Reviewerly/exHarmony huggingface dataset:
Employee Turnover in the Fast Food Restaurants: Investigating the Role of Human Resource Management Practices

High Turnover (TO) rate among Fast Food Industry (FFI) employees is a critical issue faced by the Jordanian hospitality industry and be detrimental to the growth of the industry. Following that, is important to analyse the factors that lead to high TO rate among FFI employees. This study aims to examine the effect of Human Resource Management Practices (HRMP) and Intention to Leave (ITL) among FFI employees in Jordan. Five HRMP have been included in this study namely training, reward, benefit, performance appraisal and staffing. Using a sample of 245 FFI front-line employees working in Amman, this study has employed a quantitative research approach to answer the research questions. Multiple regression analyses using SPSS was performed to test the hypotheses of this study. As expected, HRMP namely, reward and benefit dimensions of HRMP found to be most significant practices in influencing ITL in this study. The findings of this study contribute to existing literature on the management of Human Resource (HR) and employee TO. It provides insights on the relationships between HRMP and ITL. Practical implications are also provided to managers to reduce TO among FFI employees in Jordan.
Opinions Summarization: Aspect Similarity Recognition Relaxes the Constraint of Predefined Aspects

Recently research in opinions summarization focuses on rating expressions by aspects and/or sentiments they carry.To extract aspects of an expression, most studies require a predefined list of aspects or at least the number of aspects.Instead of extracting aspects, we rate expressions by aspect similarity recognition (ASR), which evaluates whether two expressions share at least one aspect.This subtask relaxes the limitation of predefining aspects and makes our opinions summarization applicable in domain adaptation.For the ASR subtask, we propose an attention-cell LSTM model, which integrates attention signals into the LSTM gates.According to the experimental results, the attention-cell LSTM works efficiently for learning latent aspects between two sentences in both settings of in-domain and cross-domain.In addition, the proposed extractive summarization method using ASR shows significant improvements over baselines on the Opinosis corpus.
Seeing More Than Whitespace — Tokenisation and Disambiguation in a North Sámi Grammar Checker

Communities of lesser resourced languages like North Sámi benefit from language tools such as spell checkers and grammar checkers to improve literacy. Accurate error feedback is dependent on well-tokenised input, but traditional tokenisation as shallow preprocessing is inadequate to solve the challenges of real-world language usage. We present an alternative where tokenisation remains ambiguous until we have linguistic context information available. This lets us accurately detect sentence boundaries, multiwords and compound error detection. We describe a North Sámi grammar checker with such a tokenisation system, and show the results of its evaluation.
Evaluating Teachers’ Performance: A Need for Effective Teaching

This article reports a study, which aims to evaluate the EFL teachers’ performance of teaching in the English Education Department of Universitas Muhammadiyah Semarang (Unimus). The study was conducted to find out how competent the English lecturers/university teachers in the Department are in conducting an English Language Teaching (ELT) program in the classroom. A case study was employed to five teachers who taught the fifth-semester students in the Academic Year of 2017/2018. Through an observation during their teaching and learning process by involving four observers and through a questionnaire distributed to the 13 students in the fifth semester. The study shows the different results of teachers’ performance from both the teachers’ and students’ perspectives. Based on observation, it is revealed that the teachers’ performance in ELT program does not show a satisfactory result yet. The teachers tend to use unvarying methods and focus on certain students without knowing that some of them have learning problems. Meanwhile, from the questionnaire distributed to the students, it shows that the teachers have good competencies in conducting an ELT program in the classroom in which one of the indicators is seen from the personality of the teachers.
Monitoring Soil Surface Mineralogy at Different Moisture Conditions Using Visible Near-Infrared Spectroscopy Data

The soil minerals determine essential soil properties such as the cation exchange capacity, texture, structure, and their capacity to form bonds with organic matter. Any alteration of these organo-mineral interactions due to the soil moisture variations needs attention. Visible near-infrared imaging spectroscopy is capable of assessing spectral soil constituents that are responsible for the organo-mineral interactions. In this study, we hypothesized that the alterations of the surface soil mineralogy occur due to the moisture variations. For eight weeks, under laboratory conditions, imaging spectroscopy data were collected on a 72 h basis for three Silty Loam soils varying in the organic matter (no, low and high) placed at the drying-field capacity, field capacity and waterlogging-field capacity treatments. Using the Spectral Information Divergence image classifier, the image area occupied by the Mg-clinochlore, goethite, quartz coated 50% by goethite, hematite dimorphous with maghemite was detected and quantified (percentage). Our results showed these minerals behaved differently, depending on the soil type and soil treatment. While for the soils with organic matter, the mineralogical alterations were evident at the field capacity state, for the one with no organic matter, these changes were insignificant. Using imaging spectroscopy data on the Silty Loam soil, we showed that the surface mineralogy changes over time due to the moisture conditions.
Commonsense inference in human-robot communication

Natural language communication between machines and humans are still constrained.The article addresses a gap in natural language understanding about actions, specifically that of understanding commands.We propose a new method for commonsense inference (grounding) of high-level natural language commands into specific action commands for further execution by a robotic system.The method allows to build a knowledge base that consists of a large set of commonsense inferences.The preliminary results have been presented.
Design of Reporting, Evaluation, and Monitoring Application for Student Organization in University

In few decades, the development of information system has been increased rapidly. It is because most organization in various sector of industries, commerce, government, or even education become highly dependent on the use of information system. The purpose of this study is to design the application that will facilitate the reporting, evaluation, and monitoring activities of student organization based on what user needs. The object of this study is student affair department in one of faculty in one of universities in Indonesia. The method employed in this study to design the system is waterfall. The system designed in this study is focus on the activities related to student organization activities. The result of this study found that there are eight dimensions of web quality that has to be fulfilled by the system according to the result of focus group discussion and Delphi method. The system designed in this study was adjusted to the needs that have been defined previously.&#x0D; &#x0D; Keywords—Information system design, student organization, waterfall method
The Role of Visual Tools and a Virtual Learning Environment in Student Teachers’ Internship

The relevance of this work is conditioned by the important role and aims of a teaching internship within the framework of student teachers' training.The use of a virtual learning environment requires a comprehensive experimental evaluation and may contribute to the resolution of a number of problems which are specific to the teaching internship.The article deals with the evaluation of an educational process implemented outside the university, and this evaluation must be performed with regard to multi-tiered interaction between the participants of educational process.The main theses of this research may be correlated with the stages of planning and undergoing of teaching internships.The following tools are used during development of the motivational and axiological basis of internships, the stage of its implementation, and subsequent self-assessment: a set of videos (which summarize selected topics) created by senior students when they were undertaking similar internships; simple graphic instructions which allow students to plan and undergo their internship effectively, write an internship report, and create and attach videos to their reports; expert analytical forms necessary to assess the course of internship and its results.The research included a survey among student teachers who were asked to identify difficult aspects of internship's planning and implementation in a specifically created collective environment for research data with the use of the following means: creation of collective questionnaires, visual representation of the tabulated survey data, and statistical analysis with the use of summarized tables.Based on the analysis of the work results of student teachers who have already done their internship and acquired the experience of educational process planning, the major issues were identified and described and visual tools for overcoming these issues were tested.The article describes an approach that helps student teachers overcome the barriers between existing visual educational tools within their training and insufficient orientation of school internships towards these tools' effective application in higher education.The methods of students' motivation for self-education and their implementation during the teaching internship were experimentally assessed in this research.
INVESTIGATING THE DETERMINANTS OF FINANCIAL DEVELOPMENT IN OPEC COUNTRIES: AN APPLICATION OF BAYESIAN MODEL AVERAGING APPROACH

The purpose of this study is to investigate the most significant determinants of financial development in OPEC countries during 2014-2016. To this end, this paper considered 34 explanatory variables including several economic and policy variables determining four different aspects of financial development as the degree of depth, efficiency, stability and quality of financial services. In order to obtain more reliable results and overcome the uncertainty problem in this study, we applied Bayesian Model Averaging (BMA) technique. The results indicated that better institutional indicators such as rule of law, government effectiveness, and corruption avoidance are associated with greater financial depth, efficiency, and stability. More importantly, the results revealed that the development in the oil sector could support financial development, and in particular contribute to greater depth and efficiency of the stock market. There are some important implications in this research for policymakers to promote financial development in OPEC countries.Keywords: Financial development, Oil, OPEC, Bayesian model averagingJEL Classifications: G10, G20, C11DOI: https://doi.org/10.32479/ijeep.8498
Attractors and asymptotic dynamics of open discrete-time quantum walks on cycles

Open quantum walks often lead to a classical asymptotic behavior. Here we look for a simple open quantum walk whose asymptotic behavior can be nonclassical. We consider a discrete-time quantum walk on an $n$-cycle subject to a random coin-dependent phase shift at a single position. This finite system, whose evolution is described by only two Kraus operators, can exhibit all kinds of asymptotic behavior observable in quantum Markov chains: It either evolves towards a maximally mixed state, or partially mixed state, or tends to an oscillatory motion on an asymptotic orbit. We find that the asymptotic orbits do not have a product structure; therefore, the corresponding states can manifest entanglement between the position and the coin degrees of freedom, even if the system started in a product state.
Z&amp;lt;sub&amp;gt;2&amp;lt;/sub&amp;gt; (Z&amp;lt;sub&amp;gt;2&amp;lt;/sub&amp;gt;+uZ&amp;lt;sub&amp;gt;2&amp;lt;/sub&amp;gt;)(Z&amp;lt;sub&amp;gt;2&amp;lt;/sub&amp;gt;+uZ&amp;lt;sub&amp;gt;2&amp;lt;/sub&amp;gt;+u&amp;lt;sup&amp;gt;2&amp;lt;/sup&amp;gt;Z&amp;lt;sub&amp;gt;2&amp;lt;/sub&amp;gt;)-Additive Cyclic Codes

In this paper, we introduce the algebraic structure of Z 2 (Z 2 +uZ 2 ) (Z 2 +uZ 2 +u 2 Z 2 ) -additive codes and Z 2 (Z 2 +uZ 2 ) (Z 2 +uZ 2 +u 2 Z 2 ) -additive cyclic codes.Compared to the Z 2 Z 4 Z 8 -additive codes, the Gray image of any Z 2 (Z 2 +uZ 2 ) (Z 2 +uZ 2 +u 2 Z 2 ) -linear code will always be a linear binary code.Therefore, we consider the Z 2 (Z 2 +uZ 2 ) (Z 2 +uZ 2 +u 2 Z 2 )additive cyclic codes as a (Z 2 +uZ 2 +u 2 Z 2 ) [x] -submodule of Z 2 α ×(Z 2 +uZ 2 ) β ×(Z 2 +uZ 2 +u 2 Z 2 ) θ .We give the definition of Z 2 (Z 2 +uZ 2 ) (Z 2 +uZ 2 +u 2 Z 2 ) -additive codes with generator matrices and parity-check matrices.Furthermore, we give the fundamental result on considering their additive cyclic codes with generator polynomials and spanning sets.
Assessing the Lexico-Semantic Relational Knowledge Captured by Word and Concept Embeddings

Deep learning currently dominates the benchmarks for various NLP tasks and, at the basis of such systems, words are frequently represented as embeddings --vectors in a low dimensional space-- learned from large text corpora and various algorithms have been proposed to learn both word and concept embeddings. One of the claimed benefits of such embeddings is that they capture knowledge about semantic relations. Such embeddings are most often evaluated through tasks such as predicting human-rated similarity and analogy which only test a few, often ill-defined, relations. In this paper, we propose a method for (i) reliably generating word and concept pair datasets for a wide number of relations by using a knowledge graph and (ii) evaluating to what extent pre-trained embeddings capture those relations. We evaluate the approach against a proprietary and a public knowledge graph and analyze the results, showing which lexico-semantic relational knowledge is captured by current embedding learning approaches.
PERGESERAN LAYANAN PERPUSTAKAAN PERGURUAN TINGGI MELALUI KONSEP VIRTUAL LIBRARY (Studi Kasus di Perpustakaan Universitas Mercu Buana Jatisampurna )

The development of information technology in the end encourage librarians to increase the use of ICT within the administering College Library. His goal was to be able to run the College Library functions with either IE as the brain knowledge and supporting the learning process through the availability of existing collections in the library. Librarians are beginning to understand that the service given by the library against pemustakanya can continue to improve in so well that pemustaka especially in access to information. The purpose of access to information in the era of the revolution Indutsri 4.0 at this time is how information can be received by pemustaka in quick time effectively and efficiently. Implementation of the virtual library on the College Library has the ability in solving problems, information explosion of the presence information and the influence of development of information technology. College Library's needs clearly felt it is important to use the right information technology, so that it can access a variety of information from around the world.
Analisis Faktor Pendukung Penjualan pada DOC Ayam Broiler Menggunakan Algoritma MOORA pada PT. Karya Semangat Mandiri Pematangsiantar

Day Old Chicken (DOC) is one day old chicken, usually weighs and weighs an average of 35-40 grams. Researchers took a case study at PT. Karya Semangat Mandiri which is a child of PT. Charoen Pokphand where the company produces animal feed, Day Old Chicks and Indonesia's largest processed food company in Balaraja is one of the leading companies in the field of agribusiness in Indonesian. PT. Karya Semangat Mandiri is a subsidiary where in its implementation it still has problems, especially in the selection of Broiler Chicken DOC quality that will be distributed to several partners that have been incorporated. In this study, the authors analyzed the strategy of increasing sales in the selection of Broiler Chicken DOC Quality using the MOORA Algorithm. The author obtained data directly from PT. Karya Semangat Mandiri. The attributes used are eight, namely the title (C1) , abstract (C2) , introduction (C3) , objectives (C4) , methods (C5), results and discussion (C6) , conclusions (C7) and bibliography (C8). With this analysis, it is expected recomended to PT. Karya Semangat Mandiri in increasing sales so that it can add partners who want to join in it based on the algorithm used.
Identifikasi Ekstraksi Fitur untuk Gerakan Tangan dalam Bahasa Isyarat (SIBI) Menggunakan Sensor MYO Armband

Indonesian: Indonesian SIBI has been widely reviewed by researchers using different types of cameras and sensors. The ultimate goal is to produce a strong, fast and accurate movement recognition process. One that supports talk of movement using sensors on the MYO Armband tool. This paper explains how to use raw data generated from the MYO Armband sensor and extract integration so that it can be used to facilitate complete hand, arm and combination movements in the SIBI sign language dictionary. MYO armband uses five sensors: accelerometer, gyroscope, orientation, euler-orientation and EMG. Each sensor produces data that is different in scale and size. This requires a process to make the data uniform. This study uses the min-max method to normalize any data on the MYO Armband sensor and the Moment Invariant method to extract the vector features of hand movements. Testing is done using sign language Movement statistics both dynamic signals. Testing is done using cross validation.
No, you’re not alone: A better way to find people with similar experiences on Reddit

We present a probabilistic clustering algorithm that can help Reddit users to find posts that discuss experiences similar to their own.This model is built upon the BERT Next Sentence Prediction model and reduces the time complexity for clustering all posts in a corpus from O(n 2 ) to O(n) with respect to the number of posts.We demonstrate that such probabilistic clustering can yield a performance better than baseline clustering methods based on Latent Dirichlet Allocation (Blei et al., 2003) and Word2Vec (Mikolov et al., 2013).Furthermore, there is a high degree of coherence between our probabilistic clustering and the exhaustive comparison O(n 2 ) algorithm in which the similarity between every pair of posts is found.This makes the use of the BERT Next Sentence Prediction model more practical for unsupervised clustering tasks due to the high runtime overhead of each BERT computation.
Determining Optimal Mining Work Size on the OpenCL Platform for the Ethereum Cryptocurrency

In terms of cryptocurrency, mining is a process of creating a new transaction block to add it to the blockchain. The cryptocurrency protocol should ensure the reliability of new transaction blocks. One of the popular mining protocols is the Proof-of-Work protocol, which requires the miner to perform a certain work to verify its right to add a new block into the blockchain. To perform this work, high-performance hardware is used, such as GPU. On the program level, hardware needs special computing framework, for example, CUDA or OpenCL. In this article, we discuss Ethereum cryptocurrency mining using the OpenCL standard. The Ethereum cryptocurrency is the most popular cryptocurrency with GPU-based mining. There are several open-source implementations of the Ethereum cryptocurrency miners. The host-part of the OpenCL-miner is considered, which makes the research results independent of the mining algorithm and allows using the results of the research in the mining of other cryptocurrencies. During the research, we have found the problems, which lead to mining productivity loss, and we are looking for the ways to resolve these problems and thus increase mining performance. As part of solving these problems, we have developed the algorithm for the functioning of the miner and proposed the methodology of determining the optimal size of OpenCL work, which allows to reduce the impact of problems found and achieve maximum mining productivity using OpenCL framework.
Analisis Metode Naive Bayes dalam Memprediksi Tingkat Pemahaman Mahasiswa Terhadap Mata Kuliah Berdasarkan Posisi Duduk

In the lecture room there can be more than 30 students and not all of them get comfortable sitting positions, comfortable to look forward to, comfortable to see lecturers and comfortable to show what the lecturers say so students who sit in the front position and position behind are not the same understand the subject given by the lecturer. hence the purpose of the study is to describe the influence of seating in the lecture hall on the level of student achievement during lecture hours taking place using the Naive Bayes method, in order to find out whether students sitting in the front position will be more understanding than the sitting position at the back so that they can improve achievement scores . after gaining experience in occupying different seating positions, students are asked to fill out a questionnaire relating to the chosen seating position in each form. It is hoped that this study can determine the effect of understanding students or not on subjects based on seating position so that later the output of this system can be an evaluation material to improve student achievement.
EFFICACY OF THE SPIDER WEB METABOLITES ACTIVITY AGAINST MULTI DRUG RESISTANCE (MDR) BACTERIA

Antibiotic resistance, which is emerging among pathogenic bacteria, is a leading cause of treatment failure worldwide with particular reference to developing countries.Thus, there is a need to explore and discover novel antimicrobial agents.The objective of this study was to investigate antibacterial activity of spider web metabolites and characterize certain antibacterial compounds.Web solvent extract (methanol, ethanol and acetone) was biologically screened for antibacterial activity against seven multiple drug resistant bacteria including three Gram negative bacteria (E.coli, A. baumannii, and S. typhi) and four gram positive bacteria (S. aureus, Bacillus, E. faecalis and S. pneumonae) using well diffusion test.Solvent extracts with the concentrations of (3.3 mg/ml 4.95 mg/ml 6.6 mg/ml 8.25 mg/ml 9.9 mg/ml and 11.55 mg/ml) were used to check the efficiency against MDR bacteria.Solvent extract of web metabolites exhibited significant activity against all seven MDR bacteria, by producing clear growth inhibition zones ranging in diameter from 04 to 22 mm.Considerable activities was exhibited against E. faecalis (22 mm), E. coli (14 mm) and S. typhi (15 mm).Acetone solvent extracts showed high antibacterial activity against most MDR bacteria.Solvent extracts with concentrations less than 5 mg/ml did not exhibit sufficient activity.Higher activities were related to concentrations higher than 6 mg/ml.Findings of the current study indicated that spider web metabolites may show promising antimicrobial activity against MDR bacteria.Additionally, the results suggest that spider web may be a broad spectrum antimicrobial agent, wherein its individual constituents contribute to its antimicrobial activity.