Reviewerly/exHarmony huggingface dataset:
Software Quality Assurance Practices for Medical Mobile Applications

Technological advancements have major challenges in the Medical Mobile Application(MMA) development process. Software applications have a strategic market in the software manufacturing industries. These provide solutions to major real-life problems. The major specifications in any software project are its quality. Software quality assurance (SQA) and Software Quality Management (SQM) are the key processes. This paper evaluates the SQA and SQM activities of the MMA development process through a research survey. The survey was conducted to verify the practices related to both SQA and SQM activities in the MMA development process. The study includes the 17 types of MMA and 9 of which were low-risk-based general healthcare MMA's. The information was gathered utilizing the SEI maturity questionnaire that emphasis the SQA and SQM activities. The instrument administered the MMA developers and software project managers involved in the survey.
WHAT IS THE PROFESSIONAL FLEXIBILITY OF FUTURE TEACHERS

WHAT IS THE PROFESSIONAL FLEXIBILITY OF FUTURE TEACHERS &nbsp; Anna Cherepanova Lecturer of the Department of State and Foreign Languages, Almaty Technological University, Kazakhstan, Almaty &nbsp; ABSTRACT The article considers
DIGITAL VISUALIZATION OF STORYTELLING AS A METHOD OF FORMATION OF COMMUNICATIVE COMPETENCE OF FUTURE EDUCATORS

The proposed article analyses storytelling as a method of forming the communicative competence of future educators. Storytelling is seen as a method of improving students’ communicative competence and as a means of digital visualization. However, the concept of communicative competence includes mastering the necessary set of not only speech knowledge but also skills in the communicative aspect of any professional activity, as well as the practical use of communication tools necessary for the formation of a socially active personality oriented in the modern world. We are currently using new techniques that will help future educators to form speech competence (phonetics, vocabulary, grammar) of preschool children through the introduction into the educational process of methods that allow: to speak, write and listen. This method allows to implement the educational process at the Pedagogical Institute of Borys Grinchenko Kyiv University with extensive use of multimedia forms of teaching material on the example of the content module “Theatrical Art as a Component of Preschool Education”, integrated course “Polyart Education of Preschool Children” for students majoring in 013 “Primary Education”, specialization “Preschool Education”. Students learn to solve problems, reveal ideas, use a cloud of words, compose comics, intelligence maps, interactive books, cartoons, videos, collages. The tasks of storytelling are covered: to capture the attention of the reader or viewer; to inspire trust; to create associations; to stimulate the emotional sphere and evoke empathy; to memorize stories. The main elements of storytelling and the main software tools for creating digital visualization of storytelling are identified. The essence of the concept of “storytelling” as a method of formation of communicative competence is substantiated and analysed. The activities of the Center for Innovative Educational Technologies (ICR) in the practical training of future educators are revealed and a list of tools and programmes such as Closr, ZooBurst, Narrable, Storify, Metta, PowToon, Moovly, Wideo and GoAnimate, Chogger and ToonDoo, used in the work with students are presented.
Exponential Reduction in Sample Complexity with Learning of Ising Model Dynamics

The usual setting for learning the structure and parameters of a graphical model assumes the availability of independent samples produced from the corresponding multivariate probability distribution. However, for many models the mixing time of the respective Markov chain can be very large and i.i.d. samples may not be obtained. We study the problem of reconstructing binary graphical models from correlated samples produced by a dynamical process, which is natural in many applications. We analyze the sample complexity of two estimators that are based on the interaction screening objective and the conditional likelihood loss. We observe that for samples coming from a dynamical process far from equilibrium, the sample complexity reduces exponentially compared to a dynamical process that mixes quickly.
Prototype of Application Machine Translation Lampung Language Sentence of Api Dialect Dictionary Based Using Python Programming

Prototype of apllication machine translation Lampung language sentence of Api dialect was build using python programming collaborated with Lampung language dictionary. Nowadays students in Lampung province still translating Lampung language into Indonesian language using manual dictionary. Another choice is translating Lampung language sentence into Indonesian language automatically and still using the dictionary, especially digital dictionary with translation ability. In this approach, sentence was parted into several parts according to spacing, the result is a word list that will be matched into the key in dictionary database. The result of matching is called value, a word in Indonesianlanguage, that will be arranged again into an Indonesian languege sentence. Lampung language need to be conserved. In context of conserving and avoid its extinction. Thisis very important because Lampung language is an identity for its region. Institution of education must help to conserve Lampung language. Academics have the potential to use computer-based tools as an effort to preserve the Lampung language digitally according to current technological developments. The main objective of this research is to build a prototype of Lampung Api dialect machine translator application. Prototype applicationcreated as an alternative solution plan in translating Lampung language while maintaining the use of the dictionary. In building this application the waterfall method approach is used with the main focus on the sentence translation algorithm. The application can translate Lampung sentences according to the vocabulary contained in the reference dictionary used. The next potential research that can be done is to translate sentences by paying attention to aspects of morphology, syntax, semantics in Lampung language.Keywords: prototype, dictionary, Lampung languege, python programming
A Design Science Tool to Improve Code Maintainability for Hypertext Pre-processor (PHP) Programs

Aim/Purpose: A design science tool to improve code maintainability for PHP programs. Background: This paper addresses this issue by providing an enhancement to an existing tool that specifically addresses and improves program maintainability for PHP programs. Methodology: This paper uses design science research which involves creating or modifying one or more artifacts. In this case, the artifact is PHP Code Sniffer, which was modified to improve code maintainability of PHP programs. Contribution: This paper provides a method of improving code maintainability of PHP programs. Findings: Code quality in terms of maintainability is a modern-day issue. No tool specifically addresses maintainability. When updating PHP code that has poor maintainability, there is a much higher likelihood that errors will be introduced than with code that is more maintainable. Recommendations for Practitioners: For PHP developers and project leaders dealing with PHP programs, running the modified PHP Code Sniffer will improve code maintainability. Recommendations for Researchers: Examine ways to improve other code quality aspects such as reliability, security, usability, efficiency, and so on. Impact on Society: PHP programs, which run the background processes behind most web pages, will be more robust, reliable, and correct. Future Research: Expand this to investigate improving maintainability for other common programming languages.
The Features of Teachers’ Training in the Field of Application of Information Technologies in Education

The article observes the modern trends in teachers’ training in the field of using of information technologies in education. The purpose of the article is to identify the drawbacks of the existing educational system in this field and to offer recommendations for their elimination. The authors have analyzed the experience of pedagogical high schools of Russia in teaching application of information technologies in education, in particular, the experience of Moscow City University, that was one of the first in Russia to establish Department of Application of Information Technologies in Education for conducting basics of application of information technologies in education training of future teachers. The authors identified the main drawbacks of current pedagogical training in sphere of application of information technologies in education and gave recommendations on how to make it more effective. They formulated the priority direction in training of application of information technologies in education and the main goals and objectives of training teachers in this field. The authors singled out the key elements of the content of application of information technologies in education courses for teachers, and principles characterizing the application of information technologies in education as educational discipline. Recommendations formulated in the article will be useful for educational courses creation in sphere of application of information technologies in education aimed at training of future and current teachers of schools and high schools.
An Artificial Neural Network based Adaptive Histogram Equalization Algorithm for Enhancement of Low Contrast Images

The implementation of an image contrast enhancement algorithm along with artificial intelligence techniques can have various applications besides modern photography. It basically ameliorates the quality of low contrast images. The main focus of this research is developing a new image contrast enhancement method that combines the concept of artificial intelligence and histogram equalization techniques to provide a contrast distribution for the low contrast images by utilizing the classifier to prevent data loss from images. In this research an ANN based AHE algorithm for enhancement of low contrast images is proposed. The main objectives of this research is to study the existing digital image contrast enhancement techniques to find out the exact problems and to classify the level of contrast in a digital image as low or high, so as to ascertain whether enhancement is required or not. The concept of ANN with AHE is used here to find out the contrast level of the image before processing for contrast enhancement. For validation of the proposed ANN-AHE algorithm, a comparison with the existing techniques are performed on the behalf of performance parameters such as PSNR, MSE, Entropy, QI, QRCM, CQE, SSIM and Computational Time. The simulation of the proposed model is performed in MATLAB 2016a with the help of image processing and artificial neural network toolbox.
Matrix Sketching for Secure Collaborative Machine Learning

Collaborative learning allows participants to jointly train a model without data sharing. To update the model parameters, the central server broadcasts model parameters to the clients, and the clients send updating directions such as gradients to the server. While data do not leave a client device, the communicated gradients and parameters will leak a client's privacy. Attacks that infer clients' privacy from gradients and parameters have been developed by prior work. Simple defenses such as dropout and differential privacy either fail to defend the attacks or seriously hurt test accuracy. We propose a practical defense which we call Double-Blind Collaborative Learning (DBCL). The high-level idea is to apply random matrix sketching to the parameters (aka weights) and re-generate random sketching after each iteration. DBCL prevents clients from conducting gradient-based privacy inferences which are the most effective attacks. DBCL works because from the attacker's perspective, sketching is effectively random noise that outweighs the signal. Notably, DBCL does not much increase computation and communication costs and does not hurt test accuracy at all.
Mastering Your Entire Developer Ecosystem

There is more to getting set up for Android development than just installing Android Studio. While you can do just that – and only that – you will eventually find there are other aspects of your computer, and the software it runs, that will make a big difference to your productivity, ambition, and competence as an Android developer. This chapter is not exhaustive, but does give you a lot of important foundational considerations, as well as links to where to go next to learn more. Read on!
The importance of justice as a moral value

Justice plays an important role today as a broad concept that has its place in all spheres of social life.On the moral aspect of justice, the National Encyclopedia of Uzbekistan states that “the moral aspect of justice means to treat people equally, not to offend each other’s dignity, to follow the rules of morality.” Ethical qualities are formed in the family, educational institution, neighborhood and work community. People develop insights and conclusions about moral values. The role of these structures in the rise of justice to the level of moral value is invaluable. As we strive to form the perfect man, we must pay attention to the principles of justice on all fronts.
Supervised Learning Techniques for Classification Of Students’ Tweets

In today’s era, up-to-date information can be retrieved from social network, internet community and data forums. People especially the younger generation share their feelings, happiness, experience and also day to day happenings in the social media platforms like Twitter. There exists large volume of unstructured data in it. The proposed system concentrates on the learning process of the engineering students and the problems faced by them during their study from their twitter posts. Since the data collected is huge, Apache hadoop map reduce environment is used for processing. The system includes pre-processing of tweets, calculating F1 measure, identifying prominent categories, identifying word and category probability and finally classifies tweets to the respective categories. The supervised learning techniques such as multiclass SVM based Platt Scaling, Naive Bayes and logistic regression are used to identify heavy study load, lack of social engagement and sleep problems. Comparing the results attained, SVM achieves an accuracy score of 84% which is 5 to 10 percent higher than Logistic Regression and Naive Bayesian method.
"Take It Outside, People!": Bridging Ecoacoustics and Improvised Music

The era of COVID-19 has profoundly shaken the foundations of our lives. Our event venues have closed; the support systems that we depend on for delivering works of art have all been shuttered. In response, musicians have turned to the digital world. While the digital world has become an important collaborative interface, I believe it is imperative to also explore the opposite direction—and take it outside! Even pre-COVID-19, it has been important to expand musical methodologies by connecting music creation systems with environmental sound practices in new ways. As recent developments in technology have opened up the possibilities of new types of environmentally based artistic engagement, artists of all kinds increasingly feel a profound need to participate in climate crisis activism through creative work.Immersive participation is at the center of the fields of ecoacoustics, soundscape ecology, and related fields. These practices involve acts of listening and responding in participatory environmental engagement. Meanwhile, the field of critical improvisation has expanded from methodologies rooted in music and other arts to connect to a tapestry of multidisciplinary enquiries. I postulate that a shared fundamental human musical “task-scape” lies deep within the behavior systems of both improvised music and environmentally based sound practices. Both areas are constructed with methodologies for engaging with interactive dynamics of the unexpected, and both explore the profound phenomena between the observer and sound.  In this article, I will illuminate how to bring these fields together in new ways by connecting pedagogies and practices within these arenas. Moreover, I will connect these to some of the more profound issues of our time through methodologies of improvised music and ecoacoustics to create new opportunities for performance and practice during and after COVID-19 as well as offer new types of research and artistic expression in regard to climate crisis.
A Novel Clustering Based Near Duplicate Video Retrieval Model

There are various video related tools, such as video sharing, recording, marketing, and consulting. Ironically the video-related tasks are uploading, sharing, posting and searching the video content as per the need and requirement. There is an increase in the usage of video posting, sharing and uploading upon the social media for various purposes. The increase in the usage of near-duplicate videos (NDVs) created on the Internet are in various forms, such as simple reformatting, to specific purchases, transformations, editions, and mixtures of distinct impacts. Joint multi-view hashing is a promising alternative for translating videos into compact and low-dimensional binary codes, inspired by observing multiple retrieval models. With this form of hashing video storage and time usage in the recovery process is increased. The main purpose of this work is to build a novel clustering model to maintain multiple feature structures and to reduce the retrieval process's time consumption.
An assessment of the UK approach to parametric claims after <i>Actavis v Eli Lilly</i>

An assessment of the UK approach to parametric claims after Actavis v Eli Lilly Ilya Gribanov Ilya Gribanov Email: ilya.gribanov@outlook.com Search for other works by this author on: Oxford Academic Google Scholar Journal of Intellectual Property Law & Practice, Volume 16, Issue 2, February 2021, Pages 109–123, https://doi.org/10.1093/jiplp/jpaa210 Published: 09 January 2021
Importance of dictions when teaching singer-actor

Singing can be called a musical speech, and therefore the singing voice differs from the spoken one not only in range and strength, but also in timbre, that is, it differs in the so-called voice coloring. In the training of vocalists, it is important to understand that there is a close relationship between the diction of the vocalist and his voice formation. The activity and coherence of the work of articulatory organs determines the quality of pronunciation of speech sounds, legibility of words, or diction. This topic is relevant today - practice shows that many students of vocals need staging diction. In addition, vocal pedagogy necessarily involves teaching a clear and expressive pronunciation of words, as a necessary condition for the performance of a vocal work. And I must say that the expressiveness of diction cannot be obtained without certain techniques.
The Seventh International Olympiad in Cryptography NSUCRYPTO: problems and solutions.

The International Olympiad in Cryptography NSUCRYPTO is the unique Olympiad containing scientific mathematical problems for professionals, school and university students from any country. Its aim is to involve young researchers in solving curious and tough scientific problems of modern cryptography. In 2020, it was held for the seventh time. Prizes and diplomas were awarded to 84 participants in the first round and 49 teams in the second round from 32 countries. In this paper, problems and their solutions of NSUCRYPTO'2020 are presented. We consider problems related to attacks on ciphers and hash functions, protocols, permutations, primality tests, etc. We discuss several open problems on JPEG encoding, Miller -- Rabin primality test, special bases in the vector space, AES-GCM. The problem of a modified Miller -- Rabin primality test was solved during the Olympiad. The problem for finding special bases was partially solved.
Is speech perception what speech perception tests test?

Speech signals employed in clinical and research contexts are thought to be realistic or representative to the extent that they consist of phonetic, lexical, and morphosyntactic content. These characteristics may be assumed to ensure that speech perception tests are representative of the demands of real-world speech perception and understanding, and therefore that these tests are predictive of real-world speech understanding. However, there are numerous reports of discrepancies between the results of speech perception tests and real-world speech understanding and hearing device benefit. To make optimal use of existing speech tests, and to design more predictive speech tests in the future, it is important to consider how clinical and research speech tests do and do not represent the process and demands of everyday speech understanding. Speech and language examples from a single talker engaged in conversation with a hearing-impaired interlocutor in a range of realistic acoustic environments will be contrasted with widely used recordings of BKB sentences produced by the same talker. The absence of much natural variation in standard speech test materials, as well as a failure to quantify perception of information which cannot be captured orthographically, will be discussed as limitations to the generalizability of standard speech test results.
Analytical translation quality assessment

In translation quality assessment, analytical instruments, such as error taxonomies differentiating various error categories, are commonly used. Several studies state that the types of errors made in translation may differ depending on the translation aids used, viz. none (referred to as human translation - HT), machine translation (MT) or translation memories (TMs). An overview is presented of the most frequent error types in these different studies, confirming that different translation aids (or the lack thereof) generate different error types. We analyze whether the most frequent error types from the reviewed studies fit into the pre-established categories from five different error taxonomies, viz. the Canadian Language Quality Measurement System (Sical), the SAE J 2450 quality metric, MeLLANGE, the Multidimensional Quality Metrics (MQM) framework and the Smart Computer-Aided Translation Environment (SCATE) error taxonomy, and also discuss the ATA Framework for Standardized Error Marking. In this way, the completeness of these error taxonomies for translation training and other purposes can be determined. From our review, it transpires that most of the error taxonomies pay great attention to language quality in the target text, in addition to source text to target text transfer, and that this also has great importance for translation training.
A Novel study on Awareness and Preference of College Students towards Educational Based Mobile Application

This research study titled a study on awareness and preference of the college students towards educational based mobile application was to identify the awareness and preferences of students studying colleges in India towards education based mobile apps. The study focused on collecting information on the level of technology used, extent of mobile usage, convenience and preferences of the students in using education based mobile apps. The data was collected using questionnaire the data collected was analyzed using various statistical tools like Percentage Analysis, Factor Analysis, Chi-Square test, and correlation. The research tools aimed to pinpoint the requirement and opinions of the Engineering college students and to suggest inputs about technological requirement similar the prospect of the students.