Reviewerly/exHarmony huggingface dataset:
Sleepy Channels

Payment channels (PC) are a promising solution to the scalability issue of cryptocurrencies, allowing users to perform the bulk of the transactions off-chain without needing to post everything on the blockchain. Many PC proposals however, suffer from a severe limitation: Both parties need to constantly monitor the blockchain to ensure that the other party did not post an outdated transaction. If this event happens, the honest party needs to react promptly and engage in a punishment procedure. This means that prolonged absence periods (e.g., a power outage) may be exploited by malicious users. As a mitigation, the community has introduced watchtowers, a third-party monitoring the blockchain on behalf of off-line users. Unfortunately, watchtowers are either trusted, which is critical from a security perspective, or they have to lock a certain amount of coins, called collateral, for each monitored PC in order to be held accountable, which is financially infeasible for a large network. We present Sleepy Channels, the first bi-directional PC protocol without watchtowers (or any other third party) that supports an unbounded number of payments and does not require parties to be persistently online. The key idea is to confine the period in which PC updates can be validated on-chain to a short, pre-determined time window, which is when the PC parties have to be online. This behavior is incentivized by letting the parties lock a collateral in the PC, which can be adjusted depending on their mutual trust and which they get back much sooner if they are online during this time window. Our protocol is compatible with any blockchain that is capable of verifying digital signatures (e.g., Bitcoin), as shown by our proof of concept. Moreover, our experimental results show that Sleepy Channels impose a communication and computation overhead similar to state-of-the-art PC protocols while removing watchtower's collateral and fees for the monitoring service.
A Design Framework for Smart Glass Augmented Reality Experiences in Heritage Sites

Despite the growing applications of smart glass Augmented Reality (AR) in heritage, there is not a framework that can serve as a base for designing meaningful and educational immersive heritage experiences. This article proposes such a prototype design framework for AR experiences in heritage sites, drawing on literature that connects affective experiences with learning and practically exploring AR as a non-didactic storytelling medium. Smart glass AR is considered here an important technology milestone for creating affective interactions, one that offers visitors/viewers new ways to experience, embody, and have a physical and social interaction with a localized past and learn about it.
Putting your best face forward: How instructor emoji use influences students’ impressions of credibility, immediacy, and liking

This project explores the impacts of emojis on students' impressions when used in a course welcome email. We adopt a 4 × 3 factorial design to determine how different emojis (i.e., , , ) impact students' impressions of credibility, immediacy, and liking. Data from students (N = 368) indicates emoji choice does impact impressions. Consistently, instructors' emoji use resulted in decreased perceived competence and trustworthiness but increased perceived caring, immediacy, and liking. Findings have implications for instructors who engage in technologically-mediated out-of-class communication and want to strengthen early student-instructor relationships. Limitations and future directions are also discussed.
Paradigm changes and new challenges for media education: Review and science mapping (2000-2021)

Information, communication, and digitalization technologies have driven the unlimited access to knowledge, thereby promoting creativity, economic and cultural development, and the emergence of a global world at breakneck speed over recent decades. Across its multiple dynamics, this digital revolution has opened new educational opportunities that are closely connected to emerging technologies and, recently, to artificial intelligence. These advances have had an unexpected impact on people’s lives, altering the values of society and our understanding of the role of education and the modern school in this scenario of global communication. In this context, media education arises from the clear influence of electronic devices and digital technology on society. The aim of this study is to review our understanding of the scientific relevance of the terms “media education” and “educommunication” during the last two decades to describe its evolution on the basis of its terms, locations, thematic stages, and methodological approaches using a systematic quantitative–qualitative review of 598 articles collected from the Web of Science between 2000 and 2021. The results suggest that such scientific interest can be divided into two stages, viz. reflections on media education in its terminological diversity (2000–2012) and measurement, implementation, training, and educommunicative digitization in terms of technological–digital development (2013–2021). We conclude that studies in this transdisciplinary field, which have historically been spread across North and South America, Europe, North Africa, and the North/South East Asia–Pacific region, have broadened their perspective from early criticism of media education to consider the “glocalization” of media education, directing interest toward the cultural digitization of the Global South, algorithmic literacy, and the digital and ethical–critical (self-)management of individual and collective identity.
SimLess

Many researchers migrate scientific serverless workflows or function choreographies (FCs) on Function-as-a-Service (FaaS) to benefit from its high scalability and elasticity. Unfortunately, the heterogeneity of federated FaaS hampers decisions on appropriate parameter setup to run FCs. Consequently, scientists must choose between accurate but tedious and expensive experiments or simple but cheap and less accurate simulations. Unfortunately, related works support either simulation models for serverfull workflows running on virtual machines and containers or partial FaaS models for individual serverless functions focused on execution time and neglecting various kinds of federated overheads.
Games and the Metaverse

The metaverse has become a topic of interest in both industry and academic settings. Research and development that focus on the 'metaverse' explore the immersive future of the internet, where distributed people from around the world can connect through virtual social environments. Unsurprisingly, the term has gained traction in the digital gaming realm as many related games and play research topics directly contribute to the metaverse. We propose to host a panel at CHI PLAY 2022 which will facilitate discussion amongst researchers in the field regarding the current landscape of the metaverse in game research, and opportunities and challenges to propel the future evolution of research in this area.
Recent Studies on the Effects of Refactoring in Software Quality: Challenges and Open Issues

Refactoring is widely thought to improve software quality. Several studies, however, claimed that the effect of refactoring on software quality could be positive, negative, or have no effect. When using refactoring techniques to improve software quality, software developers face difficulties in selecting appropriate techniques. There has been no research into the contradictions in the effect of refactoring on software quality. Therefore, this study reviewed 30 recent empirical studies on the effect of various refactoring techniques on various internal and external software quality attributes. This review has three goals: first, to identify related empirical studies; second, to identify the applied refactoring techniques, internal and external quality attributes, and third, to analyze the relationship between refactoring and software quality. There were 18 studies that found that refactoring improves software quality, and 12 studies that found the opposite. More research is needed to understand the trade-off between improving and worsening various attributes. Current challenges and open issues that need further investigation have been identified and discussed.
Earthquake early warning systems based on low-cost ground motion sensors: A systematic literature review

Earthquake early warning system (EEWS) plays an important role in detecting ground shaking during an earthquake and alerting the public and authorities to take appropriate safety measures, reducing possible damages to lives and property. However, the cost of high-end ground motion sensors makes most earthquake-prone countries unable to afford an EEWS. Low-cost Microelectromechanical systems (MEMS)-based ground motion sensors are becoming a promising solution for constructing an affordable yet reliable and robust EEWS. This paper contributes to advancing Earthquake early warning (EEW) research by conducting a literature review investigating different methods and approaches to building a low-cost EEWS using MEMS-based sensors in different territories. The review of 59 articles found that low-cost MEMS-based EEWSs can become a feasible solution for generating reliable and accurate EEW, especially for developing countries and can serve as a support system for high-end EEWS in terms of increasing the density of the sensors. Also, this paper proposes a classification for EEWSs based on the warning type and the EEW algorithm adopted. Further, with the support of the proposed EEWS classification, it summarises the different approaches researchers attempted in developing an EEWS. Following that, this paper discusses the challenges and complexities in implementing and maintaining a low-cost MEMS-based EEWS and proposes future research areas to improve the performance of EEWSs mainly in 1) exploring node-level processing, 2) introducing multi-sensor support capability, and 3) adopting ground motion-based EEW algorithms for generating EEW.
Self-generation of Möbius solitons and chaotic waveforms in magnonic-optoelectronic oscillators under simultaneous action of optic and magnonic nonlinearities

Self-generation of microwave nonlinear waveforms in the magnonic-optoelectronic oscillator (MOEO) was investigated. Nonlinear dynamics of the MOEO was due to both optical and magnonic paths of the oscillator circuit. Four-magnon parametric interactions in the magnonic path and cosine transfer function of the electro-optical modulator caused double nonlinearity of the MOEO. Gain coefficient was used as a control parameter. We found that during a route from regular to chaotic dynamics, the oscillator generates two unusual waveforms: symmetry-breaking soliton-like modes of Möbius type and periodic pulses with chaotic amplitude modulation. Nonlinear waveforms were characterized using a time series analysis. Peculiarities of the signals and their spectra in regular and chaotic regimes of self-generation are discussed. We expect that the multiple nonlinearity of the MOEO may be useful for investigation of various fundamental effects in complex time-delayed systems and for development of novel circuits for neuromorphic computing.
Towards an implementation of immersive experience application for marketing and promotion through virtual exhibition

VR technologies offering powerful immersion and rich interaction have gained significant interest from researchers and practitioners. In this study, a virtual exhibition was created using Virtual Reality (VR) named GATBooth. The experiment conducts by comparing the VR application to the desktop (PC) version of GATBooth. Fourteen college students were evaluated as participants to measure the level of immersion using the Igroup Presence Questionnaire (IPQ). In the General Presence (PRES), Spatial Presence (SP), and Experienced Realism (REAL), the result show VR are more significant (p < 0.05), but the level of awareness of Involvement (INV) is no different (p > 0.467). The conclusion of the experiment indicated that Virtual Reality and PC technology could be used for promotion, marketing, and virtual exhibition.
What simulation can do for HCI research

research-article Share on What simulation can do for HCI research Authors: Roderick Murray-Smith University of Glasgow University of GlasgowView Profile , Antti Oulasvirta Aalto University Aalto UniversityView Profile , Andrew Howes University of Birmingham University of BirminghamView Profile , Jörg Müller University of Bayreuth University of BayreuthView Profile , Aleksi Ikkala Aalto University Aalto UniversityView Profile , Miroslav Bachinski University of Bergen University of BergenView Profile , Arthur Fleig University of Bayreuth University of BayreuthView Profile , Florian Fischer University of Bayreuth University of BayreuthView Profile , Markus Klar University of Bayreuth University of BayreuthView Profile Authors Info & Claims InteractionsVolume 29Issue 6November - December 2022pp 48–53https://doi.org/10.1145/3564038Published:03 November 2022Publication History 1citation427DownloadsMetricsTotal Citations1Total Downloads427Last 12 Months427Last 6 weeks32 Get Citation AlertsNew Citation Alert added!This alert has been successfully added and will be sent to:You will be notified whenever a record that you have chosen has been cited.To manage your alert preferences, click on the button below.Manage my AlertsNew Citation Alert!Please log in to your account Save to BinderSave to BinderCreate a New BinderNameCancelCreateExport CitationPublisher SiteGet Access
A zero-watermarking algorithm for vector geographic data based on feature invariants

Previous studies on zero-watermarking algorithms for vector geographic data focus on improving the robustness against geometrical attacks, compression attacks and object attacks. However, there are limited zero-watermarking algorithms against projection transformation. In this study, we proposed a zero-watermarking algorithm for vector geographic data based on feature invariants. After any projection transformation of vector geographic data, the number of vertices and relative storage order of objects keep consistent. Therefore, the number of vertices and relative storage order of objects can be considered as the feature invariants. The proposed algorithm consists of three steps. Firstly, according to the relative storage order of objects, the watermark bit is determined by comparing the number of vertices between any two objects. Secondly, the watermark index is calculated by the number of vertices of two objects. Then, a feature matrix is constructed by combining the watermark bit and the watermark index. Finally, the XOR operation is performed between the feature matrix and the scrambled watermark image to generate the zero-watermark image. The experimental results show that the watermark information with NC of 1.0 can be detected from the vector geographic data after any projection transformation, which shows that the algorithm can resist any projection transformation. At the same time, the useful watermark information with minimum NC values of 1.0, 0.911, 0.84, and 1.0 can be detected from the vector geographic data after the geometrical attack, object addition attack, object deletion attack and precision reduction attack. Therefore, the proposed algorithm can effectively against geometrical attacks, object addition attacks, object deletion attacks and precision reduction attacks, showing superior performance compared with previous algorithms.
Autocorrelative weak-value amplification and simulating the protocol under strong Gaussian noise

By choosing more orthogonality between preselection and postselection states, one can significantly improve the sensitivity in general optical quantum metrology based on the weak-value amplification (WVA) approach. However, increasing the orthogonality decreases the probability of detecting photons and makes the weak measurement difficult, especially when the weak measurement is disturbed by strong noise and the pointer is drowned in noise with a negative-decibel signal-to-noise ratio (SNR). In this article we introduce and numerically evaluate a modified weak-measurement protocol with a temporal pointer, namely, the autocorrelative weak-value amplification (AWVA) approach. Specifically, a small longitudinal time delay (tiny phase shift) $\ensuremath{\tau}$ of a Gaussian pulse is measured by implementing two simultaneous autocorrelative weak measurements under Gaussian white noise with different SNRs. The small quantities $\ensuremath{\tau}$ are obtained by measuring the autocorrelation coefficient of the pulses instead of fitting the shift of the mean value of the probe in the standard WVA technique. Simulation results show that the AWVA approach outperforms the standard WVA technique in the time domain with smaller statistical errors, remarkably increasing the precision of weak measurement under a strong noise background.
LK-AKA: A lightweight location key-based authentication and key agreement protocol for S2S communication

As a supplement to terrestrial networks, satellite communication networks have a lot of advantages, such as wide coverage, large communication capacity, reliable communication quality, and seamless global connectivity, which are highly competitive with traditional communication technologies. However, there are still many security issues and efficiency problems in satellite networks due to the characteristics of satellite communications, such as highly exposed satellite links, dynamical topology, and the limited computational power and storage resources of satellites. Therefore, it is a crucial issue to design a lightweight and secure authentication mechanism to ensure the security of satellite-to-satellite communication (S2S). This paper proposes a lightweight authentication and key agreement scheme for S2S communication based on the symmetric cryptographic system and the satellite location key (LK) constructed by satellite orbital parameters and location information. The formal verification tool Scyther is employed to evaluate the proposed scheme’s security. The security analysis results show that it has good performance in providing security properties and resistance to typical attacks, such as replay attacks, impersonation attacks, and Man-In-The-Middle (MITM) attacks. In addition, the performance analysis results demonstrate that our scheme has desired efficiency in terms of signaling overhead, computational overhead, and bandwidth overhead. • Authentication and key agreement for satellite-to-satellite communication. • The location key is calculated based on the GPS coordinates of the satellite. • The symmetric cryptosystem and location key of the satellite. • The orbital parameters of the satellite have changed.
Decentring the discoverer: how AI helps us rethink scientific discovery

Abstract This paper investigates how intuitions about scientific discovery using artificial intelligence (AI) can be used to improve our understanding of scientific discovery more generally. Traditional accounts of discovery have been agent-centred : they place emphasis on identifying a specific agent who is responsible for conducting all, or at least the important part, of a discovery process. We argue that these accounts experience difficulties capturing scientific discovery involving AI and that similar issues arise for human discovery. We propose an alternative, collective-centred view as superior for understanding discovery, with and without AI. This view maintains that discovery is performed by a collective of agents and entities, each making contributions that differ in significance and character, and that attributing credit for discovery depends on various finer-grained properties of the contributions made. Detailing its conceptual resources, we argue that this view is considerably more compelling than its agent-centred alternative. Considering and responding to several theoretical and practical challenges, we point to concrete avenues for further developing the view we propose.
Salient detection via the fusion of background-based and multiscale frequency-domain features

Salient object detection is a fundamental problem in image processing and computer vision. Many saliency detection algorithms based on the background and frequency-domain are used to extract salient object clues. However, the former causes the real object to be submerged in the detected object areas, especially in complex or small object scenes. While the latter will lead to the loss of some object information when detecting large objects. To solve these problems and achieve better object detection results, we propose a fusion framework for salient object detection by fusing background and frequency-domain features. The background features of the image are extracted by an improved background model. This model represents the spatial layout of the image area with respect to the image boundaries. Meanwhile, we present a new frequency-domain processing method to obtain multiscale frequency-domain features and mark the saliency of the object at different scales. Within our framework, inspired by human visual attention, we use the idea of a self-attention mechanism to capture the intrinsic relation between background and multiscale frequency-domain features. In addition, this fusion framework provides a three-dimensional Gaussian convolution kernel, which expands two-dimensional local information to three dimensions for feature fusion, thus producing more accurate salient objects. Experiment results demonstrate that the proposed method consistently outperforms eleven state-of-the-art methods on five challenging and complicated datasets in terms of four evaluation metrics.
Fast combined-frequency phase extraction for phase shifting profilometry

Due to the nonlinearity in phase shifting profilometry (PSP) system, the captured images are often distorted with fringe harmonics, resulting in inaccurate phase map and measurement. Considering the fact that the phase error can be significantly reduced by modeling high-order fringe harmonics, this work formulates the phase extraction problem - with different frequency images and high-order fringe harmonic model - as a maximum likelihood estimation (MLE). To optimize it efficiently, we thus propose a combined-frequency phase extraction (CFPE) solution by introducing a latent phase map and incorporating the famous expectation-maximization (EM) framework. As a result, our CFPE method only needs ∼5% execution time of a high-order baseline, whilst keeps the high-order accuracy. Tested on synthetic images as well as practical measurements, our CFPE method demonstrated its performance improvement of efficiency and accuracy. In addition, our detailed implementation with experimental arrangement is also provided for interested researchers.