Reviewerly/exHarmony huggingface dataset:
Analysis of feature representation in dictionary learning and sparse coding algortihms for low resolution image

Abstract Super-Resolution (SR) is used to recover a high-resolution (HR) image from the image with low-resolution (LR). SR is important in the biometric identification and the face recognition is an area that bring attention to people. However, the performance of the current systems is affected by the resolution of the input images. Thus, this paper is focusing on the analysis of feature representations in dictionary learning and sparse coding methods for LR image. The input image is the Lena image in grey scale. A total number of 23 features were extracted from the image patches to develop different learned dictionaries using the k-singular value decomposition (k-SVD) algorithm. The denoised images were then produced by using the Douglas-Rachford algorithm. Most of the feature representations were able to produce a final image with Peak-to-Signal Noise Ratio (PSNR) and Structural Similarity Index Matric (SSIM) values of approximately 29 dB to 30 dB and 0.8300 to 0.8600 respectively. However, the denoised image produced with gradient direction obtained only 27.6676 dB and 0.7881 for PSNR and SSIM. Therefore, when different features were extracted for conducting the dictionary learning and sparse coding algorithm, denoised image with different PSNR and SSIM were produced at the end of the process.
Subjective evaluation of a traffic stream quality by drivers

Smart City phenomenon tends to be very strongly focused on citizens and their quality of life rather than measurable parameters of traffic, information and economics. In regard to traffic, very important parameter is Level of Service (LoS), quantification of which can be a troublesome task due to the number of observed parameters and qualitative nature of the phenomenon. Moreover, the subjective interpretation of LoS may differ for such user groups like police officers, traffic dispatchers and drivers which makes experts opinion less applicable. In the following study authors created an experiment aiming on the evaluation of recorded traffic situations by drivers (from drivers' perspective). The subjective qualitative assessment of respondents was compared to the quantitative data collected by traffic detectors installed in the places where recording took place. The results provide an innovative view on accepted and commonly used Level of Service evaluation methods and scales.
Analytical Estimation of Self-Orthogonal Code Multithreshold Decoders Efficiency

Multithreshold decoders (MTD) of self-orthogonal codes (SOC) for channels with errors as well as erasure channels are discussed. The work offers analytical estimations of MTD efficiency considering SOC structure as well as decoder parameters. These estimations are shown to correspond well with computer simulation results allowing us to estimate the area of MTD efficient operation in the conditions of high noise level.
Exploring Ontology-Based Information Through the Progressive Disclosure of Visual Answers to Related Queries

Web search has become the predominant method for people to fulfill their information needs. Although widespread, the traditional model for search result pages is only satisfactory if the user knows quite precisely how to phrase their query to match their intended information. We propose a new model for search page results, which goes beyond providing a navigable list of visualization search results, by implicitly generating related queries to expand the search space and progressively disclosing the corresponding results.
Evaluating Extreme Learning Machine Models in the Presence of Concept Drift in Streaming Data

This paper discusses concept drift in online streaming data and evaluates the performance of different Extreme Learning Machine (ELM) based techniques on classifying online streaming data in the presence of concept drift. It also compares the performance of a hybrid model called Online Recurrent ELM (OR-ELM) with traditional recurrent neural networks, in terms of training speed and accuracy, on streaming data that has concept drift. The results of our experiments show that OR-ELM has better accuracy and faster training time.
Using String-Comparison Measures to Improve and Evaluate Collaborative Filtering Recommender Systems

Recommender Systems are expert systems that utilize the user’s interests in order to recommend different products. One of the main techniques employed in this type of system is the Collaborative Filtering which recommends products to users based on their interactions and on what items similar users have liked in the past. However, many traditional methods for determining similarity do not consider temporal information neither the rich information that is contained in sequentially-ordered user interactions. Therefore, the present work proposes the usage of traditional string comparison approaches for defining new similarity measures between pairs of users that take into consideration time-ordered data. The general idea is to model the similarity computation between users as an approximate string matching problem and to employ classical algorithms that solve it. Experiments conducted in different application domains demonstrate that the measures based on a string-comparison approach can improve accuracy. Furthermore, they represent a new way of evaluating the performance of sequence-based recommendation.
AI Mobility Solutions for an Active Ageing Society. Introducing Aesthetic Affordances in the Design of Smart Wheelchairs

In the next paper we argue that user-centered product design can play an important role in the development of a new generation of smart wheelchairs that places an emphasis on the users' functional and aesthetical needs. We present the concept of "aesthetic affordance" [1] and propose interaction aesthetics and user scenarios as valid frameworks for designing AI mobility devices for elderly users. The term "affordance" in this specific case study is seen as bringing together the capability of a device to enable a specific action [2] and the possibility of that device to communicate a certain meaning [3]. We stress out how the smart wheelchairs, which successfully convey their actual mobility support function, can help the elderly people become more easily accepted as active citizens by the rest of the community. In this sense the aesthetics of the product have an equal importance to the innovative AI implementations. An initial review of the existent AI augmented wheelchairs revealed an overall lack of concern about the aesthetic functions of the mobility devices and more important the lack of consideration of how the person using it is perceived by the rest of the society. To support this argument we present the different design and development phases of a new concept for the working prototype of a wheelchair created for a large Japanese company. Although the concept has received international acclaim from the design community, we suggest that the most important feature of the product, that of addressing the important ergonomic issue of aesthetic affordance, is still left implicit and needs further investigation.
Mixed Μock-up Μeets ErgoCAM: Feasibility Study for Prospective Ergonomic Evaluation of Manual Assembly Processes in Real-Time Using Augmented Reality and Markerless Posture Analysis

The sustainable planning of production systems and processes requires a high degree of flexibility in the processes, both in terms of the production methods used and scalability, in order to be able to react to changing requirements at short notice. These requirements often hamper companies’ efforts to guarantee health-promoting working conditions and systems as the workload involved in a correspondingly short-cycle analysis and evaluation of stressors would be too great. As a result, the individual needs of employees, such as adapting the workplace to suit personal constitutional traits, are often not taken into account sufficiently. In order to address this problem, two prototypical systems for digitally supported workplace design are tested in this paper. The focus lies on a mixed mock-up demonstrator, which combines classic mock-up planning with augmented reality technology and enables the generation of individualized manual assembly workstations. This demonstrator is used and examined in conjunction with ErgoCAM, a prototype of a markerless system, to evaluate individual postures in real time. The aim is to ascertain which benefits the combination of the systems offers with regard to the flexible and early ergonomic evaluation of assembly workstations in practice. Specifically, in a feasibility study, it is examined to which extent a reliable ergonomic evaluation of assembly operations is possible by combining the two prototypes.
On Computational Performances of the Actual Image Classification Methods in C# and Python

Convolutional Neural Networks (CNNs) built in Python, have become the methodology of choice in image classification. On the other hand, recently formulated Capsule Networks (CapsNets) show potential of deeper understanding of the objects' relations within the images, thereby promising better classification accuracy. The primary aim of this research is to analyze the computational aspects when the two algorithms are implemented in two different programming platforms such as Python and C#. As compared to the equivalent implementations in Python, the results show that C#-based CNN implementation can provide better computational efficiency. Also, C# implementation of CapsNets results in smaller number of epochs for the network to get stabilized, as compared to the Python-based implementation. Finally, at the price of higher computational costs, the results confirm the thesis that, in terms of the handwritten digit classification accuracy, the CapsNets will outperform CNNs.
Software Engineering Worldwide

Software engineering is a key discipline in computer science. Its purpose is to develop software products and services of high quality within economic constraints that meet customer requirements and create value. Considerable shares of the societal and industrial infrastructure depend on software, and software has become a key driver for innovation. So far, so good, but who shapes software engineering, who defines what the problems to be solved look like, and who decides about the importance of certain streams in software engineering research and practice? Furthermore, is software engineering in the USA or in Europe the same as, e.g., software engineering in Oceania or Africa? In this new column Software Engineering Worldwide, we aim to provide an overview of software engineering, its importance and its manifestation, in different regions worldwide. We wish to take a look behind the scenes to learn about the different environments and the respective key problems to be addressed in "local" software engineering research, practice, and education. We also aim to open the minds of the community regarding the involvement of new locations not yet on the software engineering map, and to stimulate constructive discussion on how to better involve such locations.
Asymptotically Optimal Learning in Fuzzy Environments

The paper continues our approach for measuring fuzzy values with a game of learning finite automata that are able to make an optimal choice among several alternatives. In principle, with such a game it is possible to measure any fuzzy values with certain precision. For the mentioned game we used previously a linear tactics automaton as the construction with asymptotically optimal behavior. However, our study showed that its asymptotical optimality is achieved under certain restriction concerning the fuzzy environment. In practice the mentioned automata allow to measure fuzzy value only when it is greater than 0.5. Presently, architecture has been chosen, referred to as trusting automata. The architecture of such an automaton has been proposed many years ago by Prof. V. I. Krinsky. In this paper we proved mathematically that the trusting automata do have the asymptotically optimal property for arbitrary values of memberships in the fuzzy environment. Consequently, the trusting automata may be used to measure arbitrary membership values in the game procedure described above without any restriction.
Back to the Future and Forward to the Past: Zukunftsmusik and the aesthetics of immersive classical music experience

We showcase relevant aesthetic considerations of an interaction design for immersive experience informed by Zukunftsmusik.The 'Zukunftsmusiker' movement emerged at the verge of the 20th century and intends to encompass a holistic experience incorporating the active participation of all senses with its corresponding action.Amongst other features, we highlight aspects related to diegesis, agency, and attention centring of the visual and auditory field by examining two renditions of The Ravens, a 3D 360-degrees guided experience as well as a 6-degrees-of-freedom multi-view experience of the eponymous piano composition by the first author.With their design rationale of participatory experience, these renditions aim to set off a renewed technological consideration of the Zukunftsmusik paradigm.Ultimately, this paradigm may reach out towards an audience demographic that was previously mostly unknown in contemporary music: The user.
Ethnographic Practice and the Problem of Context in Interaction Design Education

This paper investigates the concept of context as it relates to interaction design education. Based on the results of research in which interaction design students suggest that the need to learn business contexts are as important as understanding user contexts, I argue for the application of ethnographic methods to the problem of teaching the contexts of business. This is a novel approach that shifts the historical focus of ethnographic practices in interaction design from analyzing users to analyzing the business field. To do this, I first explain some terms—context, interaction design, and ethnography. Second, I analyze the results of the survey and interview session to get a full sense of the importance of context to interaction design students. Finally, I explain the value of incorporating ethnographic practices.
Blockchain Technology: A Bibliometric Analysis

Blockchain is a decentralized transaction and data management technology. It is a relatively new technology with a wide variety of applications that may in time come to affect the whole economy and be recognized as the latest general-purpose technology. The aim of this study is to explore the literature growth and author productivity of blockchain technology research from 2008 to 2019. 9239 articles were retrieved from Scopus database and analyzed with bibliometrics approach using different perspective views. Blockchain and Blockchain Technology were used as search terms in order to run the query and obtain data. The search was performed on Title, Abstract and Keywords. The search excluded the year 2020 as we are still in the first quarter of the year. Results revealed that first publication with blockchain technology can be tracked back to 2010, and 2019 was the peak time for blockchain research. Moreover, results revealed that Chain and USA are considered to be the most productive countries producing more research, and Chinese organizations were predominant and controlling the research of the new technology. The key author was found by Scopus to be Wang, F.Y with 38 different works.
Evaluation of a Facial Recognition Engines for a Surveillance System

This paper presents the evaluation of a facial recognition system when considered in an operational context for the South African environment. Often, performance measures, such as recognition rate, are considered outside of context, which does not provide sufficient information for selecting an appropriate recognition engine. Design Science Research (DSR) in conjunction with elaborated Action Design Research (eADR) was used to translate a real-world scenario to an abstracted research problem. The goal of DSR is to provide an artefact, which in this case is presented in the form of a workable realworld system architecture with a cost-effective recognition engine. Three experiments were conducted on commercial recognition engines, as well as on an open-source engine to determine the performance on MUCT and a subset of the LFW data sets, as well as on a self-constructed database of localized data. Finally, costs were compared between open-source and commercial recognition engines, and a scenario was put forward to show the cost-effectiveness of these two systems in a specific example. Ultimately, it is known that the performance of a facial recognition system is affected by the performance of the recognition engine, but it was evident that the total system must be considered before an informed decision on a recognition engine can be made.
Effects of Recipient Information and Urgency Cues on Phishing Detection

Phishing causes significant economic damage and erodes consumer trust in business communication. To better filter phishing emails, researchers have paid a substantial amount of attention to the characteristics of phishing emails. This study focused on the effects of recipient information and urgency cues on phishing detection. A total of 518 participants performed role-playing tasks in which they needed to discriminate legitimate emails and phishing emails. The results showed that the main effects of urgency cues and recipient information were significant. Under the condition of time constraints, the likelihood of replying to the phishing emails increased, and the likelihood of searching for the relevant information decreased. When recipient information was added to the phishing emails, the likelihood of replying to the phishing emails decreased, and the likelihood of deleting the phishing emails and searching the for relevant information increased. Meanwhile, the interaction effect of recipient information and time pressure was also significant. When recipient information was added to the phishing emails, the urgency cues had a significant negative effect on the detection behaviors. Under the condition of time constraints and recipient information addition, the likelihood of replying to the phishing emails increased, and the likelihood of deleting the phishing emails and searching for the relevant information decreased. These findings showed that phishing email characteristics strongly affect phishing susceptibility. A sense of urgency resulted in stress and impulsive behavior, and thus, the participants preferred quickly respond and perform less research. By exploring the mechanism underlying phishing processing, this study deepens the understanding of detecting deception and motivates more effective strategies or assistance systems to protect individuals from online fraud.
Constructing a Highly Accurate Japanese Sign Language Motion Database Including Dialogue

Sign language is a visual language. Research into Sign language, including in related areas such as linguistics and engineering is lagging behind spoken language. One reason for this is the absence of a common database available to researchers from different areas. This paper defines how to words are selected for inclusion in the sign language database, how to select informants, what format the data are included in and how to record the data. Also, the database includes three-dimensional behavioral data based on dialogue. The following explains the results.
Efficient Arbitrary Simultaneously Entangling Gates on a trapped-ion quantum computer

Efficiently entangling pairs of qubits is essential to fully harness the power of quantum computing. Here, we devise an exact protocol that simultaneously entangles arbitrary pairs of qubits on a trapped-ion quantum computer. The protocol requires classical computational resources polynomial in the system size, and very little overhead in the quantum control compared to a single-pair case. We demonstrate an exponential improvement in both classical and quantum resources over the current state of the art. We implement the protocol on a software-defined trapped-ion quantum computer, where we reconfigure the quantum computer architecture on demand. Together with the all-to-all connectivity available in trapped-ion quantum computers, our results establish that trapped ions are a prime candidate for a scalable quantum computing platform with minimal quantum latency.
How Can We “Visualize” the World? Essential Foundations of Information Design for Best Practices

Relations between data can be very complex, and therefore finding unique ways to accurately convey these data in order to detect trends, patterns and outliers is a very valuable opportunity. The purpose of this study is to highlight current challenges facing Information Design (ID), considering the overload of information that is inherent to modern living. How can we “visualize” the world? What are the functional, aesthetic and cognitive principles that interfere with the way we visualize information and prepare that information? What visual variables can we use to produce visual information that aims to build a functional visual message that a particular audience can understand? The main objectives are: a) to clarify some concepts linked to the act of visualizing; b) to present certain factors that influence the perception of visual information; c) to highlight the main advantages of visual information. The present study is qualitative, and it was supported based on the documentary analysis of several authors. The role of ID is to transform chaos into order and information into meanings and knowledge, helping people to reach information. In an era where we are constantly surrounded by information and messages, all of which trying to get our attention, the way in which information is organized, written and presented is extremely important, so that we can all understand it. Visualizing the world is the best way to understand it in an efficient way.
The control algorithm of a programmable tandem detonator

Abstract The article describes the results of laboratory tests of the algorithm of control of programmable detonators designed for tandem systems. Control elements were made on the basis of microcontrollers using RISC architecture. The detonator has a system to quickly excite the precursor charge and can be programmed at any time to delay the detonation of the main charge. The lack of delay in excitation of the precursor charge was realized using a comparator. The article presents the results of preliminary laboratory tests of the control algorithm of the executed system. The flexibility of the solution to program any delay time for the excitation of the main load provides a wide range of practical applications.
Designing and Developing a Sandbox-Style Tangible AR for Geoscience Learning

Considering the potential of sandbox-style tangible augmented reality and its enabling technologies to improve users’ engagement, this study intends to design and develop a tangible AR environment for students’ geoscience learning in museums. With reference to the basic functionality of a tangible AR, and the possibilities of AR to support meaning making for science learning, this study firstly developed a sandbox-style tangible AR environment to enable basic interactivity. And the school curriculum of geoscience for the local community in Taiwan was then referred in order to develop the instructional plans with the sandbox TAR. Finally, there were four AR learning packages in total completed with expert teachers’ review. These four lessons consisted of different infusion of tangible AR elements that allowed learners to search, connect, collect and generate geographical information. A preliminary user testing with 5 college students were conducted to confirm the quality of system instruction and the functionality of the system.