Reviewerly/exHarmony huggingface dataset:
Obstacles of Implementation of Dry Laboratories from the Science Teachers' Perspective in Na'our District

The current study aimed to identify the obstacles ofimplementation of dry laboratories from the science teachers' perspective in Na'our District.The study used the descriptive analytical method.To collect data, a questionnaire wasdeveloped.In its initial form, this questionnaire consisted of (50) items and in its final form (49) items They are divided into (5) fields: the computer lab equipment, (10) items, the curriculum: (11) items, the school administration: (9) items, the teacher's field: (11) items and the student's field: (8) items.The study population consisted of all science teachers in Na'our District, who were (92) male and female teachers -(47) male and (45) female teachers-according to the statistics of the Jordanian Ministry of Education for the academic year 2021/2022.The sample was chosen randomly as (59) male and female teachers accounted for (64%) of the study population.The results showed that thedegree of obstacles of implementation of virtual laboratories from the perspective of the science teachers in Na'our District was high, and the results of the study indicated that there were no statistically significant differences at the level of The significance (α≥0.05) in the obstacles to implementationof virtual laboratories from the perspective of science teachers in Na'our District was attributed to gender, scientific qualification and experience.The study introduced several recommendations, the most important of which is providing the appropriate infrastructure for the implementation of dry laboratories through qualified and trained human resources, as well as the required communication lines.Also, the need to prepare training programs for students, teachers and administrators in schools to make the most from technology in conducting dry experiments.Other recommendations were the Ministry initiative to develop policies and strategies for education based ontoday's requirements and scientific and technical development, and adopting educational and technological plans to utilize scientific transformations in comprehensive human development projects.
The Fluid Discontinuity Theory

Theoretical Physics is perhaps the only class of philosophies that has really enhanced and evolved itself to a lot of extent seeking clues towards the ultimate nature of reality. Stretching from the Theory of General Relativity and Quantum Physics, it’s been diversified with quite peculiar answers to multiple deep facets. However, still there is a significant fragment of Physics which is yet to be developed in that theoretical frame of system where the mathematical analysis turns in a more definitive role and thus, holds the intersection of certain other branches of the field and this area is Fluid Dynamics or Hydrodynamics. Although there is no question over some forsooth brilliant contributions in the regime but still, this discovery will deal with a nonpareil strand in order to fill some gaps which will determine new findings to lead the coming times much exclusively through the realm. The proposed discovery in this paper, being chronicle on the most primordial basis; is about quilting the distinction of waves as a whole in the fluid being in layered form and its impact via penetration of mass into those in form of respective disturbance in its fabrication of fundamental geometry. In other words, the idea proposed is about investigating and evolving the understanding of fluid discontinuity in distinctive extents forming geometrical patterns which is the idea that has also been undertaken to insights by some of the greatest Philosophers, Physicists, and Mathematicians of the last two centuries from Helmholtz to Lord Kelvin to Einstein but unfortunately it could not be attained in a full turn of deeper understanding in terms of Theoretical and Mathematical evolution as attempted by all these greatest forefathers of Sciences. In order to extract the idea with the overlap of modern mathematical integration, the entire formation of the defined system is taken into the account by establishing geometrical interpretations which will also develop more protean insights into the field and fill many further gaps in the classical regime of the Dynamics and gives a modern turn to it. The fabrication of the idea is systematically unfolded in terms of both Theoretical &amp; Mathematical engagements concerning to the respective structures taking place in form of different theories partaking in an evolutionary methodology.
Efficient Crime Analysis Based on Hybrid Approach by Combining Dynamic Time Wrapping Algorithm with K-Means Clustering Approach.

Abstract: Crime is a preeminent issue where the main concern has been worried by individual, the local area and government. Wrongdoing forecast utilizes past information and in the wake of investigating information, anticipate the future wrongdoing with area and time. In present days sequential criminal cases quickly happen so it is a provoking assignment to anticipate future wrongdoing precisely with better execution. Clustering different time series into similar groups is a challenging clustering task because each data point is an ordered sequence. The most common approach to time series clustering is to flatten the time series into a table, with a column for each time index (or aggregation of the series) and directly apply standard clustering algorithms like k-means. But this doesn’t always work well on Time Series Data. The paper focuses on combining the features of K-Means Clustering algorithm with Dynamic Time Wrapping Algorithm for efficient Crime prediction and analysis
A Study of the Education Teacher Performance Assessment (edTPA) in the United States and the Application of Social-Emotional Learning for Pre-Service Teachers

The quality of teachers, as an important factor influencing the quality of education, has become a major concern for countries in the 21st century. Improving the quality of teacher candidate preparation is an important foundation for improving the overall quality of the teaching force. The US government and Stanford University have developed a nationwide system of performance assessment standards for teacher candidates (the Education Teacher Performance Assessment, hereafter referred to as edTPA), or edTPA, with the aim of further improving the quality of basic education for teachers by strengthening their professionalism and increasing national competitiveness. The edTPA aims to further improve the quality of basic education and increase national competitiveness by strengthening the professionalism of teachers. This authentic assessment of teacher performance is an innovation and development of the traditional quantitative assessment, and a large number of experiments have proved that it can better predict the practical ability of teacher candidates in education and teaching, help them to make progress, and make their assessment educational and developmental. The assessment criteria also provide relevant guidance for the learning of social-emotional competencies in pre-service teacher education, and may also provide useful references for the development of expressive assessment for teacher candidates in China.
Emotional Attitudes towards the Components of the Digital Environment (Based on the Text Analysis of Network Comments)

One of the psychological effects of digitalization is the establishment of specific relationships between a person and the cyber environment and its components. The paper presents the results of a study of the emotional component of attitudes towards the components of the digital environment, carried out using emotive-predicate analysis, a new method of computer text processing implemented in TITANIS, an advanced social media text analysis tool. Using this method, it is possible to automatically extract descriptions of emotional situations from texts in which the components of the digital environment are the cause or subject of 68 emotional states. The texts of 2048 online videos posted in the Russian-language segment of YouTube served as the material for the analysis. According to the frequency of occurrence, emotional situations involving various components of the digital environment are quite typical for even thematically irrelevant online discussions. The components of the digital environment mentioned in non-thematic discussions as participants in emotional situations are classified into the following three groups: (1) general concepts of digital technologies; (2) digital devices; (3) activities mediated by digital technologies. The lexemes of the latter group, denoting various aspects of network communication, are included in the vast majority of descriptions of emotional situations involving the components of the digital environment, and six times more often as causes of emotions than as subjects of emotional states. In general, the emotional attitude towards the components of the cyber environment as a whole is characterized as balanced, without a noticeable predominance of negative or positive emotions. However, negative states are more often attributed to the components of the cyber environment as the subjects than as the causes of emotions. The practical significance of the described method of text analysis as a means of assessing the emotional component of attitudes towards the components of the digital environment is determined by the influence that affective reactions of users have on the demand for technical innovations and the direction of their development.
An Approach of Deep Learning Neural Network Model for Image Security

Abstract: Securing the Image and video data have applications in various fields like internet communication, multimedia systems, medical imaging, Telemedicine, and military communication. Watermarking protects digital intellectual property. It helps to prove the origin of an image and discourages unaccredited copies or distribution. The proposed method uses the concept of binding a secret message within another, ordinary, message. Our algorithm is used to unobtrusively hide a small message within the noisy regions of a larger image. Deep neural networks are simultaneously trained to create the hiding and revealing processes and are designed to specifically work as a pair. Different models are implemented to check the performance of the algorithm. The results are evaluated using 40,000 different types of images. With the state of art techniques like hiding the image in the least significant bits of the carrier image, our approach compresses and distributes the secret image’s representation across all of the available bits
Cooperative Multi-Agent Trajectory Generation with Modular Bayesian Optimization

We present a modular Bayesian optimization framework that efficiently generates time-optimal trajectories for a cooperative multi-agent system, such as a team of UAVs.Existing methods for multi-agent trajectory generation often rely on overly conservative constraints to reduce the complexity of this highdimensional planning problem, leading to suboptimal solutions.We propose a novel modular structure for the Bayesian optimization model that consists of multiple Gaussian process surrogate models that represent the dynamic feasibility and collision avoidance constraints.This modular structure alleviates the stark increase in computational cost with problem dimensionality and enables the use of minimal constraints in the joint optimization of the multi-agent trajectories.The efficiency of the algorithm is further improved by introducing a scheme for simultaneous evaluation of the Bayesian optimization acquisition function and random sampling.The modular BayesOpt algorithm was applied to optimize multi-agent trajectories through six unique environments using multi-fidelity evaluations from various data sources.It was found that the resulting trajectories are faster than those obtained from two baseline methods.The optimized trajectories were validated in real-world experiments using four quadcopters that fly within centimeters of each other at speeds up to 7.4 m/s.
Implementation of the Conversational Hybrid Design Model to Improve Usability in the FAQ

FAQ is an important part of a system because it is used to make it easier for users to solve problems faced by users. Some FAQ systems have even started using Chatbot technology to make it easier for users. Chatbots have been widely used as a medium for services in almost all fields. Starting from marketing, service systems, education, health, culture and entertainment. Various types of chatbots have sprung up, ranging from text-based like short messaging applications to voice-based ones. However, not all forms of chatbot designs have been successfully implemented in the FAQ system. Adjustments need to be made, especially considering the persona of the user. This research provides a solution by implementing a hybrid conversational design. Hybrid conversation design is accomplished by incorporating text, voice, and buttons into the chatbot interface. Conversation activities with this hybrid interface provide keywords that users may search for in the form of buttons. The hybrid design of the FAQ Chatbot is proven to be able to improve user usability compared to full text chatbots and full text FAQs. The increase in user usability is measured using UEQ, the results of which show an increase in usability from all existing aspects. However, the implementation of this hybrid design also has the consequence that the conversation management system must have structured initial information.&#x0D;
Academic Performance and Ability of Sixth Grade Students in Science and Technology and Life Education Under the New Normal

This study aimed to determine the Academic Performance and Competencies of Grade VI pupils in Technology andLivelihood Education at Basud Elementary School for School Year 2020-2021.The descriptive-correlational method of research was used to gather data to answer the problems of the study.The researcher used a teacher made test to determine the performance level of the male and female pupils.The findings revealed that the academic performance of the pupils is not significantly related with their competencies in the said areas. An action plan may be designed to improve the academic performance and competencies of the pupils in the four areas of Technology and Livelihood education.Based on the findings of the study, the researcher drawn the following conclusions: 1.) The pupils have satisfactory academic performance in Home Economics and Agriculture while very satisfactory academic performance in Industrial Arts and Information and Communication Technology. 2.) Majority of the pupils have acquired moving mastery to closely approximating mastery in their competencies relative to the four areas of Technology and Livelihood Education. 3.) The academic performance of the pupils and their competencies are not significantly related in Home Economics, Agriculture, Industrial Arts, and ICT. 4.) An action plan was proposed in order to improve the academic performance and competencies of the pupils in TLE.Based on the results and in the light of the findings and conclusions drawn, the following recommendations are proposed:1.) The teacher may consider additional intervention aside from the modular distance learning so as to supplement the learning of the pupils especially on the areas which require teacher-assisted instruction. 2.) The school heads may procure instructional materials and equipment that the teachers and pupils utilize in the actual conduct of the competencies contained in the four areas. 3.)The teacher may continually improve the systems and procedure in delivering their instruction regardless of the delivery modalities utilized so as to ensure the sustained academic performance and competencies of the pupils in TLE.4.) The action plan may be submitted to the concerned authorities for further evaluation and review prior to its implementation and adoption.5.) Further study may be conducted to include other intermediate pupils and making the scope wider in nature.
INNOVATIONS IN THE EDUCATIONAL PROCESS// ACADEMY JOURNAL ISSN 2733-0923, no. 1(19) (April 20, 2022)/ Chief Editor V. Klevtsov /Open European Academy of Public Sciences : Tallinn, Estonia, 2022 - P. 9-12.

The article is devoted to innovative technologies in the educational system. Innovative technologies significantly enrich the process of teaching foreign languages. The monotonous work is replaced by an intellectual creative search, during which a new type of personality is formed, active and ambitious, oriented to continuous self-education and development. A modern teacher should not only possess knowledge in the field of information and communication technologies (ICT) but also be an expert in their application in professional activities. Application efficiency of innovative technologies will depend on how creative the teacher is using them. It is widely known that ICT can’t replace the role of the teacher in the educational process. In this article, ICTs are presented only as an instrument for submitting material aimed at revealing the creative potential of the learner.
Leadership Skills of School Principals in the Directorate of Education in Jerash Governorate from the Point of View of Teachers

The current research aims to identify the leadership skills of school principals in the Directorate of Education in Jerash Governorate from the teachers' point of view. The researcher used the descriptive approach, where a questionnaire was designed as a tool for data collection and the research sample consisted of (105) male and female teachers in the schools of education in Jerash Governorate, and they were selected in the available way. The results indicated a (high) level of leadership skills for school principals in the Directorate of Education in Jerash Governorate from the teachers’ point of view, and the field (human skills) ranked first with a high degree, followed by the field (intellectual skills) in the second place with a high degree, followed by the field (technical skills) ) ranked third with a high degree. The results also indicated that there were no statistically significant differences (α = 0.05) due to the effect of the variables of gender and years of experience for the leadership skills of school principals in the Directorate of Education in Jerash Governorate from the teachers' point of view. Keywords: Leadership skills, teachers, school administrators DOI: 10.7176/JEP/13-17-17 Publication date: June 30 th 2022
Learning-Augmented Algorithms for Online Steiner Tree

This paper considers the recently popular beyond-worst-case algorithm analysis model which integrates machine-learned predictions with online algorithm design. We consider the online Steiner tree problem in this model for both directed and undirected graphs. Steiner tree is known to have strong lower bounds in the online setting and any algorithm’s worst-case guarantee is far from desirable. This paper considers algorithms that predict which terminal arrives online. The predictions may be incorrect and the algorithms’ performance is parameterized by the number of incorrectly predicted terminals. These guarantees ensure that algorithms break through the online lower bounds with good predictions and the competitive ratio gracefully degrades as the prediction error grows. We then observe that the theory is predictive of what will occur empirically. We show on graphs where terminals are drawn from a distribution, the new online algorithms have strong performance even with modestly correct predictions.
Learning Probably Approximately Complete and Safe Action Models for Stochastic Worlds

We consider the problem of learning action models for planning in unknown stochastic environments that can be defined using the Probabilistic Planning Domain Description Language (PPDDL). As input, we are given a set of previously executed trajectories, and the main challenge is to learn an action model that has a similar goal achievement probability to the policies used to create these trajectories. To this end, we introduce a variant of PPDDL in which there is uncertainty about the transition probabilities, specified by an interval for each factor that contains the respective true transition probabilities. Then, we present SAM+, an algorithm that learns such an imprecise-PPDDL environment model. SAM+ has a polynomial time and sample complexity, and guarantees that with high probability, the true environment is indeed captured by the defined intervals. We prove that the action model SAM+ outputs has a goal achievement probability that is almost as good or better than that of the policies used to produced the training trajectories. Then, we show how to produce a PPDDL model based on this imprecise-PPDDL model that has similar properties.
Formación política desde la educación básica en Chiclayo

The objective of this study was to evaluate the educational policy of citizen participation in regular basic education, aimed at the formation of a student political culture, in educational institutions in Chiclayo. It was proposed as a quantitative research, non-experimental design, descriptive cross-sectional type. Based on a sample made up of 298 fifth grade high school students in Educational Institutions of the Chiclayo District, who applied two questionnaires, one on educational policy of citizen participation, and another on political culture. Among the results, it was observed that 39% of the students presented a low level of citizen participation, from the perspective of knowledge and participatory intervention both inside and outside the institution. Likewise, 36% showed a regular level in political culture, in relation to the cognitive aspect, and high in the affective aspect. They did not know the mechanisms that exist to participate in public affairs, but despite this they showed interest in political issues. The implementation of an educational policy of citizen participation from regular basic education will contribute significantly to the formation of a student political culture in the educational institutions of Chiclayo.
Using Reinforcement Learning for Operating Educational Campuses Safely during a Pandemic (Student Abstract)

The COVID-19 pandemic has brought a significant disruption not only on how schools operate but also affected student sentiments on learning and adoption to different learning strategies. We propose CampusPandemicPlanR, a reinforcement learning-based simulation tool that could be applied to suggest to campus operators how many students from each course to allow on a campus classroom each week. The tool aims to strike a balance between the conflicting goals of keeping students from getting infected, on one hand, and allowing more students to come into campus to allow them to benefit from in-person classes, on the other. Our preliminary results show that reinforcement learning is able to learn better policies over iterations, and that different Pareto-optimal tradeoffs between these conflicting goals could be obtained by varying the reward weight parameter.
An Extraction and Representation Pipeline for Literary Characters

Readers of novels need to identify and learn about the characters as they develop an understanding of the plot. The paper presents an end-to-end automated pipeline for literary character identification and ongoing work for extracting and comparing character representations for full-length English novels. The character identification pipeline involves a named entity recognition (NER) module with F1 score of 0.85, a coreference resolution module with F1 score of 0.76, and a disambiguation module using both heuristic and algorithmic approaches. Ongoing work compares event extraction as well as speech extraction pipelines for literary characters representations with case studies. The paper is the first to my knowledge that combines a modular pipeline for automated character identification, representation extraction and comparisons for full-length English novels.