Search results for: approximate algorithm
Commenced in January 2007
Frequency: Monthly
Edition: International
Paper Count: 3889

Search results for: approximate algorithm

3019 Screen Method of Distributed Cooperative Navigation Factors for Unmanned Aerial Vehicle Swarm

Authors: Can Zhang, Qun Li, Yonglin Lei, Zhi Zhu, Dong Guo

Abstract:

Aiming at the problem of factor screen in distributed collaborative navigation of dense UAV swarm, an efficient distributed collaborative navigation factor screen method is proposed. The method considered the balance between computing load and positioning accuracy. The proposed algorithm utilized the factor graph model to implement a distributed collaborative navigation algorithm. The GNSS information of the UAV itself and the ranging information between the UAVs are used as the positioning factors. In this distributed scheme, a local factor graph is established for each UAV. The positioning factors of nodes with good geometric position distribution and small variance are selected to participate in the navigation calculation. To demonstrate and verify the proposed methods, the simulation and experiments in different scenarios are performed in this research. Simulation results show that the proposed scheme achieves a good balance between the computing load and positioning accuracy in the distributed cooperative navigation calculation of UAV swarm. This proposed algorithm has important theoretical and practical value for both industry and academic areas.

Keywords: screen method, cooperative positioning system, UAV swarm, factor graph, cooperative navigation

Procedia PDF Downloads 79
3018 Critically Sampled Hybrid Trigonometry Generalized Discrete Fourier Transform for Multistandard Receiver Platform

Authors: Temidayo Otunniyi

Abstract:

This paper presents a low computational channelization algorithm for the multi-standards platform using poly phase implementation of a critically sampled hybrid Trigonometry generalized Discrete Fourier Transform, (HGDFT). An HGDFT channelization algorithm exploits the orthogonality of two trigonometry Fourier functions, together with the properties of Quadrature Mirror Filter Bank (QMFB) and Exponential Modulated filter Bank (EMFB), respectively. HGDFT shows improvement in its implementation in terms of high reconfigurability, lower filter length, parallelism, and medium computational activities. Type 1 and type 111 poly phase structures are derived for real-valued HGDFT modulation. The design specifications are decimated critically and over-sampled for both single and multi standards receiver platforms. Evaluating the performance of oversampled single standard receiver channels, the HGDFT algorithm achieved 40% complexity reduction, compared to 34% and 38% reduction in the Discrete Fourier Transform (DFT) and tree quadrature mirror filter (TQMF) algorithm. The parallel generalized discrete Fourier transform (PGDFT) and recombined generalized discrete Fourier transform (RGDFT) had 41% complexity reduction and HGDFT had a 46% reduction in oversampling multi-standards mode. While in the critically sampled multi-standard receiver channels, HGDFT had complexity reduction of 70% while both PGDFT and RGDFT had a 34% reduction.

Keywords: software defined radio, channelization, critical sample rate, over-sample rate

Procedia PDF Downloads 148
3017 An MIPSSTWM-based Emergency Vehicle Routing Approach for Quick Response to Highway Incidents

Authors: Siliang Luan, Zhongtai Jiang

Abstract:

The risk of highway incidents is commonly recognized as a major concern for transportation authorities due to the hazardous consequences and negative influence. It is crucial to respond to these unpredictable events as soon as possible faced by emergency management decision makers. In this paper, we focus on path planning for emergency vehicles, one of the most significant processes to avoid congestion and reduce rescue time. A Mixed-Integer Linear Programming with Semi-Soft Time Windows Model (MIPSSTWM) is conducted to plan an optimal routing respectively considering the time consumption of arcs and nodes of the urban road network and the highway network, especially in developing countries with an enormous population. Here, the arcs indicate the road segments and the nodes include the intersections of the urban road network and the on-ramp and off-ramp of the highway networks. An attempt in this research has been made to develop a comprehensive and executive strategy for emergency vehicle routing in heavy traffic conditions. The proposed Cuckoo Search (CS) algorithm is designed by imitating obligate brood parasitic behaviors of cuckoos and Lévy Flights (LF) to solve this hard and combinatorial problem. Using a Chinese city as our case study, the numerical results demonstrate the approach we applied in this paper outperforms the previous method without considering the nodes of the road network for a real-world situation. Meanwhile, the accuracy and validity of the CS algorithm also show better performances than the traditional algorithm.

Keywords: emergency vehicle, path planning, cs algorithm, urban traffic management and urban planning

Procedia PDF Downloads 80
3016 Wind Diesel Hybrid System without Battery Energy Storage Using Imperialist Competitive Algorithm

Authors: H. Rezvani, H. Monsef, A. Hekmati

Abstract:

Nowadays, the use of renewable energy sources has been increasingly great because of the cost increase and public demand for clean energy sources. One of the fastest growing sources is wind energy. In this paper, Wind Diesel Hybrid System (WDHS) comprising a Diesel Generator (DG), a Wind Turbine Generator (WTG), the Consumer Load, a Battery-based Energy Storage System (BESS), and a Dump Load (DL) is used. Voltage is controlled by Diesel Generator; the frequency is controlled by BESS and DL. The BESS elimination is an efficient way to reduce maintenance cost and increase the dynamic response. Simulation results with graphs for the frequency of Power System, active power, and the battery power are presented for load changes. The controlling parameters are optimized by using Imperialist Competitive Algorithm (ICA). The simulation results for the BESS/no BESS cases are compared. Results show that in no BESS case, the frequency control is more optimal than the BESS case by using ICA.

Keywords: renewable energy, wind diesel system, induction generator, energy storage, imperialist competitive algorithm

Procedia PDF Downloads 560
3015 Enhancing the Dynamic Performance of Grid-Tied Inverters Using Manta Ray Foraging Algorithm

Authors: H. E. Keshta, A. A. Ali

Abstract:

Three phase grid-tied inverters are widely employed in micro-grids (MGs) as interphase between DC and AC systems. These inverters are usually controlled through standard decoupled d–q vector control strategy based on proportional integral (PI) controllers. Recently, advanced meta-heuristic optimization techniques have been used instead of deterministic methods to obtain optimum PI controller parameters. This paper provides a comparative study between the performance of the global Porcellio Scaber algorithm (GPSA) based PI controller and Manta Ray foraging optimization (MRFO) based PI controller.

Keywords: micro-grids, optimization techniques, grid-tied inverter control, PI controller

Procedia PDF Downloads 132
3014 Design of Microwave Building Block by Using Numerical Search Algorithm

Authors: Haifeng Zhou, Tsungyang Liow, Xiaoguang Tu, Eujin Lim, Chao Li, Junfeng Song, Xianshu Luo, Ying Huang, Lianxi Jia, Lianwee Luo, Qing Fang, Mingbin Yu, Guoqiang Lo

Abstract:

With the development of technology, countries gradually allocated more and more frequency spectrums for civilization and commercial usage, especially those high radio frequency bands indicating high information capacity. The field effect becomes more and more prominent in microwave components as frequency increases, which invalidates the transmission line theory and complicate the design of microwave components. Here a modeling approach based on numerical search algorithm is proposed to design various building blocks for microwave circuits to avoid complicated impedance matching and equivalent electrical circuit approximation. Concretely, a microwave component is discretized to a set of segments along the microwave propagation path. Each of the segment is initialized with random dimensions, which constructs a multiple-dimension parameter space. Then numerical searching algorithms (e.g. Pattern search algorithm) are used to find out the ideal geometrical parameters. The optimal parameter set is achieved by evaluating the fitness of S parameters after a number of iterations. We had adopted this approach in our current projects and designed many microwave components including sharp bends, T-branches, Y-branches, microstrip-to-stripline converters and etc. For example, a stripline 90° bend was designed in 2.54 mm x 2.54 mm space for dual-band operation (Ka band and Ku band) with < 0.18 dB insertion loss and < -55 dB reflection. We expect that this approach can enrich the tool kits for microwave designers.

Keywords: microwave component, microstrip and stripline, bend, power division, the numerical search algorithm.

Procedia PDF Downloads 379
3013 Overview of Adaptive Spline interpolation

Authors: Rongli Gai, Zhiyuan Chang

Abstract:

At this stage, in view of various situations in the interpolation process, most researchers use self-adaptation to adjust the interpolation process, which is also one of the current and future research hotspots in the field of CNC machining. In the interpolation process, according to the overview of the spline curve interpolation algorithm, the adaptive analysis is carried out from the factors affecting the interpolation process. The adaptive operation is reflected in various aspects, such as speed, parameters, errors, nodes, feed rates, random Period, sensitive point, step size, curvature, adaptive segmentation, adaptive optimization, etc. This paper will analyze and summarize the research of adaptive imputation in the direction of the above factors affecting imputation.

Keywords: adaptive algorithm, CNC machining, interpolation constraints, spline curve interpolation

Procedia PDF Downloads 205
3012 Large Time Asymptotic Behavior to Solutions of a Forced Burgers Equation

Authors: Satyanarayana Engu, Ahmed Mohd, V. Murugan

Abstract:

We study the large time asymptotics of solutions to the Cauchy problem for a forced Burgers equation (FBE) with the initial data, which is continuous and summable on R. For which, we first derive explicit solutions of FBE assuming a different class of initial data in terms of Hermite polynomials. Later, by violating this assumption we prove the existence of a solution to the considered Cauchy problem. Finally, we give an asymptotic approximate solution and establish that the error will be of order O(t^(-1/2)) with respect to L^p -norm, where 1≤p≤∞, for large time.

Keywords: Burgers equation, Cole-Hopf transformation, Hermite polynomials, large time asymptotics

Procedia PDF Downloads 334
3011 Design of a Chaotic Trajectory Generator Algorithm for Mobile Robots

Authors: J. J. Cetina-Denis, R. M. López-Gutiérrez, R. Ramírez-Ramírez, C. Cruz-Hernández

Abstract:

This work addresses the problem of designing an algorithm capable of generating chaotic trajectories for mobile robots. Particularly, the chaotic behavior is induced in the linear and angular velocities of a Khepera III differential mobile robot by infusing them with the states of the H´enon chaotic map. A possible application, using the properties of chaotic systems, is patrolling a work area. In this work, numerical and experimental results are reported and analyzed. In addition, two quantitative numerical tests are applied in order to measure how chaotic the generated trajectories really are.

Keywords: chaos, chaotic trajectories, differential mobile robot, Henon map, Khepera III robot, patrolling applications

Procedia PDF Downloads 309
3010 Top-K Shortest Distance as a Similarity Measure

Authors: Andrey Lebedev, Ilya Dmitrenok, JooYoung Lee, Leonard Johard

Abstract:

Top-k shortest path routing problem is an extension of finding the shortest path in a given network. Shortest path is one of the most essential measures as it reveals the relations between two nodes in a network. However, in many real world networks, whose diameters are small, top-k shortest path is more interesting as it contains more information about the network topology. Many variations to compute top-k shortest paths have been studied. In this paper, we apply an efficient top-k shortest distance routing algorithm to the link prediction problem and test its efficacy. We compare the results with other base line and state-of-the-art methods as well as with the shortest path. Then, we also propose a top-k distance based graph matching algorithm.

Keywords: graph matching, link prediction, shortest path, similarity

Procedia PDF Downloads 358
3009 Discrete Tracking Control of Nonholonomic Mobile Robots: Backstepping Design Approach

Authors: Alexander S. Andreev, Olga A. Peregudova

Abstract:

In this paper, we propose a discrete tracking control of nonholonomic mobile robots with two degrees of freedom. The electro-mechanical model of a mobile robot moving on a horizontal surface without slipping, with two rear wheels controlled by two independent DC electric, and one front roal wheel is considered. We present back-stepping design based on the Euler approximate discrete-time model of a continuous-time plant. Theoretical considerations are verified by numerical simulation. The work was supported by RFFI (15-01-08482).

Keywords: actuator dynamics, back stepping, discrete-time controller, Lyapunov function, wheeled mobile robot

Procedia PDF Downloads 415
3008 An Improved GA to Address Integrated Formulation of Project Scheduling and Material Ordering with Discount Options

Authors: Babak H. Tabrizi, Seyed Farid Ghaderi

Abstract:

Concurrent planning of the resource constraint project scheduling and material ordering problems have received significant attention within the last decades. Hence, the issue has been investigated here with the aim to minimize total project costs. Furthermore, the presented model considers different discount options in order to approach the real world conditions. The incorporated alternatives consist of all-unit and incremental discount strategies. On the other hand, a modified version of the genetic algorithm is applied in order to solve the model for larger sizes, in particular. Finally, the applicability and efficiency of the given model is tested by different numerical instances.

Keywords: genetic algorithm, material ordering, project management, project scheduling

Procedia PDF Downloads 302
3007 Instance Selection for MI-Support Vector Machines

Authors: Amy M. Kwon

Abstract:

Support vector machine (SVM) is a well-known algorithm in machine learning due to its superior performance, and it also functions well in multiple-instance (MI) problems. Our study proposes a schematic algorithm to select instances based on Hausdorff distance, which can be adapted to SVMs as input vectors under the MI setting. Based on experiments on five benchmark datasets, our strategy for adapting representation outperformed in comparison with original approach. In addition, task execution times (TETs) were reduced by more than 80% based on MissSVM. Hence, it is noteworthy to consider this representation adaptation to SVMs under MI-setting.

Keywords: support vector machine, Margin, Hausdorff distance, representation selection, multiple-instance learning, machine learning

Procedia PDF Downloads 34
3006 Clustering Categorical Data Using the K-Means Algorithm and the Attribute’s Relative Frequency

Authors: Semeh Ben Salem, Sami Naouali, Moetez Sallami

Abstract:

Clustering is a well known data mining technique used in pattern recognition and information retrieval. The initial dataset to be clustered can either contain categorical or numeric data. Each type of data has its own specific clustering algorithm. In this context, two algorithms are proposed: the k-means for clustering numeric datasets and the k-modes for categorical datasets. The main encountered problem in data mining applications is clustering categorical dataset so relevant in the datasets. One main issue to achieve the clustering process on categorical values is to transform the categorical attributes into numeric measures and directly apply the k-means algorithm instead the k-modes. In this paper, it is proposed to experiment an approach based on the previous issue by transforming the categorical values into numeric ones using the relative frequency of each modality in the attributes. The proposed approach is compared with a previously method based on transforming the categorical datasets into binary values. The scalability and accuracy of the two methods are experimented. The obtained results show that our proposed method outperforms the binary method in all cases.

Keywords: clustering, unsupervised learning, pattern recognition, categorical datasets, knowledge discovery, k-means

Procedia PDF Downloads 259
3005 Hull Detection from Handwritten Digit Image

Authors: Sriraman Kothuri, Komal Teja Mattupalli

Abstract:

In this paper we proposed a novel algorithm for recognizing hulls in a hand written digits. This is an extension to the work on “Digit Recognition Using Freeman Chain code”. In order to find out the hulls in a user given digit it is necessary to follow three steps. Those are pre-processing, Boundary Extraction and at last apply the Hull Detection system in a way to attain the better results. The detection of Hull Regions is mainly intended to increase the machine learning capability in detection of characters or digits. This can also extend this in order to get the hull regions and their intensities in Black Holes in Space Exploration.

Keywords: chain code, machine learning, hull regions, hull recognition system, SASK algorithm

Procedia PDF Downloads 400
3004 Measuring Fluctuating Asymmetry in Human Faces Using High-Density 3D Surface Scans

Authors: O. Ekrami, P. Claes, S. Van Dongen

Abstract:

Fluctuating asymmetry (FA) has been studied for many years as an indicator of developmental stability or ‘genetic quality’ based on the assumption that perfect symmetry is ideally the expected outcome for a bilateral organism. Further studies have also investigated the possible link between FA and attractiveness or levels of masculinity or femininity. These hypotheses have been mostly examined using 2D images, and the structure of interest is usually presented using a limited number of landmarks. Such methods have the downside of simplifying and reducing the dimensionality of the structure, which will in return increase the error of the analysis. In an attempt to reach more conclusive and accurate results, in this study we have used high-resolution 3D scans of human faces and have developed an algorithm to measure and localize FA, taking a spatially-dense approach. A symmetric spatially dense anthropometric mask with paired vertices is non-rigidly mapped on target faces using an Iterative Closest Point (ICP) registration algorithm. A set of 19 manually indicated landmarks were used to examine the precision of our mapping step. The protocol’s accuracy in measurement and localizing FA is assessed using simulated faces with known amounts of asymmetry added to them. The results of validation of our approach show that the algorithm is perfectly capable of locating and measuring FA in 3D simulated faces. With the use of such algorithm, the additional captured information on asymmetry can be used to improve the studies of FA as an indicator of fitness or attractiveness. This algorithm can especially be of great benefit in studies of high number of subjects due to its automated and time-efficient nature. Additionally, taking a spatially dense approach provides us with information about the locality of FA, which is impossible to obtain using conventional methods. It also enables us to analyze the asymmetry of a morphological structures in a multivariate manner; This can be achieved by using methods such as Principal Components Analysis (PCA) or Factor Analysis, which can be a step towards understanding the underlying processes of asymmetry. This method can also be used in combination with genome wide association studies to help unravel the genetic bases of FA. To conclude, we introduced an algorithm to study and analyze asymmetry in human faces, with the possibility of extending the application to other morphological structures, in an automated, accurate and multi-variate framework.

Keywords: developmental stability, fluctuating asymmetry, morphometrics, 3D image processing

Procedia PDF Downloads 140
3003 Finding a Set of Long Common Substrings with Repeats from m Input Strings

Authors: Tiantian Li, Lusheng Wang, Zhaohui Zhan, Daming Zhu

Abstract:

In this paper, we propose two string problems, and study algorithms and complexity of various versions for those problems. Let S = {s₁, s₂, . . . , sₘ} be a set of m strings. A common substring of S is a substring appearing in every string in S. Given a set of m strings S = {s₁, s₂, . . . , sₘ} and a positive integer k, we want to find a set C of k common substrings of S such that the k common substrings in C appear in the same order and have no overlap among the m input strings in S, and the total length of the k common substring in C is maximized. This problem is referred to as the longest total length of k common substrings from m input strings (LCSS(k, m) for short). The other problem we study here is called the longest total length of a set of common substrings with length more than l from m input string (LSCSS(l, m) for short). Given a set of m strings S = {s₁, s₂, . . . , sₘ} and a positive integer l, for LSCSS(l, m), we want to find a set of common substrings of S, each is of length more than l, such that the total length of all the common substrings is maximized. We show that both problems are NP-hard when k and m are variables. We propose dynamic programming algorithms with time complexity O(k n₁n₂) and O(n₁n₂) to solve LCSS(k, 2) and LSCSS(l, 2), respectively, where n1 and n₂ are the lengths of the two input strings. We then design an algorithm for LSCSS(l, m) when every length > l common substring appears once in each of the m − 1 input strings. The running time is O(n₁²m), where n1 is the length of the input string with no restriction on length > l common substrings. Finally, we propose a fixed parameter algorithm for LSCSS(l, m), where each length > l common substring appears m − 1 + c times among the m − 1 input strings (other than s1). In other words, each length > l common substring may repeatedly appear at most c times among the m − 1 input strings {s₂, s₃, . . . , sₘ}. The running time of the proposed algorithm is O((n12ᶜ)²m), where n₁ is the input string with no restriction on repeats. The LSCSS(l, m) is proposed to handle whole chromosome sequence alignment for different strains of the same species, where more than 98% of letters in core regions are identical.

Keywords: dynamic programming, algorithm, common substrings, string

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3002 Markov-Chain-Based Optimal Filtering and Smoothing

Authors: Garry A. Einicke, Langford B. White

Abstract:

This paper describes an optimum filter and smoother for recovering a Markov process message from noisy measurements. The developments follow from an equivalence between a state space model and a hidden Markov chain. The ensuing filter and smoother employ transition probability matrices and approximate probability distribution vectors. The properties of the optimum solutions are retained, namely, the estimates are unbiased and minimize the variance of the output estimation error, provided that the assumed parameter set are correct. Methods for estimating unknown parameters from noisy measurements are discussed. Signal recovery examples are described in which performance benefits are demonstrated at an increased calculation cost.

Keywords: optimal filtering, smoothing, Markov chains

Procedia PDF Downloads 317
3001 Wind Energy Resources Assessment and Micrositting on Different Areas of Libya: The Case Study in Darnah

Authors: F. Ahwide, Y. Bouker, K. Hatem

Abstract:

This paper presents long term wind data analysis in terms of annual and diurnal variations at different areas of Libya. The data of the wind speed and direction are taken each ten minutes for a period, at least two years, are used in the analysis. ‘WindPRO’ software and Excel workbook were used for the wind statistics and energy calculations. As for Derna, average speeds are 10 m, 20 m, and 40 m, and respectively 6.57 m/s, 7.18 m/s, and 8.09 m/s. Highest wind speeds are observed at SSW, followed by S, WNW and NW sectors. Lowest wind speeds are observed between N and E sectors. Most frequent wind directions are NW and NNW. Hence, wind turbines can be installed against these directions. The most powerful sector is NW (29.4 % of total expected wind energy), followed by 19.9 % SSW, 11.9% NNW, 8.6% WNW and 8.2% S. Furthermore in Al-Maqrun: the most powerful sector is W (26.8 % of total expected wind energy), followed by 12.3 % WSW and 9.5% WNW. While in Goterria: the most powerful sector is S (14.8 % of total expected wind energy), followed by SSE, SE, and WSW. And Misalatha: the most powerful sector is S, by far represents 28.5% of the expected power, followed by SSE and SE. As for Tarhuna, it is by far SSE and SE, representing each one two times the expected energy of the third powerful sector (NW). In Al-Asaaba: it is SSE by far represents 50% of the expected power, followed by S. It can to be noted that the high frequency of the south direction winds, that come from the desert could cause a high frequency of dust episodes. This fact then, should be taken into account in order to take appropriate measures to prevent wind turbine deterioration. In Excel workbook, an estimation of annual energy yield at position of Derna, Al-Maqrun, Tarhuna, and Al-Asaaba meteorological mast has been done, considering a generic wind turbine of 1.65 MW. (mtORRES, TWT 82-1.65MW) in position of meteorological mast. Three other turbines have been tested. At 80 m, the estimation of energy yield for Derna, Al-Maqrun, Tarhuna, and Asaaba is 6.78 GWh or 3390 equivalent hours, 5.80 GWh or 2900 equivalent hours, 4.91 GWh or 2454 equivalent hours and 5.08 GWh or 2541 equivalent hours respectively. It seems a fair value in the context of a possible development of a wind energy project in the areas, considering a value of 2400 equivalent hours as an approximate limit to consider a wind warm economically profitable. Furthermore, an estimation of annual energy yield at positions of Misalatha, Azizyah and Goterria meteorological mast has been done, considering a generic wind turbine of 2 MW. We found that, at 80 m, the estimation of energy yield is 3.12 GWh or 1557 equivalent hours, 4.47 GWh or 2235 equivalent hours and 4.07GWh or 2033 respectively . It seems a very poor value in the context of possible development of a wind energy project in the areas, considering a value of 2400 equivalent hours as an approximate limit to consider a wind warm economically profitable. Anyway, more data and a detailed wind farm study would be necessary to draw conclusions.

Keywords: wind turbines, wind data, energy yield, micrositting

Procedia PDF Downloads 188
3000 Development of Configuration Software of Space Environment Simulator Control System Based on Linux

Authors: Zhan Haiyang, Zhang Lei, Ning Juan

Abstract:

This paper presents a configuration software solution in Linux, which is used for the control of space environment simulator. After introducing the structure and basic principle, it is said that the developing of QT software frame and the dynamic data exchanging between PLC and computer. The OPC driver in Linux is also developed. This driver realizes many-to-many communication between hardware devices and SCADA software. Moreover, an algorithm named “Scan PRI” is put forward. This algorithm is much more optimizable and efficient compared with "Scan in sequence" in Windows. This software has been used in practical project. It has a good control effect and can achieve the expected goal.

Keywords: Linux OS, configuration software, OPC Server driver, MYSQL database

Procedia PDF Downloads 289
2999 A Feature Clustering-Based Sequential Selection Approach for Color Texture Classification

Authors: Mohamed Alimoussa, Alice Porebski, Nicolas Vandenbroucke, Rachid Oulad Haj Thami, Sana El Fkihi

Abstract:

Color and texture are highly discriminant visual cues that provide an essential information in many types of images. Color texture representation and classification is therefore one of the most challenging problems in computer vision and image processing applications. Color textures can be represented in different color spaces by using multiple image descriptors which generate a high dimensional set of texture features. In order to reduce the dimensionality of the feature set, feature selection techniques can be used. The goal of feature selection is to find a relevant subset from an original feature space that can improve the accuracy and efficiency of a classification algorithm. Traditionally, feature selection is focused on removing irrelevant features, neglecting the possible redundancy between relevant ones. This is why some feature selection approaches prefer to use feature clustering analysis to aid and guide the search. These techniques can be divided into two categories. i) Feature clustering-based ranking algorithm uses feature clustering as an analysis that comes before feature ranking. Indeed, after dividing the feature set into groups, these approaches perform a feature ranking in order to select the most discriminant feature of each group. ii) Feature clustering-based subset search algorithms can use feature clustering following one of three strategies; as an initial step that comes before the search, binded and combined with the search or as the search alternative and replacement. In this paper, we propose a new feature clustering-based sequential selection approach for the purpose of color texture representation and classification. Our approach is a three step algorithm. First, irrelevant features are removed from the feature set thanks to a class-correlation measure. Then, introducing a new automatic feature clustering algorithm, the feature set is divided into several feature clusters. Finally, a sequential search algorithm, based on a filter model and a separability measure, builds a relevant and non redundant feature subset: at each step, a feature is selected and features of the same cluster are removed and thus not considered thereafter. This allows to significantly speed up the selection process since large number of redundant features are eliminated at each step. The proposed algorithm uses the clustering algorithm binded and combined with the search. Experiments using a combination of two well known texture descriptors, namely Haralick features extracted from Reduced Size Chromatic Co-occurence Matrices (RSCCMs) and features extracted from Local Binary patterns (LBP) image histograms, on five color texture data sets, Outex, NewBarktex, Parquet, Stex and USPtex demonstrate the efficiency of our method compared to seven of the state of the art methods in terms of accuracy and computation time.

Keywords: feature selection, color texture classification, feature clustering, color LBP, chromatic cooccurrence matrix

Procedia PDF Downloads 137
2998 Fuzzy Inference Based Modelling of Perception Reaction Time of Drivers

Authors: U. Chattaraj, K. Dhusiya, M. Raviteja

Abstract:

Perception reaction time of drivers is an outcome of human thought process, which is vague and approximate in nature and also varies from driver to driver. So, in this study a fuzzy logic based model for prediction of the same has been presented, which seems suitable. The control factors, like, age, experience, intensity of driving of the driver, speed of the vehicle and distance of stimulus have been considered as premise variables in the model, in which the perception reaction time is the consequence variable. Results show that the model is able to explain the impacts of the control factors on perception reaction time properly.

Keywords: driver, fuzzy logic, perception reaction time, premise variable

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2997 Computational Fluid Dynamics Simulations and Analysis of Air Bubble Rising in a Column of Liquid

Authors: Baha-Aldeen S. Algmati, Ahmed R. Ballil

Abstract:

Multiphase flows occur widely in many engineering and industrial processes as well as in the environment we live in. In particular, bubbly flows are considered to be crucial phenomena in fluid flow applications and can be studied and analyzed experimentally, analytically, and computationally. In the present paper, the dynamic motion of an air bubble rising within a column of liquid is numerically simulated using an open-source CFD modeling tool 'OpenFOAM'. An interface tracking numerical algorithm called MULES algorithm, which is built-in OpenFOAM, is chosen to solve an appropriate mathematical model based on the volume of fluid (VOF) numerical method. The bubbles initially have a spherical shape and starting from rest in the stagnant column of liquid. The algorithm is initially verified against numerical results and is also validated against available experimental data. The comparison revealed that this algorithm provides results that are in a very good agreement with the 2D numerical data of other CFD codes. Also, the results of the bubble shape and terminal velocity obtained from the 3D numerical simulation showed a very good qualitative and quantitative agreement with the experimental data. The simulated rising bubbles yield a very small percentage of error in the bubble terminal velocity compared with the experimental data. The obtained results prove the capability of OpenFOAM as a powerful tool to predict the behavior of rising characteristics of the spherical bubbles in the stagnant column of liquid. This will pave the way for a deeper understanding of the phenomenon of the rise of bubbles in liquids.

Keywords: CFD simulations, multiphase flows, OpenFOAM, rise of bubble, volume of fluid method, VOF

Procedia PDF Downloads 123
2996 A Survey on Various Technique of Modified TORA over MANET

Authors: Shreyansh Adesara, Sneha Pandiya

Abstract:

The mobile ad-hoc network (MANET) is an important and open area research for the examination and determination of the performance evolution. Temporary ordered routing algorithm (TORA) is adaptable and distributed MANET routing algorithm which is totally dependent on internet MANET Encapsulation protocol (IMEP) for the detection of the link and sensing of the link. If IMEP detect the wrong link failure then the network suffer from congestion and unnecessary route maintenance. Thus, the improvement in link detection method of TORA is introduced by various methods on IMEP by different perspective from different person. There are also different reactive routing protocols like AODV, TORA and DSR has been compared for the knowledge of the routing scenario for different parameter and using different model.

Keywords: IMEP, mobile ad-hoc network, protocol, TORA

Procedia PDF Downloads 442
2995 Numerical Calculation of Heat Transfer in Water Heater

Authors: Michal Spilacek, Martin Lisy, Marek Balas, Zdenek Skala

Abstract:

This article is trying to determine the status of flue gas that is entering the KWH heat exchanger from combustion chamber in order to calculate the heat transfer ratio of the heat exchanger. Combination of measurement, calculation, and computer simulation was used to create a useful way to approximate the heat transfer rate. The measurements were taken by a number of sensors that are mounted on the experimental device and by a thermal imaging camera. The results of the numerical calculation are in a good correspondence with the real power output of the experimental device. Results show that the research has a good direction and can be used to propose changes in the construction of the heat exchanger, but still needs enhancements.

Keywords: heat exchanger, heat transfer rate, numerical calculation, thermal images

Procedia PDF Downloads 616
2994 Enumerative Search for Crane Schedule in Anodizing Operations

Authors: Kanate Pantusavase, Jaramporn Hassamontr

Abstract:

This research aims to develop an algorithm to generate a schedule of multiple cranes that will maximize load throughputs in anodizing operation. The algorithm proposed utilizes an enumerative strategy to search for constant time between successive loads and crane covering range over baths. The computer program developed is able to generate a near-optimal crane schedule within reasonable times, i.e. within 10 minutes. Its results are compared with existing solutions from an aluminum extrusion industry. The program can be used to generate crane schedules for mixed products, thus allowing mixed-model line balancing to improve overall cycle times.

Keywords: crane scheduling, anodizing operations, cycle time minimization

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2993 Support Vector Regression with Weighted Least Absolute Deviations

Authors: Kang-Mo Jung

Abstract:

Least squares support vector machine (LS-SVM) is a penalized regression which considers both fitting and generalization ability of a model. However, the squared loss function is very sensitive to even single outlier. We proposed a weighted absolute deviation loss function for the robustness of the estimates in least absolute deviation support vector machine. The proposed estimates can be obtained by a quadratic programming algorithm. Numerical experiments on simulated datasets show that the proposed algorithm is competitive in view of robustness to outliers.

Keywords: least absolute deviation, quadratic programming, robustness, support vector machine, weight

Procedia PDF Downloads 527
2992 An Enhanced Distributed Weighted Clustering Algorithm for Intra and Inter Cluster Routing in MANET

Authors: K. Gomathi

Abstract:

Mobile Ad hoc Networks (MANET) is defined as collection of routable wireless mobile nodes with no centralized administration and communicate each other using radio signals. Especially MANETs deployed in hostile environments where hackers will try to disturb the secure data transfer and drain the valuable network resources. Since MANET is battery operated network, preserving the network resource is essential one. For resource constrained computation, efficient routing and to increase the network stability, the network is divided into smaller groups called clusters. The clustering architecture consists of Cluster Head(CH), ordinary node and gateway. The CH is responsible for inter and intra cluster routing. CH election is a prominent research area and many more algorithms are developed using many different metrics. The CH with longer life sustains network lifetime, for this purpose Secondary Cluster Head(SCH) also elected and it is more economical. To nominate efficient CH, a Enhanced Distributed Weighted Clustering Algorithm (EDWCA) has been proposed. This approach considers metrics like battery power, degree difference and speed of the node for CH election. The proficiency of proposed one is evaluated and compared with existing algorithm using Network Simulator(NS-2).

Keywords: MANET, EDWCA, clustering, cluster head

Procedia PDF Downloads 398
2991 Integrated Navigation System Using Simplified Kalman Filter Algorithm

Authors: Othman Maklouf, Abdunnaser Tresh

Abstract:

GPS and inertial navigation system (INS) have complementary qualities that make them ideal use for sensor fusion. The limitations of GPS include occasional high noise content, outages when satellite signals are blocked, interference and low bandwidth. The strengths of GPS include its long-term stability and its capacity to function as a stand-alone navigation system. In contrast, INS is not subject to interference or outages, have high bandwidth and good short-term noise characteristics, but have long-term drift errors and require external information for initialization. A combined system of GPS and INS subsystems can exhibit the robustness, higher bandwidth and better noise characteristics of the inertial system with the long-term stability of GPS. The most common estimation algorithm used in integrated INS/GPS is the Kalman Filter (KF). KF is able to take advantages of these characteristics to provide a common integrated navigation implementation with performance superior to that of either subsystem (GPS or INS). This paper presents a simplified KF algorithm for land vehicle navigation application. In this integration scheme, the GPS derived positions and velocities are used as the update measurements for the INS derived PVA. The KF error state vector in this case includes the navigation parameters as well as the accelerometer and gyroscope error states.

Keywords: GPS, INS, Kalman filter, inertial navigation system

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2990 Common Fixed Point Results and Stability of a Modified Jungck Iterative Scheme

Authors: Hudson Akewe

Abstract:

In this study, we introduce a modified Jungck (Dual Jungck) iterative scheme and use the scheme to approximate the unique common fixed point of a pair of generalized contractive-like operators in a Banach space. The iterative scheme is also shown to be stable with respect to the maps (S,T). An example is taken to justify the convergence of the scheme. Our result is a generalization and improvement of several results in the literature on single map T.

Keywords: generalized contractive-like operators, modified Jungck iterative scheme, stability results, weakly compatible maps, unique common fixed point

Procedia PDF Downloads 348