Reviewerly/exHarmony huggingface dataset:
Evaluation of English Language Learning (ELL) Websites using Automated Evaluation Tool

English Language Learning (ELL) websites provide excellent opportunities for language learning.In order to provide interactive, fun learning experiences, many teachers opt to use ELL websites and end up facing problems regarding the websites' accessibility and usability.Websites' quality is a key factor for users' acceptance and satisfaction.The proliferation of a variety of free and unique website testing tools has made it possible to quickly assess the quality of websites.This quantitative study aims at evaluating 5 free ELL websites in terms of Search Engine Optimization (SEO), performance, usability, social aspects and links using an automated evaluation tool i.e., SEOptimer.All in all, none of the 5 websites evaluated scored the overall grade A+ which indicates a critical need to improve the 5 aspects evaluated in order to increase their quality.This study contributes to the improvement of selected free ELL websites.Besides, it substantially advances the online learning trend in Malaysia by accentuating the potential free ELL websites to be explored and utilised by teachers to provide authentic English language learning experiences.Above all, the 5 aspects evaluated by SEOptimer form a comprehensive guide which will be useful for the curriculum developer and Ministry of Education to develop personalised online resources and websites for Malaysian primary students in ensuring quality education for all.
Impact of ICT Usage on Employee Performance among Medium Manufacturing Enterprises (MMEs): Mediating Role of Employee Engagement and Knowledge Sharing

Small and medium-sized businesses (SMEs) are an essential component of national economies worldwide since they are responsible for creating jobs, delivering services with added value, and advancing overall innovation.SMEs play an essential role in the generation of jobs in Malaysia, and the productivity of these enterprises is significantly correlated with employee performance.Literature on employee performance in SMEs still needs to be improved, despite the fact that these businesses significantly contribute to the country's GDP.This study investigates how ICT usage affects employee performance within Malaysian SMEs.In order to determine how the use of ICT usage influences employee performance in SMEs, the authors turned to the social exchange theory.This study presents a cross-sectional survey analyzed using SmartPLS 3.3.9for multivariate statistical analysis.An integrated research framework was developed by bringing together significant aspects from existing literature.301 employees of selected SMEs completed the survey.The findings of the study indicate that ICT usage affects employee performance.The study was done in SMEs, and the analysis is based on cross-sectional data that cannot be generalized to a broader range of industries.The study's outcomes will aid stakeholders, lawmakers, and SME management in lobbying for effective and well-articulated ICT usage strategies to enhance employee engagement, knowledge exchange, and performance.This study contributes to the literature by giving empirical evidence that ICT usage influences employee performance in Malaysian SMEs.
Mesh distance for dimension reduction and visualization of numerical simulation data

Computational modeling frequently generates sets of related simulation runs, known as ensembles. These simulations often output 3D surface mesh data, where the geometry and variable values of the mesh are changing with each time step. Comparing these ensembles depends on comparing not only geometric properties, but also associated field data. In this paper, we propose a new metric for comparing mesh geometry combined with field data variables. Our measure is a generalization of the well-known Metro algorithm used in mesh simplification. The Metro algorithm can compare two meshes but doesn't consider field variables. Our metric evaluates a single variable in combination with the mesh geometry. Combining our metric with multidimensional scaling, we visualize a low dimensional representation of all the time steps from a set of example ensembles to demonstrate the effectiveness of this approach.
Synergies Between Operations Research and Quantum Information Science

This article highlights synergies between quantum information science (QIS) and operations research for QIS-curious operations researchers (and vice-versa).
An Automated Identification Approach for Partial Discharge Detection Using Density-Based Clustering Without User Inputs

A recently published state-of-the-art density-based clustering technique called ICFSFDP for partial discharge detection requires various sensitive user-defined input parameters. This paper presents a parameter-free clustering technique called PDAutoClust for partial discharge detection. The PDAutoClust algorithm can produce high-quality clusters for partial discharge datasets without requiring user-defined input parameters. PDAutoClust produces high-quality clustering results by utilizing a vein-based density clustering approach. The vein of a cluster is produced by using multivariate kernel density estimation (KDE) and a unique neighborhood set (UNS). We compared the performance of PDAutoClust against ICFSFDP and seven other state-of-the-art density-based and non-density-based clustering techniques by using four partial discharge datasets in terms of adjusted rand index, normalized mutual information, F1-score, and purity. Another contribution of the paper is a novel merging technique used with PDAutoClust to merge small non-viable clusters that a clustering technique may produce. PDAutoClust produces the final clusters for a dataset by merging the non-viable clusters that a clustering technique may produce. We also evaluate the performance of PDAutoClust with merging technique versus PDAutoClust without merging technique using four datasets. Simulation results for PDAutoClust with the merging technique show good performance compared to ICFSFDP and seven other state-of-the-art clustering techniques. We also performed an ablation study to demonstrate the importance of the steps involved in PDAutoClust.
Product Sales Promotion Recommendation Strategy with Purchase Pattern Analysis FP-Growth Algorithm

The development of retail business technology is related to the need for management to meet customer demands by using technology. To help make effective sales strategic decisions, it is necessary to optimize the use of information technology on existing sales transaction data. The transaction database that has been stored as a company archive asset can be used for processing information that is useful in increasing product sales and promotions. This study aims to provide an analysis related to the product sales pattern of PT. X in Sumbawa Besar city. PT. X is a retail company that sells distributes daily consumer goods. The algorithm used is Frequent Pattern – Growth which is one of the algorithms in data mining used to find relationships in large data based on the number of occurrences of these data relationships. The Association Rule Mining method can be used in the retail business field, known as Market Basket Analysis. The application used for testing is Rapidminer 9.10. The research stages include: data collection, data preparation, FP-Growth algorithm implementation, result analysis and conclusions. The results of the tests carried out resulted in 819 rules with a total of 85 rules. The results of grouping strong rules based on the combination and number of products that produce information that is expected to be used as recommendations to promote products with discount, cross-selling, up-selling, product bundling and other types of promotions to increase product sales.
ACCESS SERVER: Dreaming, practicing and making access

ACCESS SERVER is an e-mail server that anonymizes, collects and financially compensates access requests that disabled people send to cultural institutions. This design research project pushes institutions towards caring for disability access, and upholds disabled knowledges that are currently underdiscussed, underpaid and not cared for by cultural institutions in Europe. In line with the UN Disability Treaty from 2016, ACCESS SERVER supports cultural institutions in transforming their practices so that accessibility is cared for. In this paper, we conceptualize ACCESS SERVER in relation to access, ableism and direct and indirect discrimination. We tend to conflicts, questions, and frictional anti-assimilationist crip technoscience (Hamraie and Fritsch, 2019) perspectives, and locate friction and its relation to heat as a link through technical practices that take shape against ableist cultural institutional infrastructures. In analyzing frictional experiences that emerged when institutional workers encountered the concepts around ACCESS SERVER and our demands for access, we identify three key barriers to partnership building between disabled people and institutions on the basis of our experiences with a European cultural institution: lack of accountability, lack of engagement and barrier guilt. Finally, we discuss technical-financial questions to realize ACCESS SERVER
Management Information System Web-Base on Blood Donation Service

Blood donation is an activity of sharing blood from a person to others in need. This activity was carried out because of the large number of patients in the hospital who needed blood for their illness. The amount of blood needed is not proportional to the amount of blood stock in the hospital, so it is deficient and requires a lot of blood from donors. The scarcity of blood stocks does not occur only in hospitals but also in PMI (Indonesian Red Cross) so that patients or families have difficulty finding blood to meet the needs of patients. The method used in these crisis conditions is to contact a few random people, or create information on personal social media about who can donate blood. This method is less efficient and effective because the data of potential donors is often also not qualified and data collection is also still done manually by the blood transfusion unit. Information technology is one of the solutions in providing information and data collection as well as management in the blood transfusion unit PMI Deli Serdang. In this case the R&amp;D method ( Research And Development) can help develop a management information system to collect data in blood donation services at PMI Deli Serdang.
MOBILE LIBRARY APPLICATION MODELING FOR STRENGTHENING DIGITAL-BASED STUDENT'S READING WRITING INTEREST

Digital literacy is very important at this time. Proficiency in using technology is a must in order to compete nationally and internationally. One way to improve literacy patterns is to obtain a lot of information and reading materials through the library. Technological devel-opments make libraries have to innovate so that conventional libraries become digital li-braries. At the library of the State Islamic University of North Sumatra (UINSU) Medan itself, the literacy pattern has utilized the digital library. It just needs better innovation by creating responsive mobile applications. This application model will focus on providing digital books so that they can be accessed from anywhere without having to visit the li-brary. The development of this application model uses the Research and Development (R&amp;D) method and is designed using the UML model and with various tools and various programming languages such as Android Studio, HTML, CSS, and PHP which will later produce a responsive web view. There are 3 access rights in the mobile library application, namely Administrators, Library Members and Library Visitors who have their own access rights. This application model runs well on the android platform which is relevant to today and makes it easy for users because it can be accessed anywhere and anytime and has online reading, borrowing and returning features.
Researchers Productivity Level Clustering Based On H-Index and Citation Using The Fuzzy C-Means Algorithm

The fuzzy C-Means algorithm is a partition-based clustering algorithm.Fuzzy C-Means is very helpful in modeling data whose distribution has outliers. Outliers are where there is a data object that is far apart from the existing clusters. Fuzzy C-Means groups data by minimizing the membership function of a data set. so that each piece of data can be a member of more than one group. In this study, the dataset used was the paper citation vs. H-index dataset in the Kaggle.com repository. This dataset is known to have outliers in fuzzy C-Means and has better performance compared to the K-Means and K-Medoid algorithms in modeling datasets that have outliers.
Decision Support System for Sentiment Analysis of Youtube Comments on Government Policies

Sentiment analysis is the process of classifying a text dataset as positive, negative or neutral. Youtube is one of the popular media used to provide responses to a problem. In the Jokowi era, infrastructure development was carried out massively and evenly, one of which was in Bali Province, namely the construction of the Mengwi-Gilimanuk Toll Road. The construction of the Mengwi-Gilimanuk Toll Road consumed a lot of people's agricultural land, which resulted in various pro and con responses from the community. From these problems, sentiment analysis is carried out to get community reviews related to the object being analyzed by utilizing algorithms to be able to classify opinions, in the construction of this system the naïve bayes algorithm is used with testing methods namely accuracy, precision, and recall. From the sentiment analysis conducted by utilizing 18 video links on YouTube with 701 comments, it produces positive sentiment as much as 50.64%, negative sentiment as much as 7.70% and neutral sentiment as much as 39.23%.
Surveillance detection of anomalous activities with optimized deep learning technique in crowded scenes

The performance of conventional surveillance systems is challenged by high error detection rates in busy scenes, which has significantly affected the accurate detection of the current surveillance system. Feature representation and object pattern extraction from different scenes have made deep learning (DL) promising methods in surveillance systems, compared to the approaches where features are created manually. To improve the detection accuracy, this paper presents an intelligent DL technique that combines convolutional neural network (CNN) and long short-term memory (LSTM). CNN extracts and learns the object features from a set of raw images, while the LSTM is then used by gated mechanisms to store important information from the extracted features. The proposed method was validated using datasets from the University of California San Diego (UCSD). The result shows that the model achieves 95% accuracy, which is superior compared to other conventional detection models.
Problems with the problem of consciousness. Abstractions and pseudo-abstractions

The problem of consciousness is explored in the article from conceptual and terminologi­cal perspective. The question of the origins of the ambiguity of the relevant philosophical terms is discussed and relevant examples are given. The basic premise of the study is the as­sertion that abstraction works as a differentiation of differences that characterize and sep­arate kinds of experience. A methodological distinction is made between abstraction and pseudo-abstraction, which can bear the same name, in this case “consciousness”. Termi­nology is interpreted as naming of abstractions of different levels and of realizable expe­riences. The term “consciousness” denotes an element of the ultimate distinction “con­sciousness/objective world”, abstracted from a series of distinctions that characterize the types and levels of experience. Pseudo-abstraction is formed from a series of pre-ex­isting meanings of the word “consciousness” without regard to realizable types of experi­ence as types of distinctions. There are two main alternative trends in the formulation of the problem of consciousness – structural-genetic and phenomenological. The high­lighted tendencies have something in common: the vagueness of the meaning in the use of the word “consciousness” and its functioning as a pseudo-abstraction. The ideological aspect of the problem is also considered. The principle of empiricism is identified with the recognition of the primacy of the diversity of experience as the source of abstraction. An alternative is formulated concerning the problem of the unity of consciousness. Husserl’s argumentation, through which an attempt is made to single out the sphere of consciousness as independent of any type of objectivity and as self-sufficient is analyzed, as well as the way he introduces such terms as “consciousness”, “sensation”, “experi­ence”, “perception” “intentionality”. Husserl’s thought experiment, the purpose of which is to prove the identity of the sensation of color from a real and illusory object, is sub­jected to a detailed analysis.
THE USE OF SHORT STORY AS MEDIA IN TEACHING NARRATIVE WRITING SKILL AT THE THIRD LEVEL OF INSTITUT PRIMA BHAKTI ( IPB ) PAMEKASAN

Writing is one of English skill. Writing is the most difficult skill to be mastered. The using of short story as media make the students easier to be the best writer. The researcher research the English teacher at IPB in using short story as media in teaching narrative writing skill. The purpose of this research are to know how the english teacher use short story as the media in teaching writing at third level of Institut Prima Bhakti (IPB) Pamekasan, second to know the students obtacle in using story as the media in teaching writing at third level of Institut Prima Bhakti (IPB) Pamekasan, and the third is to know the students responses the use of short story as media in teaching writing at third level of Institut Prima Bhakti (IPB) Pamekasan. The method used in this research was qualitative research. It was held on 20 June until 25 July 2016. In this class there were 12 students, 10 boys and 2 girls. The researcher used get the data are observation, interview, and documentation. The use of short story as media at IPB pamekasan is based by Ghasemy procedure there four steps in using short story in teaching narrative the first is pre-activities where students required to identify the new vocabulary a ttext of short story in group work, then discussed it in class. Second activities is comprehension work the teacher can help students prepare questions which can ultimately lead to the overall understanding of the text and explain narrative text. After that is Textual analysis and group work here the teacher started to ask the students to rewrite the story of the short story that their alredy disscussed. And the last is post-assignment or further task, the teacher asked the students to compose narrative text
THE TEACHERS’ DIFFICULTIES IN ENGLISH INSTRUCTION AT MTS RAUDATUL ULUM

The researcher investigates the specific problems as follows: (1) What are the teachers’ difficulties in English instruction at MTS Raudhatul Ulum? (2) How do the teachers overcome those difficulties in English instruction at MTS Raudhatul Ulum? This research use descriptive qualitative method because the researcher describe the teachers’ difficulties in English instruction and how the teachers overcome their difficulties. In collection the data the researcher use two kinds of data collection: observation and interview (interactive technique). Data source taken from the observation and interview. The interview were distributed to 2 English teachers of MTS Raudhatul Ulum. Teachers get three main difficulties that become a problem in English instruction. They were the difficulty on students’ mindset, difficulty on students’ interest toward English, and the last were the difficulty on students’ ability, the teachers difficult to instruct the students when they taught in the classroom. 2. There are three ways that the researcher found to overcoming those difficulties. The first is the teachers give spirit, the second is the teacher mix the language, using Indonesian language and both Indonesian and English language, but sometime the teacher using Arabic language, and the last is the teacher using innovative strategies when they taught in the classroom.
Video Image Analysis of Sports Skill Training on Account of Fuzzy Clustering Algorithm

With the development of Internet and audio and video technology, a large amount of training in the field of sports is stored in audio and video formats in various image analysis files. Professionals edit and optimize the audio and video of various activities in a large number of sports fields, which allows most netizens to check and watch, and refine the processing of this kind of video. In order to meet the market demand, all kinds of audio and video resources are modified, processed, and carefully packaged, so that the product has a new look. Sports skills training video image analysis application in the development of the Internet and audio and video technology to break through the obstacles of various important social issues in the field of video image analysis and application. This article studies a series of theories and knowledge of image analysis application in sports field, reveals the concept and definition of fuzzy clustering algorithm, and carries on application case disposal to sports skills training video image analysis application. By analyzing the actual effect of video images, based on fuzzy clustering algorithm for sports skills training video image analysis application study, test result shows that sports skills training based on fuzzy clustering algorithm video image analysis application in sports skill training video image analysis applications in image processing complexity, collaborative filterability, The efficiency of denoising and spatial accuracy is 83.32%, 90.01%, 92.25% and 98.10%.
The Effect of Using The Think Pair Share Learning Model To Enhance The Capability to Comprehending The German Text

This study aims to see the effect of using the Think Pair Share learning model on the ability to understand the text in the Arbeit am Text course. The TPS learning model is a cooperative learning model that can increase learner participation in the learning process. The sample for this research was the fifth-semester students of the 2019/2020 academic year with 22 students as respondents. This study consists of two variables, namely the independent variable and the dependent variable. The independent variable is the TPS learning model, while the dependent variable is the ability to understand the text. The method used in this research is an experimental method using data collection techniques Pre and Post Test. The data were then analyzed using the T-Test. With a significant level of Î± = 0.05, the results of the analysis show that the t count is greater than the t table, namely 7.93 â‰¥ 1.72. This shows that there is a significant effect of using the TPS learning model on students' ability to understand the text. Based on the results, it is concluded that the TPS learning model contributes to the improvement of students' ability to understand German language texts in the Arbeit am Text course