فهرست مطالب

International Journal of Engineering
Volume:31 Issue: 2, Feb 2018

  • TRANSACTIONS B: APPLICATIONS
  • تاریخ انتشار: 1396/12/08
  • تعداد عناوین: 22
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  • G. Najafpour Pages 188-195
    A sensitive electrochemical sensor was fabricated for selective detection of nitric oxide (NO) based on electrochemically reduced graphene (ErGO)-polyaniline (PANI)-gold nanoparticles (AuNPs) nanocomposite. It was coated on a gold (Au) electrode through stepwise electrodeposition to form AuNPs-PANI-ErGO/Au electrode. The AuNPs-PANI-rGO nanocomposite was characterized by Field Emission Scanning Electron Microscopy (FESEM) and UV-vis. Electrochemical behavior of modified electrode was analyzed by cyclic voltammetry (CV) and chronoamperometry (CA) techniques. CVs of AuNPs-PANI-ErGO/Au, PANI-ErGO/Au and ErGO/Au electrodes showed that conductivity of AuNPs-PANI-ErGO/Au was higher than others. Nafion was used to improve selectivity of modified electrode. Nafion/AuNPs-PANI-ErGO/Au electrode represented favorable electrochemical and electrocatalytic behavior towards NO oxidation. The resultant electrode exhibited a high sensivity of 0.113 μA/μM over a wide linear range from 0.8 × 10−6 to 86 × 10−6 M with a low detection limit of 2.5 × 10−7 M (S/N=3). In addition, the sensor had excellent stability, as well as reproducibility and selectivity, which makes it possible to detect NO quickly and accurately.
    Keywords: Nitric oxide sensor, Reduced graphene oxide, Gold nanoparticle, Polyaniline, Cyclic voltammetry
  • M. Jalilkhani, A. R. Manafpour Pages 196-203
    Incremental Dynamic Analysis (IDA) procedure is now considered as a robust tool for estimating the seismic sidesway collapse capacity of structures. However, the procedure is time-consuming and requires numerous nonlinear response-history analyses. This paper proposes a simplified Modal Pushover Analysis (MPA) procedure for IDA of RC moment-resisting frames. The proposed method uses the dynamic response of an equivalent single-degree-of-freedom (SDOF) system, characterized by a bilinear relationship between the lateral force (F) and roof-displacement (D). The F-D relationship is determined by the ‘first-mode’ pushover analysis of the structure. Four regular RC moment-resisting frames designed based on the current US building codes are selected and subjected to the proposed method. The analysis results obtained from the original MPA-based IDA method, SPO2IDA and the method proposed by Shafei et al are also presented for comparison. The performance of the proposed method is then evaluated through comparisons with the results obtained from IDAs. The results show that the proposed method is able to efficiently estimate the dynamic capacity of the example buildings for different seismic performance levels. Nonetheless like to MPA-based IDA and SPO2IDA methods less accueate results are obtained by the proposed procedure for 16% and 84% IDA fractiles in most case studies.
    Keywords: sidesway collapse capacity, pushover analysis, IDA method, RC moment-resisting frame
  • M. Feizbahr, K. K. Choong, F. Rostami, M. Shahrokhi Pages 212-219
    The indispensable vital structure in any harbor is a breakwater in order to make available calm water region inshore. Pile breakwater can be employed as a small coastal protection structure where tranquility required is low. This study is concerned with CFD study on the performance of perforated hollow pile to dissipate wave energy and the novelty of this investigation is the role of perforation layout in dissipating energy of water. Pile models under two different incident waves with constant water depth and wave amplitude have been classified into two groups with two different wavelengths, making a total of 10 models which has been simulated numerically by computational flow solver FLOW 3D. The analytical results of simulations show changes in the velocity profiles after piles while dissipation happened in the vicinity of the pile. The result implied the perforated models can perform better than the non-perforated ones and energy dissipation was found much more significant in perforated piles.
    Keywords: breakwater, perforation, hollow piles, Flow 3D, wave modeling, coastal-protection
  • M. Asgari, A. Kheyroddin, H. Naderpour Page 228
    Critical Success Factors (CSFs) are used to support and evaluate the success of a strategic and tactical approach in project implementation in order to increase the probability of success. This system is used by executors in project delivery to achieve improved performance capabilities with limited resources. The present paper aims to identify the impact of CSFs amongst the main elements involved in construction industry of projects in Iran (Owner, Contractor, and Consultant). Therefore, 41 CSFs-related indices based on present research conditions in Iran were selected and classified into five major categories: (1) Financial, (2) Interactive Processes, (3) Human Resources, (4) Contractual Arrangements, and (5) Project Characteristics. To analyze the CSFs of project, the required data were collected by questionnaire based on randomized sampling method by project managers, chief executive officers, and experts of construction industry of Owners, Contractors, and Consultant who have working experience in major projects in Iran. The results indicated that indices related to human resources group from the point of view of Owners and Contractors as well as the indices related to financial and project participants from the point of view of Consultant are the main success priorities in projects. Moreover, the indices of “adequacy of plans and specifications” and “Project manager competency” were elected indices common in previous and present studies. The results of this study will provide the project managers with practical solutions in order to benefit the findings as guidelines for CSFs formation according to Construction projects in Iran.
    Keywords: Project Success, Critical Success Factor, Construction Project, Client, Contractor, Consultant, IRAN
  • S. J. Seyyedyazdi, H. Hassanpour Page 241
    Super-resolution (SR) is a technique that produces a high resolution (HR) image via employing a number of low resolution (LR) images from the same scene. One of the degradations that attenuates performance of the SR is the blurriness of the input LR images. In many previous works in the SR, the blurriness of the LR images is assumed to be due to the integral effect of the image sensor of the image acquisition device, while in practice, there are some other factors that blur the LR images, such as diffraction, motion of the object and/or acquisition device, atmospheric blurring and defocus blur. To apply the super-resolution process accurately, we need to know the degradation model applied on HR image leading to LR ones. In this paper, we aim to use the LR images blurriness to find the blurring kernel applied on the HR image. Hence we setup a simulation experiment in which the blurring kernel is limited to be one of the predetermined kernels. In the experiment, the blurriness of the LR images is supposed to be unknown, and is estimated using a blur kernel estimation method. Then the estimated blur kernels of the LR images are fed to an artificial neural network (ANN) to determine the blur kernels associated with the HR image. Experiment results show the use of determined blur kernels improves the quality of output HR image.
    Keywords: Super-resolution, Blur kernel, Blur Kernel Estimation, Neural Network
  • A. Shukla, S. Kumar, H. Singh Page 242
    Numerous works has been done for load balancing of web servers in grid environment. Reason behinds popularity of grid environment is to allow accessing distributed resources which are located at remote locations. For effective utilization, load must be balanced among all resources. Importance of load balancing is discussed by distinguishing the system between without load balancing and with load balancing. Various performance metrics that need to be considered for designing an efficient load balancing algorithm are also described. Intensive review of literature of different load balancing approaches for web servers have been carried out and presented in this paper. On the basis of literature survey, a new dynamic load balancing mechanism is proposed for optimizing waiting time and cost.
    Keywords: load balancing, load migration, QoS, delay, queueing, cost optimization, web server
  • A. Salarpour, H. Khotanlou Page 250
    Multivariate time series (MTS) data are ubiquitous in science and daily life, and how to measure their similarity is a core part of MTS analyzing process. Many of the research efforts in this context have focused on proposing novel similarity measures for the underlying data. However, with the countless techniques to estimate similarity between MTS, this field suffers from a lack of comparative studies using quantitative and large scale evaluations. In order to provide a comprehensive validation, an extensive evaluation of similarity measures for MTS clustering were conducted. The 14 well-known similarity measures with their variants and testing their effectiveness on 23 MTS datasets coming from a wide variety of application domains were re-implemented. In this paper, an overview of these different techniques is given and the empirical comparison regarding their effectiveness based on agglomerative clustering task is presented. Furthermore, the statistical significance tests were used to derive meaningful conclusions. It has been found that all of similarity measures are equivalent, in terms of clustering F-measure, and there is no significant difference between similarity measures based on our datasets. The results provide a comparative background between similarity measures to find the most proper method in terms of performance and computation time in this field.
    Keywords: Multivariate time series, similarity measures, clustering, evaluation
  • S. Valiollahi, G. Ardeshir Pages 270-255
    A simple general-purpose I-V model for all operating modes of deep-submicron MOSFETs is presented. Considering the most dominant short channel effects with simple equations including few extra parameters, a reasonable trade-off between simplicity and accuracy is established. To further improve the accuracy, model parameters are optimized over various channel widths and full range of operating voltages using a heuristic optimization algorithm. The obtained results demonstrate only 1.28% and 0.97% average error in IBM 0.13um CMOS technology for NMOS and PMOS, respectively, comparing with the accurate physically-based BSIM3 model. Furthermore, the tolerance of the model accuracy against parameters variation is investigated.
    Keywords: deep submicron, heuristic optimization, MOSFET modeling, nth-power law model, short channel effects, sub-threshold current
  • V. Ranga, L. Sumi Page 278
    Traffic congestion worldwide has led to loss of human lives due to failure in transporting accident victims, critical patients, medical equipment and medicines on time. With the unending growth in vehicular traffic everywhere, Internet of Things (IOT) and Vehicular Ad Hoc Network (VANET) have embarked as a promising platform for an Intelligent Traffic Management System (ITMS). Many researches have been done to clear emergency vehicles, but they have not only failed to meet the target travel time of an emergency vehicle, but also failed to provide solutions, when traffic signals are hacked. This paper proposes an intelligent traffic management system for a Smart City that is inspired by the concepts of IoT and VANET. In the proposed solution, emergency vehicles are scheduled to prioritize them for a smooth passage through the traffics based on incident type. It not only navigates ambulances in finding the shortest possible paths till their destination, but also presents a solution to detect and respond to hacking of traffic signals. To show the superiority of our proposed system, a simulated environment modeling actual roads and vehicle movements has been demonstrated using CupCarbon simulator. Comparative results exhibits superior performance of our proposed system over the other recently proposed ITS for emergency vehicles, in terms of both congestion avoidance, transmission delay, travel time and respond to hacking.
    Keywords: Internet of Things (IoT), Vehicular Ad-hoc network (VANET), Intelligent Traffic Management System (ITMS), Emergency vehicles, Road Side Units (RSUs), Smart Cities
  • M. Rasouli Khatir, H. Ghoreishy, S. A. Gholamian Page 284
    This paper proposes the virtual flux based direct power control for Vienna rectifier. No need for the input voltage sensors, the current regulation loop and PWM voltage modulation block along with the active and reactive power decoupling are some of the salient advantages of this method that make it suitable for controlling the conventional active rectifiers. However, due to the three-level nature of the Vienna configuration, balancing the output capacitors voltages is inevitable leading to a modified virtual flux based technique. Applying this modification, a separate switching table has been jammed into the proposed technique in order to control the capacitors voltages. Simulation results show the superiority of the virtual flux technique over the conventional Vienna control techniques from point of the mentioned advantages.
    Keywords: Capacitor voltage balancing, Direct power control, Vienna rectifier, Virtual flux
  • R. K. Godi, B. K Page 292
    Memories are most important building blocks in many digital systems. As the Integrated Circuits requirements are growing, the test circuitry must grow as well. There is a need for more efficient test techniques with low power and high speed. Many Memory Built in Self-Test techniques have been proposed to test memories. Compared with combinational and sequential circuits memory testing utilizes more amount of power. Test circuitry is intensively used for memory testing. This may cause excessive power consumption during memory testing. Sophisticated and efficient techniques with less overhead on power must be needed. Regarding memories, power consumption is very much high during testing when compared with normal functional mode. March test algorithms are popular testing techniques used for memory testing. Power consumption during testing can be reduced by reducing the switching activity in test circuitry. A new test technique is proposed in this paper to reduce power consumption in test mode by reducing the switching activity in Built in Self-Test circuitry. Address sequencing in the address decoder is changed in such a way that it reduces switching activity.
    Keywords: Built in Self-Test (BIST), Low Power Test, March Test Algorithm, Memory Built in Self-Test (MBIST), Memory Testing
  • A. Moradi, Y. Alinejad-Beromi, M. Parsa, M. Mohammadi Page 299
    In this article, a multi-objective planning is demonstrated for reactive power compensation in radial distribution networks with wind generation via unified power quality conditioner (UPQC). UPQC model, based on phase angle control (PAC), is used. In presented method, optimal locating of UPQC-PAC is done by simultaneous minimizing of objective functions such as: grid power loss, percentage of nodes with voltage drop, and capacity of UPQC. The proposed model is a complicated non-linear optimization problem. For introducing group of non-dominated solutions, a multi-objective grey wolf optimizer (MOGWO) algorithm based on probabilistic load flow is used, then a fuzzy sets theory is used to achieve the best response. In order to evaluate reliability of mentioned approach, simulation is done on 33-bus distribution network.
    Keywords: fuzzy sets theory, multi-objective grey wolf optimizer (MOGWO), radial distribution network, reactive power compensation, unified power quality conditioner (UPQC), wind generation
  • S. Gol, G. Ardeshir, M. Zahabi, A. Ale Ahmad Page 307
    The commutation process causes current ripple to be generated in the drive system of brushless DC (BLDC) motor. This, in turn, leads to output torque ripple. Mechanical vibration and acoustic noise are its influences which are undesirable phenomenon in some applications. A new method is presented in this paper which reduces torque ripple and commutation period in the entire range of motor speed. This method is designed and implemented based on two-segment pulse-width modulation (PWM) and DC-link voltage doubling during commutation. Based on the presented theory and given the influence of DC-link voltage on ripple magnitude, some experiments are carried out in which simultaneous association of the above mentioned factors in reducing current ripple and commutation time in the entire speed range of rotor has been proved. The experimental results show that the current ripple magnitude in high speed range is almost 20 times less than conventional method based on H-PWM_L-ON technique.
    Keywords: Brushless DC Motors, motor drive system, commutation torque ripple, pulse-width modulation, DC-link voltage
  • A. Gharehkhani, E. Abbaspour-Sani Page 315
    In this paper a new design for 6 bit DMTL phase shifter with only 32 MEMS switches is proposed. The reduction in number of switches in ordinary 6 bit phase shifter from 63 to 32 is due to combination of one 5.625 degree for least significant bit and 11.25 degree for the rest of the switches. Decreasing the number of the switches reduces the die-size as well as loss of the CPW line. Analytical study and simulation with HFSS and COMSOL software is carried out for the proposed structure. Maximum return loss of phase shifter is -10.5 dB and mean RMS phase error is 1.4o . Although two different structural switches are used but the pull in voltages are identical. The total structure size is 1.5*18.5 mm2 , and surface micromachining process is proposed for the phase shifter.
    Keywords: MEMS, shunt capacitive switch, DMT phase shifter, actuation voltage
  • P. Kumar, S. K. Chaudhary Page 322
    In this paper, a new comparative approach has been proposed for reliable controller design. Scientists and engineers are often confronted with the analysis, design, and synthesis of real-life problems. The first step in such studies is the development of a 'mathematical model' which can be considered as a substitute for the real problem. The mathematical model is used here as a plant. Fractional integrals and derivatives have found wide application in the control of dynamical systems when the controlled system and the controller are described by a set of fractional order differential equations. Here the stability of fractional order system is checked at the different level and it is found that the stability region is large in the complex plane. This large stability region provides the more flexibility for system implementation in the control engineering. Generally, an analytically or experimentally approaches are used for designing the controller. If a fractional order controller design approach used for a given plant then the controlled parameter gives the better result.
    Keywords: Fractional Order Controller, Fractional Order Calculus, Stability, Performance Analysis, MATLAB, Function Under Class, Ziegler-Nichols Method
  • R. Saleh, H. Farsi Page 331
    In this paper, a proposed ensemble classification for fully polarimetric synthetic aperture radar (PolSAR) data using a global-local classification approach is presented. In the first step, to perform the global classification, the training feature space is divided into a specified number of clusters. In the next step to carry out the local classification over each of these clusters, which contains elements of several classes, a base classifier is trained. Thus, an ensemble of classifiers has been formed which each of them acts professionally in a part of the feature space. To achieve more diversity, the data set is independently partitioned into variable number of clusters by classifier and K-means algorithm. To combine outputs of different arrangements, majority voting, Naïve Bayes and a heuristic combination rule with taking into account the classification accuracy and reliability (which in PolSAR classification less attention has been paid to it) as objective functions, are used. The experimental results over two PolSAR images prove effectiveness of the proposed algorithms in comparison to the baseline methods.
    Keywords: PolSAR data, Ensemble classification, Global-local classification, H, α classifier, Clustering, Multi objective optimization, Reliability
  • R. Sadeghi Rad, N. Nahavandi, Ali Hosseinzadeh, S.H. Zegordi Page 346
    In this paper, a mathematical programming model is presented for integrated problem of closed loop supply chain network design and supplier selection. The suppliers propose discount policy based on purchase amount and loyalty of buyers which are both taken from the elements of RFM (Recency, Frequency and Monetary) technique. The main objective of this paper which is formulated by a mixed-integer programming model is to minimize the total cost through determining location of facilities, production plan, inventory levels, flows between facilities, transportation type, purchasing amount and selecting best supplier based on a beneficial relationship. Sensitivity analysis is carried out to validate the model and examine the effects of considering discount according to purchase amount and loyalty on the supply chains costs and decisions. Computational results show the effectiveness and usefulness of the model.
    Keywords: Supplier selection, Closed-loop Supply Chain Network, Loyalty, Discount
  • M. Maleki Rastaghi, F. Barzinpour Pishvaee Page 365
    This paper presents a multi-objective and multi-service location-allocation model with capacity planning to design a healthcare facilities network through considering a referral system. Therefore, a mixed integer nonlinear programming (MINLP) model containing two objective functions is proposed. The first objective function is relates to minimization of total opening cost, minimization of total set up cost of different types of services and minimization of total traveled distance by patients to reach each facility. The second objective function in the model aims to minimize maximum normalized workload between opened facilities in each level. Specifying location of different facilities, allocating patients zones to family physician centers, establishing an optimal flow between different levels in the network and determining the optimal capacity for different specialized and super specialty facilities are main strategic and tactical decisions in the proposed model. In order to solve the proposed model and arrive at Pareto solutions, a primary nonlinear integer program is transformed to linearize the model and then, an augmented -constraint method is applied on numerical examples. Finally, the results obtained by sensitivity analysis on the main parameters are reported to show that the presented model can be used to design a multi-level healthcare facility network.
    Keywords: Healthcare network design, Location-allocation, Referral system, Capacity planning, Family physician centers, Augmented ε-constraint
  • A. Mohsenzadeh Ledari, A. Arshadi Khamseh Pages 374-382
    In this paper, a three-echelon supply chain , including two producers, distributor and retailer who produce products in different brands have been considered. Any manufacturer, has a separate channel and the exclusive retailer offers their products, which have been prepared from the distributor (exclusive market) with discount or other manufacturer. In this paper pricing decisions on substitute products with different brands on the market has been developed in exclusive and non-exclusive markets for loyal and indifferent customers. The demand for products depend on the distance from brand and ideal product prices. In this model retailer buys product from distributor, but as in the real world ,we face with disruption risk in each channel between the retailer and distributor, only some percentage of orders will be met by distributor and the remains will be done as special orders by manufacturer. The aim of this paper is maximizing the profitability of the entire supply chain, so that optimal selling price to be determined in every channel. Finally, numerical examples and sensitivity analysis have been done on them .
    Keywords: Pricing, Three echelon supply chain, Game theory, Disruption risk, Special order, Brand value, substitute product
  • E. Maleki, G. H. Farrahi Page 382
    Shot peening (SP), as one of the severe plastic deformation (SPD) methods is employed for surface modification of the engineering components by improving the metallurgical and mechanical properties. Furthermore artificial neural network (ANN) has been widely used in different science and engineering problems for predicting and optimizing in the last decade. In the present study, effects of conventional shot peening (CSP) and severe shot peening (SSP) on properties of AISI 1060 high carbon steel were modelled and compared via ANN. In order to networks training, the back propagation (BP) error algorithm is developed and data of experimental test results are employed. Experimental data illustrates that SSP has superior influence than CSP to improve the properties. Different networks with different structures are trained with try and error process and the one which had the best performance is selected for modeling. Testing of the ANN is carried out using experimental data which they were not used during networks training. Distance from the surface (depth), SP intensity and coverage are regarded as inputs and microhardness, residual stress and grain size are gathered as outputs of the networks. Comparison of predicted and experimental values indicates that the networks are tuned finely and adjusted carefully; therefore, they have good agreement.
    Keywords: artificial neural network, severe shot peening, residual stress, coverage, Almen intensity