Search results for: modulation based on Sub-Nyquist sampling jamming method
Commenced in January 2007
Frequency: Monthly
Edition: International
Paper Count: 16375

Search results for: modulation based on Sub-Nyquist sampling jamming method

2365 Dynamic Performances of Tubular Linear Induction Motor for Pneumatic Capsule Pipeline System

Authors: Wisuwat Plodpradista

Abstract:

Tubular linear induction motor (TLIM) can be used as a capsule pump in a large pneumatic capsule pipeline (PCP) system. Parametric performance evaluation of the designed 1-meter diameter PCP-TLIM system yields encouraging results for practical implementation. The capsule thrust and speed inside the TLIM pump can be calculated from the combination of the PCP fluid mechanics and the TLIM equations. The TLIM equivalent circuits derived from those of the conventional three-phase induction motor are used as a model to predict the static test results of a small-scale PCP-TLIM system. In this paper, additional dynamic tests are performed on the same small-scale PCP-TLIM system with two capsules of different diameters. The behaviors of the capsule inside the pump are observed and analyzed. The dynamic performances from the dynamic tests are compared with the theoretical predictions based on the TLIM equivalent circuit model.

Keywords: Pneumatic capsule pipeline, Tubular linear induction motor

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2364 Use of Cultural Symbols for Transferring House to the Home in the Case of Famagusta

Authors: M. Sokhanvar, S. M. Shahidipour

Abstract:

One of the essential requirements for the human beings is the house for living. This is necessary to make the place of satisfaction for contemporary houses residents by attention to their culture. In this article represented the relevant theoretical literature on cultural symbols by use the architecture semiotic to construct the houses as a better place for living. In fact, make a place for everyday life with changing the house to the home is one of the most challengeable subject for architects all around the world. The target of this article is to find Cypriot houses cultural symbols that assist architect to design and build contemporary houses, to make more satisfaction for its residents according to Cypriot life style and their culture. This paper is based on researching the effect of cultural symbols on housing, would require various types of methods. However, this study focuses on two methods, which are quantitative and qualitative. The purpose of the case-specific study is to finding the symbols that used in contemporary houses by attention to the Cypriot cultural symbols in Famagusta houses.

Keywords: Houses, home, architectural symbols, cultural symbols.

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2363 Variant Polymorphisms of GST and XRCC Genes and the Early Risk of Age Associated Disease in Kazakhstan

Authors: Zeinep A. Berkimbayeva, Almagul T. Mansharipova, Elmira M. Khussainova, Leyla B. Djansugurova

Abstract:

It is believed that DNA damaging toxic metabolites contributes to the development of different pathological conditions. To prevent harmful influence of toxic agents, cells developed number of protecting mechanisms, such as enzymatic reaction of detoxification of reactive metabolites and repair of DNA damage. The aim of the study was to examine the association between polymorphism of GSTT1/GSTM1 and XRCC1/3 genes and coronary artery disease (CAD) incidence. To examine a polymorphism of these genes in CAD susceptibility in patients and controls, PCR based genotyping assay was performed. For GST genes, frequency of GSTM1 null genotype among CAD affected group was significantly increased than in control group (P<0.001). Frequencies of the GSTT1 null and positive alleles are almost equal in both groups (P>0.1). We found that neither XRCC1 Arg399Gln nor XRCC3 Thr241Met were associated with CAD risk. Obtained data suggests that GSTM1 null genotype carriers are more susceptible to CAD development.

Keywords: Cardiovascular disease, DNA reparation, gene polymorphism, risk factors, xenobiotic detoxification.

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2362 A Quantitative Study Identifying the Prevalence of Anxiety in Dyslexic Students in Higher Education

Authors: Amanda Abbott-Jones

Abstract:

Adult students with dyslexia in higher education can receive support for their cognitive needs but may also experience negative emotion such as anxiety due to their dyslexia in connection with their studies. This paper aims to test the hypothesis that adult dyslexic learners have a higher prevalence of academic and social anxiety than their non-dyslexic peers. A quantitative approach was used to measure differences in academic and social anxiety between 102 students with a formal diagnosis of dyslexia compared to 72 students with no history of learning difficulties. Academic and social anxiety was measured in a questionnaire based on the State-Trait Anxiety Inventory. Findings showed that dyslexic students showed statistically significant higher levels of academic, but not social anxiety in comparison to the non-dyslexic sample. Dyslexic students in higher education show academic anxiety levels that are well above what is shown by students without dyslexia. The implications of this for the dyslexia practitioner is that delivery of strategies to deal with anxiety should be seen equally as important, if not more so, than interventions to deal with cognitive difficulties.

Keywords: Academic, anxiety, dyslexia, quantitative, students, university.

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2361 Modelling Conditional Volatility of Saving Rate by a Time-Varying Parameter Model

Authors: Katleho D. Makatjane, Kalebe M. Kalebe

Abstract:

The present paper used time-varying parameters which are based on the score function of a probability density at time t to model volatility of saving rate. We used a scaled likelihood function to update the parameters of the model overtime. Our results revealed high diligence of time-varying since the location parameter is greater than zero. Furthermore, we discovered a leptokurtic condition on saving rate’s distribution. Kapetanios, Shin-Shell Nonlinear Augmented Dickey-Fuller (KSS-NADF) test showed that the saving rate has a nonlinear unit root; therefore, it can be modeled by a generalised autoregressive score (GAS) model. Additionally, value at risk (VaR) and conditional tail expectation (CTE) indicate that 99% of the time people in Lesotho are saving more than spending. This puts the economy in high risk of not expanding. Therefore, the monetary policy committee (MPC) of Lesotho should revise their monetary policies towards this high saving rates risk.

Keywords: Generalized autoregressive score, time-varying, saving rate, Lesotho.

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2360 A Quality Optimization Approach: An Application on Next Generation Networks

Authors: Gülfem I. Alptekin, S. Emre Alptekin

Abstract:

The next generation wireless systems, especially the cognitive radio networks aim at utilizing network resources more efficiently. They share a wide range of available spectrum in an opportunistic manner. In this paper, we propose a quality management model for short-term sub-lease of unutilized spectrum bands to different service providers. We built our model on competitive secondary market architecture. To establish the necessary conditions for convergent behavior, we utilize techniques from game theory. Our proposed model is based on potential game approach that is suitable for systems with dynamic decision making. The Nash equilibrium point tells the spectrum holders the ideal price values where profit is maximized at the highest level of customer satisfaction. Our numerical results show that the price decisions of the network providers depend on the price and QoS of their own bands as well as the prices and QoS levels of their opponents- bands.

Keywords: cognitive radio networks, game theory, nextgeneration wireless networks, spectrum management.

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2359 Extending the Flipped Classroom Approach: Using Technology in Module Delivery to Students of English Language and Literature at the British University in Egypt

Authors: Azza Taha Zaki

Abstract:

Technology-enhanced teaching has been in the limelight since the 90s when educators started investigating and experimenting with using computers in the classroom as a means of building 21st. century skills and motivating students. The concept of technology-enhanced strategies in education is kaleidoscopic! It has meant different things to different educators. For the purpose of this paper, however, it will be used to refer to the diverse technology-based strategies used to support and enrich the flipped learning process, in the classroom and outside. The paper will investigate how technology is put in the service of teaching and learning to improve the students’ learning experience as manifested in students’ attendance and engagement, achievement rates and finally, students’ projects at the end of the semester. The results will be supported by a student survey about relevant specific aspects of their learning experience in the modules in the study.

Keywords: Attendance, British University, Egypt, flipped, student achievement, student-centred, student engagement, students’ projects.

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2358 k-Neighborhood Template A-Type Three-Dimensional Bounded Cellular Acceptor

Authors: Makoto Nagatomo, Yasuo Uchida, Makoto Sakamoto, Tuo Zhang, Tatsuma Kurogi, Takao Ito, Tsunehiro Yoshinaga, Satoshi Ikeda, Masahiro Yokomichi, Hiroshi Furutani

Abstract:

This paper presents a four-dimensional computational model, k-neighborhood template A-type three-dimensional bounded cellular acceptor (abbreviated as A-3BCA(k)), and discusses the hierarchical properties. An A-3BCA(k) is a four-dimensional automaton which consists of a pair of a converter and a configuration-reader. The former converts the given four-dimensional tape to the three- and two- dimensional configuration and the latter determines the acceptance or nonacceptance of given four-dimensional tape whether or not the derived two-dimensional configuration is accepted. We mainly investigate the difference of the accepting power based on the difference of the configuration-reader. It is shown that the difference of the accepting power of the configuration-reader tends to affect directly that of the A-3BCA(k) for the case when the converter is deterministic. On the other hand, results are not analogous for the nondeterministic case.

Keywords: Cellular acceptor, configuration-reader, converter, finite automaton, four-dimension, on-line tessellation acceptor, parallel/sequential array acceptor, turing machine.

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2357 In Vitro and Experimental Screening of Mangrove Herbal Extract against Vibrio Alginolyticus in Marine Ornamental Fish

Authors: N. B. Dhayanithi, T. T. Ajith Kumar, T. Balasubramanian

Abstract:

Present study summarizes the control of Vibrio alginolyticus infection in hatchery reared Clownfish, Amphiprion sebae with the extract of the mangrove plant, Avicennia marina. Fishes with visible symptoms of hemorrhagic spots were chosen and the genomic DNA of the causative bacterium was isolated and sequenced based on 16S rDNA gene. The in vitro assay revealed that a fraction of A. marina leaf extract elucidated with ethyl acetate: methanol (6:4) showed a high activity (28 mm) at 125 μg/ml concentrations. About 4 % of the fraction fed along with live V. alginolyticus was significantly decreased the cumulative mortality (P<0.05) in the experimental groups than the control group. The responsible fraction was investigated by gas chromatography - mass spectroscopy and found the presence of active compounds. This is the first research in India to control vibriosis infection in marine ornamental fish with mangrove leaf extract.

Keywords: Amphiprion seabe, Avicennia marina, Gas Chromatography - Mass Spectroscopy, Vibrio alginolyticus

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2356 The Effect of Gross Vehicle Weight on the Stability of Heavy Vehicle during Cornering

Authors: Nurzaki Ikhsan, Ahmad Saifizul Abdullah, Rahizar Ramli

Abstract:

One of the functions of the commercial heavy vehicle is to safely and efficiently transport goods and people. Due to its size and carrying capacity, it is important to study the vehicle dynamic stability during cornering. Study has shown that there are a number of overloaded heavy vehicles or permissible Gross Vehicle Weight (GVW) violations recorded at selected areas in Malaysia assigned by its type and category. Thus, the objective of this study is to investigate the correlation and effect of the GVW on heavy vehicle stability during cornering event using simulation. Various selected heavy vehicle types and category are simulated using IPG/Truck Maker® with different GVW and road condition (coefficient of friction of road surface), while the speed, driver characteristic, center of gravity of load and road geometry are constant. Based on the analysis, the relationship between GVW and lateral acceleration were established. As expected, on the same value of coefficient of friction, the maximum lateral acceleration would be increased as the GVW increases.

Keywords: Heavy Vehicle, Road Safety, Vehicle Stability, Lateral Acceleration, Gross Vehicle Weight.

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2355 Blockchain’s Feasibility in Military Data Networks

Authors: Brenden M. Shutt, Lubjana Beshaj, Paul L. Goethals, Ambrose Kam

Abstract:

Communication security is of particular interest to military data networks. A relatively novel approach to network security is blockchain, a cryptographically secured distribution ledger with a decentralized consensus mechanism for data transaction processing. Recent advances in blockchain technology have proposed new techniques for both data validation and trust management, as well as different frameworks for managing dataflow. The purpose of this work is to test the feasibility of different blockchain architectures as applied to military command and control networks. Various architectures are tested through discrete-event simulation and the feasibility is determined based upon a blockchain design’s ability to maintain long-term stable performance at industry standards of throughput, network latency, and security. This work proposes a consortium blockchain architecture with a computationally inexpensive consensus mechanism, one that leverages a Proof-of-Identity (PoI) concept and a reputation management mechanism.

Keywords: Blockchain, command & control network, discrete-event simulation, reputation management.

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2354 Prediction of California Bearing Ratio from Physical Properties of Fine-Grained Soils

Authors: Bao Thach Nguyen, Abbas Mohajerani

Abstract:

The California Bearing Ratio (CBR) has been acknowledged as an important parameter to characterize the bearing capacity of earth structures, such as earth dams, road embankments, airport runways, bridge abutments and pavements. Technically, the CBR test can be carried out in the laboratory or in the field. The CBR test is time-consuming and is infrequently performed due to the equipment needed and the fact that the field moisture content keeps changing over time. Over the years, many correlations have been developed for the prediction of CBR by various researchers, including the dynamic cone penetrometer, undrained shear strength and Clegg impact hammer. This paper reports and discusses some of the results from a study on the prediction of CBR. In the current study, the CBR test was performed in the laboratory on some finegrained subgrade soils collected from various locations in Victoria. Based on the test results, a satisfactory empirical correlation was found between the CBR and the physical properties of the experimental soils.

Keywords: California bearing ratio, fine-grained soils, pavement, soil physical properties.

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2353 Slug Tracking Simulation of Severe Slugging Experiments

Authors: Tor Kindsbekken Kjeldby, Ruud Henkes, Ole Jørgen Nydal

Abstract:

Experimental data from an atmospheric air/water terrain slugging case has been made available by the Shell Amsterdam research center, and has been subject to numerical simulation and comparison with a one-dimensional two-phase slug tracking simulator under development at the Norwegian University of Science and Technology. The code is based on tracking of liquid slugs in pipelines by use of a Lagrangian grid formulation implemented in Cµ by use of object oriented techniques. An existing hybrid spatial discretization scheme is tested, in which the stratified regions are modelled by the two-fluid model. The slug regions are treated incompressible, thus requiring a single momentum balance over the whole slug. Upon comparison with the experimental data, the period of the simulated severe slugging cycle is observed to be sensitive to slug generation in the horizontal parts of the system. Two different slug initiation methods have been tested with the slug tracking code, and grid dependency has been investigated.

Keywords: Hydrodynamic initiation, slug tracking, terrain slugging, two-fluid model, two-phase flow.

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2352 Long-Term Study for the Effect of Ovariectomy on Rat Bone - Use of In-Vivo Micro-CT -

Authors: Dae Gon Woo, Chang Yong Ko, Tae Woo Lee, Han Sung Kim, Beob Yi Lee

Abstract:

In the present study, changes of morphology and mechanical characteristics in the lumbar vertebrae of the ovariectomised (OVX) rat were investigated. In previous researches, there were many studies about morphology like volume fraction and trabecular thickness based on Micro - Computed Tomography (Micro - CT). However, detecting and tracking long-term changes in the trabecular bone of the lumbar vertebrae for the OVX rat were few. For this study, one female Sprague-Dawley rat was used: an OVX rat. The 4th Lumbar of the OVX rat was subjected to in-vivo micro-CT. Detecting and tracking long-term changes could be investigated in the trabecular bone of the lumbar vertebrae for an OVX rat using in-vivo micro-CT. An OVX rat was scanned at week 0 (just before surgery), at week 4, at week 8, week 16, week 22 and week 56 after surgery. Finite element (FE) analysis was used to investigate mechanical characteristics of the lumbar vertebrae for an OVX rat. When the OVX rat (at week 56) was compared with the OVX rat (at week 0), volume fraction was decreased by 80% and effective modulus was decreased by 75%.

Keywords: OVX rats, Trabecular bone, In-vivo Micro-CT, FE analysis

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2351 Emotion Classification using Adaptive SVMs

Authors: P. Visutsak

Abstract:

The study of the interaction between humans and computers has been emerging during the last few years. This interaction will be more powerful if computers are able to perceive and respond to human nonverbal communication such as emotions. In this study, we present the image-based approach to emotion classification through lower facial expression. We employ a set of feature points in the lower face image according to the particular face model used and consider their motion across each emotive expression of images. The vector of displacements of all feature points input to the Adaptive Support Vector Machines (A-SVMs) classifier that classify it into seven basic emotions scheme, namely neutral, angry, disgust, fear, happy, sad and surprise. The system was tested on the Japanese Female Facial Expression (JAFFE) dataset of frontal view facial expressions [7]. Our experiments on emotion classification through lower facial expressions demonstrate the robustness of Adaptive SVM classifier and verify the high efficiency of our approach.

Keywords: emotion classification, facial expression, adaptive support vector machines, facial expression classifier.

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2350 The American Christian Right Women’s Advocacy Groups and US Foreign Policy

Authors: Mohd Afandi Salleh

Abstract:

The paper examines two women advocacy groups of the American Christian Right, namely: Concerned Women for America (CWA) and Eagle Forum. Focus will be placed on their interests in American foreign policy and global social policy particularly during the George W. Bush administration. It examines the organizations’ historical backgrounds, and study their agendas, issues and forms of international engagement which relate to American foreign policy. The paper shows that the Christian Right movement is not a monolithic movement in term of its focus, objectives or activism. Despite their diversity, various actions of these advocacy groups have strengthened the role of the Christian Right in exerting its influence on US foreign policy. Finally, it contends that, although traditionally the Christian Right advocacy groups’ motives for activism are strongly based on the Bible and Judeo–Christian values, the arguments and ideas behind their present struggle are presented in a very nationalistic, secular and pragmatic vein.

Keywords: Christian Right, Concerned Women for America, Eagle Forum, Global social policy, US foreign policy.

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2349 Measuring Text-Based Semantics Relatedness Using WordNet

Authors: Madiha Khan, Sidrah Ramzan, Seemab Khan, Shahzad Hassan, Kamran Saeed

Abstract:

Measuring semantic similarity between texts is calculating semantic relatedness between texts using various techniques. Our web application (Measuring Relatedness of Concepts-MRC) allows user to input two text corpuses and get semantic similarity percentage between both using WordNet. Our application goes through five stages for the computation of semantic relatedness. Those stages are: Preprocessing (extracts keywords from content), Feature Extraction (classification of words into Parts-of-Speech), Synonyms Extraction (retrieves synonyms against each keyword), Measuring Similarity (using keywords and synonyms, similarity is measured) and Visualization (graphical representation of similarity measure). Hence the user can measure similarity on basis of features as well. The end result is a percentage score and the word(s) which form the basis of similarity between both texts with use of different tools on same platform. In future work we look forward for a Web as a live corpus application that provides a simpler and user friendly tool to compare documents and extract useful information.

Keywords: GraphViz representation, semantic relatedness, similarity measurement, WordNet similarity.

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2348 ‘Daily Speaking’: Designing an App for Construction of Language Learning Model Supporting ‘Seamless Flipped’ Environment

Authors: Zhou Hong, Gu Xiao-Qing, Lıu Hong-Jiao, Leng Jing

Abstract:

Seamless learning is becoming a research hotspot in recent years, and the emerging of micro-lectures, flipped classroom has strengthened the development of seamless learning. Based on the characteristics of the seamless learning across time and space and the course structure of the flipped classroom, and the theories of language learning, we put forward the language learning model which can support ‘seamless flipped’ environment (abbreviated as ‘S-F’). Meanwhile, the characteristics of the ‘S-F’ learning environment, the corresponding framework construction and the activity design of diversified corpora were introduced. Moreover, a language learning app named ‘Daily Speaking’ was developed to facilitate the practice of the language learning model in ‘S-F’ environment. In virtue of the learning case of Shanghai language, the rationality and feasibility of this framework were examined, expecting to provide a reference for the design of ‘S-F’ learning in different situations.

Keywords: Seamless learning, flipped classroom, seamless-flipped environment, language learning model.

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2347 Quantum Computing: A New Era of Computing

Authors: Jyoti Chaturvedi Gursaran

Abstract:

Nature conducts its action in a very private manner. To reveal these actions classical science has done a great effort. But classical science can experiment only with the things that can be seen with eyes. Beyond the scope of classical science quantum science works very well. It is based on some postulates like qubit, superposition of two states, entanglement, measurement and evolution of states that are briefly described in the present paper. One of the applications of quantum computing i.e. implementation of a novel quantum evolutionary algorithm(QEA) to automate the time tabling problem of Dayalbagh Educational Institute (Deemed University) is also presented in this paper. Making a good timetable is a scheduling problem. It is NP-hard, multi-constrained, complex and a combinatorial optimization problem. The solution of this problem cannot be obtained in polynomial time. The QEA uses genetic operators on the Q-bit as well as updating operator of quantum gate which is introduced as a variation operator to converge toward better solutions.

Keywords: Quantum computing, qubit, superposition, entanglement, measurement of states, evolution of states, Scheduling problem, hard and soft constraints, evolutionary algorithm, quantum evolutionary algorithm.

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2346 Elephant Herding Optimization for Service Selection in QoS-Aware Web Service Composition

Authors: Samia Sadouki Chibani, Abdelkamel Tari

Abstract:

Web service composition combines available services to provide new functionality. Given the number of available services with similar functionalities and different non functional aspects (QoS), the problem of finding a QoS-optimal web service composition is considered as an optimization problem belonging to NP-hard class. Thus, an optimal solution cannot be found by exact algorithms within a reasonable time. In this paper, a meta-heuristic bio-inspired is presented to address the QoS aware web service composition; it is based on Elephant Herding Optimization (EHO) algorithm, which is inspired by the herding behavior of elephant group. EHO is characterized by a process of dividing and combining the population to sub populations (clan); this process allows the exchange of information between local searches to move toward a global optimum. However, with Applying others evolutionary algorithms the problem of early stagnancy in a local optimum cannot be avoided. Compared with PSO, the results of experimental evaluation show that our proposition significantly outperforms the existing algorithm with better performance of the fitness value and a fast convergence.

Keywords: Elephant herding optimization, web service composition, bio-inspired algorithms, QoS optimization.

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2345 Evaluation and Analysis of the Secure E-Voting Authentication Preparation Scheme

Authors: Nidal F. Shilbayeh, Reem A. Al-Saidi, Ahmed H. Alsswey

Abstract:

In this paper, we presented an evaluation and analysis of E-Voting Authentication Preparation Scheme (EV-APS). EV-APS applies some modified security aspects that enhance the security measures and adds a strong wall of protection, confidentiality, non-repudiation and authentication requirements. Some of these modified security aspects are Kerberos authentication protocol, PVID scheme, responder certificate validation, and the converted Ferguson e-cash protocol. Authentication and privacy requirements have been evaluated and proved. Authentication guaranteed only eligible and authorized voters were permitted to vote. Also, the privacy guaranteed that all votes will be kept secret. Evaluation and analysis of some of these security requirements have been given. These modified aspects will help in filtering the counter buffer from unauthorized votes by ensuring that only authorized voters are permitted to vote.

Keywords: E-Voting preparation stage, blind signature protocol, nonce based authentication scheme, Kerberos authentication protocol, pseudo voter identity scheme PVID.

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2344 Mean-Square Performance of Adaptive Filter Algorithms in Nonstationary Environments

Authors: Mohammad Shams Esfand Abadi, John Hakon Husøy

Abstract:

Employing a recently introduced unified adaptive filter theory, we show how the performance of a large number of important adaptive filter algorithms can be predicted within a general framework in nonstationary environment. This approach is based on energy conservation arguments and does not need to assume a Gaussian or white distribution for the regressors. This general performance analysis can be used to evaluate the mean square performance of the Least Mean Square (LMS) algorithm, its normalized version (NLMS), the family of Affine Projection Algorithms (APA), the Recursive Least Squares (RLS), the Data-Reusing LMS (DR-LMS), its normalized version (NDR-LMS), the Block Least Mean Squares (BLMS), the Block Normalized LMS (BNLMS), the Transform Domain Adaptive Filters (TDAF) and the Subband Adaptive Filters (SAF) in nonstationary environment. Also, we establish the general expressions for the steady-state excess mean square in this environment for all these adaptive algorithms. Finally, we demonstrate through simulations that these results are useful in predicting the adaptive filter performance.

Keywords: Adaptive filter, general framework, energy conservation, mean-square performance, nonstationary environment.

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2343 Enhancement of Thermal Performance of Latent Heat Solar Storage System

Authors: Rishindra M. Sarviya, Ashish Agrawal

Abstract:

Solar energy is available abundantly in the world, but it is not continuous and its intensity also varies with time. Due to above reason the acceptability and reliability of solar based thermal system is lower than conventional systems. A properly designed heat storage system increases the reliability of solar thermal systems by bridging the gap between the energy demand and availability. In the present work, two dimensional numerical simulation of the melting of heat storage material is presented in the horizontal annulus of double pipe latent heat storage system. Longitudinal fins were used as a thermal conductivity enhancement. Paraffin wax was used as a heat-storage or phase change material (PCM). Constant wall temperature is applied to heat transfer tube. Presented two-dimensional numerical analysis shows the movement of melting front in the finned cylindrical annulus for analyzing the thermal behavior of the system during melting.

Keywords: Latent heat, numerical study, phase change material, solar energy.

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2342 Neural Network Ensemble-based Solar Power Generation Short-Term Forecasting

Authors: A. Chaouachi, R.M. Kamel, R. Ichikawa, H. Hayashi, K. Nagasaka

Abstract:

This paper presents the applicability of artificial neural networks for 24 hour ahead solar power generation forecasting of a 20 kW photovoltaic system, the developed forecasting is suitable for a reliable Microgrid energy management. In total four neural networks were proposed, namely: multi-layred perceptron, radial basis function, recurrent and a neural network ensemble consisting in ensemble of bagged networks. Forecasting reliability of the proposed neural networks was carried out in terms forecasting error performance basing on statistical and graphical methods. The experimental results showed that all the proposed networks achieved an acceptable forecasting accuracy. In term of comparison the neural network ensemble gives the highest precision forecasting comparing to the conventional networks. In fact, each network of the ensemble over-fits to some extent and leads to a diversity which enhances the noise tolerance and the forecasting generalization performance comparing to the conventional networks.

Keywords: Neural network ensemble, Solar power generation, 24 hour forecasting, Comparative study

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2341 What the Future Holds for Social Media Data Analysis

Authors: P. Wlodarczak, J. Soar, M. Ally

Abstract:

The dramatic rise in the use of Social Media (SM) platforms such as Facebook and Twitter provide access to an unprecedented amount of user data. Users may post reviews on products and services they bought, write about their interests, share ideas or give their opinions and views on political issues. There is a growing interest in the analysis of SM data from organisations for detecting new trends, obtaining user opinions on their products and services or finding out about their online reputations. A recent research trend in SM analysis is making predictions based on sentiment analysis of SM. Often indicators of historic SM data are represented as time series and correlated with a variety of real world phenomena like the outcome of elections, the development of financial indicators, box office revenue and disease outbreaks. This paper examines the current state of research in the area of SM mining and predictive analysis and gives an overview of the analysis methods using opinion mining and machine learning techniques.

Keywords: Social Media, text mining, knowledge discovery, predictive analysis, machine learning.

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2340 Determination of Sensitive Transmission Lines Due to the Effect of Protection System Hidden Failure in a Critical System Cascading Collapse

Authors: N. A. Salim, M. M. Othman, I. Musirin, M. S. Serwan

Abstract:

Protection system hidden failures have been identified as one of the main causes of system cascading collapse resulting to power system instability. In this paper, a systematic approach is presented in order to identify the probability of a system cascading collapse by taking into consideration the effect of protection system hidden failure. This includes the accurate calculation of the probability of hidden failure as it will provide significant impinge on the findings of the probability of system cascading collapse. The probability of a system cascading collapse is then used to identify the initial tripping of sensitive transmission lines which will contribute to a critical system cascading collapse. Based on the results obtained from this study, it is important to decide on the accurate value of the hidden failure probability as it will affect the probability of a system cascading collapse.

Keywords: Critical system cascading collapse, hidden failure, probability of cascading collapse, sensitive transmission lines.

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2339 Spatial Data Mining by Decision Trees

Authors: S. Oujdi, H. Belbachir

Abstract:

Existing methods of data mining cannot be applied on spatial data because they require spatial specificity consideration, as spatial relationships. This paper focuses on the classification with decision trees, which are one of the data mining techniques. We propose an extension of the C4.5 algorithm for spatial data, based on two different approaches Join materialization and Querying on the fly the different tables. Similar works have been done on these two main approaches, the first - Join materialization - favors the processing time in spite of memory space, whereas the second - Querying on the fly different tables- promotes memory space despite of the processing time. The modified C4.5 algorithm requires three entries tables: a target table, a neighbor table, and a spatial index join that contains the possible spatial relationship among the objects in the target table and those in the neighbor table. Thus, the proposed algorithms are applied to a spatial data pattern in the accidentology domain. A comparative study of our approach with other works of classification by spatial decision trees will be detailed.

Keywords: C4.5 Algorithm, Decision trees, S-CART, Spatial data mining.

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2338 Depth Camera Aided Dead-Reckoning Localization of Autonomous Mobile Robots in Unstructured Global Navigation Satellite System Denied Environments

Authors: David L. Olson, Stephen B. H. Bruder, Adam S. Watkins, Cleon E. Davis

Abstract:

In global navigation satellite system (GNSS) denied settings, such as indoor environments, autonomous mobile robots are often limited to dead-reckoning navigation techniques to determine their position, velocity, and attitude (PVA). Localization is typically accomplished by employing an inertial measurement unit (IMU), which, while precise in nature, accumulates errors rapidly and severely degrades the localization solution. Standard sensor fusion methods, such as Kalman filtering, aim to fuse precise IMU measurements with accurate aiding sensors to establish a precise and accurate solution. In indoor environments, where GNSS and no other a priori information is known about the environment, effective sensor fusion is difficult to achieve, as accurate aiding sensor choices are sparse. However, an opportunity arises by employing a depth camera in the indoor environment. A depth camera can capture point clouds of the surrounding floors and walls. Extracting attitude from these surfaces can serve as an accurate aiding source, which directly combats errors that arise due to gyroscope imperfections. This configuration for sensor fusion leads to a dramatic reduction of PVA error compared to traditional aiding sensor configurations. This paper provides the theoretical basis for the depth camera aiding sensor method, initial expectations of performance benefit via simulation, and hardware implementation thus verifying its veracity. Hardware implementation is performed on the Quanser Qbot 2™ mobile robot, with a Vector-Nav VN-200™ IMU and Kinect™ camera from Microsoft.

Keywords: Autonomous mobile robotics, dead reckoning, depth camera, inertial navigation, Kalman filtering, localization, sensor fusion.

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2337 A Real Time Expert System for Decision Support in Nuclear Power Plants

Authors: Andressa dos Santos Nicolau, João P. da S.C Algusto, Claudio Márcio do N. A. Pereira, Roberto Schirru

Abstract:

In case of abnormal situations, the nuclear power plant (NPP) operators must follow written procedures to check the condition of the plant and to classify the type of emergency. In this paper, we proposed a Real Time Expert System in order to improve operator’s performance in case of transient or accident with reactor shutdown. The expert system’s knowledge is based on the sequence of events (SoE) of known accident and two emergency procedures of the Brazilian Pressurized Water Reactor (PWR) NPP and uses two kinds of knowledge representation: rule and logic trees. The results show that the system was able to classify the response of the automatic protection systems, as well as to evaluate the conditions of the plant, diagnosing the type of occurrence, recovery procedure to be followed, indicating the shutdown root cause, and classifying the emergency level.

Keywords: Emergence procedure, expert system, operator support, PWR nuclear power plant.

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2336 Enhancing Multi-Frame Images Using Self-Delaying Dynamic Networks

Authors: Lewis E. Hibell, Honghai Liu, David J. Brown

Abstract:

This paper presents the use of a newly created network structure known as a Self-Delaying Dynamic Network (SDN) to create a high resolution image from a set of time stepped input frames. These SDNs are non-recurrent temporal neural networks which can process time sampled data. SDNs can store input data for a lifecycle and feature dynamic logic based connections between layers. Several low resolution images and one high resolution image of a scene were presented to the SDN during training by a Genetic Algorithm. The SDN was trained to process the input frames in order to recreate the high resolution image. The trained SDN was then used to enhance a number of unseen noisy image sets. The quality of high resolution images produced by the SDN is compared to that of high resolution images generated using Bi-Cubic interpolation. The SDN produced images are superior in several ways to the images produced using Bi-Cubic interpolation.

Keywords: Image Enhancement, Neural Networks, Multi-Frame.

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