Reviewerly/exHarmony huggingface dataset:
Classification of Markov Encrypted Traffic on Gaussian Mixture Model Constrained Clustering

In order to solve the problem that traditional analysis approaches of encrypted traffic in encryption transmission of network application only consider the traffic classification in the complete communication process with ignoring traffic classification in the simplified communication process, and there are a lot of duplication problems in application fingerprints during state transition, a new classification approach of encrypted traffic is proposed. The article applies the Gaussian mixture model (GMM) to analyze the length of the message, and the model is established to solve the problem of application fingerprint duplication. The fingerprints with similar lengths of the same application are divided into as few clusters as possible by constrained clustering approach, which speeds up convergence speed and improves the clustering effect. The experimental results show that compared with the other encryption traffic classification approaches, the proposed approach has 11.7%, 19.8%, 6.86%, and 5.36% improvement in TPR, FPR, Precision, and Recall, respectively, and the classification effect of encrypted traffic is significantly improved.
EXCLUSIVE: After Stephen Moore's failed Fed bid, he's creating a crypto central bank

Moore has joined a group of entrepreneurs who are starting what they describe as a new type of central bank they believe will stabilize cryptocurrencies like bitcoin and its myriad of imitators.
Improving Subconscious Communicative Competence through Reading Argumentative for Post-Beginner Students in Reading Class, Panca Marga University of Probolinggo

This study is to analyze the subsconcious communicative competence using argumentative reading for post-beginner student in reading class. The theory used in this study is the communicative competence theory developed by Savignon and linguistic competence developed by Canale and Swain. The method used is classroom action research. The finding of this study is improving the subsconcious communicative competence using argumentative reading. The finding of this study are expected to have not only practical significance, but to a certain degree also theoritical significance.
CryptoCredit

When developing models for regulated decision making, sensitive features like age, race and gender cannot be used and must be obscured from model developers to prevent bias. However, the remaining features still need to be tested for correlation with sensitive features, which can only be done with the knowledge of those features. We resolve this dilemma using a fully homomorphic encryption scheme, allowing model developers to train linear regression and logistic regression models and test them for possible bias without ever revealing the sensitive features in the clear. We demonstrate how it can be applied to leave-one-out regression testing, and show using the adult income data set that our method is practical to run.
AUDIT-ABLE PROCUREMENT PROCESS WITH CLOUD COMPUTING BLOCKCHAIN

From raw materials to distribution to after-sale support, understanding the location and flow of products within your supply chain is critical and not only for maximizing efficiency. Transparency in the supply chain is one of the most important and difficult areas for enhancing logistics and supply chain management. Consumers demand transparency on where and how products are made. Distrust between organizations has historically discouraged them from sharing or relying on shared data. The smart contract is the key component of the blockchain, which has rendered blockchain beyond the reach of cryptocurrency and accessible to a variety of applications such as banking, IoT, supply chain, electronic identification, business process management and more. And with digital supply chain, integration has become complex. In this paper, it explains how the blockchain will contribute to the procurement process because of the characteristics possessed. Characterized as an open-source, decentralized, distributed transaction data storage database. This technology enables two sides to transact directly using duplicate, connected ledgers called blockchains instead of relying on centralized intermediaries. This makes transactions significantly more transparent than centralized systems ' operations. As a consequence, transactions are performed on the basis of network agreement without depending on explicit confidence, but on distributed confidence. There are many opportunities to use this technology to enhance the transparency of the supply chain management. Blockchain technology has the potential to transform how businesses are organized and managed. It allows companies to eliminate transaction costs and use outside resources as easily as internal resources.
Eye movement analysis as a tool to evaluate virtual reality systems and human behaviour

Virtual Reality technologies are evolving at a fast pace. It is important to establish if these novel solutions met the goals they were developed for (i. e., to evaluate if they are effective). These technological-based products, whether based on a conventional PC setup or an immersive virtual reality setup, predominantly rely on the stimulation of the sight. With this, the eye movement analysis appears as an important metric to evaluate technological environments. Through eye movement analysis can establish how persons collect information and what influences their actions and decisions and determine certain preferences or behaviours.
Modeling of Convolutional Neural Network Architecture for Recognizing The Pandava Mask

This research was conducted to observe the use of architectural model Convolutional Neural Networks (CNN) LeNEt, which was suitable to use for Pandava mask objects. The Data processing in the research was 200 data for each class or similar with 1000 trial data. Architectural model CNN LeNET used input layer 32x32, 64x64, 128x128, 224x224 and 256x256. The trial result with the input layer 32x32 succeeded, showing a faster time compared to the other layer. The result of accuracy value and validation was not under fitted or overfit. However, when the activation of the second dense process as changed from the relu to sigmoid, the result was better in sigmoid, in the tem of time, and the possibility of overfitting was less. The research result had a mean accuracy value of 0.96.
PENGARUH EDUKASI DENGAN MEDIA SOSIAL INSTAGRAM DAN YOUTUBE TERHADAP PENGETAHUAN GIZI SEIMBANG PADA SISWA SMA NEGERI 1 CIKARANG UTARA

Education with social media on Instagram and YouTube is an interesting preventive way for teenagers, especially in improving nutritional knowledge. Increased knowledge about nutrition can influence attitudes and behavior in the selection of nutritionally balanced food ingredients, so that indirectly will affect the nutritional status of adolescents. This research was conducted to find out the influence of Instagram and YouTube social media on balanced nutrition knowledge in students of SMA Negeri 1 Cikarang Utara. This type of research is Quasi-experiment, with one group pretest-posttest design. The respondents were 52 students, 11th graders (26 students, Instagram groups; 26 students, YouTube groups) and were intervened through Instagram posts and YouTube videos twice each in one week and repeated for four weeks. The results of this study showed that there is an influence of nutrition education with Instagram social media on knowledge (p= 0.000) and there is an influence of nutrition education with YouTube social media on knowledge (p= 0.010). Then, providing nutrition education with Instagram can affect knowledge by (41.9%) and with YouTube (24.3%).
WALKING INTO A PROTEIN MOLECULE TOGETHER: UNIVERSITY STUDENTS’ EXPLORATION OF AN ENZYME-SUBSTRATE INTERACTION IN IMMERSIVE VIRTUAL REALITY

Immersive virtual reality (IVR) is an advanced and interactive 3D visualisation platform which can help learners to build better understanding of molecular structures and interactions. This study investigated how one of the IVR applications developed by our research team helped students to advance their conceptual understanding of an enzyme-substrate interaction. Sixty-six first- and second-year university students were paired to participate in collaborative learning tasks in IVR. Student-generated diagrams, videos of VR sessions and pre- and post-interviews were analysed to evaluate students’ conceptual development. Initially, using diagrams, students described enzyme reactions in terms of a simple two-dimensional lock-and-key model. During the IVR sessions, students held extensive discussions with their partners regarding the 3D enzyme structure and circled around in the virtual space to explore the structure and electron density of the catalytic chamber. Embodied actions such as pulling the substrate into the catalytic chamber helped students to appreciate the importance of molecular shape in catalytic reactions. In the post-interviews, students discussed the bulkiness of the enzyme, its structural specificity, as well as the reasons for its high catalytic efficiency. Our findings suggest that interactive and collaborative IVR helped students visualise and gain a deep understanding of this complex enzyme-substrate molecular interaction.
Approximate Langevin Monte Carlo with Adaptation for Bayesian Full-Waveform Inversion

The first author would like to thank Tristan van Leeuwen at Utrecht University for visiting his research lab, which led to this work, and his continuous support. The research visits and the work reported here were supported by funding from King Abdullah University of Science and Technology (KAUST).
Design and Implementation of Secure System for Virtual Machine Image in Cloud Computing

Cloud computing which uses re-appropriating and remote handling of utilizations previously showed up around ten years prior. Distributed computing based on research in virtualization, circulated processing, utility registering, and web administrations. It decreases the data innovation overhead for beginning another business and it very well may be gotten to from anyplace. One of the ideas utilized for building distributed computing is virtualization, which has its own security hazards, yet they are not explicit to the cloud. The critical downside to taking on distributed computing is security since customers use another person's CPU and hard circle for handling and putting away information. This paper proposes a security system to get Virtual Machine Images in a virtualization layer in the cloud climate. Getting the virtual machine picture is critical as it will most presumably influence the security of distributed computing.
Highlighting Readability Issues by the Content Analysis of a Legal Text, for Translation Purposes. Case Study

In a globalized world, linguistic harmonization leads to complex translation issues. Globalization contributed to the intricacy of the economic, social and political background, and triggered urgent requirements regarding the harmonization of legislation, which, in turn, entailed the necessity to tackle legal terminology and terminological differences. In the first part of the paper, we have briefly presented some features of the technical language and several issues caused by its intricacy. The second part of the work analyzes a specialized text in terms of lexical density, dealing with aspects such as text statistics, frequency and top words, frequency of word structures, as our main purpose has been to contribute to an enhanced understanding of specialized texts. Both jurists and translators should approach legal concepts carefully when transposing them into the target-language, in order to avoid misunderstandings. Moreover, multicultural knowledge and flexibility are only some of the requirements of a faithful legal translation.
Knowledge Sharing in Sport Organizations: The Role of Social Capital

Knowledge management and its dimensions have an important role in the sustainable development of sport organizations; therefore, the main objective of this study was to investigate the effect of social capital components on knowledge sharing in sport and youth offices in Kerman. 193 staff in sport and youth offices in Kerman participated in this study through a total sampling approach, and completed a valid and reliable questionnaire. The findings of the research by applying structural equation modeling demonstrated that the social capital components (mutual respect and trust, participation and teamwork, social cohesion, openness to criticism, and relationship networks) had a positive and significant effect on the knowledge sharing in sport and youth offices in Kerman. According to the research findings, developing social capital and its components can play an important role in the process of knowledge sharing in sport and youth offices in Kerman.
COULD YOUTUBE BENEFIT SECONDARY EDUCATION’S ELT?

YouTube is definitely a digital platform that seems to be one of the most-used search engines nowadays. It offers an endless supply of authentic, real-life, up-to-date materials that may benefit English Language Teaching (ELT). This research aims to investigate to what extent the authentic materials through YouTube may benefit English Language Teaching of secondary education in Indonesia. This descriptive qualitative study employed questionnaires, classroom observations and textbook analysis as the data collection methods. A purposive sample of 125 XI graders of senior high school participated in this study. This primary research was followed by secondary one by reviewing recent literary works systematically. The results of the study suggest that Indonesian students seemingly need more exposure to English language and the advance of information and communication technologies (ICTs), particularly YouTube, is likely to foster English Language Teaching of secondary education in Indonesia since it provides abundant authentic materials related to real-life contexts.
When similarities are motivated by contrasts. Two puzzles of Hungarian sentence structure

In Hungarian generative grammar, the terms topic and focus designate structural positions associated with logico-semantic functions. The present chapter highlights the fact that elements sharing the behaviour of “topics” and “foci” are highly varied, and that logico-semantic definitions only capture prioritized subsets of the relevant data. I argue that preverbal, inversion-triggering elements (“foci” and the negative particle) are overriders, with their semantic commonality depending on relationships of contrast vis-a-vis a baseline clause type, that of neutral positive declarative clauses. With regard to sentence-initial, weakly stressed expressions (“topics” and “sentence adverbials”), I propose that they are contextualizers, generating supporting context for the processing of a message. Here, the baseline can be identified as the situation where no explicit contextualization is necessary.
Annual Awards to Teachers in Mathematics and Computer Science &amp; IT

This paper presents the winners of the 2021 Awards to Teachers in Mathematics and Computer Science given annually by the International Foundation “Sts. Cyril and Methodius” for high achievements in identifying and developing gifted students in the last five years. The winners of the annual awards are determined jointly with the Union of Mathematicians in Bulgaria.
Motion Guided Attention Fusion To Recognize Interactions From Videos

We present a dual-pathway approach for recognizing fine-grained interactions from videos. We build on the success of prior dual-stream approaches, but make a distinction between the static and dynamic representations of objects and their interactions explicit by introducing separate motion and object detection pathways. Then, using our new Motion-Guided Attention Fusion module, we fuse the bottom-up features in the motion pathway with features captured from object detections to learn the temporal aspects of an action. We show that our approach can generalize across appearance effectively and recognize actions where an actor interacts with previously unseen objects. We validate our approach using the compositional action recognition task from the Something-Something-v2 dataset where we outperform existing state-of-the-art methods. We also show that our method can generalize well to real world tasks by showing state-of-the-art performance on recognizing humans assembling various IKEA furniture on the IKEA-ASM dataset.
S&P500 Index Direction Prediction Using Textual Tweets and Their Corresponding Sentiment

In this paper, a novel method is proposed to predict the direction of Standard & Poor 500 (S&P500) index using the tweets in this regard as well as the index amount from the day before. At the beginning, using a dataset of all tweets and their corresponding posting times about S&P500 index, companies and securities are considered as features of the study. Next, these feature vectors are assigned three different labels based on the direction of the index change from the day before and whether the change is significant enough, creating a classification problem. Building a sentiment analysis tool based on T5 transformer which attempts to combine all the downstream tasks into a text-to-text format, sentiment feature is added to each tweet in the dataset. Lastly, after balancing the data and preprocessing the textual information through an NLP pipeline, a deep neural network is proposed to classify the processed data. It is shown that using the tweets and their corresponding sentiments, the proposed method for movement direction prediction of the S&P500 index outperformed other existing models.
Professionalism of Educators Using English In Teaching-Learning While Training Process In BDK Makassar

A language is a tool of communication. English is an international language in the world. Education training place is a place to civil servants follows training, which handles by educators in that place whereas following by adults people especially for Religious Ministary Affairs. So, when training in the process, educators professionalism is very important to delivered the materials for the participants and all the elements are using language, but especially for educators when they using English. A language is a tool of communication, how far our understanding in English, and how far we can use it.
GeoTiff Data Curation Primer

This work was created as part of the “Specialized Data Curation” Workshop #3 held at Washington University in St. Louis, MO on November 5-6, 2019.
Hand Gesture Detection Using Segmentation

Hand gesture detection is a project which recognizes the gesture of hands and detect accordingly. Hand Gesture recognition is an important technique for creating user-friendly interfaces. Hand gesture is recognized by robots, for example, can take human commands, and those who are deaf or who cannot speak, can recognize the sign language for communication. Hand gesture recognition in video games could help by allowing players to use gestures to interact with the game rather than a controller. Moreover, to account for the infinite number of possible hand positions in three dimensions, such an algorithm must be more robust. It must also be capable of working with video rather than static images.
100 PERCENT REMOVAL EFFICIENCY OF AQUATIC PLANT FROM WASTE WATER

Water pollution has become one of the most serious problems of today’s civilization. Lemnaceae is one of the aquatic plant species successfully used for wastewater treatment. It is very efficient in removing pollutant. This paper mainly focuses on the treatment of waste water by phytoremediation process using the plant ‘Lemnaceae’ and has given emphasis to the removal of heavy metals by the plant. Lemnaceae could grow in sewage; they absorb and digest the pollutants in wastewater, thus converting sewage effluents to relatively clean water. Thus, the plants hold promise as a natural water purification system, which could be established at a fraction of the cost of a conventional sewage treatment facility. The study conducted in this regard revealed how efficiently wastewater could be treated using the plant ‘Lemnaceae’.Water pollution has become one of the most serious problems of today’s civilization. Lemnaceae is one of the aquatic plant species successfully used for wastewater treatment. It is very efficient in removing pollutant. This paper mainly focuses on the treatment of waste water by phytoremediation process using the plant ‘Lemnaceae’ and has given emphasis to the removal of heavy metals by the plant. Lemnaceae could grow in sewage; they absorb and digest the pollutants in wastewater, thus converting sewage effluents to relatively clean water. Thus, the plants hold promise as a natural water purification system, which could be established at a fraction of the cost of a conventional sewage treatment facility. The study conducted in this regard revealed how efficiently wastewater could be treated using the plant ‘Lemnaceae’.
Electronic Customer Satisfaction Using Electronic Personalization and Social Media Marketing Model

Electronic personalization and social media considered innovative models used in the marketing strategy to achieve customer satisfaction by adopting modern tools that offer products and services based on personal preferences. The study employed a quantitative approach using a questionnaire distributed to a convenience sample consisted of (622) customers in the five-star hotels in Jordan. (573) questionnaires were valid and tested using AMOS.4. The study results indicated that social media marketing has a significantly positive impact on customer satisfaction and electronic personalization and there is a significantly positive impact of social media marketing on customer satisfaction through the intermediate role of electronic personalization. Accordingly, the management of five stars hotels should be Adopt electronic marketing tools and models to enhance the level of customer satisfaction in the global competition.
ECONOMICS, CULTURE, EDUCATION: GENDER ASPECT

This article examines the close relationship between culture and economics, with a particular emphasis on the gender aspect. It analyzes the role of art education in the development of Russian humanitarian sphere and the levelling of gender inequality. The article promotes the idea that it is the cultural progression that determines economic development, and discusses the current state of affairs, in which the cultural sphere remains a non-priority, and therefore financially lagging, non-prestigious and suffering from gender imbalances, as proven by our own sociological surveys, presented in the article. The study was carried out in 2018–2019 in five cities of the Russian Federation, where students from XNUMX higher educational institutions were interviewed. These surveys were designed to determine the level of interest of Russian youth in the cultural sphere, demonstrating the plans and intentions of young Russians regarding their professional future and career choice. At the same time, the respondents' answers were analyzed according to a number of parameters, including gender. Based on the results of the surveys, as well as on the analysis of existing literature and statistics, conclusions are drawn about the role of public policy and the need for changes — not only in the field of financing culture, but also in relation to the tasks of art education, responsible primarily for the spiritual state of society, both in the present and (due to its educational function) and in the future. The methodology of our work is defined by its interdisciplinarity, which involves subjects ranging from sociology and economics to cultural studies and pedagogics.