Search results for: radial installation limit error

Authors: Mohammad Javadi

Abstract:

Serial hierarchical support vector machine (SHSVM) is proposed to discriminate three brain tissues which are white matter (WM), gray matter (GM), and cerebrospinal fluid (CSF). SHSVM has novel classification approach by repeating the hierarchical classification on data set iteratively. It used Radial Basis Function (rbf) Kernel with different tuning to obtain accurate results. Also as the second approach, segmentation performed with DAGSVM method. In this article eight univariate features from the raw DTI data are extracted and all the possible 2D feature sets are examined within the segmentation process. SHSVM succeed to obtain DSI values higher than 0.95 accuracy for all the three tissues, which are higher than DAGSVM results.

Keywords: Brain segmentation, DTI, hierarchical, SVM.

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Authors: R. S. Al Abri, M. H. Albadi, M. H. Al Abri, U. K. Al Rasbi, M. H. Al Hasni, S. M. Al Shidi

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This paper presents an analysis study on the impacts of the changes of the capacitor banks, the loss of a transformer, and the installation of distributed generation on the voltage total harmonic distortion and harmonic resonance. The study is applied in a real system in Oman, Sohar Industrial Port–C Substation Network. Frequency scan method and Fourier series analysis method are used with the help of EDSA software. Moreover, the results are compared with limits specified by national Oman distribution code.

Keywords: Power quality, capacitor bank, voltage total harmonics distortion, harmonic resonance, frequency scan.

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

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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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Authors: Ana Pauna

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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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Authors: Chime Charles C., Ikechukwu Alexander Okorie, Ekanem E.J., Kagbu J. A.

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The assessment of surface waters in Enugu metropolis for fecal coliform bacteria was undertaken. Enugu urban was divided into three areas (A1, A2 and A3), and fecal coliform bacteria analysed in the surface waters found in these areas for four years (2005-2008). The plate count method was used for the analyses. Data generated were subjected to statistical tests involving; Normality test, Homogeneity of variance test, correlation test, and tolerance limit test. The influence of seasonality and pollution trends were investigated using time series plots. Results from the tolerance limit test at 95% coverage with 95% confidence, and with respect to EU maximum permissible concentration show that the three areas suffer from fecal coliform pollution. To this end, remediation procedure involving the use of saw-dust extracts from three woods namely; Chlorophora-Excelsa (C-Excelsa),Khayan-Senegalensis,(CSenegalensis) and Erythrophylum-Ivorensis (E-Ivorensis) in controlling the coliforms was studied. Results show that mixture of the acetone extracts of the woods show the most effective antibacterial inhibitory activities (26.00mm zone of inhibition) against E-coli. Methanol extract mixture of the three woods gave best inhibitory activity (26.00mm zone of inhibition) against S-areus, and 25.00mm zones of inhibition against E-Aerogenes. The aqueous extracts mixture gave acceptable zones of inhibitions against the three bacteria organisms.

Keywords: Coliform bacteria, Pollution, Remediation, Saw-dust

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Authors: Seyed Sadegh Naseralavi, Sadegh Balaghi, Ehsan Khojastehfar

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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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Authors: I. A. Farhat

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The problem of optimal planning of multiple sources of distributed generation (DG) in distribution networks is treated in this paper using an improved Ant Colony Optimization algorithm (ACO). This objective of this problem is to determine the DG optimal size and location that in order to minimize the network real power losses. Considering the multiple sources of DG, both size and location are simultaneously optimized in a single run of the proposed ACO algorithm. The various practical constraints of the problem are taken into consideration by the problem formulation and the algorithm implementation. A radial power flow algorithm for distribution networks is adopted and applied to satisfy these constraints. To validate the proposed technique and demonstrate its effectiveness, the well-know 69-bus feeder standard test system is employed.cm.

Keywords: About Ant Colony Optimization (ACO), Distributed Generation (DG).

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Authors: Georgi Bebrov, Rozalina Dimova

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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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Authors: M. Jagabar Sathik, K. Ramani

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In this paper family of multilevel inverter topology with reduced number of power switches is presented. The proposed inverter can generate both even and odd level. The proposed topology is suitable for symmetric structure. The proposed symmetric inverter results in reduction of power switches, power diode and gate driver circuits and also it may further minimize the installation area and cost. To prove the superiority of proposed topology is compared with conventional topologies. The performance of this symmetric multilevel inverter has been tested by computer based simulation and prototype based experimental setup for nine-level inverter is developed and results are verified.

Keywords: Cascaded H- Bridge (CHB), Multilevel Inverter (MLI), Nearest Level Modulation (NLM), Total Harmonic Distortion (THD).

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Authors: Bikramaditya Das, Susmita Das

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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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Authors: N. R. Harris, J. Curry

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This paper describes the construction and operation of an experimental LoRaWAN network surrounding the University of Southampton in the United Kingdom. Following successful installation, an experimental node design is built and characterised, with particular emphasis on radio range. Several configurations are investigated, including different data rates, and varying heights of node. It is concluded that although range can be great (over 8 km in this case), environmental topology is critical. However, shorter range implementations, up to about 2 km in an urban environment, are relatively insensitive although care is still needed. The example node and the relatively simple base station reported demonstrate that LoraWan can be a very low cost and practical solution to Internet of Things type applications for distributed monitoring systems with sensors spread over distances of several km.

Keywords: Wireless sensor network, LoRa, internet of things, propagation.

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Authors: I. Laurence Aroquiaraj, K. Thangavel

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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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Authors: A. S. Gorobtsov, A. S. Polyanina, A. E. Andreev

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The movement of points feet of the anthropomorphous robot in space occurs along some stable trajectory of a known form. A large number of modifications to the methods of control of biped robots indicate the fundamental complexity of the problem of stability of the program trajectory and, consequently, the stability of the control for the deviation for this trajectory. Existing gait generators use piecewise interpolation of program trajectories. This leads to jumps in the acceleration at the boundaries of sites. Another interpolation can be realized using differential equations with fractional derivatives. In work, the approach to synthesis of generators of program trajectories is considered. The resulting system of nonlinear differential equations describes a smooth trajectory of movement having rectilinear sites. The method is based on the theory of an asymptotic stability of invariant sets. The stability of such systems in the area of localization of oscillatory processes is investigated. The boundary of the area is a bounded closed surface. In the corresponding subspaces of the oscillatory circuits, the resulting stable limit cycles are curves having rectilinear sites. The solution of the problem is carried out by means of synthesis of a set of the continuous smooth controls with feedback. The necessary geometry of closed trajectories of movement is obtained due to the introduction of high-order nonlinearities in the control of stabilization systems. The offered method was used for the generation of trajectories of movement of point’s feet of the anthropomorphous robot. The synthesis of the robot's program movement was carried out by means of the inverse method.

Keywords: Control, limits cycle, robot, stability.

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Authors: Amir Atrian, Javad Jafari Fesharaki, Gh. Hossein Majzoobi, Mahsa Sheidaee

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The analytical solution of functionally graded piezoelectric hollow cylinder which is under radial electric potential and non-axisymmetric thermo-mechanical loads, are presented in this paper. Using complex Fourier series and estimation of power law for variations of material characterizations through the thickness, the electro thermo mechanical behavior of the FGPM cylinder is obtained. The stress and displacement distributions and the effect of electric potential field on the cylinder behavior are also presented and some applicable results are offered at the end of the paper.

Keywords: Analytical, FGM, Fourier series, Non-axisymmetric, Piezoelectric, Thermo-elasticity

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

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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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Authors: Won-Sub Lee, Sung-Gaun Kim

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Rotational Smart Lighting Control System can supply the quantity of lighting which is required to run plants by rotating few LED and Fluorescent instead of that are used in the existing plant factories.The initial installation of the existing plants factory is expensive, so in order to solve the problem with smart lighting control system was developed. The beam required intensity for the growth of crops, Photosynthetic Photon Flux Density(PPFD)is calculated; and the number of LED, are installed on the blades, set; using the Lighting Simulation Program.Relux, it is able to confirm that the difference of the beam intensity between the center and the outer of lighting system when the lighting device is rotating.

Keywords: Plant Factory, Lighting Control System, Rotational Lighting System, Lighting Equipment

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Authors: Fazıl Gökgöz, Fahrettin Filiz

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Load forecasting has become crucial in recent years and become popular in forecasting area. Many different power forecasting models have been tried out for this purpose. Electricity load forecasting is necessary for energy policies, healthy and reliable grid systems. Effective power forecasting of renewable energy load leads the decision makers to minimize the costs of electric utilities and power plants. Forecasting tools are required that can be used to predict how much renewable energy can be utilized. The purpose of this study is to explore the effectiveness of LSTM-based neural networks for estimating renewable energy loads. In this study, we present models for predicting renewable energy loads based on deep neural networks, especially the Long Term Memory (LSTM) algorithms. Deep learning allows multiple layers of models to learn representation of data. LSTM algorithms are able to store information for long periods of time. Deep learning models have recently been used to forecast the renewable energy sources such as predicting wind and solar energy power. Historical load and weather information represent the most important variables for the inputs within the power forecasting models. The dataset contained power consumption measurements are gathered between January 2016 and December 2017 with one-hour resolution. Models use publicly available data from the Turkish Renewable Energy Resources Support Mechanism. Forecasting studies have been carried out with these data via deep neural networks approach including LSTM technique for Turkish electricity markets. 432 different models are created by changing layers cell count and dropout. The adaptive moment estimation (ADAM) algorithm is used for training as a gradient-based optimizer instead of SGD (stochastic gradient). ADAM performed better than SGD in terms of faster convergence and lower error rates. Models performance is compared according to MAE (Mean Absolute Error) and MSE (Mean Squared Error). Best five MAE results out of 432 tested models are 0.66, 0.74, 0.85 and 1.09. The forecasting performance of the proposed LSTM models gives successful results compared to literature searches.

Keywords: Deep learning, long-short-term memory, energy, renewable energy load forecasting.

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Authors: I. Razmi, N. Choupani

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The incidence of mechanical fracture of an automobile piston rings prompted development of fracture analysis method on this case. The three rings (two compression rings and one oil ring) were smashed into several parts during the power-test (after manufacturing the engine) causing piston and liner to be damaged. The radial and oblique cracking happened on the failed piston rings. The aim of the fracture mechanics simulations presented in this paper was the calculation of particular effective fracture mechanics parameters, such as J-integrals and stress intensity factors. Crack propagation angles were calculated as well. Two-dimensional fracture analysis of the first compression ring has been developed in this paper using ABAQUS CAE6.5-1 software. Moreover, SEM fractography was developed on fracture surfaces and is discussed in this paper. Results of numerical calculations constitute the basis for further research on real object.

Keywords: Compression piston ring, Crack, Fracture mechanics, SEM fractography.

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Authors: Emad Hazbkhah, Abdolreza Zahiri, Hossein Ghorbanizade Kharazi, Afshin Kiani

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Establishing pumping stations is one of the most common ways of providing water from rivers. There are many issues involved in the design and operation of pumping stations most important of which is the problem of sedimentation. One of the significant issues which must be taken into consideration in designing pumping stations is the operation method and technical matters related to it. Safety and convenience of operation is one of the issues that must be always considered by the designer. Some of the major issues in making decisions regarding the type of design for the station are geographical condition, the location of the station and availability of experts in maintenance and operation of the station. Dimensions of the station must allow free movement for checking and operating pumps after installation of pumps and plumbing system.

Keywords: Boneh Basht, Iran, pumping station.

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Authors: Hou Youfu, Wang Daoming, Meng Qingrui

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To reveal the temperature field distribution of disc brake in downward belt conveyor, mathematical models of heat transfer for disc brake were established combined with heat transfer theory. Then, the simulation process was stated in detail and the temperature field of disc brake under conditions of dynamic speed and dynamic braking torque was numerically simulated by using ANSYS software. Finally the distribution and variation laws of temperature field in the braking process were analyzed. Results indicate that the maximum surface temperature occurs at a time before the brake end and there exist large temperature gradients in both radial and axial directions, while it is relatively small in the circumferential direction.

Keywords: Downward belt conveyor, Disc brake, Temperature field, Numerical simulation.

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

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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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Authors: Yilun Shang

Abstract:

We consider a heterogeneously mixing SIR stochastic epidemic process in populations described by a general graph. Likelihood theory is developed to facilitate statistic inference for the parameters of the model under complete observation. We show that these estimators are asymptotically Gaussian unbiased estimates by using a martingale central limit theorem.

Keywords: statistic inference, maximum likelihood, epidemicmodel, heterogeneous mixing.

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Authors: Toshihiko Matsuka, James E. Corter

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Most neural network (NN) models of human category learning use a gradient-based learning method, which assumes that locally-optimal changes are made to model parameters on each learning trial. This method tends to under predict variability in individual-level cognitive processes. In addition many recent models of human category learning have been criticized for not being able to replicate rapid changes in categorization accuracy and attention processes observed in empirical studies. In this paper we introduce stochastic learning algorithms for NN models of human category learning and show that use of the algorithms can result in (a) rapid changes in accuracy and attention allocation, and (b) different learning trajectories and more realistic variability at the individual-level.

Keywords: category learning, cognitive modeling, radial basis function, stochastic optimization.

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Authors: Hanan Mahmoud Ezzat Mahmoud, Alaa Abd El Fatah Hefnawy

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In this paper, we present a system for content-based retrieval of large database of classified satellite images, based on user's relevance feedback (RF).Through our proposed system, we divide each satellite image scene into small subimages, which stored in the database. The modified radial basis functions neural network has important role in clustering the subimages of database according to the Euclidean distance between the query feature vector and the other subimages feature vectors. The advantage of using RF technique in such queries is demonstrated by analyzing the database retrieval results.

Keywords: content-based image retrieval, large database of image, RBF neural net, relevance feedback

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Authors: M. H. Pour, V. M. Nansa, M. Saberi, A. M. Ghanadi, A. Aghayari, M. Mirzajanzadeh

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Stirred tanks have applications in many chemical processes where mixing is important for the overall performance of the system. In present work 5%v of the tank is filled by solid particles with diameter of 700 m that Rushton Turbine and Propeller impeller is used for stirring. An Eulerian-Eulerian Multi Fluid Model coupled and for modeling rotating of impeller, moving reference frame (MRF) technique was used and standard-k-
model was selected for turbulency. Flow field, radial velocity and axial distribution of solid for both of impellers was investigation and comparison. Comparisons of simulation results between Rushton Turbine and propeller impeller shows that final quality of solid-liquid slurry in different rotating speed for propeller impeller is better than the Rushton Turbine.

Keywords: CFD, Particle Velocity, Propeller Impeller, Rushton Turbine.

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Authors: Vijay R. Khawale, Shashank B. Thakare

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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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Authors: Zhipeng Feng, Huanhuan Qi, Pingchuan Shen, Fenggang Zang, Yixiong Zhang

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Numerical simulations of vortex-induced vibration of a three-dimensional flexible tube under uniform turbulent flow are calculated when Reynolds number is 1.35×10⁴. In order to achieve the vortex-induced vibration, the three-dimensional unsteady, viscous, incompressible Navier-Stokes equation and LES turbulence model are solved with the finite volume approach, the tube is discretized according to the finite element theory, and its dynamic equilibrium equations are solved by the Newmark method. The fluid-tube interaction is realized by utilizing the diffusion-based smooth dynamic mesh method. Considering the vortex-induced vibration system, the variety trends of lift coefficient, drag coefficient, displacement, vertex shedding frequency, phase difference angle of tube are analyzed under different frequency ratios. The nonlinear phenomena of locked-in, phase-switch are captured successfully. Meanwhile, the limit cycle and bifurcation of lift coefficient and displacement are analyzed by using trajectory, phase portrait, and Poincaré sections. The results reveal that: when drag coefficient reaches its minimum value, the transverse amplitude reaches its maximum, and the “lock-in” begins simultaneously. In the range of lock-in, amplitude decreases gradually with increasing of frequency ratio. When lift coefficient reaches its minimum value, the phase difference undergoes a suddenly change from the “out-of-phase” to the “in-phase” mode.

Keywords: Vortex induced vibration, limit cycle, CFD, FEM.

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

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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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Authors: Edward J. Kansa, Pavel Holoborodko

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Continuously differentiable radial basis functions (RBFs) are meshfree, converge faster as the dimensionality increases, and is theoretically spectrally convergent. When implemented on current single and double precision computers, such RBFs can suffer from ill-conditioning because the systems of equations needed to be solved to find the expansion coefficients are full. However, the Advanpix extended precision software package allows computer mathematics to resemble asymptotically ideal Platonic mathematics. Additionally, full systems with extended precision execute faster graphical processors units and field-programmable gate arrays because no branching is needed. Sparse equation systems are fast for iterative solvers in a very limited number of cases.

Keywords: Meshless spectrally convergent, partial differential equations, extended arithmetic precision, no branching.

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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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