Search results for: cognitive functions
Commenced in January 2007
Frequency: Monthly
Edition: International
Paper Count: 1408

Search results for: cognitive functions

1198 Adaptive Shape Parameter (ASP) Technique for Local Radial Basis Functions (RBFs) and Their Application for Solution of Navier Strokes Equations

Authors: A. Javed, K. Djidjeli, J. T. Xing

Abstract:

The concept of adaptive shape parameters (ASP) has been presented for solution of incompressible Navier Strokes equations using mesh-free local Radial Basis Functions (RBF). The aim is to avoid ill-conditioning of coefficient matrices of RBF weights and inaccuracies in RBF interpolation resulting from non-optimized shape of basis functions for the cases where data points (or nodes) are not distributed uniformly throughout the domain. Unlike conventional approaches which assume globally similar values of RBF shape parameters, the presented ASP technique suggests that shape parameter be calculated exclusively for each data point (or node) based on the distribution of data points within its own influence domain. This will ensure interpolation accuracy while still maintaining well conditioned system of equations for RBF weights. Performance and accuracy of ASP technique has been tested by evaluating derivatives and laplacian of a known function using RBF in Finite difference mode (RBFFD), with and without the use of adaptivity in shape parameters. Application of adaptive shape parameters (ASP) for solution of incompressible Navier Strokes equations has been presented by solving lid driven cavity flow problem on mesh-free domain using RBF-FD. The results have been compared for fixed and adaptive shape parameters. Improved accuracy has been achieved with the use of ASP in RBF-FD especially at regions where larger gradients of field variables exist.

Keywords: CFD, Meshless Particle Method, Radial Basis Functions, Shape Parameters

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1197 BER Analysis of Energy Detection Spectrum Sensing in Cognitive Radio Using GNU Radio

Authors: B. Siva Kumar Reddy, B. Lakshmi

Abstract:

Cognitive Radio is a turning out technology that empowers viable usage of the spectrum. Energy Detector-based Sensing is the most broadly utilized spectrum sensing strategy. Besides, it's a lot of generic as receivers doesn't would like any information on the primary user's signals, channel data, of even the sort of modulation. This paper puts forth the execution of energy detection sensing for AM (Amplitude Modulated) signal at 710 KHz, FM (Frequency Modulated) signal at 103.45 MHz (local station frequency), Wi-Fi signal at 2.4 GHz and WiMAX signals at 6 GHz. The OFDM/OFDMA based WiMAX physical layer with convolutional channel coding is actualized utilizing USRP N210 (Universal Software Radio Peripheral) and GNU Radio based Software Defined Radio (SDR). Test outcomes demonstrated the BER (Bit Error Rate) augmentation with channel noise and BER execution is dissected for different Eb/N0 (the energy per bit to noise power spectral density ratio) values.

Keywords: BER, Cognitive Radio, GNU Radio, OFDM, SDR, WiMAX.

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1196 A New Voting Approach to Texture Defect Detection Based on Multiresolutional Decomposition

Authors: B. B. M. Moasheri, S. Azadinia

Abstract:

Wavelets have provided the researchers with significant positive results, by entering the texture defect detection domain. The weak point of wavelets is that they are one-dimensional by nature so they are not efficient enough to describe and analyze two-dimensional functions. In this paper we present a new method to detect the defect of texture images by using curvelet transform. Simulation results of the proposed method on a set of standard texture images confirm its correctness. Comparing the obtained results indicates the ability of curvelet transform in describing discontinuity in two-dimensional functions compared to wavelet transform

Keywords: Curvelet, Defect detection, Wavelet.

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1195 Cognitive Radio Spectrum Management

Authors: Swapnil Singhal, Santosh Kumar Singh

Abstract:

The emerging Cognitive Radio is combo of both the technologies i.e. Radio dynamics and software technology. It involve wireless system with efficient coding, designing, and making them artificial intelligent to take the decision according to the surrounding environment and adopt themselves accordingly, so as to deliver the best QoS. This is the breakthrough from fixed hardware and fixed utilization of the spectrum. This software-defined approach of research is centralized at user-definition and application driven model, various software method are used for the optimization of the wireless communication. This paper focused on the Spectrum allocation technique using genetic algorithm GA to evolve radio, represented by chromosomes. The chromosomes gene represents the adjustable parameters in given radio and by using GA, evolving over the generations, the optimized set of parameters are evolved, as per the requirement of user and availability of the spectrum, in our prototype the gene consist of 6 different parameters, and the best set of parameters are evolved according to the application need and availability of the spectrum holes and thus maintaining best QoS for user, simultaneously maintaining licensed user rights. The analyzing tool Matlab is used for the performance of the prototype.

Keywords: ASDR, Cognitive Radio, QoS, Spectrum.

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1194 I-Vague Normal Groups

Authors: Zelalem Teshome Wale

Abstract:

The notions of I-vague normal groups with membership and non-membership functions taking values in an involutary dually residuated lattice ordered semigroup are introduced which generalize the notions with truth values in a Boolean algebra as well as those usual vague sets whose membership and non-membership functions taking values in the unit interval [0, 1]. Various operations and properties are established.

Keywords: Involutary dually residuated lattice ordered semigroup, I-vague set, I-vague group and I-vague normal group.

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1193 Reading Strategy Awareness of English Major Students

Authors: Hsin-Yi Lien

Abstract:

The study explored the role of metacognition in foreign language anxiety on a sample of 411 Taiwanese students of English as a Foreign Language. The reading strategy inventory was employed to evaluate the tertiary learners’ level of metacognitive awareness and a semi-structured background questionnaire was also used to examine the learners’ perceptions of their English proficiency and satisfaction of their current English learning. In addition, gender and academic level differences in employment of reading strategies were investigated. The results showed the frequency of reading strategy use increase slightly along with academic years and males and females actually employ different reading strategies. The EFL tertiary learners in the present study utilized cognitive strategies more frequently than metacognitive strategies or support strategies. Male students use metacognitive strategy more often while female students use cognitive and support strategy more frequently.

Keywords: Cognitive strategy, gender differences, metacognitive strategy, support strategy.

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1192 Evaluating Sinusoidal Functions by a Low Complexity Cubic Spline Interpolator with Error Optimization

Authors: Abhijit Mitra, Harpreet Singh Dhillon

Abstract:

We present a novel scheme to evaluate sinusoidal functions with low complexity and high precision using cubic spline interpolation. To this end, two different approaches are proposed to find the interpolating polynomial of sin(x) within the range [- π , π]. The first one deals with only a single data point while the other with two to keep the realization cost as low as possible. An approximation error optimization technique for cubic spline interpolation is introduced next and is shown to increase the interpolator accuracy without increasing complexity of the associated hardware. The architectures for the proposed approaches are also developed, which exhibit flexibility of implementation with low power requirement.

Keywords: Arithmetic, spline interpolator, hardware design, erroranalysis, optimization methods.

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1191 A Cognitive Robot Collaborative Reinforcement Learning Algorithm

Authors: Amit Gil, Helman Stern, Yael Edan

Abstract:

A cognitive collaborative reinforcement learning algorithm (CCRL) that incorporates an advisor into the learning process is developed to improve supervised learning. An autonomous learner is enabled with a self awareness cognitive skill to decide when to solicit instructions from the advisor. The learner can also assess the value of advice, and accept or reject it. The method is evaluated for robotic motion planning using simulation. Tests are conducted for advisors with skill levels from expert to novice. The CCRL algorithm and a combined method integrating its logic with Clouse-s Introspection Approach, outperformed a base-line fully autonomous learner, and demonstrated robust performance when dealing with various advisor skill levels, learning to accept advice received from an expert, while rejecting that of less skilled collaborators. Although the CCRL algorithm is based on RL, it fits other machine learning methods, since advisor-s actions are only added to the outer layer.

Keywords: Robot learning, human-robot collaboration, motion planning, reinforcement learning.

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1190 Prediction of Saturated Hydraulic Conductivity Dynamics in an Iowan Agriculture Watershed

Authors: Mohamed Elhakeem, A. N. Thanos Papanicolaou, Christopher Wilson, Yi-Jia Chang

Abstract:

In this study, a physically-based, modeling framework was developed to predict saturated hydraulic conductivity (Ksat) dynamics in the Clear Creek Watershed (CCW), Iowa. The modeling framework integrated selected pedotransfer functions and watershed models with geospatial tools. A number of pedotransfer functions and agricultural watershed models were examined to select the appropriate models that represent the study site conditions. Models selection was based on statistical measures of the models’ errors compared to the Ksat field measurements conducted in the CCW under different soil, climate and land use conditions. The study has shown that the predictions of the combined pedotransfer function of Rosetta and the Water Erosion Prediction Project (WEPP) provided the best agreement to the measured Ksat values in the CCW compared to the other tested models. Therefore, Rosetta and WEPP were integrated with the Geographic Information System (GIS) tools for visualization of the data in forms of geospatial maps and prediction of Ksat variability in CCW due to the seasonal changes in climate and land use activities. 

Keywords: Saturated hydraulic conductivity, pedotransfer functions, watershed models, geospatial tools.

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1189 The Role of Emotions in the Consumer: Theoretical Review and Analysis of Components

Authors: Mikel Alonso López

Abstract:

The early eighties saw the rise of a new research trend in several prestigious journals, mainly articles that related emotions with the decision-making processes of the consumer, and stopped treating them as external elements. That is why we ask questions such as: what are emotions? Are there different types of emotions? What components do they have? Which theories exist about them? In this study, we will review the main theories and components of emotion analysing the cognitive factor and the different emotional states that are generally recognizable with a focus in the classic debate as to whether they occur before the cognitive process or the affective process.

Keywords: Emotion, consumer behaviour, feelings, decision making.

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1188 Examining the Performance of Three Multiobjective Evolutionary Algorithms Based on Benchmarking Problems

Authors: Konstantinos Metaxiotis, Konstantinos Liagkouras

Abstract:

The objective of this study is to examine the performance of three well-known multiobjective evolutionary algorithms for solving optimization problems. The first algorithm is the Non-dominated Sorting Genetic Algorithm-II (NSGA-II), the second one is the Strength Pareto Evolutionary Algorithm 2 (SPEA-2), and the third one is the Multiobjective Evolutionary Algorithms based on decomposition (MOEA/D). The examined multiobjective algorithms are analyzed and tested on the ZDT set of test functions by three performance metrics. The results indicate that the NSGA-II performs better than the other two algorithms based on three performance metrics.

Keywords: MOEAs, Multiobjective optimization, ZDT test functions, performance metrics.

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1187 Association of Brain Derived Neurotrophic Factor with Iron as well as Vitamin D, Folate and Cobalamin in Pediatric Metabolic Syndrome

Authors: Mustafa M. Donma, Orkide Donma

Abstract:

The impact of metabolic syndrome (MetS) on cognition and functions of the brain is being investigated. Iron deficiency and deficiencies of B9 (folate) as well as B12 (cobalamin) vitamins are best-known nutritional anemias. They are associated with cognitive disorders and learning difficulties. The antidepressant effects of vitamin D are known and the deficiency state affects mental functions negatively. The aim of this study is to investigate possible correlations of MetS with serum brain-derived neurotrophic factor (BDNF), iron, folate, cobalamin and vitamin D in pediatric patients. 30 children, whose age- and sex-dependent body mass index (BMI) percentiles vary between 85 and 15, 60 morbid obese children with above 99th percentiles constituted the study population. Anthropometric measurements were taken. BMI values were calculated. Age- and sex-dependent BMI percentile values were obtained using the appropriate tables prepared by the World Health Organization (WHO). Obesity classification was performed according to WHO criteria. Those with MetS were evaluated according to MetS criteria. Serum BDNF was determined by enzyme-linked immunosorbent assay. Serum folate was analyzed by an immunoassay analyzer. Serum cobalamin concentrations were measured using electrochemiluminescence immunoassay. Vitamin D status was determined by the measurement of 25-hydroxycholecalciferol [25-hydroxy vitamin D3, 25(OH)D] using high performance liquid chromatography. Statistical evaluations were performed using SPSS for Windows, version 16. The p values less than 0.05 were accepted as statistically significant. Although statistically insignificant, lower folate and cobalamin values were found in MO children compared to those observed for children with normal BMI. For iron and BDNF values, no alterations were detected among the groups. Significantly decreased vitamin D concentrations were noted in MO children with MetS in comparison with those in children with normal BMI (p ≤ 0.05). The positive correlation observed between iron and BDNF in normal-BMI group was not found in two MO groups. In THE MetS group, the partial correlation among iron, BDNF, folate, cobalamin, vitamin D controlling for waist circumference and BMI was r = -0.501; p ≤ 0.05. None was calculated in MO and normal BMI groups. In conclusion, vitamin D should also be considered during the assessment of pediatric MetS. Waist circumference and BMI should collectively be evaluated during the evaluation of MetS in children. Within this context, BDNF appears to be a key biochemical parameter during the examination of obesity degree in terms of mental functions, cognition and learning capacity. The association observed between iron and BDNF in children with normal BMI was not detected in MO groups possibly due to development of inflammation and other obesity-related pathologies. It was suggested that this finding may contribute to mental function impairments commonly observed among obese children.

Keywords: Brain-derived neurotrophic factor, iron, Vitamin B9, Vitamin B12, Vitamin D.

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1186 Rhetorical Communication in the CogSci Discourse Community: The Cognitive Neurosciences (2004) in the Context of Scientific Dissemination

Authors: Lucia Abbamonte, Olimpia Matarazzo

Abstract:

In recent years linguistic research has turned increasing attention to covert/overt strategies to modulate authorial stance and positioning in scientific texts, and to the recipients' response. This study discussed some theoretical implications of the use of rhetoric in scientific communication and analysed qualitative data from the authoritative The Cognitive Neurosciences III (2004) volume. Its genre-identity, status and readability were considered, in the social interactive context of contemporary disciplinary discourses – in their polyphony of traditional and new, emerging genres. Evidence was given of the ways its famous authors negotiate and shape knowledge and research results – explicitly appraising team work and promoting faith in the fast-paced progress of Cognitive Neuroscience, also through experiential metaphors – by presenting a set of examples, ordered according to their dominant rhetorical quality.

Keywords: Appraisal, disciplinary discourses, experientialmetaphors, genre, identity, knowledge, readability, rhetoric, strategies, theoretical implications.

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1185 Analysis of Different Combining Schemes of Two Amplify-Forward Relay Branches with Individual Links Experiencing Nakagami Fading

Authors: Babu Sena Paul, Ratnajit Bhattacharjee

Abstract:

Relay based communication has gained considerable importance in the recent years. In this paper we find the end-toend statistics of a two hop non-regenerative relay branch, each hop being Nakagami-m faded. Closed form expressions for the probability density functions of the signal envelope at the output of a selection combiner and a maximal ratio combiner at the destination node are also derived and analytical formulations are verified through computer simulation. These density functions are useful in evaluating the system performance in terms of bit error rate and outage probability.

Keywords: co-operative diversity, diversity combining, maximal ratio combining, selection combining.

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1184 Unsupervised Texture Classification and Segmentation

Authors: V.P.Subramanyam Rallabandi, S.K.Sett

Abstract:

An unsupervised classification algorithm is derived by modeling observed data as a mixture of several mutually exclusive classes that are each described by linear combinations of independent non-Gaussian densities. The algorithm estimates the data density in each class by using parametric nonlinear functions that fit to the non-Gaussian structure of the data. This improves classification accuracy compared with standard Gaussian mixture models. When applied to textures, the algorithm can learn basis functions for images that capture the statistically significant structure intrinsic in the images. We apply this technique to the problem of unsupervised texture classification and segmentation.

Keywords: Gaussian Mixture Model, Independent Component Analysis, Segmentation, Unsupervised Classification.

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1183 Using Data Mining for Learning and Clustering FCM

Authors: Somayeh Alizadeh, Mehdi Ghazanfari, Mohammad Fathian

Abstract:

Fuzzy Cognitive Maps (FCMs) have successfully been applied in numerous domains to show relations between essential components. In some FCM, there are more nodes, which related to each other and more nodes means more complex in system behaviors and analysis. In this paper, a novel learning method used to construct FCMs based on historical data and by using data mining and DEMATEL method, a new method defined to reduce nodes number. This method cluster nodes in FCM based on their cause and effect behaviors.

Keywords: Clustering, Data Mining, Fuzzy Cognitive Map(FCM), Learning.

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1182 The Epistemological Crisis in the Theory of Vittorio Guidano

Authors: Mauricio Otaíza Morales

Abstract:

This work shows a basic philosophical difficulty in the constructivist foundations of the cognitive posracionalist psychology of Vittorio Guidano. This is a difficulty caused by the problem of the existential crisis. It will be analyzed how Guidano-s suggestions about this problem depend on felt experience. Then it will appear how Guidano-s philosophy and psychotherapy must turn towards a phenomenological approach. Finally, some references are given about Eugen Gendlin-s philosophy which could be considered as a radical way to confront these questions.

Keywords: Cognitive posracionalist psychology of VittorioGuidano, Epistemological crisis, Existential crisis, Experience asdirectly felt.

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1181 Application of Adaptive Neuro-Fuzzy Inference System in Smoothing Transition Autoregressive Models

Authors: Ε. Giovanis

Abstract:

In this paper we propose and examine an Adaptive Neuro-Fuzzy Inference System (ANFIS) in Smoothing Transition Autoregressive (STAR) modeling. Because STAR models follow fuzzy logic approach, in the non-linear part fuzzy rules can be incorporated or other training or computational methods can be applied as the error backpropagation algorithm instead to nonlinear squares. Furthermore, additional fuzzy membership functions can be examined, beside the logistic and exponential, like the triangle, Gaussian and Generalized Bell functions among others. We examine two macroeconomic variables of US economy, the inflation rate and the 6-monthly treasury bills interest rates.

Keywords: Forecasting, Neuro-Fuzzy, Smoothing transition, Time-series

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1180 Preliminary Toxicological Evaluations of Polypeptide-K Isolated from Momordica Charantia in Laboratory Rats

Authors: M Nazrul-Hakim, A Yaacob, Y Adam, A Zuraini

Abstract:

This study examined the toxicological effects and safety of polypeptide k isolated from the seeds of Momordica charantia in laboratory rats. 30 male Sprague Dawley rats (12 weeks old, bodyweight 180-200 g) were randomly divided into 3 groups (1000 mg/kg, 500 mg and 0 mg/kg). Rats were acclimatized to laboratory conditions for 7 days and at day 8 rats were dosed orally with polypeptide k (in 2% DMSO/normal saline) and the controls received the dosed vehicle only. Rats were then observed for 72 hours before sacrificed. Rats were anaesthetized by pentobarbital (50 mg/kg ip) and 2-3.0 mL of blood was taken by cardiac puncture and rats were scarified by anaesthetic overdose. Immediately, organs (heart, lungs, liver, kidneys) were weigh and taken for histology. Organ sections were then evaluated by a histopathologist. Serum samples were assayed for liver functions (ALT and γ-GT) and kidney functions (BUN and creatinine). All rats showed normal behavior after the dosing and no statistical changes were observed in all blood parameters and organ weight. Histological examinations revealed normal organ structures. In conclusion, dosing of rats up to 1000 mg/kg did not have any effects on the rat behavior, liver or kidney functions nor histology of the selected organs.

Keywords: Polypeptide k, safety, histology, toxicology, Momordica charantia

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1179 Hybrid Function Method for Solving Nonlinear Fredholm Integral Equations of the Second Kind

Authors: jianhua Hou, Changqing Yang, and Beibo Qin

Abstract:

A numerical method for solving nonlinear Fredholm integral equations of second kind is proposed. The Fredholm type equations which have many applications in mathematical physics are then considered. The method is based on hybrid function  approximations. The properties of hybrid of block-pulse functions and Chebyshev polynomials are presented and are utilized to reduce the computation of nonlinear Fredholm integral equations to a system of nonlinear. Some numerical examples are selected to illustrate the effectiveness and simplicity of the method.

Keywords: Hybrid functions, Fredholm integral equation, Blockpulse, Chebyshev polynomials, product operational matrix.

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1178 Improve Safety Performance of Un-Signalized Intersections in Oman

Authors: Siham G. Farag

Abstract:

The main objective of this paper is to provide a new methodology for road safety assessment in Oman through the development of suitable accident prediction models. GLM technique with Poisson or NBR using SAS package was carried out to develop these models. The paper utilized the accidents data of 31 un-signalized T-intersections during three years. Five goodness-of-fit measures were used to assess the overall quality of the developed models. Two types of models were developed separately; the flow-based models including only traffic exposure functions, and the full models containing both exposure functions and other significant geometry and traffic variables. The results show that, traffic exposure functions produced much better fit to the accident data. The most effective geometric variables were major-road mean speed, minor-road 85th percentile speed, major-road lane width, distance to the nearest junction, and right-turn curb radius. The developed models can be used for intersection treatment or upgrading and specify the appropriate design parameters of T-intersections. Finally, the models presented in this thesis reflect the intersection conditions in Oman and could represent the typical conditions in several countries in the middle east area, especially gulf countries.

Keywords: Accidents Prediction Models (APMs), Generalized Linear Model (GLM), T-intersections, Oman.

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1177 Development of Heterogeneous Parallel Genetic Simulated Annealing Using Multi-Niche Crowding

Authors: Z. G. Wang, M. Rahman, Y. S. Wong, K. S. Neo

Abstract:

In this paper, a new hybrid of genetic algorithm (GA) and simulated annealing (SA), referred to as GSA, is presented. In this algorithm, SA is incorporated into GA to escape from local optima. The concept of hierarchical parallel GA is employed to parallelize GSA for the optimization of multimodal functions. In addition, multi-niche crowding is used to maintain the diversity in the population of the parallel GSA (PGSA). The performance of the proposed algorithms is evaluated against a standard set of multimodal benchmark functions. The multi-niche crowding PGSA and normal PGSA show some remarkable improvement in comparison with the conventional parallel genetic algorithm and the breeder genetic algorithm (BGA).

Keywords: Crowding, genetic algorithm, parallel geneticalgorithm, simulated annealing.

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1176 Strongly Coupled Finite Element Formulation of Electromechanical Systems with Integrated Mesh Morphing using Radial Basis Functions

Authors: D. Kriebel, J. E. Mehner

Abstract:

The paper introduces a method to efficiently simulate nonlinear changing electrostatic fields occurring in micro-electromechanical systems (MEMS). Large deflections of the capacitor electrodes usually introduce nonlinear electromechanical forces on the mechanical system. Traditional finite element methods require a time-consuming remeshing process to capture exact results for this physical domain interaction. In order to accelerate the simulation process and eliminate the remeshing process, a formulation of a strongly coupled electromechanical transducer element will be introduced which uses a combination of finite-element with an advanced mesh morphing technique using radial basis functions (RBF). The RBF allows large geometrical changes of the electric field domain while retain high element quality of the deformed mesh. Coupling effects between mechanical and electrical domains are directly included within the element formulation. Fringing field effects are described accurate by using traditional arbitrary shape functions.

Keywords: electromechanical, electric field, transducer, simulation, modeling, finite-element, mesh morphing, radial basis function

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1175 Circular Approximation by Trigonometric Bézier Curves

Authors: Maria Hussin, Malik Zawwar Hussain, Mubashrah Saddiqa

Abstract:

We present a trigonometric scheme to approximate a circular arc with its two end points and two end tangents/unit tangents. A rational cubic trigonometric Bézier curve is constructed whose end control points are defined by the end points of the circular arc. Weight functions and the remaining control points of the cubic trigonometric Bézier curve are estimated by variational approach to reproduce a circular arc. The radius error is calculated and found less than the existing techniques.

Keywords: Control points, rational trigonometric Bézier curves, radius error, shape measure, weight functions.

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1174 Dynamic TDMA Slot Reservation Protocol for QoS Provisioning in Cognitive Radio Ad Hoc Networks

Authors: S. M. Kamruzzaman

Abstract:

In this paper, we propose a dynamic TDMA slot reservation (DTSR) protocol for cognitive radio ad hoc networks. Quality of Service (QoS) guarantee plays a critically important role in such networks. We consider the problem of providing QoS guarantee to users as well as to maintain the most efficient use of scarce bandwidth resources. According to one hop neighboring information and the bandwidth requirement, our proposed protocol dynamically changes the frame length and the transmission schedule. A dynamic frame length expansion and shrinking scheme that controls the excessive increase of unassigned slots has been proposed. This method efficiently utilizes the channel bandwidth by assigning unused slots to new neighboring nodes and increasing the frame length when the number of slots in the frame is insufficient to support the neighboring nodes. It also shrinks the frame length when half of the slots in the frame of a node are empty. An efficient slot reservation protocol not only guarantees successful data transmissions without collisions but also enhance channel spatial reuse to maximize the system throughput. Our proposed scheme, which provides both QoS guarantee and efficient resource utilization, be employed to optimize the channel spatial reuse and maximize the system throughput. Extensive simulation results show that the proposed mechanism achieves desirable performance in multichannel multi-rate cognitive radio ad hoc networks.

Keywords: TDMA, cognitive radio, ad hoc networks, QoSguarantee, dynamic frame length.

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1173 User Selections on Social Network Applications

Authors: C. C. Liang

Abstract:

MSN used to be the most popular application for communicating among social networks, but Facebook chat is now the most popular. Facebook and MSN have similar characteristics, including usefulness, ease-of-use, and a similar function, which is the exchanging of information with friends. Facebook outperforms MSN in both of these areas. However, the adoption of Facebook and abandonment of MSN have occurred for other reasons. Functions can be improved, but users’ willingness to use does not just depend on functionality. Flow status has been established to be crucial to users’ adoption of cyber applications and to affects users’ adoption of software applications. If users experience flow in using software application, they will enjoy using it frequently, and even change their preferred application from an old to this new one. However, no investigation has examined choice behavior related to switching from Facebook to MSN based on a consideration of flow experiences and functions. This investigation discusses the flow experiences and functions of social-networking applications. Flow experience is found to affect perceived ease of use and perceived usefulness; perceived ease of use influences information ex-change with friends, and perceived usefulness; information exchange influences perceived usefulness, but information exchange has no effect on flow experience.

Keywords: Consumer behavior, social media, technology acceptance model.

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1172 Periodic Solutions of Recurrent Neural Networks with Distributed Delays and Impulses on Time Scales

Authors: Yaping Ren, Yongkun Li

Abstract:

In this paper, by using the continuation theorem of coincidence degree theory, M-matrix theory and constructing some suitable Lyapunov functions, some sufficient conditions are obtained for the existence and global exponential stability of periodic solutions of recurrent neural networks with distributed delays and impulses on time scales. Without assuming the boundedness of the activation functions gj, hj , these results are less restrictive than those given in the earlier references.

Keywords: Recurrent neural networks, global exponential stability, periodic solutions, distributed delays, impulses, time scales.

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1171 A Set Theory Based Factoring Technique and Its Use for Low Power Logic Design

Authors: Padmanabhan Balasubramanian, Ryuta Arisaka

Abstract:

Factoring Boolean functions is one of the basic operations in algorithmic logic synthesis. A novel algebraic factorization heuristic for single-output combinatorial logic functions is presented in this paper and is developed based on the set theory paradigm. The impact of factoring is analyzed mainly from a low power design perspective for standard cell based digital designs in this paper. The physical implementation of a number of MCNC/IWLS combinational benchmark functions and sub-functions are compared before and after factoring, based on a simple technology mapping procedure utilizing only standard gate primitives (readily available as standard cells in a technology library) and not cells corresponding to optimized complex logic. The power results were obtained at the gate-level by means of an industry-standard power analysis tool from Synopsys, targeting a 130nm (0.13μm) UMC CMOS library, for the typical case. The wire-loads were inserted automatically and the simulations were performed with maximum input activity. The gate-level simulations demonstrate the advantage of the proposed factoring technique in comparison with other existing methods from a low power perspective, for arbitrary examples. Though the benchmarks experimentation reports mixed results, the mean savings in total power and dynamic power for the factored solution over a non-factored solution were 6.11% and 5.85% respectively. In terms of leakage power, the average savings for the factored forms was significant to the tune of 23.48%. The factored solution is expected to better its non-factored counterpart in terms of the power-delay product as it is well-known that factoring, in general, yields a delay-efficient multi-level solution.

Keywords: Factorization, Set theory, Logic function, Standardcell based design, Low power.

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1170 Statistical Approach to Basis Function Truncation in Digital Interpolation Filters

Authors: F. Castillo, J. Arellano, S. Sánchez

Abstract:

In this paper an alternative analysis in the time domain is described and the results of the interpolation process are presented by means of functions that are based on the rule of conditional mathematical expectation and the covariance function. A comparison between the interpolation error caused by low order filters and the classic sinc(t) truncated function is also presented. When fewer samples are used, low-order filters have less error. If the number of samples increases, the sinc(t) type functions are a better alternative. Generally speaking there is an optimal filter for each input signal which depends on the filter length and covariance function of the signal. A novel scheme of work for adaptive interpolation filters is also presented.

Keywords: Interpolation, basis function, over-sampling.

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1169 Simulating and Forecasting Qualitative Marcoeconomic Models Using Rule-Based Fuzzy Cognitive Maps

Authors: Spiros Mazarakis, George Matzavinos, Peter P. Groumpos

Abstract:

Economic models are complex dynamic systems with a lot of uncertainties and fuzzy data. Conventional modeling approaches using well known methods and techniques cannot provide realistic and satisfactory answers to today-s challenging economic problems. Qualitative modeling using fuzzy logic and intelligent system theories can be used to model macroeconomic models. Fuzzy Cognitive maps (FCM) is a new method been used to model the dynamic behavior of complex systems. For the first time FCMs and the Mamdani Model of Intelligent control is used to model macroeconomic models. This new model is referred as the Mamdani Rule-Based Fuzzy Cognitive Map (MBFCM) and provides the academic and research community with a new promising integrated advanced computational model. A new economic model is developed for a qualitative approach to Macroeconomic modeling. Fuzzy Controllers for such models are designed. Simulation results for an economic scenario are provided and extensively discussed

Keywords: Macroeconomic Models, Mamdani Rule Based- FCMs(MBFCMs), Qualitative and Dynamics System, Simulation.

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