Search results for: filtering algorithm
Commenced in January 2007
Frequency: Monthly
Edition: International
Paper Count: 3796

Search results for: filtering algorithm

1786 Removal of Heavy Metal, Dye and Salinity from Industrial Wastewaters by Banana Rachis Cellulose Micro Crystal-Clay Composite

Authors: Mohd Maniruzzaman, Md. Monjurul Alam, Md. Hafezur Rahaman, Anika Amir Mohona

Abstract:

The consumption of water by various industries is increasing day by day, and the wastewaters from them are increasing as well. These wastewaters consist of various kinds of color, dissolved solids, toxic heavy metals, residual chlorine, and other non-degradable organic materials. If these wastewaters are exposed directly to the environment, it will be hazardous for the environment and personal health. So, it is very necessary to treat these wastewaters before exposing into the environment. In this research, we have demonstrated the successful processing and utilization of fully bio-based cellulose micro crystal (CMC) composite for the removal of heavy metals, dyes, and salinity from industrial wastewaters. Banana rachis micro-cellulose were prepared by acid hydrolysis (H₂SO₄) of banana (Musa acuminata L.) rachis fiber, and Bijoypur raw clay were treated by organic solvent tri-ethyl amine. Composites were prepared with varying different composition of banana rachis nano-cellulose and modified Bijoypur (north-east part in Bangladesh) clay. After the successful characterization of cellulose micro crystal (CMC) and modified clay, our targeted filter was fabricated with different composition of cellulose micro crystal and clay in the locally fabricated packing column with 7.5 cm as thickness of composites fraction. Waste-water was collected from local small textile industries containing basic yellow 2 as dye, lead (II) nitrate [Pb(NO₃)₂] and chromium (III) nitrate [Cr(NO₃)₃] as heavy metals and saline water was collected from Khulna to test the efficiency of banana rachis cellulose micro crystal-clay composite for removing the above impurities. The filtering efficiency of wastewater purification was characterized by Fourier transforms infrared spectroscopy (FTIR), X-ray diffraction (X-RD), thermo gravimetric analysis (TGA), atomic absorption spectrometry (AAS), scanning electron microscopy (SEM) analyses. Finally, our all characterizations data are shown with very high expected results for in industrial application of our fabricated filter.

Keywords: banana rachis, bio-based filter, cellulose micro crystal-clay composite, wastewaters, synthetic dyes, heavy metal, water salinity

Procedia PDF Downloads 118
1785 Optimization of Robot Motion Planning Using Biogeography Based Optimization (Bbo)

Authors: Jaber Nikpouri, Arsalan Amralizadeh

Abstract:

In robotics manipulators, the trajectory should be optimum, thus the torque of the robot can be minimized in order to save power. This paper includes an optimal path planning scheme for a robotic manipulator. Recently, techniques based on metaheuristics of natural computing, mainly evolutionary algorithms (EA), have been successfully applied to a large number of robotic applications. In this paper, the improved BBO algorithm is used to minimize the objective function in the presence of different obstacles. The simulation represents that the proposed optimal path planning method has satisfactory performance.

Keywords: biogeography-based optimization, path planning, obstacle detection, robotic manipulator

Procedia PDF Downloads 283
1784 A PHREEQC Reactive Transport Simulation for Simply Determining Scaling during Desalination

Authors: Andrew Freiburger, Sergi Molins

Abstract:

Freshwater is a vital resource; yet, the supply of clean freshwater is diminishing as the consequence of melting snow and ice from global warming, pollution from industry, and an increasing demand from human population growth. The unsustainable trajectory of diminishing water resources is projected to jeopardize water security for billions of people in the 21st century. Membrane desalination technologies may resolve the growing discrepancy between supply and demand by filtering arbitrary feed water into a fraction of renewable, clean water and a fraction of highly concentrated brine. The leading hindrance of membrane desalination is fouling, whereby the highly concentrated brine solution encourages micro-organismal colonization and/or the precipitation of occlusive minerals (i.e. scale) upon the membrane surface. Thus, an understanding of brine formation is necessary to mitigate membrane fouling and to develop efficacious desalination technologies that can bolster the supply of available freshwater. This study presents a reactive transport simulation of brine formation and scale deposition during reverse osmosis (RO) desalination. The simulation conceptually represents the RO module as a one-dimensional domain, where feed water directionally enters the domain with a prescribed fluid velocity and is iteratively concentrated in the immobile layer of a dual porosity model. Geochemical PHREEQC code numerically evaluated the conceptual model with parameters for the BW30-400 RO module and for real water feed sources – e.g. the Red and Mediterranean seas, and produced waters from American oil-wells, based upon peer-review data. The presented simulation is computationally simpler, and hence less resource intensive, than the existent and more rigorous simulations of desalination phenomena, like TOUGHREACT. The end-user may readily prepare input files and execute simulations on a personal computer with open source software. The graphical results of fouling-potential and brine characteristics may therefore be particularly useful as the initial tool for screening candidate feed water sources and/or informing the selection of an RO module.

Keywords: desalination, PHREEQC, reactive transport, scaling

Procedia PDF Downloads 125
1783 Identification of Nonlinear Systems Structured by Hammerstein-Wiener Model

Authors: A. Brouri, F. Giri, A. Mkhida, A. Elkarkri, M. L. Chhibat

Abstract:

Standard Hammerstein-Wiener models consist of a linear subsystem sandwiched by two memoryless nonlinearities. Presently, the linear subsystem is allowed to be parametric or not, continuous- or discrete-time. The input and output nonlinearities are polynomial and may be noninvertible. A two-stage identification method is developed such the parameters of all nonlinear elements are estimated first using the Kozen-Landau polynomial decomposition algorithm. The obtained estimates are then based upon in the identification of the linear subsystem, making use of suitable pre-ad post-compensators.

Keywords: nonlinear system identification, Hammerstein-Wiener systems, frequency identification, polynomial decomposition

Procedia PDF Downloads 498
1782 Network Traffic Classification Scheme for Internet Network Based on Application Categorization for Ipv6

Authors: Yaser Miaji, Mohammed Aloryani

Abstract:

The rise of recent applications in everyday implementation like videoconferencing, online recreation and voice speech communication leads to pressing the need for novel mechanism and policy to serve this steep improvement within the application itself and users‟ wants. This diversity in web traffics needs some classification and prioritization of the traffics since some traffics merit abundant attention with less delay and loss, than others. This research is intended to reinforce the mechanism by analysing the performance in application according to the proposed mechanism implemented. The mechanism used is quite direct and analytical. The mechanism is implemented by modifying the queue limit in the algorithm.

Keywords: traffic classification, IPv6, internet, application categorization

Procedia PDF Downloads 550
1781 Parallel Asynchronous Multi-Splitting Methods for Differential Algebraic Systems

Authors: Malika Elkyal

Abstract:

We consider an iterative parallel multi-splitting method for differential algebraic equations. The main feature of the proposed idea is to use the asynchronous form. We prove that the multi-splitting technique can effectively accelerate the convergent performance of the iterative process. The main characteristic of an asynchronous mode is that the local algorithm does not have to wait at predetermined messages to become available. We allow some processors to communicate more frequently than others, and we allow the communication delays to be substantial and unpredictable. Accordingly, we note that synchronous algorithms in the computer science sense are particular cases of our formulation of asynchronous one.

Keywords: parallel methods, asynchronous mode, multisplitting, differential algebraic equations

Procedia PDF Downloads 547
1780 Three-Level Converters Back-To-Back DC Bus Control for Torque Ripple Reduction of Induction Motor

Authors: T. Abdelkrim, K. Benamrane, B. Bezza, Aeh Benkhelifa, A. Borni

Abstract:

This paper proposes a regulation method of back-to-back connected three-level converters in order to reduce the torque ripple in induction motor. First part is dedicated to the presentation of the feedback control of three-level PWM rectifier. In the second part, three-level NPC voltage source inverter balancing DC bus algorithm is presented. A theoretical analysis with a complete simulation of the system is presented to prove the excellent performance of the proposed technique.

Keywords: back-to-back connection, feedback control, neutral-point balance, three-level converter, torque ripple

Procedia PDF Downloads 485
1779 The Regulation of Reputational Information in the Sharing Economy

Authors: Emre Bayamlıoğlu

Abstract:

This paper aims to provide an account of the legal and the regulative aspects of the algorithmic reputation systems with a special emphasis on the sharing economy (i.e., Uber, Airbnb, Lyft) business model. The first section starts with an analysis of the legal and commercial nature of the tripartite relationship among the parties, namely, the host platform, individual sharers/service providers and the consumers/users. The section further examines to what extent an algorithmic system of reputational information could serve as an alternative to legal regulation. Shortcomings are explained and analyzed with specific examples from Airbnb Platform which is a pioneering success in the sharing economy. The following section focuses on the issue of governance and control of the reputational information. The section first analyzes the legal consequences of algorithmic filtering systems to detect undesired comments and how a delicate balance could be struck between the competing interests such as freedom of speech, privacy and the integrity of the commercial reputation. The third section deals with the problem of manipulation by users. Indeed many sharing economy businesses employ certain techniques of data mining and natural language processing to verify consistency of the feedback. Software agents referred as "bots" are employed by the users to "produce" fake reputation values. Such automated techniques are deceptive with significant negative effects for undermining the trust upon which the reputational system is built. The third section is devoted to explore the concerns with regard to data mobility, data ownership, and the privacy. Reputational information provided by the consumers in the form of textual comment may be regarded as a writing which is eligible to copyright protection. Algorithmic reputational systems also contain personal data pertaining both the individual entrepreneurs and the consumers. The final section starts with an overview of the notion of reputation as a communitarian and collective form of referential trust and further provides an evaluation of the above legal arguments from the perspective of public interest in the integrity of reputational information. The paper concludes with certain guidelines and design principles for algorithmic reputation systems, to address the above raised legal implications.

Keywords: sharing economy, design principles of algorithmic regulation, reputational systems, personal data protection, privacy

Procedia PDF Downloads 457
1778 Natural Convection between Two Parallel Wavy Plates

Authors: Si Abdallah Mayouf

Abstract:

In this work, the effects of the wavy surface on free convection heat transfer boundary layer flow between two parallel wavy plates have been studied numerically. The two plates are considered at a constant temperature. The equations and the boundary conditions are discretized by the finite difference scheme and solved numerically using the Gauss-Seidel algorithm. The important parameters in this problem are the amplitude of the wavy surfaces and the distance between the two wavy plates. Results are presented as velocity profiles, temperature profiles and local Nusselt number according to the important parameters.

Keywords: free convection, wavy surface, parallel plates, fluid dynamics

Procedia PDF Downloads 298
1777 Variations in Spatial Learning and Memory across Natural Populations of Zebrafish, Danio rerio

Authors: Tamal Roy, Anuradha Bhat

Abstract:

Cognitive abilities aid fishes in foraging, avoiding predators & locating mates. Factors like predation pressure & habitat complexity govern learning & memory in fishes. This study aims to compare spatial learning & memory across four natural populations of zebrafish. Zebrafish, a small cyprinid inhabits a diverse range of freshwater habitats & this makes it amenable to studies investigating role of native environment in spatial cognitive abilities. Four populations were collected across India from waterbodies with contrasting ecological conditions. Habitat complexity of the water-bodies was evaluated as a combination of channel substrate diversity and diversity of vegetation. Experiments were conducted on populations under controlled laboratory conditions. A square shaped spatial testing arena (maze) was constructed for testing the performance of adult zebrafish. The square tank consisted of an inner square shaped layer with the edges connected to the diagonal ends of the tank-walls by connections thereby forming four separate chambers. Each of the four chambers had a main door in the centre. Each chamber had three sections separated by two windows. A removable coloured window-pane (red, yellow, green or blue) identified each main door. A food reward associated with an artificial plant was always placed inside the left-hand section of the red-door chamber. The position of food-reward and plant within the red-door chamber was fixed. A test fish would have to explore the maze by taking turns and locate the food inside the right-side section of the red-door chamber. Fishes were sorted from each population stock and kept individually in separate containers for identification. At a time, a test fish was released into the arena and allowed 20 minutes to explore in order to find the food-reward. In this way, individual fishes were trained through the maze to locate the food reward for eight consecutive days. The position of red door, with the plant and the reward, was shuffled every day. Following training, an intermission of four days was given during which the fishes were not subjected to trials. Post-intermission, the fishes were re-tested on the 13th day following the same protocol for their ability to remember the learnt task. Exploratory tendencies and latency of individuals to explore on 1st day of training, performance time across trials, and number of mistakes made each day were recorded. Additionally, mechanism used by individuals to solve the maze each day was analyzed across populations. Fishes could be expected to use algorithm (sequence of turns) or associative cues in locating the food reward. Individuals of populations did not differ significantly in latencies and tendencies to explore. No relationship was found between exploration and learning across populations. High habitat-complexity populations had higher rates of learning & stronger memory while low habitat-complexity populations had lower rates of learning and much reduced abilities to remember. High habitat-complexity populations used associative cues more than algorithm for learning and remembering while low habitat-complexity populations used both equally. The study, therefore, helped understand the role of natural ecology in explaining variations in spatial learning abilities across populations.

Keywords: algorithm, associative cue, habitat complexity, population, spatial learning

Procedia PDF Downloads 279
1776 Direct Torque Control of Induction Motor Employing Differential Evolution Algorithm

Authors: T. Vamsee Kiran, A. Gopi

Abstract:

The undesired torque and flux ripple may occur in conventional direct torque control (DTC) induction motor drive. DTC can improve the system performance at low speeds by continuously tuning the regulator by adjusting the Kp, Ki values. In this differential evolution (DE) is proposed to adjust the parameters (Kp, Ki) of the speed controller in order to minimize torque ripple, flux ripple, and stator current distortion.The DE based PI controller has resulted is maintaining a constant speed of the motor irrespective of the load torque fluctuations.

Keywords: differential evolution, direct torque control, PI controller

Procedia PDF Downloads 418
1775 Comparative Study of Universities’ Web Structure Mining

Authors: Z. Abdullah, A. R. Hamdan

Abstract:

This paper is meant to analyze the ranking of University of Malaysia Terengganu, UMT’s website in the World Wide Web. There are only few researches have been done on comparing the ranking of universities’ websites so this research will be able to determine whether the existing UMT’s website is serving its purpose which is to introduce UMT to the world. The ranking is based on hub and authority values which are accordance to the structure of the website. These values are computed using two web-searching algorithms, HITS and SALSA. Three other universities’ websites are used as the benchmarks which are UM, Harvard and Stanford. The result is clearly showing that more work has to be done on the existing UMT’s website where important pages according to the benchmarks, do not exist in UMT’s pages. The ranking of UMT’s website will act as a guideline for the web-developer to develop a more efficient website.

Keywords: algorithm, ranking, website, web structure mining

Procedia PDF Downloads 498
1774 Numerical Simulation on Airflow Structure in the Human Upper Respiratory Tract Model

Authors: Xiuguo Zhao, Xudong Ren, Chen Su, Xinxi Xu, Fu Niu, Lingshuai Meng

Abstract:

The respiratory diseases such as asthma, emphysema and bronchitis are connected with the air pollution and the number of these diseases tends to increase, which may attribute to the toxic aerosol deposition in human upper respiratory tract or in the bifurcation of human lung. The therapy of these diseases mostly uses pharmaceuticals in the form of aerosol delivered into the human upper respiratory tract or the lung. Understanding of airflow structures in human upper respiratory tract plays a very important role in the analysis of the “filtering” effect in the pharynx/larynx and for obtaining correct air-particle inlet conditions to the lung. However, numerical simulation based CFD (Computational Fluid Dynamics) technology has its own advantage on studying airflow structure in human upper respiratory tract. In this paper, a representative human upper respiratory tract is built and the CFD technology was used to investigate the air movement characteristic in the human upper respiratory tract. The airflow movement characteristic, the effect of the airflow movement on the shear stress distribution and the probability of the wall injury caused by the shear stress are discussed. Experimentally validated computational fluid-aerosol dynamics results showed the following: the phenomenon of airflow separation appears near the outer wall of the pharynx and the trachea. The high velocity zone is created near the inner wall of the trachea. The airflow splits at the divider and a new boundary layer is generated at the inner wall of the downstream from the bifurcation with the high velocity near the inner wall of the trachea. The maximum velocity appears at the exterior of the boundary layer. The secondary swirls and axial velocity distribution result in the high shear stress acting on the inner wall of the trachea and bifurcation, finally lead to the inner wall injury. The enhancement of breathing intensity enhances the intensity of the shear stress acting on the inner wall of the trachea and the bifurcation. If human keep the high breathing intensity for long time, not only the ability for the transportation and regulation of the gas through the trachea and the bifurcation fall, but also result in the increase of the probability of the wall strain and tissue injury.

Keywords: airflow structure, computational fluid dynamics, human upper respiratory tract, wall shear stress, numerical simulation

Procedia PDF Downloads 231
1773 Response of a Bridge Crane during an Earthquake

Authors: F. Fekak, A. Gravouil, M. Brun, B. Depale

Abstract:

During an earthquake, a bridge crane may be subjected to multiple impacts between crane wheels and rail. In order to model such phenomena, a time-history dynamic analysis with a multi-scale approach is performed. The high frequency aspect of the impacts between wheels and rails is taken into account by a Lagrange explicit event-capturing algorithm based on a velocity-impulse formulation to resolve contacts and impacts. An implicit temporal scheme is used for the rest of the structure. The numerical coupling between the implicit and the explicit schemes is achieved with a heterogeneous asynchronous time-integrator.

Keywords: bridge crane, earthquake, dynamic analysis, explicit, implicit, impact

Procedia PDF Downloads 292
1772 Lacunarity measures on Mammographic Image Applying Fractal Dimension and Lacunarity Measures

Authors: S. Sushma, S. Balasubramanian, K. C. Latha, R. Sridhar

Abstract:

Structural texture measures are used to address the aspect of breast cancer risk assessment in screening mammograms. The current study investigates whether texture properties characterized by local Fractal Dimension (FD) and lacunarity contribute to assess breast cancer risk. Fractal Dimension represents the complexity while the lacunarity characterize the gap of a fractal dimension. In this paper, we present our result confirming that the lacunarity value resulted in algorithm using mammogram images states that level of lacunarity will be low when the Fractal Dimension value will be high.

Keywords: breast cancer, fractal dimension, image analysis, lacunarity, mammogram

Procedia PDF Downloads 377
1771 GPU-Based Back-Projection of Synthetic Aperture Radar (SAR) Data onto 3D Reference Voxels

Authors: Joshua Buli, David Pietrowski, Samuel Britton

Abstract:

Processing SAR data usually requires constraints in extent in the Fourier domain as well as approximations and interpolations onto a planar surface to form an exploitable image. This results in a potential loss of data requires several interpolative techniques, and restricts visualization to two-dimensional plane imagery. The data can be interpolated into a ground plane projection, with or without terrain as a component, all to better view SAR data in an image domain comparable to what a human would view, to ease interpretation. An alternate but computationally heavy method to make use of more of the data is the basis of this research. Pre-processing of the SAR data is completed first (matched-filtering, motion compensation, etc.), the data is then range compressed, and lastly, the contribution from each pulse is determined for each specific point in space by searching the time history data for the reflectivity values for each pulse summed over the entire collection. This results in a per-3D-point reflectivity using the entire collection domain. New advances in GPU processing have finally allowed this rapid projection of acquired SAR data onto any desired reference surface (called backprojection). Mathematically, the computations are fast and easy to implement, despite limitations in SAR phase history data size and 3D-point cloud size. Backprojection processing algorithms are embarrassingly parallel since each 3D point in the scene has the same reflectivity calculation applied for all pulses, independent of all other 3D points and pulse data under consideration. Therefore, given the simplicity of the single backprojection calculation, the work can be spread across thousands of GPU threads allowing for accurate reflectivity representation of a scene. Furthermore, because reflectivity values are associated with individual three-dimensional points, a plane is no longer the sole permissible mapping base; a digital elevation model or even a cloud of points (collected from any sensor capable of measuring ground topography) can be used as a basis for the backprojection technique. This technique minimizes any interpolations and modifications of the raw data, maintaining maximum data integrity. This innovative processing will allow for SAR data to be rapidly brought into a common reference frame for immediate exploitation and data fusion with other three-dimensional data and representations.

Keywords: backprojection, data fusion, exploitation, three-dimensional, visualization

Procedia PDF Downloads 64
1770 An Investigation about Rate Of Evaporation from the Water Surface and LNG Pool

Authors: Farokh Alipour, Ali Falavand, Neda Beit Saeid

Abstract:

The calculation of the effect of accidental releases of flammable materials such as LNG requires the use of a suitable consequence model. This study is due to providing a planning advice for developments in the vicinity of LNG sites and other sites handling flammable materials. In this paper, an applicable algorithm that is able to model pool fires on water is presented and applied to estimate pool fire damage zone. This procedure can be used to model pool fires on land and could be helpful in consequence modeling and domino effect zone measurements of flammable materials which is needed in site selection and plant layout.

Keywords: LNG, pool fire, spill, radiation

Procedia PDF Downloads 388
1769 On Hankel Matrices Approach to Interpolation Problem in Infinite and Finite Fields

Authors: Ivan Baravy

Abstract:

Interpolation problem, as it was initially posed in terms of polynomials, is well researched. However, further mathematical developments extended it significantly. Trigonometric interpolation is widely used in Fourier analysis, while its generalized representation as exponential interpolation is applicable to such problem of mathematical physics as modelling of Ziegler-Biersack-Littmark repulsive interatomic potentials. Formulated for finite fields, this problem arises in decoding Reed--Solomon codes. This paper shows the relation between different interpretations of the problem through the class of matrices of special structure - Hankel matrices.

Keywords: Berlekamp-Massey algorithm, exponential interpolation, finite fields, Hankel matrices, Hankel polynomials

Procedia PDF Downloads 508
1768 A Mean–Variance–Skewness Portfolio Optimization Model

Authors: Kostas Metaxiotis

Abstract:

Portfolio optimization is one of the most important topics in finance. This paper proposes a mean–variance–skewness (MVS) portfolio optimization model. Traditionally, the portfolio optimization problem is solved by using the mean–variance (MV) framework. In this study, we formulate the proposed model as a three-objective optimization problem, where the portfolio's expected return and skewness are maximized whereas the portfolio risk is minimized. For solving the proposed three-objective portfolio optimization model we apply an adapted version of the non-dominated sorting genetic algorithm (NSGAII). Finally, we use a real dataset from FTSE-100 for validating the proposed model.

Keywords: evolutionary algorithms, portfolio optimization, skewness, stock selection

Procedia PDF Downloads 189
1767 Object Oriented Classification Based on Feature Extraction Approach for Change Detection in Coastal Ecosystem across Kochi Region

Authors: Mohit Modi, Rajiv Kumar, Manojraj Saxena, G. Ravi Shankar

Abstract:

Change detection of coastal ecosystem plays a vital role in monitoring and managing natural resources along the coastal regions. The present study mainly focuses on the decadal change in Kochi islands connecting the urban flatland areas and the coastal regions where sand deposits have taken place. With this, in view, the change detection has been monitored in the Kochi area to apprehend the urban growth and industrialization leading to decrease in the wetland ecosystem. The region lies between 76°11'19.134"E to 76°25'42.193"E and 9°52'35.719"N to 10°5'51.575"N in the south-western coast of India. The IRS LISS-IV satellite image has been processed using a rule-based algorithm to classify the LULC and to interpret the changes between 2005 & 2015. The approach takes two steps, i.e. extracting features as a single GIS vector layer using different parametric values and to dissolve them. The multi-resolution segmentation has been carried out on the scale ranging from 10-30. The different classes like aquaculture, agricultural land, built-up, wetlands etc. were extracted using parameters like NDVI, mean layer values, the texture-based feature with corresponding threshold values using a rule set algorithm. The objects obtained in the segmentation process were visualized to be overlaying the satellite image at a scale of 15. This layer was further segmented using the spectral difference segmentation rule between the objects. These individual class layers were dissolved in the basic segmented layer of the image and were interpreted in vector-based GIS programme to achieve higher accuracy. The result shows a rapid increase in an industrial area of 40% based on industrial area statistics of 2005. There is a decrease in wetlands area which has been converted into built-up. New roads have been constructed which are connecting the islands to urban areas as well as highways. The increase in coastal region has been visualized due to sand depositions. The outcome is well supported by quantitative assessments which will empower rich understanding of land use land cover change for appropriate policy intervention and further monitoring.

Keywords: land use land cover, multiresolution segmentation, NDVI, object based classification

Procedia PDF Downloads 176
1766 Inverse Polynomial Numerical Scheme for the Solution of Initial Value Problems in Ordinary Differential Equations

Authors: Ogunrinde Roseline Bosede

Abstract:

This paper presents the development, analysis and implementation of an inverse polynomial numerical method which is well suitable for solving initial value problems in first order ordinary differential equations with applications to sample problems. We also present some basic concepts and fundamental theories which are vital to the analysis of the scheme. We analyzed the consistency, convergence, and stability properties of the scheme. Numerical experiments were carried out and the results compared with the theoretical or exact solution and the algorithm was later coded using MATLAB programming language.

Keywords: differential equations, numerical, polynomial, initial value problem, differential equation

Procedia PDF Downloads 434
1765 Providing Security to Private Cloud Using Advanced Encryption Standard Algorithm

Authors: Annapureddy Srikant Reddy, Atthanti Mahendra, Samala Chinni Krishna, N. Neelima

Abstract:

In our present world, we are generating a lot of data and we, need a specific device to store all these data. Generally, we store data in pen drives, hard drives, etc. Sometimes we may loss the data due to the corruption of devices. To overcome all these issues, we implemented a cloud space for storing the data, and it provides more security to the data. We can access the data with just using the internet from anywhere in the world. We implemented all these with the java using Net beans IDE. Once user uploads the data, he does not have any rights to change the data. Users uploaded files are stored in the cloud with the file name as system time and the directory will be created with some random words. Cloud accepts the data only if the size of the file is less than 2MB.

Keywords: cloud space, AES, FTP, NetBeans IDE

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1764 Automated, Objective Assessment of Pilot Performance in Simulated Environment

Authors: Maciej Zasuwa, Grzegorz Ptasinski, Antoni Kopyt

Abstract:

Nowadays flight simulators offer tremendous possibilities for safe and cost-effective pilot training, by utilization of powerful, computational tools. Due to technology outpacing methodology, vast majority of training related work is done by human instructors. It makes assessment not efficient, and vulnerable to instructors’ subjectivity. The research presents an Objective Assessment Tool (gOAT) developed at the Warsaw University of Technology, and tested on SW-4 helicopter flight simulator. The tool uses database of the predefined manoeuvres, defined and integrated to the virtual environment. These were implemented, basing on Aeronautical Design Standard Performance Specification Handling Qualities Requirements for Military Rotorcraft (ADS-33), with predefined Mission-Task-Elements (MTEs). The core element of the gOAT enhanced algorithm that provides instructor a new set of information. In details, a set of objective flight parameters fused with report about psychophysical state of the pilot. While the pilot performs the task, the gOAT system automatically calculates performance using the embedded algorithms, data registered by the simulator software (position, orientation, velocity, etc.), as well as measurements of physiological changes of pilot’s psychophysiological state (temperature, sweating, heart rate). Complete set of measurements is presented on-line to instructor’s station and shown in dedicated graphical interface. The presented tool is based on open source solutions, and flexible for editing. Additional manoeuvres can be easily added using guide developed by authors, and MTEs can be changed by instructor even during an exercise. Algorithm and measurements used allow not only to implement basic stress level measurements, but also to reduce instructor’s workload significantly. Tool developed can be used for training purpose, as well as periodical checks of the aircrew. Flexibility and ease of modifications allow the further development to be wide ranged, and the tool to be customized. Depending on simulation purpose, gOAT can be adjusted to support simulator of aircraft, helicopter, or unmanned aerial vehicle (UAV).

Keywords: automated assessment, flight simulator, human factors, pilot training

Procedia PDF Downloads 137
1763 ScRNA-Seq RNA Sequencing-Based Program-Polygenic Risk Scores Associated with Pancreatic Cancer Risks in the UK Biobank Cohort

Authors: Yelin Zhao, Xinxiu Li, Martin Smelik, Oleg Sysoev, Firoj Mahmud, Dina Mansour Aly, Mikael Benson

Abstract:

Background: Early diagnosis of pancreatic cancer is clinically challenging due to vague, or no symptoms, and lack of biomarkers. Polygenic risk score (PRS) scores may provide a valuable tool to assess increased or decreased risk of PC. This study aimed to develop such PRS by filtering genetic variants identified by GWAS using transcriptional programs identified by single-cell RNA sequencing (scRNA-seq). Methods: ScRNA-seq data from 24 pancreatic ductal adenocarcinoma (PDAC) tumor samples and 11 normal pancreases were analyzed to identify differentially expressed genes (DEGs) in in tumor and microenvironment cell types compared to healthy tissues. Pathway analysis showed that the DEGs were enriched for hundreds of significant pathways. These were clustered into 40 “programs” based on gene similarity, using the Jaccard index. Published genetic variants associated with PDAC were mapped to each program to generate program PRSs (pPRSs). These pPRSs, along with five previously published PRSs (PGS000083, PGS000725, PGS000663, PGS000159, and PGS002264), were evaluated in a European-origin population from the UK Biobank, consisting of 1,310 PDAC participants and 407,473 non-pancreatic cancer participants. Stepwise Cox regression analysis was performed to determine associations between pPRSs with the development of PC, with adjustments of sex and principal components of genetic ancestry. Results: The PDAC genetic variants were mapped to 23 programs and were used to generate pPRSs for these programs. Four distinct pPRSs (P1, P6, P11, and P16) and two published PRSs (PGS000663 and PGS002264) were significantly associated with an increased risk of developing PC. Among these, P6 exhibited the greatest hazard ratio (adjusted HR[95% CI] = 1.67[1.14-2.45], p = 0.008). In contrast, P10 and P4 were associated with lower risk of developing PC (adjusted HR[95% CI] = 0.58[0.42-0.81], p = 0.001, and adjusted HR[95% CI] = 0.75[0.59-0.96], p = 0.019). By comparison, two of the five published PRS exhibited an association with PDAC onset with HR (PGS000663: adjusted HR[95% CI] = 1.24[1.14-1.35], p < 0.001 and PGS002264: adjusted HR[95% CI] = 1.14[1.07-1.22], p < 0.001). Conclusion: Compared to published PRSs, scRNA-seq-based pPRSs may be used not only to assess increased but also decreased risk of PDAC.

Keywords: cox regression, pancreatic cancer, polygenic risk score, scRNA-seq, UK biobank

Procedia PDF Downloads 89
1762 Determining Abnomal Behaviors in UAV Robots for Trajectory Control in Teleoperation

Authors: Kiwon Yeom

Abstract:

Change points are abrupt variations in a data sequence. Detection of change points is useful in modeling, analyzing, and predicting time series in application areas such as robotics and teleoperation. In this paper, a change point is defined to be a discontinuity in one of its derivatives. This paper presents a reliable method for detecting discontinuities within a three-dimensional trajectory data. The problem of determining one or more discontinuities is considered in regular and irregular trajectory data from teleoperation. We examine the geometric detection algorithm and illustrate the use of the method on real data examples.

Keywords: change point, discontinuity, teleoperation, abrupt variation

Procedia PDF Downloads 156
1761 Mathematics Vision of the Companies' Growth with Educational Technologies

Authors: Valencia P. L. Rodrigo, Morita A. Adelina, Vargas V. Martin

Abstract:

This proposal consists of an analysis of macro concepts involved within an organization growth using educational technologies, which will relate each concept, in a mathematical way with a vision of harmonic work. Working collaboratively, competitively and cooperatively so that this growth is harmonious and homogenous, coining a new term, Harmonic Work. The Harmonic Work ensures that the organization grows in all business directions, allowing managers to project a much more accurate growth, making clear the contribution of each department, resulting in an algorithm that analyzes each of the variables both endogenous and exogenous, establishing different performance indicators in its process of growth.

Keywords: business projection, collaboration, competitiveness, educational technology, harmonious growth

Procedia PDF Downloads 310
1760 Fast Terminal Sliding Mode Controller For Quadrotor UAV

Authors: Vahid Tabrizi, Reza GHasemi, Ahmadreza Vali

Abstract:

This paper presents robust nonlinear control law for a quadrotor UAV using fast terminal sliding mode control. Fast terminal sliding mode idea is used for introducing a nonlinear sliding variable that guarantees the finite time convergence in sliding phase. Then, in reaching phase for removing chattering and producing smooth control signal, continuous approximation idea is used. Simulation results show that the proposed algorithm is robust against parameter uncertainty and has better performance than conventional sliding mode for controlling a quadrotor UAV.

Keywords: quadrotor UAV, fast terminal sliding mode, second order sliding mode t

Procedia PDF Downloads 530
1759 Modelling Soil Inherent Wind Erodibility Using Artifical Intellligent and Hybrid Techniques

Authors: Abbas Ahmadi, Bijan Raie, Mohammad Reza Neyshabouri, Mohammad Ali Ghorbani, Farrokh Asadzadeh

Abstract:

In recent years, vast areas of Urmia Lake in Dasht-e-Tabriz has dried up leading to saline sediments exposure on the surface lake coastal areas being highly susceptible to wind erosion. This study was conducted to investigate wind erosion and its relevance to soil physicochemical properties and also modeling of wind erodibility (WE) using artificial intelligence techniques. For this purpose, 96 soil samples were collected from 0-5 cm depth in 414000 hectares using stratified random sampling method. To measure the WE, all samples (<8 mm) were exposed to 5 different wind velocities (9.5, 11, 12.5, 14.1 and 15 m s-1 at the height of 20 cm) in wind tunnel and its relationship with soil physicochemical properties was evaluated. According to the results, WE varied within the range of 76.69-9.98 (g m-2 min-1)/(m s-1) with a mean of 10.21 and coefficient of variation of 94.5% showing a relatively high variation in the studied area. WE was significantly (P<0.01) affected by soil physical properties, including mean weight diameter, erodible fraction (secondary particles smaller than 0.85 mm) and percentage of the secondary particle size classes 2-4.75, 1.7-2 and 0.1-0.25 mm. Results showed that the mean weight diameter, erodible fraction and percentage of size class 0.1-0.25 mm demonstrated stronger relationship with WE (coefficients of determination were 0.69, 0.67 and 0.68, respectively). This study also compared efficiency of multiple linear regression (MLR), gene expression programming (GEP), artificial neural network (MLP), artificial neural network based on genetic algorithm (MLP-GA) and artificial neural network based on whale optimization algorithm (MLP-WOA) in predicting of soil wind erodibility in Dasht-e-Tabriz. Among 32 measured soil variable, percentages of fine sand, size classes of 1.7-2.0 and 0.1-0.25 mm (secondary particles) and organic carbon were selected as the model inputs by step-wise regression. Findings showed MLP-WOA as the most powerful artificial intelligence techniques (R2=0.87, NSE=0.87, ME=0.11 and RMSE=2.9) to predict soil wind erodibility in the study area; followed by MLP-GA, MLP, GEP and MLR and the difference between these methods were significant according to the MGN test. Based on the above finding MLP-WOA may be used as a promising method to predict soil wind erodibility in the study area.

Keywords: wind erosion, erodible fraction, gene expression programming, artificial neural network

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1758 Survival Data with Incomplete Missing Categorical Covariates

Authors: Madaki Umar Yusuf, Mohd Rizam B. Abubakar

Abstract:

The survival censored data with incomplete covariate data is a common occurrence in many studies in which the outcome is survival time. With model when the missing covariates are categorical, a useful technique for obtaining parameter estimates is the EM by the method of weights. The survival outcome for the class of generalized linear model is applied and this method requires the estimation of the parameters of the distribution of the covariates. In this paper, we propose some clinical trials with ve covariates, four of which have some missing values which clearly show that they were fully censored data.

Keywords: EM algorithm, incomplete categorical covariates, ignorable missing data, missing at random (MAR), Weibull Distribution

Procedia PDF Downloads 394
1757 A Comparative Study of Multi-SOM Algorithms for Determining the Optimal Number of Clusters

Authors: Imèn Khanchouch, Malika Charrad, Mohamed Limam

Abstract:

The interpretation of the quality of clusters and the determination of the optimal number of clusters is still a crucial problem in clustering. We focus in this paper on multi-SOM clustering method which overcomes the problem of extracting the number of clusters from the SOM map through the use of a clustering validity index. We then tested multi-SOM using real and artificial data sets with different evaluation criteria not used previously such as Davies Bouldin index, Dunn index and silhouette index. The developed multi-SOM algorithm is compared to k-means and Birch methods. Results show that it is more efficient than classical clustering methods.

Keywords: clustering, SOM, multi-SOM, DB index, Dunn index, silhouette index

Procedia PDF Downloads 589