Reviewerly/exHarmony huggingface dataset:
Students’ Satisfaction with e-Learning in Saudi Higher Education during the COVID-19 Outbreak

During the COVID-19 pandemic, e-learning has been used as an alternative teaching approach to cover the academic vacuum produced by the pandemic’s new reality owing to countrywide school closures. The study aimed at investigating the students’ satisfaction level toward e-learning implementation during the COVID-19 outbreak. A quantitative research design, where 345 university undergraduate students from the different clusters (Health, Science, and Management) were surveyed regarding their satisfaction with e-learning. A self-administered questionnaire was developed and sent to participants for data collection. The validity and reliability of the questionnaire were determined. SPSS was used to understand and interpret the results of the research. To analyze the data, multiple statistical analyses were performed, including mean, standard deviations, and ANOVA. The study’s findings shows that students’ satisfaction level with e-learning platforms is generally medium, but with varying degrees from one item to another. The findings revealed no statistically significant differences in the use of e-learning at the level (α = 0.05) for gender. This study demonstrates that e-learning has grown in popularity among students all over the world, particularly during the COVID-19 pandemic lockdown period. However, there is a need of major reform of the curriculum in compliance with remote teaching and learning ideas. Faculty and student training toward the use of technology is also mandatory for continuous improvement for teaching best practices.
INFORMATION AND COMMUNICATION TECHNOLOGY APPLICATION MANAGEMENT SOLUTIONS IN TEACHING METHOD INNOVATION IN PRIMARY SCHOOLS IN THANH THUY DISTRICT, PHU THO PROVINCE TO MEET THE NEW GENERAL EDUCATION PROGRAM IN 2018

In the past time, the application of information and communication technology in teaching method innovation and application management of information and communication technology in teaching method innovation in primary schools in Thanh Thuy district, Phu Tho province’s response to the new general education program in 2018 has achieved certain results. From the survey and research on the current situation of information and communication technology application management in teaching method innovation in primary schools in Thanh Thuy district, Phu Tho province to meet the digital transformation era, analyzing the advantages and disadvantages, the reason for which the article has stated a system of solutions to manage information and communication technology application in teaching method innovation in primary schools in Thanh Thuy district, Phu Tho province to meet the new general education program in 2018. Keywords: Information and communication technology application management solutions; Innovating teaching methods; Primary schools; Thanh Thuy district, Phu Tho province; New general education program 2018.
Analysis Of Clean Water And Hot Water Needs Plumbing System In The Building

The plumbing system is an inseparable part of a multi-storey building. The plumbing system at the hotel is used to provide clean water and hot water needs. To meet the need for clean water in the design of an 8 floors building with a total of 45 inhabitants, an average number of 2,706 people per month and 100 visitors per day, a ground water tank capacity of 404.5 is required. m3 / and for the top water tank (Roof Tank) used a water reservoir of 21.59 m3. Based on the results of calculations for hot water needs where the toll of hot water needs per day is 12,900 liters including heat loss with 100% hotel occupancy and for heating time, it is obtained 9.79 hours / day using 2 units of heater heater 21.04 Kw
A Novel High-Speed Data Encryption Scheme for Internet of Medical Things Using Modified Elliptic Curve Diffie–Hellman and Advance Encryption Standard

The security of data in an IoT network is of utmost importance. The medical IoT devices need to implement the security protocols in the devices to safeguard the crucial information. This paper proposes a novel high-speed data encryption scheme using elliptic curve cryptography (ECC) for key generation, key length reduction, Diffie–Hellman key exchange, SHA-256 and advance encryption standard (AES). The proposed hybrid data encryption scheme begins with elliptic curve key generation. Each authorized user in the broadcast range generated a private key using ECC. The proposed key reduction algorithm reduces the size of the secret key generated. This key is exchanged efficiently between the broadcast members using Diffie–Hellman key exchange. Each user then generates their final encryption keys. These keys are encoded using SHA-256 algorithm for further security. These keys are then used to encrypt the data using AES algorithm and sent to the cloud. The intended receivers can check the identity of the sender and decrypt the data using their own keys. The proposed method also includes user identity authentication. The origin of the message is verified to authenticate the sender of the message. This implementation is apt for home automation applications where data collected by medical devices like Fitbit and watches need to be shared among multiple users. The proposed method is at par in providing security to the data in much less time. The throughput, key generation time, key length, encryption time, decryption time and memory usage, Avalanche effect are efficient in comparison to existing methods.
The Relation of Personality, Gender, and Achievement in Science Classes

The personality facets of 1911 students in a college science class taken primarily by future engineers and physical scientists were measured with the Big Five Inventory (BFI).The relation of personality to four measures of academic achievement were compared: high school GPA (HSGPA), ACT/SAT mathematics score, physics test average, and physics course grade.The Conscientiousness facet was the strongest predictor of achievement for HSGPA, test average, and grade, but not for ACT/SAT score.Personality explained more variance in college achievement measures than in high school measures.The personality facets explained 2% additional variance in test average over HSGPA and ACT/SAT and 3% in course grade for men; 5% additional variance in test average and 7% in course grade for women.
Mathematical Model of Screw Vacuum Pump Working Process

The screw vacuum pump combines high performance, low ultimate pressure and ability to create an oil-free vacuum. The calculation of the pump characteristics can be performed using mathematical modeling. The article considers main stages of creating a mathematical model: constructing the geometry of the rotors, calculating the dependence of the working cavity volume and the area of the suction and discharge windows on the angle of rotor rotation, determining the main directions of gas flows, calculating the dependence of pressure and temperature on the angle of rotor rotation. The thermodynamic model of the working process is based on gas state differential equations describing the laws of mass and energy conservation in control volumes, taking account of heat transfer and overflows. The classification of slotted channels in a screw pump is given, and a method for calculating gas backflows through them is proposed. The calculated dependences of the speed of action on the inlet pressure for various rotor speeds are presented. The developed model can be used for calculating the pumping characteristics of a screw vacuum pump at the design stage.
The Impact of Virtual Professional Development on ESL Teachers' Self-Efficacy Toward Teaching English Learners

Despite burgeoning use of teacher virtual professional development (VPD; Author, 2015), there is limited research specifically on VPD designed for English as a second language (ESL) teachers.This study examined if participation in a VPD program could improve ESL teachers' sense of self-efficacy toward working with English learners (ELs).A t-test and analyses of covariance (ANCOVA) were conducted with participant pre-and post-survey data (n=61).Results indicated a significant improvement in teachers' self-efficacy toward working with ELs, after completing the program.There was no difference in teacher self-efficacy improvement among different racial/ethnic groups or by location.
(p,α)-k anonymous algorithm based on dynamic data

At present, most privacy protection models only consider static data, and it is easy for attackers to deduce some privacy data through data tables. In view of the changing characteristics of data, this paper proposes a set of dynamic data processing strategies, which are processed according to whether the data appears for the first time and the frequency of occurrence, and the KL divergence is adopted in the process of calculating similarity. Based on the dynamic data processing strategy, this paper proposes a (p,α)-Sensitive k anonymity algorithm for dynamic data. Through the analysis of the experimental results, it can be seen that the algorithm can protect the privacy of dynamic data and increase a certain amount of data-availability.
Argentinian International Higher Education under COVID-19

Before the pandemic, the governance of international higher education in Argentina was complex but not perceived as an issue that needed urgent attention. COVID-19 re-kindled not only the field’s academic debates but also the need for strategies and proactive policy-making from the State. This chapter argues that the management of the pandemic activated three dimensions of the issue: first, a claim or appeal to the national state for the administration or management of the emergency and risk situation; secondly, a resurface of previous debates on the need for regulation of the transnational sector and finally, the necessary reactivation of regional arenas to promote cooperation or integration activities). This work focuses on the two critical issues for governance in international higher education: distance education and international scientific collaborations and present a comprehensive socio-historical background of each issue in Argentina to situate the state of the discussion and provides some key points (capabilities and challenges) for future policies on the issue. Finally, the chapter shows that the current situation demands an in-depth dialogue on persistent inequalities and internal asymmetries in the higher education sector and the need to redirect these debates as well as the centrality of the State as a key-player, while respecting the autonomy of institutions.
The Moderating Effects of the Use of Multiple Instructional Strategies on English Learners' Reading Performance

The purpose of this study was to examine if teachers' frequency of using four different instructional strategies (graphic organizers, scaffolding, interactive read aloud, and leveled questions) moderates the relationship of ELLs' reading performance between their pretest and posttest.A multilevel path analysis using structural equation modeling was employed.Thirty-six teachers and 386 third grade ELLs were recruited for this study.The overall findings revealed that the teachers' increased frequency of using each of the four instructional strategies could assist ELLs with better enhancing their reading performance.The findings further indicated that ELLs' reading performance should improve if their teachers used the four strategies simultaneously and increase their frequency of use.
Measuring Inferential Integrative Reasoning Using Modern Objective Measurement

We constructed a new taxonomy for inferential thinking, a construct called integrative inferential reasoning (IIR).IIR extends Pearson and Johnson's (1978) framework of text-implicit and script-implicit inferences, and integrates several other prominent literacy theories to form a unified inferential reasoning construct.We validated our construct using a researcher-made IIR instrument which was administered to 72 participants.Participants answered open-ended inference questions about various aspects of visual narratives presented in comic-strip format.We categorized participants' responses as exemplifying one of the levels of IIR: text-implicit, script-implicit, or a combination of both.We used item response models to validate the ordinal nature of IIR, and its structure.Specifically, we fit Masters' (1982) Partial Credit Model and obtained a Wright map, mean location data, fit statistics, and reliability estimates.Results confirmed that the IIR construct behaves ordinally.Additionally, age was found to be a reliable predictor of IIR, and item types (each modeled as a separate dimension) were found to have reasonable latent correlations between the dimensions.This research provides important insights for teaching and assessing narrative comprehension, and demonstrates a good example of using modern objective measurement methods.
A new approach to text feature extraction using BiReGU and capsule networks

Traditional single-model text feature representation methods lack multi-level representation of features and cannot extract global and local information well. To this end, the text uses a two-layer ReGU network (BiReGU) and a capsule network to extract the global semantic and local semantic features of the text respectively, combining attention mechanisms and interaction forms to obtain a more comprehensive multi-level feature representation of the text. In addition, the traditional capsule network dynamic routing algorithm suffers from the problem of noisy capsule interference. This paper proposes to reduce the weight of noisy capsules based on the attention mechanism and Capsule's feature extraction method, thus reducing the interference to subsequent capsules. Comparative experiments are conducted on a generic dataset and the experimental results demonstrate the effectiveness of the proposed method.
Circuit teaching simulation platform technology based on deep learning optimization

Like the existing software simulation experiment platform, the remote camera can also provide a realistic scene effect, giving the experiment user a sense of presence, thus greatly improving the quality and effectiveness of the experiment. It is verified and evaluated in the actual measurement environment that the research on the sampling method of the characteristic value samples is less involved. Thus, there is a certain gap between engineering practice and the application of instrument measurement. In order to solve the problems of less measurable nodes, less fault feature information and fault information from simulation in analog circuits, this paper chooses the low-frequency noise spectral density that can best reflect the fault feature information as the feature parameter through the study of circuit noise mechanism and noise superposition theorem. The paper also proposes an improved average period cross-spectrum method based on a low-frequency noise detection technology. With low-pass filter, low noise amplifier module, ADC sampling module and FPGA platform, the utilization rate of experimental facilities is high. Proved by experiments, the technology in this paper can reduce the number of facilities needed for the same experimental task, and reduce the cost of school laboratory construction and maintenance.
Applications of Blockchain Technology in Cyber Attacks Prevention

There had been umpteen cyber security concerns in the last decade with the attacks scourge being on the rise. These attacks can be mitigated using Blockchain Technology (BT) as an impenetrable technology to prevent data security breaches, integrity attack, digital identity attack, phishing attack, and injection attack, among others. BT is applicable in various industries regarding cyber security to mitigating recent attacks around the globe. Data decentralization, encryption, network monitoring, and contract negotiation guarantees data security and integrity in blockchain, thereby increasing resilience toward attacks to ensure data confidentiality and integrity. Blockchain applications in digital identity prevent inaccessibility, data insecurity, and fraudulent identities with key benefits to organizations, users, and IoT coordination systems. Decentralized Identifier (DID) ensures higher security in electronic identities management and storage when users sign up to a self-determined data platform. Data immortality accompanied with a DID such as attestations and secure DID using cryptography are some of the security features blockchain offers. BT offers the best method to mitigating injection attack through classical best practices by keeping up with all the threat vectors. Injection attack has been confirmed to be a challenge as BT continues to evolve. Strong security perimeter is developed around applications using blockchain technology.
Quantitative Measurements Extraction and Annotation Optimization in Whole Slide Imaging

The adoption of digital pathology is growing rapidly, demanding new tools for decision support and better workflow. The improvements to the software and hardware are promoting a remote-ready environment where the glass slides are acquired in multiple distributed places, sent to a central repository, and reviewed in a collaborative modus operandi. Many of these solutions are already operating in the Cloud making use of standard Web interfaces and applications. However, the review process of a slide is still an arduous process due to the high resolution of images, requesting the integration of artificial intelligence tools for decision support. However, the huge number of pathologies evaluated and their specificities make this process hard and the regulatory authorities only recently started approving the first solutions for clinical use. This article presents a research platform, fully integrated within a PACS ecosystem compliant with the DICOM standard and built using pure web technologies. The platform was used in a scientific project to help pathologists annotate cases for the development of artificial intelligence tools. Preliminary results in the annotation of Helicobacter Pylori samples scanned at 40x magnification show that manual annotation is impracticable for pathologists and requests more automated approaches that are capable of improving the current annotation workflows.
Pose Estimation Algorithm Derived From 3D Optical Flow

calculation method of 3D optical flow is proposed in this paper, which uses the aligned depth image and grayscale image to calculate the speed of pixel movement in 3D space. According to the obtained 3D optical flow, a direct normal pose estimation algorithm combining depth image information is proposed. The algorithm uses the gray value and the compensated depth value as the observation quantity to construct the least-squares problem, and solves the pose by means of graph optimization. The algorithm considers regions with large depth gradients and adds the compensated depth to the cost function. And according to the performance of 3D optical flow in the experiment, it is believed that the weight of the gray value should be higher than that of the depth value in the optimization problem. Compared with the direct method pose estimation algorithm, the algorithm proposed in this paper makes full use of the depth information. Experiments on the TUM dataset show that the improved pose estimation algorithm is more accurate than the original algorithm in scenes with better depth image quality, and the accuracy improvement is relatively more obvious in low-texture scenes.
Self-Sensing Processor Systems: Robust sensors and actuator systems

High-performance systems that form the compute backbone of the IoT are increasingly challenged by the stringent compute requirements of emerging cloud-native applications. This is particularly evident for modern machine-learning and artificial intelligence applications. As an example, consider the neural network (NN) training problem. NNs for natural language processing applications already require training a trillion parameters (shown in <xref ref-type="fig" rid="fig1">Figure 1</xref>), thereby imposing a 100&#x00D7; growth in compute requirements, all within a year <xref ref-type="bibr" rid="ref1">[1]</xref>&#x0021
Accurate and efficient traffic participant detection based on optimized features and multi-scale localization confidence

Traffic participant detection, which locates targets participating in road traffic such as vehicles and humans, is a critical research goal in autonomous driving and intelligent transportation technology, in which targets of various scales are challenging to handle. To address this problem, we propose an accurate and efficient traffic participant detector called FM-RepPoints to increase detection precision of multi-scale targets via optimized features and localization confidence. We first present a parameter-efficient backbone Dilated-ResNeSt to extract complicated urban scene features with less inference time. An adaptive attention module is then added to calibrate the features according to the corresponding targets. Moreover, we set the multi-scale localization confidence for traffic participants of various scales based on the sensitivity analysis. The proposed network outperforms the basic network by 3.3 points mAP; the accuracy of vehicles and humans is improved by 4.5% and 2.1%, respectively. Compared with state-of-the-art algorithms, the proposed method achieves the highest accuracy while maintaining average inference speed, thereby accomplishing the best speed-accuracy trade-off.
Some observations on distance measurement words in Finnish and Swedish

The paper presents an overview of words denoting units of measurement in the Finnish and Swedish languages. Comparative studies between these two languages seem relevant because they have been used in the neighboring regions and countries with a long history of political, cultural, and people-to-people interaction. First, the study describes metalexemes of space and distance in Swedish and Finnish. Next, using thesauri, topical dictionaries and corpora, the study applies the combination of quantitative and qualitative approaches to identify and evaluate pragmatics and communication context for utterances of measure words. Then, the paper identifies several categories of measurement words in the languages, taking etymology into consideration, such as traditional measures, SI-units, foreign units and analyzes their use in the contexts of corpora representing modern discourse. The paper highlights the differences and similarities in how Swedish and Finnish use different categories of the vocabulary items. The detailed analysis of contexts provides observations about collocations and topics of news where these measure words occur. Moreover, the study addresses the impact of Swedish and Russian on Finnish, due to the historical and political circumstances. According to the data studied, the study infers that Finnish and Swedish use all types of measurement words. However, the frequency, contexts of the occurrences and speech situations differ. Some categories tend to be used in a limited amount of topics, while others have no restrictions in usage. The study is expected to contribute to practical dimensions of working with the languages, namely teaching and translation.