Search results for: Iterative learning control

Authors: Salvatore Marra, Francesco C. Morabito

Abstract:

In this paper we present an efficient approach for the prediction of two sunspot-related time series, namely the Yearly Sunspot Number and the IR5 Index, that are commonly used for monitoring solar activity. The method is based on exploiting partially recurrent Elman networks and it can be divided into three main steps: the first one consists in a “de-rectification" of the time series under study in order to obtain a new time series whose appearance, similar to a sum of sinusoids, can be modelled by our neural networks much better than the original dataset. After that, we normalize the derectified data so that they have zero mean and unity standard deviation and, finally, train an Elman network with only one input, a recurrent hidden layer and one output using a back-propagation algorithm with variable learning rate and momentum. The achieved results have shown the efficiency of this approach that, although very simple, can perform better than most of the existing solar activity forecasting methods.

Keywords: Elman neural networks, sunspot, solar activity, time series prediction.

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Authors: D. G. Piliposyan

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Propagation of electro-elastic waves in a piezoelectric waveguide with finite stacks and a defect layer is studied using a modified transfer matrix method. The dispersion equation for a periodic structure consisting of unit cells made up from two piezoelectric materials with metallized interfaces is obtained. An analytical expression, for the transmission coefficient for a waveguide with finite stacks and a defect layer, that is found can be used to accurately detect and control the position of the passband within a stopband. The result can be instrumental in constructing a tunable waveguide made of layers of different or identical piezoelectric crystals and separated by metallized interfaces.

Keywords: Defect mode, Bloch waves, periodic phononic crystal, piezoelectric composite waveguide.

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Authors: Margaret F. Shipley

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Fuzzy logic can be used when knowledge is incomplete or when ambiguity of data exists. The purpose of this paper is to propose a proactive fuzzy set- based model for reacting to the risk inherent in investment activities relative to a complete view of portfolio management. Fuzzy rules are given where, depending on the antecedents, the portfolio size may be slightly or significantly decreased or increased. The decision maker considers acceptable bounds on the proportion of acceptable risk and return. The Fuzzy Controller model allows learning to be achieved as 1) the firing strength of each rule is measured, 2) fuzzy output allows rules to be updated, and 3) new actions are recommended as the system continues to loop. An extension is given to the fuzzy controller that evaluates potential financial loss before adjusting the portfolio. An application is presented that illustrates the algorithm and extension developed in the paper.

Keywords: Portfolio Management, Financial Market Monitoring, Fuzzy Controller, Fuzzy Logic,

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Authors: Frank Emmert Streib, Matthias Dehmer, Gökhan H. Bakır, Max Mühlhauser

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In this paper we investigate the influence of external noise on the inference of network structures. The purpose of our simulations is to gain insights in the experimental design of microarray experiments to infer, e.g., transcription regulatory networks from microarray experiments. Here external noise means, that the dynamics of the system under investigation, e.g., temporal changes of mRNA concentration, is affected by measurement errors. Additionally to external noise another problem occurs in the context of microarray experiments. Practically, it is not possible to monitor the mRNA concentration over an arbitrary long time period as demanded by the statistical methods used to learn the underlying network structure. For this reason, we use only short time series to make our simulations more biologically plausible.

Keywords: Dynamic Bayesian networks, structure learning, gene networks, Markov chain Monte Carlo, microarray data.

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Authors: Song Meng, Dianfu Ma, Yongwang Zhao, Jianxin Li

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Cooperative visual modeling is more and more necessary in our complicated world. A collaborative environment which supports interactive operation and communication is required to increase work efficiency. We present a collaborative visual modeling framework which collaborative platform could be built on. On this platform, cooperation and communication is available for designers from different regions. This framework, which is different from other collaborative frameworks, contains a uniform message format, a message handling mechanism and other functions such as message pretreatment and Role-Communication-Token Access Control (RCTAC). We also show our implementation of this framework called Orchestra Designer, which support BPLE workflow modeling cooperatively online.

Keywords: colllaborative framework; visual modeling; message handling mechanism

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Authors: Lin, Huifen, Fang, Yueh-chiu

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This study explores perceptions of English as a Foreign Language (EFL) learners on using computer mediated communication technology in their learner of English. The data consists of observations of both synchronous and asynchronous communication participants engaged in for over a period of 4 months, which included online, and offline communication protocols, open-ended interviews and reflection papers composed by participants. Content analysis of interview data and the written documents listed above, as well as, member check and triangulation techniques are the major data analysis strategies. The findings suggest that participants generally do not benefit from computer-mediated communication in terms of its effect in learning a foreign language. Participants regarded the nature of CMC as artificial, or pseudo communication that did not aid their authentic communicational skills in English. The results of this study sheds lights on insufficient and inconclusive findings, which most quantitative CMC studies previously generated.

Keywords: computer-mediated communication, EFL, writing

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Authors: Dr.K.Sri Rama Krishna, J.Lakshmi Narayana, Dr.L.Pratap Reddy

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Microstrip lines, widely used for good reason, are broadband in frequency and provide circuits that are compact and light in weight. They are generally economical to produce since they are readily adaptable to hybrid and monolithic integrated circuit (IC) fabrication technologies at RF and microwave frequencies. Although, the existing EM simulation models used for the synthesis and analysis of microstrip lines are reasonably accurate, they are computationally intensive and time consuming. Neural networks recently gained attention as fast and flexible vehicles to microwave modeling, simulation and optimization. After learning and abstracting from microwave data, through a process called training, neural network models are used during microwave design to provide instant answers to the task learned.This paper presents simple and accurate ANN models for the synthesis and analysis of Microstrip lines to more accurately compute the characteristic parameters and the physical dimensions respectively for the required design specifications.

Keywords: Neural Models, Algorithms, Microstrip Lines, Analysis, Synthesis

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Authors: Shun-Chang Chang

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In this paper, different nonlinear dynamics analysis techniques are employed to unveil the rich nonlinear phenomena of the electromagnetic system. In particular, bifurcation diagrams, time responses, phase portraits, Poincare maps, power spectrum analysis, and the construction of basins of attraction are all powerful and effective tools for nonlinear dynamics problems. We also employ the method of Lyapunov exponents to show the occurrence of chaotic motion and to verify those numerical simulation results. Finally, two cases of a chaotic electromagnetic system being effectively controlled by a reference signal or being synchronized to another nonlinear electromagnetic system are presented.

Keywords: bifurcation, Poincare map, Lyapunov exponent, chaotic motion.

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Authors: Arshia Azam, J. Amarnath, Ch. D. V. Paradesi Rao

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The advantage of solving the complex nonlinear problems by utilizing fuzzy logic methodologies is that the experience or expert-s knowledge described as a fuzzy rule base can be directly embedded into the systems for dealing with the problems. The current limitation of appropriate and automated designing of fuzzy controllers are focused in this paper. The structure discovery and parameter adjustment of the Branched T-S fuzzy model is addressed by a hybrid technique of type constrained sparse tree algorithms. The simulation result for different system model is evaluated and the identification error is observed to be minimum.

Keywords: Fuzzy logic, branch T-S fuzzy model, tree modeling, complex nonlinear system.

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Authors: E. Ardil, Erdem Uçar, Parvinder S. Sandhu

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As the majority of faults are found in a few of its modules so there is a need to investigate the modules that are affected severely as compared to other modules and proper maintenance need to be done on time especially for the critical applications. In this paper, we have explored the different predictor models to NASA-s public domain defect dataset coded in Perl programming language. Different machine learning algorithms belonging to the different learner categories of the WEKA project including Mamdani Based Fuzzy Inference System and Neuro-fuzzy based system have been evaluated for the modeling of maintenance severity or impact of fault severity. The results are recorded in terms of Accuracy, Mean Absolute Error (MAE) and Root Mean Squared Error (RMSE). The results show that Neuro-fuzzy based model provides relatively better prediction accuracy as compared to other models and hence, can be used for the maintenance severity prediction of the software.

Keywords: Software Metrics, Fuzzy, Neuro-Fuzzy, SoftwareFaults, Accuracy, MAE, RMSE.

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Authors: M.A.A. Younis, N. A. Rahim, S. Mekhilef

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This paper presents the design and analysis of a parallel connected inverter configuration of. The configuration consists of parallel connected three-phase dc/ac inverter. Series resistors added to the inverter output to maintain same current in each inverter of the two parallel inverters, and to reduce the circulating current in the parallel inverters to the minimum. High frequency third harmonic injection PWM (THIPWM) employed to reduce the total harmonic distortion and to make maximum use of the voltage source. DSP was used to generate the THIPWM and the control algorithm for the converter. Selected experimental results have been shown to validate the proposed system.

Keywords: Three-phase inverter, Third harmonic injection PWM, inverters parallel connection.

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Authors: Ethan Shafer, Timothy Graziano, Jay Fisher

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This research seeks to answer whether first-year courses at institutions of higher learning can impact STEM major selection. Unlike many universities, an entry-level technology course (often referred to as CS0) is required for all United States Military Academy (USMA) students–regardless of major–in their first year of attendance. Students at the Academy choose their major at the end of their first year of studies. Through student responses to a multi-semester survey, this paper identifies a number of factors that potentially influence STEM major selection. Student demographic data, pre-existing exposure and access to technology, perceptions of STEM subjects, and initial desire for a STEM major are captured before and after taking a CS0 course. An analysis of factors that contribute to student perception of STEM and major selection are presented. This work provides recommendations and suggestions for institutions currently providing or looking to provide CS0-like courses to their students.

Keywords: STEM major, STEM, pedagogy, digital literacy.

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Authors: Xia Zhou, Shouming Zhong

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The problem of delay-range-dependent exponential synchronization is investigated for Lur-e master-slave systems with delay feedback control and Markovian switching. Using Lyapunov- Krasovskii functional and nonsingular M-matrix method, novel delayrange- dependent exponential synchronization in mean square criterions are established. The systems discussed in this paper is advanced system, and takes all the features of interval systems, Itˆo equations, Markovian switching, time-varying delay, as well as the environmental noise, into account. Finally, an example is given to show the validity of the main result.

Keywords: Synchronization, delay-range-dependent, Markov chain, generalized Itō's formula, brownian motion, M-matrix.

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Authors: Cuong Nguyen Khac, Ju H. Park, Ho-Youl Jung

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This paper proposes a new approach to perform the problem of real-time face detection. The proposed method combines primitive Haar-Like feature and variance value to construct a new feature, so-called Variance based Haar-Like feature. Face in image can be represented with a small quantity of features using this new feature. We used SVM instead of AdaBoost for training and classification. We made a database containing 5,000 face samples and 10,000 non-face samples extracted from real images for learning purposed. The 5,000 face samples contain many images which have many differences of light conditions. And experiments showed that face detection system using Variance based Haar-Like feature and SVM can be much more efficient than face detection system using primitive Haar-Like feature and AdaBoost. We tested our method on two Face databases and one Non-Face database. We have obtained 96.17% of correct detection rate on YaleB face database, which is higher 4.21% than that of using primitive Haar-Like feature and AdaBoost.

Keywords: AdaBoost, Haar-Like feature, SVM, variance, Variance based Haar-Like feature.

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Authors: Nasir Mehmood, Jens Ogniewski, Vinodh Ravinath

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This paper describes the design of a real-time audiorange digital oscilloscope and its implementation in 90nm CMOS FPGA platform. The design consists of sample and hold circuits, A/D conversion, audio and video processing, on-chip RAM, clock generation and control logic. The design of internal blocks and modules in 90nm devices in an FPGA is elaborated. Also the key features and their implementation algorithms are presented. Finally, the timing waveforms and simulation results are put forward.

Keywords: CMOS, VLSI, Oscilloscope, Field Programmable Gate Array (FPGA), VHDL, Video Graphics Array (VGA)

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Authors: J. T. Manhire

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A tax authority wants to take actions it knows will foster the greatest degree of voluntary taxpayer compliance to reduce the “tax gap.” This paper suggests that even if a tax authority could attain a state of complete knowledge, there are constraints on whether and to what extent such actions would result in reducing the macro-level tax gap. These limits are not merely a consequence of finite agency resources. They are inherent in the system itself. To show that this is one possible interpretation of the tax gap data, the paper formulates known results in a different way by analyzing tax compliance as a population with a single covariate. This leads to a standard use of the logistic map to analyze the dynamics of non-compliance growth or decay over a sequence of periods. This formulation gives the same results as the tax gap studies performed over the past fifty years in the U.S. given the published margins of error. Limitations and recommendations for future work are discussed, along with some implications for tax policy.

Keywords: Tax law, tax compliance, tax gap, income tax.

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Authors: C. Tung, P.-L. Tso

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This paper presents a complete procedure for tool path planning and blade machining in 5-axis manufacturing. The actual cutting contact and cutter locations can be determined by lead and tilt angles. The tool path generation is implemented by piecewise curved approximation and chordal deviation detection. An application about drive surface method promotes flexibility of tool control and stability of machine motion. A real manufacturing process is proposed to separate the operation into three regions with five stages and to modify the local tool orientation with an interactive algorithm.

Keywords: 5-axis machining, tool orientation, lead and tilt angles, tool path generation.

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Authors: Koson Pitaksuttayaprot, Winai Jaikla

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The realization of current-mode quadrature oscillators using current controlled current conveyor transconductance amplifiers (CCCCTAs) and grounded capacitors is presented. The proposed oscillators can provide 2 sinusoidal output currents with 90º phase difference. It is enabled non-interactive dual-current control for both the condition of oscillation and the frequency of oscillation. High output impedances of the configurations enable the circuit to be cascaded without additional current buffers. The use of only grounded capacitors is ideal for integration. The circuit performances are depicted through PSpice simulations, they show good agreement to theoretical anticipation.

Keywords: Current-mode, Oscillator, Integrated circuit, CCCCTA.

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Authors: Norshamsuri Ali, Hafizulfika, Salim Ali Al-Kathiri, Abdulla Al-Attas, Suhairi Saharudin, Mohamed Ridza Wahiddin

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We demonstrate single-photon interference over 10 km using a plug and play system for quantum key distribution. The quality of the interferometer is measured by using the interferometer visibility. The coding of the signal is based on the phase coding and the value of visibility is based on the interference effect, which result a number of count. The setup gives full control of polarization inside the interferometer. The quality measurement of the interferometer is based on number of count per second and the system produces 94 % visibility in one of the detectors.

Keywords: single photon, interferometer, quantum key distribution.

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Authors: A. Althobaiti, M. Munro

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Communication and effective information exchange within technology has become a crucial part of delivering knowledge to students during the learning process. It enables better understanding, builds trust and respect, and increases the sharing of knowledge between students. This paper examines the communication between undergraduate students and their lecturers during the traditional lecture and when using the Interactive Electronic Lecture System (IELS). The IELS is an application that offers a set of components which support the effective communication between students and their peers and between students and their lecturers. Moreover, this paper highlights communication skills such as sender, receiver, channel and feedback. It will show how the IELS creates a rich communication environment between its users and how they communicate effectively. To examine and assess the effectiveness of communication, an experiment was conducted on groups of users; students and lecturers. The first group communicated in the traditional lecture while the second group communicated by means of the IELS application. The results show that there was more effective communication between the second group than the first.

Keywords: Communication, effective information exchange.

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Authors: Premvadee Na Nakornpanom

Abstract:

Code- mixing in spontaneous speech has been widely discussed, but not in virtual situations; especially in context of the third language learning students. Thus, this study is an attempt to explore the linguistic characteristics of the mixing of Japanese, English and Thai in a mobile Line chat room by students with their background of English as L2, Japanese as L3 and Thai as mother tongue. The result found that insertion of Thai content words is a very common linguistic phenomenon embedded with the other two languages in the sentences. As chatting is to be ‘relational’ or ‘interactional’, it affected the style of lexical choices to be speech-like, more personal and emotionally-related. A personal pronoun in Japanese is often mixed into the sentences. The Japanese sentence-final question particle か “ka” was added to the end of the sentence based on Thai grammar rules. Some unique characteristics were created while chatting.

Keywords: Code-mixing, Japanese, English, Thai, Line chat.

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Authors: William Anderson, Kyle Kobold, Oleg Yakimenko

Abstract:

Green microgrids using mostly renewable energy (RE) for generation, are complex systems with inherent nonlinear dynamics. Among a variety of different optimization tools there are only a few ones that adequately consider this complexity. This paper evaluates applicability of two somewhat similar optimization tools tailored for standalone RE microgrids and also assesses a machine learning tool for performance prediction that can enhance the reliability of any chosen optimization tool. It shows that one of these microgrid optimization tools has certain advantages over another and presents a detailed routine of preparing input data to simulate RE microgrid behavior. The paper also shows how neural-network-based predictive modeling can be used to validate and forecast solar power generation based on weather time series data, which improves the overall quality of standalone RE microgrid analysis.

Keywords: Microgrid, renewable energy, complex systems, optimization, predictive modeling, neural networks.

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Authors: Marzieh Moosavi- Nasab, Safoora Pashangeh, Maryam Rafsanjani

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Xanthan gum is a microbial polysaccharide of great commercial significance. The purpose of this study was to select the optimum fermentation time for xanthan gum production by Xanthomonas campestris (NRRL-B-1459) using 10% sugar beet molasses as a carbon source. The pre-heating of sugar beet molasses and the supplementation of the medium were investigated in order to improve xanthan gum production. Maximum xanthan gum production in fermentation media (9.02 g/l) was observed after 4 days shaking incubation at 25°C and 240 rpm agitation speed. A solution of 10% sucrose was used as a control medium. Results indicated that the optimum period for xanthan gum production in this condition was 4 days.

Keywords: Biomass, Molasses, Xanthan gum, Xanthomonascampestris

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Authors: Chokri Slim

Abstract:

The neural network's performance can be measured by efficiency and accuracy. The major disadvantages of neural network approach are that the generalization capability of neural networks is often significantly low, and it may take a very long time to tune the weights in the net to generate an accurate model for a highly complex and nonlinear systems. This paper presents a novel Neuro-fuzzy architecture based on Extended Kalman filter. To test the performance and applicability of the proposed neuro-fuzzy model, simulation study of nonlinear complex dynamic system is carried out. The proposed method can be applied to an on-line incremental adaptive learning for the prediction of financial time series. A benchmark case studie is used to demonstrate that the proposed model is a superior neuro-fuzzy modeling technique.

Keywords: Neuro-fuzzy, Extended Kalman filter, nonlinear systems, financial time series.

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Authors: Jafreezal Jaafar, Hasiah Mohamed, Hazida Razali

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This paper focuses on the 3D reconstruction of the architectural design of Darul Ridzuan Museum. It has concentrated on designing exterior part of the building according to colored digital photo of the real museum. Besides viewing the architecture, walkthroughs are generated for the user to control it in an easier way. User can travel through the museum to get the feel of the environment and to explore the design of the museum as a whole; both exterior and interior. The result has shown positive result in terms of realism, navigation, collision detection, suitability, usability and user-s acceptance. In brief, the 3D virtual museum has provided an alternative to present a real museum.

Keywords: Virtual Heritage, 3D Modelling, Virtual Museum, Usability Evaluation

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Authors: N.M Khairi, M.I. Naimah, M.S.B. Shah Rizam, M.T. Nooritawati, Z.A. Husna

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Changes in stem diameter of orchid plants were investigated in a control growing climate. Previous studies have focused on stem diameter in relation to plant water on terrestrial plants in order to schedule the irrigation. The objective of this work was to evaluate the ability of the strain gauges to capture changes in the epiphytes plant stem. Experiments were carried out by using the sympodial orchid, Dendrobium Sonia in a stressed condition. From the findings, the sensor can detect changes in the plant stem and the result can easily be used as a reference for further studies for the development of a proper watering system.

Keywords: Strain gauge, stem diameter, Dendrobium Sonia, epiphyte, terrestrial

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Authors: Wiroon Sriborrirux, Sorakrai Kraipui, Nakorn Indra-Payoong

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One of the most importance of intelligence in-car and roadside systems is the cooperative vehicle-infrastructure system. In Thailand, ITS technologies are rapidly growing and real-time vehicle information is considerably needed for ITS applications; for example, vehicle fleet tracking and control and road traffic monitoring systems. This paper defines the communication protocols and software design for middleware components of B-VIS (Burapha Vehicle-Infrastructure System). The proposed B-VIS middleware architecture serves the needs of a distributed RFID sensor network and simplifies some intricate details of several communication standards.

Keywords: Middleware, RFID sensor network, Cooperativevehicle-infrastructure system, Enterprise Java Bean.

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Authors: Darren Zou

Abstract:

Forecasting the stock market is a very challenging task. Various economic indicators such as GDP, exchange rates, interest rates, and unemployment have a substantial impact on the stock market. Time series models are the traditional methods used to predict stock market changes. In this paper, a machine learning method, Bayesian Additive Regression Tree (BART) is used in predicting stock market indexes based on multiple economic indicators. BART can be used to model heterogeneous treatment effects, and thereby works well when models are misspecified. It also has the capability to handle non-linear main effects and multi-way interactions without much input from financial analysts. In this research, BART is proposed to provide a reliable prediction on day-to-day stock market activities. By comparing the analysis results from BART and with time series method, BART can perform well and has better prediction capability than the traditional methods.

Keywords: Bayesian, Forecast, Stock, BART.

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Authors: Sarma. M.V.R.K, Saharan. K, Prakash. A, Bisaria. V. S, Sahai.V

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Vermiculite was used to develop inorganic carrier-based formulations of fluorescent pseudomonad strains R62 and R81. The effect of bio-inoculation of fluorescent pseudomonad strains R62 and R81 (plant growth promoting and biocontrol agent) on growth responses of Vigna-mungo under field condition was enumerated. The combined bioinoculation of these two organisms in a formuation increased the pods yield by 300% in comparison to the control crop. There was also significant increment in the other plant growth responses such as dry root weight, dry shoot weight, shoot length and number of branches per plant.

Keywords: Bio-inoculants formulation, Fluorescent pseudomonad, Plant growth promotion activity.

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Authors: Moulay A. Akhloufi, Abdelhakim Bendada

Abstract:

Face recognition in the infrared spectrum has attracted a lot of interest in recent years. Many of the techniques used in infrared are based on their visible counterpart, especially linear techniques like PCA and LDA. In this work, we introduce a probabilistic Bayesian framework for face recognition in the infrared spectrum. In the infrared spectrum, variations can occur between face images of the same individual due to pose, metabolic, time changes, etc. Bayesian approaches permit to reduce intrapersonal variation, thus making them very interesting for infrared face recognition. This framework is compared with classical linear techniques. Non linear techniques we developed recently for infrared face recognition are also presented and compared to the Bayesian face recognition framework. A new approach for infrared face extraction based on SVM is introduced. Experimental results show that the Bayesian technique is promising and lead to interesting results in the infrared spectrum when a sufficient number of face images is used in an intrapersonal learning process.

Keywords: Face recognition, biometrics, probabilistic imageprocessing, infrared imaging.

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