Reviewerly/exHarmony huggingface dataset:
Wind Power and Mind Genomics Cartography: Accelerating Our Understanding of a Topic through a Templated Analysis System

We introduce a novel approach to understand how people feel about new technologies, doing so in a short, easy-to-implement experiment.The objective is to understand public sentiment regarding current problems and current solutions to problems.The approach measures both the emotional appeal and the rational appeal of a situation and solutions, using a newly emerging science, Mind Genomics.Respondents evaluate combinations of messages (vignettes) about problems and technological solutions to these problems, rating the vignettes on a scale which intertwines emotional appeal (believe) with economic appraisal (invest).The analysis of the data sheds light on how a person feels about different aspects of the topic, without the person being able to 'game the system.'The approach contributes both to consumer research and to behavioral economics.
Self-supervised degraded document image binarization method based on second-order central moments and multi-scale network

In this work, we propose an effective self-supervised method for document image binarization. The proposed method is based on image second-order central moment and multi-scale convolution neural network (CNN). It effectively binarizes document images by addressing degradation issues (such as uneven illumination, ink stain, and fading). We first remove noticeable noise and performs data normalization in preprocessing step. Then the pseudo binarization image is generated by the second-order central moment algorithm. Then a multi-scale self-supervised network is utilized to distinguish the foreground (character) from the degraded image (background). We combine traditional image processing and selfsupervised networks to ensure the efficiency and effectiveness of the method while improving the generalization ability on multiple data sets. Extensive experiments show that the proposed model performs best in DIBCO benchmarks.
Biotechnology Risk Assessment Research Grants Program (USDA)

Federal Grants & ContractsVolume 46, Issue 2 p. 7-8 Grants alerts Biotechnology Risk Assessment Research Grants Program (USDA) First published: 11 December 2021 https://doi.org/10.1002/fgc.32124Read 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. Volume46, Issue216 December 2021Pages 7-8 RelatedInformation
Evaluating the Performances of ROC Curve Estimation Methods for Different Distributions and Different Kernel Functions

Objective: Receiver operating characteristic (ROC) curve is a statistical method used to examine the actual effectiveness of a diagnostic test or a biomarker in a comprehensive and reliable way. Several methods have been proposed to estimate ROC curve properly. The aim of the present study is to compare recent ROC curve estimation methods for different distribution and sample sizes. Material and Methods: Log-concave density and smooth log-concave density estimate based ROC curve estimation, kernel based ROC curve estimation with Gaussian, Epanechnikov, rectangular, triangular kernels, and binormal ROC estimation methods were compared for different simulation scenarios. Results: The ROC curve estimation methods based on kernel estimates gave their best performances when the biomarker values of non-diseased group are normal but the biomarker values of the diseased group are right-skewed, with a notable difference from other methods. Epanechnikov and rectangular kernel methods yielded better performance than other kernel methods in small sample sizes; but this difference disappeared as the sample size increased. The methods based on kernel or log-concave density estimate gave their worst results for the simulation scenario where the data were nonnormal but symmetric. Conclusion: The performances of the other methods examined in the study exceeded the performance of the binormal method in highly skewed data in both groups and when the distribution of diseased and non-diseased populations were right-skewed and normal, respectively.
Quantum Repeater Networks

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Improvement of the Pedagogical Staff Management in Vocational and Technical Institutions in the Course of Employment

The article discusses the main issues related to the study of important aspects of management of pedagogical staff in vocational and technical institutions in the process of labour activity. The tasks, principles, organizational forms, content, directions and the mechanism of control teaching staff in the new socio-economic conditions of functioning of vocational and technical institutions are lighted on the basis of the detailed analysis of literary sources by the author and the main concepts of the identified problems are analyzed.&#x0D; The necessity of revitalization of the strategy and policy of personnel management of vocational schools is proved, their essence, tasks and principles of the vocational and technical education system are revealed. The tasks of team personnel management which were given to the conditions of such activities are clarified. In the research work the considerable attention to the main roles and respective functions of the head of the educational institution in the management of the teaching staff is paid; the typical features of activities of effective leader and affecting its effectiveness factors are highlighted; compulsory skills and necessary qualities of the modern leader that form the foundation of effective personnel management are classified.&#x0D; In the conclusions the author summarized the results of a study on this stated issue.
Exploiting Triangle Patterns for Heterogeneous Graph Attention Network

Recently, graph neural networks (GNNs) have been improved under the influence of various deep learning techniques, such as attention, autoencoders, and recurrent networks. However, real-world graphs may have multiple types of vertices and edges, such as graphs of social networks, citation networks, and e-commerce data. In these cases, most GNNs that consider a homogeneous graph as input data are not suitable because they ignore the heterogeneity. Meta-path-based methods have been researched to capture both heterogeneity and structural information of heterogeneous graphs. As a meta-path is a type of graph pattern, we extend the use of meta-paths to exploit graph patterns. In this study, we propose TP-HAN, a heterogeneous graph attention network for exploiting triangle patterns. In the experiments using DBLP and IMDB, we show that TP-HAN outperforms the state-of-the-art heterogeneous graph attention network.
The professional image of a modern university lecturer

The article analyzes the structure of the university lecturer image consisting of basic competencies, a social status and professional competencies – didactic skills, conceptual training, and professional-Self. The article considers the factors affecting the professional image of the universities’ teaching staff, nowadays, such as: the transition to a skills-oriented education, the Russian employers’ requirements for university graduates, the commercialization of higher education, and the students’ audience specifics of the represented by generation “Z”, preferring the Internet resources as the main information sources. The article highlights the professional image of the teaching staff both in the eyes of the administrative structures of universities and students. A pilot study of the teaching staff professional image perception as seen from the students’s perspective was carried out the department of industrial policy and business administration of Kazan National Research Technological University. Due to the conducted research, it became possible to establish the most important characteristics of the internal image of a university lecturer from the students’ point of view and the significance of his/her external image.
New Architecture Quantum Perceptron using Quantum Circuit

the learning algorithm that is not optimal is due to the incomplete use of quantum in the perceptron quantum learning algorithm which is the background of this research. Previous research has shown that the proposed architectural form still needs to increase its probability value to be more optimal. The previous probability was 90.7%. The proposed model is a quantum circuit architecture in a quantum perceptron algorithm consisting of a quantum bit gate. The researchers conducted training and testing of the proposed quantum circuit architecture using quantum computer of the IBM Quantum Experience. This research produces a perceptron quantum architecture model using a quantum circuit that can solve problems regarding data classification. After measuring the proposed quantum circuit architecture, it shows a 100% probability. After training and testing, the probability is 100%, the same as that at the time of measurement. Then it produces the same output of |111100000000000000〉. The resulting probability shows a significant increase from the previous 90, 7%.
THE EMPIRICAL REVIEW ON THE WORKING ENVIRONMENT, MOTIVATION AND SOCIAL ATTRIBUTES ON CAREER PERFORMANCE IN OMAN

A strategically effective, hygienic, and healthy environment ensures bringing satisfaction among the employees while a drab, challenging, and competitive atmosphere leaves a seriously poor impact on the employees. At different times, employees are required to face a number of challenges, both operational and organizations where they are essentially expected to invest their best knowledge, skills, and experience, However, in a poorly developed atmosphere an employee basically refuses to invest his or her abilities which ultimately creates challenges for the organization. Therefore, the aim of the present study is to evaluate the effects of the working environment, motivation and social factors on career performance in Oman. The study used online empirical recourses by the name of working environment, motivation and social factors and career performance in different online database sources such as Google Scholars, Springer Link, Wiley, Science Direct, JSTOR, Emerald full text, Scopus, and EBSCO HOST, etc. The review findings summarized that maintaining a sophistically impressive working environment basically helps an organization to maintain a good image before the pool of skilled candidates in the market and helping it to acquire the best talents. Moreover, the study also concluded that the majority of the organizations across the globe are focusing on maintaining an effective working atmosphere to keep the employees more engaged to the organization than that of the other and it has a significant role in the comprehensive development of the organization. The findings of the study draw a guideline for future scope of empirical indebt study in the area of the career performance in Oman and the regions.
Sentiment Analysis Pemutusan Hubungan Kerja Akibat Pandemi Covid-19 Menggunakan Algoritma NaïveBayes Dan PSO

The Pandemic Covid-19 in Indonesia in 2020 had an impact on Termination of Employment (PHK), this has received various public opinions on social media. At a time when the poverty rate is high and unemployment increases every year, it becomes a factor of public disapproval of Termination of Employment (PHK). It is necessary to classify public opinion into a negative opinion or a positive opinion on this issue. The purpose of this study is to analyze the sentiment towards layoffs to determine negative or positive opinions using the Naïve Bayes algorithm by adding feature selection. The research stages consist of data collection, text preprocessing, feature selection, and application of algorithms. The testing process in this study uses the Rapid Miner application. The test results in this study using the Naive Bayes Algorithm, the accuracy value is 93.57% and for addition to the Naïve Bayes + PSO feature selection, the accuracy value is 93.71%. The best accuracy value in sentiment analysis of layoffs in the covid-19 pandemic is the addition of the PSO feature selection in the Naïve Bayes Algorithm, which is 0.14% better.
Scientific-methodical activity of the pedagogues of the Special Piano Department of the State Conservatory of Chisinau during the years 1950–1970

The article describes the methodological and scientific works of the Special Piano department teachers from the Chisinau State Conservatory, created in the period 1950–1970s. The most common type of unpublished articles are reviews of colleagues’ concerts, reports, abstracts, essays and musical collections. The most serious scientific plans of the teachers were related to the genre of the dissertation. In the 1960s. the scientific and methodological articles of teachers of the department of Special Piano begin to appear. The most significant part of them is formed by music collections, composed of the music of Moldovan composers. T. Voitsekhovskaya and A. Dailis compiled and edited musical aids for students of different ages. The uniqueness of these scientific and methodological opuses is due to the specifics of the material under study – the subject of a special piano, the subtleties of which are familiar to authors, pianists-teachers and performers from their direct professional activities. The named scientific publications opened the way for further research of pianists, who became especially numerous at the turn of the XX–XXI centuries.
On Star Expressions and Completeness Theorems

An open problem posed by Milner asks for a proof that a certain axiomatisation, which Milner showed is sound with respect to bisimilarity for regular expressions, is also complete.One of the main difficulties of the problem is the lack of a full Kleene theorem, since there are automata that can not be specified, up to bisimilarity, by an expression.Grabmayer and Fokkink (2020) characterise those automata that can be expressed by regular expressions without the constant 1, and use this characterisation to give a positive answer to Milner's question for this subset of expressions.In this paper, we analyse Grabmayer and Fokkink's proof of completeness from the perspective of universal coalgebra, and thereby give an abstract account of their proof method.We then compare this proof method to another approach to completeness proofs from coalgebraic language theory.This culminates in two abstract proof methods for completeness, what we call the local and global approaches, and a description of when one method can be used in place of the other.
A proposed architecture for single-species qubits in trapped-ion systems

An arrangement of qubits employs multiple metastable states of a single ionic species to simplify computing architecture.
CREATING VISUAL ASSETS OF KOREAN VOCABULARY CARD GAME NOLJA

ABSTRACT &#x0D; The Korean vocabulary card game Nolja is a game designed to assist the learning process of Korean vocabulary in an interactive way and suitable for women aged 15-25 years. However, as a new game, Nolja has a fatal problem with its design, namely, the placement of illustrations on the player card which makes the game finish too quickly, there are no tools to assess language proficiency on the card, the typeface on the card is less legible, and strokes on the illustration are too thin, Therefore, it is necessary to design a visual asset for the Nolja vocabulary card game. Visual asset design for Nolja includes game theme design, illustration, educational game system, layout, and content arrangement. This design aims to produce a Nolja card game design that is interactive, educational, and suitable for women aged 15-25 years who have the motivation and function to convey Korean language subject matter well. The design is carried out by qualitative methods through interviews with experts and extreme users in the game and learning the Korean language, distributing surveys to 100 target markets. This design is also supported by data collection from literature studies from books, journals, and articles from the Internet. The design produces a visual asset for the Nolja vocabulary card game with a stronger educational game system and a design style that matches the target market's wishes so that it can be well received by the market.&#x0D; &#x0D; Keyword: Korean language, Visual learning media, Flashcards, Picture card games, Visual assets.
Short technical text classification

Recent work in machine learning has provided promising results regarding short text classification. However, in case of technical abstracts and datasets, there are some cases when unsupervised algorithms fail to reach the optimal results. This paper presents a detailed description of a text classification system for short technical texts and datasets from a single domain, together with experiments. In order to be effective, it has been built as a mix between machine learning algorithms and keywords determined by an expert’s point of view.
Critical Success Factor For E-learning in the Covid -19 Pandemic: A Case Study in Jordan

The questionnaire was in three parts. Part A was Availability of E-learning requirements related to technical, administrative and financial aspects Part B was Disadvantages of E-learning and Part C E-learning obstacles. And It was written using Google Forms, and the link was shared through multimedia. The reliability of instrument was determined. Data collected were analyzed using simple percentage and t_test and Anova was used to test the hypotheses. The result collected and analyzed showed that; the majority of study (84.0%) respondents were in the middle age between 29 to 48 years old. Males were accounted for less than one fifth (18.0%) of sample. And we found out through the results teachers with 12 to 22 years of experience found of obstacles of E- learning in comparison with those with the lowest number of years of experience, and that state schools have more obstacles than private schools.
Digital Economy and Modern Programming Technologies: Some Experimental Results

This paper presents the findings of an empirical analysis that tested several theories about the relationship between software quality, expressed in terms of defect density, and cost estimation drivers (cost factors). The study employs three cost factors: work effort, project size (measured in function points), and average assigned work per team member. also, in the paper we supported the empirical study with relationship between project size and defect. The study makes use of the ISBSG repository data collection update 12. ISBSG dataset of 6006 completed projects. Regression Analysis and stepwise Analysis of Variance (ANOVA) are used for statistical analyses. Our research shows that project size and work effort have a significant negative impact on defect density. In addition, results the relationship between project size and defect indicate a weak correlation between size and defects. This result corroborates some of the recently published empirical results. On the other hand, the average amount of work assigned to each team member has a significant positive effect on defect density. These results imply that when assigning resources to a project, these quality factors should be taken into account in order to reduce defect density and, as a result, the product’s maintenance cost.
Pd and Audio Programming in the 21st Century

In celebration of the 25th anniversary of Pure Data, this essay discusses the development of audio programming up to the present, and considers the role that Pd can continue to play in the computer music of the future.
On An Invisible Architecture: An Antidote To Ocularcentric Space

&lt;div&gt;Invisible; something that is unseen, unnoticed, or ignored. Related to the awareness or recognition of an object as opposed to its actual presence, the problem with the invisible is the unknowingness of its very existence. While our bodies occupy diverse spatial conditions, they absorb a variety of visible and invisible information through the senses. As the geography of our increasingly digitized urban landscape creates conditions of solitude and alienation, the other senses become suppressed, manifested through our obsession with the eye, vision, and image. Identifying the non-place and its effect on inhabitants will serve as a point of departure in exploring the potentials for an architecture to become invisible — that is, for a space to exist beyond our infatuation with its aesthetic or visual character. Designing an atlas for the senses between the urban and natural context of Toronto and its ravines, this thesis aims to reintroduce architectural meaning through the body’s sensorial apparatus. In progressing beyond our current&lt;/div&gt;&lt;div&gt;ocularcentric state, we can use the senses as perceptual mechanisms to begin a dialogue addressing the non-place-ness of urbanity. In doing so, architecture becomes more relatable, engendering new spatial, perceptual, and emotional relationships within the memory of space.&lt;/div&gt;
ONLINE ANALYSIS OF A RANDOM SIGNAL USING COMPUTER AIDED SYSTEM

This paper attempts to describe an effective experimental approach to determine the characteristics of the random signal detected in the two-phase flow.This is a Computer-aided data acquisition system reporting data acquisition and data logging of parameters like root mean square (RMS), time, power spectral density (PSD), histogram and probability distribution of a random signal generated by two-phase flow in a vertical channel.The system employs virtual instrumentation software LabVIEW and data acquisition board (DAQ).The measurement and control are accomplished and integrated into the process by using a computerized data acquisition system (DAQ) and comprehensive virtual instrument (VI), which was developed using the LabVIEW application software and DAQ board.In addition, this system allows for easy modification and enhancement of a virtual instrument by modification of the software program.
An Adaptive and Interactive Educational Game Platform for English Learning Enhancement using AI and Chatbot Techniques

As our world becomes more globalized, learning new languages will be an essential skill to communicate across countries and cultures and as a means to create better opportunities for oneself [4]. This holds especially true for the English language [5]. Since the rise of smartphones, there have been many apps created to teach new languages such as Babbel and Duolingo that have made learning new languages cheap and approachable by allowing users to practice briefly whenever they have a free moment for. This is where we believe those apps fail. These apps do not capture the interest or attention of the user’s for long enough for them to meaningfully learn. Our approach is to make a video game that immerses our player in a world where they get to practice English verbally with NPCs and engage with them in scenarios they may encounter in the real world [6]. Our approach will include using chatbot AI to engage our users in realistic natural conversation while using speech to text technology such that our user will practice speaking English [7].