Adaptive wavelet thresholding with robust hybrid features for text-independent speaker identification system

The robustness of speaker identification system over additive noise channel is crucial for real-world applications. In speaker identification (SID) systems, the extracted features from each speech frame are an essential factor for building a reliable identification system. For clean environments, the identification system works well; in noisy environments, there is an additive noise, which is affect the system. To eliminate the problem of additive noise and to achieve a high accuracy in speaker identification system a proposed algorithm for feature extraction based on speech enhancement and a combined features is presents. In this paper, a wavelet thresholding pre-processing stage, and feature warping (FW) techniques are used with two combined features named power normalized cepstral coefficients (PNCC) and gammatone frequency cepstral coefficients (GFCC) to improve the identification system robustness against different types of additive noises. Universal Background Model Gaussian Mixture Model (UBM-GMM) is used for features matching between the claim and actual speakers. The results showed performance improvement for the proposed feature extraction algorithm of identification system comparing with conventional features over most types of noises and different SNR ratios

Utilising the Intel RealSense camera for measuring health outcomes in clinical research

Applications utilising 3D Camera technologies for the measurement of health outcomes in the health and wellness sector continues to expand. The Intel® RealSense™ is one of the leading 3D depth sensing cameras currently available on the market and aligns itself for use in many applications, including robotics, automation, and medical systems. One of the most prominent areas is the production of interactive solutions for rehabilitation which includes gait analysis and facial tracking. Advancements in depth camera technology has resulted in a noticeable increase in the integration of these technologies into portable platforms, suggesting significant future potential for pervasive in-clinic and field based health assessment solutions. This paper reviews the Intel RealSense technology’s technical capabilities and discusses its application to clinical research and includes examples where the Intel RealSense camera range has been used for the measurement of health outcomes. This review supports the use of the technology to develop robust, objective movement and mobility-based endpoints to enable accurate tracking of the effects of treatment interventions in clinical trials

Percent fluid overload for prediction of fluid de-escalation in critically ill patients in Saudi Arabia: a prospective observational study

Background Percent fluid overload greater than 5% is associated with increased mortality. The appropriate time for fluid deresuscitation depends on the patient's radiological and clinical findings. This study aimed to assess the applicability of percent fluid overload calculations for evaluating the need for fluid deresuscitation in critically ill patients. Methods This was a single-center, prospective, observational study of critically ill adult patients requiring intravenous fluid administration. The study's primary outcome was median percent fluid accumulation on the day of fluid deresuscitation or intensive care unit (ICU) discharge, whichever came first. Results A total of 388 patients was screened between August 1, 2021, and April 30, 2022. Of these, 100 with a mean age of 59.8±16.2 years were included for analysis. The mean Acute Physiology and Chronic Health Evaluation (APACHE) II score was 15.4±8.0. Sixty-one patients (61.0%) required fluid deresuscitation during their ICU stay, while 39 (39.0%) did not. Median percent fluid accumulation on the day of deresuscitation or ICU discharge was 4.5% (interquartile range [IQR], 1.7%–9.1%) and 5.2% (IQR, 2.9%–7.7%) in patients requiring deresuscitation and those who did not, respectively. Hospital mortality occurred in 25 (40.9%) of patients with deresuscitation and six (15.3%) patients who did not require it (P=0.007). Conclusions The percent fluid accumulation on the day of fluid deresuscitation or ICU discharge was not statistically different between patients who required fluid deresuscitation and those who did not. A larger sample size is needed to confirm these findings

Influence of upconversion transition process on the performance of inband pumped holmium-doped silica fiber amplifiers

In this report, a theoretical model of in-band pumped holmium-doped silica fiber amplifiers (HDFAs) is presented. This model is developed to consider the influence of energy transfer up-conversion (ETU) on the HDFAs performance. The advantage of this model is to investigate the properties of HDFAs as a function of holmium-doped fiber length and doping concentration. A good agreement is observed between the simulation results and the previous experimental findings. Our simulation results show the negative impact of ETU process to deteriorate the HDFAs performance and this process may have bigger effect at high holmium doped concentration. This is the first time to our knowledge that the influence of upconversion process is theoretically investigated on the performance of in-band pumped HDFAs

The restorative effect of well-designed open space on the physiological health of the obese adults in Saudi Arabia

It has been found that the restorative environment literature heavily focused on the relationship between experiencing open spaces and psychological health. Yet, the effect of open spaces on physiological health and wellbeing did not received similar attentions. According to World Health Organization, obesity and its related diseases become a critical physiological health issue, especially in Saudi Arabia. Saudi citizens have been recorded among the highest in obesity. This highlights the need of strategies that involve open spaces to control the prevalence of obesity and improve the human physiological health. Thus, this study attempts to identify the physiological restorative effect of open spaces on the obese adult males before and after engaging in physical activities by measuring the changes in the glucose level in the blood and the blood pressure, in the city of Yanbu Alsenayah, which is a well-designed city in Saudi Arabia. The data was collected over five days by monitoring the glucose level, blood pressure level, and heartbeat rate of 38 obese adult males before and after the usage of open spaces. The collected data was analyzed by using SPSS Version 24. The results suggest that there are differences in the readings of the glucose level and blood pressure of the respondents. It indicates that engaging in physical activities in well-designed open spaces, controls obesity and related diseases. Also, it suggests that the design and the facilities at well-designed open spaces attract and motivate the users to be physically active which improve the weight loss

Emotional intelligence weakly predicts academic success in medical programs: a multilevel meta-analysis and systematic review

Abstract Background Emotional intelligence (EI) is a predictive factor of academic success in undergraduate Doctor of Medicine (MD) programs. Although some research suggests a positive association between EI and academic success in MD programs, other research reports neither an association nor a negative correlation between the two variables. The current study aimed to resolve these contradictory findings by conducting a systematic review and a meta-analysis using research from 2005 to 2022. Methods Data were analyzed using a multilevel modeling approach to (a) estimate the overall relationship between EI and academic success in MD programs and (b) determine whether the mean effect size varies according to country (United States vs. non-United States countries), age, EI test, EI task nature (ability-based vs. trait-based), EI subscales, and academic performance criteria (grade point average vs. examinations). Results Findings from 20 studies (m = 105; N = 4,227) indicated a positive correlation between EI and academic success (r = .13, 95% CI [.08, – .27], p < .01). Moderator analyses indicated that the mean effect size significantly varied according to EI tests and EI subscales. Moreover, three-level multiple regression analyses showed that between-study variance explained 29.5% of the variability in the mean effect size, whereas within-study variance explained 33.5% of the variability in the mean effect. Conclusions Overall, the current findings show that EI is significantly, albeit weakly, related to academic success in MD programs. Medical researchers and practitioners can therefore focus on integrating EI-related skills into the MD curriculum or target them through professional development training and programs

Parental Attitudes Towards STEM Scale: Development and Psychometric Properties

This study describes the development of the Science, Technology, Engineering, and Mathematics (STEM) Scale, intended to assess parental attitudes toward school programs designed to deliver STEM, and evaluates its psychometric properties. The study group included 400 parents of students (138 males and 262 females) enrolled in STEM programs throughout the KSA. As a result of the analysis, a 40-item scale comprising four subscales was developed: (a) perceived value, (b) perceived control, (c) affective component, and (d) intention component. Exploratory and confirmatory factor analyses confirmed a four-factor structural model that had a satisfactory fit. Cronbach’s alpha of the overall scale demonstrated good internal consistency. Preliminary results suggest that parental attitudes toward the STEM scale have adequate convergent and divergent validity