Reviewerly/exHarmony huggingface dataset:
Ciphertext-Policy Attribute-Based Encryption Scheme for Secure Organizations’ Bitcoin Wallet Access

Bitcoin is a totally decentralized digital cryptocurrency stored in a wallet managed by the user using his private key.In organizations, to allow the employees to access organization wallet, bitcoins need to be managed based on each department's or team's budget.Organization's hierarchy need each department to have its bitcoins independently and control the wallet by employee's attributes as his position, email, and department to make the access more realistic and flexible.In this paper, the organization's wallet (superwallet) is divided into subwallets; a subwallet is assigned for each department based on this department's budget.This paper introduces a ciphertext-policy attributed-based encryption (CP-ABE) to control the access of organization's bitcoin subwallets.In the proposed CP-ABE scheme, a tree-based access structure will be used including AND, OR, and threshold gates with a flexible and secure access structure model.Therefore, the proposed scheme can keep the structures of organizations.Moreover, security of the proposed scheme has been analyzed.
Geometry of Relevant Implication II

This note extends earlier results on geometrical interpretations of the logic KR to prove some additional results, including a simple undecidability proof for the four-variable fragment of KR.
Closed group private chat application with translation feature with firebase database

Language is crucial in the multilingual workplace. Countless conversation apps are currently accessible on the Google Play and Apple App stores. These applications have a number of features that help the user's tasks. With this project, just experimented with new functionality that allows the user message to be translated based on their choices. This software also has a crucial feature called closed group private chatting. It may be quite useful for debating matters related to their field of study among intellectuals and academics. It is determined by their area of interest.
THE IMPACT OF HYBRID ELT ON EFL TEACHERS AND STUDENTS AT SECONDARY SCHOOLS DURING THE COVID 19 PANDEMIC

The COVID-19 pandemic outbreak contrived change in various sectors, forcing the education sector to adjust and modify the daily conduct of teaching and learning in schools. This research highlights modifications done by schools as they have applied Hybrid Learning (HL) as an adjustment in the learning-teaching process. This study asked EFL Teachers and Students from thirty different schools in Surabaya and Sidoarjo in English Foreign Language (EFL) classes to complete the survey about how Hybrid Learning is implemented in their classes. This research analyzed the responses by using the descriptive design. Teachers' and students' responses about the changes in teaching instruments they used, school facilities to support their classes, period of adjustments, and their preference to choose either HL EFL to compare to conventional EFL class is collected through a survey. Their result shows that 1) Adjustments require a short period for students and teachers. 2) School facilities to support EFL HL classes. The study implies that conducting HL in emergencies requires adjustments. Thus, sufficient preparation from authorities is needed.Â
Blockchain for Optimized Pattern Recognition: Comparative Study

Machine Learning and specifically Deep Learning systems have received much interest recently in many fields including the domain of Pattern Recognition.However, these systems usually relay on centralized data for training, which causes vulnerability and security issues.In addition, the complexity of the learning algorithms and the fast growth of the amounts of data in the recent years is another challenge for these systems.Blockchain has the ability to solve the data security problems due to its decentralized nature.In the other hand, parallel optimizations can reduce the training time of the learning algorithms.In this paper, we'll be discovering the benefits of integrating Blockchain technology and Parallelism with the Pattern Recognition systems.We'll be discussing papers that implemented the Blockchain technology, Learning systems, and also the Parallel Optimization methods in the medicine field.Most of these papers focus on the prediction, early diagnosis, and diagnosis of certain diseases such as Cancer, COVID-19...etc.We'll make a comparative study between these works based on several criteria: Blockchain technology, Learning algorithms, Parallel optimization methods, Datasets, and the Accuracy.Furthermore, We will present in-depth analyses of these papers outlining the advantages and limits of each one.
An Analysis of the Grammatical Errors in the Written English Compositions of JSS 1 Pupils in Five Junior Secondary Schools in Bo City, Southern Sierra Leone

This study focuses on the grammatical errors in the essays written by JSS1 pupils in five junior secondary schools in Bo city. It aims at identifying the errors occurring in the use English grammar by pupils, classifying the errors, determining their frequency levels and their sources. The descriptive survey design was used in this study, where out of a population of 853 pupils, 250 pupils were used a sample for this study. Each of the pupils was asked to write an essay, and the scripts were marked to identify all grammatical errors made by the pupils. From this study, it was discovered that out of 250 scripts, 32% of the pupils were not able to communicate their thoughts meaningfully. Out of the comprehensible scripts the following errors were identified and their frequencies: wrong use of tense 29.54%, errors in spelling 24.67%, errors in the choice of words 13.13%, wrong use of prepositions 7.79%, verb addition errors 5.84%, preposition addition errors 4.87%, pronoun addition, subject-verb agreement errors, wrong use of pronouns, plural and verb omission errors all received 1.62% each. The study further revealed that a good number of errors discovered from students’ writings were intralingual errors.
Social Engineering Attack concepts, frameworks, and Awareness: A Systematic Literature Review

The growth of data exchange and the dependency on the digital world through cyberspace raise security risks.Social engineering attacks occupy high percentage of total cybercrimes.It is also classified as the major cause of financial losses in cyberspace.This shows the need to clarify social engineering definition and clarify the proposed frameworks solutions by different researchers.This paper explores the previous researches that try to extract different concepts and perspectives which are called lifecycles, phases, frameworks, models, or a mix of them, knowing this and the development of the framework help us facing the threat of social engineering.Most of the studies agree on the effect of a comprehensive framework and how it affects positively.The results express the need for more empirical studies, government permissions, financial support to improve the conceptual frameworks to apply them to a wide range of societies, and more focus on awareness responsibility for government, users, and organizations.This study is A systematic literature review that uses Prisma methodology to extract and analyze eligible research criteria to achieve the objective of describing social engineering attack frameworks comprehensively This paper finds are the urgent need for an empirical comprehensive conceptual framework and government support to facilitate access to data, education curriculum, and enact laws.On the other hand, it emphasizes limitations, risk of bias, and future work in each study.In future work, the author suggests adding the defense perspective as a phase.
VARIATIONAL ITERATION METHOD FOR SOLVING FUZZY BOUNDARY VALUE PROBLEMS

Abstract: &#x0D; This paper will find the approximate solution to the linear and nonlinear fuzzy boundary value problems using the variational iteration method. The numerical scheme is based on analyzing the fuzzy problem into two crisp sub-problems. The first is for the upper solution and the second is for the lower solution of the fuzzy solution. Also, the convergence of the obtained variational iteration formula has been proved to converge to the exact solution of the problem under consideration in each illustrative example, since there is no general formula that may be obtained for the correction functional related to the problem under consideration which is due to the variation of the general Lagrange multiplier from one problem to another.&#x0D; Keywords:Fuzzy boundary value problems, variational iteration method, solution of fuzzy differential equations using variational iteration method.
Characterizing Warm Temperature during April 2019 Monsoon Transition in the Central part of Java

Warmer temperature than normal has been observed in the central part of Java Island-Indonesia during the monsoon transition in 2019. To explain the environmental process related to temperature variability, this research aims to characterize the process related to temperature anomaly and explain the contributing factors in terms of radiation balance and latent heat flux. This research uses the data from two meteorological stations from the Indonesian Bureau of Meteorology, Climatology, and Geophysics (BMKG) and the National Centers for Environmental Prediction (NCEP/NCAR) Reanalysis Project to explain the temperature anomaly. Several parameters, such as near-surface air temperature and humidity, cloudiness, solar and longwave radiation, as well as latent heat flux are obtained from the reanalysis data. This study focuses on descriptive time-series data analysis to explain the factors that contribute to the April 2019 temperatures. The results of this study show the effect of the Madden–Jullian Oscillation (MJO) on weather anomalies. The increase in humidity when the study area is traversed by the MJO causes an increase in humidity followed by intensive cloud formation and the release of latent heat in the cloud. The release of latent heat contributes significantly to the increase in temperature compared to the effect of the shortwave and longwave radiation balance. Thus, atmospheric phenomena in the tropics need to be studied further concerning warmer temperatures because they can be significantly affected by climate change.
Cost-effective Detection Model for Injected Automatic Dependent Surveillance-Broadcast Messages (ADS-B) for Secure Aviation Control

Abstract Automatic Dependent Surveillance-Broadcast (ADS-B) is considered the future of aviation surveillance and traffic control as it allows different types of aircraft to transmit and gain information about their and other nearby aircraft's positions, velocity, and various other variables periodically. But, as this protocol still show that it lacks in terms of security and that researchers are still developing more methods and frameworks in order to secure this technology, we decided to join the initiative and propose an efficient detection method to help aid with detecting any attempts at injecting these messages which would cause multiple risks to aircrafts such as causing collision avoidance system failure, reporting wrong status of an aircraft, or even stealing it. This paper focused mainly on three different attacks; path modification, ghost aircraft injection, and velocity drift attacks. The dataset we utilized consisted of authentic messages captured from the OpenSky Network and generated injected messages using PyCharm. This study aims to provide a revolutionary methodology that, even in the face of new attacks (zero-day attacks), can successfully detect injected messages. The main advantage was utilizing a recent dataset to create more reliable and adaptive training and testing materials, which were then preprocessed before using different machine learning algorithms to feasibly create the most accurate and time-efficient model. The best outcomes of the binary classification were obtained with 99.14% accuracy, an F1-Score of 99.14%, and a Matthews' Correlation Coefficient (MCC) of 0.982. At the same time, the best outcomes of the multiclass classification were obtained with 99.41% accuracy, an F1-Score of 99.37%, and a Matthews' Correlation Coefficient (MCC) of 0.988. The dataset is thought to offer good outcomes, but the model still requires more testing and a bigger dataset, bearing in mind that the model still needs to be tested against other types of attacks.
When will one help? Understanding audience intervention in online harassment of women journalists

While online harassment directed towards women journalists are under wide discussion, the mechanism of audience intervention in stopping online harassment is less explored. Integrating bystander invention, ambivalent sexism, and social identity theories, we propose and test an integrative framework of audience intervention in online harassment of women journalists. Results from an online experiment in Hong Kong showed that type of harassment, ideological similarity between the audience member and the harassed journalist, and the presence of other responsive bystanders could shape the appraisal of harassment incidents and willingness to intervene. The study advances the literature by clarifying the contextual nuances and challenges of audience intervention in online harassment of women journalists. It bears practical implications on how to defend women journalists so as to protect press freedom, cultivate journalist-audience relationship, and enhance an inclusive and egalitarian online space.
E-CLASSROOM LANGUAGE: A CONVERSATION ANALYSIS OF SYNCHRONOUS INSTRUCTIONS DURING THE COVID-19 OUTBREAK

A growing body of research has documented classroom language use in traditional classrooms. However, how teachers use language in virtual classrooms remains largely under-researched. This study was carried out to fill this gap. The purpose was to examine teachers' use of classroom language in synchronous virtual classrooms and how it facilitated learning opportunities for EFL learners. Under the qualitative research framework, video recordings of online instructional activities were analyzed using a conversation analysis approach. The results show that the majority of expressions used in online synchronous instructions were quite similar to those used in traditional classrooms except for the expressions like "let me share my screen," "turn on the camera," and "I will mute everyone." The results also show that teachers' e-classroom language use provided learning opportunities for students employing recast, scaffolding, and extended wait time for students' turns. Information on teachers' classroom language use in online learning environments presented in this paper is based on limited data, and further studies involving more significant participants are recommended.
THE DEVELOPMENT OF INTRODUCTION TO ESSAY WRITING COURSE’S TEXTBOOK BASED ON HOTS-TECH INTEGRATED WITH CM-PBL (CASE METHOD-PROJECT BASED LEARNING)

Despite many studies focusing on writing materials, few developed e-book writing materials for university students. This study aims to 1) analyze the students' and lecturers' needs related to the development of the Introduction to Essay Writing Course's textbook based on HOTS-Tech (Higher Order Thinking Skill-Technology) integrated with CM-PBL (Case Method-Project Based Learning) and 2) to develop an Introduction to Essay Writing Course's textbook based on HOTS-Tech integrated with CM-PBL. This study employs R &amp;D with the ADDIE model (Analyze, Design, Develop, Implement, Evaluate). Participants in the current study are 35 university students and four lecturers. We employed instruments such as questionnaires, interviews, and observations. Data collection traces the ADDIE model, while the data analysis employs non-parametric statistics with a descriptive quantitative model. The result shows that the book adheres contents of the book, material presentation, presentation order, the balance of the chapter, language use, and layout. The activities should cover higher-order thinking skills (HOTs) under main categories; analyzing, evaluating, and creating. The current study implies that EFL university teachers embed technology and HOTs in the Essay Writing e-book to promote the techno-skill of the current generation.
Efficient Secret Key Generation Using Langrage’s Interpolation and Discrete Wavelet Transform Function for Internet of Things

Data security during information flow has been a difficult challenge in Internet of Things (IoT).To improve security status various conventional cryptographic methods such as public, private, and hybrid key generation had been utilized by various researchers.But these methods are associated with a lack of secure communication between two or more devices.In view of this, a lot of effort is being put into the physical layer of security.In this concept signal-based encryption and key generation are used as the major components in the security of data.In this research, we present a physical layer security technique based on wavelet transforms and Langrage's interpolation.The wavelet based function precedes the sampling of Received Signal Strength (RSS) and convolution of the Langrage's interpolation and generates a session shared key for communication.The size of the generated key is 128 bits and 1024 bits during the authentication process of sharing information.The proposed algorithm's performance is evaluated through a simulation modeling environment.Different standard data bench for performance analysis is also used.The proposed technique is evaluated in two scenarios; Line of Sight (LoS) and Non-Line of Sight (NLoS).The proposed algorithm is contrasted with key generation techniques based on Lagrange and Skyglow (SKG).As compare to Skyglow and Lagrange's algorithms, the proposed algorithm achieves a 3-5% improvement in overall efficiency for key generation validation.
The Influence of Tutorial Videos of Making Basic Patterns of Women's Body on The Learning Outcomes of Deaf Students

This study aims to see the impact of a learning design using video tutorials to improve the learning outcomes of deaf students. This research was conducted at SLB Negeri Binjai with a total sample of 8 people who participated in a fashion skills program. The research method used is quasi-experimental with a time series design approach. Data analysis was performed using Ms. software. Excel and SPSS. The results showed that video tutorials on making the archetype of a woman's body can provide a positive increase in the learning outcomes of deaf students which can be seen from the results of the pretest and posttest of students who continue to experience an increase in learning outcomes.
Data Stream: Statistics, Challenges, Concept Drift Detector Methods, Applications and Datasets

Through real-world applications, the data stream is generated.In contrast to traditional data, data streams have different characteristics; a huge and endless amount, on-line arriving with high speed, single processing as well as the nature of being not static, in the sense that it evolves over time; this is the concept drift.Accordingly, the mining and analysis of the data stream is an arduous and attractive task.Various frameworks for data stream (analysis, mining, etc.) have been proposed over the past years.In the same context, identifying the number of classes of data streams is an important initial step when designing a model for processing the data stream.At present, deep neural networks (DNNs) are a fundamental technique in various applications.DNNs have many structures, including the multilayer perceptron (MLP).In this paper, we propose a deep neural network (DNN) model based on multilayer perceptron (MLP) to classify the streaming datasets and detect their classes as an analysis step for this data type.The proposed model tests different synthetic and real-world stream datasets.The results proved that this model detects the actual number of classes for the given stream dataset.Moreover, this paper presents a systematic review of data stream, its statistics, challenges, concept drift detector methods, data stream applications in different sectors in addition to the streaming datasets.
A Review on Deep Learning Solutions for Steganalysis

Steganalysis methods have developed to attack steganography, a technique used to hide secret information in a digital media.The traditional way of steganalysis is performed as feature extraction followed by classification.With the popularity of Deep Learning (DL) in the field of computer vision, researchers started applying deep learning for steganalysis problems also.Soon they found promising results with DL as it automates the feature extraction step and classification results can be used to better learn the features.Thus, the tedious task of manual extraction of features with a separate classification step is unified in deep learning giving optimistic results.This work provides a better insight into steganalysis evolution using deep learning and provides a broad review on how researchers have successfully applied Convolutional Neural Network (CNN) by using steganalysis specific activation functions, different convolutional layers and others.Researchers have compared their results with each other as well as state-of-the-art before deep learning (Rich Models + Ensemble Classifier).Initially, CNNs were created from scratch in the field of steganalysis but later researchers moved to highly efficient pretrained networks such as SRNet, ResNet and EfficientNet and found significant improvement in results on more challenging datasets such as ALASKA-I and ALASKA-II.The reason for such improvement is that pretrained networks are already trained on a very large dataset of images for some classification tasks and thus can be finetuned easily to other classification tasks with improved results.
Pengembangan Model Bahan Ajar Berbasis Canva untuk Materi Tematik pada Kelas 2 di SDN Tangerang 15

In the world of education, it is necessary to focus on teaching material models to be applied or implemented to students in the learning process so that they can be effectively adapted to achieve the goal, namely student learning outcomes. So that by utilizing the appropriate model of teaching materials it will be effective in increasing the motivation and also the learning outcomes of students at school. Particular attention is paid to the use of online media or the CANVA platform used by Tangerang 15 Elementary School to be precise for Grade 2 students to be one of the efforts of a teacher to increase motivation and also interest students in the learning process. The method used in this research is literature study by utilizing several journals as well as previous literacy related to the topic taken by the researcher. From the results of research that has been carried out by utilizing several previous studies also that by utilizing learning media on the CANVA platform it is very suitable to be applied in order to increase motivation and also learning outcomes for class 2 students at SDN Tangerang 15 because it utilizes audio-visual, color features, audio, characters, illustrations, photos, and others that can be adapted to the creativity of students and can enhance their ideas and creativity, especially in thematic subjects.