Reviewerly/exHarmony huggingface dataset:
Algebraic Lexicon Grammar

This article aims at showing an application of graph theory to the description of the syntactic relations between words in English. Graph theory is part of Network Science, a new and compelling branch of mathematics that has undergone huge development over the past 20 years. The linguistic theoretical background is the Lexicon Grammar (LG) that in turn is built on the ground of the Harrisian grammar for operators and arguments. Graph theory is particularly useful in order to show how sentences have underlying structures that can be visualized through the use of graphs, and whose properties can be measured and quantified with the typical mathematical tools used by the researchers in the field of Network Science. A graph is a set of nodes (also called ‘vertices’) and links (also called ‘edges’); the links connect the nodes. Each sentence will be described as a graph, in which the words have to be seen as the nodes and the syntactic relations between the words are the links.
Multi-image blind super-resolution in variational Bayesian framework

Multi-frame image super-resolution method fuses the information of multi-frame low-resolution images to reconstruct high-resolution images. For multi-frame image super-resolution, the accurate estimation of blur kernel of low-resolution image is prerequisite for efficiency information fusion. Traditional super-resolution method usually assumes a known blur kernel and uses the Gaussian filter blur kernel for the enhancement. It also needs to tune the parameters by time-consuming hand-tuning. The proposed method acquires the super-resolution method based on the variational Bayesian method. The high-resolution image, the blur kernel and the model parameters are estimated simultaneously and automatically in the optimal stochastic sense. Experiments and simulations demonstrate that the proposed blind super-resolution method based on blur kernel self-adaptive estimation outperforms the state-of-art super-resolution method in variational Bayesian framework, especially, for the high signal to noise ratio scenarios.
Cultivation of College Students’ Digital Economic Honesty in the Teaching of Statistics

With the rapid development and wide application of network information technology, the digital economy era puts forward higher requirements for the honesty behavior of college students in China and more suggestions for the teaching of Statistics.Aiming at the problems in the traditional teaching process of Statistics, such as the low awareness of integrity, the disconnection between teaching content and digital economy, students' poor manipulative ability and the slow update of teachers' knowledge, this paper, combined with the characteristics of big data and digital economy era, puts forward some suggestions and reflections on the reform of the teaching of statistical courses from "establishing integrity, appreciating integrity, maintaining integrity and delivering integrity" and other aspects.
A Study on Steganography Concealing Data

Steganography is a process of hiding or concealing confidential information from unauthorized access. Steganography used in various fields such as military, aerospace and industrial applications. Steganography techniques are used for secure transmission of data from sender to receiver. The computer programmers, begins applying steganography techniques to video as well as audio files. This time multimedia data like image, audio, video are used as a cover media by steganography systems because public often send digital pictures in email and other Internet communication. The purpose of this review is to bring the idea of Steganography for young researchers.
TOWARD SUSTAINABLE BEHAVIOUR CHANGE: AN APPROACH FOR CYBER SECURITY EDUCATION TRAINING AND AWARENESS

Effective information security education, training and awareness (SETA) is essential for protecting organisational information resources. Whilst most organisations invest significantly in implementing SETA programs, the number of incidents resulting from employee noncompliance with security policy are increasing. This trend may indicate that many current SETA programs are not as effective as they should be. We argue that existing SETA programs are not optimal in changing employee behaviour to comply with security policy as they lack a theoretical base that can inform and guide the development of SETA programs. This study draws on knowledge from the medical domain on the use of theory to design an intervention to bring about sustainable behaviour change. The paper therefore adopts an intervention design process, based on the behaviour change wheel (BCW) framework, to develop a theory-informed SETA development process. The paper demonstrates the use of BCW in the analysis of the target behaviour and the selection of suitable strategies and techniques to change the target behaviour. The proposed SETA development process provides a sound basis for future empirical work including focus groups and action research.
Peningkatan Digital Literasi Terhadap Ujaran Kebencian di Media Sosial Melalui Program “Room of Law” Bagi Siswa Sekolah Menengah Atas di Kota Serang

The purpose of this community service activity is to provide education and understanding to students and the school towards the potential and dangers of hate speech through social media. It is hoped that through this activity encourage school students to avoid and combat the behavior of speech utterances especially on social media. The activity method is Participatory Learning and Action which emphasizes socialization, discussion and training and digital literacy education. The results of the “Room of Law” activities in this service show that students' knowledge is still weak about the utterances of hate in social media and the threat of punishment resulting from acts of hate speech. This service is still being carried out to create Agent of Against Hate Speech through training and education for Training of Train students.
360° recruitment: a holistic recruitment process

Purpose This paper aims to introduce the concept of 360° recruitment, which is a systematic, practical and holistic recruitment process that provides a reliable employee-selection structure for an organization of any size. Design/methodology/approach The recruitment process, which begins with establishing the correct selection criteria, provides a 360° view of a candidate by combining assessments, job interviews, reference checks and job previews. Findings Hiring the right employees is critical for the growth and success of an organization. However, many companies do not have an effective and reliable recruitment process that enables them to hire top-notch talent who are highly compatible with the firm. The 360° recruiting process is a practical technique that enables organizations to evaluate job applicants from multiple angles while reducing the uncertainty and the biases that are inherent in a typical recruiting process. Originality/value The 360° recruitment process is comprehensive yet practical and can be used by an organization of any size. The technique, if properly administered, will optimize recruiting and ensure that qualified and compatible employees are hired into the organization.
PEMBELAJARAN METODE DEMONTRASI DAN ALAT PERAGA TERHADAP HASIL BELAJAR PKN SISWA KELAS III SDN 004 TERATAK BULUH KECAMATAN SIAK HULU

This study aims to improve the learning outcomes of PKN by applying learning methods demonstration and teaching aids of third grade students of SDN 004 Teratak Buluh. This research is a classroom action research that includes activities with stages of planning, action, observation, and reflection. The results showed that the increase in student PKN learning outcomes on average students before classroom action research, namely, 66.8 experienced an increase in the first cycle of 76.4 and again increased in the second cycle of 80.4. Based on the results of the study, it can be concluded that by applying the demonstration learning method and the demonstration tool can improve the low PKN learning outcomes of class III SDN 004 Teratak Buluh, District of Siak Hulu, Kampar Regency.
Integration of Information Hiding and Compression for Biomedical Signals

This study proposes a method to reduce the carrying amount of Electrocardiogram (ECG) network transmission while preserving the original characteristics of ECG and protecting personal privacy. In watermarking part, we perform the quantization-based digital watermark encryption technology on the ECG signals to protect patient rights and information. In addition, the hidden information can be extracted without the original ECG. In compression part, we adopt the threshold-based compression technology to reduce the data amount of the ECG signal and preserve the original characteristics of ECG signals at the same time. The recovery of the compressed ECG signal adopts cubic spline. Experimental results verify the efficiency of the proposed method.
Transnational governance and cybercrime control: dilemmas, developments and emerging research agendas

Two areas of criminological literature, addressing respectively globalization and cybercrimes, often converge upon the assumption that global integration via electronic communication networks has transformed the contours of criminal activity, unleashing a flow of crime problems that transcends borders and overwhelms attempts to establish control. Such assessment is nowadays commonplace in both criminological discourse and in wider popular and political consciousness. This chapter takes stock of the current contours of global cybercrime and seeks to critically assess (and perhaps challenge) the claim that the processes underpinning it either go unchallenged or are irreversible. In a turbulent period where reactions against globalization are gaining political and popular traction, it is necessary to consider how reassertions of national sovereignty on the economic, political and legal planes might impact upon global flows of illegal and illicit communication, and in turn may reshape efforts to criminalize and control a range of online practices.
Using the Moodle educational platform in the process of learning RCT

This article is devoted to the analysis of the main advantages of the educational system Moodle, in terms of the possibility of its use along with traditional means of training in the organization of the educational process, in particular, during the teaching of Russian to foreign students in higher education.
Appreciation and creation of children's English picture books

The surface of the text appears to be static, without sound and movement, and the story of the text is accompanied by beautiful pictures that takes the reader into a space of delusion that is full of magic and fun, especially for imagination. For imaginative children, the secrets they want to know are always hidden in the story. Children's English Picture Book plays an essential role in helping children understand the world, learn knowledge, and enrich their emotions. The application in kindergarten is pervasive. Therefore, the appreciation and creation skills of picture books are worthy of study and discussion. Children's English Picture Book is faced with a group of young children who are full of curiosity and doubts about the world. We must consider the age characteristics and emotional needs of young children when appreciating and creating children's English picture books.
Dirichlet Simplex Nest and Geometric Inference.

We propose Dirichlet Simplex Nest, a class of probabilistic models suitable for a variety of data types, and develop fast and provably accurate inference algorithms by accounting for the model's convex geometry and low dimensional simplicial structure. By exploiting the connection to Voronoi tessellation and properties of Dirichlet distribution, the proposed inference algorithm is shown to achieve consistency and strong error bound guarantees on a range of model settings and data distributions. The effectiveness of our model and the learning algorithm is demonstrated by simulations and by analyses of text and financial data.
A 3D Finite Radon Transform

The present work is devoted to the development of the extension of FRT (Finite Radon Transform) to the tridimensional case.One simple formulation is proposed and it is shown that it is the exact discretization of the continuous Discrete Radon Transform.More precisely this is the case when the sampling is given on a regular grid i.e. the continuous function is filtered by the mean of the box function.Relation of this transform with the Discrete Fourier one is given and is for some help in numerical implementation.
Avaliação do programa de Primeiros Socorros em Saúde Mental em estudantes de licenciatura em enfermagem

Background: The Mental Health First Aid (MHFA®) educational program has the potential to increase mental health literacy, reduce personal stigma, and empower individuals for their mental health. Objective: To evaluate the impact of MHFA training program in undergraduate nursing students. Methodology: Pre-experimental study, with a single group design, pre- and post-intervention assessment, applied to a sample of 46 undergraduate nursing students. The Questionnaire for Assessment of Mental Health Literacy was applied as a data collection tool. The data were analyzed using the IBM SPSS V24.0 and G-Power 3.1 software programs. Results: At the end of the program, students showed an improvement in all components of mental health literacy about depression, increasing their confidence to provide first aid. Conclusion: The program proves to be an adequate tool for increasing the mental health literacy of nursing students
Development of Motion Learning Media and Energy Conservation Law Through Coaster Tracks Based on Logger Pro Analysis

Research has been conducted to find out relation position and speed to time, for objects that glide on a magnetic foundation by applying the Research and Development method. Data retrieval is done by using video train motion recordings which are analyzed using Logger Pro. The results of the analysis are represented in the form of data and graphics. Based on the data analysis and fitting using the Logger Pro, the following values are obtained: vtrain 0.027 m/s, atrain 0.034 m/s2, average train velocity 0.02572 m/s and average train acceleration 0.03662 m/s2 with RMSE (Root Mean Square Error) value of 0.013 m. The acceleration value obtained is very small and almost close to zero, so it can be said that objects that experience irregular straight motion. The graph representation of velocity over time shows an increase in speed that is not constant. This is because there is still friction between the train and the runway and friction between magnets along the track with friction forces 4,566 N. The value of kinetic energy, potential energy, and mechanical energy can be determined by using the results of Logger Pro analysis.Telah dilakukan penelitian untuk mengetahui grafik keterkaitan posisi dan kecepatan terhadap waktu, untuk benda yang meluncur di atas landasan magnetik dengan menerapkan metode Research and Development. Pengambilan data dilakukan dengan menggunakan video rekaman gerak kereta yang dianalisis menggunakan Logger Pro. Hasil analisis direpresentasikan dalam bentuk data dan grafik. Berdasarkan analisis dan fitting data menggunakan Logger Pro diperoleh nilai sebagai berikut vkereta 0,027 m/s, akereta 0,034 m/s2, v rata-rata kereta 0,02572 m/s dan arata-rata kereta 0,03662 m/s2 dengan nilai RMSE (Root Mean Square Eror) sebesar 0,013 m. Nilai percepatan yang diperoleh sangat kecil dan hampir mendekati nol, sehingga dapat dikatakan bahwa benda mengalami gerak lurus beraturan. Representasi grafik kecepatan terhadap waktu memperlihatkan pertambahan kecepatan yang tidak konstan. Hal ini dikarenakan masih terdapat gesekan yang terjadi antara kereta dengan landasan maupun gesekan antar magnet di sepanjang lintasan dengan gaya gesek 4,566 N. Nilai energi kinetik, energi potensial, dan energi mekanik dapat ditentukan besarnya menggunakan data hasil analisis Logger Pro.
Five Classification of Mammography Images Based on Deep Cooperation Convolutional Neural Network

Mammography is currently the preferred imaging method for breast cancer screening. Masses and calcification are the main positive signs of mammography. Due to the variable appearance of masses and calcification, a significant number of breast cancer cases are missed or misdiagnosed if it is only depended on the radiologists’ subjective judgement. At present, most of the studies are based on the classical Convolutional Neural Networks (CNN), which uses the transfer learning to classify the benign and malignant masses in the mammography images. However, the CNN is designed for natural images which are substantially different from medical images. Therefore, we propose a Deep Cooperation CNN (DCCNN) to classify mammography images of a data set into five categories including benign calcification, benign mass, malignant calcification, malignant mass and normal breast. The data set consists of 695 normal cases from DDSM, 753 calcification cases and 891 mass cases from CBIS-DDSM. Finally, DCCNN achieves 91% accuracy and 0.98 AUC on the test set, whose performance is superior to VGG16, GoogLeNet and InceptionV3 models. Therefore, DCCNN can aid radiologists to make more accurate judgments, greatly reducing the rate of missed and misdiagnosis.
Assessment of Hourly Solar Direct Normal Irradiance using Eight Broadband Clear Sky Models: Study of Four Moroccan Arid Sites

This paper presents a statistical comparative study of eight important parametric broadband clear sky models, against Meteosat-derived data, to estimate solar hourly direct normal irradiance (DNI) for four Moroccan arid zone sites. To achieve this aim, four sites well spread across this climatic zone were selected, and four references days were chosen. The statistical parameters such as relative mean bias error (rMBE), the relative root mean square error (rRMSE), and the determination coefficientÂ are calculated. According to these results, the Bird model produces acceptable estimates with 62.5% of good results of rMBE ranging between 0 and 6%; 25% of average results of rRMSE ranging between 11% and 14%, and 62.5% of good results of ranging between 0.90 and 0.96. The comparison of both means of DNI, calculated and measured for a given site and day of reference, using the paired t-test, states that for a level of significance of 1%, the Bird model and the REST2 model give in the quarter of the studied cases conforming means of hourly DNI. For a level of significance of 0.1%, the Bird model is more proficient and gives conforming means in almost half of the cases studied. Despite all these performances displayed by the Bird Model, it remains average and does not reach the required level in some sites at certain times. The elaboration of a new simpler DNI estimation model giving higher performances for this zone of high solar potential is of great interest.
Angel or Demon? Characterizing Variations Across Twitter Timeline of Technical Support Campaigners

Technical Support spam, which abuse Web 2.0 and carry out social engineering attacks have been in existence for a very long time, despite several measures taken to thwart such attacks. Although recent research has looked into unveiling tactics employed by spammers to lure victims, damage done on Online Social Networks is largely unexplored. In this paper, we perform the first large-scale study to understand the behavior of technical support spammers, and compare them with the legitimate technical support offered to OSN users by several brands such as Microsoft, Facebook, Amazon.We analyze the spam and legitimate accounts over a period of 20 months, and provide a taxonomy of the different types of spammers that are active in Tech Support spam landscape. We develop an automated mechanism to classify spammers from legitimate accounts, achieving a precision, recall of 99.8%.Our results shed light on the threats associated with billions of users using OSNs from Tech Support spam, and can help researchers and OSN service providers in developing effective countermeasures to fight them.
Tests measure progress of quantum computers

Designers propose benchmarks and metrics for not-yet-useful machines.
DEVELOPMENT OF THE ADULTS’ SUBJECTNESS ACTIVITY IN FACEBOOK

The article deals with various aspects of subjectness activity development in social networks, Facebook in particular. The definitions of the following concepts are given: "subject", "subjectness", "levels of subjectness activity", "subjectness activity", "structural organization of the subjectness activity", "representative subjectness". The components of the subjectness structural organization, the level of its manifestation and related phenomena are analyzed. The structural organization of the self-development subjectness (activity) is defined: formation and achievement of personal goals, motivation to self-development; intellectual initiation (reflection and introspection, determination of thinking) and other metacognitions; self-sufficiency; social activity; freedom of choice and responsibility for it; initiative; self-realization; communicativeness, predictive thinking. A special role of self-development subjectness facilitated by self-design and development of intelligence, as factors of subjectness activity and existence of subjectness in general, is noted. A questionnaire on the subjectness activity level of social networks users was developed. The technologies of forming the subjectness activity of Internet users in the form of Internet training were developed and described. The experimental study "Internet training on the subjectness activity development of adult social networks users" was conducted in two phases. The average value of subjectness activity level of different groups of Internet users was determined. It was confirmed that the development of subjectness activity of adult users of social networks corresponds to the level of their motivation to self-development and development of intellectual initiation, as well as other intellectual metacognitions. The main advantages and limitations of online trainings in social networkswere described. The prospects for further research of subjectness and subjectness activity were presented.
VETUS - Visual Exploration of Time Use Data to Support Environmental Assessment of Lifestyles.

The time-use (or activity) patterns individuals perform on a typical day – their individual lifestyles – fundamentally shape our society and the environment we live in. Not only are lifestyles evolving over time, driven by societal and technological change, they also significantly contribute to the achievement of Sustainable Development Goal 12 “responsible consumption and production”, namely through the resource use and emissions associated with goods and services consumed to perform activities. We created an interactive, browser-based tool to visualize and intuitively explore statistical time-use data. The visualization helps to gain an overview about the available data, identify and compare common time-use patterns and draw up hypotheses about the relationship between changes in lifestyles and their social and environmental consequences. We use the tool to compare time-use data from different regions, time periods as well as socio-economic and demographic backgrounds and estimate the associated energy consumption. From a time-use perspective, any technological change which triggers changes in time allocation can only be environmentally sustainable if the environmental impact of the total of the activities performed after the change is lower than before.