The non-standard finite difference scheme for linear fractional PDEs in fluid mechanics

AbstractA non-standard finite difference scheme is developed to solve the linear partial differential equations with time- and space-fractional derivatives. The Grunwald–Letnikov method is used to approximate the fractional derivatives. Numerical illustrations that include the linear inhomogeneous time-fractional equation, linear space-fractional telegraph equation, linear inhomogeneous fractional Burgers equation and the fractional wave equation are investigated to show the pertinent features of the technique. Numerical results are presented graphically and reveal that the non-standard finite difference scheme is very effective and convenient for solving linear partial differential equations of fractional order

Post COVID-19 effect on medical staff and doctors' productivity analysed by machine learning

The COVID-19 pandemic has profoundly affected the healthcare sector and the productivity of medical staff and doctors. This study employs machine learning to analyze the post-COVID-19 impact on the productivity of medical staff and doctors across various specialties. A cross-sectional study was conducted on 960 participants from different specialties between June 1, 2022, and April 5, 2023. The study collected demographic data, including age, gender, and socioeconomic status, as well as information on participants' sleeping habits and any COVID-19 complications they experienced. The findings indicate a significant decline in the productivity of medical staff and doctors, with an average reduction of 23% during the post-COVID-19 period. These results reflect the overall impact observed following the entire course of the COVID-19 pandemic and are not specific to a particular wave. The analysis revealed that older participants experienced a more pronounced decline in productivity, with a mean decrease of 35% compared to younger participants. Female participants, on average, had a 28% decrease in productivity compared to their male counterparts. Moreover, individuals with lower socioeconomic status exhibited a substantial decline in productivity, experiencing an average decrease of 40% compared to those with higher socioeconomic status. Similarly, participants who slept for fewer hours per night had a significant decline in productivity, with an average decrease of 33% compared to those who had sufficient sleep. The machine learning analysis identified age, specialty, COVID-19 complications, socioeconomic status, and sleeping time as crucial predictors of productivity score. The study highlights the significant impact of post-COVID-19 on the productivity of medical staff and doctors in Iraq. The findings can aid healthcare organizations in devising strategies to mitigate the negative consequences of COVID-19 on medical staff and doctors' productivity

Resistivity network and structural model of the oxide cathode for CRT application

In this paper, the electrical properties of oxide cathode and oxide cathode plus, supplied by LG Philips Displays, have been investigated in relation to different cathode activation regimes and methods. Oxide cathode activation treatment for different durations has been investigated. The formations of the compounds associated to the diffusion of reducing elements (Mg, Al, and W) to the Ni cap surface of oxide cathode were studied by a new suggestion method. Scanning electron microscopy (SEM) coupled with energy dispersive X-ray spectroscopy (EDX) was used as analytical techniques. Al, W, and Mg doping elements take place during heating to 1080 K (Ni-Brightness) under a rich controlled Ba–SrO atmosphere through an acceleration life test. The chemical transport of these elements was occurred mainly by the Ni cap grain boundary mechanism with significant pile-up of Mg compounds. Al and W show a superficial concentrations and distribution. A new structural and resistivity network model of oxide cathode plus are suggested. The new structural model shows a number of metallic and metallic oxide pathways are exist at the interface or extended through the oxide coating. The effective values of the resistances and the type of the equivalent circuit in the resistivity network model are temperature and activation time dependent.</p

Speed Control of Hydraulic Elevator by Using Electro-Hydraulic Servo Mechanism

المصعد الهيدروليكي هو أحد أنواع المصاعد المستخدمة في المباني ذات الارتفاع المنخفض والذي لا يزيد عن الثلاث طوابق. في هذا البحث تم نصب وتنفيذ وتشغيل نموذج مصغر لمصعد هيدروليكي والتحقق النظري والتجريبي باستخدام صمام تناسبي، ومسيطر نوع PI. تم تنفيذ المصعد مع ثلاث طوابق بارتفاع كلي يبلغ 76 سم مع جميع المكونات والملحقات الهيدروليكية والكهربائية، حيث ان اتمتة المصعد كانت باستخدام مايكرو كونترولر اردوينو ِArduino نوع أونو. UNO برنامج الحاسوب اللابفيو LABVEIW تم استخدامه للسيطرة على المصعد من خلال مسوق التيار المستمر L298 DC. أفضل قيم لباراميترات المسيطر PI تم الحصول عليها تجريبيا. النتائج أظهرت دعم وتحسين الأداء للمصعد الهيدروليكي من خلال استخدام نظام المؤازرة الكهروهيدروليكي لتحقيق التوقف السلس وراحة المستخدمين للمصعد في التنقل بحركة انسيابية بين الطوابق.An electro-hydraulic elevator is a new type of enhanced elevators used in low-rise buildings, no more than eight floors. In this paper, an electro-hydraulic servo system for controlling the speed of a hydraulic elevator prototype by using a proportional valve and PI controller has been investigated theoretically and experimentally. A three floors elevator prototype model with 76cm height has been built, including hydraulic components and electrical components. The elevator system is automated using an Arduino UNO board based Data Acquisition (DAQ) system. LabVIEW software is programmed to control the hydraulic elevator system through L298 DC drive via the DAQ board. The best PI gains have been calculated experimentally using Ziegler–Nichols, trial and error methods. The results showed the effectiveness of the use of Electro-hydraulic servomechanism in enhancing the performance of the hydraulic elevator in terms of comfort and smoothness when people travelled through the elevator floors

Cyclic Self-Organizing Map for Object Recognition

Object recognition is an important machine learning (ML) application. To have a robust ML application, we need three major steps: (1) preprocessing (i.e. preparing the data for the ML algorithms); (2) using appropriate segmentation and feature extraction algorithms to abstract the core features data and (3) applying feature classification or feature recognition algorithms. The quality of the ML algorithm depends on a good representation of the data. Data representation requires the extraction of features with an appropriate learning rate. Learning rate influences how the algorithm will learn about the data or how the data will be processed and treated. Generally, this parameter is found on a trial-and-error basis and scholars sometimes set it to be constant. This paper presents a new optimization technique for object recognition problems called Cyclic-SOM by accelerating the learning process of the self-organizing map (SOM) using a non-constant learning rate. SOM uses the Euclidean distance to measure the similarity between the inputs and the features maps. Our algorithm considers image correlation using mean absolute difference instead of traditional Euclidean distance. It uses cyclical learning rates to get high performance with a better recognition rate. Cyclic-SOM possesses the following merits: (1) it accelerates the learning process and eliminates the need to experimentally find the best values and schedule for the learning rates; (2) it offers one form of improvement in both results and training; (3) it requires no manual tuning of the learning rate and appears robust to noisy gradient information, different model architecture choices, various data modalities and selection of hyper-parameters and (4) it shows promising results compared to other methods on different datasets. Three wide benchmark databases illustrate the efficiency of the proposed technique: AHD Base for Arabic digits, MNIST for English digits, and CMU-PIE for faces

Graphene as a buffer layer for silicon carbide-on-insulator structures

We report an innovative technique for growing the silicon carbide-on-insulator (SiCOI) structure by utilizing polycrystalline single layer graphene (SLG) as a buffer layer. The epitaxial growth was carried out using a hot-mesh chemical vapor deposition (HM-CVD) technique. Cubic SiC (3C-SiC) thin film in (111) domain was realized at relatively low substrate temperature of 750 °C. 3C-SiC energy bandgap of 2.2 eV was confirmed. The Si-O absorption band observed in the grown film can be caused by the out-diffusion of the oxygen atom from SiO2 substrate or oxygen doping during the cleaning process. Further experimental works by optimizing the cleaning process, growth parameters of the present growth method, or by using other growth methods, as well, are expected to realize a high quality SiCOI structure, thereby opening up the way for a breakthrough in the development of advanced ULSIs with multifunctionalities

Demystifying communication signal lost for network redundancy connectivity: evidence from coverage analysis studies on AMR systemarticle

These studies report on the communication signal lost factors that were analyzed and supported by evidences on coverage analysis activities for Automatic Meter Reading (AMR) systems. We have categorized the influential signal lost factors into four core elements that were concluded based on our field measurement studies. We have conducted measurement on Received Signal Strength Indicator (RSSI) parameter and outline the steps and techniques of such research activity. Our results show that a single network connection might not be able to support for reliable Internet network connectivity for critical communication device like AMR system. Hence, applying network redundancy technique into developing a more functional communication module could be an effective solution to combat the issue on signal lost for AMR meters.Keywords: Signal strength; AMR; Cognitive Network Selection; Network redundancy;Signal lost

Reduced graphene oxide-multiwalled carbon nanotubes hybrid film with low Pt loading as counter electrode for improved photovoltaic performance of dye-sensitised solar cells

In this work, the role of reduced graphene oxide (rGO) with hyperbranched surfactant and its hybridisation with multiwalled carbon nanotubes (MWCNTs) and platinum (Pt) nanoparticles (NPs) as counter electrode (CE) were investigated to determine the photovoltaic performance of dye-sensitised solar cells (DSSCs). Sodium 1,4-is(neopentyloxy)-3-(neopentyloxycarbonyl)- 1,4-dioxobutane-2-sulphonate (TC14) surfactant was utilised as dispersing and stabilising agent in electrochemical exfoliation to synthesise graphene oxide (GO) as initial solution for rGO production prior to its further hybridisation and fabrication as thin film. A chemical reduction process utilising hydrazine hydrate was conducted to produce rGO due to the low temperature process and water-based GO solution. Subsequently, hybrid solution was prepared by mixing 1 wt% MWCNTs into the produced rGO solution. TC14-rGO and TC14-rGO_MWCNTs hybrid solution were transferred into fluorine-doped tin oxide substrate to fabricate thin film by spraying deposition method. Finally, the CE films were prepared by coating with thin Pt NPs. Photoanode film was prepared by a two-step process: hydrothermal growth method to synthesise titanium dioxide nanowires (TiO2 NWs) and subsequent squeegee method to apply TiO2 NPs. According to solar simulator measurement, the highest energy conversion efficiency (η) was achieved by using CE-based TC14-rGO_MWCNTs/Pt (1.553%), with the highest short current density of 4.424 mA/cm2. The highest η was due to the high conductivity of CE hybrid film and the morphology of fabricated TiO2 NWs/TiO2 NPs. Consequently, the dye adsorption was high, and the photovoltaic performance of DSSCs was increased. This result also showed that rGO and rGO_MWCNTs hybrid can be used as considerable potential candidate materials to replace Pt gradually

Neither predator nor prey:What trafficking discourses miss about masculinities, mobility and work

Within trafficking discourses, men appear as predatory and exploitative, while boys appear as victims. This flattens the complexities of social life and obscures the ways that constructs of masculinity frame the trajectories of labour migrants and their brokers. This article challenges those discourses, drawing on research with two groups of labour migrants characterized as ‘victims of trafficking’, as well as with ‘traffickers’ who help them to move and work. The first are adolescents moving from Benin to the gravel quarries of Abeokuta, Nigeria. The second are adults from across West Africa who have made the illegal journey to Italy, where they live in ‘ghettos’ and work as gang labourers on harvests. In each case, migrants and their brokers come from the same or similar communities; (shared) ideals of masculinity structure their mobility and labour. Gendered transitions towards adulthood, the pressure to attain riches and status and a duty of responsibility to those younger and less successful are important. A focus on their masculinities takes us beyond ‘victim-perpetrator’ dyads.</p

Impact of ecological factors on nationwide supply chain performance

Environmental responsibility is an integrated part of responsible supply chain management and involves several steps.The objective of this study is to investigate the role of ecological factors in the supply chain. Therefore, this study examined the role of GDP growth rate, the degree of openess, the rate of exchange and balance of payment effect on foreign direct investment (FDI) and FDI effect on the supply chain. Different national and international frameworks and tools guide companies in their work with sustainability and environmental supply chain management. UN’s Global Compact is one of the main international frameworks. In this study, data were collected from Indonesian ecologists. Email addresses of Indonesian ecologists were collected and email was sent to them to get responses. Only one hundred email addresses were found of various ecologists. Therefore, the total sample size was one hundred. From total one hundred, sixty ecologists responded. Outcomes of the study show that increases in GDP growth rate, the degree of openness and balance of payment increases the nationwide supply chain performance. Decreases in GDP growth rate, the degree of openness and balance of payment decreases the nationwide supply chain performance. However, increases in the rate of exchange decrease the FDI growth rate which ultimately decreases the supply chain practice