Reviewerly/exHarmony huggingface dataset:
Automatic MCQ Generator

QUESTION is an essential tool to assess the knowledge or understanding of a learner. Assessment is crucial in learning and question is essential for assessment. Multiple choice question (MCQ) is the most widespread form of a question for various levels of assessment. MCQs have many advantages including quick evaluation, less testing time, consistent scoring, and the possibility of an electronic evaluation. Many examinations use MCQ based question papers through a computerized environment. However, manual preparation of MCQs is time-consuming and costly. Therefore, the research community devoted substantial effort to find the techniques for automatic generation of MCQs. The research on automatic MCQ generation started at least 20 years ago. As an early attempt, we find the system developed by Coniam David in1997 [1]. Since then, many MCQ generation systems have been developed in various languages and domains, and for various applications.MCQs are playing a vital role in all organizations, evaluating a person capability or eligibility for a particular purpose. Our Proposed idea to generate MCQs with software can help those kinds of organizations and institutes to evaluate one in a easy and time efficient manner. Manual preparation of exam questions is a challenging task for educators especially within a short time frame. It requires a lot of time and efforts in order to meet the standard quality of exam questions. This research introduces an automated exam question generator to resolve this issue in preparation of multiple choice exam questions.
Giving Incentives and the Impact on the Discipline of Economic Teachers in Implementing Their Assignment

This study aims to determine the effect of giving incentives to the discipline of economics teachers in carrying out assignments at SMA Negeri 12 Pekanbaru. The population is 8 teachers, because the population is small, the authors make the population as a sample. Data collection techniques that the author uses are questionnaires, interviews, and documentation. And the data processing technique that the author uses is a simple linear regression formula and product moment correlation with the help of the SPSS version 16.0 program. Based on the presentation and analysis of the data, it is known that the provision of incentives has a significant effect on the discipline of economics teachers in carrying out their duties at SMA Negeri 12 Pekanbaru. This is evidenced by the results of the analysis that observation = 0.938 is greater than Rtable at a significant level of 5% (0.838 &gt; 0.707) this means that Ha is accepted, Ho is rejected. ro observation = 0.938 is greater than Rtable at a significant level of 1% (0.938 &gt; 0.834) This means that Ha is accepted, Ho is rejected. Thus it can be concluded that there is a significant effect between the provision of incentives on the discipline of economics teachers in carrying out their duties of 0.881 X 100% = 88.1%.
Measuring Students’ Perceptions of Quality Online Learning in the Era of COVID-19 – A Case Study of Students in the Accounting Department at Taif University –: قياس اتجاهات الطلبة نحو جودة التعليم الالكتروني أثناء فترة جائحة كورونا (COVID19) – دراسة ميدانية على طلبة قسم المحاسبة بجامعة الطائف –

This study aimed to identify students' attitudes about distance learning in accounting courses. The study used a descriptive analysis approach, and a sample of 470 students from Taif University’s Accounting Department was selected. The results indicated that there was a positive relationship between students and their levels of satisfaction with distance learning due to their communication with each other and their teachers and the quality of education and its outcomes.
Data-driven Storytelling to Support Decision Making in Crisis Settings: A Case Study

Data-driven storytelling helps to communicate facts, easing comprehension and decision making, particularly in crisis settings such as the current COVID-19 pandemic. Several studies have reported on general practices and guidelines to follow in order to create effective narrative visualizations. However, research regarding the benefits of implementing those practices and guidelines in software development is limited. In this article, we present a case study that explores the benefits of including data visualization best practices in the development of a software system for the current health crisis. We performed a quantitative and qualitative analysis of sixteen graphs required by the system to monitor patients&amp;#39; isolation and circulation permits in quarantine due to the COVID-19 pandemic. The results showed that the use of storytelling techniques in data visualization contributed to an improved decision-making process in terms of increasing information comprehension and memorability by the system stakeholders.
Hybrid Encryption Algorithms for Medical Data Storage Security in Cloud Database

Cloud database are derivatives of Cloud computing. At present, most medical institutions store data in cloud database. Although the cloud database improves the efficiency of use, it also poses a huge impact and challenge to the secure storage of data. The article proposes a hybrid algorithm to solve the data security problem in the hospital cloud database. First, the AES algorithm is improved. The improved algorithm is called P-AES algorithm. The P-AES algorithm is then combined with the RSA algorithm, called a hybrid algorithm. The experimental results show that the hybrid encryption algorithm has the advantages of fast encryption and decryption speed, high security, good processing ability for longer data, and can solve the data security problem in cloud database to a certain extent. The algorithm has been successfully applied to hospital information management system.
Overcoming Factors Inhibiting Students' Interest in Reading Through the Concept of Self Awareness

This study to discuss overcoming factors inhibit reading interest students through concept self awareness. Data collection techniques by interviews. Data analysis techniques by data reduction, data presentation, and drawing conclusions. Reading must do especially for students. However, reading interest several students posgraduate PAI UIN Sunan Kalijaga is still low, because there are several factors that hinder their reading interest, namely: 1) low motivation to read; 2) amount of entertainment in this era makes students more to spend time playing handphone, games and watching TV; 3) sometimes difficult to concentrate. The solution with concept self awareness, namely: 1) we must realize to be able to change from problems; 2) make decisions, for example problem low motivation to read by starting to read from the reading we like, problem the amount of entertainment in this era makes students more to spend time playing cellphone, games and watching TV by we have to prepare a special time to read, problem sometimes difficult to concentrate by we can read in a time / place that is quiet / / comfortable so can concentrate fully without distraction; 3) learn to realize the decision; 4) do it little by little; 5) continuous practice; 6) consistent.
Construction of APN permutations via Walsh zero spaces

A Walsh zero space (WZ space) for $$f:{\mathbb {F}_{2^n}}\rightarrow {\mathbb {F}_{2^n}}$$ is an n-dimensional vector subspace of $${\mathbb {F}_{2^n}}\times {\mathbb {F}_{2^n}}$$ whose all nonzero elements are Walsh zeros of f. We provide several theoretical and computer-free constructions of WZ spaces for Gold APN functions $$f(x)=x^{2^{i}+1}$$ on $${\mathbb {F}_{2^n}}$$ where n is odd and $$\gcd (i,n)=1$$ . We also provide several constructions of trivially intersecting pairs of such spaces. We illustrate applications of our constructions that include constructing APN permutations that are CCZ equivalent to f but not extended affine equivalent to f or its compositional inverse.
Laborapparatus: A Student Guide Website About Laboratory Apparatus

This research capstone project was conducted to develop a website using the Wix Website Builder that comprises common laboratory apparatuses found in biology laboratories, chemistry laboratories, and physics laboratories. A total of 37 respondents was determined using purposive sampling: 15 High School Students, 15 IT Experts, and 7 Science and Research Teachers. The independent variable of this study is the level of acceptability in terms of content, design, and functionality, and the dependent variable is Laborapparatus: A Student Guide Website about Laboratory Apparatus. The researchers made a questionnaire to gather data on both variables. Frequency count, sum, percentage, and mean were used as the statistical tools in this study. Overall results showed that the level of acceptability of the website in terms of content, design, and functionality among the three groups was under the description “Very Highly Acceptable.” The “Very Highly Acceptable” description proves that the website was found beneficial by the respondents because they have gained knowledge, as the website encompasses pictures, videos, and information about the chosen different laboratory apparatuses found in biology laboratories, chemistry laboratories, and physics laboratories.
Investigating the role of mediator of knowledge sharing and information on the impact of social networks on empowerment of agricultural jihad employees

Today, with the advances in science and technology and the increasing need for societies to exchange information, people are turning to new ways of communicating and interacting. Virtual networks also allow for the formation of new communities because of the interactive space. In the meantime, with the transition from traditional to modern, the communication and interaction of farmers and activists in this sector to get acquainted with new methods is extremely felt. The aim of this study was to investigate the mediating role of knowledge and information sharing in relation to the effect of using social networks on the empowerment of agricultural jihad employees in southern Kerman using a survey method. The statistical population of this study was the employees of Jihad Keshavarzi in southern Kerman. The sample size was determined by simple random sampling using Krejcie and Morgan table of 206 people. Data collection tools were employee empowerment questionnaires, knowledge and information sharing, social networks. To test the research hypotheses, the data were processed using SPSS23 and LISREL8.80 software. The results showed that the use of social networks is directly related to the sharing of knowledge and information of Jihad Keshavarzi employees in the southern city of Kerman. The use of social networks has a direct relationship with empowerment of agricultural jihad employees in Kerman. Sharing knowledge and information with empowerment of staff in southern Kerman agriculture has a direct relationship. Eventually, the results showed that knowledge and information sharing in relation to the impact of the use of social network and empowerment in the staff of the southern agricultural jihad of Kerman has a mediator.
Chapter 3. Visualizations of a Digital Collection’s Data

Chapter 3 of Library Technology Reports (vol. 57, no. 1) focuses on basic visualizations created for the Clyde W. Tombaugh Papers digital collection hosted at the NMSU Library. In the context of Tombaugh’s biography and his papers, the selection of graphs provides a range of views that address specific questions about the content and development of the collection. Each plot is accompanied by its brief interpretation and the R script used to create it, as well as its explanation, including operations on data and R functions.
Practical Guideline for Digital Forensics Laboratory Accreditation – A Case Study

Digital forensics is a branch of forensic science that is used to assist investigation of cybercrime cases. Digital evidence, such as from mobile devices and computers, are analysed and the data are interpreted to assist the court of law in understanding what has taken place. In order to provide an assurance to the stakeholder on the accuracy of the forensic result, ISO/IEC 17025 has been used by forensic accreditation bodies to accredit laboratories. This paper, presents the case study in getting a digital forensics laboratory accreditation, the methodology, and the lesson learnt. This paper is hoped to provide guidance to those who would like to pursue accreditation for their Digital Forensics Laboratories (DFL).
Adaptive Services Architecture for a Co Creation Process with High Ability Students

With the aim of motivating High Ability students in their learning process, we propose their participation in the co‑creation of their own learning material. However, their participation is not enough because the process should also be a personal experience adapted to students’ characteristics and context. For that purpose, we defined a learning material co‑creation process, called Co‑CreHAs, which guides the adaptation of co‑created material according to High Ability students’ learning needs. For said adaptation, we implemented AdaptHAs (i.e., the model used to adapt Co‑CreHAs). In this paper, we present the design and validation of the architecture of adaptive services of AdaptHAs. Such architecture design is based on the analysis of the characteristics of high abilities and the co‑creation process. This analysis allowed us to identify the kind of adaptation profiles that needed to be defined, participants’ aspects that would be worked on in each profile, and the parts of the process where we could use those profiles in order to personalize it. The architecture was validated through the analysis of three real co‑creation experiences with High Ability students, their parents, and their teachers using the Co-CreHAs extension for Moodle, which was developed applying said architecture. The results of this validation show that the architecture guides the adaptation of the co‑creation and the development of software that can be implemented to put into practice such co‑creation with the adaptive services previously defined. Furthermore, we observed that the proposed process and the implemented adaptation can influence High Ability students’ motivation to co-create their own learning material.
The Semantics and Syntax of Prepositional Constructions with the Lexical Verb Go in Written and Spoken Discourse

A prepositional construction consists of a lexical verb followed by a preposition with which it is semantically and/ or syntactically linked. The main focus of this analysis is the lexical verb go occurring within prepositional constructions. The aim of this paper is to present the frequency and distribution of prepositional verbs in written and spoken discourse. We will also determine all prepositional constructions with the lexical verb go, and present their practical use and distribution in different registers. Given that when distinguishing prepositional verbs, the semantic criteria of idiomaticity must be supplemented by syntactic criteria, we will also show all possible meanings of each prepositional construction found in the analyzed material, and determine the type of transitivity of each meaning. Furthermore, we will compare the distribution and syntactic features of each prepositional construction with the lexical verb go in different registers, and show similarities, disimilarities and all characteristics of their practical use in written and spoken discourse.
Anomaly detection for solar thermal parabolic trough power plants with artificial intelligence

Defects and faults in parabolic trough power plants often lead to lower energy production. The automated detection of such anomalies could reduce downtimes and increaseefficiency.The anomaly detection is based on sensor data which are measured anyway for the operation of the plant. The measured data are high-dimensional data in a spatio-temporalcontext.In the first step, the efficient preprocessing and visualization of the solar field andweather data is realized. From the existing sensor data useful features are extracted,which build the input for further approaches of anomaly detection models.Regarding the given problem, approaches that make use of methods of artificial intelligence are presented. One approach is pursued. The basic idea of this approach is theconsideration of multivariate time series on loop level, which are segmented and clustered. For the segmentation of the time series three different segmentation methodsbased on the bottom-up or sliding-window principle are compared. For clustering, thedensity-based DBSCAN algorithm is used.The results of the anomaly detection show that about 93 % of the detected time seriessegments behave unusually from the data point of view due to manual interventions inthe operation of the power plant. Suggestions for an improvement are given to reducethe number of false detections. Furthermore, weaknesses of the implemented approachare pointed out.
AI3SD Video: Explainable Machine Learning for Trustworthy AI

Black box AI systems for automated decision making, often based on machine learning over (big) data, map a user’s features into a class or a score without exposing the reasons why. This is problematic not only for the lack of transparency, but also for possible biases inherited by the algorithms from human prejudices and collection artifacts hidden in the training data, which may lead to unfair or wrong decisions. The future of AI lies in enabling people to collaborate with machines to solve complex problems. Like any efficient collaboration, this requires good communication, trust, clarity and understanding. Explainable AI addresses such challenges and for years different AI communities have studied such topic, leading to different definitions, evaluation protocols, motivations, and results. This lecture provides a reasoned introduction to the work of Explainable AI (XAI) to date, and surveys the literature with a focus on machine learning and symbolic AI related approaches. We motivate the needs of XAI in real-world and large-scale application, while presenting state-of-the-art techniques and best practices, as well as discussing the many open challenges.
La autopercepción de la competencia digital ciudadana del alumnado universitario de educación

The acquisition of Digital Competence (DC) of teachers in their initial university training is essential to be citizens of a fully digitised society. Our main objective focuses on the self-perception of the students of the Faculty of Education of the University of Alicante about their own digital competence based on the DigComp 2.1 European Framework. A total of 185 students participated in this research and a quantitative method. An online questionnaire with 44 items designed based on other references was used. The data analysis was carried out with SPSS version 20.0. The results indicate an intermediate self-perceived level by the students, showing greater mastery in dimensions such as security, and less in content creation and problem solving. It is algo worth noting that there are few differences between the variables gender and age in terms of DC. In short, the transcendence of DC in university students as citizens is recognised. Due to current demands, there is a demand for more training, a renewal of university curricula, better trained university teaching staff and the need for continuous training in the field of ICT.
Design The Modified Multi Practical Swarm Optimization To Enhance Fraud Detection

Financial fraud remains an ever-increasing problem in the financial industry with numerous consequences. The detection of fraudulent online transactions via credit cards has always been done using data mining (DM) techniques. However, fraud detection on credit card transactions (CCTs), which on its own, is a DM problem, has become a serious challenge because of two major reasons, (i) the frequent changes in the pattern of normal and fraudulent online activities, and (ii) the skewed nature of credit card fraud datasets. The detection of fraudulent CCTs mainly depends on the data sampling approach. This paper proposes a combined SVM- MPSO-MMPSO technique for credit card fraud detection. The dataset of CCTs which consists of 284,807 transactions performed by European cardholders in 2013 was used in this study. The proposed technique was applied to both the raw dataset and the pre-processed dataset. The performance of these techniques is evaluated based on accuracy, and the fastest time it takes to detect fraud. This paper, proposed a technique that uses SVM, MPSO and MMPSO to form an ensemble for the detection of credit card fraud
資料インデックスとしての動的映像の可能性 / Potential of Video as Resource Index

学術調査で記録される多くの動的映像は冗長であるものの、調査行程のリニア性が担保されている。この特性を活かし、別種資料の整理にも寄与できるインデックスとして活用できないだろうか。半世紀前に記録された動的記録映像の情報粒度分析から、未遂の写真整理再開の可能性を検証する。Many videos recorded in academic research are redundant, but they grantee the linearity of the research process. Isn't it possible to make use of this characteristic as an index that can contribute to organizing different kinds of materials? I'd like to consider the possibility of resuming the attempted photo archive from an information granularity analysis of video records recorded half a century ago.
Holistic knowledge and research practice in teachers. A study in virtual learning contexts during the COVID-19 pandemic.

The descriptive correlational study, whose main purpose was to determine the degree of relationship between the holistic knowledge of research and the practice of research in primary school teachers in virtual learning contexts during the COVID-19 pandemic, involved 90 primary school teachers from different Local Educational Management Units of the Regional Education Management of La Libertad, Peru. Two structured questionnaires were used to collect data on holistic knowledge and research practice, the validity of which was established through expert judgment and reliability with the split-half method, with r values greater than 0.80. After the analysis of correlations on the study variables, applying the Spearman Rho coefficient, the values rs=0.209 and p=0.049<0.05 were found, which allowed rejecting the null hypothesis and proceeding to accept the alternative hypothesis; that is, there is a direct, moderate and significant relationship between holistic scientific knowledge and the practice of research in virtual learning contexts generated in the pandemic. Likewise, similar results were obtained when relating holistic knowledge with the dimensions of the research practice: the exploration and observation of educational phenomena, and the planning and implementation of projects.
Critical Analysis of the Organizational Framework of the Discipline-Based Economics Education Program in Indonesia

Abstract : There is ample evidence to suggest that economics education should be built on a multidisciplinary basis, including technology-based and non-technology-based, to help graduates work with cross-disciplinary economic issues in a multi-cultural environment. Therefore, if a variety of different disciplines supports a study program in Economics, the benefits of economics education are integrating multidisciplinary academic resources and improving quality and efficiency. To facilitate economic science education that is supported by multi-disciplinary disciplines. This study investigates the organisational framework of economic science education programs at universities and colleges of economics or tertiary institutions in Indonesia. This study finds that the administrative framework for economic science education in Indonesia is similar and generally accepted and does not support the scientific potential of across disciplines. Keywords : Academic organization, economics education, multi-disciplinary, Indonesia