Reviewerly/exHarmony huggingface dataset:
Analysis of understanding of midwife students of midwife care as the impact of online learning

The purpose of this study was to analyze the understanding of midwifery students towards midwifery care as a result of online learning at the midwifery academy of Tahirah Al Baeti Bulukumba. This study is a quantitative descriptive study, a form of activity by measuring the level of understanding of students to family planning midwifery care as a result of online learning and probability sampling techniques with a total of 45 respondents. Analysis of data in this study is obtained from research instruments in the form of quantitative data. Quantitative data are obtained from the results of data processing case tests and surveys. The results of the study of Student Understanding Before and During the COVID-19 Pandemic on the creation of Family Planning Midwifery Care, namely an increase in understanding of the creation of family planning midwifery care by 20%, shows that students actively remain disciplined in carrying out learning activities through online, namely by self-study after online learning and able to understand the lecture materials provided by lecturers.
Students’ Views on the use of Augmented Reality Technology in Teaching Science

As a result of recent technological developments, many mobile applications used in the educational environments have emerged. One of these applications is the augmented reality technology used in smartphones and tablets. Many augmented reality applications are now prepared with 4D-technology and are employed to transform virtual environments into real life situations. In this study, we examined the views of 6th-grade students about using augmented reality technology in teaching science. Designed as a phenomenological research from the qualitative research methods, this study was conducted with nine 6th-grade volunteer students studying in a secondary school in the district of Göynücek in Amasya Province during the 2017-2018 academic year. The data were collected through interviews, using a semi-structured form. We analyzed the data set, by applying descriptive analysis method using NVivo 9 program. Categories emerged from the student views. We modeled the qualitative data in terms of these categories. Based on the research findings it was concluded that the augmented reality activities carried out provided permanent learning about the systems in our body and increased positive attitudes and interests towards the lessons, according to the students' opinions. We concluded that the science teaching with the use of augmented reality technology will provide positive learning outcomes on students. Further, teachers should receive and be provided with professional development on augmented reality to be able to use it more efficiently. This study is expected to contribute to researchers and practitioners in the future.
Different Activity, Different Risk, Different Rules? Exploring Cryptocurrency System Service Providers' Duties and Responsibilities

Cryptocurrencies are based on digitally signed updates (transactions) to a ledger maintained in a decentralized manner according to consensus mechanisms in compliance with consented protocols. Although being presented as peer-to-peer systems, there are several service providers in a cryptocurrency system. Among them are protocol developers who develop the rules and implement these in open source software, and full nodes contributing to the peer-to-peer distribution of transactions and appending these transactions to the ledger according to the consensus mechanisms. This paper explores the duties and responsibilities of such service providers, individually and as a group, and provides a discussion of whether they should be subject to special duties and responsibilities. This issue seems crucial to explore alongside mainstream adoption of cryptocurrencies.
SARATOV PERIODICALS OF THE 1918-1921 AS A SOURCE ON THE HISTORY OF REGIONAL BOOK PUBLISHING IN THE FIELD OF EDUCATION AND SCIENCE

Saratov periodicals of the 1918-1921 are valuable sources on the history of the regional book publishing in different fi elds
A New "Offline + Online" Teaching Model of College English Based on Cloud Computing

Cloud computing is a new platform for Contemporary College Students' English education. It is based on the construction of theory, cooperative learning and learning community, and is of great help to improve the quality of College Students' English teaching. This paper analyzes and discusses the College English teaching model based on cloud computing. The ecological teaching mode based on cloud computing platform combines cloud computing with ecological teaching concept, which can help teachers abandon the traditional filling teaching mode. The platform can support autonomous learning and meet the requirements of students' personality development. The experimental results show that cloud computing has good openness and sharing. Through cloud computing, the "co construction, sharing and sharing" of high-quality teaching resources can be realized. This method can achieve the balance of educational resources and inject new vitality into the traditional means of College English teaching.
Instructional Video using Wondershare Filmora 9 in the Interpretive Reading Course for English Language Education Students

The Covid-19 pandemic has had a significant impact on education. The implementation of online learning results in the lack of availability of appropriate learning media to support the implementation of online learning. This study aims to develop learning videos using Wondershare Filmora 9 in the Interpretive Reading course for third semester students of English Education. The development of this learning video uses the ADDIE development model which consists of the analysis, design, development, implementation, and evaluation stages. The results of the validity of interactive multimedia development will be presented with two main points which include: subject matter experts, and learning media experts. The subjects of this research include experts, namely 2 subject experts, and 2 learning media experts. The method used in collecting data is the observation method, interview method, and questionnaire method. The data analysis technique in this research is descriptive qualitative and descriptive quantitative. The data collection instrument in this study was using a questionnaire. The results of the validation carried out by material experts I and II were 93.84%, while the results of the validation carried out by media experts I and II were 87.05%. It can be concluded that the learning video that has been developed with the help of Wondershare Filmora 9 is very suitable for use in interpretive reading courses. Based on these results and conclusions, learning videos can be used as an alternative in overcoming the problem of the lack of media availability in online learning.
A Hybrid Sparse Representation Model for Image Restoration

Group-based sparse representation (GSR) uses image nonlocal self-similarity (NSS) prior to grouping similar image patches, and then performs sparse representation. However, the traditional GSR model restores the image by training degraded images, which leads to the inevitable over-fitting of the data in the training model, resulting in poor image restoration results. In this paper, we propose a new hybrid sparse representation model (HSR) for image restoration. The proposed HSR model is improved in two aspects. On the one hand, the proposed HSR model exploits the NSS priors of both degraded images and external image datasets, making the model complementary in feature space and the plane. On the other hand, we introduce a joint sparse representation model to make better use of local sparsity and NSS characteristics of the images. This joint model integrates the patch-based sparse representation (PSR) model and GSR model, while retaining the advantages of the GSR model and the PSR model, so that the sparse representation model is unified. Extensive experimental results show that the proposed hybrid model outperforms several existing image recovery algorithms in both objective and subjective evaluations.
Breast Tumors Diagnosis Using Fuzzy Inference System and Fuzzy C-Means Clustering

Many of the researches have been successful in the field of computer-aided diagnosis because of the important results the intelligent computing approaches have achieved in this field. In this paper the robust classification method is presented, that attempts to classify the tissue suspicion region as normal or not normal by using a Fuzzy Inference System (FIS) using the Fuzzy C-Mean (FCM) clustering for fuzzification of the Gray-Level Co-Occurrence Matrix (GLCM) feature and a match shape function for fuzzification of matrix shape, then by using (T-norm) generate 729 rules (243 rules based on normal DB case, 243 rules based on benign case, 243 rules based on malignant case), after that the best Eighteen rules are selected (best 6 rules based on normal DB case, best 6 rules based on benign DB case, best 6 rules based on malignant DB case) by using genetic algorithm, then make summation for each group if the summation of 6 rules based on normal DB is greater than other summation of two group (best 6 rules based on benign DB case and best 6 rules based on malignant DB case) that mean resulted of the classification step is normal. The model approved efficiency classification rate of 97.5% of input dataset image.
Satisfaction of College and University Students With Education: a Comparative Analysis

The problem of student satisfaction with secondary vocational and higher education is one of the central ones for both students and educational institutions. The social well-being of students at each university and college, their achievement of academic success largely depends on its solution. It is proved that students 'satisfaction with education affects the students' life success and their assessment of the possible results of this influence. The novelty of the material consists in a comparative study of student opinions and assessments concerning the problems of satisfaction with the received education.
INFLUENCING FACTORS OF BUSINESS INTELLIGENCE CONTINUANCE USAGE INTENTION: A CASE STUDY OF GOVERNMENT-OWNED INSURANCE COMPANY

Business Intelligence is a technological trend in supporting strategic analysis and decision making in organizations.Many organizations claimed to have successfully adopted Business Intelligence, many also reported failure after adoption.Taspen is one of government-owned insurance company in Indonesia that has problems with the use of Business Intelligence, it decreased to reach 16% in the first year.Based on these facts it is necessary to analyze the factors that influence the continued use of Business Intelligence in the company.This study uses a quantitative approach through the distribution of questionnaires to decision makers and users of Business Intelligence.From the results of data collection, there were 195 respondents who were analyzed using Covariance Based SEM (CB-SEM) with the help of IBM Amos v22 software.This study proposes a framework model that combines External Stimuli, Affective Response, and Cognitive Response to the continuity of Business Intelligence use.The results of this study indicate that Information Integration and productivity increase are the most significant factors influencing the continuity of Business Intelligence use.Factors such as influence organizations and influence peers still need to be investigated further to identify the causes of the weak influence on the continued use of Business Intelligence.
Image quality assessment

Quality assessment is an integral stage in the processing and analysis of digital images in various automated systems. With the increase in the number and variety of devices that allow receiving data in various digital formats, as well as the expansion of human activities in which information technology (IT) is used, the need to assess the quality of the data obtained is growing. As well as the bar grows for the requirements for their quality. The article describes the factors that deteriorate the quality of digital images, areas of application of image quality assessment functions, a method for normalizing proximity measures, classes of digital images and their possible distortions, image databases available on the Internet for conducting experiments on assessing image quality with visual assessments of experts.
Contributions of Body-Orientation to Mental Ball Dropping Task During Out-of-Body Experiences

Out-of-body experiences (OBEs) provide fascinating insights into our understanding of bodily self-consciousness and the workings of the brain. Studies that examined individuals with brain lesions reported that OBEs are generally characterized by participants experiencing themselves outside their physical body (i.e., disembodied feeling) (Blanke and Arzy, 2005). Based on such a characterization, it has been shown that it is possible to create virtual OBEs in immersive virtual environments (Ehrsson, 2007; Ionta et al., 2011b; Bourdin et al., 2017). However, the extent to which body-orientation influences virtual OBEs is not well-understood. Thus, in the present study, 30 participants (within group design) experienced a full-body ownership illusion (synchronous visuo-tactile stimulation only) induced with a gender-matched full-body virtual avatar seen from the first-person perspective (1PP). At the beginning of the experiment, participants performed a mental ball dropping (MBD) task, seen from the location of their virtual avatar, to provide a baseline measurement. After this, a full-body ownership illusion (embodiment phase) was induced in all participants. This was followed by the virtual OBE illusion phase of the experiment (disembodiment phase) in which the first-person viewpoint was switched to a third-person perspective (3PP), and participants' disembodied viewpoint was gradually raised to 14 m above the virtual avatar, from which altitude they repeated the MBD task. During the experiment, this procedure was conducted twice, and the participants were allocated first to the supine or the standing body position at random. Results of the MBD task showed that the participants experienced increased MBD durations during the supine condition compared to the standing condition. Furthermore, although the findings from the subjective reports confirmed the previous findings of virtual OBEs, no significant difference between the two postures was found for body ownership. Taken together, the findings of the current study make further contributions to our understanding of both the vestibular system and time perception during OBEs.
Proposed Method to Allocate the Blood Units by Using a Hybrid of Real-Time Algorithms on the Cloud Environment

Blood units are a sensitive, scarce, and important resource in the health care system, which must be allocated to beneficiaries accurately, quickly, and efficiently.In this paper, we will propose a new method to allocate the blood units, which will be the major part of an integrated real-time system on a cloud environment, backed by smart device applications.The proposed method will use a hybrid of real-time algorithms some of supply chain principles, to develop the allocating operation of blood units to address the problems associated with the use of current traditional methods to allocate blood units.Where, the current methods in their works heavily rely on human intervention, paper documents, and traditional supply chain algorithms.Also, current methods suffer from many problems, including the potential for human error and dependence on the local scale to supply blood units most of the time, in addition to a high rate of miss allocation of blood units, especially for critical cases, And this is what we are working to overcome in the proposed method, to improve the performance of the allocation of blood units, and this, in turn, will improve the health care services provided to the beneficiaries.This proposed method will be applied to allocating blood units within the health care system of Nineveh Governorate.
Psychological and Pedagogical Bases of Standardization of Digital Educational Products and Digital Technologies

This article is aimed at the analysis of the features of the ecosystem of the digital educational environment.As a research method the testing method was used, which allows to effectively determine the complex of personal determinants of the personality of a pupil as a subject of educational activity, which are important for his psychological safety when using digital educational technologies and digital educational products.The article describes the peculiarity of the current stage of development of the practices of using digital educational technologies and digital educational products in the school educational process.The authors analyzed the psychological and pedagogical foundations of standardization of digital educational products and digital technologies in the educational environment of the school.The authors of the articlefor the first time -investigated the digital education ecosystem and identified psychological and pedagogical requirements for the use of digital educational products and digital technologies in the educational process.The following psychological and pedagogical requirements are defined: compliance of digital educational technologies and digital educational products with a zone of child's immediate development; taking into account the leading activity in each age period when using digital educational technologies and digital educational products; taking into account specific psychological neoplasms of students at each age stage; taking into account the need for compliance of digital educational products and digital technologies with students' self-knowledge through understanding and finding personal meanings; the safety of digital educational technologies and
Implementasi Graph Clustering Algorithm Modification Maximum Standard Deviation Reduction (MMSDR) dalam Clustering Provinsi di Indonesia Menurut Indikator Kesejahteraan Rakyat

&lt;p&gt;The population of Indonesia from year to year has increased. The increase in population must also be accompanied by increased economic growth in Indonesia. The increase in economic growth in Indonesia is marked by the reduction in the number of poor people in Indonesia. In addition, the increase in economic growth is reflected in the equitable distribution of public income in the country. Even though there are still many Indonesian people who are not yet prosperous in economic terms. To overcome, it is necessary to have clustering and characteristics of 34 provinces in Indonesia by implementing the Modification Maximum Standard Deviation Reduction (MMSDR) graph clustering algorithm. The data used are indicators of public welfare in 2017 obtained from the Central Statistics Agency. There are 9 indicators of community welfare used in this research. There are four stages in the MMSDR algorithm namely the "MST", "Subdivide", "Biggest Stepping" and "Create Clusters" processes. The results of this study can be seen from the distance between the nodes or between one province and another province produced 22 clusters. From the cluster results obtained using the MMSDR algorithm on welfare data, there are many clusters formed with cluster members formed at most two nodes (province).&lt;/p&gt;&lt;p&gt; Keywords: MMSDR, Clustering, Welfare of People&lt;/p&gt;
Smart Pharmacy Kanban System in Post Covid Era

Maintaining social distancing is crucial in all aspects of life in this pandemic situation.Stock updation is an important aspect in pharmacy to provide effective supply chain with the use of sensors.The availability of appropriate stock ensures that the product can be delivered to customer on time.In the advent of Enterprise Management System (ERM), most hospitals are integrating these software systems.However, manual effort is required for the updation of stocks in the ERM software which results in overhead costs such as payroll.In the existing model, if some of the old stocks are stocked for long time, it may lead to the waste of stocks.In order to avoid all of above problems, a Kanban planning based model has been built to implement the stock updation in pharmacy where all the hospitals can be benefited by reducing the manual work.This system also reduces the inadvertent errors caused by the workers and the number of employees and provide more effective supply chain to the hospital.It can enable designed to maintain the social distancing of pharmacists also enabling better storage their oxygen cylinders and vaccines in a particular place.
Development of Smart Paper Engineering (SMART-PEN) Thematic Media Using the RADEC Model to Train Creative Skills and Critical Thinking Elementary School Students

Literacy competence is essential so that Indonesian human resources can compete.And 21st-century skills that students must have, namely collaboration, communication, critical thinking, and creativity (4C).The purpose of this development research is to improve the literacy and 4C skills of SD Muhammadiyah Sudagaran Wonosobo students by using thematic learning tools in the form of Smart Paper Engineering (Smart-Pen) Thematic Media based on the (Read, Answer, Discuss, Explain, Create) RADEC Model.The research model used is ADDIE(Analyze, Design, Develop, Implement, and Evaluate) which was developed by Dick and Carry.Based on the hypothesis that the SMART-PEN thematic media design with the RADEC model is valid and effective in training elementary school students' 4C skills.The results of the research on Smart Paper Engineering (Smart-Pen) Thematic Media Development Using the Radec Model to Train Critical Thinking Skills students got a score of 87.10% with very good criteria for developing critical thinking and 80.65% training creative thinking with good criteria.The impact of Smart-Pen for students are 1) Students have critical thinking skills; 2) Students are more enthusiastic about learning; 3) Students can become creative directors and find specifications for in-depth learning media; 4) Learners can innovate; 5) as a reference and development media for teachers in conducting learning 6) Smart-pen is effectively used in training critical and creative thinking skills.
Case Study of Few-Shot Learning in Text Recognition Models

Optical text recognition models are widely applied in document processing systems. However, a high-quality text recognition model usually requires large number of samples, extensive amount of time and computation resources. In this paper, we propose a few-shot learning framework for unsegmented text recognition, which comprises of a conventional encoder-decoder recognition module, as well as a generative module for convolutional feature generation. In the meta-training stage, a base model for general text recognition and feature vector generation is trained with large synthesized text image dataset. In the meta-testing stage, the base model is adjusted with a small number of authentic samples. With the complementation of synthesized feature vectors, the base model is adapted to the target dataset distribution. The proposed framework only requires a few authentic samples. It is both data- and time- efficient in adapting existing models to new target datasets. Experimental results on authentic datasets used in industrial applications show that the proposed meta-testing approach outperforms conventional transfer learning by up to 5.84%.