Search results for: lexical and numerical error-recognition tasks

Authors: Ade Dwi Utami

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Pedagogic competence is the basic competence of teachers to perform their tasks as educators. The ability to assess has become one of the demands in teachers pedagogic competence. Teachers ability to assess is related to curriculum instructions and applications. This research is aimed at obtaining data concerning teachers ability to assess that comprises of understanding assessment, determining assessment type, tools and procedure, conducting assessment process, and using assessment result information. It uses mixed method of explanatory technique in which qualitative data is used to verify the quantitative data obtained through a survey. The technique of quantitative data collection is by test whereas the qualitative data collection is by observation, interview and documentation. Then, the analyzed data is processed through a proportion study technique to be categorized into high, medium and low. The result of the research shows that teachers ability to assess can be grouped into 3 namely, 2% of high, 4% of medium and 94% of low. The data shows that teachers ability to assess is still relatively low. Teachers are lack of knowledge and comprehension in assessment application. The statement is verified by the qualitative data showing that teachers did not state which aspect was assessed in learning, record children’s behavior, and use the data result as a consideration to design a program. Teachers have assessment documents yet they only serve as means of completing teachers administration for the certification program. Thus, assessment documents were not used with the basis of acquired knowledge. The condition should become a consideration of the education institution of educators and the government to improve teachers pedagogic competence, including the ability to assess.

Keywords: assessment, early childhood education, pedagogic competence, teachers

Procedia PDF Downloads 246

Authors: Hung-Yu Lin

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Background: Parts of researchers assert that external hyperactivity behaviors of ADHD children interfere with their abilities to perform internal cognitive tasks; however, there are still other researchers hold the opposite viewpoint, the external high level of activity may serve as the role of improving internal executive function.Objectives: Thisstudy explored the effects of external motor behavior of ADHD on internal visual attentional performance. Methods: A randomized, two-period crossover design was used in this study, a total of 80 children (aged 6-12) were recruited in this study. 40participants have received ADHD diagnosis, and others are children with typically developing. These children were measured through the visual edition of TOVA (The Test of Variables of Attention) when they wore actigraphy, their testing behavior and movement data werecollected through closely observation and the actigraphies under different research conditions. Result: According to the research result, the author found (1) Higherfrequencyof movement under attentional testing condition was found in children with ADHD, comparing to children with typically developing, and (2) Higher frequency of foot movement showed better attentional performance of the visual attentional test in children with ADHD. However, these results were not showed in children with typically developing. Conclusions: The findings support the functional working memory model, which advocated that a positive relation between gross motor activity and attentional performance within the context of attentive behavior in children with ADHD.

Keywords: ADHD, movement, visual attention, children

Procedia PDF Downloads 189

Authors: M. Ranjeeth, S. Anuradha

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Spectrum sensing is the main feature of cognitive radio technology. Spectrum sensing gives an idea of detecting the presence of the primary users in a licensed spectrum. In this paper we compare the theoretical results of detection probability of different fading environments like Rayleigh, Rician, Nakagami-m fading channels with the simulation results using energy detection based spectrum sensing. The numerical results are plotted as P_f Vs P_d for different SNR values, fading parameters. It is observed that Nakagami fading channel performance is better than other fading channels by using energy detection in spectrum sensing. A MATLAB simulation test bench has been implemented to know the performance of energy detection in different fading channel environment.

Keywords: spectrum sensing, energy detection, fading channels, probability of detection, probability of false alarm

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Authors: Kyoungjin Kim

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Nanoscale thermites such as the composite mixture of nano-sized aluminum and molybdenum trioxide powders possess several technical advantages such as much higher reaction rate and shorter ignition delay, when compared to the conventional energetic formulations made of micron-sized metal and oxidizer particles. In this study, the self-propagation of combustion wave in compacted pellets of nanoscale thermite composites is modeled and computationally investigated by utilizing the activation energy reduction of aluminum particles due to nanoscale particle sizes. The present computational model predicts the speed of combustion wave propagation which is good agreement with the corresponding experiments of thermite reaction. Also, several characteristics of thermite reaction in nanoscale composites are discussed including the ignition delay and combustion wave structures.

Keywords: nanoparticles, thermite reaction, combustion wave, numerical modeling

Procedia PDF Downloads 380

Authors: Y. A. Yahaya, Ahmad Tijjani Asabe

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This paper focuses on the formulation of 3-step hybrid Adams type method for the solution of first order differential equation (ODE). The methods which was derived on both grid and off grid points using multistep collocation schemes and also evaluated at some points to produced Block Adams type method and Adams moulton method respectively. The method with the highest order was selected to serve as the corrector. The convergence was valid and efficient. The numerical experiments were carried out and reveal that hybrid Adams type methods performed better than the conventional Adams moulton method.

Keywords: adam-moulton type (amt), corrector method, off-grid, block method, convergence analysis

Procedia PDF Downloads 626

Authors: Siti Ruhliah Lizarose Samion, Mohamed Sukri Mat Ali

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The effect of sawtooth plate thickness on the aerodynamic noise generated in flow at a Reynolds number of 150 is numerically investigated. Two types of plate thickness (hthick=0.2D and hthin=0.02D) are proposed. Flow simulations are carried out using Direct Numerical Simulation, whereas the calculation of aerodynamic noise radiated from the flow is solved using Curle’s equation. It is found that the flow behavior of thin sawtooth plate, consisting counter-rotating-vortices, is more complex than that of the thick plate. This then explains well the generated sound in both plates cases. Sound generated from thin plat is approximately 0.5 dB lower than the thick plate. Findings from current study provide better understanding of the flow and noise behavior in edge serrations via understanding the case of a sawtooth plate.

Keywords: aerodynamic sound, bluff body, sawtooth plate, Curle analogy

Procedia PDF Downloads 436

Authors: Caroline Denaes

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The ability to read is crucial for a successful path in school and in a social and professional context. Children with mild intellectual disability are confronted to serious difficulties in literacy. A lot of them do not read or are illiterate. Only one child out of five is able to acquire basic reading skills, which increases the likelihood to misfit in society, especially when these children grow up and cannot manage themselves in situations requiring higher reading levels. One way to help these children acquiring basic reading skills is to use analogical reasoning, as some researchers demonstrated that this mechanism is fundamental for any reading process. For this purpose, we developed computerized analogies displayed on a touch screen tablet. Analogies are comparisons that give children a framework they can use to understand new information. They work by comparing one thing to another in order to emphasize some mutual quality. If one of the items is unfamiliar, that mutual quality can help make it understandable, or it can cause the children to consider something familiar in some new way, such as transferring what they know about familiar words to help them identify unfamiliar words. In addition, using touch screen tablets represents several advantages: the ease of use, the relevance to this specific population and the appeal of a self-directed activity gives individuals and practitioners a modern tool that differs from the traditional paper-and-pencil material. In addition, the touch screen dimension is especially appropriate for children as assistive technology has been found to be more motivating that any other types of devices and improves the children’ attention span.

Keywords: literacy, intellectual disabilities, touch screen techonology, literacy skill

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Authors: H. M. Mobarak, Helen Wu, Keqin Xiao

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In this work, a three-dimensional finite element model was developed to investigate the crack breathing behavior at different crack locations considering the effect of unbalance force. A two-disk rotor with a crack is simulated using ABAQUS. The duration of each crack status (open, closed and partially open/closed) during a full shaft rotation was examined to analyse the crack breathing behavior. Unbalanced shaft crack breathing behavior was found to be different at different crack locations. The breathing behavior of crack along the shaft length is divided into different regions depending on the unbalance force and crack location. The simulated results in this work can be further utilised to obtain the time-varying stiffness matrix of the cracked shaft element under the influence of unbalance force.

Keywords: crack breathing, crack location, slant crack, unbalance force, rotating shaft

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Authors: Emmanuel Okechukwu Nwafor, Folake Olubunmi Akintayo, Denis Alcides Rezende

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Decision tree models are versatile and interpretable machine learning algorithms widely used for both classification and regression tasks, which can be related to cities, whether physical or digital. The aim of this research is to assess how well decision tree algorithms can predict trip purposes in Makurdi, Nigeria, while also exploring their connection to the strategic digital city initiative. The research methodology involves formalizing household demographic and trips information datasets obtained from extensive survey process. Modelling and Prediction were achieved using Python Programming Language and the evaluation metrics like R-squared and mean absolute error were used to assess the decision tree algorithm's performance. The results indicate that the model performed well, with accuracies of 84% and 68%, and low MAE values of 0.188 and 0.314, on training and validation data, respectively. This suggests the model can be relied upon for future prediction. The conclusion reiterates that This model will assist decision-makers, including urban planners, transportation engineers, government officials, and commuters, in making informed decisions on transportation planning and management within the framework of a strategic digital city. Its application will enhance the efficiency, sustainability, and overall quality of transportation services in Makurdi, Nigeria.

Keywords: decision tree algorithm, trip purpose, intelligent transport, strategic digital city, travel pattern, sustainable transport

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Authors: Hadi Kafil, Ali Ecder

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Heat transfer by natural convection in two-dimensional and three-dimensional axisymmetric enclosure fitted with partially heated vertical walls is investigated numerically. The range of Rayleigh number is varied from 10³ until convective flow becomes unstable. This research focuses on multiplicity and transition phenomena in natural convection and is based on a parametric analysis to study the onset of bifurcations. It is found that, even at low Rayleigh numbers, the flow undergoes a series of turning-point bifurcations which increase the rate of natural convention. On the other hand, by partially heating or cooling the walls, more effective results can be achieved for both heating and cooling applications, such as cooling of electronic devices and heating processes in solidification and crystal growth.

Keywords: natural convection, partial heated, onset of bifurcation, Rayleigh number

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Authors: Konysbek Aksaule

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The purpose of this work is to explore new and effective ways of teaching English to students who are studying a foreign language since the timeliness of the problem disclosed in this article is due to the high level of English proficiency that potential specialists must have due to high competition in the context of global globalization. The article presents an analysis of the feasibility and effectiveness of using an authentic feature film in teaching English to students. The methodological basis of the study includes an assessment of the level of students' proficiency in a foreign language, the stage of evaluating the film, and the method of selecting the film for certain categories of students. The study also contains a list of practical tasks that can be applied in the process of viewing and perception of an original feature film in a foreign language, and which are aimed at developing language skills such as speaking and listening. The results of this study proved that teaching English to students through watching an original film is one of the most effective methods because it improves speech perception, speech reproduction ability, and also expands the vocabulary of students and makes their speech fluent. In addition, learning English through watching foreign films has a huge impact on the cultural views and knowledge of students about the country of the language being studied and the world in general. Thus, this study demonstrates the high potential of using authentic feature film in English lessons for pedagogical science and methods of teaching English in general.

Keywords: university, education, students, foreign language, feature film

Procedia PDF Downloads 148

Authors: Jingting Luo, Yong Wang, Ying Wang

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Pedestrian detection in image or video data is a very important and challenging task in security surveillance. The difficulty of this task is to locate and detect pedestrians of different scales in complex scenes accurately. To solve these problems, a deep neural network (RT-YOLOv3) is proposed to realize real-time pedestrian detection at different scales in security monitoring. RT-YOLOv3 improves the traditional YOLOv3 algorithm. Firstly, the deep residual network is added to extract vehicle features. Then six convolutional neural networks with different scales are designed and fused with the corresponding scale feature maps in the residual network to form the final feature pyramid to perform pedestrian detection tasks. This method can better characterize pedestrians. In order to further improve the accuracy and generalization ability of the model, a hybrid pedestrian data set training method is used to extract pedestrian data from the VOC data set and train with the INRIA pedestrian data set. Experiments show that the proposed RT-YOLOv3 method achieves 93.57% accuracy of mAP (mean average precision) and 46.52f/s (number of frames per second). In terms of accuracy, RT-YOLOv3 performs better than Fast R-CNN, Faster R-CNN, YOLO, SSD, YOLOv2, and YOLOv3. This method reduces the missed detection rate and false detection rate, improves the positioning accuracy, and meets the requirements of real-time detection of pedestrian objects.

Keywords: pedestrian detection, feature detection, convolutional neural network, real-time detection, YOLOv3

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Authors: Omar Dib, Alexandre Caminada, Marie-Ange Manier

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The purpose of this study is to introduce a novel approach to solve the one-to-one shortest path problem. A directed connected graph is assumed in which all edges’ weights are positive. Our method is based on a memetic algorithm in which we combine a genetic algorithm (GA) and a variable neighborhood search method (VNS). We compare our approximate method with two exact algorithms Dijkstra and Integer Programming (IP). We made experimentations using random generated, complete and real graph instances. In most case studies, numerical results show that our method outperforms exact methods with 5% average gap to the optimality. Our algorithm’s average speed is 20-times faster than Dijkstra and more than 1000-times compared to IP. The details of the experimental results are also discussed and presented in the paper.

Keywords: shortest path problem, Dijkstra’s algorithm, integer programming, memetic algorithm

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Authors: Ranajay Bhowmick

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Analysis of stresses for an infinitesimal tetrahedron leads to a situation where we obtain a cubic equation consisting of three stress invariants. This cubic equation, when solved for a definite condition, gives the principal stresses directly without requiring any cumbersome and time-consuming trial and error methods or iterative numerical procedures. Since the failure criterion of different materials are generally expressed as functions of principal stresses, an attempt has been made in this study to incorporate the solutions of the cubic equation in the form of principal stresses, obtained for a definite condition, into some of the established failure theories to determine their modified descriptions. It has been observed that the failure theories can be represented using the quadratic stress invariant and the orientation of the principal plane.

Keywords: cubic equation, stress invariant, trigonometric, explicit solution, principal stress, failure criterion

Procedia PDF Downloads 137

Authors: Ibrahim M. Elmojtaba, Rayan M. Altayeb

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Visceral leishmaniasis (VL) is a vector-borne disease caused by the protozoa parasite of the genus leishmania. The transmission of the parasite to humans and animals occurs via the bite of adult female sandflies previously infected by biting and sucking blood of an infectious humans or animals. In this paper we use a previously proposed model, and then applied two optimal controls, namely treatment and vaccination to that model to investigate optimal strategies for controlling the spread of the disease using treatment and vaccination as the system control variables. The possible impact of using combinations of the two controls, either one at a time or two at a time on the spread of the disease is also examined. Our results provide a framework for vaccination and treatment strategies to reduce susceptible and infection individuals of VL in five years.

Keywords: visceral leishmaniasis, treatment, vaccination, optimal control, numerical simulation

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Authors: Omar M. Aldenali

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Planning is one of the most important phases of the management science and network planning, which represents the project activities relationship. Critical path is one of the project management techniques used to plan and control the execution of a project activities. The objective of this paper is to implement a fuzzy logic approach to arrange network planning on construction projects. This method is used to finding out critical path in the fuzzy construction project network. The trapezoidal fuzzy numbers are used to represent the activity construction project times. A numerical example that represents a house construction project is introduced. The critical path method is implemented on the fuzzy construction network activities, and the results showed that this method significantly affects the completion time of the construction projects.

Keywords: construction project, critical path, fuzzy network project, planning

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Authors: B. Chetti, W. A. Crosby

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This paper presents a numerical analysis for the dynamic performance of a finite journal bearing lubricated with couple stress fluid taking into account the effect of the deformation of the bearing liner. The modified Reynolds equation has been solved by using finite difference technique. The dynamic characteristics in terms of stiffness coefficients, damping coefficients, critical mass and whirl ratio are evaluated for different values of eccentricity ratio and elastic coefficient for a journal bearing lubricated with a couple stress fluids and a Newtonian fluid. The results show that the dynamic characteristics of journal bearings lubricated with couple stress fluids are improved compared to journal bearings lubricated with Newtonian fluids.

Keywords: journal bearing, elastohydrodynamic, stability, couple stress

Procedia PDF Downloads 362

Authors: Iman Janghorban Esfahani

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Due to the increased use of irrigation in agriculture, the importance and need for highly reliable water pumping systems have significantly increased. The pumping of the groundwater is essential to provide water for both drip and furrow irrigation to increase the agricultural yield, especially in arid regions that suffer from scarcities of surface water. The most common irrigation pumping systems (IPS) consume conventional energies through the use of electric motors and generators or connecting to the electricity grid. Due to the shortage and transportation difficulties of fossil fuels, and unreliable access to the electricity grid, especially in the rural areas, and the adverse environmental impacts of fossil fuel usage, such as greenhouse gas (GHG) emissions, the need for renewable energy sources such as photovoltaic systems (PVS) as an alternative way of powering irrigation pumping systems is urgent. Integration of the photovoltaic systems with irrigation pumping systems as the Photovoltaic Powered-Irrigation Pumping System (PVP-IPS) can avoid fossil fuel dependency and the subsequent greenhouse gas emissions, as well as ultimately lower energy costs and improve efficiency, which made PVP-IPS systems as an environmentally and economically efficient solution for agriculture irrigation in every region. The greatest problem faced by integration of PVP with IPS systems is matching the intermittence of the energy supply with the dynamic water demand. The best solution to overcome the intermittence is to incorporate a storage system into the PVP-IPS to provide water-on-demand as a highly reliable stand-alone irrigation pumping system. The water storage tank (WST) is the most common storage device for PVP-IPS systems. In the integrated PVP-IPS with a water storage tank (PVP-IPS-WST), a water storage tank stores the water pumped by the IPS in excess of the water demand and then delivers it when demands are high. The Freshwater pinch analysis (FWaPA) as an alternative to mathematical modeling was used by other researchers for retrofitting the off-grid battery less photovoltaic-powered reverse osmosis system. However, the Freshwater pinch analysis has not been used to integrate the photovoltaic systems with irrigation pumping system with water storage tanks. In this study, FWaPA graphical and numerical tools were used for retrofitting an existing PVP-IPS system located in Salahadin, Republic of Iraq. The plant includes a 5 kW submersible water pump and 7.5 kW solar PV system. The Freshwater Composite Curve as the graphical tool and Freashwater Storage Cascade Table as the numerical tool were constructed to determine the minimum required outsourced water during operation, optimal amount of delivered electricity to the water pump, and optimal size of the water storage tank for one-year operation data. The results of implementing the FWaPA on the case study show that the PVP-IPS system with a WST as the reliable system can reduce outsourced water by 95.41% compare to the PVP-IPS system without storage tank.

Keywords: irrigation, photovoltaic, pinch analysis, pumping, solar energy

Procedia PDF Downloads 138

Authors: Hamad M. Alhajeri

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Swirling chamber is a promising cooling method for heavily thermally loaded parts like turbine blades due to the additional circumferential velocity and therefore improved turbulent mixing of the fluid. This paper investigates numerically the effect of turbulence model on the heat convection of the swirling chamber. Grid independence analysis is conducted to obtain the proper grid dimension. The work validated with experimental data available in the literature. Flow analysis using improved delayed detached eddy simulation turbulence model and Reynolds averaged Navier-Stokes k-ɛ turbulence model is carried. The flow characteristic near the exit is reformed when improved delayed detached eddy simulation model used.

Keywords: gas turbine, Nusselt number, flow characteristics, heat transfer

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Authors: Abdelazim Makki Ibrahim, Esamaldeen Ali

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This study aims at analysing the load settlement behavior and predict the bearing capacity of piled raft foundation a series of finite element models with different foundation configurations and stiffness were established. Numerical modeling is used to study the behavior of the piled raft foundation due to the complexity of piles, raft, and soil interaction and also due to the lack of reliable analytical method that can predict the behavior of the piled raft foundation system. Simple analytical models are developed to predict the average settlement and the load sharing between the piles and the raft in piled raft foundation system. A simple example to demonstrate the applications of these charts is included.

Keywords: finite element, pile-raft foundation, method, PLAXIS software, settlement

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Authors: Atish Bagchi, Siva Chandrasekaran

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Background: According to World Bank national accounts data, the estimated global manufacturing value-added output in 2020 was 13.74 trillion USD. These manufacturing processes are monitored, modelled, and controlled by advanced, real-time, computer-based systems, e.g., Industrial IoT, PLC, SCADA, etc. These systems measure and manipulate a set of physical variables, e.g., temperature, pressure, etc. Despite the use of IoT, SCADA etc., in manufacturing, studies suggest that unplanned downtime leads to economic losses of approximately 864 billion USD each year. Therefore, real-time, accurate detection, classification and prediction of machine behaviour are needed to minimise financial losses. Although vast literature exists on time-series data processing using machine learning, the challenges faced by the industries that lead to unplanned downtimes are: The current algorithms do not efficiently handle the high-volume streaming data from industrial IoTsensors and were tested on static and simulated datasets. While the existing algorithms can detect significant 'point' outliers, most do not handle contextual outliers (e.g., values within normal range but happening at an unexpected time of day) or subtle changes in machine behaviour. Machines are revamped periodically as part of planned maintenance programmes, which change the assumptions on which original AI models were created and trained. Aim: This research study aims to deliver a Graph Neural Network(GNN)based hybrid forecasting model that interfaces with the real-time machine control systemand can detect, predict machine behaviour and behavioural changes (anomalies) in real-time. This research will help manufacturing industries and utilities, e.g., water, electricity etc., reduce unplanned downtimes and consequential financial losses. Method: The data stored within a process control system, e.g., Industrial-IoT, Data Historian, is generally sampled during data acquisition from the sensor (source) and whenpersistingin the Data Historian to optimise storage and query performance. The sampling may inadvertently discard values that might contain subtle aspects of behavioural changes in machines. This research proposed a hybrid forecasting and classification model which combines the expressive and extrapolation capability of GNN enhanced with the estimates of entropy and spectral changes in the sampled data and additional temporal contexts to reconstruct the likely temporal trajectory of machine behavioural changes. The proposed real-time model belongs to the Deep Learning category of machine learning and interfaces with the sensors directly or through 'Process Data Historian', SCADA etc., to perform forecasting and classification tasks. Results: The model was interfaced with a Data Historianholding time-series data from 4flow sensors within a water treatment plantfor45 days. The recorded sampling interval for a sensor varied from 10 sec to 30 min. Approximately 65% of the available data was used for training the model, 20% for validation, and the rest for testing. The model identified the anomalies within the water treatment plant and predicted the plant's performance. These results were compared with the data reported by the plant SCADA-Historian system and the official data reported by the plant authorities. The model's accuracy was much higher (20%) than that reported by the SCADA-Historian system and matched the validated results declared by the plant auditors. Conclusions: The research demonstrates that a hybrid GNN based approach enhanced with entropy calculation and spectral information can effectively detect and predict a machine's behavioural changes. The model can interface with a plant's 'process control system' in real-time to perform forecasting and classification tasks to aid the asset management engineers to operate their machines more efficiently and reduce unplanned downtimes. A series of trialsare planned for this model in the future in other manufacturing industries.

Keywords: GNN, Entropy, anomaly detection, industrial time-series, AI, IoT, Industry 4.0, Machine Learning

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Authors: A. M. Sagir

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The aim of this paper is to investigate the performance of the developed linear multistep block method for solving first order initial value problem of Ordinary Differential Equations (ODEs). The method calculates the numerical solution at three points simultaneously and produces three new equally spaced solution values within a block. The continuous formulations enable us to differentiate and evaluate at some selected points to obtain three discrete schemes, which were used in block form for parallel or sequential solutions of the problems. A stability analysis and efficiency of the block method are tested on ordinary differential equations involving practical applications, and the results obtained compared favorably with the exact solution. Furthermore, comparison of error analysis has been developed with the help of computer software.

Keywords: block method, first order ordinary differential equations, linear multistep, self-starting

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Authors: P. Byrnes, F. A. DiazDelaO

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The Support Vector Machine (SVM) has become widely recognised as one of the leading algorithms in machine learning for both regression and binary classification. It expresses predictions in terms of a linear combination of kernel functions, referred to as support vectors. Despite its popularity amongst practitioners, SVM has some limitations, with the most significant being the generation of point prediction as opposed to predictive distributions. Stemming from this issue, a probabilistic model namely, Probabilistic Classification Vector Machines (PCVM), has been proposed which respects the original functional form of SVM whilst also providing a predictive distribution. As physical system designs become more complex, an increasing number of classification tasks involving industrial applications consist of more than two classes. Consequently, this research proposes a framework which allows for the extension of PCVM to a multi class setting. Additionally, the original PCVM framework relies on the use of type II maximum likelihood to provide estimates for both the kernel hyperparameters and model evidence. In a high dimensional multi class setting, however, this approach has been shown to be ineffective due to bad scaling as the number of classes increases. Accordingly, we propose the application of Markov Chain Monte Carlo (MCMC) based methods to provide a posterior distribution over both parameters and hyperparameters. The proposed framework will be validated against current multi class classifiers through synthetic and real life implementations.

Keywords: probabilistic classification vector machines, multi class classification, MCMC, support vector machines

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Authors: Bi Yan-Qiang, Shang Yonghong, Lin Boying, Ji Xinyan, Li Xiyuan

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The heat-resistant material has important application in the aerospace field. The reliability of the connection between the heat-resisting material and the body determines the success or failure of the project. In this paper, lock-in infrared thermography non-destructive testing technology is used to detect the stability of the thermal-resistant structure. The phase relationship between the temperature and the heat flow is calculated by the numerical method, and the influence of the heating frequency and power is obtained. The correctness of the analysis is verified by the experimental method. Through the research, it can provide the basis for the parameter setting of heat flux including frequency and power, improve the efficiency of detection and the reliability of connection between the heat-resisting material and the body.

Keywords: infrared non-destructive, thermal insulation material, reliability, connection

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Authors: William Mahony, L. Jacqueline Hirth, Richard Rupp, Sandra Gonzalez, Roger Zoorob

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Background: The impact of the COVID-19 pandemic on physicians has been considered by many researchers, but less is known about non-physician healthcare workers. The aim of this study is to examine the association of COVID-19 safety training and communication with stress. Methods: A 91-item online survey was distributed, starting January 2, 2021, to non-physician healthcare workers, including physician assistants, nurse practitioners, and medical assistants (MAs) in the United States through email and social media. A $1 donation was made to the Red Cross for each completed survey. The survey consisted of demographics, occupational questions, and perceived stress (perceived stress scale, PSS). Items on the PSS were combined for an overall score and categorized according to the severity of perceived stress. Chi-square tests were performed for bivariate analyses of categorical variables. Results: Of the 284 participants consenting to complete the survey, 197 participants completed the full survey. MAs made up most of the sample at 79%. Among all respondents, 47% had moderate PSS scores (scored between 14 and 26), and 51% had severe PSS scores (scored between 27 and 40). Unvaccinated participants reported statistically significantly lower levels of perceived stress (p = 0.002). Performing tasks outside of typical job responsibilities was not associated with PSS scores (p = .667). Discussion: Non-physician healthcare workers demonstrated a high level of perceived stress overall. The association between vaccination status and perceived stress should be examined in order to evaluate whether vaccination levels could be improved with further education about the virus and associated risks.

Keywords: COVID-19, SARS-Cov-2, nursing, public health

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Authors: Nirupma Bhatti

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This empirical study was aimed to compare the effectiveness of Computer Assisted Instruction (CAI) and Conventional Method (CM) in attaining and retaining mathematical concepts. Instructional and measuring tools were developed for five units of Matrix Algebra, two of Calculus and five of Numerical Analysis. Reliability and validity of these tools were also examined in pilot study. Ninety undergraduates participated in this study. Pre-test – post-test equivalent – groups research design was used. SPSS v.16 was used for data analysis. Findings supported CAI as better mode of instruction for attainment and retention of basic mathematical concepts. Administrators should motivate faculty members to develop Computer Assisted Instructional Material (CAIM) in mathematics for higher education.

Keywords: attainment, CAI, CAIM, conventional method, retention

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Authors: Eashwari Dahoe, Jody Scheuer, Harm-Jan Vink

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Alzheimer's disease is a progressive brain condition and is the most common form of dementia. Dementia is a global concern. It is an increasing crisis due to the worldwide aging population. The disease alters the body in different stages leading to several issues. The most common issues result in memory loss, responsive decline, and social decline. During the various stages, the dementia patient must be supported more in performing daily tasks. Eventually, the patient will have to be cared for entirely. There are many efforts in various domains to support this brain condition. This study focuses on the connection between three generations of solutions in the domain of technology and the struggles they tackle. To gather information regarding the struggles seniors with dementia face data has been acknowledged through reading scientific articles. The struggles are extracted from these articles and classified into various category struggles. To gather information regarding the three generations of technology data has been acknowledged through reading scientific articles regarding the generations. After understanding the difference between the three generations, international technological solutions from the past 20 years are connected to the generation they fit. This info is mainly collected through research on companies that aim to improve the lives of senior citizens with early stages of dementia. Eventually, the technological solutions (divided by generations) are linked to the struggles they tackle. By connecting the struggles and the solutions , it is hoped that this paper contributes to an informative overview of the currently available technological solutions and the struggles they tackle.

Keywords: Alzheimer’s disease, technological solutions to support dementia, struggles of seniors with dementia, struggles of dementia

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Authors: Gabriela Kloudova, Miloslav Stehlik, Peter Sos

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The quality of sleep can affect combat performance where the vigilance, accuracy and reaction time are a decisive factor. In the present study, airborne and special units are measured on duty using actigraphy fingerprint scoring algorithm and QEEG (quantitative EEG). Actigraphic variables of interest will be: mean nightly sleep duration, mean napping duration, mean 24-h sleep duration, mean sleep latency, mean sleep maintenance efficiency, mean sleep fragmentation index, mean sleep onset time, mean sleep offset time and mean midpoint time. In an attempt to determine the individual somnotype of each subject, the data like sleep pattern, chronotype (morning and evening lateness), biological need for sleep (daytime and anytime sleepability) and trototype (daytime and anytime wakeability) will be extracted. Subsequently, a series of recommendations will be included in the training plan based on daily routine, timing of the day and night activities, duration of sleep and the number of sleeping blocks in a defined time. The aim of these modifications in the training plan is to reduce day-time sleepiness, improve vigilance, attention, accuracy, speed of the conducted tasks and to optimize energy supplies. Regular improvement of the training supposed to have long-term neurobiological consequences including neuronal activity changes measured by QEEG. Subsequently, that should enhance cognitive functioning in subjects assessed by the digital cognitive test batteries and improve their overall performance.

Keywords: sleep quality, combat performance, actigraph, somnotype

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Authors: Mahmood Dehqan, Peyman Peyvasteh

Abstract:

In recent years there has been a growing interest in issues concerning the impact of sociocultural theory (SCT) of learning on different aspects of second/foreign language learning. This study aimed to find the possible effects of sociocultural teaching techniques on reading strategy of EFL learners. Indeed, the present research compared the impact of peer and teacher scaffolding on EFL learners’ reading strategy use across two proficiency levels. To this end, a pre-test post-test quasi-experimental research design was used and two instruments were utilized to collect the data: Nelson English language test and reading strategy questionnaire. Ninety five university students participated in this study were divided into two groups of teacher and peer scaffolding. Teacher scaffolding group received scaffolded help from the teacher based on three mechanisms of effective help within ZPD: graduated, contingent, dialogic. In contrast, learners of peer scaffolding group were unleashed from the teacher-fronted classroom as they were asked to carry out the reading comprehension tasks with the feedback they provided for each other. Results obtained from ANOVA revealed that teacher scaffolding group outperformed the peer scaffolding group in terms of reading strategy use. It means teacher’s scaffolded help provided within the learners’ ZPD led to better reading strategy improvement compared with the peer scaffolded help. However, the interaction effect between proficiency factor and teaching technique was non-significant, leading to the conclusion that strategy use of the learners was not affected by their proficiency level in either teacher or peer scaffolding groups.

Keywords: peer scaffolding, proficiency level, reading strategy, sociocultural theory, teacher scaffolding

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Authors: Leila Jafari, Viliam Makis

Abstract:

In this paper, the joint optimization of the economic manufacturing quantity (EMQ), safety stock level, and condition-based maintenance (CBM) is presented for a partially observable, deteriorating system subject to random failure. The demand is stochastic and it is described by a Poisson process. The stochastic model is developed and the optimization problem is formulated in the semi-Markov decision process framework. A modification of the policy iteration algorithm is developed to find the optimal policy. A numerical example is presented to compare the optimal policy with the policy considering zero safety stock.

Keywords: condition-based maintenance, economic manufacturing quantity, safety stock, stochastic demand

Procedia PDF Downloads 464