Search results for: instance selection
438 The Maximum Likelihood Method of Random Coefficient Dynamic Regression Model
Authors: Autcha Araveeporn
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The Random Coefficient Dynamic Regression (RCDR) model is to developed from Random Coefficient Autoregressive (RCA) model and Autoregressive (AR) model. The RCDR model is considered by adding exogenous variables to RCA model. In this paper, the concept of the Maximum Likelihood (ML) method is used to estimate the parameter of RCDR(1,1) model. Simulation results have shown the AIC and BIC criterion to compare the performance of the the RCDR(1,1) model. The variables as the stationary and weakly stationary data are good estimates where the exogenous variables are weakly stationary. However, the model selection indicated that variables are nonstationarity data based on the stationary data of the exogenous variables.Keywords: Autoregressive, Maximum Likelihood Method, Nonstationarity, Random Coefficient Dynamic Regression, Stationary.
Procedia APA BibTeX Chicago EndNote Harvard JSON MLA RIS XML ISO 690 PDF Downloads 1636437 Computationally Efficient Adaptive Rate Sampling and Adaptive Resolution Analysis
Authors: Saeed Mian Qaisar, Laurent Fesquet, Marc Renaudin
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Mostly the real life signals are time varying in nature. For proper characterization of such signals, time-frequency representation is required. The STFT (short-time Fourier transform) is a classical tool used for this purpose. The limitation of the STFT is its fixed time-frequency resolution. Thus, an enhanced version of the STFT, which is based on the cross-level sampling, is devised. It can adapt the sampling frequency and the window function length by following the input signal local variations. Therefore, it provides an adaptive resolution time-frequency representation of the input. The computational complexity of the proposed STFT is deduced and compared to the classical one. The results show a significant gain of the computational efficiency and hence of the processing power. The processing error of the proposed technique is also discussed.
Keywords: Level Crossing Sampling, Activity Selection, Adaptive Resolution Analysis, Computational Complexity
Procedia APA BibTeX Chicago EndNote Harvard JSON MLA RIS XML ISO 690 PDF Downloads 1251436 Forecasting Direct Normal Irradiation at Djibouti Using Artificial Neural Network
Authors: Ahmed Kayad Abdourazak, Abderafi Souad, Zejli Driss, Idriss Abdoulkader Ibrahim
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In this paper Artificial Neural Network (ANN) is used to predict the solar irradiation in Djibouti for the first Time that is useful to the integration of Concentrating Solar Power (CSP) and sites selections for new or future solar plants as part of solar energy development. An ANN algorithm was developed to establish a forward/reverse correspondence between the latitude, longitude, altitude and monthly solar irradiation. For this purpose the German Aerospace Centre (DLR) data of eight Djibouti sites were used as training and testing in a standard three layers network with the back propagation algorithm of Lavenber-Marquardt. Results have shown a very good agreement for the solar irradiation prediction in Djibouti and proves that the proposed approach can be well used as an efficient tool for prediction of solar irradiation by providing so helpful information concerning sites selection, design and planning of solar plants.Keywords: Artificial neural network, solar irradiation, concentrated solar power, Lavenberg-Marquardt.
Procedia APA BibTeX Chicago EndNote Harvard JSON MLA RIS XML ISO 690 PDF Downloads 1067435 A New Heuristic Approach for Optimal Network Reconfiguration in Distribution Systems
Authors: R. Srinivasa Rao, S. V. L. Narasimham
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This paper presents a novel approach for optimal reconfiguration of radial distribution systems. Optimal reconfiguration involves the selection of the best set of branches to be opened, one each from each loop, such that the resulting radial distribution system gets the desired performance. In this paper an algorithm is proposed based on simple heuristic rules and identified an effective switch status configuration of distribution system for the minimum loss reduction. This proposed algorithm consists of two parts; one is to determine the best switching combinations in all loops with minimum computational effort and the other is simple optimum power loss calculation of the best switching combination found in part one by load flows. To demonstrate the validity of the proposed algorithm, computer simulations are carried out on 33-bus system. The results show that the performance of the proposed method is better than that of the other methods.Keywords: Distribution system, network reconfiguration, powerloss reduction, radial network, heuristic technique.
Procedia APA BibTeX Chicago EndNote Harvard JSON MLA RIS XML ISO 690 PDF Downloads 2765434 Decision-Making Tool for Planning the Construction of Infrastructure Projects
Authors: R. Monib, C. I. Goodier, A. Gibb
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The aim of this paper is to investigate the key drivers in planning the construction phase for infrastructure projects to reduce project delays. To achieve this aim, the research conducted three case studies using semi-structured and unstructured interviews (n = 59). The results conclude that a lack of modularization awareness is among the key factors attributed to project delays. The current emotive and ill-informed approach to decision-making, coupled with the lack of knowledge regarding appropriate construction method selection, prevents the potential benefits of modularization being fully realized. To assist with decision-making for the best construction method, the research presents project management tools to help decision makers to choose the most appropriate construction approach through optimizing the use of modularization in engineering and construction (EC). A decision-making checklist is presented in this paper. This checklist tool assists the project team in determining the best construction method, taking into consideration the module type.
Keywords: Infrastructure, modularization, decision support, planning.
Procedia APA BibTeX Chicago EndNote Harvard JSON MLA RIS XML ISO 690 PDF Downloads 67433 An Experimental Comparison of Unsupervised Learning Techniques for Face Recognition
Authors: Dinesh Kumar, C.S. Rai, Shakti Kumar
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Face Recognition has always been a fascinating research area. It has drawn the attention of many researchers because of its various potential applications such as security systems, entertainment, criminal identification etc. Many supervised and unsupervised learning techniques have been reported so far. Principal Component Analysis (PCA), Self Organizing Maps (SOM) and Independent Component Analysis (ICA) are the three techniques among many others as proposed by different researchers for Face Recognition, known as the unsupervised techniques. This paper proposes integration of the two techniques, SOM and PCA, for dimensionality reduction and feature selection. Simulation results show that, though, the individual techniques SOM and PCA itself give excellent performance but the combination of these two can also be utilized for face recognition. Experimental results also indicate that for the given face database and the classifier used, SOM performs better as compared to other unsupervised learning techniques. A comparison of two proposed methodologies of SOM, Local and Global processing, shows the superiority of the later but at the cost of more computational time.
Keywords: Face Recognition, Principal Component Analysis, Self Organizing Maps, Independent Component Analysis
Procedia APA BibTeX Chicago EndNote Harvard JSON MLA RIS XML ISO 690 PDF Downloads 1871432 Combustion and Emission Characteristics in a Can-type Combustion Chamber
Authors: Selvakuma Kumaresh, Man Young Kim
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Combustion phenomenon will be accomplished effectively by the development of low emission combustor. One of the significant factors influencing the entire Combustion process is the mixing between a swirling angular jet (Primary Air) and the non-swirling inner jet (fuel). To study this fundamental flow, the chamber had to be designed in such a manner that the combustion process to sustain itself in a continuous manner and the temperature of the products is sufficiently below the maximum working temperature in the turbine. This study is used to develop the effective combustion with low unburned combustion products by adopting the concept of high swirl flow and motility of holes in the secondary chamber. The proper selection of a swirler is needed to reduce emission which can be concluded from the emission of Nox and CO2. The capture of CO2 is necessary to mitigate CO2 emissions from natural gas. Thus the suppression of unburned gases is a meaningful objective for the development of high performance combustor without affecting turbine blade temperature.
Keywords: Combustion, Emission, Can-type Combustion Chamber, CFD, Motility of Holes, Swirl Flow.
Procedia APA BibTeX Chicago EndNote Harvard JSON MLA RIS XML ISO 690 PDF Downloads 3493431 Enhanced Performance of Fading Dispersive Channel Using Dynamic Frequency Hopping(DFH)
Authors: Walid M. Saad
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techniques are examined to overcome the performance degradation caused by the channel dispersion using slow frequency hopping (SFH) with dynamic frequency hopping (DFH) pattern adaptation. In DFH systems, the frequency slots are selected by continuous quality monitoring of all frequencies available in a system and modification of hopping patterns for each individual link based on replacing slots which its signal to interference ratio (SIR) measurement is below a required threshold. Simulation results will show the improvements in BER obtained by DFH in comparison with matched frequency hopping (MFH), random frequency hopping (RFH) and multi-carrier code division multiple access (MC-CDMA) in multipath slowly fading dispersive channels using a generalized bandpass two-path transfer function model, and will show the improvement obtained according to the threshold selection.Keywords: code division multiple access (CDMA), dynamic channel allocation (DCA), dynamic channel assignment, frequency hopping, matched frequency hopping (MFH).
Procedia APA BibTeX Chicago EndNote Harvard JSON MLA RIS XML ISO 690 PDF Downloads 1698430 Epistemological Functions of Emotions and Their Relevance to the Formation of Citizens and Scientists
Authors: Dení Stincer Gómez, Zuraya Monroy Nasr
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Pedagogy of science historically has given priority to teaching strategies that mobilize the cognitive mechanisms leaving out emotional mechanisms. Modern epistemology, cognitive psychology and psychoanalysis begin to argue and prove that emotions are relevant epistemological functions. They are 1) the selection function: that allows the perception and reason choose, to multiple alternative explanation of a particular fact, those are relevant and discard those that are not, 2) heuristic function: that is related to the activation cognitive processes that are effective in the process of knowing; and 3) the so-called content-bearing function: it argues that emotions provide the material reasoning that is subsequently transformed into linguistic propositions. According to these hypotheses, scientific knowledge seems to come from emotions that meet these functions. This paper argues that science education must start from the presence of certain emotions in the learner if we want to form citizens with a scientific or cultural future.
Keywords: Epistemic emotions, science education, formation of citizens and scientists, epistemic functions of emotions.
Procedia APA BibTeX Chicago EndNote Harvard JSON MLA RIS XML ISO 690 PDF Downloads 453429 A Novel Method for the Characterization of Synchronization and Coupling in Multichannel EEG and ECoG
Authors: Manfred Hartmann, Andreas Graef, Hannes Perko, Christoph Baumgartner, Tilmann Kluge
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In this paper we introduce a novel method for the characterization of synchronziation and coupling effects in multivariate time series that can be used for the analysis of EEG or ECoG signals recorded during epileptic seizures. The method allows to visualize the spatio-temporal evolution of synchronization and coupling effects that are characteristic for epileptic seizures. Similar to other methods proposed for this purpose our method is based on a regression analysis. However, a more general definition of the regression together with an effective channel selection procedure allows to use the method even for time series that are highly correlated, which is commonly the case in EEG/ECoG recordings with large numbers of electrodes. The method was experimentally tested on ECoG recordings of epileptic seizures from patients with temporal lobe epilepsies. A comparision with the results from a independent visual inspection by clinical experts showed an excellent agreement with the patterns obtained with the proposed method.Keywords: EEG, epilepsy, regression analysis, seizurepropagation.
Procedia APA BibTeX Chicago EndNote Harvard JSON MLA RIS XML ISO 690 PDF Downloads 1421428 Greywater Treatment Using Activated Biochar Produced from Agricultural Waste
Authors: Pascal Mwenge, Tumisang Seodigeng
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The increase in urbanisation in South Africa has led to an increase in water demand and a decline in freshwater supply. Despite this, poor water usage is still a major challenge in South Africa, for instance, freshwater is still used for non-drinking applications. The freshwater shortage can be alleviated by using other sources of water for non-portable purposes such as greywater treated with activated biochar produced from agricultural waste. The success of activated biochar produced from agricultural waste to treat greywater can be both economically and environmentally beneficial. Greywater treated with activated biochar produced from agricultural waste is considered a cost-effective wastewater treatment. This work was aimed at determining the ability of activated biochar to remove Total Suspended Solids (TSS), Ammonium (NH4-N), Nitrate (NO3-N), and Chemical Oxygen Demand (COD) from greywater. The experiments were carried out in 800 ml laboratory plastic cylinders used as filter columns. 2.5 cm layer of gravel was used at the bottom and top of the column to sandwich the activated biochar material. Activated biochar (200 g and 400 g) was loaded in a column and used as a filter medium for greywater. Samples were collected after a week and sent for analysis. Four types of greywater were treated: Kitchen, floor cleaning water, shower and laundry water. The findings showed: 95% removal of TSS, 76% of NO3-N and 63% of COD on kitchen greywater and 85% removal of NH4-N on bathroom greywater, as highest removal of efficiency of the studied pollutants. The results showed that activated biochar produced from agricultural waste reduces a certain amount of pollutants from greywater. The results also indicated the ability of activated biochar to treat greywater for onsite non-potable reuse purposes.
Keywords: Activated biochar produced from agriculture waste, ammonium (NH4-N), chemical oxygen demand (COD), greywater, nitrate (NO3-N), total suspended solids (TSS).
Procedia APA BibTeX Chicago EndNote Harvard JSON MLA RIS XML ISO 690 PDF Downloads 1400427 A Dual Fitness Function Genetic Algorithm: Application on Deterministic Identical Machine Scheduling
Authors: Saleem Z. Ramadan, Gürsel A. Süer
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In this paper a genetic algorithm (GA) with dual-fitness function is proposed and applied to solve the deterministic identical machine scheduling problem. The mating fitness function value was used to determine the mating for chromosomes, while the selection fitness function value was used to determine their survivals. The performance of this algorithm was tested on deterministic identical machine scheduling using simulated data. The results obtained from the proposed GA were compared with classical GA and integer programming (IP). Results showed that dual-fitness function GA outperformed the classical single-fitness function GA with statistical significance for large problems and was competitive to IP, particularly when large size problems were used.
Keywords: Machine scheduling, Genetic algorithms, Due dates, Number of tardy jobs, Number of early jobs, Integer programming, Dual Fitness functions.
Procedia APA BibTeX Chicago EndNote Harvard JSON MLA RIS XML ISO 690 PDF Downloads 2058426 Experimental Measurements of Evacuated Enclosure Thermal Insulation Effectiveness for Vacuum Flat Plate Solar Thermal Collectors
Authors: Paul Henshall, Philip Eames, Roger Moss, Stan Shire, Farid Arya, Trevor Hyde
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Encapsulating the absorber of a flat plate solar thermal collector in vacuum by an enclosure that can be evacuated can result in a significant increase in collector performance and achievable operating temperatures. This is a result of the thermal insulation effectiveness of the vacuum layer surrounding the absorber, as less heat is lost during collector operation. This work describes experimental thermal insulation characterization tests of prototype vacuum flat plate solar thermal collectors that demonstrate the improvement in absorber heat loss coefficients. Furthermore, this work describes the selection and sizing of a getter, suitable for maintaining the vacuum inside the enclosure for the lifetime of the collector, which can be activated at low temperatures.
Keywords: Vacuum, thermal, flat-plate solar collector.
Procedia APA BibTeX Chicago EndNote Harvard JSON MLA RIS XML ISO 690 PDF Downloads 1618425 A Genetic and Simulated Annealing Based Algorithms for Solving the Flow Assignment Problem in Computer Networks
Authors: Tarek M. Mahmoud
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Selecting the routes and the assignment of link flow in a computer communication networks are extremely complex combinatorial optimization problems. Metaheuristics, such as genetic or simulated annealing algorithms, are widely applicable heuristic optimization strategies that have shown encouraging results for a large number of difficult combinatorial optimization problems. This paper considers the route selection and hence the flow assignment problem. A genetic algorithm and simulated annealing algorithm are used to solve this problem. A new hybrid algorithm combining the genetic with the simulated annealing algorithm is introduced. A modification of the genetic algorithm is also introduced. Computational experiments with sample networks are reported. The results show that the proposed modified genetic algorithm is efficient in finding good solutions of the flow assignment problem compared with other techniques.Keywords: Genetic Algorithms, Flow Assignment, Routing, Computer network, Simulated Annealing.
Procedia APA BibTeX Chicago EndNote Harvard JSON MLA RIS XML ISO 690 PDF Downloads 2244424 Effective Software-Based Solution for Processing Mass Downstream Data in Interactive Push VOD System
Authors: Ni Hong, Wu Guobin, Wu Gang, Pan Liang
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Interactive push VOD system is a new kind of system that incorporates push technology and interactive technique. It can push movies to users at high speeds at off-peak hours for optimal network usage so as to save bandwidth. This paper presents effective software-based solution for processing mass downstream data at terminals of interactive push VOD system, where the service can download movie according to a viewer-s selection. The downstream data is divided into two catalogs: (1) the carousel data delivered according to DSM-CC protocol; (2) IP data delivered according to Euro-DOCSIS protocol. In order to accelerate download speed and reduce data loss rate at terminals, this software strategy introduces caching, multi-thread and resuming mechanisms. The experiments demonstrate advantages of the software-based solution.Keywords: DSM-CC, data carousel, Euro-DOCSIS, push VOD.
Procedia APA BibTeX Chicago EndNote Harvard JSON MLA RIS XML ISO 690 PDF Downloads 1478423 An Algorithm for Determining the Arrival Behavior of a Secondary User to a Base Station in Cognitive Radio Networks
Authors: Danilo López, Edwin Rivas, Leyla López
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This paper presents the development of an algorithm that predicts the arrival of a secondary user (SU) to a base station (BS) in a cognitive network based on infrastructure, requesting a Best Effort (BE) or Real Time (RT) type of service with a determined bandwidth (BW) implementing neural networks. The algorithm dynamically uses a neural network construction technique using the geometric pyramid topology and trains a Multilayer Perceptron Neural Networks (MLPNN) based on the historical arrival of an SU to estimate future applications. This will allow efficiently managing the information in the BS, since it precedes the arrival of the SUs in the stage of selection of the best channel in CRN. As a result, the software application determines the probability of arrival at a future time point and calculates the performance metrics to measure the effectiveness of the predictions made.
Keywords: Cognitive radio, MLPNN, base station, prediction, best effort, real time.
Procedia APA BibTeX Chicago EndNote Harvard JSON MLA RIS XML ISO 690 PDF Downloads 1433422 Methane versus Carbon Dioxide: Mitigation Prospects
Authors: Alexander J. Severinsky, Allen L. Sessoms
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Atmospheric carbon dioxide (CO2) has dominated the discussion around the causes of climate change. This is a reflection of a 100-year time horizon for all greenhouse gases that became a norm. The 100-year time horizon is much too long – and yet, almost all mitigation efforts, including those set in the near-term frame of within 30 years, are still geared toward it. In this paper, we show that for a 30-year time horizon, methane (CH4) is the greenhouse gas whose radiative forcing exceeds that of CO2. In our analysis, we use the radiative forcing of greenhouse gases in the atmosphere, because they directly affect the rise in temperature on Earth. We found that in 2019, the radiative forcing (RF) of methane was ~2.5 W/m2 and that of carbon dioxide was ~2.1 W/m2. Under a business-as-usual (BAU) scenario until 2050, such forcing would be ~2.8 W/m2 and ~3.1 W/m2 respectively. There is a substantial spread in the data for anthropogenic and natural methane (CH4) emissions, along with natural gas, (which is primarily CH4), leakages from industrial production to consumption. For this reason, we estimate the minimum and maximum effects of a reduction of these leakages, and assume an effective immediate reduction by 80%. Such action may serve to reduce the annual radiative forcing of all CH4 emissions by ~15% to ~30%. This translates into a reduction of RF by 2050 from ~2.8 W/m2 to ~2.5 W/m2 in the case of the minimum effect that can be expected, and to ~2.15 W/m2 in the case of the maximum effort to reduce methane leakages. Under the BAU, we find that the RF of CO2 will increase from ~2.1 W/m2 now to ~3.1 W/m2 by 2050. We assume a linear reduction of 50% in anthropogenic emission over the course of the next 30 years, which would reduce the radiative forcing of CO2 from ~3.1 W/m2 to ~2.9 W/m2. In the case of "net zero," the other 50% of only anthropogenic CO2 emissions reduction would be limited to being either from sources of emissions or directly from the atmosphere. In this instance, the total reduction would be from ~3.1 W/m2 to ~2.7 W/m2, or ~0.4 W/m2. To achieve the same radiative forcing as in the scenario of maximum reduction of methane leakages of ~2.15 W/m2, an additional reduction of radiative forcing of CO2 would be approximately 2.7 -2.15 = 0.55 W/m2. In total, one would need to remove ~660 GT of CO2 from the atmosphere in order to match the maximum reduction of current methane leakages, and ~270 GT of CO2 from emitting sources, to reach "negative emissions". This amounts to over 900 GT of CO2.
Keywords: Methane Leakages, Methane Radiative Forcing, Methane Mitigation, Methane Net Zero.
Procedia APA BibTeX Chicago EndNote Harvard JSON MLA RIS XML ISO 690 PDF Downloads 615421 DC-to-DC Converters for Low-Voltage High-Power Renewable Energy Systems
Authors: Abdar Ali, Rizwan Ullah, Zahid Ullah
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This paper focuses on the study of DC-to-DC converters, which are suitable for low-voltage high-power applications. The output voltages generated by renewable energy sources such as photovoltaic arrays and fuel cell stacks are generally low and required to be increased to high voltage levels. Development of DC-to-DC converters, which provide high step-up voltage conversion ratios with high efficiencies and low voltage stresses, is one of the main issues in the development of renewable energy systems. A procedure for three converters−conventional DC-to-DC converter, interleaved boost converter, and isolated flyback based converter, is illustrated for a given set of specifications. The selection among the converters for the given application is based on the voltage conversion ratio, efficiency, and voltage stresses.Keywords: Flyback converter, interleaved boost, photovoltaic array, fuel cell, switch stress, voltage conversion ratio, renewable energy.
Procedia APA BibTeX Chicago EndNote Harvard JSON MLA RIS XML ISO 690 PDF Downloads 2770420 Dissolved Oxygen Prediction Using Support Vector Machine
Authors: Sorayya Malek, Mogeeb Mosleh, Sharifah M. Syed
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In this study, Support Vector Machine (SVM) technique was applied to predict the dichotomized value of Dissolved oxygen (DO) from two freshwater lakes namely Chini and Bera Lake (Malaysia). Data sample contained 11 parameters for water quality features from year 2005 until 2009. All data parameters were used to predicate the dissolved oxygen concentration which was dichotomized into 3 different levels (High, Medium, and Low). The input parameters were ranked, and forward selection method was applied to determine the optimum parameters that yield the lowest errors, and highest accuracy. Initial results showed that pH, Water Temperature, and Conductivity are the most important parameters that significantly affect the predication of DO. Then, SVM model was applied using the Anova kernel with those parameters yielded 74% accuracy rate. We concluded that using SVM models to predicate the DO is feasible, and using dichotomized value of DO yields higher prediction accuracy than using precise DO value.
Keywords: Dissolved oxygen, Water quality, predication DO, Support Vector Machine.
Procedia APA BibTeX Chicago EndNote Harvard JSON MLA RIS XML ISO 690 PDF Downloads 2207419 Feature Extraction for Surface Classification – An Approach with Wavelets
Authors: Smriti H. Bhandari, S. M. Deshpande
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Surface metrology with image processing is a challenging task having wide applications in industry. Surface roughness can be evaluated using texture classification approach. Important aspect here is appropriate selection of features that characterize the surface. We propose an effective combination of features for multi-scale and multi-directional analysis of engineering surfaces. The features include standard deviation, kurtosis and the Canny edge detector. We apply the method by analyzing the surfaces with Discrete Wavelet Transform (DWT) and Dual-Tree Complex Wavelet Transform (DT-CWT). We used Canberra distance metric for similarity comparison between the surface classes. Our database includes the surface textures manufactured by three machining processes namely Milling, Casting and Shaping. The comparative study shows that DT-CWT outperforms DWT giving correct classification performance of 91.27% with Canberra distance metric.
Keywords: Dual-tree complex wavelet transform, surface metrology, surface roughness, texture classification.
Procedia APA BibTeX Chicago EndNote Harvard JSON MLA RIS XML ISO 690 PDF Downloads 2232418 Structural Analysis of Username Segment in E-Mail Addresses of Engineering Institutes of Gujarat State of India
Authors: Jatinderkumar R. Saini
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E-mail has become a key mechanism of electronic communication. This is true for professional organizations that like to communicate with their subjects online and are slowly shifting to paper-less office. The current paper focuses specifically on academic institutions offering Engineering course in Gujarat state and attempts for textual analysis of the usernames of the institutional e-mail addresses. We found that the institutions tend to design the username segment of their e-mail addresses by choosing words or combination of words from specific categories. The paper also highlights the use of special characters, digits and random words in designing the usernames. On the sidelines, the paper lists the style of employing department names and designations for the design process. To the best of our knowledge, this is the first formal attempt to analyze the selection of words employed for designing username segment of e-mail addresses of engineering institutions.
Keywords: E-mail address, Institute, Engineering, Username.
Procedia APA BibTeX Chicago EndNote Harvard JSON MLA RIS XML ISO 690 PDF Downloads 1672417 Aerodynamic Analysis and Design of Banners for Remote-Controlled Aircraft
Authors: Peyman Honarmandi, Mazen Alhirsh
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Banner towing is a major form of advertisement. It consists of a banner showing a logo or a selection of words or letters being towed by an aircraft. Traditionally bush planes have been used to tow banners given their high thrust capabilities, however, with the development of Remote-Controlled (RC) aircraft, they could be a good replacement as RC planes mitigate the risk of human life and can be easier to operate. This paper studies the best banner design to be towed by an RC aircraft. This is done by conducting wind tunnel testing on an array of banners with different materials and designs. A pull gauge is used to record the drag force during testing which is then used to calculate the coefficient of drag, Cd. The testing results show that the best banner design would be a hybrid design with a solid and mesh material. The design with the lowest Cd of 0.082 was a half ripstop nylon half polyester mesh design. On the other hand, the design with highest Cd of 0.305 involved incorporating a tail chute to decrease fluttering.
Keywords: Aerodynamics of banner, banner design, banner towing, drag coefficients of banner, RC aircraft banner.
Procedia APA BibTeX Chicago EndNote Harvard JSON MLA RIS XML ISO 690 PDF Downloads 551416 Signal Driven Sampling and Filtering a Promising Approach for Time Varying Signals Processing
Authors: Saeed Mian Qaisar, Laurent Fesquet, Marc Renaudin
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The mobile systems are powered by batteries. Reducing the system power consumption is a key to increase its autonomy. It is known that mostly the systems are dealing with time varying signals. Thus, we aim to achieve power efficiency by smartly adapting the system processing activity in accordance with the input signal local characteristics. It is done by completely rethinking the processing chain, by adopting signal driven sampling and processing. In this context, a signal driven filtering technique, based on the level crossing sampling is devised. It adapts the sampling frequency and the filter order by analysing the input signal local variations. Thus, it correlates the processing activity with the signal variations. It leads towards a drastic computational gain of the proposed technique compared to the classical one.Keywords: Level Crossing Sampling, Activity Selection, Adaptive Rate Filtering, Computational Complexity.
Procedia APA BibTeX Chicago EndNote Harvard JSON MLA RIS XML ISO 690 PDF Downloads 1353415 Graphical Password Security Evaluation by Fuzzy AHP
Authors: Arash Habibi Lashkari, Azizah Abdul Manaf, Maslin Masrom
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In today's day and age, one of the important topics in information security is authentication. There are several alternatives to text-based authentication of which includes Graphical Password (GP) or Graphical User Authentication (GUA). These methods stems from the fact that humans recognized and remembers images better than alphanumerical text characters. This paper will focus on the security aspect of GP algorithms and what most researchers have been working on trying to define these security features and attributes. The goal of this study is to develop a fuzzy decision model that allows automatic selection of available GP algorithms by taking into considerations the subjective judgments of the decision makers who are more than 50 postgraduate students of computer science. The approach that is being proposed is based on the Fuzzy Analytic Hierarchy Process (FAHP) which determines the criteria weight as a linear formula.Keywords: Graphical Password, Authentication Security, Attack Patterns, Brute force attack, Dictionary attack, Guessing Attack, Spyware attack, Shoulder surfing attack, Social engineering Attack, Password Entropy, Password Space.
Procedia APA BibTeX Chicago EndNote Harvard JSON MLA RIS XML ISO 690 PDF Downloads 1925414 Hybrid Algorithm for Frequency Channel Selection in Wi-Fi Networks
Authors: Cesar Hernández, Diego Giral, Ingrid Páez
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This article proposes a hybrid algorithm for spectrum allocation in cognitive radio networks based on the algorithms Analytical Hierarchical Process (AHP) and Technique for Order of Preference by Similarity to Ideal Solution (TOPSIS) to improve the performance of the spectrum mobility of secondary users in cognitive radio networks. To calculate the level of performance of the proposed algorithm a comparative analysis between the proposed AHP-TOPSIS, Grey Relational Analysis (GRA) and Multiplicative Exponent Weighting (MEW) algorithm is performed. Four evaluation metrics are used. These metrics are accumulative average of failed handoffs, accumulative average of handoffs performed, accumulative average of transmission bandwidth, and accumulative average of the transmission delay. The results of the comparison show that AHP-TOPSIS Algorithm provides 2.4 times better performance compared to a GRA Algorithm and, 1.5 times better than the MEW Algorithm.Keywords: Cognitive radio, decision making, hybrid algorithm, spectrum handoff, wireless networks.
Procedia APA BibTeX Chicago EndNote Harvard JSON MLA RIS XML ISO 690 PDF Downloads 2150413 Selection of Extracurricular Education Facilities and Organizational Performance Analysis of Meg-city Spatial System
Authors: Chen Zhang, Wei Yaping
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With the rapid expansion of city scale and the excessive concentration of population, achieving relative equality of extracurricular education resources and improving spatial service performance of relevant facilities become necessary arduous tasks. In urban space, extracurricular education facilities should offer better service to its targeted area and promote the equality and efficiency of education, which is accomplished by the allocation of facilities. Based on questionnaire and survey for local students in Hangzhou City in 2009, this study classifies extracurricular education facilities in meg-city and defines the equalization of these facilities. Then it is suggested to establish extracurricular education facilities system according to the development level of city and demands of local students, and to introduce a spatial analysis method into urban planning through the aspects of spatial distribution, travel cost and spatial service scope. Finally, the practice of nine sub-districts of Hangzhou is studied.Keywords: extracurricular education facilities, equalization, spatial service performance, meg-city
Procedia APA BibTeX Chicago EndNote Harvard JSON MLA RIS XML ISO 690 PDF Downloads 1414412 Bio-inspired Audio Content-Based Retrieval Framework (B-ACRF)
Authors: Noor A. Draman, Campbell Wilson, Sea Ling
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Content-based music retrieval generally involves analyzing, searching and retrieving music based on low or high level features of a song which normally used to represent artists, songs or music genre. Identifying them would normally involve feature extraction and classification tasks. Theoretically the greater features analyzed, the better the classification accuracy can be achieved but with longer execution time. Technique to select significant features is important as it will reduce dimensions of feature used in classification and contributes to the accuracy. Artificial Immune System (AIS) approach will be investigated and applied in the classification task. Bio-inspired audio content-based retrieval framework (B-ACRF) is proposed at the end of this paper where it embraces issues that need further consideration in music retrieval performances.
Keywords: Bio-inspired audio content-based retrieval framework, features selection technique, low/high level features, artificial immune system
Procedia APA BibTeX Chicago EndNote Harvard JSON MLA RIS XML ISO 690 PDF Downloads 1584411 Determining the Best Fitting Distributions for Minimum Flows of Streams in Gediz Basin
Authors: Naci Büyükkaracığan
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Today, the need for water sources is swiftly increasing due to population growth. At the same time, it is known that some regions will face with shortage of water and drought because of the global warming and climate change. In this context, evaluation and analysis of hydrological data such as the observed trends, drought and flood prediction of short term flow has great deal of importance. The most accurate selection probability distribution is important to describe the low flow statistics for the studies related to drought analysis. As in many basins In Turkey, Gediz River basin will be affected enough by the drought and will decrease the amount of used water. The aim of this study is to derive appropriate probability distributions for frequency analysis of annual minimum flows at 6 gauging stations of the Gediz Basin. After applying 10 different probability distributions, six different parameter estimation methods and 3 fitness test, the Pearson 3 distribution and general extreme values distributions were found to give optimal results.
Keywords: Gediz Basin, goodness-of-fit tests, Minimum flows, probability distribution.
Procedia APA BibTeX Chicago EndNote Harvard JSON MLA RIS XML ISO 690 PDF Downloads 2498410 Accurate Fault Classification and Section Identification Scheme in TCSC Compensated Transmission Line using SVM
Authors: Pushkar Tripathi, Abhishek Sharma, G. N. Pillai, Indira Gupta
Abstract:
This paper presents a new approach for the protection of Thyristor-Controlled Series Compensator (TCSC) line using Support Vector Machine (SVM). One SVM is trained for fault classification and another for section identification. This method use three phase current measurement that results in better speed and accuracy than other SVM based methods which used single phase current measurement. This makes it suitable for real-time protection. The method was tested on 10,000 data instances with a very wide variation in system conditions such as compensation level, source impedance, location of fault, fault inception angle, load angle at source bus and fault resistance. The proposed method requires only local current measurement.Keywords: Fault Classification, Section Identification, Feature Selection, Support Vector Machine (SVM), Thyristor-Controlled Series Compensator (TCSC)
Procedia APA BibTeX Chicago EndNote Harvard JSON MLA RIS XML ISO 690 PDF Downloads 2508409 Natural Language Database Interface for Selection of Data Using Grammar and Parsing
Authors: N. D. Karande, G. A. Patil
Abstract:
Databases have become ubiquitous. Almost all IT applications are storing into and retrieving information from databases. Retrieving information from the database requires knowledge of technical languages such as Structured Query Language (SQL). However majority of the users who interact with the databases do not have a technical background and are intimidated by the idea of using languages such as SQL. This has led to the development of a few Natural Language Database Interfaces (NLDBIs). A NLDBI allows the user to query the database in a natural language. This paper highlights on architecture of new NLDBI system, its implementation and discusses on results obtained. In most of the typical NLDBI systems the natural language statement is converted into an internal representation based on the syntactic and semantic knowledge of the natural language. This representation is then converted into queries using a representation converter. A natural language query is translated to an equivalent SQL query after processing through various stages. The work has been experimented on primitive database queries with certain constraints.
Keywords: Natural language database interface, representation converter, syntactic and semantic knowledge
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