Reviewerly/exHarmony huggingface dataset:
Semi-Supervised Speech Recognition via Graph-based Temporal Classification

Semi-supervised learning has demonstrated promising results in automatic speech recognition (ASR) by self-training using a seed ASR model with pseudo-labels generated for unlabeled data. The effectiveness of this approach largely relies on the pseudo-label accuracy, for which typically only the 1-best ASR hypothesis is used. However, alternative ASR hypotheses of an N-best list can provide more accurate labels for an unlabeled speech utterance and also reflect uncertainties of the seed ASR model. In this paper, we propose a generalized form of the connectionist temporal classification (CTC) objective that accepts a graph representation of the training labels. The newly proposed graph-based temporal classification (GTC) objective is applied for self-training with WFST-based supervision, which is generated from an N-best list of pseudo-labels. In this setup, GTC is used to learn not only a temporal alignment, similarly to CTC, but also a label alignment to obtain the optimal pseudo-label sequence from the weighted graph. Results show that this approach can effectively exploit an N-best list of pseudo-labels with associated scores, considerably outperforming standard pseudo-labeling, with ASR results approaching an oracle experiment in which the best hypotheses of the N-best lists are selected manually.
Novel whale optimized Bayesian network structure learning for reliability analysis and fault diagnosis of complex real application systems

Bayesian networks (BN) have step by step emerge as one of the essential successes in Artificial Intelligence (AI) investigation. Founding an operative BN structure is the core of the mastering and foundation and submission of BN. In these network SL, the vintage approach of using expert to build the community shape is regularly substituted with the aid of the facts gaining knowledge of structure technique. However, because of the massive quantity of possible community systems, the quest area is much big. The technique of BN studying over training facts commonly has the troubles of precision is low or complexity is high, which make the SL of fluctuate substantially from that of truth, which has a terrific stimulus on the reason and sensible application of BN. In order to overcome this difficult. In this paper, Novel Whale Optimization Algorithm for BN Structure Learning (SL) is (WO-BNS) introduced. The proposed WO-BNS has examined in reliability evaluation and fault prognosis of complex structures with actual case packages. In extra, fault prognosis is studied for figuring out essential components, essential reasons, and diagnosis routes. Experimental simulation effects display that the proposed WO-BNS SL algorithm has better shape and convergence.
AN EXHAUSTIVE REVIEW ON WEB MINING TOOLS AND APPLICATIONS

In the present era, the web is an archive of knowledge in any form like text, audio-video,graphics and different media. Web mining is a procedure of data mining concerning searching, extractingimportant and useful data from web servers, databases and logs. The motive of this paper is to present thecomparative analysis and outcomes of such software for web mining
Iterative Creation of a Chinese Data Set for Relation Extraction

This thesis aims to use an iterative way to create a Chinese data set with the help of NLP tools and the LSTM (Long Short Term Memory) model. The goal of this task is twofold: 1) Create a Chinese d ...
Psychological and Pedagogical Conditions for Creating the Learning Environment in the Multiethnic Space of the University

The present research featured the psychological and pedagogical conditions that shape the learning environment in the multiethnic space at university. The article focuses on the methods and technologies that develop a multiethnic learning environment based on the psychological phenomena of leadership and group norms. These methods evolved from psychological theories of leadership, norm formation, and small group development. The article also describes how these methods and technologies can be implemented in practice in order to provide the most favorable environment in conditions of ethnic diversity. The technologies include directing leader’s activity and developing group norms. The first technology sets behavior patterns and develops personal qualities of the leader while attracting other students’ attention to his or her activities. The method of developing group norms includes instruction, group discussion, private counseling on intercultural issues, and teacher’s own role model. Methods and technologies for creating a favorable learning environment are based on the need to bring up an ethno-oriented personality. These methods affect psychological characteristics of students, especially those associated with the ability to modify one’s behavior for beneficial intercultural communication. In the context of the multicultural learning practice, the educational tasks of the selected technologies of psycho-pedagogical interaction are to immerse students in the cognitive multicultural process, thus using the multicultural environment of the university as a factor of self-development.
Socio-instrumental Aspects in Usability Heuristic Studies: Systematic Review

Nowadays, usability mainly perceived as a basis of the instrumental evaluation of an information system (IS) capability. Notably, rule-of-thumb usability heuristic evaluation (HE) is widely known a ...
The Use of Behaviourism Approach in Writing a Narrative Text Applied to Grade Class XI of SMK Negeri 1 Pancur Batu-Deli Serdang, Sumatera Utara Academic Year 2016/2017

There were some reasons why indirect feedback can be durable, but it would kept only in mind of receiver and the feedback can just lost in certain time. In contrast, the indirect feedback, the thought and comment would be saved for every long time in memories. The data of this research consisted of two kinds. They were quantitative data (Writing Narrative text result) and the qualitative data (diary notes and observation sheet) which had been gathered within two cycles. Cycle I consisted of three meetings and cycle II consisted of two meetings and there was writing narrative test I in the first meeting to get the students’ basic level understanding that was pre test. So, totally there were six tests in five meetings in this research. From this research, there was an increased improvement in writing narrative text by using behaviourism approach, because this theory displays more attention from the teacher to the students.
Revolutionizing Medical Data Sharing Using Advanced Privacy Enhancing Technologies: Technical, Legal and Ethical Synthesis

Multisite medical data sharing is critical in modern clinical practice and medical research. The challenge is to conduct data sharing that preserves individual privacy and data usability. The shortcomings of traditional privacy-enhancing technologies mean that institutions rely on bespoke data sharing contracts. These contracts increase the inefficiency of data sharing and may disincentivize important clinical treatment and medical research. This paper provides a synthesis between two novel advanced privacy enhancing technologies (PETs): Homomorphic Encryption and Secure Multiparty Computation (defined together as Multiparty Homomorphic Encryption or MHE). These PETs provide a mathematical guarantee of privacy, with MHE providing a performance advantage over separately using HE or SMC. We argue MHE fulfills legal requirements for medical data sharing under the General Data Protection Regulation (GDPR) which has set a global benchmark for data protection. Specifically, the data processed and shared using MHE can be considered anonymized data. We explain how MHE can reduce the reliance on customized contractual measures between institutions. The proposed approach can accelerate the pace of medical research whilst offering additional incentives for healthcare and research institutes to employ common data interoperability standards.
LibGuides: ASU Library Digital Credentials: Credential Links

ASU Library is launching a new digital credentials service that will enable faculty to integrate credentials into Canvas.
Sound as a Style Somponent of Art Rock: Formation Ways and Factors

Relevance of research. Recent studies of rock music by representatives of academic musicology are more and more often devoted to matters of style. An important component of rock stylistics is sound that is first of all related to timbre coloristic and texture characteristics of sounding. It is the sound that highlights the creative individuality of rock musicians and becomes a key to support rock bands awareness. Sound obtains a special value in the creative practice of art rock (including progressive rock) that is an intersection of rock and academic music. This is why the studies of sound formation factors are important, both merely artistic and those beyond artistic.Main objective of the study. The purpose of the article is through the example of creative work of rock bands that are the main art rock representatives (“Genesis”, “Gentle Giant”, “King Crimson”, “Pink Floyd”, “Yes”) define the ways and different in nature factors of sound formation process. The research methods. The choice of research methods is determined by specificity of material, namely by the fact that the musical notation of the music being analyzed is not available. The main in the study is the comparative method that allows us to clarify common displays and difference in sound formation or art rock bands, as well as respectively modified intonational analysis methods.Results and conclusions. Sound arises as a style category that defines individual character of sounding. The creative practice of rock music typically involves unity of the author(s) of the music and the performer(s), therefore rock music is considered as a result of combination of the composer’s and the performer’s intentions in the artistic communication. The ensemble specificity of rock bands requires special attention to the nature of relation of vocal and instrumental components and the analysis of their importance in the sound formation of one or another band. Consideration of sound in the context of timbre and timbre formation allowed to state the spread in the practice of art rock of trends that previously formed in the field of academic music of the 20th century: significant expansion of instruments, use of noise and specific sounds, rethinking the possibilities of various instruments, experiments with musical texture.A special role of music producers, arrangers and sound directors in the sound formation has been noted. It is emphasized that the search for new sounds stimulated the design of fundamentally new electromechanical (such as Mellotron) and electronic instruments. It is shown with the example of specific groups that the formation of sound in art rock is often the result of inter-genre and stylistic synthesis, when distant genre-style layers become material for textural, dynamic, agogical experiments. It is claimed that further research into the sound will provide an opportunity to get closer to understanding the mechanisms of style formation in rock music.
Smart Bike System

&lt;p&gt;Vehicles being the most widely used machines need to get smarter compared to their current technology. The necessity described by the younger generation of users, the millennials, for their devices to be smart and their vision to have more computerized and smarter applications of various sensors. The invention and development of better-computerized systems for infotainment and control of vehicles have taken speed and research is done mainly in an open-source on Linux kernel-based operating systems. The Smart Bike System is a Raspberry pi based operating system(AGL) for bikes tracks the various components of the bike like Speed, Quantity of fuel, Distance covered in a single trip, Temperature, Date and Time. We make a note that the current system of dashboards for representing the various aspects of a bike is old. A significant improvement would be made in the quality of the bike and the way people use it if the current computer technology of the world embraces the vehicular system. Automotive Grade Linux(AGL) is an (open source tech) operating system for automobiles which when installed on a computer in synchronization with the parts of a motor-bike has an ability to display more information in a more colorful and animated format like a computer desktop but specifically for automobiles.&lt;/p&gt;
Knowledge-driven SPARQL Query Construction Based on Feedback Mechanism

Abstract According to the survey, the performance of the existing knowledge graph answering system in entity linking, relation linking and SPARQL query construction in terms of execution time and accuracy cannot meet the requirements of knowledge graph answering system. For this challenge, a new feedback mechanism based Knowledge-Driven query construction method is proposed. This method takes the entity set and predicate set in the problem as input, and constructs SPARQL query statements in a knowledge-driven way to solve simple and complex problems, and further proposes heuristic ideas to deal with implicit entity problems. At the same time, the method also proposes to feed back the query results of the knowledge graph to the entity link and relationship connection steps, so that the SPARQL query statement is optimized again. The evaluation results of the LC_QuAD data show that this method outperform the existing state of the art in precision and recall rate.
Programs about Books and Reading in Central Television

For a long time, various programs about books and reading appeared on TV and then disappeared. They were lost in the TV broadcasting and programs among other programs, cinema films and TV movies. And when programs were closed, they were quickly forgotten. The purpose of this article is to reveal all such TV programs. The author studied the period of more than 50 years. The article gives the names of TV shows about books and reading, belonging to certain channels, and the time of airing. As possible, the author discloses their intent, concepts, content and the names of TV presenters. The sources for the article were weekly bulletins about TV programs, and in the last 30 years — also articles, notes, interviews in professional and general periodicals. In Soviet times, there were TV programs “In the world of books”, “Bookshop”, “Reading circle”. In 1978—1979, the TV presenter of the “Reading circle” was N.M. Sikorsky, then Director of the V.I. Lenin State Library of the USSR. In post-Soviet Russia, there got more broadcasts of that kind. These were both educational programs (“Book yard”, “Graphoman”, “Exlibris”, “Book storehouse”) and numerous commercial ones (“Bookstore”, “Home library”, “Bibliomania”, “World of books with Leonid Kuravlev”, “Book news”, “Book world”). The author gives more details are tells about the program “Graphoman”, which was invented and presented by A.N. Shatalov, the poet, critic and publisher. The program originated in 1994 and was broadcast on various channels for more than 10 years. Programs of the recent years are “Book for breakfast”, “Various Readings”, “Words order”, “Figure of speech”, “Pro-Reading”, “Book measurement”, “What to read?”. For over half a century, television actively supported the initiators and creators of various programs that promoted books and reading. This activity has slightly declined in recent years. But viewers continue to learn from the TV screen about new books and watch events in the book industry.
Mathematical Methods in Monitoring the Quality of Student Performance

The article deals with the statistical analysis of the effectiveness of the educational process at university. The research featured factors affecting the quality of training university students. The authors employed quantitative and qualitative indicators and organizational and pedagogical approaches, as well as methods of correlation and variance analysis. The indicators were systematized and generalized in order to identify the extent of their impact on the effectiveness of the factors under consideration. The reliability of the results was checked using the Pearson test. The methodology of the study was based on the identification of factors that affect the students’ achievements. A factor is a condition for good quality education. Based on the principles of general and professional education of the individual, the authors identified two groups of factors: 1) those related to the performance of the general education stage (academic performance, training profile); 2) those related to the results of higher education (academic performance, areas of training, course of study, academics). The academic performance of the first-year students did not depend on the results of the Unified State Exam and school grades. This dependence began to manifest itself during the second year, i.e. after the adaptation period. Statistical processing provided a mathematical model of the dependence of academic performance on the identified factors. The model can be used to predict the results of academic performance, as well as to adjust the learning process in order to improve the quality of university graduates' training, e.g. additional consultations, new information technologies, changes in the curriculum, level-based differentiation of content, tasks, individualized tasks, etc. The results are of interest for organizers of psychological and pedagogical support of professional self-determination for university students and their socio-psychological adaptation.
Face Verification across Aging using Deep Learning with Histogram of Oriented Gradients

One of the complex procedures which affect man's face shape and texture is facial aging.These changes tend to deteriorate the efficacy of systems that automatically verify faces.It seems that CNN (also known as Convolutional Neural Networks) are thought to be one of the most common deep learning approaches where multiple layers are trained robustly while maintaining the minimum number of learned parameters to improve system performance.In this paper, a deeper model of convolutional neural network is fitted with Histogram of Oriented Gradients (HOG) descriptor to handle feature extraction and classification of two face images with the age gap is proposed.Furthermore, the model has been trained and tested in the MORPH and FG-NET datasets.Experiments on FG-NET achieve a state of the arts accuracy (reaching 100%) while results on MORPH dataset have significant improvements in accuracy of 99.85%.
Safe Reinforcement Learning for Automated Vehicles

Fully automated vehicles have the potential to increase road safety and improve traffic flow by taking the human element out of the driving loop. They can also provide mobility to people who are unable to operate a conventional vehicle. Safe automated vehicles must be able to respond in emergency situations or drive on slippery roads in bad weather conditions. Therefore it is crucial to have a safe and robust control strategy that can use the full handling capabilities of the vehicle. This thesis presents how safe reinforcement learning can be used to design a steering policy that can drive an automated vehicle at the limit of friction. The steering policies are trained using the Lyapunov Safe Actor-Critic (LSAC) algorithm. LSAC is a combination of the Soft Actor-Critic (SAC) algorithm and a Lyapunov stability analysis to solve constrained control problems. The performance of LSAC is tested in a vehicle simulator against SAC and Model Predictive Control (MPC) in a series of tests that include changing lanes at different speeds, recovering from a destabilizing collision, and driving on a race track at the limit of friction. The experiments show that LSAC outperforms MPC and SAC control strategies in terms of safety and vehicle stability. LSAC can recover from larger disturbances than MPC and SAC. A control strategy is presented that will keep the vehicle stable when driving at the limit of friction but can use the maneuverability of an unstable vehicle when is it necessary to avoid dangerous situations. Additionally, a policy is presented that can find the fastest way around a race track while staying within the track limits.
Implementation of Word Square Learning Model in Vocabulary Learning (adjectives and nouns) Japanese Language in 11th Grade Students at YADIKA High School, Langowan District

Teacher Deployment Program Activities in Schools (PDS) are very beneficial for the lecturers and the school as well as LPTK. The Teacher Deployment Program in Schools (PDS) has a symbiotic nature of mutualism, meaning that it benefits both parties, both the school and the Lecturer and LPTK. An innovative learning model that can encourage students' understanding of Japanese vocabulary mastery. One form of innovative learning models is the Word Square learning model. Word Square learning model can be used to encourage students 'understanding of the subject matter, can train students' discipline, can train their attitudes carefully and critically and can stimulate students to think effectively. Of the 20 students who were tested in the pre-test before applying the Word Squared learning model in studying Japanese vocabulary can be seen from the results of the average grade of 49.5. Whereas after using the Word Square learning model, the progress of learning outcomes is so well evidenced by the average grade of the post-test that reaches 90.15. This proves that the application of the Word Square learning model in learning Japanese vocabulary plays a big role in a teaching and learning system, especially for education.
Effectivity and students’ satisfaction to a tutorial in statistics through a webinar

Abstract The aim of the article was a review of the tutorials through webinars on Educational Statistics courses for students of the Master’s Degree in Basic Education of Universitas Terbuka. The focus of the research was students’ views on the effectiveness and satisfaction of the webinar in terms of engagement, complexity, and task orientation. The respondents of the study consisted of 74 students of the master’s degree program in primary education. Data analysis used PLS-SEM to predict causal relationships among the variables understudied. The results showed that: 1) engagement gave an effect to effectivity, but did not give an effect to satisfaction, 2) complexity brought an effect to satisfaction but did not give an effect to effectivity, and 3) task orientation gave an effect to effectivity and satisfaction. Recommendations: 1) to increase the effectiveness of mathematics tutoring through webinars, it is necessary to increase student engagement and time efficiency of learning activities, and 2) to increase satisfaction with mathematics tutoring through webinars, it is necessary to improve the ease of implementing webinars (technical and procedures) and efficiency of learning time.