Search results for: hybrid remote teams

Authors: Alsaidi M. Altaher, Mohd Tahir Ismail

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Wavelet thresholding has been a power tool in curve estimation and data analysis. In the presence of outliers this non parametric estimator can not suppress the outliers involved. This study proposes a new two-stage combined method based on the use of the median filter as primary step before applying wavelet thresholding. After suppressing the outliers in a signal through the median filter, the classical wavelet thresholding is then applied for removing the remaining noise. We use automatic boundary corrections; using a low order polynomial model or local polynomial model as a more realistic rule to correct the bias at the boundary region; instead of using the classical assumptions such periodic or symmetric. A simulation experiment has been conducted to evaluate the numerical performance of the proposed method. Results show strong evidences that the proposed method is extremely effective in terms of correcting the boundary bias and eliminating outlier’s sensitivity.

Keywords: boundary correction, median filter, simulation, wavelet thresholding

Procedia PDF Downloads 427

Authors: Yichao Liu, Peter Fransson, Julian Heidecke, Jonas Wallin, Joacim Rockloev

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Dengue, a mosquito-borne viral disease, poses a significant public health challenge in endemic tropical or subtropical countries, including Sri Lanka. To reveal insights into the complexity of the dynamics of this disease and study the drivers, a comprehensive model capable of both robust forecasting and insightful inference of drivers while capturing the co-circulating of several virus strains is essential. However, existing studies mostly focus on only one aspect at a time and do not integrate and carry insights across the siloed approach. While mechanistic models are developed to capture immunity dynamics, they are often oversimplified and lack integration of all the diverse drivers of disease transmission. On the other hand, purely data-driven methods lack constraints imposed by immuno-epidemiological processes, making them prone to overfitting and inference bias. This research presents a hybrid model that combines machine learning techniques with mechanistic modelling to overcome the limitations of existing approaches. Leveraging eight years of newly reported dengue case data, along with socioeconomic factors, such as human mobility, weekly climate data from 2011 to 2018, genetic data detecting the introduction and presence of new strains, and estimates of seropositivity for different districts in Sri Lanka, we derive a data-driven vector (SEI) to human (SEIR) model across 16 regions in Sri Lanka at the weekly time scale. By conducting ablation studies, the lag effects allowing delays up to 12 weeks of time-varying climate factors were determined. The model demonstrates superior predictive performance over a pure machine learning approach when considering lead times of 5 and 10 weeks on data withheld from model fitting. It further reveals several interesting interpretable findings of drivers while adjusting for the dynamics and influences of immunity and introduction of a new strain. The study uncovers strong influences of socioeconomic variables: population density, mobility, household income and rural vs. urban population. The study reveals substantial sensitivity to the diurnal temperature range and precipitation, while mean temperature and humidity appear less important in the study location. Additionally, the model indicated sensitivity to vegetation index, both max and average. Predictions on testing data reveal high model accuracy. Overall, this study advances the knowledge of dengue transmission in Sri Lanka and demonstrates the importance of incorporating hybrid modelling techniques to use biologically informed model structures with flexible data-driven estimates of model parameters. The findings show the potential to both inference of drivers in situations of complex disease dynamics and robust forecasting models.

Keywords: compartmental model, climate, dengue, machine learning, social-economic

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Authors: Krishan Kumar, Mohit Mittal, Pramod Kumar

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Wireless sensor network is one of the most promising communication networks for monitoring remote environmental areas. In this network, all the sensor nodes are communicated with each other via radio signals. The sensor nodes have capability of sensing, data storage and processing. The sensor nodes collect the information through neighboring nodes to particular node. The data collection and processing is done by data aggregation techniques. For the data aggregation in sensor network, clustering technique is implemented in the sensor network by implementing self-organizing feature map (SOFM) neural network. Some of the sensor nodes are selected as cluster head nodes. The information aggregated to cluster head nodes from non-cluster head nodes and then this information is transferred to base station (or sink nodes). The aim of this paper is to manage the huge amount of data with the help of SOM neural network. Clustered data is selected to transfer to base station instead of whole information aggregated at cluster head nodes. This reduces the battery consumption over the huge data management. The network lifetime is enhanced at a greater extent.

Keywords: artificial neural network, data clustering, self organization feature map, wireless sensor network

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Authors: Lin-Lin Liu, Song-Qi Hu, Yin Wang

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Paraffin-based fuels are regarded to be a promising fuel of hybrid rocked motor because of the high regression rate, low price, and environmental friendliness. Graphene Oxide (GO) is an attractive energetic material which is expected to be widely used in propellants, explosives, and some high energy fuels. Paraffin-based fuels with paraffin and GO as raw materials were prepared, and the oxidation process of the samples was investigated by thermogravimetric analysis differential scanning calorimetry (TG/DSC) under oxygen (O₂) and nitrous oxide (N₂O) atmospheres. The oxidation reaction kinetics of the fuels was estimated through the non-isothermal measurements and model-free isoconversional methods based on the experimental results of TGA. The results show that paraffin-based fuels are easier oxidized under O₂ rather than N₂O with atmospheres due to the lower activation energy; GO plays a catalytic role for the oxidation of paraffin-based fuels under the both atmospheres, and the activation energy of the oxidation process decreases with the increase of GO; catalytic effect of GO on the oxidation of paraffin-based fuels are more obvious under O₂ atmospheres than under N₂O atmospheres.

Keywords: graphene oxide, paraffin-based fuels, oxidation, activation energy, TGA

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Authors: Faraji Sepideh

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Nowadays, purchase rate of the smart device is increasing and user authentication is one of the important issues in information security. Alphanumeric strong passwords are difficult to memorize and also owners write them down on papers or save them in a computer file. In addition, text password has its own flaws and is vulnerable to attacks. Graphical password can be used as an alternative to alphanumeric password that users choose images as a password. This type of password is easier to use and memorize and also more secure from pervious password types. In this paper we have designed a more secure graphical password system to prevent shoulder surfing, smudge and brute force attack. This scheme is a combination of two types of graphical passwords recognition based and Cued recall based. Evaluation the usability and security of our proposed scheme have been explained in conclusion part.

Keywords: brute force attack, graphical password, shoulder surfing attack, smudge attack

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Authors: Safayat Ali Shaikh

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Software has been developed for optimal cropping pattern in an irrigation project considering land constraint, water availability constraint and pick up flow constraint using modified Simplex Algorithm. Artificial Neural Network Models (ANN) have been developed to predict rainfall. AR (1) model used to generate 1000 years rainfall data to train the ANN. Simulation has been done with expected rainfall data. Eight number crops and three types of soil class have been considered for optimization model. Area under each crop and each soil class have been quantified using Modified Simplex Algorithm to get optimum net return. Efficacy of the software has been tested using data of large irrigation project in India.

Keywords: artificial neural network, large irrigation project, modified simplex algorithm, optimal cropping pattern

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Authors: Martha Hough RN

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Background: New nursing graduates lack the critical thinking skills required to provide safe nursing care. Critical thinking is essential in providing safe, competent, and skillful nursing interventions. Educational institutions must provide a curriculum that improves nursing students' critical thinking abilities. In addition, the recent pandemic resulted in nursing students who previously received in-person clinical but now most clinical has been converted to remote learning, increasing the use of simulations. Unfolding medium and high-fidelity simulations and Socratic questioning are used in many simulations debriefing sessions. Methodology: Google Scholar was researched with the keywords: critical thinking of nursing students with unfolding simulation, which resulted in 22,000 articles; three were used. A second search was implemented with critical thinking of nursing students Socratic questioning, which resulted in two articles being used. Conclusion: Unfolding simulations increase nursing students' critical thinking, especially during the briefing (pre-briefing and debriefing) phases, where most learning occurs. In addition, the use of Socratic questions during the briefing phases motivates other questions, helps the student analyze and critique their thinking, and assists educators in probing students' thinking, which further increases critical thinking.

Keywords: briefing, critical thinking, Socratic thinking, unfolding simulations

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Authors: Liang Wang, Wei Zhang

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There have been some existing researches on design-based engineering learning (DBEL) and project-based or problem-based engineering learning (PBEL). Those findings have greatly promoted the reform of engineering education in China. However, the engineering with a big E means that more and more engineering activities are designed and operated by communities of practice (CoPs), namely community-based engineering learning. However, whether community-based engineering learning can promote students' innovation has not been verified in published articles. This study fills this gap by investigating the relationship between community-based learning approach and students’ creativity, using engineering identity as an intermediary variable. The goal of this study is to discover the core features of community-based engineering learning, and make the features more beneficial for students’ creativity. The study created and adapted open survey items from previously published studies and a scale on learning community, students’ creativity and engineering identity. Firstly, qualitative content analysis methods by MAXQDA were used to analyze 32 open-ended questionnaires. Then the authors collected data (n=322) from undergraduate students in engineering competition teams and engineering laboratories in Zhejiang University, and structural equation modelling (SEM) was used to understand the relationship between different factors. The study finds: (a) community-based engineering learning has four main elements like real-task context, self-inquiry learning, deeply-consulted cooperation and circularly-iterated design, (b) community-based engineering learning can significantly enhance the engineering undergraduate students’ creativity, and (c) engineering identity partially moderated the relationship between community-based engineering learning and undergraduate students' creativity. The findings further illustrate the value of community-based engineering learning for undergraduate students. In the future research, the authors should further clarify the core mechanism of community-based engineering learning, and pay attention to the cultivation of undergraduate students’ engineer identity in learning community.

Keywords: community-based engineering learning, students' creativity, engineering identity, moderate effect

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Authors: Debesh R. Roy

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The fundamental issue in understanding the origin and growth mechanism of nanomaterials, from a fundamental unit is a big challenging problem to the scientists. Recently, an immense attention is generated to the researchers for prediction of exceptionally stable atomic cluster units as the building units for future smart materials. The present study is a systematic investigation on the stability and electronic properties of a series of bimetallic (semiconductor-alkaline earth) clusters, viz., BxMg3 (x=1-5) is performed, in search for exceptional and/ or unusual stable motifs. A very popular hybrid exchange-correlation functional, B3LYP as proposed by A. D. Becke along with a higher basis set, viz., 6-31+G[d,p] is employed for this purpose under the density functional formalism. The magic stability among the concerned clusters is explained using the jellium model. It is evident from the present study that the magic stability of B4Mg3 cluster arises due to the jellium shell closure.

Keywords: atomic clusters, density functional theory, jellium model, magic clusters, smart nanomaterials

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Authors: Surita Maini, Sanjay Dhanka

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Machine learning (ML) involves developing algorithms and statistical models that enable computers to learn and make predictions or decisions based on data without being explicitly programmed. Because of its unlimited abilities ML is gaining popularity in medical sectors; Medical Imaging, Electronic Health Records, Genomic Data Analysis, Wearable Devices, Disease Outbreak Prediction, Disease Diagnosis, etc. In the last few decades, many researchers have tried to diagnose Breast Cancer (BC) using ML, because early detection of any disease can save millions of lives. Working in this direction, the authors have proposed a hybrid ML technique RBF SVM, to predict the BC in earlier the stage. The proposed method is implemented on the Breast Cancer UCI ML dataset with 569 instances and 32 attributes. The authors recorded performance metrics of the proposed model i.e., Accuracy 98.24%, Sensitivity 98.67%, Specificity 97.43%, F1 Score 98.67%, Precision 98.67%, and run time 0.044769 seconds. The proposed method is validated by K-Fold cross-validation.

Keywords: breast cancer, support vector classifier, machine learning, hyper parameter tunning

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Authors: Henry Kuppen

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In the last decade, tree managers have faced many threats of pests and diseases and the effects of climate change. Managers will recognize that they have to put more energy and more money into tree management. By recognizing the cause behind this, the opportunity will arise to build sustainable tree populations for the future. More and more, unwanted larvae are sprayed, ash dieback infected trees are pruned or felled, and emerald ash borer is knocking at the door of West Europe. A lot of specific knowledge is needed to produce management plans and best practices. If pest and disease have a large impact, society loses complete tree species and need to start all over again building urban forest. But looking at the cause behind it, landscape design, and tree species selection, the sustainable solution does not present itself in managing these threats. Every pest or disease needs two important basic ingredients to be successful: climate and food. The changing climate is helping several invasive pathogens to survive. Food is often designed by the landscapers and managers of the urban forest. Monocultures promote the success of pathogens. By looking more closely at the basics, tree managers will realise very soon that the solution will not be the management of pathogens. The long-term solution for sustainable tree populations is a different design of our urban landscape. The use of tree species diversity can help to reduce the impact of climate change and pathogens. Therefore landscapers need to be supported. They are the specialists in designing the landscape using design values like canopy volume, ecosystem services, and seasonal experience. It’s up to the species specialist to show what the opportunities are for different species that meet the desired interpretation of the landscape. Based on landscapers' criteria, selections can be made, including tree species related requirements. Through this collaboration and formation of integral teams, sustainable plant design will be possible.

Keywords: climate change, landscape design, resilient landscape, tree species selection

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Authors: David Nantes, George Gilbert

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There are a lot of risks that might crop up as a tunneling project develops, and it's crucial to be aware of them. Due to the unexpected nature of tunneling projects and the interconnectedness of risk occurrences, the risk assessment approach presents a significant challenge. The purpose of this study is to provide a hybrid FDEMATEL-ANP model to help prioritize risks during tunnel construction projects. The ambiguity in expert judgments and the relative severity of interdependencies across risk occurrences are both taken into consideration by this model, thanks to the Fuzzy Decision-Making Trial and Evaluation Laboratory (FDEMATEL). The Analytic Network Process (ANP) method is used to rank priorities and assess project risks. The authors provide a case study of a subway tunneling construction project to back up the validity of their methodology. The results showed that the proposed method successfully isolated key risk factors and elucidated their interplay in the case study. The proposed method has the potential to become a helpful resource for evaluating dangers associated with tunnel construction projects.

Keywords: risk, prioritization, FDEMATEL, ANP, tunneling construction projects

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Authors: Elisaveta Doncheva, Jelena Djokikj, Ognen Tuteski, Bojana Hadjieva

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In the past decade, additive manufacturing technology or 3D printing has been promoted as an efficient method for fabricating hybrid composite materials and structures with superior mechanical properties and complex shape and geometry. Fused deposition modeling (FDM) process is commonly used additive manufacturing technique for production of polymer products. Therefore, many studies and experiments are focused on investigating the possibilities for improving the obtained results on product properties as a key factor for expanding the spectrum of their application. This article provides an extensive review on recent research advances in FDM and reports on studies that cover the effects of process parameters, material, and design of the product properties. The paper conclusions provide a clear up-to date information for optimum efficiency and enhancement of the mechanical properties of 3D printed samples and recommends further research work and investigations.

Keywords: additive manufacturing, critical parameters, filament, print orientation, 3D printing

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Authors: Nunila Ferreira de Oliveira, Silvana Martins Mishima

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Diabetes mellitus type 2 (DM2) prevalence, is increasing on the world, in Brazil is considered a public health problem. Treatment focuses on glycemic control depending primarily of lifestyle changes - not drug treatment (NDT), may involve drug therapy (DT) and requires continuous health monitoring. In Brazil this monitoring is performed by the Unified Health System (SUS) through Primary Health Care (PHC), which stimulate people with DM2 empowerment for care management. SUS was approved in 1988 and the PHC operationalization was strengthened with the creation of the Family Health Strategy (FHS) in 1994. Our aim was to analyze the people with DM2 participation in front of the care management health monitoring in the FHS. Qualitative research was carried out through non-participant observation of attendance of 25 people with DM2 in the FHS and interviewed at home. Ethical guidelines were followed. It was found that people with DM2 only follow professionals’ recommendations that make sense according to their own conceptions of health/disease; most of them emphasize the importance of (DT) with little emphasis on the NDT, was found great difficulty in the NDT and lack of knowledge about the disease and care. As regards monitoring the FHS, were observed therapeutic practices based on the bio medical model, although the APS search for another care perspective; NDT is not systematically accompanied by the health team and takes place a few educational activities on the DM2 in the FHS, with low user adoption. The work of the FHS is done by multidisciplinary teams, but we see the need for greater participation of nurses in clinical-care follow-up of this population and may also act in adapting to the NDT. Finally we emphasize the need for professional practices that consider the difficulties to care management by people with DM2, especially because of the NDT. It is noticed that the measures recommended by the FHS professionals are not always developed by people with DM2. We must seek the empowerment of people with DM2 to manage the form of care associated with the FHS team, seeking to reduce the incidence of complications and higher quality of life.

Keywords: diabetes mellitus, primary health care, nursing, management of care

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Authors: Chaudhuri Manoj Kumar Swain, Susmita Das

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This paper explores a detailed procedure of predicting a path loss (PL) model and its application in estimating the coverage probability in a WiMAX network. For this a hybrid approach is followed in predicting an empirical PL model of a 2.65 GHz WiMAX network deployed in a suburban environment. Data collection, statistical analysis, and regression analysis are the phases of operations incorporated in this approach and the importance of each of these phases has been discussed properly. The procedure of collecting data such as received signal strength indicator (RSSI) through experimental set up is demonstrated. From the collected data set, empirical PL and RSSI models are predicted with regression technique. Furthermore, with the aid of the predicted PL model, essential parameters such as PL exponent as well as the coverage probability of the network are evaluated. This research work may assist in the process of deployment and optimisation of any cellular network significantly.

Keywords: WiMAX, RSSI, path loss, coverage probability, regression analysis

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Authors: Zaki Ahmad Khan, Jamshed Siddiqui, Abdus Samad

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The Scheduling and mapping of tasks on a set of processors is considered as a critical problem in parallel and distributed computing system. This paper deals with the problem of dynamic scheduling on a special type of multiprocessor architecture known as Linear Crossed Cube (LCQ) network. This proposed multiprocessor is a hybrid network which combines the features of both linear type of architectures as well as cube based architectures. Two standard dynamic scheduling schemes namely Minimum Distance Scheduling (MDS) and Two Round Scheduling (TRS) schemes are implemented on the LCQ network. Parallel tasks are mapped and the imbalance of load is evaluated on different set of processors in LCQ network. The simulations results are evaluated and effort is made by means of through analysis of the results to obtain the best solution for the given network in term of load imbalance left and execution time. The other performance matrices like speedup and efficiency are also evaluated with the given dynamic algorithms.

Keywords: dynamic algorithm, load imbalance, mapping, task scheduling

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Authors: Manish Saha, Manish Kumar Niranjan, Saket Asthana

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The K₀.₅Na₀.₅NbO₃ (KNN) system has emerged as one of the most promising lead-free piezoelectric over the years. In this work, we perform a comprehensive investigation of electronic structure, lattice dynamics and dielectric/ferroelectric properties of the room temperature phase of KNN by combining ab-initio DFT-based theoretical analysis and experimental characterization. We assign the symmetry labels to KNN vibrational modes and obtain ab-initio polarized Raman spectra, Infrared (IR) reflectivity, Born-effective charge tensors, oscillator strengths etc. The computed Raman spectrum is found to agree well with the experimental spectrum. In particular, the results suggest that the mode in the range ~840-870 cm-¹ reported in the experimental studies is longitudinal optical (LO) with A_1 symmetry. The Raman mode intensities are calculated for different light polarization set-ups, which suggests the observation of different symmetry modes in different polarization set-ups. The electronic structure of KNN is investigated, and an optical absorption spectrum is obtained. Further, the performances of DFT semi-local, metal-GGA and hybrid exchange-correlations (XC) functionals, in the estimation of KNN band gaps are investigated. The KNN bandgap computed using GGA-1/2 and HSE06 hybrid functional schemes are found to be in excellant agreement with the experimental value. The COHP, electron localization function and Bader charge analysis is also performed to deduce the nature of chemical bonding in the KNN. The solid-state reaction and hydrothermal methods are used to prepare the KNN ceramics, and the effects of grain size on the physical characteristics these ceramics are examined. A comprehensive study on the impact of different synthesis techniques on the structural, electrical, and photocatalytic properties of ferroelectric ceramics KNN. The KNN-S prepared by solid-state method have significantly larger grain size as compared to that for KNN-H prepared by hydrothermal method. Furthermore, the KNN-S is found to exhibit higher dielectric, piezoelectric and ferroelectric properties as compared to KNN-H. On the other hand, the increased photocatalytic activity is observed in KNN-H as compared to KNN-S. As compared to the hydrothermal synthesis, the solid-state synthesis causes an increase in the relative dielectric permittivity (ε^') from 2394 to 3286, remnant polarization (P_r) from 15.38 to 20.41 μC/cm^², planer electromechanical coupling factor (k_p) from 0.19 to 0.28 and piezoelectric coefficient (d_33) from 88 to 125 pC/N. The KNN-S ceramics are also found to have a lower leakage current density, and higher grain resistance than KNN-H ceramic. The enhanced photocatalytic activity of KNN-H is attributed to relatively smaller particle sizes. The KNN-S and KNN-H samples are found to have degradation efficiencies of RhB solution of 20% and 65%, respectively. The experimental study highlights the importance of synthesis methods and how these can be exploited to tailor the dielectric, piezoelectric and photocatalytic properties of KNN. Overall, our study provides several bench-mark important results on KNN that have not been reported so far.

Keywords: lead-free piezoelectric, Raman intensity spectrum, electronic structure, first-principles calculations, solid state synthesis, photocatalysis, hydrothermal synthesis

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Authors: Draou Azeddine, Mazin Alahmadi, Abdulrahmane Alkassem, Alamri Abdullah

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The demand for electric power in Saudi Arabia is steadily increasing with economic growth. More power plants should be installed to increase generation capacity and meet demand. Electricity in Saudi Arabia is mainly dependent on fossil fuels, which are a major problem as they deplete natural resources and increase CO₂ emissions. In this research work, performance and techno-economic analyzes are conducted to evaluate a microgrid system based on hybrid PV/wind diesel power sources as a stand-alone system for rural electrification in Saudi Arabia. The total power flow, maximum power point tracking (MPPT) efficiency, effectiveness of the proposed control strategy, and total harmonic distortion (THD) are analyzed in MATLAB/Simulink environment. Various simulation studies have been carried out under different irradiation conditions. The sizing, optimization, and economic feasibility analysis were performed using Homer energy software.

Keywords: WIND, solar, microgrid, energy

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Authors: A. I. Alajtal, H. G. M. Edwards, M. A. Elbagermi

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Raman spectroscopy is currently a part of the instrumentation suite of the ESA ExoMars mission for the remote detection of life signatures in the Martian surface and subsurface. Terrestrial analogues of Martian sites have been identified and the biogeological modifications incurred as a result of extremophilic activity have been studied. Analytical instrumentation protocols for the unequivocal detection of biomarkers in suitable geological matrices are critical for future unmanned explorations, including the forthcoming ESA ExoMars mission to search for life on Mars scheduled for 2018 and Raman spectroscopy is currently a part of the Pasteur instrumentation suite of this mission. Here, Raman spectroscopy using 785nm excitation was evaluated for determining various concentrations of beta-carotene in admixture with polyaromatic hydrocarbons and usnic acid have been investigated by Raman microspectrometry to determine the lowest levels detectable in simulation of their potential identification remotely in geobiological conditions in Martian scenarios. Information from this study will be important for the development of a miniaturized Raman instrument for targetting Martian sites where the biosignatures of relict or extant life could remain in the geological record.

Keywords: raman spectroscopy, mars-analog, beta-carotene, PAHs

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Authors: Jason West

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Low profitability in agriculture production along with increasing scrutiny over environmental effects is limiting food production at scale. In contrast, the mining sector offers access to resources including energy, water, transport and chemicals for food production at low marginal cost. Scalable agricultural production can benefit from the nexus of resources (water, energy, transport) offered by mining activity in remote locations. A decision support bioeconomic model for controlled environment vertical farms was used. Four submodels were used: crop structure, nutrient requirements, resource-crop integration, and economic. They escalate to a macro mathematical model. A demonstrable dynamic systems framework is needed to prove productive outcomes are feasible. We demonstrate a generalized bioeconomic macro model for controlled environment production systems in minesites using systems dynamics modeling methodology. Despite the complexity of bioeconomic modelling of resource-agricultural dynamic processes and interactions, the economic potential greater than general economic models would assume. Scalability of production as an input becomes a key success feature.

Keywords: crop production systems, mathematical model, mining, agriculture, dynamic systems

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Authors: Muhammad Affan, Muhammad Ilyas Raza, Muhammad Harris Hashmi

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This work is attributed to the battery management unit design of student Satellites under Pakistan National Student Satellite Program (PNSSP). The aim has been to design a customized, low-cost, efficient, reliable and less-complex battery management scheme for the Satellite. Nowadays, Lithium Ion (Li-ion) batteries have become the de-facto standard for remote applications, especially for satellites. Li-ion cells are selected for secondary storage. The design also addresses Li-ion safety requirements by monitoring, balancing and protecting cells for safe and prolonged operation. Accurate voltage measurement of individual cells was the main challenge because all the actions triggered were based on the digital voltage measurement. For this purpose, a resistive-divider network is used to maintain simplicity and cost-effectiveness. To cater the problem of insufficient i/o pins on microcontroller, fast multiplexers and de-multiplexers were used. The discrepancy inherited in the given design is the dissipation of heat due to the dissipative resistors. However, it is still considered to be the optimum adoption, considering the simple and cost-effective nature of the passive balancing technique. Furthermore, it is a completely unique solution, customized to meet specific requirements. However, there is still an option for a more advanced and expensive design.

Keywords: satellite, battery module, passive balancing, dissipative

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Authors: Mohammadhadi Mirmohammadi, Reza Safian, Hossein Haddad

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This paper presents an innovative solution for complex multi-objective optimization problem which is a part of efforts toward maximizing rolling mill throughput and minimizing processing costs in tandem cold rolling. This computational intelligence based optimization has been applied to the rolling schedules of tandem cold rolling mill. This method involves the combination of two derivative-free optimization procedures in the form of nested loops. The first optimization loop is based on Improving Hit and Run method which focus on balance of power, force and reduction distribution in rolling schedules. The second loop is a real-coded genetic algorithm based optimization procedure which optimizes energy consumption and productivity. An experimental result of application to five stand tandem cold rolling mill is presented.

Keywords: derivative-free optimization, Improving Hit and Run method, real-coded genetic algorithm, rolling schedules of tandem cold rolling mill

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Authors: Terry Teo, Sun Woh Lye, Yufei Li, Zainuddin Zakaria

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Wearable devices such as Electroencephalography (EEG) hold immense potential in the monitoring and assessment of a person’s task engagement. This is especially so in remote or online sites. Research into its use in measuring an individual's cognitive state while performing task activities is therefore expected to increase. Despite the growing number of EEG research into brain functioning activities of a person, key challenges remain in adopting EEG for real-time operations. These include limited portability, long preparation time, high number of channel dimensionality, intrusiveness, as well as level of accuracy in acquiring neurological data. This paper proposes an approach using a 4-6 EEG channels to determine the cognitive states of a subject when undertaking a set of passive and active monitoring tasks of a subject. Air traffic controller (ATC) dynamic-tasks are used as a proxy. The work found that when using the channel reduction and identifier algorithm, good trend adherence of 89.1% can be obtained between a commercially available BCI 14 channel Emotiv EPOC+ EEG headset and that of a carefully selected set of reduced 4-6 channels. The approach can also identify different levels of engagement activities ranging from general monitoring ad hoc and repeated active monitoring activities involving information search, extraction, and memory activities.

Keywords: assessment, neurophysiology, monitoring, EEG

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Authors: Mehran Nasiri, Ardeshir Poornemat

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The aim of this study was to investigate the current and ideal situations of the process of talent identification in Iranian football from the point of view of Iranian instructors of the Asian Football Confederation (AFC). This research was a descriptive-analytical study; in data collection phase a questionnaire was used, whose face validity was confirmed by experts of Physical Education and Sports Science. The reliability of questionnaire was estimated through the use of Cronbach's alpha method (0.91). This study involved 122 participants of Iranian instructors of the AFC who were selected based on stratified random sampling method. Descriptive statistics were used to describe the variables and inferential statistics (Chi-square) were used to test the hypotheses of the study at significant level (p ≤ 0.05). The results of Chi-square test related to the point of view of Iranian instructors of the AFC showed that the grass-roots scientific method was the best way to identify football players (0.001), less than 10 years old were the best ages for talent identification (0.001), the Football Federation was revealed to be the most important organization in talent identification (0.002), clubs were shown to be the most important institution in developing talents (0.001), trained scouts of Football Federation were demonstrated to be the best and most appropriate group for talent identification (0.001), and being referred by the football academy coaches was shown to be the best way to attract talented football players in Iran (0.001). It was also found that there was a huge difference between the current and ideal situation of the process of talent identification in Iranian football from the point of view of Iranian instructors of the AFC. Hence, it is recommended that the policy makers of talent identification for Iranian football provide a comprehensive, clear and systematic model of talent identification and development processes for the clubs and football teams, so that the talent identification process helps to nurture football talents more efficiently.

Keywords: current situation, talent finding, ideal situation, instructors (AFC)

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Authors: Tayebeh Jameh-Bozorgi, M. Soleymani

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In this research, the role of social networks in promoting ethics in Iranian sports was investigated. The research adopted a descriptive-analytic method, and the survey’s population consisted of all the athletes invited to the national football, volleyball, wrestling and taekwondo teams. Considering the limited population, the size of the society was considered as the sample size. After the distribution of the questionnaires, 167 respondents answered the questionnaires correctly. The data collection tool was chosen according to Hamid Ghasemi`s, standard questionnaire for social networking and mass media, which has 28 questions. Reliability of the questionnaire was calculated using Cronbach's alpha coefficient (94%). The content validity of the questionnaire was also approved by the professors. In this study, descriptive statistics and inferential statistical methods were used to analyze the data using statistical software. The benchmark tests used in this research included the following: Binomial test, Friedman test, Spearman correlation coefficient, Vermont Creamers, Good fit test and comparative prototypes. The results showed that athletes believed that social network has a significant role in promoting sport ethics in the community. Telegram has been known to play a big role than other social networks. Moreover, the respondents' view on the role of social networks in promoting sport ethics was significantly different in both men and women groups. In fact, women had a more positive attitude towards the role of social networks in promoting sport ethics than men. The respondents' view of the role of social networks in promoting the ethics of sports in the study groups also had a significant difference. Additionally, there was a significant and reverse relationship between the sports experience and the attitude of national athletes regarding the role of social networks in promoting ethics in sports.

Keywords: ethics, social networks, mass media, Iranian sports, internet

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Authors: Baluku Nathan

Abstract:

Transferring critically ill patients from one health facility to another poses a major risk to the patient because of increased oxygen demands. transferring patients with critical COVID-19 from a rural health canter in a rural district to a national referral hospital over 350 km in 7 hours would require three size H oxygen cylinders for successful transfer. It was always difficult to arrange the three size cylinders in the ambulance as workspace was greatly compromised for the ambulance assistant. Purpose: The purpose of this study was to investigate the impact and effectiveness of transport ventilators on the transportation of the critically ill patients from rural health canters to national referral hospitals in Uganda. Methodology: This was a descriptive cross-sectional study conducted in sept 2022 among critical care nurses and ambulance assistants who had used both methods of transportation (ventilators and cylinders). A semi structured questionnaire was used to collect quantitative data after informed consent. Results: From the findings, distribution of transport ventilators to the regional referral hospitals by the Ministry of Health has gradually improved patient transfer as the team requires less than one size oxygen cylinder to successfully transfer a patient. We use two ambulance assistants (a critical care nurse and another nurse who has been trained on use of the ventilator) when transferring patients with critical COVID-19 as the teams have to interchange over the long distance. Conclusions: Transport ventilators are effective and efficient in transferring critically ill patients, therefore should be rolled out to lower levels coupled with user training to improve outcomes of patients transferred in ambulances in lower income countries.

Keywords: emergency medical technician, critically ill, COVID-19, transport ventilator

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Authors: Ljerka Kratofil Krehula, Vanja Gilja, Andrea Husak, Sniježana Šuka, Zlata Hrnjak-Murgić

Abstract:

Zinc oxide (ZnO) can be used as photocatalysts for water purification. However, one particular interest is given on the integration of inorganic ZnO nanoclusters with conducting polymers because the resulting nanocomposites may possess unique properties and enhanced photocatalytic activity in comparison to pure ZnO, using UV and also visible light. It is needed to explore the appropriate structure of polypyrrole that can induce activation of ZnO photocatalyst since the synthesis of organic/inorganic hybrid materials can result in a synergistic and complementary feature, increasing ZnO photocatalytic efficiency. In this paper several different composites of polypyrrole/zinc oxide (ZnO) were studied. Composite samples were characterized by X-ray powder diffraction (XRD), Fourier transform infrared spectroscopy (FTIR), cyclic voltammetry (CV) and scanning electron microscopy (SEM). The photocatalytic efficiency of prepared samples was studied as a decomposition of Reactive Red 45 (RR 45) dye, which was monitored by UV-Vis spectroscopy as a change in absorbance of characteristic wavelength at 542 nm. Results show good photocatalytic efficiency of all nanocomposite samples.

Keywords: photocatalysis, polypyrrole, wastewater, zinc oxide

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Authors: Yang Yiting

Abstract:

This paper employs CiteSpace to conduct a visualiazation analysis of literature on college English writing teaching researches published in core journals from the CNKI database and CSSCI journals between 2002 and 2022. It aims to explore the characteristics of researches and future directions on college English writing teaching. The present study yielded the following major findings: the field primarily focuses on innovative writing teaching models and methods, the integration of traditional classroom teaching and information technology, and instructional strategies to enhance students' writing skills. The future research is anticipated to involve a hybrid writing teaching approach combining online and offline teaching methods, leveraging the "Internet+" digital platform, aiming to elevate students' writing proficiency. This paper also presents a prospective outlook for college English writing teaching research in China.

Keywords: citespace, college English, writing teaching, visualization analysis

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Authors: Zahra Afshordi

Abstract:

Instagram, as an everyday life social network, hosts from the ultrasound image of an unborn fetus to the pictures of newly placed gravestones and funerals. It is a platform that allows its users to create a second identity independently from and at the same time in relation to the real space identity. The motives behind this identification are what this article is about. This article studies the motivations of Instagram users mourning for celebrities with a focus on the death of MohammadReza Shajarian. The Shajarian’s death had a wide reflection on Instagram Persian-speaking users. The purpose of this qualitative survey is to comprehend and study the user’s motivations in posting mourning and memorializing content. The methodology of the essay is a hybrid methodology consisting of content analysis and open-ended interviews. The results highlight that users' motives are more than just simple sympathy and include political protest, gaining cultural capital, reaching social status, and escaping from solitude.

Keywords: case study, celebrity, identity, Instagram, mourning, qualitative survey

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Authors: Ashley L. Freeman, Jessica D. Watkins

Abstract:

TeleEmergency Medicine (TeleEM) is an innovative approach leveraging virtual technology to deliver specialized emergency medical care across diverse healthcare settings, including internal acute care and critical access hospitals, remote patient monitoring, and nurse triage escalation, in addition to external emergency departments, skilled nursing facilities, and community health centers. TeleEM represents a significant advancement in the delivery of emergency medical care, providing healthcare professionals the capability to deliver expertise that closely mirrors in-person emergency medicine, exceeding geographical boundaries. Through qualitative research, the extension of timely, high-quality care has proven to address the critical needs of patients in remote and underserved areas. TeleEM’s service design allows for the expansion of existing services and the establishment of new ones in diverse geographic locations. This ensures that healthcare institutions can readily scale and adapt services to evolving community requirements by leveraging on-demand (non-scheduled) telemedicine visits through the deployment of multiple video solutions. In terms of financial management, TeleEM currently employs billing suppression and subscription models to enhance accessibility for a wide range of healthcare facilities. Plans are in motion to transition to a billing system routing charges through a third-party vendor, further enhancing financial management flexibility. To address state licensure concerns, a patient location verification process has been integrated through legal counsel and compliance authorities' guidance. The TeleEM workflow is designed to terminate if the patient is not physically located within licensed regions at the time of the virtual connection, alleviating legal uncertainties. A distinctive and pivotal feature of TeleEM is the introduction of the TeleEmergency Medicine Care Team Assistant (TeleCTA) role. TeleCTAs collaborate closely with TeleEM Physicians, leading to enhanced service activation, streamlined coordination, and workflow and data efficiencies. In the last year, more than 800 TeleEM sessions have been conducted, of which 680 were initiated by internal acute care and critical access hospitals, as evidenced by quantitative research. Without this service, many of these cases would have necessitated patient transfers. Barriers to success were examined through thorough medical record review and data analysis, which identified inaccuracies in documentation leading to activation delays, limitations in billing capabilities, and data distortion, as well as the intricacies of managing varying workflows and device setups. TeleEM represents a transformative advancement in emergency medical care that nurtures collaboration and innovation. Not only has advanced the delivery of emergency medicine care virtual technology through focus group participation with key stakeholders, rigorous attention to legal and financial considerations, and the implementation of robust documentation tools and the TeleCTA role, but it’s also set the stage for overcoming geographic limitations. TeleEM assumes a notable position in the field of telemedicine by enhancing patient outcomes and expanding access to emergency medical care while mitigating licensure risks and ensuring compliant billing.

Keywords: emergency medicine, TeleEM, rural healthcare, telemedicine

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