Reviewerly/exHarmony huggingface dataset:
Influence of Job Characteristics on Employees’ Job Satisfaction: An Empirical Study

The objectives of the present study were to find out the influence of job characteristics on the job satisfaction in employees of Community Rehabilitation Projects and Sustainable Livelihood Project of non-Governmental organization. To respond to the problems presented and established on the literature reviewed, the researcher proposed several null hypotheses.Methodology - The present study adopted survey method. Purposive random sampling technique was embraced to choose samples and the data was collected by using virtual platform. 38 items were used to assess the job satisfaction of the employee in our present study.  Participants, n = 267 (89%) returned the filled questionnaires.Findings - The findings of the present study of showed that the job satisfaction exists among the employees at mean value 5.65 with standard deviation of 0.64. It was very evident from the analysis that both job characteristics and psychological states are important for the employees’ job satisfaction. The results were interesting and displayed that all the variables had significant relationship between skill variety, task identity, task significance, degree of autonomy and feedback and their perception of job satisfaction. The results revealed that the significant levels between all the variables were (0.00) which is significant at (0.05). All the values of correlation coefficient (r) between the variables of psychological states were interesting and showed less than 0.5 (r  <=  0.5), which indicated us there was a low positive correlation between the variables of job characteristics.
VUT Libraries: Faculty of Applied and Computer Sciences: Search Google Scholar

This guide contains genral library information for the Faculty of Applied and Computer Sciences.
Rekomendasi Pembentukan Kelompok Kerja bagi Mahasiswa berbasis Sentiment-Epistemic Analysis

Lots of learning methods have been applied to the current learning system. One of the learning methods currently being developed is Collaborative Learning. Collaborative Learning encourages students to interact actively in a work group. The research methodology consists of three steps. The first step is the process of analyzing the sentiment of the textual history of the conversation or discussion from the CLSReborns Forum. The next step is to categorize the text into one of the predetermined epistemic groups. Next, visualize the model in an epistemic network graph based on the singular value decomposition. Finally, the working group's recommendations are built on k-means clustering. This study categorizes sentiment-epistemic analysis into three collaborative aspects, namely: project management, attitudes and technology. The results of this study succeeded in creating to recommend working groups based on epistemic-sentiments.
Decoding Multivariate Multiplicity Codes on Product Sets.

The multiplicity Schwartz-Zippel lemma bounds the total multiplicity of zeroes of a multivariate polynomial on a product set. This lemma motivates the multiplicity codes of Kopparty, Saraf and Yekhanin [J. ACM, 2014], who showed how to use this lemma to construct high-rate locally-decodable codes. However, the algorithmic results about these codes crucially rely on the fact that the polynomials are evaluated on a vector space and not an arbitrary product set. In this work, we show how to decode multivariate multiplicity codes of large multiplicities in polynomial time over finite product sets (over fields of large characteristic and zero characteristic). Previously such decoding algorithms were not known even for a positive fraction of errors. In contrast, our work goes all the way to the distance of the code and in particular exceeds both the unique decoding bound and the Johnson radius. For errors exceeding the Johnson radius, even combinatorial list-decodablity of these codes was not known. Our algorithm is an application of the classical polynomial method directly to the multivariate setting. In particular, we do not rely on a reduction from the multivariate to the univariate case as is typical of many of the existing results on decoding codes based on multivariate polynomials. However, a vanilla application of the polynomial method in the multivariate setting does not yield a polynomial upper bound on the list size. We obtain a polynomial bound on the list size by taking an alternative view of multivariate multiplicity codes. In this view, we glue all the partial derivatives of the same order together using a fresh set of variables. We then apply the polynomial method by viewing this as a problem over the field () of rational functions in .
Analisis Pengaruh Teknik Think Pair Share dan Minat Membaca Terhadap Kemampuan Menulis Eksposisi pada Taruna Akademi Maritim Cirebon

The aims of this study was to analyze the differences in the exposition writing skills of cadets who taught with the think-pair-share technique and reading interest cadets. This study used an experimental method, in which the experimental group was given treatment with the think-pair-share technique, while the control group was taught without the think-pair-share technique. The two groups were further differentiated based on groups with high and low reading interest. The population in this study were cadets’ level 1 in the first semester at the Cirebon Maritime Academy in the academic year of 2020/2021. The samples are cadets of Nautika 1 as the control class and cadets of Nautika 2 as the experimental class with 25 cadets each. Exposition writing ability data were collected through an exposition writing test while reading interest data were collected by filling out a reading interest questionnaire. The data analysis used was ANOVA with the help of the SPSS program.The conclusion in this study is that the exposition writing ability of cadets who have taught using the think-pair-share technique is better than cadets who taught without it. The exposition writing ability of cadets who have a high reading interest is better than cadets who have a low reading interest. There is an interaction between learning techniques and reading interest in influencing the ability to write exposition.
Development of Scientific and Methodical Competence of Teachers of Vocational Education Institutions

The materials of the article will be useful to the managers of vocational education institutions in the context of improving the scientific and methodical work of the institution, lecturers of postgraduate education institutions, whose activities are directly related to the professional development of pedagogical staff of vocational education institutions.
LibGuides: Virtual Library Research Guide: Identifying Research Sources

This guide provides help on accessing Snow College library resources Learn how to identify books, newspapers, encyclopedias and more.
Integration of Mobile Learning in Education: Perceptions of Prospective Teachers

M-Learning is the use of mobile and handheld IT devices for learning. It became a cheaper source of information and communication, which is now in the access of anyone, anytime and anywhere using mobile devices. This qualitative research was conducted on 21 prospective teachers from the University of Education selected through stratified and random sampling techniques to explore the awareness and perception regarding M-Learning. The semi-structured interview protocol was used to collect the data. It was got validated by experts. Data were analyzed using thematic analysis. The study concluded that prospective teachers used mobile devices for communication, academics, recreation and social networking. M-Learning created ease in learning and improved it. It made learning flexible, gave better understanding and saved time. Lack of facilities, unethical use and traditional classroom environment were the hurdles in its implementation. Facilities needed to be provided; parents and teachers should protect the youngsters from unethical use.
LibGuides: King Science Library: 2021 Golden Sower Nominees

King Science & Technology Magnet Library 2021-2022 Golden Sower Chapter Book & Novel Nominees
The Usage of Quick Response Code and Captive Portal for Wi-Fi Security and Bandwidth

Internet of Things (IoT) allows different devices to communicate with each other without the compulsion to use outdated-fashioned communication styles such as data cables, external flash drives, and disks. Nowadays, people connect their smartphones to Wi-Fi in the public area by manually inputting a Wi-Fi password on their smartphones, which is regarded as a problem, mainly when the password is complex and confusing. This research demonstrates the feasibility of using the Quick Response (QR) code and the Captive Portal featured in router Tenda W15E AC1200, to guard the Wi-Fi password and to avoid unwanted users from exploiting the Wi-Fi public area. Simulation by using an open source QR code generator software to acquire the Wi-Fi QR code and experimentation from both qualitative and quantitative approaches are therefore necessary. As a result, the safety of the Wi-Fi public area is protected as the password is not revealed to the user.
Peningkatan Kemampuan Menyimak Melalui Teknik Bisik Berantai

The purpose of this study was to determine the increase in listening skills trought the chain whisper technique for students in language XI class at SMA PGRI Gelekat Lewo Boru East Flores NTT. This type ofresearch is a classroom action research which consists of two cycles. The subjects in this study are for students in language XI class at SMA PGRI Gelekat Lewo Boru. The data in this study consisted of qualitative and quantitative data. Qualitative data were obtained through observation and quantitative data were obtained through the results of the listening ability test. The instrument in this study was a multiple choice and true false test. The results of data analysis showed that the listening language with the scores obtained by students in the first cycle was 80.4% and the second cycle was 87.2%. These results indicate that the application of the chain whisper technique can improve the listening ability for students in language XI class at SMA PGRI Gelekat Lewo Boru East Flores NTT.
Being “geek” in digital communication: The case of Chinese online customer reviews

In popular culture, the stereotypically iconized “geek” can be identified in different media narratives from mainstream television to magazines. Drawing upon insights from sociolinguistics and business communication studies, this paper attempts to identify the discursive constructs of “being geek” in Chinese digital business communication. By collecting the discourse data of online customer reviews from amazon.cn and analyzing the data based on the framework of Critical Discourse Analysis, the study investigates how linguistic mechanisms operate in the shaping of geek culture and the construction of “being geek” in the participatory communication of business. The results revealed lexical variables and generic intertextuality are prominent in the discourse construction of “being geek”, to create a stimulus for a promotional culture in business communication.
Malayalam Visual Genome 1.0

Data-------Malayalam Visual Genome (MVG for short) 1.0 has similar goals as Hindi Visual Genome (HVG) 1.1: to support the Malayalam language. Malayalam Visual Genome 1.0 is the first multi-modal dataset in Malayalam for machine translation and image captioning.Malayalam Visual Genome 1.0 serves in WAT 2021 Multi-Modal Machine Translation Task.Malayalam Visual Genome is a multimodal dataset consisting of text and images suitable for English-to-Malayalam multimodal machine translation task and multimodal research. We follow the same selection of short English segments (captions) and the associated images from Visual Genome as HGV 1.1 has. For MVG, we automatically translated these captions from English to Malayalam and manually corrected them, taking the associated images into account.The training set contains 29K segments. Further 1K and 1.6K segments are provided in development and test sets, respectively, which follow the same (random) sampling from the original Hindi Visual Genome.A third test set is called ``challenge test set'' and consists of 1.4K segments. The challenge test set was created for the WAT2019 multi-modal task by searching for (particularly) ambiguous English words based on the embedding similarity and manually selecting those where the image helps to resolve the ambiguity. The surrounding words in the sentence however also often include sufficient cues to identify the correct meaning of the ambiguous word. For MVG, we simply translated the English side of the test sets to Malayalam, again utilizing machine translation to speed up the process.Dataset Formats----------------------The multimodal dataset contains both text and images.The text parts of the dataset (train and test sets) are in simple tab-delimited plain text files.All the text files have seven columns as follows:Column1 - image_idColumn2 - XColumn3 - YColumn4 - WidthColumn5 - HeightColumn6 - English TextColumn7 - Malayalam TextThe image part contains the full images with the corresponding image_id as the file name. The X, Y, Width and Height columns indicate the rectangular region in the image described by the caption.Data Statistics-------------------The statistics of the current release are given below.Parallel Corpus Statistics---------------------------------Dataset Segments English Words Malayalam Words---------- -------------- -------------------- -----------------Train 28930 143112 107126Dev 998 4922 3619Test 1595 7853 5689Challenge Test 1400 8186 6044-------------------- ------------ ------------------ ------------------Total 32923 164073 122478The word counts are approximate, prior to tokenization.Citation-----------If you use this corpus, please cite the following paper:@article{hindi-visual-genome:2019, title={{Hindi Visual Genome: A Dataset for Multimodal English-to-Hindi Machine Translation}}, author={Parida, Shantipriya and Bojar, Ond{\v{r}}ej and Dash, Satya Ranjan}, journal={Computaci{\'o}n y Sistemas}, volume={23}, number={4}, pages={1499--1505}, year={2019} }
A New Proposed Coding Method for Steganography Purpose

Transferring data in a safe way is one of the things that have been of interest since ancient times. Data hiding or steganography is a method used to protect the data during its transmission. Coding is a method to represent the data in another shape, so a high level of security is achieved by using coding and hiding data together. The proposed method is a hybrid between coding and hiding, but this paper focuses on proposed a data coding part only, such that the cover text (that used for information hiding) will be used to extract private information between the sender and the receiver for coding process, and the output of the proposed coding method can be used for information hiding process. Apply the proposed coding method will provide a high level of security and complexity and produce ASCII of non-printed characters which can be employed for steganography purposes to obtain complete similarity between secret text and cover text.
РЕШЕНИЕ ЗАДАЧИ КЛАССИФИКАЦИИ ДОКУМЕНТОВ ВУЗА НА ОСНОВЕ МЕТОДОВ ИНТЕЛЛЕКТУАЛЬНОГО АНАЛИЗА

The article considers a problem of classification of text documents of a higher educational institution using machine learning methods such as the Bayes method, the k-nearest neighbors algorithm, the decision tree method, and the support-vector machines. The study is conducted on a set of documents of the Siberian State Automobile and Highway University, Omsk, using the Python programming language. Preliminary processing of documents for the study is carried out. All studied documents are divided into four classes namely the order, the instruction, the letter, and the notice of a vacant position. The process of classification of documents of a higher educational institution is presented. A comparative analysis of the classification results of each machine learning method is carried out on such metrics as the correctness of the classification algorithm, accuracy, completeness, F-measure, and the running time of the algorithm. As a result of the research, the author gives recommendations on the application of the considered methods for the classification of university documents. The author suggests using a combination of methods to optimize the operation of the documents classifier.
El-Picker: a machine learning-enhanced robust P-phase picker for real-time seismic monitoring

Identifying the arrival times of seismic P-phases plays a significant role in real-time seismic monitoring, which provides critical guidance for emergency response activities. While considerable research has been conducted on this topic, efficiently capturing the arrival times of seismic P-phases hidden within intensively distributed and noisy seismic waves, such as those generated by the aftershocks of destructive earthquakes, remains a real challenge since most common existing methods in seismology rely on laborious expert supervision. To this end, in this paper, we present a machine learning-enhanced framework based on ensemble learning strategy, EL-Picker, for the automatic identification of seismic P-phase arrivals on continuous and massive waveforms. More specifically, EL-Picker consists of three modules, namely, Trigger, Classifier, and Refiner, and an ensemble learning strategy is exploited to integrate several machine learning classifiers. An evaluation of the aftershocks following the Ms 8.0 Wenchuan earthquake demonstrates that EL-Picker can not only achieve the best identification performance but also identify 120% more seismic P-phase arrivals as complementary data. Meanwhile, experimental results also reveal both the applicability of different machine learning models for waveforms collected from different seismic stations and the regularities of seismic P-phase arrivals that might be neglected during the manual inspection. These findings clearly validate the effectiveness, efficiency, flexibility, and stability of EL-Picker.
The Design of New Digital Resources of Personalized Support of Reading Skills for Novice Readers and Children with Dyslexia: A Presentation of the iRead Software Linguistic Domain Models

The aim of the current paper is to present and discuss the development, structure, content, and use of a flexible, scalable and cost-effective cloud-based software system used in the iRead project.The iRead Project (Infrastructure and Integrated Tools for Personalized Learning of Reading Skills) aimed to offer personalized learning services to novice readers and students with reading difficulties or dyslexia by developing an integrated supportive tool for tablets, the iRead software, which includes a set of educational applications, like mini-games, an e-reader and a text classifier. iRead is built and operates around a comprehensive knowledge base, which includes a structured and detailed model of linguistic content that is essential to reading development, the domain model. iRead Domain models are essential for the operation of all iRead apps and were designed to provide personalized learning support to students with dyslexia by enabling each app to select linguistic content based on the particular learning needs of each student. The sophisticated and thorough structure and linguistic content of the iRead domain models, along with the ability of iRead to adapt to students’ needs, constitute unique features that render iRead innovative.
Usability improvement of a mobile graphing calculator application

Previous research has established that the integration of mobile technologies and related mobile applications in mathematics education can enhance learning in various ways. Additionally, there is a growing body of literature that recognises the importance of the usability of educational mobile applications. Thus, it is important to study how these mobile applications can be designed and developed in order to best support the impact on educational achievements. This paper presents an overview of possible usability issues of mobile graphing calculator applications and provides recommendations on how to overcome these concerns. The contribution of this paper is to propose helpful suggestions for designers and developers of mobile mathematics applications in order to develop easy to use applications that best support mobile technology enhanced learning in mathematics education.
The Corona Warning App of the German Federal Government – How perceived data protection issues hindered any effectiveness

Since June 17th, 2020 the Corona Warn App of the German Federal Government has been available for download. After a sharp increase downloads stagnate around a total of 20 million, which is roughly one fourth of the population. Whether everyone who downloaded it actually uses it, is questionable. ObjectivesWe want to show that the underlying concept of an app is questionable, even if each inhabitant with a smartphone downloads and uses it, it would cover barely half of each encounter where COVID-19 could actually be transmitted. Prior workThis work is the scientific, extended version of a short article we published in the September 2020 issue of the “Behordenspiegel”, a monthly magazine covering German public administration issues. ApproachWe use statistical methods to show that, (i) even in the very best case with a perfectly working app the coverage would have been roughly half of all relevant encounters (ii) and that the voluntary usage of this app as well as the free decision of the infected individual to publish its (anonymized) data to warn others in fact reduces any effectiveness considerably. In addition we show that (iii) due to the design of the app there is a likely limit where the app will not be able to warn its users for mathematical and cryptographical reasons. ResultsWe demonstrate by statistical means that this app could never have worked and why similar apps neither would work, let aside probably the “Trace Together” initiative of Singapore, which is based on a combination of an app plus physical tokens for those who do not own nor use smartphones (https://www.tracetogether.gov.sg/). We define some requirements a successful COVID-19 tracing solution must fulfill. ImplicationsWe show that such apps arenot a solution for the problem, rather an obstacle to a real solution, because they lull their (few) users into a false sense of security which is obviously wrong, based on real figures. Value The paper contributes to transparency of government action during the COVID-19 pandemic. We show that other ways of contact tracing must be pursued in order to be effective and hinder the pandemic from escalating rather than providing a false feeling of safety.
Agile: 3 Steps to Get Started

Want to apply agile across your whole organization? Consider this advice around centers of excellence, process, and tools.
Predicting Fraudulent Financial Statements Using Fraud Detection Models

The key purpose of the research is to provide scientific data on the association between fraud causes and false financial statements. The paper gave further insight into the applicability of Altman's z-score and Dechow f-score to the exposure of false financial statements by Jordanian industrial owners. The duration of research included the years from 2015 to 2019. The Dependent variable in the analysis was the false financial statement, while the separate fraud factors were financial security, external strain, financial priorities and the essence of the business. The analysis of the research takes a methodological model utilizing a multiple regression procedure to evaluate the theories of the study. The final findings of the analysis presented conclusive proof that Jordanian manufacturing firms were engaged in the conduct of false financial statements; while some of the triangle fraud variables were identified without any correlation with fraudulent financial reports; other factors were found to be strongly associated with fraud. As regards the accuracy of the fraud models, the findings of the analysis confirmed the validity and specificity of all the fraud detection models adopted in the study.