Reviewerly/exHarmony huggingface dataset:
Visual Grounding Strategies for Text-Only Natural Language Processing

Visual grounding is a promising path toward more robust and accurate Natural Language Processing (NLP) models. Many multimodal extensions of BERT (e.g., VideoBERT, LXMERT, VL-BERT) allow a joint modeling of texts and images that lead to state-of-the-art results on multimodal tasks such as Visual Question Answering. Here, we leverage multimodal modeling for purely textual tasks (language modeling and classification) with the expectation that the multimodal pretraining provides a grounding that can improve text processing accuracy. We propose possible strategies in this respect. A first type of strategy, referred to as transferred grounding consists in applying multimodal models to text-only tasks using a placeholder to replace image input. The second one, which we call associative grounding, harnesses image retrieval to match texts with related images during both pretraining and text-only downstream tasks. We draw further distinctions into both strategies and then compare them according to their impact on language modeling and commonsense-related downstream tasks, showing improvement over text-only baselines.
Library Guides: A Faculty Guide to Kanopy Streaming Video: OneSearch Method - All Streaming Video Databases

How faculty can find, request, and link to Kanopy streaming videos, and also check license expiration dates.
UCF Research Guides: UCF Libraries at Valencia College: Valencia Osceola

See this guide for information about the UCF Libraries at Valencia West, Valencia Osceola, and Valencia East
Short Term Effect of Virtual Reality on Eye Accommodative Ability

Virtual reality (VR) is a fast-growing technology in the world today. Many countries use virtual reality for many purposes such as education, military and entertainment. Despite the benefits of VR, harmful effects of VR on the users are still inconclusive. With only a few reliable studies that investigate the effect of virtual reality on the users especially on the eyes, yet still there are a lot more things we do not know about the effects of VR. The purpose of this study was to compare the amplitude of accommodation before and after watching 3-dimesional (3D) movie utilizing VR and notebook (control group). Thirty-two participants volunteered in this study and all participants underwent amplitude of accommodation (AA) test using Royal Army Force (RAF) rule before and after watching three-dimensional (3D) movie for 30 minutes using VR and two-dimensional (2D) movie by laptop. The amplitude of accommodation between pre- and post-watching 3D movie on VR was insignificantly changed (p= &gt;0.05). The similar trend was also found after 30 minutes watching movie using laptop (p= &gt;0.05). The utilization of VR and laptop for 30 minutes did insignificantly alter the eye accommodation.
A Data Compression Approach for Big Data Classification

Abstract - A data compression approach for big data classification is used, first, to compress large size dataset into small size dataset, then to created and build the classification model for the compressed dataset and evaluate the model’s accuracy. Data compression algorithms are used to compress and reduce the size of dataset. The compression mechanisms help to increase and optimize operational efficiencies, enable cost reductions, and reduce risks for the business operations. It is becoming costly to process large size datasets, which need to be reduced by using compression techniques. The compression algorithm controls each bit of a dataset and optimizes the size without losing any data subsequently by using a lossless data compression approach. In a lossless data compression technique, data can be compressed without loss. Therefore, the restored dataset is equal to the original form of the dataset. In this thesis, a classification model for the initial datasets has been created and built by using a J48 classification algorithm. The built-in model of the original datasets has been evaluated to get the evaluation statistics of the model, the accuracy of the model, and the confusion matrix results of the model. Then, it is possible to extract correctly and incorrectly classified instances of a given dataset. The built-in decision tree has root, internal, and leave nodes, which draws paths of the tree. A path is a way from the root-through-internal-to-leave node and the number of paths are equal to the number of leaves. In each path, there are one or more instances. We can extract the paths of correctly and incorrectly classified instances from the classifier model. In addition, it is also possible to extract instances from the paths. In order to get paths of the tree and an instance from a path, it is required to generate and get the source strings of the tree. We can extract instances from the tree or from each path and create a compressed small dataset. Then we can concatenate one compressed dataset with the other compressed dataset and create another compressed dataset. Like the original dataset, we can created and built classification models for the compressed datasets. The models have been evaluated and the evaluation results of the compressed dataset model have been compared with the evaluation results of the original dataset model. As a result, we can see the accuracy of the classification models of the original and compressed datasets. The initial datasets have been selected from UCI Machine Learning Repository.
avatar—Automated Feature Wrangling for Machine Learning

A large part of the time invested in data science is spent on manual preparation of data. Transforming wrongly formatted columns into useful features takes up a significant part of this time. We present the avatar algorithm for automatically learning programs that perform this type of feature wrangling. Instead of relying on users to guide the wrangling process, avatar directly uses the predictive performance of machine learning models to measure its progress during wrangling. We use datasets from Kaggle to show that avatar improves raw data for prediction, and square it off against human data scientists.
Testing agreement between lexicographers: A case of homonymy and polysemy

In this paper we compare Oxford Lexico and Merriam Webster dictionaries with Princeton WordNet with respect to the description of semantic (dis)similarity between polysemous and homonymous senses that could be inferred from them. WordNet lacks any explicit description of polysemy or homonymy, but as a network of linked senses it may be used to compute semantic distances between word senses. To compare WordNet with the dictionaries, we transformed sample entry microstructures of the latter into graphs and cross-linked them with the equivalent senses of the former. We found that dictionaries are in high agreement with each other, if one considers polysemy and homonymy altogether, and in moderate concordance, if one focuses merely on polysemy descriptions. Measuring the shortest path lengths on WordNet gave results comparable to those on the dictionaries in predicting semantic dissimilarity between polysemous senses, but was less felicitous while recognising homonymy.
The study of potential evapotranspiration (PET) in UMP Gambang

Potential evapotranspiration (PET) is a term represents the combination of two processes water cycle whereby water is lost to the atmosphere from the soil and water bodies by evaporation meanwhile transpiration from vegetation or plant. PET is a complex and one of the most essential process in the hydrological cycle. It is useful to measure the atmospheric water demand of the region and hence could be used for various applications such as irrigation scheduling, drought monitoring, and crop production and understanding climate change impacts. The objectives of the study are to analyse the value of PET by using radiation-based methods; Penman-Monteith (PM) and Turc and temperature-based methods; Blaney-Criddle (BC) and Thornthwaite (TW) method in UMP Gambang and to evaluate the performance of PET estimation method. In this study, the comparison was made in term of values of PET by using Penman-Monteith, Turc, Blaney-Criddle and Thornthwaite methods with the exact PET values. It was found that radiation-based methods gave better performance compared to temperature-based methods in estimation of PET in the study. In radiation-based methods, PM method is the appropriate method to estimate PET in UMP Gambang with the highest accuracy of (R2 = 0.6447 for 2016, 0.6028 for 2017 and 0.6007 for 2018) and the lowest value of (RMSE = 0.3056 for 2017, 0.5836 for 2018) compared to the other methods.
MULTILINGUAL THEMATIC PICTURE DICTIONARY: ASSISTING YOUNG LEARNERS’ LITERACY

This study aimed at developing a media, named a multilingual thematic picture dictionary to support the development of fourth grade elementary school students’ literacy. This study applied Design and Development research with Analysis, Design, Development, and Evaluation model proposed by Richey and Klein (2007). The subjects of the research were the fourth grade elementary school students who studied in rural and urban area. The data in this study were obtained from observation, interview, questionnaire, document analysis, content validity judgment, and quality judgment. The data obtained were collected by using four instruments, namely; observation sheet, interview guide, questionnaire, and expert judgment sheet. The data were analyzed qualitatively and quantitatively. The results showed that the multilingual thematic picture dictionary contents were relevant to the criteria of a good multilingual thematic picture dictionary and was categorized as an excellent category. Keywords: literacy, young learner, dictionary
LibGuides: Emotional Design: Emotional Design Theory

This quick guide provides you with information on the library collections, services and facilities that are useful for this topic.
5 Best Password Manager for Windows/Mac/Android in 2021!

Passwords are difficult to remember sometimes. And for most people, it happens most of the time. That’s why there are many reported issues online ...
The Use Of YouTube As Teaching Media In Public Speaking Class: Students Perspective

This study discusses students' perspectives on the use of YouTube as a teaching medium in a public speaking class. The purpose of this study is how the students' perspectives on the use of YouTube as a teaching media in Public Speaking Class. Researchers are interested in this problem because the use of YouTube is applied as a teaching media in the Public Speaking class as a task shift or as a substitute for class meetings. Researchers also want to find out whether there are advantages and disadvantages in using YouTube as a teaching media in Public Speaking class.This type of research is descriptive qualitative. Researchers use interviews to get data from students because researchers want to know about students' perspectives in-depth and interviews are the right technique for collecting data. The sample in this study was five students of English education at the Muhammadiyah University of Surakarta who had taken public speaking courses. The results of this study are: (1) Using YouTube as a learning medium is helpfulfor students who are not confident in speaking in public and more careful preparation. (2) YouTube allows the students to be creative. (3) The using of YouTube in learning increase students’ vocabulary. (4) Disadvantages of using YouTube are the absence of classroom meeting and technical problems are challenging.
KEDISIPLINAN BELAJAR SISWA DALAM PROSES PEMBELAJARAN DI SEKOLAH DASAR

The aims of this study is to reveal the types of disciplinary learning of students in elementary schools, and the factors that influence them. This research uses descriptive quantitative design. The subjects of this study were 26 students of class III A, while 24 students of class III B were used to trial questionnaire research instruments. The data collection technique was carried out through distributing questionnaires which were then followed up through an interview process. Based on the results of trials on 26 items of the learning discipline questionnaire, 24 items were declared valid and had very high reliability, namely 0, 979. The results showed that in the aspect of student attendance, both male students and female students were included in the very strong category. In the aspect of following lessons in class, female students are in the very strong category, while male students are in the strong category. In the aspect of doing assignments, both male, and female students are in the strong category, and in the aspect of external, and internal factors are also in the strong category.
Content-based Models of Quotation

We explore the task of quotability identification, in which, given a document, we aim to identify which of its passages are the most quotable, i.e. the most likely to be directly quoted by later derived documents. We approach quotability identification as a passage ranking problem and evaluate how well both feature-based and BERT-based (Devlin et al., 2019) models rank the passages in a given document by their predicted quotability. We explore this problem through evaluations on five datasets that span multiple languages (English, Latin) and genres of literature (e.g. poetry, plays, novels) and whose corresponding derived documents are of multiple types (news, journal articles). Our experiments confirm the relatively strong performance of BERT-based models on this task, with the best model, a RoBERTA sequential sentence tagger, achieving an average rho of 0.35 and NDCG@1, 5, 50 of 0.26, 0.31 and 0.40, respectively, across all five datasets.
The effect of Partner Share Strategy to Students' Speaking Ability at Senior High School 2 Koto Baru Solok

Partner share strategy is one of the cooperative learning strategies which develop both students’ social and higher level of cognitive skills.The strengths of this technique were used to solve students’ learning problem in EFL learning to speak at class X of Islamic Senior High Scholl 2 Koto Baru Solok. The result of the experiment showed that means score of experimental class in post-testwas 73.60 higher than the control class (66.97). It indicates that teaching speaking skill through Partner Share Strategy was successfully upgrade students social and cognitive competence in spoken English. Therefore, it is recommended that the English teacher should determine the use of partner share strategy in teaching speaking. Other researchers were also suggested to carry out further studies to deal with the issues particularly in the level of Senior High School.
Reflections on Higher EeWork Under the Mode of "Suspension of Classes without Suspension of Schooling"

The online teaching mode of “suspension of classes without suspension of schooling” is a new teaching mode and means in the epidemic period. As a result of the COVID-19 epidemic, higher education is also facing new challenges. Unlike basic education, higher education has more extensive and specialized special requirements. In order to better promote and apply this method to the teaching work, this paper analyzes the main characteristics and existing problems of the online teaching mode of “suspension of classes without suspension of schooling” from the four aspects of students, teachers, university management and social level, aiming at the countermeasures and suggestions for the development of online teaching.
AfriKI: Machine-in-the-Loop Afrikaans Poetry Generation

This paper proposes a generative language model called AfriKI. Our approach is based on an LSTM architecture trained on a small corpus of contemporary fiction. With the aim of promoting human creativity, we use the model as an authoring tool to explore machine-in-the-loop Afrikaans poetry generation. To our knowledge, this is the first study to attempt creative text generation in Afrikaans.
LibGuides: Library Orientation: RemoteXs

The purpose of this guide is to introduce you to services and resources available at your Library.
Correction to: Development of efficient and robust Eikonal solver variants for first-arrival seismic modeling

A Correction to this paper has been published: https://doi.org/10.1007/s10596-020-10022-1
RETRACTED: Research on Optimization Plan of Enterprise Employee Training under the Background of Big Data

Abstract This article takes SMEs as the research object, and aims to study the problems and optimization schemes of SME employee training under the background of big data. This article uses a combination of literature reading, statistical analysis and questionnaire survey to investigate the employees of a certain company’s specific production base, and conducts research and analysis on the company’s employee training management. This article first introduces some concepts of modern enterprise training, and then analyzes the status quo of enterprise employee training. Through the interviews and questionnaires issued to the employees of the company, it analyzes the problems and causes of the company’s employee training management, and provides optimized solutions for the company’s employee training. The experimental results of this paper show that the optimization of corporate employee training programs under the background of big data plays a positive role in corporate management. It improves employee enthusiasm and work commitment, and increases the number of corporate trainings.
Genre Analysis based on Principal Component Analysis and Random Forest

When you listen to music, have you ever noticed that some songs are similar to the other while some are quite different?Maybe this is a universal phenomenon, however, our work try to provide fascinating insights into the characteristics and development of music.We create the adjacency matrix of 5603 musical artists to demonstrate the relationship between them, then we draw a subnetwork to show the connection between the influencers and the followers of Classical music in the 1930s.After that, we try to quantify the influences and similarities between these artists, using the adjacency matrix and principal component analysis (PCA) method, and establishing two indicators: 'influence' and 'dissimilarities'.To test the practicability of the previous indicators, we apply them to analyze the genres of music, including the a comparison of influences and similarities between and within genres, the developing process of genres and the relationship of different genres.Especially, we use the random forest method to work out what distinguishes a genre.We find that artists within genre are statitically more similar to artists between genre.
Research Guides: Library Workshop Descriptions: Unix Command-line

Information, materials, and schedules for all currently offered library workshops The Unix Command-line is a powerful tool for users to interact with their computer. Although using a command-line requires some practice, it becomes much more intuitive and efficient than a Graphical User Interface (GUI).
Subject Guides: Welcome to Special Collections: Finding a personal researcher

A guide to visiting the Special Collections department at the University of Iowa Libraries.
RETRACTED: Design of Network Teaching Platform Based on Artificial Intelligence Technology

Abstract In recent years, the rapid development of network teaching has played an important role in the popularization of distance education in China. With the development of network technology, compared with the traditional teaching mode, network teaching platform has more and more obvious advantages, and has become one of the important tools of teaching and learning. However, the traditional network teaching platform is lack of intelligence and interactivity, which can be compensated by artificial intelligence technology. Therefore, this paper puts forward the design and research of network teaching platform based on artificial intelligence technology. In this paper, the development of artificial intelligence platform, as well as the application of artificial intelligence platform, can greatly promote the development of artificial intelligence teaching platform. In this paper, according to the shortcomings of the existing network teaching platform, combined with artificial intelligence technology for optimization and improvement, through the optimization algorithm, simplified steps and other operations, further enhance the intelligence of the teaching platform. In order to further understand the application of network teaching platform in the actual teaching process in our country, this paper has carried out relevant investigation and research. The results show that 3.5% of the students who use the network teaching platform have a good use of the network teaching platform, and the results show that 3.5% of the college students use the network teaching platform in a week.
Meta-model of the teaching and learning environment based on ICT integration in the e-learning systems

In a globalizing world driven by the rapid development of ICT, the education system is facing the challenge of promptly seeking and applying suitable methods that can be introduced into the classroom. The main purpose of the paper is to investigate the degree of integration of ICT into the learning process.A meta-model for the integration of ICT tools into the teaching and learning environment has been defined. A methodology has been proposed for evaluating the level of ICT knowledge and utilization and the impact of ICT on the learning process after the introduction of the proposed model. Finally, the results obtained from the study have been appropriately analysed.
Analysis and Detection of WBC Cancer Cells Using Random Forest Classifier

The stem cells which are present in the bone marrow produces the blood cells in our body. There are totally three types of blood cells presents in the blood and they are Red Blood Cells , White Blood Cells and the Platelets. From the above three classifications, White blood cells play an important role. Because it protects our body from the infection by fighting with the foreign agent. According to World Health Organisation (WHO), cancer is considered as the second leading cause of death in the World. Thus, the main scope of the project is to detect the cancer cells present in the white blood cells. The WBC Cancer cells are further divided in to two major categories. They are ALL (Acute Lympotic Leukemia), and AML (Acute Myolegenous Leukemia) both of the categories include similar symptoms diseases that may confusing in diagnosing. To avoid this confusion and produce high accuracy results, Random Forest Classifier is used.
An improved density peaks clustering algorithm based on CURE

As a new density-based clustering algorithm, clustering by fast search and find of Density Peaks (DP) algorithm regards each density peak as a potential clustering center when dealing with a single cluster with multiple density peaks, therefore it is difficult to determine the correct number of clusters in the data set.To solve this problem, a mixed density peak clustering algorithm namely C-DP was proposed.Firstly, the density peak points were considered as the initial clustering centers and the dataset was divided into sub-clusters.Then, learned from the Clustering Using Representatives algorithm (CURE), the scattered representative points were selected from the sub-clusters, the clusters of the representative point pairs with the smallest distance were merged, and a parameter contraction factor was introduced to control the shape of the clusters.The experimental results show that the C-DP algorithm has better clustering effect than the DP algorithm.The comparison of the F-measure Index shows that the C-DP algorithm improves the accuracy of clustering when datasets contain multiple density peaks in a single cluster.