Reviewerly/exHarmony huggingface dataset:
EDUCOLOGYCAL TRAINING IN ENSURING THE QUALITY OF EDUCATION AT THE UNIVERSITY

The article is devoted to the analysis of the content of educologycal training in the educational programs «Preschool Education», «Primary Education», «Management of Educational Institutions» full-time and part-time at Borys Grinchenko Kyiv University, which involves studying the interdisciplinary course «Educology». The article emphasizes the contribution of educology as a scientific phenomenon in ensuring the quality of university education due to its integrated and interdisciplinary nature. A significant difference between the object of study of education and other humanities is that educology is a kind of educational synergy for the study of education, which generates a systematic set of educational sciences such as philosophy of education, history of education, educational policy, educational law, education management, economics of education, sociology of education, culturology of education. The authors analyzed the effectiveness of teaching the discipline «Educology» on the basis of a survey of undergraduates of the university, in which special attention was paid to the development of critical thinking; awareness of patterns, trends, sources of education and educational systems; application of a synergetic approach in education management; formation of the ability to find means of solving current problems in the field of education; understanding of education as a specific sector of the economy, mechanisms of competitiveness of educational institutions, understanding of education as a social institution, the role of legal aspects in the development of education, etc. It is proved that the study of the course «Educology» will contribute to the development of future professionals in the field of education skills to systematically solve the multifaceted problem of ensuring the quality of education at the university; consider prospects and forecast changes to improve it.
The Problem of Formation of Civic and Social Competencies of Teenagers in the Process of Socio-Pedagogical Communication

The article is devoted to the problem of formation of civic and social competencies of teenagers in the process of social and pedagogical communication. The main focus is on revealing the essence and content of concepts «civic competence», «social competence». Features of adolescence, and also the importance and possibilities of formation civic and social competencies of this age period in the process of socio-pedagogical communication are revealed. It is noted that there is a need for more detailed study: the content of the concept «civic and social competencies of teenagers»; features of the formation of civic and social competencies of teenagers in the process of socio-pedagogical communication; technologies for the formation of civic and social competencies of adolescents in the process of socio-pedagogical communication; criteria, indicators and levels of formation of civic and social competencies of adolescents; improvement of diagnostic tools of assessment of the level of civic and social competencies of adolescents, and also improving the content, forms and methods of training of subjects of the process of formation of civic and social competencies of adolescents in general secondary education institutions; development of scientific-methodical and information support of the process of civic and social competencies of adolescents among general secondary education institutions, etc.
PRINCIPLES OF MODEL CONSTRUCTION OF DEVELOPMENT OF PEDAGOGICAL COMPETENCE OF FUTURE TEACHERS OF PSYCHOLOGY IN MASTER'S DEGREE

The article reveals the principles of building a model of formation of pedagogical competence in future teachers of psychology in graduate school. In particular, the conceptual block of the model of development of pedagogical competence of future teachers of psychology in the conditions of master's degree defines ideology of the specified development and contains such pedagogical principles: system, continuity, professional orientation, innovation, democratization, electiveness, creativity, professional mobility, problems; unity of scientific, educational and professional activity; informatization; independence, reflectivity.
Semi-supervised semantic segmentation via image-to-image translation

Semantic segmentation is an important task in computer vision that aims to infer pixel-level semantic label information in images. Recently significant progresses have been made in deep neural networks-driven segmentation techniques, but these often require a large number of labels to supervise neural network training. Obtaining a sufficient number of labeled training data is challenging and sometimes impractical in real-world applications. This paper aims to study a semi-supervised semantic segmentation via image-to-image (I2I) translation technique. I2I is an emerging technique that maps an image from a domain to another domain. We uniquely treat the image semantic segmentation as an I2I translation task that infers semantic labels of objects (target domain) from input image (source domain) in a weakly supervised way. Particularly, we develop a two-pass strategy of I2I combining images with real and pseudo labels for semi-supervised model learning. The first pass uses unsupervised models to generate pseudo labels that combine with inputs to form pseudo-labeled samples. Since the pseudo-labeled images may undermine the quality of the model, they have to be specifically constrained in training by a noise correction framework to ensure good performance. Therefore, we boost the performance by incorporating both real and the pseudo labeled samples into the second pass to train a model based on a supervised architecture. Our goal is to bridge the gap between supervised and unsupervised learning for semantic object segmentation in practical. Extensive evaluations are conducted to demonstrate the efficiency and effectiveness of the proposed technique.
ASSESSING WRITING OF EFL STUDENTS OF AKADEMI MARITIM NUSANTARA CILACAP

English as a foreign language is always be considered a difficult language to be learned. There are four language skills that must be mastered, those are listening, reading, speaking, and writing. Writing is the most difficult skill to be learned among those four. In order to know the mastery of writing ability, assessment should be done. Assessing writing sometimes difficult to be done because the lecturer does not know what to be done and how to assess writing ability. This paper attempts to help the lecturer understand the key factors in assessing writing called validity and reliability. The goal of this paper is to enrich the knowledge of the lecturer about the technique of assessing writing.
PRACTICAL ASPECTS OF REALIZING CYBERNETIC APPROACH IN THE FORMATION OF ECONOMIC LITERACY OF ARCHITECTURE PROGRAM STUDENTS

A currently topical problem of realizing the cybernetic approach in professional education is discussed. It is noted that the process of forming the information competence of specialists of college education can be effectively built if the concepts of the cybernetic approach in controlling students’ educational activities are taken into consideration. Subsystems of controlling the cybernetic approach in college education are revealed: objective, didactic, content, subjective, components and results. The didactic system that includes management strategies, modern software and iconography is described in detail.
Two-Dimensional Wavelet based Medical Videos using Hidden Markov Tree Model

Wavelet based statistical image denoising is vital preprocessing technique in real world imaging. Most of the medical videos inherit system introduced noise during acquisition as a result of additional image capturing techniques, resulting in the poor quality of video for examination. So, we needed a trade-off between preservation and noise reduction of the actual image content to retains all the necessary information. The existing techniques are based on time-frequency domain where the wavelet coefficients need to be independent or jointly Gaussian. In denoising arena there is a need to exploit the temporal dependencies of wavelet coefficients with non-Gaussian nature. Here we present a YCbCr (Luminance-Chrominance) based denoising strategy on Hidden Markov Model (HMM) based on Multiresolution Analysis in the framework of Expectation-Maximization algorithm. Proposed algorithm applies denoising technique independently on each frame of the video. It models Non-Gaussian statistics of each wavelet coefficient and captures the statistical dependencies between coefficients. Denoised frames are restored inversely by processing the wavelet coefficients. Significant results are visualized through objective as well as subjective analysis. Peak Signal-to-Noise Ratio (PSNR) and Structural Similarity Index Metric (SSIM) like parameters are used for the quality assessment of proposed method in comparison with Gray scale and Red, Green, Blue (RGB) scale videos coefficients.
GCDH@LT-EDI-EACL2021: XLM-RoBERTa for Hope Speech Detection in English, Malayalam, and Tamil

This paper describes approaches to identify Hope Speech in short, informal texts in English, Malayalam and Tamil using different machine learning techniques. We demonstrate that even very simple baseline algorithms perform reasonably well on this task if provided with enough training data. However, our best performing algorithm is a cross-lingual transfer learning approach in which we fine-tune XLM-RoBERTa.
How the Middle East used Social Media in 2020

This report is the ninth in an annual series of publications, dating back to 2012, showcasing the latest developments in social media across the Middle East and North Africa (MENA) region. This year’s study is produced in partnership with the New Media Academy. The New Media Academy was inaugurated in June 2020, by His Highness Sheikh Mohammed bin Rashid Al Maktoum, UAE Vice President and Prime Minister, and ruler of Dubai, to work within the space of development, with a focus on harnessing opportunities in the digital space. Using a broad range of industry, academic and media sources, we dive into the trends - and biggest stories - which shaped MENA’s relationship with social media during the past year. Not surprisingly, this study is heavily influenced by the impact of COVID-19. The novel coronavirus impacted on everyone’s lives around the world, including the Middle East. One by-product of the pandemic could be seen in our changing media habits. Social media usage - across all platforms - increased during the early stages of the outbreak. More widely, given the importance of social media in our media diets, platforms, industry and governments alike sought to use these networks to promote public health messages, as well as counter misinformation related to the COVID crisis. Alongside these developments, we have also seen continued investment in content on social media platforms - especially during Ramadan - and growing partnerships between traditional media players and social media channels and influencers. These developments reflect the popularity of high quality digital content consumed on social media, and a desire to reach audiences on these platforms, or bring existing social audiences onto other networks. We expect that this synergy will only rise, not least because many media habits developed during the pandemic may well continue post-COVID. As a result, social networks will become an increasingly important source for talent spotting, as well as a key avenue for content and information consumption. This trend, as we outline at the end of this report, matters for brands, creators and influencers, as well as governments and other public entities. Social media is already an important part of digital media habits and digital marketing strategies. In 2021, that importance looks set to continue and grow even further.
Comparative Study of Homogeneous Class and Heterogeneous Class of Participation Level and Result Learning in System Reproduction Classes of SMA/MA

The study is intended to determine how the differences between classes of homogeneous and class heterogeneous on the level of participation and the results of learning in class XI of the system of reproduction. The research is including field research with the approach of quantitative use study comparisons. Intake sample used technique purposive sampling and using three classes. the class is heterogeneous, class homogeneous male (M) and class heterogenous female (FM). Instruments retrieval of data using the data test multiple choice (posttest) and questionnaire level of participation. Mechanichal analysis of the data using a test statistic one way ANOVA and test Tukey as the test continued. The results of the study indicate that 1) the level of participation in class heterogeneous, class homogeneous male and class homogeneous female is not there differences in views of the value of the significant of 0,122 which means 0,122 &gt; 0,05 and Fcount of 2,185 &lt;Ftable. 2) The result of study on class of heterogenous, class homogeneous male, class homogeneous female there are differences in view on the value of significant of 0,000. Wich means that 0,000 &lt;0.05 and Fcount amounted to 52,657&gt; Ftable, based on test Tukey class that has the value of the results of studying the best is the class of homogeneous male.
Image and Text Steganography Using Convolutional Neural Network

Steganography has been used since centuries for concealment of messages in a cover media where messages were physically hidden. The goal in our project is to hide digital messages using modern steganography techniques. An N * N RGB pixel secret message (either text or image) is to be transmitted in another N * N RGB container image with minimum changes in its contents. The cover image also called the carrier can be publicly visible. In this project, along with LSB encoding, deep learning modules using the Adam algorithm are used to train the model that comprises a hiding network and a reveal network. The encoder neural network determines where and how to place the message, dispersing it throughout the bits of cover image. The decoder network on the receiving side, which is simultaneously trained with the encoder, reveals the secret image. The main aspect of this work is it produces minimal distortion to the secret message. Thus, preserving its integrity. Also, other steganography softwares cannot be used to reveal the message since the model is trained using a deep learning algorithm which complicates its steganalysis. The network is only trained once, irrespective of the different container images and secret messages given as inputs. Thus, this work has wide and secure applications in many fields.
CAPTURED: Crime Stoppers tip leads to New Jersey arrest of ID theft suspect wanted in Snohomish County

Acting on a Washington’s Most Wanted tip to Crime Stoppers of Puget Sound, East Brunswick, NJ Police arrested Jeremiah Wysocki.  On Thursday, July 29, 2021, Patrolman Robert Thuring and other East Brunswick Police Officers conducted surveillance at the Studio 6 Motel looking for Wysocki who I  featured for on Washington’s Most Wanted for Everett Police several times this year.
Research on Improving Teaching Ability of Young Teachers in Local Undergraduate Universities

This study presents the present teaching ability of young teachers in local universities and its influencing factors. In view of the insufficiency in the present situation, improvement measures are proposed. This study made use of the full time faculty members as respondents from China local undergraduate universities. Selected department chairpersons were also chosen for the FGD which helped the researcher come up strategies to enhance teachers' teaching ability-based from the findings on this study, the following conclusions : the young teachers’ teaching level is professional, but the causes, including unbalanced development teaching ability, teaching academic attitudes, the system construction and activity support factors influence teachers' teaching ability development, we need to strengthen the school performance appraisal and title appraisal system, increase the supply of faculty development activities, and improve the teachers’ attitude to students and teaching.
Status Quo of Entrepreneurship in the Mekong River Delta

In the context of an integrated economy with many opportunities and challenges, especially the Coronavirus disease (Covid-19) is causing many difficulties for all nations of the world, entrepreneurship is seen as an effective method to handle social problems and create new values for the economy. Promoting entrepreneurship in the Mekong River Delta is an urgent issue that determines each locality's long-term economic development potential. This study explores the status quo of entrepreneurship in the Mekong River Delta (MRD). The data for this study comes from two sources. First, secondary data was collected from three main publishments: (1) The report of Global Entrepreneurship Monitoring (GEM) about Entrepreneurship index in Vietnam 2017/2018, (2) 2017 Survey of Entrepreneurs and MSMEs in Vietnam, and (3) research papers related to entrepreneurship in the MRD. Second, primary data comes from the survey results of 406 graduates from colleges and universities in the MRD. The data was presented by graphs and tables. There are five key findings. First, entrepreneurial models in the MRD are not really creative and innovative. A mmajority of their products are popular and old, only 22,4% are new products. Second, business activities in the start-up stage, 41.1% of business operations have less than 25% foreign customers. Third, there are 93.3% of start-ups expect to create more than 6 jobs for the market. Fourth, 86% of people started a business because there was no better job choice. Fifth, commercializing and transferring scientific research results of the MRD’s government to the enterprise were evaluated the best in the ecosystem.
HANDICRAFTS MAKE DECORATIVE LAMPS FROM PLASTIC SPOONS AS A CREATIVITY EFFORT STKIP SINGKAWANG STUDENTS

&lt;p&gt;Decorative lights are one of the room accessories that can beautify the house. In addition to making the atmosphere of the house more cheerful, decorative lights can also be a simple solution to decorating a room without having to pay a fortune. In the modern era like today, people are increasingly creative in creating home gardens so that they become more beautiful. In the midst of society, various kinds of lamps are circulating in demand. Here, the team created a new, unique and interesting innovation, namely a decorative lamp in the shape of a lotus flower, made from an arrangement of plastic spoons attached to a used jar. This necessary material is quite easy to find and we find a lot in the environment around us because it is often used as daily necessities. There are many important factors that must be considered in order to promote this business, including choosing the right location, a good marketing strategy and determining a price that is affordable for the community. The business analysis of the handicrafts of decorative lamps from used bottles and plastic spoons includes a SWOT analysis. The team did this strategy to sell handicrafts from used jars and plastic spoons by promoting it. The budget for making handicrafts from used jars and plastic spoons is IDR 10,220,000. the schedule for the implementation of this craft for 3 months.&lt;/p&gt;
Computer-Aided Diagnostic System for Digital Mammography

In this work, Computer-Aided Detection (CADe) and Computer-Aided Diagnosis (CADx) systems are developed and tested using the public and freely available mammographic databases named MIAS and DDSM databases, respectively. CADe system is used to differentiate between normal and abnormal tissues, and it assists radiologists to avoid missing a breast abnormality. At the same time, CADx is developed to distinguish between normal, benign and malignant breast tissues, and it helps radiologists to decide whether a biopsy is needed when reading a diagnostic mammogram or not. Any CAD system is constituted of typical stages including preprocessing and segmentation of mammogram images, extraction of regions of interest (ROI), features removal, features selection and classification. In both proposed CAD systems, ROIs are selected using a window size of 32×32 pixels, then a total of 543 features from four different feature categories are extracted from each ROI and then normalized. After that, the selection of the most relevant features is performed using four different selection methods from MATLAB Pattern Recognition Toolbox v.5 (PRtool5) named Sequential Backward Selection (SBS), Sequential Forward Selection (SFS), Sequential Floating Forward Selection (SFFS) and Branch and Bound Selection (BBS) methods. We also utilized Principal Component Analysis (PCA) as the fifth method to reduce the dimensions of the features set. After that, we used different classifiers such as Support Vector Machines (SVM), K-voting Nearest Neighbor (K-NN), Quadratic Discriminant Analysis (QDA) and Artificial Neural Networks (ANN) for the classification. Both CAD systems have the same implementation stages but different output. CADe systems are designed to detect breast abnormalities while CADx system indicates the likelihood of malignancy of lesions. Finally, we independently compared the performance of all classifiers with each selection method in both modes. The evaluation of the proposed CAD systems is done using performance indices such as sensitivity, specificity, the area under the curve (AUC) of the Receiver Operating Characteristic (ROC) curves, the overall accuracy and Cohen-k factor. Both CAD systems provided encouraging results. These results were different corresponding to the selection method and classifier.
Improving Student’s Writing Achievement Through Multiple Intelligences

The aim of this research was to find out whether there was a significant difference of students’ writing achievement before and after being taught through students’ multiple intelligences. The sample of the research was eleventh grade students of Islamic high school in Sekayu, Musi Banyuasin, South Sumatera. The research was conducted by applying quasi experimental in terms of pretest – posttest non- equivalent group design. The sample of this research was 62 science students. The Mean of posttest’s score was higher than pre-test. It means that there is an increase of students’ writing achievement after being taught through their multiple intelligences.