Reviewerly/exHarmony huggingface dataset:
Evaluating The Impact of Mindfulness Service on Air Travel Experience and Satisfaction: A Mediation and Moderation Model

The concept of mindfulness is enhanced now a days over the world. It’s significant positive effects on person’s health not only valuable solution for people facing problems, like depression and anxiety but also makes a desire for society to enhance individual’s quality in many phases of life. To fulfilment of the objective of this study convenient sampling techniques is used to collected the data from the concerned respondents. To access and measurement of the model convergent validity, and discriminant validity is used and to measure the hypothesis path analysis is used. The results of it create positive travel experience which lead to higher customer satisfaction. Moreover, due to significant effects on travel anxiety and higher satisfaction with the service, customer more attract and loyal to airline. In order to take the large range of passengers the study was conducted as a survey which was taken at the international departure gate of Allama Iqbal International Airport Lahore. Data was collected and compiled from passengers who were frequent flyers in different airlines. The study also focusses on the relationship between mindfulness and travel experience with airlines of their choice. The Service quality acting as a moderator between mindfulness mediation and its effects on travel experience to improve customer satisfaction. Mindfulness has a limited attention in business perspective but this study investigates mindfulness as a business model. Mindfulness service create a positive effect to satisfied airline passengers during different phases of flight to enhance positive travel experience. There for, the possible impact of flight anxiety is investigated for better understanding of mindfulness meditation effect with the help of airline service quality.
Analysis Of The Use Of Hashtags As A Social Movement In Determining Public Opinion On Social Media "Twitter" (Study On Hastag #Sahkanruupks)

Social media is not only used as a medium for entertainment but its users use it as a medium in shaping public opinion. A medium is needed to convey opinions and also become a discussion space for communicators and communicants. Twitter is one of the social media that provides a place for its users to convey opinions, exchange ideas, discourse and attract public sympathy through the tweets feature. This research is used to describe the reality that is happening to twitter users who care about developing issues such as this sexual violence case. This is evidenced by the creation of the hashtag #SahkanRUUPKS and the accounts that tweeted through the hashtag #SahkanRUUPKS. This research uses descriptive qualitative research methods, namely exploration and clarification of a phenomenon or social reality. By using the critical discourse analysis approach of Teun A. Van Dijk model. In conclusion, there are three levels of dimensions used in showing the discourse of support for the ratification of the sexual violence elimination bill, namely macro structure, superstructure and micro structure, as well as social cognition and social context used to see the author's awareness in writing his tweets.
An Empirical Study of Car Failure Causes Based on Machine Learning Methods

Car breakdowns are a widespread issue for car owners, circulation roads and maintenance companies in all the world, leading to significant economic and safety implications. In order to develop more effective preventive maintenance strategies and minimize these consequences, this study has aimed to gain valuable insights into the primary causes of car breakdowns. In order to achieve this, a survey targeting drivers from all Moroccan cities as a sample is conducted, focusing on breakdown types, their frequencies, as well as maintenance practices. The study has employed significant variables, including driver demographics, car brand and model, horsepower, fuel type, and maintenance practices, in a prediction test to anticipate car breakdowns. Statistical and machine learning algorithms, such as regression and classification analysis, have been used to identify six underlying factors contributing to car breakdowns in Morocco. This research provides crucial insights for car owners, maintenance companies, and policymakers to improve preventive maintenance strategies and decrease the economic and safety impacts of car breakdowns that could be applied in all the world.
Using Sentiment Analysis of Arabic Tweets to Fine-Tune CRM Structure

Understanding how customers perceive the services they receive has always been crucial to a business’s success. It is widely accepted that Customer Relationship Management (CRM) and Customer Experience Management (CEM) have both been shown to aid businesses in making better decisions by providing them with better information. Unfortunately, in real-world business applications, there are distinctions between customer opinions collected through customer relationship management (CRM) and the real customer opinions gathered via social media for customer experience management (CEM). It is critical to close this gap between the two to match customer expectations. Both CRM and CEM have been recognised as tools that can help firms make better decisions. However, until recently, the problem of integrating unstructured data from CEM directly into CRM was largely ignored, and, particularly in the Arabic language, it has remained unsolved. Thus, the goal of this study is to offer a framework for CRM modification via CEM that integrates a semantic orientation method and supervised machine learning. Sentiment analysis was utilised to enhance the CRM structure to add important aspects that were missing. The results of this study show that businesses could undoubtedly make more informed decisions by expanding their CRM structure to incorporate more of the issues discussed by customers on social media. Surprisingly, the negative class had the most label matching between CRM and CEM.
Digital Transformation in University Education at Dong Thap University: An Overview

Abstract : Nowadays, University education in Vietnam is faced with opportunities and challenges that need to be modified to chase up the development of the region and the world. The covid-19 epidemic has altered the form and training organization system at many universities in Vietnam, Dong Thap university (DThU) is not an exception. To keep up with the development tendency of the modern education system, digital transformation is an urgent mission that contributes to enhancing the effic iency and quality of education. This essay will present a view on digital transformation in education at DThU. From actual research, articles that analyze advantages and adversities as well as propose a digital transformation paradigm at DThU to improve training efficiency, and upgrade education productivity in Vietnam and other countries in the region. Keywords : Digital Transformation, The Covid-19 Epidemic, University Education, University Management.
The Utilization of Artificial Intelligence Based Chatbot in Interactive Learning Media

Abstract: After the spread of the COVID-19 virus, the world of learning is no longer the same as it was before the pandemic, especially at the university level, which requires students to be more active in finding lots of learning references via the internet. Active learning has a close relationship with the use of artificial intelligence technology, in this study researchers designed an interactive learning media that applied Artificial Intelligence (AI) Assisted Chatbot. The multimedia development method used in this research is the Multimedia Development Lifecycle (MDLC) method. Interactive learning media is built using Android Studio, and the retrievalbased chatbot is built with Python, Tensorflow, Hard (Extension for Tensorflow), NumPy, and Matplotlib. The researcher applies the White box and Black box testing methods to test whether the learning media that have been made have worked according to the user's needs. The chatbot model that has been applied to this learning media when tested with the BLEU metricgets a result of 0.1117, this shows the chatbot produces good answers and provides credible learning references. There is a difference in student learning outcomes after using chatbot-based learning media in basic electronics subjects, the utilization of chatbotbased learning media is able to improve student learning outcomes, especially in the student weaknesses section, the chatbot can provide detailed explanations and guide students in solving linear equation problems. Keywords: Artificial Intelligence; Chatbot; Interactive Learning Media; Retreival-based Chatbot;
The development of two-variable function derivative learning using Geogebra

Mathematics learning model using GeoGebra software has become a handy tool in teaching mathematical concepts and applications. Students can conduct experiments and explore mathematical concepts in an interactive and fun way with GeoGebra software. Using GeoGebra in learning mathematics of two-variable functions can increase students' understanding on the topic discussed, strengthen mathematical computational and visualization skills, and motivate them to know more and better complex mathematical concepts. From this perspective, this study aims to know the impact of using GeoGebra on students' understanding of the derivative of a function of two variables. Furthermore, this study was conducted on two groups of students, namely the control group (not using GeoGebra) of 53 students and the experimental group (using GeoGebra) consisting of 50 students. Based on these results descriptively students in the experimental group have higher scores on the assessment of skills in determining partial derivatives and their application. Statistically, there is a difference between the experimental and control groups in understanding the function of the derivative of the two variables.
Computational thinking in the curricular component of mathematics in basic education: Possibilities and challenges

This article highlights and discusses aspects of the perceptions of a group of Mathematics teachers in Basic Education about Computational Thinking (CT) and its possibilities of working simultaneously with the curricular component of Mathematics in Basic Education. The case study was carried out through a continuing education course and focused on the application of questionnaires with open questions, as well as on reports on the inclusion of activities, by the participants, in their teaching practice during the course. The responses were analyzed from a qualitative perspective and the results highlight the predominance of lack of knowledge on the subject, especially with regard to the use of methodologies that develop computational thinking associated with specific objects of Mathematics knowledge.
Assessing the use of self–regulatory oral communication strategies by Polish learners of Spanish: The feasibility of adapting the OCSI

Language learning strategies (LLS) have evolved from a research construct approached mostly from a functional perspective to one which is investigated in specific contexts of particular skills, subsystems, and types of learners. Moreover, LLS use has been linked to self-regulated learning. From this angle, language learners may be approached as individuals resorting to various ways of enhancing their performance across macro- and micro-skills. Among them, oral communication strategies (OCS) are essential because they directly affect the effectiveness of interaction and, consequently, determine how much the learners themselves may benefit from it in terms of progress. Among inventories developed to assess the use of OCS, the Oral Communication Strategy Inventory (OCSI, Nakatani, 2006) is particularly appealing. First, it was developed on a basis of two consecutive studies, one of which was based on insights from a large sample of learners. Second, its scales were distinguished by means of robust factor analysis. For these reasons, it has been used in studies into foreign language learners’ use of OCS (e.g., Pawlak, 2015, 2018). This notwithstanding, apart from the investigation by Yaman and Kavasoğlu (2013), no studies relying on the OCSI (Nakatani, 2006) discuss its adaptability to local conditions in terms of its fulfilment of goodness criteria for psychometric tests. Attempting to bridge this gap in research, the present paper considers the feasibility of adapting the OCSI to assess OCS use by Polish learners of Spanish in extended curriculum settings. Overall, the results of the study show that after some minor adjustments, the inventory may be used as a reliable and valid instrument.
Cyber Security Threats and Protection Technologies for Al Rajhi Bank

Technologies are the basis of practically every social action in today's connected world. Although technology has greatly benefited the banking industry, experts have noted the challenges and risks of cybersecurity. A bank can detect, analyze and protect people from these risks thanks to real-time conditions. The majority of financial institutions, including Al Rajhi Bank, are implementing technology in their daily operations as a result of the COVID-19 outbreak [1], which exposes them to cybersecurity issues. The purpose of this project is to investigate and search for encryption algorithms used by Al-Rajhi Bank and what are the most important security attacks that Al-Rajhi Bank faces, as this was done by communicating with an employee in the information technology department at Al-Rajhi Bank, and interviewing. In addition, a literature review of related works, investigation of algorithms and comparison was carried out, in order to verify the efficiency and strength of encryption algorithms in Al-Rajhi Bank and the results of previous works. Al Rajhi Bank's algorithms are very effective and secure, but the various decision-makers believe that as technology develops, financial institutions should think about incorporating other encryption algorithms, like Rivest-Shamir-Adleman (RSA), Triple Data Encryption Standard (TDES), and Twofish algorithms, into their cyber security systems.
Teacher Innovation through Knowledge Management and Personality Strengthening

This study aims to increase teacher innovation by examining knowledge management and personality relationships. The method used is a combination of correlation approaches and Sitorem analysis. There were 271 samples from a population of 1684 elementary school teachers with civil servant status using multistage proportional sampling. Data analysis comprised normality, homogeneity, linearity, and multiple regression tests. The study's results prove a solid or significant relationship between knowledge management and personality and teacher innovation, as indicated by the correlation coefficient ry123 = 0.652. SITOREM analysis shows that based on the order of priority, improvements that need to be increased include knowledge dissemination, awareness, openness, personal consideration, and business and organizational innovation. At the same time, the indicators that are maintained and developed are influence, product innovation, emotional stability, process innovation, inspirational motivation, application of knowledge, knowledge storage, agreeableness, service innovation, knowledge acquisition, intellectual stimulation, extraversion, and knowledge evaluating.
From Idea to Functional ETD: Experiences from the University of Novi Sad, Serbia

This paper reviews different phases of introducing and usage of Electronic Theses and Dissertations – ETD at the University of Novi Sad with special emphasis on specific requirements, challenges and further directions of development and use of ETD systems at the University.
The Challenges of the Current and Retrospective Digital Archiving of Doctoral Dissertations: Toward Integration of Several University Collections at the University Library “Svetozar Marković” in Belgrade

The University library “Svetozar Marković” possesses the most extensive and most valuable collection of doctoral dissertations defended at the University of Belgrade and other universities in Serbia or abroad, but this corpus is not unique. It can be divided into several sub-collections: current doctoral dissertations, which include mandatory archiving since 2012; a collection of doctoral dissertations digitized retrospectively by users’ demand; and, finally, a collection of old Serbian dissertations, which includes those defended by Serbian scientists at foreign universities and defended at the University of Belgrade at the beginning of the 20th century. In this paper, these sub-collections are described, analyzed, and observed through several criteria (completeness, existing support, location, availability, and copyright issues). The importance of a straightforward procedure was revealed, and copyright issues were identified as predominant. Legal regulations at the national or university level, together with library institutions that perform digitization services, can achieve desirable results.
IMAGEWARE SCAN MANAGER APPLICATION IN ARCHIVES MANAGEMENT AT PT ESA TAWANG CIPTA SIDOARJO

PT Esa Tawang Cipta is a company engaged in education and training in the world of aviation. The company offers education and training packages for aviation security (AVSEC), ground staff and Air Cargo. The prepared instructors have experience in the field of aviation. In addition to the field of education and training, there are other business fields, namely in the field of cargo. Archives are something that cannot be separated from the organization because in it there are sources of information and can also be used as the memory center of a company or organization. In this advanced era, many office work has been done electronically, one of which is archiving. Archives at PT Esa Tawang Cipta still use conventional archives. In the implementation of the archives at PT Esa Tawang Cipta there were problems because the documents in the education and training fields were mixed with the cargo business sector. This makes it difficult to find the archives needed and slows down archiving activities. Therefore, electronic archives to facilitate the implementation of archives in the company. The electronic archive through the IWSM application at PT Esa Tawang Cipta is organized into 3 workgroups, 11 template worksheets, 22 worksheets, 51 fields. In addition, a manual book for running the IWSM application was also made.
Ensemble Machine Learning to “Boost” Ubiquitination-sites Prediction

Ubiquitination-site prediction is an important task because ubiquitination is a critical regulatory function for many biological processes such as proteasome degradation, DNA repair and transcription, signal transduction, endocytoses, and sorting. However, the highly dynamic and reversible nature of ubiquitination makes it difficult to experimentally identify specific ubiquitination sites. In this paper, we explore the possibility of improving the prediction of ubiquitination sites using ensemble machine learning methods including Random Forest (RF), Adaptive Boosting (ADB), Gradient Boosting (GB), and eXtreme Gradient Boosting (XGB). By doing grid search with the 4 ensemble methods and 6 comparison non-ensemble learning methods including Naïve Base (NB), Logistic Regression (LR), Decision Trees (DT), Support Vector Machine (SVM), LASSO, and k-Nearest Neighbor (KNN), we find that all the four ensemble methods significantly outperform one or more non-ensemble methods included in this study. XGB outperforms 3 out of the 6 nonensemble methods that we included; ADB and RF both outperform 2 of the 6 non-ensemble methods; GB outperforms one non-ensemble method. Comparing the four ensemble methods among themselves. GB performs the worst; XGB and ADB are very comparable in terms of prediction, but ADB beats XGB by far in terms of both the unit model training time and total running time. Both XGB and ADB tend to do better than RF in terms of prediction, but RF has the shortest unit model training time out of the three. In addition, we notice that ADB tends to outperform XGB when dealing with small-scale datasets, and RF can outperform either ADB or XGB when data are less balanced. Interestingly, we find that SVM, LR, and LASSO, three of the non-ensemble methods included, perform comparably with all the ensemble methods. Based on this study, ensemble is a promising way of significantly improving Ubiquitinationsite prediction using protein segment data.
Sustainability Practices and Financial Stability of Non-Financial Companies in Sub-Saharan Africa: Camel Parameter Ratio Approach

Most countries in Sub-Saharan Africa (SSA) have witnessed challenges with their financial stability, as most of their non-financial companies could not balance their performance. The study examined the effect of sustainability practices on financial stability of listed non-financial companies in SSA, using CAMEL parameter. Within the framework of ex-post facto research design, 183 non-financial companies Listed on the exchanges of Ghana, Nigeria and Johannesburg, South Africa as at December 31, 2020 constituted the population from which purposive sampling technique was used to draw a sample of 20 firms based on pre-determined criteria. Data covered 10 years period from 2011 to 2020 were analysed via Ordinary Least Squares (OLS) estimation techniques. The study concluded that Size and age significantly enhanced the effect of sustainability practices on the CAMEL ratio of the firms. Hence, strict monitoring and low risk profile on the part of the directors of corporate non-financial companies were recommended. Keywords: Sustainability practice, Financial Stability, Economic Value Added, CAMEL Parameters ratio.
REARRANGMENT OF ARCHIVES HANDLING AT HUMAN RESOURCES DEPARTMENT-GENERAL AFFAIR PT BETON ELEMENINDO PERKASA BATUJAJAR

An archive is a collection of documents, documents, or files that have value for the company. The role of archives in a company is as a memory center, a controlling tool, a source of information used by companies to carry out analysis, planning activities, development, weighing in decision making, problem formulation, making attachments, accountability, assessment and control as precisely as possible. Archival rearrangement is the rearrangement of information and archive forms for the benefit of archive retrieval. The condition of handling archives in the Human Resources Department of PT Beton Elemenindo Perkasa can be said to be less precise, this can be seen from the number of missing archives, irregularly stored archives, there are still archives that use inappropriate storage systems, lack of equipment and supplies used to store archives. files. This phenomenon causes difficulties in the process of finding the archives needed by the company, so that it can hinder the company's work. Therefore, it is necessary to reorganize the archive handling project at the Human Resources DepartmentGeneral Affair of PT Beton Elemenindo Perkasa Batujajar by updating the storage system, storage procedures, archive borrowing procedures, archive discovery procedures, and adding archive facilities. The purpose of the archive handling reorganization project is to optimize the handling of existing records so that they are more effective and efficient. This project has been tested on June 3rd, 2021 with related parties, namely the Human Resources Department-General Affair Staff who doubles as archivist and the manager of the department. Based on the trials that have been carried out on this project, it can be said that the archive handling project at the Human Resources Department-General Affairs PT Beton Elemenindo Perkasa Batujajar is appropriate and very helpful for administrative staff in handling existing archives.