Search results for: Function estimation
2880 Statistical Estimation of Spring-back Degree Using Texture Database
Authors: Takashi Sakai, Shinsaku Kikuta, Jun-ichi Koyama
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Using a texture database, a statistical estimation of spring-back was conducted in this study on the basis of statistical analysis. Both spring-back in bending deformation and experimental data related to the crystal orientation show significant dispersion. Therefore, a probabilistic statistical approach was established for the proper quantification of these values. Correlation was examined among the parameters F(x) of spring-back, F(x) of the buildup fraction to three orientations after 92° bending, and F(x) at an as-received part on the basis of the three-parameter Weibull distribution. Consequent spring-back estimation using a texture database yielded excellent estimates compared with experimental values.
Keywords: Bending, Spring-back, Database, Crystallographic Orientation, Texture, SEM-EBSD, Weibull distribution, Statistical analysis.
Procedia APA BibTeX Chicago EndNote Harvard JSON MLA RIS XML ISO 690 PDF Downloads 18992879 A Case Study to Assess the Validity of Function Points
Authors: Neelam Bawane nee' Singhal, C. V. Srikrishna
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Many metrics were proposed to evaluate the characteristics of the analysis and design model of a given product which in turn help to assess the quality of the product. Function point metric is a measure of the 'functionality' delivery by the software. This paper presents an analysis of a set of programs of a project developed in Cµ through Function Points metric. Function points are measured for a Data Flow Diagram (DFD) of the case developed at initial stage. Lines of Codes (LOCs) and possible errors are calculated with the help of measured Function Points (FPs). The calculations are performed using suitable established functions. Calculated LOCs and errors are compared with actual LOCs and errors found at the time of analysis & design review, implementation and testing. It has been observed that actual found errors are more than calculated errors. On the basis of analysis and observations, authors conclude that function point provides useful insight and helps to analyze the drawbacks in the development process.Keywords: Function Points, Data Flow Diagram, Lines ofCodes.
Procedia APA BibTeX Chicago EndNote Harvard JSON MLA RIS XML ISO 690 PDF Downloads 36712878 Subclasses of Bi-Univalent Functions Associated with Hohlov Operator
Authors: Rashidah Omar, Suzeini Abdul Halim, Aini Janteng
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The coefficients estimate problem for Taylor-Maclaurin series is still an open problem especially for a function in the subclass of bi-univalent functions. A function f ϵ A is said to be bi-univalent in the open unit disk D if both f and f-1 are univalent in D. The symbol A denotes the class of all analytic functions f in D and it is normalized by the conditions f(0) = f’(0) – 1=0. The class of bi-univalent is denoted by The subordination concept is used in determining second and third Taylor-Maclaurin coefficients. The upper bound for second and third coefficients is estimated for functions in the subclasses of bi-univalent functions which are subordinated to the function φ. An analytic function f is subordinate to an analytic function g if there is an analytic function w defined on D with w(0) = 0 and |w(z)| < 1 satisfying f(z) = g[w(z)]. In this paper, two subclasses of bi-univalent functions associated with Hohlov operator are introduced. The bound for second and third coefficients of functions in these subclasses is determined using subordination. The findings would generalize the previous related works of several earlier authors.
Keywords: Analytic functions, bi-univalent functions, Hohlov operator, subordination.
Procedia APA BibTeX Chicago EndNote Harvard JSON MLA RIS XML ISO 690 PDF Downloads 9462877 Blind Channel Estimation for Frequency Hopping System Using Subspace Based Method
Authors: M. M. Qasaymeh, M. A. Khodeir
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Subspace channel estimation methods have been studied widely, where the subspace of the covariance matrix is decomposed to separate the signal subspace from noise subspace. The decomposition is normally done by using either the eigenvalue decomposition (EVD) or the singular value decomposition (SVD) of the auto-correlation matrix (ACM). However, the subspace decomposition process is computationally expensive. This paper considers the estimation of the multipath slow frequency hopping (FH) channel using noise space based method. In particular, an efficient method is proposed to estimate the multipath time delays by applying multiple signal classification (MUSIC) algorithm which is based on the null space extracted by the rank revealing LU (RRLU) factorization. As a result, precise information is provided by the RRLU about the numerical null space and the rank, (i.e., important tool in linear algebra). The simulation results demonstrate the effectiveness of the proposed novel method by approximately decreasing the computational complexity to the half as compared with RRQR methods keeping the same performance.
Keywords: Time Delay Estimation, RRLU, RRQR, MUSIC, LS-ESPRIT, LS-ESPRIT, Frequency Hopping.
Procedia APA BibTeX Chicago EndNote Harvard JSON MLA RIS XML ISO 690 PDF Downloads 20442876 Presentation of a Mix Algorithm for Estimating the Battery State of Charge Using Kalman Filter and Neural Networks
Authors: Amin Sedighfar, M. R. Moniri
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Determination of state of charge (SOC) in today’s world becomes an increasingly important issue in all the applications that include a battery. In fact, estimation of the SOC is a fundamental need for the battery, which is the most important energy storage in Hybrid Electric Vehicles (HEVs), smart grid systems, drones, UPS and so on. Regarding those applications, the SOC estimation algorithm is expected to be precise and easy to implement. This paper presents an online method for the estimation of the SOC of Valve-Regulated Lead Acid (VRLA) batteries. The proposed method uses the well-known Kalman Filter (KF), and Neural Networks (NNs) and all of the simulations have been done with MATLAB software. The NN is trained offline using the data collected from the battery discharging process. A generic cell model is used, and the underlying dynamic behavior of the model has used two capacitors (bulk and surface) and three resistors (terminal, surface, and end), where the SOC determined from the voltage represents the bulk capacitor. The aim of this work is to compare the performance of conventional integration-based SOC estimation methods with a mixed algorithm. Moreover, by containing the effect of temperature, the final result becomes more accurate.
Keywords: Kalman filter, neural networks, state-of-charge, VRLA battery.
Procedia APA BibTeX Chicago EndNote Harvard JSON MLA RIS XML ISO 690 PDF Downloads 14032875 Explicit Chain Homotopic Function to Compute Hochschild Homology of the Polynomial Algebra
Authors: Z. Altawallbeh
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In this paper, an explicit homotopic function is constructed to compute the Hochschild homology of a finite dimensional free k-module V. Because the polynomial algebra is of course fundamental in the computation of the Hochschild homology HH and the cyclic homology CH of commutative algebras, we concentrate our work to compute HH of the polynomial algebra, by providing certain homotopic function.
Keywords: Exterior algebra, free resolution, free and projective modules, Hochschild homology, homotopic function, symmetric algebra.
Procedia APA BibTeX Chicago EndNote Harvard JSON MLA RIS XML ISO 690 PDF Downloads 14992874 The Ability of Forecasting the Term Structure of Interest Rates Based On Nelson-Siegel and Svensson Model
Authors: Tea Poklepović, Zdravka Aljinović, Branka Marasović
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Due to the importance of yield curve and its estimation it is inevitable to have valid methods for yield curve forecasting in cases when there are scarce issues of securities and/or week trade on a secondary market. Therefore in this paper, after the estimation of weekly yield curves on Croatian financial market from October 2011 to August 2012 using Nelson-Siegel and Svensson models, yield curves are forecasted using Vector autoregressive model and Neural networks. In general, it can be concluded that both forecasting methods have good prediction abilities where forecasting of yield curves based on Nelson Siegel estimation model give better results in sense of lower Mean Squared Error than forecasting based on Svensson model Also, in this case Neural networks provide slightly better results. Finally, it can be concluded that most appropriate way of yield curve prediction is Neural networks using Nelson-Siegel estimation of yield curves.
Keywords: Nelson-Siegel model, Neural networks, Svensson model, Vector autoregressive model, Yield curve.
Procedia APA BibTeX Chicago EndNote Harvard JSON MLA RIS XML ISO 690 PDF Downloads 32482873 Some Solitary Wave Solutions of Generalized Pochhammer-Chree Equation via Exp-function Method
Authors: Kourosh Parand, Jamal Amani Rad
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In this paper, Exp-function method is used for some exact solitary solutions of the generalized Pochhammer-Chree equation. It has been shown that the Exp-function method, with the help of symbolic computation, provides a very effective and powerful mathematical tool for solving nonlinear partial differential equations. As a result, some exact solitary solutions are obtained. It is shown that the Exp-function method is direct, effective, succinct and can be used for many other nonlinear partial differential equations.
Keywords: Exp-function method, generalized Pochhammer- Chree equation, solitary wave solution, ODE's.
Procedia APA BibTeX Chicago EndNote Harvard JSON MLA RIS XML ISO 690 PDF Downloads 15892872 A New Approach to Solve Blasius Equation using Parameter Identification of Nonlinear Functions based on the Bees Algorithm (BA)
Authors: E. Assareh, M.A. Behrang, M. Ghalambaz, A.R. Noghrehabadi, A. Ghanbarzadeh
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In this paper, a new approach is introduced to solve Blasius equation using parameter identification of a nonlinear function which is used as approximation function. Bees Algorithm (BA) is applied in order to find the adjustable parameters of approximation function regarding minimizing a fitness function including these parameters (i.e. adjustable parameters). These parameters are determined how the approximation function has to satisfy the boundary conditions. In order to demonstrate the presented method, the obtained results are compared with another numerical method. Present method can be easily extended to solve a wide range of problems.Keywords: Bees Algorithm (BA); Approximate Solutions; Blasius Differential Equation.
Procedia APA BibTeX Chicago EndNote Harvard JSON MLA RIS XML ISO 690 PDF Downloads 18012871 Solar Cell Parameters Estimation Using Simulated Annealing Algorithm
Authors: M. R. AlRashidi, K. M. El-Naggar, M. F. AlHajri
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This paper presents Simulated Annealing based approach to estimate solar cell model parameters. Single diode solar cell model is used in this study to validate the proposed approach outcomes. The developed technique is used to estimate different model parameters such as generated photocurrent, saturation current, series resistance, shunt resistance, and ideality factor that govern the current-voltage relationship of a solar cell. A practical case study is used to test and verify the consistency of accurately estimating various parameters of single diode solar cell model. Comparative study among different parameter estimation techniques is presented to show the effectiveness of the developed approach.Keywords: Simulated Annealing, Parameter Estimation, Solar Cell.
Procedia APA BibTeX Chicago EndNote Harvard JSON MLA RIS XML ISO 690 PDF Downloads 25572870 The New Relative Efficiency Based on the Least Eigenvalue in Generalized Linear Model
Authors: Chao Yuan, Bao Guang Tian
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A new relative efficiency is defined as LSE and BLUE in the generalized linear model. The relative efficiency is based on the ratio of the least eigenvalues. In this paper, we discuss about its lower bound and the relationship between it and generalized relative coefficient. Finally, this paper proves that the new estimation is better under Stein function and special condition in some degree.Keywords: Generalized linear model, generalized relative coefficient, least eigenvalue, relative efficiency.
Procedia APA BibTeX Chicago EndNote Harvard JSON MLA RIS XML ISO 690 PDF Downloads 11882869 Extremal Properties of Generalized Class of Close-to-convex Functions
Authors: Norlyda Mohamed, Daud Mohamad, Shaharuddin Cik Soh
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Let Gα ,β (γ ,δ ) denote the class of function f (z), f (0) = f ′(0)−1= 0 which satisfied e δ {αf ′(z)+ βzf ′′(z)}> γ i Re in the open unit disk D = {z ∈ı : z < 1} for some α ∈ı (α ≠ 0) , β ∈ı and γ ∈ı (0 ≤γ <α ) where δ ≤ π and α cosδ −γ > 0 . In this paper, we determine some extremal properties including distortion theorem and argument of f ′( z ) .Keywords: Argument of f ′(z) , Carathéodory Function, Closeto- convex Function, Distortion Theorem, Extremal Properties
Procedia APA BibTeX Chicago EndNote Harvard JSON MLA RIS XML ISO 690 PDF Downloads 13542868 A Pipelined FSBM Hardware Architecture for HTDV-H.26x
Authors: H. Loukil, A. Ben Atitallah, F. Ghozzi, M. A. Ben Ayed, N. Masmoudi
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In MPEG and H.26x standards, to eliminate the temporal redundancy we use motion estimation. Given that the motion estimation stage is very complex in terms of computational effort, a hardware implementation on a re-configurable circuit is crucial for the requirements of different real time multimedia applications. In this paper, we present hardware architecture for motion estimation based on "Full Search Block Matching" (FSBM) algorithm. This architecture presents minimum latency, maximum throughput, full utilization of hardware resources such as embedded memory blocks, and combining both pipelining and parallel processing techniques. Our design is described in VHDL language, verified by simulation and implemented in a Stratix II EP2S130F1020C4 FPGA circuit. The experiment result show that the optimum operating clock frequency of the proposed design is 89MHz which achieves 160M pixels/sec.Keywords: SAD, FSBM, Hardware Implementation, FPGA.
Procedia APA BibTeX Chicago EndNote Harvard JSON MLA RIS XML ISO 690 PDF Downloads 16402867 Algebraic Approach for the Reconstruction of Linear and Convolutional Error Correcting Codes
Authors: Johann Barbier, Guillaume Sicot, Sebastien Houcke
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In this paper we present a generic approach for the problem of the blind estimation of the parameters of linear and convolutional error correcting codes. In a non-cooperative context, an adversary has only access to the noised transmission he has intercepted. The intercepter has no knowledge about the parameters used by the legal users. So, before having acess to the information he has first to blindly estimate the parameters of the error correcting code of the communication. The presented approach has the main advantage that the problem of reconstruction of such codes can be expressed in a very simple way. This allows us to evaluate theorical bounds on the complexity of the reconstruction process but also bounds on the estimation rate. We show that some classical reconstruction techniques are optimal and also explain why some of them have theorical complexities greater than these experimentally observed.
Keywords: Blind estimation parameters, error correcting codes, non-cooperative context, reconstruction algorithm
Procedia APA BibTeX Chicago EndNote Harvard JSON MLA RIS XML ISO 690 PDF Downloads 21962866 Blind Source Separation based on the Estimation for the Number of the Blind Sources under a Dynamic Acoustic Environment
Authors: Takaaki Ishibashi
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Independent component analysis can estimate unknown source signals from their mixtures under the assumption that the source signals are statistically independent. However, in a real environment, the separation performance is often deteriorated because the number of the source signals is different from that of the sensors. In this paper, we propose an estimation method for the number of the sources based on the joint distribution of the observed signals under two-sensor configuration. From several simulation results, it is found that the number of the sources is coincident to that of peaks in the histogram of the distribution. The proposed method can estimate the number of the sources even if it is larger than that of the observed signals. The proposed methods have been verified by several experiments.Keywords: blind source separation, independent component analysys, estimation for the number of the blind sources, voice activity detection, target extraction.
Procedia APA BibTeX Chicago EndNote Harvard JSON MLA RIS XML ISO 690 PDF Downloads 13012865 Reasons for the Slow Uptake of Embodied Carbon Estimation in the Sri Lankan Building Sector
Authors: Amalka Nawarathna, Nirodha Fernando, Zaid Alwan
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Global carbon reduction is not merely a responsibility of environmentally advanced developed countries, but also a responsibility of developing countries regardless of their less impact on global carbon emissions. In recognition of that, Sri Lanka as a developing country has initiated promoting green building construction as one reduction strategy. However, notwithstanding the increasing attention on Embodied Carbon (EC) reduction in the global building sector, they still mostly focus on Operational Carbon (OC) reduction (through improving operational energy). An adequate attention has not yet been given on EC estimation and reduction. Therefore, this study aims to identify the reasons for the slow uptake of EC estimation in the Sri Lankan building sector. To achieve this aim, 16 numbers of global barriers to estimate EC were identified through existing literature. They were then subjected to a pilot survey to identify the significant reasons for the slow uptake of EC estimation in the Sri Lankan building sector. A questionnaire with a three-point Likert scale was used to this end. The collected data were analysed using descriptive statistics. The findings revealed that 11 out of 16 challenges/ barriers are highly relevant as reasons for the slow uptake in estimating EC in buildings in Sri Lanka while the other five challenges/ barriers remain as moderately relevant reasons. Further, the findings revealed that there are no low relevant reasons. Eventually, the paper concluded that all the known reasons are significant to the Sri Lankan building sector and it is necessary to address them in order to upturn the attention on EC reduction.
Keywords: Embodied carbon emissions, embodied carbon estimation, global carbon reduction, Sri Lankan building sector.
Procedia APA BibTeX Chicago EndNote Harvard JSON MLA RIS XML ISO 690 PDF Downloads 8252864 The Study of the Discrete Risk Model with Random Income
Authors: Peichen Zhao
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In this paper, we extend the compound binomial model to the case where the premium income process, based on a binomial process, is no longer a linear function. First, a mathematically recursive formula is derived for non ruin probability, and then, we examine the expected discounted penalty function, satisfy a defect renewal equation. Third, the asymptotic estimate for the expected discounted penalty function is then given. Finally, we give two examples of ruin quantities to illustrate applications of the recursive formula and the asymptotic estimate for penalty function.
Keywords: Discounted penalty function, compound binomial process, recursive formula, discrete renewal equation, asymptotic estimate.
Procedia APA BibTeX Chicago EndNote Harvard JSON MLA RIS XML ISO 690 PDF Downloads 14232863 Thermal Modeling of Dry-Transformers and Estimating Temperature Rise
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Temperature rise in a transformer depends on variety of parameters such as ambient temperature, output current and type of the core. Considering these parameters, temperature rise estimation is still complicated procedure. In this paper, we present a new model based on simple electrical equivalent circuit. This method avoids the complication associated to accurate estimation and is in very good agreement with practice.Keywords: Thermal modeling, temperature rise, equivalent thermal circuit.
Procedia APA BibTeX Chicago EndNote Harvard JSON MLA RIS XML ISO 690 PDF Downloads 38112862 Memory Estimation of Internet Server Using Queuing Theory: Comparative Study between M/G/1, G/M/1 and G/G/1 Queuing Model
Authors: L. K. Singh, Riktesh Srivastava
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How to effectively allocate system resource to process the Client request by Gateway servers is a challenging problem. In this paper, we propose an improved scheme for autonomous performance of Gateway servers under highly dynamic traffic loads. We devise a methodology to calculate Queue Length and Waiting Time utilizing Gateway Server information to reduce response time variance in presence of bursty traffic. The most widespread contemplation is performance, because Gateway Servers must offer cost-effective and high-availability services in the elongated period, thus they have to be scaled to meet the expected load. Performance measurements can be the base for performance modeling and prediction. With the help of performance models, the performance metrics (like buffer estimation, waiting time) can be determined at the development process. This paper describes the possible queue models those can be applied in the estimation of queue length to estimate the final value of the memory size. Both simulation and experimental studies using synthesized workloads and analysis of real-world Gateway Servers demonstrate the effectiveness of the proposed system.Keywords: M/M/1, M/G/1, G/M/1, G/G/1, Gateway Servers, Buffer Estimation, Waiting Time, Queuing Process.
Procedia APA BibTeX Chicago EndNote Harvard JSON MLA RIS XML ISO 690 PDF Downloads 19352861 Clustering Unstructured Text Documents Using Fading Function
Authors: Pallav Roxy, Durga Toshniwal
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Clustering unstructured text documents is an important issue in data mining community and has a number of applications such as document archive filtering, document organization and topic detection and subject tracing. In the real world, some of the already clustered documents may not be of importance while new documents of more significance may evolve. Most of the work done so far in clustering unstructured text documents overlooks this aspect of clustering. This paper, addresses this issue by using the Fading Function. The unstructured text documents are clustered. And for each cluster a statistics structure called Cluster Profile (CP) is implemented. The cluster profile incorporates the Fading Function. This Fading Function keeps an account of the time-dependent importance of the cluster. The work proposes a novel algorithm Clustering n-ary Merge Algorithm (CnMA) for unstructured text documents, that uses Cluster Profile and Fading Function. Experimental results illustrating the effectiveness of the proposed technique are also included.Keywords: Clustering, Text Mining, Unstructured TextDocuments, Fading Function.
Procedia APA BibTeX Chicago EndNote Harvard JSON MLA RIS XML ISO 690 PDF Downloads 19842860 A Dual Fitness Function Genetic Algorithm: Application on Deterministic Identical Machine Scheduling
Authors: Saleem Z. Ramadan, Gürsel A. Süer
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In this paper a genetic algorithm (GA) with dual-fitness function is proposed and applied to solve the deterministic identical machine scheduling problem. The mating fitness function value was used to determine the mating for chromosomes, while the selection fitness function value was used to determine their survivals. The performance of this algorithm was tested on deterministic identical machine scheduling using simulated data. The results obtained from the proposed GA were compared with classical GA and integer programming (IP). Results showed that dual-fitness function GA outperformed the classical single-fitness function GA with statistical significance for large problems and was competitive to IP, particularly when large size problems were used.
Keywords: Machine scheduling, Genetic algorithms, Due dates, Number of tardy jobs, Number of early jobs, Integer programming, Dual Fitness functions.
Procedia APA BibTeX Chicago EndNote Harvard JSON MLA RIS XML ISO 690 PDF Downloads 20682859 Effect of Channel Estimation on Capacity of MIMO System Employing Circular or Linear Receiving Array Antennas
Authors: Xia Liu, Marek E. Bialkowski
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This paper reports on investigations into capacity of a Multiple Input Multiple Output (MIMO) wireless communication system employing a uniform linear array (ULA) at the transmitter and either a uniform linear array (ULA) or a uniform circular array (UCA) antenna at the receiver. The transmitter is assumed to be surrounded by scattering objects while the receiver is postulated to be free from scattering objects. The Laplacian distribution of angle of arrival (AOA) of a signal reaching the receiver is postulated. Calculations of the MIMO system capacity are performed for two cases without and with the channel estimation errors. For estimating the MIMO channel, the scaled least square (SLS) and minimum mean square error (MMSE) methods are considered.Keywords: MIMO, channel capacity, channel estimation, ULA, UCA, spatial correlation
Procedia APA BibTeX Chicago EndNote Harvard JSON MLA RIS XML ISO 690 PDF Downloads 13642858 Detection and Pose Estimation of People in Images
Authors: Mousa Mojarrad, Amir Masoud Rahmani, Mehrab Mohebi
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Detection, feature extraction and pose estimation of people in images and video is made challenging by the variability of human appearance, the complexity of natural scenes and the high dimensionality of articulated body models and also the important field in Image, Signal and Vision Computing in recent years. In this paper, four types of people in 2D dimension image will be tested and proposed. The system will extract the size and the advantage of them (such as: tall fat, short fat, tall thin and short thin) from image. Fat and thin, according to their result from the human body that has been extract from image, will be obtained. Also the system extract every size of human body such as length, width and shown them in output.Keywords: Analysis of Image Processing, Canny Edge Detection, Human Body Recognition, Measurement, Pose Estimation, 2D Human Dimension.
Procedia APA BibTeX Chicago EndNote Harvard JSON MLA RIS XML ISO 690 PDF Downloads 22992857 Random Access in IoT Using Naïve Bayes Classification
Authors: Alhusein Almahjoub, Dongyu Qiu
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This paper deals with the random access procedure in next-generation networks and presents the solution to reduce total service time (TST) which is one of the most important performance metrics in current and future internet of things (IoT) based networks. The proposed solution focuses on the calculation of optimal transmission probability which maximizes the success probability and reduces TST. It uses the information of several idle preambles in every time slot, and based on it, it estimates the number of backlogged IoT devices using Naïve Bayes estimation which is a type of supervised learning in the machine learning domain. The estimation of backlogged devices is necessary since optimal transmission probability depends on it and the eNodeB does not have information about it. The simulations are carried out in MATLAB which verify that the proposed solution gives excellent performance.
Keywords: Random access, LTE/LTE-A, 5G, machine learning, Naïve Bayes estimation.
Procedia APA BibTeX Chicago EndNote Harvard JSON MLA RIS XML ISO 690 PDF Downloads 4472856 Kalman-s Shrinkage for Wavelet-Based Despeckling of SAR Images
Authors: Mario Mastriani, Alberto E. Giraldez
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In this paper, a new probability density function (pdf) is proposed to model the statistics of wavelet coefficients, and a simple Kalman-s filter is derived from the new pdf using Bayesian estimation theory. Specifically, we decompose the speckled image into wavelet subbands, we apply the Kalman-s filter to the high subbands, and reconstruct a despeckled image from the modified detail coefficients. Experimental results demonstrate that our method compares favorably to several other despeckling methods on test synthetic aperture radar (SAR) images.Keywords: Kalman's filter, shrinkage, speckle, wavelets.
Procedia APA BibTeX Chicago EndNote Harvard JSON MLA RIS XML ISO 690 PDF Downloads 16052855 Function of miR-125b in Zebrafish Neurogenesis
Authors: Minh T. N. Le, Cathleen Teh, Ng Shyh-Chang, Vladimir Korzh, Harvey F. Lodish, Bing Lim
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MicroRNAs are an important class of gene expression regulators that are involved in many biological processes including embryogenesis. miR-125b is a conserved microRNA that is enriched in the nervous system. We have previously reported the function of miR-125b in neuronal differentiation of human cell lines. We also discovered the function of miR-125b in regulating p53 in human and zebrafish. Here we further characterize the brain defects in zebrafish embryos injected with morpholinos against miR-125b. Our data confirm the essential role of miR-125b in brain morphogenesis particularly in maintaining the balance between proliferation, cell death and differentiation. We identified lunatic fringe (lfng) as an additional target of miR-125b in human and zebrafish and suggest that lfng may mediate the function of miR-125b in neurogenesis. Together, this report reveals new insights into the function of miR- 125b during neural development of zebrafish.Keywords: microRNA, miR-125b, neurogenesis, zebrafish.
Procedia APA BibTeX Chicago EndNote Harvard JSON MLA RIS XML ISO 690 PDF Downloads 18682854 Real Time Video Based Smoke Detection Using Double Optical Flow Estimation
Authors: Anton Stadler, Thorsten Ike
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In this paper, we present a video based smoke detection algorithm based on TVL1 optical flow estimation. The main part of the algorithm is an accumulating system for motion angles and upward motion speed of the flow field. We optimized the usage of TVL1 flow estimation for the detection of smoke with very low smoke density. Therefore, we use adapted flow parameters and estimate the flow field on difference images. We show in theory and in evaluation that this improves the performance of smoke detection significantly. We evaluate the smoke algorithm using videos with different smoke densities and different backgrounds. We show that smoke detection is very reliable in varying scenarios. Further we verify that our algorithm is very robust towards crowded scenes disturbance videos.Keywords: Low density, optical flow, upward smoke motion, video based smoke detection.
Procedia APA BibTeX Chicago EndNote Harvard JSON MLA RIS XML ISO 690 PDF Downloads 14192853 A Practical and Efficient Evaluation Function for 3D Model Based Vehicle Matching
Authors: Yuan Zheng
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3D model-based vehicle matching provides a new way for vehicle recognition, localization and tracking. Its key is to construct an evaluation function, also called fitness function, to measure the degree of vehicle matching. The existing fitness functions often poorly perform when the clutter and occlusion exist in traffic scenarios. In this paper, we present a practical and efficient fitness function. Unlike the existing evaluation functions, the proposed fitness function is to study the vehicle matching problem from both local and global perspectives, which exploits the pixel gradient information as well as the silhouette information. In view of the discrepancy between 3D vehicle model and real vehicle, a weighting strategy is introduced to differently treat the fitting of the model’s wireframes. Additionally, a normalization operation for the model’s projection is performed to improve the accuracy of the matching. Experimental results on real traffic videos reveal that the proposed fitness function is efficient and robust to the cluttered background and partial occlusion.Keywords: 3D-2D matching, fitness function, 3D vehicle model, local image gradient, silhouette information.
Procedia APA BibTeX Chicago EndNote Harvard JSON MLA RIS XML ISO 690 PDF Downloads 16342852 Direction of Arrival Estimation Based on a Single Port Smart Antenna Using MUSIC Algorithm with Periodic Signals
Authors: Chen Sun, Nemai Chandra Karmakar
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A novel direction-of-arrival (DOA) estimation technique, which uses a conventional multiple signal classification (MUSIC) algorithm with periodic signals, is applied to a single RF-port parasitic array antenna for direction finding. Simulation results show that the proposed method gives high resolution (1 degree) DOA estimation in an uncorrelated signal environment. The novelty lies in that the MUSIC algorithm is applied to a simplified antenna configuration. Only one RF port and one analogue-to-digital converter (ADC) are used in this antenna, which features low DC power consumption, low cost, and ease of fabrication. Modifications to the conventional MUSIC algorithm do not bring much additional complexity. The proposed technique is also free from the negative influence by the mutual coupling between elements. Therefore, the technique has great potential to be implemented into the existing wireless mobile communications systems, especially at the power consumption limited mobile terminals, to provide additional position location (PL) services.
Keywords: Direction-of-arrival (DOA) estimation, electronically steerable parasitic array radiator (ESPAR), multiple single classifications (MUSIC), position location.
Procedia APA BibTeX Chicago EndNote Harvard JSON MLA RIS XML ISO 690 PDF Downloads 29922851 A Modified Spiral Search Algorithm and Its Embedded System Architecture Design
Authors: Nikolaos Kroupis, Minas Dasygenis, Dimitrios Soudris, Antonios Thanailakis
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One of the most growing areas in the embedded community is multimedia devices. Multimedia devices incorporate a number of complicated functions for their operation, like motion estimation. A multitude of different implementations have been proposed to reduce motion estimation complexity, such as spiral search. We have studied the implementations of spiral search and identified areas of improvement. We propose a modified spiral search algorithm, with lower computational complexity compared to the original spiral search. We have implemented our algorithm on an embedded ARM based architecture, with custom memory hierarchy. The resulting system yields energy consumption reduction up to 64% and performance increase up to 77%, with a small penalty of 2.3 dB, in average, of video quality compared with the original spiral search algorithm.
Keywords: Spiral Search, Motion Estimation, Embedded Systems, Low Power
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