Reviewerly/exHarmony huggingface dataset:
A STUDY THE TECHNIQUES OF ASSESSING THE QUALITY OF SOFTWARE PRODUCTS

In order to improve the scientific and methodological base of data and measurement systems of testing laboratories within the stage of software products certification, the article suggests an integrated approach to assessing the quality of software.The approach includes structural analysis of information and measurement tasks, implementation of ISO standards when developing information features models and creating databases as well as formalized representation of the vector of features of quality in the course of software testing, based on comparison of current measurements with specified requirements of standards (images).A cognitive model of software product quality was obtained on the basis of the analysis of fuzzy cognitive maps and weakly structured scenarios of interaction between external and internal factors affecting the formation of quality properties of software products.The results of modeling are presented and conclusions are formulated.
Video Activity Recognition Based on Objects Detection Using Recurrent Neural Networks

Recognition of human actions in videos is a challenging task, which has received a significant amount of attention in the research community. We introduce an end-to-end multitask model that jointly learns object-action relationships. We compare it with different training objectives, validate its effectiveness for detecting objects-actions in videos, First we fine-tune a Resnet model to detect objects in videos, second a Neural Network model is used for sequence learning to get the object-action correlation. Finally, we apply our multitask architecture to detect visual relationships between objects to recognize activities in videos of the MSR Daily Activity Dataset.
Adapting a university subject to online learning in times of COVID-19: a chance to improve

COVID-19 has been an opportunity to improve the teaching of Social Responsibility at the UFV. The pandemic has increased the urgency of trustworthy mass media and that is something to be taught at University. Training in values such as ethics and social justice for journalism students can also be done through online service-learning. We proceed to make a description of the subject, as well as its curricular adaptation using new resources due to confinement. We carry out a qualitative analysis, applying Atlas.ti on the material produced by the students, to show how they have become agents of social change. The main consequence is the significant increase in the degree of social responsibility of the university student during the pandemic through different forms of communication from the usual ones. The pandemic has provided an opportunity to rethink the subject and has enriched the experience of the university student in the search for collaborative solutions and help, reinforcing their social commitment to the common good through on line learning. © 2021 Universidad de Murcia. All rights reserved.
Non-NAT Definite Diagnosis Models of COVID-19 Based on Hematological Features

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Media space as an element of the digital educational ecosystem

In response to the challenge of informatization of social processes, an information space and a digital educational environment emerge and develop in the field of professional education. Purpose of the article: analysis of the digital educational ecosystem of professional educational institutions. Methodology. The study analyzes the electronic elements used in the modern digital educational ecosystem. Competencies identified by cluster analysis of competency models are presented. Findings. The media space as an electronic environment created by technical means of communication is one of the key elements of the digital educational ecosystem, which allows creating innovative conditions for the development of vocational education
Reimagining Educational Experiences via Artificial Intelligence and New Technologies

Recent technological advances allow greater worldwide access to educational resources - but more critically, they allow the re-envisioning of educational experiences. Progressive, active educational methods such as learning by doing have long been effective and engaging but have been difficult to implement for large audiences. New technologies allow the creation of effective, enjoyable and individualized learning experiences that better prepare students for their future personal and work lives and create a new culture of lifelong learning - and can be potentially available to anyone, worldwide. This chapter provides examples of new, imaginative educational experiences that take advantage of technological advances, and it walks through theories and principles from the fields of education, computer science and cognitive science that can aid in the design and creation of innovative learning experiences. It describes ways in which new technologies such as virtual reality (VR), augmented reality (AR), holograms, artificial intelligence, the Internet of Things (IoT) and other new and emerging technologies, can be used to reimagine education on a large scale.
Designing and Engineering Interactive Computing Systems

This issue of the Proceedings of the ACM on Human-Computer Interaction features contributions in the intersection of human-computer interaction and software engineering, with further disciplines blending into a rich set of scientific works. 2021 is the first time the annual conference on Engineering Interactive Computing Systems (EICS) is hosted in the Netherlands and in the context of an Industrial Design department. We take this opportunity to focus on the relations and influence of the design discipline on the work of the EICS community. This resulted in a new set of topics for EICS, which were already partly reflected in the many submissions we received in three extensive review rounds throughout 2020 and the beginning of 2021. In this editorial we offer a perspective on what EICS is not yet, looking at the inclusion of and interplay with design as a related discipline.
Features of high-precision measurements of laser beam lateral displacements in hybrid 3D scanning fiber-optic measuring heads

Abstract The article discusses the features of using a feedback sensor based on an acousto-optical (AO) laser measuring system (LMS) for high-precision control of transverse displacements of the laser beam in hybrid 3D scanning adaptive fiber-optic measuring heads. Scanning circular movements of a laser beam with a frequency of 1, 5, 10 kHz, formed by a miniature fiber-optic piezoscanner, are considered. Two working sections are created from the circular trajectory formed by a moving laser beam, which are its orthogonal projections, and the current position of the optical spot of each of them is measured in AO LMS. The frequency and accuracy parameters of the AO LMS for traveling ultrasonic waves excited in the AO modulator used as a measure (ruler) are analyzed. The dependences on the length of the ultrasonic waves of the Doppler frequency range, the signal-to-noise ratio of the photodetector, the phase error and the error of transverse displacements, the number of distinguishable angular deviations within 180°, and the spatial resolution are determined and analyzed.
Optimization Of Time-Driven Scheduling Technique For Serverless Cloud Computing

Serverless Computing has become more common by providing lower costs, better elasticity and enhanced usability. Taken as a consequence that resource restrained infrastructure requires efficient low-latent calculations, it also becomes a common execution model for edge computing. However, the cloud mitigation of hyper scale in the cold start server is not scaled to small 10-100kW edge sites, resulting in weak threshold latencies for edge deployments of existing VMs and containers. This is particularly acute since latency requirements are expected to range from micro seconds to seconds in future edge computing workloads. SledgeEDF is the first time that the serverless execution paradigm applies conventional real- time admittance management systems and time-driven scheduling techniques.
Investigating the Effects of Information Security Awareness in the Third Sector

Information security awareness (ISA) focuses on the user’s responsibility and understanding of risk, to ensure that acceptable working practices are adopted under these broad principles, thereby re ...
TURN-TAKING STRATEGIES IN OPRAH WINFREY SHOW WITH MICHELLE OBAMA

Turn-taking strategies are the strategy for taking the turn in the conversation, such as interviews, debates, meetings, discussions, or any conversation model. Turn-taking is a condition in which the speakers involved in conversation take the turn to speak. When people have a conversation, they should understand the strategy or how they manage the conversation technique. This study attempted to determine the turn taking strategies used in the interview between Oprah Winfrey and Michelle Obama as the object of this study. Three problems arise in this study that involved the types of turn-taking strategies, the context, and the success of using turn-taking strategies in an interview between Oprah Winfrey and Michelle Obama. In conducting the analysis, a descriptive qualitative method used taanalyze the data in the form of utterances in the conversation. The data of this analysis shows the types of turn-taking strategies used in interviews consist of overlap, interruption, and backchannel signal using by both participants. The researcher also found the context and how successful of using turn-taking strategies based on the response given by interlocutors.  Keywords: Turn-taking strategies, context, interview
The interplay between morphological typology and script on a novel multi-layer Algerian dialect corpus

Recent years have seen a rise in interest for cross-lingual transfer betweenlanguages with similar typology, and between languages of various scripts.However, the interplay between morphological typology and difference in scripton cross-lingual transfer is a less studied problem. We explore this interplayon cross-lingual transfer for two supervised tasks, namely part-of-speechtagging and sentiment analysis. We introduce a newly annotated corpus ofAlgerian user-generated comments comprising parallel annotations of Algerianwritten in Latin, Arabic, and code-switched scripts, as well as annotations forsentiment and topic categories. We perform baseline experiments by fine-tuningmulti-lingual language models. We further explore the effect of script vs.morphological typology in cross-lingual transfer by fine-tuning multi-lingualmodels on languages which are a) morphologically distinct, but use the samescript, b) morphologically similar, but use a distinct script, or c) aremorphologically similar and use the same script. We find there is a delicaterelationship between script and typology for part-of-speech, while sentimentanalysis is less sensitive.
EvoGAN: an evolutionary GAN for face aging and rejuvenation.

In biology, evolution is the gradual change in the characteristics of a species over several generations. It has two properties: 1) The change is gradual, and 2) long-term changes are relied on short-term changes. Face aging/rejuvenation, which renders younger or elder facial images, follows the principles of evolution. Inspired by this, we propose an Evolutionary GANs (EvoGAN) for face aging/rejuvenation by making each age transformation smooth and decomposing a long-term transformation into several short-terms. Specifically, since short-term facial changes are gradual and relatively easy to render, we first divide the ages into several groups (i.e., chronologically from child, adult to elder). Then, for each pair of adjacent groups, we design two age transforms for face aging and rejuvenation, which are supposed to preserve personal identify information and predict age-specific characteristics. Compared with the mainstream for face aging/rejuvenation, i.e., conditional GANs based methods utilizing one-hot age vector as an age transformation condition, our smooth EvoGAN abandons this condition and can better predict age-specific factors (e.g., the drastic shape and appearance change from an adult to a child). To evaluate our EvoGAN, we construct a challenging dataset FFHQ_Age. Extensive experiments conducted on the dataset demonstrate that our model is able to generate significantly better results than the state-of-the-art methods qualitatively and quantitatively.
Random Forest Classification-Based Video Event Detection Utilizing Hand Crafted Features

Huge amount of user-generated video content is shared and downloaded by millions of users across the globe, every minute. The sudden raise of this web content made event detection in videos a major demanding field of research in recent days. Detecting events automatically in large user-generated video datasets (UGV) is a challenging task because of its poor quality and un structured content. In this work, random forest classifier is used to detect events in UCF 101 dataset by utilizing handcrafted features like HOG and Tamura. The performance is measured in terms of accuracy, specificity, sensitivity, false discovery rate, false omission rate, and error rate.
Automatic Edge Correction for Nodule Cancer Segmentation using Fast Scanning Algorithm

Nodule detection is one of the goals in the field of medical imaging. The problem that often occurs from the detectionof nodules in medical images such as mammographic image is the result of improper segmentation, which results inlow segmentation accuracy. The low accuracy of segmentation can affect the area and shape of nodules. These twofeatures can be used for the classification of the cancer stage. Therefore, a method that can be used to improvesegmentation accuracy is proposed, namely edge correction. The initial edge nodules are obtained using a quantumcanny enhancement method. Edge correction is done adaptively by looking at the pixel values around the edge pixelsso that the actual edge pixels are obtained. Edge correction can also connect broken edges by looking at the edgepattern and direction. The results of this proposed method increase the average segmentation accuracy from 87%,which is the result of segmentation without using edge correction, to 95.1%. Accuracy is assessed using the Jaccardsimilarity method.
Multi-Level Thresholding for Image Segmentation on Medical Images Using Multi Otsu and Sine Cosine Optimization Algorithm

Image thresholding is deciding stage in many image processing algorithms. It helps to segment the image, which results in successful prediction correctly. The Sine Cosine is a meta heuristic optimization algorithm that outperforms many conventional algorithms because of its unique principle. Since lung cancer is the most deadly illness, creating a significant number of deaths worldwide, this research used lung cancer CT images. On lung cancer Computed Tomography (CT) images, this paper illustrates how to use the Otsu multi thresholding objective function and Sine Cosine nature-inspired optimization algorithms. The proposed approach uses the Otsu multi thresholding technique on a CT image as an objective function in the Sine Cosine algorithm (SCA).  It aids in selecting elite solutions by measuring fitness for a given range of candidate solutions. When the Algorithm's output was evaluated using PSNR and SSIM, as well as calculation time, it was observed that the proposed approach performed higher.
A Model for Processing Arabic Text on Twitter

This paper proposes a model that can be used as a framework for preprocessing Arabic text on Twitter for data analysis and information extraction. The model provides an online collection of Arabic text on Twitter and stores it in a structured database. The source data are then preprocessed to derive clean, meaningful Arabic text from which information can be extracted. The paper presents new methods and algorithms for preprocessing unstructured Arabic text on social media, and it provides solutions that address the difficulties of working with Arabic text on social media, including uncleaned, informal, and dialect language. The preprocessed Arabic text is stored in structured database tables to provide a useful data set to which information selection and data analysis algorithms can be applied. The implementation of the model yields a useful and full-featured dataset, and the text is presented as the source data, the cleaned data and separate Arabic words with their stems, roots and morphologies, among other forms. In addition, the model shows how information can be selected and extracted from this dataset.
An Analysis of First Language Interference on Students’ Speaking of English as Foreign Language at Man 4 Mandailing Natal

This research was aimed to find out the types of interference, how first languageinterference in speaking English, and why the first language interference in speakingEnglish at second-grade students MAN 4 Mandailing Natal. This research discussesinterference. The researcher discussed first language interference in speaking Englishat the second-grade students at MAN 4 Mandailing Natal. It is one of thebilingualism aspects that occurs when someone is learning in English. In this case,the interference of the first language into English. The first language of the studentsis Mandailing language. It is chosen because the students sometimes use their firstlanguage that often contains an error when they are speaking English. The researcherfocused on speaking English in the classroom discussion. The researcher used aqualitative method. Data were collected from observation and interview. Theresearcher selected some sentences included interference by using Weinreich theoryand analyze them. As a result of the research, the research found that most of thestudents do the interference in words pronunciation, they didn’t know how tomention the correct vocabulary in English, then in grammatical patterns and the lastvocabulary use that they applied their first language when the students don’t get theappropriate word to express their mind. So, the researcher concludes that there arethree types of interference, phonological interference, grammatical interference, andlexical interference. Interference occurred when students speak English. There aremany errors due to first language interference that influence the English language. Inother words, their language interfered with their first language, namely Mandailinglanguage and those caused by the students who didn’t master English well
Semi Supervised Multi Text Classifications for Telugu Documents

As the amount of information available on the internet grows at a rapid pace, text classification becomes critical. This data is in an unstructured state and will need to be digitized. Due to the digital nature of these documents, data must be organized by automatically assigning a collection of documents to predefined labels based on their content. To mitigate the growing impact of news text classification, keyword detection approaches based on mostly supervised classification methods have been proposed. However, in practice, the given data is largely unlabeled, necessitating the use of semi-supervised learning techniques instead. We examine the effectiveness of a semi-supervised method for Telugu news articles in this paper. It also addresses some of the most pressing issues in automated text classification, including dealing with unstructured text, handling large numbers of attributes using natural language processing techniques, and dealing with missing metadata due to Telugu's morphological complexity. After classification, semi-supervised clustering is used to classify patterns. Unlabeled texts are used to adapt the centroids, while unlabeled texts are used to capture text cluster silhouette coefficients. To that end, the aim of this study is to use semi-supervised learning methods to investigate the effect of n-gram feature selection on news article text classification. Statistical results classification rate, precision, recall and F-score for news articles are  validated. The results show that the approaches significantly improve the performance.
Mutual authentication and data security in IOT using hybrid mac id and elliptical curve cryptography

Internet of Things (IoT) is a new emergent technology of the Internet. The Internet that we use today runs with human interposing. The Internet of Things which is the extended version of the internet which aims to offer the machine to machine communication or the device may be referred to as objects we call it object to object communication, which is without the involvement of the humans. With the growth of IOT in the market there are many considerable subjects relating to privacy, authentication, data confidentiality, data protection and other problems where solutions to these issues to be derived. This paper works on providing Mutual authentication and data security. A light weight Approach has been employed by generating Hybrid MAC ID for mutual authentication and using Elliptical Curve for secure data transfer which provides authentication and data confidentiality in the IoT Network.
OPTIMALISASI PERAWATAN TALI-TALI TAMBAT DI KM.KELIMUTU

Indonesia is a country known as a maritime country whose territory is largely waters and consists of islands. Therefore, sea transportation is very important to connect the islands spread throughout Indonesia. One means of sea transportation is sea transport in the form of a ship. A shipping company operates its ships from one port to another, so the shipping company must take care of the vessel operated at the port at which it stops. Activities take care of all ship needs starting from the beginning of the arrival of the ship, while at the port until the time of departure. The purpose of observations made by the author is to know the optimization of maintenance of mooring ropes on KM. KELIMUTU ships. The research methodology used by the author in this observation is in the form of books, internet, laws, ministerial regulations, and other sources. The type of observation used by the author is descriptive qualitative. This observation takes place at PT. PELNI Semarang Branch. Source of data obtained from informants, events or activities, documents and archives. The results obtained from observations that the author made was the optimization of mooring rope treatment in KM.KELIMUTU PT. PELNI Semarang branch at the port of Tanjung Emas Semarang. Broadly spaking, the systems and procedures for operating the ropes on a passenger ship begin before the ship docked to dock, when the ship arrives from preparation to implementation, before the ship departs from preparation to implementation, the ropes needed when handling arrivals and ship departure and related institutions during activities at the port.Keyword : Optimization, maintenance of mooring ropes.