Reviewerly/exHarmony huggingface dataset:
DETECTION OF ILLICIT MESSAGES IN TWITTER USING SUPPORT VECTOR MACHINE AND VGG16

Human trafficking is a serious issue all around the world. Millions of men, women, and children are drawn into illicit activities and become victims as a result. People smuggling is prevalent in many nations, particularly among children and teens under the age of 14. Social media platforms serve as hurdles to the proliferation of these crimes through the internet environment, where subtle messages urge the use of unlawful services. It is critical to automatically detect these communications in real time. These aid government officials in preventing social networking crimes. Machine Learning and Deep Learning Algorithms are used to detect, preprocess, and classify suspicious tweets based on gender and age group, as well as photos from the tweets.Convolution Neural Networks (CNN) is used in the current techniques for detecting unauthorized tweets and photos. Although the CNN algorithms is effective at identifying human photographs, they are unable to locate all real-time tweets. When compared to VGG16, the picture information used is not considered adequately. To identify unlawful messages, CNN is utilized, although with lower accuracy rates.The suggested approach extracts images of people and hashtags or language relevant to minors (under 14 years) in real time and preprocesses it to remove misspelt and noisy data, after which the tweets are classed as suspicious or not. Support Vector Machine (SVM) and VGG16 are used to classify the gender and age of the photos in the tweets. Machine Learning and Deep Learning Algorithms such as SVM and VGG16 are used to identify, preprocess, classify, and determine the accuracy of these text and image tweets in order to remove misspelt and noisy data.
Rancang Bangun Dashboard Informasi Covid-19 Dengan Metode RAD

In 2019, a type of virus that is now known as COVID-19 (coronavirus diseases-19) was discovered. The virus found in Wuhan, China is a contagious virus that has claimed many lives. In Indonesia alone, cases of the COVID-19 virus (coronavirus diseases-19) were first confirmed in March 2020. The World Health Organization has determined that the COVID-19 virus (coronavirus diseases-19) is a pandemic on March 9, 2020. This has caused many people who are worried if they want to do activities outside the home. So a system is needed regarding the development of Covid-19, especially in Indonesia, to provide information and knowledge to the public so that it is hoped that it can prevent the transmission of the COVID-19 virus. Based on this background, the author will build an information dashboard that can be accessed by the public anywhere and anytime to see the development of Covid-19. By using the RAD (Rapid Application Development) method, it is hoped that later the system can be quickly built and used. In coding the program the author uses PHP as server-side with API integration from kawalcorona and HTML, CSS, Javascript as client-side. It is hoped that the system created will be used by the public as a reliable and accurate covid-19 information.
Design Of Automation Institutional Repository Library System Of Web-Based National University Using Open Source "Senayan 9: Bulian: Design Of Automation Institutional Repository Library System Of Web-Based National University Using Open Source "Senayan 9: Bulian

The rapid technological development in the Digital Age spurred every organization to participate in implementing it in order to facilitate work and improve services. The library as a repository of professional institutions also participated in implementing the automation system. The National University as a professional institution also needs to develop an automation system that applies Free Open Source Software (FOSS) technology. The Senayan Library Management System (SLiMS) application that utilizes WEB-based on FOSS can be implemented as a repository  automation system. Compared to other library automation systems, SLiMS 9: Bulian has many advantages. In addition, SLiMS has a large community network in almost every city in Indonesia and even abroad.
PENGARUH PENDEKATAN PEMBELAJARAN KONTEKSTUAL BERBANTUAN MEDIA VISUAL TERHADAP PENINGKATAN MOTIVASI BERPRESTASI DAN HASIL BELAJAR IPA PADA SISWA

This study aims to determine the magnitude of the influence of the contextual learning model assisted by visual media to increase achievement motivation and science learning outcomes in students. This research is a quasi-experimental research with the design of The Posttest-Only Control-Group Design. The study population was all fourth grade elementary school students in Cluster II Abang District, Karangasem Regency in the 2019/2020 school year. Based on the characteristics of the population and individual randomization cannot be done, the sampling in this study was the group random sampling technique. Student achievement motivation data were collected using a questionnaire and science learning outcomes using multiple choice tests. Data were analyzed using MANOVA (Multivariate Analysis of Variance) assisted by SPSS 17.00 for windows. The results showed that: First, there is a significant difference in achievement motivation between students who learn with contextual learning assisted by visual media and students who learn using conventional learning models in class IV SD students in Cluster II Abang District. Second, there are significant differences in science learning outcomes between students who learn with contextual learning assisted by visual media and students who learn with conventional learning models in grade IV SD students in Cluster II Abang District. Third, simultaneously there is a significant difference in achievement motivation and science learning outcomes between students who learn with contextual learning assisted by visual media and students who learn using conventional learning models in grade IV SD students in Cluster II Abang District.
Εφαρμογή για την αναγνώριση αντικειμένων σε κινητές συσκευές με χρήση μηχανικής μάθησης

With the development of technology and the great spread of mobile devices, a large part of thepopulation has come into contact with a number of new technologies, which in the past were only availablethrough the use of specialized devices, or were not available at all. One technology that has become readilyavailable with the development of mobile devices is computer vision.In this thesis we will present the development of an educational software for mobile devices usingthe Android operating system, which will help users to identify objects through a photo, mark them on itand list below the three best answers with an indication of the percentage of certainty per item. This softwareis considered educational because it can be used as an aid but also as a tool by users to identify objects intheir space. In addition, it can help identify electronic items from people who do not have the appropriateknowledge.To achieve the goal of this thesis, the application was written using Kotlin as the programminglanguage. Also, for the training of the custom models of machine learning, Google’s AutoML technologieswere used, and for object detection and for image labeling, Google’s ML Kit tools were utilized.For the training of machine learning models, the CIFAR – 100 was used, and also a dataset featuringelectronics, and a dataset containing five different types of flowers.While using the application, it was found that the objects in the tested images were identified by amajority. In the first machine learning model, with the usual objects, it was observed that if the objectbelongs to some of the categories contained in the model, then the correct answer appears in the first threepredictions. In the second model of machine learning, with electronic items, the most erroneous predictionswere observed mainly due to the limited detection of objects. In the latest model of machine learning, withflowers, 100% success of object recognition was observed due to the small number of categories.
Try on this eyewear virtually through Warby Parker

Warby Parker continues to put the customer first, now offering an augmented reality feature to virtually try on glasses.
Mitigation of Poetry Text into Emotional States Based on Twitter Real-time Dataset using Convolution Neural Network

There are a lot of obstacles to progress in continuing to use social media poetry resources for evaluating consumer groups, but don't give up. A central role in human behaviour is played by feelings, there are also opportunities to observe emotions by text analysis in messages from social media for helping to identify psychiatric problems or observing the general public sentiment in a group. classification methods that relied on a lexicon and a pack of vocabulary used in previous studies The current study carried out using deep learning methods on the impact of hashtags found in Twitter has, although it does not allow for other potential hashtags that may not have existed during the time span the analysis was done. The algorithm aims to enhance the detection of emotions on real-time streaming financial data that's fetched from Twitter. the overarching goal is to correctly identifying all of this is to allow for proper understanding of the different emotions that a specific tweet conveys.
Selection of Hardware and Software for Library Automation

Libraries play a vital role in the educational, industrial, and technological progress of a country. The progress of the nation depends upon advanced knowledge gained by educationists, technologists, engineers, and scientists of the country. Hence the role of libraries in Universities and then educational institutions is to activate a free flow of information from the point of generation to the point of the utilization of information efficiently and effectively. Information Technology has changed the role of the libraries in acquire, maintain, and distribute the information to the users. Library Automation itself is an application of computers in libraries to maintain inhouse operations such as acquisition, cataloguing serials control, and circulation. Effective library automation depends on the selection of hardware, software & proper training to the library staff.
Asymmetric Influence in AI-Augmented Systems: Evidence From the Initial Coin Offering Market

The growing consensus that human intelligence and artificial intelligence (AI) are complementary has led to the emergence of AI-augmented systems. In this paper, we investigate whether AI agents influence human decisions in the high-risk environments of initial coin offering (ICO) where most ICO fail. Using panel data from a leading ICO evaluation platform that uses AI to augment human experts, we examine how humans integrate the assessments of AI agents into their assessments when real outcomes are at stake. Our results show that AI agents exert an asymmetric influence on human decisions. When the AI agent rates an ICO low, the decisions of human experts follow it. When the AI agent rates an ICO high, the decisions of human experts deviate from it. Thus, we conclude that human experts use the AI agent’s low score to screen out ICOs and use the agent’s high score as a trigger to investigate an ICO more deeply and come to their own conclusions about its potential. The same human experts that were influenced by low AI ratings were not influenced by other human experts.
A Scrutiny Of Blockchain Technology And Its Utilization

In The Bounteous Technological Development World, The Blockchain Is ARadical Emerging Technology Which Is The Root Of The Most Materializing Cryp-Tocurrencies Such As Bitcoin, Litecoin And Abounding Cryptocurrencies. Ethereum Is ABlockchain Based Distributed Computing Platform Which Uses Smart Contracts For TheTransaction Of Bitcoins. Smart Contracts Allow The People To Perform The TransactionsOf The Bitcoins Without Any Third-Party Hindrance. Such Transactions Are IrreparableTransactions. The Ethereum Platform Is An Open Source Platform Which Produces TheDecentralized Virtual Machine Called EVM (Ethereum Virtual Machine). This Research IsMeant To Give An Overview On The Development Of The Application Using The SmartContract In Blockchain Ethereum Technology.
Developing REST Integrations

In the last chapter, you were introduced to Apache Camel and Quarkus, you got started on the system integration discussion, and you learned a little bit about the evolution of the technologies approached by this book. This basic knowledge is extremely important to allow you to dive deeper into more specific conversations. Now, I’ll discuss synchronous communication using REST.
Elon Musk boasts 'diamond hands' as bitcoin implodes

As Bitcoin and other cryptocurrencies take a beat down, Elon Musk sends a message to his haters.
DEVELOPING STUDENTS’ POSITIVE BEHAVIOUR THROUGH THE IMPLEMENTATION OF POSITIVE REINFORCEMENT IN EFL CLASS

This paper is aimed at explaining why the use of positive reinforcement in EFL class could promote and develop the students’ positive behavior. This paper is a library research in which the data were collected by analyzing articles, papers and journals. Positive reinforcement can be used in the teaching and learning processes to make the students behave appropriately in the class. The use of positive reinforcement in the classroom is important because a student who experiences positive reinforcement often shows a better willingness to demonstrate positive behavior. The discussion covers the reasons why using positive reinforcement is important, how it can manage the students’ behavior, the implementation, the anticipated impact, and the way to overcome it. Keywords: Positive reinforcement, positive behavior, EFL class
Pesquisa Arquivística uma análise dos Planos de Atividade Complementar do curso de Arquivologia da Universidade de Brasília (2007-2019)

This article aims to identify and analyze the research developed in the Archival Science Programat University of Brasília, inthe form of the Plano de Atividade Complementar(PAC). Through investigations that contribute to the expansion of archival knowledge and enable the generation of new discoveries, PAC has in its composition a faculty advisor and Archival Science undergraduate students. As a methodology, a quali-quantitative analysis of this production was proposed, adopting, as a theoretical reference, the classification defined by Couture and Lajeunesse (2014) for archival research. The results indicate a low rate of students enrolled in research of this nature and present three themes with greater incidence. Some investigations have won awards at scientific events and others have been published in national and foreign journals.
Knowledge of L2 Grammar

In response to a request to comment on the essence of L2 grammar, the vast majority of individuals would in all likelihood simply start talking about the knowledge of rules, the ability to explain them and the capacity to use them correctly, presumably in controlled exercises (e.g., putting the verbs in brackets in the right form or paraphrasing) or on different kinds of tests.
THE REALIZATION OF CODE MIXING AND CODE SWITCHING OF INDONESIAN CELEBRITIES' CAPTION ON INSTAGRAM

Code mixing and code switching are sociolinguistics phenomenon that occur in a communication process and become trend of language style for Indonesian. Therefore, this research focuses on the realization of code mixing and code switching that emerges on Indonesia celebrities’ caption on Instagram. This research aims to find out analysis of code mixing and code switching realized by Indonesian celebrities on Instagram. Specifically, this research investigated kinds of code mixing and code switching, and the dominant kinds of code mixing and code switching realized by Indonesian celebrities on Instagram. To analyze the data, the researchers transcribed celebrities’ caption on Instagram that contain code mixing and code switching. This research was descriptive qualitative method and collecting the data by utilizing documentation method. This research employed content analysis that focused on analyzing the kinds of code mixing and code switching. The result after analyzing the data, there were 18 code switching and 13 code mixing. The Indonesian celebrities dominantly used external code switching and insertion code mixing on their caption in Instagram. Keywords: Code mixing, code switching, kinds of code mixing, kinds of code switching
Teacher-student Collaborative Assessment (TSCA) in English Writing Teaching

NOTICE OF RETRACTION: While investigating potential publication-related misconduct in connection with the ICIMTech 2021 Conference Proceedings, serious concerns were raised that cast doubt on the integrity of the peer-review process and all papers published in the Proceedings of this Conference. The integrity of the entire Conference has been called into question. As a result, of its investigation, ACM has decided to retract the Entire Conference Proceedings and all related papers from the ACM Digital Library.
Contributos para o perfil das gestoras e curadoras de informação em Portugal

This article provides the results of the Google generation information behaviour’s study. Through the analysis ofinformation behaviour modelsdeveloped by Information Management and Curation M.A. students, from NOVA University, it was possible to give inputs to the profile of this new profissional. These models proved to be determinant to infer the competences and skills of the students and, combined with literature review, take us to the conclusion that these new information professionals have hybrid profiles with transversal and interdisciplinary competences, namely, the capability to adapt to the uncertainity resulting by the steady technological evolution and information massive production.
TEAM GAME TOURNAMENT (TGT) COOPERATIVE MODEL EFFECT TO SENIOH HIGH SCHOOL STUDENT’S MOTIVATION

This research is an experimental research which aims to see the influence of Teams Game Tournament (TGT) learning model on the motivation of students on immune system material at SMA Pembangunan Laboratorium UNP academic year 2018/2019. The implementation of this study does not allow researchers to control variables as a whole so that this study belongs to the quasi-experimental category with the design of control group posttest only design. Sampling in this study used saturation sampling technique. The technique of data analysis used statistical tests, namely the t test. The results of statistical tests showed that in a significant term (α = 0.05) the value of tcount&gt; t tableis obtained, which is 3.28 &gt; 1.67, then H0 is rejected and H1 is accepted. It can be concluded that the motivation of students using the Teams Game Tournament (TGT) learning model is higher than the motivation of students who use conventional learning. It can be interpreted that there is an influence of the Teams Game Tournament (TGT) learning model on the motivation of students on immune system material at SMA Pembangunan Laboratorium UNP.
Inverse Transform Sampling Using Ray Tracing Hardware

Accurate radiance estimates of high dynamic range textures require importance sampling to direct rays toward influential regions. However, traditional inverse transform sampling involves several expensive searches to locate these highly influential pixels. We propose a reformulation of inverse transform sampling that replaces these texture space searches with a single hardware-accelerated ray traversal search using cumulative probability geometry. We evaluate the performance and scalability of our approach on a set of emissive dome light textures and demonstrate significant improvements over traditional solutions.
Covid Pandemic-19 Guide Students to New Normal Era

The World Health Organization stated that the Covid 19 problem is an emergency public health problem of international concern. This condition changes all human activities. Likewise with student activities. In the world the new normal lecture activities can be done in various ways, including; Lectures from face to face in class, long distance education in a network (online) with an online system. Normality during and after Pandemic Covid-19 4 (Four) Society Megashifts, namely stay at home, go virtual, empathic society, and bottom of the pyramid.
A Scaling Law for Synthetic-to-Real Transfer: A Measure of Pre-Training.

Synthetic-to-real transfer learning is a framework in which we pre-train models with synthetically generated images and ground-truth annotations for real tasks. Although synthetic images overcome the data scarcity issue, it remains unclear how the fine-tuning performance scales with pre-trained models, especially in terms of pre-training data size. In this study, we collect a number of empirical observations and uncover the secret. Through experiments, we observe a simple and general scaling law that consistently describes learning curves in various tasks, models, and complexities of synthesized pre-training data. Further, we develop a theory of transfer learning for a simplified scenario and confirm that the derived generalization bound is consistent with our empirical findings.
Side-channel information leakage analysis and countermeasures in an embedded CPU microarchitecture

Side-channel attacks (SCAs) have become a significant threat nowadays to cryptographic devices, especially central processing units (CPUs). Based on the implementation of AES-128, the side-channel information leakage analysis is carried out in a 32-bit CPU microarchitecture in this work. Correlation power analysis (CPA) results show that it is obvious to reveal the secret key by using only 30 power traces based on the net-list simulation. Three flexibly configurable hardware-based countermeasures are proposed to prevent information leakage in the arithmetic and logic unit (ALU), register file (RF) and load/store unit (LSU), respectively, which are the most sensitive components according to our analysis. The proposed countermeasures have different protection effects on the CPU since the required trace number to reveal the secret key has increased from 30 to 100∼120,000. Moreover, the anti-attack capability of the CPU is improved by 4000 times using the three countermeasures simultaneously. The proposed countermeasures can be freely combined while considering the CPU security and implementation overhead. In practice, the anti-attack capability of the CPU can be further improved when the proposed countermeasures are implemented in real-world measurements, because additional noise will be introduced during the measurements.
Learning Image Segmentation from Few Annotations

How to build machine learning models from few annotations is an open research question. This article shows an application of a meta-learning algorithm (REPTILE) to solve the problem of object segmentation. We evaluate how using REPTILE during a pre-training phase accelerates the learning process without loosing performance of the resulting segmentation in poor labeling conditions, and compare these results against training the detectors using basic transfer learning. Two scenarios are tested: (i) how segmentation performance evolves through training epochs with a fixed amount of labels and (ii) how segmentation performance improves with an increasing amount of labels after a fixed amount of epochs. The results suggest that REPTILE is useful making learning faster in both cases.