Reviewerly/exHarmony huggingface dataset:
ACTIVE INTERACTION AS LECTURERS’ STRATEGIES TO PROMOTE SPEAKING CLASSROOM

The goal of this study is to understand the strategies of lecturers and the dominant strategies of lecturers used by lecturers. This research discussed about the promotion of active participation in speaking classrooms by lecturers. This research employed qualitative design for analysis.The instrument were a questionnaire focused on (Jia,2013) theory and an interview. The results demonstrated that the lecturers completely used all strategies namely, improving questioning strategies, attending to learners' linguistic level, implementing cooperative learning, building positive teacher-learner rapports, reducing classroom anxiety. From those strategies, The highest percentage of strategies implementation leads to attending to learners' linguistic level. The result implies that it is necessary to introduce the use of strategies to encourage active classroom to develop the comprehension of the students and to establish an efficient way to teach speaking. Keywords: Strategies, Teaching Srategy, Speaking.
Multivariate Chebyshev polynomials and FFT-like algorithms

This dissertation investigates the application of multivariate Chebyshev polynomials in the algebraic signal processing theory for the development of FFT-like algorithms for discrete cosine transforms on weight lattices of compact Lie groups. After an introduction of the algebraic signal processing theory, a multivariate Gauss-Jacobi procedure for the development of orthogonal transforms is proven. Two theorems on fast algorithms in algebraic signal processing, one based on a decomposition property of certain polynomials and the other based on induced modules, are proven as multivariate generalizations of prior theorems. The definition of multivariate Chebyshev polynomials based on the theory of root systems is recalled. It is shown how to use these polynomials to define discrete cosine transforms on weight lattices of compact Lie groups. Furthermore it is shown how to develop FFT-like algorithms for these transforms. Then the theory of matrix-valued, multivariate Chebyshev polynomials is developed based on prior ideas. Under an existence assumption a formula for generating functions of these matrix-valued Chebyshev polynomials is deduced.
Hybrid Recommendation System for Better Mining Rules Generation of User and Consumer Data

In today's world, data and information play an essential role in each field, including online and software data. However, it is a challenging task to abstract &amp; sorted consumer data for use. To solve this data overloading and sorting of useful data, a Hybrid Recommendation System (HRS) comes into existence. HRS's focus is to suggest the best applicable and useful items to the related customers or users. The recommendations can be applied to decision-making processes, like which types of things to get, which new videos to watch, which online latest games and software to search, or the best product. The benefits of the Hybrid Recommendation System persist on the quality efficiency of the system. The efficient things can be calculated in easy to use, reliable, accurate, and expandable. This proposed HRS's primary goal is to better mining rules based on user and consumer data to improve the Hybrid Recommendation System's accuracy.
Measures to contain COVID-19 in view of the EU CFR right to the protection of personal data concerning health

31 December 2019 saw the first communication referring to 27 existing cases of a pneumonia of unknown aetiology, later named SARS-CoV-2 (COVID-19) During the initial months of 2020, the illness spread to practically every country in the world To tackle the pandemic, European institutions and member states have adopted various kinds of measures, particularly concerning health and economics, which in some cases conflict with that which is set out in the Charter of Fundamental Rights of the European Union In considering the legal framework of the Charter, throughout this article there will be an analysis of the modulations and limitations to the fundamental right to the protection of personal data concerning health (art 8 of the CFR) brought about by the measures adopted in response to the health crisis Examining European laws and jurisprudence, the study focuses on the relevant authorities, the necessary proceedings, the requirements of the restrictive measures and the problems of both personal data processing and Big Data
Upper bound on the total variation between Dirichlet and multivariate normal distributions

In this paper, we prove an asymptotic expansion for the ratio of the Dirichlet density to the multivariate normal density with the same mean and covariance matrix. The expansion is then used to derive an upper bound on the total variation between the corresponding probability measures. Other potential applications are briefly discussed.
Mburisano Covid-19 multilingual corpus

This corpus was created to aid development of the AwezaMed Covid-19 speech-to-speech mobile application. The project within which it was created, Mburisano, was funded by the Department of Sport, Arts and Culture (DSAC).A selection of English sentences was generated in consultation with medical domain experts, and these sentences were manually translated into all official South African languages. The sentences formed the basis of the rapid development of Grammatical Framework (GF) application grammars for all the languages, to aid spoken communication about Covid-19 with a particular focus on screening and triage. The corpus is presented as a limited domain, manually translated parallel corpus in all 11 official South African languages.The AwezaMed Covid-19 application can be found [here](https://play.google.com/store/apps/details?id=za.co.aweza.covid19&gl=ZA).
Function Optimization using Evolutionary Game Theory Algorithm

There are many models that can be used to make intelligent behaviors in solving complex problems. Game theory is one of them and can be used efficiently in decision making. In this paper, we study an evolutionary game theory algorithm (EGTA) and tested the algorithm in optimization function. It works with a set of players (i.e., solutions) and used an expected payoff mechanism. The payoff estimation mechanism makes a player being able to make a decision rationally. On the other hand, it generates new offspring using the imitation operator and belief-learning operator. The imitation operator tries to learn from other player's strategies; one player updates its quality by strategically learning from another better player. Belief learning is a strategy where a player tries to improve its chromosome/solution by estimation and analyze previous information. The algorithm has been tested in solving several benchmark function optimization problems and compared with the other four methods. The game theory-based algorithm outperformed other algorithms on accuracy and stability.
Experimental accreditation of outputs of noisy quantum computers

We provide and experimentally demonstrate an accreditation protocol that upper-bounds the variation distance between noisy and noiseless probability distributions of the outputs of arbitrary quantum computations. We accredit the outputs of twenty-four quantum circuits executed on programmable superconducting hardware, ranging from depth four circuits on ten qubits to depth twenty-one circuits on four qubits. Our protocol requires implementing the quantum circuit along with a number of random Clifford circuits and subsequently post-processing the outputs of these Clifford circuits. Importantly, the number of Clifford circuits is chosen to obtain the bound with the desired confidence and accuracy, and is independent of the size and nature of the target circuit. We thus demonstrate a practical and scalable method of ascertaining the correctness of the outputs of arbitrary-sized noisy quantum computers$-$the ultimate arbiter of the utility of the computer itself.
Las TIC en las prácticas de enseñanza de la escritura en la Universidad Nacional Experimental del Táchira (UNET)

The purpose of this dissertation is to identify the ICTs that UNET language teachers use in the teachingpractices of writing in the Language and Communication course, as well as to specify the training in digitalcompetencies they possess. It was based on the interpretative paradigm with a complementary yet mainlyqualitative approach; the method used was the ethnomethodology through a semi-structured interviewconducted with seven professors, in addition to a questionnaire addressed to 100 students. The resultsshowed that professors privilege traditional resources in their practices, but use the Moodle platform. It isconcluded that among the various ICTs resources, they have instrumental competencies for the use of thevirtual classroom; however, few of them make a reflective and systematic use of it, since most use it onlyfor informative purposes and as a repository of information on aspects related to academic writing.
Intelligent frame selection as a privacy-friendlier alternative to face recognition

The widespread deployment of surveillance cameras for facial recognition gives rise to many privacy concerns. This study proposes a privacy-friendly alternative to large scale facial recognition. While there are multiple techniques to preserve privacy, our work is based on the minimization principle which implies minimizing the amount of collected personal data. Instead of running facial recognition software on all video data, we propose to automatically extract a high quality snapshot of each detected person without revealing his or her identity. This snapshot is then encrypted and access is only granted after legal authorization. We introduce a novel unsupervised face image quality assessment method which is used to select the high quality snapshots. For this, we train a variational autoencoder on high quality face images from a publicly available dataset and use the reconstruction probability as a metric to estimate the quality of each face crop. We experimentally confirm that the reconstruction probability can be used as biometric quality predictor. Unlike most previous studies, we do not rely on a manually defined face quality metric as everything is learned from data. Our face quality assessment method outperforms supervised, unsupervised and general image quality assessment methods on the task of improving face verification performance by rejecting low quality images. The effectiveness of the whole system is validated qualitatively on still images and videos.
A Movie and Book Recommender System using Surprise Recommendation

With viable amounts of global Internet users and their online shopping spree, the world has led towards an astonishing and exponential digital data growth. It is of at most importance that this data has to be properly consumed and utilized when it comes to providing personalized content to both users and service providers. This is where the role of a Recommender System comes into active participation. These systems being user-centric are used to provide information that suits to the needs and interest of a user. In this paper, two types of Recommender systems are proposed. The first one is a Movie recommender and the second a Book recommender. For the movie recommender, the MovieLens dataset is used and the personalized Book content is obtained applying various prediction algorithms available in Surprise Recommendation kit. We make use of the Books-crossing dataset that has the book relevant information along with its ratings. We use the collaborative and content-based filtering techniques for obtaining recommendations and the systems are also evaluated using different metrics like RMSE, test time and the error factor.
REPRESENTASI NILAI KEJUJURAN DALAM NOVEL ORANG-ORANG BIASA KARYA ANDREA HIRATA SEBAGAI BAHAN PEMBELAJARAN LITERASI

This study aimed to describe and explain the character educational value of honesty in the novel ofOrang-Orang Biasa. The data in this study were used the values of honesty in the form of dialoguequotes, sentences, and paragraphs in novels. The data source was from the novel of Orang-OrangBiasa by Andrea Hirata. The technique of collecting data were used documentation techniques withreading and recording of relevant data. Meanwhile, the data analysis technique used an interactivemodel analysis which include four steps, namely: (1) data collection; (2) data reduction; (3) datapresentation; and (4) drawing conclusions. The results showed that the novel contains the value ofhonesty represented by two figures in the form of honesty in speaking, honesty and sincerity inwillingness, and honesty in action. Consequently, the novel of Orang-Orang Biasa can be used asreading material for senior high school students in literacy learning
Turtle-shell data embedding method with high image fidelity

In this paper, a modified version of the turtle-shell data hiding (TDH) scheme is proposed, aiming at improving the quality of stego-image. TDH scheme was first proposed by Chang et al. in 2014. In comparison to other schemes at that time, the scheme exhibited a superior visual quality in the premise of ensuring high embedding capacity (EC). However, in the TDH scheme proposed by Chang et al., the rules to seek for the search space of the hiding message suffers the drawbacks of omitting the better alternative pixel pair. The scheme proposed in this paper modifies the embedding rule by allowing the selection of a proper region than the search space proposed by Chang et al., so as to better hide data and minimise the image distortion. According to the experimental results with the same EC, the visual quality of the stego-image in the proposed method is 0.41 dB higher than that of stego-image in Chang et al.'s method.
Maximum Likelihood Channel Decoding with Quantum Annealing Machine

We formulate maximum likelihood (ML) channel decoding as a quadratic unconstraint binary optimization (QUBO) and simulate the decoding by the current commercial quantum annealing machine, D-Wave 2000Q. We prepared two implementations with Ising model formulations, generated from the generator matrix and the parity-check matrix respectively. We evaluated these implementations of ML decoding for low-density parity-check (LDPC) codes, analyzing the number of spins and connections and comparing the decoding performance with belief propagation (BP) decoding and brute-force ML decoding with classical computers. The results show that these implementations are superior to BP decoding in relatively short length codes, and while the performance in the long length codes deteriorates, the implementation from the parity-check matrix formulation still works up to 1k length with fewer spins and connections than that of the generator matrix formulation due to the sparseness of parity-check matrices of LDPC.
Water Wave Energy Harvesting Power Producing Stations as the Only Solution Avoid Coming Point of No Return

The newly invented and patented as US Patent on energy harvesting power producing apparatus is considered in the paper. This device could have the various applications. The authors consider the most effective application – to use it as the water wave energy harvesting power producing station. Based on analysis of numerous facts, evidences, articles, observations it is confirmed that the point of no return has high probability to happen in coming 20 – 30 years. It means that at a point of no return the catastrophic impact of the damaged Mother Nature would ruin the mankind. In coming point of no return the increase of our planet temperature; increase the climate change, increase of CO2, etc., will happen. Then the people will begin die due to dirty atmosphere, harmful and dangerous water and poisoned food. The authors provide the proof that the water wave energy harvesting power producing stations can guarantee only solution avoid coming point of no return. The proposed device is the vibration energy harvesting damper that is adjustable to a broad range of frequencies. The device includes a support structure that is securable to a vibrating object, a tuned mass retained by the support structure and movable in a rectilinear direction, a magnet vibrationally coupled to and spaced apart from the tuned mass, a coil surrounding the magnet, and at least one biasing assembly connecting two or more of the support structure, the tuned mass and the magnet. The at least one biasing assembly includes a fixed biasing member and an adjustable biasing member arranged in parallel. The adjustable biasing member is configured to adjust the combined stiffness coefficient of the biasing assembly. There were analytical study, design, manufacturing and test provided for proposed advance schemes of the water wave energy harvesting power producing station. It was concluded that such station would be effective to replace fossil-fuel station and solar panel and wind turbine stations.
regulatory framework of the soviet system of vocational education in the 1970s

The Russian educational system today is undergoing a process of deep, systemic reformation. This process is expressed in a rethinking of the essence, aims, objectives, and strategic attitudes of the educational system. The state policy in the field of education considers the general trends of world development, which determine the need for significant changes in the educational sphere at the present stage. The condition of the educational system and the prospects for its development in any legal state are primarily determined by the legislation on education. Therefore, the purpose of this article is to present the analysis of domestic legislation. which regulates the vocational education. Nowadays, great interest among researchers is shown to the Soviet experience of the development of the educational system. Turning to this experience makes it possible to avoid the mistakes of the past, to equalize existing contradictions and to choose the most productive way to develop the system of vocational and technical education in our days.
LibGuides: eBook Collections at UVic Libraries: eBooks: Health, Science & Engineering

A guide to the eBook collections at UVic Libraries eBook collections specifically targeted to health, science and engineering
STUDENTS’ PERCEPTION ON INTEGRATING GALLERY WALK IN TEACHING HISTORY OF ENGLISH LITERATURE

Learning and teaching English, especially in learning literature history, is closely related to the intelligence ability to speak, write, listen and read. Moreover, this intelligence can be developed with the help of teachers through certain strategies. This study aims to answer questions about the perceptions, strengths and weaknesses of students on the use of the gallery walk strategy in the literature history course.Qualitative research with a descriptive approach was applied to this research. Participants in this study were 80 students in semester 3 batch 2019. The data from this study were collected through a questionnaire designed in such a way as to find out how students' perceptions of using the gallery walk strategy were analyzed in three stages: data reduction, data presentation, then making and verify conclusions.The results showed that some students believed that teaching using the gallery walk strategy really helped students understand easily what would be conveyed in learning. In addition, the teacher's role is also very important in providing motivation and knowledge related to the implementation of the gallery walk strategy. This study aims to determine how students' perceptions and to know the strengths and weaknesses of using the gallery walk strategy.
Classification of Anemia with Digital Images of Nails and Palms using the Naive Bayes Method

Purpose : Early detection of anemia based on nails and palms images by applying the Naive Bayes method, as well as to measure the level of accuracy in detecting anemia. Design/methodology/approach : Using the Naive Bayes method. System development uses the waterfall method. Findings/result : Based on the results of the tests that have been carried out, the resulting accuracy is 87.5% with varying light intensities and is 92.3% by using a light intensity of 5362 Lux. Originality/value/state of the art : The difference between this study and previous research is in the image pre-processing method and classification method. In this study, the images of the nails and palms were converted to the YCbCr color space to be segmented and color features extracted. Then the color features will be classified using the Naive Bayes classification method. The output of this system is the result of the input image classification, whether normal or anemic.
LibGuides: Library Guide for Faculty & Staff, Fall 2021: Recommendations for Additions to the Library's Collection

This guide is for faculty & staff who need guidance on accessing library resources at Moorpark College during the reopening of campus.
XAI—An Approach for Understanding Decisions Made by Neural Network

For the longest time, most machine learning models have been viewed as black boxes. However, decisions with high stake cannot be taken without an explanation. So, model explainability and interpretability have become very important. Explainable artificial intelligence is a novel approach that aims to address how a model makes decisions. This paper throws light on understanding contribution of layer wise neurons involved in making decisions. Explanation of correlation between inputs and outputs and how the model arrived at that decision is the main focus of this application. The proposed application provides an explanation in the form of probabilities for numeric attributes and superpixel shading for images. A lot of models can be passed to this application and hence it makes it useful in all the use cases where neural networks are used for decision making. For the experimental purpose, we have considered a model for detecting the presence of malaria parasite in the blood sample image and classify it as parasitized or uninfected class. In the results section, different input images are taken and the analysis about the factors contributing to the model output is discussed.
The Adoption Footprints of Free and Open-Source Library Management Systems in Higher Education Institutions in Zambia

Many libraries the world over have turned to free and open-source library management systems (FOSLMS) for their automation needs. The main objective of this study was to investigate the extent to which FOSLMS were being used in libraries in Zambian higher education institutions (HEIs). Furthermore, the study sought to investigate factors that influence the adoption of FOSLMS in HEIs. The study was quantitative in design and data was collected from 142 HEIs with functioning libraries. The findings revealed that 42 (78%) out of 54 libraries in HEIs that have automated their operations use FOSLMS. Koha was found to be the most used FOSLMS and that low cost of adoption was the principal factor fueling FOSLMS’s adoption in HEIs in Zambia. Given the findings, the study recommends that the Zambian Government introduces a policy promoting the use of FOSS in public institutions including HEIs; the Library and Information Association of Zambia raise awareness of FOSLMS through workshops and conferences; the Zambian library science schools include, in their undergraduate programs, modules on FOSLMS.
Quantum Illumination using Quasi-Bell States

Quantum illumination is one of the application protocols of This protocol uses entanglement for target detection. The protocol was first proposed by Lloyd, and its performance was later studied by Tan et al. In a lossy environment, they considered a Gaussian state in the presence of thermal noise. Entanglement with nonorthogonal states, such as coherent states, produces These states have been shown to be capable of perfect entanglement. In this paper, we consider quantum illumination using quasi-Bell states, and compute the minimum error probability of quantum illumination under these states.