Technique for order performance by similarity to ideal solution for solving complex situations in multi-criteria optimization of the tracking channels of GPS baseband telecommunication receivers

Global positioning system (GPS) has undergone intensive development, starting as an advanced specialized tool to a general-purpose gadget used in our daily lives. GPS exists in new technologies, applications, and consumer products, especially in smartphones and tablets. In a GPS receiver design, power consumption and localization accuracy are critical factors that affect the outcome of a GPS receiver system. Theoretically, increasing the number of required tracking channels in a GPS baseband receiver increases the design complexity and size of this system. Thus, power consumption can significantly increase. The receiver should acquire and track numerous satellites to improve the location accuracy of a position, thereby indicating that the receiver requires a high number of tracking channels. Thus, optimizing these tracking channels to balance the conflict among performance parameters is a difficult and challenging task. This paper presents a technique for order performance by similarity to ideal solution (TOPSIS) for solving complex situations for multi-criteria optimization of the tracking channels of GPS baseband telecommunication receiver. Nine operation modes of GPS receiver were evaluated by each design parameter, such as power consumption, localization accuracy, and time with no position available for static and dynamic positioning. Then, the TOPSIS was utilized and implemented to measure and rank the overall performance of tracking channel selection. Results of this study indicate that (1) multi-objective optimization is a reliable strategy for visualizing the trade-off among the GPS design parameters and providing a dynamic power consumption planning. (2) The best aggregated performance of the GPS receiver occurs when the number of tracking channels equals five and six for static and dynamic positioning, respectively. (3) The most frequent number of available satellites is eight, whereas the other number of satellites is a rare case to acquire. However, GPS standards require that available GPS satellites are constantly 12 at any time and place.     

A new hybrid adaptive combination technique for ECG signal enhancement

This paper proposes a new de-noising system technique which is composed of Adaptive line enhancer (ALE) with the discrete wavelet transform (DWT) in order to improve the demerit of the ALE. A new adaptive algorithm which depends mainly on the second order resemblance between a signal and its delayed version is also derived and proposed for the ALE. Unlike the conventional DWT process where an estimation of a specific threshold is taken into account, here the ALE based proposed adaptive algorithm is exploited to enhance the detail coefficients. Therefore, the entire system works well for canceling Gaussian and non-Gaussian noise. Some experiments are carried out on an ECG signal to show the effectiveness of the proposed system. It illustrates from the simulations that the proposed technique demonstrates spectacular results for separating various noise types from the contaminated ECG signal. Finally, the proposed adaptive algorithm is compared with the leaky least mean square algorithm of the bases of mean square error. It is found that the performance of the proposed algorithm provides faster convergence rate and lower steady-state error. Consequently, the overall proposed system model represents a workable solution for ECG signal enhancement.

     

Supercritical Fluid Extraction and Chromatography of Lipids in Bilberry

A supercritical fluid extraction (SFE) method has been developed for the extraction of lipids in bilberry. Experimental design was used to optimize pressure, temperature and extraction time using CO₂ as solvent. Best SFE condition for total lipids was 450 bar, 60 °C and 45 min. The SFE method was compared to conventional Bligh & Dyer (B&D) extraction. The amount of fatty acid methyl esters (FAME) was found to be 4.84 ± 0.06 mg and 4.564 ± 0.003 mg per g of the freeze‐dried bilberry sample for the developed SFE and B&D methods, respectively, while the amount of total lipids was found to be 54.40 ± 6.06 mg and 65.70 ± 0.67 mg per g of sample for SFE and B&D, respectively. This discrepancy between FAME and total lipids could be explained by the presence of wax esters, sterol esters, carotenoids and phospholipids, as determined by supercritical fluid chromatography.     

Comprehensive review and analysis of anti-malware apps for smartphones

Telecommunication Systems - The new and disruptive technologies for ensuring smartphone security are very limited and largely scattered. The available options and gaps in this research area must be...     

Rescuing emergency cases of COVID-19 patients: An intelligent real-time MSC transfusion framework based on multicriteria decision-making methods

Applied Intelligence - Mesenchymal stem cells (MSCs) have shown promising ability to treat critical cases of coronavirus disease 2019 (COVID-19) by regenerating lung cells and reducing immune...     

A new DOA estimation approach for QPSK Alamouti STBC using ICA technique‐based PSO algorithm

Alamouti space time block code (STBC) has been a revolutionary technology in multiple‐input multiple‐output (MIMO) wireless communication since it provides full transmission diversity. To reduce a multi‐path effect and a consumed power, the dynamic beam‐forming technique should be used to enable antennas focusing on a particular area. The aim of this paper is how to reduce the computational complexities of independent component analysis (ICA) and speed up the algorithm used in estimating the direction of arrival (DOA) angles. First, we derive a simple formula to reduce the number of unknown DOA to be one only. Then, real‐imaginary (Re‐Im) decomposition for MIMO system is used to reduce the computational complexities of ICA algorithm. The novel criteria used in this paper is that the kurtosis measuring for the extracted source will be minimum at one of the unknown values of DOA angles. Finally, particle swarm optimization (PSO) will be used as an effective tool to locate the DOA angle positions that minimize the kurtosis measuring. Performance analysis of the proposed approach with QPSK Alamouti STBC in MIMO channel was implemented using MATLAB. The validated criterions for the new approach were first examined. Then, root‐mean‐square‐error (RMSE) was employed to test the proposed approach at different SNR levels. The main parameters that influence on this approach were evaluated. It was found that superior performance could be obtained at ?DOA > 10⁰ when antenna spacing set to be λ/2 using at least 10³ snapshots. The important point observed during simulations was computational complexity (and latency) of the proposed approach was reduced to the minimum by employing Re‐Im decomposition model and PSO algorithm. Consequently, this approach is very efficient for hardware implementations.     

Multi-criteria decision-making for coronavirus disease 2019 applications: a theoretical analysis review

The influence of the ongoing COVID-19 pandemic that is being felt in all spheres of our lives and has a remarkable effect on global health care delivery occurs amongst the ongoing global health crisis of patients and the required services. From the time of the first detection of infection amongst the public, researchers investigated various applications in the fight against the COVID-19 outbreak and outlined the crucial roles of different research areas in this unprecedented battle. In the context of existing studies in the literature surrounding COVID-19, related to medical treatment decisions, the dimensions of context addressed in previous multidisciplinary studies reveal the lack of appropriate decision mechanisms during the COVID-19 outbreak. Multiple criteria decision making (MCDM) has been applied widely in our daily lives in various ways with numerous successful stories to help analyse complex decisions and provide an accurate decision process. The rise of MCDM in combating COVID-19 from a theoretical perspective view needs further investigation to meet the important characteristic points that match integrating MCDM and COVID-19. To this end, a comprehensive review and an analysis of these multidisciplinary fields, carried out by different MCDM theories concerning COVID19 in complex case studies, are provided. Research directions on exploring the potentials of MCDM and enhancing its capabilities and power through two directions (i.e. development and evaluation) in COVID-19 are thoroughly discussed. In addition, Bibliometrics has been analysed, visualization and interpretation based on the evaluation and development category using R-tool involves; annual scientific production, country scientific production, Wordcloud, factor analysis in bibliographic, and country collaboration map. Furthermore, 8 characteristic points that go through the analysis based on new tables of information are highlighted and discussed to cover several important facts and percentages associated with standardising the evaluation criteria, MCDM theory in ranking alternatives and weighting criteria, operators used with the MCDM methods, normalisation types for the data used, MCDM theory contexts, selected experts ways, validation scheme for effective MCDM theory and the challenges of MCDM theory used in COVID-19 studies. Accordingly, a recommended MCDM theory solution is presented through three distinct phases as a future direction in COVID19 studies. Key phases of this methodology include the Fuzzy Delphi method for unifying criteria and establishing importance level, Fuzzy weighted Zero Inconsistency for weighting to mitigate the shortcomings of the previous weighting techniques and the MCDM approach by the name Fuzzy Decision by Opinion Score method for prioritising alternatives and providing a unique ranking solution. This study will provide MCDM researchers and the wider community an overview of the current status of MCDM evaluation and development methods and motivate researchers in harnessing MCDM potentials in tackling an accurate decision for different fields against COVID-19.