Reviewerly/exHarmony huggingface dataset:
The Paradoxical Relationship between Principals’ Transformational Leadership Styles and Teachers’ Motivation

Leadership and motivation are inseparable.Principals' transformational leadership has been a focus on education for over a decade because of the crucial role it plays in influencing the performance of teachers and students.There is a call for principals who are more transformational and less transactional.Prior research has established that principals who adopt the transformational leadership style can motivate their teachers to ensure the higher academic achievement of students.Nonetheless, there is limited study on the relationship between the transformational leadership styles of principals and teacher motivation in most developing countries such as Ghana.Using the Multifactor Leadership Questionnaire (MLQ 6S), this study investigates the four dimensions of transformational leadership; idealized influence, inspirational motivation, intellectual stimulation, and individualized consideration of teacher motivation in some selected basic schools in Eastern Region, Ghana.Findings indicate that although principals self-reported higher transformational leadership style, it had no significant relationship with teacher motivation.Three of the four dimensions of transformational leadership negatively correlated with teacher motivation ("idealized influence, inspirational motivation, and intellectual stimulation).Teachers also reported low motivation.Further analysis revealed that principals equally practiced the transactional leadership style and less of the laissez-faire leadership style.The laissezfaire leadership style negatively correlated with teacher motivation.School administrators are encouraged to organize more leadership training programs for principals, and ensure teachers are adequately motivated to improve the academic performance of students.
CrESt Use Cases

Abstract In this chapter, we present three use cases that are used throughout this book to demonstrate the various systems engineering methods presented: vehicle platooning, adaptable and flexible factories, and autonomous transport robots. The use cases are chosen from real-life industrial tasks and exhibit all software engineering challenges that are specific to the development of collaborative embedded systems.
An Experiment on Teaching English as a Foreign Language in Romanian Schools Using Mastery Learning Strategies

The last 29 years of education in the democratic system in Romania have shown that the use of mastery learning strategies is not present in our nowadays teaching-learning process. Even though studies were carried out to show the effectiveness of these strategies teachers still feel reluctant whether to implement a mastery learning model or not. The subject emphasized in this paper is related to the implementation of a mastery learning strategy during the teaching of English as a second language in a public school in Bucharest, Romania.&#x0D; Keywords: education, mastery learning, Romanian schools, knowledge, learning strategies
Disposisi Matematis Dan Kemandirian Belajar Mahasiswa Pada Perkuliahan Daring Berbantuan Google Classroom Masa Covid-19

This study aims to analyze the mathematical disposition and self-regulated learning of online lectures with the help of Google Classroom. This type of research is descriptive quantitative. This study's subjects were 34 students of the first semester of the Mathematics Education Study Program consisting of 11 male students and 23 female students determined by the saturated sampling method. From the research results, it can be concluded that students' mathematical disposition through learning assisted by Google Classroom has high criteria. The mathematical disposition of male and female students through learning assisted by Google Classroom has high criteria. Still, the level of mathematical disposition of male students is slightly higher than female students. Meanwhile, student self-regulated learning with the help of Google Classroom obtains very high criteria. For male and female students, both have very high learning independence criteria in carrying out learning with the help of Google Classroom.Keywords: Mathematical Disposition, Self-regulated learning, Google Classroom, Online Lectures, Gender
COMPARATIVE STUDY OF PHOTOVOLTAIC ARRAY OPTIMUM TILT ANGLE AND ORIENTATION WITH MULTI-OBJECTIVE CONSIDERATION

Photovoltaic (PV) solar energy system converts sunlight to electricity and referred as one of promising system for production of a renewable energy resources. Tilt angle and orientation have important effect on PV output. Positioning of PV system using tilt angle and orientation, therefore, according to path of radiation of sunlight is very critical to obtain more efficient energy conversion from PV panels. In this study, determination of optimum tilt angle and orientation studied for a grid-connected hybrid wind-PV-battery system. Firstly, general calculations of PV completed using a numerical method as follow: annual solar radiation (Wh/m2), annual energy production using radiation and temperature (Wh/m2), energy production using radiation, temperature and wind speed (Wh/m2). Secondly, cost of electricity for a grid-connected wind-PV-battery hybrid systems ($/year) depending on solar radiation, weather conditions and electricity market data were obtained using numerical method. It founded that optimum tilt angle varied between 26° - 27° for first three scenario and for the last case is 9°. As for orientation, it changed from south to west for all cases. Moreover, it seems that results of this study might be a reference and preliminary study for scientist and researcher/engineers to simplify designing and evaluating PV system.
Cross-Lingual Visual Grounding

Visual grounding is a vision and language understanding task aiming at locating a region in an image according to a specific query phrase. However, most previous studies only address this task for the English language. Although there are previous cross-lingual vision and language studies, they work on image and video captioning, and visual question answering. In this paper, we present the first work on cross-lingual visual grounding to expand the task to different languages to study an effective yet efficient way for visual grounding on other languages. We construct a visual grounding dataset for French via crowdsourcing. Our dataset consists of 14k, 3k, and 3k query phrases with their corresponding image regions for 5k, 1k, and 1k training, validation and test images, respectively. In addition, we propose a cross-lingual visual grounding approach that transfers the knowledge from a learnt English model to a French model. Despite that the size of our French dataset is 1/6 of the English dataset, experiments indicate that our model achieves an accuracy of 65.17%, which is comparable to the accuracy 69.04% of the English model. Our dataset and codes are available at https://github.com/ids-cv/Multi-Lingual-Visual-Grounding.
FORECASTING FARMER EXCHANGE RATE IN CENTRAL JAVA PROVINCE USING VECTOR INTEGRATED MOVING AVERAGE

Farmer Exchange Rate (FER) is an indicator that can be used to measure the level of farmers welfare. For every agriculture sector, FER is affected by the historical price of harvest from the corresponding sector and historical prices of other agriculture sectors. In Central Java Province, rice &amp; palawija, horticulture, and fisheries are the largest agriculture sectors which is the main livelihood for most of the population. FER forecasting is a crucial thing to determine the level of farmers welfare in the future. One method that can be used to predict the value of a variable that is influenced by the historical value of several variables is Vector Time Series. An empirical study was conducted using FER data from the rice &amp; palawija, horticulture and fisheries sectors for January 2011-June 2017 in Central Java Province. The results obtained show that by using the VIMA(2.1) model, the FER prediction was very accurate, with MAPE values were 1.91% (rice &amp; palawija sector), 2.44% (horticulture sector), and 2.18% (fisheries sector).
THE IMPLEMENTATION OF EXTRACTION FEATURE USING GLCM AND BACK-PROPAGATION ARTIFICIAL NEURAL NETWORK TO CLASIFY LOMBOK SONGKET WOVEN CLOTH

The aimed of this study was to apply the feature extraction method of GLCM and Back-propagation Artificial Neural Network (ANN) to classify Lombok's typical Songket woven cloth by classifying based on the texture of the Songket woven cloth. Songket woven cloth in Lombok in terms of weaving and texture are vary from region to region. For example the songket woven cloth in Pringgasela Village, Sukarara Village and Sade Village has differences in texture and motifs. For this reason, this study focuses on classifying Lombok's typical Songket woven cloth by performing feature extraction on woven cloth using the GLCM method and the classification method uses Back-propagation Artificial Neural Network (ANN). For data collection, the data was taken directly from the Songket weaving centers in Pringgasela, Sade and Sukarara. In the classification stage the training data used were 64 data and 11 test data. Then the epoch used was 41 iterations with a time of 0:00:04, with neurons 80 and 100. The use of neurons 80 generated 18% which was successful in the classification. While using 100 neurons generated 100% successful which was can be classified. Based on the classification results obtained, the use of 100 neurons gained good classification results.
The challenges and opportunities of using 360-degree video technology in online lecturing: A case study in higher education business studies

&#x0D; Novel technologies can offer many benefits for learning and teaching and employ the constructivist learning theories and pedagogical methods. Using online video streaming the students can be present at the lecture even if they are not physically present at the classroom. 360 video technology allows the user to monitor the learning environment extensively from wider angle than usual camera technology. When using this technology in education it may also pose didactic or pedagogical challenges to the teacher and lead to the rejection of otherwise usable technologies. In this study, we explore the opportunities and challenges associated with using 360 video technology in learning. What didactical and pedagogical challenges are associated to the use of this technology and how these challenges can be overcome? In this study the 360 video technology was tested with business students in higher education settings and students opinions about the usefulness of the technology was inquired. Addition the teacher’s experiences was used in analyzing the challenges and opportunities. From students point of view it was in particular interesting how 360 technology can convey a sense of presence to remote students. The findings seem to indicate that the sense of presence was felt more comprehensive among students who participated online. This could help students to focus more on instructions. On the other hand concentrating profoundly to instructions may lead to better learning experience and outcomes because it empowers situational learning. The most didactical and pedagogical challenges were teachers cognitive overload and inactivity of the technology.
Lee at SemEval-2020 Task 5: ALBERT Model Based on the Maximum Ensemble Strategy and Different Data Sampling Methods for Detecting Counterfactual Statements

This article describes the system submitted to SemEval 2020 Task 5: Modelling Causal Reasoning in Language: Detecting Counterfactuals.In this task, we only participate in the subtask A which is detecting counterfactual statements.In order to solve this sub-task, first of all, because of the problem of data balance, we use the undersampling and oversampling methods to process the data set.Second, we used the ALBERT model and the maximum ensemble method based on the ALBERT model.Our methods achieved a F1 score of 0.85 in subtask A.
Higher Education Libraries under Uncertainty: the Specific of the Staff’ Remote Work Organizing

Uncertainty of the current academic year and long-term future in higher education institutions of Ukraine and the world, significant changes in national higher education, distancing of learning and research processes require urgent communicative reloading of libraries. The purpose of the article: a) definition and characteristics of the organization of remotely working teams (teams) of libraries of higher education institutions at the stage of transfer of library teams to remote work; b) identification of approaches that already take place in Ukraine in the context of the COVID-19 epidemic. The author has investigated the administrative aspect of the initial stage of the organization of the transfer of higher education libraries of Ukraine to remote work in the first 2 months (13.03–13.05.2020) of the introduction of quarantine in connection with the pandemic COVID-19. A thorough analysis of professional literature, sites of libraries and library associations, social networks, and self-reflection of the author’s own experience as a director of the university library during the pandemic has been carried out. Interviews (April 22–24, 2020) with 8 directors of higher education libraries of Ukraine were conducted in order to better understand the organizational aspects of the need for rapid transfer of employees to remote work. An online survey among 63 heads and leading specialists of higher education libraries of Ukraine on the topic “Models of remote work of university library teams in conditions of uncertainty” (May 25–31, 2020) was conducted. The priority actions of the library management and stages of these actions at the transfer of library collectives to remote work are defined. Four models of organization of remotely working teams (collectives) have been revealed and characterized: Model 1 – Standard; Model 2 – Pro; Model 3 – Starting; Model 4 – Zero conditional. According to the analysis of online survey data, 11.11 % of respondents attributed their library to Model 1, 50.79 % to Model 2, 38.10 % to Model 3, and 0 % to Model 4. Also, 93.65 % of respondents confirmed that higher education libraries of Ukraine have rapidly adapted librarians to remote work, an obligatory component of which is the improvement of professional competencies.
Prospects for the Development of Distance Education Technologies in Ukraine

The article outlines prospects for the development of distance education technologies in Ukraine, analysis of the characteristics of the model of distance learning in the education system. The necessity of training specialists in the field of distance education is emphasized. The importance of development of information resources and educational and methodological developments in support of new technologies of distance learning in higher education institutions of Ukraine is noted. Based on the analysis of technological advances that contribute to the improvement of the results of the use of remote technologies in the HEA, the most promising of them are identified: adaptive learning technologies, mobile learning, virtual, augmented and hybrid realities, next-generation learning management systems, artificial intelligence and natural user interfaces. As a result of the analysis of scientific works, the following prospects for the development of distance learning in Ukraine were highlighted: updating of software and hardware base for the introduction of new technologies in higher education; organization of cooperation between developers of distance learning software products, distance education methodologists and teachers of HEA to develop strategies for the use of new information technologies in distance learning; staffing of distance learning, training of specialists in the field of distance education; development and distribution of platforms with an intuitive not complex software interface for creating distance courses; creation or adaptation of information technologies and electronic educational and methodological developments to support new technologies of distance learning in the Defense Law of Ukraine.
Armed and Partially Covered Face Related Robberies Alerting System Using Computer Vision

Robbery is the completed or attempted theft, directly from a person, of property or cash by force or threat of force, with or without a weapon, and with or without injury.Armed robbery is a serious crime that can traumatically that emotionally and mentally profoundly traumatize its victims.Armed robbery is usually motivated by a desire to acquire money, which is then commonly used to buy drugs.[1] However, some armed robbers are associated with the crime.[2] In the current decade, armed robbery is one of the major issues in society.According to Statista research department, there were more than 0.25 million armed robberies happened in the USA in 2018.[3] Moreover, these robberies accounted for an estimated $438 million in losses.[2] .Moreover is the USA there were more than 10000 murders, victims, by weapons in 2018.[4]When analyzing most of these armed robberies have happened locations are Banks, Gas or Service stations, and commercial houses in the USA.To monitor and act accordingly to the issue still, there is no proper method.Present in most places there are several security officers to monitor these robberies within 24H using CCTV cameras.In this research, the authors propose a novel approach to prevent this issue using a computer vision-based armed robberies alerting system.Here this system is able to detect the weapons of the robbers.Since most of the time robbers come with partially covered faces.In this research, the proposed system is able to detect partially covered faces also.When the system identified weapons or a partially covered face in a bank or a commercial house, it will send an alert by notifying the risk of the robbery to the in house security officers and relevant authorities.The proposed solution used an object detection model and a facial landmark identification based approach to detect robbers.Because of this system, no longer the security officers need to monitor CCTV cameras by themselves
Data analysis using representation theory and clustering algorithms

This work aims to expand the knowledge of the area of data analysis through persistence homology and representations of directed graphs. To be specific, we looked for how we can analyze homology cluster groups using agglomerative Hierarchical Clustering algorithms and methods. Additionally, the Wine data, which is offered in R studio, was analyzed using various cluster algorithms such as Hierarchical Clustering, K-Means Clustering, and PAM Clustering. The goal of the analysis was to find out which cluster's method is proper for a given numerical dataset. We tried to find the agglomerative hierarchical clustering method by testing the data that will be the optimal clustering algorithm among these three; K-Means, PAM, and Random Forest methods. By comparing each model's accuracy value with cultivar coefficients, we concluded that K-Means methods are the most helpful when working with numerical variables. On the other hand, PAM clustering and Gower with Random Forest are the most beneficial approaches when using categorical variables. These tests can determine the optimal number of clustering groups, given the data set, and by doing the proper analysis. Using those the project, we can apply our method to several industrial areas such that clinical, business, and others. For example, people can make different groups based on each patient who has a common disease, required therapy, and other things in the clinical society. Additionally, people can expect to get several clustered groups based on the marginal profit, marginal cost, or other economic indicators for the business area.
Human Activity Recognition using Machine Learning Approach

The growing development in the sensory implementation has facilitated that the human activity can be used either as a tool for remote control of the device or as a tool for sophisticated human behaviour analysis. With the aid of the skeleton of the human action input image, the proposed system implements a basic but novel process that can only recognize the significant joints. The proposed system contributes a cost-effective human activity recognition system along with efficient performance in recognizing the significant joints. A template for an activity recognition system is also provided in which the reliability of the process of recognition and system quality is preserved with a good balance. The research presents a condensed method of extraction of features from spatial and temporal features of event feeds that are further subject to the mechanism of machine learning to improve the performance of recognition. The significance of the proposed study is reflected in the results, which when trained using KNN, show higher accuracy performance. The proposed system demonstrated 10-15% of memory usage over 532 MB of digitized real-time event information with 0.5341 seconds of processing time consumption. Therefore on a practical basis, the supportability of the proposed system is higher. The outcomes are the same for both real-time object flexibility captures and static frames as well.
Problems in Teaching Tourism Register for English Specific Purposes (ESP) Class

The purpose of this research was to find out the problems in teaching tourism register in English Specific Purposes (ESP) class. Students are expected to know the tourism register as the new group of vocabulary and being able to use them in the related field. When the tourism register is implanted in the course, there were some problems appeared. By reading many literatures related to the topic, the problems can be investigated. It was found that there are some problems which influenced the teaching method in ESP class. The problems can be generalized into two main problems namely; the lecturer’s problems and student’s problems. The lecturer’s problems consist of ineffective teaching and learning method includes the design material which is not fit enough for some ESP students. The student’s problems are divided into the student English proficiency, lack of vocabulary, lack of motivation and basic skill in reading, writing, listening and speaking skills.
Virtual environments and meaningful english language learning as second language L2 in high school students: a case study

The research focused on analyzing the virtual environments’ elements and their influence on the English language’ significant learning in students aged 15 to 16 years of high school fifth year of an Educational Institution in the Ambato city, Ecuador. Current educational practices impose changes and challenges necessary for the improvement of the teaching-learning process, which networked applications become learning places such as: "Edmodo". The virtual environment’ main components analyzed are: content management, planning and mapping of the curriculum, participation and administration of students, communication and collaboration, communication in real time. On the other hand, the activities to generate meaningful learning must involve and support combinations of: active, constructive, intentional, authentic and cooperative learning. This information was collected through the survey technique, raised both towards the authorities, teachers and students. Subsequently, the statistical analysis of Chi square was used to detect significant results. Thus, these results showed that most of the students exhibit a lack of knowledge on virtual environments and consider that the use of this alternative educational pedagogical technology would help to improve the Meaningful Learning process in students.