Reviewerly/exHarmony huggingface dataset:
Efficient Codebook and Factorization for Second Order Representation Learning

Learning rich and compact representations is an open topic in many fields such as object recognition or image retrieval. Deep neural networks have made a major breakthrough during the last few years for these tasks but their representations are not necessary as rich as needed nor as compact as expected. To build richer representations, high order statistics have been exploited and have shown excellent performances, but they produce higher dimensional features. While this drawback has been partially addressed with factorization schemes, the original compactness of first order models has never been retrieved, or at the cost of a strong performance decrease. Our method, by jointly integrating codebook strategy to factorization scheme, is able to produce compact representations while keeping the second order performances with few additional parameters. This formulation leads to state-of-the-art results on three image retrieval datasets.
Secure Computation Offloading in Vehicle Networks Based on Block Chains

Abstract: VANETs (vehicular ad hoc networks) have become an essential component of current intelligent transportation systems (ITS). However, under the influence of hostile mobile vehicles, security threats pose a threat to offloading vehicle duties to the cloud server. How to address the complicated computation offloading of vehicles while assuring the cloud server's high security is an essential research subject. We investigated the safety and offloading of a multi-vehicle ECCO system based on cloud blockchain in this research. To begin, we present a distributed hierarchical software-defined VANET (SDVs) framework to construct a security architecture in order to attain agreement in the vehicular context. Second, to increase offloading security, we suggest using blockchain-based access management, which protects the cloud from unauthorised offloading. Finally, we decide task offloading by jointly optimising offloading decisions, consensus mechanism decisions, computation resource allocation, and channel bandwidth to tackle the intense computing problem of approved vehicles.
A new evolutionary ensemble learning of multimodal feature selection from microarray data

Abstract In the last decades, data has grown exponentially with respect to the number of samples and features, which makes feature selection more challenging. An optimization method called multimodal optimization techniques is employed to find several optimal solutions. The main contribution of multimodal optimization techniques is providing several optimal solutions instead of a single solution. Since multimodal optimization algorithm naturally provides several answers, in this paper the potential and information of several answers are used to address the issues of selecting features from microarray data, using hidden information in the data, and creating an ensemble of classifiers. After pre-processing of data, several optimal feature subsets are obtained by firefly-based multimodal optimization algorithm to tap the potential of and information in several answers. The mutual information method is used as the fitness function to evaluate the suggested subset of features. Then, each subset of features is used to learn a classifier and such classifiers are learned on data whose features are presented by a multimodal optimization algorithm, and these classifiers are combined. To select a proper combination, a particle swarm optimization algorithm is used. Finally, the algorithm for the datasets of the microarray is evaluated in terms of cancer diagnosis. The algorithmic method efficiency is evaluated by applying it on 11 datasets. The results suggested the superiority and proper function of the multimodal feature selection method compared with other methods.
AN ANALYSIS OF LISTENING COMPREHENSION ROLE IN IMPROVING STUDENT’S SPEAKING ABILITY AT ENGLISH STUDY PROGRAM ISLAMIC UNIVERSITY OF INDRAGIRI

This study aims to determine the role of listening comprehension in improving students speaking ability at English Study Program Islamic University of Indragiri. This type of research is descriptive quantitative. The population of this research is the students of English Study Program at Islamic University of Indragiri. The number of population and samples from this study were 36 people, taken using a total sampling technique. To determine the role of listening comprehension in improving students speaking ability, the researcher gave a questionnaire as an instrument. For data analysis, researchers used Likert scale as a measurement of the variables. The test results show the role of listening comprehension in improving students speaking ability at English Study Program Islamic University of Indragiri is in a high level with an average of 132.4. The researcher concludes that listening comprehension has a great role in improving students speaking ability at English Study Program Islamic University of Indragiri.
AN ANALYSIS OF TEACHERS’ PERCEPTION ON THE USE OF AUTHENTIC ENGLISH READING MATERIALS OF VIA ENGLISH COURSE

This study aims to determine the teacher's perception of the Via English Course about authentic materials that can be taken from the internet, magazines, and newspapers and so on. This type of research is descriptive quantitative. The population of this study are teachers at the Via English Course for the 2021/2022 academic year. The number of population and samples from this study were 11 people taken using total sampling technique. To find out the teacher's perception of using authentic materials in reading skills. Researchers collected data that is quantitative data. For data analysis, the researcher used observational analysis and a questionnaire to determined the final result of the teacher's perception in using authentic material in reading skills. The results of the test show that the teacher's perception of using authentic material in Via English Course Tembilahan is categorized with an average of 88.9% (Very Good). The researcher concluded that the teacher's perception of using authentic material in the Tembilahan English Course was very good because by using authentic material students were more active and more enthusiastic in reading English.
ANALYSIS OF THE STUDENTS’ WRITING DIFFICULTIES OF ANALYTICAL EXPOSITION TEXT AT XI GRADE OF MA MIFTAHUL HUDA SUNGAI LUAR

The purpose of this research is to know the students' writing difficulties of Analytical Exposition text at XI grade of MA Miftahul Huda Sungai Luar and the most dominant the students' writing difficulties Analytical Exposition text at XI grade of MA Miftahul Huda Sungai Luar. This research was achieved by conducting a descriptive quantitative study. The total population of this research was 51 students. The sample of this research was 51 students of eleventh-grade students of MA Miftahul Huda Sungai Luar. The researcher used total sampling to take the sample. The researcher gave a questionnaire to collect data. The questionnaire consists of 15 statements based on Writing Difficulties indicators. The questionnaire was using the Likert Scale. This questionnaire revealed that students' writing difficulties in analytical exposition text rely on high category, with 77.88%. The most dominant of the students' writing difficulties of Analytical Exposition was difficulty in developing ideas in long sentences. It means that they are difficulties in physiology with the average was 79.14% with high category. Based on the research results, the researcher concluded the Students had high difficulties Writing Analytical Exposition texts. They need to improve themselves to become easy to develop ideas in long sentences. The teacher's role is essential to guide them to be easier to develop ideas in long sentences.
THE EFFECTIVENESS OF USING ENGLISH SONGS AS WARMING UP ACTIVITY TO ENHANCE STUDENTS’ MOTIVATION IN ENGLISH CLASSROOM AT THE EIGHTH GRADE OF SMPN I ENOK

Motivation is a factor which important in do something. For the Students, motivation is one factor that influences the teaching-learning process in the classroom. This time, motivation is a factor that becomes a problem for the students SMPN I Enok. This problem is the background of the problem in this research. To solve the students' motivation in the English classroom, the researcher conducted the experimental research with a quasi-experimental design with applying the English song as a warming-up activity to solve the problem. This research aimed to know the effectiveness of using English songs as a warming-up activity to enhance students' motivation in the English classroom at the eighth grade of SMPN I Enok. The data collection technique in this research was a questionnaire, and the instruments were 15 Close Ended statements using the Likert Scale type. This research sample was 50 students of the eighth-grade SMPN I Enok as a control and experimental class. After getting the data using the questionnaire, the researchers found that English song as warming up activity was useful to enhance students” motivation in English classroom with the result t-observed was 19,85 while t-table was 2,01 from 5% and 2,68 from 1%. The t-observed score was higher than the t-table. Based on the result, H0 (null hypothesis) is rejected, and H1 (alternative hypothesis) is accepted. It also means that English song as warming up activity was sufficient to enhance students' motivation in the English classroom at the eighth grade of SMPN I Enok in academic years 2018/2019.
A STUDY ON THE STUDENT’S LEARNING STRATEGIES IN READING COMPREHENSION AT ELEVENTH GRADE OF IPS OF SMA TRI TUNGGAL PULAU BURUNG

The primary purpose of this study was to determine students' learning strategies in reading comprehension. This research was conducted at the eleventh grade of IPS of SMA Tri Tunggal Pulau Burung. This type of research is descriptive and uses total sampling techniques in determining research samples. This study's population was 53 students, and researchers took 30 students from them to be sampled in this study. Data collecting techniques use questionnaires from the questionnaire to find out the strategy in reading it. Then, this research shows that the value of students strategies in reading is mean values with result of cognitive strategies 37.93 % at Low category, metacognitive strategies 33.5 % at Low category, socio-affective strategies 33.2 % at Low category. From this study, it can be concluded that the students learning strategies in reading comprehension at the eleventh grade of IPS of Tri Tunggal Pulau Burung are in a low category. Findings showed that the students use cognitive strategies in reading comprehension at the eleventh grade of IPS of SMA Tri Tunggal Pulau burung.
THE RELATIONSHIP BETWEEN LEARNERS’ AUTONOMY AND THEIR ACHIEVEMENT IN LEARNING ENGLISH AT 11TH GRADE OF SMA NEGERI 1 TEMBILAHAN HULU

The problem of this research was Learners' achievement seems low, while their autonomy seems higher. The method of this research was quantitative correlation research. Therefore, the purpose of this study was to investigate the correlation between learners' autonomy (Variable X) with learners' achievement (Variable Y). The sample of this study was 145 students of eleventh-grade students of SMAN 1 Tembilahan Hulu. The researcher gave questionnaires of learners' autonomy to collect data and asked the value of their English teacher's achievement. After the data has been collected, it was found that the average of learners' autonomy is 77,9%, it was in the "high category," And the average of learners' achievement was 81,6%, it was in the "high category". Based ." those findings, researchers analyzed the relationship between learners' autonomy and their achievement using the Pearson r formula; the results was 0.1999 (rxy) it was in "very low correlation," after found out the score of rxy researcher noting to the table of degree of freedom (df) N (number of respondents) – nr (variables) where 145 – 2 is 143. By consulting r table product-moment, it is found in the significant of 1% being obtained at 0.1371 and 5% is 0.1631. By comparing the values of rxy = 0.1999 and r table = 0.1371 and 0.1631, rxy is bigger than r table. This means that autonomy and achievement have a very low correlation. If learners have good autonomy, they will have a good achievement in English.
Quantum Image Processing -- Challenges and Future Research Issues

Image processing on quantum platform is a hot topic for researchers now a day. Inspired from the idea of quantum physics, researchers are trying to shift their focus from classical image processing towards quantum image processing.This paper starts with a brief review of the principles which underlie quantum computing, and also deals with some of the basics of qubits and quantum computing.Then this paper starts to deal with some different methods of image storage, representation and retrieval in a quantum system.This paper also describes the advantages of using those methods in quantum systems compare to classical systems. In the next section, a short discussion on some of the important aspects, comparison among them and applications of quantum image processing is presented. A few other hot topics and open problems in quantum image processing are mentioned in this paper. This review article will provide the readership an overview of progress witnessed in the area of Quantum Image processing while also simulating further interest to pursue more advanced research in it.
A Transfer Learning End-to-End ArabicText-To-Speech (TTS) Deep Architecture

Speech synthesis is the artificial production of human speech. A typical text-to-speech system converts a language text into a waveform. There exist many English TTS systems that produce mature, natural, and human-like speech synthesizers. In contrast, other languages, including Arabic, have not been considered until recently. Existing Arabic speech synthesis solutions are slow, of low quality, and the naturalness of synthesized speech is inferior to the English synthesizers. They also lack essential speech key factors such as intonation, stress, and rhythm. Different works were proposed to solve those issues, including the use of concatenative methods such as unit selection or parametric methods. However, they required a lot of laborious work and domain expertise. Another reason for such poor performance of Arabic speech synthesizers is the lack of speech corpora, unlike English that has many publicly available corpora and audiobooks. This work describes how to generate high quality, natural, and human-like Arabic speech using an end-to-end neural deep network architecture. This work uses just $\langle$ text, audio $\rangle$ pairs with a relatively small amount of recorded audio samples with a total of 2.41 hours. It illustrates how to use English character embedding despite using diacritic Arabic characters as input and how to preprocess these audio samples to achieve the best results.
Discussion of "On nearly assumption-free tests of nominal confidence interval coverage for causal parameters estimated by machine learning"

We congratulate the authors on their exciting paper, which introduces a novel idea for assessing the estimation bias in causal estimates. Doubly robust estimators are now part of the standard set of tools in causal inference, but a typical analysis stops with an estimate and a confidence interval. The authors give an approach for a unique type of model-checking that allows the user to check whether the bias is sufficiently small with respect to the standard error, which is generally required for confidence intervals to be reliable.
The Effectiveness of Supervised Machine Learning Algorithms in Predicting Software Refactoring

Refactoring is the process of changing the internal structure of software to improve its quality without modifying its external behavior. Empirical studies have repeatedly shown that refactoring has a positive impact on the understandability and maintainability of software systems. However, before carrying out refactoring activities, developers need to identify refactoring opportunities. Currently, refactoring opportunity identification heavily relies on developers' expertise and intuition. In this paper, we investigate the effectiveness of machine learning algorithms in predicting software refactorings. More specifically, we train six different machine learning algorithms (i.e., Logistic Regression, Naive Bayes, Support Vector Machine, Decision Trees, Random Forest, and Neural Network) with a dataset comprising over two million refactorings from 11,149 real-world projects from the Apache, F-Droid, and GitHub ecosystems. The resulting models predict 20 different refactorings at class, method, and variable-levels with an accuracy often higher than 90%. Our results show that (i) Random Forests are the best models for predicting software refactoring, (ii) process and ownership metrics seem to play a crucial role in the creation of better models, and (iii) models generalize well in different contexts.
On training deep networks for satellite image super-resolution

The capabilities of super-resolution reconstruction (SRR)---techniques for enhancing image spatial resolution---have been recently improved significantly by the use of deep convolutional neural networks. Commonly, such networks are learned using huge training sets composed of original images alongside their low-resolution counterparts, obtained with bicubic downsampling. In this paper, we investigate how the SRR performance is influenced by the way such low-resolution training data are obtained, which has not been explored up to date. Our extensive experimental study indicates that the training data characteristics have a large impact on the reconstruction accuracy, and the widely-adopted approach is not the most effective for dealing with satellite images. Overall, we argue that developing better training data preparation routines may be pivotal in making SRR suitable for real-world applications.
Reflections on Lament Of 30 % Matric Pass Mark In South African Schools

This study examines the minimum matric pass mark of 30 percent in South African schools which has remained one of the most worrisome concerns in the education sector in terms of the quality of education delivered by schools and the number of pupils produced each year. The 30 percent figure contradicts one of Department of Basic Education's core objectives, which is to commit to quality, because 30 percent cannot reach perfection. Therefore this study's primary aim was to show reflections on lament on 30 percent matric pass mark in South African schools and the predicted end result of this 30 percent matric pass mark if it is not adjusted. The long-term goal of the project was to investigate the implications of maintaining the matriculation cut-off score of 30 percent rather than raising it to a threshold of 50 percent. This study make use of content analysis to analyse data from social media that include Facebook, twitter and blogs post. The results made it clear that there is a need for the government to take education seriously by upgrading the pass rate from 30 percent going up, the study shows that the policy should be reviewed or amended with a minimum pass mark of 50 percent in order for learners to be able to qualify for NSC on HC entrance requirements. The results shows that with at 50% pass mark learners will have various opportunities, such as continuing their education in tertiary education or entering the job market. The study suggests recommendations such as the matric learners must be awarded certificate based on 100 percent exam percentage by removing 25 percent of school based assessment as it counts to the final promotion mark in Grade 12..
Legal Regulation on Cyberbullying of Children

With the prevalence of social networking sites, cyberbullying of children has intensified all over the world and caused serious social problems. Compared with traditional bullying, cyberbullying is more widespread, the methods are more diverse, and the harm to children is more persistent.To further legally regulate children's cyberbullying behavior, the relevant laws of China, the United States, and Japan were selected to investigate, to find out the common points of their laws on children's cyberbullying. The final paper proposes that the behavior of children's cyberbullying should be punished by law, and the correct guidance of society, schools, and families to children's use of the Internet should be strengthened.
Stochastic optimization in digital pre-distortion of the signal

In this paper, we test the performance of some modern stochastic optimization methods and practices in application to digital pre-distortion problem, that is a valuable part of processing signal on base stations providing wireless communication. In first part of our study, we focus on search of the best performing method and its proper modifications. In the second part, we proposed the new, quasi-online, testing framework that allows us to fit our modelling results with the behaviour of real-life DPD prototype, retested some selected of practices considered in previous section and approved the advantages of the method occured to be the best in real-life conditions. For the used model, maximum achieved improvement in depth was 7% in standard regime and 5% in online one (metric itself is of logarithmic scale). We also achieved a halving of the working time preserving 3% and 6% improvement in depth for the standard and online regime, correspondingly. All comparisons are made to the Adam method, which was highlighted as the best stochastic method for DPD problem in paper [Pasechnyuk et al., 2021], and to the Adamax method, that is the best in the proposed online regime.
Integrated Room Temperature Single Photon Source for Quantum Key Distribution

High-purity single photon sources (SPS) that can operate at room temperature are highly desirable for a myriad of applications, including quantum photonics and quantum key distribution. In this work, we realise an ultra-bright solid-state SPS based on an atomic defect in hexagonal boron nitride (hBN) integrated with a solid immersion lens (SIL). The SIL increases the source efficiency by a factor of six, and the integrated system is capable of producing over ten million single photons per second at room temperature. Our results are promising for practical applications of SPS in quantum communication protocols.
The Effects of Vocabulary Mastery and Logical Thinking on Junior High School Students’ Listening Skill

This research is aimed as follows: To get empirical data and analyze the effects of vocabulary mastery and logical thinking towards students’ listening skills at Junior High School in East Cirebon. This research is done by Kolmogorov-Smirnov method, ANOVA Table, Proportional Correct for testing the item difficulties, by a biserial coefficient, and by Kuder Richarsson testing. The research was held at Junior High School in East Cirebon. Data collective done by giving a test for listening skill (yes/no or true-false / 37 items), test for vocabulary mastery (Multiple choice/ 20 items), and test for logical thinking (multiple choice/20 items) given to the class at, SMP N 1 Ciledug, SMP N 1 Pabedilan, and SMP N 1 Losari. The result of the study identifies the effect of Vocabulary Mastery on Student’s Listening skills (coefficient of 0,745 and coefficient determination of 55,4%). The effect of logical thinking towards student’s listening skill (Sig = 0.031 and ttest = 2,183; while ttable = 1,98. There is an effect of vocabulary mastery and logical thinking on students’ listening skills (Sig = 0.000 and ttest = 4,757 while ttable = 1,98.).