bluuebunny/crossref_metadata_2025 huggingface dataset:
Emergency Department Admissions of Children with Chest Pain before and during COVID-19 Pandemic
Authors: Lubrano Riccardo , Martucci Vanessa , Marcellino Alessia , Sanseviero Mariateresa , Sinceri Alessandro , Testa Alessia , Frasacco Beatrice , Gizzone Pietro , Del Giudice Emanuela , Ventriglia Flavia , Bloise Silvia
Published: January 2023

Objectives: We compared the number of accesses, causes, and instrumental evaluations of chest pain in children between the pre-COVID-19 era and the COVID-19 period and analyzed the assessment performed in children with chest pain, highlighting unnecessary examinations. Methods: We enrolled children with chest pain admitted to our emergency department between January 2019 and May 2021. We collected demographic and clinical characteristics and findings on physical examinations, laboratory tests, and diagnostic evaluations. Then, we compared the number of accesses, causes, and instrumental assessments of chest pain between the pre-COVID-19 era and the COVID-19 era. Results: A total of 111 patients enrolled (mean age: 119.8 ± 40.48 months; 62 males). The most frequent cause of chest pain was idiopathic (58.55%); we showed a cardiac origin in 4.5% of the cases. Troponin determination was performed in 107 patients, and the value was high only in one case; chest X-rays in 55 cases and echocardiograms in 25 cases showed pathological findings, respectively, in 10 and 5 cases. Chest pain accesses increased during the COVID-19 era (p < 0.0001), with no differences in the causes of chest pain between the two periods. Conclusions: The increase in accesses for chest pain during the COVID-19 pandemic confirms that this symptom generates anxiety among parents. Furthermore, our findings demonstrate that the evaluation of chest pain is still extensive, and new chest pain assessment protocols in the pediatric age group are needed.
Prevalence and Risk Factors of Asthma in Children and Adolescents in Rabigh, Western Saudi Arabia
Authors: Alahmadi Turki S. , Hegazi Moustafa A. , Alsaedi Hani , Hamadallah Hanaa , Atwah Ali F. , Alghamdi Abdulrahman A. , Altherwi Haya M. , Alghamdi Majd S. , Albeshri Ebtihal M. , Alzanbaqi Moud I. , Bamakhish Abubaker M. , El-Baz Mohamed S.
Published: January 2023

The worldwide prevalence of asthma in children is variable. The different epidemiological definitions of asthma, the use of various methods of measurement, and the environmental variations between countries are responsible for such different prevalence rates. This study has been performed to identify the prevalence/risk factors of asthma in Saudi children/adolescents in Rabigh. A cross-sectional epidemiological survey has been conducted using the validated Arabic version of the “International Study of Asthma and Allergies in Childhood questionnaire”. Data on the sociodemographic characteristics of participants and risk factors of asthma have also been collected. Three hundred and forty-nine Children/adolescents with an age range of 5–18 years have been randomly selected for an interview from public places and houses in different regions of Rabigh City. The prevalence rates of physician-diagnosed asthma, any wheezing, and wheezing in the last 12 months among children/adolescents (mean age: 12.22 ± 4.14 years) have remarkably increased in association with the rapidly developing industrialization of Rabigh from previously recorded rates of 4.9%, 7.4%, and 6.4% in the only study that has previously been conducted in Rabigh in 1998 to 31.5%, 23.5%, and 14.9%, respectively. The univariate analysis has detected some significant risk factors for asthma. However, in younger aged children (5–9 years), allergic rhinitis, associated chronic illnesses, and viral respiratory infection-induced wheezing have remained significant risk factors of any wheezing. Drug allergy, exposure to dust, and viral respiratory infection-induced wheezing have persisted as significant risk factors for wheezing in the last 12 months. Eczema in the family, exposure to perfumes/incense, and viral respiratory infection-induced wheezing have remained as significant risk factors of physician-diagnosed asthma. The results of this survey should be useful in future targeted preventive plans/measures with special attention to improving air quality to limit the progressive increase in asthma prevalence in Rabigh, as well as in other similar industrial communities.
Tablet-Based Praxis Developed for Children in Primary Education Studying Natural Sciences and Mathematics
Authors: Ricoy María-Carmen , Sánchez-Martínez Cristina
Published: January 2023

Information and Communication Technologies are now a common feature in classroom activities. The aim of this study was to present praxis developed for the tablet for use by primary education students (aged 6–12) studying the natural sciences and mathematics. This research is qualitative and follows the narrative-ethnographic approach. The study sample consisted of 120 primary education students and 52 educational blogs. The results and conclusions reveal praxis that is rarely innovative or ludic. The bulk of tablet-based activities were for natural sciences classes rather than mathematics, and the most common practice with the tablet in the natural sciences was information searching and content exploration. The most widely used apps were the Google search engine, YouTube and the tablet’s default apps (camera, image and video editor). Course content in the natural sciences focused on living beings and states of matter, and the activities developed for children to do on the tablet aimed to foster learning through discovery, exploration and enquiry. In mathematics, a traditional methodological approach was apparent in children’s use of the tablet for typical activities related to units of measurement.
Dental Age Estimation Using Deep Learning: A Comparative Survey
Authors: Mohamed Essraa Gamal , Redondo Rebeca P. Díaz , Koura Abdelrahim , EL-Mofty Mohamed Sherif , Kayed Mohammed
Published: January 2023

The significance of age estimation arises from its applications in various fields, such as forensics, criminal investigation, and illegal immigration. Due to the increased importance of age estimation, this area of study requires more investigation and development. Several methods for age estimation using biometrics traits, such as the face, teeth, bones, and voice. Among then, teeth are quite convenient since they are resistant and durable and are subject to several changes from childhood to birth that can be used to derive age. In this paper, we summarize the common biometrics traits for age estimation and how this information has been used in previous research studies for age estimation. We have paid special attention to traditional machine learning methods and deep learning approaches used for dental age estimation. Thus, we summarized the advances in convolutional neural network (CNN) models to estimate dental age from radiological images, such as 3D cone-beam computed tomography (CBCT), X-ray, and orthopantomography (OPG) to estimate dental age. Finally, we also point out the main innovations that would potentially increase the performance of age estimation systems.
Numerical Assessment of Terrain Relief Influence on Consequences for Humans Exposed to Gas Explosion Overpressure
Authors: Skob Yurii , Yakovlev Sergiy , Korobchynskyi Kyryl , Kalinichenko Mykola
Published: January 2023

This study aims to reconstruct hazardous zones after the hydrogen explosion at a fueling station and to assess an influence of terrain landscape on harmful consequences for personnel with the use of numerical methods. These consequences are measured by fields of conditional probability of lethal and ear-drum injuries for people exposed to explosion waves. An “Explosion Safety®” numerical tool is applied for non-stationary and three-dimensional reconstructions of the hazardous zone around the epicenter of the explosion of a premixed stoichiometric hemispheric hydrogen cloud. In order to define values of the explosion wave’s damaging factors (maximum overpressure and impulse of pressure phase), a three-dimensional mathematical model of chemically active gas mixture dynamics is used. This allows for controlling the current pressure in every local point of actual space, taking into account the complex terrain. This information is used locally in every computational cell to evaluate the conditional probability of such consequences for human beings, such as ear-drum rupture and lethal outcome, on the basis of probit analysis. To evaluate the influence of the landscape profile on the non-stationary three-dimensional overpressure distribution above the Earth’s surface near the epicenter of an accidental hydrogen explosion, a series of computational experiments with different variants of the terrain is carried out. Each variant differs in the level of mutual arrangement of the explosion epicenter and the places of possible location of personnel. The obtained results indicate that any change in working-place level of terrain related to the explosion’s epicenter can better protect personnel from the explosion wave than evenly leveled terrain, and deepening of the explosion epicenter level related to working place level leads to better personnel protection than vice versa. Moreover, the presented coupled computational fluid dynamics and probit analysis model can be recommended to risk-managing experts as a cost-effective and time-saving instrument to assess the efficiency of protection structures during safety procedures.
Cyclic Behavior of FRP Strengthened Beam-Column Joints under Various Concrete Damage Levels
Authors: Al-Rousan Rajai , Nusier Osama , Abdalla Khairedin , Alhassan Mohammad , Vougioukas Emmanouil A. , Stamos Athanassios A. , Lagaros Nikos D.
Published: January 2023

This paper is intended to examine the efficiency of utilizing the FRP composite material with an externally bonded technique in enhancing the behavior of the damaged B-C joints and controlling their failure mode using the NLFEA approach. At first, the modeled Beam-Column joint was validated as per the previously-attained experimentally-attained results. Later, the model was widened to experiment with the impact of axial-column load and the concrete compressive strength on the reinforced and un-reinforced models with FRP. To run the experiment, there were three cases of applying the axial column load: no load applied (0%), applying 25%, applying 50%, and applying 75%, while the concrete compressive strength degradation level was (0% damage), (25% damage), and (50% damage). All models were evaluated for structural performance, considering: the failure mode, stresses distribution, and the ultimate capacities in pulling and pushing with its corresponding displacements. However, the horizontal load-displacement hysteretic loops and envelopes, stiffness degradation, displacement ductility, and energy dissipation were reported. The experimental results revealed that using FRP to externally-reinforce B-C joints improved overall cyclic performance, as the FRP caused a rise in the ultimate load capacity, horizontal displacement, ductility of displacement, and displacement energy dissipation, while it slowed down the stiffness degradation. In addition, the FRP material converted the failure mode of the region between the joint and column from brittle to ductile due to the formation of a plastic hinge only on the side of the beam when the axial column load exceeded 25%. It must be noticed that when the column’s axial load is less than 25%, the ultimate capacity of axial load and resultant deflection is solely improved. However, it has been stated that increasing the column’s axial loading by 25% increases the resulting stiffness degradation by 3% for undamaged joints, which further increases by 16% for each increased damage level. In contrast, the absorbed energy is increased by 170% under axial loading, increasing by 25%, which is reduced to only one-fourth under the various damage levels. Generally, the resulting observations help specialized engineers retrofit appropriate B-C joints in already-standing buildings due to their accuracy.
Safe and Timely Delivery of Essential Surgical Care for Skin Cancer in a Pandemic
Authors: Jackson Cullison Stephanie R. , Celen Arda , Doudican Nicole A. , Carucci John A. , Stevenson Mary L.
Published: January 2023

Many surgical practices closed at the onset of the COVID-19 pandemic. We implemented operational changes to safely continue treating patients with cutaneous tumors during the pandemic. This study seeks to evaluate the impact of pandemic-based operational changes on safety, access, and treatment. Here, we report results from a retrospective study from a single academic office-based surgical practice that provided treatment to patients with skin cancer between November 2019 and September 2020. Time to treatment, tumor area, and upstaging after treatment were compared among patients seen “pre-pandemic” (November 2019 to March 2020), during the “pause” (March 2020 to June 2020), and in the “reopening” (June 2020 to September 2020). One-way ANOVA or Fisher Exact analyses were performed, and p < 0.05 was considered significant. Our study included 691 patients (22–101 years old) with a total of 912 tumors. No cases of COVID-19 transmission occurred during the study period. The time from consultation to treatment was reduced during the pause and reopening periods relative to pre-pandemic (p ≤ 0.002), and the average Mohs post-operative defect size remained unchanged throughout the study period (p = 0.75). Consistent with the prioritization of higher-risk tumors in the pandemic peak, a significant reduction in the treatment of basal cell carcinoma tumors was noted during the pause (p = 0.01), and cutaneous squamous cell carcinoma tumors were upstaged more frequently after treatment (p < 0.001). Our findings demonstrate that practice modifications can permit essential surgical care to be delivered safely to patients with high-risk skin cancers during a pandemic.
A Drought Dataset Based on a Composite Index for the Sahelian Climate Zone of Niger
Authors: Garba Issa , Abdourahamane Zakari Seybou , Mirzabaev Alisher
Published: January 2023

Agricultural drought monitoring in Niger is relevant for the implementation of effective early warning systems and for improving climate change adaptation strategies. However, the scarcity of in situ data hampers an efficient analysis of drought in the country. The present dataset was created for agricultural drought characterization in the Sahelian climate zone of Niger. The dataset comprises the three-month scale and monthly time series of a composite drought index (CDI) and their corresponding drought classes at a spatial resolution of 1 km2 for the period 2000–2020. The CDI was generated from remote sensing data, namely CHIRPS (Climate Hazards Group InfraRed Precipitation with Stations), normalized difference vegetation index (NDVI) and land surface temperature (LST) from MODIS (Moderate Resolution Imaging Spectroradiometer). A weighing technique combining entropy and Euclidian distance was applied in the CDI derivation. From the present dataset, the extraction of the CDI time series can be performed for any location of the study area using its geographic coordinates. Therefore, seasonal drought characteristics, such as onset, end, duration, severity and frequency can be computed from the CDI time series using the theory of runs. The availability of the present dataset is relevant for the socio-economic assessment of drought impacts at small spatial scales, such as district and household level. This dataset is also important for the assessment of drought characteristics in remote areas or areas inaccessible due to civil insecurity in the country as it was entirely generated from remote sensing data. Finally, by including temperature data, the dataset enables drought modelling under global warming.
LGCM and PLS-SEM in Panel Survey Data: A Systematic Review and Bibliometric Analysis
Authors: Mohd Ghazali Zulkifli , Wan Yaacob Wan Fairos , Wan Omar Wan Marhaini
Published: January 2023

The application of Latent Growth Curve Model (LGCM) and Partial Least Square Structural Equation Modeling (PLS-SEM) has gained much attention in panel survey studies. This study explores the distributions and trends of LGCM, and PLS-SEM used in panel survey data. It highlights the gaps in the current and existing approaches of PLS-SEM practiced by researchers in analyzing panel survey data. The integrated bibliometric analysis and systematic review were employed in this study. Based on the reviewed articles, the LGCM and PLS-SEM showed an increasing trend of publication in the panel survey data. Though the popularity of LGCM was more outstanding than PLS-SEM for the panel survey data, LGCM has several limitations such as statistical assumptions, reliable sample size, number of repeated measures, and missing data. This systematic review identified five different approaches of PLS-SEM in analyzing the panel survey data namely pre- and post-approach with different constructs, a path comparison approach, a cross-lagged approach, pre- and post-approach with the same constructs, and an evaluation approach practiced by researchers. None of the previous approaches used can establish one structural model to represent the whole changes in the repeated measure. Thus, the findings of this paper could help researchers choose a more appropriate approach to analyzing panel survey data.
Merkel Cell Carcinoma in Kidney Transplant Recipients
Authors: Wu Henry H. L. , Pye Isobel , Chinnadurai Rajkumar
Published: January 2023

Merkel cell carcinoma (MCC) is an uncommon form of skin neoplasm with poor histological differentiation and an aggressive disease process, leading to high recurrence and mortality. There are multiple risk factors in which being in an immunocompromised state is a significant factor, and the discovery of Merkel cell polyomavirus (MCPyV) since 2008 has strengthened causal associations between MCC and immunosuppression. Individuals who have undergone kidney transplantation are therefore more susceptible to having MCC, secondary to post-transplant immunosuppression which plays a vital role in reducing the risk of transplant kidney rejection. Over recent years a rise in the incidence of MCC following kidney transplantation is noted, with increased reporting of such cases. Whilst localized MCC is observed, MCC metastasis to the lymphatic system, brain, bone, liver, lung, and heart has been previously observed in patients with transplanted kidneys. Kidney metastasis is less common and has been only reported in recent years with greater frequency. The management of aggressive, metastatic MCC has historically been palliative, and prognosis is poor. Recently, the use of immune checkpoint inhibitors for metastatic MCC in multi-center phase II clinical trials have shown promising survival outcomes and have been approved for use in countries such as the United States as a first-line treatment. In this review we will explore the potential pathophysiological processes of MCC manifesting post-kidney transplantation. We will then evaluate the epidemiology of MCC within the context of kidney transplantation, before discussing the various clinical presentations, diagnostic measures, surveillance strategies, and current treatment options as well as future directions to best manage MCC in kidney transplant recipients.
The Deceptive COVID-19: Lessons from Common Molecular Diagnostics and a Novel Plan for the Prevention of the Next Pandemic
Authors: Mouliou Dimitra S.
Published: January 2023

The COVID-19 pandemic took place during the years 2020–2022 and the virus, named SARS-CoV-2, seems likely to have resulted in an endemic disease. Nevertheless, widespread COVID-19 has given rise to several major molecular diagnostics’ facts and concerns that have emerged during the overall management of this disease and the subsequent pandemic. These concerns and lessons are undeniably critical for the prevention and control of future infectious agents. Furthermore, most populaces were introduced to several new public health maintenance strategies, and again, some critical events arose. The purpose of this perspective is to thoroughly analyze all these issues and the concerns, such as the molecular diagnostics’ terminologies, their role, as well as the quantity and quality issues with a molecular diagnostics’ test result. Furthermore, it is speculated that society will be more vulnerable in the future and prone to emerging infectious diseases; thus, a novel preventive medicine’s plan for the prevention and control of future (re)emerging infectious diseases is presented, so as to aid the early prevention of future epidemics and pandemics.
Correlations of the Osteoporosis Self-Assessment Tool for Asians (OSTA) and Three Panoramic Indices Using Quantitative Ultrasound (QUS) Bone Densitometry
Authors: Kiswanjaya Bramma , Bachtiar-Iskandar Hanna H. , Yoshihara Akihiro
Published: January 2023

This study aimed to evaluate the correlation between the Osteoporosis Self-Assessment Tool for Asians (OSTA) and three panoramic indices in relation to z-score and t-score values using quantitative ultrasound (QUS) bone densitometry. The sensitivity, specificity, and area under the curve (AUC) of the OSTA index were also measured using the QUS tool to evaluate the method’s performance in identifying people at risk of osteoporosis. The study employed a cross-sectional design with 387 participants (190 men, 197 women). Patients’ mandibular cortical indexes (MCI), mandibular cortical widths (MCW), and panoramic mandibular indexes (PMI) were measured from panoramic images. The sensitivity, specificity, and AUC were calculated using an OSTA index cutoff of ≤−1 and a t-score of ≤−1.0 for the QUS bone densitometry. The coefficient correlation of the OSTA index with the z-score (r = −0.563, p < 0.001) and t-score (r = −0.740, p < 0.001) shows a higher value than the MCI, MCW, and PMI, per the QUS. The sensitivity, specificity, and AUC values with a cutoff t-score of ≤−1.0 per the QUS in men was 90%, 50%, and 0.812, and in women, 96.8%, 30%, and 0.862. The OSTA index is a simple method that can be used in general dental practice.
Detection of the Altitude and On-the-Ground Objects Using 77-GHz FMCW Radar Onboard Small Drones
Authors: Başpınar Ömer Oğuzhan , Omuz Berk , Öncü Ahmet
Published: January 2023

Small drones are being utilized by researchers for applications such as object tracking, imaging and remote sensing as they have become more available, inexpensive and mobile with the advancements in sensor and UAV technologies. They can be equipped with sensors such as cameras and radars. Radars can be used onboard for navigation aid by detecting range and velocity, as well as for radar imaging applications. Although they are used in the latter commonly, radars can be used in navigation aid as well since they are barely affected by weather conditions or smoke. FMCW radars are suitable for drones since they can be lightweight and can detect range and velocity. Therefore, an FMCW radar-equipped drone system is designed and implemented for UAV positioning applications. A postprocessing algorithm is developed for detecting the altitude above ground level as well as the amount of reflection coming from the material on the ground surface, and a range compensation method is proposed to improve the performance of the algorithm. The results of a field experiment showed that the radar system and the postprocessing algorithm can be used for drone-based airborne positioning applications. Altitude values obtained with the radar postprocessing are in agreement with the altitude of the drone. Reflections coming from the metal objects are distinguished from those coming from the ground. With the range compensation method, minimum detectable altitude value is improved and the magnitude of ground reflections obtained from different altitudes became similar. The proposed system and algorithm can be utilized in navigation and in landing aid applications.
Coalition Game Based Distributed Clustering Approach for Group Oriented Unmanned Aerial Vehicle Networks
Authors: Zhang Mengge , Li Jie , Wu Xinning , Wang Xiangke
Published: January 2023

Clustering is an effective solution to improve the management efficiency of large-scale systems. One one hand, UAVs performing the same task have a similar moving tendency. One the other hand, the network topology of the UAV swarms is dynamically changing. Considering the above two aspects, our main contributrons are designing a group-oriented distributed clustering algorithm based on the coalition game that couples task attributes and communication attributes. The clustering goal is to divide UAVs performing the same task into one cluster and make each cluster have more UAVs under the cluster size limits, thus improving communication efficiency. The proposed algorithm comprehensively considers the task group information and communication link stability as the coalition value. UAVs decide whether to leave their current coalition based on coalition values. Through periodic parallel switch operations selection, UAVs are divided into the desired clustering structure. Simulations verify that our clustering algorithm is effective and better than the existing ones, especially in communication link stability, cluster numbers, and load balance.
A Novel Linkable Ring Signature on Ideal Lattices
Authors: Cao Chengtang , You Lin , Hu Gengran
Published: January 2023

In this paper, a novel linkable ring signature scheme is constructed. The hash value of the public key in the ring and the signer’s private key are based on random numbers. This setting makes it unnecessary to set the linkable label separately for our constructed scheme. When judging the linkability, it is necessary to determine whether the number of the intersections of the two sets reaches the threshold related to the number of the ring members. In addition, under the random oracle model, the unforgeability is reduced to the SVPγ problem. The anonymity is proved based on the definition of statistical distance and its properties.
Two-Sample Tests Based on Data Depth
Authors: Shi Xiaoping , Zhang Yue , Fu Yuejiao
Published: January 2023

In this paper, we focus on the homogeneity test that evaluates whether two multivariate samples come from the same distribution. This problem arises naturally in various applications, and there are many methods available in the literature. Based on data depth, several tests have been proposed for this problem but they may not be very powerful. In light of the recent development of data depth as an important measure in quality assurance, we propose two new test statistics for the multivariate two-sample homogeneity test. The proposed test statistics have the same χ2(1) asymptotic null distribution. The generalization of the proposed tests into the multivariate multisample situation is discussed as well. Simulations studies demonstrate the superior performance of the proposed tests. The test procedure is illustrated through two real data examples.
A Comparative Study of the Effects of Distance Learning and Face-to-Face Learning during the COVID-19 Pandemic on Learning Mathematical Concepts in Primary Students of the Kingdom of Bahrain
Authors: Alabdulaziz Mansour Saleh , Tayfour Enas Anwar
Published: January 2023

The main objective of this study is to compare the effectiveness of face-to-face learning and distance learning in helping fourth-grade primary students learn mathematical concepts. The data were collected from 120 fourth-grade students selected purposively and divided into two groups: a control group comprising 60 students, who used a face-to-face programme in their third grade, and an experimental group comprising 60 students, who used a distance learning programme in their third grade. A diagnostic test was used to measure their understanding of previous mathematical concepts. The current research revealed two interesting results: First, there were no statistically significant differences (p-value < 0.05) in rounding and ordering numbers, space concept, perimeter concept, and graphs between the face-to-face mode and distance learning mode, where students’ results were almost similar. Second, there were statistically significant differences (p-value < 0.05) in the concepts of expanding pictures of numbers (verbal, analytic, and standard), compare numbers, basic arithmetic operations, units of measurement, geometric shapes, sides, and data visualisation in favour of the group of students who were taught in a face-to-face learning mode.
Use of Arduino in Primary Education: A Systematic Review
Authors: García-Tudela Pedro Antonio , Marín-Marín José-Antonio
Published: January 2023

In the last two decades, technological advances have been spectacular, and their transcendence has touched all areas of society. Specifically, in the field of education, these advances have allowed projects and approaches such as computational thinking to be taken up more strongly through interdisciplinary visions such as the STEM subjects and technological devices such as Arduino. The main objective of this article is to analyse the uses of Arduino and the achievements it has attained at primary-education level. To this end, a systematic review was carried out in the SCOPUS and Web of Science databases. The methodology used was the PRISMA statement and the SALSA framework. In accordance with the exclusion criteria applied, nine scientific papers from the last seven years were obtained. The qualitative software ATLAS.ti was used to extract the results. These papers reveal that the most commonly used methodology for incorporating the Arduino board into teaching is problem based learning (PBL) in the context of STEM subjects. In addition, programming environments, such as Scratch, and other electronic components have been used, which have enabled the development of computational thinking and the acquisition of technological knowledge, among other achievements.
Engagement Assessment for the Educational Web-Service Based on Largest Lyapunov Exponent Calculation for User Reaction Time Series
Authors: Nikulchev Evgeny , Gusev Alexander , Gazanova Nurziya , Magomedov Shamil , Alexeenko Anna , Malykh Artem , Kolyasnikov Pavel , Malykh Sergey
Published: January 2023

Contemporary digital platforms provide a large number of web services for learning and professional growth. In most cases, educational web services only control access when connecting to resources and platforms. However, for educational and similar resources (internet surveys, online research), which are characterized by interactive interaction with the platform, it is important to assess user engagement in the learning process. A fairly large body of research is devoted to assessing learner engagement based on automatic, semi-automatic, and manual methods. Those methods include self-observation, observation checklists, engagement tracing based on learner reaction time and accuracy, computer vision methods (analysis of facial expressions, gestures, and postures, eye movements), methods for analyzing body sensor data, etc. Computer vision and body sensor methods for assessing engagement give a more complete objective picture of the learner’s state for further analysis in comparison with the methods of engagement tracing based on learner’s reaction time, however, they require the presence of appropriate sensors, which may often not be applicable in a particular context. Sensory observation is explicit to the learner and is an additional stressor, such as knowing the learner is being captured by the webcam while solving a problem. Thus, the further development of the hidden engagement assessment methods is relevant, while new computationally efficient techniques of converting the initial signal about the learner’s reaction time to assess engagement can be applied. On the basis of the hypothesis about the randomness of the dynamics of the time series, the largest Lyapunov exponent can be calculated for the time series formed from the reaction time of learners during prolonged work with web interfaces to assess the learner’s engagement. A feature of the proposed engagement assessment method is the relatively high computational efficiency, absence of high traffic loads in comparison with computer vision as well as secrecy from the learner coupled with no processing of learner’s personal or physical data except the reaction time to questions displayed on the screen. The results of experimental studies on a large amount of data are presented, demonstrating the applicability of the selected technique for learner’s engagement assessment.
Empirical Evidence to Support a Nudge Intervention for Increasing Online Engagement in Higher Education
Authors: Brown Alice , Basson Marita , Axelsen Megan , Redmond Petrea , Lawrence Jill
Published: January 2023

Student engagement is recognised as being a critical factor linked to student success and learning outcomes. The same holds true for online learning and engagement in higher education, where the appetite for this mode of learning has escalated worldwide over several decades, and as a result of COVID-19. At the same time teachers in higher education are increasingly able to access and utilise tools to identify and analyse student online behaviours, such as tracking evidence of engagement and non-engagement. However, even with significant headway being made in fields such as learning analytics, ways in which to make sense of this data, and to utilise data to inform interventions and refine teaching approaches, continue to be areas that would benefit from further insights and exploration. This paper reports on a project that sought to investigate whether low levels of student online engagement could be enhanced through a course specific intervention strategy designed to address student engagement with online materials in a regional university. The intervention used course learning analytics data (CLAD) in combination with the behavioral science concept of nudging as a strategy for increasing student engagement with online content. The study gathered qualitative and quantitative data to explore the impact of nudging on student engagement with 187 students across two disciplines, Education and Regional/Town Planning. The results not only revealed that the use of the nudge intervention was successful in increasing the levels of engagement in online courses but also revealed that the prerequisites for nudging were needed in order to increase success rates. The paper points to the value for the broader awareness, update, and use of learning analytics as well as nudging at a course, program, and institutional level to support student online engagement.
Changing the Narratives of Physics-Learning in Secondary Schools: The Role of Culture, Technology, and Locational Context
Authors: Oladejo Adekunle Ibrahim , Okebukola Peter Akinsola , Akinola Victor Olu , Amusa Jamiu Oluwadamilare , Akintoye Hakeem , Owolabi Tunde , Shabani Juma , Olateju Taibat Tejumola
Published: January 2023

This study is concerned with the persistent underperformance of secondary school students in Nigeria in physics. The study was conducted in two phases. Phase one was a survey of difficult concepts in physics, while phase two explored the potency of culturo-techno-contextual approach (CTCA) in breaking the barriers to meaningful learning of refractive indices, which ranked the most difficult concept in phase one of the study. A total of 1621 SS3 students from Nigeria and Ghana participated in the survey phase. The second phase employed a mixed-methods approach (quasi-experimental and interviews) with a total of 205 SS1 students. The control group was taught with the lecture method and had 96 students (54 males; 42 females), while the experimental group, taught with CTCA, had 109 students (65 females; 44 males). Both groups had a pretest and posttest using the achievement test in refractive indices; treatment lasted four weeks. Data gathered in the survey were analyzed using mean rank analysis, and refractive indices was perceived as the most difficult to learn. Phase two data were analyzed using one-way ANCOVA since intact classes were used. The result obtained showed that the experimental group performed better (mean for experimental = 15.49; control 11.97; F (1, 202) = 64.48; p < 0.01)) than the control group. Implications of the study are highlighted and the need for further studies is recommended.
Exploring LoRa and Deep Learning-Based Wireless Activity Recognition
Authors: Xiao Yang , Chen Yunfan , Nie Mingxing , Zhu Tao , Liu Zhenyu , Liu Chao
Published: January 2023

Today’s wireless activity recognition research still needs to be practical, mainly due to the limited sensing range and weak through-wall effect of the current wireless activity recognition based on Wi-Fi, RFID (Radio Frequency Identification, RFID), etc. Although some recent research has demonstrated that LoRa can be used for long-range and wide-range wireless sensing, no pertinent studies have been conducted on LoRa-based wireless activity recognition. This paper proposes applying long-range LoRa wireless communication technology to contactless wide-range wireless activity recognition. We propose LoRa and deep learning for contactless indoor activity recognition for the first time and propose a more lightweight improved TPN (Transformation Prediction Network, TPN) backbone network. At the same time, using only two features of the LoRa signal amplitude and phase as the input of the model, the experimental results demonstrate that the effect is better than using the original signal directly. The recognition accuracy reaches 97%, which also demonstrate that the LoRa wireless communication technology can be used for wide-range activity recognition, and the recognition accuracy can meet the needs of engineering applications.
Development of Bidirectional Pulsed Power Supply and Its Effect on Copper Plating Effect of Printed Circuit Board Via-Filling
Authors: Chen Wenguang , Wang Shoutao , Liu Zhijian , Wei Caiyi , Peng Yuanyuan
Published: January 2023

A bidirectional pulse power supply with continuously adjustable forward parameters 8 V/20 A and reverse parameters 20 V/50 A was designed using DSP (Digital Signal Processor), and the bidirectional pulse power supply was used to test copper plating on printed circuit boards with filled via holes. The effects of frequencies, pulse width ratios of forward and reverse currents, and current densities on the copper plating effect were investigated by the single variable method and were compared with DC copper plating. The experimental results showed that compared with DC power supply, the bidirectional pulse power supply had a better effect and a faster speed on via-filling copper plating, and can also reduce the use of additives, which is in line with green development. The parameters of the pulse affected the plating effect to varying degrees. In this solution system, the optimal parameters for bidirectional pulse plating are frequency 1 kHz, forward pulse current density 4 ASD (Ampere per Square Decimeter) with 50% duty cycle, and reverse pulse current density 16 ASD with 2.5% duty cycle.
A Wire-Bonded Patch Antenna for Millimeter Wave Applications
Authors: Bogdan Grzegorz , Sobolewski Jakub , Bajurko Paweł , Yashchyshyn Yevhen , Oklej Jan , Ostaszewski Dariusz
Published: January 2023

Wire bonds are one of the most common interconnects used in microelectronics; however, their application to millimeter wave monolithic microwave integrated circuits (MMICs) may severely decrease the overall system performance due to transmission loss, radiation loss, and impedance mismatch. The goal of this work was to optimize a wire-bonded patch antenna to minimize losses and maximize the gain in the frequency range from 81 to 83 GHz. Optimization was based on electromagnetic simulations of different variants of the wire bond. Results show that the optimized structure demonstrates two major advantages. Firstly, it does not require any external matching network; hence, it can be directly connected to a contact pad of an MMIC die. Secondly, the wire bond radiation effect is utilized to enhance the patch antenna gain at the broadside direction.
Drive System Inverter Modeling Using Symbolic Regression
Authors: Glučina Matko , Anđelić Nikola , Lorencin Ivan , Baressi Šegota Sandi
Published: January 2023

For accurate and efficient control performance of electrical drives, precise values of phase voltages are required. In order to achieve control of the electric drive, the development of mathematical models of the system and its parts is often approached. Data-driven modeling using artificial intelligence can often be unprofitable due to the large amount of computing resources required. To overcome this problem, the idea is to investigate if a genetic programming–symbolic regressor (GPSR) algorithm could be used to obtain simple symbolic expressions which could estimate the mean phase voltages (black-box inverter model) and duty cycles (black-box compensation scheme) with high accuracy using a publicly available dataset. To obtain the best symbolic expressions using GPSR, a random hyperparameter search method and 5-fold cross-validation were developed. The best symbolic expressions were chosen based on their estimation performance, which was measured using the coefficient of determination (R2), mean absolute error (MAE), and root mean squared error (RMSE). The best symbolic expressions for the estimation of mean phase voltages achieved R2, MAE, and RMSE values of 0.999, 2.5, and 2.8, respectively. The best symbolic expressions for the estimation of duty cycles achieved R2, MAE, and RMSE values of 0.9999, 0.0027, and 0.003, respectively. The originality of this work lies in the application of the GPSR algorithm, which, based on a mathematical equation it generates, can estimate the value of mean phase voltages and duty cycles in a three-phase inverter. Using the obtained model, it is possible to estimate the given aforementioned values. Such high-performing estimation represents an opportunity to replace expensive online equipment with a cheaper, more precise, and faster approach, such as a GPSR-based model. The presented procedure shows that the symbolic expression for the accurate estimation of mean phase voltages and duty cycles can be obtained using the GPSR algorithm.
An Improved SVM with Earth Mover’s Distance Regularization and Its Application in Pattern Recognition
Authors: Feng Rui , Dong Haitao , Li Xuri , Gu Zhaochuang , Tian Runyang , Li Houde
Published: January 2023

A support vector machine (SVM) aims to achieve an optimal hyperplane with a maximum interclass margin and has been widely utilized in pattern recognition. Traditionally, a SVM mainly considers the separability of boundary points (i.e., support vectors), while the underlying data structure information is commonly ignored. In this paper, an improved support vector machine with earth mover’s distance (EMD-SVM) is proposed. It can be regarded as an improved generalization of the standard SVM, and can automatically learn the distribution between the classes. To validate its performance, we discuss the necessity of the structural information of EMD-SVM in the linear and nonlinear cases, respectively. Experimental validation was designed and conducted in different application fields, which have shown its superior and robust performance.
A Survey on Resource Management for 6G Heterogeneous Networks: Current Research, Future Trends, and Challenges
Authors: Alhashimi Hayder Faeq , Hindia MHD Nour , Dimyati Kaharudin , Hanafi Effariza Binti , Safie Nurhizam , Qamar Faizan , Azrin Khairul , Nguyen Quang Ngoc
Published: January 2023

The sixth generation (6G) mobile communication system is expected to meet the different service needs of modern communication scenarios. Heterogeneous networks (HetNets) have received a lot of attention in recent years due to their potential as a novel structure for evolutionary networks. When compared to homogeneous networks, HetNets provide more potential for spatial spectrum reuse and higher quality of service (QoS). However, effective resource management (RM) solutions are essential to prevent interference and accomplish spectrum sharing due to mutual interference. This paper presents a comprehensive review of resource management in 6G HetNets. The study aims to give crucial background on HetNets to aid in the creation of more effective methods in this field of study. First, a detailed examination of recent work is presented in resource management aspects such as power allocation, user association, mode selection, and spectrum allocation. Second, we identify the most severe challenges associated with the current resource management methods and propose suitable solutions. Finally, several open issues and emerging areas of research are highlighted.
Machine Learning Techniques for Non-Terrestrial Networks
Authors: Giuliano Romeo , Innocenti Eros
Published: January 2023

Traditionally, non-terrestrial networks (NTNs) are used for a limited set of applications, such as TV broadcasting and communication support during disaster relief. Nevertheless, due to their technological improvements and integration in the 5G 3GPP standards, NTNs have been gaining importance in the last years and will provide further applications and services. 3GPP standardization is integrating low-Earth orbit (LEO) satellites, high-altitude platform stations (HAPSs) and unmanned aerial systems (UASs) as non-terrestrial elements (NTEs) in the NTNs within the terrestrial 5G standard. Considering the NTE characteristics (e.g., traffic congestion, processing capacity, oscillation, altitude, pitch), it is difficult to dynamically set the optimal connection based also on the required service to properly steer the antenna beam or to schedule the UE. To this aim, machine learning (ML) can be helpful. In this paper, we present novel services supported by the NTNs and their architectures for the integration in the terrestrial 5G 3GPP standards. Then, ML techniques are proposed for managing NTN connectivity as well as to improve service performance.
A Magnetic Field Containment Method for an IPT System with Multiple Transmitting Coils Based on Reflective Properties
Authors: Yang Xu , Yang Junfeng , Fan Jing , Wang Bao , Li Dingzhen
Published: January 2023

Inductive power transfer (IPT) systems with multiple transmitting coils are mainly used in specific scenarios, such as IPT sharing platforms and dynamic wireless charging of electric vehicles, etc. However, it faces problems of electromagnetic field leakage and low efficiency. A new magnetic field containment method based on reflective properties is proposed to solve the above shortcomings. Firstly, the reflective properties and performance figures of the IPT system with a unified passive compensation network are described and derived. Then, an S−LCL topology appropriate for the time−varying coupling IPT system is presented, where the IPT system’s transmitter consists of multiple coils that are compatible with one or more moving receivers and is powered by an inverter. Then, magnetic field focusing, power transfer and overall efficiency are analyzed and simulated. Finally, an experimental prototype is built to validate the feasibility of the proposed system. The experimental results show that the proposed method can increase the power transfer of the coupled transmitting coil and reduce the magnetic field leakage of the standby transmitting coils without complex shielding measures, switch, position detection and communication circuits.