Search results for: training time
5719 Effect of Fermentation Time on Xanthan Gum Production from Sugar Beet Molasses
Authors: Marzieh Moosavi- Nasab, Safoora Pashangeh, Maryam Rafsanjani
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Xanthan gum is a microbial polysaccharide of great commercial significance. The purpose of this study was to select the optimum fermentation time for xanthan gum production by Xanthomonas campestris (NRRL-B-1459) using 10% sugar beet molasses as a carbon source. The pre-heating of sugar beet molasses and the supplementation of the medium were investigated in order to improve xanthan gum production. Maximum xanthan gum production in fermentation media (9.02 g/l) was observed after 4 days shaking incubation at 25°C and 240 rpm agitation speed. A solution of 10% sucrose was used as a control medium. Results indicated that the optimum period for xanthan gum production in this condition was 4 days.Keywords: Biomass, Molasses, Xanthan gum, Xanthomonascampestris
Procedia APA BibTeX Chicago EndNote Harvard JSON MLA RIS XML ISO 690 PDF Downloads 37165718 Designing and Implementing a Novel Scheduler for Multiprocessor System using Genetic Algorithm
Authors: Iman Zangeneh, Mostafa Moradi, Mazyar Baranpouyan
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System is using multiple processors for computing and information processing, is increasing rapidly speed operation of these systems compared with single processor systems, very significant impact on system performance is increased .important differences to yield a single multi-processor cpu, the scheduling policies, to reduce the implementation time of all processes. Notwithstanding the famous algorithms such as SPT, LPT, LSPT and RLPT for scheduling and there, but none led to the answer are not optimal.In this paper scheduling using genetic algorithms and innovative way to finish the whole process faster that we do and the result compared with three algorithms we mentioned.
Keywords: Multiprocessor system, genetic algorithms, time implementation process.
Procedia APA BibTeX Chicago EndNote Harvard JSON MLA RIS XML ISO 690 PDF Downloads 15475717 Data Mining Approach for Commercial Data Classification and Migration in Hybrid Storage Systems
Authors: Mais Haj Qasem, Maen M. Al Assaf, Ali Rodan
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Parallel hybrid storage systems consist of a hierarchy of different storage devices that vary in terms of data reading speed performance. As we ascend in the hierarchy, data reading speed becomes faster. Thus, migrating the application’ important data that will be accessed in the near future to the uppermost level will reduce the application I/O waiting time; hence, reducing its execution elapsed time. In this research, we implement trace-driven two-levels parallel hybrid storage system prototype that consists of HDDs and SSDs. The prototype uses data mining techniques to classify application’ data in order to determine its near future data accesses in parallel with the its on-demand request. The important data (i.e. the data that the application will access in the near future) are continuously migrated to the uppermost level of the hierarchy. Our simulation results show that our data migration approach integrated with data mining techniques reduces the application execution elapsed time when using variety of traces in at least to 22%.Keywords: Data mining, hybrid storage system, recurrent neural network, support vector machine.
Procedia APA BibTeX Chicago EndNote Harvard JSON MLA RIS XML ISO 690 PDF Downloads 17255716 Dynamic Analysis of Porous Media Using Finite Element Method
Authors: M. Pasbani Khiavi, A. R. M. Gharabaghi, K. Abedi
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The mechanical behavior of porous media is governed by the interaction between its solid skeleton and the fluid existing inside its pores. The interaction occurs through the interface of gains and fluid. The traditional analysis methods of porous media, based on the effective stress and Darcy's law, are unable to account for these interactions. For an accurate analysis, the porous media is represented in a fluid-filled porous solid on the basis of the Biot theory of wave propagation in poroelastic media. In Biot formulation, the equations of motion of the soil mixture are coupled with the global mass balance equations to describe the realistic behavior of porous media. Because of irregular geometry, the domain is generally treated as an assemblage of fmite elements. In this investigation, the numerical formulation for the field equations governing the dynamic response of fluid-saturated porous media is analyzed and employed for the study of transient wave motion. A finite element model is developed and implemented into a computer code called DYNAPM for dynamic analysis of porous media. The weighted residual method with 8-node elements is used for developing of a finite element model and the analysis is carried out in the time domain considering the dynamic excitation and gravity loading. Newmark time integration scheme is developed to solve the time-discretized equations which are an unconditionally stable implicit method Finally, some numerical examples are presented to show the accuracy and capability of developed model for a wide variety of behaviors of porous media.
Keywords: Dynamic analysis, Interaction, Porous media, time domain
Procedia APA BibTeX Chicago EndNote Harvard JSON MLA RIS XML ISO 690 PDF Downloads 18595715 A Constitutive Model for Time-Dependent Behavior of Clay
Authors: T. N. Mac, B. Shahbodaghkhan, N. Khalili
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A new elastic-viscoplastic (EVP) constitutive model is proposed for the analysis of time-dependent behavior of clay. The proposed model is based on the bounding surface plasticity and the concept of viscoplastic consistency framework to establish continuous transition from plasticity to rate dependent viscoplasticity. Unlike the overstress based models, this model will meet the consistency condition in formulating the constitutive equation for EVP model. The procedure of deriving the constitutive relationship is also presented. Simulation results and comparisons with experimental data are then presented to demonstrate the performance of the model.
Keywords: Bounding surface, consistency theory, constitutive model, viscosity.
Procedia APA BibTeX Chicago EndNote Harvard JSON MLA RIS XML ISO 690 PDF Downloads 27275714 Online Partial Discharge Source Localization and Characterization Using Non-Conventional Method
Authors: Ammar Anwar Khan, Nissar R. Wani, Nazar Malik, Abdulrehman Al-Arainy, and Saad Alghuwainem
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Power cables are vulnerable to failure due to aging or defects that occur with the passage of time under continuous operation and loading stresses. PD detection and characterization provide information on the location, nature, form and extent of the degradation. As a result, PD monitoring has become an important part of condition based maintenance (CBM) program among power utilities. Online partial discharge (PD) localization of defect sources in power cable system is possible using the time of flight method. The information regarding the time difference between the main and reflected pulses and cable length can help in locating the partial discharge source along the cable length. However, if the length of the cable is not known and the defect source is located at the extreme ends of the cable or in the middle of the cable, then double ended measurement is required to indicate the location of PD source. Use of multiple sensors can also help in discriminating the cable PD or local/ external PD. This paper presents the experience and results from online partial discharge measurements conducted in the laboratory and the challenges in partial discharge source localization.Keywords: Power cables, partial discharge localization, HFCT, condition based monitoring.
Procedia APA BibTeX Chicago EndNote Harvard JSON MLA RIS XML ISO 690 PDF Downloads 28175713 Improving Decision Support for Organ Transplant
Authors: I. McCulloh, A. Placona, D. Stewart, D. Gause, K. Kiernan, M. Stuart, C. Zinner, L. Cartwright
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We find in our data that an alarming number of viable deceased donor kidneys are discarded every year in the US, while waitlisted candidates are dying every day. We observe as many as 85% of transplanted organs are refused at least once for a patient that scored higher on the match list. There are hundreds of clinical variables involved in making a clinical transplant decision and there is rarely an ideal match. Decision makers exhibit an optimism bias where they may refuse an organ offer assuming a better match is imminent. We propose a semi-parametric Cox proportional hazard model, augmented by an accelerated failure time model based on patient-specific suitable organ supply and demand to estimate a time-to-next-offer. Performance is assessed with Cox-Snell residuals and decision curve analysis, demonstrating improved decision support for up to a 5-year outlook. Providing clinical decision-makers with quantitative evidence of likely patient outcomes (e.g., time to next offer and the mortality associated with waiting) may improve decisions and reduce optimism bias, thus reducing discarded organs and matching more patients on the waitlist.
Keywords: Decision science, KDPI, optimism bias, organ transplant.
Procedia APA BibTeX Chicago EndNote Harvard JSON MLA RIS XML ISO 690 PDF Downloads 1575712 Block-Based 2D to 3D Image Conversion Method
Authors: S. Sowmyayani, V. Murugan
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With the advent of three-dimension (3D) technology, there are lots of research in converting 2D images to 3D images. The main difference between 2D and 3D is the visual illusion of depth in 3D images. In the recent era, there are more depth estimation techniques. The objective of this paper is to convert 2D images to 3D images with less computation time. For this, the input image is divided into blocks from which the depth information is obtained. Having the depth information, a depth map is generated. Then the 3D image is warped using the original image and the depth map. The proposed method is tested on Make3D dataset and NYU-V2 dataset. The experimental results are compared with other recent methods. The proposed method proved to work with less computation time and good accuracy.
Keywords: Depth map, 3D image warping, image rendering, bilateral filter, minimum spanning tree.
Procedia APA BibTeX Chicago EndNote Harvard JSON MLA RIS XML ISO 690 PDF Downloads 3345711 Six Sigma Process and its Impact on the Organizational Productivity
Authors: Masoud Hekmatpanah, Mohammad Sadroddin, Saeid Shahbaz, Farhad Mokhtari, Farahnaz Fadavinia
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The six sigma method is a project-driven management approach to improve the organization-s products, services, and processes by continually reducing defects in the organization. Understanding the key features, obstacles, and shortcomings of the six sigma method allows organizations to better support their strategic directions, and increasing needs for coaching, mentoring, and training. It also provides opportunities to better implement six sigma projects. The purpose of this paper is the survey of six sigma process and its impact on the organizational productivity. So I have studied key concepts , problem solving process of six sigmaas well as the survey of important fields such as: DMAIC, six sigma and productivity applied programme, and other advantages of six sigma. In the end of this paper, present research conclusions. (direct and positive relation between six sigma and productivity)
Keywords: Six sigma, project management, quality, theory, productivity.
Procedia APA BibTeX Chicago EndNote Harvard JSON MLA RIS XML ISO 690 PDF Downloads 69585710 New Approaches on Stability Analysis for Neural Networks with Time-Varying Delay
Authors: Qingqing Wang, Shouming Zhong
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Utilizing the Lyapunov functional method and combining linear matrix inequality (LMI) techniques and integral inequality approach (IIA) to analyze the global asymptotic stability for delayed neural networks (DNNs),a new sufficient criterion ensuring the global stability of DNNs is obtained.The criteria are formulated in terms of a set of linear matrix inequalities,which can be checked efficiently by use of some standard numercial packages.In order to show the stability condition in this paper gives much less conservative results than those in the literature,numerical examples are considered.
Keywords: Neural networks, Globally asymptotic stability , LMI approach , IIA approach , Time-varying delay.
Procedia APA BibTeX Chicago EndNote Harvard JSON MLA RIS XML ISO 690 PDF Downloads 19305709 A Study of the Trade-off Energy Consumption-Performance-Schedulability for DVFS Multicore Systems
Authors: Jalil Boudjadar
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Dynamic Voltage and Frequency Scaling (DVFS) multicore platforms are promising execution platforms that enable high computational performance, less energy consumption and flexibility in scheduling the system processes. However, the resulting interleaving and memory interference together with per-core frequency tuning make real-time guarantees hard to be delivered. Besides, energy consumption represents a strong constraint for the deployment of such systems on energy-limited settings. Identifying the system configurations that would achieve a high performance and consume less energy while guaranteeing the system schedulability is a complex task in the design of modern embedded systems. This work studies the trade-off between energy consumption, cores utilization and memory bottleneck and their impact on the schedulability of DVFS multicore time-critical systems with a hierarchy of shared memories. We build a model-based framework using Parametrized Timed Automata of UPPAAL to analyze the mutual impact of performance, energy consumption and schedulability of DVFS multicore systems, and demonstrate the trade-off on an actual case study.Keywords: Time-critical systems, multicore systems, schedulability analysis, performance, memory interference, energy consumption.
Procedia APA BibTeX Chicago EndNote Harvard JSON MLA RIS XML ISO 690 PDF Downloads 4485708 Qualitative Modelling for Ferromagnetic Hysteresis Cycle
Authors: M. Mordjaoui, B. Boudjema, M. Chabane, R. Daira
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In determining the electromagnetic properties of magnetic materials, hysteresis modeling is of high importance. Many models are available to investigate those characteristics but they tend to be complex and difficult to implement. In this paper a new qualitative hysteresis model for ferromagnetic core is presented, based on the function approximation capabilities of adaptive neuro fuzzy inference system (ANFIS). The proposed ANFIS model combined the neural network adaptive capabilities and the fuzzy logic qualitative approach can restored the hysteresis curve with a little RMS error. The model accuracy is good and can be easily adapted to the requirements of the application by extending or reducing the network training set and thus the required amount of measurement data.Keywords: ANFIS modeling technique, magnetic hysteresis, Jiles-Atherton model, ferromagnetic core.
Procedia APA BibTeX Chicago EndNote Harvard JSON MLA RIS XML ISO 690 PDF Downloads 15725707 Visual-Graphical Methods for Exploring Longitudinal Data
Authors: H. W. Ker
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Longitudinal data typically have the characteristics of changes over time, nonlinear growth patterns, between-subjects variability, and the within errors exhibiting heteroscedasticity and dependence. The data exploration is more complicated than that of cross-sectional data. The purpose of this paper is to organize/integrate of various visual-graphical techniques to explore longitudinal data. From the application of the proposed methods, investigators can answer the research questions include characterizing or describing the growth patterns at both group and individual level, identifying the time points where important changes occur and unusual subjects, selecting suitable statistical models, and suggesting possible within-error variance.Keywords: Data exploration, exploratory analysis, HLMs/LMEs, longitudinal data, visual-graphical methods.
Procedia APA BibTeX Chicago EndNote Harvard JSON MLA RIS XML ISO 690 PDF Downloads 20795706 Using Gaussian Process in Wind Power Forecasting
Authors: Hacene Benkhoula, Mohamed Badreddine Benabdella, Hamid Bouzeboudja, Abderrahmane Asraoui
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The wind is a random variable difficult to master, for this, we developed a mathematical and statistical methods enable to modeling and forecast wind power. Gaussian Processes (GP) is one of the most widely used families of stochastic processes for modeling dependent data observed over time, or space or time and space. GP is an underlying process formed by unrecognized operator’s uses to solve a problem. The purpose of this paper is to present how to forecast wind power by using the GP. The Gaussian process method for forecasting are presented. To validate the presented approach, a simulation under the MATLAB environment has been given.Keywords: Forecasting, Gaussian process, modeling, wind power.
Procedia APA BibTeX Chicago EndNote Harvard JSON MLA RIS XML ISO 690 PDF Downloads 17665705 A Real Time Set Up for Retrieval of Emotional States from Human Neural Responses
Authors: Rashima Mahajan, Dipali Bansal, Shweta Singh
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Real time non-invasive Brain Computer Interfaces have a significant progressive role in restoring or maintaining a quality life for medically challenged people. This manuscript provides a comprehensive review of emerging research in the field of cognitive/affective computing in context of human neural responses. The perspectives of different emotion assessment modalities like face expressions, speech, text, gestures, and human physiological responses have also been discussed. Focus has been paid to explore the ability of EEG (Electroencephalogram) signals to portray thoughts, feelings, and unspoken words. An automated workflow-based protocol to design an EEG-based real time Brain Computer Interface system for analysis and classification of human emotions elicited by external audio/visual stimuli has been proposed. The front end hardware includes a cost effective and portable Emotiv EEG Neuroheadset unit, a personal computer and a set of external stimulators. Primary signal analysis and processing of real time acquired EEG shall be performed using MATLAB based advanced brain mapping toolbox EEGLab/BCILab. This shall be followed by the development of MATLAB based self-defined algorithm to capture and characterize temporal and spectral variations in EEG under emotional stimulations. The extracted hybrid feature set shall be used to classify emotional states using artificial intelligence tools like Artificial Neural Network. The final system would result in an inexpensive, portable and more intuitive Brain Computer Interface in real time scenario to control prosthetic devices by translating different brain states into operative control signals.
Keywords: Brain Computer Interface (BCI), Electroencephalogram (EEG), EEGLab, BCILab, Emotiv, Emotions, Interval features, Spectral features, Artificial Neural Network, Control applications.
Procedia APA BibTeX Chicago EndNote Harvard JSON MLA RIS XML ISO 690 PDF Downloads 52865704 A New Scheduling Algorithm Based on Traffic Classification Using Imprecise Computation
Authors: Farzad Abtahi, Sahar Khanmohamadi, Bahram Sadeghi Bigham
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Wireless channels are characterized by more serious bursty and location-dependent errors. Many packet scheduling algorithms have been proposed for wireless networks to guarantee fairness and delay bounds. However, most existing schemes do not consider the difference of traffic natures among packet flows. This will cause the delay-weight coupling problem. In particular, serious queuing delays may be incurred for real-time flows. In this paper, it is proposed a scheduling algorithm that takes traffic types of flows into consideration when scheduling packets and also it is provided scheduling flexibility by trading off video quality to meet the playback deadline.Keywords: Data communication, Real-time, Scheduling, Video transport.
Procedia APA BibTeX Chicago EndNote Harvard JSON MLA RIS XML ISO 690 PDF Downloads 14595703 Relative Radiometric Correction of Cloudy Multitemporal Satellite Imagery
Authors: Seema Biday, Udhav Bhosle
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Repeated observation of a given area over time yields potential for many forms of change detection analysis. These repeated observations are confounded in terms of radiometric consistency due to changes in sensor calibration over time, differences in illumination, observation angles and variation in atmospheric effects. This paper demonstrates applicability of an empirical relative radiometric normalization method to a set of multitemporal cloudy images acquired by Resourcesat1 LISS III sensor. Objective of this study is to detect and remove cloud cover and normalize an image radiometrically. Cloud detection is achieved by using Average Brightness Threshold (ABT) algorithm. The detected cloud is removed and replaced with data from another images of the same area. After cloud removal, the proposed normalization method is applied to reduce the radiometric influence caused by non surface factors. This process identifies landscape elements whose reflectance values are nearly constant over time, i.e. the subset of non-changing pixels are identified using frequency based correlation technique. The quality of radiometric normalization is statistically assessed by R2 value and mean square error (MSE) between each pair of analogous band.Keywords: Correlation, Frequency domain, Multitemporal, Relative Radiometric Correction
Procedia APA BibTeX Chicago EndNote Harvard JSON MLA RIS XML ISO 690 PDF Downloads 19695702 Discrete Vector Control for Induction Motor Drives with the Rotor Time Constant Update
Authors: A.Larabi, M.S. Boucherit
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In this paper, we investigated vector control of an induction machine taking into account discretization problems of the command. In the purpose to show how to include in a discrete model of this current control and with rotor time constant update. The results of simulation obtained are very satisfaisant. That was possible thanks to the good choice of the values of the parameters of the regulators used which shows, the founded good of the method used, for the choice of the parameters of the discrete regulators. The simulation results are presented at the end of this paper.
Keywords: Induction motor, discrete vector control, PIRegulator, transformation of park, PWM.
Procedia APA BibTeX Chicago EndNote Harvard JSON MLA RIS XML ISO 690 PDF Downloads 14985701 An Approximation Method for Exact Boundary Controllability of Euler-Bernoulli System
Authors: Abdelaziz Khernane, Naceur Khelil, Leila Djerou
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The aim of this work is to study the numerical implementation of the Hilbert Uniqueness Method for the exact boundary controllability of Euler-Bernoulli beam equation. This study may be difficult. This will depend on the problem under consideration (geometry, control and dimension) and the numerical method used. Knowledge of the asymptotic behaviour of the control governing the system at time T may be useful for its calculation. This idea will be developed in this study. We have characterized as a first step, the solution by a minimization principle and proposed secondly a method for its resolution to approximate the control steering the considered system to rest at time T.Keywords: Boundary control, exact controllability, finite difference methods, functional optimization.
Procedia APA BibTeX Chicago EndNote Harvard JSON MLA RIS XML ISO 690 PDF Downloads 14725700 Inventory Control for a Joint Replenishment Problem with Stochastic Demand
Authors: Bassem Roushdy, Nahed Sobhy, Abdelrhim Abdelhamid, Ahmed Mahmoud
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Most papers model Joint Replenishment Problem (JRP) as a (kT,S) where kT is a multiple value for a common review period T,and S is a predefined order up to level. In general the (T,S) policy is characterized by a long out of control period which requires a large amount of safety stock compared to the (R,Q) policy. In this paper a probabilistic model is built where an item, call it item(i), with the shortest order time between interval (T)is modeled under (R,Q) policy and its inventory is continuously reviewed, while the rest of items (j) are periodically reviewed at a definite time corresponding to itemKeywords: Inventory management, Joint replenishment, policy evaluation, stochastic process
Procedia APA BibTeX Chicago EndNote Harvard JSON MLA RIS XML ISO 690 PDF Downloads 30335699 Development of an Adhesive from Prosopis africana Seed Endosperm (Okpeyi)
Authors: Nwangwu Florence Chinyere, Ene Rosemary Ndidiamaka
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This research work is an experimental study, through development of an adhesive from Prosopis africana endosperm. The prosopis seed for this work were obtained from Enugu State in the South East part of Nigeria. The seeds were prepared by separating the endosperm from the seed coat and cotyledon. Three methods were used to separate them, which are acidic method, roasting method and boiling method. 20g of seed were treated with different concentrations (25, 40, 55, 70, and 85% w/w) at 100°C and constant time (30 minutes), under continuous stirring with magnetic stirrer. Also 20g of seed were treated with sulphuric acid of concentrations 40% w/w at 100°C with different time (10, 15, 20, 25, 30 minutes), under continuous stirring with magnetic stirrer. Finally, 20g of seed were treated with sulphuric acid of concentrations 40% w/w at different temperature (20°C, 40°C, 60°C, 80°C, and 100°C) with constant time (30 minutes), under continuous stirring with magnetic stirrer. The whole endosperm extracted was adhesive. The physical properties of the adhesive were determined (appearance, odour, taste, solubility, pH, size, and binding strength). The percentage of the adhesive yield makes the commercialization of the seed in Nigeria possible and profitable. The very high viscosity attained at low concentrations makes prosopis adhesive an excellent thickener in the food industry.Keywords: Endosperm, adhesive, ethanol, Prosopis africana seed.
Procedia APA BibTeX Chicago EndNote Harvard JSON MLA RIS XML ISO 690 PDF Downloads 14145698 Affecting Factors of the Mechanical Properties to Phenolic/Fiber Composite
Authors: Thirapat Kitinirunkul, Nattawat Winya, Komson Prapunkarn
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Influences of the amount of phenolic, curing temperature and curing time on the Mechanical Properties of phenolic/fiber composite were investigated by using two-level factorial design. The latter was used to determine the affects of those factors on mechanical properties. The purpose of this study was to investigate the affects of amount of phenolic, curing temperature and curing time of the composite to determine the best condition for mechanical properties according to MIL-I-24768 by the tensile strength is more than 103 MPa.
Keywords: Phenolic Resin, Composite, Fiber Composite, Affecting Factors.
Procedia APA BibTeX Chicago EndNote Harvard JSON MLA RIS XML ISO 690 PDF Downloads 41025697 Effect of Pack Aluminising Conditions on βNiAl Coatings
Authors: A. D. Chandio, P. Xiao
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In this study, nickel aluminide coatings were deposited onto CMSX-4 single crystal superalloy and pure Ni substrates by using in-situ chemical vapour deposition (CVD) technique. The microstructural evolutions and coating thickness (CT) were studied upon the variation of processing conditions i.e. time and temperature. The results demonstrated (under identical conditions) that coating formed on pure Ni contains no substrate entrapments and have lower CT in comparison to one deposited on the CMSX-4 counterpart. In addition, the interdiffusion zone (IDZ) of Ni substrate is a γ’-Ni3Al in comparison to the CMSX-4 alloy that is βNiAl phase. The higher CT on CMSX-4 superalloy is attributed to presence of γ-Ni/γ’-Ni3Al structure which contains ~ 15 at.% Al before deposition (that is already present in superalloy). Two main deposition parameters (time and temperature) of the coatings were also studied in addition to standard comparison of substrate effects. The coating formation time was found to exhibit profound effect on CT, whilst temperature was found to change coating activities. In addition, the CT showed linear trend from 800 to 1000 °C, thereafter reduction was observed. This was attributed to the change in coating activities.
Keywords: βNiAl, in-situ CVD, CT, CMSX-4, Ni, microstructure.
Procedia APA BibTeX Chicago EndNote Harvard JSON MLA RIS XML ISO 690 PDF Downloads 24005696 Incorporation of Long-Term Redundancy in ECG Time Domain Compression Methods through Curve Simplification and Block-Sorting
Authors: Bachir Boucheham, Youcef Ferdi, Mohamed Chaouki Batouche
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We suggest a novel method to incorporate longterm redundancy (LTR) in signal time domain compression methods. The proposition is based on block-sorting and curve simplification. The proposition is illustrated on the ECG signal as a post-processor for the FAN method. Test applications on the new so-obtained FAN+ method using the MIT-BIH database show substantial improvement of the compression ratio-distortion behavior for a higher quality reconstructed signal.Keywords: ECG compression, Long-term redundancy, Block-sorting, Curve Simplification.
Procedia APA BibTeX Chicago EndNote Harvard JSON MLA RIS XML ISO 690 PDF Downloads 15125695 A Performance Evaluation of Oscillation Based Test in Continuous Time Filters
Authors: Eduardo Romero, Marcelo Costamagna, Gabriela Peretti, Carlos Marqués
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This work evaluates the ability of OBT for detecting parametric faults in continuous-time filters. To this end, we adopt two filters with quite different topologies as cases of study and a previously reported statistical fault model. In addition, we explore the behavior of the test schemes when a particular test condition is changed. The new data reported here, obtained from a fault simulation process, reveal a lower performance of OBT not observed in previous work using single-deviation faults, even under the change in the test condition.
Keywords: Testing, analog fault simulation, analog filter test, oscillation based test.
Procedia APA BibTeX Chicago EndNote Harvard JSON MLA RIS XML ISO 690 PDF Downloads 14305694 A Survey of IMRT and VMAT in UK
Authors: A. Taqaddas
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Purpose: This E-survey was carried out to facilitate the implementation and Education of VMAT (Volumetric Modulated Arc Therapy) in Radiotherapy-RT departments and reasons for not using IMRT (Intensity Modulated Radiotherapy). VMAT Skills in demand were also identified. Method: E-Survey was distributed to NHS hospitals across UK by email. Thirty NHS and related centres in England, 21 in Scotland, 3 in Ireland and 1 in Wales were contacted. This Survey was intended for those working in RT and Medical Physics and who were responsible for Treatment Planning and training. Results: This E-survey have indicated pathways adopted by staff to acquire VMAT skills, strategies to efficiently implement VMAT in RT departments and for obtaining VMAT Education. Conclusion: Despite poor survey response this survey has managed to highlight requirements for education and implementation of VMAT that are also applicable to IMRT. Other RT centres in world can also find these results useful.
Keywords: IMRT, Radiotherapy, Treatment Planning, VMAT.
Procedia APA BibTeX Chicago EndNote Harvard JSON MLA RIS XML ISO 690 PDF Downloads 24665693 Optimization of Deglet-Nour Date (Phoenix dactylifera L.) Phenol Extraction Conditions
Authors: Lekbir Adel, Alloui-Lombarkia Ourida, Mekentichi Sihem, Noui Yassine, Baississe Salima
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The objective of this study was to optimize the extraction conditions for phenolic compounds, total flavonoids, and antioxidant activity from Deglet-Nour variety. The extraction of active components from natural sources depends on different factors. The knowledge of the effects of different extraction parameters is useful for the optimization of the process, as well for the ability to predict the extraction yield. The effects of extraction variables, namely types of solvent (methanol, ethanol and acetone) and extraction time (1h, 6h, 12h and 24h) on phenolics extraction yield were evaluated. It has been shown that the time of extraction and types of solvent have a statistically significant influence on the extraction of phenolic compounds from Deglet-Nour variety. The optimised conditions yielded values of 80.19 ± 6.37 mg GAE/100 g FW for TPC, 2.34 ± 0.27 mg QE/100 g FW for TFC and 90.20 ± 1.29% for antioxidant activity were methanol solvent and 6 hours of time. According to the results obtained in this study, Deglet-Nour variety can be considered as a natural source of phenolic compounds with good antioxidant capacity.
Keywords: Deglet-Nour variety, Date palm Fruit, Phenolic compounds, Total flavonoids, Antioxidant activity, Extraction, Optimization.
Procedia APA BibTeX Chicago EndNote Harvard JSON MLA RIS XML ISO 690 PDF Downloads 26595692 Evolving Neural Networks using Moment Method for Handwritten Digit Recognition
Authors: H. El Fadili, K. Zenkouar, H. Qjidaa
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This paper proposes a neural network weights and topology optimization using genetic evolution and the backpropagation training algorithm. The proposed crossover and mutation operators aims to adapt the networks architectures and weights during the evolution process. Through a specific inheritance procedure, the weights are transmitted from the parents to their offsprings, which allows re-exploitation of the already trained networks and hence the acceleration of the global convergence of the algorithm. In the preprocessing phase, a new feature extraction method is proposed based on Legendre moments with the Maximum entropy principle MEP as a selection criterion. This allows a global search space reduction in the design of the networks. The proposed method has been applied and tested on the well known MNIST database of handwritten digits.Keywords: Genetic algorithm, Legendre Moments, MEP, Neural Network.
Procedia APA BibTeX Chicago EndNote Harvard JSON MLA RIS XML ISO 690 PDF Downloads 16545691 Smart Side View Mirror Camera for Real Time System
Authors: Nunziata Ivana Guarneri, Arcangelo Bruna, Giuseppe Spampinato, Antonio Buemi
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In the last decade, automotive companies have invested a lot in terms of innovation about many aspects regarding the automatic driver assistance systems. One innovation regards the usage of a smart camera placed on the car’s side mirror for monitoring the back and lateral road situation. A common road scenario is the overtaking of the preceding car and, in this case, a brief distraction or a loss of concentration can lead the driver to undertake this action, even if there is an already overtaking vehicle, leading to serious accidents. A valid support for a secure drive can be a smart camera system, which is able to automatically analyze the road scenario and consequentially to warn the driver when another vehicle is overtaking. This paper describes a method for monitoring the side view of a vehicle by using camera optical flow motion vectors. The proposed solution detects the presence of incoming vehicles, assesses their distance from the host car, and warns the driver through different levels of alert according to the estimated distance. Due to the low complexity and computational cost, the proposed system ensures real time performances.
Keywords: Camera calibration, ego motion, kalman filters, object tracking, real time systems.
Procedia APA BibTeX Chicago EndNote Harvard JSON MLA RIS XML ISO 690 PDF Downloads 8765690 Bayesian Deep Learning Algorithms for Classifying COVID-19 Images
Authors: I. Oloyede
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The study investigates the accuracy and loss of deep learning algorithms with the set of coronavirus (COVID-19) images dataset by comparing Bayesian convolutional neural network and traditional convolutional neural network in low dimensional dataset. 50 sets of X-ray images out of which 25 were COVID-19 and the remaining 20 were normal, twenty images were set as training while five were set as validation that were used to ascertained the accuracy of the model. The study found out that Bayesian convolution neural network outperformed conventional neural network at low dimensional dataset that could have exhibited under fitting. The study therefore recommended Bayesian Convolutional neural network (BCNN) for android apps in computer vision for image detection.Keywords: BCNN, CNN, Images, COVID-19, Deep Learning.
Procedia APA BibTeX Chicago EndNote Harvard JSON MLA RIS XML ISO 690 PDF Downloads 848