Search results for: Error estimation
Commenced in January 2007
Frequency: Monthly
Edition: International
Paper Count: 2141

Search results for: Error estimation

1331 A Robust Approach to the Load Frequency Control Problem with Speed Regulation Uncertainty

Authors: S. Z. Sayed Hassen

Abstract:

The load frequency control problem of power systems has attracted a lot of attention from engineers and researchers over the years. Increasing and quickly changing load demand, coupled with the inclusion of more generators with high variability (solar and wind power generators) on the network are making power systems more difficult to regulate. Frequency changes are unavoidable but regulatory authorities require that these changes remain within a certain bound. Engineers are required to perform the tricky task of adjusting the control system to maintain the frequency within tolerated bounds. It is well known that to minimize frequency variations, a large proportional feedback gain (speed regulation constant) is desirable. However, this improvement in performance using proportional feedback comes about at the expense of a reduced stability margin and also allows some steady-state error. A conventional PI controller is then included as a secondary control loop to drive the steadystate error to zero. In this paper, we propose a robust controller to replace the conventional PI controller which guarantees performance and stability of the power system over the range of variation of the speed regulation constant. Simulation results are shown to validate the superiority of the proposed approach on a simple single-area power system model.

Keywords: Robust control, power system, integral action, minimax LQG control.

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1330 Fuzzy Logic System for Tractive Performance Prediction of an Intelligent Air-Cushion Track Vehicle

Authors: Altab Hossain, Ataur Rahman, A. K. M. Mohiuddin, Yulfian Aminanda

Abstract:

Fuzzy logic system (FLS) is used in this study to predict the tractive performance in terms of traction force, and motion resistance for an intelligent air cushion track vehicle while it operates in the swamp peat. The system is effective to control the intelligent air –cushion system with measuring the vehicle traction force (TF), motion resistance (MR), cushion clearance height (CH) and cushion pressure (CP). Ultrasonic displacement sensor, pull-in solenoid electromagnetic switch, pressure control sensor, micro controller, and battery pH sensor are incorporated with the Fuzzy logic system to investigate experimentally the TF, MR, CH, and CP. In this study, a comparison for tractive performance of an intelligent air cushion track vehicle has been performed with the results obtained from the predicted values of FLS and experimental actual values. The mean relative error of actual and predicted values from the FLS model on traction force, and total motion resistance are found as 5.58 %, and 6.78 % respectively. For all parameters, the relative error of predicted values are found to be less than the acceptable limits. The goodness of fit of the prediction values from the FLS model on TF, and MR are found as 0.90, and 0.98 respectively.

Keywords: Cushion pressure, Fuzzy logic, Motion resistance, Traction force.

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1329 Effect of Transmission Codes on Hybrid SC/MRC Diversity Reception MQAM system over Rayleigh Fading Channels

Authors: J.S. Ubhi, M.S. Patterh, T.S. Kamal

Abstract:

In this paper, the effect of transmission codes on the performance of coherent square M-ary quadrature amplitude modulation (CSMQAM) under hybrid selection/maximal-ratio combining (H-S/MRC) diversity is analysed. The fading channels are modeled as frequency non-selective slow independent and identically distributed Rayleigh fading channels corrupted by additive white Gaussian noise (AWGN). The results for coded MQAM are computed numerically for the case of (24,12) extended Golay code and compared with uncoded MQAM under H-S/MRC diversity by plotting error probabilities versus average signal to noise ratio (SNR) for various values L and N in order to examine the improvement in the performance of the digital communications system as the number of selected diversity branches is increased. The results for no diversity, conventional SC and Lth order MRC schemes are also plotted for comparison. Closed form analytical results derived in this paper are sufficiently simple and therefore can be computed numerically without any approximations. The analytical results presented in this paper are expected to provide useful information needed for design and analysis of digital communication systems over wireless fading channels.

Keywords: Error probability, diversity reception, Rayleigh fading channels, wireless digital communications.

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1328 A Model for Estimation of Efforts in Development of Software Systems

Authors: Parvinder S. Sandhu, Manisha Prashar, Pourush Bassi, Atul Bisht

Abstract:

Software effort estimation is the process of predicting the most realistic use of effort required to develop or maintain software based on incomplete, uncertain and/or noisy input. Effort estimates may be used as input to project plans, iteration plans, budgets. There are various models like Halstead, Walston-Felix, Bailey-Basili, Doty and GA Based models which have already used to estimate the software effort for projects. In this study Statistical Models, Fuzzy-GA and Neuro-Fuzzy (NF) Inference Systems are experimented to estimate the software effort for projects. The performances of the developed models were tested on NASA software project datasets and results are compared with the Halstead, Walston-Felix, Bailey-Basili, Doty and Genetic Algorithm Based models mentioned in the literature. The result shows that the NF Model has the lowest MMRE and RMSE values. The NF Model shows the best results as compared with the Fuzzy-GA based hybrid Inference System and other existing Models that are being used for the Effort Prediction with lowest MMRE and RMSE values.

Keywords: Neuro-Fuzzy Model, Halstead Model, Walston-Felix Model, Bailey-Basili Model, Doty Model, GA Based Model, Genetic Algorithm.

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1327 A Xenon Mass Gauging through Heat Transfer Modeling for Electric Propulsion Thrusters

Authors: A. Soria-Salinas, M.-P. Zorzano, J. Martín-Torres, J. Sánchez-García-Casarrubios, J.-L. Pérez-Díaz, A. Vakkada-Ramachandran

Abstract:

The current state-of-the-art methods of mass gauging of Electric Propulsion (EP) propellants in microgravity conditions rely on external measurements that are taken at the surface of the tank. The tanks are operated under a constant thermal duty cycle to store the propellant within a pre-defined temperature and pressure range. We demonstrate using computational fluid dynamics (CFD) simulations that the heat-transfer within the pressurized propellant generates temperature and density anisotropies. This challenges the standard mass gauging methods that rely on the use of time changing skin-temperatures and pressures. We observe that the domes of the tanks are prone to be overheated, and that a long time after the heaters of the thermal cycle are switched off, the system reaches a quasi-equilibrium state with a more uniform density. We propose a new gauging method, which we call the Improved PVT method, based on universal physics and thermodynamics principles, existing TRL-9 technology and telemetry data. This method only uses as inputs the temperature and pressure readings of sensors externally attached to the tank. These sensors can operate during the nominal thermal duty cycle. The improved PVT method shows little sensitivity to the pressure sensor drifts which are critical towards the end-of-life of the missions, as well as little sensitivity to systematic temperature errors. The retrieval method has been validated experimentally with CO2 in gas and fluid state in a chamber that operates up to 82 bar within a nominal thermal cycle of 38 °C to 42 °C. The mass gauging error is shown to be lower than 1% the mass at the beginning of life, assuming an initial tank load at 100 bar. In particular, for a pressure of about 70 bar, just below the critical pressure of CO2, the error of the mass gauging in gas phase goes down to 0.1% and for 77 bar, just above the critical point, the error of the mass gauging of the liquid phase is 0.6% of initial tank load. This gauging method improves by a factor of 8 the accuracy of the standard PVT retrievals using look-up tables with tabulated data from the National Institute of Standards and Technology.

Keywords: Electric propulsion, mass gauging, propellant, PVT, xenon.

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1326 Content and Resources based Mobile and Wireless Video Transcoding

Authors: Ashraf M. A. Ahmad

Abstract:

Delivering streaming video over wireless is an important component of many interactive multimedia applications running on personal wireless handset devices. Such personal devices have to be inexpensive, compact, and lightweight. But wireless channels have a high channel bit error rate and limited bandwidth. Delay variation of packets due to network congestion and the high bit error rate greatly degrades the quality of video at the handheld device. Therefore, mobile access to multimedia contents requires video transcoding functionality at the edge of the mobile network for interworking with heterogeneous networks and services. Therefore, to guarantee quality of service (QoS) delivered to the mobile user, a robust and efficient transcoding scheme should be deployed in mobile multimedia transporting network. Hence, this paper examines the challenges and limitations that the video transcoding schemes in mobile multimedia transporting network face. Then handheld resources, network conditions and content based mobile and wireless video transcoding is proposed to provide high QoS applications. Exceptional performance is demonstrated in the experiment results. These experiments were designed to verify and prove the robustness of the proposed approach. Extensive experiments have been conducted, and the results of various video clips with different bit rate and frame rate have been provided.

Keywords: Content, Object detection, Transcoding, Texture, Temporal, Video.

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1325 Tractive Performance Prediction for Intelligent Air-Cushion Track Vehicle: Fuzzy Logic Approach

Authors: Altab Hossain, Ataur Rahman, A. K. M. Mohiuddin, Yulfian Aminanda

Abstract:

Fuzzy logic approach is used in this study to predict the tractive performance in terms of traction force, and motion resistance for an intelligent air cushion track vehicle while it operates in the swamp peat. The system is effective to control the intelligent air –cushion system with measuring the vehicle traction force (TF), motion resistance (MR), cushion clearance height (CH) and cushion pressure (CP). Sinkage measuring sensor, magnetic switch, pressure sensor, micro controller, control valves and battery are incorporated with the Fuzzy logic system (FLS) to investigate experimentally the TF, MR, CH, and CP. In this study, a comparison for tractive performance of an intelligent air cushion track vehicle has been performed with the results obtained from the predicted values of FLS and experimental actual values. The mean relative error of actual and predicted values from the FLS model on traction force, and total motion resistance are found as 5.58 %, and 6.78 % respectively. For all parameters, the relative error of predicted values are found to be less than the acceptable limits. The goodness of fit of the prediction values from the FLS model on TF, and MR are found as 0.90, and 0.98 respectively.

Keywords: Cushion pressure, Fuzzy logic, Motion resistance, Traction force.

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1324 Evolutionary Techniques for Model Order Reduction of Large Scale Linear Systems

Authors: S. Panda, J. S. Yadav, N. P. Patidar, C. Ardil

Abstract:

Recently, genetic algorithms (GA) and particle swarm optimization (PSO) technique have attracted considerable attention among various modern heuristic optimization techniques. The GA has been popular in academia and the industry mainly because of its intuitiveness, ease of implementation, and the ability to effectively solve highly non-linear, mixed integer optimization problems that are typical of complex engineering systems. PSO technique is a relatively recent heuristic search method whose mechanics are inspired by the swarming or collaborative behavior of biological populations. In this paper both PSO and GA optimization are employed for finding stable reduced order models of single-input- single-output large-scale linear systems. Both the techniques guarantee stability of reduced order model if the original high order model is stable. PSO method is based on the minimization of the Integral Squared Error (ISE) between the transient responses of original higher order model and the reduced order model pertaining to a unit step input. Both the methods are illustrated through numerical example from literature and the results are compared with recently published conventional model reduction technique.

Keywords: Genetic Algorithm, Particle Swarm Optimization, Order Reduction, Stability, Transfer Function, Integral Squared Error.

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1323 Expert Witness Testimony in the Battered Woman Syndrome

Authors: Ana Pauna

Abstract:

The Expert Witness Testimony in the Battered Woman Syndrome Expert witness testimony (EWT) is a kind of information given by an expert specialized in the field (here in BWS) to the jury in order to help the court better understand the case. EWT does not always work in favor of the battered women. Two main decision-making models are discussed in the paper: the Mathematical model and the Explanation model. In the first model, the jurors calculate ″the importance and strength of each piece of evidence″ whereas in the second model they try to integrate the EWT with the evidence and create a coherent story that would describe the crime. The jury often misunderstands and misjudges battered women for their action (or in this case inaction). They assume that these women are masochists and accept being mistreated for if a man abuses a woman constantly, she should and could divorce him or simply leave at any time. The research in the domain found that indeed, expert witness testimony has a powerful influence on juror’s decisions thus its quality needs to be further explored. One of the important factors that need further studies is a bias called the dispositionist worldview (a belief that what happens to people is of their own doing). This kind of attributional bias represents a tendency to think that a person’s behavior is due to his or her disposition, even when the behavior is clearly attributed to the situation. Hypothesis The hypothesis of this paper is that if a juror has a dispositionist worldview then he or she will blame the rape victim for triggering the assault. The juror would therefore commit the fundamental attribution error and believe that the victim’s disposition caused the rape and not the situation she was in. Methods The subjects in the study were 500 randomly sampled undergraduate students from McGill, Concordia, Université de Montréal and UQAM. Dispositional Worldview was scored on the Dispositionist Worldview Questionnaire. After reading the Rape Scenarios, each student was asked to play the role of a juror and answer a questionnaire consisting of 7 questions about the responsibility, causality and fault of the victim. Results The results confirm the hypothesis which states that if a juror has a dispositionist worldview then he or she will blame the rape victim for triggering the assault. By doing so, the juror commits the fundamental attribution error because he will believe that the victim’s disposition, and not the constraints or opportunities of the situation, caused the rape scenario.

Keywords: bias, expert/witness testimony, attribution error, jury, rape myth

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1322 Effects of Various Wavelet Transforms in Dynamic Analysis of Structures

Authors: Seyed Sadegh Naseralavi, Sadegh Balaghi, Ehsan Khojastehfar

Abstract:

Time history dynamic analysis of structures is considered as an exact method while being computationally intensive. Filtration of earthquake strong ground motions applying wavelet transform is an approach towards reduction of computational efforts, particularly in optimization of structures against seismic effects. Wavelet transforms are categorized into continuum and discrete transforms. Since earthquake strong ground motion is a discrete function, the discrete wavelet transform is applied in the present paper. Wavelet transform reduces analysis time by filtration of non-effective frequencies of strong ground motion. Filtration process may be repeated several times while the approximation induces more errors. In this paper, strong ground motion of earthquake has been filtered once applying each wavelet. Strong ground motion of Northridge earthquake is filtered applying various wavelets and dynamic analysis of sampled shear and moment frames is implemented. The error, regarding application of each wavelet, is computed based on comparison of dynamic response of sampled structures with exact responses. Exact responses are computed by dynamic analysis of structures applying non-filtered strong ground motion.

Keywords: Wavelet transform, computational error, computational duration, strong ground motion data.

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1321 Proposal of Optimality Evaluation for Quantum Secure Communication Protocols by Taking the Average of the Main Protocol Parameters: Efficiency, Security and Practicality

Authors: Georgi Bebrov, Rozalina Dimova

Abstract:

In the field of quantum secure communication, there is no evaluation that characterizes quantum secure communication (QSC) protocols in a complete, general manner. The current paper addresses the problem concerning the lack of such an evaluation for QSC protocols by introducing an optimality evaluation, which is expressed as the average over the three main parameters of QSC protocols: efficiency, security, and practicality. For the efficiency evaluation, the common expression of this parameter is used, which incorporates all the classical and quantum resources (bits and qubits) utilized for transferring a certain amount of information (bits) in a secure manner. By using criteria approach whether or not certain criteria are met, an expression for the practicality evaluation is presented, which accounts for the complexity of the QSC practical realization. Based on the error rates that the common quantum attacks (Measurement and resend, Intercept and resend, probe attack, and entanglement swapping attack) induce, the security evaluation for a QSC protocol is proposed as the minimum function taken over the error rates of the mentioned quantum attacks. For the sake of clarity, an example is presented in order to show how the optimality is calculated.

Keywords: Quantum cryptography, quantum secure communcation, quantum secure direct communcation security, quantum secure direct communcation efficiency, quantum secure direct communcation practicality.

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1320 Suppression of Narrowband Interference in Impulse Radio Based High Data Rate UWB WPAN Communication System Using NLOS Channel Model

Authors: Bikramaditya Das, Susmita Das

Abstract:

Study on suppression of interference in time domain equalizers is attempted for high data rate impulse radio (IR) ultra wideband communication system. The narrow band systems may cause interference with UWB devices as it is having very low transmission power and the large bandwidth. SRAKE receiver improves system performance by equalizing signals from different paths. This enables the use of SRAKE receiver techniques in IRUWB systems. But Rake receiver alone fails to suppress narrowband interference (NBI). A hybrid SRake-MMSE time domain equalizer is proposed to overcome this by taking into account both the effect of the number of rake fingers and equalizer taps. It also combats intersymbol interference. A semi analytical approach and Monte-Carlo simulation are used to investigate the BER performance of SRAKEMMSE receiver on IEEE 802.15.3a UWB channel models. Study on non-line of sight indoor channel models (both CM3 and CM4) illustrates that bit error rate performance of SRake-MMSE receiver with NBI performs better than that of Rake receiver without NBI. We show that for a MMSE equalizer operating at high SNR-s the number of equalizer taps plays a more significant role in suppressing interference.

Keywords: IR-UWB, UWB, IEEE 802.15.3a, NBI, data rate, bit error rate.

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1319 Pectoral Muscles Suppression in Digital Mammograms Using Hybridization of Soft Computing Methods

Authors: I. Laurence Aroquiaraj, K. Thangavel

Abstract:

Breast region segmentation is an essential prerequisite in computerized analysis of mammograms. It aims at separating the breast tissue from the background of the mammogram and it includes two independent segmentations. The first segments the background region which usually contains annotations, labels and frames from the whole breast region, while the second removes the pectoral muscle portion (present in Medio Lateral Oblique (MLO) views) from the rest of the breast tissue. In this paper we propose hybridization of Connected Component Labeling (CCL), Fuzzy, and Straight line methods. Our proposed methods worked good for separating pectoral region. After removal pectoral muscle from the mammogram, further processing is confined to the breast region alone. To demonstrate the validity of our segmentation algorithm, it is extensively tested using over 322 mammographic images from the Mammographic Image Analysis Society (MIAS) database. The segmentation results were evaluated using a Mean Absolute Error (MAE), Hausdroff Distance (HD), Probabilistic Rand Index (PRI), Local Consistency Error (LCE) and Tanimoto Coefficient (TC). The hybridization of fuzzy with straight line method is given more than 96% of the curve segmentations to be adequate or better. In addition a comparison with similar approaches from the state of the art has been given, obtaining slightly improved results. Experimental results demonstrate the effectiveness of the proposed approach.

Keywords: X-ray Mammography, CCL, Fuzzy, Straight line.

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1318 Design of an Intelligent Location Identification Scheme Based On LANDMARC and BPNs

Authors: S. Chaisit, H.Y. Kung, N.T. Phuong

Abstract:

Radio frequency identification (RFID) applications have grown rapidly in many industries, especially in indoor location identification. The advantage of using received signal strength indicator (RSSI) values as an indoor location measurement method is a cost-effective approach without installing extra hardware. Because the accuracy of many positioning schemes using RSSI values is limited by interference factors and the environment, thus it is challenging to use RFID location techniques based on integrating positioning algorithm design. This study proposes the location estimation approach and analyzes a scheme relying on RSSI values to minimize location errors. In addition, this paper examines different factors that affect location accuracy by integrating the backpropagation neural network (BPN) with the LANDMARC algorithm in a training phase and an online phase. First, the training phase computes coordinates obtained from the LANDMARC algorithm, which uses RSSI values and the real coordinates of reference tags as training data for constructing an appropriate BPN architecture and training length. Second, in the online phase, the LANDMARC algorithm calculates the coordinates of tracking tags, which are then used as BPN inputs to obtain location estimates. The results show that the proposed scheme can estimate locations more accurately compared to LANDMARC without extra devices.

Keywords: BPNs, indoor location, location estimation, intelligent location identification.

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1317 Digital Twin of Real Electrical Distribution System with Real Time Recursive Load Flow Calculation and State Estimation

Authors: Anosh Arshad Sundhu, Francesco Giordano, Giacomo Della Croce, Maurizio Arnone

Abstract:

Digital Twin (DT) is a technology that generates a virtual representation of a physical system or process, enabling real-time monitoring, analysis, and simulation. DT of an Electrical Distribution System (EDS) can perform online analysis by integrating the static and real-time data in order to show the current grid status and predictions about the future status to the Distribution System Operator (DSO), producers and consumers. DT technology for EDS also offers the opportunity to DSO to test hypothetical scenarios. This paper discusses the development of a DT of an EDS by Smart Grid Controller (SGC) application, which is developed using open-source libraries and languages. The developed application can be integrated with Supervisory Control and Data Acquisition System (SCADA) of any EDS for creating the DT. The paper shows the performance of developed tools inside the application, tested on real EDS for grid observability, Smart Recursive Load Flow (SRLF) calculation and state estimation of loads in MV feeders.

Keywords: Digital Twin, Distribution System Operator, Electrical Distribution System, Smart Grid Controller, Supervisory Control and Data Acquisition System, Smart Recursive Load Flow.

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1316 Emergency Generator Sizing and Motor Starting Analysis

Authors: Mukesh Kumar Kirar, Ganga Agnihotri

Abstract:

This paper investigates the preliminary sizing of generator set to design electrical system at the early phase of a project, dynamic behavior of generator-unit, as well as induction motors, during start-up of the induction motor drives fed from emergency generator unit. The information in this paper simplifies generator set selection and eliminates common errors in selection. It covers load estimation, step loading capacity test, transient analysis for the emergency generator set. The dynamic behavior of the generator-unit, power, power factor, voltage, during Direct-on-Line start-up of the induction motor drives fed from stand alone gene-set is also discussed. It is important to ensure that plant generators operate safely and consistently, power system studies are required at the planning and conceptual design stage of the project. The most widely recognized and studied effect of motor starting is the voltage dip that is experienced throughout an industrial power system as the direct online result of starting large motors. Generator step loading capability and transient voltage dip during starting of largest motor is ensured with the help of Electrical Transient Analyzer Program (ETAP).

Keywords: Sizing, induction motor starting, load estimation, Transient Analyzer Program (ETAP).

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1315 Measurement of Real Time Drive Cycle for Indian Roads and Estimation of Component Sizing for HEV using LABVIEW

Authors: Varsha Shah, Patel Pritesh, Patel Sagar, PrasantaKundu, RanjanMaheshwari

Abstract:

Performance of vehicle depends on driving patterns and vehicle drive train configuration. Driving patterns depends on traffic condition, road condition and driver behavior. HEV design is carried out under certain constrain like vehicle operating range, acceleration, decelerations, maximum speed and road grades which are directly related to the driving patterns. Therefore the detailed study on HEV performance over a different drive cycle is required for selection and sizing of HEV components. A simple hardware is design to measured velocity v/s time profile of the vehicle by operating vehicle on Indian roads under real traffic conditions. To size the HEV components, a detailed dynamic model of the vehicle is developed considering the effect of inertia of rotating components like wheels, drive chain, engine and electric motor. Using vehicle model and different Indian drive cycles data, total tractive power demanded by vehicle and power supplied by individual components has been calculated.Using above information selection and estimation of component sizing for HEV is carried out so that HEV performs efficiently under hostile driving condition. Complete analysis is carried out in LABVIEW.

Keywords: BLDC motor, Driving cycle, LABVIEW Ultracapacitors, Vehicle Dynamics,

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1314 The Non-Stationary BINARMA(1,1) Process with Poisson Innovations: An Application on Accident Data

Authors: Y. Sunecher, N. Mamode Khan, V. Jowaheer

Abstract:

This paper considers the modelling of a non-stationary bivariate integer-valued autoregressive moving average of order one (BINARMA(1,1)) with correlated Poisson innovations. The BINARMA(1,1) model is specified using the binomial thinning operator and by assuming that the cross-correlation between the two series is induced by the innovation terms only. Based on these assumptions, the non-stationary marginal and joint moments of the BINARMA(1,1) are derived iteratively by using some initial stationary moments. As regards to the estimation of parameters of the proposed model, the conditional maximum likelihood (CML) estimation method is derived based on thinning and convolution properties. The forecasting equations of the BINARMA(1,1) model are also derived. A simulation study is also proposed where BINARMA(1,1) count data are generated using a multivariate Poisson R code for the innovation terms. The performance of the BINARMA(1,1) model is then assessed through a simulation experiment and the mean estimates of the model parameters obtained are all efficient, based on their standard errors. The proposed model is then used to analyse a real-life accident data on the motorway in Mauritius, based on some covariates: policemen, daily patrol, speed cameras, traffic lights and roundabouts. The BINARMA(1,1) model is applied on the accident data and the CML estimates clearly indicate a significant impact of the covariates on the number of accidents on the motorway in Mauritius. The forecasting equations also provide reliable one-step ahead forecasts.

Keywords: Non-stationary, BINARMA(1, 1) model, Poisson Innovations, CML

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1313 Low Value Capacitance Measurement System with Adjustable Lead Capacitance Compensation

Authors: Gautam Sarkar, Anjan Rakshit, Amitava Chatterjee, Kesab Bhattacharya

Abstract:

The present paper describes the development of a low cost, highly accurate low capacitance measurement system that can be used over a range of 0 – 400 pF with a resolution of 1 pF. The range of capacitance may be easily altered by a simple resistance or capacitance variation of the measurement circuit. This capacitance measurement system uses quad two-input NAND Schmitt trigger circuit CD4093B with hysteresis for the measurement and this system is integrated with PIC 18F2550 microcontroller for data acquisition purpose. The microcontroller interacts with software developed in the PC end through USB architecture and an attractive graphical user interface (GUI) based system is developed in the PC end to provide the user with real time, online display of capacitance under measurement. The system uses a differential mode of capacitance measurement, with reference to a trimmer capacitance, that effectively compensates lead capacitances, a notorious error encountered in usual low capacitance measurements. The hysteresis provided in the Schmitt-trigger circuits enable reliable operation of the system by greatly minimizing the possibility of false triggering because of stray interferences, usually regarded as another source of significant error. The real life testing of the proposed system showed that our measurements could produce highly accurate capacitance measurements, when compared to cutting edge, high end digital capacitance meters.

Keywords: Capacitance measurement, NAND Schmitt trigger, microcontroller, GUI, lead compensation, hysteresis.

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1312 A Combined Conventional and Differential Evolution Method for Model Order Reduction

Authors: J. S. Yadav, N. P. Patidar, J. Singhai, S. Panda, C. Ardil

Abstract:

In this paper a mixed method by combining an evolutionary and a conventional technique is proposed for reduction of Single Input Single Output (SISO) continuous systems into Reduced Order Model (ROM). In the conventional technique, the mixed advantages of Mihailov stability criterion and continued Fraction Expansions (CFE) technique is employed where the reduced denominator polynomial is derived using Mihailov stability criterion and the numerator is obtained by matching the quotients of the Cauer second form of Continued fraction expansions. Then, retaining the numerator polynomial, the denominator polynomial is recalculated by an evolutionary technique. In the evolutionary method, the recently proposed Differential Evolution (DE) optimization technique is employed. DE method is based on the minimization of the Integral Squared Error (ISE) between the transient responses of original higher order model and the reduced order model pertaining to a unit step input. The proposed method is illustrated through a numerical example and compared with ROM where both numerator and denominator polynomials are obtained by conventional method to show its superiority.

Keywords: Reduced Order Modeling, Stability, Mihailov Stability Criterion, Continued Fraction Expansions, Differential Evolution, Integral Squared Error.

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1311 Specification Requirements for a Combined Dehumidifier/Cooling Panel: A Global Scale Analysis

Authors: Damien Gondre, Hatem Ben Maad, Abdelkrim Trabelsi, Frédéric Kuznik, Joseph Virgone

Abstract:

The use of a radiant cooling solution would enable to lower cooling needs which is of great interest when the demand is initially high (hot climate). But, radiant systems are not naturally compatibles with humid climates since a low-temperature surface leads to condensation risks as soon as the surface temperature is close to or lower than the dew point temperature. A radiant cooling system combined to a dehumidification system would enable to remove humidity for the space, thereby lowering the dew point temperature. The humidity removal needs to be especially effective near the cooled surface. This requirement could be fulfilled by a system using a single desiccant fluid for the removal of both excessive heat and moisture. This task aims at providing an estimation of the specification requirements of such system in terms of cooling power and dehumidification rate required to fulfill comfort issues and to prevent any condensation risk on the cool panel surface. The present paper develops a preliminary study on the specification requirements, performances and behavior of a combined dehumidifier/cooling ceiling panel for different operating conditions. This study has been carried using the TRNSYS software which allows nodal calculations of thermal systems. It consists of the dynamic modeling of heat and vapor balances of a 5m x 3m x 2.7m office space. In a first design estimation, this room is equipped with an ideal heating, cooling, humidification and dehumidification system so that the room temperature is always maintained in between 21C and 25C with a relative humidity in between 40% and 60%. The room is also equipped with a ventilation system that includes a heat recovery heat exchanger and another heat exchanger connected to a heat sink. Main results show that the system should be designed to meet a cooling power of 42W.m−2 and a desiccant rate of 45 gH2O.h−1. In a second time, a parametric study of comfort issues and system performances has been achieved on a more realistic system (that includes a chilled ceiling) under different operating conditions. It enables an estimation of an acceptable range of operating conditions. This preliminary study is intended to provide useful information for the system design.

Keywords: Dehumidification, nodal calculation, radiant cooling panel, system sizing.

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1310 A Rule-based Approach for Anomaly Detection in Subscriber Usage Pattern

Authors: Rupesh K. Gopal, Saroj K. Meher

Abstract:

In this report we present a rule-based approach to detect anomalous telephone calls. The method described here uses subscriber usage CDR (call detail record) data sampled over two observation periods: study period and test period. The study period contains call records of customers- non-anomalous behaviour. Customers are first grouped according to their similar usage behaviour (like, average number of local calls per week, etc). For customers in each group, we develop a probabilistic model to describe their usage. Next, we use maximum likelihood estimation (MLE) to estimate the parameters of the calling behaviour. Then we determine thresholds by calculating acceptable change within a group. MLE is used on the data in the test period to estimate the parameters of the calling behaviour. These parameters are compared against thresholds. Any deviation beyond the threshold is used to raise an alarm. This method has the advantage of identifying local anomalies as compared to techniques which identify global anomalies. The method is tested for 90 days of study data and 10 days of test data of telecom customers. For medium to large deviations in the data in test window, the method is able to identify 90% of anomalous usage with less than 1% false alarm rate.

Keywords: Subscription fraud, fraud detection, anomalydetection, maximum likelihood estimation, rule based systems.

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1309 Application of KL Divergence for Estimation of Each Metabolic Pathway Genes

Authors: Shohei Maruyama, Yasuo Matsuyama, Sachiyo Aburatani

Abstract:

Development of a method to estimate gene functions is an important task in bioinformatics. One of the approaches for the annotation is the identification of the metabolic pathway that genes are involved in. Since gene expression data reflect various intracellular phenomena, those data are considered to be related with genes’ functions. However, it has been difficult to estimate the gene function with high accuracy. It is considered that the low accuracy of the estimation is caused by the difficulty of accurately measuring a gene expression. Even though they are measured under the same condition, the gene expressions will vary usually. In this study, we proposed a feature extraction method focusing on the variability of gene expressions to estimate the genes' metabolic pathway accurately. First, we estimated the distribution of each gene expression from replicate data. Next, we calculated the similarity between all gene pairs by KL divergence, which is a method for calculating the similarity between distributions. Finally, we utilized the similarity vectors as feature vectors and trained the multiclass SVM for identifying the genes' metabolic pathway. To evaluate our developed method, we applied the method to budding yeast and trained the multiclass SVM for identifying the seven metabolic pathways. As a result, the accuracy that calculated by our developed method was higher than the one that calculated from the raw gene expression data. Thus, our developed method combined with KL divergence is useful for identifying the genes' metabolic pathway.

Keywords: Metabolic pathways, gene expression data, microarray, Kullback–Leibler divergence, KL divergence, support vector machines, SVM, machine learning.

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1308 Modeling and Experimental Studies on Solar Crop Dryer Coupled with Reversed Absorber Type Solar Air Heater

Authors: Vijay R. Khawale, Shashank B. Thakare

Abstract:

The experiment was carried out to study the performance of solar crop dryer coupled with reversed absorber type solar air heater (SD2). Excel software is used to analyse the raw data obtained from the drying experiment to develop a model. An attempt is made in this paper to correlate the collector efficiency, dryer efficiency and pick-up efficiency. All these efficiencies are dependent on the parameters such as solar flux, ambient temperature, collector outlet temperature and moisture content. The simulation equation was developed to predict the values of collector efficiency. The parameters a, n and drying constant k were determined from a plot of curve using a drying models. Experimental data of drying red chili in conventional solar dryer and solar dryer coupled with reversed absorber solar air heater was compared by fitting with three drying models. The moisture content will be rapidly reduced in solar dryer with reversed absorber due to higher drying temperatures. The best fit model was selected to describe the drying behavior of red chili. For SD2 the values of the coefficient of determination (R2=0.997), mean bias error (MBE=0.00026) and root mean square error (RMSE=0.016) were used to determine the goodness or the quality of the fit. Pages model showed a better fit to drying red chili among Newton model and Henderson & Pabis model.

Keywords: Solar dryer, red chili, reversed absorber, reflector, Buckingham pi theorem, drying model.

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1307 Rapid Determination of Biochemical Oxygen Demand

Authors: Mayur Milan Kale, Indu Mehrotra

Abstract:

Biochemical Oxygen Demand (BOD) is a measure of the oxygen used in bacteria mediated oxidation of organic substances in water and wastewater. Theoretically an infinite time is required for complete biochemical oxidation of organic matter, but the measurement is made over 5-days at 20 0C or 3-days at 27 0C test period with or without dilution. Researchers have worked to further reduce the time of measurement. The objective of this paper is to review advancement made in BOD measurement primarily to minimize the time and negate the measurement difficulties. Survey of literature review in four such techniques namely BOD-BARTTM, Biosensors, Ferricyanidemediated approach, luminous bacterial immobilized chip method. Basic principle, method of determination, data validation and their advantage and disadvantages have been incorporated of each of the methods. In the BOD-BARTTM method the time lag is calculated for the system to change from oxidative to reductive state. BIOSENSORS are the biological sensing element with a transducer which produces a signal proportional to the analyte concentration. Microbial species has its metabolic deficiencies. Co-immobilization of bacteria using sol-gel biosensor increases the range of substrate. In ferricyanidemediated approach, ferricyanide has been used as e-acceptor instead of oxygen. In Luminous bacterial cells-immobilized chip method, bacterial bioluminescence which is caused by lux genes was observed. Physiological responses is measured and correlated to BOD due to reduction or emission. There is a scope to further probe into the rapid estimation of BOD.

Keywords: BOD, Four methods, Rapid estimation

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1306 Video Matting based on Background Estimation

Authors: J.-H. Moon, D.-O Kim, R.-H. Park

Abstract:

This paper presents a video matting method, which extracts the foreground and alpha matte from a video sequence. The objective of video matting is finding the foreground and compositing it with the background that is different from the one in the original image. By finding the motion vectors (MVs) using a sliced block matching algorithm (SBMA), we can extract moving regions from the video sequence under the assumption that the foreground is moving and the background is stationary. In practice, foreground areas are not moving through all frames in an image sequence, thus we accumulate moving regions through the image sequence. The boundaries of moving regions are found by Canny edge detector and the foreground region is separated in each frame of the sequence. Remaining regions are defined as background regions. Extracted backgrounds in each frame are combined and reframed as an integrated single background. Based on the estimated background, we compute the frame difference (FD) of each frame. Regions with the FD larger than the threshold are defined as foreground regions, boundaries of foreground regions are defined as unknown regions and the rest of regions are defined as backgrounds. Segmentation information that classifies an image into foreground, background, and unknown regions is called a trimap. Matting process can extract an alpha matte in the unknown region using pixel information in foreground and background regions, and estimate the values of foreground and background pixels in unknown regions. The proposed video matting approach is adaptive and convenient to extract a foreground automatically and to composite a foreground with a background that is different from the original background.

Keywords: Background estimation, Object segmentation, Blockmatching algorithm, Video matting.

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1305 Development of EPID-based Real time Dose Verification for Dynamic IMRT

Authors: Todsaporn Fuangrod, Daryl J. O'Connor, Boyd MC McCurdy, Peter B. Greer

Abstract:

An electronic portal image device (EPID) has become a method of patient-specific IMRT dose verification for radiotherapy. Research studies have focused on pre and post-treatment verification, however, there are currently no interventional procedures using EPID dosimetry that measure the dose in real time as a mechanism to ensure that overdoses do not occur and underdoses are detected as soon as is practically possible. As a result, an EPID-based real time dose verification system for dynamic IMRT was developed and was implemented with MATLAB/Simulink. The EPID image acquisition was set to continuous acquisition mode at 1.4 images per second. The system defined the time constraint gap, or execution gap at the image acquisition time, so that every calculation must be completed before the next image capture is completed. In addition, the <=-evaluation method was used for dose comparison, with two types of comparison processes; individual image and cumulative dose comparison monitored. The outputs of the system are the <=-map, the percent of <=<1, and mean-<= versus time, all in real time. Two strategies were used to test the system, including an error detection test and a clinical data test. The system can monitor the actual dose delivery compared with the treatment plan data or previous treatment dose delivery that means a radiation therapist is able to switch off the machine when the error is detected.

Keywords: real-time dose verification, EPID dosimetry, simulation, dynamic IMRT

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1304 Movie Genre Preference Prediction Using Machine Learning for Customer-Based Information

Authors: Haifeng Wang, Haili Zhang

Abstract:

Most movie recommendation systems have been developed for customers to find items of interest. This work introduces a predictive model usable by small and medium-sized enterprises (SMEs) who are in need of a data-based and analytical approach to stock proper movies for local audiences and retain more customers. We used classification models to extract features from thousands of customers’ demographic, behavioral and social information to predict their movie genre preference. In the implementation, a Gaussian kernel support vector machine (SVM) classification model and a logistic regression model were established to extract features from sample data and their test error-in-sample were compared. Comparison of error-out-sample was also made under different Vapnik–Chervonenkis (VC) dimensions in the machine learning algorithm to find and prevent overfitting. Gaussian kernel SVM prediction model can correctly predict movie genre preferences in 85% of positive cases. The accuracy of the algorithm increased to 93% with a smaller VC dimension and less overfitting. These findings advance our understanding of how to use machine learning approach to predict customers’ preferences with a small data set and design prediction tools for these enterprises.

Keywords: Computational social science, movie preference, machine learning, SVM.

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1303 Construction of Attitude Reference Benchmark for Test of Star Sensor Based on Precise Timing

Authors: Tingting Lu, Yonghai Wang, Haiyong Wang, Jiaqi Liu

Abstract:

To satisfy the need of outfield tests of star sensors, a method is put forward to construct the reference attitude benchmark. Firstly, its basic principle is introduced; Then, all the separate conversion matrixes are deduced, which include: the conversion matrix responsible for the transformation from the Earth Centered Inertial frame i to the Earth-centered Earth-fixed frame w according to the time of an atomic clock, the conversion matrix from frame w to the geographic frame t, and the matrix from frame t to the platform frame p, so the attitude matrix of the benchmark platform relative to the frame i can be obtained using all the three matrixes as the multiplicative factors; Next, the attitude matrix of the star sensor relative to frame i is got when the mounting matrix from frame p to the star sensor frame s is calibrated, and the reference attitude angles for star sensor outfield tests can be calculated from the transformation from frame i to frame s; Finally, the computer program is finished to solve the reference attitudes, and the error curves are drawn about the three axis attitude angles whose absolute maximum error is just 0.25ÔÇ│. The analysis on each loop and the final simulating results manifest that the method by precise timing to acquire the absolute reference attitude is feasible for star sensor outfield tests.

Keywords: Atomic time, attitude determination, coordinate conversion, inertial coordinate system, star sensor.

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1302 Air Quality Forecast Based on Principal Component Analysis-Genetic Algorithm and Back Propagation Model

Authors: Bin Mu, Site Li, Shijin Yuan

Abstract:

Under the circumstance of environment deterioration, people are increasingly concerned about the quality of the environment, especially air quality. As a result, it is of great value to give accurate and timely forecast of AQI (air quality index). In order to simplify influencing factors of air quality in a city, and forecast the city’s AQI tomorrow, this study used MATLAB software and adopted the method of constructing a mathematic model of PCA-GABP to provide a solution. To be specific, this study firstly made principal component analysis (PCA) of influencing factors of AQI tomorrow including aspects of weather, industry waste gas and IAQI data today. Then, we used the back propagation neural network model (BP), which is optimized by genetic algorithm (GA), to give forecast of AQI tomorrow. In order to verify validity and accuracy of PCA-GABP model’s forecast capability. The study uses two statistical indices to evaluate AQI forecast results (normalized mean square error and fractional bias). Eventually, this study reduces mean square error by optimizing individual gene structure in genetic algorithm and adjusting the parameters of back propagation model. To conclude, the performance of the model to forecast AQI is comparatively convincing and the model is expected to take positive effect in AQI forecast in the future.

Keywords: AQI forecast, principal component analysis, genetic algorithm, back propagation neural network model.

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