Reviewerly/exHarmony huggingface dataset:
Development of the Automated Tool to Perform Analysis and Visualization of User Reviews

User reviews have gradually spread in the mobile application industry as a research method to help developers of mobile applications understand the requirements and impressions of users. However, identifying ways of interpreting mass user reviews is a critical challenge faced by developers. Adopting the thought of information visualisation, this research developed a website by an iterative process of data collecting, analysis and evaluations to analyse user reviews and to generate visual charts depicting analysis results. Following the visualised information provided in the website, mobile application developers will be able to analyse user reviews individually. This will enable them to plan further improvements on applications developed based on the graphical information that represents the real needs of users. Moreover, this graphical information-generating website is expected to improve overall rating of a software on a download platform, which would lead to the larger number of downloads and hence, greater benefits.
TLS Library for Isolated Enclaves : Optimizing the performance of TLS libraries for SGX

Nowadays cloud computing systems handle large amounts of data and process this data across different systems. It is essential to considering data security vulnerabilities and data protection.One me ...
An ode to conference proceedings from the U.S. Southwest

In this era of online indexing and scholarly social media, it is easier than ever for researchers to find papers and authors that they are interested in. But as access to information expands, choices over what information to consume are increasingly driven by pre-existing prejudices and confirmation bias. In this context, it takes ever more discipline for scholars to not become locked in their own echo chambers. All of us can see the damage that this same tendency is doing to our public life, so we should try to guard against the same thing happening in scholarship.
Characterizing Consensus in the Heard-Of Model

The Heard-Of model is a simple and relatively expressive model of distributed computation. Because of this, it has gained a considerable attention of the verification community. We give a characterization of all algorithms solving consensus in a fragment of this model. The fragment is big enough to cover many prominent consensus algorithms. The characterization is purely syntactic: it is expressed in terms of some conditions on the text of the algorithm.
Вычислительные алгоритмы расчета алгебраического иммунитета нелинейных узлов замены симметричных шифров

Block of nonlinear replacements (complication node, substitution block, S-box) is an important element of most modern symmetric ciphers. This is an elementary cryptographic primitive designed to mix input data and introduce non-linearity. By replacing small blocks with other blocks, mixing and scattering of data is achieved, and repeated cyclic repetition of such a procedure makes it possible to achieve the required cryptographic properties of the cipher. Many different criteria are put forward to substitution blocks (balance, high nonlinearity, low autocorrelation, correlation immunity, required avalanche properties, and many others). Each criterion expresses a formalized requirement of resistance to certain types of cryptographic analysis (differential, linear, etc.), i.e. when designing ciphers, they use an integrated approach, choosing S-blocks according to the totality of individual indicators. With the development of algebraic cryptanalysis, a new indicator of the effectiveness of substitution nodes has appeared – algebraic immunity, which is calculated as the minimum degree of the simplest (in a sense) algebraic equation describing the S-block. To search for such an equation, special methods are used, based on the construction of Grobner bases. If you specify a knot of substitutions through a Boolean function, then to calculate algebraic immunity it is enough to find a function of the least degree from the annihilator space. This article discusses various methods of calculating algebraic immunity, analyzes their computational efficiency, discusses implementation details, substantiates methods for optimizing calculations in terms of time (in terms of number of operations) and capacitive (in terms of memory costs) of complexity. An advanced algorithm for calculating algebraic immunity is proposed, optimized for computing resources, including the necessary RAM sizes. The results of experimental studies are presented, in particular, the results of calculations of the algebraic immunity of 8x8 S-blocks for some well-known modern ciphers (AES, Kalina, Grasshopper, BelT), as well as the results obtained for random 8x8, 9x9 and 10x10 S-blocks.
Sistem Pendukung Keputusan Pemilihan Guru Berprestasi Menggunakan Metode Profile Matching Pada SMK Insan Global

The teacher is the most important milestone in advancing education, is considered as someone who can inspire, motivate and the most important role is to influence the quality of education of students in school. However, in the Global Insan Vocational School the process of selecting outstanding teachers is still subjective, because it is only based on the assessment of the principal and is not based on certain criteria for the process of selecting outstanding teachers so that it causes injustice between one teacher and another and is not well targeted. The criteria for selecting outstanding teachers in Global Insan Vocational Schools is the aspect of discipline, aspects of teacher performance, aspects of integrity, and aspects of behavior. In calculating the writer using the Profile matching method, which is a research method that can be used in decision support systems, the process of evaluating competencies is carried out by comparing one value profile (the value of competency needs) with several other competency value profiles, so that the results of the difference between competency needs can be known. needed, the difference between competencies is called a gap, where the smaller gap has a higher value. The aspects used in this study are Discipline, Teacher Performance, Integrity, and Behavior. Where every aspect has criteria as their choice
Education, Activism and Digital Technologies: A Systematic Review

espanolPocos estudios en el campo educativo se han preocupado por la relacion entre educacion y activismo mediado por tecnologias digitales. Sin embargo, dadas las crecientes oleadas de activismo y movilizacion en el mundo con diversas expresiones educativas, esta relacion merece un analisis exhaustivo. El presente articulo indaga como la literatura cientifica ha conceptualizado la relacion entre educacion y activismo mediado por tecnologias digitales, a traves de una revision sistematica de estudios internacionales publicados entre 1996 y 2016. El enfoque metodologico de esta investigacion se baso en un analisis tematico, el cual permitio identificar patrones y relaciones emergentes en la literatura cientifica analizada. Se revisaron 392 articulos y se seleccionaron 40 para un analisis mas detallado. Los resultados permiten sostener que, para entender los vinculos entre el activismo mediado por tecnologias digitales y la educacion, es necesario problematizar ciertas distinciones conceptuales que hacen algunos estudios al referirse, por ejemplo, a la educacion formal, no formal e informal. A partir de alli se propone una nueva taxonomia de practicas politicas que permiten superar esta y otras distinciones presentes en la literatura cientifica. Se concluye que es necesario incorporar un “giro practico” al momento de analizar los vinculos entre activismo, tecnologias digitales y educacion, ya que este enfoque permite desafiar las distinciones y oposiciones binarias identificadas en la produccion de conocimiento analizada. EnglishAlthough digital activism and mobilization around education is booming worldwide, few educational studies have addressed the relationship between education and activism mediated by digital technologies. This article explores how the scientific literature has conceptualized the relationship between education and activism mediated by digital technologies through a systematic review of international studies published between 1996 and 2016. The research uses thematic analysis to identify emergent patterns and relationships in the scientific literature. Thus, 392 articles were reviewed, and 40 were selected for a more detailed analysis. The findings show that it is necessary to problematize certain conceptual distinctions that some studies make (e.g., formal, non-formal, informal education). We propose a new typology of political practices, which transcend this type of distinctions present in the scientific literature. Conclusions address a necessary integration of a “practical turn” when analyzing the links between activism, digital technologies, and education since this approach allows one to challenge the binary distinctions and oppositions identified in the scientific production of knowledge.
Classification of Prepared and Extemporaneous Speech and Possibility of Application in Education

담화 상황에 따른 즉흥적 말하기와 준비된 말하기의 구분 양상은 교육 현장에서 그 실효성이 거의 없다고 해도 과언이 아니다. 특히 즉흥적 말하기와 관련해서는 더욱 그러하다. 이는 구분 자체의 문제라기보다는 이를 구분하는 교육적 기준의 마련에 문제가 있었다고 볼 수 있다. 이를 위해 본고는 맥락, 지식, 기억, 언어투식, 텍스트성의 다섯 가지 기준에 따라 준비된 말하기와 즉흥적 말하기를 구분하였다. 아울러 본고는 이러한 기준에 따라 삶과 앎, 심리학과 수사학, 일화기억과 의미기억, 구어성과 문어성, 통사결속과 의미연결로 구분하여 즉흥적 말하기와 준비된 말하기의 기준 근거를 마련하였다. 이는 말하기 교육상으로 즉흥적 말하기의 교육적 실효성을 높이고, 특히 말하기와 듣기의 생태학적 환경에 부합하는 교육 환경을 구성하는 데 일조할 것이다.It is not an exaggeration to say that the distinction between extemporaneous speaking and prepared speaking according to the discourse situation had little effectiveness in the field of education. Especially when it comes to extemporaneous speaking. This is not a problem of the classification itself, but rather a problem with the preparation of the criteria for classifying it. To this end, this paper divided the prepared speech and extemporaneous speech according to five criteria: context, knowledge, memory, language register, and textuality. In addition, this paper prepared the basis for extemporaneous and prepared speech by dividing it into life and knowledge, psychology and rhetoric, episodic memory and semantic memory, spoken and written language, and cohesion and coherence. This will enhance the educational effectiveness of extemporaneous speaking in terms of speaking education, and in particular, will help to construct an educational environment that matches the ecological environment of speaking and listening.
Timing attacks and local timing attacks against Barrett's modular multiplication algorithm.

Montgomery’s and Barrett’s modular multiplication algorithms are widely used in modular exponentiation algorithms, e.g. to compute RSA or ECC operations. While Montgomery’s multiplication algorithm has been studied extensively in the literature and many side-channel attacks have been detected, to our best knowledge no thorough analysis exists for Barrett’s multiplication algorithm. This article closes this gap. For both Montgomery’s and Barrett’s multiplication algorithm, differences of the execution times are caused by conditional integer subtractions, so-called extra reductions. Barrett’s multiplication algorithm allows even two extra reductions, and this feature increases the mathematical difficulties significantly. We formulate and analyse a two-dimensional Markov process, from which we deduce relevant stochastic properties of Barrett’s multiplication algorithm within modular exponentiation algorithms. This allows to transfer the timing attacks and local timing attacks (where a second side-channel attack exhibits the execution times of the particular modular squarings and multiplications) on Montgomery’s multiplication algorithm to attacks on Barrett’s algorithm. However, there are also differences. Barrett’s multiplication algorithm requires additional attack substeps, and the attack efficiency is much more sensitive to variations of the parameters. We treat timing attacks on RSA with CRT, on RSA without CRT, and on Diffie–Hellman, as well as local timing attacks against these algorithms in the presence of basis blinding. Experiments confirm our theoretical results.
Context Aware Physical Activity Recognition Using Social Objects

Social Internet of Things (SIoT) is defined as social network of intelligent and smarter objects. The social objects namely smartphones, tablets, etc., have become part of our lives and have made life simpler and smarter. Smart objects on the other side have also made mankind lazy resulting in a sedentary lifestyle. Research in human physical activity recognition is not new and has attracted many new avenues in the recent past. In this paper, we have proposed a simple application that classifies human physical activities like sitting, standing, walking, jogging, climbing upstairs and downstairs using smartphones without the need of an external server or a personal computer. For the first time in literature, a smartphone is able to identify and classify the physical activities of the owner and notify the percentage of activeness and passiveness at regular time intervals. The triaxial accelerometer in the smartphone was used for data collection with the phone being carried in the subject’s trouser pocket/held near the hip region. Initially five different machine learning algorithms namely KStar, J48, Naive Bayes, SMO, and Multilayer perception were used for classification using WEKA. Amongst them the J48 algorithm was chosen as the candidate for classification in the smartphone. The Weka.jar file was added to the smartphone’s library for this purpose. Periodically, the smartphone was able to notify the activities done by the owner along with the timestamp. Keywords: Machine learning, physical activity recognition, smartphone, social objects, triaxial accelerometer Cite this Article: A. Meena Kowshalya, M. Lincy, R. Suvarna. Context Aware Physical Activity Recognition Using Social Objects. International Journal of Computer Science and Programming Language. 2020; 6(1): 41–50p.
THE UTILIZATION OF MASSIVE OPEN ONLINE COURSE CONCEPT DURING CORONA PANDEMIC OUTBREAK

The development of the digital world in the industrial era 4.0 is currently encouraging the creation of innovation in various fields and aspects of life. With easy internet access and digital innovation in every public service, of course, it has a positive impact on human life today. The creation of innovations in various fields of business both for the manufacturing business, food and beverage, convection, tourism, services, health and not lagging in the field of education services at this time. With these abnormal environmental conditions, of course, the use of digital media and internet connections has an important role when searching and disseminating information, as a medium of communication and strongly supports the teaching and learning process online. The problem is how an educator (instructor) can improve self-competence, independent learning when staying at home. The concept of massive open online courses is the right solution for educators and anyone who wants to improve their competence and learn online with a variety of material topics to choose from.
El ciberlenguaje: la imagen como una nueva escritura en la comunicación digital en la sociedad actual

espanolEl presente trabajo de investigacion tiene como objetivo el estudio del lenguaje escrito como medio de expresion del hombre, asi como de la invencion derivada del desarrollo tecnologico y, concretamente, de la expansion de las redes sociales, de una tipologia mucho mas centrada en la imagen y los simbolos graficos tales como los emojis, GIFs o memes: el ciberlenguaje. De este modo, se pretende comprobar si esta adaptacion linguistica propia de Internet, donde el poder de las palabras es sustituido por el del contenido visual, conlleva la evolucion del hombre o su retroceso como ser humano, pues bien es sabido que el lenguaje y, especificamente, la escritura, han sido invenciones determinantes del exito evolutivo de los seres humanos. EnglishThe aim of this research work is to study a written language as a means of expression, as well as the invention derived from technological development and, specifically, the expansion of social networks of a new typology much more focused on the image and the graphic symbols like emojis, GIFs or memes: the cyber language. In this way, here we attempt to verify if this linguistic adaptation of the Internet, where the power of the words is replaced by the one of the visual content, involves man’s evolution or his recoil as a human being; as it is commonly said , language and, concretely, writing have been determinant inventions in the evolutionary success of human beings.
DUMPLING: Cross-Domain Data Security Sharing Based on Blockchain

Blockchain is an effective solution for data sharing. The usual practice is to write metadata and the hash of raw data to the blockchain. This design does not take the confidentiality of metadata into account. The data provider wants to freely decide whether to share data through the data applicant’s search conditions, without exposing what data they have. This paper presents a Cross-Domain data security sharing model called DUMPLING, which is based on consortium blockchain. It achieves trusted data transaction evidence and privacy protection search. Analysis shows that the system has good security and efficiency.
Loop Theory of Universe

According to the standard Big Bang model, the universe was born during a period of inflation that began about 13.8 billion years ago. Like a rapidly expanding balloon, it swelled from a size smaller than an electron to nearly its current size within a tiny fraction of a second. Initially, the universe was permeated only by energy. Some of this energy congealed into particles, which assembled into light atoms like hydrogen and helium. These atoms clumped first into galaxies, then stars, inside whose fiery furnaces all the other elements were forged. This is the generally agreed-upon picture of our universe’s origins as depicted by scientists. This model explains many of the things, such as the remarkable smoothness of space-time on large scales and the even distribution of galaxies on opposite sides of the universe. But sometimes their are things which make the theory little uncomfortable to accept. The theory which states that the Universe underwent a rapid inflation early in its history cannot be accepted so easily, and it relies on the existence of a mysterious form of energy in the universe’s beginning that has long since disappeared.”For some scientists, inflation is a clunky addition to the Big Bang model, a necessary complexity appended to make it fit with observations. This wouldn’t be the last addition. ”We’ve also learned there has to be dark matter in the universe, and now dark energy,” said Paul Steinhardt, a theoretical physicist at Princeton University. ”So the way the model works today is you say, ’OK, you take some Big Bang, you take some inflation, you tune that to have the following properties, then you add a certain amount of dark matter and dark energy.’ These things aren’t connected in a coherent theory.” If you talk about a line segment than we know about the start and end of that line segment. In the same way we are taking the Universe a line segment so that we know where is the begining and the end of universe. But to be clear it is not that much simple as we thought of it,instead it is way more complex than tha
Adaptive Exploitation of Pre-trained Deep Convolutional Neural Networks for Robust Visual Tracking

Due to the automatic feature extraction procedure via multi-layer nonlinear transformations, the deep learning-based visual trackers have recently achieved great success in challenging scenarios for visual tracking purposes. Although many of those trackers utilize the feature maps from pre-trained convolutional neural networks (CNNs), the effects of selecting different models and exploiting various combinations of their feature maps are still not compared completely. To the best of our knowledge, all those methods use a fixed number of convolutional feature maps without considering the scene attributes (e.g., occlusion, deformation, and fast motion) that might occur during tracking. As a pre-requisition, this paper proposes adaptive discriminative correlation filters (DCF) based on the methods that can exploit CNN models with different topologies. First, the paper provides a comprehensive analysis of four commonly used CNN models to determine the best feature maps of each model. Second, with the aid of analysis results as attribute dictionaries, adaptive exploitation of deep features is proposed to improve the accuracy and robustness of visual trackers regarding video characteristics. Third, the generalization of the proposed method is validated on various tracking datasets as well as CNN models with similar architectures. Finally, extensive experimental results demonstrate the effectiveness of the proposed adaptive method compared with state-of-the-art visual tracking methods.
DESIGNING AN ENGLISH TEACHING MATERIAL FOR TENTH GRADE STUDENTS OF CULINARY STUDY PROGRAM

This study was aimed to design a book that can be used as supplementary material to teach English for culinary study program. This study was classified as Research and Development (R&amp;D). The step of conducting this study used ADDIE model with the exclusion of implementation (I) stage and evaluation (E) stage so this study tended to focus on doing three phases only; analyze, design, and develop. The subjects of this research were English teacher and 32 tenth grade students of culinary study program of SMKN 3 Singkawang. The tools for obtaining the data were questionnaires, interview, and internal validation. The result of this study is a course book for culinary study program namely English for Culinary for beginner level. Internal validation was carried out up to two times to have better product.
Improving Classification Accuracy of Ensemble Learning for Symbolic Data Trough Neural Networks’ Feature Extraction

The key element that has a major impact on the modeling process is the method selection and selection of variables (information that will be used in the model). One of the approaches that allow to improve model’s accuracy is the selection of variables and the second one is the transformation of variables. The paper presents a procedure that combines these two approaches—extracting variables from neural networks (multilayer perceptron for symbolic data) as the method of variable selection for the purposes of ensemble learning for symbolic data. The main aim of the paper is to analyze the usefulness of the proposed approach for the prediction power of the ensemble model. In the empirical part, a symbolic data set describing a thousand German borrowers is used.