Reviewerly/exHarmony huggingface dataset:
Impact of grading system on student academic performance during the COVID-19 pandemic

The grading systems used for assessment students' knowledge in traditional and distance learning differ and give different assessments of learning outcomes, which affects the indicators of student academic performance. The trends of modern education are aimed at the increasing involvement of distance forms in the educational process of universities, which requires a certain synchronization of grading systems at the level of learning outcomes. The research is aimed at identification and confirmation of the existence of differences between the results of assessment in traditional and distance learning forms, which are reflected in the indicators of student performance. The study used methods of nonparametric analysis using the STATISTICA 10.0 program. The Mann-Whitney U-test was used to compare independent populations in cases where there were no signs of normal data distribution, and Pearson's Chi-square test was used to compare nominal values. To compare related (paired) quantitative samples, the Wilcoxon test was used. The research results showed a statistically significant increase in student academic performance during the COVID-19 pandemic during distance learning. Therefore, when comparing the indicators of student performance in the spring semesters of 2018/2019 and 2019/2020 academic years, significant differences were found in the U-criterion and Chi-square with different levels (p &lt;0.05, p &lt;0.01, p &lt;0.001) depending on the course of study and the performance indicator. The only exceptions are the senior students of Master's programmes who have shown a decline in academic performance. According to the results of the study, it can be concluded that the distance grading system makes lower requirements for learning outcomes in terms of student academic performance indicators, which overestimates them relative to the traditional form of education.
Assessing Quality of a Business and Information Technology Alignment Large Enrollment Course

The alignment of Business and Information Technology (BITa) has permeated almost all companies today, mainly due to the benefits that are perceived in their effectiveness and efficiency of their processes, both internal and external.Therefore, higher education must ensure the best settings for equipping IT-related professionals with appropriate BITa knowledge and skills.Consequently, practices related to course quality assessment emerge as critical and helpful since they are capable of generating information to improve teaching and learning processes.This study aims to describe and discuss quality assessment paths for three essential aspects in a large enrollment BITa course: examinations' design, workload, and alignment of activities and concepts to learning objectives.The course includes three main activities to promote the learning process: consultancy project development, examinations, and practical sessions with IT.We developed mixedmethod research to analyze through surveys (N=110), focus groups (four sessions), workload estimator (N=251), and expert consultation (nine experts), the quality of the three aspects of interest.Data indicates that the course curriculum is welldesigned, facilitating the development of BITa knowledge and skills in students.The results also uncover interesting information on helpful pedagogical practices to improve the course curriculum.The proposed approach could be extrapolated to other BITa courses and other courses with large enrollment to understand the students' experiences in relation to the three critical characteristics of learning and teaching practices studied.
Automatic Prediction of Ischemia-Reperfusion Injury of Small Intestine Using Convolutional Neural Networks: A Pilot Study

Acute intestinal ischemia is a life-threatening condition. The current gold standard, with evaluation based on visual and tactile sensation, has low specificity. In this study, we explore the feasibility of using machine learning models on images of the intestine, to assess small intestinal viability. A digital microscope was used to acquire images of the jejunum in 10 pigs. Ischemic segments were created by local clamping (approximately 30 cm in width) of small arteries and veins in the mesentery and reperfusion was initiated by releasing the clamps. A series of images were acquired once an hour on the surface of each of the segments. The convolutional neural network (CNN) has previously been used to classify medical images, while knowledge is lacking whether CNNs have potential to classify ischemia-reperfusion injury on the small intestine. We compared how different deep learning models perform for this task. Moreover, the Shapley additive explanations (SHAP) method within explainable artificial intelligence (AI) was used to identify features that the model utilizes as important in classification of different ischemic injury degrees. To be able to assess to what extent we can trust our deep learning model decisions is critical in a clinical setting. A probabilistic model Bayesian CNN was implemented to estimate the model uncertainty which provides a confidence measure of our model decisions.
Multicultural Aspects of 21st Century Learning Using Digital Posters

21st century learning is learning that has the characteristics of being accessible, digital oriented, big data science and this learning is not limited to the distance of space and time. Poster presentation is a general form of educational information that is easily accessible, can be spread quickly with the presence of television, gadgets and the internet. This research method is descriptive qualitative method. While the research data in the form of educational posters. The results of this study are in the form of poster media requirements that are used as educational media, namely; 1) The content shall not contents that may offend the community/learning participants. The presented content shall be accepted by audience even with language and cultural differences. 2) The information shall be clear thus the message of the poster is well conveyed to audience with different cultural aspect. 3) The contents should be attractive, contains illustration images, and explanatory writings that make audience interested in the poster. 4) The development of digital poster with various version of local language may increase acceptabability among local language speaker.
Hippocampus Segmentation Method Based on Subspace Patch-Sparsity Clustering in Noisy Brain MRI

Since the hippocampus is of small size, low contrast, and irregular shape, a novel hippocampus segmentation method based on subspace patch-sparsity clustering in brain MRI is proposed to improve the segmentation accuracy, which requires that the representation coefficients in different subspaces should be as sparse as possible, while the representation coefficients in the same subspace should be as average as possible. By restraining the coefficient matrix with the patch-sparse constraint, the coefficient matrix contains a patch-sparse structure, which is helpful to the hippocampus segmentation. The experimental results show that our proposed method is effective in the noisy brain MRI data, which can well deal with hippocampus segmentation problem.
The Software Industry IS STILL the Problem

The time is way overdue for IT engineers to be subject to professional liability, like almost every other engineering profession. Before you tell me that is impossible, please study how the very same thing happened with electricity, planes, cranes, trains, ships, automobiles, lifts, food processing, buildings, and, for that matter, driving a car.
Data visualization with the programming language R

Data visualization is an extremely valuable skill in science, finance and journalism. Learning to program will help reproducible data analysis and will increase the different types of visualization that can be generated. The statistical programming language R is a very useful programming language. The R community is friendly, supportive and very diverse including students, academics, health scientists, journalists and professional data scientists. An experience of R or another programming language such as Python or JavaScript will improve your science and your employment opportunities in and outside of research. Programming is a useful skill in education, finance, journalism and other areas too.
Implementation of Aerial Panoramic Photography for Environmental Studies Through VR Experiences

Technology allows us to experience situations from a different perspective. This project investigated many parts and techniques for better VR experiences. Aerial photography: Aerial photography provides a broad view of the changes in a landscape. However, aerial photography cannot offer a microscopic perspective of the changes with novel panoramas and landscape photos. A parallax compensation algorithm for stitching videos enables the user to reduce the time required to fix stitching issues in post-production. The experiment results indicated that the optimum camera height was 500 m, slightly higher than the clouds. An appropriate number of spatial samples were selected during photography to obtain high-quality images. The researchers avoided restricted flight areas and designed the image acquisition method according to the selected flight path, which were then combined in the post-processing step. Those 360-degree-aerial-images trigger young people's environmental awareness, which enhances the creator's sense of environmental protection.
Comparing HMAX and BoVW Models for Large-Scale Image Classification

Image classification is one of the most important topics in computer vision. It became crucial for large image datasets. In the literature, several image classification approaches are proposed. In this context, Bag-of-Visual Words (BoVW) model has been widely used. The BoVW model relies on building visual vocabulary and images are represented as histograms of visual words. However, recently, attention has been shifted to the use of complex architectures which are characterized by multilevel processing. HMAX (Hierarchical Max-pooling model) model has attracted a great deal of attention in image classification, due to its architecture, which alternates layers of feature extraction with layers of pooling. This paper aims at comparing bags of visual words model to HMAX model for image classification using large datasets. To achieve this goal, we study the use of image features obtained by BoVW model with SIFT (Scale-Invariant Feature Transform) descriptors, and we compare them to HMAX features. Image classification is performed by using the support vector machine (SVM) classifiers. Both HMAX and BoVW models are tested on ImageNet and OpenImages datasets and results have shown that the classification performance obtained by HMAX model outperforms the classification using BoVW model.
Impact of Information Technology on the Banking Sector in Developing Countries

The new world requires development in terms of technology and the use of it, in addition, people are leaning over the use of internet nowadays. In that terms, I propose a system of mobile banking for the Bank of Muscat. The system is mobile device activated and could be used to remotely access one's bank account and perform given operations and transactions; payments, transfers, enquiries of the account and other services to be demonstrated later on. The service I am proposing has to be updated and promoted accordingly as some users are not in good terms with using m-banking services just yet.
Analisis Perspektif Fraud Pentagon pada Terjadinya Kecurangan Akademik Mahasiswa Akuntansi

The purpose of this research is to show the fraud pentagon perspective on academic cheating in accounting students. The independent variabels in this research are pressure, opportunity, rationalization, capabilities, and personal ethics, while dependent variabel is academic cheating. This research used primary data on online questionnaire. The sample of this research used purposive sampling with criteria of STIE Perbanas Surabaya active accounting students until 2019 and willing to fill out a questionnaire. The research used multiple linear regression. The result is pressure, opportunity, rationalization, and capabilities no effect on cheating academic, while personal ethics negative effect on cheating academic. This is because STIE Perbanas Surabaya has character building activities namely Super Soft skills Mentoring (SSM) which makes the students have good personal ethics, so that minor academic cheating occurs.
Field Quality Control of Spectral Solar Irradiance Measurements by Comparison with Broadband Measurements

Measurement of solar spectral irradiance is required in an increasingly wide variety of technical applications, such as atmospheric studies, health, and solar energy, among others. The solar spectral irradiance at ground level has a strong dependence on many atmospheric parameters. In addition, spectroradiometer optics and detectors have high sensitivity. Because of this, it is necessary to compare with a reference instrumentation or light source to verify the quality of measurements. A simple and realistic test for validating solar spectral irradiance measurements is presented in this study. This methodology is applicable for a specific spectral range inside the broadband range from 280 to 4000 nm under cloudless sky conditions. The method compares solar spectral irradiance measurements with both predictions of clear-sky solar spectral irradiance and measurements of broadband instruments such as pyrheliometers. For the spectral estimation, a free atmospheric transmittance simulation code with the air mass calculation as the mean parameter was used. The spectral direct normal irradiance (Gbλ) measurements of two different spectroradiometers were tested at Plataforma Solar de Almería, Spain. The results are presented in this article. Although only Gbλ measurements were considered in this study, the same methodology can be applied to the other solar irradiance components.
Query-Based Retrieval Using Universal Sentence Encoder

In Natural language processing, various tasks can be implemented with the features provided by word embeddings. But for obtaining embeddings for larger chunks like sentences, the efforts applied through word embeddings will not be sufficient. To resolve such issues sentence embeddings can be used. In sentence embeddings, complete sentences along with their semantic information are represented as vectors so that the machine finds it easy to understand the context. In this paper, we propose a Question Answering System (QAS) based on sentence embeddings. Our goal is to obtain the text from the provided context for a user-query by extracting the sentence in which the correct answer is present. Traditionally, infersent models have been used on SQUAD for building QAS. In recent times, Universal Sentence Encoder with USECNN and USETrans have been developed. In this paper, we have used another variant of the Universal sentence encoder, i.e. Deep averaging network in order to obtain pre-trained sentence embeddings. The results on the SQUAD-2.0 dataset indicate our approach (USE with DAN) performs well compared to Facebook’s infersent embedding.
IDENTIFYING THE USE OF QUIZZES FOR STUDENTS DURING ONLINE LEARNING

The purpose of this study is to identify the use of quizzes for students during online learning. This research is descriptive qualitative research. Data will be collected through questionnaires and interviews on research subjects. The data collected will be analyzed qualitatively to describe the phenomena that occur in the field. Based on data from the research results, there are 47 students (29%) who chose E-learning quiz as a quiz that they often use.; 34 students (22%) who chose Quizizz; 30 students (18%) who chose Google Form Quiz; 23 students (14%) who chose quiz on the website as a quiz that they often get / use in learning; 19 students (11%) who choose Kahoot as a quiz that they often get / use in learning; and five students (3%) who choose Wondershare Quiz Creator as a quiz they often get / use in learning. This study proves that all types of quizzes are very helpful for students to review previous learning materials. In addition, this quiz can attract students to increase the duration of study at home.Keywords: Identification, Quiz, Online Learning
Parent Hamiltonian as a benchmark problem for variational quantum eigensolvers

The variational quantum eigensolver (VQE), which has attracted attention as a promising application of noisy intermediate-scale quantum devices, finds a ground state of a given Hamiltonian by variationally optimizing the parameters of quantum circuits called Ans\"atze. Since the difficulty of the optimization depends on the complexity of the problem Hamiltonian and the structure of the Ans\"atze, it has been difficult to systematically analyze the performance of optimizers for the VQE. To resolve this problem, we propose a technique to construct a benchmark problem whose ground state is guaranteed to be achievable with a given Ansatz by using the idea of a parent Hamiltonian of a low-depth parametrized quantum circuit. We compare the convergence of several optimizers by varying the distance of the initial parameters from the solution and find that the converged energies showed a thresholdlike behavior depending on the distance. This work provides a systematic way to analyze optimizers for the VQE and contribute to the design of the Ansatz and its initial parameters.
Pengaruh Strategi Pembelajaran berbasis E-Learning dan Motivasi Belajar terhadap Prestasi Mata Pelajaran Sejarah Kebudayaan Islam (SKI)

The purposes of this study are 1) to determine the effect of e-learning learning strategies on the achievement of SKI subjects; 2) to determine the effect of learning motivation on the achievement of SKI subjects; 3) to determine the effect of e-learning based learning strategies and learning motivation on the achievement of SKI subjects. The study used a quantitative approach with a population of 78 students. Data were taken through a questionnaire with validity and reliability tests. Multiple regression techniques analyzed the research data. The research object is MA NU Gesi Sragen students academic year 2020/2021. The results showed that e-learning-based learning strategies and learning motivation positively influenced student achievement in SKI subjects for MA NU Gesi Sragen students in the academic year 2020/2021.
Real-Time Face Mask Detector Using Convolutional Neural Networks Amidst COVID-19 Pandemic

The COVID-19 pandemic provoked many changes in our everyday life. For instance, wearing protective face masks has become a new norm and is an essential measure, having been imposed by countries worldwide. As such, during these times, people must wear masks to enter buildings. In view of this compelling need, the objective of this paper is to create a real-time face mask detector that uses image recognition technology to identify: (i) if it can detect a human face in a video stream and (ii) if the human face, which was detected, was wearing an object that it looked like a face mask and if it was properly worn. Our face mask detection model is using OpenCV Deep Neural Network (DNN), TensorFlow and MobileNetV2 architecture as an image classifier and after training, achieved 99.64% of accuracy.
Development of Reading Fluency from the Perspective of Automaticity Theory

Reading fluency has been a persistent problem among learners. A couple of experimental studies reveal the existence of this problem in many primary and secondary schools as well. In the past century, experimental psychologists have popularized automaticity theory as a relevant paradigm in developing children’s reading fluency. The theory identifies four important aspects that feature automaticity, which are speed, autotomy, effortlessness, and lack of conscious awareness. This study adopted a documentary review where various studies were collected, thoroughly reviewed and finally examined for qualitative analysis. The study aimed at expanding understanding of reading fluency by examining roles prayed by teachers in the development of child’s reading fluency basing on automaticity theory. There were similar findings related to reading fluency and automaticity theory from various publications reviewed. However, this study considered three of them, which have shown significant information across the topic and have been cited in various books and world-class journals.
The Combination of Narrative News and VR Games: Comparison of Various Forms of News Games

The information explosion makes it easier to ignore information that requires social attention, and news games can make that information stand out. There is also considerable research that shows that people are more likely to remember narrative content. Virtual environments can also increase the amount of information a person can recall. If these elements are blended together, it may help people remember important information. This research aims to provide directional results for researchers interested in combining VR and narrative, enumerating the advantages and limitations of using text or non-text plot prompts in news games. It also provides hints for the use of virtual environments as learning platforms in news games. The research method is to first derive a theoretical derivation, then create a sample of news games, and then compare the experimental data of the sample to prove the theory. The research compares the survey data of a VR game that presents a story in non-text format (Group VR), a game that presents the story in non-text format (Group NVR), a VR game that presents the story in text (Group VRIT), and a game that presents the story in text (Group NVRIT) will be compared and analyzed. This paper describes the experiment. The results of the experiment show that among the four groups, the means that can make subjects remember the most information is a VR news game with a storyline. And there is a positive correlation between subjects' experience and confidence in recognizing memories, and empathy is positively correlated with the correctness of memories. In addition, the effects of "VR," "experience," and "presenting a story from text or video" on the percentage of correct answers differed depending on the type of question.