Search results for: Software Estimation
Commenced in January 2007
Frequency: Monthly
Edition: International
Paper Count: 3027

Search results for: Software Estimation

1497 Motion Planning of SCARA Robots for Trajectory Tracking

Authors: Giovanni Incerti

Abstract:

The paper presents a method for a simple and immediate motion planning of a SCARA robot, whose end-effector has to move along a given trajectory; the calculation procedure requires the user to define in analytical form or by points the trajectory to be followed and to assign the curvilinear abscissa as function of the time. On the basis of the geometrical characteristics of the robot, a specifically developed program determines the motion laws of the actuators that enable the robot to generate the required movement; this software can be used in all industrial applications for which a SCARA robot has to be frequently reprogrammed, in order to generate various types of trajectories with different motion times.

Keywords: Motion planning, SCARA robot, trajectory tracking.

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1496 Performance Evaluation of a Minimum Mean Square Error-Based Physical Sidelink Share Channel Receiver under Fading Channel

Authors: Yang Fu, Jaime Rodrigo Navarro, Jose F. Monserrat, Faiza Bouchmal, Oscar Carrasco Quilis

Abstract:

Cellular Vehicle to Everything (C-V2X) is considered a promising solution for future autonomous driving. From Release 16 to Release 17, the Third Generation Partnership Project (3GPP) has introduced the definitions and services for 5G New Radio (NR) V2X. Since establishing a simulator for C-V2X communications is an essential preliminary step to achieve reliable and stable communication links, this paper proposes a complete framework of a link-level simulator based on the 3GPP specifications for the Physical Sidelink Share Channel (PSSCH) of the 5G NR Physical Layer (PHY). In this framework, several algorithms in the receiver part, i.e., sliding window in channel estimation and Minimum Mean Square Error (MMSE)-based equalization, are developed. Finally, the performance of the developed PSSCH receiver is validated through extensive simulations under different assumptions.

Keywords: Yang Fu, Jaime Rodrigo Navarro, Jose F. Monserrat, Faiza Bouchmal, Oscar Carrasco Quilis

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1495 Smartphone-Based Human Activity Recognition by Machine Learning Methods

Authors: Yanting Cao, Kazumitsu Nawata

Abstract:

As smartphones are continually upgrading, their software and hardware are getting smarter, so the smartphone-based human activity recognition will be described more refined, complex and detailed. In this context, we analyzed a set of experimental data, obtained by observing and measuring 30 volunteers with six activities of daily living (ADL). Due to the large sample size, especially a 561-feature vector with time and frequency domain variables, cleaning these intractable features and training a proper model become extremely challenging. After a series of feature selection and parameters adjustments, a well-performed SVM classifier has been trained. 

Keywords: smart sensors, human activity recognition, artificial intelligence, SVM

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1494 Websites for Hypothesis Testing

Authors: František Mošna

Abstract:

E-learning has become an efficient and widespread means of education at all levels of human activities. Statistics is no exception. Unfortunately the main focus in statistics teaching is usually paid to the substitution in formulas. Suitable websites can simplify and automate calculations and provide more attention and time to the basic principles of statistics, mathematization of real-life situations and following interpretation of results. We now introduce our own web-site for hypothesis testing. Its didactic aspects, the technical possibilities of the individual tools, the experience of use and the advantages or disadvantages are discussed in this paper. This web-site is not a substitute for common statistical software but should significantly improve the teaching of statistics at universities.

Keywords: E-learning, hypothesis testing, PHP, websites.

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1493 Novel Rao-Blackwellized Particle Filter for Mobile Robot SLAM Using Monocular Vision

Authors: Maohai Li, Bingrong Hong, Zesu Cai, Ronghua Luo

Abstract:

This paper presents the novel Rao-Blackwellised particle filter (RBPF) for mobile robot simultaneous localization and mapping (SLAM) using monocular vision. The particle filter is combined with unscented Kalman filter (UKF) to extending the path posterior by sampling new poses that integrate the current observation which drastically reduces the uncertainty about the robot pose. The landmark position estimation and update is also implemented through UKF. Furthermore, the number of resampling steps is determined adaptively, which seriously reduces the particle depletion problem, and introducing the evolution strategies (ES) for avoiding particle impoverishment. The 3D natural point landmarks are structured with matching Scale Invariant Feature Transform (SIFT) feature pairs. The matching for multi-dimension SIFT features is implemented with a KD-Tree in the time cost of O(log2 N). Experiment results on real robot in our indoor environment show the advantages of our methods over previous approaches.

Keywords: Mobile robot, simultaneous localization and mapping, Rao-Blackwellised particle filter, evolution strategies, scale invariant feature transform.

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1492 Effect of Environmental Conditions on Energy Efficiency of AAC-based Building Envelopes

Authors: V. Koci, J. Madera, R. Cerny

Abstract:

Calculations of energy efficiency of several AACbased building envelopes under different climatic conditions are presented. As thermal insulating materials, expanded polystyrene and hydrophobic and hydrophilic mineral wools are assumed. The computations are accomplished using computer code HEMOT developed at Department of Materials Engineering, Faculty of Civil Engineering at the Czech Technical University in Prague. The climatic data of Athens, Kazan, Oslo, Prague and Reykjavík are obtained using METEONORM software.

Keywords: climatic conditions, computational simulation, energy efficiency, thermal insulation

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1491 Determination of Optical Constants of Semiconductor Thin Films by Ellipsometry

Authors: Aïssa Manallah, Mohamed Bouafia

Abstract:

Ellipsometry is an optical method based on the study of the behavior of polarized light. The light reflected on a surface induces a change in the polarization state which depends on the characteristics of the material (complex refractive index and thickness of the different layers constituting the device). The purpose of this work is to determine the optical properties of semiconductor thin films by ellipsometry. This paper describes the experimental aspects concerning the semiconductor samples, the SE400 ellipsometer principle, and the results obtained by direct measurements of ellipsometric parameters and modelling using appropriate software.

Keywords: Ellipsometry, optical constants, semiconductors, thin films.

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1490 Profitability and Budgeting of Kenaf Cultivation and Fiber Production in Kelantan Districts

Authors: Hamdon A. Abdelrhman

Abstract:

The purpose of the analysis is estimation of viability and profitability of kenaf plant farming in Kelantan State. The monetary information was gathered through interviewing kenaf growers as well group discussion. In addition, the production statistics were collected from Kenaf factory administrative group. The monetary data were analyzed using the Precision financial Calculator. For kenaf production per hectare three scenarios of productivity were adopted, they were 15, 12 and ten; the research results exposed that, when kenaf productivity was 15 ton and the agronomist received financial supports from kenaf administration, the margin profit reached up to 37% which is almost dual profitability that is expected without government support. The financial analysis explains that, the adopted scenarios of the productivity are feasible when Benefit Cost Ratio (BCR) was used as financial indicator. Nonetheless, the kenaf productivity of 15 ton is the superlative viable among the others and payback period is 5 years which equals to middle period time to return the invested amount back. The study concluded that for the farmer to increase the productivity of kenaf per hectare the well farming practices as well as continuously farmers financial support are highly needed.

Keywords: Margin profit, farming practices, financial analysis, kenaf cultivation.

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1489 Pressure Capacity Reduction of X52 Pipeline Steel Damaged by a Semi-Elliptical Pitting Corrosion

Authors: S. M. Kazerouni Sangi, Y. Gholipour

Abstract:

Steel made pipelines with different diameters are used for transmitting oil and gas which in many cases are buried in soil under the sea bed or immersed in sea water. External corrosion of pipes is an important form of deterioration due to the aggressive environment of sea water. Corrosion normally results in pits. Hence, using the finite element method, namely ABAQUS software, this paper estimates the amount of pressure capacity reduction of a pipecontaining a semi-elliptical pitting corrosion and the rate of corrosion during the pipeline life of 25 years.

Keywords: Petroleum Transmission, Pipeline, PressureCapacity, Semi-Elliptical Pitting Corrosion.

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1488 Lumped Parameter Models for Numerical Simulation of the Dynamic Response of Hoisting Appliances

Authors: Giovanni Incerti, Luigi Solazzi, Candida Petrogalli

Abstract:

This paper describes three lumped parameters models for the study of the dynamic behavior of a boom crane. The models here proposed allows to evaluate the fluctuations of the load arising from the rope and structure elasticity and from the type of the motion command imposed by the winch. A calculation software was developed in order to determine the actual acceleration of the lifted mass and the dynamic overload during the lifting phase. Some application examples are presented, with the aim of showing the correlation between the magnitude of the stress and the type of the employed motion command.

Keywords: Crane, dynamic model, overloading condition, vibration.

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1487 A Study of Panel Logit Model and Adaptive Neuro-Fuzzy Inference System in the Prediction of Financial Distress Periods

Authors: Ε. Giovanis

Abstract:

The purpose of this paper is to present two different approaches of financial distress pre-warning models appropriate for risk supervisors, investors and policy makers. We examine a sample of the financial institutions and electronic companies of Taiwan Security Exchange (TSE) market from 2002 through 2008. We present a binary logistic regression with paned data analysis. With the pooled binary logistic regression we build a model including more variables in the regression than with random effects, while the in-sample and out-sample forecasting performance is higher in random effects estimation than in pooled regression. On the other hand we estimate an Adaptive Neuro-Fuzzy Inference System (ANFIS) with Gaussian and Generalized Bell (Gbell) functions and we find that ANFIS outperforms significant Logit regressions in both in-sample and out-of-sample periods, indicating that ANFIS is a more appropriate tool for financial risk managers and for the economic policy makers in central banks and national statistical services.

Keywords: ANFIS, Binary logistic regression, Financialdistress, Panel data

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1486 A 3D Approach for Extraction of the Coronaryartery and Quantification of the Stenosis

Authors: Mahdi Mazinani, S. D. Qanadli, Rahil Hosseini, Tim Ellis, Jamshid Dehmeshki

Abstract:

Segmentation and quantification of stenosis is an important task in assessing coronary artery disease. One of the main challenges is measuring the real diameter of curved vessels. Moreover, uncertainty in segmentation of different tissues in the narrow vessel is an important issue that affects accuracy. This paper proposes an algorithm to extract coronary arteries and measure the degree of stenosis. Markovian fuzzy clustering method is applied to model uncertainty arises from partial volume effect problem. The algorithm employs: segmentation, centreline extraction, estimation of orthogonal plane to centreline, measurement of the degree of stenosis. To evaluate the accuracy and reproducibility, the approach has been applied to a vascular phantom and the results are compared with real diameter. The results of 10 patient datasets have been visually judged by a qualified radiologist. The results reveal the superiority of the proposed method compared to the Conventional thresholding Method (CTM) on both datasets.

Keywords: 3D coronary artery tree extraction, segmentation, quantification, fuzzy clustering, and Markov random field

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1485 The Influence of the Fin Set-up to the Cooling Output of the Floor Heating Convector

Authors: F. Lemfeld, K. Frana

Abstract:

This article deals with the numerical simulation of the floor heating convector in 3D. Presented convector can operate in two modes – cooling mode and heating mode. This initial numerical simulation is focused on cooling mode of the convector. Models with different temperature of the fins are compared and three various shapes of the fins are examined as well. The objective of the work is to predict air flow and heat transfer inside convector for further optimalization of these devices. For the numerical simulation was used commercial software Ansys Fluent.

Keywords: Cooling output, floor heating convector, numericalsimulation, optimalization.

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1484 A Self Organized Map Method to Classify Auditory-Color Synesthesia from Frontal Lobe Brain Blood Volume

Authors: Takashi Kaburagi, Takamasa Komura, Yosuke Kurihara

Abstract:

Absolute pitch is the ability to identify a musical note without a reference tone. Training for absolute pitch often occurs in preschool education. It is necessary to clarify how well the trainee can make use of synesthesia in order to evaluate the effect of the training. To the best of our knowledge, there are no existing methods for objectively confirming whether the subject is using synesthesia. Therefore, in this study, we present a method to distinguish the use of color-auditory synesthesia from the separate use of color and audition during absolute pitch training. This method measures blood volume in the prefrontal cortex using functional Near-infrared spectroscopy (fNIRS) and assumes that the cognitive step has two parts, a non-linear step and a linear step. For the linear step, we assume a second order ordinary differential equation. For the non-linear part, it is extremely difficult, if not impossible, to create an inverse filter of such a complex system as the brain. Therefore, we apply a method based on a self-organizing map (SOM) and are guided by the available data. The presented method was tested using 15 subjects, and the estimation accuracy is reported.

Keywords: Absolute pitch, functional near-infrared spectroscopy, prefrontal cortex, synesthesia.

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1483 Experimental and Analytical Dose Assessment of Patient's Family Members Treated with I-131

Authors: Marzieh Ebrahimi, Vahid Changizi, Mohammad Reza Kardan, Seyed Mahdi Hosseini Pooya, Parham Geramifar

Abstract:

Radiation exposure to the patient's family members is one of the major concerns during thyroid cancer radionuclide therapy. The aim of this study was to measure the total effective dose of the family members by means of thermoluminescence personal dosimeter, and compare with those calculated by analytical methods. Eighty-five adult family members of fifty-one patients volunteered to participate in this research study. Considering the minimum and maximum range of dose rate from 15 µsv/h to 120 µsv/h at patients' release time, the calculated mean and median dose values of family members were 0.45 mSv and 0.28 mSv, respectively. Moreover, almost all family members’ doses were measured to be less than the dose constraint of 5 mSv recommended by Basic Safety Standards. Considering the influence parameters such as patient dose rate and administrated activity, the total effective doses of family members were calculated by TEDE and NRC formulas and compared with those of experimental results. The results indicated that, it is fruitful to use the quantitative calculations for releasing patients treated with I-131 and correct estimation of patients' family doses.

Keywords: Effective dose, thermoluminescence, I-131, Thyroid cancer.

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1482 Estimation of Real Power Transfer Allocation Using Intelligent Systems

Authors: H. Shareef, A. Mohamed, S. A. Khalid, Aziah Khamis

Abstract:

This paper presents application artificial intelligent (AI) techniques, namely artificial neural network (ANN), adaptive neuro fuzzy interface system (ANFIS), to estimate the real power transfer between generators and loads. Since these AI techniques adopt supervised learning, it first uses modified nodal equation method (MNE) to determine real power contribution from each generator to loads. Then the results of MNE method and load flow information are utilized to estimate the power transfer using AI techniques. The 25-bus equivalent system of south Malaysia is utilized as a test system to illustrate the effectiveness of both AI methods compared to that of the MNE method. The mean squared error of the estimate of ANN and ANFIS power transfer allocation methods are 1.19E-05 and 2.97E-05, respectively. Furthermore, when compared to MNE method, ANN and ANFIS methods computes generator contribution to loads within 20.99 and 39.37msec respectively whereas the MNE method took 360msec for the calculation of same real power transfer allocation. 

Keywords: Artificial intelligence, Power tracing, Artificial neural network, ANFIS, Power system deregulation.

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1481 A Comparison of Some Thresholding Selection Methods for Wavelet Regression

Authors: Alsaidi M. Altaher, Mohd T. Ismail

Abstract:

In wavelet regression, choosing threshold value is a crucial issue. A too large value cuts too many coefficients resulting in over smoothing. Conversely, a too small threshold value allows many coefficients to be included in reconstruction, giving a wiggly estimate which result in under smoothing. However, the proper choice of threshold can be considered as a careful balance of these principles. This paper gives a very brief introduction to some thresholding selection methods. These methods include: Universal, Sure, Ebays, Two fold cross validation and level dependent cross validation. A simulation study on a variety of sample sizes, test functions, signal-to-noise ratios is conducted to compare their numerical performances using three different noise structures. For Gaussian noise, EBayes outperforms in all cases for all used functions while Two fold cross validation provides the best results in the case of long tail noise. For large values of signal-to-noise ratios, level dependent cross validation works well under correlated noises case. As expected, increasing both sample size and level of signal to noise ratio, increases estimation efficiency.

Keywords: wavelet regression, simulation, Threshold.

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1480 A Numerical Framework to Investigate Intake Aerodynamics Behavior in Icing Conditions

Authors: Ali Mirmohammadi, Arash Taheri, Meysam Mohammadi-Amin

Abstract:

One of the major parts of a jet engine is air intake, which provides proper and required amount of air for the engine to operate. There are several aerodynamic parameters which should be considered in design, such as distortion, pressure recovery, etc. In this research, the effects of lip ice accretion on pitot intake performance are investigated. For ice accretion phenomenon, two supervised multilayer neural networks (ANN) are designed, one for ice shape prediction and another one for ice roughness estimation based on experimental data. The Fourier coefficients of transformed ice shape and parameters include velocity, liquid water content (LWC), median volumetric diameter (MVD), spray time and temperature are used in neural network training. Then, the subsonic intake flow field is simulated numerically using 2D Navier-Stokes equations and Finite Volume approach with Hybrid mesh includes structured and unstructured meshes. The results are obtained in different angles of attack and the variations of intake aerodynamic parameters due to icing phenomenon are discussed. The results show noticeable effects of ice accretion phenomenon on intake behavior.

Keywords: Artificial Neural Network, Ice Accretion, IntakeAerodynamics, Design Parameters, Finite Volume Method.

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1479 Reform Framework for Urban Land Management in Serbia in the Period of Transition

Authors: Slavka Zeković

Abstract:

A preliminary evaluation of the urban land system is presented in the article together with the instruments of land policy in Serbia. The main reason for the analysis is demand for definition of reform framework for urban land management in Serbia in the period of transition towards market-led system. It is concluded that due to the limitations of the current regulation it will be impossible in the future to apply market principles in the urban land policy (supply and demand of land, land capitalization, investment efficiency, et al.). Based on the estimation that the urban land system and land policy are key factors of competitiveness between regions and towns in Serbia, it is necessary to initiate changes in this field. There are indicated on an option of privatization of urban public land and possible establishment of leasehold land. A comparative analysis of the possibilities of the reform urban land system in Serbia has been carried out in relation to two approaches of market systems: (a) with dominant private ownership of urban land (neo/liberal approach) and (b) with dominant public ownership of urban land (system of leasehold)whose findings can be a basis for further study of the new system in Serbia.. The attanied results are part of studies matter for the making of Strategy of territorial development of Serbia.

Keywords: Urban Land System, Urban Land Management, Instruments of Land Policy, Evaluation, Market.

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1478 Soft-Sensor for Estimation of Gasoline Octane Number in Platforming Processes with Adaptive Neuro-Fuzzy Inference Systems (ANFIS)

Authors: Hamed.Vezvaei, Sepideh.Ordibeheshti, Mehdi.Ardjmand

Abstract:

Gasoline Octane Number is the standard measure of the anti-knock properties of a motor in platforming processes, that is one of the important unit operations for oil refineries and can be determined with online measurement or use CFR (Cooperative Fuel Research) engines. Online measurements of the Octane number can be done using direct octane number analyzers, that it is too expensive, so we have to find feasible analyzer, like ANFIS estimators. ANFIS is the systems that neural network incorporated in fuzzy systems, using data automatically by learning algorithms of NNs. ANFIS constructs an input-output mapping based both on human knowledge and on generated input-output data pairs. In this research, 31 industrial data sets are used (21 data for training and the rest of the data used for generalization). Results show that, according to this simulation, hybrid method training algorithm in ANFIS has good agreements between industrial data and simulated results.

Keywords: Adaptive Neuro-Fuzzy Inference Systems, GasolineOctane Number, Soft-sensor, Catalytic Naphtha Reforming

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1477 Perceptual JPEG Compliant Coding by Using DCT-Based Visibility Thresholds of Color Images

Authors: Kuo-Cheng Liu

Abstract:

Effective estimation of just noticeable distortion (JND) for images is helpful to increase the efficiency of a compression algorithm in which both the statistical redundancy and the perceptual redundancy should be accurately removed. In this paper, we design a DCT-based model for estimating JND profiles of color images. Based on a mathematical model of measuring the base detection threshold for each DCT coefficient in the color component of color images, the luminance masking adjustment, the contrast masking adjustment, and the cross masking adjustment are utilized for luminance component, and the variance-based masking adjustment based on the coefficient variation in the block is proposed for chrominance components. In order to verify the proposed model, the JND estimator is incorporated into the conventional JPEG coder to improve the compression performance. A subjective and fair viewing test is designed to evaluate the visual quality of the coding image under the specified viewing condition. The simulation results show that the JPEG coder integrated with the proposed DCT-based JND model gives better coding bit rates at visually lossless quality for a variety of color images.

Keywords: Just-noticeable distortion (JND), discrete cosine transform (DCT), JPEG.

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1476 Adjusted Ratio and Regression Type Estimators for Estimation of Population Mean when some Observations are missing

Authors: Nuanpan Nangsue

Abstract:

Ratio and regression type estimators have been used by previous authors to estimate a population mean for the principal variable from samples in which both auxiliary x and principal y variable data are available. However, missing data are a common problem in statistical analyses with real data. Ratio and regression type estimators have also been used for imputing values of missing y data. In this paper, six new ratio and regression type estimators are proposed for imputing values for any missing y data and estimating a population mean for y from samples with missing x and/or y data. A simulation study has been conducted to compare the six ratio and regression type estimators with a previous estimator of Rueda. Two population sizes N = 1,000 and 5,000 have been considered with sample sizes of 10% and 30% and with correlation coefficients between population variables X and Y of 0.5 and 0.8. In the simulations, 10 and 40 percent of sample y values and 10 and 40 percent of sample x values were randomly designated as missing. The new ratio and regression type estimators give similar mean absolute percentage errors that are smaller than the Rueda estimator for all cases. The new estimators give a large reduction in errors for the case of 40% missing y values and sampling fraction of 30%.

Keywords: Auxiliary variable, missing data, ratio and regression type estimators.

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1475 A Tool for Checking Conformance of UML Specification

Authors: Rosziati Ibrahim, Noraini Ibrahim

Abstract:

Unified Modeling Language (UML) is a standard language for modeling of a system. UML is used to visually specify the structure and behavior of a system. The system requirements are captured and then converted into UML specification. UML specification uses a set of rules and notations, and diagrams to specify the system requirements. In this paper, we present a tool for developing the UML specification. The tool will ease the use of the notations and diagrams for UML specification as well as increase the understanding and familiarity of the UML specification. The tool will also be able to check the conformance of the diagrams against each other for basic compliance of UML specification.

Keywords: Software Engineering, Unified Modeling Language (UML), UML Specification.

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1474 End-to-End Pyramid Based Method for MRI Reconstruction

Authors: Omer Cahana, Maya Herman, Ofer Levi

Abstract:

Magnetic Resonance Imaging (MRI) is a lengthy medical scan that stems from a long acquisition time. Its length is mainly due to the traditional sampling theorem, which defines a lower boundary for sampling. However, it is still possible to accelerate the scan by using a different approach such as Compress Sensing (CS) or Parallel Imaging (PI). These two complementary methods can be combined to achieve a faster scan with high-fidelity imaging. To achieve that, two conditions must be satisfied: i) the signal must be sparse under a known transform domain, and ii) the sampling method must be incoherent. In addition, a nonlinear reconstruction algorithm must be applied to recover the signal. While the rapid advances in Deep Learning (DL) have had tremendous successes in various computer vision tasks, the field of MRI reconstruction is still in its early stages. In this paper, we present an end-to-end method for MRI reconstruction from k-space to image. Our method contains two parts. The first is sensitivity map estimation (SME), which is a small yet effective network that can easily be extended to a variable number of coils. The second is reconstruction, which is a top-down architecture with lateral connections developed for building high-level refinement at all scales. Our method holds the state-of-art fastMRI benchmark, which is the largest, most diverse benchmark for MRI reconstruction.

Keywords: Accelerate MRI scans, image reconstruction, pyramid network, deep learning.

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1473 Ohmic Quality Factor and Efficiency Estimation for a Gyrotron Cavity

Authors: R. K. Singh, P.K.Jain

Abstract:

Operating a device at high power and high frequency is a major problem because wall losses greatly reduce the efficiency of the device. In the present communication, authors analytically analyzed the dependence of ohmic/RF efficiency, the fraction of output power with respect to the total power generated, of gyrotron cavity structure on the conductivity of copper for the second harmonic TE0,6 mode. This study shows a rapid fall in the RF efficiency as the quality (conductivity) of copper degrades. Starting with an RF efficiency near 40% at the conductivity of ideal copper (5.8 x 107 S/m), the RF efficiency decreases (upto 8%) as the copper quality degrades. Assuming conductivity half that of ideal copper the RF efficiency as a function of diffractive quality factor, Qdiff, has been studied. Here the RF efficiency decreases rapidly with increasing diffractive Q. Ohmic wall losses as a function of frequency for 460 GHz gyrotron cavity excited in TE0,6 mode has also been analyzed. For 460 GHz cavity, the extracted power is reduced to 32% of the generated power due to ohmic losses in the walls of the cavity.

Keywords: Diffractive quality factor, Gyrotron, Ohmic wall losses, Open cavity resonator, RF Efficiency.

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1472 Analysis of Synchronous Machine Excitation Systems: Comparative Study

Authors: Shewit Tsegaye, Kinde A. Fante

Abstract:

This paper presents the comparison and performance evaluation of synchronous machine excitation models. The two models, DC1A and AC4A, are among the IEEE standardized model structures for representing the wide variety of synchronous machine excitation systems. The performance evaluation of these models is done using SIMULINK simulation software. The simulation results obtained using transient analysis show that the DC1A excitation system is more reliable and stable than AC4A excitation system.

Keywords: Excitation system, synchronous machines, AC and DC regulators.

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1471 VoIP Networks Performance Analysis with Encryption Systems

Authors: Edward Paul Guillen, Diego Alejandro Chacon

Abstract:

The VoIP networks as alternative method to traditional PSTN system has been implemented in a wide variety of structures with multiple protocols, codecs, software and hardware–based distributions. The use of cryptographic techniques let the users to have a secure communication, but the calculate throughput as well as the QoS parameters are affected according to the used algorithm. This paper analyzes the VoIP throughput and the QoS parameters with different commercial encryption methods. The measurement–based approach uses lab scenarios to simulate LAN and WAN environments. Security mechanisms such as TLS, SIAX2, SRTP, IPSEC and ZRTP are analyzed with μ-LAW and GSM codecs.

Keywords: VoIP, Secure VoIP, Throughput Analysis, VoIP QoS evaluation

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1470 Multiband CPW-Fed Slot Antenna with L-slot Bowtie Tuning Stub

Authors: Prapoch Jirasakulporn

Abstract:

This paper presents a multiband CPW-fed slot antenna with L-slot bowtie tuning stub. The proposed antenna has been designed for PCS 1900, UMTS, WLAN 802.11 a/b/g and bluetooth applications, with a cost-effective FR4 substrate. The proposed antenna still radiate as omni-directional in azimuth plane and sufficient bandwidth for all above mentions. The proposed antenna works as dual-wideband, bandwidth at low frequency band and high frequency are about 45.49 % and 22.39 % respectively. The experimental results of the constructed prototype are presented and also compared with simulation results using a commercial software tool.

Keywords: multiband antenna, slot antenna, CPW-fed, L-slotbowtie stub

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1469 Studies on Seasonal Variations of Physico- Chemical Parameters of Fish Farm at Govt. Nursery Unit, Muzaffargarh, Punjab, Pakistan

Authors: Muhammad Naeem, Abdus Salam, Muhammad Ashraf, Muhammad Imran, Mehtab Ahmad, Muhammad Jamshed Khan, Muhammad Mazhar Ayaz, Muzaffar Ali, Arshad Ali, Memoona Qayyum Abir Ishtiaq

Abstract:

The present study was designed to demonstrate the seasonal variations in physico-chemical parameters of fish farm at Govt. Nursery Unit, Muzaffargarh, Department of Fisheries Govt. of Punjab, Pakistan for a period of eight months from January to August 2008. Water samples were collected on fifteen days basis and have been analyzed for estimation of Air temperature, Water temperature, Light penetration, pH, Total dissolved oxygen, Clouds, Carbonates, Bicarbonates, Total carbonates, Total dissolved solids, Chlorides, Calcium and Hardness. Seasonal fluctuations were observed in all the physico-chemical parameters of fish farm. The overall physicochemical parameters of fish pond water remained within the tolerable range throughout the study period.

Keywords: Freshwater, Fish farm, Water quality, Seasonal variation, Chemical factor

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1468 Novel SNC-NN-MRAS Based Speed Estimator for Sensor-Less Vector Controlled IM Drives

Authors: A.Venkadesan, S.Himavathi, A.Muthuramalingam

Abstract:

Rotor Flux based Model Reference Adaptive System (RF-MRAS) is the most popularly used conventional speed estimation scheme for sensor-less IM drives. In this scheme, the voltage model equations are used for the reference model. This encounters major drawbacks at low frequencies/speed which leads to the poor performance of RF-MRAS. Replacing the reference model using Neural Network (NN) based flux estimator provides an alternate solution and addresses such drawbacks. This paper identifies an NN based flux estimator using Single Neuron Cascaded (SNC) Architecture. The proposed SNC-NN model replaces the conventional voltage model in RF-MRAS to form a novel MRAS scheme named as SNC-NN-MRAS. Through simulation the proposed SNC-NN-MRAS is shown to be promising in terms of all major issues and robustness to parameter variation. The suitability of the proposed SNC-NN-MRAS based speed estimator and its advantages over RF-MRAS for sensor-less induction motor drives is comprehensively presented through extensive simulations.

Keywords: Sensor-less operation, vector-controlled IM drives, SNC-NN-MRAS, single neuron cascaded architecture, RF-MRAS, artificial neural network

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