Estimation of the effectiveness of Au nanoparticles concentration in peristaltic flow through a curved channel by using a data driven stochastic numerical paradigm based on artificial neural network ...is presented in this study. In the modelling, nano composite is considered involving multi-walled carbon nanotubes coated with gold nanoparticles with different slip conditions. Modeled differential system of the physical problem is numerically analyzed for different scenarios to predict numerical data for velocity and temperature by Adams Bashforth method and these solutions are used as a reference dataset of the networks. Data is processed by segmentation into three categories i.e., training, validation and testing while Levenberg-Marquart training algorithm is adopted for optimization of networks results in terms of performance on mean square errors, train state plots, error histograms, regression analysis, time series responses, and auto-correlation, which establish the accurate and efficient recognition of trends of the system.
This study investigated the current state of information literacy (IL) skills among lawyers practicing at the District Bar Association of Sargodha, Punjab, Pakistan. A cross-sectional survey using a ...questionnaire was conducted to collect data from 297 lawyers. The questionnaire comprised 20 statements related to information literacy along with certain demographic variables. Each lawyer was personally visited in the assigned chamber by one of the researchers to record responses. Both descriptive (frequencies, percentages, mean scores, standard deviations) and inferential statistics (Pearson correlation coefficient, t-test, and one-way analysis of variance) were applied for data analysis in SPSS. The results showed that a large majority of lawyers participating in the survey never received any formal training concerning information literacy. However, most of these lawyers perceived IL skills as important in the context of their workplace especially in conducting legal research. These lawyers were more competent in the basic IL skills and less competent in advanced IL skills. In addition, the lawyers’ age, practical experience, practicing levels, computer proficiency, and English Language proficiency predicted their levels of IL skills. There was a critical need for the development of IL instruction programs for not only practicing lawyers but also for law students to improve their skills since these lawyers felt less competent with advanced levels of IL skills. It is hoped that the present study contributes to the existing body of WIL literature focusing especially on the role of IL in the context of legal work and outlining the current state of lawyers’ IL skills in Pakistan as no such study has appeared so far.
Self-efficacy toward information literacy is and has been demonstrated as an essential and fundamental key for academic performance and lifelong learning of students at all levels. This research ...reported the results of a cross-sectional survey carried out to investigate the correlatives of information literacy self-efficacy among business students at the University of Management and Technology, Lahore. The questionnaire contained an Information Literacy Self-Efficacy Scale, which along with sociodemographic and academic variables was utilized for collecting data from 350 students. The survey participants were recruited through a convenient sampling procedure due to accessibility issues and time limitations. The data were analyzed by applying both descriptive and inferential statistics using SPSS. The results revealed that the business students had high self-efficacy for basic information literacy skills and low self-efficacy for advanced-level information literacy skills. Age, study program, study stage, proficiency for computer, and English language appeared to be the correlatives of students’ information literacy self-efficacy. The pragmatic insights generated in this research might be used as a guide by university librarians, especially those who are engaged in information literacy instructions for designing a need-based and student-centered curriculum for information literacy instruction programs.
Elliptic curve cryptography provides better security and is more efficient as compared to other public key cryptosystems with identical key size. In this article, we present a new method for the ...construction of substitution boxes(S-boxes) based on points on elliptic curve over prime field. The resistance of the newly generated S-box against common attacks such as linear, differential and algebraic attacks is analyzed by calculating their non-linearity, linear approximation, strict avalanche, bit independence, differential approximation and algebraic complexity. The experimental results are further compared with some of the prevailing S-boxes presented in Shi et al. (Int Conf Inf Netw Appl 2:689–693,
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https://doi.org/10.1007/s00521-012-0914-5
,
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). Comparison reveals that the proposed algorithm generates cryptographically strong S-boxes as compared to some of the other exiting techniques.
The sustainable power development requires the study of power quality while taking into account of electrical equipment is an important aspect because it highly compromises the overall efficiency ...including quality, reliability and continuity of power flow. The aim for smooth power flow is only accomplished if compatibility is met between all the instruments connected to the system. The odd harmonics both on amplitude and phase domain must be known in order to exactly cop up with their adverse effects on overall working of the system. In this regard, parameter estimation is performed in detail for diverse generation size (gs) and particle size (ps), besides for altered signal to noise ratio. Firefly optimization technique under different scenarios for both phase and amplitude parameters accurately estimated the power signal harmonics and proved its robustness under different noise levels. The MSE values achieved by FFO are 6.54 × 10−3, 1.04 × 10−5 and 1.35 × 10−6 for 20 dB, 50 dB and 80 dB respectively for gs = 200 in case study 1. While the respective results in case study 2 are 7.33 × 10−3, 6.67 × 10−6 and 6.59 × 10−9 for gs = 1000. Whereas no significant effect in performance is seen with the change in ps values.
In this study, a novel adaptive strategy is designed based on fractional least mean square (LMS) algorithm for parameter estimation of Hammerstein nonlinear autoregressive moving average system with ...exogenous noise (HN-ARMAX). The design scheme consists of parameterization of HN-ARMAX systems to obtain linear-in-parameter models and to use fractional LMS algorithm for adapting unknown parameter vectors. The performance analysis of the proposed method is carried out based on convergence to the desired values of HN-ARMAX systems, and comparison is made with state-of-the-art kernel LMS and Volterra LMS algorithms. The consistency in terms of accuracy and convergence is established through the results of statistical analysis based on sufficient large number of independent runs rather than single successful run of the algorithm. The performance of proposed scheme is superior due to its strong mathematical foundations, nonlinear weight updating mechanism and more convergence controlling variables but at the cost of bit more computational requirements.
•The fractional gradient based innovative fractional order LMS (I-FOLMS) algorithm is presented for power signal estimation.•The I-FOLMS is fast in terms of convergence for high fractional orders and ...good at steady state for low fractional orders.•The effectiveness of the I-FOLMS is verified through comparison with the standard FOLMS for different fractional orders.
Parameter estimation is an important issue for the quality monitoring and reliability assessment of power systems. In this study, an innovative fractional order least mean square (I-FOLMS) adaptive algorithm is presented for an effective parameter estimation. The I-FOLMS algorithm exploits the fractional gradient in its recursive parameter update mechanism, because its performance can be tuned by means of the fractional order. High values of the fractional order are good for fast convergence, but lead to steady state mis-adjustments. While, low values provide a smooth steady state behavior, but require a compromise in the convergence rate. The effective performance of I-FOLMS is verified and validated through two numerical examples of power signals estimation for different levels of noise variance and values of the fractional orders.
•This study presents a novel fractional order adaptive algorithm, called MIFLMS.•The MIFLMS extends the scalar innovation into a vector innovation.•It reveals a faster convergence speed than the FLMS ...with no noticeable increase in the computational burden.•The proposed algorithm effectively estimates the parameters of nonlinear systems.•The MIFLMS is more robust than the FLMS and provide consistent accurate and convergent performance.
The development of procedures based on fractional calculus is an emerging research area. This paper presents a new perspective regarding the fractional least mean square (FLMS) adaptive algorithm, called multi innovation FLMS (MIFLMS). We verify that the iterative parameter adaptation mechanism of the FLMS uses merely the current error value (scalar innovation). The MIFLMS expands the scalar innovation into a vector innovation (error vector) by considering data over a fixed window at each iteration. Therefore, the MIFLMS yields better convergence speed than the standard FLMS by increasing the length of innovation vector. The superior performance of the MIFLMS is verified through parameter identification problem of input nonlinear systems. The statistical performance indices based on multiple independent trials confirm the consistent accuracy and reliability of the proposed scheme.
This paper presents a sliding-window approximation-based fractional least mean square (FLMS) algorithm for parameter estimation of Hammerstein nonlinear autoregressive moving average system with ...exogenous noise. The FLMS algorithm available in the literature makes use of data available at the current iteration only (or memory-less algorithm). This results in poor convergence rate of the algorithm, and the presence of immeasurable noise terms in the information vector makes identification a difficult task. The sliding-window approximation-based fractional LMS (SW-FLMS) algorithm uses not only the current data but also the past data at each iteration. The proposed algorithm uses sliding-window approximation of the expectation where the length of data used by SW-FLMS algorithm determines the size of sliding window. Moreover, a variable convergence approach is also proposed for fast convergence of SW-FLMS algorithm. Compared with the standard FLMS algorithm, the proposed SW-FLMS algorithms can converge at a fast rate to highly accurate parameter estimates. Estimation accuracy and convergence rate of the standard FLMS algorithm and proposed methods are evaluated for 200 independent runs. Simulation results confirm that performance of standard FLMS algorithm can be improved by the use of proposed modifications.
To determine and compare plasma thrombomodulin, von Willebrand factor and von Willebrand factorcleaving protease levels between pre-eclamptic and healthy pregnant females.
The cross-sectional, ...comparative study was conducted at the Department of Haematology, University of Health Sciences, Lahore, Pakistan, from November 2019 to December 2020, and comprised pregnant females who were divided into healthy pregnant group A and pre-eclamptic group B. Plasma thrombomodulin and von Willebrand factor-cleaving protease levels were determined by using commercially available enzyme-linked immunosorbent assay kit, and von Willebrand factor level was determined by using immuno-turbidimetric assay kit. Data was analysed using SPSS 25.
Of the 88 participants, there were 44(50%) females with mean age 25.5±6 years in group A and 44(50%) in group B with mean age 26±5 years. Median thrombomodulin level in group B was significantly higher than group A (p=0.003). Median von Willebrand factor-cleaving protease levels were lower in group B compared to group A (p=0.838). A significant difference in von Willebrand factor level was observed between the groups (p=0.038).
Females with pre-eclampsia had significantly higher plasma levels of von Willebrand factor and thrombomodulin than healthy pregnant subjects.
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