndia

Purpose-In wireless sensor networks,improving the network lifetime is considered as the prime objective that needs to be significantly addressed during data *** the traditional data aggregation techniques,cluster-based dominating set algorithms are identified as more effective in aggregating data through cluster ***,the existing cluster-based dominating set algorithms suffer from a major drawback of energy deficiency when a large number of communicating nodes need to collaborate for transferring the aggregated ***,due to this reason,the energy of each communicating node is gradually decreased and the network lifetime is also *** increase the lifetime of the network,the proposed algorithm uses two sets:Dominating set and hit ***/methodology/approach-The proposed algorithm uses two sets:Dominating set and hit *** dominating set constructs an unequal clustering,and the hit set minimizes the number of communicating nodes by selecting the optimized cluster head for transferring the aggregated data to the base *** simulation results also infer that the proposed optimized unequal clustering algorithm(OUCA)is greater in improving the network lifetime to a maximum amount of 22%than the existing cluster head selection approach considered for ***-In this paper,lifetime of the network is prolonged by constructing an unequal cluster using the dominating set and electing an optimized cluster head using hit *** dominator set chooses the dominator based on the remaining energy and its node degree of each *** optimized cluster head is chosen by the hit set to minimize the number of communicating nodes in the *** proposed algorithm effectively constructs the clusters with a minimum number of communicating nodes using the dominating and hit *** simulation result confirms that the proposed algorithm prolonging the lifetime of the network efficiently when compared with the existing algorithms.

关键词： Unequal clustering Hit set Dominating set Network lifetime

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An Ensemble Based Approach for Sentiment Classification in Asian Regional Language

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computer Systems Science & Engineering 2023年第3期44卷 2457-2468页

作者： Mahesh B.Shelke Jeong Gon Lee Sovan Samanta Sachin N.Deshmukh G.Bhalke Daulappa Rahul B.Mannade Arun Kumar Sivaraman Department of Computer Science and Information Technology Dr.Babasaheb Ambedkar Marathwada UniversityAurangabadMaharashtra431004India Division of Applied Mathematics Wonkwang University460Iksan daeroIksan SiJeonbuk54538Korea Department of Mathematics Tamralipta MahavidyalayaTamlukWest Bengal721636India Department of Electronics and Telecommunication Engineering AISSMSCOEPuneMaharashtra411001India Department of Information Technology Govemment College of EngineeringAurangabadMaharashtra431005India School of Computer Science and Engineering Vellore Institute of TechnologyChennai600127India

In today’s digital world,millions of individuals are linked to one another via the Internet and social *** opens up new avenues for information exchange with *** analysis(SA)has gotten a lot of attention during the last *** analyse the challenges of Sentiment Analysis(SA)in one of the Asian regional languages known as Marathi in this study by providing a benchmark setup in which wefirst produced an annotated dataset composed of Marathi text acquired from microblogging websites such as *** also choose domain experts to manually annotate Marathi microblogging posts with positive,negative,and neutral *** addition,to show the efficient use of the annotated dataset,an ensemble-based model for sentiment analysis was *** contrast to others machine learning classifier,we achieved better performance in terms of accuracy for ensemble classifier with 10-fold cross-validation(cv),outcomes as 97.77%,f-score is 97.89%.

关键词： Sentiment analysis machine learning lexical resource ensemble classifier

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Fuzzy Logic-Based Deep Learning for Human-Machine Interaction and Gesture Recognition in Uncertain and Noisy Environments 1

Fuzzy Logic-Based Deep Learning for Human-Machine Interactio...

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1st International Conference on Advances in computer Science, Electrical, Electronics, and Communication Technologies, CE2CT 2025

作者： Anand, John Thamilarasi, V. Rayal, Ashish Gupta, Himanshu Kumar Jyothi, Kamboji Vishwakarma, Pramatma Greater Noida201310 India Department of Computer Science & Engineering Tamilnadu Salem-16 India School of Applied and Life Sciences Uttaranchal University Department of Mathematics Dehradun248007 India Bipin Tripathi Kumaon Institute of Technology Department of Electrical Engineering Almora Dwarahat India Chaitanya Bharathi Institute of Technology Department of Mathematics AP Proddatur India Lovely Professional University Department of Computer Aplication Punjab 144411 India

ISBN: (纸本)9798331518578

Conventional deep learning methods have considerable hurdles when it comes to Human-Machine Interaction (HMI) and gesture identification in noisy and uncertain situations. A Fuzzy Logic-Based Deep Learning (Fuzzy DL) method is presented in this work to improve the resilience, accuracy, and adaptability of human gesture recognition in a variety of scenarios. We test several algorithms on various datasets, lighting situations, and noise levels, such as CNN, LSTM, Transformer, and Fuzzy DL. The outcomes show that Fuzzy DL functions better than other systems, retaining 91.0% accuracy at high noise levels and reaching 97.5% accuracy under typical circumstances. In comparison to traditional structures, it also shows faster inference times and a lower mean squared error. Its superiority is further demonstrated by comparative analysis on precision, recall, and F1-score. This study presents a robust and noise-resilient solution for real-world HMI applications, including as assistive systems and virtual interfaces. The outcomes indicate that incorporating fuzzy logic with DL substantially enhances gesture recognition in difficult environments. © 2025 IEEE.

关键词： Contrastive Learning

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Prognostic Kalman Filter Based Bayesian Learning Model for Data Accuracy Prediction

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computers, Materials & Continua 2022年第7期72卷 243-259页

作者： S.Karthik Robin Singh Bhadoria Jeong Gon Lee Arun Kumar Sivaraman Sovan Samanta A.Balasundaram Brijesh Kumar Chaurasia S.Ashokkumar Department of ECE College of Engineering and TechnologySRM Institute of Science and TechnologyVadapalaniChennai600026India Department of CSE Birla Institute of Applied Sciences(BIAS)BhimtalUttarakhand263136India Division of Applied Mathematics Wonkwang University460Iksan-DaeroIksan-SiJeonbuk54538Korea School of Computer Science and Engineering Vellore Institute of Technology(VIT)Chennai600127India Department of Mathematics Tamralipta MahavidyalayaWest Bengal721636India School of Computer Science and Engineering Center for Cyber Physical SystemsVellore Institute of Technology(VIT)Chennai600127India Indian Institute of Information Technology(IIIT) LucknowUttar Pradesh226002India Department of Computer Science and Engineering Saveetha School of EngineeringSIMATSChennai602105India

Data is always a crucial issue of concern especially during its prediction and computation in digital *** paper exactly helps in providing efficient learning mechanism for accurate predictability and reducing redundant data *** also discusses the Bayesian analysis that finds the conditional probability of at least two parametric based predictions for the *** paper presents a method for improving the performance of Bayesian classification using the combination of Kalman Filter and *** method is applied on a small dataset just for establishing the fact that the proposed algorithm can reduce the time for computing the clusters from *** proposed Bayesian learning probabilistic model is used to check the statistical noise and other inaccuracies using unknown *** scenario is being implemented using efficient machine learning algorithm to perpetuate the Bayesian probabilistic *** also demonstrates the generative function forKalman-filer based prediction model and its *** paper implements the algorithm using open source platform of Python and efficiently integrates all different modules to piece of code via Common Platform Enumeration(CPE)for Python.

关键词： Bayesian learning model kalman filter machine learning data accuracy prediction

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PARALLEL SCALABILITY OF THREE-LEVEL FROSch PRECONDITIONERS TO 220000 CORES USING THE THETA SUPERcomputer

PARALLEL SCALABILITY OF THREE-LEVEL FROSch PRECONDITIONERS T...

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作者： Heinlein, Alexander Rheinbach, Oliver Rover, Friederike Delft University of Technology Faculty of Electrical Engineering Mathematics & Computer Science Delft Institute of Applied Mathematics Mekelweg 4 Delft2628 CD Netherlands Technische Universität Bergakademie Freiberg Freiberg09596 Germany

The parallel performance of the three-level fast and robust overlapping Schwarz (FROSch) preconditioners is investigated for linear elasticity. The FROSch framework is part of the Trilinos software library and contains a parallel implementation of different preconditioners with energy minimizing coarse spaces of generalized Dryja-Smith-Widlund type. The three-level extension is constructed by a recursive application of the FROSch preconditioner to the coarse problem. In this paper, the additional steps in the implementation in order to apply the FROSch preconditioner recursively are described in detail. Furthermore, it is shown that no explicit geometric information is needed in the recursive application of the preconditioner. In particular, the rigid body modes, including the rotations, can be interpolated on the coarse level without additional geometric information. Parallel results for a three-dimensional linear elasticity problem obtained on the Theta supercomputer (Argonne Leadership Computing Facility, Argonne, IL) using up to 220 000 cores are discussed and compared to results obtained on the SuperMUC-NG supercomputer (Leibniz Supercomputing Centre, Garching, Germany). Notably, it can be observed that a hierarchical communication operation in FROSch related to the coarse operator starts to dominate the computing time on Theta, which has a dragonfly interconnect, for 100 000 message passing interface (MPI) ranks or more. The same operation, however, scales well and stays within the order of a second in all experiments performed on SuperMUC-NG, which uses a fat tree network. Using hybrid MPI/OpenMP parallelization, the onset of the MPI communication problem on Theta can be delayed. Further analysis of the performance of FROSch on large supercomputers with dragonfly interconnects will be necessary. © 2022 Alexander Heinlein, Oliver Rheinbach, and Friederike Röver.

关键词： Supercomputers

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"It’s like an explosion": Cyberwarfare harms for civilian population in Ukraine during the Russian invasion

"It’s like an explosion": Cyberwarfare harms for civilian p...

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2025 CHI Conference on Human Factors in Computing Systems, CHI EA 2025

作者： Kulyk, Oksana Kickbusch, Jari Mayer, Peter IT University of Copenhagen Copenhagen Denmark Department of Mathematics and Computer Science University of Southern Denmark Odense Denmark Institute of Applied Informatics and Formal Description Methods Karlsruhe Institute of Technology Karlsruhe Germany

ISBN: (纸本)9798400713958

Studies on civilian costs of cyberwarfare operations are crucial in understanding how to protect the population in large-scale cyberattacks conducted by state actors. In this preliminary study, we conduct interviews (N=5) focusing on the harms experienced by Ukrainian civilians due to Russian cyberwarfare operations since the start of the full-scale invasion in 2022 as well as mitigation measures for protection of the civil society. The findings include harms such as lack of information, lack of access to essential services, physical harms, anxiety and lack of trust in the government. The study shows that cyberwarfare operations have the potential of causing severe harm to civilians and that there is a need for future studies to be conducted and adopted by institutions in order to develop measures to mitigate, not only in Ukraine but in any countries in risk of such attacks. © 2025 Copyright held by the owner/author(s).

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