Reviewerly/exHarmony huggingface dataset:
EFL Teachers’ Perceptions on the Implementation of Mobile-Assisted Language Learning in Saudi Arabia During COVID-19: Challenges and Affordances

This study aimed to explore EFL teachers’ perceptions regarding mobile-assisted language learning (MALL) in elementary schools in Saudi Arabia, including their attitudes, levels of proficiency, and challenges they experienced regarding the use of MALL. The study also sought to investigate whether EFL teachers’ backgrounds have any significant impact on their perceptions of MALL. To this end, survey data were collected from 123 EFL teachers who have worked in elementary schools in Saudi Arabia. The results revealed teachers’ positive perceptions of MALL, particularly during the COVID-19 pandemic. Overall, participants stated that mobile learning is beneficial and has the potential to support and enhance EFL teaching. Most EFL teachers reported that they did not have a sufficient level of skills/abilities required to develop MALL activities and cited some challenges they faced. The results also indicate a significant difference among participants’ perceptions of MALL based on their professional development and teaching experience, but no difference based on their gender was found. These results indicate that placing a greater emphasis on offering professional development in MALL for Saudi EFL teachers could cultivate both greater proficiency and the ability to overcome challenges. This study concludes by providing recommendations on how to improve MALL implementation as well as directions for future research.
QR Code Supported GIS Web System for University Facility Damage Report

This aim of this study is to develop a Quick Response (QR) code supported web-based geographical information system (GIS) for facility damage report in university buildings. In general, some academic buildings such as facility management system of Faculty of Architecture, Planning and Surveying (FSPU), Universiti Teknologi MARA (UiTM) encounter a problem of technicians spending more time to manually search for information on damaged equipment. Data processing such as scanning, georeferencing, and digitizing of the building plans were performed to create geodatabase file of the building. QR Codes at the different rooms were then generated by utilising QR Code Generator software. The waterfall or SDLC model was applied to produce a web-based system. This integrated system has facilitated the users with Home and Menus pages that benefit the outsourced parties to directly receive damages reports of the faculty. A survey of user satisfaction was also conducted to evaluate the practicality of the system and the result has shown that the system has the potential to be used by the department of facilities management by integrating with existing database system (e-Aduan) towards a better facility damage management. The proposed web-based system application will assist technicians and staff in managing the facility easier.
BYOD CONCEPT IN THE FORMATION OF AN INNOVATIVE EDUCATIONAL ENVIRONMENT FOR THE FUTURE EDUCATION BACHELORS TRAINING

One of the main reasons for the increased attention to the problem of introduction of mobile technologies in the educational process is the convenience and ease of use of existing tools for search, creation and use.Using these technologies, you can significantly increase the efficiency of the process of professional training of teachers, to intensify their educational and cognitive and independent activities.In the process of his activity, the teacher has to solve problems related to the search for existing mobile technologies, analyzing them for the feasibility of use in the educational process and creating their own.To train a competent specialist who is able to effectively use the ideas of the BYOD concept to solve the problem of their professional training is an important task of higher pedagogical education.The innovative educational sphere, organized on the basis of the BYOD concept, contains effective means that stimulate creativity in future teachers, reflexive actions, creativity in solving professional problems.It focuses on creating such an environment in higher education that would stimulate each student to take non-standard actions, to search for a creative way out of problematic situations that are so abundant in pedagogical reality.We found that the pedagogical purpose of the BYOD concept can be: propaedeutic acquaintance with the lecture material; classroom lecture for self-study; admission to laboratory classes; virtual laboratory workshop; self-control, etc. Measures for the use of mobile technologies and services in the process of training future teachers should be based on an informatization strategy (IT strategy), which is designed to determine the role and place of mobile technologies in ensuring the activities of an educational institution and solving problems of its development for a certain period.A modern teacher cannot effectively solve professional problems put forward by pedagogical reality if he does not have experience in research and innovation and is not ready to create the necessary atmosphere of scientific research in the context of practical pedagogical work based on the BYOD concept.
MAPPING RESEARCH WASTE FILTER CIGARETTE BUTTS AS A SUBSTITUTE FOR COARSE AGGREGATE IN CONCRETE BY THE METHOD OF SYSTEMATIC LITERATURE REVIEW

This study aims to determine the mapping of research related to cigarette butts filter waste as coarse aggregate for making concrete according to its category. This study uses systematic literature review techniques to conduct research by analyzing the literature. Literature collection is done by searching several digital libraries by entering a search string that has been made based on the research queation with publication limits between 2011-2020. The results showed that from 182 literature obtained 4 of them were suitable for analysis. Based on the 4 literatures, it is known that normal concrete and lightweight concrete are produced from cigarette butts filter waste. The concrete that is most often made is normal concrete and the best compressive strength value that can be produced is 29.6 MPa with a cigarette butt filter waste mixture of 0.1% of the concrete density. The best quality produced is medium quality with K 300.84 and is included in the category of structural concrete.
Big Data Analytics to Authenticate Bank Notes Using K-Means Clustering

The main objective of this work is to use the given dataset (about the information of different variables of the different kind of bank notes that were analyzed) in such a way using an algorithm that will group the large values in the data as efficiently as possible into two groups of values then we can use those groups and make a model that can in future identify a forged note from the real ones.Forged banknotes are a major problem that the bank must tackle.It is very important to find a solution to stop this criminal action.One of the most important steps is to be able to identify which banknote is forged.There are many solutions to identify the forged banknote.In this manuscript, we propose one of the solutions to identify the forged banknotes using one of the machine learning methods called "K-Means Clustering".
A New Representation for Span-based CCG Parsing

This paper proposes a new representation for CCG derivations.CCG derivations are represented as trees whose nodes are labeled with categories strictly restricted by CCG rule schemata.This characteristic is not suitable for span-based parsing models because they predict node labels independently.In other words, span-based models may generate invalid CCG derivations that violate the rule schemata.Our proposed representation decomposes CCG derivations into several independent pieces and prevents the span-based parsing models from violating the schemata.Our experimental result shows that an off-theshelf span-based parser with our representation is comparable with previous CCG parsers.
Reflections on the Role of Higher Education Institutions in Introducing Emerging Technologies Into the Educational Process in the Face of the Pandemic Challenge COVID-19

Abstract The pandemic COVID-19 has had an impact around the world and in the European Union, putting unprecedented pressure on education and training systems. It has fundamentally changed the way we learn, teach, communicate and collaborate in our education and training communities. This has implications for students, families, teachers, trainers, institutional leaders and society as a whole. Most European Member States have decided to extend the physical closure of education and training institutions, while mobilising alternative solutions and support for distance education and learning, especially digital solutions. This transformation has challenged education and training systems and stakeholders in these areas in Member States, particularly students and families, as well as teachers and trainers, but it has also provided them with valuable learning and training experiences, accelerated the digital transformation of education and training institutions. Emerging and disruptive technologies have undergone numerous and sufficient changes to ensure this. Thus, they will change the face and vision of higher education institutions.
A Study on the Learner’s Satisfaction of on-line PBL classes in Korean College

The quick move to non-face-to-face education caused by the sudden attack of the COVID-19 led to many problems such as faculty’s burden and stress from the planning and designing of suitable on-line classes, technology system problems for both students and faculty and students’ complaints of the low quality of education. Especially Project-based learning (PBL) has more challenges because it is learners-centred and is usually done in face-to-face environment. The primary purpose of this study is to investigate the factors affecting the learner’s satisfaction of non-face-to-face on-line PBL classes in terms of interaction and learner’s factors during the attack of COVID-19 pandemic. The data Was collected through questionnaires, from 175 undergraduate students at S women’s university who took the on-line PBL classes. SEM (Structural Equation Model) was used for empirical test using SmartPLS. The results of the empirical analysis reveal that interaction and media utilization self-efficacy are likely to predict learner’s satisfaction. Keywords: COVID-19, On-line PBL class, Satisfaction, Interaction, IT self-efficacy, Motivation
Examining the effect of teacher’s self-efficacy on job satisfaction

The paper aims to examine the effect of teachers' self-efficacy on job satisfaction. To deepen the study, literature was reviewed and theories were established. The study used the descriptive correlational research design. The total enumeration was the sampling design of the study. It used questionnaires to gather the data. The study found that the teachers' self-efficacy is very high along the three dimensions of teachers' self-efficacy which include self-efficacy in student engagement, instructional strategies, and classroom management. While teachers' job satisfaction was considered high, not very high along the two dimensions such as satisfaction with the work itself and personal growth and career development. Concerning the correlation, it was found that there is a significant correlation between teachers' self-efficacy and job satisfaction.
Comparative Analysis of Prediction Model In Weather Forecasting System For Agricultural Development

Agriculture is the backbone of a country.If a country is able to yield very good food it can be one of the best countries in the world.Rainfall is playing a vital role in field of agriculture.Predicting weather conditions for agriculture is a challenging and most needed feature for agriculture for every country.In the recent years, Data Analytics has played a vital role in detecting the challenges and risks in certain factors.We use Learning algorithms to predict challenges and risk faced in each problem.By predicting them in prior we may take certain actions before itis leaving out of our hand.The learning and prediction algorithms help to classify, predict and to make changes if needed.This study aims in predicting weather (i.e., Rainfall) which helps every agriculturist to predict weather and to sow different types of plants based on the weather condition.This study not only helps for agriculture it also helps in various fields like fishing, sports, transportation, tourism, etc. Weather forecasting is based on the available historical data.The predictions are done using various algorithms like Artificial Neural Network (ANN), Support Vector Machine (SVM) and Linear Regression (LR).The results infer that the prediction model using Support Vector Machine gives the best accuracy when compared with Linear Regression and Artificial Neural Network.This prediction helps people in planting crops and helps to make decision based on the weather condition.
Prediction of Accuracy in Emergency Health Records using Hybrid Machine Learning Model

The quantity of digital information contained in electronic health records(EHR) has increased dramatically during the last ten years. Numerous researchers have discovered that these records may be used for a variety of other purposes as well, including applications in clinical informatics. Additionally, within the same time period, significant advancements in the area of deep learning have been made by the machine learning community. Using EHR data, we examine the existing research on applying deep learning to clinical activities. In this article we will discuss various deep learning techniques used for the classification of electronic health records along with proposing of Hybrid model for finding classification accuracy of various models.
Information Systems Curriculum Analysis for the MaCuDE Project

This paper represents a report on the first phase of the Management Curriculum for the Digital Era (MaCuDE) disciplinary task force on information systems (IS). As its final goal, the MaCuDE project intends to recommend changes to business curricula based on the influence of digital technologies on business transformation, specifically, the widespread use of big data analytics (BDA) and artificial intelligence (AI) technologies in the organizations. In this report, we focus on describing the current status of both undergraduate and graduate IS curricula in business schools. Aligned with the most recent curriculum development work that the Association for Information Systems (AIS) and Association for Computing Machinery (ACM) have conducted, we highlight the growing importance of the BDA and AI topic areas in IS curricula. Based on the MaCuDE project survey conducted in early 2020, we summarize the core digital topics and tools that the programs covered based on a sample of global IS departments from 17 undergraduate programs and 23 graduate programs.
Color Correction Using Color Checkers

In this work, we present a simple but a different approach to correct colors of digital photographs.Pictures taken on digital cameras do not portray the actual colors of the photo that a naked eye can see.This is because of the surroundings and the lighting conditions a photo is captured in.The problem of colors is solved here using an external component called a color checker.The algorithm takes 2 inputs and gives a color corrected output which helps photographers and a few other areas of work where pictures play an important role.The method we propose has been tuned and tested on various image data.The paper deals with image processing and machine learning for color calibration and to detect the colorchecker on the target image and uses Python programming language to get the output.
Fake News Detection System Using machine Learning

Expansion of deluding data in ordinary access news sources, for example, web-based media channels, news web journals, and online papers have made it testing to distinguish reliable news sources, hence expanding the requirement for computational apparatusesready to give bits of knowledge into the unwavering quality of online substance. In this paper, every person center around the programmed ID of phony substance in the news stories. In the first place, all of us present a dataset for the undertaking of phony news identification. All and sundry depict the pre-preparing, highlight extraction, characterization and forecast measure in detail. We've utilized Logistic Regression language handling strategies to order counterfeit news. The prepreparing capacities play out certain tasks like tokenizing, stemming and exploratory information examination like reaction variable conveyance and information quality check (for example invalid or missing qualities). Straightforward pack of-words, n-grams, TF-IDF is utilized as highlight extraction strategies. Strategic relapse model is utilized as classifier for counterfeit news identification with likelihood of truth.
I Am the Robot: Teen Collaboration in an Asymmetric, Virtual Reality Game

Virtual reality (VR) offers potential as a collaborative tool for both technology design and human-robot interaction. We utilized a participatory, human-centered design (HCD) methodology to develop a collaborative, asymmetric VR game to explore teens’ perceptions of, and interactions with, social robots. Our paper illustrates three stages of our design process; ideation, prototyping, and usability testing with users. Through these stages we identified important design requirements for our mid-fidelity environment. We then describe findings from our pilot test of the mid-fidelity VR game with teens. Due to the unique asymmetric virtual reality design, we observed successful collaborations, and interesting collaboration styles across teens. This study highlights the potential for asymmetric VR as a collaborative design tool as well as an appropriate medium for successful teen-to-teen collaboration.
Sentiment Analysis of Smartphone Accounting Application Users

The focus of this research is to summarize the reviews conducted by accounting application users to explore what aspects they like about the accounting application. This research uses review sentences with a total of 4923 review sentences on Google and Apple platforms. The review mining method used in this study implements the Feature-Based Summarization (FBS). The conclusion of this study is that there are six product features that are preferred by accounting application users. The product features are reports, transactions, bookkeeping, profit, category, and customers. This research has explored product features in accounting applications, but not all product features are discussed by users. Therefore, the discussion on review sentences focuses on the six product features. This study is able to provide practical recommendations to Small-Medium Enterprises (SMEs) actors in making smartphone-based application decisions they will use. This study recommends SMEs to use accounting applications with the above product features. This is because the strong discussion of opinions on product features explains the preference for product features for actors in helping them prepare financial reports. As qualitative research, this study does not have the ability to generalize the results of the study to a population.
COMPARISON OF HEURISTIC EVALUATION AND COGNITIVE WALKTHROUGH METHODS IN DOING USABILITY EVALUATION OF MOBILE-BASED DEL EGOV CENTRE HOSPITAL INFORMATION SYSTEM

Usability is a factor that indicates the success of an interactive product or system, such as a mobile application. The increasing use of smartphones demands a more accurate and effective usability evaluation method to find usability problems, so that they can be used for product improvement in the development process. This study compares the Cognitive Walkthrough method with Heuristic Evaluation in evaluating the usability of the SIRS Del eGov Center mobile application. Evaluation with these two methods will be carried out by three evaluators who act as experts. Finding problems and recommending improvements from each method will produce an improvement prototype made in the form of a high-fidelity prototype. Each prototype will be tested against ten participants using the Usability Testing method, which will generate scores through the SUS table. From the test scores, the percentage of Likert scale and the success rate of each prototype will be found. The results show that between the two usability evaluation methods, the Heuristic Evaluation method is the more effective method, finds more usability problems, and has a higher Likert scale percentage, which is 66.5%, while Cognitive Walkthrough is 64.75%.
Data Augmentation Methods for Anaphoric Zero Pronouns

In pro-drop language like Arabic, Chinese, Italian, Japanese, Spanish, and many others, unrealized (null) arguments in certain syntactic positions can refer to a previously introduced entity, and are thus called anaphoric zero pronouns.The existing resources for studying anaphoric zero pronoun interpretation are however still limited.In this paper, we use five data augmentation methods to generate and detect anaphoric zero pronouns automatically.We use the augmented data as additional training materials for two anaphoric zero pronoun systems for Arabic.Our experimental results show that data augmentation improves the performance of the two systems, surpassing the state-of-the-art results.
Geographical Information System for Mapping and Analysis of Agricultural Areas in Merauke Regency

This Geographical Information System Mapping and Analysis Study aims to map and analyze the range of potential seed plant returns in several sub-districts in Merauke, which consists of several criteria for structural land use and land use intensity. Building Management, Circulation and Connecting Systems, Open Space and Green Systems, Quality Environmental Management, Environmental Infrastructure and Utilities Systems and Building and Environmental Conservation. This research was made using Simple Additive Weighting (SAW) which allows the search for optimal alternative solutions and the latest technological developments related to a method and presentation of information. The final result of this research is that web-based GIS is expected to be a source of reference / reference that is easily accessed by stakeholders related to agriculture, providing an overview of the various potentials of farming, especially sub-districts that have potential. availability of suitable land, provides an overview of the quantity of agricultural land use that has been utilized, and can be used as a guideline for policy development in the field of superior agriculture at the regional and national levels.
Usage of Energy Efficient Sensor Nodes on Wearable Device for fall and Child Abduction Detection

Falling is the most hazardous occasions that frequently occur among senior individuals, patients which requires medicinal consideration in time. Fall discovery frameworks could support senior individuals and patients to live autonomously. A programmed continuous fall discovery framework may discover fall occasions among old individuals in time that lessen the general setback rate. This device also helps to find the location of child when kidnapped which makes anyone to find out the child from kidnappers easily. The proposed framework utilizes the accelerometer and tilt sensors to structure an ongoing fall recognition framework additionally to recognize up to 4 various types of fall occasions (forward, in reverse, rightward and leftward), and compact ,wearable, ease and with high exactness rate. Machine learning algorithm is applied to predict if fall has happened or not ,so it is easy to avoid the false events effectively. Since the midriff is the focal point of gravity in the human body, the framework is progressively helpful when put at the midsection. The framework incorporates a programmed ongoing fall recognition gadget, energy utilization of sensor nodes in an IoT-based fall discovery framework and displays a structure of an altered sensor nodes and GSM texting capacity which can issue fall alert, send emergency help message.