Reviewerly/exHarmony huggingface dataset:
Exploiting Human Cognitive Architecture to Design a New Cultural Narrative for Non-captive Audiences: The TOURiBOOST Project

Heritage settings generate often a spatiotemporal gap between the object and the audience, as the tangible form is perceivable by the eye, but the meanings are codified. This particular condition, further supported by cultural and mentality differences, impedes non-captive audiences to fulfill satisfactory experiences. Following Aristotelian hermeneutics we defend that the spatio-temporal gap in heritage settings is of cognitive nature. Thus, to understand and embrace heritage values and effectively bridge the gap between the object and the observer, we need to link the audience to heritage meanings and values. The supply side, is often unaware of the human cognitive architecture, thus narratives and descriptions stay codified in the expert language, while the demand side is looking for compelling stories and multisensory experiences. The still ongoing ERASMUS + Project 2018-1-TR01-KA203-058344 (TOURiBOOST) for Higher Education builds an attempt to design and test a knowledge acquisition pattern for non-captive audiences from a human cognitive architecture point of view. In this vein, we present the design for the production of a multimedia iBook presenting 30 heritage places in TR/HU/NL/IT/GR with the principal aim to create the enabling environment for both onsite and dislocated audiences to engage in critical thinking and inspire them to replace gazing and clicking with cognition and emotions.
Collecting unification and presentation of multimedia content and product configurations in multilingual product catalogs

This article describes the issue of multimedia content presentation in product catalogs. The article is focused on unification of multimedia resources, their preprocessing and subsequent presentation in unified form. It discusses the issue of descriptive metadata, which serves to unify the naming of identical or very similar property values that manufacturers give different names, especially for better marketing support. Furthermore, the article focuses on the issue of creating configuration trees for the sale of new cars across various automakers. A system for unifying parameters and their values for pairing comparable resources is described, including the definition of dependencies and conditional configurations. Possibilities of their presentation and updating using publicly available data sources are discussed. The ways of multimedia presentation and configuration trees are presented on a real car demand project.
PHOTOGENIC – A Tool for Best Photo Generation from Multiple Group Photographs

Cameras play an important role in capturing precious moments of people's lives in a photograph that can be seen and cherished by them or by their loved ones any time in their lives. This makes it imperative to have a perfect photograph which can describe that moment well. However, it is very difficult to time and capture a group photograph where everyone is looking their best. There are instances when multiple group photos are taken but in one of the photographs a particular person might have his/her eyes open and is smiling whereas someone else's eyes are closed because he/she was blinking. However, in another photograph that person has his/her eyes closed or is not smiling but rest of the people look good. Whatever the case may be, it becomes very difficult to have one perfect group photograph. Thus, if we can pick and blend the good facial features of each person from these multiple photos and merge into a single photo, we can get a better resultant group photograph with the best of their facial features in it. To do this, one could use softwares like Abode Photoshop or other such image editing tools. However, it requires the user to be well versed with that software and demands a lot of effort and user's valuable time to correct the photographs. To make this process easy and better, we have developed a tool that uses OpenCV at its core and follows a sequence of steps for generating the best photograph out of multiple group photographs clicked at a particular instance. By using this tool one can effortlessly get the best group photograph where everyone is smiling with their eyes open.
Impact Analysis of Order of Presentation on Champion Book Decision in Bibliobattle

This paper analyzes the degree of influence of the presentation order on the voting behavior of participants in the book review game, Bibliobattle, and examines ways to reduce this influence. We collected and analyzed the data of Bibliobattle games that were spontaneously conducted in various places, and this method was applied to research other communication-field mechanism designs. We classified the results of approximately 800 Bibliobattle games collected from the Internet by the order of presentation. Subsequently, we compared the number of Champion Book awards secured by the first and second, and last and last but one in the presentations when compared to others in the presentation order. Consequently, the possibility of the first and second presenters acquiring a Champion Book award has a detrimental effect on the other presenters in the order. Conversely, the possibility of the last and second-last presenters acquiring a Champion Book award is advantageous for the other presenters in the order. We considered the possibility that the response order effect influences voting in the Bibliobattle game. Also, by performing the voting process in the reverse order of the presentation, we examined the way to reduce the influence of the response order effect.
System for Efficient Storage and Version Control of Arbitrary File Collections

Many modern version control systems are designed to store program source code and provide an extensive functionality for this field of activity. This article describes an approach towards applying general version control concepts for storage of arbitrary file collections. The goal of this work is creation of a version control system that is applicable for storage of arbitrary file collections, performs a more efficient storage of frequently changed files and uses a more generic approaches towards version control, compared to version control systems of source code. Main concepts along with general algorithms of described system are presented in this paper. This paper also describes main applications of developed system and its system requirements.
Linear Complexity of Generalized Cyclotomic Sequences of Order 4 over <mml:math xmlns:mml="http://www.w3.org/1998/Math/MathML" id="M1"><mml:mrow><mml:msub><mml:mrow><mml:mi mathvariant="double-struck">F</mml:mi></mml:mrow><mml:mrow><mml:mi>l</mml:mi></mml:mrow></mml:msub></mml:mrow></mml:math>

Generalized cyclotomic sequences of period <mml:math xmlns:mml="http://www.w3.org/1998/Math/MathML" id="M2"><mml:mrow><mml:mi>p</mml:mi><mml:mi>q</mml:mi></mml:mrow></mml:math> have several desirable randomness properties if the two primes p and q are chosen properly. In particular, Ding deduced the exact formulas for the autocorrelation and the linear complexity of these sequences of order 2. In this paper, we consider the generalized sequences of order 4. Under certain conditions, the linear complexity of these sequences is developed over a finite field <mml:math xmlns:mml="http://www.w3.org/1998/Math/MathML" id="M3"><mml:mrow><mml:msub><mml:mrow><mml:mi mathvariant="double-struck">F</mml:mi></mml:mrow><mml:mrow><mml:mi>l</mml:mi></mml:mrow></mml:msub></mml:mrow></mml:math>. The results show that, in many cases, they have high linear complexity.
Analyzing dissipation effects on the non-classicality witnessing by a qubit via the entangled state representation

In this paper, we study detection of the state non-classicality for a quantum harmonic oscillator by a qubit in the presence of dissipation effects. We show that dissipation can enhance the effectiveness of the method in case of using the corrected form of the related nonclassicality witness. Such an improvement is attributed to the fact that dissipation leads to probing a surface, instead of a curve, of the complex plane for non-classicality condition on normally-ordered characteristic function.
Contexts for Linguistic Investigative Advice

Drawing together all the previous chapters, Chapter 6 explicates the ways in which forensic linguistics can continue to provide support to the work of undercover online officers. Breaking down traditional constraints that have seen the work of the forensic linguist in this area limited to authorship analysis tasks, we sustain the argument here that we can usefully contribute to the strategy of authorship synthesis. While there is enormous potential for linguistic contributions to these policing tasks of identity assumption and infiltration, there are, of course, limitations. Both are discussed in detail in this chapter.
Global Modal Space Control for a Hydraulically Driven Stewart Platform

This paper presents a global modal space controller for hydraulically driven Stewart platforms that has high control performance in a large overall workspace. The relationship between the modes and the platform position is analyzed employing perturbation theory. According to the principle of mode relativity, a new real-time mode-tracing algorithm is developed to resolve the mode-jumping phenomenon in the global workspace. Applying the proposed algorithm and combining dynamic pressure feedback correction, the global modal space controller of the parallel manipulator is estimated. Experimental results show the proposed controller has good performance and can broaden the bandwidth in the global workspace.
The Future of Face Recognition Technology and Ethico: Legal Issues

This chapter summarises the impact of face recognition technology on privacy and confidentiality and looks to the future of FRT in terms of its technical developments, and the main ethico-legal issues that may arise. Moreover, the use of FRT by commercial enterprises and governments is divergent when, opposing interests occur between the lawmakers and the public, and between the public and commercial enterprises. The future of FRT should, and to some extent shall, also be shaped by its ethical acceptability and legal regulation. Ultimately, an individual’s identity is intimately tied up with their face, and direct technological recognition by the facial contours will be a continuing issue of social concern and sensitivity.
Backward Design with Virtual Learning Ecosystem Model to Enhance Design Thinking and Innovation

The purposes of this study were: 1. to develop Backward Design with Virtual Learning Ecosystem Model to Enhance Design Thinking and Innovation, 2. to evaluate about the suitability of Backward Design with Virtual Learning Ecosystem Model to Enhance Design Thinking and Innovation by 3 Educational experts and 4 Information and Communication Technology for Education experts. The findings indicated that the Backward Design with Virtual Learning Ecosystem Model to Enhance Design Thinking and Innovation consists of 4 elements as follows: Input including 6 elements (1) objectives (2) lecturer (3) learner (4) hardware (5) software (6) network. Secondly, the process includes (1) goal (2) Identify desired results (3) Determine acceptable evidence (4) Plan learning experiences and instruction. Thirdly, output that is Summative Design Thinking skill and Innovation Learning achievement and innovation. Fourthly, Feedback that use to verify the mistake in each procedure. From the evaluate of Backward Design with Virtual Learning Ecosystem Model to Enhance Design Thinking and Innovation, It was found that the result of estimation about the learning model is proper in the highest level ($$ {\bar{\text{X}}} $$ = 4.67, S.D. = 0.47). It’s shown that it can bring that model to use for the development of ability, design thinking, and innovation.
Blve: Should the Current Software Version Be Suitable for Release?

Recently, agile development has become a popular software development method and many version iterations occur during agile development. It is very important to ensure the quality of each software version. However in actual development, it is difficult to know every stage or version about large-scale software development. That means developers do not know exactly which version the current project corresponds to. Simultaneously, there are many necessary requirements for software release in actual development. When we know exactly the version corresponding to the current project, we can know whether the current software version meets the release requirements. Therefore, we need a good software version division method. This paper presents a novel software version division method Blve by using machine learning method. We construct an accurate division model trained with Support Vector Regression method (SVR) to divide software version by processing the data which is commonly recorded in bug list. Then, we process the results of the regression and use the classification indicators for evaluation. In addition, we propose a slope-based approach to optimize the model, and this optimization can improve the accuracy performance measure to about 95%.
Evaluation of Navigation Commands Based on Conceptual Attributes to Enhance Human-Robot Interaction

Natural voice commands can be used as an interaction modality to improve assistive robots. Recent developments with voice modality have failed to model the unique attributes of human communication such as incompleteness, inconsistency, uncertainty and unpredictability. Human-human conversations are volatile with uncertainty and unpredictability. These attributes should be evaluated properly in order to design more robust natural vocal command model. Aside from the language attributes, there are other factors amounts to familiarity of vocal commands. Therefore in this paper, we evaluate the unique language attributes of vocal commands related to robot navigation and other factors affecting the human robot encounters. Human study was carried out in order to identify above attributes and understand the effect on navigation commands. Further experiments were conducted to understand the differences between human-robot and human-human conversations.
Succinct Representations in Collaborative Filtering: A Case Study using Wavelet Tree on 1,000 Cores

User-Item (U-I) matrix has been used as the dominant data infrastructure of Collaborative Filtering (CF). To reduce space consumption in runtime and storage, caused by data sparsity and growing need to accommodate side information in CF design, one needs to go beyond the U-I Matrix. In this paper, we took a case study of Succinct Representations in Collaborative Filtering, rather than using a U-I Matrix. Our key insight is to introduce Succinct Data Structures as a new infrastructure of CF. Towards this, we implemented a User-based K-Nearest-Neighbor CF prototype via Wavelet Tree, by first designing a Accessible Compressed Documents (ACD) to compress U-I data in Wavelet Tree, which is efficient in both storage and runtime. Then, we showed that ACD can be applied to develop an efficient intersection algorithm without decompression, by taking advantage of ACD's characteristics. We evaluated our design on 1,000 cores of Tianhe-II supercomputer, with one of the largest public data set ml-20m. The results showed that our prototype could achieve 3.7 minutes on average to deliver the results.
Machine Learning Techniques to Detect Fraud in Credit Cards on the HPCC Systems Platform

Credit cards, while convenient and attractive, are susceptible to frauds, leading to data and privacy breaches. Identifying fraudulent transactions in a cost effective and timely manner is a challenge for companies supplying these cards. Machine learning models provide an easy method to quickly identify anomalies in credit card transactions. In this paper, three models, Random Forest (Learning Trees), Long Short Term Memory and Convolutional Neural Networks on HPCC Systems distributed computing platform have been used to classify a series of transactions as ‘Fraudulent’ or ‘Non fraudulent’. Although all three models give outstanding results, Random Forests (Learning Trees) and Convolutional Neural Networks perform the best, with 0.99 precision, recall and F1 score.
It’s Time for Data! Modulations of Representation: Visible, Perceptible, Imaginable

“Representing is a transitive verb which demands an object” (Gombrich 1985, p. 214). But what are the possible modulations of this object? And, likewise, what is the extent of representation? These are the questions we have posed in carrying out a particular experiment: creating an infographic to give shape to a musical performance, String Quartet no. 10 Op. 74 by Ludwig van Beethoven. The experiment aims to combine knowledge and experience, logic and aesthetics, function and metaphor. By exercising these aspects, we would like to verify some of the possible extensions of representation with an approach that is at once modulated and synthetic, notational and systemic. The experiment has entailed considerations and reflections, requiring us to make some choices that will become as clear as possible in the paper’s development.
Application for Three-Dimensional Graph Data Visualization in VR

Data visualization is the best way to display information in easy-to-understand visual forms, such as line charts, graphs, pie charts, etc. Data Visualization has emerged in the pre-computer era, but many automated data visualization tools are now available. Now it's easier to use this way of displaying information, because all the work with data visualization in the form of graphics has been transferred to computing systems. The main purpose of data visualization is to present data in such a way that it is easy to understand what is presented and draw conclusions. To do this, the data is converted into visual information, because people are the easiest to perceive and process visual information (and well-designed visualizations use it [1] ).
Study of Smartcards Technology

Smart cards have gained popularity in many domains by providing different facilities in every domain. Such cards are beneficial for storing credentials and access information. The cards are easy to carry and provides easy and fast computations. The cards have certain limitations due to the possible attacks on them. This chapter gives an overview of the smartcards including its history, physical design, life cycle. It also provides an overview of the possible threats on smartcards and its application area.
Component Deformation Measurement Based on Point Cloud

For the problem of fuel rod bending and distortion, we independently developed a point cloud processing system based on monocular laser. The monocular laser device is used to obtain an outer edge contour image of the fuel rod, and the cross-sectional outer edge point cloud is processed based on the outer edge point. The cloud is adapted to the cross section and the fuel rod deformation is calculated based on the cross section. This article focuses on the use of cross sections to calculate fuel rod deformation and bending deformation. The method described in this paper is to obtain the outer cross-point of the fuel rod after using the upper and lower sets of monocular laser systems, and then use the total least squares method to fit the upper cross section and the lower cross section. The lower part of the point cloud data fitting part is used as the reference plane, and then the centroid displacement and the normal vector offset of the other cross sections relative to the reference plane are calculated. Finally, the two parameters are used to indicate the bending and twisting of the fuel rod.
Reliability Analysis of Fuzzy Bayesian Networks Based on Uncertain Ordered Weighted Operators

After analyzing the shortcomings of traditional fault tree analysis methods, a fuzzy Bayesian network reliability analysis method based on fault tree is proposed. This method of modeling uses the Bayesian method, the event polymorphism of complex systems is described by the node polymorphism expression feature of Bayesian network theory, and the uncertain logical relationship between events is described by the conditional probability table of Bayesian network. Based on the Bayesian model, the fuzzy set theory is introduced, and the experts fuzzy evaluation of event probability is described by triangular fuzzy numbers. In the evaluation information of the experts with uncertain weights, the expert evaluation information of the uncertain weights is calculated by using the uncertainty-ordered weighted average operator to calculate the expert weights, and finally the exact value of the occurrence probability of different states is obtained. Substituting it into the Bayesian network to calculate the probability of occurrence of different states of the leaf nodes, and then calculating the posterior probability of each root node and its importance.
Service-Oriented Modeling for Cyber Threat Analysis

The future of enterprise cyber defense is predictive and the use of model-based threat hunting is an enabling technique. Current approaches to threat modeling are predicated on the assumption that models are used to develop better software, rather than to describe threats to software being used as a service (SaaS). In this paper, we propose a service-modeling methodology that will facilitate pro-active cyber defense for organizations adopting SaaS. We model structural and dynamic elements to provide a robust representation of the defensible system. Our approach is validated by implementing a prototype and by using it to model a popular course management system.
Using cloud cover forecasts for estimating a solar powered vehicles' range

This paper investigates whether PV panels mounted on the roof of an EV will extend the range and if so, by how much. Further, Global Horizontal Irradiance (GHI) prediction was done, based on cloud cover and clear sky GHI. Regression techniques was used for the GHI prediction. It was concluded that PV panels on the roof of an EV will lead to a very small increase in range as the EV drives, where the charge gained as the EV is parked, has a more positive effect.
Light Field Video for Immersive Content Production

Light field video for content production is gaining both research and commercial interest as it has the potential to push the level of immersion for augmented and virtual reality to a close-to-reality experience. Light fields densely sample the viewing space of an object or scene using hundreds or even thousands of images with small displacements in between. However, a lack of standardised formats for compression, storage and transmission, along with the lack of tools to enable editing of light field data currently make it impractical for use in real-world content production. In this chapter we address two fundamental problems with light field data, namely representation and compression. Firstly we propose a method to obtain a 4D temporally coherent representation from the input light field video. This is an essential problem to solve that will enable efficient compression editing. Secondly, we present a method for compression of light field data based on the eigen texture method that provides a compact representation and enables efficient view-dependent rendering at interactive frame rates. These approaches achieve an order of magnitude compression and temporally consistent representation that are important steps towards practical toolsets for light field video content production.