Reviewerly/exHarmony huggingface dataset:
Construction of network teaching and research course platform based on multimedia and deep learning

Abstract Today's online courses are widely used. This is also one of the main ways many people pursue learning. With the rapid advancement of China's education reform, people are no longer satisfied with the traditional classroom teaching. With the emergence of deep learning technology, today's university education and other adult education have begun to change to mixed teaching methods. Building a network teaching and research platform based on multimedia and deep learning is a hot topic today. This paper expounds the current situation of traditional curriculum teaching. Finally, it expounds the construction of multimedia network teaching and research course platform.
A Tight Computational Indistinguishability Bound for Product Distributions

Assume that distributions $$X_0,X_1$$ (respectively $$Y_0,Y_1$$ ) are $$d_X$$ (respectively $$d_Y$$ ) indistinguishable for circuits of a given size. It is well known that the product distributions $$X_0Y_0,\,X_1Y_1$$ are $$d_X+d_Y$$ indistinguishable for slightly smaller circuits. However, in probability theory where unbounded adversaries are considered through statistical distance, it is folklore knowledge that in fact $$X_0Y_0$$ and $$X_1Y_1$$ are $$d_X+d_Y-d_X\cdot d_Y$$ indistinguishable, and also that this bound is tight. We formulate and prove the computational analog of this tight bound. Our proof is entirely different from the proof in the statistical case, which is non-constructive. As a corollary, we show that if X and Y are d indistinguishable, then k independent copies of X and k independent copies of Y are almost $$1-(1-d)^k$$ indistinguishable for smaller circuits, as against $$d\cdot k$$ using the looser bound. Our bounds are useful in settings where only weak (i.e. non-negligible) indistinguishability is guaranteed. We demonstrate this in the context of cryptography, showing that our bounds, coupled with the XOR Lemma, yield straightforward computational generalization to the analysis for information-theoretic amplification of weak oblivious transfer protocols.
Doublespeak in the Language of Advertisement

The primary function of language is communication, which advertisers make abundant use of in order to attract consumers to their products, by way of using the power of words. One of which is the use of doublespeak. Advertisement use doublespeak to promote, attract and persuade people to buy their products. This is a form of deception as doublespeak is a language that makes the bad seem good, the negative appear positive and the unpleasant appear attractive. Advertisements from the Nigerian daily newspapers such as Leadership, Punch, Guardian and Daily Trust were used as data for the analysis of the data used for the purpose of this paper. Rhetorical theory is the theoretical framework adopted for this paper. Persuasion which is at the heart of rhetoric’s is employed by advertisers to appeal to the emotions of consumers. This is achieved using persuasive language. Fifteen adverts have been analyzed in order to establish the use of doublespeak in advertisement. The findings of the analysis reveal that most of the advertising captions contain doublespeak as well as ambiguity and the weasel claim. Readers of the advertisement are left to figure the meaning out for themselves.
Youth Trust in Social Media Companies and Expectations of Justice: Accountability and Repair after Online Harassment

Social media platforms aspire to deliver fair resolutions after online harassment. Platforms rely on sanctions like removing content or banning users but these punitive responses provide little opportunity for justice or reparation for targets of harassment. This may be especially important for youth, who experience pervasive harassment which can have uniquely harmful effects on their wellbeing. We conducted a text-message based survey with 832 U.S. adolescents and young adults, ages 14-24, to explore their attitudes towards social media companies’ responses to online harassment. We find that youth are twice as likely (41% versus 20%) not to trust social media companies’ ability to achieve a fair resolution as they are to trust them. Nearly two-thirds (62%) of youth expressed a preference for an apology from the offender after online harassment, and they were twice as likely to prefer a private apology to a public one (29% versus 14%). Preferences also vary by identity, revealing how a one-size-fits-all approach can harm some youth while benefitting others. We reflect on the opportunities and risks associated with institutional trust and restorative justice for supporting youth who experience online harassment
Pengembangan LKPD Berbasis Model Kooperatif Think Pair-Share Untuk Meningkatkan Aktivitas Belajar

The purpose of this research is to make LKPD based on TPS cooperative model in order to increase student mathematics learning activities. This study applies the plomp development model with data collection techniques in the form of observation guides, questionnaires, and tests. The subjects are students in class IX from MAN 1 Makassar. From the development activities, the results stated that was made could increase the learning activities of students which were strengthened by the fulfillment of 5 points from 6 predetermined ideal criteria, and the fulfillment of points 3-6 which were the essence of learning. This LKPD has also fulfilled the validity, practicality, and effectiveness of a product made, namely the acquisition of the validity category is very valid, the practicality category is positive, and the effectiveness category is very positive.
Features of the Use of Distance Learning Technologies in Education

Distance learning is actively spreading all over the world. This form of conducting classes incorporates computer and Internet learning technologies, connects the teacher and the student. You can study remotely, practically, in any course. Although, as you know, distance learning has emerged as a condition for teaching exact and technical disciplines. Distance learning is optimally suited for the development of professionally and informationally significant competencies, personal development, the formation of system thinking, the organization of independent work of students.
Increasing Students' Learning Motivation Through e-Student Worksheet

During the Covid-19 pandemic, it is mandatory for every education unit to implement the PJJ system. This causes various problems, including a decrease in students' learning motivation. This study aims to determine the application of e-Student Worksheet Live Worksheet in learning to increase learning motivation in Grade II elementary school students. The approach used is a qualitative approach. The type of research used in this research is Classroom Action Research (CAR). The subjects used in this study were educators and class II students at Kraton Elementary School , Kediri Regency. The data collected in this study is the data of the thematic learning implementation process using the e-Student Worksheet Live Worksheet. The results showed that the use of e-Student Worksheet Live worksheet can increase teacher activities and student activities in learning activities and can increase students' learning motivation. For teachers, teachers should make variations in learning activities. One of them is by applying learning media in the form of e-Student Worksheet Live worksheet so that students do not get bored following learning activities and can be actively involved in learning activities.
Estimating Human Mass Gathering on a Particular Time and Space Estimation by using Machine Learning

With the expanding populace, evaluating swarm thickness is a typical issue for swarm observation in Computer Vision. This issue stays a difficult assignment because of various varieties in scale issues created by various blocked uproars, changing shapes, and point of view variety. To handles these difficulties and to give a decent condition of precision we, in this way, center to gather a tremendous measure of datasets with shifting thickness levels and manufacture an Allied-CNN model. The assortment of the datasets is done from different sources like YouTube and some genuine recordings. The Allied-CNN model is worked in python and prepared on a named dataset of thousand item pictures from different points of view, for deciding thickness levels (as low thickness, medium thickness, and high thickness). Preparing results for thickness estimation show the preparation set precision arrives at 94.8%, the greatest approval exactness of just 88% is accomplished. Along these lines, this model aids in ordering a picture as low thickness, medium thickness, and high thickness. Estimations on this group datasets show that the proposed Allied-CNN performs modest outcomes contrasted with the cutting-edge strategies.
Large Scale Conditional Multitask Learning for Natural Language Processing

RESUME: Recemment, les “Masked Language Models” (MLMs) entraines sur une large base de donneesnon etiquetees ont genere des resultats de pointe pour plusieurs tâches dans le domaine du Traitement de Langage Naturel (NLP). Un grand nombre des soumissions les mieux classees au benchmark “General Language Understanding Evaluation” (GLUE) utilisent un modele base sur l’architecture “Bidirectional Encoder Representations from Transformers” (BERT).La formule “BERT + “fine tuning” par tâche individuelle” demeure prevalente dans la recherche ; cet outil permet en effet a plusieurs chercheurs d’aboutir a des resultats de pointe.Cependant, la methode du “fine-tuning” manque d’efficacite quant a la quantite de parametres utilises, puisqu’il est probable qu’elle requiere un nouveau modele pour chaque tâche.De plus, cette methode est susceptible d’entrainer la perte des connaissances acquises durant l’etape riche en donnees du pre-entrainement, ce qui pourrait affecter la performance de generalisation du modele. L’Apprentissage Multi-Tâche (MTL) est une approche efficace par transfert inductif inspiree par les modes d’apprentissage de l’humain qui s’avere prometteuse dans le domaine du Traitement de Langage Naturel. Pourtant, le MTL n’atteint pas le meme niveau de performance que l’approche du “fine-tuning” qui est encore appliquee apres l’etape de l’Apprentissage Multi-Tâche dans plusieurs etudes. Ce manque de performance est du aux difficultes additionnelles telles que le transfert negatif, le sur-apprentissage de tâches pauvresen donnees et la perte de connaissances. ----------ABSTRACT: Recently, deep contextualized Masked Language Models (MLMs) trained on massive amount of unlabeled data pushed state-of-the-art (SOTA) results in many Natural Language Processing (NLP) tasks. Many leading submissions on the well-known General Language Understanding Evaluation (GLUE) benchmark are based on the Bidirectional Encoder Representations from Transformers (BERT) architecture. The formula BERT + single task continues to stay popular in many recent studies, constantly pushing SOTA results. However, fine-tuning is parameter inefficient since it may require a new model for each task. Moreover, it might overwrite the knowledge acquired during the data extensive pretraining, potentially hurting the generalization performance. Inspired by human ability to apply knowledge across tasks, multitask learning (MTL) is a powerful inductive transfer learning approach that showed promising in many NLP tasks. However, MTL alone doesn’t reach the performance of fine-tuning approach and many studies still apply fine-tuning after the MTL step. This lack of performance is attributed to the additional challenges like negative transfer, overfitting of low resource tasks and catastrophic forgetting.
Side-Impact Collisions involving Passenger Vehicles in Real-World Crashes

&#x0D; &#x0D; &#x0D; In Malaysia, 6,570 fatalities were recorded as a result of road deaths in 2016. From that figure, 1,197 or 18.2% were involved in side- impact collisions. An in-depth crash investigation study was conducted by utilizing data from the MIROS crash investigation database (MICARS) to better understand the mechanism and characteristics of the crash and to correlate the impact and damages profile with the injury outcome of the involved occupants related to the side-impact crash. The data obtained from MICARS for this study was selected from 2007 until 2016, during which MIROS had investigated 794 for both East and West Malaysia. Out of that number, 41 cases involving passenger vehicles were selected for analysis purposes. The results found that the risk of serious or fatal injury to nearside occupants was eight times higher compared to the far-side occupants. Besides that, the use of the restraint system does not show a significant association with the occupants' fatality. In a conclusion, car manufacturers should equip all new passenger vehicle models with passive safety features such as side and curtain airbags and should also increase the rigidity of the side structure of the said vehicles to reduce the injury severity level of the occupants. Furthermore, the government needs to review all these issues together with the vehicle manufacturers to make it become a Malaysian Standard before mandating it for all passenger vehicles in Malaysia. Thus, continuous efforts and commitment by car manufacturers and the government are essential to produce safer cars with proper and adequate active and passive safety features.&#x0D; &#x0D; &#x0D;
Awareness of Competences and Teacher Education Plan that Special Education Experts should have to Prepare for the Era of Intelligent Information Revolution

The purpose of this study is to bring awareness towards the capabilities of future societies; that special education experts will need to prepare a plan to accommodate for potential technological enhancements, as the era of intelligent information approaches. A total of eight special teachers; as well as general teachers, professors, and big data experts; were conducted through numerous 1:1 in-depth interviews in order to analyze the results. The results were largely divided into servant-leadership competency, as well as future-oriented job competency; this is due to the high-level competencies that special teachers must acquire in the era of the Intelligent Information Revolution. In the servant-leadership competency, the competency between facilitators will assist in learning. The competency of both flexible thinking and communication linking are based on specialized knowledge. The ability to execute data-based decision making and individualized education were derived as sub competencies. In the future-oriented job competency, data processing, and interpretation competency; the ability to understand and use advanced technology, affect sensibility, and human dignity detection capabilities were derived. These results add up to a total of six basic competencies and two advanced competencies. Based on these results, a three-step plan was proposed in order to enhance the capabilities that will be required for special education experts in the future. Because of this, contents that are necessary for future research were discussed.
LibGuides: Cataloging Work Group: Resources

LSP Cataloging Work Group Main Lib Guide- information on events, documentation, and resources
A Lidar Unit

In this chapter, we’ll examine another device I used in my autonomous rover – a Lidar Unit that supports localization and navigation. Appendix A2 describes the simple custom-built Lidar Unit built around a USB-connected Arduino. The Lidar Unit is a real-life example of off-loading tasks from the Raspberry Pi to an Arduino, in particular to leverage the microcontroller’s “near-real-time” nature.
Visual Analytics System for Evaluating IVF Data Predicting Live Birth

Research into the impact of In Vitro Fertilization (IVF) enables customer systems is still in its infancy. Little is known about effective designs and visual analytics by applying the concept of machine learning, how people use these systems in their real-life settings and how the patient can virtually analyses the records by viewing the essential attributes used for building the project. A method is built to represent a tool to support decision making for patient analysis with fertility problems. To design and future development by assessing how patients undergo in vitro fertilization (IVF) using a visual analytics system in their real life setting and how it could be used for data visualization of patients records with the help of machine learning concept and some of the python libraries for plotting. The concept of IVF can be extended to find out excellent co-relations between the attributes used in the dataset and visually displaying the musing the concept of data visualization. An in depth formative evaluation of the essential attributes which are necessary for the IVF treatment is achieved by data visualization. It helps people know the significance of data by summarizing and presenting a large amount of data in an easy and self-explanatory format and helps communicate information clearly and effectively. In this paper, we will make use of data visualization for the IVF dataset to find out a variety of relationships between the attributes and present them in graphical format which is easy to understand.
Research Guides: Using Primo: The Library Discovery Search Tool: How to Search Everything

Learn how to use the features of Primo, including how to SEARCH EVERYTHING - books, e-books, journal or newspaper articles, how to borrow print materials from the UFindNJ network of academic libraries, and how to access and manage your library account.
Thai Tokenization with Attention Mechanism

Word segmentation is an important preprocessing step in natural language processing applications, particularly in languages with no demarcation indicators including Thai. A simple method like dictionary-based segmentation does not consider the context of the sentence. This paper proposes an attention-based deep learning approach for Thai word segmentation. With the help of attention, the model can learn character correlations across the entire sentence without gradient vanishing or gradient explode problems and tokenize them into word vectors. The goal of this research is to test three different types of attention mechanisms to determine the effectiveness of word tokenization. The visualization of attention for each attention mechanism is also included as an outcome.
Education, capability and skills

This chapter extends the topic of learning more broadly than in previous chapters, focusing initially on the implications of digitalisation for both the content and delivery of education Such functions extend in the digital society to the specific knowledge and skills needed to operate effectively within every part of it, i.e. mastery of the ‘Internet of Everything’. Because of the speed of technological transformation attention is drawn to the challenges digitalisation presents to management of education and the taught curriculum. The chapter also considers the distinctive contributions informal and formal education make to generic skills and lifelong learning, the central aim of which is building in a changing world, capabilities that match economic and life course needs. Amartya Sen’s unifying ideas about freedom to achieve also have a central role.
Semantic Reasoning with Differentiable Graph Transformations.

This paper introduces a differentiable semantic reasoner, where rules are presented as a relevant set of graph transformations. These rules can be written manually or inferred by a set of facts and goals presented as a training set. While the internal representation uses embeddings in a latent space, each rule can be expressed as a set of predicates conforming to a subset of Description Logic.
SOCIAL MEDIA TOOLS AND LIBRARY SERVICES IN UNIVERSITIES IN NIGERIA

The research work was on social media tools and library services in universities in Nigeria. A descriptive survey research design was used for the study. The population of the study was 23 librarians working in the university of Uyo library. A checklist and structured questionnaire were used for collection of data for this study. The instruments were subjected to face validation and were also subjected to pilot test using Cronbach Alpha which gave a reliability coefficient value of 0.92. Data collected from the study were analyzed using mean scores. The study found that online information services, e-mail services, current awareness services, and internet services were the available library services in university of Uyo. Also, the available social media tools for library services in university of Uyo are Facebook, Whatsapp, Twitter, Instagram, and Library thing. Moreso, the extent of utilization of social media tools for library services in university of Uyo was high on Facebook, Whatsapp, Twitter, Instagram, blogs, Instant Messaging (IM), and Rich Site Summary (RSS). Similarly, the challenges faced by librarians in utilizing social media tools for library services in university of Uyo are inadequate funding to procure social media tools for library services , insufficiency of ICT infrastructure , erratic power supply, poor maintenance culture on social media tools, and poor support of administrators towards the adoption of social media tools for library services. Furthermore, the solution to the problems affecting librarians in using social media tools for library services in university of Uyo are adequate funding to procure social media tools for library services, sufficiency of ICT infrastructure, good power supply, routine maintenance culture on social media tools, and subsidized cost of data to use social media tools. The study concluded that social media tools have been so helpful and have served as a reliable platform for university libraries to provide library services to her users. The study recommended that there should be availability of e-learning resources like e-content, e-library, and dedicated e-learning portal to speed up the utilization of social media tools for library services
Teaching Critical Reading Through Online

The literacy ability of Indonesian children is lower than children in other countries. In addition, students' vocabulary mastery is low. Even though the teacher had given vocabulary instruction to the students during the reading comprehension class, they still translated the text word by word into Indonesian. This study analyzes the effect of online learning on the acquisition of critical reading among students. This study used a pre-experimental study without a control group. Tests for the validity and reliability of reading comprehension texts and vocabulary tests were conducted before the test involving 40 participants. The technique used to collect data is a test. Validity and reliability were measured using some of the same texts used as pre-test and post-test. The pre-test and post-test scores were analyzed by Wilcoxon statistical analysis to test their reading scores before and after the intervention on the same subjects. The findings from the t-test revealed that the critical reading intervention was beneficial for students. Further studies showed that the instructional intervention adopted could help them improve their reading comprehension performance. These findings are expected to provide a teaching model that responds to the typical rise of today's online learning.