Reviewerly/exHarmony huggingface dataset:
Digital Transformation of Educational Services in COVID-19 Pandemia: Social and Technological Aspects

This article focuses on the socio-technological aspects of the digital transformation of education as the most critical and relevant subject in the context of a pandemic COVID-19. The purpose of this study is to identify the problems of digital transformation of educational services and the factors that determine its prospects based on an analysis of the technological and social aspects of digital education during the emergency transition of the higher education system to distance and online education in the context of the COVID-19 pandemic. The methodological basis of the study was the theory of marketing, information technology, educational sciences, sociology, as well as desk and field marketing research of the behavior of international and Russian digital consumers of educational services. The main findings of the study were: presentation of the author's definition of the category “digital consumer” and updating the definition of “consumer behavior” in the context of digital consumption; systematization of digital resources for online learning, based on the involvement of universities in the academic and research multi-gigabit Internet network; setting the global social and technological problems based on the “digital divide” (digital gap), insufficient security and protection of personal data of students and teachers, and the social well-being of digital consumers; the features of the behavior of the digital consumer of educational services were revealed; the socio-technological factors influencing the prospects for the digital transformation of educational services have been identified.
Vehicle document verificati on using qrcode

Now a days Vehicle document verification is mand at oryinevery where.People have to carry the Driving License,Insurance and RC book etc., at any time while driving. In this case there may be a chance to forget or missing or fakedocuments submission. This Web Application tries to rectify the difficulty of this situation by providing QR CODE. TheAuthenticated persons are using this application to verify the documents by using QR CODE SCANNER. It is an easy way toverify the documents of the vehicles using QR scanner. Driving License, Insurance and RC book details can be checked by the Authenticated persons like Trafficpolice.There is no need to carrya Hard copy of the documents.A QR code is attached with the number plate during registration. While scanning the QR code it gives the detailsabout the vehicle holder’s details such as Driving license, RC book. Mainly helps the traffic police to give the penalty for thosewho violates the traffic rules and can retrieve the previous data about that person. Overall documents are handled byauthorizedpersons only.
Library at UCC: Game Design and Development: Blogs

This guide is designed for students in the Game Design and Development A.A.S. (Associate in Applied Science) program.
Best Cluster Optimization with Combination of K-Means Algorithm And Elbow Method Towards Rice Production Status Determination

Indonesia is the third-largest country in the world with rice production reaching 83,037,000 and became the highest production in southeast Asia spread in several provinces in Indonesia The problem found that such product has not been able to cover the needs of Indonesian people with a very high population so that in the research conducted information excavation to generate potential to the pile of data that has been described and analyzed by BPS with clustering topics. Clustering will help related parties, especially the ministry of agriculture, in determining land development priorities and can minimize the shortage of rice production nationally. Grouping process by involving the K-means algorithm to group rice production with a combination of the elbow method as part of determining the number of clusters that will be recommended with attributes supporting the area of harvest, productivity, and production. Method of researching with data cleaning activities, data integration, data transformation, and application of K-means with a combination of elbow and pattern evaluation. The results achieved based on the work description with a combination of K-Means and elbow provide cluster recommendations that are the best choice or the most optimal is iteration 2 which is the lowest rice production group with a total of 22 provinces, rice production with a medium category of 9 and production with the highest category with 3 regions
The Effects of Work-family Conflict on Female Correctional Officials’ Turnover Intention : Mediating Effects of Job Satisfaction

This study analyzed the mediating effects of job satisfaction on the effects of work-family conflict on female correctional officials’ turnover intention using the process macro of Hayes(2013) in order to verify the effect. According to the results of analysis, female correctional officials’ work-family conflict had no direct effect on their turnover intention and it was identified that work-family conflict bypassed job satisfaction to affect the turnover intention. That is, job satisfaction completely mediated the relationship between work-family conflict and turnover intention. These findings suggested that an Employee Assistance Program should be in place to prevent the outflow of excellent human resources.
E-Health Registration System Using QR Code

E-Health UTHM is an application that was developed to enable students and staff to register for medical or dental services in the health centre by scanning QR code and getting a medical summary from a doctor. The manual process in UTHM Health Centre required staff and students to place their matric card in a box at the registration counter and wait for the medical staff to call them. Therefore, this is a manual process for every patient in the health centre and it is important to digitize the process of registration. Object oriented software development method is used in this project and this application is developed using Android Studio software and Firebase database. Overall, E-Health UTHM may enable patients to register for services by scanning QR code and viewing medical summary.
An Online Path Planning with Modified Autonomous Parallel Parking Controller for Collision Avoidance

In recent years,Nakrani, Naitik M. investigation of algorithms for autonomous vehicle design is one of the significant fields of research.Joshi, Maulin M. Autonomous parking is a challenging issue, especially where traffic density is high, and people have to opt for parallel parking than garage parking. The design of an autonomous parking controller generally does not take into consideration nearby obstacles presence while maneuvering. The addition of an online path planning module can significantly improve the usability of such a controller for real-time applications. In this paper, an angle correction module is introduced that improves the standalone parking controller using ultrasonic sensor information to generate optimized path planning and avoid collision. Simulations results show the efficacy of the proposed work and support the design of the angle correction module. This type of intelligent correction module will surely ease the parking problem in a dense area and make parking safer, being collision-free solutions.
Promises and Pitfalls: Taking a Closer Look at How Interactive Infographics Affect Learning From News

This study investigates how interactive infographics affect individuals’ understanding of news. We conducted a survey experiment ( N = 293) to isolate the effects of a clickable graph and a slider graph on memory of the interactive graphical content and the surrounding text-based content, respectively. Moreover, to shed light on the underlying mechanisms linking interactive infographics with individuals’ cognitive responses en route to learning, we test a model with interface assessment, absorption, and elaboration as key mediators of information acquisition. Overall, the findings point to a negative impact of interactive infographics on news consumers’ memory. However, allowing users to interact with information displayed in graphics cannot be expected to uniformly affect the learning process; instead, the impact of interactive visual content depends on how the use of specific interactive modalities initiates both affective and cognitive processes in audiences when reading online news.
Silver: Novel Rendering Engine for Data Hungry Computer Vision Models

Large-scale synthetic data is needed to support the deep learning big-bang that started in the recent decade and influenced almost all scientific fields. Most of the synthetic data generation solutions are task-specific or unscalable while the others are expensive, based on commercial games, or unreliable. In this work, a new rendering engine called Silver is presented in detail. Photo-realism, diversity, scalability, and full 3D virtual world generation at run-time are the key aspects of this work. The photo-realism was approached by utilizing the state-of-the-art High Definition Render Pipeline (HDRP) of the Unity game engine. In parallel, the Procedural Content Generation (PCG) concept was employed to create a full 3D virtual world at run-time, while the scalability of the system was attained by taking advantage of the modular approach followed as we built the system from scratch. Silver can be used to provide clean, unbiased, and large-scale training and testing data for various computer vision tasks.
LibGuides: How To Get Your True-Crime Fix Digitally: Interacting with your favorite True-Crime Blogs and Podcasts

Are you an amateur crime detective? Do you find yourself on Google late in the night searching for details about the latest true crime story? The search is over: here is the ultimate guide to getting your true-crime fix, whether through podcasts, videos, Here are some great blogs that cover everything from serial killers to a unsolved murder down the street.
Legislative Policy of the Republic Islamic of Iran on Cybercrime

With the advancement of technology and the use of computers in all economic, military, and social affairs, various crimes can occur in the field of computers; therefore, the legislature passed the Law on Cybercrime in 56 articles in 2009 to prevent and combat these crimes. And 25 noted that it is one of the most complete cybercrime and cybercrime laws; however, there is no definition of cybercrime in the E-commerce and Cybercrime law of the Islamic Republic of Iran, which is likely to be the reason Let the fundamental disagreements among jurists come from this concept. Generally speaking, those offenses that are committed by abusing a computer system are against the law, though these types of crimes can include traditional computer-based crimes - such as fraud and Theft - as well as emerging crimes that have come to life with the advent of computers - such as crimes against the accuracy and integrity of the data, he knew. In this research, the facts, legal, material and psychological elements as well as punishment of each cybercrime have been investigated.
How deep is your emotion? Emojis facial expressions on the emotional processing of text messages

Despite emojis are already an integral part of human communication, little is known about how their use may affect the emotional processing of the text messages sent in platforms such as WhatsApp or Twitter. Here, we aimed to analyze how the brief presentation (34 ms) of emojis congruent with the emotional content of sentences designed to represent the five basic emotions, and neutral situations, relative to their verbal equivalents or the absence of any stimulus as control, affects the processing of the emotional content of these sentences using an affective appraisal task combined with the masked priming paradigm. Results showed that, although the use of emojis did not appear to affect the level of arousal elicited by the sentences, they did impact the speed with which these responses were made, though only in sentences associated with the emotions of sadness and disgust. Specifically, in these sentences, the prior presentation of the emoji produced longer responses when compared to the control stimulus. These results suggest that the use of emojis does not seem to offer advantages in the emotional processing of written messages, at least at early stages of processing.
Deep Learning based Face Mask Detection for COVID-19 Safety

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To Overcome Limitations of Computer Vision Datasets

Author(s): Liu, Bo | Advisor(s): Vasconcelos, Nuno | Abstract: Large-scale datasets play a key role in the success of modern computer vision models. However, there are limitations of current datasets due to the data collection strategy. When an object has a canonical pose, pose bias is usually common. And models can only perform good on specific poses. We mitigate this by introducing two data augmentation methods, one in feature space with feature transfer, the other in image space with novel view synthesis. Both of them can improve the pose diversity of the current dataset. Imbalance class distribution is the nature of real world. To deal with this problem, we first discuss the few-shot open-set problem. By introducing meta-learning to open-set detection, PEELER rejects unseen samples with no cost of seen class accuracy. With a larger class label space, long-tailed recognition problem is then discussed. GistNet improve the long-tailed performance by geometry transfer, while Breadcrumb mitigates the over-fitting of few-shot samples by feature back-tracking. Last but not least, the task of semi-supervised long-tailed recognition is introduced. Alternate learning is presented to combine semi-supervised learning with long-tailed recognition. All of above mentioned methods are proved to be useful when facing certain limitations of computer vision datasets.
Research on Auxiliary Target Extraction and Recognition Technology in Big Data Environment

With the rapid development of global aviation industry, the flight volume is rising rapidly, and the aviation industry is also rapidly entering the era of big data. In this paper, the digital extraction of image information assisted target recognition technology is used to extract the route and waypoint information on the picture and make it into vector civil aviation route. Combined with the massive flight plan and target trajectory on the Internet, track feature matching is realized to assist users to quickly discover targets.
The reminders migration in iOS 13 took ...

The reminders migration in iOS 13 took a long time for me. But, everything appears to be there now and is syncing correctly.
LibGuides: Using EndNote: Creating a Bibliography

This guide will help you become familiar with the reference management software EndNote Web
Structured Data Extraction Using Machine Learning from Image of Unstructured Bills/Invoices

The identification and extraction of unstructured data have always been one of the most difficult challenges of computer vision. Parsing this sort of large data is very challenging; however, recent advancements in computer vision technology help make this feasible. A ubiquitous commonplace item that many consumers receive is difficult to be transformed into raw data. Receipts contain a dense amount of data that can be useful for future analysis, but there exists no widely available solution for transforming receipts into structured data. Existing solutions are either very costly or inaccurate. This paper introduces a data pipeline for the identification, cropping, and extraction of unstructured data within healthcare bills/invoice images. This pipeline outperforms existing solutions by a large margin, and offers the ability to automatically pull out semantic data such as description and unit price from an image of a bill. It achieves this success by using Logistic Regression, KNeighbours, and OpenCV Scikit to crop the image. Optical Character Recognition (OCR) is applied to detect chunks of text and process the image. The accuracy observed is approximately 93% for Logistic Regression and 81% for KNeighbours.
Optimization of a Shape Metric Based on Information Theory Applied to Segmentation Fusion and Evaluation in Multimodal MRI for DIPG Tumor Analysis

In medical imaging, the construction of a reference shape from a set of segmentation results from different algorithms or image modalities is an important issue when dealing with the evaluation of segmentation without knowing the gold standard or when an evaluation of the inter or intra expert variability is needed. It is also interesting to build this consensus shape to merge the results obtained for the same target object from automatic or semi-automatic segmentation methods. In this paper, to deal with both segmentation fusion and evaluation, we propose to define such a “mutual shape” as the optimum of a criterion using both the mutual information and the joint entropy of the segmentation methods. This energy criterion is justified using the similarities between quantities of information theory and area measures and is presented in a continuous variational framework. We investigate the applicability of our framework for the fusion and evaluation of segmentation methods in multimodal MR images of diffuse intrinsic pontine glioma (DIPG).
Research on comprehensive evaluation model of network security based on information entropy

In order to evaluate the network security effectively, this paper uses the accelerated genetic Algorithm's mold and analytic hierarchy process to select the index, constructs the computer network security evaluation index system, in this paper, an improved method of combining subjective and objective weights with AHP and information entropy is proposed to rank the importance of factors affecting network security, and then the evaluation model of network security is established by using fuzzy and comprehensive evaluation method, the model is applied to the evaluation of a network security status, and the results of 81.1 score and “security” level are obtained.
Tweet Fragmentation Technique: An Automatic Detection of Malicious Tweet on Social Networking

Immense volume of short messages that is tweets are being shared among various clients and information on long range informal communication locales and microblogging destinations, for example, Twitter, Facebook and so forth. Twitter gets more than 400 million tweets for every day. Constant examination is extremely troublesome and testing undertaking on such gigantic information likewise questioning and recovery of information is additionally troublesome. Such a huge number of tweets contain colossal measure of commotion and repetition. Existing frameworks were generally chipped away at the static and the constrained information. The different existing frameworks were proposed to address these issues and furthermore they gave some arrangement. Summarization is the way toward involving a content document in such way that short summary produced by using the essential keywords of the first document. There is need of dynamic way to deal with condense information delivered by Twitter feeds. This paper proposes the novel method, which produce the significant substance based summery inside less measure of time. We also propose to detect the malicious tweets for offline and online tweets. Especially, in the proposed framework multi-subject summarization is performed on the online dataset which thusly require the less measure of time when contrasted with the other existing framework. So time productivity is improved by using the proposed framework.
Deep Contextualized Self-training for Low Resource Dependency Parsing

Neural dependency parsing has proven very effective, achieving state-of-the-art results on numerous domains and languages. Unfortunately, it requires large amounts of labeled data, that is costly and laborious to create. In this paper we propose a self-training algorithm that alleviates this annotation bottleneck by training a parser on its own output. Our Deep Contextualized Selftraining (DCST) algorithm utilizes representation models trained on sequence labeling tasks that are derived from the parser’s output when applied to unlabeled data, and integrates these models with the base parserthrough a gating mechanism. We conduct experiments across multiple languages, both in low resource in-domain and in cross-domain setups, and demonstrate that DCST substantially outperforms traditional self-training as well as recent semi-supervised training methods.
The Correlation between Vocabulary Achievement and Reading Comprehension

The study investigated the correlation between students’ vocabulary mastery and their reading comprehension. Data were collected from 32 eighth grade students of SMPN 11 Palembang. The test item of vocabulary mastery and reading comprehension were given to the students to measure their level of vocabulary mastery and reading comprehension. The results were compared to find out the correlation between those variables. The result showed that there was a significant correlation between students’ vocabulary mastery and their reading comprehension. The technique of collecting data was by using a test. A try out test was also done to find out the validity. After the data of the students’ vocabulary mastery and their achievement in reading comprehension were collected, the data werestatistically computed to find out the correlation between the two variables. The result of applying the pearson correlation shows that the coefficient correlation is 0. 807. It means that there is a significant correlation between the vocabulary mastery and reading comprehension. It is suggested that to have a good mastery of reading comprehension, students should have a good mastery of vocabulary.
PENGARUH STRATEGI PEMBELAJARAN ROLE PLAYING TERHADAP HASIL BELAJAR EKONOMI PADA PESERTA DIDIK KELAS X IPS

The problem in research in MAN 1 Pesawaran is the low learning outcomes, learning that is still centered on the teacher, still lack of interaction between students in learning and the learning process using role playing learning strategies that have not been applied in MAN 1 Pesawaran. The purpose of this study is to determine the effect of role playing learning strategies on economic learning outcomes in class X students. Even semester MAN 1 Pesawaran school year 2018/2019. This study uses an experimental method using role playing learning strategies. The population in this study were students of class X. IPS totaling 110 students, the sample consisted of class X. IPS 1 as an experimental class of 36 people and X. IPS 2 as a control class of 36 people. Hypothesis testing uses the ttest statistical formula. Based on the testing of variance homogeneity both samples were obtained Fhit <Fdaf which is 1.46 <1.80 and the normality test data obtained from the experimental class X2hit = 3.48 and the control class X2hit = 2.76, where X2daf = 7.81 where the value of X2hit <X2hit. In testing hypotheses and calculating economic learning outcomes data using a statistical formula, it can be thit = 3.23 and ttab = 2.00 at a significant level of 5%. This means that there is the influence of role playing learning strategies on the results of economic learning in class X students. IPS even semester MAN 1 Pesawaran academic year 2018/2019.