Reviewerly/exHarmony huggingface dataset:
The Relationship Between Education and Agricultural Productivity: The Moderating Effect of NGO

The importance of education on all aspect of human endeavor is incontestable as education plays a significant role in human and economic development of a nation.Many studies around the globe have proved that education is the most potent tool in poverty reduction effort.This is because as the level of education increases the probability of becoming poor also reduces.The purpose of this study is to examine the moderating effect of NGO on the relationship between education and agricultural productivity in Katsina State Nigeria.The study adopted a quantitative method by using questionnaire as the instrument for data collection.A total of 430 questionnaires was distributed to the respondents from the six-local government of the state and 410 were returned accounting for 95 percent rate of return and 400 screened questionnaires was used for further analysis.Partial Least Square-Structural Equation Modelling PLS-SEM was used as data analysis tools.The major finding of the study indicated that, there exists positive relationship between education and agricultural productivity and NGO also moderate the relationship between education and agricultural productivity.Conclusively this study revealed that education is a viable mechanism for improving agricultural productivity.This study suggested that, government at various level should partner with NGO in bringing about development, especially of the rural areas.This study has contributed to the literature in development studies as this study is the first to introduce NGO as a moderating variable in development study.
Multi-label segmentation of bone, muscle, and fat in CT volumes via convex relaxation

The segmentation of bone, fat and muscle tissue in CT volumes is of special interest for surgeons and radiologists in order to diagnose some diseases and/or in surgery planning. These tissues are very difficult to delineate due to the presence of multiple and different structures and the similarity in terms of Hounsfield values with surrounding organs. In this paper, an automatic algorithm to implement the segmentation of bone, muscle and fat tissue is shown. The segmentation is carried out by minimizing an energy function via convex relaxation. In previous works carried out by the authors, only two labels had been considered (bone and muscle) and the methods had strong problems to segment skeletal muscle accurately due to the presence of internal organs with Hounsfield values similar to those within muscle tissue. In the present work, prior knowledge about the distribution of skeletal muscle in abdominal, chest and pelvis CT volumes has been considered by including a binary distance transform in the computation of the cost terms. Furthermore, a third label corresponding to fat tissue has been included in the segmentation. A public database has been used to assess the performance of the algorithm. Different metrics such as DICE, Jaccard, specificity, sensitivity and Positive Predictive Value (PPV) indexes have been obtained to evaluate the algorithm performance The technique has been compared with a previous multi-label scheme, a Hybrid level-set model implementation and a thresholding algorithm. The algorithm proposed outperformed the other methods in all the metrics considered.
Tractable Learning of Sparsely Used Dictionaries from Incomplete Samples

In dictionary learning, we seek a collection of atoms that sparsely represent a given set of training samples. While this problem is well-studied, relatively less is known about the more challenging case where the samples are incomplete, i.e., we only observe a fraction of their coordinates. In this paper, we develop and analyze an algorithm to solve this problem, provided that the dictionary satisfies additional low-dimensional structure.
Prediction System of Police Officer Admissions Number using Analysis of Variance Method

Police officer admission attracts people to be able to contribute for their country.There could be many youths who want to participate on it.Based on that number, we believe that a prediction system about the admission of police officer is important to notice a decent candidate.This research generated a prediction system to find out how many police officers are received at each year.The object of this research is the North Sumatra Police Chief.This study used the ANOVA method, that is a two-way ANOVA procedure which is classified using statistical product and service solutions (SPSS) version 16 to determine the admission of prospective police officers from year to year.Supporting factors in the recruitment of prospective police officers is the ability of intelligence candidates to be seen from year to year.
STUDENTS’ ANXIETY IN SPEAKING ENGLISH AT SECOND SEMESTER OF ENGLISH STUDY PROGRAM AT UNIVERSITY OF PASIR PENGARAIAN

Anxiety is uncomfortable feeling that someone feels in facing any situation. Anxiety is common problem in speaking especially to learners.The purpose of the research was to find out the factors and the types of students’ anxiety in speaking at second semester students of English study program at University of Pasir Pengaraian. This research was design a descriptive qualitative research and instrument that the researcher used in collecting the data is questionnaire. The sample of the research were 15students. The finding result of the research showed, there were 14 students classified into state anxiety, and 1 students classified into trait anxiety. So the most of second semester students were classified into state anxiety.This result was taken from open-ended questions.
Attributes, Vestments, Context and Inscription in the Identification of Nubian Paintings: Proposing the ‘Multi-Layer’ Image Recognition Method

The aim of this paper is to present a method that enables identification of Nubian paintings whose tituli have not been preserved or are incomplete. This method is reminiscent of the laborious piecing together of mosaics from scattered and incomplete tesserae. The attributes, vestments or contexts are such tesserae, which taken into consideration together enable the composing of a mosaic, piece by piece. Some interpretations of the paintings were made during excavations, without time for deeper analysis. Identifications created in this way have become so merged with the images, and then repeated frequently, that it was very difficult to change them and introduce a new perspective on already widely accepted opinions. In this article, I have focused on a few select examples that show how one can identify individual paintings, but also how one can fall into the trap of too easy comparisons and attributions. A scholar studying Nubian art has to be cautious as its iconography is sometimes so original that it cannot be easily compared to Byzantine or any other cultural patterns.
The Study of the phenomenon of the youth subculture and its place in the cultural and educational environment of the Russian higher education institution

The article considers the youth subculture from the position of its place in the cultural and educational environment on the example of universities in Tyumen. The authors concluded that the concept of subculture accumulates a certain system of values and attitudes inherent in this or that isolated social community, as well as their ways of behavior and life styles. In the process of analysis it was determined that there was a positive attitude towards youth subcultures in universities. At the same time, the educational environment of universities is not always able to accept the diversity of youth subcultures. In this regard, the authors proposed some areas of interaction between universities and youth subcultures - the introduction of trendy elective courses in the educational space, the development of technical creativity through the maker culture, strengthening the health of students through the introduction of sports subcultures, etc.
Terminological discrepancies in the field of software testing: A case of mistake, error, bug, defect, fault, and failure in the specialist language of IT

Terminological discrepancies in the field of software testing: a case of mistake, error, bug, defect, fault, and failure in the specialist language of ITThe article seeks to arrive at a proper understanding of the most challenging words in the field of software testing, i.e., mistake, error, bug, defect, fault, and failure. The paper presents a semantic analysis of the words, for non-English practitioners of IT find it difficult to discriminate between them. The article is based on native English texts such as dictionaries, blog posts, software testing manuals and the like in order to ensure linguistic reliability and better understanding of the terms. The meaning of selected terms is compared by means of standard dictionaries and those dedicated to IT practitioners. Moreover, a theoretical overview of terminological issues in IT is conducted.
SMMS: Document Management in Agile Model for Software Maintenance

Study shows that most challenging task in software development life cycle is software maintenance, because all of changes made must documented for future used. Thus, an efficient and newest documentation is vital in software maintenance to ensure its activities will not jeopardized. However, this is not as we thought. The popular models such as agile development has ruined the importance of maintenance tasks in software development life cycle. The agile models focused only on verbal communication within development team to provide faster development where the information of the product and its features exists within the heads of the developers but any changes will not documented in a design document. Therefore, the major problem of Agile models is the absence of latest documentation and this issue supposed not exist in software maintenance which is depend on previous documentation. Thus, our aim is to add document management in agile model for software maintenance processes. The result shows that our concept is successful and useful for software maintenance.
THE FORMATION AND DEVELOPMENT OF MEDIA LITERACY OF STUDENTS AS AN IMPORTANT TASK IN STUDENT SCIENTIFIC CIRCLE’S WORK

The article briefly analyzes the changes in the interpretation of the term content of media literacy according to the modern tasks of Ukrainian higher education. Besides, the prediction of further development of media literacy as a competence is made, and five main principles of media literacy, concerning scientific messages, are interpreted. Short guidelines of these principles are given and they are based on the discussions of the student scientific club’s meetings.
KLASIFIKASI PEMINJAMAN BUKU MENGGUNAKAN NEURAL NETWORK BACKPROPAGATION

Book lending is a form of service provided by the library.Borrowing is very closely related to inventory.In library A in determining the inventory of books, library staff has difficulty in determining what types of books are needed by students.Where the determination of the number and type of books has not used a definite calculation system, only based on the estimated number of students and courses of each study program.Therefore a classification of borrowing types of books is needed based on student book lending transactions, the data used in this study were 269,116 from 2014 to 2019 months 6.The types of books processed were 184 types of books from 1700 types of books, the first step carried out perform forecasting techniques to predict the target inventory of each type of book in the following year, the second stage of the book lending transaction data is processed to determine the classification of book types using neural network backpropagation.Obtained the results of the error rate or MSE of 0.021, using hidden layer 9 and the activation function tansiq with epoch 2000, with the recommended number of book types recommended for restocking as many as 86 types of books with the number of predictions in each type of book.The third stage is to test the data validation to determine the level of classification and prediction errors, the last step is a regression test that shows a significant correlation of 0.006 with the data variables being tested namely prediction, classification and target data.The results of this study can provide book type recommendation data.along with the number of predictions in each type of book needed in the coming year using the neural network backpropagation method with an accuracy rate of 95.5%.
Multi-formalism Models for Performance Engineering

Nowadays, the necessity to predict the performance of cloud and edge computing-based architectures has become paramount, in order to respond to the pressure of data growth and more aggressive level of service agreements. In this respect, the problem can be analyzed by creating a model of a given system and studying the performance indices values generated by the model’s simulation. This process requires considering a set of paradigms, carefully balancing the benefits and the disadvantages of each one. While queuing networks are particularly suited to modeling cloud and edge computing architectures, particular occurrences—such as autoscaling—require different techniques to be analyzed. This work presents a review of paradigms designed to model specific events in different scenarios, such as timeout with quorum-based join, approximate computing with finite capacity region, MapReduce with class switch, dynamic provisioning in hybrid clouds, and batching of requests in e-Health applications. The case studies are investigated by implementing models based on the above-mentioned paradigms and analyzed with discrete event simulation techniques.
СТРУКТУРНО-ТИПОЛОГІЧНІ ОСОБЛИВОСТІ ПЕРЕХОДУ ДРУКОВАНИХ ВИДАНЬ ДОНЕЧЧИНИ В МЕРЕЖУ

&lt;div&gt;&lt;p&gt;&lt;em&gt;In the course of the study, the theoretical foundations of the work were specified using a descriptive method. The monitoring method was used to capture and perform an initial analysis of the data obtained from the sites and printed versions of the newspaper’s, as well as to collect the material required to disclose the topic of the material. The method of comparison allowed us to establish the similarity and difference between indicators and definitions. The traditional methods of analysis and synthesis, as well as the structural method, have been used to summarize and systematize the data obtained.&lt;/em&gt;&lt;/p&gt;&lt;/div&gt;&lt;p&gt;&lt;em&gt;At this point in the scientific discourse on the theme of the digital transformation of newspapers critical lacks conceptual works. We can assume that this is due to the changing trends of digital development, which make it difficult to develop a common vision and common understanding of theoretical approaches to the problem.&lt;/em&gt;&lt;/p&gt;&lt;p&gt;&lt;em&gt;We have identified and confirmed the following trends:&lt;/em&gt;&lt;/p&gt;&lt;p&gt;&lt;em&gt;– reducing the frequency of certain print media (the publication is becoming weekly)&lt;/em&gt;&lt;/p&gt;&lt;p&gt;&lt;em&gt;– reduction in the number of newspapers;&lt;/em&gt;&lt;/p&gt;&lt;p&gt;&lt;em&gt;– readership of publications is diverse, but remains unchanged (information, advertising and general political prevail editions)&lt;/em&gt;&lt;/p&gt;&lt;p&gt;&lt;em&gt;– creation of special online versions to support traditional print media (integration of traditional media with the Internet)&lt;/em&gt;&lt;/p&gt;&lt;p&gt;&lt;em&gt;– advantages of the sites over the printed version;&lt;/em&gt;&lt;/p&gt;&lt;p&gt;&lt;em&gt;– active introduction of the use of social networks in the activities of the media of Donetsk region.&lt;/em&gt;&lt;/p&gt;&lt;p&gt;&lt;em&gt;It was found that the example of successful application of the strategy «print-first» (first on paper) are the newspapers «Priazovskiy rabochiy» and «Sobytiya». While the newspaper «Znamya industrii» differs with the transition to the model «convergent-first» (initially convergence).&lt;/em&gt;&lt;/p&gt;&lt;p&gt;&lt;em&gt;The article discusses the structural and typological changes in the print media of the Donetsk region during the transition to the network and identifies the development trends of print media on the network from 2012 to 2019.Media transform more and more under the influence of time, so regional print media require popularization, transformation and integration of web spaces to meet the needs of the audience.&lt;/em&gt;&lt;/p&gt;&lt;p&gt;&lt;strong&gt;&lt;em&gt;Key words:&lt;/em&gt;&lt;/strong&gt;&lt;em&gt; &lt;/em&gt;&lt;em&gt;online edition; online media; network media; informational portal; print mass-media; print site; social media; social network.&lt;/em&gt;&lt;/p&gt;
A Perspective Evaluation of Group Work in English Language Classroom

This paper provides insights into how Jordanian university students perceive their experiences in learning English through group work activities. A total of 55 students of Mutah University who learn English as a preparation for their TOEFL examination took part in this quantitative study which was carried out in the first semester of the 2019 academic year. The respondents are from different majors, such as Business Administration and International Relations. Data were collected through three sets of questionnaires with a 5 point Likert scale which focused on the learner perspectives regarding the use of group work for English language learning, the student-peer collaboration, and the student-teacher collaboration involved in the group work activities. Descriptive statistics involving frequency counts and percentage were used to analyze the data. The findings revealed that the majority of the students had positive views regarding the use of group work for language learning. They were also satisfied with the collaboration with their peers and the teacher throughout the group work activities. However, in comparison, the student-peer collaboration is perceived as less positive than the student-teacher collaboration. This study concludes that group work is favoured by the students but for the group work to be successful, their collaborative skills need to be improved.
Improving Text Summarization Using Latent Semantic Analysis

Text Summarization is a method of generating a shorter version of the given document using natural language processing that enables the users to quickly identify the major points of a document. Text summarization aims at getting the most symbolic content in a system in a compact form from given document while it retains the semantic information of text to a large extent. It is considered to be an effective way of attempting the information and solves the problem of presenting information in more condense form. There are different approaches to produce well defined form of summaries and one of the modern methods is Latent Semantic Analysis. Though the available information about any topic is large and incredible, so there is a need for rapid view of those articles to determine accordance of the article as per user’s wish. In this paper, the successive way of summarizing the text document by involving the sequence of the techniques and its evaluation using rouge scores was engaged. The SVD plays an important role in separating important sentences from input document. Every sentence is enabled with rank based on its importance in original document. Sentence selection is done based on their ranks and the summary generated. The rouge will produce three distinct scores as, Recall, Precision and F-score. The F-score is considered for evaluating the correctness of summary. The observation of three distinct summaries by reducing input document by 1/2nd, 1/3rd, 1/4th rouge scores and f-score is found to provide the effective results in summarizing the text document.
Combining active learning and graph-based semi-supervised learning

The scarcity of labeled data is a common problem in many applications. Semi-supervised learning (SSL) aims to minimize the need for human annotation combining a small set of label data with a huge amount of unlabeled data. Similarly to SSL, Active Learning (AL) reduces the annotation efforts selecting the most informative points for annotation. Few works explore AL and graph-based SSL, in this work, we combine both strategies and explore different techniques: two graph-based SSL and two query strategy of AL in a pool-based scenario. Experimental results in artificial and real datasets indicate that our approach requires significantly less labeled instances to reach the same performance of random label selection.
Penerapan Algoritma C4.5 Untuk Klasifikasi Penempatan Tenaga Marketing

Marketing is a job that has a scope of work to market a product. Marketing is at the forefront of the company. The problem that often occurs in companies is not having a reliable marketing force. The problem arises because the process of accepting new marketing is still not done professionally. This happens because there is no systematic standard method to assess the feasibility of marketing candidates. Therefore it is necessary to analyze the marketing placement so that it can determine the feasibility of a new marketing placement problem. Through the results of the analysis of new marketing placements, it can be seen whether the marketing candidates passed or did not qualify. Of the problems that exist testing the data mining classification method to find out the algorithm to predict marketing feasibility is to use an algorithm that is C4.5. After testing with the C4.5 algorithm the results obtained are that the C4.5 algorithm produces an accuracy value of 91.10% and an AUC value of 0.921 with a diagnosis level of Excellent Classification. So that the conclusion C4.5 algorithm is a good algorithm to be applied to the feasibility of marketing placement. Keywords : Marketing Feasibility, Data Mining, C4.5
Hubungan Efikasi Diri Dan Kecemasan Dengan Motivasi Belajar Pada Mahasiswa

Purpose: to determine the relationship of self-efficacy and anxiety with learning motivation. Methodology: quantitative type with analytic design and cross sectional approach. Results: respondents in this study were 123 respondents, the distribution of the highest learning motivation variables with moderate learning motivation levels (69,9%), while for the highest self-efficacy variables with high self-efficacy levels (97.6%) and for variables anxiety is highest with moderate anxiety level (57,7%). The results of correlation analysis on learning motivation variables with self-efficacy obtained P 0,000 and the results of the correlation coefficient r 0.527. While the results of correlation analysis on variables Motivation learning with Anxiety obtained P 0.025 and the results of the correlation coefficient r -0.203. Conclusion: there is a relationship between self-efficacy and anxiety with learning motivation.
An Efficient Algorithm for Informational Retrieval using Web Usage Mining

Retrieval of information from the database and web log files is a very time consuming process.There are many techniques and models to retrieve data from the web.There are two types of data available on the web i.e. structured and unstructured.If data is structured then retrieval of information is an easy task.Otherwise, firstly apply the algorithm to unstructured data and then models will be applied.Vector space and Boolean models are used for IR.In this paper, we compare both Boolean model & Vector Space model techniques to retrieve data from the web (log files) and proposed a new algorithm based on time, frequency, memory consumption, etc.