The proceedings contain 13 papers. The topics discussed include: potential effect of upstream sediment trap by a dam on dissolved organic matter transported into the three Gorges Reservoir, China;an advanced Fourier d...
The proceedings contain 13 papers. The topics discussed include: potential effect of upstream sediment trap by a dam on dissolved organic matter transported into the three Gorges Reservoir, China;an advanced Fourier descriptor based on centroid contour distances;stratified control strategy of vehicle longitudinal active collision avoidance;Chinese description generation of dual attention images based on multi-modal fusion;research on the impact of internet consumer credit on Hunan residents' consumption structure;prediction of sea clutter based on recurrent neural network;studies on the evaluation of college classroom teaching quality based on SVM multiclass classification algorithm;and teaching cases analysis of integration of electromechanical control of linkage mechanism.
The proceedings contain 45 papers. The special focus in this conference is on modeling, simulation and optimization. The topics include: Enhancement and Gray-Level optimization of Low Light Images;Prediction of Liver ...
ISBN:
(纸本)9789819968657
The proceedings contain 45 papers. The special focus in this conference is on modeling, simulation and optimization. The topics include: Enhancement and Gray-Level optimization of Low Light Images;Prediction of Liver Disease Using Machine Learning Approaches Based on KNN Model;Modelling of Embedded Cracks by NURBS-Based Extended Isogeometric Analysis;a New Version of Artificial Rabbits optimization for Solving Complex Bridge Network optimization Problem;regression Analysis on Synthesis of Biodiesel from Rice Bran Oil;a Study on Vision-Based Human Activity Recognition Approaches;in-Store Monitoring of Harvested Tomatoes Using Internet of Things;A Compact Microstrip Hexagonal Patch Antenna with a Slotted Ground Plane for RF Energy Harvesting Applications;on P-refinement in Topology optimization;hierarchical Aadhaar-Based Anonymous eSign Based on Group Signatures;swarm Intelligence for Estimating Model Parameters in Thermodynamic Systems;development of a Protocol on Various IoT-Based Devices Available for Women Safety;a Review on Indian Language Identification Using Deep Learning;markov Process Based IoT Model for Road Traffic Prediction;optimization of Process Parameters in Biodiesel Production from Waste Cooking Oil Using Taguchi-Grey Relational Analysis;a Novel D-Latch Design for Low-Power and Improved Immunity;anonymous and Privacy Preserving Attribute-Based Decentralized DigiLocker Using Blockchain Technology;FIFO Memory Implementation with Reduced Metastability;Diabetic Retinopathy Detection Using Ensemble of CNN Architectures;computational Analysis of Darrieus Vertical Axis Wind Turbines for Exhaust Air Energy Extraction;narrow Band 5G Antenna;rectangular and Cylindrical Slotted Microstrip Patch Antenna Design for Biomedical Application;An Implementation of Machine Learning-Based Healthcare Chabot for Disease Prediction (MIBOT);fabrication of Patient Specific Distal Femur with Additive Manufacturing.
The proceedings contain 57 papers. The topics discussed include: nonlinear dynamical analysis of composite boring bar with nano-carbon materials;research on chemical composition and weathering of ancient glass based o...
The proceedings contain 57 papers. The topics discussed include: nonlinear dynamical analysis of composite boring bar with nano-carbon materials;research on chemical composition and weathering of ancient glass based on grey correlation;application of green's function in frequency solution for wind turbine blade modelled as box beam;flap-lag flutter of high-speed rotating blade section of wind turbine;research on algorithms of system vibration in yaw process of large wind turbine;research on online diagnosis of ship main engine with unbalanced sample;research on the classification of inherent risks of cranes based on interval laminar analysis method-index method;performance research of dual power flow continuous differential steering system for tracked vehicle;study of the ejection process of cold ejection system with flexible cylinder by corpuscular method;and simulation and experimental study on anti-damage performance of gun and ammunition cabinet.
Manufacturing turbine blades using metal injection molding (MIM) is a complex process that requires precise control over parameters to achieve high dimensional accuracy. Inadequate management of shrinkage, frozen volu...
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Manufacturing turbine blades using metal injection molding (MIM) is a complex process that requires precise control over parameters to achieve high dimensional accuracy. Inadequate management of shrinkage, frozen volume, and volume filled leads to dimensional deviations, resulting in defects or reduced performance of turbine blades in operation. Optimizing these response factors ensures reliable production and high-quality turbine blades. This study investigates the influence of process parameters in metal injection molding by evaluating their significance and interaction. A three-level central composite design (CCD) approach-based response surface methodology analysis was applied to statistically specify the effect of important numerical and categorical process variables: mold temperature, melt temperature, injection time, flow rate on the critical response process output variables concerning product quality, namely shrinkage, frozen volume, and volume filled. By using a face-centered design, a total of 30 simulation data was fitted. Analysis of variance (ANOVA) was then performed to assess the significance of factors and their interactions at a 95% confidence level (p < 0.05). Subsequently, empirical models were developed and rigorously validated against the simulation results. The optimum process parameters of the metal part were characterized as follows: mold temperature of 15 degrees C, 138 degrees C of melt temperature, 2.5 s of injection time, and 94 cm3/s flow rate. The results are expected to advance the metal injection molding industry by providing valuable references and enhancing the understanding of the optimization process.
The proceedings contain 50 papers. The special focus in this conference is on modeling, simulation and optimization. The topics include: Fast Implementation for Computational Method of Optimum Attacking Play in Rugby ...
ISBN:
(纸本)9789811908354
The proceedings contain 50 papers. The special focus in this conference is on modeling, simulation and optimization. The topics include: Fast Implementation for Computational Method of Optimum Attacking Play in Rugby Sevens;AHP-GRA Integrated Methodology for Decision-Making in WEDM of Ti-6Al-4 V Alloy;defect Detection Using Correlation Approach for Frequency Modulated Thermal Wave Imaging;comparative Study of Aero and Non-aero Formula Student Type Race Car Using Optimum Lap;simulation and Stabilization of a Custom-Made Quadcopter in Gazebo Using ArduPilot and QGroundControl;MNIST Image Classification Using Convolutional Neural Networks;A Contemporary Initiative to Uphold Cease COVID-19 Using Keras and Tensorflow;double Sampling Plans for Life Test Based on Marshall–Olkin Extended Exponential Distribution;modeling and simulation of Electric Vehicle with Synchronous Reluctance Motor;effect of Suspension Parameter on Lateral Dynamics Study of High Speed Railway Vehicle;modeling Clusters in Streamflow Time Series Based on an Affine Process;a Comparative Study of Various Traditional and Hybrid Cryptography Algorithm Models for Data Security;Assessing and Predicting Urban Growth Patterns Using ANN-MLP and CA Model in Jammu Urban Agglomeration, India;Chaotic Lorenz Time Series Prediction via NLMS Algorithm with Fuzzy Adaptive Step Size;Channel Adaptive Equalizer Design Based on FIR Filter via FVSS-NLMS Algorithm;Direct Adaptive Inverse Control Based on Nonlinear Volterra Model via Fractional LMS Algorithm;indirect Adaptive Inverse Control Synthesis via Fractional Least Mean Square Algorithm;thermo-Economic Analysis for the Feasibility Study of a Binary Geothermal Power Plant in India;V2G/G2V Bi-directional On-Board EV Charger Using Two Phase Interleaved DC-DC Converter;hydrodynamic Coupling Between Comoving Microrobots;preface.
Ground settlement prediction for shield construction is highly important and challenging. This study introduces a machine learning algorithm combined with finite element numerical simulation, i.e., machine learning-fi...
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Ground settlement prediction for shield construction is highly important and challenging. This study introduces a machine learning algorithm combined with finite element numerical simulation, i.e., machine learning-finite element mesh optimization. For surface subsidence prediction, 16 combination models of ANN, KNN, RF and SVR were optimized by PSO, GA, BT and BO, involving raw data preprocessing, principal component analysis, hyperparameter selection and prediction accuracy evaluation. A subway shield tunneling project was analyzed, in which the meshes of finite element numerical models were discretized into different sizes from 1.0m to 2.0m. In total, 360 sets of data points were extracted from the simulation results, including stress, strain, shield jacking force, internal friction angle, cohesion force, and settlement, of which 252 data points were used as the input parameters of machine learning model. Analysis of average error rate of finite element-machine learning coupling models showed that the finite element model had the highest accuracy of settlement prediction when the mesh size of the finite element model was 1.4m, and the GA-SVR model had the highest accuracy and generalization ability in ground settlement prediction. This study highlights the uniqueness of machine learning-finite element mesh optimization model in application.
In this study, the effects of tray shape, loading thickness, electrode gap, vacuum level, and vacuum pulsation ratio on the heating performance during radio frequency pulsed vacuum drying (RFPVD) were systematically i...
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In this study, the effects of tray shape, loading thickness, electrode gap, vacuum level, and vacuum pulsation ratio on the heating performance during radio frequency pulsed vacuum drying (RFPVD) were systematically investigated. First, based on the established RF heating model, the radiative heat transfer equation was coupled to improve the accuracy of heat transfer simulation under vacuum conditions. simulation results showed that the temperature uniformity index (TUI) in RF heating stage was reduced to 0.13 by suppressing the edge aggregation effect of the electric field with circular tray. Additionally, single-layer stacking and increased loading thickness effectively improved the heating rate;however, the resulting enhancement of edge aggregation resulted in the TUI increased to 0.31. When a loading thickness of 45 mm was applied, adjusting the electrode gap to 95 mm increased the heating rate and avoided the localized overheating during the heating stage. At a defined drying temperature, an appropriate vacuum level modulated the moisture evaporation rate to optimize the temperature distribution. The RFPVD experiments verified that ideal temperature distribution uniformity (TUI <0.112) and post-drying moisture content consistency (coefficient of variation<5 %) could be obtained using multi-parameter optimization guided by simulation results. This study provides a theoretical basis and process optimization strategy for improving heating uniformity in RFPVD drying of granular materials.
This paper studies the application of the Bayesian optimization algorithm in DHCPv6 stateful allocation, addressing the efficiency issues of traditional allocation strategies in high-load scenarios. By constructing a ...
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This proceedings volume gathers a selection of papers presented at the Fifth internationalconference on High Performance Scientific Computing, which took place in Hanoi on March 5-9, 2012. The conference was organize...
ISBN:
(纸本)9783319359199
This proceedings volume gathers a selection of papers presented at the Fifth internationalconference on High Performance Scientific Computing, which took place in Hanoi on March 5-9, 2012. The conference was organized by the Institute of Mathematics of the Vietnam Academy of Science and Technology (VAST), the Interdisciplinary Center for Scientific Computing (IWR) of Heidelberg University, Ho Chi Minh City University of Technology, and the Vietnam Institute for Advanced Study in Mathematics. The contributions cover the broad interdisciplinary spectrum of scientific computing and present recent advances in theory, development of methods, and practical applications. Subjects covered include mathematical modeling; numerical simulation; methods for optimization and control; parallel computing; software development; and applications of scientific computing in physics, mechanics and biomechanics, material science, hydrology, chemistry, biology, biotechnology, medicine, sports, psychology, transport, logistics, communication networks, scheduling, industry, business and finance.
Schmitt Trigger Circuits (STCs) play a crucial role in digital and analog signal processing by providing noise immunity and stable switching behavior. However, optimizing STC performance for low-power, high-speed appl...
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Schmitt Trigger Circuits (STCs) play a crucial role in digital and analog signal processing by providing noise immunity and stable switching behavior. However, optimizing STC performance for low-power, high-speed applications remains a challenging task. This study proposes a novel approach using the Multi-Objective Mayfly optimization Algorithm (MOMA) to optimize key STC parameters, including power dissipation, propagation delay, and hysteresis voltage. The optimization process was conducted using MATLAB, whereas LTSpice was employed for circuit-level validation using 0.25 mu m/2.5 V CMOS technology. To identify the best trade-off solutions, various weighting methods were applied, including Statistical Variance, Standard Deviation, CRITIC, and Mean methods, ensuring a balanced evaluation of circuit performance. Numerical results show that the optimized STC achieved a 23% reduction in propagation delay, a 38% decrease in power dissipation, and improved noise immunity while maintaining robust switching characteristics. These findings confirm the effectiveness of MOMA in designing low-power, high-performance STCs suitable for modern VLSI, biomedical, and IoT applications.
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