Reviewerly/exHarmony huggingface dataset:
INTERNET RESOURCES FOR QUALIFICATION UPGRADE, SCIENTIFIC, EDUCATIONAL AND PROFESSIONAL ACTIVITIES

Objective. The article aims to familiarize with online resources, useful to librarians, scientists, teachers, and students. Methods. Overview of online resources for distance learning, qualification upgrade, scientific, educational and professional activities. Results. The description and characteristics of Internet resources for scientific, educational and professional activities is given. Conclusions. Distance learning is an important component of continuous professional development, a convenient modern format of professional improvement. The advantage of distance learning is the opportunity to learn at a convenient time and in any place. The use of modern Internet tools (including author identifiers) in your activities opens up new opportunities.
Improving the performance of graph database queries using linear algebra operations

The application of graph databases to different domains is gaining momentum. The Resource Description Framework (RDF) is one of the data models supported by graph databases, and SPARQL is the standard query language for RDF graphs. These databases are also known as RDF triplestores. Many triplestores are implemented over the relational data model, using tables to store graphs and translating SPARQL queries into SQL queries, and this approach can lead to unnecessary overheads. On the other hand, in the context of High- Performance Computing (HPC), implementations over hybrid hardware platforms using Numerical Linear Algebra (NLA) operations have become an effective and efficient computing strategy in the last decade. In particular, Graphics Processing Units (GPUs) have been adopted to perform general-purpose computations due to their high performance, reasonable prices, and an attractive relationship between computing capacity and energy consumption. In the context described above, this paper presents an initial study on the efficient implementation of a set of SPARQL queries in terms of NLA operations. Additionally, we evaluate the performance of implementing these operations on GPUs.
Wrapper Classes

In this chapter, you will learn: the wrapper classes in Java and how to use them, how to get primitive values from strings, how boxing and unboxing works in Java.
Deutsch’s Algorithm

In Part 1 of this book, you learned about some of the theoretical concepts of quantum computing, and in Part 2, you got acquainted with Microsoft Q#, a quantum programming language and simulator. Actual quantum algorithms, and, as an extension on that, quantum programs, are hard to invent and write. Firstly, you need a very specific problem to solve, and secondly, you need to think of a process that can leverage quantum properties to solve your problem.
Hybrid Scheduling Strategy in Cloud Computing based on Optimization Algorithms

As a platform for offering on-demand services, cloud computing has increased in relevance and appeal. It has a pay-per-use model for its services. A cloud service provider's primary goal is to efficiently use resources by reducing execution time, cost, and other factors while increasing profit. As a result, effective scheduling algorithms remain a key issue in cloud computing, and this topic is categorized as an NP-complete problem. Researchers previously proposed several optimization techniques to address the NP-complete problem, but more work is needed in this area. This paper provides an overview of strategy for successful task scheduling based on a hybrid heuristic approach for both regular and larger workloads. The previous method handles the jobs adequately, but its performance degrades as the task size becomes larger. The proposed optimum scheduling method employs two distinct techniques to select the suitable VM for the specified job. To begin, it enhances the LJFP method by employing OSIG, an upgraded version of the Genetic Algorithm, to choose solutions with improved fitness factors, crossover, and mutation operators. This selection returns the best machines, and PSO then chooses one for a specific job. The appropriate machine is chosen depending on several factors, including the expected execution time, current load, and energy usage. The proposed algorithm's performance is assessed using two distinct cloud scenarios with various VMs and tasks, and overall execution time and energy usage are calculated. The proposed algorithm outperforms existing techniques in terms of energy and average execution time usage in both scenarios.
Appendix 1: Measurement of dynamics in aerial manoeuvres

Book DOI: 10.1049/SBRA518E Chapter DOI: 10.1049/SBRA518E_appendix1 ISBN: 9781785613890 e-ISBN: 9781785613906
Generating Entertaining Human-Like Sokoban Initial States

Procedural content generation (PCG) has been an effective strategy to quickly meet the demands of users waiting for new game boards, characters, objects, environment, narrative, etc. One feature of relevance in automated generators is the credibility of the generated content—that it produces content susceptible of being confused with human-created content. In this study, we propose an offline PCG method for generating credible initial Sokoban states, that are also entertaining for players. For this, we propose a hybrid PCG approach, combining an ad-hoc heuristic for generating base Sokoban boards with an evolutionary algorithm for positioning elements on it. We then evaluate the boards created through a user study. Results demonstrate that the proposed hybrid PCG approach is capable of generating content that is indistinguishable from human-made game boards while also being entertaining to play. The implemented PCG approach is an example of the use of evolutionary algorithms in the search for new content. Its controllability via the objective function and constraints of the optimization model, makes it suitable for generating content that meets the requirements of game designers.
Blazor State Management

Blazor is used to build Single-Page Applications and has a stateful programming model, meaning that a Blazor application keeps its state in memory, as long as the user does not refresh the browser. Refreshing the browser will restart your Blazor application, losing all state in memory. How can you keep the application’s state? In this chapter, we will look at how your application can manage its state and pass data between pages, browser tabs, and even different browsers. Some of these techniques we have been using before, and we will also look at building complex Blazor applications using the redux pattern.
Informed Universal Differential Equations for Symbolic Identification of Parasitic Effects on a real Cart-pole System

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

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Iterator

Whenever you start working with complicated data structures, you encounter the problem of traversal. This can be handled in different ways, but the most common way of traversing, say, a vector is using something called an iterator.
Implementation of Rapidchain on BaaS to improve Blockchain efficiency

The challenge of scalability faced in blockchain has acquired huge traction recently. Even though there are several ways possible to estimate scalability of a blockchain network such as number of channels or number of peers or the consensus protocol etc. In this paper, ‘number of transactions’ has been used as the factor to measure scalability. In the context of the aforementioned introduction, ‘Sharding’ is one of the techniques which has capability to increase multifold transactions which can be processed and thus holds promising potential to enhance scalability of the blockchain network. Sharding technique basically sub-groups the overall network of blockchain in to different components called as committees or shards where each shard or the committee works on different batches of the transactions. The intention of this paper is to elucidate a way of implementing Rapidchain protocol to maximise resiliency for securing shards along with increase in number of transactions. The aforementioned optimization will have result of increasing the efficiency of the blockchain and at the same shall preserve the characteristic of decentralization also. In addition to enhancing scalability and transaction rate, optimising energy consumption for transactions validation by using Hyperledger integration with BaaS void of ‘mining’, are also the major focus points of this paper.
Intake

OpflowVolume 47, Issue 10 p. 2-2 Departments Intake First published: 09 December 2021 https://doi.org/10.1002/opfl.1613Read the full textAboutPDF ToolsRequest permissionExport citationAdd to favoritesTrack citation ShareShare Give accessShare full text accessShare full-text accessPlease review our Terms and Conditions of Use and check box below to share full-text version of article.I have read and accept the Wiley Online Library Terms and Conditions of UseShareable LinkUse the link below to share a full-text version of this article with your friends and colleagues. Learn more.Copy URL Share a linkShare onFacebookTwitterLinked InRedditWechat No abstract is available for this article. Volume47, Issue10December 2021Pages 2-2 RelatedInformation
Cost Matrix Algorithm for Cloud VM Migration

Cloud computing is one of the trending technologies on the market today. Many physical machines host lots of virtual machines, present in a cloud-based data Centre run various enormous services and applications. Because of the strategy that promotes and uses in cloud technology. Cloud-to-Cloud (C2C) migration enables businesses to move between different cloud environments without having to redo their overall structure. During the C2C migration, many virtual machines (VMs) are migrated from one cloud computing environment to another. A Cloud Service Provider must monitor, assess, and govern the load balance for servers while VMs are transferred. It demonstrates the need of considering VM migration as a critical activity. In this Paper the Proposed algorithm will migrate the system to a cloud data center with an efficient cost based on the different parameters like the Memory, CPU, etc.,
CBR Based Emergency Disposal Plan Establishment

In the process of railway operation, equipment faults are inevitable; however, establishing emergency disposal plans manually is time-consuming, which may affect the efficiency and safety of railway operation. With lots of on-site historical emergency disposal cases, this paper introduces an assistant decision-making model based on CBR (Case-based Reasoning). A case database based on the case representation is constructed by keywords extracted from text files. The location information is used to perform case screening. Then, the attribute similarities of the detailed information can be obtained through similarity calculation. Meanwhile, the AHP (analytic hierarchy process) is used to obtain the weight vector of each attribute to calculate the case similarities to obtain the most similar case. According to the most similar emergency disposal plan, combined with the train diagram, the emergency disposal plan for the current fault is automatically established, which can reduce the time of establishment and execution.
Revisiting countability of English in terms of learnability

AS Parrot (2010) points out, acquiring countability of nouns is the core of grammar on nouns. But IL (interlanguage) learners have difficulty in acquiring the countability (Celce-Murcia & Larson-Freeman, 1999; Cowan, 2013). To cope with this problem, based on semantic features presented by Aarts (2018) and Fromkin, Rodman & Hyams (2014), this study proposes ‘a system of countability on nouns’ in order to distinguish countable from uncountable nouns, which consists of 3 semantic features, [±countable]/[±abstract]/[±amorphous]. The system tells us that countable nous have [+countable]/[-abstract]/[-amorphous], whereas uncountable nous have [-countable]/[+abstract]/[+amorphous]. Also, it shows us that the conversion of countability can be accounted for by assigning converted or reversed values to the 3 semantic features.. In a sense, the system could be said to be a ‘linguistic sense’ to the distinction between countable and uncountable nouns. To activate this sense, this study suggests ‘5 viable criteria’ for specifying the system to teaching in practice, and a kind of consciousness raising tasks (CR tasks) for applying it to the classroom. In conclusion, the system, the 5 viable criteria, and the CR tasks will be enhancing learnability for IL learners in acquiring the countability as well as teachability for teachers in teaching it.
Memory-less discrete Gaussian sampler on FPGA

The work presented in this paper aims to develop and to implement on FPGA a memory-less discrete Gaussian sampler in the context of lattice-based cryptography. The memory-less characteristic of the proposed sampler arises from the need to integrate Lattice-Based Cryptography schemes in constrained devices. The rejection method is chosen because it offers the possibility to design a sampler that does not need any precomputed table. The implemented hardware architecture enables us to generate discrete Gaussian samples for any given standard deviation without using any precomputed tables.
The Effect of Project Management on Long-term Project Performance: Forecasting Construction Engineering Industry

최근 건설프로젝트는 대형화, 복잡화되고 있으며 다수의 개별 사업들이 종합적으로 연계된 복합사업으로 발주되는 경우가 증가하고 있는 추세여서 프로젝트 수행의 위험도는 증가하고 있고 프로젝트 관리역량 부족으로 손실이 발생되고 있는 실정이다. 이러한 상황속에서 프로젝트의 성과를 달성하기 위해서는 체계적이고 전문적인 프로젝트 관리가 필요하다는 인식이 대두되고 있다. 본 연구는 프로젝트를 기반으로 하는 건설엔지니어링 산업에서 프로젝트 관리가 단기적 프로젝트 성과와 장기적 프로젝트 성과에 미치는 영향과 단기적 프로젝트 성과가 기업의 장기적 프로젝트 성과에 미치는 영향을 검증하였다. 그 결과, 첫째, 계약관리와 리스크관리가 단기적 프로젝트 성과에 영향을 미치는 것으로 나타났다. 둘째, 계약관리 및 멀티프로젝트관리가 장기적 프로젝트 성과에 영향을 미치는 것으로 나타났다. 셋째, 단기적 프로젝트 성과는 장기적 프로젝트 성과에 미치는 것으로 나타났다. 본 연구를 통해 건설엔지니어링 기업의 장기적인 프로젝트 성과 및 목표달성을 위해서는 체계적인 프로젝트 관리의 필요성을 증명하고, 이를 통해 프로젝트 관리의 표준화와 글로벌 경쟁력을 확보하여 부가가치가 높은 PM 시장 진출에 일조하고자 한다.In recent years, construction projects are increasing in complexity and size, and the number of projects that are comprehensively linked complex projects is increasing; therefore, the risk regarding project implementation is increasing&#8212;consequently, the loss caused by the lack of project management capabilities of engineers is also increasing. In this situation, there is a growing perception that systematic and professional project management is necessary to ensure strong project performance, that is, project management is essential for ensuring that project completion criteria are fulfilled. This study verified the effect of project management on short- term project performance and long-term project performance in the project-based construction engineering industry, and the effect of short-term project performance on long-term project performance of companies. Consequently, first, this study revealed that contract and risk management affect short-term project performance. Second, this study showed that contract and multi-project management influence long-term project performance. Finally, this study revealed that short-term project performance influences long-term project performance. Thus, this study proved that systematic project management is necessary for ensuring strong performance of long-term projects and goal achievement of construction engineering companies; thus, project management enhances the global competitiveness of these companies, facilitating their entry in the high value-added PM market.
Current Status and Implications of Doctoral Dissertations Related to Writing in Korea

이 논문은 국내 대학의 글쓰기 관련 박사학위논문의 현황을 분석하고, 이를 바탕으로 시사점을 도출하는 것을 목적으로 한다. 이를 위해 학술연구정보서비스(RISS)를 통해 수집한 211편의 박사학위논문을 대상으로 SPSS 26과 R 프로그램을 활용하여 통계분석과 텍스트마이닝을 실시했다. 분석 결과, 글쓰기 관련 박사학위논문은 2005년 이전까지는 21편에 불과했으나, 2006∼2010년에는 55편, 2011∼2015년에는 83편으로 대폭 증가하였다. 또한 글쓰기 관련 박사학위논문은 다양한 학문 분야에서 발표되었음을 확인할 수 있었다. 이때 세부 주제는 주로 글쓰기 교육과 관련된 것이며, 글쓰기 치유나 디지털 시대의 글쓰기 특성 등을 다룬 연구들도 등장했다. 이러한 분석 결과를 통해 도출한 시사점은 크게 두 가지다. 첫째, 글쓰기 교육 방법 이외에 글쓰기 인지 과정과 원리 등과 같은 글쓰기 이론을 깊이 있게 탐구하는 연구가 이루어져야 한다. 둘째, 글쓰기는 융합 연구 분야로서의 토대를 갖추고 있으므로 다양한 학문 분야와의 융합 연구가 이루어질 필요가 있다. 이 연구는 박사학위논문으로 연구 대상을 한정하여, 글쓰기 연구자의 배출 현황을 살펴볼 수 있었다는 점에서 의의가 있다. 이에 이 연구가 이후 글쓰기를 학위논문의 주제로 삼고자 하는 연구자들에게 주요한 기초 자료로 활용될 수 있기를 기대해 본다.The purpose of this study is to analyze the current status of doctoral dissertations related to writing at domestic universities and to suggest implications based on them. To this end, statistical analysis and text mining were conducted using SPSS 26 and R program on 211 doctoral dissertations collected through the ‘Research Information Sharing Service(RISS)’. As a result of the analysis, there were only 21 writing-related doctoral dissertations until 2005, but the number increased significantly to 55 between 2006 and 2010, and 83 between 2011 and 2015. In addition, it was confirmed that the doctoral dissertations related to writing were published in various academic fields. At this time, detailed topics were mainly related to writing education, and other studies dealing with writing healing and writing characteristics in the digital age also appeared. There are two major implications drawn from these analysis results. First, in addition to teaching methods of writing, research should be conducted to deeply explore writing theories such as writing cognitive processes and principles. Second, since writing has a foundation as a field of convergence research, it is necessary to conduct convergence research with various academic fields. This study is meaningful in that it was possible to examine the current status of writing researchers by limiting the research subject to a doctoral dissertation. Therefore, it is expected that this study can be used as a major basic data for researchers who want to make writing the subject of their thesis.
An Exhaustive Survey on Automatic Text Summarization Using Machine Learning Approches

Automatic Text Summarization (ATS) is the key challenge in the area of Natural Language Processing (NLP). It deals with generalizing a summary from a given text without losing the vital information. This is a contemporary area because of exponential content growth in internet and applied in summarizing the content available in books, newsletters, internal document analysis, patent research, e-learning etc. Various machine learning approaches are used in order to achieve the performance of human-generated summaries. The system fails to perform at few areas like checking grammatical errors and paraphrasing the sentences after the summary creation. This work provides a brief view on methods and approaches used in ATS.
An Integrated Method for Large Deformable Registration of Brain Images

Large deformable registration of brain images is essential for a variety of clinical imaging applications. State-of-the-art diffeomorphic registration methods, such as large deformation diffeomorphic mapping (LDDMM), have high computational complexity and often require pre-processing to account for large, global displacements or rotations. In this paper, we present an integrated method that fuses landmark-based thin-plate splines (TPS), patch-based B-spline and partial differential equation (PDE) based registrations synergistically to achieve improved accuracy and efficiency for large deformable registration of brain image. Landmark-based TPS and patch-based B-spline were used for global affine transformation followed by deformable registration using LDDMM. The anatomical discrepancies between the source and target images were significantly reduced after TPS and B-spline based registration. As a result, the PDE based deformable registration could be done efficiently and effectively. The performance of the proposed method has been evaluated using simulation and real human brain image data, which provided more accurate registration than spline or PDE-based methods. Moreover, the computational efficiency of our method was significantly better than PDE-based methods. The proposed method may be useful for handling large deformable registration of brain images in various brain imaging applications.
Classification

Let’s begin with a common class of problems called classification problems. A classification problem requires you to infer/predict the class/category to which a new observation belongs based on values of some observed attributes. For example, infer whether a mail is “spam” or “regular” based on the body of the mail, sender’s email address, etc.; infer whether a digital payment transaction is “fraud” or “non-fraud” based on the details of the transaction like the location of the transaction, the amount and mode of payment, etc.
Top-Level Synsets in the RuWordNet Thesaurus

This paper describes one verification method for RuWordNet, the Russian language thesaurus (lexical ontology). Top-level synonymic sets, i.e., synonymic sets for which there are not hypernyms, are considered. It is shown that many of them do not represent generic terms and, therefore, the RuWordNet structure must be more specific. 5 general strategies are described for introducing new synonymic sets and/or semantic relations to fill the gaps detected. The strategies are based on an analysis of the structure of phrases and use information from dictionaries. This paper has also specifically exemplified how to implement the strategies.
“THANK YOU, IT REALLY MAKES MY DAY”: COMPLIMENT RESPONSES REVISITED

Complimenting is a typical speaking act and the method in which it is responded to can vary based on the culture of the speakers as well as the influence of other circumstances. The purpose of this study was to provide a more in-depth knowledge of compliment response research based on how it is used by university students learning EFL in everyday life. Furthermore, this study also aims at finding out if exposure to another culture affects university students learning English as a second language while responding to compliments. The data were garnered using data elicitation method by complimenting the participants’ look, possession, character, or aptitude. The finding found that the participants used ten types of responses; listed from the most frequently used type of compliment responses to the least used type of compliment responses: Comment Acceptance (8), Appreciation Token (2), Comment History (2), Question (2), Praise Upgrade (1), Reassignment (1), Return (1), Scale Down (1), Disagreement (1), and Qualification (1). According to the data, the majority of students in an international English literature class at Brawijaya University are likely to accept the compliments. Students tend to take compliments by thanking them and then making related comments. English-speaking countries consider a simple "thank you" to be an adequate response to a praise. This present study also confirms that short term encounterance with foreign culture exposure slightly affect EFL learners’ way of responding to compliments. This shows that the students learn the English language culture in terms of compliment.
Ethereum

The Bitcoin blockchain model has proved to be a paradigm valid for cryptocurrencies, so as to spread interest and study about blockchain in various fields of application.