Reviewerly/exHarmony huggingface dataset:
Artificial Intelligence Registration of Image Series Based on Multiple Features

Multi-source image series vary in quality. To fuse the feature information of multi-source image series, it is necessary to deeply explore the relevant registration and fusion techniques. The existing techniques of image registration and fusion lack a unified multi-feature-based algorithm framework, and fail to achieve real-time accurate registration. To solve these problems, this paper probes into the artificial intelligence (AI) registration of image series based on multiple features. Firstly, the Harris corner detector was selected to extract the corners of multi-source image series, before explaining and improving the flow of the algorithm. In addition, the deep convolutional neural network (DCNN) VGG16 was improved to extract the features of multi-source image series. Finally, the spatial transformation network was adopted to pre-register the image series, and the image series was deformed and restored based on the region-constrained moving least squares. The proposed registration algorithm was proved effective through experiments.
The Impact of Raising Awareness of Arabic and English Word Order Differences on Arabs’ English Use

English is a language with a rigid word order, whereas Arabic is more flexible. Canonical English word order is often a challenge for users whose first language is flexible. This study explores how Arabic learners transfer their knowledge of Arabic word order styles into the English language, and it compares Arabic learners’ use of English word order before and after raising learners’ awareness of Arabic and English word order differences. The significance of this study is manifested in its employment of both Error Analysis and Contrastive Analysis to determine priorities for efforts. The study employed an action research design to investigate the impact of adapting Galperin’s teaching model alongside explicit teaching of differences in Arabic and English word order. Four Arabic English language teachers and 142 Saudi students participated in the present study. The participating students were taking a beginning-level English course at a Saudi university. Through mixed-method approaches, the findings of the pretest and posttest showed that some learners used their knowledge and experience of Arabic standard and slang word order to compose sentences in English. This study concludes that the intervention helps Arabic learners avoid committing word order errors, as the posttest scores are better than the pretest scores at a statistically significant level.
The Provision of Safety in Water Areas: Legal Issues

Threats in water areas have forced the legislator to address the issues related to the safety of people staying in these areas, who are required to exercise due diligence in order to protect the life and health of themselves and others. Due diligence is a fundamental factor in providing security. Along with diligence, to perform water rescue it was appropriate to conduct an analysis of threats, including an identification of the places where the safety of people using water areas for swimming, bathing, practising water sports, and recreation, could be endangered. The analysis was conducted by entities who are professionals in the field of water security, i.e. the Police and the bodies authorised to perform water rescue.
Overview of Anonymous Authentication in Mobile Communication

With the development of mobile communication, while users enjoy higher-value services, they are always concerned about whether their privacy is leaked. Therefore, it is very important to ensure anonymity in the service process. This paper briefly introduces the importance of anonymous authentication, summarizes the commonly used techniques of anonymous authentication such as group signature and ring signature, summarizes the typical anonymous authentication schemes and some existing problems, and points out that anonymous authentication will become the focus of research.
Threshold adaptation and XOR accumulation algorithm for objects detection

&lt;span&gt;Object detection, tracking and video analysis are vital and energetic tasks for intelligent video surveillance systems and computer vision applications. Object detection based on background modelling is a major technique used in dynamically objects extraction over video streams. This paper presents the threshold adaptation and XOR accumulation (TAXA) algorithm in three systematic stages throughout video sequences. First, the continuous calculation, updating and elimination of noisy background details with hybrid statistical techniques. Second, thresholds are calculated with an effective mean and gaussian for the detection of the pixels of the objects. The third is a novel step in making decisions by using XOR-accumulation to extract pixels of the objects from the thresholds accurately. Each stage was presented with practical representations and theoretical explanations. On high resolution video which has difficult scenes and lighting conditions, the proposed algorithm was used and tested. As a result, with a precision average of 0.90% memory uses of 6.56% and the use of CPU 20% as well as time performance, the result excellent overall superior to all the major used foreground object extraction algorithms. As a conclusion, in comparison to other popular OpenCV methods the proposed TAXA algorithm has excellent detection ability.&lt;/span&gt;
Corrigendum: Exercising With a Six Pack in Virtual Reality: Examining the Proteus Effect of Avatar Body Shape and Sex on Self-Efficacy for Core-Muscle Exercise, Self-Concept of Body Shape, and Actual Physical Activity

[This corrects the article DOI: 10.3389/fpsyg.2021.693543.].
Prospective English Teachers’ Knowledge on Mind Mapping

The purpose of this research was investigating prospective English teachers’ knowledge on mind mapping by using a questionnaire. There were 142 respondents from various semesters of their study in English Department, Faculty of Teacher Training and Education, in three cities in Indonesia, i.e., Medan, Sidoarjo, and Poso. The questionnaire consisted of 7 items of close and open-ended questions that asked about the prospective English teachers’ knowledge on mind mapping and its usage. Questionnaire was analyzed using descriptive quantitative research method. Result showed that almost 50% of the prospective English teachers have known about mind mapping. This bases result can be suggested to extend by analyzing its usage in another skills of English learned by these prospective teachers.&#x0D; &#x0D; Received: 31 October 2021 / Accepted: 24 December 2021 / Published: 5 March 2022
MERGING EPISTEMIC AND TEMPORAL MODELS: A HISTORY-FREE APPROACH

There are two approaches to merging temporal and epistemic models. The first one consists in starting with a temporal model and enriching it with epistemic dimension (as temporal epistemic logic), while the second one is supposed to start with an epistemic model introducing temporal dimension (dynamic epistemic logic, epistemic temporal logic). The proposed evolutionary epistemic model (EEM) is based on the standard epistemic model with an evolutionary relation. EEM captures knowledge changes in terms of the evolution of worlds included in different epistemic contexts. Unlike other temporal-epistemic models, EEM is free from the concept of history and enriched with quantification operators over the worlds’ evolution stages.
Design and Development of a VHF Telemetry Two-way Radio Device Network Downtime/Uptime Alerting Prototype

This paper presents the design and development of a VHF telemetry Two-way radio device network downtime/uptime alerting prototype. Telemetry network monitoring using VHF 2-way radio Streaming is a paradigm in networking management that has not been deployed. The framework enables continuous monitoring of the mobile and fixed access points of the mining fleet management Wi-Fi system (in the case of the Barrick Lumwana mine, Zambia). Considering the significance of real-time alerts in a mining facility, critical systems such as slope monitoring radars, mobile emergency alerts, and timely copper production reports must be monitored in real-time. The results for the performance warnings of the telemetry access points collectively accounted for a response alert time of 1999ms from the samples collected which translated to 0.29% compared to the SNMP system that registered a total of 689500ms for the samples collected which translates to 99.71% of the total response time of 691499ms. The results derived from the VHF 2-way radio telemetry prototype show that this system performs better than the traditional SNMP network monitoring system. We recommend that this IP network prototype is used in open-pit mines alongside Motorola telemetry two-way radios.
An Adaptive Fuzzy Neural Network Based On Progressive Gaussian Approximate Filter with Variable Step Size

The nonlinear filtering problem is a hot spot in robot navigation research. As an advanced method that can effectively improve the robustness and accuracy of the system, the progressive Gaussian approximate filter with variable step size (PGAFVS) still has some shortcomings, how to resolve the nonlinear filtering problem in the application of tightly coupled integration under the premise of the prior uncertainty and further promote robustness high measurement accuracy, which becomes the purpose of this paper. This paper formulates the processing of trajectory tracking measurement noise problem as a Kalman filtering procedure and the measurement noise covariance matrix in controller, is jointly estimated based on the progressive Gaussian approximate filter (PGAF), after that, PGAFVS can be deduced. Then we proposed an adaptive fuzzy and backpropagation neural network controller based on PGAFVS (AFNPGA-VS) that can improve the application of tightly coupled integration under the premise of the prior uncertainty and further promote robustness high measurement accuracy. The simulation results show that the proposed algorithm outperforms the state-of-the-art methods.
Hate speech’s double damage: A semi-automated approach toward direct and indirect targets

Democracies around the world have been facing increasing challenges with hate speech online as it contributes to a tense and thus less discursive public sphere. In that, hate speech online targets free speech both directly and indirectly, through harassments and explicit harm as well as by informing a vicious environment of irrationality, misrepresentation, or disrespect. Consequently, platforms have implemented varying means of comment-moderation techniques, depending both on policy regulations and on the quantity and quality of hate speech online. This study seeks to provide descriptive measures between direct and indirect targets in light of different incentives and practices of moderation on both social media and news outlets. Based on three distinct samples from German Twitter, YouTube, and a set of four news outlets, it applies semi-automated content analyses using a set of five cross-sample classifiers. Thereby, the largest amounts of visible hate speech online depict rather implicit devaluations of ideas or behavior. More explicit forms of hate speech online, such as insult, slander, or vulgarity, are only rarely observable and accumulate around certain events (Twitter) or single videos (YouTube). Moreover, while hate speech on Twitter and YouTube tends to target particular groups or individuals, hate speech below news articles shows a stronger focus on debates. Potential reasons and implications are discussed in light of political and legal efforts in Germany.
Mahasiswa Kesejahteraan Sosial FISIP USU Meningkatkan Minat Baca Anak Panti

The author did practicum II at the Ora Et Labora Nusantara Orphanage. The second practicum carried out by the author was to examine the problems experienced by orphans. The problems experienced by orphanages are the lack of reading culture so that they have difficulty in learning. Especially during the current pandemic, children prefer to spend time playing with their friends at the orphanage rather than taking the time to study. From this problem, the author is interested and has the aim of increasing interest in reading for orphans which is a mini project from this author on education to children. The author has a client (group) who is experiencing this problem. The group consists of children who are still in elementary school (SD). The author uses the stages of social groupwork in his research from the preparation stage to the termination stage. The method used is the Delphi method using Focus Group Discussion (FGD). After doing all the stages of social groupwork, the results are presented by the author so that the orphanage children can continue the reading culture so that they have no difficulty in learning at school.
Interlibrary loan developments at the National Library of Canada / Développements relatifs au prêt entre bibliothèques à la Bibliothèque nationale du Canada

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Developed High Scale Bagging Algorithm for E-Tourism Advising System

Filtering huge amounts of data is a very critical issue with the explosion of data over the web and cloud storage. A need to classify and sort these data is linked to that issue to facilitate data management and database building for various applications. Machine learning techniques are the most suitable to deal with such big data. One of the applications that can be implemented in machine learning is a tourist advising system that harvests data from tourism sites and aggregates different types of data about them (humidity, temperature, distance from user’s country, etc…) and classifies them. These data should be updated constantly, since the system provides real-time decision based on real-time data, where they are used later on by a bagging system to provide the user with suggested tourism sites with percentage to how suitable these sites according to the preferences submitted in addition to some other criteria.
A study of attitude of primary school teachers towards tribal children in Kalahandi district of Odisha

The present study is considered of two dimensions.The first dimension deals with the manifestation of teachers' attitude or influence of teachers' attitude on their behavior with children in and outside the classroom and involvement of teacher in different school activities.The focus is to study the impact of teacher's attitude as related in their behavior with children in teaching learning situation.A significant positive relationship between teacher's attitude and teacher behavior with children is found in the study.It is revealed that the positive attitude of teachers influences their behavior with tribal children positively.The study also found out that there is significant and positive relationship in between teachers' attitude and their involvement in school activities.Thus, it can be inferred that attitude influences the day to day activities of teacher in school.Positive attitude is also manifested in teachers' accountability, responsibility and alertness for rendering better and effective service.The Second dimension deals with relationship between teachers' attitude and students' achievement and perception of those teachers by students.The study found out significant and positive relationship between teachers' attitude and students' achievement and also with students' perception on teachers.It is also found out that there is significant and positive relationship between teachers' attitude and students' perception of teachers.Thus it can be inferred that teachers having positive attitudes were better perceived by the students and students taught by those teachers perform better in academic achievement.
Tobacco Spatial Data Intelligent Visual Analysis

A multi-module visualization framework is designed and a visual analysis system called TobaccoGeoVis is implemented to analyze tobacco spatial data efficiently. The proposed system provides a visualization technology for overlaying multiple graphics on a map to enrich the form of tobacco spatial data visualization. The system also adopts artificial intelligence algorithms and multi-view linkage interactive methods and provides flexible data-attribute field mapping and graphical parameter configuration to analyze tobacco spatial data. We demonstrated that the system is user-friendly and the applied visualization methods are effective using cases selected from the three sets of data.
Parents’ Mathematics Anxiety and Their Contribution to Mathematics Education

This study aims to investigate the mathematics anxieties of primary and middle school parents and their contributions to the teaching of mathematics. The data of the research were collected using “Mathematics Anxiety Scale for Parents,” “Parents’ Contribution to the Mathematics Education Scale,” and “Parent Form,” developed by the researcher. This research was designed as a survey study, and obtained data were analyzed using SPSS 16. Some of the conclusions that are achieved in this investigation are as follows: mathematics anxiety of parents were found to be low whereas their participation in their children's mathematics education was high, there was no difference in the mathematics anxiety of the children in accordance with the grade level they were enrolled in, the participation of primary school parents in mathematics education was found to be higher than that of the middle school parents, there was no difference between mathematics anxiety of mothers and fathers, mothers participated in the mathematics education more than fathers did, mathematics anxiety of parents decreased as their graduation and mathematics knowledge increased, thus, their participation in mathematics education increased, there was a high and inverse relationship between mathematics anxiety and participation in mathematics education.
Development of Mathematics Digital Creative (Magic) Book for Elementary School

The digitalization of education is a logical consequence of changing times. No one could have predicted that technology would be adopted so quickly by industry and society. The Covid-19 pandemic has cause students, teachers and schools to carry out teaching and learning activities by relying on digital technology. The use of e-book is becoming a trend because it is more environmentally friendly and more economical. The purpose of this research is to develop a 4C-oriented Mathematics Digital Creative (Magic) Book for elementary school students to determine the development process, feasibility, and effectiveness of its use. The results of the research show that the users gave a positive rating for the MAGIC Book. The use of digital modules provides benefits in learning, especially in online learning.
THE EFFECTIVENESS OF USING EDUCATIONAL GAMES AS A MEDIA FOR TEACHING ENGLISH TO CHILDREN WITH SPECIAL NEEDS

Realizing how vital English language education is today. Because children with special needs also have the right to learn like normal children, and because children with special needs will prefer games to games, the authors choose to use new teaching media in the form of educational games. The educational games used in this research are the Bingo alphabet, Charades, and Braille. Where all three are related to supporting students' abilities in learning English. This study aims to: Describe and analyze educational games and how they affect students. The author uses a case study method to describe and analyze three educational games at a private school in Tanjungpandan. The findings of this study are: (1) Students can improve their English skills through educational games that have several values that are by student learning which make the game more suitable to be used as a medium for learning English in the classroom for students. With special needs; (2) There are some visible results through the game. First, learning styles suit students so that they feel interested in learning. Second, motivation and background affect each student's learning progress, especially English.
Aspects of readiness of higher education teachers for continuing professional development

The article highlights the necessity to increase attention to the formation of the readiness of teachers of higher education institutions for continuing professional self-improvement. The readiness of teachers for professional self-improvement is considered a multifaceted personal-professional formation, structurally represented by the unity of functionally interconnected components: motivational-value, organizational-activity; emotional and volitional; information-cognitive, reflexive-evaluative. The criteria for diagnosing this phenomenon are differentiated: awareness of the necessity for purposeful continuing professional self-improvement; theoretical training, the level of professionally oriented knowledge, practical and operational training, the formation of practical skills and abilities of professional self-improvement. A set of individual psychological qualities important for continuing professional self-improvement and future professional activity in general; focus on self-analysis, self-assessment of professional improvement are analyzed. The levels of teachers’ readiness for continuing professional self-improvement are determined and characterized: critical, passive, basic, optimal, creative. We also defined several aspects of analysis and self-analysis of professional activity, training through the organization of personality-oriented interactive activities, updating teachers’ professional experience, ensuring a selective attitude to problems, educational material, focusing on the formation and implementation of the program of personal and professional self-development.
Analysis of earthquake hazards prediction with multivariate adaptive regression splines

&lt;p&gt;&lt;span&gt;Earthquake research has not yielded promising results, either in the form of causes or revealing the timing of their future events. Many methods have been developed, one of which is related to data mining, such as the use of hybrid neural networks, support vector regressor, fuzzy modeling, clustering, and others. Earthquake research has uncertain parameters and to obtain optimal results an appropriate method is needed. In general, several predictive data mining methods are grouped into two categories, namely parametric and non-parametric. This study uses a non-parametric method with multivariate adaptive regression spline (MARS) and conic multivariate adaptive regression spline (CMARS) as the backward stage of the MARS algorithm. The results of this study after parameter testing and analysis obtained a mathematical model with 16 basis functions (BF) and 12 basis functions contributing to the model and 4 basis functions not contributing to the model. Based on the level of variable contribution, it can be written that the epicenter distance is 100 percent, the magnitude is 31.1 percent, the location temperature is 5.5 percent, and the depth is 3.5 percent. It can be concluded that the results of the prediction analysis of areas in Lombok with the highest earthquake hazard level are Malaka, Genggelang, Pemenang, Tanjung, Tegal Maja, Senggigi, Mangsit. Meninting, and Malimbu.&lt;/span&gt;&lt;/p&gt;
IMPLEMENTING PREDICT OBSERVE EXPLAIN (POE) STRATEGY TO TEACH READING EXPOSITION TEXT

The purpose of this study was to investigate if POE (Predict, Observe, Explain) strategy influenced students' reading ability when reading an exposition text. This study was conducted using an experimental design. Purposive sampling was used to select the sample. The sample consisted of 42 students. The research instrument was a multiple-choice test with 40 questions about the exposition text. A t-test was used to analyze the data. Based on the independent sample t-test, the value of t- obtained was -6.793 at significance level p&lt;0.005 in the two-tailed testing and df=40, the critical value of t-table was 2.0210. Since the value of t-obtain (-6.793) was higher than t-table (2.0210) and p-value (0.00) was less than the α value (0.05), it meant that Predict, Observe, Explain strategy helped students learn quickly to understand the content of the text.