Reviewerly/exHarmony huggingface dataset:
Method of Performance Analysis of Time-Critical Applications Using DB-Nets

These days, most of time-critical business processes are performed using computer technologies. As an example, one can consider financial processes including trading on stock exchanges powered by electronic communication protocols such as the Financial Information eXchange (FIX) Protocol. One of the main challenges emerging with such processes concerns maintaining the best possible performance since any unspecified delay may cause a large financial loss or other damage. Therefore, performance analysis of time-critical systems and applications is required. In the current work, we develop a novel method for a performance analysis of time-critical applications based on the db-net formalism, which combines the ability of colored Petri nets to model a system control flow with the ability to model relational database states. This method allows to conduct a performance analysis for time-critical applications that work as transactional systems and have log messages which can be represented in the form of table records in a relational database. One of such applications is a FIX protocol-based trading communication system. This system is used in the work to demonstrate applicability of the proposed method for time-critical systems performance analysis. However, there are plenty of similar systems existing for different domains, and the method can also be applied for a performance analysis of these systems. The software prototype is developed for testing and demonstrating abilities of the method. This software prototype is based on an extension of Renew software tool, which is a reference net simulator. The testing input for the software prototype includes a test log with FIX messages, provided by a software developer of testing solutions for one of the global stock exchanges. An application of the method for quantitative analysis of maximum acceptable delay violations is presented. The developed method allows to conduct a performance analysis as a part of conformance checking of a considered system. The method can be used in further research in this domain as well as in testing the performance of real time-critical software systems.
Point of Sale Framework-Based Code Igniter and Model View Controller Using Lighthouse Testing

The success of companies engaged in the field of distributors is not only from good and smart human resources, but how ready the company's way to provide tools or programs supporting the work of employees. Some of the problems are the administration system between the company's internal divisions, so there are restrictions on the processing of input data, processes, outputs that are still manual. Web Application is made to facilitate employees to conduct administrative activities with the access role of each user admin division, for example inventory data, creation of sales invoices, road letters, procurement forms and bookkeeping. In addition, The Web View application is already responsive in this sense can adjust the device PC / Tablet / Mobile, then for visualization of data calculation already using cart / data graphics in real time, and there is also a feature preview, download and print JPEG, PNG, PDF, Barcode and QR code. Web Testing This application with black box method and shows it is running well and no error method, so it can be declared passed. Web Creation This application involves the LTE 2.0 Admin Template with bootstrap CSS, for programmer frameworks using MVC model view controllers that exist in the Code Igniter 3.0 framework so that it is faster and easier to implement or developed in other field companies or in the manufacturing industry. Tests using lighthouse for perform by 94% showed that the application designed to have a good performance for display results, and its access value of 60%, indicating that the process related to responsiveness between users is appropriate both using PC / Tablet / Mobile
한국 현대사를 활용한 한국 문화 교육 내용 구성 연구

This study examined the necessity of Korean history education as part of Korean culture education. The study selected Korean contemporary history as the contents of history education for Korean language learners by analyzing preceding studies and surveys. Teaching Korean contemporary history to foreign students can satisfy the significance and usefulness that is the principle of content selection of Korean culture education. It can also satisfy the content selection criteria mentioned in history education—whether the content is applicable to solving the present problem and whether the content is relevant to me. This paper selected 8 contents of contemporary history education that can be used in the form of special classes at universities or language schools, referring to the study of Korean history education and high school textbooks of modern and contemporary history. Studying Korean contemporary history will allow foreign learners to gain a deeper understanding of the current issues in Korean society and of the Korean people.
Experiences with the Introduction of AI-based Tools for Moderation Automation of Voice-based Participatory Media Forums

Voice-based discussion forums where users can record audio messages which are then published for other users to listen and comment, are often moderated to ensure that the published audios are of good quality, relevant, and adhere to editorial guidelines of the forum. There is room for the introduction of AI-based tools in the moderation process, such as to identify and filter out blank or noisy audios, use speech recognition to transcribe the voice messages in text, and use natural language processing techniques to extract relevant metadata from the audio transcripts. We design such tools and deploy them within a social enterprise working in India that runs several voice-based discussion forums. We present our findings in terms of the time and cost-savings made through the introduction of these tools, and describe the feedback of the moderators towards the acceptability of AI-based automation in their workflow. Our work forms a case-study in the use of AI for automation of several routine tasks, and can be especially relevant for other researchers and practitioners involved with the use of voice-based technologies in developing regions of the world.
A Survey of Pre-Service Teachers ICT’s Competencies in Papua

This research analyzes the ICT Competencies of Pre-services Teachers in Papua, including the Region of Sorong, Merauke, Jayapura, and Manokwari. This research aims to discover the students of Teachers' Training Faculty spread in Papua competencies on ICT. The measurement of ICT competencies is carried out using a model developed by Tondeur for preservice teachersusing questionnaires that consisted of 19 items. Questionnaires were distributed to Papua Region covering Jayapura and Merauke, West Papua region covering Sorong and Manokwari. Sixty-eight respondents became the data in this study. Data were analyzed using XL Stats to find the mean and standard deviation. The findings in this study were; the low competencies were found on Papuan Indigenous Pre-service teachers, and the high competencies were found in science discipline compared to non-science in Papua and West Papua Indonesia. The low ability of native Papuan students in managing information in the digital world is indicated by the lack of awareness of preservice teachers in developing a sense of responsibility in using ICT as a communication medium and activities involving ICT use.
Data Mining Menggunakan Algoritma K-Nearest Neighbor Dalam Menentukan Kredit Macet Barang Elektronik

Business is an activity that is routinely carried out by many people, one of the promising businesses is a business that provides the needs of electronic goods to meet the needs of daily life, high demand causes business people to be more careful and selective in seeing the pattern of customers who want perform transactions in order to avoid business risks appropriately. Business people use a credit system to increase sales for a long time, but the obstacle that often occurs is that many customers who use credit services often delay payments to make the company's finances unstable so someone needs to predict someone who has the potential to do bad credit for electronic goods. using a system that helps business owners to make it easier to process data and predict patterns of bad credit for electronic goods that have been formed from previous data using the KNN algorithm approach, so that the results show the closeness of the value to the data of old customers, both those who pay properly and those who make payments in default and it can be obtained that the processing process accelerates data processing with precise results in the problem solving process
Amazon lifts mask requirement for fully vaccinated warehouse workers

Amazon will lift its mask requirement for warehouse workers effective Monday, the ecommerce giant announced.
LibGuides: University of Limpopo Library Technical Services: Collection Arrangement: University of Limpopo (UL.) Library

The Library Technical Services lib-guide aim to promote library services and facilitate access to materials for users within University of Limpopo (UL), its satellite campuses, and the world. Locating library materials on the shelves
QUALIFYING YOUTH FOR THE LABOR MARKET AND MECHANISMS FOR FINANCING YOUTH EMPLOYMENT IN CITIES IN THE MIDDLE EAST AND NORTH AFRICA REGION ... WITH EXPOSURE TO THE EXPERIENCES OF CAIRO AND ALEXANDRIA

Young people hope for tomorrow and makers of the future, and young people are distinguished by tremendous but caged energies looking through to convert that energy into real, tangible production that contributes to pushing the rates of economic, social and political development. Young people in the cities of the Middle East and North Africa region suffer from families of unemployment and poverty that threaten social security and also threaten the path of development of all kinds. It is the responsibility of the municipalities of cities in the Middle East and North Africa region, the governments and the private sector as well to fulfill their duty towards young people who represent an important qualitative and numerical segment of the population. And training them and equipping them with the necessary skills required in the labor market, as well as undertaking projects that ensure the employment of young people to ensure their inclusion and make them participate in making their present and future. During the following chapters, the researcher reviews pictures, programs, and projects to rehabilitate young people for the labor market and employ them in order to present a model or mechanisms that contribute to reducing or eliminating youth unemployment, as well as submitting proposals for activating youth rehabilitation and employment programs.
Decentralized Stock Market using Blockchain

The conventional stock market platform possesses vulnerabilities such as high transaction costs, centrally managed governance which is vulnerable to attacks, lack of market transparency activities and methodologies, third party intervention and an unreliable environment. Blockchain is a technological breakthrough that is rapidly evolving the digital world by providing a new perspective on system security, adaptability, and efficiency. It provides a safe and secure means of exchanging any form of goods, service, or transaction. The presented blockchain-based implementation addresses the inadequacies of the centralized stock market infrastructure by verifying the authenticity of user’s holdings, imposing self-enforced smart contracts and achieving democratic and precise execution and agreement decisions by consensus mechanisms. Thus replacing the need for a centralized authority which preserves the credibility of the stock exchange process. The solution is validated by executing a model in Ethereum. This contributes to a reduction in overall transaction costs owed to brokers and central authorities.
Teacher�s Strategies to Overcome Students� Difficulties When Implementing Time Token Arends Method in Learning Speaking English

This study concerned with the teacher�s strategies in learning speaking English. This research is focused on how the teacher overcomes the students� weaknesses in learning speaking English when implementing Time Token Arends method. By using a descriptive qualitative research within a teacher of MA Al-Bairuny as a subject of its research found that: (1) the student had difficulty in inhibition such as: difficulty in starting to speak because of being worried of making mistakes, difficulty in answering the question from the teacher, and they felt nervous and shy to speak in front of the class. (1) The teacher used �Look in the Face� strategy to overcome the difficulties; (2) the teacher used �Communication� strategies to overcome the students� difficulties in nothing to say, such as: students had no idea to speak, student got difficulty to express what he wanted to speak, and student had no bravery to express their thought; (3) the teacher used �Interdependence� strategies to overcome the students� difficulties in un-event participant; (4) the teacher used �Responsibility� strategies to overcome students� difficulties in mother tongue used, such as: students felt easier for communication each other using Java Language, so they ignored the teacher�s instruction for speaking English; (5) then, after the learning process, teacher made a schedule for this group to evaluate their teamwork process in order to give them motivation and evaluation. Thus, the students� improvement on their speaking skill has been the aim of the research.
Multicultural education: Reflection on the Best Practice of successful teachers in schools

The current study aims to identify the performance and criteria of the success of outstanding teachers in the field of multicultural education. To this reason, qualitative research and the method of the best practice have been used as the basis of the research and semi-structured interview were used to collect data and to analyze qualitative content for analyzing data. In order to use the best practice method, four stages including plan, search, observation and collect and analysis were implemented. The number of successful teachers in multicultural education in 2014-2015 included 5 people who were interviewed by all teachers in a semi-structured interview. The interviews were conducted by the teachers on the paper and analyzed using the content analysis method. Findings show that 14 key points in the success of teachers in multicultural education played an important role. Tips like teachers 'positive attitudes toward diversity and differences and similarities, the use of speech and speech styles of students at home and their culture in classroom conversations, continuous communication with students' parents, recognition of the multiple identities of students and the development of language, their historical and cultural knowledge in class, the living environments of students outside of school.the living environments of students outside of school.
Designing an Online Achievement Test for General English Classes

Over the past few years, there has been a growing interest in utilizing technology in language education. It is due to the rapid development of ICT (Information and Communication Technology) which deploys computers, smartphones, and the Internet. These technological advances also have a great impact on language tests and assessment. Gradually, „traditional tests‟ such as paper-based tests, have been replaced by so-called online tests. In terms of practicality and test administration, online tests appear to be more practically administered as the test takers do not need to prepare paper and pencils or other stationery to do the test. In addition, earlier studies on online tests reported that they affect students‟ learning in a better way such as improving students‟ retention. Thus, the present study attempts to propose a design of an online achievement test specifically devised for students of general English classes at a private university. A test was devised then 16 teachers were involved to try it out and they completed a questionnaire to give feedback on the test and to give their opinion on online and paper-based tests. The findings indicate that 13 teachers preferred the online test to the paper-based test due to its efficiency and practicality.
Modelling a subregular bias in phonological learning with Recurrent Neural Networks

A number of experiments have demonstrated what seems to be a bias in human phonological learning for patterns that are simpler according to Formal Language Theory (Finley and Badecker 2008; Lai 2015; Avcu 2018). This paper demonstrates that a sequence-to-sequence neural network (Sutskever et al. 2014), which has no such restriction explicitly built into its architecture, can successfully capture this bias. These results suggest that a bias for patterns that are simpler according to Formal Language Theory may not need to be explicitly incorporated into models of phonological learning.
HOW MACHINE LEARNING METHOD PERFORMANCE FOR IMBALANCED DATA

This study will examine the application of several classification methods to machine learning models by taking into account the case of imbalanced data. The research was conducted on a case study of classification modeling for working status in Banten Province in 2020. The data used comes from the National Labor Force Survey, Statistics Indonesia. The machine learning methods used are Classification and Regression Tree (CART), Naïve Bayes, Random Forest, Rotation Forest, Support Vector Machine (SVM), Neural Network Analysis, One Rule (OneR), and Boosting. Classification modeling using resample techniques in cases of imbalanced data and large data sets is proven to improve classification accuracy, especially for minority classes, which can be seen from the sensitivity and specificity values that are more balanced than the original data (without treatment). Furthermore, the eight classification models tested shows that the Boost model provides the best performance based on the highest sensitivity, specificity, G-mean, and kappa coefficient values. The most important/most influential variables in the classification of working status are marital status, education, and age.
Review on Workflow Scheduling in Cloud Environment: A Comprehensive Study

For enterprise application development, cloud computing is going to new-fangled paradigm that meets the needs of today's enterprises and helps them efficiently executing workflows in business and scientific applications. Workflow applications often require a very intricate runtime environment that is hard to create and maintain. Thus, cloud infrastructure is valued as an implementation platform for positioning technical workflows with features such as on-demand provisioning, scalability, reproducibility and resilience. To schedule multiple workflows in the cloud, we need to design the workflow before scheduling it. Therefore, in this paper we review the diverse work done by researchers for the workflow design as well as workflow scheduling.
Drafting Copyright Exceptions: From the Law in Books to the Law in Action. By Emily Hudson. [Cambridge University Press, 2020. xxv + 380 pp. Hardback £95.00 ISBN 978-1-107-04331-2.]

Drafting Copyright Exceptions: From the Law in Books to the Law in Action. By Emily Hudson. [Cambridge University Press, 2020. xxv + 380 pp. Hardback £95.00 ISBN 978-1-107-04331-2.] - Volume 80 Issue 2
Multi-objective Evaluation Software Algorithm for Timbre

This paper first studies the universal standards of subjective timbre evaluation in vocal music performance, and then discusses how to quantify and code these standards to input into intelligent objective evaluation software. This paper briefly describes the working principle and implementation method of the core algorithm in the software, as well as the final test results. The core of this paper is to establish the relationship between subjective evaluation and machine objective evaluation, so that the intelligent evaluation results of vocal music can meet the subjective evaluation standards, so as to further promote the accuracy and practicability of the intelligent evaluation system of vocal music.
NI-UDA: Graph Adversarial Domain Adaptation from Non-shared-and-Imbalanced Big Data to Small Imbalanced Applications

We propose a new general Graph Adversarial Domain Adaptation (GADA) based on semantic knowledge reasoning of class structure for solving the problem of unsupervised domain adaptation (UDA) from the big data with non-shared and imbalanced classes to specified small and imbalanced applications (NI-UDA), where non-shared classes mean the label space out of the target domain. Our goal is to leverage priori hierarchy knowledge to enhance domain adversarial aligned feature representation with graph reasoning. In this paper, to address two challenges in NI-UDA, we equip adversarial domain adaptation with Hierarchy Graph Reasoning (HGR) layer and the Source Classifier Filter (SCF). For sparse classes transfer challenge, our HGR layer can aggregate local feature to hierarchy graph nodes by node prediction and enhance domain adversarial aligned feature with hierarchy graph reasoning for sparse classes. Our HGR contributes to learn direct semantic patterns for sparse classes by hierarchy attention in self-attention, non-linear mapping and graph normalization. our SCF is proposed for the challenge of knowledge sharing from non-shared data without negative transfer effect by filtering low-confidence non-shared data in HGR layer. Experiments on two benchmark datasets show our GADA methods consistently improve the state-of-the-art adversarial UDA algorithms, e.g. GADA(HGR) can greatly improve f1 of the MDD by \textbf{7.19\%} and GVB-GD by \textbf{7.89\%} respectively on imbalanced source task in Meal300 dataset. The code is available at https://gadatransfer.wixsite.com/gada.
BERT Embeddings for Automatic Readability Assessment

Automatic readability assessment (ARA) is the task of evaluating the level of ease or difficulty of text documents for a target audience. For researchers, one of the many open problems in the field is to make such models trained for the task show efficacy even for low-resource languages. In this study, we propose an alternative way of utilizing the information-rich embeddings of BERT models with handcrafted linguistic features through a combined method for readability assessment. Results show that the proposed method outperforms classical approaches in readability assessment using English and Filipino datasets, obtaining as high as 12.4% increase in F1 performance. We also show that the general information encoded in BERT embeddings can be used as a substitute feature set for low-resource languages like Filipino with limited semantic and syntactic NLP tools to explicitly extract feature values for the task.
Compressed Sensing Based on Tensor Network Machine Learning

We introduce the scheme of compressed sensing based on tensor-network machine learning, which enables to compress and communicate information through the generative tensor-network states.The state Ψ is first obtained by unsupervised learning of tensor network, which characterizes the set of training images.With Ψ and a small amount of pixels from a specific image that is to be sent, one can obtain a projected state Ψ , from which the whole sent image can be reconstructed.The key problem of selecting pixels from a specific image is solved by investigating the entanglement in the state Ψ .