Reviewerly/exHarmony huggingface dataset:
LibGuides: LibAnswers Training Guide for UL Employees: Queues

This is a guide for how to use LibAnswers at the CMU University Libraries. The guide includes materials for learning about the system, and our policies for use. This page lists the queues and groups set up within the libraries.
Scaling up an Unsupervised Image-to-Image Translation Framework from Basic to Complex Scenes

Unsupervised image-to-image translation methods have received a lot of attention in the last few years. Multiple techniques emerged tackling the initial challenge from different perspectives. Some focus on learning as much as possible from several target style images for translations while other make use of object detection in order to produce more realistic results on content-rich scenes. In this work, we assess how a method that has initially been developed for single object translation performs on more diverse and content-rich images. Our work is based on the FUNIT[1] framework and we train it with a more diverse dataset. This helps understanding how such method behaves beyond their initial frame of application. We present a way to extend a dataset based on object detection. Moreover, we propose a way to adapt the FUNIT framework in order to leverage the power of object detection that one can see in other methods.
Abstract Data Types

Programs operate on data. It is thus natural to start our considerations of how to think about programs by a discussion of how to think about data types. For this purpose, we do not really need to know how the objects of a type are concretely represented (such representations have been discussed in Chap. chapter:models); we may rather focus on the properties that are satisfied by the operations which have been given to us to work with these objects. This view is also in line with modern software engineering that abstracts from the implementation details of data by encapsulating them in classes that only expose a (more or less) well documented method interface to the user.
LibGuides: BTC: Diverse Children's Literature: Book Awards

A starting place to learn how to search for diverse literature in the Ballenger Teachers Center Collection
LibGuides: System Wide Holds - Training Guide: Check-in/Check-out

The purpose of this guide is to provide staff a reference resource for processing Requests and Holds on NLPL materials.
LibGuides: STEM Research Project | Summer 2021: Databases & Research

Educating Students About the Role of Technology on Selective Attention and Memory project funded by the School of Science AISLE Grant.
Paraphrasing as a Strategy to Develop Reading Comprehension at The Tertiary Level of Education

The three aims of this study are to determine (1) the reading proficiency and the motivation level of a group of tertiary level learners, (2) how far paraphrasing as a strategy can help in developing the reading comprehension of the learners, and (3) whether this strategy also motivates the learners to read more. This study employed a quasi-experimental design. The research population comprised all 18 students in the third semester of the MA in ELT (English Language Teaching) programme of Gauhati University. The data were collected by using (1) two types of tests to measure abilities in literal and inferential comprehension, (2) paraphrasing as technique for reading and (3) questionnaires. The results showed that there was a greater engagement with the text and higher levels of motivation while using the paraphrasing strategy. However, more research needs to be carried out to obtain conclusive evidence that the reading comprehension of students can be developed substantially with the use of the paraphrasing strategy.
Library Website & LibGuides: Document Delivery Services : Home

Document Delivery Service (DDS) is a service for KAUST students, faculty and staff to request full-text articles and book chapters (maximum 3 chapters) not available in the Library sources.
Detection Limits and Near-Field Ground Motions of Fast and Slow Earthquakes

&amp;lt;p&amp;gt;We investigate theoretical limits to detection of fast and slow seismic events and discuss spatial variations of ground motion expected from an synthetic family of M6 earthquakes at short epicentral distances. The performed analyses are based on synthetic velocity seismograms calculated with the discrete wavenumber method assuming seismic velocities and attenuation properties of the crust in Southern California. The examined source properties include &amp;amp;#160;magnitudes ranging from M -1.0 to M 6.0, static stress drops (0.1-10 MPa), and slow and fast ruptures (0.1-0.9 of shear wave velocity). For the M 6.0 events we also consider variations in rise times producing crack- and pulse-type events and different rupture directivities. We found slow events produce ground motions with considerably lower amplitude than corresponding regular fast earthquakes with the same magnitude, and hence are significantly more difficult to detect. The static stress drop and slip rise time also affect the maximum radiated seismic motion, and thus event detectability. Apart from geometrical factors, the saturation and depletion of seismic ground motion at short epicentral distances stem from radiation pattern, earthquake size (magnitude, stress drop), and rupture directivity. The rupture velocity, rise time and directivity affect significantly the spatial pattern of the ground motions. The results can help optimizing detection of slow and fast dynamic small earthquakes and understand the spatial distribution of ground motion generated by large events.&amp;lt;/p&amp;gt;
Pre-operational testing

This chapter will outline the importance and key challenges in piloting test items and tasks prior to a live (operational) test administration. It will discuss the relevance of pre-operational testing for ensuring valid and reliable language tests and locate it within the test development cycle as well as validation frameworks. The chapter will also highlight some useful methods for researching and analyzing prototype tasks and pilot items. It will conclude with recommendations for good practice.
EffCNet: An Efficient CondenseNet for Image Classification on NXP BlueBox

Intelligent edge devices with built-in processors vary widely in terms of capability and physical form to perform advanced Computer Vision (CV) tasks such as image classification and object detection, for example.With constant advances in the field of autonomous cars and UAVs, embedded systems and mobile devices, there has been an ever-growing demand for extremely efficient Artificial Neural Networks (ANN) for real-time inference on these smart edge devices with constrained computational resources.With unreliable network connections in remote regions and an added complexity of data transmission, it is of an utmost importance to capture and process data locally instead of sending the data to cloud servers for remote processing.Edge devices on the other hand, offer limited processing power due to their inexpensive hardware, and limited cooling and computational resources.In this paper, we propose a novel deep convolutional neural network architecture called EffCNet which is an improved and an efficient version of CondenseNet Convolutional Neural Network (CNN) for edge devices utilizing self-querying data augmentation and depthwise separable convolutional strategies to improve real-time inference performance as well as reduce the final trained model size, trainable parameters, and Floating-Point Operations (FLOPs) of EffCNet CNN.Furthermore, extensive supervised image classification analyses are conducted on two benchmarking datasets: CIFAR-10 and CIFAR-100, to verify real-time inference performance of our proposed CNN.Finally, we deploy these trained weights on NXP BlueBox which is an intelligent edge development platform designed for self-driving vehicles and UAVs, and conclusions will be extrapolated accordingly.
Classifying toric surface codes of dimension 7

Toric surface codes are a class of error-correcting codes coming from a lattice polytope defining a two-dimensional toric variety. Previous authors have mostly completed classifications of these toric surface codes with dimension up to $k = 7.$ In this note, we correct an error in the classification of the $k=7$ case started in \cite{HLYZZ}, and disprove one of their conjectures.
Stochastic Rounding for Image Interpolation and Scan Conversion

The stochastic rounding (SR) function is proposed to evaluate and demonstrate the effects of stochastically rounding row and column subscripts in image interpolation and scan conversion.The proposed SR function is based on a pseudorandom number, enabling the pseudorandom rounding up or down any non-integer row and column subscripts.Also, the SR function exceptionally enables rounding up any possible cases of subscript inputs that are inferior to a pseudorandom number.The algorithm of interest is the nearest-neighbor interpolation (NNI) which is traditionally based on the deterministic rounding (DR) function.Experimental simulation results are provided to demonstrate the performance of NNI-SR and NNI-DR algorithms before and after applying smoothing and sharpening filters of interest.Additional results are also provided to demonstrate the performance of NNI-SR and NNI-DR interpolated scan conversion algorithms in cardiac ultrasound videos.
Performance Analysis of Different Word Embedding Models forText Classification

The task of classifying an unstructured document tothe proper category to which it belongs to is becoming a herculeantask because of the steady but exponential growth in the volume of information shared over the internet. Text classification isthe task of allocating the documents into one or more number of predefined categories. In general, this technique is used in thefield of information retrieval, text summarization and, text extraction. From extant literature, the performance of textclassification system depends on adequate textual representation of the text document. To perform the classification task,transformation of text into feature vectors is a very important stage. Several textual representation techniques such as bag ofwords, n-gram and topic models have been proposed by authors to capture the real semantics of web documents but are fraughtwith several challenges such as semantic mismatch and multiple meanings of words.Thus, this paper proposes word embedding’s to solve the document representation problem in text classification systems. Inorder to achieve this task, this research work utilizes different word embedding algorithms to represent documents which arealso used in conjunction with classification algorithms to determine the most effective embedding model. Results obtainedconfirms the earlier assumption that Word2Vec performs robustly on very high dimensional text such as web documents, it alsocaptures the real semantics of the web document The performance metrics employed in this research work are Precision, fmeasureand accuracy.
Virtualization of Digital Location-Based Experiences

Digital location-based experiences, such as app-guided digital scavengers, depend on users being on-site. The requirement to be on-site is a virtue, but it can also be a shortcoming of location-based experiences, such as in the COVID 19 pandemic. This workshop addresses the possibilities of eliminating the on-site requirement, thus extending the potential application of location-based experiences. First, virtualization approaches will be presented, which allow eliminating the need to be on-site, such as the usage of 360° technologies or the employment of videoconferencing software. Further, various challenges, such as the application of existing design principles for location-based experiences and instructional design for virtualized location-based experiences, are discussed and options to overcome the limitations imposed by the virtualization. This paper provides insights into theoretical foundations relevant to solving the aspects of virtualizing location-based experiences. The workshop results are intended to provide lasting advancements to eliminating the on-site requirements for location-based experiences.
Generation of Virtual Humans for Virtual Reality, Medicine, and Domestic Assistance

Virtual humans are employed in various applications including computer games, special effects in movies, virtual try-ons, medical surgery planning, and virtual assistance. This thesis deals with virtual humans and their computer-aided generation for different purposes. In a first step, we derive a technique to digitally clone the face of a scanned person. Fitting a facial template model to 3D-scanner data is a powerful technique for generating face avatars, in particular in the presence of noisy and incomplete measurements. Consequently, there are many approaches for the underlying non-rigid registration task, and these are typically composed from very similar algorithmic building blocks. By providing a thorough analysis of the different design choices, we derive a face matching technique tailored to high-quality reconstructions from high-resolution scanner data. We then extend this approach in two ways: An anisotropic bending model allows us to more accurately reconstruct facial details. A simultaneous constrained fitting of eyes and eyelids improves the reconstruction of the eye region considerably. Next, we extend this work to full bodies and present a complete pipeline to create animatable virtual humans by fitting a holistic template character. Due to the careful selection of techniques and technology, our reconstructed humans are quite realistic in terms of both geometry and texture. Since we represent our models as single-layer triangle meshes and animate them through standard skeleton-based skinning and facial blendshapes, our characters can be used in standard VR engines out of the box. By optimizing computation time and minimizing manual intervention, our reconstruction pipeline is capable of processing entire characters in less than ten minutes. In a following part of this thesis, we build on our template fitting method and deal with the problem of inferring the skin surface of a head from a given skull and vice versa. Starting with a method for automated estimation of a human face from a given skull remain, we extend this approach to bidirectional facial reconstruction in order to also estimate the skull from a given scan of the skin surface. This is based on a multilinear model that describes the correlation between the skull and the facial soft tissue thickness on the one hand and the head/face surface geometry on the other hand. We demonstrate the versatility of our novel multilinear model by estimating faces from given skulls as well as skulls from given faces within just a couple of seconds. To foster further research in this direction, we made our multilinear model publicly available. In a last part, we generate assistive virtual humans that are employed as stimuli for an interdisciplinary study. In the study, we shed light on user preferences for visual attributes of virtual assistants in a variety of smart home contexts.
Towards an Accountable Internet of Things: A Call for Reviewability

As the IoT becomes increasingly ubiquitous, concerns are being raised about how IoT systems are being built and deployed. Connected devices will generate vast quantities of data, which drive algorithmic systems and result in real-world consequences. Things will go wrong, and when they do, how do we identify what happened, why they happened, and who is responsible? Given the complexity of such systems, where do we even begin?This chapter outlines aspects of accountability as they relate to IoT, in the context of the increasingly interconnected and data-driven nature of such systems. Specifically, we argue the urgent need for mechanisms—legal, technical, and organisational—that facilitate the review of IoT systems. Such mechanisms work to support accountability, by enabling the relevant stakeholders to better understand, assess, interrogate and challenge the connected environments that increasingly pervade our world.
실시간 쌍방향 원격수업에서 의사소통중심 교수법

This study explores not only Korean college students’ perceptions of employing Communicative Language Teaching (CLT) in a synchronous online course using Zoom, a videoconferencing tool, but also factors influencing their perceptions. Twenty students, who had low English proficiency taking Practical English III during the COVID-19 pandemic, took part in this study. Data from surveys and individual interviews were collected. Both descriptive analysis of survey data and thematic analysis of interviews with eight volunteers were carried out. The results show that students perceived the Zoom class positively with no preference for pair work or whole class work. In addition, there were two factors affecting students’ perceptions: the promotion of authentic interaction and participation in interesting communicative activities. The findings not only support the possibility of adopting CLT in synchronous online settings, but also suggest balancing form-focused and meaning-focused activities for beginners.
The Dilemma of Information Management and Decision Science in the Virtual World: A Study of the Disclosure of the Social Networking Sites Psychological & Manipulative Techniques and the Intellectual Security of Arab Mind

Intellectual security has become a permanent source of headache for the Arab countries because it has recently become vulnerable to many external influences resulting from the incessant effect of the social networking sites and their potential threats on the minds of the young Arab. The present study aims to delineate the threats posed by the social networking sites on the intellectual security of Arab young people. To achieve this end, the study applies the qualitative methodology through which it can analyze critically the potential threats posed by the social networking sites on the intellectual of security. The study has found that the social networking sites employ logical fallacies for brainwashing the minds of Muslims young people and changing their ideas and manipulating their thoughts and isolating them from their cultural and religious values. Young Arab students should have learnt from their tender ways of critical and creative thinking.
Algoritma C4.5 Dalam Mengklasifikasi Tindak Kejahatan Yang Sering Terjadi Di Kecamatan Siantar Barat Pematangsiantar

Crime is a problem that often occurs in everyday life and is an action that can cause certain parties to be harmed both physically and materially. Factors that influence these crimes include immorality, molestation, theft, gambling, extortion/threatening, embezzlement, fraud, and vandalism. The increase in crime at this time is very significant. Over time, crime increased in an erratic pattern. In this study, the authors tried to mine data (data mining) reports of crimes that occurred at the Siantar Barat Police, Pematangsiantar City from the previous year. The data were analyzed using the C.45 algorithm, where this algorithm aims to classify data on certain crime classes. With the creation of this system, it is hoped that it can assist the police in classifying crimes and minimizing areas prone to crime
IMPACT OF SOCIAL MEDIA ON ARABIC LANGUAGE DETERIORATION

This study investigates the effect of Facebook on Arabic language attrition, i.e., decrease in language proficiency, as exhibited in the use of Colloquial instead of Standard Arabic, use foreign words although Arabic equivalents exist, and committing spelling errors. A sample of Facebook posts and a corpus of spelling errors on Facebook were randomly selected and analyzed. Samples of college students and instructors were surveyed to find out the reasons for this new socio-linguistic phenomenon. It was found that most educated adult Facebook users use slang and Colloquial language. Some Arabic posts are fully Romanized rather than written in Arabic script. English words are transliterated and inserted in Arabic posts. Many adult Facebook users completely ignore Standard Arabic spelling rules. They spell words the way they pronounce them in their own dialects. Users do not seem to recognize word boundaries, cannot connect phonemes with the graphemes they represent and cannot distinguish vowel length. Participants reported that it is easier for them to express themselves in slang and Colloquial Arabic. They feel they are conversing with others, not writing. Therefore, they write the way they speak and do not think about spelling and grammar. Results and recommendations are given in detail.
A study on the challenges faced by the Faculties of Media Education during Covid 19 pandemic (With special reference to Pune)

Media education is a generic term for different forms of education about the media, journalism, mass communication and its allied subjects. It is the process of teaching and learning of the entire areas of communication. The media industry is one of the most thriving sectors in India and therefore media education has become an important area of study in the last two decades in India. In spite of its growing demand, the existing conventional education system has not been successful in meeting these demands. Media education in India is framed in the higher education system, comprising of programs in the universities, both government-supported and media-backed private institutions, as well as in-service and short-term courses offered by press associations and other organizations. Known as Oxford of the east in Pune there are almost 30 media education intuitions and all of them providing different media programmes.The global outbreak of COVID-19 has affected human lives in the most adverse way. The entire world is engulfed in tragedy as crisis strikes in every sector. Each person in any sector including education, health, economy, agriculture, business, entertainment etc. has been facing serious repercussions due to the outbreak of the pandemic. The media education institutions are also facing various challenges during this period. The faculties, students have faces very difficult times during this time phase. The purpose of the research is to identify the various issues faced by the different media faculties from various universities in Pune. Factors can be identified by conducting a survey based research at various universities located in Pune through in depth interview. The researcher in this research will discuss the different technical challenges faced by the faculties during this covid pandemic. The researcher also will try to find out some possible solution for these.
English Literacy untuk Meningkatkan Pemahaman Bahasa Inggris Anak-Anak Panti Asuhan Assyaamil

The purpose of this project is to increase knowledge about English and Online shop and to help them increase their income by selling products in the online shop. The implemented method of this project is to teach both English and how to sell products in the online shop to the orphans in Nongsa. The teaching methods are by oral explanation and playing games. Learning English with an oral explanation which was continued with a game about the material that has studied and Learning Online shop with an oral explanation. The result of this project is learning English by playing games is easier to understand than learning English with oral explanation and learning English will be more fun by playing games.