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αSetup-PCTL:An Adaptive Setup-Based Two-Level Preconditioner for Sequence of Linear Systems of Three-Temperature Energy Equations

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Communications in computational Physics 2022年第10期32卷 1287-1309页

作者： Silu Huang Xiaoqiang Yue Xiaowen Xu Laboratory of Computational Physics Institute of Applied Physics and ComputationalMathematicsBeijing 100088China National Center for Applied Mathematics in Hunan Key Laboratory of Intelligent Computing and Information Processing of Ministry of EducationHunan Key Laboratory for Computation and Simulation in Science and EngineeringXiangtan UniversityXiangtan 411105China

The iterative solution of the sequence of linear systems arising from threetemperature(3-T)energy equations is an essential component in the numerical simulation of radiative hydrodynamic(RHD)***,due to the complicated application features of the RHD problems,solving 3-T linear systems with classical preconditioned iterative techniques is *** address this difficulty,a physicalvariable based coarsening two-level(PCTL)preconditioner has been proposed by dividing the fully coupled system into four individual easier-to-solve *** its nearly optimal complexity and robustness,the PCTL algorithm suffers from poor efficiency because of the overhead associatedwith the construction of setup phase and the solution of ***,the PCTL algorithm employs a fixed strategy for solving the sequence of 3-T linear systems,which completely ignores the dynamically and slowly changing features of these linear *** address these problems and to efficiently solve the sequence of 3-T linear systems,we propose an adaptive two-level preconditioner based on the PCTL algorithm,referred to as α*** adaptive strategies of the αSetup-PCTL algorithm are inspired by those of αSetup-AMG algorithm,which is an adaptive-setup-based AMG solver for sequence of sparse linear *** proposed αSetup-PCTL algorithm could adaptively employ the appropriate strategies for each linear system,and thus increase the overall *** results demonstrate that,for 36 linear systems,the αSetup-PCTL algorithm achieves an average speedup of 2.2,and a maximum speedup of 4.2 when compared to the PCTL algorithm.

关键词： Sequence of linear systems sparse linear solver preconditioning methods radiation hydrodynamics simulation

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Machine Learning based Secure Data Transmission and Improvement in MANET through Internet of Things (IoT)

Machine Learning based Secure Data Transmission and Improvem...

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2023 International Conference on Intelligent Data Communication Technologies and Internet of Things, IDCIoT 2023

作者： Dinesh, G. Pawar, Yogesh Shivaji Dinshi, P. Soundararajan, S. Husain, S. Syed Reddy, Ch. Venkata Krishna Srm Institute of Science and Technology School of Computing Department of Computational Intelligence Tamil Nadu Chennai India Bhabha University Department of Electrical Engineering Madhya Pradesh Bhopal India Koneru Lakshmaiah Educational Foundation Department of Computer Science Engineering Andhra Pradesh Guntur India Velammal Institute of Technology Department of Computer Science and Engineering Tamil Nadu Chennai India K. Ramakrishnan College of Engineering Department of Electronics and Communication Engineering Tamil Nadu Tiruchirappalli India Chaitanya Bharathi Institute of Technology Department of Electrical and Electronics Engineering Telangana Hyderabad India

ISBN: (纸本)9781665474511

The term MANET stands for Mobile Ad hoc Network. MANET is a structure of wireless communication network that is combined with various nodes that are movable in various directions in the network. They are accompanied with the absence of infrastructure which helps the nodes to interconnect with the neighboring one in a random fashion. They are highly dynamic in nature. The internet of things device have the ability to communicate with the various heterogeneous networks. These IoT nodes helps to communicate with each other without the need of infrastructure. The cloud helps to store the data and tends to transmit through the nodes in the network. The secure data transmission includes the intrusion detection system, neglecting malicious attacks and selfish nodes in the network. The secure data transmission system without any constraints helps in the improvement of overall efficiency of the system. This is done through the machine learning accompanied with genetic algorithm. These biologically inspired algorithms helps to obtain exact optimum solutions helps to provide secure data transmission. © 2023 IEEE.

关键词： Internet of things

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Hybrid Optimization Based Long Short-Term Memory for Android Malware Detection

Hybrid Optimization Based Long Short-Term Memory for Android...

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2023 International Conference on Evolutionary Algorithms and Soft computing Techniques, EASCT 2023

作者： Lande, Jayapal Maheswari, M. Kamali, S.M. Dineshkumar, R. Priyanka, M.S. Sr University School of Computer Science & Artificial Intelligence Warangal India Srm Institue of Science and Technology School of Computing Department of Computational Intelligence Chennai India Annapoorana Engineering College Department of Electrical and Electronics Engineering Salem India Saveetha School of Engineering Department of Ece Sriperumbudur Thandalam India Nitte Meenakshi Institute of Technology Department of Ai and Ml Yelahanka Bengaluru India

ISBN: (纸本)9798350313413

Malware detection is process of detecting the suspicious files and activities, that can classify as benign and malicious depends on different characters like capability of infection, structure of malware and speed rate. In this paper, proposed a Particle Swarm Optimization and Ant Colony Optimization (HPSALO) based Long Short-Term Memory (LSTM) model for malware detection and classification. The combination of these two algorithms that leads to the balance between exploration and exploitation. The dataset utilized for the research is DREBIN dataset and process of data cleaning is performed by NumPy library. The feature selection is performed by combination of hybrid PSALO algorithms and selected features are given to Long Short-Term Memory (LSTM) classifier that classifies as benign and malware files. The performance of proposed method is estimated by performance metrics of accuracy, precision, recall and f1-score. The proposed method attained accuracy of 99.38%, precision of 99.30%, recall of 99.08% and f1-score of 99.42% which is comparatively higher than other existing methods like Whale Optimization Algorithm-LSTM (WOA-LSTM), Cat Swarm Optimization-LSTM (CSO-LSTM), Particle Swarm Optimization-LSTM and Ant Lion Optimization-LSTM. © 2023 IEEE.

关键词： Ant Lion Optimization Long Short-Term Memory Malware Detection NumPy and Particle Swarm Optimization

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Speech Emotion Recognition: A Brief Review of Multi-modal Multi-task Learning Approaches

Speech Emotion Recognition: A Brief Review of Multi-modal Mu...

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International Conference on Advanced engineering Theory and Applications, AETA 2022

作者： Pham, Nhat Truong Tran, Anh-Tuan Pham, Bich Ngoc Hong Dang-Ngoc, Hanh Nguyen, Sy Dzung Dang, Duc Ngoc Minh Division of Computational Mechatronics Institute for Computational Science Ton Duc Thang University Ho Chi Minh City Viet Nam Faculty of Electrical and Electronics Engineering Ton Duc Thang University Ho Chi Minh City Viet Nam Faculty of Information Technology Ho Chi Minh City Open University Ho Chi Minh City Viet Nam Department of Telecommunications Engineering Ho Chi Minh City University of Technology Ho Chi Minh City Viet Nam Laboratory for Computational Mechatronics Institute for Computational Science and Artificial Intelligence Van Lang University Ho Chi Minh City Viet Nam Faculty of Mechanical–Electrical and Computer Engineering Van Lang University Ho Chi Minh City Viet Nam Computing Fundamental Department FPT University Ho Chi Minh Viet Nam

ISBN: (纸本)9789819987023

Speech emotion recognition (SER) has become an attention-grabbing topic in recent years thanks to the development of deep learning in the field of speech processing. However, it is difficult to recognize an accurate emotional state from only speech signals. Therefore, researchers have investigated multi-modalities such as speech, visual, and text inputs to improve the emotional recognition rate of speech. In addition, to enhance the generalized deep learning models for SER, multi-task learning (MTL) strategies have also been applied in the past decade. In this paper, a brief and comprehensive review of multi-modal multi-task learning (3MTL) approaches for recognizing emotional states from speech signals is presented, including multi-modal SER, multi-task learning SER, and multi-modal multi-task learning SER. This paper also discusses about some problems that still need to be solved in 3MTL SER and gives some suggestions for the future. © The Author(s), under exclusive license to Springer Nature Singapore Pte Ltd. 2024.

关键词： Emotion Recognition

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Effect on Public Health Due to Environment Condition- Role of IoT 14

Effect on Public Health Due to Environment Condition- Role o...

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14th International Conference on computing Communication and Networking Technologies, ICCCNT 2023

作者： Joshi, Kapil Rastogi, Ritesh Singh, Anupam Kaushik, Vishal Anandaram, Harishchander Kumar, Anil Uttaranchal University Uttaranchal Institute of Technology Department of Cse Dehradun India Niet Department of Computer Science & Engineering Greater Noida India Graphic Era Hill University Department of Computer Science and Engineering Uttarakhand Dehradun India Upes School of Computer Science Dehradun India Amrita Vishwa Vidyapeetham Centre for Computational Engineering and Networking Tamil Nadu Coimbatore India Dit University School of Computing Dehradun India

ISBN: (纸本)9798350335095

The biggest environmental issues are poor air quality, polluted water, contaminated food, polluted transportation, and radiation contamination. In order to ensure sustainable growth and preserve a stable social structure, adequate monitoring is required. With the development of contemporary sensors and advancements in the internet of things (IoT), environmental surveillance has evolved into a smart environment monitoring (SEM) platform in recent decades. The emergence and widespread use of Internet of Things (IoT) devices and its supporting technologies are the driving forces behind the growth of ubiquitous systems, as shown in this study. This study analysisIoT has great promise in the environment, health, & safety (EHS) industries that involve high risk. The social health can be improved with the use of technology that manages and organises information about individuals. IoT may actually serve as the foundation for a society that is health. In this study, we discussed how the Internet of Things (IoT) may benefit individuals and how it can be used for public health. and also highlight IoT-related problems and a suggested remedy. © 2023 IEEE.

关键词： Internet of things

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Trust-aware Routing Protocol using Modified Sand Cat Swarm Optimization in Iot-Based WSN

Trust-aware Routing Protocol using Modified Sand Cat Swarm O...

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2023 International Conference on Evolutionary Algorithms and Soft computing Techniques, EASCT 2023

作者： Yamsani, Nagendar Anitha, D. Mahaboob John, Y.M. Jamuna Rani, M. Sowmya, M. Sr University School of Computer Science and Artificial Intelligence Warangal India Srm Institute of Science and Technology School of Computing Department of Computational Intelligence Kattankulathur India Mahendra College of Engineering Ece Department Salem India Sona College of Technology Department of Ece Salem India Nitte Meenakshi Institute of Technology Department of Ai and Ds Bengaluru India

ISBN: (纸本)9798350313413

The trust-aware secure route selection leverages trust-based metrics for evaluating the credibility of nodes and routes which enables the selection of the most reliable and secure paths for data transmission. Secure routing is of major significance for preventing wireless devices from other threats and effective characteristics in WSN attain an efficient secure routing selection. This research proposed the trust secure route selection utilizing Modified Sand Cat Swarm Optimization (TSRS-MSCSO) for efficient route selection. Initially, the secure nodes are identified by using energy and delay of the fitness function. After identifying secure nodes, the route selection is performed through the Modified Sand Cat Swarm Optimization algorithm. The performance of the proposed model is estimated by metrics like packet delivery ratio, throughput, delay and energy consumption with various nodes of 50, 100, 150, and 200. The proposed model attained a high packet delivery ratio of 98.8%, less delay of 3s, high throughput of 96.27%, and less energy consumption of 2.14J for 50 nodes which ensures better performance than other existing methods like Dynamic Deep Neural Network-based Particle Swarm Optimization (DDNN-PSO), Chaotic Bumble Bees Mating Optimization- Trust Sensing Model (CBBMOR-TSM) and fuzzy TOPSIS based hybrid Jarratt Butterfly Optimization (FTOPSIS-HJBO) models. © 2023 IEEE.

关键词： Energy Efficiency Internet of Things Route Selection Sand Cat Swarm Optimization Secure nodes Throughput Wireless Sensor Networks

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An Optimization Method for Renewable Energy and Energy Storage Capacity Allocation Based on Temporal Production Simulation 7

An Optimization Method for Renewable Energy and Energy Stora...

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7th IEEE Conference on Energy Internet and Energy System Integration, EI2 2023

作者： Du, Hongbo Li, Chi Chen, Liang Zhang, Jinping Kou, Caixia College of Sciences Beijing University of Posts and Telecommunications Beijing China National Key Laboratory of Renewable Energy Grid-Integration China Electric Power Research Institute Beijing China Institute of Computational Mathematics and Scientific Engineering Computing Academy of Mathematics and Systems Science Chinese Academy of Sciences Beijing China

ISBN: (纸本)9798350345094

With the rapid expansion of large-scale renewable energy bases in China, optimizing the allocation of renewable energy and energy storage capacity is crucial for improving system efficiency. In this paper, a joint optimal configuration method of wind-photovoltaic-energy storage capacity based on time series production simulation is proposed for renewable energy transmission base. Its aim is to minimize the total investment cost of the system under certain constraints about the proportion of renewable energy power generation, renewable energy utilization rate, conventional thermal power operation, energy storage power station operation, ultra-high voltage direct current (UHVDC) regulation and power transmission. To handle the nonlinear constraints, linearization is achieved by introducing integer variables. For the complex operation constraints of conventional thermal power and UHVDC channel, a simplified modeling method of start-stop cycle and adjustment cycle is proposed, which can effectively reduce the number of integer variables and improve the solving efficiency. The effectiveness of the proposed method is tested on the data of a renewable energy base in Northwest China. © 2023 IEEE.

关键词： Energy utilization

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JARVIS-Leaderboard:a large scale benchmark of materials design methods

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npj computational Materials 2024年第1期10卷 2280-2296页

作者： Kamal Choudhary Daniel Wines Kangming Li Kevin F.Garrity Vishu Gupta Aldo H.Romero Jaron T.Krogel Kayahan Saritas Addis Fuhr Panchapakesan Ganesh Paul R.C.Kent Keqiang Yan Yuchao Lin Shuiwang Ji Ben Blaiszik Patrick Reiser Pascal Friederich Ankit Agrawal Pratyush Tiwary Eric Beyerle Peter Minch Trevor David Rhone Ichiro Takeuchi Robert B.Wexler Arun Mannodi-Kanakkithodi Elif Ertekin Avanish Mishra Nithin Mathew Mitchell Wood Andrew Dale Rohskopf Jason Hattrick-Simpers Shih-Han Wang Luke E.K.Achenie Hongliang Xin Maureen Williams Adam J.Biacchi Francesca Tavazza Material Measurement Laboratory National Institute of Standards and TechnologyGaithersburgMD20899USA Department of Materials Science and Engineering University of Toronto27 King’s College CirTorontoONCanada Department of Electrical and Computer Engineering Northwestern UniversityEvanstonIL 60208USA Lewis-Sigler Institute for Integrative Genomics Princeton UniversityPrincetonNJ 08544USA Ludwig Institute for Cancer Research Princeton UniversityPrincetonNJ 08544USA Department of Physics and Astronomy West Virginia UniversityMorgantownWV 26506USA Materials Science and Technology Division Oak Ridge National LaboratoryOak RidgeTN 37831USA Center for Nanophase Materials Science Oak Ridge National LaboratoryOak RidgeTN 37831USA Computational Sciences and Engineering Division Oak Ridge National LaboratoryOak RidgeTN 37831USA Department of Computer Science and Engineering Texas A&M UniversityCollege StationTX 77843USA Globus University of ChicagoChicagoIL 60637USA Data Science and Learning Division Argonne National LabLemontIL 60439USA Institute of Nanotechnology Karlsruhe Institute of TechnologyKaiserstraße 1276131 KarlsruheGermany Institute of Theoretical Informatics Karlsruhe Institute of TechnologyKaiserstraße 1276131 KarlsruheGermany Department of Chemistry and Biochemistry and Institute for Physical Science and Technology University of MarylandCollege ParkMD 20742USA Department of Physics Applied Physics and AstronomyRensselaer Polytechnic InstituteTroyNY12180USA Department of Materials Science and Engineering University of MarylandCollege ParkMD20742USA Department of Chemistry and Institute of Materials Science and Engineering Washington University in St.LouisSt.LouisMO63130USA School of Materials Engineering Purdue UniversityWest LafayetteIN47907USA Department of Mechanical Science and Engineering University of Illinois Urbana-ChampaignUrbanaIllinois 61801USA Materials Research Laboratory University of Illinois Urbana-ChampaignUrbanaIL 61801USA Theore

Lack of rigorous reproducibility and validation are significant hurdles for scientific development across many *** science,in particular,encompasses a variety of experimental and theoretical approaches that require careful *** efforts have been developed previously to mitigate these ***,a comprehensive comparison and benchmarking on an integrated platform with multiple data modalities with perfect and defect materials data is still *** work introduces JARVIS-Leaderboard,an open-source and community-driven platform that facilitates benchmarking and enhances *** platform allows users to set up benchmarks with customtasks and enables contributions in the form of dataset,code,and meta-data *** cover the following materials design categories:Artificial Intelligence(AI),Electronic Structure(ES).

关键词： rigorous perfect enable

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Revolutionizing Face Detection: VisionaryNet’s Breakthrough in Unraveling Facial Camplexity

Revolutionizing Face Detection: VisionaryNet’s Breakthrough...

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Computer, Communication and Control (IC4), International Conference on

作者： V. Nallarasan N. Arivazhagan R. Lakshminarayanan D Sharmila Nagaveni B Sangolgi Anand M Department of Networking and Communications School of Computing SRM Institute of Science and Technology Kattankulathur Chengalpattu India Department of Computational Intelligence School of Computing SRM Institute of Science and Technology Kattankulathur Chengalpattu India Department of Electronics and Communication Engineering KPR Institute of Engineering and Technology Coimbatore India Department of Electronics and Communication Engineering Faculty of Engineering and Technology (Exclusively for women) Sharnbasva University Kalaburagi India Department of Computing Technologies SRM Institute of Science and Technology Kattankulathur Chengalpattu India

The initial step in facial recognition and analysis systems often involves facial detection. Traditional methods like Haar cascades and directed gradient histograms relied on manually designed features, limiting their effectiveness in diverse image environments. However, the emergence of deep learning in computer vision has accelerated the development of face detection frameworks, significantly improving accuracy. Detecting small-scale faces, varying positions, occlusions, blurs, and partially obscured faces in uncontrolled settings remains a persistent challenge in face identification. To address this, we propose a new approach called “Visionary Net.” This single-stage face detector has undergone refinements, boosting both detection speed and accuracy. We tested Visionary Net on two well-known datasets: Mega Face and CelebA. Notably, on the Mega Face benchmark, our method achieved an impressive AP of 48.5 at a speed of 15.2 FPS using single-scale inference and an exceptional AP of 52.7 with multi-scale inference. Implementing it with the PyTorch framework resulted in a remarkable 97.3% accuracy in successfully detecting faces. Our comprehensive experiments show that Visionary Net surpasses existing models, demonstrating superior detection and recognition capabilities across various evaluation metrics. This innovative algorithm holds significant promise for robust face detection in challenging real-world scenarios.

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Enhancing the fidelity of social media image data sets in earthquake damage assessment

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Earthquake Spectra 2025年

作者： Huang, Huili Zhang, Danrong Masalava, Anastasiya Roozbahani, Max Mahdi Roy, Nimisha Frost, J David School of Computational Science and Engineering Georgia Institute of Technology AtlantaGA United States School of Computer Science Georgia Institute of Technology AtlantaGA United States School of Computing Instruction Georgia Institute of Technology AtlantaGA United States School of Civil and Environmental Engineering Georgia Institute of Technology AtlantaGA United States

The development of artificial intelligence (AI) provides an opportunity for rapid and accurate assessment of earthquake-induced infrastructure damage using social media images. Nevertheless, data collection and labeling remain challenging due to limited expertise among annotators. This study introduces a novel four-class Earthquake Infrastructure Damage (EID) assessment data set compiled from a combination of images from several other social media image databases but with added emphasis on data quality. Unlike the previous data sets such as Damage Assessment Dataset (DAD) and Crisis Benchmark, the EID includes comprehensive labeling guidelines and a multiclass classification system aligned with established damage scales, such as HAZUS and EMS-98, to enhance the accuracy and utility of social media imagery for disaster response. By integrating detailed descriptions and clear labeling criteria, the labeling approach of EID reduces the subjective nature of image labeling and the inconsistencies found in existing data sets. The findings demonstrate a significant improvement in annotator agreement, reducing disagreement from 39.7% to 10.4%, thereby validating the efficacy of the refined labeling strategy. The EID, containing 13,513 high-quality images from five significant earthquakes, is designed to support community-level assessments and advanced computational research, paving the way for enhanced disaster response strategies through improved data utilization and analysis. The data set is available at DesignSafe: https://***/10.17603/ds2-yj8p-hs62. © The Author(s) 2025.

关键词： Tweets

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