Designs of low delay cosine modulated filter banks and subband amplifiers

This paper proposes a design of a low delay cosine modu-lated filter bank and subband amplifier coefficients for digi-tal audio hearing aids denoising applications. The objective of the design is to minimize the delay of the filter bank. Speci-fications on the maximum magnitude of both the real and the imaginary parts of the transfer function distortion and the aliasing distortion of the filter bank are imposed. Also, the constraint on the maximum absolute difference between the desirable magnitude square response and the designed mag-nitude square response of the prototype filter over both the passband and the stopband is considered. The subband am-plifier coefficients are designed based on a least squares training approach. The average mean square errors between the noisy samples and the clean samples is minimized. Com-puter numerical simulation results show that our proposed approach could significantly improve the signal-to-noise ratio of digital audio hearing aids

Validation of the comprehensive feeding practice questionnaire among school aged children in Jordan: A factor analysis study

BACKGROUND: Obesity has become a significant worldwide contributor to morbidity with an alarming increase in the incidence of childhood obesity. Few studies have evaluated parental feeding practices and their impact on child obesity in the Middle East. The Comprehensive Feeding Practice questionnaire (CFPQ; Musher-Eizenman & Holub, 2007) has been validated in different age groups and in different countries, however no previous studies have validated the questionnaire in the Middle East. METHOD: In this study, 970 children aged 6–12 completed the Arabic translated version of the CFPQ. The height and weight of the children were also measured. Confirmatory factor and exploratory factor analysis were used to evaluate different factor models. An ordinal logistic regression was conducted to evaluate the association between maternal feeding practices and child weight status. RESULTS: Confirmatory analysis of the CFPQ determined that the original 12 factor structure of the questionnaire was not suitable for this sample. The analysis suggested that the most suitable structure was an 11 factors model (CMIN/DF = 2.18, GFI = 0.92, CFI = 0.93, TLI = 0.92 and RMSEA = 0.03) that included Modelling, Monitoring, Child control, Food as a reward, Emotional regulation, Involvement, Restriction for health, Restriction for weight control, Environment, Teach and encourage and Pressure. Of the children tested, 12.6% were obese and 25.1% were overweight. The ordinal regression showed Restriction to health and weight, Emotional regulation and maternal BMI were negatively associated with healthy weight status, while Modelling, Monitoring, Child Control, Environment, Involvement, and Teach and encourage were positively associated with healthy weight status. CONCLUSION: The Arabic translated version of the CFPQ was validated among the study sample, and the best fit for the model was found to utilize 11 factors. This study indicated that child weight status was associated with maternal feeding practices. ELECTRONIC SUPPLEMENTARY MATERIAL: The online version of this article (doi:10.1186/s12966-017-0478-y) contains supplementary material, which is available to authorized users

Pulmonary function tests in Egyptian schoolchildren in rural and urban areas

Background: Previous studies have shown a negative association between urban environments and pulmonary function. Objectives: This longitudinal study examined the effect of an urban environment on pulmonary function tests of children by comparing children from an urban and a rural area in Egypt. The effect of other factors on pulmonary function, including obesity, breastfeeding and parental atopy, was also examined. Methods: Children aged 7−12 years from rural Shibin El-Kom and urban Cairo were enrolled in the study. Forced expiratory volume in the frst second (FEV1), forced vital capacity (FVC), forced expiratory rate and peak expiratory flow rate (PEFR) were measured 5 times over a period of 2 years, at 6-monthly intervals. Factorial repeated measures analysis of variance was used to evaluate the differences in the rate of change in FEV1 predicted%, FVC predicted% and PEFR between the children in Cairo and Shibin El-Kom. Generalized linear mixed models were used to analyse factors associated with pulmonary function test results. Results: Generalized linear regression showed that living in Cairo decreased log(FVC), log(FEV1) and log(PEFR). Significant differences were found in the changes occurring between the 2 locations in the last 3 visits; children in Cairo showed a smaller increase in pulmonary function. Conclusions: Differences in pulmonary function in the 2 locations increased significantly with time, indicating a negative effect on lung function of living in urban Cairo. The findings could be used to help in the development of policies in Egypt and other developing countries to improve respiratory health, including promoting breastfeeding and reducing outdoor air pollution

Recognition physical activities with optimal number of wearable sensors using data mining algorithms and deep belief network

© 2017 IEEE. Daily physical activities monitoring is benefiting the health care field in several ways, in particular with the development of the wearable sensors. This paper adopts effective ways to calculate the optimal number of the necessary sensors and to build a reliable and a high accuracy monitoring system. Three data mining algorithms, namely Decision Tree, Random Forest and PART Algorithm, have been applied for the sensors selection process. Furthermore, the deep belief network (DBN) has been investigated to recognise 33 physical activities effectively. The results indicated that the proposed method is reliable with an overall accuracy of 96.52% and the number of sensors is minimised from nine to six sensors

Impact of Reactive Obstacle on Molecular Communication between Nanomachines

© 2018 IEEE. Molecular communication is an emerging technology for communication between bio-nanomachines in an aqueous environment. In this paper, we examine the effect of a reactive obstacle, which is placed in the diffusive molecular communication channel, on the expected number of the received molecules at the receiver. We develop a particle-based simulator that can predict the number of the received molecules for both passive and absorptive receivers by considering the impact of the reactive obstacle within the communication channel. The impacts of the reaction probability and radius of the obstacle on the received signal are examined and compared with the case of absence of the obstacle. The results show significant impact for the obstacle on the received signal, particularly, for obstacle with high reaction probability and large size

Efficient diagnosis system for Parkinson's disease using deep belief network

In this paper, a deep belief network (DBN) has been adopted as an efficient technique to diagnosis the Parkinson's disease (PD). This diagnosis has been established based on the speech signal of the patients. Through the distinguishing and analyzing of the speech signal, the DBN has the ability to diagnose Parkinson's disease. To realize the diagnosis of Parkinson's disease by using DBN, the proposed system has been trained and tested with voices from a number of patients and healthy people. A feature extraction process has been prepared to be inputted to the deep belief network (DBN) which is used to create a template matching of the voices. In this paper, DBN is used to classify the Parkinson's disease which composes two stacked Restricted Boltzmann Machines (RBMs) and one output layer. Two stages of learning need to be applied to optimize the networks' parameters. The first stage is unsupervised learning which uses RBMs to overcome the problem that can cause because of the random value of the initial weights. Secondly, backpropagation algorithm is used as a supervised learning for the fine tuning. To illustrate the effectiveness of the proposed system, the experimental results are compared with different approaches and related works. The overall testing accuracy of the proposed system is 94% which is better than all of the compared methods. In short, the DBN is an effective method to diagnosis Parkinson's disease by using the speech signal

Comparison of reception mechanisms for molecular communication via diffusion

© 2018 IEEE. Molecular communication paradigm enables nanomachines or biological cells at nano/micro scales to communicate using chemical molecules. In this paper, we study different reception mechanisms in an unbounded 3-D biological medium for diffusion-based molecular communication system and compare their performances. The number of received molecules (i.e., number of activated receptors) is first analytically evaluated and then validated using a particle-based simulator developed by us. We address various receiver models, viz., passive, irreversible partially or fully absorptive, and a more general reversible receivers. The peak amplitude and peak time for passive and fully absorptive receivers are evaluated. The impact of various parameters, e.g., diffusion coefficient, separation distance, forward/backward reaction rates, on the received signal are examined