Open Science Research Excellence

Open Science Index

Commenced in January 2007 Frequency: Monthly Edition: International Paper Count: 14

14
10008579
Gender Dimension of Migrations Influenced by Genocide and Feminicides around the Globe
Authors:
Abstract:

Gender dimension of migration analyzes the intersection in between the world statistics on male and female migrations, around the world, involving the questions of youth migrations. Comparative analyses of world migration statistics as methodology offer the insight into the position of women in labor market around world. There are different forms of youth debris in contemporary world. The main problems are illegal migration, feminization of poverty, kidnapping the girls in Nigeria, femicides in Juarez and Mexico. Illegal migrations involve forced labor, rape and prostitution. Transgender youth share ideas through the online media (anti-bullying videos) and develop their own styles such as anarcho-punk, rave, or rock. Therefore, the stronger gender equality laws and laws for protection of women on work should be enforced.

13
10008917
Wireless Body Area Network’s Mitigation Method Using Equalization
Abstract:

A wireless body area sensor network (WBASN) is composed of a central node and heterogeneous sensors to supervise the physiological signals and functions of the human body. This overwhelmimg area has stimulated new research and calibration processes, especially in the area of WBASN’s attainment and fidelity. In the era of mobility or imbricated WBASN’s, system performance incomparably degrades because of unstable signal integrity. Hence, it is mandatory to define mitigation techniques in the design to avoid interference. There are various mitigation methods available e.g. diversity techniques, equalization, viterbi decoder etc. This paper presents equalization mitigation scheme in WBASNs to improve the signal integrity. Eye diagrams are also given to represent accuracy of the signal. Maximum no. of symbols is taken to authenticate the signal which in turn results in accuracy and increases the overall performance of the system.

12
10007683
Online Prediction of Nonlinear Signal Processing Problems Based Kernel Adaptive Filtering
Abstract:
This paper presents two of the most knowing kernel adaptive filtering (KAF) approaches, the kernel least mean squares and the kernel recursive least squares, in order to predict a new output of nonlinear signal processing. Both of these methods implement a nonlinear transfer function using kernel methods in a particular space named reproducing kernel Hilbert space (RKHS) where the model is a linear combination of kernel functions applied to transform the observed data from the input space to a high dimensional feature space of vectors, this idea known as the kernel trick. Then KAF is the developing filters in RKHS. We use two nonlinear signal processing problems, Mackey Glass chaotic time series prediction and nonlinear channel equalization to figure the performance of the approaches presented and finally to result which of them is the adapted one.
11
10002999
3D Liver Segmentation from CT Images Using a Level Set Method Based on a Shape and Intensity Distribution Prior
Abstract:

Liver segmentation from medical images poses more challenges than analogous segmentations of other organs. This contribution introduces a liver segmentation method from a series of computer tomography images. Overall, we present a novel method for segmenting liver by coupling density matching with shape priors. Density matching signifies a tracking method which operates via maximizing the Bhattacharyya similarity measure between the photometric distribution from an estimated image region and a model photometric distribution. Density matching controls the direction of the evolution process and slows down the evolving contour in regions with weak edges. The shape prior improves the robustness of density matching and discourages the evolving contour from exceeding liver’s boundaries at regions with weak boundaries. The model is implemented using a modified distance regularized level set (DRLS) model. The experimental results show that the method achieves a satisfactory result. By comparing with the original DRLS model, it is evident that the proposed model herein is more effective in addressing the over segmentation problem. Finally, we gauge our performance of our model against matrices comprising of accuracy, sensitivity, and specificity.

10
10001540
Reduction of Impulsive Noise in OFDM System Using Adaptive Algorithm
Abstract:
The Orthogonal Frequency Division Multiplexing (OFDM) with high data rate, high spectral efficiency and its ability to mitigate the effects of multipath makes them most suitable in wireless application. Impulsive noise distorts the OFDM transmission and therefore methods must be investigated to suppress this noise. In this paper, a State Space Recursive Least Square (SSRLS) algorithm based adaptive impulsive noise suppressor for OFDM communication system is proposed. And a comparison with another adaptive algorithm is conducted. The state space model-dependent recursive parameters of proposed scheme enables to achieve steady state mean squared error (MSE), low bit error rate (BER), and faster convergence than that of some of existing algorithm.
9
10001732
Study of Adaptive Filtering Algorithms and the Equalization of Radio Mobile Channel
Abstract:

This paper presented a study of three algorithms, the equalization algorithm to equalize the transmission channel with ZF and MMSE criteria, application of channel Bran A, and adaptive filtering algorithms LMS and RLS to estimate the parameters of the equalizer filter, i.e. move to the channel estimation and therefore reflect the temporal variations of the channel, and reduce the error in the transmitted signal. So far the performance of the algorithm equalizer with ZF and MMSE criteria both in the case without noise, a comparison of performance of the LMS and RLS algorithm.

8
10000580
A Novel RLS Based Adaptive Filtering Method for Speech Enhancement
Abstract:

Speech enhancement is a long standing problem with numerous applications like teleconferencing, VoIP, hearing aids and speech recognition. The motivation behind this research work is to obtain a clean speech signal of higher quality by applying the optimal noise cancellation technique. Real-time adaptive filtering algorithms seem to be the best candidate among all categories of the speech enhancement methods. In this paper, we propose a speech enhancement method based on Recursive Least Squares (RLS) adaptive filter of speech signals. Experiments were performed on noisy data which was prepared by adding AWGN, Babble and Pink noise to clean speech samples at -5dB, 0dB, 5dB and 10dB SNR levels. We then compare the noise cancellation performance of proposed RLS algorithm with existing NLMS algorithm in terms of Mean Squared Error (MSE), Signal to Noise ratio (SNR) and SNR Loss. Based on the performance evaluation, the proposed RLS algorithm was found to be a better optimal noise cancellation technique for speech signals.

7
11855
An Estimation of the Performance of HRLS Algorithm
Abstract:
The householder RLS (HRLS) algorithm is an O(N2) algorithm which recursively updates an arbitrary square-root of the input data correlation matrix and naturally provides the LS weight vector. A data dependent householder matrix is applied for such an update. In this paper a recursive estimate of the eigenvalue spread and misalignment of the algorithm is presented at a very low computational cost. Misalignment is found to be highly sensitive to the eigenvalue spread of input signals, output noise of the system and exponential window. Simulation results show noticeable degradation in the misalignment by increase in eigenvalue spread as well as system-s output noise, while exponential window was kept constant.
6
8799
Stages of Changes for Physical Activity among Iranian Adolescent Girls
Abstract:
Background: Regular physical activity contributes positively to physical and psychological health. In the present study, the stages of change of physical activity and the total physical Aims: The aim of this study was to investigate the proportion of adolescent girls in each stages of change and the causative factors associated with physical activity such as the related social support and self efficacy in a sample of the high school students. Methods: In this study, Social Cognitive Theory (SCT) and the Transtheorical Model (TTM) guided instrument development. The data regarding the demographics, psychosocial determinants of physical activity, stage of change and physical activity was gathered by questionnaires. Several measures of psychosocial determinants of physical activity were translated from English into Persian using the back-translation technique. These translated measures were administered to 512 ninth and tenth-grade Iranian high school students for factor analysis. Results: The distribution of the stage of change for physical activity was as follow: 18/5% in precontemplation, 23.4% in contemplation, 38.2% in preparation, 4.6% in action and 15.3% in maintenance. They were in 80.1% pre-adoption stages (precontemplation stage, contemplation stage and preparation stage) and 19.9% post-adoption stages (action stage and maintenance stage) of physical activity. There was a significant relate between age and physical activity in adolescent girls (age-related decline of physical activity) p
5
5360
Computational Intelligence Hybrid Learning Approach to Time Series Forecasting
Abstract:
Time series forecasting is an important and widely popular topic in the research of system modeling. This paper describes how to use the hybrid PSO-RLSE neuro-fuzzy learning approach to the problem of time series forecasting. The PSO algorithm is used to update the premise parameters of the proposed prediction system, and the RLSE is used to update the consequence parameters. Thanks to the hybrid learning (HL) approach for the neuro-fuzzy system, the prediction performance is excellent and the speed of learning convergence is much faster than other compared approaches. In the experiments, we use the well-known Mackey-Glass chaos time series. According to the experimental results, the prediction performance and accuracy in time series forecasting by the proposed approach is much better than other compared approaches, as shown in Table IV. Excellent prediction performance by the proposed approach has been observed.
4
5843
A Novel Forgetting Factor Recursive Least Square Algorithm Applied to the Human Motion Analysis
Abstract:

This paper is concerned with studying the forgetting factor of the recursive least square (RLS). A new dynamic forgetting factor (DFF) for RLS algorithm is presented. The proposed DFF-RLS is compared to other methods. Better performance at convergence and tracking of noisy chirp sinusoid is achieved. The control of the forgetting factor at DFF-RLS is based on the gradient of inverse correlation matrix. Compared with the gradient of mean square error algorithm, the proposed approach provides faster tracking and smaller mean square error. In low signal-to-noise ratios, the performance of the proposed method is superior to other approaches.

3
5195
Recursive Least Squares Adaptive Filter a better ISI Compensator
Abstract:

Inter-symbol interference if not taken care off may cause severe error at the receiver and the detection of signal becomes difficult. An adaptive equalizer employing Recursive Least Squares algorithm can be a good compensation for the ISI problem. In this paper performance of communication link in presence of Least Mean Square and Recursive Least Squares equalizer algorithm is analyzed. A Model of communication system having Quadrature amplitude modulation and Rician fading channel is implemented using MATLAB communication block set. Bit error rate and number of errors is evaluated for RLS and LMS equalizer algorithm, due to change in Signal to Noise Ratio (SNR) and fading component gain in Rician fading Channel.

2
10124
The Experiences of South-African High-School Girls in a Fab Lab Environment
Abstract:
This paper reports on an effort to address the issue of inequality in girls- and women-s access to science, engineering and technology (SET) education and careers through raising awareness on SET among secondary school girls in South Africa. Girls participated in hands-on high-tech rapid prototyping environment of a fabrication laboratory that was aimed at stimulating creativity and innovation as part of a Fab Kids initiative. The Fab Kids intervention is about creating a SET pipeline as part of the Young Engineers and Scientists of Africa Initiative.The methodology was based on a real world situation and a hands-on approach. In the process, participants acquired a number of skills including computer-aided design, research skills, communication skills, teamwork skills, technical drawing skills, writing skills and problem-solving skills. Exposure to technology enhanced the girls- confidence in being able to handle technology-related tasks.
1
12736
Modelling Peer Group Dieting Behaviour
Authors:
Abstract:
The aim of this paper is to understand how peers can influence adolescent girls- dieting behaviour and their body image. Departing from imitation and social learning theories, we study whether adolescent girls tend to model their peer group dieting behaviours, thus influencing their body image construction. Our study was conducted through an enquiry applied to a cluster sample of 466 adolescent high school girls in Lisbon city public schools. Our main findings point to an association between girls- and peers- dieting behaviours, thus reinforcing the modelling hypothesis.
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