Reviewerly/exHarmony huggingface dataset:
Preface: Security &amp; privacy in social big data

This special issue assembles a set of 11 papers, which provide deep research results to report the advance of security and privacy technology in social big data. This preface provides overview of all articles in the viewpoint set.
Model transformations from the SARL agent-oriented programming language to an object-oriented programming language

SARL is a general-purpose agent-oriented programming language. This language aims at providing the fundamental abstractions for dealing with concurrency, distribution, interaction, decentralisation, reactivity, autonomy and dynamic reconfiguration that are usually considered essential for implementing agent-based applications. Every programming language specifies an execution model. In the case of SARL, this execution model is defined based on the object-oriented paradigm, i.e., the run-time environment is written in Java. Accordingly, and by default, the SARL programs are transformed into their equivalent object-oriented programs written in Java. The goal of this paper is twofold. Firstly, to explain the mapping between the agent-oriented paradigm and the object-oriented paradigm. Secondly, to define transformations from the SARL constructs to the Java constructs. We advocate that these goals enable the SARL developers to understand the SARL statements, and the mapping to the equivalent executable entities.
Partially Structure-Preserving Signatures: Lower Bounds, Constructions and More

In this work we first provide a framework for defining a large subset of pairing-based digital signature schemes which we call Partially Structure-Preserving Signature (PSPS) schemes. PSPS schemes are similar in nature to structure-preserving signatures with the exception that in PSPS schemes messages are scalars from \(\mathbb {Z}_p\) instead of being group elements. This class encompasses various existing schemes which have a number of desirable features which makes them an ideal building block for many privacy-preserving cryptographic protocols. Such schemes include the widely-used schemes of Camenisch-Lysyanskaya (CRYPTO 2004) and Pointcheval-Sanders (CT-RSA 2016). We then provide various impossibility and lower bound results for variants of this class. Our results include bounds for the signature and verification key sizes as well as lower bounds for achieving strong unforgeability. We also give a generic framework for transforming variants of PSPS schemes into structure-preserving ones. As part of our contribution, we also give a number of optimal PSPS schemes which may be of independent interest. Our results aid in understanding the efficiency of pairing-based signature schemes and show a connection between this class of schemes and structure-preserving ones.
Using Multi-granular Fuzzy Linguistic Modelling Methods to Represent Social Networks Related Information in an Organized Way

Social networks are the preferred mean for experts to share their knowledge and provide information. Therefore, it is one of the best sources that can be used for obtaining data that can be used for a high amount of purposes. For instance, determining social needs, identifying problems, getting opinions about certain topics, ... Nevertheless, this kind of information is difficult for a computational system to interpret due to the fact that the text is presented in free form and that the information that represents is imprecise. In this paper, a novel method for extracting information from social networks and represent it in a fuzzy ontology is presented. Sentiment analysis procedures are used in order to extract information from free text. Moreover, multi-granular fuzzy linguistic modelling methods are used for converting the information into the most suitable representation mean.
Enumerating Multiplex Juggling Patterns.

Mathematics has been used in the exploration and enumeration of juggling patterns. In the case when we catch and throw one ball at a time the number of possible juggling patterns is well-known. When we are allowed to catch and throw any number of balls at a given time (known as multiplex juggling) the enumeration is more difficult and has only been established in a few special cases. We give a method of using cards related to embeddings of ordered partitions to enumerate the count of multiplex juggling sequences, determine these counts for small cases, and establish some combinatorial properties of the set of cards needed.
Heterogeneous Dual-Task Clustering with Visual-Textual Information

Existing visual-textual cross-modal clustering techniques focus on finding a clustering partition of different modalities by dealing with each modality dependently or integrating multiple modalities into a shared space, which may results in unsatisfactory performance due to the heterogeneous gap of different modalities.Aiming at this problem, we propose a novel heterogeneous dual-task clustering (HDC) method, which is capable of exploring high-level relatedness between visual and textual data to improve the performance of individual task.Our intuition is that although the visual and textual data are heterogenous to each other, they may share related high-level semantics and rich latent correlations, which can lead to improved performance if we treat the clustering of visual and textual data as different but related learning tasks.Specifically, the problem of heterogeneous dual-task clustering is formulated as an informationtheoretic function, in which the low-level information in each modality and high-level relatedness between multiple modalities are maximally preserved.Then, a progressive optimization method is proposed to ensure a local optimal solution.Extensive experiments show noticeable performance of the HDC approach in comparison with several state-of-the-art baselines.
Open Source Augmented Reality Applications for Small Manufacturing Businesses

This paper evaluates the possibility of implementation of a low cost augmented reality application for machine maintenance in small manufacturing businesses. Here, an open source cross platform software development kit ARToolkit was chosen, since it offers a real time marker based tracking function. As hardware, the smart glasses R7 (ODG) and a handheld device (Samsung Galaxy S3) were considered. The application was tested on a typical milling machine used in a small size tool manufacturing company. For this purpose, its maintenance procedure was extracted from a paper-based documentation and the information provided by the workers. The AR assisted procedure was implemented using markers and an intern data server providing instructions via Wi-Fi. A maintenance demonstration was successfully performed both with a smartphone and a smart glass in the laboratory and machine hall environments.
Wide Field-of-View and high visibility 3D CG technologies for AR HUDs

We have been focusing on personalized immersive display for the next generation display for more than 10 years, as shown in Fig. 1.
A Selective Multi-feature Tracker based on Confidence

In order to improve the tracking speed of trackers with multi-feature fusion mechanism, and the tracking accuracy of trackers with boundary effects caused by circular shift, a confidence-based tracker which explores the selective multi-feature fusion mechanism is proposed in this paper. Firstly, a novel confidence degree is designed, which is used to evaluate the reliability of the predicted position of the HOG feature. Secondly, a selective multi-feature fusion mechanism based on confidence degree is proposed to improve tracking speed of trackers with multi-feature fusion mechanism. To reduce the boundary effects, the thought of background-aware based on HOG feature is employed, and it was extended to the color histogram feature. To prove the effectiveness of our tracker, we test our tracker on public datasets. The experimental results demonstrate that our tracker can improve performance in tracking accuracy and speed of tracker in the above challenges and the performance on the public datasets is better than several state-of-the-art trackers.
A APRENDIZAGEM VISANDO A COMPETÊNCIA EM INFORMAÇÃO NA SOCIEDADE EM TEMPOS DE INFOESFERA

Society historically incorporates the advances of society itself and thus reconfigures itself to benefit from this new spectrum. The information and knowledge society is the new social reconfiguration present in the 21st century. In this new society, it is not enough just to be literate, to learn how to read, to study in books for the exams, to know arithmetic and to be present at school. The current information society uses new learning resources that join or replace the previous ones, it does not discard the new technologies as a learning resource, and it demands of the citizen a new competence: information literacy. A citizen who is 'literate' in information and in the resources that allow access to and use of available information and knowledge, including new technologies, especially information and communication technologies.That is why the relationship between apprentice and learning is being reconfigured, and now it needs to develop the citizens to become information literate.And for them to be and remain information literate, it is not enough learning and understanding: a lifelong learning is necessary.
Handling Evolution in Big Data Architectures

One of the purposes of Big Data systems is to support analysis of data gathered from heterogeneous data sources.Since data warehouses have been used to achieve the same goal, they could be leveraged also to provide analysis of Big Data.The problem of adapting data warehouse data and schemata to changes in user requirements and data sources has been studied by many researchers worldwide.However, innovative methods must be developed also to support evolution in Big Data systems.In this paper, we analyze architectures designed for Big Data processing and analysis described in the literature with the purpose to identify the most appropriate solution for the evolution problem.We concentrate on four architecture types: data lakes, virtual integration, polystores, and λ-architecture, and, in addition to them, we consider solutions that apply data warehouse/OLAP methods to Big Data processing and analysis.Finally, we describe our proposal of an architecture that allows to perform different kinds of analytical tasks on Big Data retrieved from multiple heterogeneous data sources with different latency and is capable of processing changes in data sources as well as evolving analysis requirements.
Development of Digital Instruction as a Guide in Wushu Training

The instructional process should be based on principles, centered on the trainees, developing the creativity of trainees, creating fun and challenging conditions, developing a variety of value-rated capabilities, providing a diverse learning experience, and learning through doing.Technology has a positive effect not only on social life but also on education.The purpose of this study is to develop digital instruction as a guide in learning Wushu to improve skills.The methodology used was research and development.The instrument used was a questionnaire using the Likers scale.The instrument validation is carried out by media experts, design, and instructional materials.The results of the feasibility of this development that digital instruction based on expert validation has an average score of 92%, which means that the product is produced to be used.The effectiveness of results based on field trials with pre and post test results has increased by 1.5 units, meaning that this product is effective in improving skills.Based on validation and effectiveness test, digital instruction was very effective as a guide in learning Wushu.Digital instruction is a support for the training instructional process so that they can develop appropriate and innovative instructional media to facilitate trainees who participated.The impact of this study is that an innovative instruction can effectively improve skills of Wushu trainees.
Development of Histogram Equalization Hardware By High-level synthesis

High-level synthesis is a technology that converts a software program into hardware. High-level synthesis can greatly reduce the load of hardware design and development. An FPGA is a device that can implement any digital hardware at any time. The combination of high-level synthesis and FPGA has been attracting attention in the field of embedded devices where the life cycle of products is short and the demand for power-saving and high-performance products is high. High-level synthesis cannot convert pure software that describes the algorithm intuitively into high-performance and low-power hardware. High-level synthesis requires an input program that considers the hardware configuration in order to generate good hardware. In this paper, we develop hardware for histogram equalization to improve image contrast using high-level synthesis. In the description of the program, in addition to general methods such as fixed-point conversion, the description method we have developed is applied. Experimental results show that the histogram equalization hardware can achieve 2.3 times performance improvement compared to software implementation.
Software Security—Exploits and Privilege Escalation

Here we discuss known methods to exploit common security vulnerabilities in programs. The focus of software security (versus, e.g., security software) is exploitable software implementation errors and design flaws; this may be combined with abuse of a system’s architectural features and functionality.
Experimental Analysis of Selective Imitation for Multifactorial Differential Evolution

Recently, evolutionary multitasking optimization (EMTO) is proposed as a new emerging optimization paradigm to simultaneously solve multiple optimization tasks in a cooperative manner. In EMTO, the knowledge transfer between tasks is mainly carried out through the assortative mating and selective imitation operators. However, in the literature of EMTO, little study on the selective imitation operator has yet been done to provide a deeper insight in the knowledge transfer across different tasks. Based on this consideration, we firstly study the influence of the inheritance probability (IP) of the selective imitation on an EMTO algorithm, multifactorial differential evolution (MFDE), through the experimental analysis. Then, an adaptive inheritance mechanism (AIM) is introduced into the selective imitation operator of MFDE to automatically adjust the IP value for different tasks at different evolutionary stages. The experimental results on a suite of single-objective multitasking benchmark problems have demonstrated the effectiveness of AIM in enhancing the performance of MFDE.
Data Centre Colocation: Challenges and Opportunities in Private, Public and Hybrid Cloud for Businesses

Data center colocation service offers businesses rental space infrastructure for equipment rack, network servers, cooling, power, physical security and internet bandwidth; with 24/7 technical supervision for close to 100% uptime promise.Enterprise in-house data centres are getting increasingly expensive to build and maintain.Many colocation providers also provide managed hosting services and Business Process Outsourcing among other services.Data centre operators face challenges from public cloud providers, and suggestions are being explored for opportunities.This paper presents 3 cloud deployment models; namely private cloud, public cloud and hybrid cloud.The three-layer model of cloud computing; namely Infrastructure as a Service (IaaS), Platform as a Service (PaaS) and Software as a Service (SaaS) is also introduced and briefly discussed.Colocation players with a global footprint are seeing the benefits of offering business platform which can adapt to customer demand and making the most out of the cloud deployment a model.
Three-dimensional organ extraction method for color volume image based on the closed-form solution strategy

Abstract: With the rapid development of computer technology, surgical training, and the digitalized teaching of human body morphology are gaining prominence in medical education. Accurate, true organ models are essential digital material for these computer-assisted systems. However, no direct three-dimensional (3D) true organ model acquisition method currently exists. Thus, the direct extraction of the interested organ models based on the existing Virtual Human Project (VHP) image set is urgently needed. In this paper, a closed-form solution-based volume matting method is proposed. Using a small quantity of graffiti in the foreground and background, target 3D regions can be extracted by closed-form solution computing. The upper triangular storage strategy and the preconditioned conjugate-gradient (PCG) method also promote robustness. Four image data sets (2 virtual human male and 2 virtual human female) from the United States National Library of Medicine (including brain slices, eye slices, lung slices, heart slices, liver slices, kidney slices, spine slices, arm slices, vastus slices, and foot slices) were selected to extract the 3D volume organ models. The experimental results show that the extracted 3D organs were acceptable and satisfactory. This method may provide technical support for medical and other scientific research fields.
Pengaruh Perbedaan Jumlah Hidden Layer dalam Jaringan Syaraf Tiruan Terhadap Prediksi Kebutuhan Captopril dan Paracetamol pada Rumah Sakit

Research to predict drug needs at the hospital in Semarang. By using the data needs drug for 6 years from January 2007 to December 2012 made the prediction that the drug needs to avoid shortages or overstocks of drugs. The system is required to obtain the necessary amount of drug in a given month in order to avoid shortages of drugs and overstocks of drugs. This study uses matlab software to design the look and design a Neural Network architecture and using Microsoft Office Excel software to provide input data. Spreadsheet data model helps the program as input to the training data. Artificial Neural Networks provide interpretations of the drug needs. any incoming data given initial weight, is processed in the hidden layer using the specified parameters are like max epoch, learning rate, activation, duration, and the pace of learning. Parameters of success using the Mean Square Error and the value of the correlation coefficient is a point of reference. The results obtained using Neural Network architecture with a number of hidden layer neurons 50 and 75 managed to get the value of an accuracy of 74.89% for the type drug Captopril, then architecture using the number of hidden layer neurons to 20 and 15 types of drug Paracetamol resulted in 86.21%. The results obtained are very varied topography which influenced the shape or characteristics of the data and the amount of data being tested as a data input. More and more data is being tested affect the accuracy percentage.
Punteggiatura in rete: i puntini di sospensione nella comunicazione mediata dal computer

This paper presents a corpus-based study of the functions of ellipses in Italian computer-mediated communication (CMC). The research is rooted in a theoretical framework where Italian punctuation is globally assigned a communicative meaning and, more specifically, ellipses are interpreted as an interactive punctuation mark. I will show that, from a quantitative point of view, the frequency of use of ellipses in CMC is more than 30 times higher than in standard writing. This is not due to the simple imitation of non-communicative prosodic features of spoken language, which is rare and restricted to chat interactions. Most uses of ellipses in CMC have a communicative meaning and can be classified either as: a) interactive uses, which are boosted by the inherent dialogic interactivity of CMC and aim at the construction of a socio-cognitive common ground between writer and reader(s); or as b) desemanticized uses, where ellipses lose their interactive meaning and retain only a basic segmentational function, akin to that displayed by the period in standard writing.
High-speed fringe projection for robot 3D vision system

The design, manufacture and test of a custom-made phase mask for use in a high-speed fringe projection system is presented. The mask produces a controlled anisotropic point spread function (PSF) that blurs binary fringes parallel to the fringe direction, to produce high quality greyscale patterns at up to the maximum projection rate, 22,000 frames s-1, of the DMD (Digital Micromirror Device)-based projector. The paper describes the numerical design method based on a binary scatter plate; a polychromatic Fourier optics model to predict the device’s optical performance; a method to design the fringe patterns; the manufacturing process, based on photolithography and reactive ion etching; and experimental validation of the phase mask performance. Noise in the computed height-encoding phase maps is found to be just 22% higher than for 8-bit greyscale fringe patterns produced by traditional temporal integration through a sequence of bit planes, but the projection rate is increased by over two orders of magnitude.
THE ROLE OF CONTINUING EDUCATION IN THE FORMATION OF THE ACADEMIC CULTURE OF TEACHING STAFF IN HIGHER EDUCATIONAL INSTITUTIONS

The thesaurus of academic culture is analyzed, the analysis of value-based social educational and scientific orientations of social categories of professionally interested teachers in prolonged employment throughout life is carried out; a semantic systematic analysis of the structure and content of cultures of the conditioned relationships between a person and society, future teachers and poly profile professional environments of their implementation and employment is carried out; a semantic systematic analysis of the structure and content of cultures of the conditioned relationships between a person and society, future teachers and poly profile professional environments of their implementation and employment is carried out; the role of ecological culture in ensuring the sustainability of social development of the noospherological paradigm of scientific knowledge is substantiated.
MODALITAS DALAM TEKS BERITA HOAKS: KAJIAN LINGUISTIK SISTEMIK FUNGSIONAL

This study aimed to examine the use of modality in news text. This research expected to improve public media literacy in identifying hoax news through modality analysis. This research presented qualitative descriptive data with systemic functional linguistic approach. This study focused on type, value, and modality orientation. The research data resource was Hoax Report of Legislative and President Election Internet Content Control Sub-directorate for the period of August 2018 by Ministry of Communication and Information of Republic Indonesia. The research result showed that modality type possibility modalization intermediate degree and modulity type obligation modulation intermediate degree to dominate other types of modality. There were also types of modality that were not found in hoax-text news. They were modality type of usuality modalization of medium degree and modality type of inclination modulation of low degree.