Reviewerly/exHarmony huggingface dataset:
Influence of COVID-19 on the Lexical Features of English in Pakistan

The study presents a corpus-based analysis of the influence of COVID-19 on the lexical features of English in Pakistan. News on Web Corpus (NOW), managed by English-Corpora.org, formerly known as BYU Corpora, with a specification of English language used in web news of more than 70 websites form Pakistan, was used data analysis. The section of the corpus of English in Pakistan news on the web contains approximately more than one billion words. The usage of 58 keywords, including the top 20 collocated words given by Oxford Dictionary (OED, 2020a), following COVID-19, from 2017 to 2019, was compared to 2020 till June 17, 2020. The analysis shows an exponential rise in the use of some new words and acronyms (e.g., self-quarantine, nCoV, and SARS). Many words that existed previously were used in media discourses to a great extent after COVID-19 (e.g., self-isolation, social-distancing, pandemic, and virus). Moreover, the trends in using such words are different in Pakistan from the trends in the other part of the World. The findings of the study may be used to expand the existing knowledge about language change, viewing coronavirus pandemic (and similar events) on the wheels of technology as another possible socio-psychological factor of language change.
Voice authentication based on the Russian-language dataset, MFCC method and the anomaly detection algorithm

Almost all people's data is stored on their personal devices.There is a need to protect information from unauthorized access.PIN codes, passwords, tokens can be forgotten, lost, transferred, brute-force attacked.For this reason, biometric authentication is gaining in popularity.Biometric data are unchanged for a long time, different for users, and can be measured.This paper explores voice authentication due to the ease of use of this technology, since obtaining voice characteristics of users doesn't require an equipment in addition to the microphone.The method of voice authentication based on an anomaly detection algorithm has been proposed.The software module for text-independent authentication has been implemented on the Python language.It's based on a new Mozilla's open source voice dataset "Common voice".Experimental results confirmed the high accuracy of authentication by the proposed method.
Facial Anthropometric Measurements and Photographs — An Interdisciplinary Study

In recent years, automatic facial analysis has attracted much interest among computer science researchers in the healthcare and computer vision fields studying facial anthropometric measurements using photographs. However, to date, there have been no healthcare or computer vision publications that use standardized photographs to differentiate features between sub-ethnic groups by leveraging the power of machine learning on two-dimensional computer vision benchmark data sets (2D CVBDs). Thus, the present work is an interdisciplinary study at the interface of healthcare and computer vision fields that attempts to fill this literature gap where we explore the use of machine learning on 2,789 photographs from eleven 2D CVBDs to identify k top discriminative features in major and sub-ethnic groups. These features are ranked based on information gain values and p-values. We also provide a comprehensive analysis of using information-gain-based and p-value-based features. Our machine learning model achieves an accuracy of 96-99%, and our findings reveal that information-gain-based features have the upper hand over p-value-based features. The top three information-gain-based features in sub-ethnic groups are: dn (distance from the tip of the nose to the center of the mouth), hf (face height) and wn (nose width), while the top three information-gain-based features in major ethnic groups are: de (distance between the inner corners of the eyelids), hf and dn. These results are then compared to the results obtained using standard deep learning techniques such as OxfordNet (VGG16), Residual Networks (ResNet50), and Inception-V3, where accuracy of 90-94% was seen. We hope that these findings will lead to future collaboration between computer vision and healthcare researchers studying facial anthropometric measurement studies.
Psychological and pedagogical study of the problems of families raising children with disabilities

The article is devoted to the issues of psychological and pedagogical study of the problems of families raising children with disabilities.The article presents the results of an experimental study of parental attitudes towards a child, behavioral attitudes, characteristics of perception and understanding of the character and personality of a child, his actions.
Anomaly Detection in Discrete Manufacturing Systems by Pattern Relation Table Approaches

Anomaly detection for discrete manufacturing systems is important in intelligent manufacturing. In this paper, we address the problem of anomaly detection for the discrete manufacturing systems with complicated processes, including parallel processes, loop processes, and/or parallel with nested loop sub-processes. Such systems can generate a series of discrete event data during normal operations. Existing methods that deal with the discrete sequence data may not be efficient for the discrete manufacturing systems or methods that are dealing with manufacturing systems only focus on some specific systems. In this paper, we take the middle way and seek to propose an efficient algorithm by applying only the system structure information. Motivated by the system structure information that the loop processes may result in repeated events, we propose two algorithms—centralized pattern relation table algorithm and parallel pattern relation table algorithm—to build one or multiple relation tables between loop pattern elements and individual events. The effectiveness of the proposed algorithms is tested by two artificial data sets that are generated by Timed Petri Nets. The experimental results show that the proposed algorithms can achieve higher AUC and F1-score, even with smaller sized data set compared to the other algorithms and that the parallel algorithm achieves the highest performance with the smallest data set.
Towards Extending UML's Activity Diagram for the Architectural Modeling, Analysis, and Implementation

SAWUML is a general-purpose software modeling language that extends UML by unifying component and sequence diagrams for the specifications of software architectures.While component diagram is used for modeling the system structures, sequence diagram is extended with the Design-by-Contract approach for the modeling of system behaviors.In this paper, we aim at enhancing the language usability by providing alternative modeling choices for practitioners.To this end, we extended SAWUML's notation set with UML's activity diagram for the behavior modeling.So, practitioners may now use either sequence or activity diagrams, while the system structures are still modeled with component diagrams.We also extended SAWUML's modeling editor for creating software architecture models together with component and activity diagrams and the code generators for automatically obtaining (i) formal models in SPIN's ProMeLa for formal verification and (ii) Java-based implementation.We illustrate our language extension with the gas station case-study.
A Stackleberg Game Theory and Improved Fuzzy Based Intrusion Detection Approach for Virtual Machine Migration Timing Problem in Cloud Computing

Current computing concepts are migrated to a an emerging technology called cloud computing.Self-adaptive resource allocation framework and intelligent machine learning framework are proposed in various research work for providing optimized resource allocation.Privacy and security are the major concerns which restricts it's adoption to clouds.Outsourcing, resource sharing and multi-tenancy are introduced by cloud to overcome security concerns.Stackelberg Game Theory Framework (SGTF) is used in proposed security model for enhancing data's confidentiality level and over cloud environment.For multiple correlated VMs (migration requests), migration problem is studied in this work and for solving the same, an Enhanced Artificial Neural Network (EANN) and IDS based on fuzzy is introduced.In this method, migration request is included with correlations between VMs and these correlated VMs are treated integrally rather than separate treatment
A Gaze-Contingent System for Foveated Multiresolution Visualization of Vector and Volumetric Data

Computational complexity is a limiting factor for visualizing large-scale scientific data. Most approaches to render large datasets are focused on novel algorithms that leverage cutting-edge graphics hardware to provide users with an interactive experience. In this paper, we alternatively demonstrate foveated imaging which allows interactive exploration using low-cost hardware by tracking the gaze of a participant to drive the rendering quality of an image. Foveated imaging exploits the fact that the spatial resolution of the human visual system decreases dramatically away from the central point of gaze, allowing computational resources to be reserved for areas of importance. We demonstrate this approach using face tracking to identify the gaze point of the participant for both vector and volumetric datasets and evaluate our results by comparing against traditional techniques. In our evaluation, we found a significant increase in computational performance using our foveated imaging approach while maintaining high image quality in regions of visual attention.
Advanced surgical navigation system using augmented reality technology

Background: Most current plate-type surgical navigation systems have the following problems: 1) The mouth opening at the operating area must be larger than the thickness of the plate and the length of the drill. 2) Irrigation with cool water is obstructed by the surgical plate, increasing the likelihood of bone burns. 3) In free end cases, the stability of the surgical plate is poor due to one-sided support. 4) In implant cases involving flap surgery, it is hard to use the surgical plate. Aim/Hypothesis: To solve these problems presented at the Background, we have developed an advanced surgical navigation system that indicates the 3D position of simulated implants in the patient's oral cavity using AR technology. Materials and Methods: The hardware components of our system are a web camera, a computer and a monitor. We use AR software and our original simulation software. The methods for using our system are as follows: 1) Make a 3D model of the patient from the CT data by volume-rendering. 2) Create a virtual mouthpiece in the AR space based on the shape of that 3D model. 3) Fit the virtual mouthpiece with the 3D model and place the 3D objects indicating the 3D position of simulated implants on the virtual mouthpiece. Then the 3D objects in the AR space move with the virtual mouthpiece. 4) Fit the virtual mouthpiece with the camera image of the patient's mouth and display the 3D objects in the oral cavity. Then the 3D objects displayed in the oral cavity work as surgical guides of drilling. Results: We tested our system on the patient's stone model and we carried out a drilling simulation on the training typodont. We also examined our system in the staff's mouth to make sure if it works in the actual oral cavity. Then we got the next Results 1) The 3D objects indicating the 3D position of simulated implants were displayed on the stone model with good stability and accuracy. 2) The 3D objects on the stone model can move in conjunction with the operation on the simulation software. 3) When there are alveolar bone or teeth together with the 3D objects, we can hide the overlapping areas. 4) The drilling simulation on the training typodont showed a good performance of our system. 5) The 3D objects were displayed in the staff's mouth proving that our system works in the actual oral cavity same as on the stone model. Conclusions and Clinical Implications: Our system has the following advantages compared with plate-type surgical navigation systems: 1) As our system has nothing to interfere with the operation in the oral cavity, all problems presented at the Background are solved. 2) Our system needs neither cost nor time for making the surgical plate. 3) At the planning stage, we can examine the 3D position of simulated implants from both anatomical and prosthodontic points of view simultaneously. Keywords: surgical navigation, surgical guide, AR technology, navigation system, guided surgery
COOPERATIVE LEARNING ON EFL PROFICIENCY; THE BEST PRACTICE AT ISLAMIC HIGH SCHOOL STUDENTS

The study was aimed at finding out the effectiveness of cooperative language learning on students' English proficiency as measured by their abilities in grammar, reading comprehension, vocabulary, and listening comprehension. The study also sought to measure students’ attitudes towards cooperative learning and motivation to learn English. This study was a comparative research design in the form of a non-equivalent control group design. The experiment lasted for twelve weeks in which two intact groups from two Class of MAN 2 Lombok Tengah were chosen as the study groups. Subjects of this study consist of 44 students who attended classes. The control group includes 53 students. This study tested the effectiveness to examine the method; two quantitative tools for data collection were used to compile the findings of the study. For starters, a pre- and post-test were administered to measure English proficiency before and after the treatment. Afterward, a questionnaire was set to measure students’ attitudes towards cooperative learning and motivation to study English in a new high school system. After analyzing the data, the results indicated that cooperative learning in the new system positively affect some aspects of the participants’ English proficiency and they had a positive attitude towards cooperative learning in the new system and a higher motivation to learn English.
Student Learning Assessment from a Virtual Field Trip

Teaching through field trips has been very effective as students learn more when they see the objects in reality. However, it is not always feasible to take a large class to field trips due to time, safety, and cost limitations. Creating 3D Virtual Reality (VR) models and immersing students in that virtual world could provide an engaging and meaningful experience to both building science and architecture students. The aim of this research was to see if Virtual Field Trips (VFTs) can replace actual field trips in times of need. For that reason, an app was created teaching students about steel connections called the Steel Sculpture App (SSA). The SSA served as VFT and the location of physical steel sculpture model served as the actual field trip. This paper focuses on student learning assessment and experience from of VFT versus the actual field trip. Scope of this study is limited to 3rd year building science and architecture students who have attained basic knowledge of structural systems. The author used controlled group and experimental group method to analyze the learning assessment. The results indicated that the students learning from VFTs scored slightly higher than those learning from actual field trip. Although, students liked learning through the actual field trip but the VFT group was able to score better because they learnt without any distractions.
Intuitionistic Fuzzy Hamiltonian Cycle by Index Matrices

In this paper, the algorithm for finding a Hamiltonian cycle in an intuitionistic fuzzy graph (IFG) is proposed, based on the theories of intuitionistic fuzzy sets (IFSs) and of index matrices (IMs).The aim of the paper is to extend the algorithm to find a fuzzy Hamiltonian cycle (FHC) in an IFG to the intuitionistic fuzzy (IFHC) using the IFSs and IMs concepts.An intuitionistic fuzzy graph example about network of Wizz air airlines is modeled by the extended IM to illustrate the proposed algorithm.In the paper also are introduced for the first time three index-type operations over IMs.
TEACHING OF ELECTROMAGNETISM WITH NDT (novel data technologies)

The importance to the affective domain in learning is underscored in many research pursuits at the expense of the cognitive development of students studying science, in particular, physics. The thesis has proposed a structure, the pedagogical technological combined medium (PTCM) founded on the electronic model, that builds on the existing premises of pedagogy, content, and technology to make space for the affective domain where these three premises intersect with each other. Establishment of the PTCM framework through a multi-loop model that explores the affective dimension as an overarching space for interaction among learners, teachers, and parents through a series of stages included home tasks, as well as seminar and out-of-university activities. The paper is wanted to show the effectiveness of the methods and techniques of teaching «Electromagnetism». The context provides the results of new technological education teaching, samples the needed literature, and also to bond strengthen the scientific research. Key words: education, teaching, modern education technology, electromagnetism.
Towards a Complete Pipeline for Segmenting Nuclei in Feulgen-Stained Images

Cervical cancer is the second most common cancer type in womenaround the world. In some countries, due to non-existent or inadequatescreening, it is often detected at late stages, making standardtreatment options often absent or unaffordable. It is a deadlydisease that could benefit from early detection approaches. It isusually done by cytological exams which consist of visually inspectingthe nuclei searching for morphological alteration. Since itis done by humans, naturally, some subjectivity is introduced. Computationalmethods could be used to reduce this, where the firststage of the process would be the nuclei segmentation. In this context,we present a complete pipeline for the segmentation of nucleiin Feulgen-stained images using Convolutional Neural Networks.Here we show the entire process of segmentation, since the collectionof the samples, passing through pre-processing, training thenetwork, post-processing and results evaluation. We achieved anoverall IoU of 0.78, showing the affordability of the approach of nucleisegmentation on Feulgen-stained images. The code is availablein: https://github.com/luizbuschetto/feulgen_nuclei_segmentation
Actions of a Brazilian public telehealth service to help coping with the new coronavirus

Abstract Background In January/2020 the respiratory disease caused by the new coronavirus was declared as an international public health emergency. In Brazil, until June 22nd there were 1,11 million confirmed cases. In this context, the Telehealth Network of Minas Gerais (TNMG), a large-scale public telehealth service, acted quickly to assist professionals and the population in coping with the disease, mainly in low resource settings. Aim To report the experience of a Brazilian public telehealth service in actions to manage COVID-19 and its impacts. Methods Experience report. Results The TNMG developed 15 infographics and 16 web lectures for health professionals and general population about key themes, such as respiratory syndromes, personal care and ventilatory support. Two of them were live, seen in real time by 13,422 professionals, mainly nurses (63.8%) and doctors (31.1%), from 45 medical specialties (most family physicians-34.0%), in all Brazilian states, especially the Southeast region (58.5%). All lectures were uploaded on TNMG's Youtube channel, each one reaching 5,300 viewers on average. Specific to support health professionals: 2 guidelines were developed - one for primary care units and other to emergency/intensive care; a category for offline (second opinion) teleconsultations was created for doubts about coronavirus; and a list with 39 Frequently Asked Questions (FAQs) was developed. For the general population: 65 FAQs were developed; a health team from a low resource setting was trained to provide online teleconsultations; and a chatbot was released to automatically answer COVID-19 related doubts and/or evaluate a user's health condition, indicating if emergency medical care was needed. All resources are freely available on TNMG's website and on its social networks. Conclusions Telehealth tools had a notable acceptance and were shown to be an effective way to disseminate information for professionals and lay population throughout the country. Key messages Telehealth tools have been proven to be an effective strategy to promote health education, for both professionals and the general population. Telemedicine plays a fundamental role on dealing with public health issues, especially on low resource settings.
The soundscape of Anthropocene

Recently, much attention has been paid to the many different forms of collaborative or participatory practice both within, and out with the academy; from practice-based research to theoretical contributions and artistic experimentations. In terms of acoustemology as described by Steven Feld, the creative processes of collaborative soundscaping practices, developed as dialogic editing, produce theories of sound as knowledge production. Within this trend of doing anthropology in sound, sound art works aim to reconnect communities to the environment and indicate the emergence and presence of an ecological and aesthetic co-evolution. Such projects, in fostering interdisciplinary approaches, allow the development of hybrid types of knowledge through dialogic exchanges, and engage multiple agents by developing audile techniques. They also raise interesting questions within collaborative and interdisciplinary creative practice, in relation to the critical examination of the instrumentality of collaboration. By focusing on field recordings and soundscape compositions this paper discusses ecological sound art works that use collaborative creativity, new technologies, and phenomenological listening, to produce dialogic and collaborative forms of epistemic and material equity. These sound art works are the result of complex expressions of creative processes that involve multiple agents, while successfully voice their authorial presence. The interdisciplinary, collaborative and open-ended nature of these projects brings forward the social and political dimension of sound and listening, which could figure in more collaborative forms of knowledge production and inspire climate action.
Secured AODV to Protect WSN Against Malicious Intrusion

One of the security issues in Wireless Sensor Networks (WSN) is intrusion detection. In this paper, wepropose a new defence mechanism based on the Ad hoc On-Demand Vector (AODV) routing protocol.AODV is a reactive protocol designed for ad hoc networks and has excellent flexibility to be adapted to a new secure version.The main objective of the proposed secured AODV routing protocol is to protect WSN against malicious intrusion and defend against adversary attacks.This secured AODV protocol works well with the WSN dynamics and topology changes due to limited available resources.It establishes secure multi-hop routing between sensor nodes with high confidence, integrity, and availability.The secured AODV utilizes an existing intrusion dataset that facilitates new collection from all the exchanged packets in the network.The protocol monitors end to end delay and avoid any additional overhead over message transfer between sensor nodes.The experimental results showed that this secured AODV could be used to fight against malicious attacks such as black hole attacks and avoid caused large transmission delays.