Scholarly

COVID-19 Pandemic Influence on Toddlers and Preschoolers’ Screen Time

Year: 2021 Volume: 15 Issue: 12 250 - 254 Pages

Abstract: The average daily screen time (ST) has been increasing in children, even at young ages. This seems to be associated with a higher incidence of neurodevelopmental disorders, and as the time of exposure increases, the greater is the functional impact. This study aims to compare the daily ST of toddlers and preschoolers previously and during the COVID-19 pandemic. A questionnaire was applied by telephone to parents/caregivers of children between 1 and 5 years old, followed up at four primary care units belonging to the Group of Primary Health Care Centers of Western Porto, Portugal. A total of 520 children were included: 52.9% male, mean age 39.4 ± 13.9 months. The mean age of first exposure to screens was 13.9 ± 8.0 months, and most of the children were exposed to more than one screen daily. Considering the WHO recommendations, before the COVID-19 pandemic, 385 (74.0%) and 408 (78.5%) children had excessive ST during the week and the weekend, respectively; during the lockdown, these values increased to 495 (95.2%) and 482 (92.7%). Maternal education and both the child's median age and the median age of first exposure to screens had a statistically significant association with excessive ST, with OR 0.2 (p = 0.03, CI 95% 0.07-0.86), OR 1.1 (p = 0.01, 95% CI 1.05-1.14) and OR 0.9 (p = 0.05, 95% CI 0. 87-0.98), respectively. Most children in this sample had a higher than recommended ST, which increased with the onset of the COVID-19 pandemic. These results are worrisome and point to the need for urgent intervention.

Fracture Toughness Properties and FTIR Analysis of Corn Fiber Green Composites

Year: 2021 Volume: 15 Issue: 12 382 - 386 Pages

Abstract: The present work introduced a green composite consisting of corn natural fiber of constant concentration of 10% by weight incorporation with poly methyl methacrylate matrix biomaterial prepared by hand lay-up technique. Corn natural fibers were treated with two concentrations of sodium hydroxide solution (3% and 5%) with different immersed time (1.5 and 3 hours) at room temperature. The fracture toughness test of untreated and alkali treated corn fiber composites were performed. The effect of chemically treated on fracture properties of composites has been analyzed using Fourier transform infrared (FTIR) spectroscopy. The experimental results showed that the alkali treatment improved the fracture properties in terms of plane strain fracture toughness KIC. It was found that the plane strain fracture toughness KIC increased by up to 62% compared to untreated fiber composites. On the other hand, increases in both concentrations of alkali solution and time of soaking to 5% NaOH and 3 hours, respectively reduced the values of KIC lower than the value of the unfilled material.

Freighter Aircraft Selection Using Entropic Programming for Multiple Criteria Decision Making Analysis

Year: 2021 Volume: 15 Issue: 12 70 - 77 Pages

Authors:
C. Ardil

Abstract: This paper proposes entropic programming for the freighter aircraft selection problem using the multiple criteria decision analysis method. The study aims to propose a systematic and comprehensive framework by focusing on the perspective of freighter aircraft selection. In order to achieve this goal, an integrated entropic programming approach was proposed to evaluate and rank alternatives. The decision criteria and aircraft alternatives were identified from the research data analysis. The objective criteria weights were determined by the mean weight method and the standard deviation method. The proposed entropic programming model was applied to a practical decision problem for evaluating and selecting freighter aircraft. The proposed entropic programming technique gives robust, reliable, and efficient results in modeling decision making analysis problems. As a result of entropic programming analysis, Boeing B747-8F, a freighter aircraft alternative ( a3), was chosen as the most suitable freighter aircraft candidate.

Advanced Jet Trainer and Light Attack Aircraft Selection Using Composite Programming in Multiple Criteria Decision Making Analysis Method

Year: 2021 Volume: 15 Issue: 12 376 - 381 Pages

Authors:
C. Ardil

Abstract: In this paper, composite programming is discussed for aircraft evaluation and selection problem using the multiple criteria decision analysis method. The decision criteria and aircraft alternatives were identified from the literature review. The importance of criteria weights was determined by the standard deviation method. The proposed model is applied to a practical decision problem for evaluating and selecting advanced jet trainer and light attack aircraft. The proposed technique gives robust and efficient results in modeling multiple criteria decisions. As a result of composite programming analysis, Hürjet, an advanced jet trainer and light attack aircraft alternative (a3), was chosen as the most suitable aircraft candidate.

Comparison of Composite Programming and Compromise Programming for Aircraft Selection Problem Using Multiple Criteria Decision Making Analysis Method

Year: 2021 Volume: 15 Issue: 11 369 - 375 Pages

Authors:
C. Ardil

Abstract: In this paper, the comparison of composite programming and compromise programming for the aircraft selection problem is discussed using the multiple criteria decision analysis method. The decision making process requires the prior definition and fulfillment of certain factors, especially when it comes to complex areas such as aircraft selection problems. The proposed technique gives more efficient results by extending the composite programming and compromise programming, which are widely used in modeling multiple criteria decisions. The proposed model is applied to a practical decision problem for evaluating and selecting aircraft problems.A selection of aircraft was made based on the proposed approach developed in the field of multiple criteria decision making. The model presented is solved by using the following methods: composite programming, and compromise programming. The importance values of the weight coefficients of the criteria are calculated using the mean weight method. The evaluation and ranking of aircraft are carried out using the composite programming and compromise programming methods. In order to determine the stability of the model and the ability to apply the developed composite programming and compromise programming approach, the paper analyzes its sensitivity, which involves changing the value of the coefficient λ and q in the first part. The second part of the sensitivity analysis relates to the application of different multiple criteria decision making methods, composite programming and compromise programming. In addition, in the third part of the sensitivity analysis, the Spearman correlation coefficient of the ranks obtained was calculated which confirms the applicability of all the proposed approaches.

Simulation with Uncertainties of Active Controlled Vibration Isolation System for Astronaut’s Exercise Platform

Year: 2021 Volume: 15 Issue: 11 361 - 368 Pages

Abstract: In a task to assist NASA in analyzing the dynamic forces caused by operational countermeasures of an astronaut’s exercise platform impacting the spacecraft, an active proportional-integral-derivative controller commanding a linear actuator is proposed in a vibration isolation system to regulate the movement of the exercise platform. Computer simulation shows promising results that most exciter forces can be reduced or even eliminated. This paper emphasizes on parameter uncertainties, variations and exciter force variations. Drift and variations of system parameters in the vibration isolation system for astronaut’s exercise platform are analyzed. An active controlled scheme is applied with the goals to reduce the platform displacement and to minimize the force being transmitted to the spacecraft structure. The controller must be robust enough to accommodate the wide variations of system parameters and exciter forces. Computer simulation for the vibration isolation system was performed via MATLAB/Simulink and Trick. The simulation results demonstrate the achievement of force reduction with small platform displacement under wide ranges of variations in system parameters.

A Program Based on Artistic and Musical Activities to Acquire Educational Concepts for Children with Learning Difficulties

Year: 2021 Volume: 15 Issue: 11 829 - 834 Pages

Abstract: The study aims to identify the extent of effectiveness of the artistic formation program using some types of pastes to reduce the hyperactivity of the kindergarten children with learning difficulties. The researchers have discussed the aforesaid topic, where the research sample included 120 children of ages between 5 to 6 years, from five schools for special needs, learning disability section, Cairo Governorate. The study used the quasi-empirical method, which depends on designing one group using the pre& post application measurements for the group to validate both, hypothesis and effectiveness of the program. The variables of the study were specified as follows; artistic formation program using Paper Mache as an independent variable, and its effect on the skills of kindergarten child with learning disabilities, as a dependent variable. The researchers utilized the application of an artistic formation program consisting of artistic and musical skills for kindergarten children with learning disabilities. The tools of the study, designed by the researchers, included: observation card used for recording the culling paper using pulp molding skills for kindergarten children with learning difficulties during practicing the artistic formation activity. Additionally, there was a program utilizing Artistic and Musical Activities for kindergarten children with learning disabilities to acquire educational concepts. The study was composed of 20 lessons for fine art activities and 20 lessons for musical activities, with obligation of giving the musical lesson with art lesson in one session to cast on the kindergarten child some educational concepts.

A Comprehensive Survey on Machine Learning Techniques and User Authentication Approaches for Credit Card Fraud Detection

Year: 2021 Volume: 15 Issue: 11 459 - 472 Pages

Abstract: With the increase of credit card usage, the volume of credit card misuse also has significantly increased, which may cause appreciable financial losses for both credit card holders and financial organizations issuing credit cards. As a result, financial organizations are working hard on developing and deploying credit card fraud detection methods, in order to adapt to ever-evolving, increasingly sophisticated defrauding strategies and identifying illicit transactions as quickly as possible to protect themselves and their customers. Compounding on the complex nature of such adverse strategies, credit card fraudulent activities are rare events compared to the number of legitimate transactions. Hence, the challenge to develop fraud detection that are accurate and efficient is substantially intensified and, as a consequence, credit card fraud detection has lately become a very active area of research. In this work, we provide a survey of current techniques most relevant to the problem of credit card fraud detection. We carry out our survey in two main parts. In the first part, we focus on studies utilizing classical machine learning models, which mostly employ traditional transnational features to make fraud predictions. These models typically rely on some static physical characteristics, such as what the user knows (knowledge-based method), or what he/she has access to (object-based method). In the second part of our survey, we review more advanced techniques of user authentication, which use behavioral biometrics to identify an individual based on his/her unique behavior while he/she is interacting with his/her electronic devices. These approaches rely on how people behave (instead of what they do), which cannot be easily forged. By providing an overview of current approaches and the results reported in the literature, this survey aims to drive the future research agenda for the community in order to develop more accurate, reliable and scalable models of credit card fraud detection.

Dissecting Big Trajectory Data to Analyse Road Network Travel Efficiency

Year: 2021 Volume: 15 Issue: 11 451 - 458 Pages

Abstract: Digital innovation has played a crucial role in managing smart transportation. For this, big trajectory data collected from trav-eling vehicles, such as taxis through installed global positioning sys-tem (GPS)-enabled devices can be utilized. It offers an unprecedented opportunity to trace the movements of vehicles in fine spatiotemporal granularity. This paper aims to explore big trajectory data to measure the travel efficiency of road networks using the proposed statistical travel efficiency measure (STEM) across an entire city. Further, it identifies the cause of low travel efficiency by proposed least square approximation network-based causality exploration (LANCE). Finally, the resulting data analysis reveals the causes of low travel efficiency, along with the road segments that need to be optimized to improve the traffic conditions and thus minimize the average travel time from given point A to point B in the road network. Obtained results show that our proposed approach outperforms the baseline algorithms for measuring the travel efficiency of the road network.

Capacities of Early Childhood Education Professionals for the Prevention of Social Exclusion of Children

Year: 2021 Volume: 15 Issue: 11 802 - 808 Pages

Abstract: Both policymakers and researchers recognize that participating in early childhood education and care (ECEC) is useful for all children, especially for those who are exposed to the high risk of social exclusion. Social exclusion of children is understood as a multidimensional construct including economic, social, cultural, health, and other aspects of disadvantage and deprivation, which individually or combined can have an unfavorable effect on the current life and development of a child, as well as on the child’s development and on disadvantaged life chances in adult life. ECEC institutions should be able to promote educational approaches that portray developmental, cultural, language, and other diversity amongst children. However, little is known about the ways in which Croatian ECEC institutions recognize and respect the diversity of children and their families and how they respond to their educational needs. That is why this paper is dedicated to the analysis of the capacities of ECEC professionals to respond to the demands of educational needs of this very diverse group of children and their families. The results obtained in the frame of the project “Models of response to educational needs of children at risk of social exclusion in ECEC institutions,” funded by the Croatian Science Foundation, will be presented. The research methodology arises from explanations of educational processes and risks of social exclusion as a complex and heterogeneous phenomenon. The preliminary results of the qualitative data analysis of educational practices regarding capacities to identify and appropriately respond to the requirements of children at risk of social exclusion will be presented. The data have been collected by interviewing educational staff in 10 Croatian ECEC institutions (n = 10). The questions in the interviews were related to various aspects of inclusive institutional policy, culture, and practices. According to the analysis, it is possible to conclude that Croatian ECEC professionals are still faced with great challenges in the process of implementation of inclusive policies, culture, and practices. There are several baselines of this conclusion. The interviewed educational professionals are not familiar enough with the whole complexity and diversity of needs of children at risk of social exclusion, and the ECEC institutions do not have enough resources to provide all interventions that these children and their families need.

Neutrosophic Multiple Criteria Decision Making Analysis Method for Selecting Stealth Fighter Aircraft

Year: 2021 Volume: 15 Issue: 10 356 - 360 Pages

Authors:
C. Ardil

Abstract: In this paper, a neutrosophic multiple criteria decision analysis method is proposed to select stealth fighter aircraft. Neutrosophic multiple criteria decision analysis methods are used to analyze the neutrosophic environment and give results under uncertainty and incompleteness. Neutrosophic numbers are used to evaluate alternatives over a set of evaluation criteria in decision making problems. Finally, the proposed model is applied to a practical decision problem for selecting stealth fighter aircraft.

Keywords:
neutrosophic sets
multiple criteria decision making analysis
stealth fighter aircraft
aircraft selection
MCDMA
SVNNs

Fundamentals of Performance Management in the World of Public Service Organisations

Year: 2021 Volume: 15 Issue: 10 789 - 794 Pages

Authors:
Daniella Kucsma

Abstract: The examination of the Public Service Organization’s performance evaluation includes several steps that help public organizations to develop a more efficient system. Public sector organizations have different characteristics than the competitive sector, so it can be stated that other/new elements become more important in their performance processes. The literature in this area is diverse, so highlighting an indicator system can be useful for introducing a system, but it is also worthwhile to measure the specific elements of the organization. In the case of a public service organization, due to the service obligation, it is usually possible to talk about a high number of users, so compliance is more difficult. For the organization, it is an important target to place great emphasis on the increase of service standards and the development of related processes. In this research, the health sector is given a prominent role, as it is a sensitive area where both organizational and individual performance is important for all participants. As a primary step, the content of the strategy is decisive, as this is important for the efficient structure of the process. When designing any system, it is important to review the expectations of the stakeholders, as this is primary when considering the design. The goal of this paper is to build the foundations of a performance management and indexing framework that can help a hospital to provide effective feedback and a direction that is important in assessing and developing a service and can become a management philosophy.

Empirical Analysis of Velocity Behavior for Collaborative Robots in Transient Contact Cases

Year: 2021 Volume: 15 Issue: 9 324 - 329 Pages

Abstract: In this paper, a suitable measurement setup is presented to conduct force and pressure measurements for transient contact cases at the example of lathe machine tending. Empirical measurements were executed on a selected collaborative robot’s behavior regarding allowable operating speeds under consideration of sensor- and workpiece-specific factors. Comparisons between the theoretic calculations proposed in ISO/TS 15066 and the practical measurement results reveal a basis for future research. With the created database, preliminary risk assessment and economic assessment procedures of collaborative machine tending cells can be facilitated.

Neural Network Supervisory Proportional-Integral-Derivative Control of the Pressurized Water Reactor Core Power Load Following Operation

Year: 2021 Volume: 15 Issue: 10 349 - 355 Pages

Abstract: This work presents the particle swarm optimization trained neural network (PSO-NN) supervisory proportional integral derivative (PID) control method to monitor the pressurized water reactor (PWR) core power for safe operation. The proposed control approach is implemented on the transfer function of the PWR core, which is computed from the state-space model. The PWR core state-space model is designed from the neutronics, thermal-hydraulics, and reactivity models using perturbation around the equilibrium value. The proposed control approach computes the control rod speed to maneuver the core power to track the reference in a closed-loop scheme. The particle swarm optimization (PSO) algorithm is used to train the neural network (NN) and to tune the PID simultaneously. The controller performance is examined using integral absolute error, integral time absolute error, integral square error, and integral time square error functions, and the stability of the system is analyzed by using the Bode diagram. The simulation results indicated that the controller shows satisfactory performance to control and track the load power effectively and smoothly as compared to the PSO-PID control technique. This study will give benefit to design a supervisory controller for nuclear engineering research fields for control application.

Automatic Classification of the Stand-to-Sit Phase in the TUG Test Using Machine Learning

Year: 2021 Volume: 15 Issue: 11 446 - 450 Pages

Abstract: Over the past several years, researchers have shown a great interest in assessing the mobility of elderly people to measure their functional status. Usually, such an assessment is done by conducting tests that require the subject to walk a certain distance, turn around, and finally sit back down. Consequently, this study aims to provide an at home monitoring system to assess the patient’s status continuously. Thus, we proposed a technique to automatically detect when a subject sits down while walking at home. In this study, we utilized a Doppler radar system to capture the motion of the subjects. More than 20 features were extracted from the radar signals out of which 11 were chosen based on their Intraclass Correlation Coefficient (ICC > 0.75). Accordingly, the sequential floating forward selection wrapper was applied to further narrow down the final feature vector. Finally, five features were introduced to the Linear Discriminant Analysis classifier and an accuracy of 93.75% was achieved as well as a precision and recall of 95% and 90% respectively.

On the Algorithmic Iterative Solutions of Conjugate Gradient, Gauss-Seidel and Jacobi Methods for Solving Systems of Linear Equations

Year: 2021 Volume: 15 Issue: 11 64 - 69 Pages

Abstract: In this paper, efforts were made to examine and compare the algorithmic iterative solutions of conjugate gradient method as against other methods such as Gauss-Seidel and Jacobi approaches for solving systems of linear equations of the form Ax = b, where A is a real n x n symmetric and positive definite matrix. We performed algorithmic iterative steps and obtained analytical solutions of a typical 3 x 3 symmetric and positive definite matrix using the three methods described in this paper (Gauss-Seidel, Jacobi and Conjugate Gradient methods) respectively. From the results obtained, we discovered that the Conjugate Gradient method converges faster to exact solutions in fewer iterative steps than the two other methods which took much iteration, much time and kept tending to the exact solutions.

Design and Construction of an Impulse Current Generator for Lightning Strike Experiments

Year: 2021 Volume: 15 Issue: 11 315 - 318 Pages

Abstract: There has been a rising trend in using impulse current generators to investigate the lightning strike protection of materials including aluminum and composites in structures such as wind turbine blade and aircraft body. The focus of this research is to present an impulse current generator built in the High Voltage Lab at Mississippi State University. The generator is capable of producing component A and D of the natural lightning discharges in accordance with the Society of Automotive Engineers (SAE) standard, which is widely used in the aerospace industry. The generator can supply lightning impulse energy up to 400 kJ with the capability of producing impulse currents with magnitudes greater than 200 kA. The electrical circuit and physical components of an improved impulse current generator are described and several lightning strike waveforms with different amplitudes is presented for comparing with the standard waveform. The results of this study contribute to the fundamental understanding the functionality of the impulse current generators and present an impulse current generator developed at the High Voltage Lab of Mississippi State University.

Comparative Study of Affricate Initial Consonants in Chinese and Slovak

Year: 2021 Volume: 15 Issue: 9 757 - 760 Pages

Authors:
Maria Istvanova

Abstract: The purpose of the comparative study of the affricate consonants in Chinese and Slovak is to increase the awareness of the main distinguishing features between these two languages taking into consideration this particular group of consonants. We determine the main difficulties of the Slovak learners in the process of acquiring correct pronunciation of affricate initial consonants in Chinese based on the understanding of the distinguishing features of Chinese and Slovak affricates in combination with the experimental measuring of voice onset time (VOT) values. The software tool Praat is used for the analysis of the recorded language samples. The language samples contain recordings of a Chinese native speaker and Slovak students of Chinese with different language proficiency levels. Based on the results of the analysis in Praat, we identify erroneous pronunciation and provide clarification of its cause.

Emotion Detection in Twitter Messages Using Combination of Long Short-Term Memory and Convolutional Deep Neural Networks

Year: 2021 Volume: 15 Issue: 9 438 - 445 Pages

Authors:
B. Golchin
N. Riahi

Abstract: One of the most significant issues as attended a lot in recent years is that of recognizing the sentiments and emotions in social media texts. The analysis of sentiments and emotions is intended to recognize the conceptual information such as the opinions, feelings, attitudes and emotions of people towards the products, services, organizations, people, topics, events and features in the written text. These indicate the greatness of the problem space. In the real world, businesses and organizations are always looking for tools to gather ideas, emotions, and directions of people about their products, services, or events related to their own. This article uses the Twitter social network, one of the most popular social networks with about 420 million active users, to extract data. Using this social network, users can share their information and opinions about personal issues, policies, products, events, etc. It can be used with appropriate classification of emotional states due to the availability of its data. In this study, supervised learning and deep neural network algorithms are used to classify the emotional states of Twitter users. The use of deep learning methods to increase the learning capacity of the model is an advantage due to the large amount of available data. Tweets collected on various topics are classified into four classes using a combination of two Bidirectional Long Short Term Memory network and a Convolutional network. The results obtained from this study with an average accuracy of 93%, show good results extracted from the proposed framework and improved accuracy compared to previous work.

Efficient Pre-Processing of Single-Cell Assay for Transposase Accessible Chromatin with High-Throughput Sequencing Data

Year: 2021 Volume: 15 Issue: 10 126 - 131 Pages

Abstract: The primary tool currently used to pre-process 10X chromium single-cell ATAC-seq data is Cell Ranger, which can take very long to run on standard datasets. To facilitate rapid pre-processing that enables reproducible workflows, we present a suite of tools called scATAK for pre-processing single-cell ATAC-seq data that is 15 to 18 times faster than Cell Ranger on mouse and human samples. Our tool can also calculate chromatin interaction potential matrices and generate open chromatin signal and interaction traces for cell groups. We use scATAK tool to explore the chromatin regulatory landscape of a healthy adult human brain and unveil cell-type specific features, and show that it provides a convenient and computational efficient approach for pre-processing single-cell ATAC-seq data.

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