Search results for: context based recommendation
Commenced in January 2007
Frequency: Monthly
Edition: International
Paper Count: 12001

Search results for: context based recommendation

7681 The Implementation of the Multi-Agent Classification System (MACS) in Compliance with FIPA Specifications

Authors: Mohamed R. Mhereeg

Abstract:

The paper discusses the implementation of the MultiAgent classification System (MACS) and utilizing it to provide an automated and accurate classification of end users developing applications in the spreadsheet domain. However, different technologies have been brought together to build MACS. The strength of the system is the integration of the agent technology with the FIPA specifications together with other technologies, which are the .NET widows service based agents, the Windows Communication Foundation (WCF) services, the Service Oriented Architecture (SOA), and Oracle Data Mining (ODM). The Microsoft's .NET widows service based agents were utilized to develop the monitoring agents of MACS, the .NET WCF services together with SOA approach allowed the distribution and communication between agents over the WWW. The Monitoring Agents (MAs) were configured to execute automatically to monitor excel spreadsheets development activities by content. Data gathered by the Monitoring Agents from various resources over a period of time was collected and filtered by a Database Updater Agent (DUA) residing in the .NET client application of the system. This agent then transfers and stores the data in Oracle server database via Oracle stored procedures for further processing that leads to the classification of the end user developers.

Keywords: MACS, Implementation, Multi-Agent, SOA, Autonomous, WCF.

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7680 A Study on Removal Characteristics of (Mn2+) from Aqueous Solution by CNT

Authors: Nassereldeen A. Kabashi, Suleyman A. Muyibi. Mohammed E. Saeed., Farhana I. Yahya

Abstract:

It is important to remove manganese from water because of its effects on human and the environment. Human activities are one of the biggest contributors for excessive manganese concentration in the environment. The proposed method to remove manganese in aqueous solution by using adsorption as in carbon nanotubes (CNT) at different parameters: The parameters are CNT dosage, pH, agitation speed and contact time. Different pHs are pH 6.0, pH 6.5, pH 7.0, pH 7.5 and pH 8.0, CNT dosages are 5mg, 6.25mg, 7.5mg, 8.75mg or 10mg, contact time are 10 min, 32.5 min, 55 min, 87.5 min and 120 min while the agitation speeds are 100rpm, 150rpm, 200rpm, 250rpm and 300rpm. The parameters chosen for experiments are based on experimental design done by using Central Composite Design, Design Expert 6.0 with 4 parameters, 5 levels and 2 replications. Based on the results, condition set at pH 7.0, agitation speed of 300 rpm, 7.5mg and contact time 55 minutes gives the highest removal with 75.5%. From ANOVA analysis in Design Expert 6.0, the residual concentration will be very much affected by pH and CNT dosage. Initial manganese concentration is 1.2mg/L while the lowest residual concentration achieved is 0.294mg/L, which almost satisfy DOE Malaysia Standard B requirement. Therefore, further experiments must be done to remove manganese from model water to the required standard (0.2 mg/L) with the initial concentration set to 0.294 mg/L.

Keywords: Adsorption, CNT, DOE, Manganese, Parameters.

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7679 Effectiveness of ICT Training Workshop for Tutors of Allama Iqbal Open University, Pakistan

Authors: Muhammad Javid Qadir, Abdul Hameed

Abstract:

The purpose of the study was to investigate the effectiveness of ICT training workshop of tutors of Allama Iqbal Open University Pakistan. The study was delimited to tutors of Multan region. The total sample comprised of 100 tutors. All the tutors who participated in ICT training workshop in Multan region were taken as sample in the study. A questionnaire having two parts, based on five point rating scale was developed by the researcher. Part one was about the competency level of computer skills while Part two was based on items related to training delivery, structure and content. Part One of questionnaire had five levels of competency about computer skills. The questionnaire was personally administered and collected back by the researcher himself on the last day of workshop. The collected data were analyzed by using descriptive statistics. Through this study it was found that majority of the tutors strongly agreed that training enhanced their computer skills. Majority of the respondents consider themselves to be generally competent in the use of computer. They also agreed that there was appropriate infrastructure and technical support in lab during training workshop. Moreover, it was found that the training imparted the knowledge of pedagogy of using computers for distance education.

Keywords: ICT, Tutors, AIOU.

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7678 Role-Governed Categorization and Category Learning as a Result from Structural Alignment: The RoleMap Model

Authors: Yolina A. Petrova, Georgi I. Petkov

Abstract:

The paper presents a symbolic model for category learning and categorization (called RoleMap). Unlike the other models which implement learning in a separate working mode, role-governed category learning and categorization emerge in RoleMap while it does its usual reasoning. The model is based on several basic mechanisms known as reflecting the sub-processes of analogy-making. It steps on the assumption that in their everyday life people constantly compare what they experience and what they know. Various commonalities between the incoming information (current experience) and the stored one (long-term memory) emerge from those comparisons. Some of those commonalities are considered to be highly important, and they are transformed into concepts for further use. This process denotes the category learning. When there is missing knowledge in the incoming information (i.e. the perceived object is still not recognized), the model makes anticipations about what is missing, based on the similar episodes from its long-term memory. Various such anticipations may emerge for different reasons. However, with time only one of them wins and is transformed into a category member. This process denotes the act of categorization.

Keywords: Categorization, category learning, role-governed category, analogy-making, cognitive modeling.

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7677 Detection of Actuator Faults for an Attitude Control System using Neural Network

Authors: S. Montenegro, W. Hu

Abstract:

The objective of this paper is to develop a neural network-based residual generator to detect the fault in the actuators for a specific communication satellite in its attitude control system (ACS). First, a dynamic multilayer perceptron network with dynamic neurons is used, those neurons correspond a second order linear Infinite Impulse Response (IIR) filter and a nonlinear activation function with adjustable parameters. Second, the parameters from the network are adjusted to minimize a performance index specified by the output estimated error, with the given input-output data collected from the specific ACS. Then, the proposed dynamic neural network is trained and applied for detecting the faults injected to the wheel, which is the main actuator in the normal mode for the communication satellite. Then the performance and capabilities of the proposed network were tested and compared with a conventional model-based observer residual, showing the differences between these two methods, and indicating the benefit of the proposed algorithm to know the real status of the momentum wheel. Finally, the application of the methods in a satellite ground station is discussed.

Keywords: Satellite, Attitude Control, Momentum Wheel, Neural Network, Fault Detection.

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7676 An Internet of Things-Based Weight Monitoring System for Honey

Authors: Zheng-Yan Ruan, Chien-Hao Wang, Hong-Jen Lin, Chien-Peng Huang, Ying-Hao Chen, En-Cheng Yang, Chwan-Lu Tseng, Joe-Air Jiang

Abstract:

Bees play a vital role in pollination. This paper focuses on the weighing process of honey. Honey is usually stored at the comb in a hive. Bee farmers brush bees away from the comb and then collect honey, and the collected honey is weighed afterward. However, such a process brings strong negative influences on bees and even leads to the death of bees. This paper therefore presents an Internet of Things-based weight monitoring system which uses weight sensors to measure the weight of honey and simplifies the whole weighing procedure. To verify the system, the weight measured by the system is compared to the weight of standard weights used for calibration by employing a linear regression model. The R2 of the regression model is 0.9788, which suggests that the weighing system is highly reliable and is able to be applied to obtain actual weight of honey. In the future, the weight data of honey can be used to find the relationship between honey production and different ecological parameters, such as bees’ foraging behavior and weather conditions. It is expected that the findings can serve as critical information for honey production improvement.

Keywords: Internet of Things, weight, honey, bee.

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7675 Optimal Supplementary Damping Controller Design for TCSC Employing RCGA

Authors: S. Panda, S. C. Swain, A. K. Baliarsingh, C. Ardil

Abstract:

Optimal supplementary damping controller design for Thyristor Controlled Series Compensator (TCSC) is presented in this paper. For the proposed controller design, a multi-objective fitness function consisting of both damping factors and real part of system electromachanical eigenvalue is used and Real- Coded Genetic Algorithm (RCGA) is employed for the optimal supplementary controller parameters. The performance of the designed supplementary TCSC-based damping controller is tested on a weakly connected power system with different disturbances and loading conditions with parameter variations. Simulation results are presented and compared with a conventional power system stabilizer and also with the TCSC-based supplementary controller when the controller parameters are not optimized to show the effectiveness and robustness of the proposed approach over a wide range of loading conditions and disturbances.

Keywords: Power System Oscillations, Real-Coded Genetic Algorithm (RCGA), Thyristor Controlled Series Compensator (TCSC), Damping Controller, Power System Stabilizer.

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7674 Several Aspects of the Conceptual Framework of Financial Reporting

Authors: Nadezhda Kvatashidze

Abstract:

The conceptual framework of International Financial Reporting Standards determines the basic principles of accounting. The said principles have multiple applications, with professional judgments being one of those. Recognition and assessment of the information contained in financial reporting, especially so the somewhat uncertain events and transactions and/or the ones regarding which there is no standard or interpretation are based on professional judgments. Professional judgments aim at the formulation of expert assumptions regarding the specifics of the circumstances and events to be entered into the report based on the conceptual framework terms and principles. Experts have to make a choice in favor of one of the aforesaid and simulate the situations applying multi-variant accounting estimates and judgment. In making the choice, one should consider all the factors, which may help represent the information in the best way possible. Professional judgment determines the relevance and faithful representation of the presented information, which makes it more useful for the existing and potential investors. In order to assess the prospected net cash flows, the information must be predictable and reliable. The publication contains critical analysis of the aforementioned problems. The fact that the International Financial Reporting Standards are developed continuously makes the issue all the more important and that is another point discussed in the study.

Keywords: Conceptual Framework for financial reporting, Qualitative characteristics of financial information, Professional judgement, Cost constraints, Financial reporting.

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7673 Simultaneous Tuning of Static Var Compensator and Power System Stabilizer Employing Real- Coded Genetic Algorithm

Authors: S. Panda, N. P. Patidar, R. Singh

Abstract:

Power system stability enhancement by simultaneous tuning of a Power System Stabilizer (PSS) and a Static Var Compensator (SVC)-based controller is thoroughly investigated in this paper. The coordination among the proposed damping stabilizers and the SVC internal voltage regulators has also been taken into consideration. The design problem is formulated as an optimization problem with a time-domain simulation-based objective function and Real-Coded Genetic Algorithm (RCGA) is employed to search for optimal controller parameters. The proposed stabilizers are tested on a weakly connected power system with different disturbances and loading conditions. The nonlinear simulation results are presented to show the effectiveness and robustness of the proposed control schemes over a wide range of loading conditions and disturbances. Further, the proposed design approach is found to be robust and improves stability effectively even under small disturbance and unbalanced fault conditions.

Keywords: Real-Coded Genetic Algorithm (RCGA), Static Var Compensator (SVC), Power System Stabilizer (PSS), Low Frequency Oscillations, Power System Stability.

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7672 1Malaysia: National Education Challenge and Nation Building

Authors: Mohd Ridhuan Tee Abdullah, Ong Hai Liaw, Wan Norhasniah Wan Husin

Abstract:

The main issue discussed is on the role of education system in the process of nation building as a means in uniting different community ethnics which later on, hoped to shape the future ethnic relation of this country. It is generally known that political socialization experienced by each ethnic community has given birth to a vernacular education system, separated along the ethnic line. Every community shapes their own education system based on their respective mother tongue language, however all are based on the same curriculum. As a result the role of education as a uniting force is not significantly effective. Historically, it has been shown that government efforts to unite the country education system under the wing of national education system (national school) is not that successful since every community (Chinese) will defend the existence of their community education system because they want to spur their mother tongue language. The clash between national education system and vernacular education system is the root cause of stalemate in the ethnic relation in Malaysia and it always becomes a flash point when the issue is raised. The question now is what is the best solution to enhance the national education system in multiethnic Malaysia?

Keywords: Political socialization, education, national unity, national school, vernacular school and 1Malaysia

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7671 Determine of Constant Coefficients to RelateTotal Dissolved Solids to Electrical Conductivity

Authors: M. Siosemarde, F. Kave, E. Pazira, H. Sedghi, S. J. Ghaderi

Abstract:

Salinity is a measure of the amount of salts in the water. Total Dissolved Solids (TDS) as salinity parameter are often determined using laborious and time consuming laboratory tests, but it may be more appropriate and economical to develop a method which uses a more simple soil salinity index. Because dissolved ions increase salinity as well as conductivity, the two measures are related. The aim of this research was determine of constant coefficients for predicting of Total Dissolved Solids (TDS) based on Electrical Conductivity (EC) with Statistics of Correlation coefficient, Root mean square error, Maximum error, Mean Bias error, Mean absolute error, Relative error and Coefficient of residual mass. For this purpose, two experimental areas (S1, S2) of Khuzestan province-IRAN were selected and four treatments with three replications by series of double rings were applied. The treatments were included 25cm, 50cm, 75cm and 100cm water application. The results showed the values 16.3 & 12.4 were the best constant coefficients for predicting of Total Dissolved Solids (TDS) based on EC in Pilot S1 and S2 with correlation coefficient 0.977 & 0.997 and 191.1 & 106.1 Root mean square errors (RMSE) respectively.

Keywords: constant coefficients, electrical conductivity, Khuzestan plain and total dissolved solids.

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7670 A Nanosensor System Based On Disuccinimydyl–CYP2E1 for Amperometric Detection of the Anti-Tuberculosis Drug, Pyrazinamide

Authors: R. F. Ajayi, U. Sidwaba, U. Feleni, S. F. Douman, E. Nxusani, L. Wilson, C. Rassie, O. Tovide, P. G. L. Baker, S. L. Vilakazi, R. Tshikhudo, E. I. Iwuoha

Abstract:

Pyrazinamide (PZA) is among the first-line pro-drugs  in the tuberculosis (TB) combination chemotherapy used to treat  Mycobacterium tuberculosis. Numerous reports have suggested that  hepatotoxicity due to pyrazinamide in patients is due to inappropriate  dosing. It is, therefore necessary to develop sensitive and reliable  techniques for determining the PZA metabolic profile of diagnosed  patients promptly and at point-of-care. This study reports the  determination of PZA based on nanobiosensor systems developed  from disuccinimidyl octanedioate modified Cytochrome P450-2E1  (CYP2E1) electrodeposited on gold substrates derivatised with  (poly(8-anilino-1-napthalene sulphonic acid) PANSA/PVP-AgNPs  nanocomposites. The rapid and sensitive amperometric PZA  detection gave a dynamic linear range of 2µM to 16µM revealing a  limit of detection of 0.044µM and a sensitivity of 1.38µA/µM. The  Michaelis-Menten parameters; KM, KM app and IMAX were calculated to  be 6.0µM, 1.41µM and 1.51x10-6 A, respectively, indicating a  nanobiosensor suitable for use in serum.

Keywords: Cytochrome P450-2E1, Disuccinimidyl octanedioate, Pyrazinamide, Tuberculosis.

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7669 A Review on the Potential of Electric Vehicles in Reducing World CO2 Footprints

Authors: S. Alotaibi, S. Omer, Y. Su

Abstract:

The conventional Internal Combustion Engine (ICE) based vehicles are a threat to the environment as they account for a large proportion of the overall greenhouse gas (GHG) emissions in the world. Hence, it is required to replace these vehicles with more environment-friendly vehicles. Electric Vehicles (EVs) are promising technologies which offer both human comfort “noise, pollution” as well as reduced (or no) emissions of GHGs. In this paper, different types of EVs are reviewed and their advantages and disadvantages are identified. It is found that in terms of fuel economy, Plug-in Hybrid EVs (PHEVs) have the best fuel economy, followed by Hybrid EVs (HEVs) and ICE vehicles. Since Battery EVs (BEVs) do not use any fuel, their fuel economy is estimated as price per kilometer. Similarly, in terms of GHG emissions, BEVs are the most environmentally friendly since they do not result in any emissions while HEVs and PHEVs produce less emissions compared to the conventional ICE based vehicles. Fuel Cell EVs (FCEVs) are also zero-emission vehicles, but they have large costs associated with them. Finally, if the electricity is provided by using the renewable energy technologies through grid connection, then BEVs could be considered as zero emission vehicles.

Keywords: Electric vehicle, fuel cell electric vehicle, hybrid electric vehicle, internal combustion engine.

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7668 Investigations of Protein Aggregation Using Sequence and Structure Based Features

Authors: M. Michael Gromiha, A. Mary Thangakani, Sandeep Kumar, D. Velmurugan

Abstract:

The main cause of several neurodegenerative diseases such as Alzhemier, Parkinson and spongiform encephalopathies is formation of amyloid fibrils and plaques in proteins. We have analyzed different sets of proteins and peptides to understand the influence of sequence based features on protein aggregation process. The comparison of 373 pairs of homologous mesophilic and thermophilic proteins showed that aggregation prone regions (APRs) are present in both. But, the thermophilic protein monomers show greater ability to ‘stow away’ the APRs in their hydrophobic cores and protect them from solvent exposure. The comparison of amyloid forming and amorphous b-aggregating hexapeptides suggested distinct preferences for specific residues at the six positions as well as all possible combinations of nine residue pairs. The compositions of residues at different positions and residue pairs have been converted into energy potentials and utilized for distinguishing between amyloid forming and amorphous b-aggregating peptides. Our method could correctly identify the amyloid forming peptides at an accuracy of 95-100% in different datasets of peptides.

Keywords: Aggregation prone regions, amyloids, thermophilic proteins, amino acid residues, machine learning.

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7667 A Mesh Free Moving Node Method To Analyze Flow Through Spirals of Orbiting Scroll Pump

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

Abstract:

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

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

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7666 Binarization of Text Region based on Fuzzy Clustering and Histogram Distribution in Signboards

Authors: Jonghyun Park, Toan Nguyen Dinh, Gueesang Lee

Abstract:

In this paper, we present a novel approach to accurately detect text regions including shop name in signboard images with complex background for mobile system applications. The proposed method is based on the combination of text detection using edge profile and region segmentation using fuzzy c-means method. In the first step, we perform an elaborate canny edge operator to extract all possible object edges. Then, edge profile analysis with vertical and horizontal direction is performed on these edge pixels to detect potential text region existing shop name in a signboard. The edge profile and geometrical characteristics of each object contour are carefully examined to construct candidate text regions and classify the main text region from background. Finally, the fuzzy c-means algorithm is performed to segment and detected binarize text region. Experimental results show that our proposed method is robust in text detection with respect to different character size and color and can provide reliable text binarization result.

Keywords: Text detection, edge profile, signboard image, fuzzy clustering.

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7665 A Framework for Scalable Autonomous P2P Resource Discovery for the Grid Implementation

Authors: Hesham A. Ali, Mofreh M. Salem, Ahmed A. Hamza

Abstract:

Recently, there have been considerable efforts towards the convergence between P2P and Grid computing in order to reach a solution that takes the best of both worlds by exploiting the advantages that each offers. Augmenting the peer-to-peer model to the services of the Grid promises to eliminate bottlenecks and ensure greater scalability, availability, and fault-tolerance. The Grid Information Service (GIS) directly influences quality of service for grid platforms. Most of the proposed solutions for decentralizing the GIS are based on completely flat overlays. The main contributions for this paper are: the investigation of a novel resource discovery framework for Grid implementations based on a hierarchy of structured peer-to-peer overlay networks, and introducing a discovery algorithm utilizing the proposed framework. Validation of the framework-s performance is done via simulation. Experimental results show that the proposed organization has the advantage of being scalable while providing fault-isolation, effective bandwidth utilization, and hierarchical access control. In addition, it will lead to a reliable, guaranteed sub-linear search which returns results within a bounded interval of time and with a smaller amount of generated traffic within each domain.

Keywords: Grid computing, grid information service, P2P, resource discovery.

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7664 An Optimization of the New Die Design of Sheet Hydroforming by Taguchi Method

Authors: M. Hosseinzadeh, S. A. Zamani, A. Taheri

Abstract:

During the last few years, several sheet hydroforming processes have been introduced. Despite the advantages of these methods, they have some limitations. Of the processes, the two main ones are the standard hydroforming and hydromechanical deep drawing. A new sheet hydroforming die set was proposed that has the advantages of both processes and eliminates their limitations. In this method, a polyurethane plate was used as a part of the die-set to control the blank holder force. This paper outlines the Taguchi optimization methodology, which is applied to optimize the effective parameters in forming cylindrical cups by the new die set of sheet hydroforming process. The process parameters evaluated in this research are polyurethane hardness, polyurethane thickness, forming pressure path and polyurethane hole diameter. The design of experiments based upon L9 orthogonal arrays by Taguchi was used and analysis of variance (ANOVA) was employed to analyze the effect of these parameters on the forming pressure. The analysis of the results showed that the optimal combination for low forming pressure is harder polyurethane, bigger diameter of polyurethane hole and thinner polyurethane. Finally, the confirmation test was derived based on the optimal combination of parameters and it was shown that the Taguchi method is suitable to examine the optimization process.

Keywords: Sheet Hydroforming, Optimization, Taguchi Method

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7663 Multi-Layer Perceptron Neural Network Classifier with Binary Particle Swarm Optimization Based Feature Selection for Brain-Computer Interfaces

Authors: K. Akilandeswari, G. M. Nasira

Abstract:

Brain-Computer Interfaces (BCIs) measure brain signals activity, intentionally and unintentionally induced by users, and provides a communication channel without depending on the brain’s normal peripheral nerves and muscles output pathway. Feature Selection (FS) is a global optimization machine learning problem that reduces features, removes irrelevant and noisy data resulting in acceptable recognition accuracy. It is a vital step affecting pattern recognition system performance. This study presents a new Binary Particle Swarm Optimization (BPSO) based feature selection algorithm. Multi-layer Perceptron Neural Network (MLPNN) classifier with backpropagation training algorithm and Levenberg-Marquardt training algorithm classify selected features.

Keywords: Brain-Computer Interfaces (BCI), Feature Selection (FS), Walsh–Hadamard Transform (WHT), Binary Particle Swarm Optimization (BPSO), Multi-Layer Perceptron (MLP), Levenberg–Marquardt algorithm.

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7662 A Comparison of Adaline and MLP Neural Network based Predictors in SIR Estimation in Mobile DS/CDMA Systems

Authors: Nahid Ardalani, Ahmadreza Khoogar, H. Roohi

Abstract:

In this paper we compare the response of linear and nonlinear neural network-based prediction schemes in prediction of received Signal-to-Interference Power Ratio (SIR) in Direct Sequence Code Division Multiple Access (DS/CDMA) systems. The nonlinear predictor is Multilayer Perceptron MLP and the linear predictor is an Adaptive Linear (Adaline) predictor. We solve the problem of complexity by using the Minimum Mean Squared Error (MMSE) principle to select the optimal predictors. The optimized Adaline predictor is compared to optimized MLP by employing noisy Rayleigh fading signals with 1.8 GHZ carrier frequency in an urban environment. The results show that the Adaline predictor can estimates SIR with the same error as MLP when the user has the velocity of 5 km/h and 60 km/h but by increasing the velocity up-to 120 km/h the mean squared error of MLP is two times more than Adaline predictor. This makes the Adaline predictor (with lower complexity) more suitable than MLP for closed-loop power control where efficient and accurate identification of the time-varying inverse dynamics of the multi path fading channel is required.

Keywords: Power control, neural networks, DS/CDMA mobilecommunication systems.

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7661 Method of Intelligent Fault Diagnosis of Preload Loss for Single Nut Ball Screws through the Sensed Vibration Signals

Authors: Yi-Cheng Huang, Yan-Chen Shin

Abstract:

This paper proposes method of diagnosing ball screw preload loss through the Hilbert-Huang Transform (HHT) and Multiscale entropy (MSE) process. The proposed method can diagnose ball screw preload loss through vibration signals when the machine tool is in operation. Maximum dynamic preload of 2 %, 4 %, and 6 % ball screws were predesigned, manufactured, and tested experimentally. Signal patterns are discussed and revealed using Empirical Mode Decomposition(EMD)with the Hilbert Spectrum. Different preload features are extracted and discriminated using HHT. The irregularity development of a ball screw with preload loss is determined and abstracted using MSE based on complexity perception. Experiment results show that the proposed method can predict the status of ball screw preload loss. Smart sensing for the health of the ball screw is also possible based on a comparative evaluation of MSE by the signal processing and pattern matching of EMD/HHT. This diagnosis method realizes the purposes of prognostic effectiveness on knowing the preload loss and utilizing convenience.

Keywords: Empirical Mode Decomposition, Hilbert-Huang Transform, Multi-scale Entropy, Preload Loss, Single-nut Ball Screw

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7660 Near-Field Robust Adaptive Beamforming Based on Worst-Case Performance Optimization

Authors: Jing-ran Lin, Qi-cong Peng, Huai-zong Shao

Abstract:

The performance of adaptive beamforming degrades substantially in the presence of steering vector mismatches. This degradation is especially severe in the near-field, for the 3-dimensional source location is more difficult to estimate than the 2-dimensional direction of arrival in far-field cases. As a solution, a novel approach of near-field robust adaptive beamforming (RABF) is proposed in this paper. It is a natural extension of the traditional far-field RABF and belongs to the class of diagonal loading approaches, with the loading level determined based on worst-case performance optimization. However, different from the methods solving the optimal loading by iteration, it suggests here a simple closed-form solution after some approximations, and consequently, the optimal weight vector can be expressed in a closed form. Besides simplicity and low computational cost, the proposed approach reveals how different factors affect the optimal loading as well as the weight vector. Its excellent performance in the near-field is confirmed via a number of numerical examples.

Keywords: Robust adaptive beamforming (RABF), near-field, steering vector mismatches, diagonal loading, worst-case performanceoptimization.

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7659 FPGA Based Parallel Architecture for the Computation of Third-Order Cross Moments

Authors: Syed Manzoor Qasim, Shuja Abbasi, Saleh Alshebeili, Bandar Almashary, Ateeq Ahmad Khan

Abstract:

Higher-order Statistics (HOS), also known as cumulants, cross moments and their frequency domain counterparts, known as poly spectra have emerged as a powerful signal processing tool for the synthesis and analysis of signals and systems. Algorithms used for the computation of cross moments are computationally intensive and require high computational speed for real-time applications. For efficiency and high speed, it is often advantageous to realize computation intensive algorithms in hardware. A promising solution that combines high flexibility together with the speed of a traditional hardware is Field Programmable Gate Array (FPGA). In this paper, we present FPGA-based parallel architecture for the computation of third-order cross moments. The proposed design is coded in Very High Speed Integrated Circuit (VHSIC) Hardware Description Language (VHDL) and functionally verified by implementing it on Xilinx Spartan-3 XC3S2000FG900-4 FPGA. Implementation results are presented and it shows that the proposed design can operate at a maximum frequency of 86.618 MHz.

Keywords: Cross moments, Cumulants, FPGA, Hardware Implementation.

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7658 Effect of Process Parameters on the Proximate Composition, Functional and Sensory Properties

Authors: C. I. Omohimi, O. P. Sobukola, K. O. Sarafadeen, L.O. Sanni

Abstract:

Flour from Mucuna beans (Mucuna pruriens) were used in producing texturized meat analogue using a single screw extruder to monitor modifications on the proximate composition and the functional properties at high moisture level. Response surface methodology based on Box Behnken design at three levels of barrel temperature (110, 120, 130°C), screw speed (100,120,140rpm) and feed moisture (44, 47, 50%) were used in 17 runs. Regression models describing the effect of variables on the product responses were obtained. Descriptive profile analyses and consumer acceptability test were carried out on optimized flavoured extruded meat analogue. Responses were mostly affected by barrel temperature and moisture level and to a lesser extent by screw speed. Optimization results based on desirability concept indicated that a barrel temperature of 120.15°C, feed moisture of 47% and screw speed of 119.19 rpm would produce meat analogue of preferable proximate composition, functional and sensory properties which reveals consumers` likeness for the product.

Keywords: Functional properties, mucuna bean flour, optimization, proximate composition, texturized meat analogue.

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7657 A Content Based Image Watermarking Scheme Resilient to Geometric Attacks

Authors: Latha Parameswaran, K. Anbumani

Abstract:

Multimedia security is an incredibly significant area of concern. The paper aims to discuss a robust image watermarking scheme, which can withstand geometric attacks. The source image is initially moment normalized in order to make it withstand geometric attacks. The moment normalized image is wavelet transformed. The first level wavelet transformed image is segmented into blocks if size 8x8. The product of mean and standard and standard deviation of each block is computed. The second level wavelet transformed image is divided into 8x8 blocks. The product of block mean and the standard deviation are computed. The difference between products in the two levels forms the watermark. The watermark is inserted by modulating the coefficients of the mid frequencies. The modulated image is inverse wavelet transformed and inverse moment normalized to generate the watermarked image. The watermarked image is now ready for transmission. The proposed scheme can be used to validate identification cards and financial instruments. The performance of this scheme has been evaluated using a set of parameters. Experimental results show the effectiveness of this scheme.

Keywords: Image moments, wavelets, content-based watermarking, moment normalization, geometric attacks.

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7656 Application of a Theoretical Framework as a Context for a Travel Behavior Change Policy Intervention

Authors: F. Moghtaderi, M. Burke, J. Troelsen

Abstract:

There has been a significant decline in active travel and a massive increase in the use of car dependent travel in many countries during the past two decades. Evidential risks for people’s physical and mental health problems are correlated with this increased use of motorized travel. These health related problems range from overweight and obesity to increased air pollution. In response to these rising concerns health professionals, traffic planers, local authorities and others have introduced a variety of initiatives to counterbalance the dominance of cars for daily journeys. However, the nature of travel behavior change interventions, which aim to reduce car use, are very complex and challenging regarding their interactions with human behavior. To change travel behavior at least two aspects have to be taken into consideration. First, how to alter attitudes and perceptions toward the sustainable and healthy modes of travel, in competition with experiences of private car use. And second, how to make these behavior change processes irreversible and sustainable. There are no comprehensive models available to guide policy interventions to increase the level of success of travel behavior change interventions across both these dimensions. A comprehensive theoretical framework is required in the effort to optimize how to facilitate and guide the processes of data collection and analysis to achieve the best possible guidelines for policy makers. Regarding the gaps in the travel behavior change research literature, this paper attempted to identify and suggest a multidimensional framework in order to facilitate planning the implemented travel behavior change interventions. A structured mixed-method model is suggested to improve the analytic power of the results according to the complexity of human behavior. In order to recognize people’s attitudes towards a specific travel mode, the Theory of Planned Behavior (TPB) was operationalized. But in order to capture decision making processes the Transtheoretical model of Behavior Change (TTM) was also used. Consequently, the combination of these two theories (TTM and TPB) has resulted in a synthesis with appropriate concepts to identify and design an implemented travel behavior change interventions.

Keywords: Behavior change theories, Theoretical framework, Travel behavior change interventions.

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7655 Artificial Neural Network based Modeling of Evaporation Losses in Reservoirs

Authors: Surinder Deswal, Mahesh Pal

Abstract:

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

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

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7654 Research on Traditional Rammed Earth Houses in Southern Zhejiang, China: Based on the Theory of Embeddedness

Authors: Han Wu, Jie Wang

Abstract:

Zhejiang’s special geographical environment has created characteristic mountain dwellings with climate adaptability. Among them, the terrain of southern Zhejiang is dominated by mountainous and hilly landforms, and its traditional dwellings have distinctive characteristics. They are often adapted to local conditions and laid out in accordance with the mountains. In order to block the severe winter weather conditions, local traditional building materials such as rammed earth are mostly used. However, with the development of urbanization, traditional villages have undergone large-scale changes, gradually losing their original uniqueness. In order to solve this problem, this paper takes traditional villages around Baishanzu National Park in Zhejiang as an example and selects nine typical villages in Jingning County and Longquan, respectively. Based on field investigations, this paper extracts the environmental adaptability of local traditional rammed earth houses from the perspective of “geographical embeddedness”. And then combined with case analysis, the paper discusses the translation and development of its traditional architectural methods in contemporary rammed earth buildings in southern Zhejiang.

Keywords: Rammed earth building, lighting, ventilation, geographical embeddedness, modernization translation.

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7653 A High Performance Technique in Harmonic Omitting Based on Predictive Current Control of a Shunt Active Power Filter

Authors: K. G. Firouzjah, A. Sheikholeslami

Abstract:

The perfect operation of common Active Filters is depended on accuracy of identification system distortion. Also, using a suitable method in current injection and reactive power compensation, leads to increased filter performance. Due to this fact, this paper presents a method based on predictive current control theory in shunt active filter applications. The harmonics of the load current is identified by using o–d–q reference frame on load current and eliminating the DC part of d–q components. Then, the rest of these components deliver to predictive current controller as a Threephase reference current by using Park inverse transformation. System is modeled in discreet time domain. The proposed method has been tested using MATLAB model for a nonlinear load (with Total Harmonic Distortion=20%). The simulation results indicate that the proposed filter leads to flowing a sinusoidal current (THD=0.15%) through the source. In addition, the results show that the filter tracks the reference current accurately.

Keywords: Active filter, predictive current control, low pass filter, harmonic omitting, o–d–q reference frame.

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7652 Freedom of Media, Democracy and Gezi Park

Authors: Emine Tirali

Abstract:

This article provides a conceptual framework of the freedom of media and its correlation with democracy. In a democracy, media should serve the publics’ right to know and reflect human rights violations and offer options for meaningful political choices and effective participation in civic affairs. On that point, the 2013 events at Gezi Park in Turkey are a good empirical example to be discussed. During the events, when self-censorship was broadly employed by mainstream Turkish media, social media filled the important role of providing information to the public. New technologies have made information into a fundamental tool for change and growth, and as a consequence, societies worldwide have merged into a single, interdependent, and autonomous organism. For this reason, violations of human rights can no longer be considered domestic issues, but rather global ones. Only global political action is an adequate response. Democracy depends on people shaping the society they live in, and in order to accomplish this, they need to express themselves. Freedom of expression is therefore necessary in order to understand diversity and differing perspectives, which in turn are necessary to resolve conflicts among people. Moreover, freedom of information is integral to freedom of expression. In this context, the international rules and laws regarding freedom of expression and freedom of information – indispensable for a free and independent media – are examined. These were put in place by international institutions such as the United Nations, UNESCO, the Council of Europe, and the European Union, which have aimed to build a free, democratic, and pluralist world committed to human rights and the rule of law. The methods of international human rights institutions depend on effective and frequent employment of mass media to relay human rights violations to the public. Therefore, in this study, the relationship between mass media and democracy, the process of how mass media forms public opinion, the problems of mass media, the neo-liberal theory of mass media, and the use of mass media by NGOs will be evaluated.

Keywords: Freedom of expression, democracy, public opinion, self-censorship.

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