Reviewerly/exHarmony huggingface dataset:
Factors Influencing the Use of Mobile Learning in Learning at Jordanian Universities from the Point of View of Experts and Students

Universities from the Point of View of Experts and Students.The Study Followed the Qualitative Curriculum as Required by the Nature of the Study, the Number of Study Members (19) Faculty Members and (25) Students of Bachelor's and Graduate Students from Public and Private Universities for the Academic Year (2019-2018), the Interview Questions were Built to Reveal Obstacles Faced by Jordanian Universities in the Use of Mobile learning in Instructional.The Results of the Study Revealed that the Opening of a Wide Area of Interaction, Participation, Opinion, Feedback, and Faculty Factor in Terms of Directions, and Training Received the Highest Percentage of Factors Influencing the Use of Mobile Learning from the Point of View of Experts, as it Turns out that the Containment of Mobile Learning Devices For a Clear Learning System, the Educational Services Provided such as Content Delivery, Message Sharing, Ideas and Tasks have the Highest Percentage of Factors Influencing the Use of Mobile Learning from the Student's Point of View.The Study also Concluded with the Following Recommendation: to Introduce the Factors Influencing the Use of Mobile Learning in Instructional in Jordanian Universities and to Study them well, to Take into Account them When Using Mobile Learning in Universities.
Multimodal Concept Detection and Annotation in Image and Video Collections

The World Wide Web has become a common-place for finding for all kinds of purposes. The amount of data which one user can be dealing with has become large and its size is countinuously growing. The relevant data for users have not only become large, but also diverse. Hence, searching relevant information from such large and diverse resources is a critical task. However, users can not always formulate appropriate queries for finding the desired resources. In order to retrieve relevant information, the semantic relationships of the information in different modalities would need to be known and specified.This thesis approaches the multimodal cross-domain semantic retrieval and fusion problem from the point of view of content-based visual analysis and statistical natural language analysis. It also aims at using cross-domain textual semantics to generate pseudo tags for images to improve the performance of the information retrieval task. The main focus of the thesis is in bridging the semantic gap between textual and visual content domains.In order to combine and project the unimodal information to multimodal space, two approaches are used: one is the Multimodal Deep Boltzmann Machine (DBM) and the other is the late fusion of unimodal Support Vector Machines (SVM). One problem of the non-linear SVM approach is its high calculation cost. In this dissertation, the homogeneous kernel map method is used to improve the efficiency of SVM. In our experiments, we adopted deep convolutional neural network features, particularly GoogLeNet features, and the retrieval results of the SVM-based approaches improved to be nearly equal to those of the Multimodal DBM approch.One drawback of the multimodal information retrieval task is the requirement to be able to perform queries in each unimodal domain. In our experiments, if the query for image domain is missing or not appropriate, the approach is just the same as ordinal text search. Additionally, the image contents and its textual description do not always match. In order to improve the multimodal information retrieval, the method of pseudo tag generation is proposed in this thesis. The generation of pseudo tags is based on a text–image semantic map, which is calculated by the cooccurrence of latent topics in text and visual concepts in text–image data. In the experiments, the multimodal information retrieval results were considerably improved by using the pseudo tags.
Politeness in Online Discussion Forums: a Comparison Between English and Slovenian

The main objective of this master’s thesis is to compare the use of politeness in English and Slovenian and to compare politeness that occurs in the selected topics of online discussion forums. Another objective is to analyse which politeness strategies are applicable in the selected online discussion forums and to determine why some of them are not applicable. The master’s thesis presents an analysis of 4 online discussion forums and 2 specific topics (health, relationships). 20 discussions were chosen for the analysis, which is based on Brown and Levinson’s Politeness Theory (1987). Positive politeness strategies, negative politeness strategies and off-record politeness strategies are determined in the analysis and the findings in English and Slovene forums are compared. The language of online discussion forums, the place of conversational computer-mediated communication, is comparable to oral communication. The findings suggest that the discussions of the online discussion forums therefore offer a great potential to analyse the use of politeness in a language. A comparison of the findings provides an insight into the use of politeness in English and Slovenian in the online discussion forums and the differences between them. The analysis shows that Brown and Levinson’s theory is applicable to both languages, which is not the case for all strategies. Several differences were found in the use of politeness, which is more often used in English.
What's the Difference Between Professional Human and Machine Translation? A Blind Multi-language Study on Domain-specific MT

Machine translation (MT) has been shown to produce a number of errors that require human post-editing, but the extent to which professional human translation (HT) contains such errors has not yet been compared to MT. We compile pre-translated documents in which MT and HT are interleaved, and ask professional translators to flag errors and post-edit these documents in a blind evaluation. We find that the post-editing effort for MT segments is only higher in two out of three language pairs, and that the number of segments with wrong terminology, omissions, and typographical problems is similar in HT.
(ghost) trio for harp, flute and viola

Author(s): Gidron, Assaf | Abstract: This music score was submitted for the Kaleidoscope 2020 Call for Scores, an open access collaboration with the UCLA Music Library.
Labeling Explicit Discourse Relations Using Pre-trained Language Models

Labeling explicit discourse relations is one of the most challenging sub-tasks of the shallow discourse parsing where the goal is to identify the discourse connectives and the boundaries of their arguments. The state-of-the-art models achieve slightly above 45% of F-score by using hand-crafted features. The current paper investigates the efficacy of the pre-trained language models in this task. We find that the pre-trained language models, when finetuned, are powerful enough to replace the linguistic features. We evaluate our model on PDTB 2.0 and report the state-of-the-art results in extraction of the full relation. This is the first time when a model outperforms the knowledge intensive models without employing any linguistic features.
4 pieces for solitary instruments to (per)form as a group op.42

Author(s): Erikson, Trond | Abstract: This music score was submitted for the Kaleidoscope 2020 Call for Scores, an open access collaboration with the UCLA Music Library.
Artificially Intelligent Copyright: Rethinking Copyright Boundaries

My dissertation explores the legal boundaries of copyright law in the wake of artificial intelligence (AI) technology. In building the theoretical foundations for my dissertation, I go through several key phases. First, I highlight important historical events and milestones in AI. I further develop the philosophical debate on AI legal personhood and deliberate whether we are approaching a singularity the next stage of AI evolution. I also explore the concept of AI as it matured through the years. In the second part, I theorize how AI can be regarded as an author under IP normative standards. Part of accepting the argument that AI deserve copyright is a willingness to change the perception that only human creations are worthy of copyright protection. I also seek an answer to two sub-questions the who and the what. The who considers the normative standards of authorship in the ongoing struggle between an authors right and the public domain. The what raise the originality debate and discusses the standard of creation. In the third part, I outline the many candidates for AI authorship the programmer, the user, the AI and an alternative legal framework for AIs ownership like the public domain or author-in-law. Finally, I discuss the outcomes of each model and provide my conclusions.
Linear Complexity of Binary Threshold Sequences Derived from Generalized Polynomial Quotient with Prime-Power Modulus

In this paper, firstly we extend the polynomial quotient modulo an odd prime [Formula: see text] to its general case with modulo [Formula: see text] and [Formula: see text]. From the new quotient proposed, we define a class of [Formula: see text]-periodic binary threshold sequences. Then combining the Legendre symbol and Euler quotient modulo [Formula: see text] together, with the condition of [Formula: see text], we present exact values of the linear complexity for [Formula: see text], and all the possible values of the linear complexity for [Formula: see text]. The linear complexity is very close to the period and is of desired value for cryptographic purpose. Our results extend the linear complexity results of the corresponding [Formula: see text]-periodic binary sequences in earlier work.
Research Guides: IDEA - The Innovation, Design, and Entrepreneurship Academy: Entrepreneurship

A collection of resources curated by New Brunswick Libraries for the Innovation, Design, and Entrepreneurship Academy.
Unlocking the Power of Quantum Encryption

Quantum technology poses a growing threat to online security. But it also provides a solution.
Transduction based approaches for dataset shift problems

Dataset Drift problems occur in every ﬁeld that extract or adjust models from data. It is named drift the phenomena which causes the training and testing datasets to differ, and may also appear at any time duringthemodelrealapplication. Inthiscontext,approachesusingTransductivelearningwereproposed to solve classiﬁcation problems under some Dataset Drift scenarios. Two strategies were deﬁned, and present satisfactory results with some limitations. The ﬁrst one is based on an Essentially Transductive Approach that uses genetic algorithm to optimize data entropy. The other one is a strategy oriented to two-dimensional spatial datasets based on Gabriel Graphs for the estimation of Gaussian Mixture Models. However, the correct analysis if the model under a drift is not systematically performed, thus the experimentation of the methods was done with study cases.
Self-adaptive random walk with pesudo-gradients for genetic evolution of an artificial neural network

To optimize the weights in an artificial neural network most methods rely gradients, which are not always obtainable or desirable. Evolutionary algorithms are instead based on Darwinian evolution where no derivative is needed. These algorithms have a set of strategy parameters that can be dynamically updated during the search to increase performance. Two ways of updating the parameters are the so called ``1/5th-rule, which uses the offspring survival rate to self adapt, and random mutation which uses inheritance and mutation to evolve the strategy parameters as well. We present an algorithm that combines the aspects of these two self adaptation methods by changing strategy parameters differently for new offspring and older survivors. We also introduce a pseudo-gradient by adding a memory of the previous step taken in the search space and let the new mutation be shifted by this remembered step. In this investigation these two methods failed to improve the performance over the ``1/5th-rule but performed better than the random mutation. The new algorithms showed promising results regarding combining the aspects of the ``1/5th-rule and random mutation. (Less)
Shape Defense

Humans rely heavily on shape information to recognize objects. Conversely, convolutional neural networks (CNNs) are biased more towards texture. This fact is perhaps the main reason why CNNs are susceptible to adversarial examples. Here, we explore how shape bias can be incorporated into CNNs to improve their robustness. Two algorithms are proposed, based on the observation that edges are invariant to moderate imperceptible perturbations. In the first one, a classifier is adversarially trained on images with the edge map as an additional channel. At inference time, the edge map is recomputed and concatenated to the image. In the second algorithm, a conditional GAN is trained to translate the edge maps, from clean and/or perturbed images, into clean images. The inference is done over the generated image corresponding to the input’s edge map. A large number of experiments with more than 10 data sets have proved the effectiveness of the proposed algorithms against FGSM and `1 PGD-40 attacks. against FGSM and `l∞ PGD-40 attacks. Further, we show that edge information can a) benefit other adversarial training methods, b) be even more effective in conjunction with background subtraction, c) be used to defend against poisoning attacks, and d) make CNNs more robust against natural image corruptions such as motion blur, impulse noise, and JPEG compression, than CNNs trained solely on RGB images. From a broader perspective, our study suggests that CNNs do not adequately account for image structures and operations that are crucial for robustness. The code is available at: https://github.com/[masked].
Research Guides: Virtual Reality at UAB Libraries: Calcflow Handouts

Virtual reality tools and services provided by the UAB Libraries are intended to support the mission of the libraries and the University of Alabama at Birmingham. Materials developed for use with the virtual reality application Calcflow.
Redox control on chromium isotope behaviour in silicate melts in contact with magnesiochromite

&amp;lt;p&amp;gt;Transition metals are of special interest for understanding the conditions of differentiation processes such as core formation. Those that have more than one oxidation state can also provide powerful constraints on changing redox conditions in the mantle over time. The ability to determine isotopic fractionations associated with differentiation processes has provided a new dimension to exploration of the conditions in the early Earth in particular. It has been recently shown that Cr isotope variations in igneous systems are strongly affected by redox conditions and chromite crystallisation.&amp;lt;/p&amp;gt;&amp;lt;p&amp;gt;In this study, we have investigated the variations in chemical composition and Cr isotopic compositions in both magnesiochromite and silicate melts during experiments performed under controlled redox conditions. The Cr isotopic compositions measured in the silicate melts in our experiments are strongly influenced by oxygen fugacity and experiments performed at 1300 &amp;amp;#176;C and -12 &amp;lt; logfO&amp;lt;sub&amp;gt;2&amp;lt;/sub&amp;gt; &amp;lt; -6 are correlated with fO&amp;lt;sub&amp;gt;2&amp;lt;/sub&amp;gt;. This suggests that Cr isotopes are a powerful tool to study changes in redox conditions in high temperature processes. The Cr isotopic composition of silicate melt reacted under more oxidising conditions (logfO&amp;lt;sub&amp;gt;2&amp;lt;/sub&amp;gt; &amp;gt; -6) are isotopically much lighter compared to melts reacted at lower oxygen fugacity. Three hypotheses are proposed to explain such variations: (i) a change in Cr bonding environment in the silicate melt (ii) a change in Cr bonding environment in the chromite (iii) volatile loss of Cr from the silicate melt. More work is needed to definitively determine the factors that control the isotopic behaviour of Cr in silicate melts.&amp;lt;/p&amp;gt;
Analysis of Electromagnetic Force in Short Circuit Fault of Generator-Motor

At present, with the continuous development of China's economy and the increasing capacity of generators, higher requirements are put forward for the operation reliability of pumped storage power stations. As the core component of the pumped storage unit, the research on the abnormal operation state of the generator-motor in China is not deep enough. In this paper, the generator-motor is taken as the research object, and the field circuit coupling time-step finite element model is established by Ansoft. This paper analyzes the law of electromagnetic force, air gap flux density and eddy current distribution of damping winding when single-phase ground short circuit fault, phase to phase short circuit fault and two-phase ground short circuit fault occur during no-load operation of generator-motor. It has reference significance for fault diagnosis of generator-motor in abnormal operation.
Addressing the challenges of privacy preserving machine learning in the context of data anonymization

Machine learning (ML) models trained on sensitive data pose a distinct threat to privacy with the emergence of numerous threat models exploiting their privacy vulnerabilities.Therefore, privacy pre ...
A limitation on the KPT interpolation.

We prove a limitation on a variant of the KPT theorem proposed for propositional proof systems by Pich and Santhanam (2020), for all proof systems that prove the disjointness of two NP sets that are hard to distinguish.
Recurrent Machine Learning and Computing with Nonlinear Optical Waves

We demonstrate that optical time-dynamics are equivalent to a recurrent neural network and that they can be trained for high-performance on complex classification tasks, paving the way for passive analog machine learning processors.
PASCAL LibGuides: PASCAL Shared Library System Communications - TEMPLATE for Members: About the Shared System

This guide will provide a template for PASCAL members for campus outreach regrading the shared library system.
The Einstein Slide

Author(s): Ciach, Brian | Abstract: This music score was submitted for the Kaleidoscope 2020 Call for Scores, an open access collaboration with the UCLA Music Library.
LibGuides: GLBC 1200 - Leading the Way : Your FYS and the Library

Fall 2020 Global Citizenship Cornerstone. Instructor: Dr. Franklin This course guide is for Dr. Sharilyn Franklin's Global Citizenship Cornerstone course.
Reed Library: Student Services: Where Can I Study/Zoom?

Get a general overview of Reed Library's study spaces, resources, and information about getting help.
Assenze/presenze

Maxime Cella (Rueil-Malmaison, France, 1980 - Udine, Italy, 2019) was a poet and translator. He began publishing his first poems in 2009 and in 2011 the booklet Dieci poesie (‘Ten Poems’) was released. This essay offers a purely formalistic reading of the posthumously published Foss’io colui (‘Were I the one who’). After analysing the metrical aspects of the poem, the paper looks at the function of the “step verses” in order to evaluate its effect on versification and on the setting of the mise en page, which will be further examined in light of rhymes’ suffixes. Before concluding on a note on the vocalic phonosymbolism of the poem, the paper will then bring to light its dense phonic plot, from which Cella’s poetic awareness and ability can be clearly observed.
Spatial Trends of Maximum and Minimum Temperatures in Different Climate Zones of Pakistan by Exploiting Ground-based and Space-borne Observations

Temperature is a key indicator of a changing climate. A trivial change in temperature can result in significant changes in weather patterns with severe repercussions on ecology and socio-economic conditions of an area. This study aims to assess the changing trends in maximum and minimum temperatures in five climatic zones of Pakistan, and compare ground-based with satellite data from AIRS over these climatic zones of Pakistan. Mann Kendall test has been used to signify the temperature trends in all zones and seasons while Sen's slope value has been used to measure the magnitude of the trends for the time period 1978 to 2016. Ground observations have been compared with AIRS satellite observations for ascending and descending air temperatures by employing correlation and mean bias error. The results show that AIRS product (AIRSX3STM) underestimates Tmax and Tmin in all zones of Pakistan with the underestimation being most prominent in zone A. The trend analysis for maximum and minimum temperatures shows an increase in temperatures for all climate zones. Overall, Pakistan's maximum temperature increased by 0.026°C/year with the maximum increase of 0.05°C/year during pre-monsoon, and the minimum temperature increased by 0.027°C/year.
Decentralized Combinatorial Optimization

Combinatorial optimization is a widely-studied class of computational problems with many theoretical and real-world applications. Optimization problems are typically tackled using hardware and software controlled by the user. Optimization can be competitive where problems are solved by competing agents in isolation, or by groups sharing hardware and software in a distributed manner. Blockchain technology enables decentralized applications (DApps). Optimization as a DApp would be run in a trustless manner where participation in the system is voluntary and problem-solving is incentivized with bitcoin, ether, or other fungible tokens. Using a purpose-built blockchain introduces the problem of bootstrapping robust immutability and token value. This is solved by building a DApp as a smart-contract on top of an existing Turing-complete blockchain platform such as Ethereum. We propose a means of using Ethereum Virtual Machine smart contracts to automate the payout of cryptocurrency rewards for market-based voluntary participation in the solution of combinatorial optimization problems without trusted intermediaries. We suggest use of this method for optimization-as-a-service, automation of contests, and long-term recording of best-known solutions.
THE IDEOLOGY OF DONALD TRUMP ON HIS SPEECH AT THE ISRAEL MUSEUM: FAIRCLOUGH’S THREE MODELS OF CDA

This research investigated the ideology of Donald Trump on his speech at the Israel museum. This research focused on analysing illocutionary acts to discover the ideology of Trump on his speech. This research used qualitative approach. The design of this research is Critical Discourse Analysis (CDA). This research used Fairclough’s three models of CDA, namely: textual analysis, discursive practice and social practice The result that showed there were five types of illocutionary acts expressed, those are representatives, directives, commissives, expressives and declaratives. Representatives was mostly expressed by Trump. Therefore, the result showed that Trump expressed all types of illocutionary act. The ideology on the speech at the Israel museum showed that Trump intended to use his power to create peace in Jerusalem.