Search results for: integral means
Commenced in January 2007
Frequency: Monthly
Edition: International
Paper Count: 5089

Search results for: integral means

4969 Optimization of E-motor Control Parameters for Electrically Propelled Vehicles by Integral Squared Method

Authors: Ibrahim Cicek, Melike Nikbay

Abstract:

Electrically propelled vehicles, either road or aerial vehicles are studied on contemporarily for their robust maneuvers and cost-efficient transport operations. The main power generating systems of such vehicles electrified by selecting proper components and assembled as e-powertrain. Generally, e-powertrain components selected considering the target performance requirements. Since the main component of propulsion is the drive unit, e-motor control system is subjected to achieve the performance targets. In this paper, the optimization of e-motor control parameters studied by Integral Squared Method (ISE). The overall aim is to minimize power consumption of such vehicles depending on mission profile and maintaining smooth maneuvers for passenger comfort. The sought-after values of control parameters are computed using the Optimal Control Theory. The system is modeled as a closed-loop linear control system with calibratable parameters.

Keywords: optimization, e-powertrain, optimal control, electric vehicles

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4968 Combined Heat and Power Generation in Pressure Reduction City Gas Station (CGS)

Authors: Sadegh Torfi

Abstract:

Realization of anticipated energy efficiency from recuperative run-around energy recovery (RER) systems requires identification of the system components influential parameters. Because simulation modeling is considered as an integral part of the design and economic evaluation of RER systems, it is essential to calibrate the developed models and validate the performance predictions by means of comparison with data from experimental measurements. Several theoretical and numerical analyses on RER systems by researchers have been done, but generally the effect of distance between hot and cold flow is ignored. The objective of this study is to develop a thermohydroulic model for a typical RER system that accounts for energy loss from the interconnecting piping and effects of interconnecting pipes length performance of run-around energy recovery systems. Numerical simulation shows that energy loss from the interconnecting piping is change linear with pipes length and if pipes are properly isolated, maximum reduction of effectiveness of RER systems is 2% in typical piping systems.

Keywords: combined heat and power, heat recovery, effectiveness, CGS

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4967 An Improved C-Means Model for MRI Segmentation

Authors: Ying Shen, Weihua Zhu

Abstract:

Medical images are important to help identifying different diseases, for example, Magnetic resonance imaging (MRI) can be used to investigate the brain, spinal cord, bones, joints, breasts, blood vessels, and heart. Image segmentation, in medical image analysis, is usually the first step to find out some characteristics with similar color, intensity or texture so that the diagnosis could be further carried out based on these features. This paper introduces an improved C-means model to segment the MRI images. The model is based on information entropy to evaluate the segmentation results by achieving global optimization. Several contributions are significant. Firstly, Genetic Algorithm (GA) is used for achieving global optimization in this model where fuzzy C-means clustering algorithm (FCMA) is not capable of doing that. Secondly, the information entropy after segmentation is used for measuring the effectiveness of MRI image processing. Experimental results show the outperformance of the proposed model by comparing with traditional approaches.

Keywords: magnetic resonance image (MRI), c-means model, image segmentation, information entropy

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4966 K-Means Based Matching Algorithm for Multi-Resolution Feature Descriptors

Authors: Shao-Tzu Huang, Chen-Chien Hsu, Wei-Yen Wang

Abstract:

Matching high dimensional features between images is computationally expensive for exhaustive search approaches in computer vision. Although the dimension of the feature can be degraded by simplifying the prior knowledge of homography, matching accuracy may degrade as a tradeoff. In this paper, we present a feature matching method based on k-means algorithm that reduces the matching cost and matches the features between images instead of using a simplified geometric assumption. Experimental results show that the proposed method outperforms the previous linear exhaustive search approaches in terms of the inlier ratio of matched pairs.

Keywords: feature matching, k-means clustering, SIFT, RANSAC

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4965 A Minimum Spanning Tree-Based Method for Initializing the K-Means Clustering Algorithm

Authors: J. Yang, Y. Ma, X. Zhang, S. Li, Y. Zhang

Abstract:

The traditional k-means algorithm has been widely used as a simple and efficient clustering method. However, the algorithm often converges to local minima for the reason that it is sensitive to the initial cluster centers. In this paper, an algorithm for selecting initial cluster centers on the basis of minimum spanning tree (MST) is presented. The set of vertices in MST with same degree are regarded as a whole which is used to find the skeleton data points. Furthermore, a distance measure between the skeleton data points with consideration of degree and Euclidean distance is presented. Finally, MST-based initialization method for the k-means algorithm is presented, and the corresponding time complexity is analyzed as well. The presented algorithm is tested on five data sets from the UCI Machine Learning Repository. The experimental results illustrate the effectiveness of the presented algorithm compared to three existing initialization methods.

Keywords: degree, initial cluster center, k-means, minimum spanning tree

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4964 Study of Sustainability Practices Ingrained in Indian Culture

Authors: Shraddha Mahore Manjrekar

Abstract:

Culture has been an integral part of the civilizations in the world. Architectural works, in the material form of buildings, are often perceived as cultural symbols and as works of art. Historical civilizations are often identified with their surviving architectural achievements. Author has observed and thought about the relation of Indian traditional cultural beliefs and their relation to the sustainable environment. There are some unwritten norms regarding the use of resources and the environment in Indian continent, that have been commonly accepted by the people for building houses and settlements since the Vedic period . The research has been done on the chanting and prayers done in a number of houses and temples in Madhya Pradesh and Maharashtra. After doing some research, it was also found that resource assessment had also been done for the entire country, and an idea of conservation of these resources was imbibed in the common people by means of some traditions, customs and beliefs. The sensitization and gratefulness about natural resources have been observed in the major beliefs and customs. This paper describes few of such beliefs and customs that are directly linked with the built environment and landscape.

Keywords: Indian culture, sacred groves, sustainability in built environment, sustainability practices

Procedia PDF Downloads 269
4963 Comparison Between Genetic Algorithms and Particle Swarm Optimization Optimized Proportional Integral Derirative and PSS for Single Machine Infinite System

Authors: Benalia Nadia, Zerzouri Nora, Ben Si Ali Nadia

Abstract:

Abstract: Among the many different modern heuristic optimization methods, genetic algorithms (GA) and the particle swarm optimization (PSO) technique have been attracting a lot of interest. The GA has gained popularity in academia and business mostly because to its simplicity, ability to solve highly nonlinear mixed integer optimization problems that are typical of complex engineering systems, and intuitiveness. The mechanics of the PSO methodology, a relatively recent heuristic search tool, are modeled after the swarming or cooperative behavior of biological groups. It is suitable to compare the performance of the two techniques since they both aim to solve a particular objective function but make use of distinct computing methods. In this article, PSO and GA optimization approaches are used for the parameter tuning of the power system stabilizer and Proportional integral derivative regulator. Load angle and rotor speed variations in the single machine infinite bus bar system is used to measure the performance of the suggested solution.

Keywords: SMIB, genetic algorithm, PSO, transient stability, power system stabilizer, PID

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4962 Creative Means to Address Mental Health in the African American Community: Arts, Advocacy, and Awareness

Authors: Denise F. Brown

Abstract:

This proposal provides an explanation of the content for a Special Topics Course to be offered Spring of 2022. The course will be titled, Creative means to address mental health in the African American Community: Arts, Advocacy, and Awareness. Research shows that African Americans are less likely to seek treatment for mental illnesses. The stigma around mental illness influences negative ideas about having psychological problems within the African American community. Assessments of how African Americans perceive mental illness will also be provided. Current research suggests that understanding mental health is just as important as understanding mental illness. The distinguishment between mental illness and mental health provides a way to not negatively point out mental illness but to better understand that psychological and emotional well-being can be achieved whether a mental illness is present or not. The course will consist of defining mental health and mental illness and then what it means to utilize creative means to become a mental health advocate within the African American community.

Keywords: arts, advocacy, black mental health, mental illness

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4961 Identification and Force Control of a Two Chambers Pneumatic Soft Actuator

Authors: Najib K. Dankadai, Ahmad 'Athif Mohd Faudzi, Khairuddin Osman, Muhammad Rusydi Muhammad Razif, IIi Najaa Aimi Mohd Nordin

Abstract:

Researches in soft actuators are now growing rapidly because of their adequacy to be applied in sectors like medical, agriculture, biological and welfare. This paper presents system identification (SI) and control of the force generated by a two chambers pneumatic soft actuator (PSA). A force mathematical model for the actuator was identified experimentally using data acquisition card and MATLAB SI toolbox. Two control techniques; a predictive functional control (PFC) and conventional proportional integral and derivative (PID) schemes are proposed and compared based on the identified model for the soft actuator flexible mechanism. Results of this study showed that both of the proposed controllers ensure accurate tracking when the closed loop system was tested with the step, sinusoidal and multi step reference input through MATLAB simulation although the PFC provides a better response than the PID.

Keywords: predictive functional control (PFC), proportional integral and derivative (PID), soft actuator, system identification

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4960 Comparative Study of Estimators of Population Means in Two Phase Sampling in the Presence of Non-Response

Authors: Syed Ali Taqi, Muhammad Ismail

Abstract:

A comparative study of estimators of population means in two phase sampling in the presence of non-response when Unknown population means of the auxiliary variable(s) and incomplete information of study variable y as well as of auxiliary variable(s) is made. Three real data sets of University students, hospital and unemployment are used for comparison of all the available techniques in two phase sampling in the presence of non-response with the newly generalized ratio estimators.

Keywords: two-phase sampling, ratio estimator, product estimator, generalized estimators

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4959 Performance Evaluation of Various Segmentation Techniques on MRI of Brain Tissue

Authors: U.V. Suryawanshi, S.S. Chowhan, U.V Kulkarni

Abstract:

Accuracy of segmentation methods is of great importance in brain image analysis. Tissue classification in Magnetic Resonance brain images (MRI) is an important issue in the analysis of several brain dementias. This paper portraits performance of segmentation techniques that are used on Brain MRI. A large variety of algorithms for segmentation of Brain MRI has been developed. The objective of this paper is to perform a segmentation process on MR images of the human brain, using Fuzzy c-means (FCM), Kernel based Fuzzy c-means clustering (KFCM), Spatial Fuzzy c-means (SFCM) and Improved Fuzzy c-means (IFCM). The review covers imaging modalities, MRI and methods for noise reduction and segmentation approaches. All methods are applied on MRI brain images which are degraded by salt-pepper noise demonstrate that the IFCM algorithm performs more robust to noise than the standard FCM algorithm. We conclude with a discussion on the trend of future research in brain segmentation and changing norms in IFCM for better results.

Keywords: image segmentation, preprocessing, MRI, FCM, KFCM, SFCM, IFCM

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4958 Early Requirement Engineering for Design of Learner Centric Dynamic LMS

Authors: Kausik Halder, Nabendu Chaki, Ranjan Dasgupta

Abstract:

We present a modelling framework that supports the engineering of early requirements specifications for design of learner centric dynamic Learning Management System. The framework is based on i* modelling tool and Means End Analysis, that adopts primitive concepts for modelling early requirements (such as actor, goal, and strategic dependency). We show how pedagogical and computational requirements for designing a learner centric Learning Management system can be adapted for the automatic early requirement engineering specifications. Finally, we presented a model on a Learner Quanta based adaptive Courseware. Our early requirement analysis shows that how means end analysis reveals gaps and inconsistencies in early requirements specifications that are by no means trivial to discover without the help of formal analysis tool.

Keywords: adaptive courseware, early requirement engineering, means end analysis, organizational modelling, requirement modelling

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4957 Experimental Study of Complete Loss of Coolant Flow (CLOF) Test by System–Integrated Modular Advanced Reactor Integral Test Loop (SMART-ITL) with Passive Residual Heat Removal System (PRHRS)

Authors: Jin Hwa Yang, Hwang Bae, Sung Uk Ryu, Byong Guk Jeon, Sung Jae Yi, Hyun Sik Park

Abstract:

Experimental studies using a large-scale thermal-hydraulic integral test facility, System–integrated Modular Advanced Reactor Integral Test Loop (SMART-ITL), have been carried out to validate the performance of the prototype, SMART. After Fukushima accident, the passive safety systems have been dealt as important designs for retaining of nuclear safety. One of the concerned scenarios for evaluating the passive safety system is a Complete Loss of Coolant Flow (CLOF). The flowrate of coolant in the primary system is maintained by Reactor Coolant Pump (RCP). When the supply of electric power of RCP is shut off, the flowrate of coolant decreases sharply, and the temperature of the coolant increases rapidly. Therefore, the reactor trip signal is activated to prevent the over-heating of the core. In this situation, Passive Residual Heat Removal System (PRHRS) plays a significant role to assure the soundness of the SMART. The PRHRS using a two-phase natural circulation is a passive safety system in the SMART to eliminate the heat of steam generator in the secondary system with heat exchanger submarined in the Emergency Cooling Tank (ECT). As the RCPs continue to coast down, inherent natural circulation in the primary system transfers heat to the secondary system. The transferred heat is removed by PRHRS in the secondary system. In this paper, the progress of the CLOF accident is described with experimental data of transient condition performed by SMART-ITL. Finally, the capability of passive safety system and inherent natural circulation will be evaluated.

Keywords: CLOF, natural circulation, PRHRS, SMART-ITL

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4956 Numerical Applications of Tikhonov Regularization for the Fourier Multiplier Operators

Authors: Fethi Soltani, Adel Almarashi, Idir Mechai

Abstract:

Tikhonov regularization and reproducing kernels are the most popular approaches to solve ill-posed problems in computational mathematics and applications. And the Fourier multiplier operators are an essential tool to extend some known linear transforms in Euclidean Fourier analysis, as: Weierstrass transform, Poisson integral, Hilbert transform, Riesz transforms, Bochner-Riesz mean operators, partial Fourier integral, Riesz potential, Bessel potential, etc. Using the theory of reproducing kernels, we construct a simple and efficient representations for some class of Fourier multiplier operators Tm on the Paley-Wiener space Hh. In addition, we give an error estimate formula for the approximation and obtain some convergence results as the parameters and the independent variables approaches zero. Furthermore, using numerical quadrature integration rules to compute single and multiple integrals, we give numerical examples and we write explicitly the extremal function and the corresponding Fourier multiplier operators.

Keywords: fourier multiplier operators, Gauss-Kronrod method of integration, Paley-Wiener space, Tikhonov regularization

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4955 Neural Network Approach for Solving Integral Equations

Authors: Bhavini Pandya

Abstract:

This paper considers Hη: T2 → T2 the Perturbed Cerbelli-Giona map. That is a family of 2-dimensional nonlinear area-preserving transformations on the torus T2=[0,1]×[0,1]= ℝ2/ ℤ2. A single parameter η varies between 0 and 1, taking the transformation from a hyperbolic toral automorphism to the “Cerbelli-Giona” map, a system known to exhibit multifractal properties. Here we study the multifractal properties of the family of maps. We apply a box-counting method by defining a grid of boxes Bi(δ), where i is the index and δ is the size of the boxes, to quantify the distribution of stable and unstable manifolds of the map. When the parameter is in the range 0.51< η <0.58 and 0.68< η <1 the map is ergodic; i.e., the unstable and stable manifolds eventually cover the whole torus, although not in a uniform distribution. For accurate numerical results we require correspondingly accurate construction of the stable and unstable manifolds. Here we use the piecewise linearity of the map to achieve this, by computing the endpoints of line segments which define the global stable and unstable manifolds. This allows the generalized fractal dimension Dq, and spectrum of dimensions f(α), to be computed with accuracy. Finally, the intersection of the unstable and stable manifold of the map will be investigated, and compared with the distribution of periodic points of the system.

Keywords: feed forward, gradient descent, neural network, integral equation

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4954 Assessing Students’ Attitudinal Response towards the Use of Virtual Reality in a Mandatory English Class at a Women’s University in Japan

Authors: Felix David

Abstract:

The use of virtual reality (VR) technology is still in its infancy. This is especially true in a Japanese educational context with very little to no exposition of VR technology inside classrooms. Technology is growing and changing rapidly in America, but Japan seems to be lagging behind in integrating VR into its curriculum. The aim of this research was to expose 111 students from Hiroshima Jogakuin University (HJU) to seven classes that involved virtual reality content and assess students’ attitudinal responses toward this new technology. The students are all female, and they are taking the “Kiso Eigo/基礎英語” or “Foundation English” course, which is mandatory for all first-year and second-year students. Two surveys were given, one before the treatment and a second survey after the treatment, which in this case means the seven VR classes. These surveys first established that the technical environment could accommodate VR activities in terms of internet connection, VR headsets, and the quality of the smartphone’s screen. Based on the attitudinal responses gathered in this research, VR is perceived by students as “fun,” useful to “learn about the world,” as well as being useful to “learn about English.” This research validates VR as a worthy educational tool and should therefore continue being an integral part of the mandatory English course curriculum at HJU University.

Keywords: virtual reality, smartphone, English learning, curriculum

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4953 Stresses Induced in Saturated Asphalt Pavement by Moving Loads

Authors: Yang Zhong, Meijie Xue

Abstract:

The purpose of this paper is to investigate the stresses and excess pore fluid pressure induced by the moving wheel pressure on saturated asphalt pavements, which is one of the reasons for a damage phenomenon in flexible pavement denoted stripping. The saturated asphalt pavement is modeled as multilayered poroelastic half space exerted by a wheel pressure, which is moving at a constant velocity along the surface of the pavement. The governing equations for the proposed analysis are based on the Biot’s theory of dynamics in saturated poroelastic medium. The governing partial differential equations are solved by using Laplace and Hankel integral transforms. The solutions for the stresses and excess pore pressure are expressed in the forms of numerical inversion Laplace and Hankel integral transforms. The numerical simulation results clearly demonstrate the induced deformation and water flow in the asphalt pavement.

Keywords: saturated asphalt pavements, moving loads, excess pore fluid pressure, stress of pavement, biot theory, stress and strain of pavement

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4952 3D Simulation of the Twin-Aperture IRON Superconducting Quadrupole for Charm-Tau Factory

Authors: K. K. Riabchenko, T. V Rybitskaya, A. A. Starostenko

Abstract:

Sper Charm-Tau Factory is a double ring e+e- collider to be operated in the center-of-mass energy range from 2 to 6 GeV, with a peak luminosity of about 1035 cm-2s-1 (Crab Waist collision) and with longitudinally polarized electrons at the IP (interaction point). One of the important elements of the cτ-factory is the superconducting two-aperture quadrupole of the final focus. It was decided to make a full-scale prototype quadrupole. The main objectives of our study included: 1) 3D modeling of the quadrupole in the Opera program, 2) Optimization of the geometry of the quadrupole lens, 3) Study of the influence of magnetic properties and geometry of a quadrupole on integral harmonics. In addition to this, the ways of producing unwanted harmonics have been studied. In the course of this work, a 3D model of a two-aperture iron superconducting quadrupole lens was created. A three-dimensional simulation of the magnetic field was performed, and the geometrical parameters of the lens were selected. Calculations helped to find sources of possible errors and methods for correcting unwanted harmonics. In addition to this, calculations show that there are no obstacles to the production of a prototype lens.

Keywords: super cτ-factory, final focus, twin aperture quadrupole lens, integral harmonics

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4951 A Mixture Vine Copula Structures Model for Dependence Wind Speed among Wind Farms and Its Application in Reactive Power Optimization

Authors: Yibin Qiu, Yubo Ouyang, Shihan Li, Guorui Zhang, Qi Li, Weirong Chen

Abstract:

This paper aims at exploring the impacts of high dimensional dependencies of wind speed among wind farms on probabilistic optimal power flow. To obtain the reactive power optimization faster and more accurately, a mixture vine Copula structure model combining the K-means clustering, C vine copula and D vine copula is proposed in this paper, through which a more accurate correlation model can be obtained. Moreover, a Modified Backtracking Search Algorithm (MBSA), the three-point estimate method is applied to probabilistic optimal power flow. The validity of the mixture vine copula structure model and the MBSA are respectively tested in IEEE30 node system with measured data of 3 adjacent wind farms in a certain area, and the results indicate effectiveness of these methods.

Keywords: mixture vine copula structure model, three-point estimate method, the probability integral transform, modified backtracking search algorithm, reactive power optimization

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4950 Robust Fractional Order Controllers for Minimum and Non-Minimum Phase Systems – Studies on Design and Development

Authors: Anand Kishore Kola, G. Uday Bhaskar Babu, Kotturi Ajay Kumar

Abstract:

The modern dynamic systems used in industries are complex in nature and hence the fractional order controllers have been contemplated as a fresh approach to control system design that takes the complexity into account. Traditional integer order controllers use integer derivatives and integrals to control systems, whereas fractional order controllers use fractional derivatives and integrals to regulate memory and non-local behavior. This study provides a method based on the maximumsensitivity (Ms) methodology to discover all resilient fractional filter Internal Model Control - proportional integral derivative (IMC-PID) controllers that stabilize the closed-loop system and deliver the highest performance for a time delay system with a Smith predictor configuration. Additionally, it helps to enhance the range of PID controllers that are used to stabilize the system. This study also evaluates the effectiveness of the suggested controller approach for minimum phase system in comparison to those currently in use which are based on Integral of Absolute Error (IAE) and Total Variation (TV).

Keywords: modern dynamic systems, fractional order controllers, maximum-sensitivity, IMC-PID controllers, Smith predictor, IAE and TV

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4949 Experimental Film Class: Watbangkapom School, Samut Songkhram

Authors: J. Areerut

Abstract:

Experimental Film Class Project is supported by the Institute for Research and Development at Suan Sunandha Rajabhat University. This project is purported to provide academic and professional services to improve the quality standards of the community and locals in accordance with the mission of the university, which is to improve and expand knowledge for the community and to develop and transfer such knowledge and professions to the next generation. Eventually, it leads to sustainable development because the development of human resources is deemed as the key for sustainable development. Moreover, the Experimental Film Class is an integral part of the teaching of film production at Suan Sunandha International School of Art (SISA). By means of giving opportunities to students for participation in projects by sharing experience, skill and knowledge and participation in field activities, it helps students in the film production major to enhance their abilities and potentials as preparation for their readiness in the marketplace. Additionally, in this class, we provide basic film knowledge, screenwriting techniques, editing and subtitles including uploading videos on social media such as YouTube and Facebook for the participant students.

Keywords: experimental film class, Watbangkapom School, participant students, basic of film production, film workshop

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4948 Compact Finite Difference Schemes for Fourth Order Parabolic Partial Differential Equations

Authors: Sufyan Muhammad

Abstract:

Recently, in achieving highly efficient but at the same time highly accurate solutions has become the major target of numerical analyst community. The concept is termed as compact schemes and has gained great popularity and consequently, we construct compact schemes for fourth order parabolic differential equations used to study vibrations in structures. For the superiority of newly constructed schemes, we consider range of examples. We have achieved followings i.e. (a) numerical scheme utilizes minimum number of stencil points (which means new scheme is compact); (b) numerical scheme is highly accurate (which means new scheme is reliable) and (c) numerical scheme is highly efficient (which means new scheme is fast).

Keywords: central finite differences, compact schemes, Bernoulli's equations, finite differences

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4947 A Computational Cost-Effective Clustering Algorithm in Multidimensional Space Using the Manhattan Metric: Application to the Global Terrorism Database

Authors: Semeh Ben Salem, Sami Naouali, Moetez Sallami

Abstract:

The increasing amount of collected data has limited the performance of the current analyzing algorithms. Thus, developing new cost-effective algorithms in terms of complexity, scalability, and accuracy raised significant interests. In this paper, a modified effective k-means based algorithm is developed and experimented. The new algorithm aims to reduce the computational load without significantly affecting the quality of the clusterings. The algorithm uses the City Block distance and a new stop criterion to guarantee the convergence. Conducted experiments on a real data set show its high performance when compared with the original k-means version.

Keywords: pattern recognition, global terrorism database, Manhattan distance, k-means clustering, terrorism data analysis

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4946 Improve Closed Loop Performance and Control Signal Using Evolutionary Algorithms Based PID Controller

Authors: Mehdi Shahbazian, Alireza Aarabi, Mohsen Hadiyan

Abstract:

Proportional-Integral-Derivative (PID) controllers are the most widely used controllers in industry because of its simplicity and robustness. Different values of PID parameters make different step response, so an increasing amount of literature is devoted to proper tuning of PID controllers. The problem merits further investigation as traditional tuning methods make large control signal that can damages the system but using evolutionary algorithms based tuning methods improve the control signal and closed loop performance. In this paper three tuning methods for PID controllers have been studied namely Ziegler and Nichols, which is traditional tuning method and evolutionary algorithms based tuning methods, that are, Genetic algorithm and particle swarm optimization. To examine the validity of PSO and GA tuning methods a comparative analysis of DC motor plant is studied. Simulation results reveal that evolutionary algorithms based tuning method have improved control signal amplitude and quality factors of the closed loop system such as rise time, integral absolute error (IAE) and maximum overshoot.

Keywords: evolutionary algorithm, genetic algorithm, particle swarm optimization, PID controller

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4945 The Beam Expansion Method, A Simplified and Efficient Approach of Field Propagation and Resonators Modes Study

Authors: Zaia Derrar Kaddour

Abstract:

The study of a beam throughout an optical path is generally achieved by means of diffraction integral. Unfortunately, in some problems, this tool turns out to be not very friendly and hard to implement. Instead, the beam expansion method for computing field profiles appears to be an interesting alternative. The beam expansion method consists of expanding the field pattern as a series expansion in a set of orthogonal functions. Propagating each individual component through a circuit and adding up the derived elements leads easily to the result. The problem is then reduced to finding how the expansion coefficients change in a circuit. The beam expansion method requires a systematic study of each type of optical element that can be met in the considered optical path. In this work, we analyze the following fundamental elements: first order optical systems, hard apertures and waveguides. We show that the former element type is completely defined thanks to the Gouy phase shift expression we provide and the latters require a suitable mode conversion. For endorsing the usefulness and relevance of the beam expansion approach, we show here some of its applications such as the treatment of the thermal lens effect and the study of unstable resonators.

Keywords: gouy phase shift, modes, optical resonators, unstable resonators

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4944 Online Battery Equivalent Circuit Model Estimation on Continuous-Time Domain Using Linear Integral Filter Method

Authors: Cheng Zhang, James Marco, Walid Allafi, Truong Q. Dinh, W. D. Widanage

Abstract:

Equivalent circuit models (ECMs) are widely used in battery management systems in electric vehicles and other battery energy storage systems. The battery dynamics and the model parameters vary under different working conditions, such as different temperature and state of charge (SOC) levels, and therefore online parameter identification can improve the modelling accuracy. This paper presents a way of online ECM parameter identification using a continuous time (CT) estimation method. The CT estimation method has several advantages over discrete time (DT) estimation methods for ECM parameter identification due to the widely separated battery dynamic modes and fast sampling. The presented method can be used for online SOC estimation. Test data are collected using a lithium ion cell, and the experimental results show that the presented CT method achieves better modelling accuracy compared with the conventional DT recursive least square method. The effectiveness of the presented method for online SOC estimation is also verified on test data.

Keywords: electric circuit model, continuous time domain estimation, linear integral filter method, parameter and SOC estimation, recursive least square

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4943 Evaluation Means in English and Russian Academic Discourse: Through Comparative Analysis towards Translation

Authors: Albina Vodyanitskaya

Abstract:

Given the culture- and language-specific nature of evaluation, this phenomenon is widely studied around the linguistic world and may be regarded as a challenge for translators. Evaluation penetrates all the levels of a scientific text, influences its composition and the reader’s attitude towards the information presented. One of the most challenging and rarely studied phenomena is the individual style of the scientific writer, which is mostly reflected in the use of evaluative language means. The evaluative and expressive potential of a scientific text is becoming more and more welcoming area for researchers, which stems in the shift towards anthropocentric paradigm in linguistics. Other reasons include: the cognitive and psycholinguistic processes that accompany knowledge acquisition, a genre-determined nature of a scientific text, the increasing public concern about the quality of scientific papers and some such. One more important issue, is the fact that linguists all over the world still argue about the definition of evaluation and its functions in the text. The author analyzes various approaches towards the study of evaluation and scientific texts. A comparative analysis of English and Russian dissertations and other scientific papers with regard to evaluative language means reveals major differences and similarities between English and Russian scientific style. Though standardized and genre-specific, English scientific texts contain more figurative and expressive evaluative means than the Russian ones, which should be taken into account while translating scientific papers. The processes that evaluation undergoes while being expressed by means of a target language are also analyzed. The author offers a target-language-dependent strategy for the translation of evaluation in English and Russian scientific texts. The findings may contribute to the theory and practice of translation and can increase scientific writers’ awareness of inter-language and intercultural differences in evaluative language means.

Keywords: academic discourse, evaluation, scientific text, scientific writing, translation

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4942 Design and Optimization of Open Loop Supply Chain Distribution Network Using Hybrid K-Means Cluster Based Heuristic Algorithm

Authors: P. Suresh, K. Gunasekaran, R. Thanigaivelan

Abstract:

Radio frequency identification (RFID) technology has been attracting considerable attention with the expectation of improved supply chain visibility for consumer goods, apparel, and pharmaceutical manufacturers, as well as retailers and government procurement agencies. It is also expected to improve the consumer shopping experience by making it more likely that the products they want to purchase are available. Recent announcements from some key retailers have brought interest in RFID to the forefront. A modified K- Means Cluster based Heuristic approach, Hybrid Genetic Algorithm (GA) - Simulated Annealing (SA) approach, Hybrid K-Means Cluster based Heuristic-GA and Hybrid K-Means Cluster based Heuristic-GA-SA for Open Loop Supply Chain Network problem are proposed. The study incorporated uniform crossover operator and combined crossover operator in GAs for solving open loop supply chain distribution network problem. The algorithms are tested on 50 randomly generated data set and compared with each other. The results of the numerical experiments show that the Hybrid K-means cluster based heuristic-GA-SA, when tested on 50 randomly generated data set, shows superior performance to the other methods for solving the open loop supply chain distribution network problem.

Keywords: RFID, supply chain distribution network, open loop supply chain, genetic algorithm, simulated annealing

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4941 Flat-Top Apodization of Laser Beams by Means of Acousto-Optics

Authors: Sergey I. Chizhikov, Vladimir Y. Molchanov, Konstantin B. Yushkov

Abstract:

We demonstrate a method for adaptive spatial shaping of laser beams by means of acousto-optic Bragg diffraction. Transformation of the angular spectrum during Bragg diffraction is used to convert Gaussian intensity distribution into a flat-top one. Theoretical model is supported by the experiment.

Keywords: acousto-optics, flat top, beam shaping, Bragg diffraction

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4940 Multi-Scaled Non-Local Means Filter for Medical Images Denoising: Empirical Mode Decomposition vs. Wavelet Transform

Authors: Hana Rabbouch

Abstract:

In recent years, there has been considerable growth of denoising techniques mainly devoted to medical imaging. This important evolution is not only due to the progress of computing techniques, but also to the emergence of multi-resolution analysis (MRA) on both mathematical and algorithmic bases. In this paper, a comparative study is conducted between the two best-known MRA-based decomposition techniques: the Empirical Mode Decomposition (EMD) and the Discrete Wavelet Transform (DWT). The comparison is carried out in a framework of multi-scale denoising, where a Non-Local Means (NLM) filter is performed scale-by-scale to a sample of benchmark medical images. The results prove the effectiveness of the multiscaled denoising, especially when the NLM filtering is coupled with the EMD.

Keywords: medical imaging, non local means, denoising, multiscaled analysis, empirical mode decomposition, wavelets

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