Reviewerly/exHarmony huggingface dataset:
BeaCON - A Research Framework Towards an Optimal Navigation

In an optimally integrated HMS (Human Machine System), human must understand the machine as well as the machine must understand the human user. Same principle applies for car NS (Navigation System) which is a human-in-the-loop system. An ideally integrated NS knows how, when and what navigation information must be provided for the user and create minimal interruption for the primary task. To do the same, NS must hold the behavioral models of the user for providing the guidance information in an effective way. A research framework which uses these principles, is needed to create such models as well as for conducting further analysis for the research problem of “Giving the driver adequate navigation information with minimal interruption”. Until now no such research framework exists and because of that further analysis of the mentioned research problem cannot be conducted. In this paper we present the research framework BeaCON: Behavior-and Context-Based Optimal Navigation that enables detailed analysis of this research problem.
Sample Value Ordering for Audio Reversible Data Hiding

Pixel value ordering (PVO) was shown to be an efficient technique for high-fidelity reversible data hiding in images. This paper proposes an audio reversible data hiding scheme inspired by PVO, namely sample value ordering (SVO). Large uniform areas are uncommon in natural images, but sections of silence are relatively common in audio samples. In order to properly exploit the nature of the host audio file, a block-based approach is employed. Non-overlapping blocks are classified into three categories: smooth, somewhat complex and complex. All samples from a smooth block are considered as possible hosts using a classic histogram shifting based approach. For somewhat complex blocks, only the maximum and minimum sample values are used for data hiding with the PVO inspired SVO. Complex blocks remain unchanged.
Usability Testing of Bank of China Automatic Teller Machine

The objective of this study is to evaluate the usability of Automatic Teller Machine (ATM) of Bank of China (BOC). Several experiments were designed to identify the reasonability and validity of existing product's navigation and its usability. Eight users, ages twenty to forty participated in the study. Response measures included System Usability Scale (SUS), questionnaire according to Leventhal and Barnes Usability Model and an interview.
Exploring the Value of Shared Experience in Augmented Reality Games

Augmented reality (AR) games have provided positive, fun, and enjoyable user experiences in various ways. While these experiences are mostly oriented to single users, AR technology naturally supports face-to-face interaction, so it is valuable to take into account shared experience in sketching game scenarios, designing user interfaces and interaction schemes, and developing technical features. In this study, we explore a novel shared experience by designing a compelling user journey and good affordance in a game called SHYGER, which is a new type of AR game interacting with 3D real objects. We also report a user study and discuss how the shared AR experience could improve the overall user experience and satisfaction.
Two-Factor Decryption: A Better Way to Protect Data Security and Privacy

Abstract Biometric information is unique to a human, so it would be desirable to use the biometric characteristic as the private key in a cryptographic system to protect data security and privacy. In this paper, we introduce a notion called two-factor decryption (TFD). Informally speaking, a TFD scheme is a variant of the public-key encryption (PKE) scheme. In a TFD scheme, messages are encrypted under public keys as that in a standard PKE scheme, but both private keys (i.e. the first factor) and biometric inputs (i.e. the second factor) are required to decrypt the ciphertexts and obtain the underlying plaintexts. We first describe a framework of TFD, and then define a formal security model for TFD. Thereafter, we present a generic construction on TFD based on the cryptographic primitives of linear sketch and functional encryption (FE) with certain properties and analyse its security. In addition, we give instantiations of TFD by applying concrete FE schemes into the generic construction and show their applications.
Optimization of an Oil Refinery Valuation System Through the Intuitionistic Fuzzy InterCriteria Analysis

In this paper, an extended form of three-dimensional intuitionistic fuzzy intercriteria analysis (3-D ICrA) is proposed and applied to analyze a dataset gathered through the staff evaluations of a catalytic oil refinery installation in Bulgaria over a three-year period. The 3-D ICrA is applied in order to reduce the set of staff assessment criteria in a refinery, taking into account the fact that their large number increases the time and cost of the staff evaluation process. The ICrA is one of the recently proposed approach for multicriteria decision making, combining the classical correlation analysis and the fuzzy logic. The approach is based on the concepts of index matrices (IMs) and intuitionistic fuzzy sets (IFSs), defined by Atanassov. The main contribution of the paper is that it illustrates the effectiveness of the proposed method to optimize the staff rating system of the catalytic oil refinery installation in Bulgaria. The open dependencies between the evaluation criteria will lead to optimization of the company’s staff rating system by removing part of these criteria and will support the decision-making process related to the motivation of human resources. The results, obtained using this approach are compared with those of the application of ICrA, Pearson’s (PCA), Spearman’s (SCA) and Kendall’s (KCA) rank correlation analysis. The results of applying these four statistical correlation analyzes to the actual data are almost identical.
The Utility of Digitally Supported Manual Interactive Mockups

By a longitudinal account of applications of one Wizard-of-Oz supporting tool, Ozlab, this paper highlights the utility of such tools beyond ordinary design evaluation. The Wizard-of-Oz method does not only allow for performing user test evaluation of interaction designs not yet programmed. Rather, the versatility of a digital but manually controlled prototype allows for many combinations of who determines the mocked up system’s responses and who acts as the prototypical user. It also supports co-design in that users will be presented interactive substantiations of their suggestions as the co-design sessions proceeds.
Encoding Reversing Petri Nets in Answer Set Programming

Reversing Petri nets (RPNs) have been proposed as a reversible approach to Petri nets, which allows the transitions of a net to be reversed. This work presents an approach towards an implementation of RPNs to support their simulation and analysis. Specifically, we define how to model RPNs in Answer Set Programming (ASP), a declarative programming framework with competitive solvers. We highlight how the methodology can be used to reason about the behavior of RPN models.
Content-Based Exploration of Archival Images Using Neural Networks

We present DAIRE (Deep Archival Image Retrieval Engine), an image exploration tool based on latent representations derived from neural networks, which allows scholars to "query" using an image of interest to rapidly find related images within a web archive. This work represents one part of our broader effort to move away from text-centric analyses of web archives and scholarly tools that are direct reflections of methods for accessing the live web. This short piece describes the implementation of our system and a case study on a subset of the GeoCities web archive.
Intuitionistic Fuzzy Assessments of the Abdominal Aorta and Its Branches

The human body is an open stationary system and has different adaptation mechanisms in changing conditions of the external and internal environment. In this aspect there is no exception to the circulatory system, respectively the arteries of the lower limbs. The narrowed or blocked arteries reduce blood flow to the lower limbs. In this case, the blood flows through the smaller blood vessels and the anastomoses (connections) between them above and below the thrombosis of the main vessel. In this research, an approach using an intelligent tool for analyzing data through fuzzy logic is presented. The intuitionistic fuzzy assessments for the blood supply evaluation of the lower limbs with peripheral artery disease are suggested. The permeability of the artery is within a certain range, limited by the minimum and maximum thresholds. The intuitionistic fuzzy evaluations determine the degree of permeability of the artery. They are formed on the basis of a set of intuitionistic fuzzy estimations $$ \left\langle {\mu ,\nu } \right\rangle $$ of real numbers from the set [0, 1] × [0, 1].
Local Q-Convexity Histograms for Shape Analysis

In this paper we propose a novel local shape descriptor based on Q-convexity histograms. We investigate three different variants: (1) focusing only on the background points, (2) examining all the points and (3) omitting the zero bin. We study the properties of the variants on a shape and on a texture dataset. In an illustrative example, we compare the classification accuracy of the introduced local descriptor to its global counterpart, and also to a variant of Local Binary Patterns which is similar to our descriptor in the sense that its histogram collects frequencies of local configurations. We show that our descriptor can reach in many cases higher classification accuracy than the others .
Designing an Augmented Reality Exhibition: Leonardo's Impossible Machines

This paper discusses the origins, development and results of the animated and augmented reality aspects of the exhibition 'Leonardo's Impossible Machines' that was developed at Ravensbourne University (London) and Birkbeck, University of London, with support from the Museo Galileo.The exhibition included novel reconstructions and visualisations of Leonardo's perpetual motion machines from the Codex Forster, and the process is explained here, along with the challenges of mounting a combined physical and AR show.
A consensual dataset for complex ontology matching evaluation

Abstract Simple ontology alignments, largely studied in the literature, link one single entity of a source ontology to one single entity of a target ontology. One of the limitations of these alignments is, however, their lack of expressiveness, which can be overcome by complex alignments, which are composed of correspondences involving logical constructors or transformation functions. While most work on complex ontology matching has been dedicated to the development of complex matching approaches, there is still a lack of benchmarks on which the complex approaches can be systematically evaluated. The aim of this paper is to present the process of constructing the consensual complex Conference dataset, describing the design choices and the methodology followed for constructing it. We discuss the issues the experts were faced with during the process and discuss the lessons learned and perspectives in the field.
Cultural Discourse in User Interface Design: Investigating Characteristics of Communicators in Microsoft Word

This paper addressed cultural factors in user interface design. Specifically, it took the words and symbols in the user interface as a discourse, and analyzed the characteristics of the communicator who created such discourse under the frame of cultural discourse studies created by Shi-xu (2015). The characteristics of communicators were revealed diachronically in a series of Microsoft Word versions through the content, forms of communication, and historical relations of the user interface discourse. The influence of Microsoft Word user interface design on other word processors such as Jinshan WPS was also investigated. Results showed that the typical words and/or symbols in the Microsoft user interface were the most frequently elements of English documents and were listed according to western thinking method. It seems that the word processors in other cultures tended to copy the form and content of the design of Microsoft Word without taking their cultural differences into consideration. How to use cultural discourse studies to design a user-centered interface was discussed.
Semantic Segmentation of the Growth Stages of Plasmodium Parasites using Convolutional Neural Networks

A child under five dies of malaria every two minutes. Limited access to diagnosis and treatment are some of reasons for this large death toll. Currently, the standard method of diagnosing malaria is manual microscopy which is expensive, tedious and prone to errors. This research proposes semantic segmentation of the growth stages of the Plasmodium parasites to aid effective diagnosis. By employing data augmentation and transfer learning, the proposed method achieved an accuracy of 85.86% on dense predictions of trophozoites, gametocytes and normal cells using 353 Giemsa-stained thin blood smear images.
The Effect of Time Pressure and Task Difficulty on Human Search

In order to study the effect of time pressure and task difficulty on human search performance, an experimental study was conducted. Thirteen people participated in the experiment. The time pressure is changed by changing the presentation time of the target information on the display. The task difficulty is changed by changing the number of the target information displayed on the computer display. Subjects' reaction time (RT), accuracy rate and eye movement data were recorded during the experiment. The results show that the subjects' reaction time decrease and accuracy rate increase. The subjects' reaction time increased and accuracy rate decreased when the task difficulty increase. Eye movement data also changed with the change of time pressure and task difficulty. When time pressure increased, the pupil diameter increased, number of fixation points decreased, fixation frequency increased and average fixation time decreased. Pupil diameter increased when task difficulty increase. So the conclusion could be made that eye movement behavior and search performance change with the change of task difficulty and time pressure. During Human-machine Interface Design, the task difficulty and time pressure need to be scientifically designed to optimize the performance of the operator.
Design thinking in the library space: Problem-solving signage like a graphic designer

Librarians and graphic designers have a lot in common. Both are information professionals that offer means or cues to help users navigate, understand and solve a problem within a certain space. Without the librarian, the library space itself becomes the interface where users are offered signage to problem-solve intuitively. Because of this, effective communication via signage and wayfinding becomes imperative to the library user experience. By empathizing with our patrons and clearly articulating what the problem is, it is possible to anticipate user needs, address them by utilizing the design-thinking process, and prototype solutions like a graphic designer. However, this is not a permanent, one-time process, and it will need to be repeated whenever the needs of the patrons evolve and new problems emerge.
An Interdisciplinary Framework for Designing Adaptive Snowsports

This literature review lays the groundwork for the past, present, and future of adaptive snowsports. The paper acknowledges the design challenges of inclusivity and individualism for adaptive snowsports equipment. In addition to surveying literature on adaptive snowsports design, various design approaches and case studies are explored to expand the discussion about different perspectives and techniques for achieving design solutions that meet the needs of many people. By engaging in a literature review, the paper presents an initial interdisciplinary recommendation that could influence designers and researchers in contributing to adaptive snowsports solutions that address these challenges to ultimately meet the needs of many.
Design and Validation of a Unity-Based Simulation to Investigate Gesture Based Control of Semi-autonomous Vehicles

The objective of this investigation is to explore the use of hand gestures to control semi-autonomous vehicles. This was achieved through the use of simulations built in Unity and real-life demonstrations. Screen-spaced simulations modeled the control of a recreational quadcopter while Virtual Reality simulations followed by actual demonstrations used a small ground vehicle. The purpose of the actual demonstrations was to validate observations and lessons learned about vehicle control and human performance from the simulations. The investigative process involved identifying natural gestures to control basic functions of a vehicle, matching them to the selected gesture capture technology, developing algorithms to interpret those gestures for vehicle control, and arranging the appropriate visual environment using the Unity game engine to investigate preferred use of those gestures. Observations and participant feedback aided in refining the gesture algorithms for vehicle control and visual information, indicated the simulations provided suitable learning experiences and environments from which to assess human performance. Results indicate that the gesture-based approach holds promise given the availability of new technology.
Displaying Art in Virtual Environments

In this paper, we explore the possibilities posed by the use of the Crytek game engine to display art in interactive virtual environments. Enabling artists, among others, to enhance their creative process by viewing virtual models of unfinished art pieces and allowing to create and experience a virtual presentation of the art pieces. Furthermore, we will present our approach during the phases of our project and the results of a showcase event with artists in which we presented our prototype.
Citation-Based Scientific Paper Summarization Using Game Theory

Given the vast amount of research-oriented literature, any new research work asks for a comprehensive literature review. This process is typically very time-consuming. Citation information of a paper is a reflection of its contributions to the researcher's group. We use the citations of the paper to generate a comprehensible and informative summary, which will reduce the time taken to review the paper. In this paper, we propose a novel evolutionary game-theoretic approach to summarize scientific papers. A set of two-player games is played to choose the most relevant sentences in the paper that should be a part of the summary. Our method doesn't require an annotated dataset with gold summaries, thus levitating the need for a large, manually created dataset, which would be a primary requirement for any supervised approach. We have evaluated our results against human-expert generated summaries and state-of-the-art methods.
Security of multimedia communication with game trick based fast, efficient, and robust color‐/gray‐scale image encryption algorithm

Abstract Freshly, an innumerable chaotic system based complex and more time‐consuming image encryption algorithms have been proposed. The majority of those have scrambling and diffusion like two phases or rounds before performing the actual encryption, which leads toward extra time consumption. So unlike those, this article presents a novel image encryption algorithm that is based on game trick. The proposed novel method is DNA based and it can accomplish dual function with one round, that is, scrambling for the bit planes and diffusion for the pixels, So we called it as DNA‐SPD. First of all, a random matrix equivalent to the size of the original image is generated through a python random array generator and seed value of the 512‐bit hexadecimal key of the original image. Second, it performs the pixel adaptive additions with MA between pixels of a plain image, random matrix, the integer value of the hash key entity, and the decimal number (DN). Third, it extracts each channel from the color image and convert it into the binary bit planes, then transformed it into the DNA bit planes through particular DNA rules. Finally, a universal DNA rule utilized to get back encrypted pixels. Various security analysis and comparison of projected results show that the proposed novel encryption method gives better results in a lesser amount of time. The proposed algorithm is robust against the well‐known and effective attacks, that is, known/chosen plaintext attacks, differential attacks, and the statistical attacks. Therefore, the proposed algorithm is more secure and reliable for the security of image communication.
An Experiment Study of Service Discovery Using the Extreme Learning Machine Based Approach

Recent years have witnessed the rapid development of Web services on the internet, providing the increasing number of online services with diverse types available today. The demand of finding the target web service that meets user's requirement is thus no longer an easy task and needs to be paid more attention. To solve this problem, this study proposed a new service discovery method, combining the Extreme Learning Machine (ELM) and Differential Evolution Algorithm (DE) to retrieve the target service. We first calculated the similarities of each service in the training set by using four different similarity measurements and obtained the corresponding DE fitness values to construct the sample vectors. Second, these vectors were used to constitute the ELM model to learn the interrelationship between the similarity scores and the DE fitness values. Finally, we simulated the discovery process on a test set. For each new query, the target service can be received through the DE fitness values that are predicted from the constructed ELM model. The experiments were conducted on a public service set and the results showed the significant implications.
POI Recommendation with Interactive Behaviors and User Preference Dynamics Embedding

Recently, Location-based Social Networks (LBSNs) have been widely used in people's daily life. This generates the demand for effective and efficient POI recommendation. Existing research focused on improving the POI recommendation performance by some extra information such as social links, geographical distance and others, but they failed to integrate those complex influenced factors together. In this paper, we propose a POI recommendation framework with interactive behaviors and user preference dynamic embedding to consider the social and geographical information with interactive behavior embedding, along with users' preference dynamics embedding, respectively. To combine the interactive behavior and users' preference dynamics behavior, we use a fusion parameter to decide the contribution of interactive behaviors embedding and user preferences embedding. Extensive experiments on two real-world datasets demonstrate the effectiveness of our proposed model.
Methods for Suppressing Discrete White Noise in Images

Methods for suppressing discrete white noise in the composition of images are considered in the article. For linear filters (operators), the residual noise level coefficient and noise reduction coefficient are introduced. A new method for estimating noise level in image composition and its use in sigma filter is considered.
Tackling the cyber skills gap

Alongside the growing complexity of cyberspace, there is a widening skills gap worldwide. This recognition has led governments to develop new strategies that will help develop a workforce ready to safeguard digital infrastructures and cyber-physical systems. This chapter surveys such initiatives taken in the UK, focusing particularly on university programmes, government strategies and national and regional competitions. The chapter concludes that while the UK has significantly expanded its repertoire of cyber training initiatives in the last six years, there is still a significant skills gap in the public sector. New initiatives should pay particular attention to skills provision for national-level cyber emergencies.