Search results for: firm performance.
Commenced in January 2007
Frequency: Monthly
Edition: International
Paper Count: 5914

Search results for: firm performance.

3364 Comparison of Multivariate Adaptive Regression Splines and Random Forest Regression in Predicting Forced Expiratory Volume in One Second

Authors: P. V. Pramila, V. Mahesh

Abstract:

Pulmonary Function Tests are important non-invasive diagnostic tests to assess respiratory impairments and provides quantifiable measures of lung function. Spirometry is the most frequently used measure of lung function and plays an essential role in the diagnosis and management of pulmonary diseases. However, the test requires considerable patient effort and cooperation, markedly related to the age of patients resulting in incomplete data sets. This paper presents, a nonlinear model built using Multivariate adaptive regression splines and Random forest regression model to predict the missing spirometric features. Random forest based feature selection is used to enhance both the generalization capability and the model interpretability. In the present study, flow-volume data are recorded for N= 198 subjects. The ranked order of feature importance index calculated by the random forests model shows that the spirometric features FVC, FEF25, PEF, FEF25-75, FEF50 and the demographic parameter height are the important descriptors. A comparison of performance assessment of both models prove that, the prediction ability of MARS with the `top two ranked features namely the FVC and FEF25 is higher, yielding a model fit of R2= 0.96 and R2= 0.99 for normal and abnormal subjects. The Root Mean Square Error analysis of the RF model and the MARS model also shows that the latter is capable of predicting the missing values of FEV1 with a notably lower error value of 0.0191 (normal subjects) and 0.0106 (abnormal subjects) with the aforementioned input features. It is concluded that combining feature selection with a prediction model provides a minimum subset of predominant features to train the model, as well as yielding better prediction performance. This analysis can assist clinicians with a intelligence support system in the medical diagnosis and improvement of clinical care.

Keywords: FEV1, Multivariate Adaptive Regression Splines Pulmonary Function Test, Random Forest.

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3363 Block Sorting: A New Characterization and a New Heuristic

Authors: Swapnoneel Roy, Ashok Kumar Thakur, Minhazur Rahman

Abstract:

The Block Sorting problem is to sort a given permutation moving blocks. A block is defined as a substring of the given permutation, which is also a substring of the identity permutation. Block Sorting has been proved to be NP-Hard. Until now two different 2-Approximation algorithms have been presented for block sorting. These are the best known algorithms for Block Sorting till date. In this work we present a different characterization of Block Sorting in terms of a transposition cycle graph. Then we suggest a heuristic, which we show to exhibit a 2-approximation performance guarantee for most permutations.

Keywords: Block Sorting, Optical Character Recognition, Genome Rearrangements, Sorting Primitives, ApproximationAlgorithms

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3362 A Study of Neuro-Fuzzy Inference System for Gross Domestic Product Growth Forecasting

Authors: Ε. Giovanis

Abstract:

In this paper we present a Adaptive Neuro-Fuzzy System (ANFIS) with inputs the lagged dependent variable for the prediction of Gross domestic Product growth rate in six countries. We compare the results with those of Autoregressive (AR) model. We conclude that the forecasting performance of neuro-fuzzy-system in the out-of-sample period is much more superior and can be a very useful alternative tool used by the national statistical services and the banking and finance industry.

Keywords: Autoregressive model, Forecasting, Gross DomesticProduct, Neuro-Fuzzy

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3361 Designing Intelligent Adaptive Controller for Nonlinear Pendulum Dynamical System

Authors: R. Ghasemi, M. R. Rahimi Khoygani

Abstract:

This paper proposes the designing direct adaptive neural controller to apply for a class of a nonlinear pendulum dynamic system. The radial basis function (RBF) neural adaptive controller is robust in presence of external and internal uncertainties. Both the effectiveness of the controller and robustness against disturbances are importance of this paper. The simulation results show the promising performance of the proposed controller.

Keywords: Adaptive Neural Controller, Nonlinear Dynamical, Neural Network, RBF, Driven Pendulum, Position Control.

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3360 Maximum Power Point Tracking Using FLC Tuned with GA

Authors: Mohamed Amine Haraoubia, Abdelaziz Hamzaoui, Najib Essounbouli

Abstract:

The pursuit of the MPPT has led to the development of many kinds of controllers, one of which is the Fuzzy Logic controller, which has proven its worth. To further tune this controller this paper will discuss and analyze the use of Genetic Algorithms to tune the Fuzzy Logic Controller. It will provide an introduction to both systems, and test their compatibility and performance.

Keywords: Fuzzy logic controller (FLC), fuzzy logic (FL), genetic algorithm (GA), maximum power point (MPP), maximum power point tracking (MPPT).

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3359 Biodiesel Production from Soybean Oil over TiO2 Supported nano-ZnO

Authors: Mbala Mukenga, Edison Muzenda, Kalala Jalama, Reinout Meijboom

Abstract:

TiO2 supported nano-ZnO catalyst was prepared by deposition-precipitation and tested for the trans-esterification reaction of soybean oil to biodiesel. The TiO2 support stabilized the nano-ZnO in a dispersed form with limited crystallite size compared to the unsupported ZnO. The final ZnO dispersion and crystallite size and the material transfer resistance in the catalyst significantly influenced the supported nano-ZnO catalyst performance.

Keywords: nano-ZnO, soybean oil, TiO2, trans-esterification

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3358 Sensorless PM Motor with Multi Degree of Freedom Fuzzy Control

Authors: Faeka M. H. Khater, Farouk I. Ahmed, Mohamed I. Abu El- Sebah

Abstract:

This paper introduces application of multi degree of freedom fuzzy(MDOFF) controller in permanent magnet (PM)drive system. The drive system model is developed for FO control. Simulation of the system is carried out to predict the performance at NL and under load,. The results indicate that application of MDOFF controller is effective for sensorless PM drive system.

Keywords: Sensorless FO controller, PM drives system, MDOFF controller.

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3357 Analysis of Poverty Reduction Strategies as Mechanism for Development in Nigeria from 1999-2014

Authors: Ahmed Usman Egye, Hamza Muhammad

Abstract:

Poverty alleviation is one of the most difficult challenges facing third world countries in their development efforts. Evidences in Nigeria showed that the number of those in poverty has continued to increase. This paper is aimed at analyzing the performance of poverty alleviation measures undertaken by successive administrations in Nigeria with a view to addressing the quagmire. The study identified the whole gamut of factors that served as stumbling blocks to the implementation of each of the strategies and recommended the involvement of local people in the identification and design of projects so that sufficient participation could be achieved.

Keywords: Poverty, development, strategies, Nigeria.

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3356 The Fabrication and Characterization of a Honeycomb Ceramic Electric Heater with a Conductive Coating

Authors: Siming Wang, Qing Ni, Yu Wu, Ruihai Xu, Hong Ye

Abstract:

Porous electric heaters, compared to conventional electric heaters, exhibit excellent heating performance due to their large specific surface area. Porous electric heaters employ porous metallic materials or conductive porous ceramics as the heating element. The former attains a low heating power with a fixed current due to the low electrical resistivity of metal. Although the latter can bypass the inherent challenges of porous metallic materials, the fabrication process of the conductive porous ceramics is complicated and high cost. This work proposed a porous ceramic electric heater with dielectric honeycomb ceramic as a substrate and surface conductive coating as a heating element. The conductive coating was prepared by the sol-gel method using silica sol and methyl trimethoxysilane as raw materials and graphite powder as conductive fillers. The conductive mechanism and degradation reason of the conductive coating was studied by electrical resistivity and thermal stability analysis. The heating performance of the proposed heater was experimentally investigated by heating air and deionized water. The results indicate that the electron transfer is achieved by forming the conductive network through the contact of the graphite flakes. With 30 wt% of graphite, the electrical resistivity of the conductive coating can be as low as 0.88 Ω∙cm. The conductive coating exhibits good electrical stability up to 500 °C but degrades beyond 600 °C due to the formation of many cracks in the coating caused by the weight loss and thermal expansion. The results also show that the working medium has a great influence on the volume power density of the heater. With air under natural convection as the working medium, the volume power density attains 640.85 kW/m3, which can be increased by 5 times when using deionized water as the working medium. The proposed honeycomb ceramic electric heater has the advantages of the simple fabrication method, low cost, and high-volume power density, demonstrating great potential in the fluid heating field.

Keywords: Conductive coating, honeycomb ceramic electric heater, high specific surface area, high volume power density.

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3355 Region-Based Segmentation of Generic Video Scenes Indexing

Authors: Aree A. Mohammed

Abstract:

In this work we develop an object extraction method and propose efficient algorithms for object motion characterization. The set of proposed tools serves as a basis for development of objectbased functionalities for manipulation of video content. The estimators by different algorithms are compared in terms of quality and performance and tested on real video sequences. The proposed method will be useful for the latest standards of encoding and description of multimedia content – MPEG4 and MPEG7.

Keywords: Object extraction, Video indexing, Segmentation, Optical flow, Motion estimators.

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3354 IKEv1 and IKEv2: A Quantitative Analyses

Authors: H.Soussi, M.Hussain, H.Afifi, D.Seret

Abstract:

Key management is a vital component in any modern security protocol. Due to scalability and practical implementation considerations automatic key management seems a natural choice in significantly large virtual private networks (VPNs). In this context IETF Internet Key Exchange (IKE) is the most promising protocol under permanent review. We have made a humble effort to pinpoint IKEv2 net gain over IKEv1 due to recent modifications in its original structure, along with a brief overview of salient improvements between the two versions. We have used US National Institute of Technology NIIST VPN simulator to get some comparisons of important performance metrics.

Keywords: Quantitative Analyses, IKEv1, IKEv2, NIIST.

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3353 Semi-Blind Two-Dimensional Code Acquisition in CDMA Communications

Authors: Rui Wu, Tapani Ristaniemi

Abstract:

In this paper, we propose a new algorithm for joint time-delay and direction-of-arrival (DOA) estimation, here called two-dimensional code acquisition, in an asynchronous directsequence code-division multiple-access (DS-CDMA) array system. This algorithm depends on eigenvector-eigenvalue decomposition of sample correlation matrix, and requires to know desired user-s training sequence. The performance of the algorithm is analyzed both analytically and numerically in uncorrelated and coherent multipath environment. Numerical examples show that the algorithm is robust with unknown number of coherent signals.

Keywords: Two-Dimensional Code Acquisition, EV-t, DSCDMA

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3352 A Fast Code Acquisition Scheme for O-CDMA Systems

Authors: Youngpo Lee, Jaewoo Lee, Seokho Yoon

Abstract:

This paper proposes a fast code acquisition scheme for optical code division multiple access (O-CDMA) systems. Unlike the conventional scheme, the proposed scheme employs multiple thresholds providing a shorter mean acquisition time (MAT) performance. The simulation results show that the MAT of the proposed scheme is shorter than that of the conventional scheme.

Keywords: Optical CDMA, acquisition, MAT, multiple-shift

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3351 Permeable Asphalt Pavement as a Measure of Urban Green Infrastructure in the Extreme Events Mitigation

Authors: Márcia Afonso, Cristina Fael, Marisa Dinis-Almeida

Abstract:

Population growth in cities has led to an increase in the infrastructures construction, including buildings and roadways. This aspect leads directly to the soils waterproofing. In turn, changes in precipitation patterns are developing into higher and more frequent intensities. Thus, these two conjugated aspects decrease the rainwater infiltration into soils and increase the volume of surface runoff. The practice of green and sustainable urban solutions has encouraged research in these areas. The porous asphalt pavement, as a green infrastructure, is part of practical solutions set to address urban challenges related to land use and adaptation to climate change. In this field, permeable pavements with porous asphalt mixtures (PA) have several advantages in terms of reducing the runoff generated by the floods. The porous structure of these pavements, compared to a conventional asphalt pavement, allows the rainwater infiltration in the subsoil, and consequently, the water quality improvement. This green infrastructure solution can be applied in cities, particularly in streets or parking lots to mitigate the floods effects. Over the years, the pores of these pavements can be filled by sediment, reducing their function in the rainwater infiltration. Thus, double layer porous asphalt (DLPA) was developed to mitigate the clogging effect and facilitate the water infiltration into the lower layers. This study intends to deepen the knowledge of the performance of DLPA when subjected to clogging. The experimental methodology consisted on four evaluation phases of the DLPA infiltration capacity submitted to three precipitation events (100, 200 and 300 mm/h) in each phase. The evaluation first phase determined the behavior after DLPA construction. In phases two and three, two 500 g/m2 clogging cycles were performed, totaling a 1000 g/m2 final simulation. Sand with gradation accented in fine particles was used as clogging material. In the last phase, the DLPA was subjected to simple sweeping and vacuuming maintenance. A precipitation simulator, type sprinkler, capable of simulating the real precipitation was developed for this purpose. The main conclusions show that the DLPA has the capacity to drain the water, even after two clogging cycles. The infiltration results of flows lead to an efficient performance of the DPLA in the surface runoff attenuation, since this was not observed in any of the evaluation phases, even at intensities of 200 and 300 mm/h, simulating intense precipitation events. The infiltration capacity under clogging conditions decreased about 7% on average in the three intensities relative to the initial performance that is after construction. However, this was restored when subjected to simple maintenance, recovering the DLPA hydraulic functionality. In summary, the study proved the efficacy of using a DLPA when it retains thicker surface sediments and limits the fine sediments entry to the remaining layers. At the same time, it is guaranteed the rainwater infiltration and the surface runoff reduction and is therefore a viable solution to put into practice in permeable pavements.

Keywords: Clogging, double layer porous asphalt, infiltration capacity, rainfall intensity.

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3350 Analog Circuit Design using Genetic Algorithm: Modified

Authors: Amod P. Vaze

Abstract:

Genetic Algorithm has been used to solve wide range of optimization problems. Some researches conduct on applying Genetic Algorithm to analog circuit design automation. These researches show a better performance due to the nature of Genetic Algorithm. In this paper a modified Genetic Algorithm is applied for analog circuit design automation. The modifications are made to the topology of the circuit. These modifications will lead to a more computationally efficient algorithm.

Keywords: Genetic algorithm, analog circuits, design.

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3349 Approximate Range-Sum Queries over Data Cubes Using Cosine Transform

Authors: Wen-Chi Hou, Cheng Luo, Zhewei Jiang, Feng Yan

Abstract:

In this research, we propose to use the discrete cosine transform to approximate the cumulative distributions of data cube cells- values. The cosine transform is known to have a good energy compaction property and thus can approximate data distribution functions easily with small number of coefficients. The derived estimator is accurate and easy to update. We perform experiments to compare its performance with a well-known technique - the (Haar) wavelet. The experimental results show that the cosine transform performs much better than the wavelet in estimation accuracy, speed, space efficiency, and update easiness.

Keywords: DCT, Data Cube

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3348 A Family of Affine Projection Adaptive Filtering Algorithms With Selective Regressors

Authors: Mohammad Shams Esfand Abadi, Nader Hadizadeh Kashani, Vahid Mehrdad

Abstract:

In this paper we present a general formalism for the establishment of the family of selective regressor affine projection algorithms (SR-APA). The SR-APA, the SR regularized APA (SR-RAPA), the SR partial rank algorithm (SR-PRA), the SR binormalized data reusing least mean squares (SR-BNDR-LMS), and the SR normalized LMS with orthogonal correction factors (SR-NLMS-OCF) algorithms are established by this general formalism. We demonstrate the performance of the presented algorithms through simulations in acoustic echo cancellation scenario.

Keywords: Adaptive filter, affine projection, selective regressor.

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3347 Linear Elasticity Problems Solved by Using the Fictitious Domain Method and Total - FETI Domain Decomposition

Authors: Lukas Mocek, Alexandros Markopoulos

Abstract:

The main goal of this paper is to show a possibility, how to solve numerically elliptic boundary value problems arising in 2D linear elasticity by using the fictitious domain method (FDM) and the Total-FETI domain decomposition method. We briefly mention the theoretical background of these methods and demonstrate their performance on a benchmark.

Keywords: Linear elasticity, fictitious domain method, Total-FETI, domain decomposition, saddle-point system.

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3346 Adaptive MPC Using a Recursive Learning Technique

Authors: Ahmed Abbas Helmy, M. R. M. Rizk, Mohamed El-Sayed

Abstract:

A model predictive controller based on recursive learning is proposed. In this SISO adaptive controller, a model is automatically updated using simple recursive equations. The identified models are then stored in the memory to be re-used in the future. The decision for model update is taken based on a new control performance index. The new controller allows the use of simple linear model predictive controllers in the control of nonlinear time varying processes.

Keywords: Adaptive control, model predictive control, dynamic matrix control, online model identification

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3345 Immobilized Liquid Membrane for Propylene- Propane Separation

Authors: Maryam TakhtRavanchi, Tahereh Kaghazchi, Ali Kargari

Abstract:

Separation of propylene-propane mixture using immobilized liquid membrane was investigated. The effect of transmembrane pressure and carrier concentration on membrane separation performance was studied. It was observed that for 30:70 (vol. %) propylene-propane mixture, at pressure of 120kPa and carrier concentration of 20wt. %, a separation factor of 474 was obtained.

Keywords: Facilitated Transport, Immobilized Liquid Membrane, Propylene-Propane Separation, Silver Nitrate.

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3344 Loading Methodology for a Capacity Constrained Job-Shop

Authors: Viraj Tyagi, Ajai Jain, P. K. Jain, Aarushi Jain

Abstract:

This paper presents a genetic algorithm based loading methodology for a capacity constrained job-shop with the consideration of alternative process plans for each part to be produced. Performance analysis of the proposed methodology is carried out for two case studies by considering two different manufacturing scenarios. Results obtained indicate that the methodology is quite effective in improving the shop load balance, and hence, it can be included in the frameworks of manufacturing planning systems of job-shop oriented industries.

Keywords: Manufacturing planning, loading, genetic algorithm, Job-Shop

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3343 A Dataset of Program Educational Objectives Mapped to ABET Outcomes: Data Cleansing, Exploratory Data Analysis and Modeling

Authors: Addin Osman, Anwar Ali Yahya, Mohammed Basit Kamal

Abstract:

Datasets or collections are becoming important assets by themselves and now they can be accepted as a primary intellectual output of a research. The quality and usage of the datasets depend mainly on the context under which they have been collected, processed, analyzed, validated, and interpreted. This paper aims to present a collection of program educational objectives mapped to student’s outcomes collected from self-study reports prepared by 32 engineering programs accredited by ABET. The manual mapping (classification) of this data is a notoriously tedious, time consuming process. In addition, it requires experts in the area, which are mostly not available. It has been shown the operational settings under which the collection has been produced. The collection has been cleansed, preprocessed, some features have been selected and preliminary exploratory data analysis has been performed so as to illustrate the properties and usefulness of the collection. At the end, the collection has been benchmarked using nine of the most widely used supervised multiclass classification techniques (Binary Relevance, Label Powerset, Classifier Chains, Pruned Sets, Random k-label sets, Ensemble of Classifier Chains, Ensemble of Pruned Sets, Multi-Label k-Nearest Neighbors and Back-Propagation Multi-Label Learning). The techniques have been compared to each other using five well-known measurements (Accuracy, Hamming Loss, Micro-F, Macro-F, and Macro-F). The Ensemble of Classifier Chains and Ensemble of Pruned Sets have achieved encouraging performance compared to other experimented multi-label classification methods. The Classifier Chains method has shown the worst performance. To recap, the benchmark has achieved promising results by utilizing preliminary exploratory data analysis performed on the collection, proposing new trends for research and providing a baseline for future studies.

Keywords: Benchmark collection, program educational objectives, student outcomes, ABET, Accreditation, machine learning, supervised multiclass classification, text mining.

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3342 Modification of Rk Equation of State for Liquid and Vapor of Ammonia by Genetic Algorithm

Authors: S. Mousavian, F. Mousavian, V. Nikkhah Rashidabad

Abstract:

Cubic equations of state like Redlich–Kwong (RK)  EOS have been proved to be very reliable tools in the prediction of  phase behavior. Despite their good performance in compositional  calculations, they usually suffer from weaknesses in the predictions  of saturated liquid density. In this research, RK equation was  modified. The result of this study show that modified equation has  good agreement with experimental data.

 

Keywords: Equation of state, modification, ammonia, genetic algorithm.

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3341 Intuition Operator: Providing Genomes with Reason

Authors: Grigorios N. Beligiannis, Georgios A. Tsirogiannis, Panayotis E. Pintelas

Abstract:

In this contribution, the use of a new genetic operator is proposed. The main advantage of using this operator is that it is able to assist the evolution procedure to converge faster towards the optimal solution of a problem. This new genetic operator is called ''intuition'' operator. Generally speaking, one can claim that this operator is a way to include any heuristic or any other local knowledge, concerning the problem, that cannot be embedded in the fitness function. Simulation results show that the use of this operator increases significantly the performance of the classic Genetic Algorithm by increasing the convergence speed of its population.

Keywords: Genetic algorithms, intuition operator, reasonable genomes, complex search space, nonlinear fitness functions

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3340 An Innovative Fuzzy Decision Making Based Genetic Algorithm

Authors: M. A. Sharbafi, M. Shakiba Herfeh, Caro Lucas, A. Mohammadi Nejad

Abstract:

Several researchers have proposed methods about combination of Genetic Algorithm (GA) and Fuzzy Logic (the use of GA to obtain fuzzy rules and application of fuzzy logic in optimization of GA). In this paper, we suggest a new method in which fuzzy decision making is used to improve the performance of genetic algorithm. In the suggested method, we determine the alleles that enhance the fitness of chromosomes and try to insert them to the next generation. In this algorithm we try to present an innovative vaccination in the process of reproduction in genetic algorithm, with considering the trade off between exploration and exploitation.

Keywords: Genetic Algorithm, Fuzzy Decision Making.

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3339 Developing of Intelligent Schools with a New Model of Strategic Management System

Authors: Ahmad Ghayoumi, Mehdi Ghayoumi

Abstract:

Intelligent schools are those which use IT devices and technologies as media software, hardware and networks to improve learning process. On the other hand Strategic management is a field that deals with the major intended and emergent initiatives taken by general managers on behalf of owners, involving utilization of resources, to enhance the performance of firms in their external environments. Here, we present a model Strategic Management System that has been applied on some schools and have made strict improvement.

Keywords: Intelligent school, Strategic management system, Learning station, Teaching station

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3338 An Energy Efficient Algorithm for Distributed Mutual Exclusion in Mobile Ad-hoc Networks

Authors: Sayani Sil, Sukanta Das

Abstract:

This paper reports a distributed mutual exclusion algorithm for mobile Ad-hoc networks. The network is clustered hierarchically. The proposed algorithm considers the clustered network as a logical tree and develops a token passing scheme to get the mutual exclusion. The performance analysis and simulation results show that its message requirement is optimal, and thus the algorithm is energy efficient.

Keywords: Critical section, Distributed mutual exclusion, MobileAd-hoc network, Token-based algorithms.

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3337 Development of Mechanical Properties of Self Compacting Concrete Contain Rice Husk Ash

Authors: M. A. Ahmadi, O. Alidoust, I. Sadrinejad, M. Nayeri

Abstract:

Self-compacting concrete (SCC), a new kind of high performance concrete (HPC) have been first developed in Japan in 1986. The development of SCC has made casting of dense reinforcement and mass concrete convenient, has minimized noise. Fresh self-compacting concrete (SCC) flows into formwork and around obstructions under its own weight to fill it completely and self-compact (without any need for vibration), without any segregation and blocking. The elimination of the need for compaction leads to better quality concrete and substantial improvement of working conditions. SCC mixes generally have a much higher content of fine fillers, including cement, and produce excessively high compressive strength concrete, which restricts its field of application to special concrete only. To use SCC mixes in general concrete construction practice, requires low cost materials to make inexpensive concrete. Rice husk ash (RHA) has been used as a highly reactive pozzolanic material to improve the microstructure of the interfacial transition zone (ITZ) between the cement paste and the aggregate in self compacting concrete. Mechanical experiments of RHA blended Portland cement concretes revealed that in addition to the pozzolanic reactivity of RHA (chemical aspect), the particle grading (physical aspect) of cement and RHA mixtures also exerted significant influences on the blending efficiency. The scope of this research was to determine the usefulness of Rice husk ash (RHA) in the development of economical self compacting concrete (SCC). The cost of materials will be decreased by reducing the cement content by using waste material like rice husk ash instead of. This paper presents a study on the development of Mechanical properties up to 180 days of self compacting and ordinary concretes with rice-husk ash (RHA), from a rice paddy milling industry in Rasht (Iran). Two different replacement percentages of cement by RHA, 10%, and 20%, and two different water/cementicious material ratios (0.40 and 0.35), were used for both of self compacting and normal concrete specimens. The results are compared with those of the self compacting concrete without RHA, with compressive, flexural strength and modulus of elasticity. It is concluded that RHA provides a positive effect on the Mechanical properties at age after 60 days. Base of the result self compacting concrete specimens have higher value than normal concrete specimens in all test except modulus of elasticity. Also specimens with 20% replacement of cement by RHA have the best performance.

Keywords: Self compacting concrete (SCC), Rice husk ash(RHA), Mechanical properties.

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3336 Nonlinear Power Measurement Algorithm of the Input Mix Components of the Noise Signal and Pulse Interference

Authors: Alexey V. Klyuev, Valery P. Samarin, Viktor F. Klyuev, Andrey V. Klyuev

Abstract:

A power measurement algorithm of the input mix components of the noise signal and pulse interference is considered. The algorithm efficiency analysis has been carried out for different interference-to-signal ratio. Algorithm performance features have been explored by numerical experiment results.

Keywords: Noise signal, pulse interference, signal power, spectrum width, detection.

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3335 Power System Contingency Analysis Using Multiagent Systems

Authors: Anant Oonsivilai, Kenedy A. Greyson

Abstract:

The demand of the energy management systems (EMS) set forth by modern power systems requires fast energy management systems. Contingency analysis is among the functions in EMS which is time consuming. In order to handle this limitation, this paper introduces agent based technology in the contingency analysis. The main function of agents is to speed up the performance. Negotiations process in decision making is explained and the issue set forth is the minimization of the operating costs. The IEEE 14 bus system and its line outage have been used in the research and simulation results are presented.

Keywords: Agents, model, negotiation, optimal dispatch, powersystems.

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