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Emerging Trends in Damage Tolerance Assessment:A Review of Smart Materials and Self-Repairable Structures

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Structural Durability & Health Monitoring 2024年第1期18卷 1-18页

作者： ali Akbar Firoozi ali Asghar Firoozi Department of Civil Engineering Faculty of Engineering&TechnologyUniversity of BotswanaGaboroneUB0061Botswana Department of Civil Engineering University Kebangsaan Malaysia(UKM)Bangi43600Malaysia

The discipline of damage tolerance assessment has experienced significant advancements due to the emergence of smart materials and self-repairable *** review offers a comprehensive look into both traditional and innovative methodologies employed in damage tolerance *** a detailed exploration of damage tolerance concepts and their historical progression,the review juxtaposes the proven techniques of damage assessment with the cutting-edge innovations brought about by smart materials and self-repairable *** subsequent sections delve into the synergistic integration of smart materials with self-repairable structures,marking a pivotal stride in damage tolerance by establishing an autonomous system for immediate damage identification and *** holistic approach broadens the applicability of these technologies across diverse sectors yet brings forth unique challenges demanding further innovation and ***,the review examines future prospects that combine advanced manufacturing processes with data-centric methodologies,amplifying the capabilities of these‘intelligent’*** review culminates by highlighting the transformative potential of this union between smart materials and self-repairable structures,promoting a sustainable and efficient engineering paradigm.

关键词： Damage tolerance smart materials self-repairable structures structural health monitoring synergy autonomous system advanced manufacturing data-driven methodologies

A methodology for damage evaluation of underground tunnels subjected to static loading using numerical modeling

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Journal of Rock Mechanics and Geotechnical Engineering 2024年第6期16卷 1993-2005页

作者： Shahriyar Heidarzadeh ali Saeidi Rock Mechanics Engineer AtkinsRéalisMontrealQuebecCanada Department of Applied Sciences Universitédu QuébecàChicoutimiChicoutimiQuebecCanada

We have proposed a methodology to assess the robustness of underground tunnels against potential *** involves developing vulnerability functions for various qualities of rock mass and static loading *** account for these variations,we utilized a Monte Carlo Simulation(MCS)technique coupled with the finite difference code FLAC^(3D),to conduct two thousand seven hundred numerical simulations of a horseshoe tunnel located within a rock mass with different geological strength index system(GSIs)and subjected to different states of static *** quantify the severity of damage within the rock mass,we selected one stress-based(brittle shear ratio(BSR))and one strain-based failure criterion(plastic damage index(PDI)).Based on these criteria,we then developed fragility ***,we used mathematical approximation techniques to produce vulnerability functions that relate the probabilities of various damage states to loading intensities for different quality classes of blocky rock *** results indicated that the fragility curves we obtained could accurately depict the evolution of the inner and outer shell damage around the ***,we have provided engineers with a tool that can predict levels of damages associated with different failure mechanisms based on variations in rock mass quality and in situ stress *** method is a numerically developed,multi-variate approach that can aid engineers in making informed decisions about the robustness of underground tunnels.

关键词： Fragility curves Underground tunnels Vulnerability functions Brittle damage FLAC3D Numerical modeling

Performance of Text-Independent Automatic Speaker Recognition on a Multicore System

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Tsinghua Science and Technology 2024年第2期29卷 447-456页

作者： Rand Kouatly Talha ali Khan Faculty of Tech and Software Engineering University of Europe for Applied SciencesPotsdam 14469Germany

This paper studies a high-speed text-independent Automatic Speaker Recognition(ASR)algorithm based on a multicore system's Gaussian Mixture Model(GMM).The high speech is achieved using parallel implementation of the feature's extraction and aggregation methods during training and testing *** memory parallel programming techniques using both OpenMP and PThreads libraries are developed to accelerate the code and improve the performance of the ASR *** experimental results show speed-up improvements of around 3.2 on a personal laptop with Intel i5-6300HQ(2.3 GHz,four cores without hyper-threading,and 8 GB of RAM).In addition,a remarkable 100%speaker recognition accuracy is achieved.

关键词： Automatic Speaker Recognition(ASR) Gaussian Mixture Model(GMM) shared memory parallel programming PThreads OpenMP

CFD simulation and optimization of an industrial cement gas-solid air classifier

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Particuology 2024年第6期89卷 172-184页

作者： Mohamadreza Esmaeilpour ali Mohebbi Vahab Ghalandari Department of Chemical Engineering Faculty of EngineeringShahid Bahonar University of KermanKermanIran Kerman Momtazan Cement Company KermanIran

An air classifier is one of the main and effective devices in cement *** this study,a three-dimensional,steady and two-phase(solid-gas)computational fluid dynamics(CFD)simulation was performed to optimize the performance of this device in the Kerman Momtazan cement plant,*** the validation of CFD results,the air flow field and air path lines between fixed blades were checked carefully and the non-uniformity in velocity distribution and the formation of vortex flows between the blades close to particle inlets were *** study tried to improve the device efficiency by changing the method of entering particles into the device,resulting in a reduction in air classifier electrical energy consumption(from 41 to 35(kW h)/t)and an increase in production rate(from 203 to 214 t/h).Additionally,the study investigated the effects of other modifiable operating conditions like rotary cage rotation speed,pressure difference,and inlet air temperature on the particle size distribution and classifier *** results showed that increasing the cage rotation speed decreased the product rate and the product particles mean diameter while increasing pressure difference or increasing temperature increased the product rate and the product particles mean *** was concluded that these modifiable operating conditions can significantly affect the performance of the air classifier in the cement industry.

关键词： Cement air classifier Computational fluid dynamics Gas-solid two-phase flow Optimization Eulerian-Lagrangian method Efficiency

Enhancing cotton resilience to challenging climates through genetic modifications

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Journal of Cotton Research 2024年第2期7卷 196-206页

作者： AHMED ali Ijaz KHAN Azeem Iqbal NEGM Mohamed A.M. IQBAL Rida AZHAR Muhammad Tehseen KHAN Sultan Habibullah RANA Iqrar ahmad Department of Plant Breeding and Genetics University of AgricultureFaisalabadFaisalabad 38000Pakistan Cotton Research Institute-Giza GizaEgypt Centre for Advanced Studies in Agriculture and Food Security University of AgricultureFaisalabadFaisalabad 38000Pakistan Centre of Agricultural Biochemistry and Biotechnology University of AgricultureFaisalabadFaisalabad 38000Pakistan School of Agriculture Sciences Zhengzhou UniversityZhengzhou 450000China

Cotton is one of the most important fiber crops that plays a vital role in the textile *** production has been unstable over the years due to climate change induced biotic stresses such as insects,diseases,and weeds,as well as abiotic stresses including drought,salinity,heat,and *** breeding methods have been used to breed climate resilient cotton,but it requires a considerable amount of time to enhance crop tolerance to insect pests and changing climatic conditions.A promising strategy for improving tolerance against these stresses is genetic *** review article discusses the role of genetic engineering in cotton *** essential concepts and techniques include genome editing via clustered regularly interspaced short palindromic repeats(CRISPR)/CRISPR-associated protein 9(CRISPR-Cas9),overexpression of target genes,downregulation using RNA interference(RNAi),and virus-induced gene silencing(VIGS).Notably,the Agrobacterium-mediated transformation has made significant contributions to using these techniques for obtaining stable transgenic plants.

关键词： Cotton Genome editing Drought Salinity Heat

A convolutional neural network to detect possible hidden data in spatial domain images

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Cybersecurity 2024年第1期7卷 37-52页

作者： Jean De La Croix Ntivuguruzwa Tohari ahmad Department of Informatics Institut Teknologi Sepuluh Nopember(ITS)Kampus ITS Keputih SukoliloSurabaya60111Indonesia African Center of Excellence in the Internet of Things College of Science and TechnologyUniversity of Rwanda3900KigaliRwanda

Hiding secret data in digital multimedia has been essential to protect the ***,attackers with a steganalysis technique may break *** steganalysis methods have good results with conventional Machine Learning(ML)techniques;however,the introduction of Convolutional Neural Network(CNN),a deep learning paradigm,achieved better performance over the previously proposed ML-based *** the existing CNN-based approaches yield good results,they present performance issues in classification accuracy and stability in the network training *** research proposes a new method with a CNN architecture to improve the hidden data detection accuracy and the training phase stability in spatial domain *** proposed method comprises three phases:pre-processing,feature extraction,and ***,in the pre-processing phase,we use spatial rich model filters to enhance the noise within images altered by data hiding;secondly,in the feature extraction phase,we use two-dimensional depthwise separable convolutions to improve the signal-to-noise and regular convolutions to model local features;and finally,in the classification,we use multi-scale average pooling for local features aggregation and representability enhancement regardless of the input size variation,followed by three fully connected layers to form the final feature maps that we transform into class probabilities using the softmax *** results identify an improvement in the accuracy of the considered recent scheme ranging between 4.6 and 10.2%with reduced training time up to 30.81%.

关键词： Information security Spatial domain steganalysis Deep learning Convolutional neural network Infrastructure

Machine learning-enhanced Monte Carlo and subset simulations for advanced risk assessment in transportation infrastructure

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Journal of Mountain Science 2024年第2期21卷 690-717页

作者： Furquan ahmad Pijush SAMUI S.S.MISHRA Department of Civil Engineering National Institute of TechnologyPatna 800006India

The maintenance of safety and dependability in rail and road embankments is of utmost importance in order to facilitate the smooth operation of transportation *** study introduces a comprehensive methodology for soil slope stability evaluation,employing Monte Carlo Simulation(MCS)and Subset Simulation(SS)with the"UPSS 3.0 Add-in"in *** on an 11.693-meter embankment with a soil slope(inclination ratio of 2H:1V),the investigation considers earthquake coefficients(kh)and pore water pressure ratios(ru)following Indian zoning *** chance of slope failure showed a considerable increase as the Coefficient of Variation(COV),seismic coefficients(kh),and pore water pressure ratios(ru)experienced an *** SS approach showed exceptional efficacy in calculating odds of failure that are notably *** computational modeling,the study optimized the worst-case scenario using ANFIS-GA,ANFIS-GWO,ANFIS-PSO,and ANFIS-BBO *** ANFIS-PSO model exhibits exceptional accuracy(training R2=0.9011,RMSE=0.0549;testing R2=0.8968,RMSE=0.0615),emerging as the most *** study highlights the significance of conducting thorough risk assessments and offers practical insights into evaluating and improving the stability of soil slopes in transportation *** findings contribute to the enhancement of safety and reliability in real-world situations.

关键词： Monte Carlo Simulation Subset Simulation Machine Learning Seismic coefficient

Benchmarking YOLOv5 models for improved human detection in search and rescue missions

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Journal of Electronic Science and Technology 2024年第1期22卷 70-80页

作者： Namat Bachir Qurban ali Memon Electrical Engineering Department College of EngineeringUnited Arab Emirates UniversityAl Ain15551United Arab Emirates

Drone or unmanned aerial vehicle(UAV)technology has undergone significant *** technology allows UAV to carry out a wide range of tasks with an increasing level of sophistication,since drones can cover a large area with ***,the increasing number of computer vision applications utilizing deep learning provides a unique insight into such *** primary target in UAV-based detection applications is humans,yet aerial recordings are not included in the massive datasets used to train object detectors,which makes it necessary to gather the model data from such *** only look once(YOLO)version 4,RetinaNet,faster region-based convolutional neural network(R-CNN),and cascade R-CNN are several well-known detectors that have been studied in the past using a variety of datasets to replicate rescue ***,we used the search and rescue(SAR)dataset to train the you only look once version 5(YOLOv5)algorithm to validate its speed,accuracy,and low false detection *** comparison to YOLOv4 and R-CNN,the highest mean average accuracy of 96.9%is obtained by *** comparison,experimental findings utilizing the SAR and the human rescue imaging database on land(HERIDAL)datasets are *** results show that the YOLOv5-based approach is the most successful human detection model for SAR missions.

关键词： Unmanned aerial vehicle(UAV) Search and rescue(SAR) You look only once(YOLO)model You only look once version 5 (YOLOv5)

Assessing Multidimensional Vulnerability of Rural Areas to Flooding:An Index‑Based Approach

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International Journal of Disaster Risk Science 2024年第1期15卷 88-106页

作者： Samavia Rasool Irfan ahmad Rana Hassam Bin Waseem Department of Urban and Regional Planning School of Civil and Environmental Engineering(SCEE)National University of Sciences and Technology(NUST)Islamabad 44000Pakistan

Vulnerability assessment is essential for understanding and launching effective flood risk reduction *** study aimed to examine the vulnerability of flood-prone rural communities in southern Punjab,Pakistan to external *** concept of vulnerability encompasses a range of dimensions,including physical,social,institutional,environmental,economic,and *** a composite index method,indices were developed for each dimension and combined to create a multidimensional measure of vulnerability.A sample of 365 communities was selected using the Yamane sampling technique,and data were collected through a questionnaire containing 65 indicators across all *** statistics and ANOVA tests were used to analyze the *** results show that communities near the Chenab River had higher attitudinal and institutional vulnerability compared to other *** attitudinal vulnerabilities were as sociated with poorly perceived flood risks and low preparedness measures,whereas institutional vulnerabilities were driven by conventional flood protection strategies,lack of institutional trust,and lack of flood risk *** research provides insights into the various components of vulnerability in flood-prone rural communities in Pakistan and demonstrates a useful methodology that can be applied to other disasters at different spatial scales.

关键词： Chenab River Flood hazard Indus River Pakistan-Rural areas:Vulnerability to flooding