Search results for: satellite data
2713 Learning a Song: an ACT-R Model
Authors: Belkacem Chikhaoui, Helene Pigot, Mathieu Beaudoin, Guillaume Pratte, Philippe Bellefeuille, Fernando Laudares
Abstract:
The way music is interpreted by the human brain is a very interesting topic, but also an intricate one. Although this domain has been studied for over a century, many gray areas remain in the understanding of music. Recent advances have enabled us to perform accurate measurements of the time taken by the human brain to interpret and assimilate a sound. Cognitive computing provides tools and development environments that facilitate human cognition simulation. ACT-R is a cognitive architecture which offers an environment for implementing human cognitive tasks. This project combines our understanding of the music interpretation by a human listener and the ACT-R cognitive architecture to build SINGER, a computerized simulation for listening and recalling songs. The results are similar to human experimental data. Simulation results also show how it is easier to remember short melodies than long melodies which require more trials to be recalled correctly.
Keywords: Computational model, cognitive modeling, simulation, learning, song, music.
Procedia APA BibTeX Chicago EndNote Harvard JSON MLA RIS XML ISO 690 PDF Downloads 15532712 A Statistical Prediction of Likely Distress in Nigeria Banking Sector Using a Neural Network Approach
Authors: D. A. Farinde
Abstract:
One of the most significant threats to the economy of a nation is the bankruptcy of its banks. This study evaluates the susceptibility of Nigerian banks to failure with a view to identifying ratios and financial data that are sensitive to solvency of the bank. Further, a predictive model is generated to guide all stakeholders in the industry. Thirty quoted banks that had published Annual Reports for the year preceding the consolidation i.e. year 2004 were selected. They were examined for distress using the Multilayer Perceptron Neural Network Analysis. The model was used to analyze further reforms by the Central Bank of Nigeria using published Annual Reports of twenty quoted banks for the year 2008 and 2011. The model can thus be used for future prediction of failure in the Nigerian banking system.
Keywords: Bank, Bankruptcy, Financial Ratios, Neural Network, Multilayer Perceptron, Predictive Model
Procedia APA BibTeX Chicago EndNote Harvard JSON MLA RIS XML ISO 690 PDF Downloads 26892711 Train the Trainer: The Bricks in the Learning Community Scaffold of Professional Development
Authors: S. Pancucci
Abstract:
Professional development is the focus of this study. It reports on questionnaire data that examined the perceived effectiveness of the Train the Trainer model of technology professional development for elementary teachers. Eighty-three selected teachers called Information Technology Coaches received four half-day and one after-school in-service sessions. Subsequently, coaches shared the information and skills acquired during training with colleagues. Results indicated that participants felt comfortable as Information Technology Coaches and felt well prepared because of their technological professional development. Overall, participants perceived the Train the Trainer model to be effective. The outcomes of this study suggest that the use of the Train the Trainer model, a known professional development model, can be an integral and interdependent component of the newer more comprehensive learning community professional development model.Keywords: change, education, learning community, professional development, school improvement, technology coach, Train the Trainer.
Procedia APA BibTeX Chicago EndNote Harvard JSON MLA RIS XML ISO 690 PDF Downloads 26272710 Forecasting Direct Normal Irradiation at Djibouti Using Artificial Neural Network
Authors: Ahmed Kayad Abdourazak, Abderafi Souad, Zejli Driss, Idriss Abdoulkader Ibrahim
Abstract:
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 10672709 Ecological Networks: From Structural Analysis to Synchronization
Authors: N. F. F. Ebecken, G. C. Pereira
Abstract:
Ecological systems are exposed and are influenced by various natural and anthropogenic disturbances. They produce various effects and states seeking response symmetry to a state of global phase coherence or stability and balance of their food webs. This research project addresses the development of a computational methodology for modeling plankton food webs. The use of algorithms to establish connections, the generation of representative fuzzy multigraphs and application of technical analysis of complex networks provide a set of tools for defining, analyzing and evaluating community structure of coastal aquatic ecosystems, beyond the estimate of possible external impacts to the networks. Thus, this study aims to develop computational systems and data models to assess how these ecological networks are structurally and functionally organized, to analyze the types and degree of compartmentalization and synchronization between oscillatory and interconnected elements network and the influence of disturbances on the overall pattern of rhythmicity of the system.Keywords: Ecological networks, plankton food webs, fuzzy multigraphs, dynamic of networks.
Procedia APA BibTeX Chicago EndNote Harvard JSON MLA RIS XML ISO 690 PDF Downloads 19802708 Well-Being in Adolescence: Fitting Measurement Model
Authors: Azlina Abu Bakar, Abdul Fatah Wan Sidek
Abstract:
Well-being has been given special emphasis in quality of life. It involves living a meaningful, life satisfaction, stability and happiness in life. Well-being also concerns the satisfaction of physical, psychological, social needs and demands of an individual. The purpose of this study was to validate three-factor measurement model of well-being using structural equation modeling (SEM). The conceptions of well-being measured such dimensions as physical, psychological and social well-being. This study was done based on a total sample of 650 adolescents from east-coast of peninsular Malaysia. The Well-Being Scales which was adapted from [1] was used in this study. The items were hypothesized a priori to have nonzero loadings on all dimensions in the model. The findings of the SEM demonstrated that it is a good fitting model which the proposed model fits the driving theory; (x2df = 1.268; GFI = .994; CFI = .998; TLI= .996; p = .255; RMSEA = .021). Composite reliability (CR) was .93 and average variance extracted (AVE) was 58%. The model in this study fits with the sample of data and well-being is important to bring sustainable development to the mainstream.Keywords: Adolescence, Structural Equation Modeling, Sustainable Development, Well-Being.
Procedia APA BibTeX Chicago EndNote Harvard JSON MLA RIS XML ISO 690 PDF Downloads 30612707 A New Technique for Solar Activity Forecasting Using Recurrent Elman Networks
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.
Procedia APA BibTeX Chicago EndNote Harvard JSON MLA RIS XML ISO 690 PDF Downloads 18462706 MIMO Broadcast Scheduling for Weighted Sum-rate Maximization
Authors: Swadhin Kumar Mishra, Sidhartha Panda, C. Ardil
Abstract:
Multiple-Input-Multiple-Output (MIMO) is one of the most important communication techniques that allow wireless systems to achieve higher data rate. To overcome the practical difficulties in implementing Dirty Paper Coding (DPC), various suboptimal MIMO Broadcast (MIMO-BC) scheduling algorithms are employed which choose the best set of users among all the users. In this paper we discuss such a sub-optimal MIMO-BC scheduling algorithm which employs antenna selection at the receiver side. The channels for the users considered here are not Identical and Independent Distributed (IID) so that users at the receiver side do not get equal opportunity for communication. So we introduce a method of applying weights to channels of the users which are not IID in such a way that each of the users gets equal opportunity for communication. The effect of weights on overall sum-rate achieved by the system has been investigated and presented.
Keywords: Antenna selection, Identical and Independent Distributed (IID), Sum-rate capacity, Weighted sum rate.
Procedia APA BibTeX Chicago EndNote Harvard JSON MLA RIS XML ISO 690 PDF Downloads 15822705 Assessment of the Validity of Sentiment Analysis as a Tool to Analyze the Emotional Content of Text
Authors: Trisha Malhotra
Abstract:
Sentiment analysis is a recent field of study that computationally assesses the emotional nature of a body of text. To assess its test-validity, sentiment analysis was carried out on the emotional corpus of text from a personal 15-day mood diary. Self-reported mood scores varied more or less accurately with daily mood evaluation score given by the software. On further assessment, it was found that while sentiment analysis was good at assessing ‘global’ mood, it was not able to ‘locally’ identify and differentially score synonyms of various emotional words. It is further critiqued for treating the intensity of an emotion as universal across cultures. Finally, the software is shown not to account for emotional complexity in sentences by treating emotions as strictly positive or negative. Hence, it is posited that a better output could be two (positive and negative) affect scores for the same body of text.
Keywords: Analysis, data, diary, emotions, mood, sentiment.
Procedia APA BibTeX Chicago EndNote Harvard JSON MLA RIS XML ISO 690 PDF Downloads 11112704 Reactive Neural Control for Phototaxis and Obstacle Avoidance Behavior of Walking Machines
Authors: Poramate Manoonpong, Frank Pasemann, Florentin Wörgötter
Abstract:
This paper describes reactive neural control used to generate phototaxis and obstacle avoidance behavior of walking machines. It utilizes discrete-time neurodynamics and consists of two main neural modules: neural preprocessing and modular neural control. The neural preprocessing network acts as a sensory fusion unit. It filters sensory noise and shapes sensory data to drive the corresponding reactive behavior. On the other hand, modular neural control based on a central pattern generator is applied for locomotion of walking machines. It coordinates leg movements and can generate omnidirectional walking. As a result, through a sensorimotor loop this reactive neural controller enables the machines to explore a dynamic environment by avoiding obstacles, turn toward a light source, and then stop near to it.Keywords: Recurrent neural networks, Walking robots, Modular neural control, Phototaxis, Obstacle avoidance behavior.
Procedia APA BibTeX Chicago EndNote Harvard JSON MLA RIS XML ISO 690 PDF Downloads 17182703 Continuity Planning in Supply Chain Networks: Degrees of Freedom and Application in the Risk Management Process
Authors: Marco Bötel, Tobias Gelau, Wendelin Gross
Abstract:
Supply chain networks are frequently hit by unplanned events which lead to disruptions and cause operational and financial consequences. It is neither possible to avoid disruption risk entirely, nor are network members able to prepare for every possible disruptive event. Therefore a continuity planning should be set up which supports effective operational responses in supply chain networks in times of emergencies. In this research network related degrees of freedom which determine the options for responsive actions are derived from interview data. The findings are further embedded into a common risk management process. The paper provides support for researchers and practitioners to identify the network related options for responsive actions and to determine the need for improving the reaction capabilities.Keywords: Supply Chain Risk Management, Business Continuity Planning, Degrees of Freedom, Risk Management Process, Mitigation Measures.
Procedia APA BibTeX Chicago EndNote Harvard JSON MLA RIS XML ISO 690 PDF Downloads 19062702 Restriction Specificity of Some Soybean Genotypes to Bradyrhizobium japonicum Serogrous
Authors: H.K. Abd El-Maksoud, H.H. Keyser
Abstract:
Competitive relationships among Bradyrhizobium japonicum USDA serogroup 123, 122 and 138 were screened versus the standard commercial soybean variety Williams and two introductions P1 377578 "671" in a field trial. Displacement of strain 123 by an effective strain should improved N2 fixation. Root nodules were collected and strain occupancy percentage was determined using strain specific fluorescent antibodies technique. As anticipated the strain USDA 123 dominated 92% of nodules due to the high affinity between the host and the symbiont. This dominance was consistent and not changed materially either by inoculation practice or by introducing new strainan. The interrelationship between the genotype Williams and serogroup 122 & 138 was found very weak although the cell density of the strain in the rhizosphere area was equal. On the other hand, the nodule occupancy of genotypes 671 and 166 with rhizobia serogroup 123 was almost diminished to zero. . The data further exhibited that the genotypes P1 671 and P1 166 have high affinity to colonize with strains 122 and 138 whereas Williams was highly promiscuous to strain 123.Keywords: B. japonicum serogroups, Competition, Host restriction, Soybean genotype.
Procedia APA BibTeX Chicago EndNote Harvard JSON MLA RIS XML ISO 690 PDF Downloads 13662701 Design and Implementation of Shared Memory based Parallel File System Logging Method for High Performance Computing
Authors: Hyeyoung Cho, Sungho Kim, SangDong Lee
Abstract:
I/O workload is a critical and important factor to analyze I/O pattern and file system performance. However tracing I/O operations on the fly distributed parallel file system is non-trivial due to collection overhead and a large volume of data. In this paper, we design and implement a parallel file system logging method for high performance computing using shared memory-based multi-layer scheme. It minimizes the overhead with reduced logging operation response time and provides efficient post-processing scheme through shared memory. Separated logging server can collect sequential logs from multiple clients in a cluster through packet communication. Implementation and evaluation result shows low overhead and high scalability of this architecture for high performance parallel logging analysis.Keywords: I/O workload, PVFS, I/O Trace.
Procedia APA BibTeX Chicago EndNote Harvard JSON MLA RIS XML ISO 690 PDF Downloads 15522700 Portfolio Management: A Fuzzy Set Based Approach to Monitoring Size to Maximize Return and Minimize Risk
Authors: Margaret F. Shipley
Abstract:
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,
Procedia APA BibTeX Chicago EndNote Harvard JSON MLA RIS XML ISO 690 PDF Downloads 18382699 Development of a Sliding-tearing Mode Fracture Mechanical Tool for Laminated Composite Materials
Authors: Andras Szekrenyes
Abstract:
This work presents the mixed-mode II/III prestressed split-cantilever beam specimen for the fracture testing of composite materials. In accordance with the concept of prestressed composite beams one of the two fracture modes is provided by the prestressed state of the specimen, and the other one is increased up to fracture initiation by using a testing machine. The novel beam-like specimen is able to provide any combination of the mode-II and mode-III energy release rates. A simple closed-form solution is developed using beam theory as a data reduction scheme and for the calculation of the energy release rates in the new configuration. The applicability and the limitations of the novel fracture mechanical test are demonstrated using unidirectional glass/polyester composite specimens. If only crack propagation onset is involved then the mixed-mode beam specimen can be used to obtain the fracture criterion of transparent composite materials in the GII - GIII plane in a relatively simple way.
Keywords: Composite, fracture mechanics, toughness testing, mixed-mode II/III fracture.
Procedia APA BibTeX Chicago EndNote Harvard JSON MLA RIS XML ISO 690 PDF Downloads 19312698 A Comparison between Hybrid and Experimental Extended Polars for the Numerical Prediction of Vertical-Axis Wind Turbine Performance using Blade Element-Momentum Algorithm
Authors: Gabriele Bedon, Marco Raciti Castelli, Ernesto Benini
Abstract:
A dynamic stall-corrected Blade Element-Momentum algorithm based on a hybrid polar is validated through the comparison with Sandia experimental measurements on a 5-m diameter wind turbine of Troposkien shape. Different dynamic stall models are evaluated. The numerical predictions obtained using the extended aerodynamic coefficients provided by both Sheldal and Klimas and Raciti Castelli et al. are compared to experimental data, determining the potential of the hybrid database for the numerical prediction of vertical-axis wind turbine performances.
Keywords: Darrieus wind turbine, Blade Element-Momentum Theory, extended airfoil database, hybrid database, Sandia 5-m wind turbine.
Procedia APA BibTeX Chicago EndNote Harvard JSON MLA RIS XML ISO 690 PDF Downloads 25472697 Case Studies of CSAMT Method Applied to Study of Complex Rock Mass Structure and Hidden Tectonic
Authors: Yuxin Chen, Qingyun Di, C. Dinis da Gama
Abstract:
In projects like waterpower, transportation and mining, etc., proving up the rock-mass structure and hidden tectonic to estimate the geological body-s activity is very important. Integrating the seismic results, drilling and trenching data, CSAMT method was carried out at a planning dame site in southwest China to evaluate the stability of a deformation. 2D and imitated 3D inversion resistivity results of CSAMT method were analyzed. The results indicated that CSAMT was an effective method for defining an outline of deformation body to several hundred meters deep; the Lung Pan Deformation was stable in natural conditions; but uncertain after the future reservoir was impounded. This research presents a good case study of the fine surveying and research on complex geological structure and hidden tectonic in engineering project.Keywords: CSAMT Surveying, Deformation Stability.
Procedia APA BibTeX Chicago EndNote Harvard JSON MLA RIS XML ISO 690 PDF Downloads 24322696 Simulation of Particle Damping under Centrifugal Loads
Authors: Riaz A. Bhatti, Wang Yanrong
Abstract:
Particle damping is a technique to reduce the structural vibrations by means of placing small metallic particles inside a cavity that is attached to the structure at location of high vibration amplitudes. In this paper, we have presented an analytical model to simulate the particle damping of two dimensional transient vibrations in structure operating under high centrifugal loads. The simulation results show that this technique remains effective as long as the ratio of the dynamic acceleration of the structure to the applied centrifugal load is more than 0.1. Particle damping increases with the increase of particle to structure mass ratio. However, unlike to the case of particle damping in the absence of centrifugal loads where the damping efficiency strongly depends upon the size of the cavity, here this dependence becomes very weak. Despite the simplicity of the model, the simulation results are considerably in good agreement with the very scarce experimental data available in the literature for particle damping under centrifugal loads.Keywords: Impact damping, particle damping, vibration control, vibration suppression.
Procedia APA BibTeX Chicago EndNote Harvard JSON MLA RIS XML ISO 690 PDF Downloads 17912695 Influence of Noise on the Inference of Dynamic Bayesian Networks from Short Time Series
Authors: Frank Emmert Streib, Matthias Dehmer, Gökhan H. Bakır, Max Mühlhauser
Abstract:
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.
Procedia APA BibTeX Chicago EndNote Harvard JSON MLA RIS XML ISO 690 PDF Downloads 16032694 Connectionist Approach to Generic Text Summarization
Authors: Rajesh S.Prasad, U. V. Kulkarni, Jayashree.R.Prasad
Abstract:
As the enormous amount of on-line text grows on the World-Wide Web, the development of methods for automatically summarizing this text becomes more important. The primary goal of this research is to create an efficient tool that is able to summarize large documents automatically. We propose an Evolving connectionist System that is adaptive, incremental learning and knowledge representation system that evolves its structure and functionality. In this paper, we propose a novel approach for Part of Speech disambiguation using a recurrent neural network, a paradigm capable of dealing with sequential data. We observed that connectionist approach to text summarization has a natural way of learning grammatical structures through experience. Experimental results show that our approach achieves acceptable performance. Procedia APA BibTeX Chicago EndNote Harvard JSON MLA RIS XML ISO 690 PDF Downloads 15762693 Developing Digital Competencies in Aboriginal Students through University-College Partnerships
Authors: W. S. Barber, S. L. King
Abstract:
This paper reports on a pilot project to develop a collaborative partnership between a community college in rural northern Ontario, Canada, and an urban university in the greater Toronto area in Oshawa, Canada. Partner institutions will collaborate to address learning needs of university applicants whose goals are to attain an undergraduate university BA in Educational Studies and Digital Technology degree, but who may not live in a geographical location that would facilitate this pathways process. The UOIT BA degree is attained through a 2+2 program, where students with a 2 year college diploma or equivalent can attain a four year undergraduate degree. The goals reported on the project are as: 1. Our aim is to expand the BA program to include an additional stream which includes serious educational games, simulations and virtual environments, 2. Develop fully (using both synchronous and asynchronous technologies) online learning modules for use by university applicants who otherwise are not geographically located close to a physical university site, 3. Assess the digital competencies of all students, including members of local, distance and Indigenous communities using a validated tool developed and tested by UOIT across numerous populations. This tool, the General Technical Competency Use and Scale (GTCU) will provide the collaborating institutions with data that will allow for analyzing how well students are prepared to succeed in fully online learning communities. Philosophically, the UOIT BA program is based on a fully online learning communities model (FOLC) that can be accessed from anywhere in the world through digital learning environments via audio video conferencing tools such as Adobe Connect. It also follows models of adult learning and mobile learning, and makes a university degree accessible to the increasing demographic of adult learners who may use mobile devices to learn anywhere anytime. The program is based on key principles of Problem Based Learning, allowing students to build their own understandings through the co-design of the learning environment in collaboration with the instructors and their peers. In this way, this degree allows students to personalize and individualize the learning based on their own culture, background and professional/personal experiences. Using modified flipped classroom strategies, students are able to interrogate video modules on their own time in preparation for one hour discussions occurring in video conferencing sessions. As a consequence of the program flexibility, students may continue to work full or part time. All of the partner institutions will co-develop four new modules, administer the GTCU and share data, while creating a new stream of the UOIT BA degree. This will increase accessibility for students to bridge from community colleges to university through a fully digital environment. We aim to work collaboratively with Indigenous elders, community members and distance education instructors to increase opportunities for more students to attain a university education.
Keywords: Aboriginal, college, competencies, digital, universities.
Procedia APA BibTeX Chicago EndNote Harvard JSON MLA RIS XML ISO 690 PDF Downloads 7752692 Optimizing Hadoop Block Placement Policy and Cluster Blocks Distribution
Authors: Nchimbi Edward Pius, Liu Qin, Fion Yang, Zhu Hong Ming
Abstract:
The current Hadoop block placement policy do not fairly and evenly distributes replicas of blocks written to datanodes in a Hadoop cluster.
This paper presents a new solution that helps to keep the cluster in a balanced state while an HDFS client is writing data to a file in Hadoop cluster. The solution had been implemented, and test had been conducted to evaluate its contribution to Hadoop distributed file system.
It has been found that, the solution has lowered global execution time taken by Hadoop balancer to 22 percent. It also has been found that, Hadoop balancer respectively over replicate 1.75 and 3.3 percent of all re-distributed blocks in the modified and original Hadoop clusters.
The feature that keeps the cluster in a balanced state works as a core part to Hadoop system and not just as a utility like traditional balancer. This is one of the significant achievements and uniqueness of the solution developed during the course of this research work.
Keywords: Balancer, Datanode, Distributed file system, Hadoop, Replicas.
Procedia APA BibTeX Chicago EndNote Harvard JSON MLA RIS XML ISO 690 PDF Downloads 49412691 Neural Networks for Short Term Wind Speed Prediction
Authors: K. Sreelakshmi, P. Ramakanthkumar
Abstract:
Predicting short term wind speed is essential in order to prevent systems in-action from the effects of strong winds. It also helps in using wind energy as an alternative source of energy, mainly for Electrical power generation. Wind speed prediction has applications in Military and civilian fields for air traffic control, rocket launch, ship navigation etc. The wind speed in near future depends on the values of other meteorological variables, such as atmospheric pressure, moisture content, humidity, rainfall etc. The values of these parameters are obtained from a nearest weather station and are used to train various forms of neural networks. The trained model of neural networks is validated using a similar set of data. The model is then used to predict the wind speed, using the same meteorological information. This paper reports an Artificial Neural Network model for short term wind speed prediction, which uses back propagation algorithm.Keywords: Short term wind speed prediction, Neural networks, Back propagation.
Procedia APA BibTeX Chicago EndNote Harvard JSON MLA RIS XML ISO 690 PDF Downloads 30522690 Parametric Studies of Wood Pyrolysis Particles
Authors: W. Afef, A. Mohamed Ammar, G. Kamel, O. Ahmed
Abstract:
In the present study, a numerical approach to describe the pyrolysis of a single solid particle of wood is used to study the influence of various conditions such as particle size, heat transfer coefficient, reactor temperature and heating rate. The influence of these parameters in the change of the duration of the pyrolysis cycle was studied. Mathematical modeling was employed to simulate the heat, mass transfer, and kinetic processes inside the reactor. The evolutions of the mass loss as well as the evolution of temperature inside the thick piece are investigated numerically. The elaborated model was also employed to study the effect of the reactor temperature and the rate of heating on the change of the temperature and the local loss of the mass inside the piece of wood. The obtained results are in good agreement with the experimental data available in the literature.
Keywords: Wood, Pyrolysis, Modeling, Convective heat transfer, Kinetic.
Procedia APA BibTeX Chicago EndNote Harvard JSON MLA RIS XML ISO 690 PDF Downloads 13662689 Modeling Nanomechanical Behavior of ZnO Nanowires as a Function of Nano-Diameter
Authors: L. Achou, A. Doghmane
Abstract:
Elastic performances, as an essential property of nanowires (NWs), play a significant role in the design and fabrication of modern nanodevices. In this paper, our interest is focused on ZnO NWs to investigate wire diameter (Dwire ≤ 400 nm) effects on elastic properties. The plotted data reveal that a strong size dependence of the elastic constants exists when the wire diameter is smaller than ~ 100 nm. For larger diameters (Dwire > 100 nm), these ones approach their corresponding bulk values. To enrich this study, we make use of the scanning acoustic microscopy simulation technique. The calculation methodology consists of several steps: determination of longitudinal and transverse wave velocities, calculation of refection coefficients, calculation of acoustic signatures and Rayleigh velocity determination. Quantitatively, it was found that changes in ZnO diameters over the ranges 1 nm ≤ Dwire ≤ 100 nm lead to similar exponential variations, for all elastic parameters, of the from: A = a + b exp(-Dwire/c) where a, b, and c are characteristic constants of a given parameter. The developed relation can be used to predict elastic properties of such NW by just knowing its diameter and vice versa.Keywords: Elastic properties, nanowires, semiconductors, ZnO.
Procedia APA BibTeX Chicago EndNote Harvard JSON MLA RIS XML ISO 690 PDF Downloads 9672688 An Anonymity-Based Secure On-Demand Routing for Mobile Ad Hoc Networks
Authors: M. Gunasekaran, K. Premalatha
Abstract:
Privacy and Security have emerged as an important research issue in Mobile Ad Hoc Networks (MANET) due to its unique nature such as scarce of resources and absence of centralized authority. There are number of protocols have been proposed to provide privacy and security for data communication in an adverse environment, but those protocols are compromised in many ways by the attackers. The concept of anonymity (in terms of unlinkability and unobservability) and pseudonymity has been introduced in this paper to ensure privacy and security. In this paper, a Secure Onion Throat (SOT) protocol is proposed to provide complete anonymity in an adverse environment. The SOT protocol is designed based on the combination of group signature and onion routing with ID-based encryption for route discovery. The security analysis demonstrates the performance of SOT protocol against all categories of attacks. The simulation results ensure the necessity and importance of the proposed SOT protocol in achieving such anonymity.
Keywords: Routing, anonymity, privacy, security and MANET.
Procedia APA BibTeX Chicago EndNote Harvard JSON MLA RIS XML ISO 690 PDF Downloads 27312687 ANN Models for Microstrip Line Synthesis and Analysis
Authors: Dr.K.Sri Rama Krishna, J.Lakshmi Narayana, Dr.L.Pratap Reddy
Abstract:
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
Procedia APA BibTeX Chicago EndNote Harvard JSON MLA RIS XML ISO 690 PDF Downloads 21392686 Texture Characterization Based on a Chandrasekhar Fast Adaptive Filter
Authors: Mounir Sayadi, Farhat Fnaiech
Abstract:
In the framework of adaptive parametric modelling of images, we propose in this paper a new technique based on the Chandrasekhar fast adaptive filter for texture characterization. An Auto-Regressive (AR) linear model of texture is obtained by scanning the image row by row and modelling this data with an adaptive Chandrasekhar linear filter. The characterization efficiency of the obtained model is compared with the model adapted with the Least Mean Square (LMS) 2-D adaptive algorithm and with the cooccurrence method features. The comparison criteria is based on the computation of a characterization degree using the ratio of "betweenclass" variances with respect to "within-class" variances of the estimated coefficients. Extensive experiments show that the coefficients estimated by the use of Chandrasekhar adaptive filter give better results in texture discrimination than those estimated by other algorithms, even in a noisy context.
Keywords: Texture analysis, statistical features, adaptive filters, Chandrasekhar algorithm.
Procedia APA BibTeX Chicago EndNote Harvard JSON MLA RIS XML ISO 690 PDF Downloads 16072685 A Relationship Extraction Method from Literary Fiction Considering Korean Linguistic Features
Authors: Hee-Jeong Ahn, Kee-Won Kim, Seung-Hoon Kim
Abstract:
The knowledge of the relationship between characters can help readers to understand the overall story or plot of the literary fiction. In this paper, we present a method for extracting the specific relationship between characters from a Korean literary fiction. Generally, methods for extracting relationships between characters in text are statistical or computational methods based on the sentence distance between characters without considering Korean linguistic features. Furthermore, it is difficult to extract the relationship with direction from text, such as one-sided love, because they consider only the weight of relationship, without considering the direction of the relationship. Therefore, in order to identify specific relationships between characters, we propose a statistical method considering linguistic features, such as syntactic patterns and speech verbs in Korean. The result of our method is represented by a weighted directed graph of the relationship between the characters. Furthermore, we expect that proposed method could be applied to the relationship analysis between characters of other content like movie or TV drama.
Keywords: Data mining, Korean linguistic feature, literary fiction, relationship extraction.
Procedia APA BibTeX Chicago EndNote Harvard JSON MLA RIS XML ISO 690 PDF Downloads 17882684 Developing Models for Predicting Physiologically Impaired Arm Reaching Paths
Authors: Nina Robson, Kenneth John Faller II, Vishalkumar Ahir, Mustafa Mhawesh, Reza Langari
Abstract:
This paper describes the development of a model of an impaired human arm performing a reaching motion, which will be used to predict hand path trajectories for people with reduced arm joint mobility. Assuming that the arm was in contact with a surface during the entire movement, the contact conditions at the initial and final task locations were determined and used to generate the entire trajectory. The model was validated by comparing it to experimental data, which simulated an arm joint impairment by physically constraining the joint motion with a brace. Future research will include using the model in the development of physical training protocols that avoid early recruitment of “healthy” Degrees-Of-Freedom (DOF) for reaching motions, thus facilitating an Active Range-Of-Motion Recovery (AROM) for a particular impaired joint.Keywords: Higher order kinematic specifications, human motor coordination, impaired movement, kinematic synthesis.
Procedia APA BibTeX Chicago EndNote Harvard JSON MLA RIS XML ISO 690 PDF Downloads 1080