Search results for: algorithm development
Commenced in January 2007
Frequency: Monthly
Edition: International
Paper Count: 19366

Search results for: algorithm development

18436 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 558
18435 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

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18434 The Principles of Democracy and Development: The Political and Philosophical Foundations of Development-Democracy in Africa

Authors: Fadeke Olu-Owolabi, Fayomi Oluyemi

Abstract:

The political and societal orders face the awesome task of overcoming the difficulties which lead to growing tensions and conflicts in Africa. At the core of analysis is the question, how stable and adaptable are established democracies, new democracies, and political and societal actors? The idea of development-democracy as implying the strong linkage between economic development and political democracy appropriately describes the distinguishing characteristic of this new demand for democracy in Africa. The theoretical study examines the political and philosophical foundation of the idea of development-democracy and the arguments presented to support the need for its adoption in Africa today. This paper critically examines the polemic between the advocates of developmental dictatorship and developmental-democracy and argues for the adoption of the latter in Africa. The paper sets out to expose for the political and philosophical foundation of developmental democracy maintaining that only democracy can facilitate development. This argument is supported further by the claim that both democracy and development are two sides of the same coin in the sense that the two are both ethical concepts. The paper also maintained that the only way by which democracy is worthwhile is when it is developmental. Finally, the paper affirms that since the two concepts of democracy and development are like the Siamese twins then the way out of Africa’s present crisis of development is to wholeheartedly embrace democracy. It posits that when genuine democracy is adopted, genuine and sustainable development can then be attained.

Keywords: democracy, development, polemic, principles

Procedia PDF Downloads 527
18433 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 202
18432 Rapid Nanoparticle Formulation Development and Screening Using NanoFabTxTM Platform

Authors: Zhen Ye, Maryam Zaroudi, Elizabeth Aisenbrey, Nicolynn E. Davis, Peng Gao

Abstract:

Nanoparticles have been used as drug delivery systems in the treatment of life-threatening diseases for decades, but traditional formulation development methods are time consuming and labor intensive. Millipore Sigma has developed a platform¬¬– NanoFabTxTM¬¬– for rapid and reproducible formulation development and screening to ensure consistentnanoparticle characteristics. Reproducible and precise control of the development process for a range of nanoparticle formulations accelerates the introduction of novel formulations to the clinic.

Keywords: Bio platform, Formulation development, NanoFabTxTM, Drug delivery

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18431 Symbolic Play and Language: A Developmental Relationship

Authors: Sherri Franklin-Guy

Abstract:

Play activities have long been utilized to support the development of expressive language in young children. More specifically, stages of symbolic play, or pretend play, have served as indicators of levels of cognitive development, the foundation of language. This presentation will examine the relationship between symbolic play and language development in toddlers and preschoolers. Implications for clinicians and educators will be discussed.

Keywords: cognition, language development, pretend play, symbolic play

Procedia PDF Downloads 247
18430 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

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18429 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 356
18428 Methodologies, Systems Development Life Cycle and Modeling Languages in Agile Software Development

Authors: I. D. Arroyo

Abstract:

This article seeks to integrate different concepts from contemporary software engineering with an agile development approach. We seek to clarify some definitions and uses, we make a difference between the Systems Development Life Cycle (SDLC) and the methodologies, we differentiate the types of frameworks such as methodological, philosophical and behavioral, standards and documentation. We define relationships based on the documentation of the development process through formal and ad hoc models, and we define the usefulness of using DevOps and Agile Modeling as integrative methodologies of principles and best practices.

Keywords: methodologies, modeling languages, agile modeling, UML

Procedia PDF Downloads 183
18427 The Mechanism of Upgrading and Urban Development in the Egyptian City: Case Study of Damietta

Authors: Lina Fayed Amin

Abstract:

The research studied, in the beginning, the related urban concepts such as the urban, development, urban development. As it also deals with the upgrading, urban upgrading, community participation and the role of local administration in development and upgrading projects. Then it studies some regional upgrading & urban development projects in Egypt followed by international projects, and the analysis the strategies followed in dealing with these projects. Afterwards, we state the regional aspects of both Damietta governorate & city, dealing with its potentials & development constraints. Followed by studying the upgrading and urban development projects strategies in reflection to the city’s crucial problems, and the constraints that faced the upgrading & development project. Then, it studied the implementation of the project’s strategies & it provided the financial resources needed for the development project in Damietta city. Followed by the studying of the urban and human development projects in the upgrading of Damietta city, as well as analyzing the different projects &analyzing the results of these projects on the aspects of the city’s needs. Then the research analysis in comparison the upgrading and urban development project in Damietta and the regional upgrading and development projects in Egypt. As well as the comparison between the upgrading and urban development project and the international projects in some Arabic and foreign countries in relation to the goals, problems, obstacles, the community participation, the finance resources and the results. Finally, it reviews the results and recommendations that were reached as a result of studying the similar urban upgrading projects in Egypt and in some Arabic and foreign countries. Followed by the analytical analysis of the upgrading and urban development in Egypt

Keywords: Damietta city, urban development, upgrading mechanisms, urban upgrading

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18426 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 300
18425 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

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18424 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

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18423 A Review on Factors Influencing Implementation of Secure Software Development Practices

Authors: Sri Lakshmi Kanniah, Mohd Naz’ri Mahrin

Abstract:

More and more businesses and services are depending on software to run their daily operations and business services. At the same time, cyber-attacks are becoming more covert and sophisticated, posing threats to software. Vulnerabilities exist in the software due to the lack of security practices during the phases of software development. Implementation of secure software development practices can improve the resistance to attacks. Many methods, models and standards for secure software development have been developed. However, despite the efforts, they still come up against difficulties in their deployment and the processes are not institutionalized. There is a set of factors that influence the successful deployment of secure software development processes. In this study, the methodology and results from a systematic literature review of factors influencing the implementation of secure software development practices is described. A total of 44 primary studies were analysed as a result of the systematic review. As a result of the study, a list of twenty factors has been identified. Some of factors that affect implementation of secure software development practices are: Involvement of the security expert, integration between security and development team, developer’s skill and expertise, development time and communication between stakeholders. The factors were further classified into four categories which are institutional context, people and action, project content and system development process. The results obtained show that it is important to take into account organizational, technical and people issues in order to implement secure software development initiatives.

Keywords: secure software development, software development, software security, systematic literature review

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18422 Investigating Sustainable Neighborhood Development in Jahanshahr

Authors: Khashayar Kashani Jou, Ilnaz Fathololoomi

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Nowadays, access to sustainable development in cities is assumed as one of the most important goals of urban managers. In the meanwhile, neighborhood as the smallest unit of urban spatial organization has a substantial effect on urban sustainability. Hence, attention to and focus on this subject is highly important in urban development plans. The objective of this study is evaluation of the status of Jahanshahr Neighborhood in Karaj city based on sustainable neighborhood development indicators. This research has been applied based on documentary method and field surveys. Also, evaluating of Jahanshahr Neighborhood of Karaj shows that it has a high level in sustainability in physical and economical dimension while a low level in cultural and social dimension. For this purpose, this neighborhood as a semi-sustainable neighborhood must take measures for development of collective spaces and efficiency of utilizing the public neighborhood spaces via collaboration of citizens and officials.

Keywords: neighborhood, sustainable development, sustainable neighborhood development, Jahanshahr neighborhood

Procedia PDF Downloads 277
18421 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

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18420 [Keynote Talk]: sEMG Interface Design for Locomotion Identification

Authors: Rohit Gupta, Ravinder Agarwal

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Surface electromyographic (sEMG) signal has the potential to identify the human activities and intention. This potential is further exploited to control the artificial limbs using the sEMG signal from residual limbs of amputees. The paper deals with the development of multichannel cost efficient sEMG signal interface for research application, along with evaluation of proposed class dependent statistical approach of the feature selection method. The sEMG signal acquisition interface was developed using ADS1298 of Texas Instruments, which is a front-end interface integrated circuit for ECG application. Further, the sEMG signal is recorded from two lower limb muscles for three locomotions namely: Plane Walk (PW), Stair Ascending (SA), Stair Descending (SD). A class dependent statistical approach is proposed for feature selection and also its performance is compared with 12 preexisting feature vectors. To make the study more extensive, performance of five different types of classifiers are compared. The outcome of the current piece of work proves the suitability of the proposed feature selection algorithm for locomotion recognition, as compared to other existing feature vectors. The SVM Classifier is found as the outperformed classifier among compared classifiers with an average recognition accuracy of 97.40%. Feature vector selection emerges as the most dominant factor affecting the classification performance as it holds 51.51% of the total variance in classification accuracy. The results demonstrate the potentials of the developed sEMG signal acquisition interface along with the proposed feature selection algorithm.

Keywords: classifiers, feature selection, locomotion, sEMG

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18419 Supporting Embedded Medical Software Development with MDevSPICE® and Agile Practices

Authors: Surafel Demissie, Frank Keenan, Fergal McCaffery

Abstract:

Emerging medical devices are highly relying on embedded software that runs on the specific platform in real time. The development of embedded software is different from ordinary software development due to the hardware-software dependency. MDevSPICE® has been developed to provide guidance to support such development. To increase the flexibility of this framework agile practices have been introduced. This paper outlines the challenges for embedded medical device software development and the structure of MDevSPICE® and suggests a suitable combination of agile practices that will help to add flexibility and address corresponding challenges of embedded medical device software development.

Keywords: agile practices, challenges, embedded software, MDevSPICE®, medical device

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18418 Constructing a New World Order through a Narrative of Infrastructural Development: The Case of the BRICS

Authors: Carolijn Van Noort

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The aim of this research is to understand how the emerging power bloc BRICS employs infrastructure development narratives to construct a new world order. BRICS is an international body consisting of five emerging countries that collaborate on economic and political issues: Brazil, Russia, India, China, and South Africa. This study explores the projection of infrastructure development narratives through an analysis of BRICS’ attention to infrastructure investment and financing, its support of the New Partnership on African Development and the establishment of the New Development Bank in Shanghai. The theory of Strategic Narratives is used to explore BRICS’ commitment to infrastructure development and to distinguish three layers: system narratives (BRICS as a global actor to propose development reform), identity narratives (BRICS as a collective identity joining efforts to act upon development aspirations) and issue narratives (BRICS committed to a range of issues of which infrastructure development is prominent). The methodology that is employed is a narrative analysis of BRICS’ official documents, media statements, and website imagery. A comparison of these narratives illuminates tensions at the three layers and among the five member states. Identifying tensions among development infrastructure narratives provides an indication of how policymaking for infrastructure development could be improved. Subsequently, it advances BRICS’ ability to act as a global actor to construct a new world order.

Keywords: BRICS, emerging powers, infrastructure development, strategic narratives

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18417 Measuring Fluctuating Asymmetry in Human Faces Using High-Density 3D Surface Scans

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

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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

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18416 Finding a Set of Long Common Substrings with Repeats from m Input Strings

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

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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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18415 Sustainable Landscape Development Assessment Tools

Authors: Nur Azemah Aminludin, Osman Mohd Tahir

Abstract:

A dynamic landscape development is important for providing healthy ecosystem which supports all life. Nowadays, many initiatives towards sustainable development have been published. They lead to better living and more efficient use of natural resources in sustaining long-term ecological, economics and social benefits. To date, many assessment tools related to built environment have been established and practiced in this region, which mostly has the purpose assessing the environment performance of buildings. Hence, an assessment tool focusing on the sustainable landscape development itself is a necessity. This paper reviews the assessment criteria and indicators that are suitable for sustainable landscape development practices. The local and global assessment tools for landscape development are investigated, analyzed and discussed critically. Consideration also is given to the integration of the assessment tools with the surrounding environmental, social, and economical aspects. In addition, the assessment criteria and indicators for assessing the landscape development in Malaysia are also reviewed and discussed. In conclusion, this paper reviews, analyzes and discusses on available local and global landscape development assessment tools for sustainability.

Keywords: assessment tool, sustainable landscape development, assessment criteria, assessment indicator

Procedia PDF Downloads 389
18414 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

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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

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18413 The Investigation on the Relationship between Religion and Development: By Focusing on Islam

Authors: Dalal Benboutrif

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Religion and Development relation is one of the most arguable phrases amongst politicians, philosophers, clerics, scientists, sociologists and even the public. The main objective of this research is to clarify the relations, contrasts and interactions between religion and the major types of development including social, political, economic and scientific developments, by focusing on Islam religion. A review of the literature was performed concerning religion and development relations and conflicts, by focusing on Islam religion and then the unprocessed tips of the review were characterized. Regarding clarification of the key points of the literature, three main sectors were considered in the research. The first sector of the research mainly focused on the philosophical views on religion, which were analyzed by main evaluation of three famous philosophers’ ideas: ‘Kant’, ‘Hegel’ and ‘Weber’, and then a critical discussion on Weber’s idea about Islam and development was applied. The second sector was specified to ‘Religion and Development’ and mainly discussed the role of religion in development through poverty reduction, the interconnection of religion, spirituality and social development, religious education effects on social development, and the relation of religion with political development. The third sector was specified to ‘Islam and Development’ and mainly discussed the Islamic golden age of science, major reasons of today’s backwardness (non-development) of most Islamic countries, and Quranic instructions regarding adaptability of Islam with development. The findings of the current research approved the research hypothesis as: ‘Religious instructions (included Islam) are not in conflict with development’, rather, it could have positive effects mainly on social development and it can pave the way for society to develop. Turkey was considered as a study model, as a successful developed Islamic country demonstrating the non-conflicting relation of Islam and development.

Keywords: development, Islam, philosophy, religion

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18412 Computational Fluid Dynamics Simulations and Analysis of Air Bubble Rising in a Column of Liquid

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

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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

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18411 A Survey on Various Technique of Modified TORA over MANET

Authors: Shreyansh Adesara, Sneha Pandiya

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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

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18410 Development of a Turbulent Boundary Layer Wall-pressure Fluctuations Power Spectrum Model Using a Stepwise Regression Algorithm

Authors: Zachary Huffman, Joana Rocha

Abstract:

Wall-pressure fluctuations induced by the turbulent boundary layer (TBL) developed over aircraft are a significant source of aircraft cabin noise. Since the power spectral density (PSD) of these pressure fluctuations is directly correlated with the amount of sound radiated into the cabin, the development of accurate empirical models that predict the PSD has been an important ongoing research topic. The sound emitted can be represented from the pressure fluctuations term in the Reynoldsaveraged Navier-Stokes equations (RANS). Therefore, early TBL empirical models (including those from Lowson, Robertson, Chase, and Howe) were primarily derived by simplifying and solving the RANS for pressure fluctuation and adding appropriate scales. Most subsequent models (including Goody, Efimtsov, Laganelli, Smol’yakov, and Rackl and Weston models) were derived by making modifications to these early models or by physical principles. Overall, these models have had varying levels of accuracy, but, in general, they are most accurate under the specific Reynolds and Mach numbers they were developed for, while being less accurate under other flow conditions. Despite this, recent research into the possibility of using alternative methods for deriving the models has been rather limited. More recent studies have demonstrated that an artificial neural network model was more accurate than traditional models and could be applied more generally, but the accuracy of other machine learning techniques has not been explored. In the current study, an original model is derived using a stepwise regression algorithm in the statistical programming language R, and TBL wall-pressure fluctuations PSD data gathered at the Carleton University wind tunnel. The theoretical advantage of a stepwise regression approach is that it will automatically filter out redundant or uncorrelated input variables (through the process of feature selection), and it is computationally faster than machine learning. The main disadvantage is the potential risk of overfitting. The accuracy of the developed model is assessed by comparing it to independently sourced datasets.

Keywords: aircraft noise, machine learning, power spectral density models, regression models, turbulent boundary layer wall-pressure fluctuations

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18409 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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18408 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

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18407 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