Reviewerly/exHarmony huggingface dataset:
Quality of Education as a Factor of University Competitiveness

The strategic orientation of any modern educational organization is to achieve competitive advantages in the market of educational services. The competitiveness of the university is directly dependent on the quality of its educational services. Evaluation of the quality of education, in turn, goes to such concepts as the rating of the university and its accreditation. Discussion of this area of higher education is actively conducted in the academic community, but its research, especially in the realities of the digital economy, is insufficient, which makes this publication relevant. The purpose of the study is to identify the actual features of achieving high competitiveness in the conditions of digital transformation by a domestic university. To do this, it is necessary to analyze the existing experience of Russian higher education in terms of responding to the challenges of digital transformation and develop recommendations for achieving high quality education in modern conditions. The research methodology is based on the theoretical foundations of professional education and the competitiveness of Russian universities. The article analyzes the domestic and international experience in assessing the quality of education, while proving that the main criterion for assessing the competitiveness of a university is the quality of learning outcomes. Methods of comparative analysis, observation and generalization are used. The study proves that modern Russian higher education does not always adequately respond to the challenges and opportunities of digital transformation. A number of systemic problems hindering the achievement of high quality of modern higher education are identified. The necessity of combining the introduction of innovative technologies of the educational process with the preservation of the advantages of traditional education is confirmed. Promising directions of constructive interaction of the university with the most important stakeholders of higher education – employers are proposed.
The Gaia Explorer, a Powerful Search Platform

Abstract After two years of development, the GAIA Explorer is now ready to assist Geoscientists at Total! This knowledge platform works like a little Google, but with a focus solely on Geosciences - for the time being. The main goal of the GAIA Explorer is to save time finding the right information. Therefore, it is particularly useful for datarooms or after business acquisitions to quickly digest the knowledge, but also for feeding databases, exploration syntheses, reservoir studies, or even staff onboarding specially when remote working. With this additional time, Geoscientists can focus on tasks with added value, such as to synthesize, find analogies or propose alternative scenarios. This new companion automatically organizes and extracts knowledge from a large number of unstructured technical documents by using Machine Learning (ML). All the models relie on Google Cloud Platform (GCP) and have been trained on our own datasets, which cover main petroleum domains such as geosciences and operations. First, the layout of more than 75,000 document pages were analyzed for training a segmentation model, which extracts three types of content (text, images and tables). Secondly, the text content extracted from about 6,500 documents labelled amongst 30 classes was used to train a model for document classification. Thirdly, more than 55,000 images were categorized amongst 45 classes to customize a model of image classification covering a large panel of figures such as maps, logs, seismic sections, or core pictures. Finally, all the terms (n-grams) extracted from objects are compared with an inhouse thesaurus to automatically tag related topics such as basin, field, geological formation, acquisition, measure. All these elementary bricks are connected and used for feeding a knowledge database that can be quickly and exhaustively searched. Today, the GAIA Explorer searches within texts, images and tables from a corpus (document collection), which can be made up of both technical and operational reports, meeting presentations and academic publications. By combining queries (keywords or natural language) with a large array of filters (by classes and topics), the outcomes are easily refined and exploitable. Since the release of a production version in February 2021 at Total, about 180 users for 30 projects regularly use the tool for exploration and development purposes. This first version is following a continuous training cycle including active learning and, preliminary user feedback is good and admits that some information would have been difficult to locate without the GAIA Explorer. In the future, the GAIA Explorer could be significantly improved by implementing knowledge graph based on an ontology dedicated specific to petroleum domains. Along with the help of Specialists in related activities such as drilling, project or contract, the tool could cover the complete range of upstream topics and be useful for other business with time.
Denoising of Biomedical Images Using Two-Dimensional Fourier-Bessel Series Expansion-Based Empirical Wavelet Transform

Image denoising is a kind of image enhancement, which is an initial step for biomedical image processing and analysis. The motivation for denoising is that an enhanced image provides more accurate analysis, interpretation, and classification. In this chapter, order-zero and order-one two-dimensional Fourier-Bessel series expansion-based empirical wavelet transform (2D-FBSE-EWT) methods are used with a wavelet thresholding approach to denoise images. Order-zero and order-one 2D-FBSE-EWT methods are variants of 2D-EWT that use the order-zero and order-one Fourier-Bessel series expansion (FBSE) spectrum instead of the Fourier transform (FT) spectrum. In a wavelet thresholding approach, adaptive thresholds are estimated for each sub-image coefficient, followed by hard thresholding of the coefficients. After thresholding of coefficients, all modified sub-images are added to get a denoised image. Peak signal-to-noise ratio is used as a performance measure parameter. For analysis purposes, three biomedical images, fundus, mammogram, and skin images, with additive white Gaussian noise of standard deviations 10, 20, 30, and 40 are used. The results of order-zero and order-one 2D-FBSE-EWT methods are then compared with the result of the 2D-empirical wavelet transform (2D-EWT). The order-zero 2D-FBSE-EWT provided better performance as compared to order-one 2D-FBSE-EWT and 2D-EWT methods.
An LFG analysis of AANN constructions

This chapter examines the construction exemplified in the title, consisting of the singular determiner <italic>a</italic> followed by an adjective, a numeral, and a plural noun (abbreviated as AANN). Building on work by Dalrymple and King (2019), Hristov captures the syntactic structure and functional properties of this construction by assuming a standard NP analysis at constituent-structure, coupled with concord and index agreement within the NP at functional-structure. It is proposed that the numeral, which acts as a modifier, agrees with the plural concord of the head noun, while the determiner proper (the article) is exceptionally allowed to agree with the N′ string <italic>staggering ten dissertations</italic> in terms of index (singular when a single-unit reading is available). Thus, without altering the formal apparatus of LFG, this proposal has the advantage of explaining a number of previously unexplained contrasts and of being able to cover a wide range of related constructions.
Wavelets

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A corpus-based analysis of linguistic difficulty of the CSAT English section under absolute grading

The present study was designed to examine the extent to which the difficulty level of the College Scholastic Aptitude Test (CSAT) English section under the absolute grading system appropriately reflects the difficulty level of the National Curriculum. Moreover, it aimed to investigate whether the CSAT English section maintains the same level of difficulty each year since the introduction of absolute grading into the English section. To achieve these goals, the study conducted a corpus-based analysis of the linguistic difficulty among High School English textbooks and CSAT reading passages (collected from 2015 to 2020). The results showed that the difficulty level of the CSAT reading passages under absolute grading was much higher than that of High School English textbooks. It was also revealed that the English sections of the CSAT under absolute and relative grading were almost identical in terms of linguistic difficulty. No significant difference was found among the difficulty levels of the three CSAT English sections under the absolute grading system (2018, 2019, 2020). The findings of the study shed some light on the implementation of the absolute grading policy and its ability to achieve its intended purpose of normalizing public education.
Challenges of Non-functional Requirements Extraction in Agile Software Development using Machine Learning

Current developments in Requirement Engineering methods have seen mutation resulting from the use of machine learning algorithms to resolve several complex Requirements Engineering problems.One of these problems is the identification and classification of non-functional requirements in the requirements documents.Machine basedlearning techniques for this challenge have been shown hopeful outcomes than traditional natural language processing approaches.However, there is still lacking of a systematic understanding these machine learning approaches.Despite the fact that non-functional requirements are critical to a software project's success, there is still no accords about what they are and how we will elicit, document, and validate them.Thus, the important task of Requirements Engineering is to properly extract non-functional requirements records from requirement files and arrange them into categories.However, this task is waste of time and prone to errors.This paper presents nonfunctional requirements importance, relates them to the process of software development and identifies its challenges and current area of research.
The Complete Collections Assessment Manual: A Holistic Approach

"The Complete Collections Assessment Manual: A Holistic Approach." Technical Services Quarterly, 38(4), pp. 452–453
SYSTEM FOR ANALYSIS, RESEARCH AND FORECAST OF EVENTS IN DISCRETE TIME DATA SEQUENCES

This paper is devoted develop software for time series forecasting using Python programming language. SARIMA model was used to develop the system.
A corpus based comparative study on the high-stakes tests in Asian EFL countries: Korea, China, and Vietnam case

Abundant corpus research has been conducted in analyzing the contents of Korean CSAT and related textbooks. Yet, those studies only abound in the Korean context. A comparative study on the EFL CSAT within a similar Asian region has been much scarcer. Thus, this study aims to investigate the detailed contents of the high-stakes tests in Korea, China, and Vietnam based on readability, syntactic complexity, and subject matter by using a corpus. The results showed that the readability level of both FRE and GFI after conducting ANOVA indicated that Korean CSAT has the highest difficulty of readability compared to China and Vietnam. However, on the FKGL measure, a study found no significant readability differences among the three countries. By having a high-difficulty text level on some readability measures, Korean CSAT seemed to contain more syntactic complexities on T-unit complexity ratio in subordination and complex nominals per T-unit in particular structure, and several other measures indicated in this study. All three countries used difficult to more difficult subject matters on their high-stakes test. The results are discussed in terms of implications for readability level, syntactic complexity, and subject matter of the English CSAT among three different EFL countries.
Ensemble Learning

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Scalable Graph Neural Networks

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The Impact of Government Spending on Economic Diversification for the Period (2004-2019) and its Reflection on the Path of Rehabilitation of the Iraqi Economy

The research aims to measure and analyze the relationship between government spending and economic diversification in Iraq for the period (2004-2019), using the ARDL model. The research concluded that there is a long-term positive equilibrium relationship between investment spending and economic diversification in Iraq. When investment spending increases by (1%), this will lead to an increase in economic diversification by (0.23%), assuming that operating spending is stable, and the opposite happens in the case of decline. In addition to the existence of a long-term inverse equilibrium relationship between operating spending and economic diversification in Iraq, as an increase in operating spending by (1%) will lead to a decrease in economic diversification by (0.73%), assuming the stability of investment spending, and the opposite will happen in the event of decline.
Locking and Latching

Different databases have different ways of doing things (what works well in SQL Server may not work as well in Oracle), and understanding how Oracle implements locking and concurrency control is absolutely vital to the success of your application. This chapter discusses Oracle’s basic approach to these issues, the types of locks that can be applied (DML, DDL, and latches), and the problems that can arise if locking is not implemented carefully (deadlocking, blocking, and escalation).
Speech Scrambling based on Particle Swarm Optimisation

Securing any communication system where important data may be transmitted through the channel is a very crucial issue. One of the good solutions in providing security for the speech is to use speech scrambling techniques. The chaotic system used in security has properties that make it a good choice for scrambling speech signal and the optimisation algorithm can provide a perfect performance when used to enhance the hybrid of more than one method. In this paper, we suggest a system that uses an optimisation method, namely, particle swarm optimisation. The evaluation measures prove that the output of the optimisation method has better performance among the methods used in the comparison, including chaotic maps and hybrid chaotic maps.
TECHNIQUES, STRATEGIES AND CRIME PREVENTION APPROCHES FOR CRIME REDUCTION IN NIGERIA

The primary role of the government is to provide safety and security of members of the society and must ensure that this particular constitutional mandate is achieved. Holistic measures are required to address crime and insecurity that is prominent in all communities in Nigeria. Crime prevention is a proactive activities and synergies between government, criminal justice system and the other role players. These activities are geared towards prevention and reduction of crime and fear of crime. It is crucial to identify root causes of crime and disorderly events, thereafter, develop crime prevention strategies and plans to address and reduce crime and its potential consequences. The paper focuses on the evaluation of strategies and approaches adopted by the criminal justice system and law enforcement in addressing crime in Nigeria communities. The study adopted qualitative methodology. Interview technique was used to collect data from carefully selected participants. Finding reveals that crime prevention includes all activities which reduce, deter, or prevent the occurrence of crime, cooperation with the community is mandated in the form of community policing, sector policing in addressing issues like poverty and unemployment through government’s redistributions strategy, criminal justice officials are not implementing crime prevention approaches effectively. Recommendation includes; specialized training for police and partners involved in crime prevention, educate role players and partners on the implementation of effective crime prevention approaches, techniques and strategies, crime problem must be addressed from the grass-root, need to recognize crime victims, the environment, the predisposing and precipitating factors that led to crime, when developing plans and intervention, need to adopt technology in the fight against crime and crime prevention.
Record Management System with Document Control

The primary purpose of this study was to provide a new way of keeping and retrieving documents in a digital form available in the Records Office and a computerized leave management system modified for the employees of Northern Iloilo Polytechnic State College Estancia, Iloilo. Specifically, this paper sought to design and develop the Record Management System with Document Control and evaluated its level of usability and performance as perceived by the target users. A total of 165 respondents of the said institution participated in the study which includes the five experts for School Year 2016-2017. The data were gathered through a survey questionnaire that primarily solicited feedbacks from respondents using the International Standard Organization/International Electrotechnical Commission 9126 Model. Descriptive research design was employed to describe the observations of the respondents based on the set objectives. The results revealed that the functionality of the system product, the level of usability as well as its performance were all interpreted as “Very Good”. This significant result implied that the respondents were impressed by the system features of the developed system in a convenient way.
A proposal of metrics for software development based on the ISO/IEC 29110 standard

Nowadays, very small entities have a large presence in the software industry in any country where on average they represent 94% (+/− 3%). Therefore, these types of companies have the need to implement quality models and standards. In this context, a standard oriented to these environments has been created: ISO/IEC 29110. This has made it possible to provide good practices to increase the quality of software products and services. However, quality should not only be qualitative but quantitative through the use of metrics. Therefore, this article proposes metrics for software development based on the ISO/IEC 29110 standard. To validate the proposed metrics, a project submitted by a software development company to obtain certification in 2020 was analyzed.
Israel

In Israel, there are no effective media accountability instruments. Media ownership patterns and a complex regulatory system put the media at the mercy of politicians and tycoons who own the main print and broadcast channels. The lust for media control by the longest-serving Prime Minister, Benyamin Netanyahu, led to political turmoil and drastically affected journalists’ freedom of expression. Independent online journalists carry the torch of media accountability in what is viewed as an alternative media. The lack of strong financial backing leads to their minimal impact. The Israel Press Council (IPC) is a voluntary body that is financially supported by private media owners and is expected to monitor the journalistic ethics of their supporters. The IPC has no enforcement powers and plays a very minor role as a media accountability instrument. The Israeli courts are the preferred arena for ethical disputes but are often used by politicians to threaten journalists in a phenomenon known as media freezing effect.
Designing MALL Environments

This chapter explores the concept of design in MALL. Design can take place at multiple levels, starting with the larger learning environment, to the digital artefacts that are used by learners, and the design of tasks for using the artefacts within the given environment. Some of the key models of general design of the learning environment, artefacts and tasks are provided with examples of how they relate directly to MALL. The complexities of designing assessment are also discussed. The chapter concludes with fundamental guidelines to bear in mind when designing MALL and outlines a list of principles for the successful implementation of mobile devices in language teaching and learning contexts.
GitOps Insights

Deploying and managing Kubernetes clusters is only a part of the life cycle of running Kubernetes clusters even when spread across multiple clouds. You also will need to deploy and run your applications on Kubernetes. This is a critical aspect of a Kubernetes life cycle, and this is because the real value Kubernetes brings to the business is through the applications running on it.
Development of a New Service Encounter Manual: The Case of A-Dutyfree Shop in Korea

The purpose of this case study is to develop a new service encounter manual for A-Dutyfree Shop. The process is based on the following steps: review the existing service encounter manual which was developed in 2013, evaluate the moment-of-truth monitoring system, survey customer satisfaction trends, and analyze the voice of customers. The project lasted for about four months (March 26-July 27, 2020) by a task force with 17 members (3 external consultants, 2 A-dutyfree shop trainers, and 12 A-dutyfree shop managers or sales managers). The project deployed five activity steps: (1) analysis of the current situation, (2) new concepts development, (3) prototyping, (4) testing and operations, and (5) documentation and follow-through management. During the project process, two work-shops were held with a subject matter expert to refine the draft manual, while reflecting the opinions of service employees as much as possible. The standard behaviors and guidelines for each step of the service encounter process were refined, best practices of service encounters for each sales area with its unique characteristics were shared, the manual was documented, and possible solutions were provided for continuous improvement of follow-on management. The results of this study provide valuable information for successful service encounters that can be effectively adopted by managers and employees in many similar service organizations.
Random Forests Using PySpark

This chapter will focus on building random forests (RFs) with PySpark for classification. It would also include hyperparameter tuning to find the best set of parameters for the model. We will learn about various aspects of ensembling and how predictions take place, but before knowing more about random forests, we must cover the building block of random forests, which is a decision tree. A decision tree can also be used for classification/regression, but in terms of accuracy, random forests do a better job at predictions due to various reasons, which we will cover later in the chapter. Let’s start to learn more about decision trees.