Search results for: workflow optimization
1193 Optimization of Surface Finish in Milling Operation Using Live Tooling via Taguchi Method
Authors: Harish Kumar Ponnappan, Joseph C. Chen
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The main objective of this research is to optimize the surface roughness of a milling operation on AISI 1018 steel using live tooling on a HAAS ST-20 lathe. In this study, Taguchi analysis is used to optimize the milling process by investigating the effect of different machining parameters on surface roughness. The L9 orthogonal array is designed with four controllable factors with three different levels each and an uncontrollable factor, resulting in 18 experimental runs. The optimal parameters determined from Taguchi analysis were feed rate – 76.2 mm/min, spindle speed 1150 rpm, depth of cut – 0.762 mm and 2-flute TiN coated high-speed steel as tool material. The process capability Cp and process capability index Cpk values were improved from 0.62 and -0.44 to 1.39 and 1.24 respectively. The average surface roughness values from the confirmation runs were 1.30 µ, decreasing the defect rate from 87.72% to 0.01%. The purpose of this study is to efficiently utilize the Taguchi design to optimize the surface roughness in a milling operation using live tooling.Keywords: live tooling, surface roughness, taguchi analysis, CNC milling operation, CNC turning operation
Procedia PDF Downloads 1351192 Technical Assessment of Utilizing Electrical Variable Transmission Systems in Hybrid Electric Vehicles
Authors: Majid Vafaeipour, Mohamed El Baghdadi, Florian Verbelen, Peter Sergeant, Joeri Van Mierlo, Kurt Stockman, Omar Hegazy
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The Electrical Variable Transmission (EVT), an electromechanical device, can be considered as an alternative solution to the conventional transmission system utilized in Hybrid Electric Vehicles (HEVs). This study present comparisons in terms of fuel consumption, power split, and state of charge (SoC) of an HEV containing an EVT to a conventional parallel topology and a series topology. To this end, corresponding simulations of these topologies are all performed in presence of control strategies enabling battery charge-sustaining and efficient power split. The power flow through the components of the vehicle are attained, and fuel consumption results of the considered cases are compared. The investigation of the results indicates utilizing EVT can provide significant added values in HEV configurations. The outcome of the current research paves its path for implementation of design optimization approaches on such systems in further research directions.Keywords: Electrical Variable Transmission (EVT), Hybrid Electric Vehicle (HEV), parallel, series, modeling
Procedia PDF Downloads 2311191 Materialized View Effect on Query Performance
Authors: Yusuf Ziya Ayık, Ferhat Kahveci
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Currently, database management systems have various tools such as backup and maintenance, and also provide statistical information such as resource usage and security. In terms of query performance, this paper covers query optimization, views, indexed tables, pre-computation materialized view, query performance analysis in which query plan alternatives can be created and the least costly one selected to optimize a query. Indexes and views can be created for related table columns. The literature review of this study showed that, in the course of time, despite the growing capabilities of the database management system, only database administrators are aware of the need for dealing with archival and transactional data types differently. These data may be constantly changing data used in everyday life, and also may be from the completed questionnaire whose data input was completed. For both types of data, the database uses its capabilities; but as shown in the findings section, instead of repeating similar heavy calculations which are carrying out same results with the same query over a survey results, using materialized view results can be in a more simple way. In this study, this performance difference was observed quantitatively considering the cost of the query.Keywords: cost of query, database management systems, materialized view, query performance
Procedia PDF Downloads 2711190 Image Segmentation with Deep Learning of Prostate Cancer Bone Metastases on Computed Tomography
Authors: Joseph M. Rich, Vinay A. Duddalwar, Assad A. Oberai
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Prostate adenocarcinoma is the most common cancer in males, with osseous metastases as the commonest site of metastatic prostate carcinoma (mPC). Treatment monitoring is based on the evaluation and characterization of lesions on multiple imaging studies, including Computed Tomography (CT). Monitoring of the osseous disease burden, including follow-up of lesions and identification and characterization of new lesions, is a laborious task for radiologists. Deep learning algorithms are increasingly used to perform tasks such as identification and segmentation for osseous metastatic disease and provide accurate information regarding metastatic burden. Here, nnUNet was used to produce a model which can segment CT scan images of prostate adenocarcinoma vertebral bone metastatic lesions. nnUNet is an open-source Python package that adds optimizations to deep learning-based UNet architecture but has not been extensively combined with transfer learning techniques due to the absence of a readily available functionality of this method. The IRB-approved study data set includes imaging studies from patients with mPC who were enrolled in clinical trials at the University of Southern California (USC) Health Science Campus and Los Angeles County (LAC)/USC medical center. Manual segmentation of metastatic lesions was completed by an expert radiologist Dr. Vinay Duddalwar (20+ years in radiology and oncologic imaging), to serve as ground truths for the automated segmentation. Despite nnUNet’s success on some medical segmentation tasks, it only produced an average Dice Similarity Coefficient (DSC) of 0.31 on the USC dataset. DSC results fell in a bimodal distribution, with most scores falling either over 0.66 (reasonably accurate) or at 0 (no lesion detected). Applying more aggressive data augmentation techniques dropped the DSC to 0.15, and reducing the number of epochs reduced the DSC to below 0.1. Datasets have been identified for transfer learning, which involve balancing between size and similarity of the dataset. Identified datasets include the Pancreas data from the Medical Segmentation Decathlon, Pelvic Reference Data, and CT volumes with multiple organ segmentations (CT-ORG). Some of the challenges of producing an accurate model from the USC dataset include small dataset size (115 images), 2D data (as nnUNet generally performs better on 3D data), and the limited amount of public data capturing annotated CT images of bone lesions. Optimizations and improvements will be made by applying transfer learning and generative methods, including incorporating generative adversarial networks and diffusion models in order to augment the dataset. Performance with different libraries, including MONAI and custom architectures with Pytorch, will be compared. In the future, molecular correlations will be tracked with radiologic features for the purpose of multimodal composite biomarker identification. Once validated, these models will be incorporated into evaluation workflows to optimize radiologist evaluation. Our work demonstrates the challenges of applying automated image segmentation to small medical datasets and lays a foundation for techniques to improve performance. As machine learning models become increasingly incorporated into the workflow of radiologists, these findings will help improve the speed and accuracy of vertebral metastatic lesions detection.Keywords: deep learning, image segmentation, medicine, nnUNet, prostate carcinoma, radiomics
Procedia PDF Downloads 901189 Operating System Support for Mobile Device Thermal Management and Performance Optimization in Augmented Reality Applications
Authors: Yasith Mindula Saipath Wickramasinghe
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Augmented reality applications require a high processing power to load, render and live stream high-definition AR models and virtual scenes; it also requires device sensors to work excessively to coordinate with internal hardware, OS and give the expected outcome in advance features like object detection, real time tracking, as well as voice and text recognition. Excessive thermal generation due to these advanced functionalities has become a major research problem as it is unbearable for smaller mobile devices to manage such heat increment and battery drainage as it causes physical harm to the devices in the long term. Therefore, effective thermal management is one of the major requirements in Augmented Reality application development. As this paper discusses major causes for this issue, it also provides possible solutions in the means of operating system adaptations as well as further research on best coding practises to optimize the application performance that reduces thermal excessive thermal generation.Keywords: augmented reality, device thermal management, GPU, operating systems, device I/O, overheating
Procedia PDF Downloads 1121188 Development of Surface-Enhanced Raman Spectroscopy-Active Gelatin Based Hydrogels for Label Free Detection of Bio-Analytes
Authors: Zahra Khan
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Hydrogels are a macromolecular network of hydrophilic copolymers with physical or chemical cross-linking structures with significant water uptake capabilities. They are a promising substrate for surface-enhanced Raman spectroscopy (SERS) as they are both flexible and biocompatible materials. Conventional SERS-active substrates suffer from limitations such as instability and inflexibility, which restricts their use in broader applications. Gelatin-based hydrogels have been synthesised in a facile and relatively quick method without the use of any toxic cross-linking agents. Composite gel material was formed by combining the gelatin with simple polymers to enhance the functional properties of the gel. Gold nanoparticles prepared by a reproducible seed-mediated growth method were combined into the bulk material during gel synthesis. After gel formation, the gel was submerged in the analyte solution overnight. SERS spectra were then collected from the gel using a standard Raman spectrometer. A wide range of analytes was successfully detected on these hydrogels showing potential for further optimization and use as SERS substrates for biomedical applications.Keywords: gelatin, hydrogels, flexible materials, SERS
Procedia PDF Downloads 1081187 Rehabilitative Walking: The Development of a Robotic Walking Training Device Using Functional Electrical Stimulation for Treating Spinal Cord Injuries and Lower-Limb Paralysis
Authors: Chung Hyun Goh, Armin Yazdanshenas, X. Neil Dong, Yong Tai Wang
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Physical rehabilitation is a necessary step in regaining lower body function after a partial paralysis caused by a spinal cord injury or a stroke. The purpose of this paper is to present the development and optimization of a training device that accurately recreates the motions in a gait cycle with the goal of rehabilitation for individuals with incomplete spinal cord injuries or who are victims of a stroke. A functional electrical stimulator was used in conjunction with the training device to stimulate muscle groups pertaining to rehabilitative walking. The feasibility and reliability of the design are presented. To validate the design functionality, motion analyses of the knee and ankle gait paths were made using motion capture systems. Key results indicate that the robotic walking training device provides a viable mode of physical rehabilitation.Keywords: functional electrical stimulation, rehabilitative walking, robotic walking training device, spinal cord injuries
Procedia PDF Downloads 1391186 Resource Constrained Time-Cost Trade-Off Analysis in Construction Project Planning and Control
Authors: Sangwon Han, Chengquan Jin
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Time-cost trade-off (TCTO) is one of the most significant part of construction project management. Despite the significance, current TCTO analysis, based on the Critical Path Method, does not consider resource constraint, and accordingly sometimes generates an impractical and/or infeasible schedule planning in terms of resource availability. Therefore, resource constraint needs to be considered when doing TCTO analysis. In this research, genetic algorithms (GA) based optimization model is created in order to find the optimal schedule. This model is utilized to compare four distinct scenarios (i.e., 1) initial CPM, 2) TCTO without considering resource constraint, 3) resource allocation after TCTO, and 4) TCTO with considering resource constraint) in terms of duration, cost, and resource utilization. The comparison results identify that ‘TCTO with considering resource constraint’ generates the optimal schedule with the respect of duration, cost, and resource. This verifies the need for consideration of resource constraint when doing TCTO analysis. It is expected that the proposed model will produce more feasible and optimal schedule.Keywords: time-cost trade-off, genetic algorithms, critical path, resource availability
Procedia PDF Downloads 1801185 Swarm Optimization of Unmanned Vehicles and Object Localization
Authors: Venkataramana Sovenahalli Badigar, B. M. Suryakanth, Akshar Prasanna, Karthik Veeramalai, Vishwak Ram Vishwak Ram
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Technological advances have led to widespread autonomy in vehicles. Empowering these autonomous with the intelligence to cooperate amongst themselves leads to a more efficient use of the resources available to them. This paper proposes a demonstration of a swarm algorithm implemented on a group of autonomous vehicles. The demonstration involves two ground bots and an aerial drone which cooperate amongst them to locate an object of interest. The object of interest is modelled using a high-intensity light source which acts as a beacon. The ground bots are light sensitive and move towards the beacon. The ground bots and the drone traverse in random paths and jointly locate the beacon. This finds application in various scenarios in where human interference is difficult such as search and rescue during natural disasters, delivering crucial packages in perilous situations, etc. Experimental results show that the modified swarm algorithm implemented in this system has better performance compared to fully random based moving algorithm for object localization and tracking.Keywords: swarm algorithm, object localization, ground bots, drone, beacon
Procedia PDF Downloads 2481184 Cessna Citation X Performances Improvement by an Adaptive Winglet during the Cruise Flight
Authors: Marine Segui, Simon Bezin, Ruxandra Mihaela Botez
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As part of a ‘Morphing-Wing’ idea, this study consists of measuring how a winglet, which is able to change its shape during the flight, is efficient. Conventionally, winglets are fixed-vertical platforms at the wingtips, optimized for a cruise condition that the airplane should use most of the time. However, during a cruise, an airplane flies through a lot of cruise conditions corresponding to altitudes variations from 30,000 to 45,000 ft. The fixed winglets are not optimized for these variations, and consequently, they are supposed to generate some drag, and thus to deteriorate aircraft fuel consumption. This research assumes that it exists a winglet position that reduces the fuel consumption for each cruise condition. In this way, the methodology aims to find these optimal winglet positions, and to further simulate, and thus estimate the fuel consumption of an aircraft wearing this type of adaptive winglet during several cruise conditions. The adaptive winglet is assumed to have degrees of freedom given by the various changes of following surfaces: the tip chord, the sweep and the dihedral angles. Finally, results obtained during cruise simulations are presented in this paper. These results show that an adaptive winglet can reduce, thus improve up to 2.12% the fuel consumption of an aircraft during a cruise.Keywords: aerodynamic, Cessna, Citation X, optimization, winglet
Procedia PDF Downloads 2341183 Assisted Video Colorization Using Texture Descriptors
Authors: Andre Peres Ramos, Franklin Cesar Flores
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Colorization is the process of add colors to a monochromatic image or video. Usually, the process involves to segment the image in regions of interest and then apply colors to each one, for videos, this process is repeated for each frame, which makes it a tedious and time-consuming job. We propose a new assisted method for video colorization; the user only has to colorize one frame, and then the colors are propagated to following frames. The user can intervene at any time to correct eventual errors in color assignment. The method consists of to extract intensity and texture descriptors from the frames and then perform a feature matching to determine the best color for each segment. To reduce computation time and give a better spatial coherence we narrow the area of search and give weights for each feature to emphasize texture descriptors. To give a more natural result, we use an optimization algorithm to make the color propagation. Experimental results in several image sequences, compared to others existing methods, demonstrates that the proposed method perform a better colorization with less time and user interference.Keywords: colorization, feature matching, texture descriptors, video segmentation
Procedia PDF Downloads 1591182 Estimating Occupancy in Residential Context Using Bayesian Networks for Energy Management
Authors: Manar Amayri, Hussain Kazimi, Quoc-Dung Ngo, Stephane Ploix
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A general approach is proposed to determine occupant behavior (occupancy and activity) in residential buildings and to use these estimates for improved energy management. Occupant behaviour is modelled with a Bayesian Network in an unsupervised manner. This algorithm makes use of domain knowledge gathered via questionnaires and recorded sensor data for motion detection, power, and hot water consumption as well as indoor CO₂ concentration. Two case studies are presented which show the real world applicability of estimating occupant behaviour in this way. Furthermore, experiments integrating occupancy estimation and hot water production control show that energy efficiency can be increased by roughly 5% over known optimal control techniques and more than 25% over rule-based control while maintaining the same occupant comfort standards. The efficiency gains are strongly correlated with occupant behaviour and accuracy of the occupancy estimates.Keywords: energy, management, control, optimization, Bayesian methods, learning theory, sensor networks, knowledge modelling and knowledge based systems, artificial intelligence, buildings
Procedia PDF Downloads 3661181 Fabrication, Testing and Machinability Evaluation of Glass Fiber Reinforced Epoxy Composites
Authors: S. S. Panda, Arkesh Chouhan, Yogesh Deshpande
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The present paper deals with designing and fabricating an apparatus for the speedy and accurate manufacturing of fiber reinforced composite lamina of different orientation, thickness and stacking sequences for testing. Properties derived through an analytical approach are verified through measuring the elastic modulus, ultimate tensile strength, flexural modulus and flexural strength of the samples. The 00 orientation ply looks stiffer compared to the 900 ply. Similarly, the flexural strength of 00 ply is higher than to the 900 ply. Sample machinability has been studied by conducting numbers of drilling based on Taguchi Design experiments. Multi Responses (Delamination and Damage grading) is obtained using the desirability approach and optimum cutting condition (spindle speed, feed and drill diameter), at which responses are minimized is obtained thereafter. Delamination increases nonlinearly with the increase in spindle speed. Similarly, the influence of the drill diameter on delamination is higher than the spindle speed and feed rate.Keywords: delamination, FRP composite, Taguchi design, multi response optimization
Procedia PDF Downloads 2661180 Comparison of the Effects of Rod Types of Rigid Fixation Devices on the Loads in the Lumbar Spine: A Finite Element Analysis
Authors: Bokku Kang, Changsoo Chon, Han Sung Kim
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We developed new design of rod of pedicle screw system that is beneficial in maintaining the spacing between the vertebrae and assessed the performance of the posterior fixation screw systems by numerical analysis according to the range of motion (flexion, extension, lateral bending, and axial rotation) of the vertebral column after inserting the pedicle screws. The simulation results showed that the conventional rod was the most low equivalent stress value among implant units in the case of flexion, extension and lateral bending of the vertebrae. In all cases except the torsional rotation, the results showed that the stress level of the single and double rounded rod exceeded about 30% to 70% compare to the conventional rod. Therefore, this product is not suitable for actual application in the field yet and it seems that product design optimization is necessary. Acknowledgement: This research was supported by the Ministry of Trade, Industry & Energy (MOTIE), Korea Institute for Advancement of Technology (KIAT) through the Encouragement Program for The Industries of Economic Cooperation Region.Keywords: lumber spine, internal fixation device, finite element method, biomechanics
Procedia PDF Downloads 3731179 An Overview on Aluminum Matrix Composites: Liquid State Processing
Authors: S. P. Jordan, G. Christian, S. P. Jeffs
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Modern composite materials are increasingly being chosen in replacement of heavier metallic material systems within many engineering fields including aerospace and automotive industries. The increasing push towards satisfying environmental targets are fuelling new material technologies and manufacturing processes. This paper will introduce materials and manufacturing processes using metal matrix composites along with manufacturing processes optimized at Alvant Ltd., based in Basingstoke in the UK which offers modern, cost effective, selectively reinforced composites for light-weighting applications within engineering. An overview and introduction into modern optimized manufacturing methods capable of producing viable replacements for heavier metallic and lower temperature capable polymer composites are offered. A review of the capabilities and future applications of this viable material is discussed to highlight the potential involved in further optimization of old manufacturing techniques, to fully realize the potential to lightweight material using cost-effective methods.Keywords: aluminium matrix composites, light-weighting, hybrid squeeze casting, strategically placed reinforcements
Procedia PDF Downloads 921178 A Systematic Approach for Identifying Turning Center Capabilities with Vertical Machining Center in Milling Operation
Authors: Joseph Chen, N. Hundal
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Conventional machining is a form of subtractive manufacturing, in which a collection of material-working processes utilizing power-driven machine tools are used to remove undesired material to achieve a desired geometry. This paper presents an approach for comparison between turning center and vertical machining center by optimization of cutting parameters at cylindrical workpieces leading to minimum surface roughness by using taguchi methodology. Aluminum alloy was taken to conduct experiments due to its unique high strength-weight ratio that is maintained at elevated temperatures and their exceptional corrosion resistance. During testing, the effects of the cutting parameters on the surface roughness were investigated. Additionally, by using taguchi methodology for each of the cutting parameters (spindle speed, depth of cut, insert diameter, and feed rate) minimum surface roughness for the process of turn-milling was determined according to the cutting parameters. A confirmation experiment demonstrates the effectiveness of taguchi method.Keywords: surface roughness, Taguchi parameter design, turning center, turn-milling operations, vertical machining center
Procedia PDF Downloads 3221177 Performance Analysis of Deterministic Stable Election Protocol Using Fuzzy Logic in Wireless Sensor Network
Authors: Sumanpreet Kaur, Harjit Pal Singh, Vikas Khullar
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In Wireless Sensor Network (WSN), the sensor containing motes (nodes) incorporate batteries that can lament at some extent. To upgrade the energy utilization, clustering is one of the prototypical approaches for split sensor motes into a number of clusters where one mote (also called as node) proceeds as a Cluster Head (CH). CH selection is one of the optimization techniques for enlarging stability and network lifespan. Deterministic Stable Election Protocol (DSEP) is an effectual clustering protocol that makes use of three kinds of nodes with dissimilar residual energy for CH election. Fuzzy Logic technology is used to expand energy level of DSEP protocol by using fuzzy inference system. This paper presents protocol DSEP using Fuzzy Logic (DSEP-FL) CH by taking into account four linguistic variables such as energy, concentration, centrality and distance to base station. Simulation results show that our proposed method gives more effective results in term of a lifespan of network and stability as compared to the performance of other clustering protocols.Keywords: DSEP, fuzzy logic, energy model, WSN
Procedia PDF Downloads 2001176 Prediction of the Solubility of Benzoic Acid in Supercritical CO2 Using the PC-SAFT EoS
Authors: Hamidreza Bagheri, Alireza Shariati
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There are many difficulties in the purification of raw components and products. However, researchers are seeking better ways for purification. One of the recent methods is extraction using supercritical fluids. In this study, the phase equilibria of benzoic acid-supercritical carbon dioxide system were investigated. Regarding the phase equilibria of this system, the modeling of solid-supercritical fluid behavior was performed using the Perturbed-Chain Statistical Association Fluid Theory (PC-SAFT) and Peng-Robinson equations of state (PR EoS). For this purpose, five PC-SAFT EoS parameters for pure benzoic acid were obtained using its experimental vapor pressure. Benzoic acid has association sites and the behavior of the benzoic acid-supercritical fluid system was well-predicted using both equations of state, while the binary interaction parameter values for PR EoS were negative. Genetic algorithm, which is one of the most accurate global optimization algorithms, was also used to optimize the pure benzoic acid parameters and the binary interaction parameters. The AAD% value for the PC-SAFT EoS, were 0.22 for the carbon dioxide-benzoic acid system.Keywords: supercritical fluids, solubility, solid, PC-SAFT EoS, genetic algorithm
Procedia PDF Downloads 5111175 A Novel Guided Search Based Multi-Objective Evolutionary Algorithm
Authors: A. Baviskar, C. Sandeep, K. Shankar
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Solving Multi-objective Optimization Problems requires faster convergence and better spread. Though existing Evolutionary Algorithms (EA's) are able to achieve this, the computation effort can further be reduced by hybridizing them with innovative strategies. This study is focuses on converging to the pareto front faster while adapting the advantages of Strength Pareto Evolutionary Algorithm-II (SPEA-II) for a better spread. Two different approaches based on optimizing the objective functions independently are implemented. In the first method, the decision variables corresponding to the optima of individual objective functions are strategically used to guide the search towards the pareto front. In the second method, boundary points of the pareto front are calculated and their decision variables are seeded to the initial population. Both the methods are applied to different constrained and unconstrained multi-objective test functions. It is observed that proposed guided search based algorithm gives better convergence and diversity than several well-known existing algorithms (such as NSGA-II and SPEA-II) in considerably less number of iterations.Keywords: boundary points, evolutionary algorithms (EA's), guided search, strength pareto evolutionary algorithm-II (SPEA-II)
Procedia PDF Downloads 2681174 Optimization of Diluted Organic Acid Pretreatment on Rice Straw Using Response Surface Methodology
Authors: Rotchanaphan Hengaroonprasan, Malinee Sriariyanun, Prapakorn Tantayotai, Supacharee Roddecha, Kraipat Cheenkachorn
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Lignocellolusic material is a substance that is resistant to be degraded by microorganisms or hydrolysis enzymes. To be used as materials for biofuel production, it needs pretreatment process to improve efficiency of hydrolysis. In this work, chemical pretreatments on rice straw using three diluted organic acids, including acetic acid, citric acid, oxalic acid, were optimized. Using Response Surface Methodology (RSM), the effect of three pretreatment parameters, acid concentration, treatment time, and reaction temperature, on pretreatment efficiency were statistically evaluated. The results indicated that dilute oxalic acid pretreatment led to the highest enhancement of enzymatic saccharification by commercial cellulase and yielded sugar up to 10.67 mg/ml when using 5.04% oxalic acid at 137.11 oC for 30.01 min. Compared to other acid pretreatment by acetic acid, citric acid, and hydrochloric acid, the maximum sugar yields are 7.07, 6.30, and 8.53 mg/ml, respectively. Here, it was demonstrated that organic acids can be used for pretreatment of lignocellulosic materials to enhance of hydrolysis process, which could be integrated to other applications for various biorefinery processes.Keywords: lignocellolusic biomass, pretreatment, organic acid response surface methodology, biorefinery
Procedia PDF Downloads 6411173 Optimal Solutions for Real-Time Scheduling of Reconfigurable Embedded Systems Based on Neural Networks with Minimization of Power Consumption
Authors: Ghofrane Rehaiem, Hamza Gharsellaoui, Samir Benahmed
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In this study, Artificial Neural Networks (ANNs) were used for modeling the parameters that allow the real-time scheduling of embedded systems under resources constraints designed for real-time applications running. The objective of this work is to implement a neural networks based approach for real-time scheduling of embedded systems in order to handle real-time constraints in execution scenarios. In our proposed approach, many techniques have been proposed for both the planning of tasks and reducing energy consumption. In fact, a combination of Dynamic Voltage Scaling (DVS) and time feedback can be used to scale the frequency dynamically adjusting the operating voltage. Indeed, we present in this paper a hybrid contribution that handles the real-time scheduling of embedded systems, low power consumption depending on the combination of DVS and Neural Feedback Scheduling (NFS) with the energy Priority Earlier Deadline First (PEDF) algorithm. Experimental results illustrate the efficiency of our original proposed approach.Keywords: optimization, neural networks, real-time scheduling, low-power consumption
Procedia PDF Downloads 3611172 Improved Dynamic Bayesian Networks Applied to Arabic On Line Characters Recognition
Authors: Redouane Tlemsani, Abdelkader Benyettou
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Work is in on line Arabic character recognition and the principal motivation is to study the Arab manuscript with on line technology. This system is a Markovian system, which one can see as like a Dynamic Bayesian Network (DBN). One of the major interests of these systems resides in the complete models training (topology and parameters) starting from training data. Our approach is based on the dynamic Bayesian Networks formalism. The DBNs theory is a Bayesians networks generalization to the dynamic processes. Among our objective, amounts finding better parameters, which represent the links (dependences) between dynamic network variables. In applications in pattern recognition, one will carry out the fixing of the structure, which obliges us to admit some strong assumptions (for example independence between some variables). Our application will relate to the Arabic isolated characters on line recognition using our laboratory database: NOUN. A neural tester proposed for DBN external optimization. The DBN scores and DBN mixed are respectively 70.24% and 62.50%, which lets predict their further development; other approaches taking account time were considered and implemented until obtaining a significant recognition rate 94.79%.Keywords: Arabic on line character recognition, dynamic Bayesian network, pattern recognition, computer vision
Procedia PDF Downloads 4231171 Removal of Copper from Wastewaters by Nano-Micro Bubble Ion Flotation
Authors: R. Ahmadi, A. Khodadadi, M. Abdollahi
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The removal of copper from a dilute synthetic wastewater (10 mg/L) was studied by ion flotation at laboratory scale. Anionic sodium dodecyl sulfate (SDS) was used as a collector and ethanol as a frother. Different parameters such as pH, collector and frother concentrations, foam height and bubble size distribution (multi bubble ion flotation) were tested to determine the optimum flotation conditions in a Denver type flotation machine. To see into the effect of bubbles size distribution in this paper, a nano-micro bubble generator was designed. The nano and microbubbles that are generated in this way were combined with normal size bubbles generated mechanically. Under the optimum conditions (concentration of SDS: 192mg/l, ethanol: 0.5%v/v, pH value: 4 and froth height=12.5 cm) the best removal obtained for the system Cu/SDS with a dry foam (water recovery: 15.5%) was 85.6%. Coalescence of nano-microbubbles with bubbles of normal size belonging to mechanical flotation cell improved the removal of Cu to a maximum floatability of 92.8% and reduced the water recovery to a 13.1%.The flotation time decreased considerably at 37.5% when the multi bubble ion flotation was used.Keywords: froth flotation, copper, water treatment, optimization, recycling
Procedia PDF Downloads 4951170 Bone Fracture Detection with X-Ray Images Using Mobilenet V3 Architecture
Authors: Ashlesha Khanapure, Harsh Kashyap, Abhinav Anand, Sanjana Habib, Anupama Bidargaddi
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Technologies that are developing quickly are being developed daily in a variety of disciplines, particularly the medical field. For the purpose of detecting bone fractures in X-ray pictures of different body segments, our work compares the ResNet-50 and MobileNetV3 architectures. It evaluates accuracy and computing efficiency with X-rays of the elbow, hand, and shoulder from the MURA dataset. Through training and validation, the models are evaluated on normal and fractured images. While ResNet-50 showcases superior accuracy in fracture identification, MobileNetV3 showcases superior speed and resource optimization. Despite ResNet-50’s accuracy, MobileNetV3’s swifter inference makes it a viable choice for real-time clinical applications, emphasizing the importance of balancing computational efficiency and accuracy in medical imaging. We created a graphical user interface (GUI) for MobileNet V3 model bone fracture detection. This research underscores MobileNetV3’s potential to streamline bone fracture diagnoses, potentially revolutionizing orthopedic medical procedures and enhancing patient care.Keywords: CNN, MobileNet V3, ResNet-50, healthcare, MURA, X-ray, fracture detection
Procedia PDF Downloads 451169 Optimization of Lean Methodologies in the Textile Industry Using Design of Experiments
Authors: Ahmad Yame, Ahad Ali, Badih Jawad, Daw Al-Werfalli Mohamed Nasser, Sabah Abro
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Industries in general have a lot of waste. Wool textile company, Baniwalid, Libya has many complex problems that led to enormous waste generated due to the lack of lean strategies, expertise, technical support and commitment. To successfully address waste at wool textile company, this study will attempt to develop a methodical approach that integrates lean manufacturing tools to optimize performance characteristics such as lead time and delivery. This methodology will utilize Value Stream Mapping (VSM) techniques to identify the process variables that affect production. Once these variables are identified, Design of Experiments (DOE) Methodology will be used to determine the significantly influential process variables, these variables are then controlled and set at their optimal to achieve optimal levels of productivity, quality, agility, efficiency and delivery to analyze the outputs of the simulation model for different lean configurations. The goal of this research is to investigate how the tools of lean manufacturing can be adapted from the discrete to the continuous manufacturing environment and to evaluate their benefits at a specific industrial.Keywords: lean manufacturing, DOE, value stream mapping, textiles
Procedia PDF Downloads 4471168 Optimal Load Factors for Seismic Design of Buildings
Authors: Juan Bojórquez, Sonia E. Ruiz, Edén Bojórquez, David de León Escobedo
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A life-cycle optimization procedure to establish the best load factors combinations for seismic design of buildings, is proposed. The expected cost of damage from future earthquakes within the life of the structure is estimated, and realistic cost functions are assumed. The functions include: Repair cost, cost of contents damage, cost associated with loss of life, cost of injuries and economic loss. The loads considered are dead, live and earthquake load. The study is performed for reinforced concrete buildings located in Mexico City. The buildings are modeled as multiple-degree-of-freedom frame structures. The parameter selected to measure the structural damage is the maximum inter-story drift. The structural models are subjected to 31 soft-soil ground motions recorded in the Lake Zone of Mexico City. In order to obtain the annual structural failure rates, a numerical integration method is applied.Keywords: load factors, life-cycle analysis, seismic design, reinforced concrete buildings
Procedia PDF Downloads 6121167 Experimental Implementation of Model Predictive Control for Permanent Magnet Synchronous Motor
Authors: Abdelsalam A. Ahmed
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Fast speed drives for Permanent Magnet Synchronous Motor (PMSM) is a crucial performance for the electric traction systems. In this paper, PMSM is drived with a Model-based Predictive Control (MPC) technique. Fast speed tracking is achieved through optimization of the DC source utilization using MPC. The technique is based on predicting the optimum voltage vector applied to the driver. Control technique is investigated by comparing to the cascaded PI control based on Space Vector Pulse Width Modulation (SVPWM). MPC and SVPWM-based FOC are implemented with the TMS320F2812 DSP and its power driver circuits. The designed MPC for a PMSM drive is experimentally validated on a laboratory test bench. The performances are compared with those obtained by a conventional PI-based system in order to highlight the improvements, especially regarding speed tracking response.Keywords: permanent magnet synchronous motor, model-based predictive control, DC source utilization, cascaded PI control, space vector pulse width modulation, TMS320F2812 DSP
Procedia PDF Downloads 6331166 A Bio-Inspired Approach for Self-Managing Wireless Sensor and Actor Networks
Authors: Lyamine Guezouli, Kamel Barka, Zineb Seghir
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Wireless sensor and actor networks (WSANs) present a research challenge for different practice areas. Researchers are trying to optimize the use of such networks through their research work. This optimization is done on certain criteria, such as improving energy efficiency, exploiting node heterogeneity, self-adaptability and self-configuration. In this article, we present our proposal for BIFSA (Biologically-Inspired Framework for Wireless Sensor and Actor networks). Indeed, BIFSA is a middleware that addresses the key issues of wireless sensor and actor networks. BIFSA consists of two types of agents: sensor agents (SA) that operate at the sensor level to collect and transport data to actors and actor agents (AA) that operate at the actor level to transport data to base stations. Once the sensor agent arrives at the actor, it becomes an actor agent, which can exploit the resources of the actors and vice versa. BIFSA allows agents to evolve their genetic structures and adapt to the current network conditions. The simulation results show that BIFSA allows the agents to make better use of all the resources available in each type of node, which improves the performance of the network.Keywords: wireless sensor and actor networks, self-management, genetic algorithm, agent.
Procedia PDF Downloads 811165 A Model of Foam Density Prediction for Expanded Perlite Composites
Authors: M. Arifuzzaman, H. S. Kim
Abstract:
Multiple sets of variables associated with expanded perlite particle consolidation in foam manufacturing were analyzed to develop a model for predicting perlite foam density. The consolidation of perlite particles based on the flotation method and compaction involves numerous variables leading to the final perlite foam density. The variables include binder content, compaction ratio, perlite particle size, various perlite particle densities and porosities, and various volumes of perlite at different stages of process. The developed model was found to be useful not only for prediction of foam density but also for optimization between compaction ratio and binder content to achieve a desired density. Experimental verification was conducted using a range of foam densities (0.15–0.5 g/cm3) produced with a range of compaction ratios (1.5-3.5), a range of sodium silicate contents (0.05–0.35 g/ml) in dilution, a range of expanded perlite particle sizes (1-4 mm), and various perlite densities (such as skeletal, material, bulk, and envelope densities). A close agreement between predictions and experimental results was found.Keywords: expanded perlite, flotation method, foam density, model, prediction, sodium silicate
Procedia PDF Downloads 4021164 Supply Chain Optimization through Vulnerability Control and Risk Prevention in Chicken Meat Use
Authors: Moise A. E., State G., Tudorache M., Custură I., Enea D. N., Osman (Defta) A., Drăgotoiu D.
Abstract:
This scientific paper explores risk management strategies in the food supply chain, with a focus on chicken raw materials, in the context of a company sourcing from the EU and non-EU. The aim of the paper is to adapt the requirements of international standards (IFS, BRC, QS, ITW, FSSC, ISO), proposing efficient methods to identify and remediate non-conformities and corrective and preventive actions. Defining the supply flow and acceptance steps promotes collaboration with suppliers to ensure the quality and safety of raw materials. To assess the risks of suppliers and raw materials, objective criteria are developed and vulnerabilities in the supply chain are analyzed, including the risk of fraud. Active monitoring of international alerts through RASFF helps to identify emerging risks quickly, and regular analysis of international trends and company performance enables continuous adaptation of risk management strategies. Implementing these measures strengthens food safety and consumer confidence in the final products supplied.Keywords: food supply chain, international standards, quality and safety of raw materials, RASFF
Procedia PDF Downloads 45