Reviewerly/exHarmony huggingface dataset:
Does economic freedom promote financial development? Evidence from EU countries

This study empirically investigates the relationship between economic freedom and financial development in EU countries. Using panel data covering the years 2000–2017 and employing fixed effects, random effects, and the generalised method of moments (GMM), the paper examines the effect of economic freedom on financial development. The research results demonstrate that greater economic freedom is conducive to financial development in the EU. These findings remain robust to the use of an alternative index of economic freedom. The results imply that policies which promote economic freedom are likely to raise the level of a country’s financial development.
Research publications and scholarly content in school education with special reference to national institute of education

The present paper emphasized on research publication, scholarly content and scholarly publication along with their clear definitions and differences.National institute of education (NIE) being part of NCERT is specialised in the field of school education and responsible for promotion, propagation and undertaking extension activities and a national research centre in the field of school education.The present paper explained in detail the kinds of scholarly publication brought out by NIE and enhances academic and research visibility of the institution.
Sistem Pakar Identifikasi Penyakit Kulit Melanoma dengan Metode Teorema Bayes

Melanoma is a skin cancer disease that occurs due to abnormal growth of melanocytes, which are cells that can produce pigment in the skin. Melanoma is one of the most vicious skin cancers and can easily spread to other organs in the human body, such as the lungs and brain. This expert system for diagnosing melanoma skin disease is a computer-based system that is used as a tool for diagnosing melanoma skin disease based on a dynamic knowledge base. The purpose of this research is to build an expert system that can identify Melanoma Skin Disease. An expert system built using the Bayes theorem method in a diagnostic process based on expert knowledge or experience. The results of this study present an expert system capable of diagnosing melanoma skin disease quickly, precisely and accurately. These results are presented in a system built in the form of a website using PHP programming with a MySQL database. Overall this expert system can be useful for patients or the general public to be able to know clearly about melanoma skin disease from the symptoms and can provide solutions in handling it.
Modeling an Adaptive e-Learning System for Improved Learning Performances

In majority of the online learning systems in use today, lack proper integration of adaptive, collaborative, personalized and ubiquitous concepts in their design and implementation.Integration of these basic concepts in online learning systems will enable adaptation, individualization, and collaboration of learning resources to learners' preferences, with an added advantage of accessibility to online resources anywhere and any time.Hence, the research proposes an Adaptive E-Learning System (AES) model that incorporates activities sequencing in a personalised, adaptive, collaborative and ubiquitous learning environment.The system model consists of the system (software) architectural diagram and mathematical model of activity sequence.The design is presented using the UML activity diagram and the class diagram.The full implementation of the system is currently being carried out and is being tested with real life cases..
Learning by Playing. A Case Study of the Education in Photography by Digital Games

Aim. The study aims to explore the current state of digital game-based learning to reflect the extent, possibilities, opportunities, and limitations of its implementation in the specific field of education as visual art, especially photography. Method. The explorative study employed the method of theoretical analysis of available literature and other secondary sources related to the issue, and subsequently applied the method of an illustrative (descriptive) case study. Results. Photo modes of commercially available digital games, originally intended to increase the players’ retention and participation, have led to the birth of a new art form, virtual photography. The technology of photo modes in a larger variety of recent games has made virtual photography available to significantly more players. Photo modes provide artistic control and creative options alongside a whole catalogue of lenses, camera parameters, and other features, reducing the financial burden associated with the purchase of photographic equipment. Furthermore, photo modes offer more than just a substitutable alternative to traditional photography, as added artistic value is found within virtual worlds. Conclusions. Despite some limitations regarding the overall implementation of digital game-based learning in photography classrooms, photo modes of commercially available digital games are a suitable tool for educational efforts in photography through both self-development and measurement of outcome-based learning.
MENAKAR PEMAAFAN PADA PENYINTAS CYBERBULLYING

The purpose of this study is to see an overview of cyberbullying survivors' forgiveness in post-pandemic life. This research uses a quantitative descriptive approach. The research subjects were obtained through a purposive sampling technique, with characteristics, students who are cyberbullying survivors, with an age range of 18-21 years. Screening is carried out with a cyberbullying questionnaire containing questions related to self-identity, types of cyberbullying (based on Willard's theory namely, flaming, harassment, denigration, impersonation, outing &amp; trickery, exclusion, and cyberstalking), repeated experiences of cyberbullying, and perpetrators of cyberbullying, to ensure that the subject is truly are truly survivors of one or more types of cyberbullying. The research subjects were 109 students who were obtained from the screening results and statements of willingness. Data collection uses a scale of forgiveness (25 items, α = .931). Data analysis was performed using the Statistical Packages for Social Sciences (SPSS) version 26.0 program. The results showed that the subject's forgiveness was in the medium category, with a total of 62 people (57%), and the empirical mean was 58.16, within the medium category range (50 – 75). These results indicate that the forgiveness of cyberbullying survivors is not optimal, there are still 32 people (29%), in the low category. This condition occurs because most of the subjects are dealing with more than one type of cyberbullying, as well as the anonymity factor of the perpetrators of cyberbullying, most of whom come from strangers. No significant differences were found between male and female survivors' forgiveness.
Machine Learning on Standard Embedded Device

Developers of ARM microcontrollers now have access to the first neural network software development tools, making machine learning in embedded systems a possibility.This study examines the application of one such tool, the STM Cube AI, on popular ARM Cortex-M microcontrollers.It evaluates and contrasts its performance with that of two others widely employed supervised machine learning (ML) algorithms, namely Support Vector Machines (SVM) and k-Nearest Neighbors (k-NN).The outcomes of three datasets demonstrate that X-Cube-AI consistently delivers good performance despite the shortcomings of the embedded platform.Popular desktop programs like TensorFlow and Keras are seamlessly incorporated into the workflow.
An Algorithm for Faster Keyword Detection on a Forensic Image

An algorithm that has been developed for keyword searching on forensic images is something that isn't widely dispersed within the forensic community, due to minimal research and literature being carried out and applied within this topic area.This research aims to build upon this by developing and enhancing the efficiency of keyword search through the creation of an algorithm.This has been tested against forensic image formats with the implementation of a scientific method.With the approach demonstrating the efficiency of an algorithm which uses parallel keyword searching to locate a keyword, this has been implemented within the algorithm that has been have created.The results collected are then cross compared against the timings of open source software tools that are developed for the keyword searching of a forensic image.
PEER EVALUATION'S IMPACT ON EFL LEARNERS’ LANGUAGE LEARNING, MORPHOLOGY UNDERSTANDING, AND VOCABULARY ACQUISITION

&lt;div&gt;&lt;p&gt;The primary goal of this study is to increase readers' understanding of assessment for language learning and development, particularly as it relates to morphology for students of EFL (English as a Foreign Language). We also consider noting the many assessment methods that might be employed to determine how well EFL students understand morphology. Second, we'll go over a variety of language-improvement strategies that we could use to help EFL students better understand English morphology. We'll look at a few benefits of peer evaluation for EFL learners' vocabulary and morphological comprehension in the third segment. This study will go over peer assessment's benefits, the process of language improvement in English morphology, and evaluation as a critical component of language learning.&lt;/p&gt;&lt;p&gt;&lt;strong&gt;&lt;span&gt;Keywords: &lt;/span&gt;&lt;/strong&gt;&lt;span&gt;morphology, assessment, affixation, compounding, conversion, etc.&lt;strong&gt;&lt;/strong&gt;&lt;/span&gt;&lt;/p&gt;&lt;/div&gt;
Decoupling Source and Semantic Encoding: An Implementation Study

Despite the remarkable achievements of modern communication systems based on Shannon’s theory, there is still considerable room for exploration in information transmission capacity, and semantic communication technology has emerged as a promising approach in this regard. Nonetheless, the benefits of semantic communication remain elusive, and the absence of a unified system model has hindered practical implementation. In this context, we contend that semantic communication can benefit from data distortion and the incorporation of natural language modeling information, such that source coding with semantic modeling information does not compromise the performance of semantic communication systems. To fortify our stance, a novel Separated Data-Semantic Coding (SDSC) system is proposed, which disentangles the source coding and semantic coding. Furthermore, relevant experiments are conducted to validate the contention and the SDSC system. By illuminating the superiority of semantic communication, the research not only contributes to the advancement of semantic communication technologies but also facilitates the development of more practical communication systems.
Cognitive Information Systems and Related Architecture Issues

The rapid developments in information technology and business, must drive the progress of Cognitive Information Systems (CIS).There are some studies on the generic model of CIS analysis and design.The work herein, seeks to combine multiple CIS and Understanding-based management systems concepts into a single design strategy (UBMSS).But they weren't identified as modeling artifacts or as building blocks as enabler that are required to construct a consistent and integrated system.The artifacts that are the basis to generate functions for CIS are as follows: semi-structured documents, models of business processes, components of knowledge management, building blocks of the enterprise, and information architecture, along with autonomous software components, and methods of Artificial Intelligence (AI).The above-described parts, were merged into a single framework for CIS modeling.This framework is based on the object-oriented paradigm.The study seeks to characterize and propose an overall model that helps us comprehend CIS and UBMSS features, allowing us to build a realistic development strategy for Cognitive Information and Cognitive Management Systems (CMSs).
Applied Linguistics Research Articles in Saudi Arabia: A Content Analysis

This study aims at investigating applied linguistics research articles (ALPRAs) in the Kingdom of Saudi Arabia (KSA) that were published during 2004 – 2022. More precisely, it sought to reveal those articles' distribution, topics they covered, research methods they adopted, data collection instruments, sample members and size, and data analysis techniques they followed. An article classification form (ACF) was adopted to analyze 455 ALPRAs, which were collected through a purposive sample. Results showed that most research articles were published during 2019 – 2022, language teaching and learning/teaching methods were the most AL investigated topics during this period, the quantitative approach dominated the ALPRAs in KSA, and questionnaires were the prevailing data collection tools. Moreover, undergraduates whose numbers ranged between 31 – 100 and 101 – 300 were the sample members and the sample size adopted in ALPRAs. The study recommended that well-designed research method courses are needed to be provided by English Departments in Saudi Universities.
A Multichannel Convolutional Neural Network for Multilabel Sentiment Classification Using Abilify Oral User Reviews

Nowadays, patients and caregivers have become very active in social media. They are sharing a lot of information about their medication and drugs in terms of posts or comments. Therefore, sentiment analysis plays an active role to compute those posts or comments. However, each post is associated with multilabel such as ease of use, effectiveness, and satisfaction. To solve this kind of problem, we propose a multichannel convolution neural network for multilabel sentiment classification using Abilify oral user comments. The multichannel represents the multiple versions of the standard model with different strides. Specifically, we use the pre-trained model to generate word vectors. The proposed model is evaluated with multilabel metrics. The results indicate that the proposed multichannel convolutional network model outperforms the traditional machine learning algorithms.
Design and Analysis of the Dual Axis Tracking System for Solar Thermal Concentrator in Erbil City using Arduino Controller

Solar thermal is a kind of renewable energy that converts solar radiation to heat using a concentrator that concentrates the heat in the focal point. The receiver is located in the focal and transfers heat to the flowed water, rising the water temperature beyond boiling. To harvest the most solar efficiency, a dual tracking system is used that tracks the sun during the daytime. This paper proposes implementing Arduino Uno dual axis tracking system for the solar parabolic concentrator dish. The tracking system is controlled and managed by using an Arduino microcontroller and light sensors. The proposed system has been installed in the city of Erbil and the testing results showed the success of the proposed system in which the dual tracking system tracked the sun precisely and the concentrator with the help of the receiver raised the flowed water to the desired temperature.
How to increase customer satisfaction in FMCG industry using social media analytics

Social media has become a component of living for more people worldwide. Businesses are undoubtedly using it to instantly and easily create, in addition to share information with all the customers and gain gained from this seamless interaction. Due to the improved social media platforms and members, the wish to watch, extract, analyze and report the info created on these platforms has also enhanced many businesses. Current labor identifies the social media analytics progression and internet show application. It identifies the different phases of the SMA process, together with their integration on the internet, to show strategy, options, and difficulties. SMA metrics for the client life cycle are discussed. A comparative analysis is still presented for different SMA plans to identify their energy to the web FMCG.
Similarity Detection in Two or More Submitted Documents

Abstract: Educational Institutions &amp; Organizations of the modern era are rapidly adopting the hybrid work culture, in the aftermath of the worldwide pandemic. Institutions &amp; Organizations frequently require authentic, original content for a wide variety of purposes. Though students &amp; employees strive towards that objective, plagiarized content often slips through scrutinization more often than the acceptable count. This paper aims to analyze and record the process &amp; outcomes of building a web application that enables similarity detection between two or more files by uploading them on the application, or in other words, determine the similarity between the files. The web application will accept two or more files as input, and return similarity percentage which will be calculated using the Levenshtein distance Algorithm, as an automated report that will be sent to the user as an email. In our case, the web application will be majorly utilized to curb similarity in assignments. Along with this, the application will have a feature that allows any teacher to compare any two or more assignments submitted in a particular class, with just one click.
Android Based Online Application for Students Information System

Abstract: Now-a-days in our daily life students use WhatsApp, Facebook, Twitter, Instagram, etc., Students get theircollege feed via email or some other applications provided but people see that few of the students do not get the information passed to them due to some technical issues and in other cases the students cannot clarify their doubt in the teachings taught in the college and face difficulty and much more issues, few of them may also face issues as it is a public IP which is given to them, So in consideration to the above issues faced by the students our team is trying to develop an application which is specifically designed for the students or you can say to the particular college. Here the developed application will perform the following tasks as sharing files, receive college feed and we are able to interactwith the faculty in the form of messaging. To develop this application, the format used is programming language JAVAlanguage to write the code for our application and the software used is Android Studio software to build an application,in this we can build, test, and debug our application easily.
Universal Language Model Fine-Tuning for Text Classification

Abstract: We describe approaches that are essential for fine-tuning a language model further utilized for text categorization and propose Universal Language Model Fine-tuning (ULMFiT), an efficient transfer learning method that can be used for any NLP activity. Transfer learning methods have greatly impacted computer vision, but existing approaches in NLP still require taskspecific modifications. Universal Language Model Fine-tuning, or ULMFiT, is an architecture and transfer learning method that can be applied to NLP tasks. It involves a 3-layer architecture. Three steps make up the training process: pre-training for the general language model on a text taken from Wikipedia; fine-tuning the language model on a target task; and fine-tuning the classifier on the target task. Deep learning techniques enable computers to learn and comprehend natural language, facilitating human-machine interaction. Deep learning models are often employed in medical research, from medication candidate identification to picture analysis. On text classification tasks, our method greatly surpasses the state-of-the-art (it is the most recent model incorporating the best and latest technology), reducing the error on most datasets. Furthermore, with only a few labeled examples, it can match the performanceof training on 100× more data.
The Influence Of Librarians' Competence On Their Performance At The Jatinangor Institute Of Home Affairs Governance (IHAG) Library

The purpose of this study is to determine the influence of librarians' digital competence on their performance at the Jatinangor IHAG Library. This is a quantitative study with data collected from 30 respondents through questionnaires. The statement items from Marguna and Sangiasseri (2020) were used to provide answers to the problem formulation. The results showed that the librarians' digital competence and performance are included in the fairly good category. In conclusion, Digital Competence (X) as the independent variable influences the dependent one, namely Librarians' Performance (Y), with a value of 31.1%.
THE EFFECT OF SELF EFFICACY ON SELF REGULATED LEARNING AMONG STUDENTS OF STATE ISLAMIC UNIVERSITY DURING ONLINE LEARNING

This study aims to learn the effect of self-efficacy on self-regulated learning during online learning for Islamic students. The sampling technique used was purposive sampling, with a total sample of 410 Raden Fatah State Islamic University (UIN) Palembang students. The results showed that the relationship or the value of the correlation coefficient between the variables of self-efficacy and self-regulated learning was 0.466. The significance value is 0.0019 where (p&lt;0.05') then (sig='0.001&lt;0.05) and the results of hypothesis testing are known that the results of the R-square test of the self-efficacy variable on self-regulated learning are 0.217. These results indicate that 21.7% of self-efficacy affects self-regulated learning variables. Thus, self-efficacy and self-regulated learning have a significant positive effect on Islamic students at the Raden Fatah State Islamic University (UIN) Palembang. In other terms, the higher the self-efficacy, the higher the level of self-regulated learning.
Factors promoting daily usage of alcoholic substances in Ubungo District

Topics concerning the usage of alcoholic substances have always caught the attention of different health science and social science professionals because of the tenacious growth in alcohol consumption and its effects. Due to such a fact, this study was conducted in Ubungo District in order to determine the factors that promote the daily usage of alcoholic substances. A cross-sectional research design and purposive sampling were employed to manifest data collection within a sample size of 240. The obtained data were gathered through semi-structured interviews and presented in tables, showing frequencies and percentages. The results show that alcoholic substances are daily consumed due to the availability of alcoholic centers, low/affordable price of alcoholic substances, the nature of works of people, bundles promotion and offers from friends/relatives, family history of the users, less purchasing restrictions, individual’s perception on alcoholic beverages, advertisement of the substances on media, and alcohol dependency and addiction. Finally, rescuing the alcohol addicts, the concerned authorities should set and enforce rules and restrictions concerning the sales and consumption of the substances; and provide psycho-educational programs and seminars on abandoning alcohol abuse, dependency, and addiction, so as to minimize financial bankruptcy and other social or family conflicts brought about by daily consumption/usage of alcoholic substances.