Reviewerly/exHarmony huggingface dataset:
Development of Wireless Kundt’s Tube Kit as an Experiment Tool in Determining Speed of Sound and Proposing for a Hearing Test

As a part of contextual learning, laboratory activity supports the physics concept attainment. The everyday physics in real-life occur from the concept of sound, by hearing a sound every day. For further application, the sound wave concept needs to be understood by a particular experiment. For gaining that purpose, this study develops Wireless Kundt's Tube kit. The study has two essential purposes: determining sound speed through the kit and examining the kit as an alternative for a hearing test. The study utilized the ADDIE research design: Analyze-Design-Develop-Implement-Evaluate stages. Specifically, the apparatus bravely brands as wireless Kundt's Tube use Bluetooth connection to integrate the smartphone's central apparatus and have easier accessibility to the students' gadget. This final kit has tried to students in 11th grade of a senior public school in East Java, Indonesia, to demonstrate how to gain their feedback. This kit passed the media and content validity as part of learning media development. The study gained a sound speed of 303.03 m/s and proposed the hearing test's idea as replacing the function of turning fork in a traditional test. It means Wireless Kundt's Tube can apply to the following instruction process as the motivational part for physics learning and a hearing test.
Methods and techniques for management of ontolodgy-based knowledge representation models in the context of BIG data

Ontology-based knowledge representation models in the context of big data are one way to reduce complexity for data processing across methods of semantic description. This research paper aims at providing an overview of the methods and techniques for efficient management of the ontology-based models that improve big data systems. For this case, the shapes constraint language (SHACL) for information validation was reviewed as the key method. The knowledge representation systems and reasoners are studied and reviewed in the paper as well. It describes approaches based on ontologies in the context of big data. The proper management of ontology-based knowledge representation models through offered methods and techniques brings improved data integration, big data quality, and business process integration.
Online Health Care System: A Survey

Abstract: Today`s technology offers many online services in almost every field. From those fields Healthcare is one of them. However, in this pandemic it is very difficult to obtain the consultation with the doctor for every health problem so to overcome this problem Online Healthcare System can be implemented. This Web application contains features like manage patient details, doctor`s detail, schedule appointments, view reports, online payment and some additional features like videos for “yoga and exercise” and a “Chatbot”, Which is a type of software that used to redirect the conversation between human beings and users which will help people to provide details according to their quires in an productive way
Deep Dive on Popular Security Models and Strategies of Cloud Computing

Cloud computing has been an ever inspiring paradigm transforming people’s lifestyles and working patterns in recent decades. Due to its dynamic provisioning of IT capabilities, cloud computing emerges as a horizon by serving critical applications. But the unavailability of security standards and models makes cloud computing security more puzzling during the transfer of sensitive information across the cloud. Various models such as the multi-tenancy model, risk accumulation model, cloud cube model, and mapping model are some of the existing security approaches of cloud computing. The multi-tenancy model offers multiple applications running on the cloud, in which virtualization isolates viruses, intrusions, and tampered information. Likewise, the risk accumulation model mitigates the inheritance of security risks from SaaS, PaaS to IaaS by satisfying SLA demands, data protection, and compliance. Cloud cube model facilitates figuration description of security attribute, which consists of four model parameters. Each parameter provides security protection at its corresponding levels encompassing interoperability, data protection, and security boundaries. More significantly, the mapping model includes compliance checks, security controls, and ontologies. Although the security models present a lateral view of cloud data protection, some security issues still need to be addressed. Several cloud security strategies are constructed for mitigating the security risks during the migration of businesses to the cloud ecosystem. For instance, secured access of physical and software entities, assessing virtualization security risks, controlling through outsourcing risks, and interoperability are some of the security strategies at the deployment level. Likewise, some of the operational procedures are providing assurance to the business flow, giving alerts proactively, preventing data leakage, notifying security incidents and response, and auditing the security incidents. Some of the security strategies include protecting the data from overspending or misspending on security controls. During security analytics, advanced automation through artificial intelligence techniques has increasingly been receiving attention in recent decades. Typically, authentication through verification and validation can perform security controls over constrained environments. Blockchain models combined with cloud security provide advanced reliability and scalability. Besides, strong security models and strategies need addressing to combat potential hackers. This chapter aims to enlighten some of the novel security models and approaches in cloud computing.
Interval Methods in Knowledge Representation

Please send your abstracts (or copies of papers that you want to see reviewed here) to vladik@utep.edu, or by regular mail to Vladik Kreinovich, Department of Computer Science, University of Texas at El Paso, El Paso, TX 79968, USA…
Mowa nienawiści w mediach społecznościowych – możliwości automatycznej detekcji i eliminacji

Hate Speech on Social Media – The Possibility of Automatic Detection and Elimination The article deals with the issues of hate speech and other forms of verbal aggression on the Internet as well as the possibility of their automatic detection. The paper discusses the studies confirming the partial effectiveness of text mining methods in the automatic detection of hate speech on social media. Hate speech is related to verbal aggression resulting from belonging to a group (national, racial, religious, etc.) and has become a significant problem in the social and economic context. Automatic detection significantly support the management of online news websites and social media due to the moderation of the received content. Moreover, eliminating online hate speech reduces its negative social and economic effects. The linguistic and cultural specificity of the hate speech are the problem, and the gap so far is solving the problem in Polish conditions. The study used the Tweeter database. Then, methods such as artificial neural networks, naïve Bayes classifier and support vector machine were used. The obtained results confirm the thesis about the possibility of using text mining methods in the process of reducing hate speech, but at the moment the described methods do not allow for full automation of the elimination of such content. The issue was presented in the article primarily in the context of the significance and scale of the problem and the possibility of solving it, and less from the point of view of the technical details.
Conversational Interaction with Historical Figures: What’s It Good For?

Historical records can tell us about the knowledge, opinions, and actions of individuals, but direct use of historical records is a complex process that is better attuned to the needs of scholars than the interests of the general public. This paper explores the potential for conversational interaction with representations of historical figures that are constructed from primary and secondary source materials. An interview study, supported by a computational prototype as a provocation, is used to elicit expert assessments of the potential uses of such systems in historical museums. Qualitative analysis of study results reveals three broad classes of design implications: situating design in archival assurance, creating immersive user experiences, and supporting active inquiries.
Introduction to cognitive psychology

Cognitive psychology made slow progress in the early years due to the growing influence of behaviourism, an approach which constrained psychologists to the investigation of externally observable behaviour. The behaviourist position was clearly stated by Watson, who maintained that psychologists should consider only events that were observable, such as the stimulus presented and any consequent behavioural response to that stimulus. The schema theory proposes that all new perceptual input is analysed by comparing it with items which are already in our memory store, such as shapes and sounds which are familiar from past experience. These stored items are referred to as ‘schemas’, and they include a huge variety of sensory patterns and concepts. Schema and Gestalt theory had a major influence on the development of cognitive psychology, by emphasising the role played by inner mental processes and stored knowledge, rather than considering only stimulus and response.
Effect of Chemical Treatment on Alpaca Fleece Reinforced Polymer Composites

Fiber which is a fortification reinforced additionally manufactured characteristic investigations demonstrate solitary counterfeit strands like glass, carbon and so on., are utilized in fiber supported plastics. despite the fact that have extraordinary explicit quality, their grounds of utilization are self-same constrained inferable from their characteristic more expensive rate of creation. In this association, partner degree examination has been distributed to frame utilization of Alpaca fleece a fiber plentifully available in Bharat. Regular filaments don't appear to be just strong and lightweight however moreover generally the most reduced. Alpaca fleece compounds are created and their mechanical possessions remain assessed. Mechanical properties of Alpaca fleece /polymer and contrasted and glass fiber/amino..
Region-level arabic dialect identification using deep learning models

The automatic classification of the Arabic language dialects is the preliminary step towards establishing many dialectal-sensitive Arabic natural language processing tasks. Arabic dialect identification entails predicting the dialects associated with specific textual inputs and classifying them under their respected labels. In this paper, we propose a novel approach by merging several distinct datasets to obtain a large, diverse, and bias-free dialectal corpus. Our dataset is a collection of parallel sentences translated into multiple dialects (MADAR), as well as tweets gathered from Twitter users (NADI-2020, NADI-2021, QADI, &amp; ARAP-Tweet 2.0). The collected dataset is classified into seven labels: Gulf, Levant, Iraq, Maghreb, Nile Basin, Yemen, and Modern Standard Arabic. The merged dataset was cleansed to produce Arabic sentences free of punctuation, non-Arabic characters, numbers, repeating characters, empty lines, and elongation characters. We obtained a high dialectal classification accuracy using a new Word2vec embedding model on the merged dialectal dataset. Seven deep learning systems were trained on a balanced subset of the dataset. These models are Convolutional Neural Network (CNN), Long Short-Term Memory (LSTM), Gated Recurrent Unit (GRU), Bidirectional-LSTM (BILSTM), Bidirectional-GRU (BIGRU), Convolutional-LSTM (CLSTM), and Convolutional-GRU (CGRU). Single-label classification tests ran on these trained models acquired a minimum accuracy of 77.90% (CNN) and a maximum accuracy of 81.52% (BILSTM). We further evaluated the accuracy of tests ran for short and long sentences with 87.52% attained accuracy for classifying short sentences with CGRU and 94.06% for long sentences using BIGRU, both of which are indications of proposed approach efficacy to move forward.
Binary Tense Structure

Chapter 3 presents an updated version of the tense system of Verkuyl (2008) organized on the basis of the three binary oppositions. The update is needed in view of a number of improvements – substantively and notationally – due to later work. The main ingredient of this chapter is the strict distinction between the notion of present domain and the notion of the fleeting point ??, which has a counterpart in the distinction between past domain and then-fleeting point ??’. The parallelism in a binary tense system is argued to be a dominant force in its organization.
Novel Method of Clone Detection by Neural Networks

Code clone is that type of engine that helps to find duplicate code patterns find within the whole code. Programmers usually adopt code reusability task from previous few years, so that time consumption can be reduces. Code reusability can be done via replication or by just copy-paste. Code reusability leads to not writing code from scratch, just copy paste the useful part of the code. In finding of duplicated code fragment or text, plagiarism detection also work pretty well but it is not applicable to the large system in finding functional clone and also it is more time consuming even at small scale which make the detection method inappropriate. In this paper, we proposed a pattern similarity conditions on the basis of textual similarity for finding the code or text clones in the large content on the basis of SVM, Neural Network using Java coding, Neural Network and Sim Cad. This approach detects code or text clones from original one. The resultant simulation is taken place in the MATLAB environment, and it has shown that it is providing better results. The proposed algorithm performance is measured using parameters i.e. FRR, FAR and Accuracy.
Intake

OpflowVolume 47, Issue 9 p. 2-2 Departments Intake First published: 04 November 2021 https://doi.org/10.1002/opfl.1597Read the full textAboutPDF ToolsRequest permissionExport citationAdd to favoritesTrack citation ShareShare Give accessShare full text accessShare full-text accessPlease review our Terms and Conditions of Use and check box below to share full-text version of article.I have read and accept the Wiley Online Library Terms and Conditions of UseShareable LinkUse the link below to share a full-text version of this article with your friends and colleagues. Learn more.Copy URL Share a linkShare onFacebookTwitterLinked InRedditWechat No abstract is available for this article. Volume47, Issue9November 2021Pages 2-2 RelatedInformation
Sustainable entrepreneurship in education through Science Maps

The promotion of innovation and entrepreneurship is part of the major national and global goals since Agenda 2030 in 193 countries. Additionally, with global warming and the pandemic caused by covid-19, these goals became strategies for global reactivation, prioritizing the environment, social and economic aspects to create resilient and conscious organizations. Educational institutions, for their part, must assume the role of articulating in a multidisciplinary way the requirements of society through their knowledge to achieve generational changes giving solutions to existing problems. This article's main objective is to show the different research fronts related to sustainable entrepreneurship in education and their relationships before and after the pandemic to identify the different areas in which research is being conducted, their interconnections, and their evolution. For this purpose, a bibliometric analysis was carried out through science maps, covering three timeframes: (2006–2014), no relevant data before 2004, (2015-2019) Agenda 2030 was signed, (2020-today) Covid-19 pandemic. The results show profound changes in traditional trends, as well as the emergence of emerging trends.
Enzymes power a greener alternative to concrete

Forged with the help of enzymes, a new alternative to concrete pulls in carbon dioxide instead of releasing it ( Matter 2022, DOI: 10.1016/j.matt.2021.12.020 ). The relatively strong material has self-healing properties and hardens in 24 h—much faster than traditional concrete, which takes nearly a month. Concrete production releases about 9% of global human-made carbon dioxide emissions, according to Nima Rahbar , a materials scientist at Worcester Polytechnic Institute. Making the stuff requires a lot of energy. “In a nutshell, concrete needs to be replaced,” he says. Rahbar and colleagues have created a stand-in for concrete that could be more sustainable. They combine sand and gelatin, chosen for its low cost, and add a solution containing calcium and a small amount of the enzyme carbonic anhydrase. They then heat molded blocks of the mixture at 100 °C for 24 h. While the bricks bake, the gelatin forms a polymer scaffold
Physics-informed neural network model for cell viability and oxygen consumption of pancreatic islets

Machine Learning (ML) and Digital Twins (DT) are at the heart of today’s different industries, ranging from advanced manufacturing to biomedical systems to resilient ecosystems, civil infrastructures, smart cities, and healthcare. They have become indispensable for solving complex problems in science, engineering, and technology development. The purpose of the MMLDT-CSET 2021 conference is to facilitate the transition of ML and DT from fundamental research to mainstream fields and technologies through advanced data science, mechanistic methods, and computational technologies. This 3-day conference features technical tracks of emerging ML-DT fields and applications, special public lectures, short courses, and demonstrations. The conference will be held in a hybrid format, featuring both on-site and virtual sessions.
Retraction: Dual Axis Solar Tracking System using LDR Senors (J. Phys.: Conf. Ser. 1916 012128)

This article (and all articles in the proceedings volume relating to the same conference) has been retracted by IOP Publishing following an extensive investigation in line with the COPE guidelines. This investigation has uncovered evidence of systematic manipulation of the publication process and considerable citation manipulation. IOP Publishing respectfully requests that readers consider all work within this volume potentially unreliable, as the volume has not been through a credible peer review process. IOP Publishing regrets that our usual quality checks did not identify these issues before publication, and have since put additional measures in place to try to prevent these issues from reoccurring. IOP Publishing wishes to credit anonymous whistleblowers and the Problematic Paper Screener [1] for bringing some of the above issues to our attention, prompting us to investigate further. [1] Cabanac G, Labbé C and Magazinov A 2021 arXiv: 2107.06751v1 Retraction published: 23 February 2022
The Effect of Misuse of Information Technology and Student Integrity on Academic Fraud Behavior of Students as Prospective Accountants

The purpose of this study was to determine (1) the effect of misuse of information technology on the academic cheating behavior of accounting students as prospective accountants, (2) the effect of student integrity on the academic cheating behavior of accounting students as prospective accountants and (3) the effect of misuse of information technology and student integrity on academic cheating behavior of accounting students as prospective accountants at Muhammadiyah University of Sidoarjo accounting students. In data analysis using tabulation of data obtained from the distribution of questionnaires, from the total number of questionnaires distributed of 100 copies, only 80 were returned and could be processed. The analytical tool used to help manage the data is SPSS software version 18.0. The analytical test used is in the form of normality, validity, and reliability tests. Hypothesis testing was carried out using data analysis tests, namely partial tests and multiple linear regression. The results obtained based on the normality test stated that all data were normal, the results of the validity test of all items in the questionnaire were declared valid because rcount &gt; rtable, all reliability test results were declared reliable. Based on the results of the t test, it can be stated that the misuse of information technology (X1), student integrity (X2), has an effect on (Y) accounting student fraud.
Means for Quality Implementation and Assurance of Context-Aware Semantic Web Service Composition

Author’s Method for Adaptive Semantic Web Service dynamic composition is enriched with the algorithms for both its Context dedicated OWL-S-specification consistent using over its Life Cycle and Cyclic Dependencies at the function level solving with the Formalisms proposed of Knot-service, Proxy-service and Simplification – for sustain Quality implementing of Web Service being formed. Quality assurance for stakeholders is proposed through dynamic verification, in particular meeting the specified context and liveness, with the process Calculus of Context-aware Ambients. The algorithms proposed increase correspondence of Web Service being formed with Customers’ expectations and enable its sustain context-aware tailoring for unified support of both modern organizations’ variable and distributed Business Processes and some problem field Customers’ needs.
Evaluating the General Claim Process Through Temporal Intuitionistic Fuzzy Pairs

This statement aims to review and evaluate the development of court proceedings in civil disputes or the so-called “general claim process” from the initiation of the case to its conclusion by the court of first instance through the use of temporal intuitionist fuzzy pairs. The obtained results can be defined as expanding the fields of application of the theory of intuitionistic fuzzy sets.
Proof of Convergence of the BPHZ Scheme

We prove in complete generality that the BPHZ scheme assigns a finite value to each Feynman diagram. The proof uses only elementary mathematics, but is magnificently clever.