Reviewerly/exHarmony huggingface dataset:
Modern methods of teaching physics in universities

The article analyzes the difficulties faced by physics teachers in higher educational institutions. The modern information-communication and educational technologies are considered, which make it possible to improve the quality of teaching physics and the assimilation of the discipline by students. The role of distance learning (DL) is emphasized in the context of a limited number of hours devoted to physics. The article examines the global trends in the development of distance learning, analyzes the role of this form of education in the modern educational process and the factors affecting the development of DL. Attention is drawn to the difficulties of implementing a virtual laboratory practice, without which it is impossible to implement full-fledged teaching of physics remotely. The use of virtual works allows observing the main principle of didactics – visualization.&#x0D; Visibility provides optimal assimilation of the material by increasing the emotional perception of the material and the use of all types of thinking in students. The need for high realism of experiments in virtual laboratories, accuracy of reproduction of the physical laws and the essence of experiments and phenomena. This allows students to develop skills in experimental work.&#x0D; The implementation of high variability in the conduct of experiments and initial data allows you to increase the efficiency of using a laboratory practice in computer classes. The paper discusses the most available software tools for creating.&#x0D; In the article analyzes modern teaching technologies, the application of which radically changes the approach to the educational process. In the article discusses such popular and effective brands of educational technologies as adaptive web resources Cerego, Grockit, Smart Sparrow, as well as adaptive technologies based on distance learning systems – Blackboard, Desire2Learn, ILIAS, Lotus Learning Space, Moodle allowing to analyze the level of learning student teaching material. The high potential possessed by mobile technologies in the distance-learning environment is noted.
A Study on Forecasting for Korean Second-hand Automobile Market Transactions

This study has made a valuable contribution in clarifying the overall size of the Korean automobile market by estimating the size of Korean used car transactions. Data from 1985 to 2018 were used in the study and the main contents are summarized as follows. The Korean used car transactions has maintained a steady upward trend since the 1980s, with a significant increase in transactions per year in 2010 and 2011 in particular. Through this research, it was confirmed that it was due to the advancement of IT infrastructure by the Ministry of Land, Infrastructure and Transport that a dummy year was used for 2010 and 2011. As a result of preliminary analysis, it was found that the variable that has a statistically significant effect on used car transactions is new car sales. In addition, the per capita income variable has a statistically significant effect on new car sales. The reg-ARIMA (p, d, q) model was applied to the analysis to reflect the pre-analysis results. In addition, the forecast of the GDP of the Bank of Korea and OECD by the year 2030 and population forecasting data were used for the analysis. In the Korean automobile market from 1985 to 2018, it is estimated that used car transactions will increase by 0.298 when one new car sales increase. We estimated the real GDP per capita by 2030 based on the estimation of income by the BOK, the OECD, and the future population prediction of the Statistics Korea. The growth of real GDP per capita in 2019 and 2020 is estimated to be 2.0%, 2.3%, 2.6-3.0% by 2020-2024, and 2.2-2.5% in 2026-2030. Considering the possibility of errors in the predictions used in the study, the optimistic scenarios assuming a 1% higher economic growth rate than the previous predictions and the situation of 1% lower pessimistic scenarios were considered. In the optimistic scenario, the annual growth rate of real GDP per capita will be between 3.0-4.0% between 2019 and 2030, and between 1.0-2.0% during the same years in pessimistic scenarios. According to estimates using the BOK and OECD estimates, the real GDP per capita, which was 33.3 million won in 2018, will increase to 44.8 million won in 2030, 50.4 million won in the optimistic scenario and 39.8 million won in the pessimistic scenario. New car sales increased from 1.53 million in 2018 to 1.46 million in 2030, 1.69 million in the optimistic scenario, and 1.22 million in the pessimistic scenario. Used car transactions increased from 3.77 million in 2018 to 4.51 million in 2030, 4.58 million in optimistic scenario and 4.44 million in pessimistic scenario.
MLinPL Keynote: Some fun examples from the intersection of machine learning and physics

Abstract: Machine learning and physics have a long history of interactions. Many machine learning techniques have roots in physics, and machine learning techniques have been applied to problems in physics for years. But this interaction has intensified recently, and the interplay touches on many of the most interesting contemporary topics in deep learning including understanding of generalization, generative models, causality, inductive bias, and inference. I will describe some of the results and exploratory work that is being done in this direction.
Deteksi SMS Spam Berbahasa Indonesia menggunakan TF-IDF dan Stochastic Gradient Descent Classifier

Short Message Service (SMS) has evolved in the last few decades. The simplicity of SMS makes this short message service attractive to use as a direct communication service on mobile devices. As the popularity of this service increases, it also harms attacks on mobile devices such as SMS spam. Spam SMS are short messages that the recipient doesn't want, such as advertisements and scams. Spam SMS can overwhelm your inbox and make your mobile device experience less good. One way to overcome this problem is to implement a machine learning model to automatically recognize and filter Spam SMS. This research aims to build a machine learning model that provides higher accuracy for detecting SMS spam in Indonesian using the TF-IDF method and the Stochastic Gradient Descent Classifier. Based on the test results, the model built can detect SMS spam and not spam with an accuracy of 97%.
32 Sleep quality, mental health, and circadian rhythms during COVID lockdown – results from the SleepQuest study

<h3>Introduction</h3> Behavioural responses to COVID-19 lockdown will define the long-term impact of psychological stressors on sleep and brain health. Here, we tease apart factors that help protect against sleep disturbance. We capitalise on the unique restrictions during COVID-19 to understand how time of day of daylight exposure and outside exercise interact with chronotype and sleep quality. <h3>Methods</h3> Participants completed our online ‘SleepQuest’ Study between 29th April 2020- 13th May 2020 and were followed up between 5th November 2020 -2nd December 2020. The SleepQuest survey comprised a set of validated questionnaires probing sleep quality, depression, anxiety, and attitudes towards sleep alongside bespoke questions on the effect of COVID-19 lockdown on sleep, time spent outside and exercising and self-help sleep measures. <h3>Results</h3> 3474 people from the UK (median age 62, range 18-91) completed the baseline data with 2781 participants followed up. Results showed sleep quality was negatively affected by the first UK lockdown restriction [mean PSQI at baseline 8.12 (2.92)] however from baseline to follow up, sleep quality improved (mean PSQI Difference=2.21; 95% CI=[2.12,2.33.]) Factors that predicted poor prolonged sleep quality were baseline sleep quality (P&lt;0.001), anxiety (P&lt;0.001) and attitudes towards sleep (P&lt;0.01). Better sleep quality was associated with going outside and exercising earlier, rather than later in the day. However, the benefit of being outside early is driven by improved sleep in ‘owl’ (p=0.0002) and not ‘lark’ (p=0.27) chronotype, whereas the benefit of early exercise (inside or outside) did not depend on chronotype. <h3>Discussion</h3> We have provided evidence to suggest anxiety and dysfunctional attitudes towards sleep predicted poorer prolonged sleep quality. Defining the interaction between chronotype, mental health and behaviour will be critical for targeted lifestyle adaptations to protect brain health through current and future crises.
DETECTION OF OSTEOPOROSIS IN PANORAMIC IMAGE RADIOGRAPH AREA OF MANDIBLE BONE USING HARRIS CORNER DETECTION

Every human will grow older. The aging process in a person is characterized by osteoporosis. Osteoporosis is a person's bone condition becomes porous and fragile. Marked by a decrease in bone tissue that is easily fragile or broken, a bent back and a shorter body. Alternative detection of osteoporosis can be done by X-ray image of the jaw bone from dental panoramik which analyzed the texture using machine learning and image processing techniques. Harris Corner Detection is a corner detection system that is often used because it is able to produce consistent values in images that experience rotation, scaling, variations in lighting and having lots of noise. Angular detection using the Harris method is based on variations in signal intensity. A large variation in intensity indicates the angle of the image. In the process of osteoporosis detection system using image processing, it is started from preprocessing, processing and final results. The data used in the study were 152 data, with 3 stages of classification, namely : 3-20 years old, 20-40 years old and 40-71 years old group. Based on the expert validation calculation that has been done, the percentage of suitability of the 3-20 years old group is 100%, group 20-40 years old is 98.78%, age group 40-71 years old is 76.47%.
Collision Avoidance for a Car-like Mobile Robots using Deep Reinforcement Learning

—The applications of mobile robots are more and more diverse and extensive. The motion planning of the mobile robots should be considered in aspect of effectiveness of the navigation, and collision-free motion is essential for mobile robots. In addition, dynamic path planning of unknown environment has always been a challenge for mobile robots. Aiming at navigation problems, this paper proposes a Deep Reinforcement Learning (DRL) based path planning algorithm which can navigate nonholonomic car-like mobile robots in an unknown dynamic environment. The output of the learned network are the robot’s translational and angular velocities for the next time step. The method combines path planning on a 2D grid with reinforcement learning and does not need any supervision. The experiments illustrate that our trained policy can be applied to solve complex navigation tasks. Furthermore, we compare the performance of our learned controller to the popular approaches. Keywords— Deep reinforcement learning, path planning, , artificial neural network, mobile robot, autonomous vehicle
STUDENTS’ ERRORS IN WRITING SIMPLE PRESENT TENSE AT COUNSELING DEPARTMENT OF ACHMAD YANI UNIVERSITY

Students’ Errors in Writing Simple Present Tense at Counseling Department of Achmad Yani University. The objective of this study is to analyze the students’ errors in writing sentences in simple present tense. The scope of the research is focused on one tenses namely simple present tense. Research method was used in this research is descriptive qualitative. Based on the result of the research, the researcher could conclude that most of subject or sample of the research did mistakes in misinformation because they write wrong in grammatical form and made the sentences were incorrect
Pengenalan Anatomi Tubuh Menggunakan Teknologi Augmented Reality Berbasis Android

Media aplikasi pembelajaran dapat mempermudah sarana dalam pembelajaran di berbagai bidang pendidikan khususnya tentang pengenalan anatomi tubuh, namun saat ini masih minim tersedianya suatu aplikasi mobile terkait hal tersebut yang dapat meningkatkan minat belajar bagi siswa dan masyarakat terutama pendidikan pada anak usia dini. Penelitian ini ditujukan untuk mengembangkan sistem pengenalan anatomi tubuh manusia menggunakan teknologi Augmented Reality berbasis Android. Metode penelitian ini adalah metode MDLC (Multimedia Development Life Cycle) dengan tahapannya meliputi: Concept, Design, Material Collecting, Assembly, Testing, dan Distribution. Data penelitian diperoleh melalui observasi, wawancara, studi literatur. Hasil penelitian diperoleh berupa aplikasi pengenalan anatomi tubuh manusia menggunakan teknologi augmented reality yang dapat membantu siswa maupun masyarakat dalam mencari informasi serta menjadi sarana media pembelajaran mengenai organ tubuh manusia. Adapun media pembelajaran augmented reality dapat memvisualisasikan konsep abstrak untuk pemahaman dan struktur suatu model objek dan memungkinkan augmented reality sebagai media yang lebih efektif sesuai dengan tujuan dari media pembelajaran.&#x0D; &#x0D; &#x0D; It is widely known that a mobile learning application can facilitate learning in various fields of education, including the introduction to human anatomy topic. However, the current availability of a mobile application associated with the topic remains insufficient despite its use to improve the student’s and community’s interest to learn, particularly in early childhood education is effective. The research aims to develop a system of introduction to human anatomy by using android-based augmented reality. The method employed in this research is Multimedia Development Life Cycle (MDLC), where its stages comprise concept, design, material collecting, assembly, testing, and distribution. The research data are collected through observation, interview, and literature study. The research result is in the form of application to introduce human anatomy by using augmented reality technology that can assist students or community in seeking information and be a learning media to introduce the human anatomy. In addition, the augmented reality media can visualize an abstract concept for comprehension and structure of object model where it enables the augmented reality to be a more effective media to meet learning media goals.
THE EFFECTS OF ONLINE LEARNING ON PG-PAUD STUDENTS’ ENGLISH LEARNING ACHIEVEMENT ASSESSED FROM THEIR PRIOR KNOWLEDGE IN THE EVEN SEMESTER OF 2019/2020 ACADEMIC YEAR

In the midst of the current outbreak of the Covid-19 virus, online learning, including learning English, is the right choice. This type of learning in its implementation requires supporting applications. Among the applications that can be used for learning English include Zoom, and Google Classroom. The use of these applications will be examined through this research. The use of this application aims to see the increase of ability in learning English course, namely in terms of reading skill. The participants in question are 12 2018 students majoring in Early Childhood Education (PG-PAUD) who, in the even semester of the 2019/2020 Academic Year, took the course English for Scientific Works, so at the same time, they are the samples of this research. The method used in this research is descriptive qualitative and the design is a case study. The results show that the participants can improve their English skills, especially in reading and writing, through this online learning. The proof is that their scores, both in every meeting and mid-term or last-term test, have always improved. Keywords :  Online Learning, Learning Achievement, English
LibGuides: Computer Engineering Libguide: E-Journals

This guide introduces Computer engineering students to the library and internet resources available to them at the Benedict College Library.
Video Conferencing enhances work credibility and efficiency during COVID 19

AbstractPresent study was carried out among 150 employees of two different types of organizations to assess themodes and barriers in communication in the organizations before and during lockdown due to Covid-19Pandemic. The employees held the opinion that transparency in communication could be maintainedthrough video conferencing. Video conferencing was found to be the most preferred one during theCovid-19 pandemic whereas face to face communication was preferred before the Covid-19 pandemicLanguage and linguistic accent used are found to be the most common barriers. During the pandemictechnological advancement has made communication effective in order to run the daily businessefficiently without putting employee’s life at stake. But lack of technological infrastructure developmentand language competency as in terms of accent and other small details was found to be a barrier asevaluated by theemployees.
Resub_Appendix_v1.1 – Supplemental material for Processes and Experiences of Creative Cognition in Seven Western Classical Composers

Supplemental material, Resub_Appendix_v1.1 for Processes and Experiences of Creative Cognition in Seven Western Classical Composers by Andrea Schiavio, Nikki Moran, Dylan van der Schyff, Michele Biasutti and Richard Parncutt in Musicae Scientiae
THE PECULIARITIES OF USING THE CONTEXTUAL LEARNING DURING THE MASTERING OF STUDY MATERIAL

One of the areas of educational activity is the use of innovative technologies that allow students to discover the inner potential of the individual and opens their new trajectories for self-realization. The paper reflects the features of using one of the areas of innovative technologies - the contextual learning. The role of the teacher and the student in the project implementation is determined, the advantages in the assessment of students and the prospects of this method in achieving the main goal of the higher education institution - the formation of a specialist as a competitive person.
The Administrative Skills Required for Basic School Principals as seen by the Teachers of These Schools in Irbid Governorate: المهارات الإدارية المطلوبة لمديري المدارس الأساسية كما يراها معلمو ومعلمات تلك المدارس في محافظة إربد

The study aimed to identify the Administrative skills required for school principals as perceived by the teachers of those schools. The researcher used the descriptive survey approach, and the tool consisted in a questionnaire consisting of (56) items distributed into seven areas that were distributed to a random sample of (250) teachers from all basic schools In Irbid Governorate, and they represent (6%) of the study population of (4150)teacher. It showed the results of the study; The general management skills of basic school principals as perceived by teachers in Irbid governorate attain an overall average (4.15 out of 5), i.e. with a (large) level of application, and at the level of fields. The area of ​​self-skills got the highest average (4.36), then the field of time management with an average (4.27), both of them with (very large), the third of which is the area of ​​financial resources management with an average (4.14), and fourth is the area of ​​decision-making with an average (4.13), and the fifth is the area of ​​strategic planning with an average (4.12), sixth in the field of information technology with an average of (4.05), and finally in the field of community service with an average of (3.86), all of which have an application estimate of (large), and the results also showed that there are no statistically significant differences at the level of significance (α= 0.05) attributed to the two variables (sex, and experience), while statistically significant differences were found at (α=0.05) due to the effect of qualification and the differences came in favor of bachelor's holders. Based on the results, the researcher presented a set of recommendations and proposals to upgrade the administrative skills of principals of basic schools in the governorate of Irbid and the whole Kingdom of Jordan.
Using Mobile Biometrics and Management Information Systems to Enhance Quality and Accountability of Cash transfer in a Girls’ Empowerment Program in Rural and Urban Poor Settings

Information and Communication technology for social protection (ICT4SP) has improved the targeting and identification of beneficiaries, while mitigating benefit fraud within the delivery of safety net and Conditional cash transfer (CCT) programs. However, poor telecommunication and power infrastructure hamper the implementation of ICT tools in low resourced and hard to reach environments. In this paper we describe how we used a mobile biometric fingerprint identification and a management information system within a randomized control trial design program to identify girls in an urban slum environment and remote arid rural area; and discuss contextual strengths and challenges encountered. Use of mobile biometrics and management information system enhanced the quality and accountability of the CCT program. The mobile biometrics system ensured accurate identification of participants, while the MIS enabled increased accountability and efficiency in the disbursement of benefits. The paper also reports challenges experienced that needed multifaceted approaches.
SOFT: Softmax-free Transformer with Linear Complexity

Vision transformers (ViTs) have pushed the state-of-the-art for various visual recognition tasks by patch-wise image tokenization followed by self-attention. However, the employment of self-attention modules results in a quadratic complexity in both computation and memory usage. Various attempts on approximating the self-attention computation with linear complexity have been made in Natural Language Processing. However, an in-depth analysis in this work shows that they are either theoretically flawed or empirically ineffective for visual recognition. We further identify that their limitations are rooted in keeping the softmax self-attention during approximations. Specifically, conventional self-attention is computed by normalizing the scaled dot-product between token feature vectors. Keeping this softmax operation challenges any subsequent linearization efforts. Based on this insight, for the first time, a softmax-free transformer or SOFT is proposed. To remove softmax in self-attention, Gaussian kernel function is used to replace the dot-product similarity without further normalization. This enables a full self-attention matrix to be approximated via a low-rank matrix decomposition. The robustness of the approximation is achieved by calculating its Moore-Penrose inverse using a Newton-Raphson method. Extensive experiments on ImageNet show that our SOFT significantly improves the computational efficiency of existing ViT variants. Crucially, with a linear complexity, much longer token sequences are permitted in SOFT, resulting in superior trade-off between accuracy and complexity.