Reviewerly/exHarmony huggingface dataset:
ENHANCING STUDENTS’ SPEAKING ABILITY THROUGH COLLABORATIVE LEARNING AT AL MAULIDIYAH ORPHANAGE IN JATIASIH BEKASI

The aim of this research was to see the improvement of the EFL learners’ speaking ability through the implementation of Storytelling Strategy using pictures. This research was also directed to explore the beneficial of collaborative learning for students of Al Maulidiyah Orphanage in Jatiasih Bekasi. The subject consisted of 15 of EFL learners. A Classroom Action Research in two cycles had been conducted within 2 meetings for every cycle. The meetings were focused on the interactivity and communicative ability among learners. The research result showed that the learners’ fulfillment of the storytelling task improved from 40% or 66.7%. It also showed that the learners’ ability in speaking performance improved. The highest improvement was seen from fluency indicator that is from 26.7% to 46.7%. While for the other two indicators namely pronunciation and vocabulary move upward a little. In conclusion, the implementation of Interactive Storytelling Strategy increased the EFL learners’ fulfillment of the storytelling task and their speaking ability
Integration of Library Automation to a Mobile Application with User Friendly Interface-AUELIB APP

The study mainly emphasis on the automation process of Library information system in Anurag University, Hyderabad, Telangana.In today's scenario Library automation is a major task for engineering college libraries, with the introduction of advance technologies in field of library and information science, major automation areas and outlines the various factors needed to be considered by the librarians while doing automation work for their respective libraries.Now a day's modern libraries are equipped with traditional resources like books magazines reports etc. with the advent of information technology they are also exaggerated with digital resources like ejournals, online research publications and web resources.The study mainly focuses on the use of automation process of libraries in various schools of Anurag University for seamless dissemination of the information.The Information Communication Technology has brought rapid changes in the performance of libraries and its services. It helps libraries in creating database of their own collections and creation them accessible for easy access to userswithin and outside the libraries through various networks and mobile applications.We have been using library management software in central library; successfully completed automation of journals, books, and magazines. Digitization of libraries reduces the unending work and preserves time and brings precision and speed & keeps material safe. It increases the efficiency in technical processing of library materials and amends the efficiency of library administration and management processes. The Anurag University central library gives much importance tothe library automation services integrated with a mobile application for an effective resource is the need of hour.The integrated approach of the mobile application will ease the process to the needy user in a short time and cost effective way to get the right information in right time at right place.The objective of the case study is understand and implement the integrated library automation process in the departments with a user friendly AUELIB mobile application for ease of accessing information.
Hematological Profile of Indian Bullfrog and Common Toad from Different Environmental Habitats

The wellbeing of human population depends on the ecosystem of earth. Amphibians from the ancient time represents a major part in the global diversity and play important role for the benefit of society worldwide. The aim of the present study was to investigate the comparative hematological study of Indian bullfrog (Hoplobatrachus tigerinus) from wetland and a common Indian toad (Duttaphrynus melanostictus) from terrestrial environment. In this study we have procured 10 sexually mature and disease-free Indian bullfrog (9.93±0.07 cm total length, 59.5±1.94 g weight) and 10 common Indian toad (8.26±0.26 cm total length, 78.6±1.36 g weight). The RBC and WBC count were found to be increased in frog than toad. Variation in RBC morphology which reveals the anemic condition in frog than that of toad. The study suggested that the environmental conditions have significant impact on status of frog and toad.
Economic Security of Ukraine’s Railway Transport in the Context of National Security

The authors consider the legislative and economic prerequisites for the need to ensure the economic security of Ukraine's railway transport in the context of national security.The research methodology is composed of such methods as a theoretical generalization for further clarification of the conceptual apparatus of railway transport economic security, a legalistic method for analysis and systematization of legal bases in the field of Ukraine's national security, an abstract-logical method for theoretical generalization and formulation of research conclusions, etc. Taking into account the dynamics and nature of railway freight transportation, conclusions about the strategic place of the industry in ensuring sustainable development of the state and, accordingly, the need to protect its economic security were drawn.The authors outline the legal principles of economic security of railway transport in the system of legal regulation of Ukraine's security policy.The article provides the author's definition of "economic security of railway transport" concept, based on current tendencies in national security.
On the Linearity and Structure of Z<sub>2</sub>s-Linear Simplex and MacDonald Codes

Z <inf xmlns:mml="http://www.w3.org/1998/Math/MathML" xmlns:xlink="http://www.w3.org/1999/xlink">2</inf> <tex xmlns:mml="http://www.w3.org/1998/Math/MathML" xmlns:xlink="http://www.w3.org/1999/xlink">$s$</tex> -additive codes are subgroups of Z <sup xmlns:mml="http://www.w3.org/1998/Math/MathML" xmlns:xlink="http://www.w3.org/1999/xlink">n</sup> <inf xmlns:mml="http://www.w3.org/1998/Math/MathML" xmlns:xlink="http://www.w3.org/1999/xlink">2</inf> s, and can be seen as a generalization of linear codes over Z <inf xmlns:mml="http://www.w3.org/1998/Math/MathML" xmlns:xlink="http://www.w3.org/1999/xlink">2</inf> and Z <inf xmlns:mml="http://www.w3.org/1998/Math/MathML" xmlns:xlink="http://www.w3.org/1999/xlink">4</inf> . A Z <inf xmlns:mml="http://www.w3.org/1998/Math/MathML" xmlns:xlink="http://www.w3.org/1999/xlink">2</inf> <tex xmlns:mml="http://www.w3.org/1998/Math/MathML" xmlns:xlink="http://www.w3.org/1999/xlink">$s$</tex> -linear code is a binary code (not necessarily linear) which is the Gray map image of a Z <inf xmlns:mml="http://www.w3.org/1998/Math/MathML" xmlns:xlink="http://www.w3.org/1999/xlink">2</inf> <tex xmlns:mml="http://www.w3.org/1998/Math/MathML" xmlns:xlink="http://www.w3.org/1999/xlink">$s$</tex> -additive code. We consider Z <inf xmlns:mml="http://www.w3.org/1998/Math/MathML" xmlns:xlink="http://www.w3.org/1999/xlink">2</inf> s- additive simplex codes of type a and β, which are a generalization over <tex xmlns:mml="http://www.w3.org/1998/Math/MathML" xmlns:xlink="http://www.w3.org/1999/xlink">$Z$</tex> <inf xmlns:mml="http://www.w3.org/1998/Math/MathML" xmlns:xlink="http://www.w3.org/1999/xlink">2</inf> <tex xmlns:mml="http://www.w3.org/1998/Math/MathML" xmlns:xlink="http://www.w3.org/1999/xlink">$s$</tex> of the binary simplex codes. These codes are related to the Z <inf xmlns:mml="http://www.w3.org/1998/Math/MathML" xmlns:xlink="http://www.w3.org/1999/xlink">2</inf> <tex xmlns:mml="http://www.w3.org/1998/Math/MathML" xmlns:xlink="http://www.w3.org/1999/xlink">$s$</tex> -additive Hadamard codes. In this paper, we use this relationship to find a linear subcode of the corresponding <tex xmlns:mml="http://www.w3.org/1998/Math/MathML" xmlns:xlink="http://www.w3.org/1999/xlink">$Z$</tex> <inf xmlns:mml="http://www.w3.org/1998/Math/MathML" xmlns:xlink="http://www.w3.org/1999/xlink">2</inf> s-linear codes, called kernel, and a representation of these codes as cosets of this kernel. In particular, this also gives the linearity of these codes. Similarly, Z <inf xmlns:mml="http://www.w3.org/1998/Math/MathML" xmlns:xlink="http://www.w3.org/1999/xlink">2</inf> <tex xmlns:mml="http://www.w3.org/1998/Math/MathML" xmlns:xlink="http://www.w3.org/1999/xlink">$s$</tex> -additive MacDonald codes are defined for <tex xmlns:mml="http://www.w3.org/1998/Math/MathML" xmlns:xlink="http://www.w3.org/1999/xlink">$s$</tex> > 2, and equivalent results are obtained.
Research on the Application of Intelligence Teaching Mode of Superstar Platform in the Teaching of Experimental Design and Data Processing

Experimental Design and Data Processing is an important core professional basic course for food science majors. This course is theoretical and practical, and there are many formulas, abstract contents and difficult to understand, and there are some problems in the teaching process, such as students' poor interest in learning, insufficient mastery of what they have learned, and inability to combine theory with practice organically. Through analyzing the existing problems, this paper puts forward some reform measures for the teaching mode of experimental design and data processing by using the intelligent teaching of Superstar platform.
Pengembangan Bingo sebagai Media Pembelajaran Sejarah di SMA

This research is motivavailabated by the unavailability of enjoyable history learning media, but still can help students in higher-order thinking that is analytical thinking. Based on observations made by students look bored ini following the history of learning so that it inhibits students in understanding the material to reach a igh level of thinking that is analytical thinking.This research aims to develop bingo as a history learning media that is feasible to use. Developing bingo media like bingo games. This research is a research and development of R&amp;d, by following the steps of developing the ADDIE model. But in this study the research procedure was carried out only at the development stage, due to the limited time of the researcher. In this study the validity test is study the validity test is based on the assessment of material experts and media experts using a questionnaire to assess the feasilibity of the media. Reseacrh data were analyzed with quantitative analysis techniques. The results of the study showed that the feasibility of the media based on the assessment of material experts was 3,57 and the assessment of media experts was 3,5. This shows that the bingo media ini history learning is very feasible to use.
Pengaruh Pemanfaatan E-Learning Quipper School Terhadap Hasil Belajar Akuntansi Yang Dimoderasi Oleh Kemandirian Belajar Siswa

This study aims to determine how the effect of the use of Quipper School e-learning on accounting learning outcomes which are moderated by student learning independence. This research is motivated by low independence and student learning outcomes. This research is a quantitative descriptive research. The research sample was 33 students consisting of two classes at the YPK Medan Vocational School. The data collection techniques used in this study were using tests and questionnaires (questionnaires). The analysis technique uses multiple regression. The results of this study based on multiple regression analysis are (1) There is an effect of the use of Quipper School E-learning on student learning outcomes. (2) There is an effect of learning independence on student learning outcomes and (3) There is an influence of quipper school on student learning outcomes which is moderated by student learning independence
Enhancing Privacy for Big Data in Healthcare Domain based on Cryptographic and Decentralized Technology Methods

Privacy is one of the biggest concerns that hinder most organizations to adopt the Big Data technology. Some mechanisms and systems have been set-up to handle huge databases. Nevertheless, the scalability requirements of Big Data are far beyond the conventional databases to handle. Therefore, it is trivial to set-up scalable privacy algorithms for conventional databases. Most data are stored in a single location, which means the records it keeps are open and effortlessly irrefutable to third parties. Centralized versions of this data make it too easy for hackers to attack. As such, in this paper, we present the opportunities and challenges of implementing cryptography and blockchain for privacy perseverance in Big Data, focusing in the healthcare domain. In addition, we also present some use cases of integrating Directed Acyclic Graph (DAG) into healthcare database framework for anchoring information security and privacy.
Robust method of determining microfacet BRDF parameters in the presence of noise via recursive optimization

Accurate bidirectional reflectance distribution function (BRDF) models are essential for computer graphics and remote sensing performance. The popular microfacet class of BRDF models is geometric-optics-based and computationally inexpensive. Fitting microfacet models to scatterometry measurements is a common yet challenging requirement that can result in a model being fit as one of several unique local minima. Final model fit accuracy is therefore largely based on the quality of the initial parameter estimate. This makes for widely varying material parameter estimates and causes inconsistent performance comparisons across microfacet models, as will be shown with synthetic data. We proposed a recursive optimization method for accurate parameter determination. This method establishes an array of local minima best fits by initializing a fixed number of parameter conditions that span the parameter space. The identified solution associated with the best fit quality is extracted from the local array and stored as the relative global best fit. This method is first applied successfully to synthetic data, then it is applied to several materials and several illumination wavelengths. This method proves to reduce manual parameter adjustments, is equally weighted across incident angles, helps define parameter stability within a model, and consistently improves fit quality over the high-error local minimum best fit from lsqcurvefit by an average of 71%.
A TECHNOLOGY TO IMPROVE PEDAGOCIG WORKERS’ PROFESSIONAL COMPETENCY UNDER QUALIFICATION IMPROVEMENT CONDITIONS

The article discloses the essence of such notions as competency, professional competency, technology; it is proved that improvement of professional competency in pedagogic workers in the course of their qualification improvement occurs due to a technology, the constituents of which are lectures, seminar classes and trainings. The authors have determined considerable differences in methodologies on conducting laboratory and practical classes in nature sciences and humanities and sociology disciplines to attain the main goals of training, as well as the methodology of teaching juridical disciplines at higher education institutions. The importance of the attained knowledge in rendering socio-psychological and corrective services to students with special learning needs and its practical application in the higher education institutions’ practices has been researched; also, the efficiency of the described technology for the qualification improvement courses attendees in their further pedagogic activities has been proved.
Off-the-shelf Convolutional Neural Network (CNN) features for Automatic Face Quality Prediction

Estimation of face image quality helps in correctly recognizing faces which in turn helps in many practical applications related to face. This paper presents a face quality prediction approach using Off-the-Shelf CNN features. Here we evaluated three image descriptors-binary patterns (LBP), Histogram of oriented gradients (HOG), Oriented Fast and Rotated Brief (ORB), and deep Convolution Neural Network (CNN) Networks pre-trained on ImageNet-VGG19, ResNet50, and VGG Small (4 layers) for feature extraction to detect face region image quality. Furthermore, to classify extracted features, we have evaluated three classifiers, that are different from each other in their own ways (SVM, DT and MLP) For experimental analysis, we created a face quality dataset by collecting images from web and publicly available face datasets and manually labeled images under seven categories-Good and six bad quality classes (e.g. Expression, Makeup, Pose, Occlusion, Illumination and Blur). The accuracy of face image classification using VGG19 along with MLP as a classifier was the highest (i.e.98.76%) followed by ResNet50 and MLP at 98.69% of accuracy. The lowest accuracy was obtained with LBP and SVM, this shows that deep features gives a better solution.
Adversary Strategy Sampling for Effective Plan Generation

Effective plan generation in adversarial environments has to take into account possible actions of adversary agents, i.e., the agent should know what the competitor will likely do. In this paper we propose a novel approach for estimating strategies of the adversary, sampling actions that interfere with the agent's ones. The estimated competitor strategies are used in plan generation by considering that agent's actions have to be applied prior to the ones of the competitor, whose estimated times dictate the agent's deadlines. Missing these deadlines entails additional plan cost.
Short-term Ultraviolet Index Forecasting Using ARIMA Model

Solar energy is recognized as an ideal renewable energy.Solar photovoltaic power generation is an important way to use solar energy.Photovoltaic power generation can alleviate the existing energy crisis and alleviate various environmental problems.As a clean and renewable energy, photovoltaic power generation is playing a prominent role in smart micro-grid.The intensity of solar radiation is fluctuating, so the successful grid connection of solar power stations requires accurate power prediction.This paper focuses on the prediction of ultraviolet power index to solve the problem of power prediction of photovoltaic power station.Based on the analysis of cumulative autoregressive moving average model, the stationary of ultraviolet index time series was detected, the order of ultraviolet index model was estimated, and the ARIM A model of ultraviolet index was determined.The prediction accuracy of the model is determined by the root mean square error (RM SE) and mean absolute error (M AE).
Touching the Sound, Sounding the Touch. The Tactile Experience in the Music of Santiago Diez-Fischer as a Presentational Symbol

The music of Argentinian composer Santiago Diez-Fischer places particular emphasis on the sense of touch. The sonic textures and the notations the composer use illustrate this. In several pieces, his writing indicates surfaces to rub, caress, and press. The resulting sound is complex, often on the edge of noise. In this article, I argue that the notion of presentational symbol as proposed by Susanne Langer serves to clarify how such music is an expression of tactile experience. I show how this notion relates to all music in general, and precisely because music is such a symbol that it can be understood and interpreted in its meaning through listening. I make the assumption that all music is presentational; however, such generality must be overcome by a more important requirement. Once we know that music is a presentational symbol, what does it symbolize? I think music symbolizes different things every time and it is possible to understand this, as long as you listen and bring your own experience into play. Here, I have tried to do this by referring to the work of Santiago Diez-Fischer. I argue then that the emotion of touch is then communicated as a specific and unique musical form. In this sense, Diez-Fischer’s music is paradigmatic.
Scalable Distributed Approximation of Internal Measures for Clustering Evaluation

An important step in cluster analysis is the evaluation of the quality of a given clustering through structural measures of goodness.Measures that do not require additional information for their evaluation (but the clustering itself), called internal measures, are commonly used because of their generality.The most widely used internal measure is the silhouette coefficient, whose naïve computation requires a quadratic number of distance calculations, unfeasible for massive datasets.Surprisingly, there are no known general methods to efficiently approximate the silhouette coefficient of a clustering with rigorously provable high accuracy.In this paper, we present the first scalable algorithm to compute such a rigorous approximation for the evaluation of clusterings based on any metric distances.Our algorithm approximates the silhouette coefficient within a mere additive error O (ε) with probability 1 -δ using a very small number of distance calculations, for any fixed ε, δ ∈ (0, 1).We also provide a distributed implementation of the algorithm using the MapReduce model, which runs in constant rounds and requires only sublinear local space at each worker, thus making our estimation approach applicable to big data scenarios.An extensive experimental evaluation provides evidence that our algorithm returns highly accurate silhouette estimates, unlike competing heuristics, while running in a fraction of the time required by the exact computation.
PREDIKSI FITUR KEMASAN PRODUK MINYAK KAYU PUTIH DENGAN SUPPORT VECTOR MACHINE (SVM)

UD Sinar Baru has eucalyptus oil products with various sizes from 30 ml to 550 ml, and the size of 550 ml is the most consumed eucalyptus oil product. However, this product has been criticized by consumers for its packaging which has not met their expectations. This study aims to obtain an accurate method of classifying consumer sentiment and obtain features that affect the redesign of the 550 ml eucalyptus oil product packaging. Collecting data using an online survey method from social media Facebook to get consumer comments using power queries. Data analysis uses the concept of the Support Vector Machine (SVM) method with the support of the WEKA application to provide sentiment analysis and accuracy of consumer comments. The results of the study present the tendency of comments on each attribute with an assessment of 83% accuracy for the entire class, 3% for positive class comments, and 57% comments for negative class. The sentiment that shows the packaging tends to be normal at 20% which is interpreted as neutral. The conclusion from the results of this study is that SMO has a very accurate prediction rate to analyze consumer sentiment about the features of the 550 ml eucalyptus oil packaging, and it is necessary to redesign the current packaging by considering the features of shape, color, size, and efficiency.
Grasping or Forgetting? MAKT: A Dynamic Model via Multi-head Self-Attention for Knowledge Tracing

The outbreak of the COVID-19 pandemic arises enormous attention to online education then knowledge tracking is an increasingly crucial task with its vigorous development.However, the surge of student historical interactions and the lack of prior knowledge is engendering a sequence of issues, such as the decrease in prediction accuracy while the increase in training time.Simultaneously, most existing approaches fail to provide in-depth insights into why a student is likely to answer the question incorrectly and what affects the knowledge state of the student.To address those issues, we propose a multi-head self-attention model named MAKT for dynamic knowledge tracing, which makes the prediction results interpretable at the model and instance level.The customized multi-head self-attention layer has high training efficiency owing to its parallelization capability and spends about 6 seconds in each epoch on a single GPU.We further visualize the attention weights of MAKT and student knowledge acquisition tracking, finding that not all historical interactions are equally important but the recent interactions profoundly establish the knowledge state of students.In the end, extensive experiments on three datasets demonstrate the robustness and superiorities of MAKT, improving ACC by 1.14 % and AUC by 1.20 % on average.