Reviewerly/exHarmony huggingface dataset:
Extra-Curricular Staff Perceptions of Extra-Curricular: A Case Study through the KJ Method

Objectives This study is to find out the perceptions of extra-curricular staffs and department team leaders about extra-curricular in universities and to explore the future development direction of non-specialty education based on this.&#x0D; Methods Data were collected by performing FGI for 16 extra-curricular staffs and department team leaders, and the collected data were qualitatively analyzed based on the KJ method to derive new ideas from heterogeneous information. The analysis process of the KJ method consists of four steps: label making, group organization, illustration, and narrative.&#x0D; Results After going through the KJ method analysis process, finally looking at the employee's perception of extracurricular education in the order of the number of labels are as follows. First, the result of staff’s perceptions of extra-curricular are Suggestion of operation direction(58), Identification of problematic situation(38), Status(30), Performance(29), Difficulty in operation(25), and Operation effort(13) were derived in the order. There are 6 groups with a total of 193 labels, and each group consists of 2 groups at 5th level, 3 groups at 4th level, and 1 group at 3rd level. Second, the team leaders were derived from the group in the order of Suggestion of operation direction(33), Performance(19), Identification of problematic situation(16), Awareness of the definition and characteristics of extra- curricular(7), which consists of four groups consisting of a totla of 75 labels, with one group of five to two stages.&#x0D; Conclusions The trial and results of this study are meaningful in that they provide specific information for establishing strategies to derive effective non-extra-curricular education operations and outcomes in the future.
A Change in the Educational Gap in the East and West Regions of Daejeon Metropolitan City: Focusing on Elementary Schools

Objectives This study analyzes the living and educational conditions that affect the education gap in the eastern and western regions of Daejeon Metropolitan City, and tries to find out how the education gap in Daejeon is changing through interviews with local elementary school teachers.&#x0D; Methods In order to study the changes in living and educational conditions in the eastern and western regions of Daejeon Metropolitan City, data from the Statistics Korea and the Educational Statistical Yearbook of the Daejeon Metropolitan Office of Education were used. Also, a focus group interview was conducted on elementary school teachers. The target was a teacher who worked at an elementary school in the Daejeon Metropolitan Office of Education and had experience working at both schools in the east and west. Through FGI, We suggest a way to bridge the educational gap.&#x0D; Results The living and educational conditions of Seo-gu (Seo-gu, Yuseong-gu) and Dongbu (Jung-gu, Dong-gu, Daedeok-gu) of Daejeon Metropolitan City were analyzed. In almost all regions, the east was inferior to the west, and the difference was deepening over time. In addition, elementary school teachers felt that the educational gap between the eastern and western regions of Daejeon Metropolitan City was widening.&#x0D; Conclusions Guarantee policies for vulnerable students should be more aggressively implemented. Support standards should be refined and the level and causes of educational disparities by administrative district and school should be in-depth investigated so that customized support can be provided according to the characteristics of each school. In particular, it is necessary to take a multi-pronged approach, such as promoting policies that guarantee basic academic ability, expanding students' educational experiences, and raising students' interest in learning at home. Finally, since this problem is not limited to education, it is suggested that all members of Daejeon Metropolitan City should be aware of the current situation and solve it together.
The Automorphism Group of $NU(3,q^2)$

Let $H(n, q^2)$ be a non-degenerate Hermitian variety of $PG(n,q^2)$, $n \geq 2$. Let $NU(n+1,q^2)$ be the graph whose vertices are the points of $PG(n,q^2) \setminus H(n,q^2)$ and two vertices $u,~v$ are adjacent if the line joining $u$ and $v$ is tangent to $H(n, q^2 )$. Then $NU(n + 1, q^2)$ is a strongly regular graph. In this paper we show that the automorphism group of the graph $NU(3,q^2)$ is isomorphic either to $P\Gamma U(3,q)$, the automorphism group of the projective unitary group $PGU(3,q)$, or to $S_{3} \wr S_{4}$, according as $q \neq 2$, or $q=2$.
Distance learning is a social risk factor

The article is devoted to an actual problem – distance learning. Distance learning is a qualitatively new progressive type of training based on modern information technologies and means of communication, the rapid surge of which is caused by the pandemic that has engulfed most of the planet. Interest in the study of the realities of post-industrial society is dictated by the need to study the nature of the transformations that occur with a person under the influence of those technological changes that have penetrated into all spheres of human existence: on the one hand, a new environment is being formed, opening up unlimited opportunities for the accumulation and transmission of information, communication in electronic network communities, on the other – these acquisitions carry potential threats and risks in both the distant and foreseeable future, and to a greater extent, in our opinion, the expected consequences of global modernization pose the greatest threat to such a specific area as education. The subject that caused the greatest number of the most acute discussions was the impact of distance learning on the quality of training of future specialists, on the degree of development of their communication skills. The main task of the article is to justify and argue distance learning as a new form of learning, to identify its problems and positive aspects. The article presents an analysis of theoretical approaches to distance learning for Russian and foreign researchers. Based on the results of a sociological study, the attitude of students to distance learning is revealed, and their assessment of the degree of development of their own communication skills in remote learning is obtained. The authors conclude that distance learning to a certain extent becomes a risk factor, depriving students of the opportunity to develop the qualities that modern conditions require of them: self-organization, self-control, and communication skills. Despite the fact that distance learning has become an integral part of the educational process, we are convinced that this form should only be a part, a component of the educational process, a "safety cushion" in a situation of force majeure. The leading form of educational classes at the university should remain the traditional classroom form of conducting classes as the only form that can prepare a person for life and successful functioning in a risk society
PSYCHOLOGICAL ASPECTS OF FORMING THE MODERN TEACHER’S PROFESSIONAL IMAGE

The article reveals the psychological aspects of forming the modern teacher’s professional image. It has been noted that the new standards of higher education increase the level of attention and requirements for the personality, professionalism and competence of future teacher, that calls out the necessity of forming the new style of social behavior. The conceptual approaches to forming the modern teacher's professional image are analyzed. It has been noted that this problem was considered by scientists in the context of psychology of individuality, formation of «I-concept» of personality, imageology, forming of pedagogical image and professional image of «I» of the future teacher, pedagogical skills of educators. It has been established that the image is a complex psychological and pedagogical phenomenon, a kind of program of human social behavior and concentrates the most important professional characteristics, which are presented through appearance and professional qualities. The teacher’s professional image is considered as a form of self-expression of the individual holistic image of personality as a realizer of the needs of micro- and macro-society in the educational services, which reveals the most expressive business and personal qualities. The teacher’s image is formed gradually and it is a method of influence on personality, a way of self-regulation and self-suggestion, the most important element of preparation for professional activity. The presented results of the empirical study ascertain that special attention should be focused on higher education, the purpose of which is to train young people competitive in the modern labor market. Therefore, the problem of creating and consolidating a positive image of young specialists who, due to little pedagogical experience, have difficulties with finding the most optimal ways of behavior in professional activities is relevant. Key words: image, professional image, structure of professional image, image functions, types of image, teacher’s image activity.
A Data-to-Image Mechanism Based on Feature Correlation for Wireless Intrusion Detection

Abstract With the rapid development of technology networks, the security problem of wireless networks is becoming more serious. Among the existing related research works on wireless network intrusion detection, Artificial Neural Network (ANN) and Deep Neural Network (DNN) are the most widely used models which can better handle multidimensional data without considering the influence of feature correlation on the results. Therefore, this study proposes an approach that calculates the feature correlation to convert non-image data into images and combines feature selection and feature extraction to improve the accuracy of CNN model detection. This approach calculates the Pearson, Spearman, and Kendall correlation coefficients to sort the features into 1D or 2D images according to the highest to the lowest correlational order. The experiment adopts the Aegean Wi-Fi Intrusion Dataset (AWID). The result shows that the best accuracy of the CNN is 99.574%, and the average accuracy is much higher than that of the DNN for non-image data.
Better semantic embeddings lead to better ZSL performance

Zero-Shot Action Recognition (ZSAR) is a thriving field as a result of the increasing diversity ofaction classes that have presented new difficulties for video comprehension. By using semanticrepresentations to connect observed and unseen events, the ZSAR challenge tries to recognise target(unseen) activities without training examples. It is still difficult to semantically characterise actionclasses and transmit knowledge from observed data due to the complexity and diversity ofactivities. Initially, semantic embeddings used were word2vec embeddings of each class label. Ithas been seen using better embeddings such as sen2vec or more recently elaborate class definitionsleads to best results. Using current action recognition datasets (like UCF101), the conventionalevaluation technique randomly divides the classes into seen and unseen. The majority of recentresearch, however, builds on pre-trained representations from the Kinetics dataset, whose classessubstantially overlap with classes from the zero-shot dataset assessment datasets. Consequently,classes that are meant to remain hidden, are present, negating the need of the premise for zero shotlearning.
RRSC-128AEAD: An Efficient Randomized Lightweight Stream Cipher Supports Authenticated Encryption with Associated Data

Abstract A proposed stream cipher, RRSC-128AEAD, supports authenticated encryption with associated data (AEAD) for checking both the authenticity and integrity of the message. This cipher includes a key and a nonce of size 128-bit each as input. It produces two different pseudo-random bit streams in parallel. One is used for encryption and another one is used for authentication purposes. It generates 64-bit MAC, based on the National Institute of Standards and Technology standardized (NIST) value, for lightweight security. The cipher efficiency in terms of randomness is analyzed by an online NIST statistical test suite. The design is compared with NIST standardized stream cipher GRAIN-128AEAD. The proposed cipher proves its efficiency in key reintroduction and probability of avoiding key leakage compared to GRAIN-128AEAD. Although both cipher initialization times are the same, some features like two independent bit streams, large internal states, and variable-length associated data and masking technique together made this proposed cipher stronger and more efficient against various types of attacks.
Sustainability and Scalability of Digital Tools for Learning: ABRACADABRA in Kenya

This paper explores factors to increase the likelihood that the implementation of ABRACADABRA, a technology-based approach to teaching and learning literacy, endures and expands beyond the initial research. Started as a pilot study in 12 classrooms, the implementation spread to more than 500 primary classrooms over six years in five areas of Kenya. Drawing from research about scalability and sustainability of educational interventions and value-expectancy-cost theory, an exploratory survey was designed to interview a range of actors involved in the software implementation. We used a combination of an a priori and data-driven coding approaches to analyse the narratives. We then built a model exploring the relationship between expectancy-value-cost beliefs and the factors associated with implementation and sustainability. The model explained an important portion of variance in the self-reported intent to use the software with the most significant contributions from policies, professional development, and students. These findings may be useful in the context of low- and medium-income countries where no research-proven principles exist to building sustainable and scalable educational interventions.
System characterization report on the Amazônia-1 multispectral sensor

First posted August 22, 2022 For additional information, contact: Director, Earth Resources Observation and Science (EROS) CenterU.S. Geological Survey47914 252nd StreetSioux Falls, SD 57198Contact Pubs Warehouse This report addresses system characterization of the Instituto Nacional de Pesquisas Espaciais Amazônia-1 satellite and is part of a series of system characterization reports produced and delivered by the U.S. Geological Survey Earth Resources Observation and Science Cal/Val Center of Excellence. These reports present and detail the methodology and procedures for characterization; present technical and operational information about the specific sensing system being evaluated; and provide a summary of test measurements, data retention practices, data analysis results, and conclusions.Amazônia-1 is a four-band imager with a 64-meter (m) pixel ground sample distance. Amazônia-1 was launched in February 2021 into a Sun-synchronous orbit of 752 kilometers with an inclination of 98.4 degrees and a swath width of 850 kilometers. The satellite has an expected lifetime of about 4 years. More information on Amazônia-1 is available in the “Land Remote Sensing Satellites Online Compendium” (https://calval.cr.usgs.gov/apps/compendium) and from the Instituto Nacional de Pesquisas Espaciais website (http://www.inpe.br/amazonia1/en/about_satellite/).The Earth Resources Observation and Science Cal/Val Center of Excellence system characterization team completed data analyses to characterize the geometric (interior and exterior), radiometric, and spatial performances. Results of these analyses indicate that the Amazônia-1 satellite has an interior geometric performance in the range of −3.584 m (−0.056 pixel) to 0.320 m (0.005 pixel) in easting and −1.984 m (−0.031 pixel) to 2.048 m (0.032 pixel) in northing in band-to-band registration, an exterior geometric performance of −37.256 m (−0.621 pixel) to 54.758 m (0.913 pixel) in easting and −12.684 m (−0.211 pixel) to 54.898 m (0.915 pixel) in northing offset in comparison to the Landsat 8 Operational Land Imager, a radiometric performance in the range of 0.030 to 0.143 in offset and 0.662 to 0.825 in slope, and a spatial performance in the range of 1.62 to 2.06 pixels for full width at half maximum, with a modulation transfer function at a Nyquist frequency in the range of 0.062 to 0.115.
Feasibility Study on Intra-Grid Location Estimation Using Power ENF Signals

The Electric Network Frequency (ENF) is a signature of power distribution networks that can be captured by multimedia recordings made in areas where there is electrical activity. This has led to an emergence of several forensic applications based on the use of the ENF signature. Examples of such applications include estimating or verifying the time-of-recording of a media signal and inferring the power grid associated with the location in which the media signal was recorded. In this paper, we carry out a feasibility study to examine the possibility of using embedded ENF traces to pinpoint the location-of-recording of a signal within a power grid. In this study, we demonstrate that it is possible to pinpoint the location-of-recording to a certain geographical resolution using power signal recordings containing strong ENF traces. To this purpose, a high-passed version of an ENF signal is extracted and it is demonstrated that the correlation between two such signals, extracted from recordings made in different geographical locations within the same grid, decreases as the distance between the recording locations increases. We harness this property of correlation in the ENF signals to propose trilateration based localization methods, which pinpoint the unknown location of a recording while using some known recording locations as anchor locations. We also discuss the challenges that need to be overcome in order to extend this work to using ENF traces in noisier audio/video recordings for such fine localization purposes.
Mask Detection Using Convolutional Neural Network Algorithm

The World Health Organizations and the Ministry of Health of the Republic of Indonesia have required the use of masks to suppress the spread of COVID-19. WHO provides guidance on how to use a good mask to cover the mouth and nose. This study aims to detect the correct use of masks using the Convolutional Neural Network. CNN is a popular Deep Learning algorithm for image data classification problems. The Mask Usage Detector is built with the help of a pre-trained MobileNetV2 model with an architecture that supports media that has minimum computations. This study will also compare the performance of three optimization methods from CNN, namely Adam, SGD, and RMSprop in detecting the use of masks. Performance will be seen from the test results by analyzing the values of accuracy, precision, and recall. The dataset used is in the form of image data of 2,029 images for 2 categories, namely "masked" and "unmasked". A total of 1,623 images were used as training data and 406 images for test data. Based on the testing process, the accuracy of each optimization is 93.84% with Adam optimization, 84.48% with SGD optimization, and 93.10% with RMSprop optimization. With the proposed model, this study obtains the performance results of the three CNN optimizations, and it is concluded that adam's optimization gives better performance results than the other two optimizations.&#x0D;
ILLOCUTIONARY ACTS AND REPRESENTATIVE FUNCTION ON ENGLISH SPEECHES YOUTUBE CHANNEL

This study aims to figure out the kinds of illocutionary acts and furthermore the function of representative performed by the inspirations of American motivators in the persuasive recordings in the English Speeches Youtube channel. This research is a qualitative descriptive study. The subjects of this examination are four videos from notable inspirations from America in English Speeches YouTube channel. In the wake of posting, choosing, and gathering the videos, the videos were watched a few times to facilitate the scientist in interpreting them. In dissecting the information, the researcher just takes utterances that permit the motivators to pass their expectations on to the audience members. The illocutionary act information performed by the motivators were arranged utilizing the instrument following Searle's hypothesis and the functions of representative performed by the motivators were grouped utilizing the instrument following Searle's hypothesis too. The main tracking down shows five sorts of illocutionary acts performed by motivators, specifically representative, directive, commissive, declarative and expressive. The subsequent tracking down shows every one of the six sorts of representative functions performed by the inspiration motivators are claiming, predicting, stating, reporting, describing, and complaining. By performing five sorts of illocutionary acts, motivators might have different approaches to communicating their expectations to audience members. In the interim, motivators can likewise do different ways to fulfill the motivation behind their demeanor through the function of representative.
Pengaruh Perilaku Belajar, Kecerdasan Emosional Dan Sistem Pembelajaran Online Terhadap Pemahaman Akuntansi

This study aims to determine the magnitude of the influence of learning behavior, emotional intelligence and online learning systems on accounting understanding. The method used in this research is quantitative with primary data in the form of distributing questionnaires to respondents. The sampling technique used purposive sampling technique, obtained a total sample of 106 students. The data analysis technique used in this research is multiple linear regression analysis technique. The results of this study indicate that learning behavior and emotional intelligence have no significant effect on accounting understanding, while the learning system has a significant effect on accounting understanding.
Analisis E-learning Universitas Muhammadiyah Palembang Pada Mahasiswa Menggunakan Metode System Usability Scale

The exchange of information with technology makes the teaching and learning process easier. At Muhammdiyah University Palembang (UMP) has created a web called E-learning to facilitate students as an online learning tool and send assignments in the form of document and video files, research and knowledge that provides facilities and services that can be utilized for UMP students. This study aims to measure the level of satisfaction of E-Learning users as supporters in the learning process at UMP tertiary institutions. The method used for this study uses the System Usability Scale (SUS) method, where this method has 10 questions and 5 Usability Testing variables. After testing 85 UMP students of the Faculty of Law, the results according to the SUS scale have an average value of: 71.6. This result is included in the Acceptable category with Grade C and it can be said that UMP E-learning is good in terms of use and has an above average score.&#x0D; Keywords:UMP, E-learning, System Usability Scale