Reviewerly/exHarmony huggingface dataset:
A key for John Doe: modeling and designing Anonymous Password-Authenticated Key Exchange protocols

Anonymous Password-Authenticated Key Exchange (\sf APAKEAPAKE) can be seen as the hybrid offspring of standard key exchange and anonymous password authentication protocols. \sf APAKEAPAKE allows a client holding a low-entropy password to establish a session key with a server, provided that the client's password is in the server's set. Moreover, no information about the password input by the client or the set of valid passwords held by the server should leak to the other party-beyond whether the client's password lies or not in the server's password database. To the best of our knowledge, all \sf APAKEAPAKE proposals to date either assume client storage or force the client to remember the index assigned to its password in the server's database. Furthermore, earlier works either provide only informal definitions or fail in some sense to properly model the primitive. In this paper, we provide a formal security model for \sf APAKEAPAKE, capturing security and anonymity provisions for both clients and servers. In addition, we present two \sf APAKEAPAKE protocols that only require clients to remember a password and that attain our sought key secrecy and anonymity guarantees. Our first protocol leverages oblivious pseudo-random functions, while the second one builds upon a special type of identity-based encryption scheme.
Satires, narratives and journalistic divides: Discourses on free speech in Western and Islamic news media

This study investigates how Western news media (The New York Times and BBC News) and Islamic news media (Al-Jazeera English and Al-Arabiya English) frame issues about freedom of expression and anti-Islamic sentiments, respectively, in the aftermath of the January 7, 2015, attacks on France’s weekly satirical newsmagazine, Charlie Hebdo. Results show a deep divide: that the Western news media, on the one hand, endorsed Charlie Hebdo’s right to offend religious sensitivities and lauded its role to protect the Western value of free speech; and that the Islamic news media, on the other, viewed the entire Western discourses as anti-Islam and anti-Muslim, emphasizing the need for good taste and professionalism in journalism.
Novel Experiment Design for Unmanned Aerial Vehicle Controller Performance Testing

Abstract Unmanned Aerial Vehicles (UAV) are becoming popular to the innovating world. This paper presents a novel experiment design to determine the performance of UAV control system. The hardware platform developed is composed of a quadcopter with a multipurpose autopilot system. While the experimental design considers both quantitative and qualitative aspects of the controller. The qualitative components dealt with the hardware compatibility, acceptability and license. On the other hand, the quantitative component measured the accuracy of waypoints, altitude hold and loiter performance of the UAV. The results shows that the new experiment design platform was able to compare two popular autopilot software in terms of performance and acceptability.
Use of Augmented Reality for the Simulation of Basic Mechanical Physics Phenomena

Abstract The augmented reality (AR), has been cataloged like the technology that will have greater penetration in the education sector in the second decade of the XXI century. According to the report horizon 2016, the first research of AR in education point out a positive impact, in collaborative learning and autonomous learning; because it allows potentiating reality with virtual information that can be supported in curricular contents. The present article exposes the development of a prototype with AR technology that simulates the uniform rectilinear movement and free fall of the subject of mechanical physics. The research is of technological development type. Included in three phases: Initially the functional and non-functional requirements were determined, then the architecture was designed using UML diagrams and finally the prototype was developed. As a result, we obtained a mobile prototype with AR with two functions, the first one allows to simulate the movement of a vehicle at a constant speed, the second allows to simulate the fall of objects that are being attracted by gravity. A technical feasibility study was carried out in which the prototype was installed in different mobile devices, without errors. It is concluded that AR has several characteristics that can be applied to educational environments to increase students’ motivation and make them live experiences that are limited access in classrooms.
Circular Bayesian classifiers using wrapped Cauchy distributions

Capturing the dependences among circular variables within supervised classification models is a challenging task. In this paper, we propose four different supervised Bayesian classification algorithms where the predictor variables follow all circular wrapped Cauchy distributions. For this purpose, we introduce four wrapped Cauchy classifiers. The bivariate wrapped Cauchy distribution is the only bivariate circular distribution whose marginals and conditionals are also wrapped Cauchy distributions, a property that makes it possible to define these models easily. Furthermore, the wrapped Cauchy tree-augmented naive Bayes classifier requires the definition of a conditional circular mutual information measure between variables that follow wrapped Cauchy distributions. Synthetic data is used to illustrate, compare and evaluate the classification algorithms (including a comparison with the Gaussian TAN classifier, decision tree, random forest, multinomial logistic regression, support vector machine and simple neural network), leading to satisfactory predictive results. We also use a real neuromorphological dataset obtained from juvenile rat somatosensory cortex cells, where we measure the bifurcation angles of the dendritic basal arbors.
Multilingual immersive communication technology: repurposing virtual reality for Italian teaching

T his paper will report on a pilot Virtual Reality (VR) project which repurposes an existing scenario-based VR asset for health sciences.The original scenario aims to prepare health care students for home visits by allowing them to experience a semi-linear conversation with a virtual Non-Player Character (NPC).This provides a safe, non-threatening environment for students to hone the necessary skills they will need once they begin their professional careers.The NPC's simulated emotional state and reactions are changed based on the student's choice of responses.The original scenario was written in English but the opportunity to convert it into an Italian language learning resource by changing the audio files was identified and implemented.The scenario involves learners to be recurrently selecting from a number of possible responses in order to help the virtual character with his grievances regarding his father's care package.
Using a Non-educational Mobile Game for Learning in Biology, Geography and Mathematics: Pokémon Go as a Case Study

ICT offers new perspectives in teaching and learning. In this paper a popular non-educational mobile game, “Pokémon Go”, is used as a background for the design of educational activities in Biology, Geography and Mathematics and as a means of informal learning. Five secondary level students (14–15 years old) participated in this study. Data were collected through observation, field notes and interviews. The participants described the activities as attractive, pleasant and creative and stated that there is a lack of engaging learning and technology use in school. The results show that an effective integration of mobile technologies can enhance learning and students’ attitude.
Contribution of mobile phones in expanding human capabilities in selected rural districts of Tanzania

Purpose This study aims to investigate the use of mobile phones in enhancing human capabilities and agricultural development among small-scale farmers in selected rural districts of Tanzania. The study assessed the potential capabilities acquired by farmers, factors that influence farmers in building their capabilities and achieving development outcomes. Design/methodology/approach The study used Sen’s capability approach as a guiding framework to investigate the link between mobile phones and agricultural development. A case study design was employed whereby focus group discussions were used to collect data. Findings The use of mobile phone services enabled rural farmers to build their financial, human and social capabilities. Rural farmers faced personal and non-personal conversion factors that influenced them in building capabilities and achieving development outcomes. The use of mobile phones led to various development outcomes. The typical development outcomes were related to access to information and communication services and reduction of transport costs. Rural farmers experienced family conflicts due to protectiveness exercised by couples through the use of mobile phones, criminal incidences such as theft and the fear of being recorded when making a phone call. Originality/value The study findings have the potential of influencing policy and practice. The findings are useful in promoting the value of mobile phones usage in empowering rural farmers and communities. The telecommunication sector and other key stakeholders can use the study findings in setting the basis for prioritising the improvement of telecommunication infrastructure in the rural areas.
3‐4: Stereoscopic Image Quality Assessment

Stereoscopic display technology provides immersive experiences in VR/AR/XR, but requires markedly higher bandwidth and is perceived differently than 2D content. Here we adapt the ISO/IEC 29170‐2 flicker paradigm for subjective assessment of low impairment stereoscopic image compression. We compared the performance VESA VDC‐M codec on stereoscopic images with 2D image performance.
Text Steganography Approaches Using Similarity of English Font Styles

Data protection has become a more critical issue and the necessity to secure a transmission channel is become more serious. Therefore, steganography, the art of hidden data into a digital media in a way that embed a secret message in the cover document without permitting anyone to suspect the data existence except the intended recipient, has become a relevant topic of research. The actual challenge in steganography is how it could obtain high robustness and capacity without damaging the cover document imperceptibility. This article presents two steganography approaches that based on the Similarity of English Font Styles (SEFS). This process has the main document font style replaced by a similar font style to embed the secret message after encoding it. This is done by using 1) the upper-case letters and punctuation marks of the carrier document or 2) the white space between words, start and end letters of each word that has more than 2 letters in the carrier document. These approaches are tested by being applied to various document formats with various font styles. From the findings, the secret message was vague to an antagonist and the stego-document size was increased and the capacity is very high. Also, the approaches are implemented using C# to develop a tool that hides a critical data in text document and the same findings were achieved.
PAxSPL: A feature retrieval process for software product line reengineering

Summary Software product lines (SPLs) are a well‐known solution to systematically create reusable software products. Among the approaches to create an SPL, the extractive approach is usually used when the organization already has a set of similar systems. These systems are analyzed to extract, categorize, and group their common and variant features throughout the SPL reengineering process. As there are different scenario variables, such as available artifacts and team experience, the activities and techniques used to perform these tasks may change. This may increase the effort and decrease the quality of retrieved features when users with low experience in SPL reengineering perform such tasks. However, there is a lack of a process supporting these tasks considering different scenarios. Therefore, we specify the P repare, A ssemble, and E x ecute Process for SPL Reengineering (PAxSPL), a process that provides support to prepare, assemble, and execute feature retrieval throughout the analysis of documentation and team experience. To initially evaluate PAxSPL, we conducted and reported an exploratory case study in a real development environment. The results indicated that our proposal helps in the assembly of a feature retrieval process according to user needs. Results were important to identify points for improvement in PAxSPL. We also could use the information gathered to improve the guidelines and provide this information to be used as basis of comparison for future users.
Exploring the implications of ‘low visibility’ specialist cyber-crime units

Using original data gathered within Australia, this paper argues that specialist cyber-policing units experience a pronounced level of low visibility within the police. This low visibility has three key dimensions. Firstly, there is low ‘vertical’ visibility as higher management and supervisors often have a limited understanding of the nature of the work and the needs of these units. Secondly, there is low ‘horizontal’ visibility as peers and colleagues within the wider organisation are similarly lacking in terms of their understanding of cyber-policing. The third dimension of low visibility concerns the external–internal visibility of the units as they relate to outside stakeholders including politics, media, the wider community and the judiciary. It is argued there is also a significant level of disinterest, disengagement and ignorance along this external–internal dimension. The implications of this ‘low visibility’ is explored and it is argued that there are consequences for the effectiveness of the units while also raising concerns around accountability and the overall prospects for progressive change.
Perfect Control for Right-Invertible Grünwald-Letnikov Plants–an Innovative Approach to Practical Implementation

A new perfect control algorithm dedicated to fractional-order right-invertible systems, i.e. plants with a greater number of input than output variables, is presented in this paper. It is shown that such a control strategy can be particularly applied with regard to practical tasks. Henceforth, the Grünwald-Letnikov difference operator Δα of an assumed order α can be truncated without loss of generality. For that reason, the so-called pole-free perfect control formula can be used to minimize the essential drawback of the Grünwald-Letnikov approach engaged, so as to define the intriguing issue regarding the robust perfect control for non-integer-order right-invertible LTI discrete-time state-space systems. Simulation examples show that the presented method can compete with a classical stable-pole one, for which the actual systems described by a fractional-order model often correspond with an inconvenient asymptotic perfect control solution given by the unlimited original operator Δα. In the end, the possibility of employing of author’s nonunique right inverses dedicated to nonsquare MIMO system matrices is demonstrated, thus giving rise to the introduction of a new powerful tool for robustification of non-integer-order closed-loop perfect control plants as well.
Augmented Reality Electric Circuit Experiment

The advancement of hardware technology, specifically in mobiles devices, has provided great computational power for running and creating sophisticated large programs such as, virtual reality, augmented reality and neural network based programs. Augmented reality (AR) is one of the finest and most exciting technologies nowadays. AR enables creating computerized objects and blending them with the real world. Which can be applied to enhance and simplify many aspects in a variety of disciplines. In result, instead of reading text and imagining experimentations it is possible to simulate the experiments through equipment and experiments as same as in real world scenarios, which can be much understandable and comprehensible. In the past decade, several institutions have adopted technological methods of teaching and learning. These instructional technologies can be used by some institutions that cannot provide enough time or proper equipment to students. This is where augmented and virtual reality are mostly favorable. In result, instead of reading text and imagining experimentations it is possible to simulate the experiments through equipment and experiments as same as in real world scenarios, which can be much understandable and comprehensible. In this paper, a model of an electric circuit is created to simulate the motion of electrons and how electric current runs through a wire and provides power for different tools. The creation of such a model involves design, modeling, simulation and animation of the model. This is done by relying on several software and frameworks such as Maya3D, Unity3D, ARKit, etc. .
A Generalized RNS Mclaughlin Modular Multiplication with Non-Coprime Moduli Sets

In this paper, we construct a generalized RNS McLaughlin modular multiplication with non-coprime moduli sets. We use a set of moduli that are non-coprime for RNS in the algorithm to take both the advantage of the fewer multiplications required for a modular multiplication in McLaughlin modular multiplication and the advantage of the moduli sets of similar sizes in classic Montgomery modular multiplication in RNS. This algorithm turns out to be scalable and simple for implementation. Formulas of parameters used for the construction of this algorithm are also presented in this paper.
Application of Data Mining Methods for Pattern Recognition in Negotiation Support Systems

Data mining methods have long been used to support organisational decision making by analysing organisational data from large databases. The present paper follows this tradition by discussing two different data mining techniques that are being implemented for pattern recognition in Negotiation Support Systems (NSSs), thereby providing process assistance to human negotiators. To this end, data from several international negotiation experiments via NSS Negoisst is used. Consequently, a suitable data representation of the underlying utility data and communication data has to be created for the applicability of data mining. Each generated data type needs individual processing treatments and almost all data mining methods lose their feasibility without a correct data representation as consequence. Once a correct data representation is found, the potential for pattern recognition in electronic negotiation data can be evaluated using descriptive and predictive methods. Whilst Association Rule Discovery is used as a descriptive technique to generate essential sets of strategic association patterns, the Decision Tree is applied as a supervised learning technique for the prediction of classification patterns. The extent to which reliable as well as valuable patterns can be derived from the electronic negotiation data and valuable predictions can be generated is examined in this paper.
A Study of Dispositions According to the IEEE Information Technology Curricula 2017 for German Industry and Student Population

The modern Computer Scientist has a set of desired skills and knowledge. Lately it has been recognized that there is a third dimension that ACM and IEEE call ”Disposition”. These are personal qualities (socio-emotional skills, behaviors, attitudes) associated with success in college and career and they should be listed as learning outcomes in modern curriculum design. In this paper we want to find out how far students gain the most important skills and dispositions in their studies. As a first step, local industry was asked which skills they think a Bachelor student needs in their daily work in order to determine the most important skills or dispositions. Subsequently, a survey was conducted that was based on these results in order to obtain students' viewpoints, including information on a specific course. They were asked to rank the skills from their point of view. In addition, they were specifically asked to comment on where they acquired the most important skills according to our industry ranking. Results show that the ranking differs from the one presented in the IEEE report both for industry and student responses. While industry and students agree mostly on the ranking, students report that the training of such skills is missing in industry but even more so at University.
Space-time volume visualization of gaze and stimulus

We present a method for the spatio-temporal analysis of gaze data from multiple participants in the context of a video stimulus. For such data, an overview of the recorded patterns is important to identify common viewing behavior (such as attentional synchrony) and outliers. We adopt the approach of space-time cube visualization, which extends the spatial dimensions of the stimulus by time as the third dimension. Previous work mainly handled eye tracking data in the space-time cube as point cloud, providing no information about the stimulus context. This paper presents a novel visualization technique that combines gaze data, a dynamic stimulus, and optical flow with volume rendering to derive an overview of the data with contextual information. With specifically designed transfer functions, we emphasize different data aspects, making the visualization suitable for explorative analysis and for illustrative support of statistical findings alike.
An Improved Opposition Based Grasshopper Optimisation Algorithm for Numerical Optimization

In this paper an improved optimization algorithm called Opposition Based Grasshopper Optimisation Algorithm (OGOA) is proposed. This is improved version of recently proposed Grasshopper Optimisation Algorithm (GOA), which mimics swarming behavior of grasshoppers in the living world. To improve the performance of GOA, Opposition based learning (OBL) is introduced in Grasshopper Optimisation Algorithm. The algorithm is tested on several numerical benchmark functions and is compared with some well known optimization algorithms.
SPL Features Quantification and Selection Based on Multiple Multi-Level Objectives

Software Product Lines (SPLs) can aid modern ecosystems by rapidly developing large-scale software applications. SPLs produce new software products by combining existing components that are considered as features. Selection of features is challenging due to the large number of competing candidate features to choose from, with different properties, contributing towards different objectives. It is also a critical part of SPLs as they have a direct impact on the properties of the product. There have been a number of attempts to automate the selection of features. However, they offer limited flexibility in terms of specifying objectives and quantifying datasets based on these objectives, so they can be used by various selection algorithms. In this research we introduce a novel feature selection approach that supports multiple multi-level user defined objectives. A novel feature quantification method using twenty operators, capable of treating text-based and numeric values and three selection algorithms called Falcon, Jaguar, and Snail are introduced. Falcon and Jaguar are based on greedy algorithm while Snail is a variation of exhaustive search algorithm. With an increase in 4% execution time, Jaguar performed 6% and 8% better than Falcon in terms of added value and the number of features selected.
P‐33: Effects of Luminance, Contrast and Saturation of HDR QLED Display on Visual System Based on Eye Movement

The effects of screen luminance, contrast and saturation of HDR video presented on QLED display on visual system were investigated. Results showed that contrast and saturation, rather than luminance, influenced visual neural systems controlling eye movements, and affected subjective display quality and viewing preference.