Reviewerly/exHarmony huggingface dataset:
Facilitating Secure Web Browsing by Utilizing Supervised Filtration of Malicious URLs

Nowadays, Internet use by all people has become a daily matter, whether to do business, buy online, education, entertainment, or social communication. Therefore, attackers exploit users of the Internet by tricking them into clicking on a specific link to carry out a phishing attack on them to collect sensitive information for users, whether credentials, usernames, email passwords banks, electronic payment information via a phishing attack that targets the end user, so many methods have appeared for protection from this type of attack, and among these methods using algorithms of machine learning (ML) to distinguish between the proper URL from the malicious phishing using several types from algorithm classification based on certain features found in any URL and using a ready-made data set, the best types of algorithm best performance are determined. It is recommended to use them based on the accuracy of the algorithm. We applied different machine learning algorithms on the same data set as Decision Tree, Logistic Regression, Linear Discriminant, Gradient, and Random Forest. The best accuracy was for the RF algorithm, with 97%.
Python-Based Free and Open-Source Web Framework Implements Data Privacy in Cloud Computing

Data sharing turn into a remarkably striking service delivered by cloud computing architecture due to its suitability and reduced cost. As a probable practice for understanding finely secured distribution of data, using a technique called Attribute-Based Encryption (ABE) with a different variety of users. In real time, ABE technique has its own drawbacks like high computation overhead and less security in cloud data storage with fine-grained data files. Processing tasks could be transferred to remote computing resources utilizing cloud computing. Cyber insurance is a realistic way of passing on cyber security risks, but data security can or cannot be improved depending on the environment's key characteristics. This paper focused on one income insurer, client participants, and insured volunteers, focusing on two different cybersecurity aspects and their impact on the standard form of contracts. Since cyber security is linked, an entity's degree of security is determined not just by its own effort and effort but also by the efforts of others operating within the same system. As such, effective resource utilization could be performed, reducing manufacturer costs, but the only drawback of cloud services is that data will be secured and reasonably priced in the cloud. Hence, before going to the cloud, all content must be encrypted. Consumers of a collision protection information-sharing system are given secure private keys so they may add or remove consumers.
Exploring iSpring Suite for Android-Based Interactive Instructional Media in Electrical Lighting Installation Subject

In today’s digital era, interactive learning media is the right solution to improve the quality of effective and efficient learning. An active engagement between students and learning media using iSpring Suite can enhance student understanding and enthusiasm and motivate students in teaching and learning. This research aims to create Android-based interactive media using iSpring Suite for electric lighting installation learning materials. This research uses the Research and Development (R&amp;D) method with a 4-D development model. This research consists of several stages: defining, designing, developing, and disseminating, and was conducted using validation sheet instruments. The results of this study indicated that the learning media experts confirmed that it was 93.8% valid. At the same time, the materials experts confirmed that it was 90.8% valid. Based on the validity percentage, Android-based interactive learning media using iSpring Suite is highly recommended for electric lighting installations subject. It has been well-tested and effectively applied as an Android-based interactive learning medium.
Transformer-based tool recommendation system in Galaxy

Abstract Background Galaxy is a web-based open-source platform for scientific analyses. Researchers use thousands of high-quality tools and workflows for their respective analyses in Galaxy. Tool recommender system predicts a collection of tools that can be used to extend an analysis. In this work, a tool recommender system is developed by training a transformer on workflows available on Galaxy Europe and its performance is compared to other neural networks such as recurrent, convolutional and dense neural networks. Results The transformer neural network achieves two times faster convergence, has significantly lower model usage (model reconstruction and prediction) time and shows a better generalisation that goes beyond training workflows than the older tool recommender system created using RNN in Galaxy. In addition, the transformer also outperforms CNN and DNN on several key indicators. It achieves a faster convergence time, lower model usage time, and higher quality tool recommendations than CNN. Compared to DNN, it converges faster to a higher precision@k metric (approximately 0.98 by transformer compared to approximately 0.9 by DNN) and shows higher quality tool recommendations. Conclusion Our work shows a novel usage of transformers to recommend tools for extending scientific workflows. A more robust tool recommendation model, created using a transformer, having significantly lower usage time than RNN and CNN, higher precision@k than DNN, and higher quality tool recommendations than all three neural networks, will benefit researchers in creating scientifically significant workflows and exploratory data analysis in Galaxy. Additionally, the ability to train faster than all three neural networks imparts more scalability for training on larger datasets consisting of millions of tool sequences. Open-source scripts to create the recommendation model are available under MIT licence at https://github.com/anuprulez/galaxy_tool_recommendation_transformers
The History of Computer Graphics and Animations

Computer graphics are creating and manipulating visual content using computers. It consists of 2D and 3D graphics, rendering techniques, and tools to generate images, animations, and interactive experiences. Ivan Edward Sutherland created the first computer graphic design in 1963 called Sketchpad. The process of taking sequential photos of drawings or models to give the impression that they are moving is called animation. Animations are breaking human boundaries by making it easy to depict fictional/fantastical worlds and worldly elements. Allowing us to break away from the grips of science and create unique fiction. Animations are now also a major part of the educational field as many schools are teaching students through CG and animations which makes learning much more fun and immersive. Due to their unparalleled visual experiences, computer graphics and animations have long since changed a wide range of sectors and communication. CG made it possible to create Japanese anime and cartoons for enjoyment. Incredible amazing effects, captivating environments, and distinctive characters in motion pictures and video games. Additionally, CG is greatly improving education by using interactive animations to make complex ideas look interesting and approachable. CG is used to create 3D models, visualizations, and data analysis. In more practical domains including engineering, medicine, and architecture. This improves diagnostics and decision-making increasing productivity. Computer graphics have made it possible to push beyond the limits of science, education, and creativity. CG has also encouraged innovations and fundamentally changed how we see and engage with the world. Their influence will only increase, creating a plethora of opportunities for mankind's future
Angular RxJS for E-commerce Development

This paper explores the use of RxJS in combination with Angular for dynamic filtering and sorting in e-commerce websites. It highlights the importance of filtering and sorting in e-commerce and the challenges faced in implementing effective filtering and sorting systems. The paper then explains how RxJS operators such as map, filter, and scan can be used to create responsive and scalable filtering and sorting systems. Additionally, it discusses the advantages of using Angular for e-commerce websites and how it facilitates the implementation of dynamic filtering and sorting systems. Code examples and case studies are provided to demonstrate the effectiveness of using RxJS and Angular for dynamic filtering and sorting in e-commerce.
One step accurate phase demodulation from a closed fringe pattern with the convolutional neural network HRUnet

Retrieving a phase map from a single closed fringe pattern is a challenging task in optical interferometry. In this paper, a convolutional neural network (CNN), HRUnet, is proposed to demodulate phase from a closed fringe pattern. The HRUnet, derived from the Unet model, adopts a high resolution network (HRnet) module to extract high resolution feature maps of the data and employs residual blocks to erase the gradient vanishing in the network. With the trained network, the unwrapped phase map can be directly obtained by feeding a scaled fringe pattern. The high accuracy of the phase map obtained from HRUnet is demonstrated by demodulation of both simulated data and actual fringe patterns. Compared results between HRUnet and two other CNNS are also provided, and the results proved that the performance of HRUnet in accuracy is superior to the two other counterparts.
Unveiling Mood Classifications in Malaysia: Analysing Code-Mixed Twitter Data for Emotional Expression

The fast rise of social media platforms has given academics unparalleled access to user-generated data, allowing for large-scale studies of public attitudes and moods. In a nation with such a rich culture as Malaysia, it is typical to see tweets written in Malay, local slang, and English. This language variation makes it more difficult to
The ripples of consonant intervals and chords arising in different tuning systems

Pure consonances are combinations of exact multiples of a fundamental frequency, particularly with the factors 2, 3, and 5. They give rise to the consonant intervals (octave, perfect fifth, and major and minor thirds) and consonant chords (major and minor). However, these kinds of consonances are only achieved in just intonation, which does not produce beats or ripples, that is, their envelopes are constant. On the contrary, other tuning systems, such as Pythagorean, meantone, or N-tone equal temperaments, which slightly differ from just intonation, actually produce beats or ripples, that is, the corresponding envelopes oscillate and, acoustically, resemble a vibrato in amplitude. In this paper, the envelopes of consonant intervals and chords are modelled mathematically by approximate formulas. They contain one variable for the intervals and two variables for the chords. The formulas include deviations of one full trigonometric period, thus being valid for any tuning system. In the case of intervals, the corresponding ripples are obtained by following a line (1D) at a specific velocity and, in the case of chords, by following a line on a graph (2D) at specific velocity and direction. The corresponding audio files considering pure tones are also obtained.
Development of Scaffolding in Stimulating Students Motivation and Language Acquisition

This study aims to get an overview of the implementation of scaffolding in student language acquisition and describe student motivation in participating in language acquisition activities with the use of scaffolding. Through the application of scaffolding, language acquisition is obtained by learners. This study uses qualitative descriptive research design because this study presents research results based on facts that exist in everyday life as they are. Language acquisition for students on the words steel tank, gondola, scour, rivers, paddled; wings, tail, antennae, beak, muzzle, ankles, as per teacher-designed scaffolding. Of the six stages of scaffolding, five stages are carried out by teachers, the last stage is reflective of students and teachers only. For the level of motivation and intelligence starting from the highest percentage of motivation based on intelligence: students who are intelligent and motivated as much as 54%, students have average intelligence and motivated 19% who are intelligent and unmotivated, 12%; Smart and unmotivated students and average and unmotivated students, 2% each. This indicates that in general, the use of scaffolding affects student motivation in language learning with the help of other activities programmed by the school.
Optical Character Recognition System for Digit Recognition Using Deep Learning

Because it is so difficult to distinguish handwritten digits, digit identification is one of the most critical applications in computer vision. This is one of the reasons why it is so tough. The field of handwritten character recognition is one in which a great deal of application of numerous deep learning models has occurred. The startling parallels that can be drawn between deep learning and the brain are primarily responsible for its meteoric rise in popularity. In this study, the Artificial Neural Network and the Convolutional Neural Network, two of the most used Deep Learning algorithms, were investigated with an eye toward the recognition process's feature extraction and classification phases. With the assistance of the categorical cross-entropy loss and the ADAM optimizer, the models were trained on the MNIST dataset. Backpropagation and gradient descent are the two methods utilized during the training process of neural networks that contain reLU activations and carry out automatic feature extraction. In computer vision, one of the most common and widely used classifiers is the Convolution Neural Network, sometimes referred to as ConvNets or Convolutional neural networks. This network is used for the recognition and categorization of images.
Forecasting Photovoltaic Output Power Based on Environmental Parameters Using Artificial Neural Network Methods

Photovoltaic is a system that can convert sunlight into electrical energy. However, photovoltaic efficiency tends to be low and its performance is affected by several environmental parameters such as dust, wind speed, humidity, temperature and other external factors. Because there are many factors that can affect the power generated, we need a power output prediction system that can assist in planning and managing as well as increasing the efficiency of photovoltaic systems. In this research a system is designed that can predict the photovoltaic output power in the short term using the Artificial Neural Network method or what is often called an artificial neural network. Predictions are made based on the effects of several environmental parameters such as wind speed, dust, humidity, and temperature on a 10 Wp photovoltaic system. Performance data for 7 days is used as a dataset and then processed using ANN with 1 input layer, 3 hidden layers and 1 output layer and 3 sample epochs (10, 100, and 1000). The results of the study can predict the output of photovoltaic power for the next 4 days with an error value of Mean Square Error (MSE) of 0.0010, Mean Absolute Error (MAE) of 0.0155, Root Mean Square Error (RMSE) of 0.0229 with an increase in power reach 0.5 to 1 watt.
ERROR ON SENTENCE STRUCTURE IN WRITING RECOUNT TEXT AT ELEVENTH GRADE OF SMK NEGERI 2 SIDUAORI

&#x0D; This research aimed at analyzing the errors on sentence structure in writing recount text made by eleventh grade of SMK Negeri2 Siduaori.This research was designed by using qualitative descriptive method. In analyzing the data, the research used theory of Miles Huberman and Saldana (20:31-33). data reduction, data display, and conclusion drawing verification. The data of this study was taken from the eleventh grade students of SMK Negeri 2 Siduaori. The data of this study are students errors in use past tense.To examine the credibility of this study the researcher used triangulation. The results of this study showed that students made errors because of they are not mastering the pattern of past tense, not mastering tenses,lessmotivation,less vocabulary. It is suggested to the teacher to pay much attention to the error in order to use appropriate strategy in teaching recount text errors, especially in use of the simple past tense, passive and active verbal sentence and in nominal sentence and students can come understand how to write a good recount text.&#x0D;
JSinAja: Javascript Programming Learning Application (React JS, React Native, Node JS) Mobile Based Using Problem Based Learning Method

This article describes the design of a mobile-based learning application for JavaScript programming using React JS, React Native, and Node JS. This application aims to provide an interactive and engaging learning experience for beginners and advanced JavaScript programming users. This application is designed to cover the basics of JavaScript programming, such as syntax, data types, control structures, functions, and objects. This application also covers more advanced topics, such as asynchronous, functional, and object-oriented programming. The application uses the React JS library for web interfaces, React Native for mobile application development, and Node JS for the backend. The app's user-friendly design has a simple and intuitive interface that guides users through the learning process. This application is also equipped with features such as materials, tutorial videos, and discussions to help users apply their knowledge and test their abilities. In the future, this application is designed to be developed further by adding new modules and features. The app also includes user feedback and analytics to improve the learning experience continuously. This application uses one of the software development methods, namely the waterfall development method, which is based on a structured and sequential sequence of stages. Hopefully, this application will provide a valuable resource for anyone interested in learning JavaScript programming, from beginners to advanced users
The Correlation between Students’ Vocabulary Mastery and Their Reading Ability at Tenth Grade of SMAN 5 Kabupaten Tangerang

The purpose of this study was to determine the relationship between students' vocabulary mastery (X) and their reading ability (Y) in the tenth grade of SMAN 5 Kabupaten Tangerang in the academic year 2019/2020. There were 80 students from 403 students of population taken as the sample of this study who were determined using random sampling techniques. The data collected was analyzed using Pearson Product Moment Correlation and the instrument used was a student's vocabulary mastery test and a student's reading ability test. In addition, research findings indicate that there is a high correlation between students' vocabulary mastery and their reading ability. It is assumed that the alternative hypothesis (Ha) in this study was accepted and the null hypothesis (Ho) is rejected. There was correlation between students' vocabulary mastery and reading ability is accepted. In conclusion, the results of the hypothesis test between students' vocabulary mastery and reading ability in tenth grade at SMAN 5 Kabupaten Tangerang shows a positive correlation. There is a high correlation between students' vocabulary mastery and their reading ability at the SMAN 5 Kabupaten Tangerang with r-coef = 0.707. However, students must improve their learning, use their time perfectly, and have good mastery in memorizing vocabulary. In reading skills, students are strongly advised to always read books. So students are familiar with the support of English conversation.
Pelatihan Wawancara Kerja dalam Bahasa Inggris bagi Siswa-Siswi Kelas XI SMK Dharma Bakti 4 Jambi

The aim of this community service is for vocational high school students to be able to speak English fluently in a job interview. Vocational high school students are prepared to be able to work directly after graduating so that job interview training is needed to prepare the students in the working area. Besides using Indonesian, job interview uses English in this era. Hence, the ability to a job interview in English is needed. The method in community service is by giving job interview training in English to students. There are two results in this community service. The first is training activity is started with several steps until the students can practice job interviews in English. The second is a job interview in English is beneficial for the students. The students are able to know the vocabulary and practice pronouncing it well for a job interview in English. The students are able to speak in English for a job interview. This community service training is important for preparing vocational high school students to work.
SITE ADAPTATION

For local analysis, solar resource is best evaluated by ground measured meteorological stations. However, when the distance to the nearest station is high, satellite-based data (historical data series) become the ideal solution, especially for regional and continental analysis. Although satellite-based methods have high levels of confidence, they can still show significant differences when compared to instantaneous values measured on the ground. In order to ensure the reliability of on-site PV generation results, satellite data correction methods known as site adaptation, using ground-measured data, have been implemented. The purpose of these methods is to minimize the error and improve the deviation between satellite-derived data and instantaneous ground measurements. The objective of this work is to present the application of the linear regression site adaptation method for data measured in the meteorological station of the Laboratory Fotovoltaica/UFSC. Additionally, complements of this method were applied by dividing the data into days with clear and cloudy skies and later by irradiance bands. It was observed that the linear regression method would present relative errors of 22.35% (rRMSE) and 1.61% (rMBE). The clear-sky division methodology showed an improvement of 0.1% in the rRMSE and 0.14% in the rMBE. Finally, the methodology of division by irradiance bands presented a result of rRMSE 0.88% worse and an rMBE 0.6% closer to the ideal trend.
FRAÇÕES SOLARES GLOBAL, DIFUSA E DIRETA DO ESPECTRO INFRAVERMELHO EM BOTUCATU/SP/BRASIL

This study describes the statistical and climatic analyses of the solar fractions KdGIV, KddIV and KdDIV for a database of the global (HGd), diffuse (Hdd) and direct (HDd) irradiations of the total spectrum, and of the global (HdGIV), diffuse (HddIV) and direct ( HdDIV) irradiations of the IV spectrum measured in the period from 2003 to 2006 in Botucatu/SP/Brazil. Also, equations are presented in order to estimate the mean fractions KdGIV, and KddIV as a function of Kt with high determination coefficients R2 = 0.958 and R2 = 0.943 respectively, and the mean fraction KdIV as a function of Kd with determination coefficient R2 = 0.982.