Reviewerly/exHarmony huggingface dataset:
The Development of Research Competence Through Digital Resources

We hope to believe that our research makes a certain theoretical and practical contribution to the development of a research competence in future foreign language teacher. We offered a definition of the research competence of future foreign language teachers as a complex and multifaceted concept that had not received the detailed consideration in the existing literature before. We have studied and identified abilities comprising the core of the research competence. The principles of the educational process aimed at the development of research competence of the above mentioned students have been highlighted. The model of future foreign language teachers’ research competence development has been constructed; a system of tasks based on digital resources has been suggested and experimental work was provided to show the efficiency of the model designed.
寃쎌젣?깆옣?먯꽌 遺?? FDI 諛?ODA???④낵

Purpose– This study compares the impact of corruption on economic growth in developing countries located in Asia and Latin...
Application of Convolutional Neural Network in Identifying Different Levels of Isokinetic Exercise Efforts.

Objective To develop a convolutional neural network （CNN） that can identify isokinetic knee exercises moment of force-time diagrams under different levels of efforts. Methods The 200 healthy young volunteers performed concentric isokinetic right knee flexion-extension reciprocating exercises with maximal effort as well as half the effort at angular velocities of 30°/s and 60°/s twice, respectively, with an interval of 45 min. The moment of force-time diagrams were collected. The 200 subjects were randomly divided into the training set （140 subjects） and the testing set （60 subjects）. The moment of force-time diagrams from subjects in the training set were used to train CNN model, and then the fully trained model was used to predict types of curves from the testing set. Random sampling of subjects along with subsequent development of models were performed 3 times. Results Under the circumstances of isokinetic knee exercises with maximal effort and half the effort, 2 400 moment of force-time diagrams were produced, respectively. Classification accuracy rates of the CNN models after the 3 trainings were 91.11%, 90.49% and 92.08%, respectively, and the average accuracy rate was 91.23%. Conclusion The CNN models developed in this study have a good effect on differentiating isokinetic moment of force-time diagrams of maximal effort exercises from those made with half the effort, which can contribute to identifying levels of efforts exerted by subjects during isokinetic knee exercises.卷积神经网络在识别等速运动配合程度中的应用.目的 开发识别不同配合程度下等速膝关节运动力矩-时间图的卷积神经网络（convolutional neural network，CNN）模型。 方法 200名健康青年志愿者分别在30°/s和60°/s角速度下各进行两次、间隔45 min的等速向心右侧膝关节全力和半力屈伸往复运动，收集力矩-时间图。200名受试者随机分为训练集（140名）与测试集（60名），用训练集受试者的力矩-时间图训练CNN模型，再用训练好的模型预测测试集内图形的类别。共进行3次随机取样与模型开发。 结果 在等速膝关节全力及半力运动条件下各收集2 400张力矩-时间图。3次训练的CNN模型分类准确率分别为91.11%、90.49%和92.08%，平均准确率为91.23%。 结论 本研究开发的CNN模型对全力及半力等速力矩-时间图具有较好的区分效果，有助于识别受试者在等速膝关节运动过程中的配合程度。.法医学；等速运动；膝关节；伪装；卷积神经网络.
Limetorrents Proxy Sites and Working Mirror Links for 2020

Limetorrents is a library for torrents. By library, we mean that this site is only offering the links from other websites or sources. They do not ...
Selecting the Number of Clusters K with a Stability Trade-off: An Internal Validation Criterion

Model selection is a major challenge in non-parametric clustering. There is no universally admitted way to evaluate clustering results for the obvious reason that no ground truth is available. The difficulty to find a universal evaluation criterion is a consequence of the ill-defined objective of clustering. In this perspective, clustering stability has emerged as a natural and model-agnostic principle: an algorithm should find stable structures in the data. If data sets are repeatedly sampled from the same underlying distribution, an algorithm should find similar partitions. However, stability alone is not well-suited to determine the number of clusters. For instance, it is unable to detect if the number of clusters is too small. We propose a new principle: a good clustering should be stable, and within each cluster, there should exist no stable partition. This principle leads to a novel clustering validation criterion based on between-cluster and within-cluster stability, overcoming limitations of previous stability-based methods. We empirically demonstrate the effectiveness of our criterion to select the number of clusters and compare it with existing methods. Code is available at https://github.com/FlorentF9/skstab .
Word-Level Speech Recognition With a Letter to Word Encoder

We propose a direct-to-word sequence model which uses a word network to learn word embeddings from letters. The word network can be integrated seamlessly with arbitrary sequence models including Connectionist Temporal Classification and encoder-decoder models with attention. We show our direct-to-word model can achieve word error rate gains over sub-word level models for speech recognition. We also show that our direct-to-word approach retains the ability to predict words not seen at training time without any retraining. Finally, we demonstrate that a word-level model can use a larger stride than a sub-word level model while maintaining accuracy. This makes the model more efficient both for training and inference.
Best practice of extracting magnetocaloric properties in magnetic simulations

In this thesis, a numerical study of simulating and computing the magnetocaloric properties of magnetic materials is presented. The main objective was to deduce the optimal procedure to obtain the ...
Multimodal Quality Estimation for Machine Translation

We propose approaches to Quality Estimation (QE) for Machine Translation that explore both text and visual modalities for Multimodal QE. We compare various multimodality integration and fusion strategies. For both sentence-level and document-level predictions, we show that state-of-the-art neural and feature-based QE frameworks obtain better results when using the additional modality.
A HYBRID MULTILEVEL KEY GENERATION ALGORITHM FOR FAST TRANSACTION BASED ON STANDARD RSA ALGORITHM

As most of the data transactions now-a-days are being made through secured smart cards owing to their low cost and ease of usage, it has become necessary to speed up the Key generation in the RSA algorithm [4]. Moreover, public key cryptography is a popular method that provides security, identification and authorization in secure transactions [5].The cryptography is classified into two types: Symmetric Key Systems and Asymmetric Key Systems. In Symmetric Key Systems same keys are used by the transmitter and receiver whereas in Asymmetric Key Systems different keys are used for encryption by the sender and decryption by the receiver. Hence these two aspects, namely speed of key generation at the same time maintaining the security are of prime importance and the major sources of motivation in carrying out the present work. During the study of the RSA algorithm, the following problems have been identified: a) the mathematical solutions of cryptographic algorithms require a large amount of calculation, which implies a higher consumption of computing resources and greater bandwidth for transaction; b) in order to store information in a database, for example four bytes, encrypted fields of approximately 600 bytes are required thus enhancing the space required c) increasing threats & vulnerabilities, due to the development of technologies [19, 20], result in the improvement of information security, which means higher cost and consumption of computational resources. This work proposes a generic model that optimizes the RSA method for information encryption, combining two different methodologies of key generation.This generic RSA model is expected to meet all the requirements and processes based on standard models accepted like cryptographic protocols and to make it suitable for transaction through smart devices like POS and other such transaction terminals.
LibGuides: Qualtrics Surveys in Research: Distributing surveys

The Qualtrics Survey platform lets you create digital surveys. This guide gives information on how to implement Qualtrics in research in a thorough a save way.
Research Guides: Data Visualization Resources: Data Sources

A guide to resources from TUL and elsewhere to help users create interesting and informative data visualizations.
SISTEM PENDUKUNG KEPUTUSAN PEMILIHAN SISWA BERPRESTASI SEBAGAI PESERTA OLIMPIADE SAINS MENGGUNAKAN METODE SIMPLE ADDITIVE WEIGHTING (SAW)

Abstract The development of science in the era of information technology today indirectly also has an impact on the world of education, especially in the selection of students as participants in the Science Olympics. MTs X need a decision support system that can classify the selection pattern of junior high school science Olympiad students by considering several criteria, namely test results, subject values, Olympic experience, report card grades, and grade level. The model used in this decision support system is Fuzzy Multiple Attribute Decision Making, using the Simple Additive Weighting method, because this method determines the weight value for each attribute, then continues with the ranking process that will select the best alternative from a number of alternatively, in this case the alternative in question is an outstanding student who will be a Science Olympiad participant. The result is that the determination of Science Olympiad participants is more accurate.
A comparative Study for Designing an Efficient Intelligence System for the Process of Discrimination

Face recognition is one of the most important biometrics techniques used to identify people. The research aims to build an efficient system by devising a new method of discrimination that includes advanced image processing techniques and intelligent techniques. This work has been implemented in several stages, the first of which is the arrangement of the database, Followed by pre-processing based on the integration of Gaborand DCT conversion. And then adopt two methods in extracting statistical features, the first dependent first-class statistics, the second dependent second-class statistics of the GLCM matrix and then draw the important features of them. In the phase of discrimination, two types of artificial neural networks were used after their construction in the 2016 MATLAB environment, BPNN and Elman. Finally, the efficiency of the methods used and the identification of the best were compared.
Book Manufacturing in the COVID-19 Era

The printed book has endured a great deal in the last fifteen years. COVID-19 has changed some things in the industry, but the printed book is still alive and well.
Proceedings of the 2019 miniKanren and Relational Programming Workshop

PrefaceThis report aggregates the papers presented at the first miniKanren and Relational Programming Workshop, hosted onAugust 2nd, 2019 in Berlin, Germany and co-located with the twenty-second International Conference on FunctionalProgramming.The miniKanren and Relational Programming Workshop is a new workshop for the miniKanren family of relational(pure constraint logic programming) languages: miniKanren, microKanren, core.logic, OCanren, Guanxi, etc. Theworkshop solicits papers and talks on the design, implementation, and application of miniKanren-like languages. Amajor goal of the workshop is to bring together researchers, implementors, and users from the miniKanren community,and to share expertise and techniques for relational programming. Another goal for the workshop is to push thestate of the art of relational programming—for example, by developing new techniques for writing interpreters, typeinferencers, theorem provers, abstract interpreters, CAD tools, and other interesting programs as relations, which arecapable of being “run backwards,” performing synthesis, etc.6 papers were submitted to the workshop, and each submission was reviewed by two to three members of the programcommittee. After deliberation, all submissions were accepted to the workshop.In addition to the six full papers presented• William E. Byrd gave a morning tutorial on miniKanren,• Daniel P. Friedman and William E. Byrd gave a closing Q&A with audience.Thanks to all presenters, participants, and members of the program committee.William E. Byrd & Nada Amin
UWM Libraries Research and Course Guides: Library Resources for Online Instruction: Add Library Content to Canvas

This guide contains information and useful no-cost/low-cost content into your online course to supplement instruction. This page contains instructions and recommended practices for adding articles and other online, print-based media to Canvas course sites.
LibGuides: Distance Education Resources: E-Books

This guide gathers the remote resources available. Get free digital access to textbooks from numerous publishers!
Research Guides: Data Visualization Resources: Data Visualization Tools

A guide to resources from TUL and elsewhere to help users create interesting and informative data visualizations.
Countering Fraud Committed Using Information Technology in Kazakhstan

The relevance of this article is that with the development of modern technologies, conditions have formed for the emergence of such a new type of crime as fraud committed with the help of modern information technologies. Today in Kazakhstan, the amount of damage caused and the number of facts of this type of crime in recent years has grown many times. The practice of law enforcement indicates that computer technology is increasingly acting as a tool for committing crimes. Most of these crimes can cause real harm to a person and the state. The aim of the article is to study the theoretical and practical aspects of countering a new type of fraud. The methodological base of the article is composed of general scientific principles, approaches and methods of scientific knowledge, dialectical and comparative methods of cognition of social and legal processes and phenomena. The theoretical and practical significance of the article lies in the fact that the results of the work can become the foundation for amendments to the legislation of Kazakhstan, as well as for the development of methodological manuals on the investigation of the type of criminal offenses in law enforcement.&#x0D;
12 Commonly Asked Questions About CIS Controls | I.S. Partners

The Center for Internet Security (CIS) is a nonprofit organization founded in 2000. Its mission is to develop, promote and sustain best practices in ...
LibGuides: EDU 461: Children's Literature: APA

This guide will help students in EDU 461 perform research and create lesson plans based on children's books.
It's Alive! Breathe new life into your practice

A valuable virtual assistant doesn’t just run in the background—it moves your practice forward.
VALUE OF CORE TO SEISMIC SCALE DATA EARLY IN THE APPRAISAL PHASE, OFFSHORE SARAWAK

Summary In mid-2018, ConocoPhillips and its joint venture partner, PETRONAS Carigali drilled 2 E&amp;A wells, Salam-2 and Patawali-1 well in Block WL4-00, Offshore Sarawak. The wells discovered oil and gas in multiple sands within the Late Miocene Cycle V interval.
How To Take A Screenshot On Android

The process of learning how to take a screenshot on Android will vary from one phone to the next depending on the make and model. So you ...
LibGuides: Coronavirus/COVID-19 Resources: Reference Materials

Find resources on the Coronavirus/COVID-19 Pandemic through Davis Library at the University of Rio Grande & Rio Grande Community College.
Geophysical Investigation for Delineating Structures Favorable to Uranium Mineralization in Al-Amerat, Sultanate of Oman

Summary The Amdeh Formation near Al-Amirat area south west of Muscat, Sultanate of Oman is characterized by well-bedded quartzite exhibiting tabular cross-beds and contorted bedding structures were geophysically investigated initially with a gamma ray spectrometry technique. The spectroscopic results of acquired gamma ray has indicated moderately high concentration of radioactive minerals showing ~100 ppm of uranium and ~1000 ppm of thorium in the placer deposit. In order to identify the extension and structural parameters of the Formation, the area was further investigated with very low frequency electromagnetic (VLF-EM) and magnetic surveys along five profiles of approximately 200 m long 20 m apart (10 m measurement intervals). In-phase and quadrature components of the VLF-EM signal were recorded at two different transmitter frequencies (15.1 and 16.4 kHz) as well as total magnetic field. Spatial location by amplitude of analytical signal and the depth to targets by Euler deconvolution and spectral analysis in the case of total magnetic field and the Fraser and K-H filtering as well as EMD based Hilbert transform analysis in the case of VLF-EM signals have revealed the possible uranium bearing structures as deep as 5-20 m. The salient features of results are highlighted and discussed in this presentation.
Constraints on the genesis of the Sandamap gold prospect, Namibia: fluid inclusion, geochronology and stable isotope studies

The Sandamap gold prospect is a metaturbidite shear zone-hosted gold mineralization located in the Neoproterozoic Damara Orogen 30 km northwest of the town of Usakos in Namibia with an estimated gold content of 240 000 t at 3.6 g/t up to 40 m below surface. This research project was aimed at constraining the age, crustal level of formation, pressure-temperature conditions during formation, sources of the mineralizing fluids, and by implication, the metal sources of the Sandamap gold mineralization. Fluid inclusion, geochronological and isotopic studies were carried out on quartz veins hosting the ore. The presence of kaolinite, alunite and jarosite suggest post-hydrothermal weathering of sulfides. Various sources of data from this study, giving rise to depths of entrapment of 4 to 14 km, temperature range of entrapment of fluids of 187 – 594 °C, stable isotope data (δ13C and δ18O), δD values and a δD vs. δ18OH2O plot are all in favour of an orogenic gold deposit. Additionally, the dominant CO2-rich and CH4-rich fluids observed at Sandamap do not contradict this interpretation. The calculated depth of entrapment of mineralization covers the lower portion of the epizonal zone to the upper portion of the hypozonal zone of gold deposits. The Sandamap mineralization’s δD values of -35‰ to -49‰ fall within the range of most published data for typical orogenic gold deposits which varies from -20 to -80‰. Moreover, the calculated δ18Owater values of the ore-fluids (+6.6 to +11.3‰) of the higher temperature aqueous group from the Sandamap mineralization fall within the range observed in typical orogenic gold deposits found in Phanerozoic terrains (+7 to +13‰). The schist hosting the mineralized shear zone with a gold content of 0.05 ppm Au or its higher grade equivalent at depth, is a possible gold source candidate. Two mechanisms of deposition were possibly at play: (i) the cooling below 500 °C and possible sulfidation (resulting from fluid-rock interaction), lowered the solubility of pyrite causing S3- and Au(HS)S3- (possible main Au carriers) to breakdown resulting in decreased Au solubility and its subsequent deposition and (ii) the elevated amount of CO2 (e.g. trench 14 where CO2-rich fluid inclusions are dominant) led to a sharp decrease in the Au(HS)2- and Au(HS)S3- concentrations, causing decreased Au solubility and its subsequent deposition. The age of mineralization obtained from 40Ar/39Ar dating of the muscovite associated with the ore-hosting quartz veins is placed at 472 ± 3 Ma. The mineralization is younger than the shear zone, which acted as a conduit for ore-fluid migration and it has no age relationship with proximal plutonic bodies. The mineralization is younger than the foliated granite (FG), which exhibits a metamorphic fabric in the form of mineral segregation, but older than the non-foliated granite (GT) which hosts a mineralized xenolith.
LibGuides: Academic Success: Outlining Alternatives

This guide covers some of the technologies and resources covered in the 1L Academic Success course Tools for creating outlines in non-traditonal formats.
LibGuides: Poetry: Research Tools

This is a general guide designed to help students get started reading poetry, aid them in beginning their research, and assist them in conducting a Close Reading. information sources within and outside of the library
Library, Information, and Technology Services: LITS Zoom Resources: Home

This page serves as a hub for any informational and training resources that LITS has produced for the Zoom software platform.
Magic Literals in Pharo

Literals are constant values (numbers, strings, etc.) used in the source code. Magic literals are the ones used without a clear explanation of their meaning. Presence of such literals harms source code readability, decreases its modularity, and encourages code duplication. Identifying magic literals is not straightforward. A literal can be considered self-explanatory in one context and magic in another. We need a heuristic to help developers spot magic literals. In this article, we study and characterize the literals in Pharo. We implemented a heuristic to detect magic literals and integrated it as a code critic rule for System Browser and Critics Browser in Pharo 7. We run our heuristic on 112,500 Pharo methods which reported 23,292 magic literals spread across 8,986 methods. We manually validated our approach on a random subset of 100 methods and found that 62% of the reported literals in those methods are indeed magic.
Fraud detection for online banking for scalable and distributed data

Online fraud causes billions of dollars in losses for banks. Therefore, online banking fraud detection is an important field of study. However, there are many challenges in conducting research in fraud detection. One of the constraints is due to unavailability of bank datasets for research or the required characteristics of the attributes of the data are not available. Numeric data usually provides better performance for machine learning algorithms. Most transaction data however have categorical, or nominal features as well. Moreover, some platforms such as Apache Spark only recognizes numeric data. So, there is a need to use techniques e.g. One-hot encoding (OHE) to transform categorical features to numerical features, however OHE has challenges including the sparseness of transformed data and that the distinct values of an attribute are not always known in advance. Efficient feature engineering can improve the algorithm’s performance but usually requires detailed domain knowledge to identify correct features. Techniques like Ripple Down Rules (RDR) are suitable for fraud detection because of their low maintenance and incremental learning features. However, high classification accuracy on mixed datasets, especially for scalable data is challenging. Evaluation of RDR on distributed platforms is also challenging as it is not available on these platforms. The thesis proposes the following solutions to these challenges: • We developed a technique Highly Correlated Rule Based Uniformly Distribution (HCRUD) to generate highly correlated rule-based uniformly-distributed synthetic data. • We developed a technique One-hot Encoded Extended Compact (OHE-EC) to transform categorical features to numeric features by compacting sparse-data even if all distinct values are unknown. • We developed a technique Feature Engineering and Compact Unified Expressions (FECUE) to improve model efficiency through feature engineering where the domain of the data is not known in advance. • A Unified Expression RDR fraud deduction technique (UE-RDR) for Big data has been proposed and evaluated on the Spark platform. Empirical tests were executed on multi-node Hadoop cluster using well-known classifiers on bank data, synthetic bank datasets and publicly available datasets from UCI repository. These evaluations demonstrated substantial improvements in terms of classification accuracy, ruleset compactness and execution speed.%%%%Doctor of Philosophy