Reviewerly/exHarmony huggingface dataset:
THE VALIDITY OF LEARNING MATERIAL ASSISTED AUGMENTED REALITY TECHNOLOGY IN THE TOPIC OF STRUCTURE AND FUNCTION OF PLANT TISSUE

The Industrial Revolution 4.0 is a comprehensive transformation of all aspects of production in industry through the combination of digital and internet technology with conventional industries. The education sector is an important field that must adapt to the demands of the times so as not to be left behind. In the world of education, especially in subjects such as Basic Biology, there are many objects that are difficult to visualize in real terms, one of which is the topic of the Structure and Function of Plant Networks. The problem can be visualized using Augmented Reality (AR) technology. The purpose of developing AR-based teaching materials is to combine biology material by applying AR technology so that learning is more interesting, meaningful, and interactive, and students can observe objects in biological studies. The product specifications developed were in the form of Basic Biology I teaching materials consisting of the BIOAR application and augmented reality-based supplement books on the topic of Plant Tissue Structure and Function. This method of developing teaching materials used R & D (Research and Development) which consisted of (1) Research and Information collection, (2) Planning, (3) Development of teaching materials based on augmented reality, (4) Validation of teaching materials by experts. The validation results showed that this augmented reality-based teaching material was declared very valid with a value of 4.52.
Android Based Learning Media Busuu for German Self-Learning

This research aimed to describe the use of Busuu android-based media for self-learning for X Language Class SMA Laboratorium UM students and to know the students responses to the use of this media. This research used descriptive qualitative method. The data sources of this research were the activities of 20 students from X Language Class and the students self. The data collection was obtained using observation and questionnaire sheets. The results of this research indicate that use of Busuu android-based media run well. Students can more understand easily of German language material and class conditions are also controlled during learning process. Based on this description, Busuu can be used as an alternative learning media for German Language self-learning.
Evaluasi Atas Implementasi Aplikasi Sistem Aplikasi Instansi Berbasis Akrual (SAIBA) Pada Satuan Kerja Lingkup Pembayaran KPPN Samarinda

This research was conducted to determine whether system quality, information quality, and service quality affect user satisfaction of the Accrual-Based Agency Accounting System application in work units in the KPPN payment area of Samarinda City partially and simultaneously. The analytical tools used in this research are validity test, reliability test, classic assumption test which consists of normality test, multicollinearity test, autocorrelation test and heteroscedasticity test, multiple linear regression analysis, F statistical test, and t statistical test. The results of the analysis that have been carried out show that the System Quality (X1) and Information Quality (X2) variables have a positive and significant effect on User Satisfaction (Y), while the Service Quality variable (X3) has a positive and insignificant effect on User Satisfaction (Y). The better quality of the SAIBA information system which is represented by ease of use, reliability, fast access, flexibility, and a high level of security, the more user satisfaction with the application will be. The better the quality of information produced in the form of information that is accurate, reliable, relevant, easy to understand, and timely, the higher the level of satisfaction of application users, because the SAIBA application is made to produce financial reports as a form of accountability for the budget that has been used by each. each agency. Service quality is not a variable that significantly affects the level of user satisfaction, but there is a positive influence between service quality and user satisfaction which indicates that the better the quality of service provided by KPPN officers in informing the implementation of the SAIBA application provided, it will increase user satisfaction. User perceptions in measuring the satisfaction level of using the SAIBA application are not on how KPPN officers provide information about application implementation, but rather on the quality of the application itself and how the quality of information generated by the application.
A Novel Framework For Iot-Based Automatic Remote Health Monitoring Using Big Data Analytics

With the tremendous development in the field of Internet of Things (IoT), huge amount of data is being continuously generated. This data is termed as the big data. Processing of big data is a crucial task as it may be helpful for inferring useful information. The big data generated by IoT devices are processed using data analytics techniques that helps to analyse and explore the hidden information behind the big data. This system is especially useful in remote health monitoring systems in which data collected by medical sensors are processed and explored. In this research, we propose a new algorithm called IoT-based automatic remote health monitoring algorithm (IARHM), that can be used for monitoring the health conditions of patients from remote locations. In this framework, sensors like temperature sensor, pressure sensor, pulse rate sensor, cholesterol level sensor and sugar level sensor are used for collecting the medical data of the patients. These data are then transmitted to the cloud. In the cloud, these data are processed using the proposed IARHM algorithm to identify the health conditions of the patients. Any kind of abnormalities are immediately reported to the care takers so that immediate actions can be taken. The performance of the proposed algorithm is validated using metrics like accuracy, F-score, recall and latency. It was observed that, the proposed system achieved very high performance with minimal latency and hence can be easily implemented for real-time monitoring purposes. The main advantage of this framework is the remote monitoring capability of the system i.e., the patients can be monitored by the caretakers from remote locations. The proposed algorithm achieves a maximum recall of 97.59% and a maximum F-score of 96.83%.
Usage of distance educational technologies for improving the effectiveness of students’ professional training

The need of increasing the effectiveness of students’ professional training determines the search for new mechanisms, models and technologies of educational process organizing at a university based on systemic, competency-based and practice-oriented approaches. The theoretical and methodological foundations of increasing the effectiveness of students’ professional training are substantiated, including key scientific approaches (systemic, competency-based, practice-oriented) and the principles of their realization (professional orientation, competitiveness, interdisciplinarity, social partnership, practice orientation, pedagogical support, regionalization). A model for increasing the effectiveness of students’ professional training using distance educational technologies has been developed and experimentally tested. The pedagogical ways of increasing the effectiveness of future specialists’ professional training in universities using distance educational technologies have been identified. Distance educational technologies are considered as a means of increasing the effectiveness of students’ professional training. Correct use and further development of the abovementioned technologies would improve the overall professional competency of intending specialists in the area of education.
Study on Colorization Method of Grayscale Image

Contrapose the problem that the traditional grayscale image colorization results are not unique, this paper proposes a color conversion method based on luminance and Local Binary Patterns (LBP) texture features, which uses an improved Gaussian Mixture Model (GMM) clustering or image segmentation. The cascading feature matching method performs fast feature matching of sub-blocks after segmentation, which overcomes the low matching accuracy of the global color conversion algorithm, long feature matching processing time, and color conversion errors. The verification results of subjective and objective evaluation experiment shows that the method has obvious advantages.
BEHAVIOUR ANALYSIS OF STUDENTS IN ONLINE EXAMINATION USING MACHINE LEARING

Logistic Regression is commonly applied to all sort of tasks and any property of the input can be a feature. It involves a more probabilistic view of classification. This paper aims at analysing the student behaviour to check whether there is a malpractice or not on online examination by the environment of the student to ensure that they gain knowledge only through their hard work and not by cheating on examination. The testing environment of the student must be silent but due to pandemic, student education has come to become a question mark. Technologies have made sure that the education of students must continue even though there is pandemic going on. As a result of solving the situation, online examination is the solution. When the student attend exams on online sitting in their home. There are sounds that they can’t control like traffic, children playing. This analysis will help to check the student’s background noises that should be and should not be in the testing environment.
Análisis de los contenidos científicos presentes en Instagram por futuros profesores de Primaria

espanolLa ciudadania percibe como se van modificando los conocimientos cientificos que le permiten responder a las cuestiones cientifico-tecnicas, tanto a nivel personal como social. En este trabajo se presenta como nuestros estudiantes, organizados en grupos, analizaron los contenidos cientificos presentes en la red social Instagram. Los documentos presentados por 15 alumnos fueron analizados para construir una guia de manejo de la red social y para valorar la posible utilizacion de Instagram en el aula. EnglishCitizens perceive how the scientific knowledge that allows them to respond to their day to day, both personally and socially, are modified. With this idea, in this work, it is presented how our students of Magisterium, organized in groups, analyzed the scientific contents present in the Instagram social network. The documents presented by 15 students were analyzed to build a management guide for the social network and from the point of view of the use of Instagram in the classroom.
Undergraduate Researcher Personas.

Personalized undergraduate research programs can help increase undergraduate students' participation in research. Personas of undergraduate researchers are a powerful means of encapsulating the richness of students' various goals, motivations, and experiences in research. Student personas can support the design of research programs with student-centered approaches that better engage undergraduate students across multiple disciplines. We used interview data and drew on Self-Determination Theory to identify students' various goals and motivations in order to build three undergraduate researcher personas in physics.
Text mining: A survey of Arabic root extraction algorithms

In all Arab countries, the Arabic language is the official language spoken andwritten and is one of the oldest known languages. This paper aims to explainand discuss the work done on extracting the root of the Arabic word andStemming algorithms. Text mining has become of interest to scientists,researchers, and users because of the existence of big data and deep learningalgorithms that can analyze giant sets of unstructured data. The basicalgorithms are used to extract and classify texts, information retrievalsystems, and indexes. Algorithms are used to extract the root of a word fromdifferent natural languages. This paper will present a brief background andcomprehensive presentation of a number of algorithms that handle theArabic text to extract the word root in its light, heavy, hybrid, leading, andMarkovian form. There are a number of papers, articles, and research papersthat deal with extracting the Arabic root from the word. This paper willpresent a brief background for a number of stemming algorithms on how toextracting the root and stem of the Arabic word, then make a comparison anddiscussion of a number of selected algorithms in terms of accuracy, data set,method of stemming regarding of strengths and weakness.
When to Buy and When to Sell Bitcoin?

We employ several technical analyses models and account for investor’s sentiment to establish a benchmark on the optimal time to entry or to exit from the Bitcoin market. Unlike companies that they have quarterly earnings, Bitcoin is not a company with earning. Yet, we argue the Bitcoin “halving” is the closest to company’s earnings. Indeed, we show that one of the key determinant of Bitcoin price fluctuation is the Bitcoin “halving,” in terms of quantity and timing. We also examine how market distraction and liquidity influence Bitcoin price. Thus, we suggest entry when stock market distraction and/or liquidity is high and we approaching the halving; exit otherwise. Collectively, we introduce two key determinants, investors’ distraction and Bitcoin halving, to understand Bitcoin price movement.
Relationship graph learning network for visual relationship detection.

Visual relationship detection aims to predict the relationships between detected object pairs. It is well believed that the correlations between image components (i.e., objects and relationships between objects) are significant considerations when predicting objects' relationships. However, most current visual relationship detection methods only exploited the correlations among objects, and the correlations among objects' relationships remained underexplored. This paper proposes a relationship graph learning network (RGLN) to explore the correlations among objects' relationships for visual relationship detection. Specifically, RGLN obtains image objects using an object detector, and then, every pair of objects constitutes a relationship proposal. All relationship proposals construct a relationship graph, in which the proposals are treated as nodes. Accordingly, RGLN designs bi-stream graph attention subnetworks to detect relationship proposals, in which one graph attention subnetwork analyzes correlations among relationships based on visual and spatial information, and the other analyzes correlations based on semantic and spatial information. Besides, RGLN exploits a relationship selection subnetwork to ignore redundant information of object pairs with no relationships. We conduct extensive experiments on two public datasets: the VRD and the VG datasets. The experimental results compared with the state-of-the-art demonstrate the competitiveness of RGLN.
Creating collaborative educational space in conditions of distanсe learning

The article is devoted to the problem of organizing the collaborative educational environment in conditions of distance learning. The author gives an essential characteristic of «collaborative environment» concept which is innovative approach in the training of future specialists. Collaboration is considered as cooperation in solution of the common task, taking into account the immersion of participants in a general communicative context. The priority aspects of the creation of collaborative education include the use of the possibilities of communication and educational technologies for structuring educational information, presenting it in various formats, developing methodological guidelines that serve as a kind of support for the successful fulfillment of tasks provided by the discipline program. The collaboration is also considered as a specific form of interaction and cooperation, which can be used both in the face-to-face and in the distance learning model. Undoubtedly, one of the most important promising tasks in the field of pedagogical research will be studying the characteristics of students and teachers’ communication in the network in order to identify conditions that contribute to constructive solution of problems arising in the training process
APLIKASI REKRUTMEN BERBASIS WEB DENGAN METODE PROTOTYPING MENGGUNAKAN FRAMEWORK YII 2

Recruitment is the process of searching, finding and attracting prospective employees to be employed in and by the organization. The recruitment process currently taking place still uses paper media so it takes a lot of time to process applications. Companies can also hire third-party services to advertise their vacancies, but of course they have to pay the costs that must be incurred by the company so that the job advertisements published can be seen by job seekers. PT Tropical Electronic as one of the leading companies in Batam still uses a recruitment process that uses paper media or hires advertising providers. This study aims to build an online recruitment within the PT Tropical Electronic company, making it easier for prospective employees to find job information at PT Tropical Electronic. The software development model that will be used is a prototyping model. Testing method using the black box testing method. The programming language used in the development of this application is PHP using the Yii2 framework and the RDBMS used is MySQL. This application is expected to facilitate the recruitment process at PT Tropical Electronic.
Students' local musical studies: project method and its implementation

This article is dedicated to the use of the project method in musical and regional studies of the university students. The research was based on years of experience of teachers and students of the Federal State Budgetary Educational Institution of Higher Education "Vologda State University". Specifically, two types of student projects carried out in the course of studying the discipline "Musical culture of the Vologda region" were analysed: firstly, group projects related to the search for materials about musical life in periodicals of previous years, and secondly, individual projects based on verbal history methods. On the one hand, students’ projects are aimed at the development of the necessary professional competencies, and on the other hand, they contribute to the gradual filling of substantial gaps in the musical history of Vologda. Similarities are identified between the project method and the concept of learning by doing where each student is positioned as an active and creative subject of study. In addition, this research highlights a significant educational potential of music and local history work.
WFN-PSC: weighted-fusion network with poly-scale convolution for image dehazing.

Image dehazing is a fundamental task for the computer vision and multimedia and usually in the face of the challenge from two aspects, i) the uneven distribution of arbitrary haze and ii) the distortion of image pixels caused by the hazed image. In this paper, we propose an end-to-end trainable framework, named Weighted-Fusion Network with Poly-Scale Convolution (WFN-PSC), to address these dehazing issues. The proposed method is designed based on the Poly-Scale Convolution (PSConv). It can extract the image feature from different scales without upsampling and downsampled, which avoids the image distortion. Beyond this, we design the spatial and channel weighted-fusion modules to make the WFN-PSC model focus on the hard dehazing parts of image from two dimensions. Specifically, we design three Part Architectures followed by the channel weighted-fusion module. Each Part Architecture consists of three PSConv residual blocks and a spatial weighted-fusion module. The experiments on the benchmark demonstrate the dehazing effectiveness of the proposed method. Furthermore, considering that image dehazing is a low-level task in the computer vision, we evaluate the dehazed image on the object detection task and the results show that the proposed method can be a good pre-processing to assist the high-level computer vision task.
«Паскалівські медитації» П’єра Бурдьє: труднощі перекладу: Лабораторія наукового перекладу

This issue of Philosophical Thought publishes materials from the seminar Laboratory of Scientific Translation, which was devoted to discussing the Ukrainian translation of Pierre Bourdieu's work Pascal Meditations. On June 30, 2020, the seminar took place at the Institute of Philosophy of the National Academy of Sciences of Ukraine. G.S. Frying pans with the support of the International Renaissance Foundation and Tempora Publishing House. The text of the Ukrainian translation was presented by the scientific editor of the work Serhiy Yosypenko. Oksana Yosypenko, the translator of the work, took part in preparing the printed version of the presentation of the translated text. The experts were Iryna Slavinska and Oleksiy Panych. Vakhtang Kebuladze moderated the seminar.
DPS-AA: Migration Strategy Model for Intranet over Cloud

Intranets & Intranet-wares have become a central junction/platform for implementing the organization’s specific work culture like computing, communication and collaboration. In order to ensure smooth and effective communication, computing and collaboration among employees, intranets play an important role. For vertical and horizontal management, we use intranet-wares for directing, reporting, collaborating, socializing, communicating and meeting or discussing the professional and social issues. Today, cloud-based computing, communication, and collaboration have created new frontiers and emerging paradigms towards re-engineering of work cultures in the organizations. In order to enhance the performance with extended features, next-generation computing, communication, and collaboration the intranet needs redesign and migration strategy over alternative technology platforms. This research paper tries to answer the research questions that how an alternative technology strategy or pathway can be explored for enhancing the performance and extending the features of the exiting designs of educational Intranets. Further; how an on-premise intranet can be migrated over cloud platforms with enhanced performance and extended/add-on features. After analysis of collected facts, understanding the issues, challenges and limitations of the existing state of art intranets, a strong need for performance enhancement and add on features was observed for Intranets. The study deeply investigated and analyzed the issues, challenges and limitations i.e. features and performances of the current state of the art of the intranets in general and on-premise Intranet of AMU in specific. Finally, an Intranet Migration Strategy Model over Hybrid Cloud was designed and developed using SaaS (i.e. AMU CloudNet). In this study, the Interact Intranet was used for designing and demonstrating the functional prototype of intranet show that how computing, communication and collaboration services can be enhanced with anytime, anywhere and boundary-less access.