Search results for: Variable Speed Drive

Authors: Shanar Askar, Shahzad Memon, LachhmanDas, MSKalhoro

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Wimax (Worldwide Interoperability for Microwave Access) is a promising technology which can offer high speed data, voice and video service to the customer end, which is presently, dominated by the cable and digital subscriber line (DSL) technologies. The performance assessment of Wimax systems is dealt with. The biggest advantage of Broadband wireless application (BWA) over its wired competitors is its increased capacity and ease of deployment. The aims of this paper are to model and simulate the fixed OFDM IEEE 802.16d physical layer under variant combinations of digital modulation (BPSK, QPSK, and 16-QAM) over diverse combination of fading channels (AWGN, SUIs). Stanford University Interim (SUI) Channel serial was proposed to simulate the fixed broadband wireless access channel environments where IEEE 802.16d is to be deployed. It has six channel models that are grouped into three categories according to three typical different outdoor Terrains, in order to give a comprehensive effect of fading channels on the overall performance of the system.

Keywords: WIMAX, OFDM, Additive White Gaussian Noise, Fading Channel, SUI, Doppler Effect.

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Authors: Elżbieta Antczak

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Cities offer important opportunities for economic development and for expanding access to basic services, including health care and education, for large numbers of people. Moreover, green areas (as an integral part of sustainable urban development) present a major opportunity for improving urban environments, quality of lives and livelihoods. This paper examines, using spatial concentration and spatial taxonomic measures, regional diversification of greenery in the cities of Poland. The analysis includes location quotients, Lorenz curve, Locational Gini Index, and the synthetic index of greenery and spatial statistics tools: (1) To verify the occurrence of strong concentration or dispersion of the phenomenon in time and space depending on the variable category, and, (2) To study if the level of greenery depends on the spatial autocorrelation. The data includes the greatest Polish cities, categories of the urban greenery (parks, lawns, street greenery, and green areas on housing estates, cemeteries, and forests) and the time span 2004-2015. According to the obtained estimations, most of cites in Poland are already taking measures to become greener. However, in the country there are still many barriers to well-balanced urban greenery development (e.g. uncontrolled urban sprawl, poor management as well as lack of spatial urban planning systems).

Keywords: Greenery, urban areas, regional spatial diversification and concentration, spatial taxonomic measure.

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Authors: Abdenour Bounsiar, Edith Grall, Pierre Beauseroy

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In this paper we are interested in classification problems with a performance constraint on error probability. In such problems if the constraint cannot be satisfied, then a rejection option is introduced. For binary labelled classification, a number of SVM based methods with rejection option have been proposed over the past few years. All of these methods use two thresholds on the SVM output. However, in previous works, we have shown on synthetic data that using thresholds on the output of the optimal SVM may lead to poor results for classification tasks with performance constraint. In this paper a new method for supervised classification with rejection option is proposed. It consists in two different classifiers jointly optimized to minimize the rejection probability subject to a given constraint on error rate. This method uses a new kernel based linear learning machine that we have recently presented. This learning machine is characterized by its simplicity and high training speed which makes the simultaneous optimization of the two classifiers computationally reasonable. The proposed classification method with rejection option is compared to a SVM based rejection method proposed in recent literature. Experiments show the superiority of the proposed method.

Keywords: rejection, Chow's rule, error-reject tradeoff, SupportVector Machine.

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Authors: A. Zahiri, A. A. Dehghani

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Although many researchers have studied the flow hydraulics in compound channels, there are still many complicated problems in determination of their flow rating curves. Many different methods have been presented for these channels but extending them for all types of compound channels with different geometrical and hydraulic conditions is certainly difficult. In this study, by aid of nearly 400 laboratory and field data sets of geometry and flow rating curves from 30 different straight compound sections and using artificial neural networks (ANNs), flow discharge in compound channels was estimated. 13 dimensionless input variables including relative depth, relative roughness, relative width, aspect ratio, bed slope, main channel side slopes, flood plains side slopes and berm inclination and one output variable (flow discharge), have been used in ANNs. Comparison of ANNs model and traditional method (divided channel method-DCM) shows high accuracy of ANNs model results. The results of Sensitivity analysis showed that the relative depth with 47.6 percent contribution, is the most effective input parameter for flow discharge prediction. Relative width and relative roughness have 19.3 and 12.2 percent of importance, respectively. On the other hand, shape parameter, main channel and flood plains side slopes with 2.1, 3.8 and 3.8 percent of contribution, have the least importance.

Keywords: ANN model, compound channels, divided channel method (DCM), flow rating curve

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Authors: Zundong Zhang, Limin Jia, Zhao Tian, Yanfang Yang

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Travel Demands influence micro-level traffic behavior, furthermore traffic states. In order to evaluate the effect of travel demands on traffic states, this paper introduces the Demand- Motivation-Behaviors (DMB) micro traffic behavior analysis model which denotes that vehicles behaviors are determines by motivations that relies on traffic demands from the perspective of behavior science. For vehicles, there are two kinds of travel demands: reaching travel destinations from orientations and meeting expectations of travel speed. To satisfy travel demands, the micro traffic behaviors are delivered such as car following behavior, optional and mandatory lane changing behaviors. Especially, mandatory lane changing behaviors depending on travel demands take strong impact on traffic states. In this paper, we define the DMB-based cellular automate traffic simulation model to evaluate the effect of travel demands on traffic states under the different δ values that reflect the ratio of mandatory lane-change vehicles.

Keywords: Demand-Motivation-Behavior, Mandatory Lane Changing, Traffic Cellular Automata.

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Authors: Abdallah S. Abdallah, A. Lynn Abbott, Mohamad Abou El-Nasr

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This paper presents a new technique for detection of human faces within color images. The approach relies on image segmentation based on skin color, features extracted from the two-dimensional discrete cosine transform (DCT), and self-organizing maps (SOM). After candidate skin regions are extracted, feature vectors are constructed using DCT coefficients computed from those regions. A supervised SOM training session is used to cluster feature vectors into groups, and to assign “face" or “non-face" labels to those clusters. Evaluation was performed using a new image database of 286 images, containing 1027 faces. After training, our detection technique achieved a detection rate of 77.94% during subsequent tests, with a false positive rate of 5.14%. To our knowledge, the proposed technique is the first to combine DCT-based feature extraction with a SOM for detecting human faces within color images. It is also one of a few attempts to combine a feature-invariant approach, such as color-based skin segmentation, together with appearance-based face detection. The main advantage of the new technique is its low computational requirements, in terms of both processing speed and memory utilization.

Keywords: Face detection, skin color segmentation, self-organizingmap.

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Authors: Sidhartha Panda, N. P. Padhy, R.N.Patel

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In this paper, genetic algorithm (GA) opmization technique is applied to design Flexible AC Transmission System (FACTS)-based damping controllers. Two types of controller structures, namely a proportional-integral (PI) and a lead-lag (LL) are considered. The design problem of the proposed controllers is formulated as an optimization problem and GA is employed to search for optimal controller parameters. By minimizing the time-domain based objective function, in which the deviation in the oscillatory rotor speed of the generator is involved; stability performance of the system is improved. The proposed controllers are tested on a weakly connected power system subjected to different disturbances. The non-linear simulation results are presented to show the effectiveness of the proposed controller and their ability to provide efficient damping of low frequency oscillations. It is also observed that the proposed SSSC-based controllers improve greatly the voltage profile of the system under severe disturbances. Further, the dynamic performances of both the PI and LL structured FACTS-controller are analyzed at different loading conditions and under various disturbance condition as well as under unbalanced fault conditions..

Keywords: Genetic algorithm, proportional-integral controller, lead-lag controller, power system stability, FACTS.

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Authors: I.Banerjee, A.K.Mahendra, T.K.Bera, B.G.Chandresh

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The scroll pump belongs to the category of positive displacement pump can be used for continuous pumping of gases at low pressure apart from general vacuum application. The shape of volume occupied by the gas moves and deforms continuously as the spiral orbits. To capture flow features in such domain where mesh deformation varies with time in a complicated manner, mesh less solver was found to be very useful. Least Squares Kinetic Upwind Method (LSKUM) is a kinetic theory based mesh free Euler solver working on arbitrary distribution of points. Here upwind is enforced in molecular level based on kinetic flux vector splitting scheme (KFVS). In the present study we extended the LSKUM to moving node viscous flow application. This new code LSKUM-NS-MN for moving node viscous flow is validated for standard airfoil pitching test case. Simulation performed for flow through scroll pump using LSKUM-NS-MN code agrees well with the experimental pumping speed data.

Keywords: Least Squares, Moving node, Pitching, Spirals.

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Authors: Santanu Santra, Utpal Roy

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Quantum-dot Cellular Automata (QCA) is one of the most substitute emerging nanotechnologies for electronic circuits, because of lower power consumption, higher speed and smaller size in comparison with CMOS technology. The basic devices, a Quantum-dot cell can be used to implement logic gates and wires. As it is the fundamental building block on nanotechnology circuits. By applying XOR gate the hardware requirements for a QCA circuit can be decrease and circuits can be simpler in terms of level, delay and cell count. This article present a modest approach for implementing novel optimized XOR gate, which can be applied to design many variants of complex QCA circuits. Proposed XOR gate is simple in structure and powerful in terms of implementing any digital circuits. In order to verify the functionality of the proposed design some complex implementation of parity generator and parity checker circuits are proposed and simulating by QCA Designer tool and compare with some most recent design. Simulation results and physical relations confirm its usefulness in implementing every digital circuit.

Keywords: Clock, CMOS technology, Logic gates, QCA Designer, Quantum-dot Cellular Automata (QCA).

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Authors: Samir Khrais, Adel Mahammod Hassan , Amro Gazawi

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The aim of this research is to evaluate surface roughness and develop a multiple regression model for surface roughness as a function of cutting parameters during the turning of flame hardened medium carbon steel with TiN-Al2O3-TiCN coated inserts. An experimental plan of work and signal-to-noise ratio (S/N) were used to relate the influence of turning parameters to the workpiece surface finish utilizing Taguchi methodology. The effects of turning parameters were studied by using the analysis of variance (ANOVA) method. Evaluated parameters were feed, cutting speed, and depth of cut. It was found that the most significant interaction among the considered turning parameters was between depth of cut and feed. The average surface roughness (Ra) resulted by TiN-Al2O3- TiCN coated inserts was about 2.44 μm and minimum value was 0.74 μm. In addition, the regression model was able to predict values for surface roughness in comparison with experimental values within reasonable limit.

Keywords: Medium carbon steel, Prediction, Surface roughness, Taguchi method

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Authors: T. H. Young, Y. S. Ciou

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The free and forced in-plane vibrations of axially moving plates are investigated in this work. The plate possesses an internal damping of which the constitutive relation obeys the Kelvin-Voigt model, and the excitations are arbitrarily distributed on two opposite edges. First, the equations of motion and the boundary conditions of the axially moving plate are derived. Then, the extended Ritz method is used to obtain discretized system equations. Finally, numerical results for the natural frequencies and the mode shapes of the in-plane vibration and the in-plane response of the moving plate subjected to arbitrary edge excitations are presented. It is observed that the symmetry class of the mode shapes of the in-plane vibration disperses gradually as the moving speed gets higher, and the u- and v-components of the mode shapes belong to different symmetry class. In addition, large response amplitudes having shapes similar to the mode shapes of the plate can be excited by the edge excitations at the resonant frequencies and with the same symmetry class of distribution as the u-components.

Keywords: Arbitrary edge excitations, axially moving plates, in-plane vibration, extended Ritz method.

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Authors: Abed Sami Qawasme, Sameer Khader

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This paper describes the effects of photovoltaic voltage changes on Multi-level inverter (MLI) due to solar irradiation variations, and methods to overcome these changes. The irradiation variation affects the generated voltage, which in turn varies the switching angles required to turn-on the inverter power switches in order to obtain minimum harmonic content in the output voltage profile. Genetic Algorithm (GA) is used to solve harmonics elimination equations of eleven level inverters with equal and non-equal dc sources. After that artificial neural network (ANN) algorithm is proposed to generate appropriate set of switching angles for MLI at any level of input dc sources voltage causing minimization of the total harmonic distortion (THD) to an acceptable limit. MATLAB/Simulink platform is used as a simulation tool and Fast Fourier Transform (FFT) analyses are carried out for output voltage profile to verify the reliability and accuracy of the applied technique for controlling the MLI harmonic distortion. According to the simulation results, the obtained THD for equal dc source is 9.38%, while for variable or unequal dc sources it varies between 10.26% and 12.93% as the input dc voltage varies between 4.47V nd 11.43V respectively. The proposed ANN algorithm provides satisfied simulation results that match with results obtained by alternative algorithms.

Keywords: Multi level inverter, genetic algorithm, artificial neural network, total harmonic distortion.

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Authors: Mohammad Saleh Vahdatpour, Yanqing Zhang

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Understanding the neural mechanisms underlying motion detection in the human visual system has long been a fascinating challenge in neuroscience and artificial intelligence. This paper presents a spiking neural network model inspired by the processing of motion information in the primate visual system, particularly focusing on the Middle Temporal (MT) area. In our study, we propose a multi-layer spiking neural network model to perform motion detection tasks, leveraging the idea that synaptic delays in neuronal communication are pivotal in motion perception. Synaptic delay, determined by factors like axon length and myelin insulation, affects the temporal order of input spikes, thereby encoding motion direction and speed. Overall, our spiking neural network model demonstrates the feasibility of capturing motion detection principles observed in the primate visual system. The combination of synaptic delays, learning mechanisms, and shared weights and delays in SMD provides a promising framework for motion perception in artificial systems, with potential applications in computer vision and robotics.

Keywords: Neural networks, motion detection, signature detection, convolutional neural network.

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Authors: Giuseppe Spampinato, Salvatore Curti, Ivana Guarneri, Arcangelo Bruna

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This document describes an advanced system and methodology for Cross Traffic Alert (CTA), able to detect vehicles that move into the vehicle driving path from the left or right side. The camera is supposed to be not only on a vehicle still, e.g. at a traffic light or at an intersection, but also moving slowly, e.g. in a car park. In all of the aforementioned conditions, a driver’s short loss of concentration or distraction can easily lead to a serious accident. A valid support to avoid these kinds of car crashes is represented by the proposed system. It is an extension of our previous work, related to a clustering system, which only works on fixed cameras. Just a vanish point calculation and simple optical flow filtering, to eliminate motion vectors due to the car relative movement, is performed to let the system achieve high performances with different scenarios, cameras and resolutions. The proposed system just uses as input the optical flow, which is hardware implemented in the proposed platform and since the elaboration of the whole system is really speed and power consumption, it is inserted directly in the camera framework, allowing to execute all the processing in real-time.

Keywords: Clustering, cross traffic alert, optical flow, real time, vanishing point.

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Authors: B. Murali Krishna, J. M. Mallikarjuna

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This paper deals with the experimental investigations of the in-cylinder tumble flows in an unfired internal combustion engine with a flat piston at the engine speeds ranging from 400 to 1000 rev/min., and also with the dome and dome-cavity pistons at an engine speed of 1000 rev/min., using particle image velocimetry. From the two-dimensional in-cylinder flow measurements, tumble flow analysis is carried out in the combustion space on a vertical plane passing through cylinder axis. To analyze the tumble flows, ensemble average velocity vectors are used and to characterize it, tumble ratio is estimated. From the results, generally, we have found that tumble ratio varies mainly with crank angle position. Also, at the end of compression stroke, average turbulent kinetic energy is more at higher engine speeds. We have also found that, at 330 crank angle position, flat piston shows an improvement of about 85 and 23% in tumble ratio, and about 24 and 2.5% in average turbulent kinetic energy compared to dome and dome-cavity pistons respectively

Keywords: In-cylinder flow, Dome piston, Cavity, Tumble, PIV

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Authors: Mansi Jhamb, R. K. Sharma, A. K. Gupta

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The distribution of a single global clock across a chip has become the major design bottleneck for high performance VLSI systems owing to the power dissipation, process variability and multicycle cross-chip signaling. A Network-on-Chip (NoC) architecture partitioned into several synchronous blocks has become a promising approach for attaining fine-grain power management at the system level. In a NoC architecture the communication between the blocks is handled asynchronously. To interface these blocks on a chip operating at different frequencies, an asynchronous FIFO interface is inevitable. However, these asynchronous FIFOs are not required if adjacent blocks belong to the same clock domain. In this paper, we have designed and analyzed a 16-bit asynchronous micropipelined FIFO of depth four, with the awareness of place and route on an FPGA device. We have used a commercially available Spartan 3 device and designed a high speed implementation of the asynchronous 4-phase micropipeline. The asynchronous FIFO implemented on the FPGA device shows 76 Mb/s throughput and a handshake cycle of 109 ns for write and 101.3 ns for read at the simulation under the worst case operating conditions (voltage = 0.95V) on a working chip at the room temperature.

Keywords: Asynchronous, FIFO, FPGA, GALS, Network-on- Chip (NoC), VHDL.

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Authors: Surinder Deswal, Mahesh Pal

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An Artificial Neural Network based modeling technique has been used to study the influence of different combinations of meteorological parameters on evaporation from a reservoir. The data set used is taken from an earlier reported study. Several input combination were tried so as to find out the importance of different input parameters in predicting the evaporation. The prediction accuracy of Artificial Neural Network has also been compared with the accuracy of linear regression for predicting evaporation. The comparison demonstrated superior performance of Artificial Neural Network over linear regression approach. The findings of the study also revealed the requirement of all input parameters considered together, instead of individual parameters taken one at a time as reported in earlier studies, in predicting the evaporation. The highest correlation coefficient (0.960) along with lowest root mean square error (0.865) was obtained with the input combination of air temperature, wind speed, sunshine hours and mean relative humidity. A graph between the actual and predicted values of evaporation suggests that most of the values lie within a scatter of ±15% with all input parameters. The findings of this study suggest the usefulness of ANN technique in predicting the evaporation losses from reservoirs.

Keywords: Artificial neural network, evaporation losses, multiple linear regression, modeling.

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Authors: M.E.Karbaschi, R.Goudarzizadeh, N.Hedayat

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Cylindrical concrete reservoirs are appropriate choice for storing liquids as water, oil and etc. By using of the pre-cast concrete reservoirs instead of the in-situ constructed reservoirs, the speed and precision of the construction would considerably increase. In this construction method, wall and roof panels would make in factory with high quality materials and precise controlling. Then, pre-cast wall and roof panels would carry out to the construction site for assembling. This method has a few faults such as: the existing weeks in connection of wall panels together and wall panels to foundation. Therefore, these have to be resisted under applied loads such as seismic load. One of the innovative methods which was successfully applied for seismic retrofitting of numerous pre-cast cylindrical water reservoirs in New Zealand, using of the high tensile cables around the reservoirs and post-tensioning them. In this paper, analytical modeling of wall and roof panels and post-tensioned cables are carried out with finite element method and the effect of height to diameter ratio, post-tensioning force value, liquid level in reservoir, installing position of tendons on seismic response of reservoirs are investigated.

Keywords: Seismic Retrofit, Pre-Cast, Concrete Reservoir, Post-Tensioning.

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Authors: War War Myint

Abstract:

Geometric design is an important part of planning process design for physical highway to fill up basic function of roads, to give good traffic service. It is found that most of the road safety problems occur at the horizontal curves and complex-compound curves. In this paper, review on Sagarinn-Myinsain Portion of Nay Pyi Taw - Mandalay highway has been conducted in aspect of geometric design induced road safety condition. Horizontal alignment of geometric features and curve details are reviewed based on (AASHTO) standard and revised by Autodesk Land Desktop Software. Moreover, 85th Percentile Operation Speeds (V85) with driver confidence on horizontal curves is evaluated in order to obtain the range of highway safety factor (FS). The length of the selected highway portion is 13.65 miles and 8 lanes. The results of this study can be used to investigate the possible hazardous locations in advance and to revise how design radius and super elevation should be for better road safety performance for the selected portion. Moreover, the relationship between highway safety and highway geometry characteristics can also be known.

Keywords: Geometric design; horizontal alignment; superelevation; 85th percentile operation speed (V85), safety factor (FS).

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Authors: Krasimir I. Ivanov, Elitsa N. Kolentsova, Dimitar Y. Dimitrov, Petya Ts. Petrova, Tatyana T. Tabakova

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This work studies the effect of chemical composition on the activity and selectivity of γ–alumina supported CuO/ MnO2/Cr2O3 catalysts toward deep oxidation of CO, dimethyl ether (DME) and methanol. The catalysts were prepared by impregnation of the support with an aqueous solution of copper nitrate, manganese nitrate and CrO3 under different conditions. Thermal, XRD and TPR analysis were performed. The catalytic measurements of single compounds oxidation were carried out on continuous flow equipment with a four-channel isothermal stainless steel reactor. Flow-line equipment with an adiabatic reactor for simultaneous oxidation of all compounds under the conditions that mimic closely the industrial ones was used. The reactant and product gases were analyzed by means of on-line gas chromatographs. On the basis of XRD analysis it can be concluded that the active component of the mixed Cu-Mn-Cr/γ–alumina catalysts consists of at least six compounds – CuO, Cr2O3, MnO2, Cu1.5Mn1.5O4, Cu1.5Cr1.5O4 and CuCr2O4, depending on the Cu/Mn/Cr molar ratio. Chemical composition strongly influences catalytic properties, this influence being quite variable with regards to the different processes. The rate of CO oxidation rapidly decrease with increasing of chromium content in the active component while for the DME was observed the reverse trend. It was concluded that the best compromise are the catalysts with Cu/(Mn + Cr) molar ratio 1:5 and Mn/Cr molar ratio from 1:3 to 1:4.

Keywords: Copper-manganese-chromium oxide catalysts, CO, deep oxidation, volatile organic compounds.

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Authors: Bin Wang, Hengyu Ji, Zhifeng Ye

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Fuel Metering Unit (FMU) in fuel system of an aeroengine sometimes has direct influence on the engine performance, which is neglected for the sake of easy access to mathematical model of the engine in most cases. In order to verify the influence of FMU on an engine model, this paper presents a co-simulation of a stepping motor driven FMU (digital FMU) in a turboshaft aeroengine, using AMESim and MATLAB to obtain the steady and dynamic characteristics of the FMU. For this method, mechanical and hydraulic section of the unit is modeled through AMESim, while the stepping motor is mathematically modeled through MATLAB/Simulink. Combining these two sub-models yields an AMESim/MATLAB co-model of the FMU. A simplified component level model for the turboshaft engine is established and connected with the FMU model. Simulation results on the full model show that the engine model considering FMU characteristics describes the engine more precisely especially in its transition state. An FMU dynamics will cut down the rotation speed of the high pressure shaft and the inlet pressure of the combustor during the step response. The work in this paper reveals the impact of FMU on engine operation characteristics and provides a reference to an engine model for ground tests.

Keywords: Fuel metering unit, stepping motor, AMESim/MATLAB, full digital simulation.

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Authors: K. Atashgar

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When an assignable cause(s) manifests itself to a multivariate process and the process shifts to an out-of-control condition, a root-cause analysis should be initiated by quality engineers to identify and eliminate the assignable cause(s) affected the process. A root-cause analysis in a multivariate process is more complex compared to a univariate process. In the case of a process involved several correlated variables an effective root-cause analysis can be only experienced when it is possible to identify the required knowledge including the out-of-control condition, the change point, and the variable(s) responsible to the out-of-control condition, all simultaneously. Although literature addresses different schemes to monitor multivariate processes, one can find few scientific reports focused on all the required knowledge. To the best of the author’s knowledge this is the first time that a multi task model based on artificial neural network (ANN) is reported to monitor all the required knowledge at the same time for a multivariate process with more than two correlated quality characteristics. The performance of the proposed scheme is evaluated numerically when different step shifts affect the mean vector. Average run length is used to investigate the performance of the proposed multi task model. The simulated results indicate the multi task scheme performs all the required knowledge effectively.

Keywords: Artificial neural network, Multivariate process, Statistical process control, Change point.

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Authors: Seyed Hamid Mirmohammad Sadeghi, Raffaella Sesana, Daniela Maffiodo

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This study presents a procedure for friction calculation of column electric power steering (C-EPS) system which affects handling and comfort in driving. The friction losses estimation is obtained from experimental tests and mathematical calculation. Parts in C-EPS mainly involved in friction losses are bearings and worm gear. In the theoretical approach, the gear geometry and Hertz law were employed to measure the normal load and the sliding velocity and contact areas from the worm gears driving conditions. The viscous friction generated in the worm gear was obtained with a theoretical approach and the result was applied to model the friction in the steering system. Finally, by viscous friction coefficient and Coulomb friction coefficient, values of friction in worm gear were calculated. According to the Bearing Company and the characteristics of each bearing, the friction torques due to load and due to speed were calculated. A MATLAB Simulink model for calculating the friction in bearings and worm gear in C-EPS were done and the total friction value was estimated.

Keywords: Friction, worm gear, column electric power steering system, Simulink, bearing, electric power steering, EPS.

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Authors: Sagir M. Yusuf, Chris Baber

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In this paper, we describe how Bayesian inferential reasoning will contributes in obtaining a well-satisfied prediction for Distributed Constraint Optimization Problems (DCOPs) with uncertainties. We also demonstrate how DCOPs could be merged to multi-agent knowledge understand and prediction (i.e. Situation Awareness). The DCOPs functions were merged with Bayesian Belief Network (BBN) in the form of situation, awareness, and utility nodes. We describe how the uncertainties can be represented to the BBN and make an effective prediction using the expectation-maximization algorithm or conjugate gradient descent algorithm. The idea of variable prediction using Bayesian inference may reduce the number of variables in agents’ sampling domain and also allow missing variables estimations. Experiment results proved that the BBN perform compelling predictions with samples containing uncertainties than the perfect samples. That is, Bayesian inference can help in handling uncertainties and dynamism of DCOPs, which is the current issue in the DCOPs community. We show how Bayesian inference could be formalized with Distributed Situation Awareness (DSA) using uncertain and missing agents’ data. The whole framework was tested on multi-UAV mission for forest fire searching. Future work focuses on augmenting existing architecture to deal with dynamic DCOPs algorithms and multi-agent information merging.

Keywords: DCOP, multi-agent reasoning, Bayesian reasoning, swarm intelligence.

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Authors: Varun Singh, Mainak Bandyopadhyay, Maharana Pratap Singh

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The shortest path (SP) problem concerns with finding the shortest path from a specific origin to a specified destination in a given network while minimizing the total cost associated with the path. This problem has widespread applications. Important applications of the SP problem include vehicle routing in transportation systems particularly in the field of in-vehicle Route Guidance System (RGS) and traffic assignment problem (in transportation planning). Well known applications of evolutionary methods like Genetic Algorithms (GA), Ant Colony Optimization, Particle Swarm Optimization (PSO) have come up to solve complex optimization problems to overcome the shortcomings of existing shortest path analysis methods. It has been reported by various researchers that PSO performs better than other evolutionary optimization algorithms in terms of success rate and solution quality. Further Geographic Information Systems (GIS) have emerged as key information systems for geospatial data analysis and visualization. This research paper is focused towards the application of PSO for solving the shortest path problem between multiple points of interest (POI) based on spatial data of Allahabad City and traffic speed data collected using GPS. Geovisualization of results of analysis is carried out in GIS.

Keywords: GIS, Outliers, PSO, Traffic Data.

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Authors: Arash Sharghi, Irina Dotu

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The developments in the Middle East region have activated the involvement of a numerous diverse state and non-state actors in the regional affairs. The goals, positions, ideologies, different, and even contrast policy behaviors had procured the spreading and continuity of crisis. Non-state actors varying from Islamic organizations to takfiri-terrorist movements on one hand and regional and trans- regional actors, from another side, seek to reach their interests in the power struggle. Here, a research worthy question comes on the agenda: taking into consideration actors’ contradictory interests and constraints what are the regional peace and stability perspectives? Therein, different actors’ aims definition, their actions and behaviors, which affect instability, can be regarded as independent variables; whereas, on the contrary, Middle East peace and stability perspective analysis is a dependent variable. Though, this regional peace and war theory based research admits the significant influence of trans-regional actors, it asserts the roots of violence to derive from region itself. Consequently, hot war and conflict prevention and hot peace assurance in the Middle East region cannot be attained only by demands and approaches of trans-regional actors. Moreover, capacity of trans-regional actors is sufficient only for a cold war or cold peace to be reached in the region. Furthermore, within the framework of current conflict (struggle) between regional actors it seems to be difficult and even impossible to turn the cold war into a cold peace in the region.

Keywords: Cold peace, cold war, hot war, Middle East, non-state actors, regional and Great powers, war theory.

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Authors: Taehyun Yoon, Keechul Jung

Abstract:

There are many researches to detect collision between real object and virtual object in 3D space. In general, these techniques are need to huge computing power. So, many research and study are constructed by using cloud computing, network computing, and distribute computing. As a reason of these, this paper proposed a novel fast 3D collision detection algorithm between real and virtual object using 2D intersection area. Proposed algorithm uses 4 multiple cameras and coarse-and-fine method to improve accuracy and speed performance of collision detection. In the coarse step, this system examines the intersection area between real and virtual object silhouettes from all camera views. The result of this step is the index of virtual sensors which has a possibility of collision in 3D space. To decide collision accurately, at the fine step, this system examines the collision detection in 3D space by using the visual hull algorithm. Performance of the algorithm is verified by comparing with existing algorithm. We believe proposed algorithm help many other research, study and application fields such as HCI, augmented reality, intelligent space, and so on.

Keywords: Collision Detection, Computer Vision, Human Computer Interaction, Visual Hull

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Authors: Kiurski S. Jelena, Kecić S. Vesna, Aksentijević M. Snežana

Abstract:

Samples of tap and wastewater were collected in three offset printing facilities in Novi Sad, Serbia. Ten physicochemical parameters were analyzed within all collected samples: pH, conductivity, m - alkalinity, p - alkalinity, acidity, carbonate concentration, hydrogen carbonate concentration, active oxygen content, chloride concentration and total alkali content. All measurements were conducted using the standard analytical and instrumental methods. Comparing the obtained results for tap water and wastewater, a clear quality difference was noticeable, since all physicochemical parameters were significantly higher within wastewater samples. The study also involves the application of simple linear regression analysis on the obtained dataset. By using software package ORIGIN 5 the pH value was mutually correlated with other physicochemical parameters. Based on the obtained values of Pearson coefficient of determination a strong positive correlation between chloride concentration and pH (r = -0.943), as well as between acidity and pH (r = -0.855) was determined. In addition, statistically significant difference was obtained only between acidity and chloride concentration with pH values, since the values of parameter F (247.634 and 182.536) were higher than F_critical (5.59). In this way, results of statistical analysis highlighted the most influential parameter of water contamination in offset printing, in the form of acidity and chloride concentration. The results showed that variable dependence could be represented by the general regression model: y = a₀ + a₁x+ k, which further resulted with matching graphic regressions.

Keywords: Pollution, printing industry, simple linear regression analysis, wastewater.

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Authors: Radwa Mabrook

Abstract:

Virtual Reality (VR) content creation is a complex and an expensive process, which requires multi-disciplinary teams of content creators. Grant schemes from technology companies help media organisations to explore the VR potential in journalism and factual storytelling. Media organisations try to do as much as they can in-house, but they may outsource due to time constraints and skill availability. Journalists, game developers, sound designers and creative artists work together and bring in new cultures of work. This study explores the collaborative experimental nature of VR content creation, through tracing every actor involved in the process and examining their perceptions of the VR work. The study builds on Actor Network Theory (ANT), which decomposes phenomena into their basic elements and traces the interrelations among them. Therefore, the researcher conducted 22 semi-structured interviews with VR content creators between November 2017 and April 2018. Purposive and snowball sampling techniques allowed the researcher to recruit fact-based VR content creators from production studios and media organisations, as well as freelancers. Interviews lasted up to three hours, and they were a mix of Skype calls and in-person interviews. Participants consented for their interviews to be recorded, and for their names to be revealed in the study. The researcher coded interviews’ transcripts in Nvivo software, looking for key themes that correspond with the research questions. The study revealed that VR content creators must be adaptive to change, open to learn and comfortable with mistakes. The VR content creation process is very iterative because VR has no established work flow or visual grammar. Multi-disciplinary VR team members often speak different languages making it hard to communicate. However, adaptive content creators perceive VR work as a fun experience and an opportunity to learn. The traditional sense of competition and the strive for information exclusivity are now replaced by a strong drive for knowledge sharing. VR content creators are open to share their methods of work and their experiences. They target to build a collaborative network that aims to harness VR technology for journalism and factual storytelling. Indeed, VR is instilling collaborative and experimental cultures in journalism.

Keywords: Collaborative culture, content creation, experimental culture, virtual reality.

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Authors: Fathi Taibi

Abstract:

Measuring the reusability of Object-Oriented (OO) program code is important to ensure a successful and timely adaptation and integration of the reused code in new software projects. It has become even more relevant with the availability of huge amounts of open-source projects. Reuse saves cost, increases the speed of development and improves software reliability. Measuring this reusability is not s straight forward process due to the variety of metrics and qualities linked to software reuse and the lack of comprehensive empirical studies to support the proposed metrics or models. In this paper, a conceptual model is proposed to measure the reusability of OO program code. A comprehensive set of metrics is used to compute the most significant factors of reusability and an empirical investigation is conducted to measure the reusability of the classes of randomly selected open-source Java projects. Additionally, the impact of using inner and anonymous classes on the reusability of their enclosing classes is assessed. The results obtained are thoroughly analyzed to identify the factors behind lack of reusability in open-source OO program code and the impact of nesting on it.

Keywords: Code reuse, Low Complexity, Empirical Analysis, Modularity, Software Metrics, Understandability.

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