Reviewerly/exHarmony huggingface dataset:
PRONUNCIATION LEARNING, PARTICIPATION, AND ATTITUDE ENHANCEMENT THROUGH MOBILE ASSISTED LANGUAGE LEARNING (MALL)

: A mobile application, Tflat English Pronunciation, is proposed in the teaching of pronunciation for it possesses features that can assist students when learning how to enunciate English words and identify English phonemic symbols.� Thus, this study presents the results of the implementation of Tflat English Pronunciation mobile courseware to gain the ability of the first semester students of English Study Program Politeknik Negeri Jember in pronouncing English words. This study is a collaborative classroom action research. Thirty students enrolling in Pronunciation class at English Study Program Politeknik Negeri Jember were taken as the source of data. The result showed that the materials and practices in Tflat courseware could enrich students' pronunciation learning, improve their participation, and nurture a positive attitude toward technological learning. The findings of this study also depict the potential and power of Mobile Assisted Language Learning (MALL) to encourage students to engage in classroom activities and monitor their learning. Hence, it can be concluded that MALL is pivotal and can be one alternative to facilitate students� pronunciation learning.�
An efficient image steganography method using multiobjective differential evolution

Information hiding is very important during the transmission, so that it cannot be disclosed to unauthenticated persons. Steganography is one of the famous methods to hide the potential information. Many methods have been proposed by researchers to make a secure stegoimage. However, most existing methods suffer from low payload, distorted cover image, and poor security. To overcome these issues, in this chapter, we propose a steganography method based on differential evolution and the least significant substitution (LSB) method. Differential evolution is utilized to optimize the mask assignment list of LSB method. The mask assignment list is considered as the solution of a differential evolution. Thereafter differential evolution updates the solutions and provides the optimized assignment list for embedding a secret image into a cover image. The experimental results show that the proposed method provides better stegoimage quality and robustness against noise attacks as compared to other steganography methods.
Technology and Innovation in Schoolchildren Training: Development of Musical and Acting Skills

Today, the main problem of additional education institutions is comprehensive pre-professional training, allowing students to master the professions of musician, dancer, or actor.In recent decades, there has been a tendency to narrow specialization in teaching children, which is the reason why modern educators seek to improve programs.The purpose of the work is to determine the content and identify innovative teaching technologies, in particular, those related to the development of musical and acting abilities.Study methods include the analysis of modern experience in applying traditional and innovative approaches to develop musical and acting skills and testing the most effective pedagogical technologies of creative development of schoolchildren.The conclusions of the study are related to the fact that the comprehensive development of schoolchildren implies not only the development of basic skills and abilities, but also the formation of artistic taste and musical and acting skills.This is necessary to create artistic images in various types of art, which needs to be taught from early childhood.An important aspect of the study is the belief that comprehensive pre-professional training of students allows one to reveal all aspects of the child's personality and determine the direction of their future professional path.Basic musical and acting skills necessary for many areas of professional activity are easily acquired in childhood due to the psychophysiological characteristics of students.Thus, the problem of the development of musical and acting skills in schoolchildren, which requires innovative approaches and modern pedagogical technologies, is actualized.
Bangla Optical Character Recognition and Text-to-Speech Conversion using Raspberry Pi

Optical Character Recognition (OCR) technology is very helpful for visually impaired or illiterate persons who are unable to read text documents but need to reach the content of the text documents.In this paper, a camera-based assistive device is used that can be applied for visually impaired or illiterate people to understand Bangla text documents by listening to the contents of the Bangla text images.This work mainly involves the extraction of the Bangla text from the Bangla text image and converts the extracted text to speech.This work has been fulfilled with Raspberry Pi and a camera module by applying the concepts of the Tesseract OCR engine, the Open Source Computer Vision, and the Google Speech Application Program Interface.This work can help people speaking Bangla language who are unable to read or have a significant loss of visual sight.
Advanced iterative algorithm for phase calibration of spatial light modulators integrated in optical instrumentation in a vibration environment

We present a method to obtain the phase modulation characteristic curve of a spatial light modulator (SLM) under severe vibration conditions. The procedure is based on the well-known advanced iterative algorithm (AIA), which allows wavefront extraction from unknown phase-shifted interferograms. Generally, AIA is used to determine the wavefront and the determined phase shifts are of little interest. In contrast, in our method, the main goal of using AIA is to determine the unknown phase shifts induced by an SLM during the calibration procedure. Using a segmented approach to calibration, AIA enables successful calibration even in the presence of additional random phase shifts due to environmental changes. This method has the potential to calibrate SLMs integrated in complex optical instruments with little to no modifications to the optical setup, no matter the environmental conditions. We demonstrate our technique by calibrating an SLM under vacuum conditions ( <mml:math xmlns:mml="http://www.w3.org/1998/Math/MathML" display="inline"> <mml:mrow class="MJX-TeXAtom-ORD"> <mml:msup> <mml:mn>10</mml:mn> <mml:mrow class="MJX-TeXAtom-ORD"> <mml:mo>−<!-- − --></mml:mo> <mml:mn>5</mml:mn> </mml:mrow> </mml:msup> </mml:mrow> <mml:mspace width="thickmathspace" /> <mml:mrow class="MJX-TeXAtom-ORD"> <mml:mrow class="MJX-TeXAtom-ORD"> <mml:mi mathvariant="normal">m</mml:mi> <mml:mi mathvariant="normal">b</mml:mi> <mml:mi mathvariant="normal">a</mml:mi> <mml:mi mathvariant="normal">r</mml:mi> </mml:mrow> </mml:mrow> </mml:math> ) in a common-path configuration compatible with usage of an SLM as a wavefront modulator at the pupil plane of an instrument. Our technique compensates for the vibrations produced by the vacuum pumps and reduces an order of magnitude the root-mean-squared error of the calibration curve evaluated with vibration errors. Our technique enhances the potential use of SLMs in complex optical systems, including aerospace optical instrumentation.
Image Compression-Encryption Scheme via Fiber Specklegram-Based Compressive Sensing and Double Random Phase Encoding

An image compression-encryption scheme utilizing the combination of fiber specklegram-based compressive sensing (CS) and double random phase encoding (DRPE) was demonstrated. The original image is compressed and encrypted by CS and then re-encrypted by DRPE. The measurement matrices for CS are constructed from multimode fiber specklegrams resulting from modes excitation and interference, which show better performance compared with those based on Gaussian random variables. Since fiber specklegrams have strong dependence on configuration, such measurement matrix can be constructed either by one specklegram or by specklegrams from different launched wavelengths. The double-encrypted image demonstrated good safety and reliability in several common attacks and presented high key sensitivity, which indicates good performance of the proposed scheme.
Review on Room Layout Estimation from a Single Image

Goal of room layout estimation is to predict the spatial layout of a room from a monocular image.It aims at finding the wall-floor, wall-wall, wall-ceiling boundaries from a single room image.The room layout can provide a better understanding of the 3D scenes.The room layout can be integrated into mixed reality games to supply a far better immersiveness experience, or utilized in other related augmented reality applications such room redecoration.Various studies have been introduced for room layout estimation.This paper review several works which deal with room layout estimation.
Enhancing African low-resource languages: Swahili data for language modelling

Language modelling using neural networks requires adequate data to guarantee quality word representation which is important for natural language processing (NLP) tasks. However, African languages, Swahili in particular, have been disadvantaged and most of them are classified as low resource languages because of inadequate data for NLP. In this article, we derive and contribute unannotated Swahili dataset, Swahili syllabic alphabet and Swahili word analogy dataset to address the need for language processing resources especially for low resource languages. Therefore, we derive the unannotated Swahili dataset by pre-processing raw Swahili data using a Python script, formulate the syllabic alphabet and develop the Swahili word analogy dataset based on an existing English dataset. We envisage that the datasets will not only support language models but also other NLP downstream tasks such as part-of-speech tagging, machine translation and sentiment analysis.
An Analytical Approach to Assess and Compare the Vulnerability Risk of Operating Systems

Operating system (OS) security is a key component of computer security.Assessing and improving OSs strength to resist against vulnerabilities and attacks is a mandatory requirement given the rate of new vulnerabilities discovered and attacks occur.Frequency and the number of different kinds of vulnerabilities found in an OS can be considered an index of its information security level.In the present study we assess five mostly used OSs, Microsoft Windows (windows 7, windows 8 and windows 10), Apple's Mac and Linux for their discovered vulnerabilities and the risk associated in each.Each discovered and reported vulnerability has an Exploitability score assigned in CVSS [27] of the national vulnerability data base.We compare the risk from vulnerabilities in each of the five Operating Systems.The Risk Indexes used are developed based on the Markov model to evaluate the risk of each vulnerability [11,21,22].Statistical methodology and underlying mathematical approach is described.The analysis includes all the reported vulnerabilities in the National Vulnerability Database [19] up to October 30, 2018.Initially, parametric procedures are conducted and measured.There are however violations of some assumptions observed.Therefore, authors recognized the need for non-parametric approaches.6838 vulnerabilities recorded were considered in the analysis.According to the risk associated with all the vulnerabilities considered, it was found that there is a statistically significant difference among average risk level for some operating systems.This indicates that according to our method some operating systems have been more risk vulnerable than others given the assumptions and limitations.Relevant Test results revealing a statistically significant difference in the Risk levels of different OSs are presented.
Stream-Based Lossless Data Compression Applying Adaptive Entropy Coding for Hardware-Based Implementation

Toward strong demand for very high-speed I/O for processors, physical performance growth of hardware I/O speed was drastically increased in this decade. However, the recent Big Data applications still demand the larger I/O bandwidth and the lower latency for the speed. Because the current I/O performance does not improve so drastically, it is the time to consider another way to increase it. To overcome this challenge, we focus on lossless data compression technology to decrease the amount of data itself in the data communication path. The recent Big Data applications treat data stream that flows continuously and never allow stalling processing due to the high speed. Therefore, an elegant hardware-based data compression technology is demanded. This paper proposes a novel lossless data compression, called ASE coding. It encodes streaming data by applying the entropy coding approach. ASE coding instantly assigns the fewest bits to the corresponding compressed data according to the number of occupied entries in a look-up table. This paper describes the detailed mechanism of ASE coding. Furthermore, the paper demonstrates performance evaluations to promise that ASE coding adaptively shrinks streaming data and also works on a small amount of hardware resources without stalling or buffering any part of data stream.
Communicative Constitution of Illicit Online Trade Collectives: An Exploration of Darkweb Market Subreddits

This study aims to understand communicative activities of an illicit cyber-trade community on an anonymous social platform, Reddit. Based on the communication-as-constitutive of organization (CCO) perspective, the study identifies participants with different levels of engagement, and examines how their discursive engagement collectively reflects the ways in which illicit market users co-orient themselves to respond to a crisis event (i.e., market shutdown). The empirical case for this study is a subreddit channel dedicated to what was once the largest dark web market: r/AlphabayMarket. We examine two month period's posting activities until market was permanently shut down in July 2017. Our analysis comprises three parts. First, a social network analysis was conducted to identify key and non-key players in the community. Second, a structural topic modeling was computed to inductively infer topic clusters. Third, posts were manually reviewed to articulate the process of co-orientation manifest in the results of topic modeling.
Location Privacy Preservation Based on Continuous Queries for Location-Based Services

In recent years, location-based services (LBSs) have become increasingly popular, as they can greatly facilitate people’s daily life. However, LBSs also raise serious concerns that the collected big data can be utilized by adversaries to track users’ movements, and infer their specific locations and living habits. To address this privacy issue, we propose an algorithm based on the k-anonymity criterion, to generate dummy locations to protect users’ privacy. We also develop a new metric, the trajectory entropy, to measure the performance of anonymity. Different from the existing technologies, which focus on the stationary location privacy, we further consider the correlation between adjacent locations in the continuous queried process. We assume it as a Markov process and exploit such Markov process to achieve privacy protection. Our simulation results on the real-life dataset show that compared with other algorithms, the proposed algorithm exhibits superior performance in providing location anonymity by resisting most attacks.
Professional training of a future biology teacher using M-learning technology

The article is defined the essence of mobile learning, its opportunities in the professional training of a future biology teacher, and outlines its advantages and disadvantages.Implementation of M-learning in the educational process of training future specialists in higher education is in three directions: access to sites with educational information (distance learning); playback of audio, text videos and image files with educational information (refinement, visualization); organization of training using electronic textbooks, training courses and specialized training information files.Organization M-learning is possible using of mobile applications -special applications for mobile phones with educational and developmental function.Representative analysis and practice testing of a various of mobile applications on the Google Play Portal revealed the possibility of using a number of mobile applications in training activities with biology students.Its can be useful in studying the species plants composition, mastering Latin terms, studying the features of practical use of plants, etc. Mobile applications for determining the plant species are represented by a large group of applications, its principle is the analysis of photos of the vegetative and generative parts of the plant and comparing them with the photobase.Some annexes offer expert advice.The reference Mobile applications can be useful in conducting the morphological description of plants, identifying the characteristics of their chemical composition and use in medicine, conducting business activity (crop production).Mobile applications of mastering biological Latin terms can be useful in mastering the disciplines of a professional training cycle.Mobile applications in chemistry can be useful in the study the chemical composition of cells, the course of metabolic processes of aerobes and anaerobes.Basic advantages and lacks of application of mobile studies are certain.M-learning is characterized by mobility and flexibility, appropriate for both classroom and non-classroom forms of student work.
Estimation of the Laser Frequency Noise Spectrum by Continuous Dynamical Decoupling

Decoherence induced by laser frequency noise is one of the most important obstacles in quantum information processing. In order to suppress this decoherence, the noise power spectral density needs to be accurately characterized. In particular, the noise spectrum measurement based on the coherence characteristics of qubits would be a meaningful and still challenging method. Here, we theoretically analyze and experimentally obtain the spectrum of laser frequency noise based on the continuous dynamical decoupling technique. We first estimate the mixture-noise (including laser and magnetic noises) spectrum up to $(2\ensuremath{\pi})530$ kHz by monitoring the transverse relaxation from an initial state $+X$, followed by a gradient descent data process protocol. Then the contribution from the laser noise is extracted by encoding the qubits on different Zeeman sublevels. We also investigate two sufficiently strong noise components by making an analogy between these noises and driving lasers whose linewidth is assumed to be negligible. This method is verified experimentally and finally helps to characterize the noise.
Effectiveness of E-Learning Media to Improve Learning Outcomes Natural Science in Primary Schools

This study aims to determine the effectiveness of the application of e-learning media in science lessons on the learning outcomes of fourth-grade students in primary school. Experimental research was conducted for four weeks with learning using e-learning media as an experimental group (n = 32) and using book-based learning as a control group (n = 30). This study used a quasi-experimental method with a pre-test and post- test control group design. The research instrument was taken from observations and scores on student learning outcomes. The data were analyzed using quantitative statistical tests. Based on the data, the researchers know that a teacher plays an important role in developing student learning media through ICT-based e-learning learning design. Also, the results of the study based on the Mann-Whitney N-gain score of students' comprehension ability obtained a significance value of 0.00 &lt;α = 0.05. So that H0 was rejected. This result shows that the ability of students to understand science using e-learning media is significantly better than students who get book-based learning.
<i>STARANISO</i>: use of a WebGL-based 3D interactive graphical display to represent and visualise data quality metrics for anisotropic macromolecular diffraction data

The STARANISO webserver for processing macromolecular diffraction data, either in the unmerged (unscaled or already scaled) state or in the already-scaled and merged state, has been available for use by the community since January 2016, during which time around 6500 user datasets have been successfully processed and the results returned to users.The server is specifically targeted at datasets with significant anisotropic diffraction in the hope that mitigation of the effects of the anisotropy will lead to improved electron-density maps, and this has indeed turned out to be the case for a significant proportion of datasets submitted.In our view a critical component of the server is a WebGL-based 3-D interactive graphical display to represent and visualise data quality metrics for anisotropically-corrected macromolecular diffraction data.We are of the view that it is impossible to adequately specify the quality of data in terms of a small number of metrics such as completeness, R meas , mean I / (I) or CC(½), whether specified as spherical bin averages or as overall averages.Equally, even knowledge of the overall anisotropy tensor and associated metrics such as anisotropic diffraction limits do not provide a full picture of the data quality.The 3-D interactive display provided by the server provides full access not only to the anisotropy analysis but also to properties and quality criteria for the dataset, such as the error model, redundancy, completeness and statistical significance.
An Analysis of Key Factors to Mobile Health Adoption using Fuzzy AHP

In the present era, ICT has brought significant facilities for the growth and innovation of organizations.Thus, with the advent of information technology in the field of healthcare, significant advances have been made in terms of the high level of care in preventing a variety of diseases and treatments as well.Mobile health, which is a part of smart health concept, helps people, at any time and place, use smart devices such as smartphones, smart watches, and the like to monitor their health status like pulse, blood pressure and so on.Therefore, this article aims to examine the effective factors on the adoption of mobile health technology.According to the field of research and the number of people considered, this study examined some of the factors affecting the adoption of mobile health technology among 19 expert experts who have mainly researched in this field.This research uses the Fuzzy AHP method.The main factors for admitting mobile health technology were divided into five main categories, including system quality, information quality, individual factors, service quality, and organizational quality.The results indicated that system quality, quality of information and individual factors have more impact on the acceptance of mobile health technology than service quality and organizational factors.In addition, according to the results obtained in this study, mobile health can be used as the most reliable and safest tools to control and monitor diseases.Ultimately, experts emphasized the need to use mobile health technology continuously.