Reviewerly/exHarmony huggingface dataset:
VIRTUALIZACIÓN DE LA EDUCACIÓN SUPERIOR POR EL COVID-19: CALIDAD DE ENSEÑANZA Y SATISFACCIÓN ACADÉMICA

The virtualization of higher education in Peru's state of health emergency has required universities toguarantee the quality of teaching. In this new scenario, the purpose of the research was to analyzethe quality of teaching and virtual academic satisfaction of university students. The methodology wasassociative, with 410 university students with and without a bachelor's degree as participants. Theresults obtained showed significant differences in the quality of teaching and academic satisfactionof students from licensed universities with respect to non-licensed ones. In addition, a high correlationwas found between the variables (r = .901), and it was even shown that the quality of teachingexplains 81.2% of the satisfaction variance. In conclusion, the quality of teaching is a determiningfactor for the development of academic satisfaction; and licensed universities offer quality in theirteaching and keep students satisfied with their services.
ANALYSIS AND DESIGN OF EMPLOYEE PAYROLL ACCOUNTING INFORMATION SYSTEM AT PUBLIC ACCOUNTING FIRM OF TASNIM, FARDIMAN, SAPUAN, NUZULIANA, RAMDAN & PARTNERS

This study aims to find out and at the same time analyze how the payroll system is currently being implemented at Public Accountant Firm Tasnim, Fardiman, Sapuan, Nuzuliana, Ramdan & Partners, whether the payroll system has been running effectively and propose a payroll accounting information system design at Public Accountant Firm Tasnim, Fardiman, Sapuan, Nuzuliana, Ramdan & Partners. The data used in this study is primary data obtained directly from Public Accountant Firm Tasnim, Fardiman, Sapuan, Nuzuliana, Ramdan & Partners and is a descriptive qualitative research, namely a case study using qualitative data obtained from internal companies. The data analysis technique used is system analysis, proceed to the proposed flowchart stage, proposed DFD, proposed ERD to payroll system design using Microsoft Access and Visual Basic 6.0. Based on the results of this study, the payroll system at Public Accountant Firm Tasnim, Fardiman, Sapuan, Nuzuliana, Ramdan & Partners still has problems in the payroll system, namely the procedure for payroll documents is still manual or still using handwriting and the calculations are still using the excel program whose input must use the formula complicated so that time is not efficient.Keywords: analysis and design, accounting information system, and employee payroll
The Application of Internet Technology and the Study of Tibetan Local Chronicles in the Qing Dynasty

With the development of Internet technology and information technology, digitization has gradually become an inevitable trend in collecting, sorting and researching on Tibetan local chronicles in the Qing Dynasty. The Tibetan local chronicles in the Qing Dynasty are the basic documents for studying the history of Tibet in the Qing Dynasty, and have important historical and academic values. This article studies the current situation and measures of the digital collection, sorting and research of Tibetan local chronicles in the Qing Dynasty under the development of Internet technology, shows that the use of Internet technology and digital analysis of Tibetan local chronicles in the Qing Dynasty is a new direction that the academic community should pay attention to by analyzes how to build a digital resource platform for ancient books and documents, collect and sort precious documents in a informatization way, build an information technology and digital talent team for local chronicles research, and build multimedia digital brands, etc .
Review of Clustering-Based Recommender Systems.

Recommender systems are one of the most applied methods in machine learning and find applications in many areas, ranging from economics to the Internet of things. This article provides a general overview of modern approaches to recommender system design using clustering as a preliminary step to improve overall performance. Using clustering can address several known issues in recommendation systems, including increasing the diversity, consistency, and reliability of recommendations; the data sparsity of user-preference matrices; and changes in user preferences over time. This work will be useful for both beginners in the field of recommender systems and specialists in related fields that are interested in examining the applicability of recommender systems. This review is focused on the analysis of the scientific literature on the topics of recommender systems and clustering models that have appeared in recent years and contains a representative list of the literature for the further exploration of this topic. In the first part, a brief introduction to the so-called classic or traditional recommendation algorithms is given, along with an overview of the clustering problem.
Alexa, are you still there? Understanding the Habitual Use of AI-Based Voice Assistants

Voice assistants are a novel class of information systems that fundamentally change human–computer interaction. Although these assistants are widespread, the utilization of these information systems is oftentimes only considered on a surface level by individuals. In addition, prior research has focused predominantly on initial use instead of looking deeper into post-adoption and habit formation. In consequence, this paper reviews how the notion of habit has been conceptualized in relation to biographical utilization of voice assistants and presents findings based on a qualitative study approach. From a perspective of post-adoption users, the study suggests that existing habits persist, and new habits hardly ever form in the context of voice assistant utilization. This paper outlines four key factors that help explain voice assistant utilization behavior and furthermore provides practical implications that help to ensure continued voice assistant use in the future.
The Basic Economic Logic of Bitcoin System

Without understanding the underling technique and governance, it is not easy for us to realize the essential of bitcoin phenomenon. I realize that the reason bitcoin system has been operating for 10 years without any authority, is it has done a great job in utilizing the economic effect of Hash Function. Due to the high flexibility in cost adjustment, Hash Function helps bitcoin get rid of the restriction from objective world. And this may bring a potential impact to the current economic structure. Based on it, this paper tries to analyze the underling technique (Public Key Encryption and Hash Function) in economics method. Then I analyze the potential impact that bitcoin brings to traditional economy and point out the dilemma the crypto-currency faces: supervision, the limit of complete distributed modes and the connection between online data and the offline assets.
Teaching A Foreign Language In Master’s Program: Distance Education

The authors rely on their own experience of teaching a foreign language in a distance educational system to IT students at the Industrial University of Tyumen. Such experience is associated with a number of difficulties: the heterogeneity of students' knowledge, a sufficiently small number of classroom hours, and the inability to obtain one-to-one counseling; the choice of adequate educational platforms and applications. A foreign language teacher has to competently and skillfully plan, organize, monitor and objectively evaluate the work of students. The distance learning process involves the use of various additional features of the Internet, online platforms and applications. That allows to search for information on the network; to engage a dialogue with students using corporate email; to plan and conduct teleconferences and webinars. All these activities have positive affect on the students’ interest to the subject "Business foreign language in the professional sphere". The authors use the educational process support system "Educon V 2:0" to manage the self-education activities, to check and choose tools for monitoring achievements, to ensure their fair assessment. The survey conducted by the authors in student groups revealed that graduates are aimed at acquiring knowledge in a non-core discipline such as foreign language, which will present them as competitive employees of leading firms not only in the domestic labor market, but also in foreign countries.
Automation Of The Process Of Teaching Students To Solve Computational Problems

Learning to solve computational problems both at school and at the university is the most important component of the educational process in any exact discipline. In the context of the digital transformation of education, the issues of automating the process of organizing personalized independent work of students to solve problems are becoming relevant. In this regard, the work aimed to substantiate and experimentally test an approach to formalizing the process of teaching students to solve computational problems. The main idea of the research is to create an automated interactive software environment developed based on structural and mental schemes and the "white box" model. To increase the effectiveness of independent learning using this environment, elements of gamification are used, visualization of the dynamics of the formation of the ability to solve problems using the forgetting factor and the A. Elo rating. Experimental testing of the created tool in the real educational process allowed us to evaluate the effectiveness and advantages of the proposed approach to automating the process of teaching students to solve computational problems. The use of problem-based structural-mental schemes allows you to create software training tools for many subject areas. The materials of the article are of interest to researchers in the field of the use of artificial intelligence in education.
Blockchain Based Course Feedback System

Blockchain Technology is an innovative tool which can be used for tracking objects in the digital world. This project explores the usage of Blockchain Technology as a Course Feedback System to track the feedback given by the students taking a course. This is to be done by implementing a smart contract on the Ethereum Blockchain which will accept the feedback given by students. This feedback will be recorded by a Survey Management System and then will be pushed onto the Blockchain for immutability and enhanced trackability. The system should be able to support the creation of a survey by the professor who is in charge of the course. The system will then have to create a matching smart contract to support the survey questions decided by the professor. After the survey goes live, the system will store the data collected during the survey and push it to the blockchain, as a complete Feedback object file or as a hash of the values entered by the student in the review.
Research on Strengthening the Quality Management of Online Teaching in Universities

Online teaching is a virtual teaching mode developed with the help of modern information technology, which is widely used in colleges and universities. Online teaching has the advantage of learning across time and space, but it also brings problems such as ineffective classroom management and poor learning effect. To improve the existing problems in the current situation, we need to do a good job in teaching preparation, strict management of teaching and learning process, timely feedback and improvement of the existing problems. Students, teachers, and organizations need to join efforts to improve the quality of teaching.
Inserted Systems of Mobile Application and Electronic Braille Alphabet Connected with Android Smartphone Device

This exploration intention is to make electronic braille that associated with Android telephone. Examination and formative methodologies are utilized for the technique. Information preparing and regulator uses Arduino nano microcontroller, Bluetooth module CH05 for Arduino speak with android versatile application through remote Bluetooth correspondence, and small solenoid are utilized as the actuator. Android application is utilized as conclusive interface with voice and touchscreen highlights. The outcomes are practical and useful braille gadgets which associated with android based application as planned. Electronic braille can shape braille letter designs with character change speed that up to 500 m.
RETHINKING SUPPLY CHAIN MANAGEMENT THROUGH NEW DIGITAL APPLICATIONS

Globalization has created complex supply chains to support free trade. The goods move across production facilities and supply chains, connecting markets involving numerous players along the way, while being subjected to different legal standards and quality requirements across multiple jurisdictions. By generating digital versions of real-world assets and tracking their pertinent data as a distributed, shared source of information, significant efficiencies and process improvements can be achieved. The use of distributed ledgers or blockchains to track goods as they move along the supply chain, makes for transparency and accuracy in the location of the goods at any point of time, in real-time. In this chapter, we provide a short discussion of artificial intelligence (AI), blockchain, and IoT applications in supply chain management and understand the benefits and the shift in the processes, in digital applications.
Fortifying Your Cloud: Mitigation Techniques for Cloud Security Flaws

The cloud has opened up massive possibilities for businesses. The ability to scale quickly without growing on-premise equipment has been a game changer in recent years. But innovation gives rise to...
PENDAMPINGAN PEMBUATAN LEMBAR KEGIATAN SISWA DARING UNTUK IMPLEMENTASI KEBIJAKAN BELAJAR DARI RUMAH BAGI GURU DI KOTA BENGKULU

One of the impacts of COVID-19 pandemic is forcing teachers and school residents to adjust teaching and learning activities at home. This mentoring activity aims to improve the knowledge and skills of SD N 69 Bengkulu City teachers to prepare worksheets that are easy for parents to understand while implementing BDR. This service activity partners are grade 1 to grade 6 teachers of SDN 69 Bengkulu City, class, religion, and health education teachers, totaling 26 teachers. This activity was carried out from August to November 2020 through observational and modeling with four phases, namely: the attention phase, the retention phase, the reproduction phase, and the motivation phase. The instrument used was a questionnaire to measure teacher knowledge about online worksheets and a rubric for assessing teacher skills in compiling online worksheets. Results and conclusions, teacher assistance activities to prepare online worksheets can: (1) Increase teachers' knowledge about online worksheets, especially those related to online worksheets' goals. (2) Improve teacher skills in compiling online worksheets, especially the fourth aspect, namely teachers' skills to collect assessment rubrics per basic subject competence in online worksheets.
Study to Find Optimal Solution for Multi-objects Detection by Background Image Subtraction with CNN in Real-Time Surveillance System

Now a day, video surveillance has gained the most attention in real-time applications. Because of the improvement in domain of machine learning, various methodologies have been designed for multi-object detection. The real-time surveillance systems are the need of various organization as security; hence, this area of research has important. This paper introduces a new methodology for Moving object detection. In the area of real-time video surveillance systems, multi-object detection and object tracking are an important step in video processing. The moving system is critical for many of the application such as operational robot, surveillance systems in military. These real-time surveillance systems are more useful for intelligence gathering, security issues, and many personal needs. Different techniques are used for this task and research is vastly done to make this system automated and to make it reliable. In this research, subjective quality assessment of object detection and object tracking is discussed in detail. In the proposed system, the background subtraction is done from the clean original image and use of CNN with this. We have applied background subtraction method with different filtering algorithms. We have implemented and tried MoD2 and KNN algorithm on the test video and fetched the foreground image. After this, we have applied CNN to track the object. After tracking the objects, we have found out the accuracy with background subtraction method and without background subtraction method. The proposed system improved by approximately 2% as compared to existing techniques.
Digital Technologies In The Higher Education System

The topic of the use of digital technologies in the field of education in connection with the development of information technologies and the changing requirements of the modern labor market is currently very relevant. Modern life dictates its own conditions, now employers need specialists who have the skills to freely use electronic technologies in their professional activities. Digital technologies are an integral part of public life and open up wide opportunities the development of competencies in the professional sphere. The article discusses the main digital educational technologies, including: cloud technologies, mobile space, web quest, online courses. The aim of the study is to reveal the essence of digital technologies in the educational space and to determine their advantages, which include visibility, accessibility, orientation to the individual abilities of students. The article discusses the theoretical and practical problems of using digital technologies in teaching humanities at a technical university. The results of our research have shown that the competent use of innovative technologies in the educational process contributes to the formation of positive motivation among students, allowing them to make it as effective as possible, meeting modern realities. It is argued that digital educational technologies in the educational space are a necessary condition for improving the efficiency and effectiveness of the educational process.
Signature Matching For Seismic Signal Identification

Seismic signals can be classified as natural or manmade by matching signature of similar events that have occurred in the past. Waveform matching techniques can be effectively used for discrimination since the events with similar location and focal mechanism have similar waveform irrespective of magnitude. The seismic signals are inherently non-stationary in nature. The analysis of such signals can be best achieved in multiresolution framework by resolving the signal using continuous wavelet transform (CWT) in time-frequency plane. In this paper similarity testing and classification of nuclear explosion and earthquake are exploited with correlation, continuous wavelet transform, cross-wavelet transform and wavelet coherence (WC) of P phase of seismogram. Clustering of seismic signals continuous wavelet spectra is performed using maximum covariance analysis. The proposed classifier has an average classification accuracy of 94%.
Scene Text Extraction using Convolutional Neural Network with Amended MSER

Content in the text format helps to communicate the relevant and specific information to users meticulously. A beneficial approach for extracting text from natural scene images is introduced which employs amended Maximally Stable Extremal Region (a-MSER) together with deep learning framework, You Only Look Once YOLOv2 network. The proposed system, a-MSER with Scene Text Extraction using Modified YOLOv2 Network (STEMYN), performs remarkably well by evaluating three publicly available datasets. The method a-MSER is used to identify the region of interest based on the variation of MSER. This algorithm considers intensity changes between text and background very effectively. The drawback of original YOLOv2, the poor detection rate for small-sized objects, is overcome by employing 1 × 1 layer with image size enhanced from 13 × 13 to 26 × 26. Focal loss is applied to improve upon the existing cross entropy classification loss of YOLOv2. The repeated convolution layer in the steep layer of the original YOLOv2 is removed to reduce the network complexity as it does not improve the system performance. Experimental results demonstrate that the proposed method is productive in identifying text from natural scene images.
Experience And Results Of Distant And Blended Learning In General Technical Disciplines

The article is devoted to the practice of usage mixed and distance learning in general technical disciplines. The expediency of using mixed learning in the process of general technical training is shown and also the relevance of lecturers' consolidated approach to the choice of content and complex of forms, means and methods of blended learning is demonstrated. A review of scientific and methodological literature of blended learning technology is carried out. The main point was determined in the course of the study, furthermore the choice was substantiated, and the essence of the implementation of the blended learning rotational model in general technical disciplines was revealed. The experience of transition from blended learning to distance forms of educational process organization is shown. The main means and level monitoring methods of general technical training are investigated. Also, the transition results from blended learning to distance learning of general technical disciplines are shown in the example of the field of study "Agroengineering". The analysis of pedagogical results showed the ineffectiveness of full distance learning in general technical disciplines.
Leveraging the Inductive Bias of Large Language Models for Abstract Textual Reasoning.

Large natural language models (such as GPT-3 or T5) demonstrate impressive abilities across a range of general NLP tasks. Here, we show that the knowledge embedded in such models provides a useful inductive bias, not just on traditional NLP tasks, but also in the nontraditional task of training a symbolic reasoning engine. We observe that these engines learn quickly and generalize in a natural way that reflects human intuition. For example, training such a system to model block-stacking might naturally generalize to stacking other types of objects because of structure in the real world that has been partially captured by the language describing it. We study several abstract textual reasoning tasks, such as object manipulation and navigation, and demonstrate multiple types of generalization to novel scenarios and the symbols that comprise them. We also demonstrate the surprising utility of \textit{compositional learning}, where a learner dedicated to mastering a complicated task gains an advantage by training on relevant simpler tasks instead of jumping straight to the complicated task.
Adaptive depth constraint-based underwater binocular image feature matching

Objective  In this paper, addressing sparse feature points and unique epipolar constraint, an adaptive depth constraint-based underwater feature matching (ADC-UFM) scheme is proposed. Methods  By combining the features from accelerated segment test (FAST) operator with scale invariant feature transform (SIFT) descriptors such that the matching accuracy can be dramatically improved. By introducing the underwater refractive factor, the matching constraint model (MCM) can be effectively established, and thereby contributing to eliminating mismatched points. The adaptive threshold choosing (ATC) module is finely devised to extremely preserve image feature information in changeable underwater environments. Results  Comprehensive experiments show that the proposed ADC-UFM scheme can outperform typical matching schemes including SIFT, speeded-up robust features (SURF) and SIFT feature matching based on underwater curve constraint (UCC-SIFT), which not only achieves 85.2% matching accuracy but also meets real-time requirements. Conclusion  The results of this study can provide a reliable guarantee for the subsequent underwater 3D reconstruction based on binocular vision system.