Reviewerly/exHarmony huggingface dataset:
Perancangan Aplikasi Secure Message Berbasis Smartphone (Studi Kasus Di Dinas Komunikasi Dan Informasi Kabupaten Takalar)

This study aims to develop software by building a secure message application based on a smartphone or android. This application was developed using a prototyping model. The prototyping model consists of several stages: the first stage, namely the gathering of needs, the second stage of building prototyping, the third stage of coding the system, the fifth stage of testing the system. The results obtained in this study are an Android-based secure message application that can improve performance for anyone who uses an Android-based smartphone. For testing using blackbox, whitebox and expert validation, this application is suitable for use
PENGEMBANGAN ONTOLOGI TUJUAN WISATA BALI DENGAN PENDEKATAN KULKUL KNOWLEDGE FRAMEWORK

Bali is one of the small islands in Indonesia that known as an international and national tourists destination. Many of Information related to tourist destinations in Bali is scattered and fragmented available on the Internet. This causes many of the potential tourists who want to find information related to tourist destinations in Bali to have to visit one site to another to aggregate the information. Besides, much of the information available on the Internet is human-readable but not for computer applications, and this becomes a challenge for computer applications to aggregate existing information. This study aims to develop an ontology model in the domain of Bali's tourism destinations by adopting the kulkul knowledge framework (Tri Hita Karana and Kala Patra Village) in which this ontology as a backbone of the semantic web can be utilised by computer-based applications to manipulate existing information for user needs. In this study, initial testing is done regarding the proposed ontological model by providing a set of questions that are commonly used by users when accessing information about tourism destination. So, it is expected that the propose ontology model will be able to provide information on tourism in Bali systematically.
FULL-TEXT RESOURCES OF THE PROJECT TYPE CREATED IN THE PRESIDENTIAL LIBRARY OF THE OFFICE OF THE PRESIDENT OF THE REPUBLIC OF AZERBAIJAN AS AN INNOVATIVE RESOURCE TYPE OF ELECTRONIC LIBRARY

One of the main issues addressed in this article is the use of new library information technologies and automation processes in libraries.For the first time in the history of library work in the country, topical issues, large-scale tasks and tasks in this area are examined in detail.The State Program emphasizes the problem of updating the libraries of the republic, raising them to the level of the most modern electronic libraries in the world, and the Presidential Library was noted as the executor of many tasks.The article analyzes the activities of the Presidential Library of the Administrative Department of the President of the Republic of Azerbaijan in the field of new technologies, the creation of an electronic library and provides a brief overview of the created innovative full-text resources of the project type in this library.
Model for deriving benthic irradiance in the Great Barrier Reef from MODIS satellite imagery: erratum

Corrections for equations in our recently published paper [ Opt. Express 27 , A1350 ( 2019 ) ] are presented.
Teachers' Perception of the Use of ICT in Foreign Language Teaching at a Higher Education Institution

The objective of this paper is to analyse and present the attitude of language teachers of a private higher education institution towards the use of ICT in the process of teaching foreign languages.Furthermore, the aim of the paper is to find out if teachers believe they have the skills and abilities necessary for the implementation of ICT tools.For this purpose, the authors have designed a questionnaire in order to examine if foreign language teachers feel motivated and prepared to implement new technologies as an integral part of their lectures.The results show a positive attitude of foreign language teachers regarding the incorporation of ICT tools in their classes, though they do not state that ICT tools are mandatory and/or essential in the language classroom.The research results also indicate that teachers use both traditional and ICT methods, which they find to be a perfect combination.These research results are very similar to the results of the previous research conducted by the same authors, but from students´ perspective, regarding the usage of ICT tools in foreign language classroom.
Text correction algorithms for correct grammar and lexical errors in the English language

The main objective of this study is to focus precisely on the discussion of the English language algorithms in the direction of grammar and lexical correction errors algorithms.The utilization of the language web-search engine has exploded in its popularity and its potential applications.The majority of search engine algorithms use error detection, which typically is not limited to a particular native language.Thus, the syntax of English web search queries, the problem was identiied by automatic speech recognition systems.In an algorithm that takes on corrections for second language learners, a new approach was introduced.In this study, the algorithm proposed will take an input sentence with a preposition error and replaces it with the correct preposition that would relate to this speciic sentence.This is based upon a rule-based and statistical approach, making it a hybrid made up of two different phases.This proposed algorithm will be useful for students, educators, and scholars.
How (Not) to Find Bugs: The Interplay Between Merge Conflicts, Co-Changes, and Bugs

Context: In a seminal work, Ball et al. [1] investigate if the information available in version control systems could be used to predict defect density, arguing that practitioners and researchers could better understand errors "if [our] version control system could talk". In the meanwhile, several research works have reported that conflict merge resolution is a time consuming and error-prone task, while other contributions diverge about the correlation between co-change dependencies and defect density. Problem: The correlation between conflicting merge scenarios and bugs has not been addressed before, whilst the correlation between co-change dependencies and bug density has been only investigated using a small number of case studies-which can compromise the generalization of the results. Goal: To address this gap in the literature, this paper presents the results of a comprehensive study whose goal is to understand whether or not (a) conflicting merge scenarios and (b) co-change dependencies are good predictors for bug density. Method: We first build a curated dataset comprising the source code history of 29 popular Java Apache projects and leverage the SZZ algorithm to collect the sets of bug-fixing and bug-introducing commits. We then combine the SZZ results with the set of past conflicting merge scenarios and co-change dependencies of the projects. Finally, we use exploratory data analysis and machine learning models to understand the strength of the correlation between conflict resolution and co-change dependencies with defect density. Findings: (a) conflicting merge scenarios are not more prone to introduce bugs than regular commits, (b) there is a negligible to a small correlation between co-change dependencies and defect density-contradicting previous studies in the literature.
Human resources policy in relation to cybernetic security in Slovak medium and small companies

Due to a mass penetration of information technologies into all business processes, researches in area of IS/IT field within medium and small companies has gained on significance. With the aim to acknowledge the status of information safety in the environment of Slovak medium and small companies a research has been carried out, which focused on identifying: threats on information systems; methods for treating information safety; and major obstacles in implementation of secure and safe policy. Within this research a special part was dedicated to companies’ human resources policy in relation to cybernetic security. The research separately focused on staff provisioning in area of IS/IT. It surveyed who and on what position is responsible for this field, what requirements should be fulfilled by such people, which knowledge is the most valued and which they miss. The second area we focused on, was the organization of the security policy in relation to all employees, but mainly to users of information systems. The research was performed in the years 2008, 2012, 2015 and 2017 and the results about human resources are presented in this article. The respondents were company owners, managers and specialists form IS/IT field.
Measurement error of spatial frequency response based on sinusoidal Siemens Star

In recent years, sinusoidal Siemens stars have been widely used as a method of measuring spatial frequency response (SFR). Previous researches pointed out that incorrect recognition of the Siemens star center could result in errors in SFR measurement, and these errors are more significant at high frequencies. To reduce the errors, this paper proposed two methods to correct the center of Siemens star. By calibrating various Siemens star centers with the proposed methods, it is found that both the two methods are highly consistent, with a difference of no more than 2 pixels.
Association Rule Model of On-demand Lending Recommendation for University Library

University library that is connected to the Internet is more convenient to search, but the huge amount of data is not convenient for users who lack a precise target.In this study, the traditional association rule algorithm was improved by a Bayesian algorithm, and then simulation experiment was carried out taking borrowing records of 1000 students as examples.In order to verify the effectiveness of the improved algorithm, it was compared with the traditional association rule algorithm and collaborative filtering algorithm.The results showed that the recommendation results of the improved association rule recommendation algorithm were more relevant to students' majors, and the coincidence degree of different students was low.In the objective evaluation of the performance of the algorithm, the accuracy, recall rate and F value showed that the personalized recommendation performance of the improved association rule algorithm was better and the improved association rule algorithm could recommend users with the book type that they need.
Best Practices for Software Development: A Systematic Literature Review

Software process standardization is crucial for organizations dedicated to software development in order to produce quality products on predictable schedules consistently. For this matter, the adoption of best practices is an essential factor in the standardization processes. However, best practices tend to be described as common sense, opinions, or casual advice and are poorly formalized and documented. Thus, it is important to know the state-of-the-art in the field of best practices in software development and their identification. Here we report the conduction of a systematic literature review (SLR) that aims to identify (a) what best practices are, (b) what are their distinctive characteristics; (c) which methods, techniques or strategies are used to identify them, and (d) how their performance is evaluated. From a total of 24 primary studies selected, we identified seven different definitions of best practice in software development, two best practice classification schemes based on their characteristics such as name, definition, stakeholders, and context. Besides, we found one method, three strategies, and five techniques used for best practice identification and two methods to evaluate their performance as separate entities in the software development life cycle. The results of this SLR will help in the identification and evaluation of best practices for a software development organization that aims to standardize their processes.
Segmenting geochemical records using hierarchical probabilistic models

Abstract Geochemical records of drill cores can be complex and multi-variate. We address the problem of automatically classifying collections of sequential geochemical data. Our approach uses a change-point analysis based on a probabilistic explanation of the binary segmentation method. Change-points, which separate geochemical data into segments of self-similar trends, are accepted only if they increase the global probability of the data set. Increased model complexity is penalised by an Occam factor that offsets improvements in explaining the data trends. Therefore, simpler models are preferred. The method is insensitive to unequally spaced samples in the geochemical records, negating the need to interpolate data for missing values. Probability analysis requires an estimation of variance in the measured data which affects our ability to detect change-points. Extension of change-point analysis to multiple variables in geochemical data sets is straightforward. Typical classification schemes only segment geochemical data into regions that are explained by constant models: we extend our analysis to include models where chemical concentrations change linearly with depth. The recursive application of the binary segmentation algorithm generates hierarchical models that can be used to classify geochemical records over a variety of distance scales. We provide a clear explanation of the development of the mathematics of change-point analysis with binary segmentation and demonstrate its utility with a suite of examples. We compare our results to published classification methods, and provide two examples of classification on data sets from peat bogs and drill core. In one example we detect linear trends in concentrations of Ti, Cr, and Zr that would not be detected with other methods.
EXAMINING INTERCULTURAL COMPETENCIES AMONG BOSNIAN HIGH SCHOOL STUDENTS

A period of globalisation and the interconnectedness of people across the world has increased the demand for greater intercultural competences among young people in particular. Being interculturally competent entails modifying behaviour in culturally appropriate ways when establishing contact with diverse cultures. The development of this competence is a long and never-ending process that which is influenced by a variety of factors, some of the most important being school policies, surroundings, individual work, personal needs and curiosity. The purpose of the current study was to investigate the impact of grade level, grade point average (GPA) and gender on intercultural competences by distributing the questionnaire developed by Portalla and Chen (2010) to 211 Bosnian high school students. The results showed that the students’ grade levels and GPAs did not have a statistically significant influence on their intercultural competences, whereas gender only had a significant impact on their intercultural competences on the Interactant Respect subscale. Due to the fact that the students should be taught intercultural competence at school, their competence is expected to improve in each study grade; thus, based on the students’ GPAs, this study may help teachers to identify a gap in their instruction and to modify their teaching content so that it contributes to the development of the students’ intercultural competence, as well as to the promotion of the importance thereof.
A Meta-Analysis Study on The Effect of Software Education on Computational Thinking

The main purpose of this study is to determine the effect of software education on elementary students' computational thinking.In this study, the meta-analysis method was employed which examined 24 studies conducted by year 2020 and have met the inclusion criteria.The types of software, group age, group size, and number of treatments were determined as moderating variables.An analysis based on a random effect model showed that the mean effect size value was calculated as 0.606 with an error of 0.08.It was also determined that there was no publication bias in the meta-analysis.According to the results of the moderator analysis, it was found that the effect of software on computational thinking of the students did not change according to the types of software education and group age, but it changed according to the group size and the number of software educational treatments.The effect size on computational thinking was high in small group(less than 6 students) and large group(more than 31 students who encouraged peer study).In addition, the number of treatments was 21 or more, the effect size was the highest.
Multi-stage Hierarchical Clustering Method Based on Hypergraph

Clustering analysis is a data analysis technique, it groups a set of data points into multiple clusters with similar data points. However, clustering of high dimensional data is still a difficult task. In order to facilitate this task, people usually use hypergraphs to represent the complex relationships between high dimensional data. In this paper, the hypergraph is used to improve the representation of the complex high dimensional data, and a multi-stage hierarchical clustering method based on hypergraph partition and Chameleon algorithm is proposed. The proposed method constructs a hypergraph in the shared-nearest-neighbor (SNN) graph from the dataset and then employs a hypergraph partitioning method hMETIS to obtain a series of subgraphs, finally those subgraphs are merged to get the final clusters. Experiments show that the proposed method is better than Chameleon algorithm and the other four clustering methods when applied on four UCI datasets.
The effects of environmental knowledge and green products awareness on green management and sustainable performance: Evidence from manufacturing sector in UAE

This research intends to figure the antecedents of Green Management and its implementation in manufacturing sector companies in UAE. The study also intends to explore the relationship between the implementation of green management and sustainable performance as measured by complied scale of social, economic and environmental performance. Quantitative research methods are used and the necessary data are collected from 134 companies by using google form survey sent to participants. Statistical Package of Social Sciences (SPSS) Version 22 is used to analyze the data. The findings of this research reveal that managers’ environmental knowledge and managers’ green product awareness were positively and significantly associated with green management and that green management was also positively and significantly associated with sustainable performance.
Zero-Knowledge Proofs for Machine Learning

Machine learning has become increasingly prominent and is widely used in various applications in practice. Despite its great success, the integrity of machine learning predictions and accuracy is a rising concern. The reproducibility of machine learning models that are claimed to achieve high accuracy remains challenging, and the correctness and consistency of machine learning predictions in real products lack any security guarantees. We introduce some of our recent results on applying the cryptographic primitive of zero knowledge proofs to the domain of machine learning to address these issues. The protocols allow the owner of a machine learning model to convince others that the model computes a particular prediction on a data sample, or achieves a high accuracy on public datasets, without leaking any information about the machine learning model itself. We developed efficient zero knowledge proof protocols for decision trees, random forests and neural networks.
Bayesian network meta-models from combat simulation for Defence decision analysis

Defence Science and Technology Group (DST) is investigating the characteristics of Land Combat Vehicles (LCVs) with a view to improving purchasing decisions between different LCV options.Using a combination of closed-loop combat simulation (i.e., one run without any human interventions) and subject matter experts (SMEs), these studies seek to understand the close combat capability factors for a future LCV.These factors are being investigated for different kinds of physical environment and different levels of enemy lethality, with each LCV's lethality, survivability, signature (the ease with which the enemy identifies friendly forces) and knowledge acquisition (friendly forces identifying enemies) being measured, yielding a multi-dimensional view of the different LCVs and their performance.Our study describes a new approach, developing a Bayesian network (BN) meta-model (i.e., a model based upon the combat simulation model; see Fig 1) that combines those multiple dimensions in a single multicriterial decision model.
WEBINAR DAN PENDAMPINGAN DARING PENULISAN ARTIKEL HASIL PENELITIAN PADA JURNAL NASIONAL TERAKREDITASI BAGI GURU BAHASA INDONESIA TINGKAT SMA KOTA BENGKULU

The understanding of Indonesian high school level teachers in Bengkulu City on writing scientific articles on research results is still low. This is evidenced by the small number of Indonesian language teacher publications in accredited national journals and it has an impact on teachers having difficulty advancing in rank. For this reason, the aim of this community service is to provide understanding to Indonesian high school teachers in Bengkulu City in writing scientific articles and how to publish them in accredited national journals through webinars and mentoring activities. The community service method uses webinars and online mentoring through the Zoom Cloud Meeting. Participants totaled 37 Indonesian high school teachers in Bengkulu City. Community service techniques use lecture, discussion, and practice techniques. Data collection techniques using questionnaires, documentation, and observation. The results of the webinar indicate that the Indonesian language teacher is able to write articles quite well, starting from writing titles, abstracts, introductions, methods, research results, discussions, conclusions and suggestions, and bibliography. However, some teachers still have difficulty in pouring out the introductory section, especially mapping research positions based on relevant research results, difficulty in pouring out the discussion, especially finding the novelty of their research results, and difficulty finding references from online journals. Then, from the results of mentoring, Indonesian language teachers still have difficulty in submitting and the process of fixing articles in the OJS system. Keywords: webinars; accompaniment; scientific journal articles; accredited national journal
Mergers and digital transformation in Danish research libraries

Abstract The Danish Ministry of Culture and Danish universities have pursued a policy of consolidation of research libraries. The wish to benefit from economies of scale was an important factor. Sustainability was another factor, the point being that the consolidation of scattered library-professional competencies will establish a secure basis for the necessary development of new library services to higher education and research. A distinctive feature are mergers, and a significant result is the current Det Kgl. Bibliotek/Royal Danish Library (RDL) which delivers service to five of the eight Danish universities. In this article, RDL’s strategy and governance are outlined.