Reviewerly/exHarmony huggingface dataset:
LightSwap: An Atomic Swap Does Not Require Timeouts at both Blockchains

Security and privacy issues with centralized exchange services have motivated the design of atomic swap protocols for decentralized trading across currencies. These protocols follow a standard blueprint similar to the 2-phase commit in databases: (i) both users first lock their coins under a certain (cryptographic) condition and a timeout; (ii-a) the coins are swapped if the condition is fulfilled; or (ii-b) coins are released after the timeout. The quest for these protocols is to minimize the requirements from the scripting language supported by the swapped coins, thereby supporting a larger range of cryptocurrencies. The recently proposed universal atomic swap protocol [IEEE S &P'22] demonstrates how to swap coins whose scripting language only supports the verification of a digital signature on a transaction. However, the timeout functionality is cryptographically simulated with verifiable timelock puzzles, a computationally expensive primitive that hinders its use in battery-constrained devices such as mobile phones. In this state of affairs, we question whether the 2-phase commit paradigm is necessary for atomic swaps in the first place. In other words, is it possible to design a secure atomic swap protocol where the timeout is not used by (at least one of the two) users? In this work, we present LightSwap, the first secure atomic swap protocol that does not require the timeout functionality (not even in the form of a cryptographic puzzle) by one of the two users. LightSwap is thus better suited for scenarios where a user, running an instance of LightSwap on her mobile phone, wants to exchange coins with an online exchange service running an instance of LightSwap on a computer. We show how LightSwap can be used to swap Bitcoin and Monero, an interesting use case since Monero does not provide any scripting functionality support other than linkable ring signature verification.
Migrating Blockchains Away from ECDSA for Post-quantum Security: A Study of Impact on Users and Applications

Blockchains use Elliptic Curve Digital Signature Algorithm (ECDSA) to secure transactions between the wallets and blockchain nodes. Due to the potential threat from quantum computers, these blockchain implementations need to migrate away from ECDSA to a post-quantum algorithm before quantum computers become powerful enough. However, the migration process is long and challenging because replacing the underlying cryptographic implementation will significantly impact several existing use-cases, causing financial losses to users and making applications fail. We study the impact of such use-cases from a user and application perspective. To partly minimize the impact, we observe that use of BIP39 Seed is key to achieving backward compatibility and propose possible strategies in choosing and adapting a BIP39-compatible post-quantum algorithm.
A Parallel Privacy-Preserving Shortest Path Protocol from a Path Algebra Problem

In this paper, we present a secure multiparty computation (SMC) protocol for single-source shortest distances (SSSD) in undirected graphs, where the location of edges is public, but their length is private. The protocol works in the Arithmetic Black Box (ABB) model on top of the separator tree of the graph, achieving good time complexity if the subgraphs of the graph have small separators (which is the case for e.g. planar graphs); the achievable parallelism is significantly higher than that of classical SSSD algorithms implemented on top of an ABB. We implement our protocol on top of the Sharemind MPC platform, and perform extensive benchmarking over different network environments. We compare our algorithm against the baseline picked from classical algorithms—privacy-preserving Bellman-Ford algorithm (with public edges).
A Blockchain-Based Architecture to Manage User Privacy Preferences on Smart Shared Spaces Privately

Smart shared spaces, such as smart buildings, represent a fast-growing market and can benefit from several sensors that generate data which can be used to improve automatisation, increase efficiency in energy management, and optimise occupant’s comfort. Equally, the smart shared spaces pose many privacy challenges as they are equipped with sensors that can potentially be used to gather data about occupants that they may or may not feel comfortable disclosing, for example, details of their daily routine or occupancy reports of their office. Due to these challenges, it can lead to the opposite results to the optimisation of occupant’s comfort as occupants may not want to use the space due to the privacy concerns. Therefore, it is important to allow the occupants to inform their privacy settings so they feel more confident knowing that their privacy preferences are being respected. We recognise that in some spaces (e.g., shared workplaces) occupants may feel uncomfortable disclosing their preferences if their anonymity is not respected due to the lack of transparency about who can control that data. Thus, this work focuses on a decentralised system based on the SITA privacy model to provide occupants of shared spaces a way to specify and manage their privacy preferences anonymously. We propose a blockchain solution through smart contracts to control how the privacy settings are shared, ensuring that the users have full control of these records. Moreover, it allows traceability over the user’s preferences data usage. Our evaluation shows that the system performs well in regard to time and usability and it can be linked to different smart building management systems. Consequently, this work demonstrates data protection in practice as it puts in place an appropriate technical and organisational measure to safeguard the individual’s privacy by increasing transparency and accountability of smart building data management in accordance to the data protection by design and default approach under the General Data Protection Regulations (GDPR).
Secure Internet Exams Despite Coercion

We study coercion-resistance for online exams. We propose two new properties, Anonymous Submission and Single-Blindness which preserve the anonymity of the links between tests, test takers, and examiners even when the parties coerce one another into revealing secrets. The properties are relevant: not even Remark!, a secure exam protocol that satisfies anonymous marking and anonymous examiners, results to be coercion resistant. Then, we propose a coercion-resistance protocol which satisfies, in addition to known anonymity properties, the two novel properties we have introduced. We prove our claims formally in ProVerif. The paper has also another contribution: it describes an attack (and a fix) to an exponentiation mixnet that Remark! uses to ensure unlinkability. We use the secure version of the mixnet in our new protocol.
Explanation of Black Box AI for GDPR Related Privacy Using Isabelle

In this paper, we present a methodology for constructing explanations for AI classification algorithms. The methodology consists of constructing a model of the context of the application in the Isabelle Infrastructure framework (IIIf) and an algorithm that allows to extract a precise logical rule that specifies the behaviour of the black box algorithm thus allowing to explain it. The explanation is given within the rich logical model of the IIIf. It is thus suitable for human audiences. We illustrate this and validate the methodology on the application example of credit card scoring with special relation to the right of explanation as given by the GDPR.
Quantum walk for SU(1,1)

We propose a scheme to implement the quantum walk for SU(1,1) in the phase space, which generalizes those associated with the Heisenberg-Weyl group. The movement of the walker described by the SU(1,1) coherent states can be visualized on the hyperboloid or the Poincar\'{e} disk. In both one-mode and two-mode realizations, we introduce the corresponding coin-flip and conditional-shift operators for the SU(1,1) group, whose relations with those for Heisenberg-Weyl group are analyzed. The probability distribution, standard deviation and the von Neumann entropy are employed to describe the walking process. The nonorthogonality of the SU(1,1) coherent states precludes the quantum walk for SU(1,1) from the idealized one. However, the overlap between different SU(1,1) coherent states can be reduced by increasing the Bargmann index $k$, which indicates that the two-mode realization provides more possibilities to simulate the idealized quantum walk.
Swarm intelligence machine-learning-assisted progressive global optimization of DNAPL-contaminated aquifer remediation strategy

Abstract Remediation projects of DNAPL-contaminated groundwater generally face difficulties of low contaminant removal rate and high remediation cost. Hence, a machine-learning-assisted mixed-integer multi-objective optimization technique was presented for efficiently programming remediation strategies. A swarm intelligence multi-kernel extreme learning machine (SI-MKELM) was proposed to build a reliable intelligent surrogate model of the multiphase flow numerical simulation model for reducing the computational cost of repetitive CPU-demanding remediation efficiency evaluations, and a hyper-heuristic homotopy algorithm was developed for progressively searching the global optimum of the remediation strategy. The results showed that: (1) The multi-kernel extreme learning machine improved by swarm intelligence algorithm significantly improved the approximation accuracy to the numerical model, and the mean residual and mean relative error were only 0.7596% and 1.0185%, respectively. (2) It only took 0.1 s to run the SI-MKELM. Replacing the numerical model with SI-MKELM considerably reduced the computational burden of the simulation–optimization process and maintained high computational accuracy for optimizing the DNAPL-contaminated aquifer remediation strategy. (3) The hyper-heuristic homotopy algorithm was capable of progressively searching the global optimum, and avoiding premature convergence in the optimization process. It effectively improved the searching ability of the traditional heuristic algorithms.
Policy-Based Holistic Application Management with BPMN and TOSCA

With the wide adoption of cloud computing across technology industries and research institutions, an ever-growing interest in cloud orchestration frameworks has emerged over the past few years. These orchestration frameworks enable the automated provisioning and decommissioning of cloud applications in a timely and efficient manner, but they offer limited or no support for application management. While management functionalities, such as configuring, monitoring and scaling single components, can be directly covered by cloud providers and configuration management tools, holistic management features, such as backing up, testing and updating multiple components, cannot be automated using these approaches. In this paper, we propose a concept to automatically generate executable holistic management workflows based on the TOSCA standard. The practical feasibility of the approach is validated through a prototype implementation and a case study.
Exploring quality adjustment in PPI cloud computing

Cloud computing services (hosting) is an important component of the Producer Price Index (PPI) for data processing, hosting, and related services. The current approach to changes in cloud services is to estimate a price change between the old and new service that is equal to the average of price changes for similar products in the PPI. This method has limitations because it does not specifically account for changes to characteristics such as microprocessor, memory, and data storage, which are key price-determining characteristics that see rapid technological change. In order to estimate price changes more accurately in this ever-evolving industry, we develop time dummy hedonic models. Our models use publicly available data while future BLS models could instead use confidential respondent data for their estimates. One of the challenges of developing models is accounting for the performance of the microprocessors used in the cloud services. One of the cloud service providers in our dataset has a performance benchmark for their cloud services. We calculate models that use this benchmark and compare them to models that use the characteristics of the microprocessors in order to evaluate the appropriateness of using microprocessor characteristics as explanatory variables in future models. The comparison between these two types of models is critical, because none of the other service providers currently has a microprocessor benchmark. We also use a statistical learning technique to select variables for our models. Finally, we discuss the feasibility of applying these models to the PPI in the future.
Human Intention Understanding and Trajectory Planning Based on Multi-modal Data

In the task of Human-Robot Interaction, human beings are at the center of the whole cooperation process. Robots always pay attention to the cooperator’s operation behavior through multi-modal information, constantly speculate on human’s operation intention, and then plan their interaction trajectory in advance. Therefore, understanding human’s operation intention and predicting human’s trajectory play an important role in the interaction between robot and human. This paper presents a framework of human intention reasoning and trajectory prediction based on multi-modal information. It mainly consists of two parts: Firstly, the robot accurately infers the human operation intention by combining four kinds of information: the human behavior identified by GCN-LSTM model, the object type obtained by YOLO, the relationship between verbs in sentences and interested objects and targets extracted by dependency parsing language, and the gesture of handheld objects obtained by GGCNN. Then, after understanding the intention of human beings, combined with some tracks that human beings are walking out of at present, KMP is used to predict the next tracks of human beings, which is the preparation for the trajectory analysis of robots in future human-computer interaction tasks. We verify the framework on several data sets, and the test results show the effectiveness of the proposed framework.
BFAct: Out-of-Distribution Detection with Butterworth Filter Rectified Activations

Out-of-Distribution (OOD) Detection has drawn a lot of attention recently due to it being an essential building block for safely deploying neural network models in real-life applications. The challenge in this field is that modern neural network tends to produce overconfident predictions on OOD data, which work against the principles of OOD detection techniques. To overcome this challenge, we propose Butterworth Filter rectified Activations (BFAct), a technique to rectify activations and drastically alleviate the overconfidence predictions on OOD data. Our work is motivated by an analysis of a neural network’s internal activation and proved to be a surprisingly effective post hoc method for the OOD Detection task. The advantage of using Butterworth Filter is that the passband of the filter has a smooth and monotonically decreasing frequency response, which helps to correct the abnormal activations to normal distribution. BFAct is not only able to generalize on various neural network architectures but also compatible with various OOD score functions. Our main experiments are evaluated on a large-scale OOD Detection benchmark based on ImageNet-1k, which is closer to practical application scenarios. We also conduct experiments on CIFAR-10 and CIFAR-100. The results illustrate that our method outperforms the state-of-the-art on both large-scale and common benchmarks.
Towards Flying Carpet: Dynamics Modeling, and Differential-Flatness-Based Control and Planning

Aerial systems assembled from multiple modules have the potential to perform tasks that are difficult for traditional aerial vehicles. In this work, we propose a novel aerial system, Carpet, which is composed by a matrix of quadrotor modules. In Carpet, a column of quadrotor modules connects to the neighbouring column via revolute joints. By adjusting the joint angles, Carpet is capable of working in flight mode and terrestrial mode. This is the first time that UAV assembly with this configuration is analyzed. The terrestrial mode could potentially increase the energy efficiency of aerial systems. While in flight mode, Carpet can fold up or expand to adapt to different tasks or environments, e.g., curling up to U form can make it more compact and agile when passing through narrow channels. The dynamics of Carpet is investigated. It is found that the entire Carpet in flight mode can produce 5D force/torque, and the joints connecting columns do not need extra actuators. The differential flatness of Carpet is analyzed. The motion controller and the trajectory generator are designed based on the differential flatness. The proposed trajectory planning method is able to guide Carpet to pass through narrow corridors. Numerical simulations are presented, illustrating the feasibility of the proposed Carpet.
Compression of Virtual Learning Images Based on Lossy and Lossless in Cloud Environment

This paper provides a comprehensive introduction to digital image, image compression and overview of E-learning. It presents the basic concepts and features of image compression techniques with different measuring qualities of image in the cloud environment for better storage space.
Interactive Input and Visualization for Planning with Temporal Uncertainty

Abstract When planning series of events or processes, everyone has to cope with temporal uncertainty. Popular examples are holiday planning or train trips. There are several approaches to visualize temporal uncertainty when temporal data and events are already defined, but common research usually does not take uncertainty into account, neither as input nor output. To develop our design, we considered a variety of common approaches for uncertainty visualization and used participatory evaluation to validate our concept. Our design aims at using this uncertainty visualization while sketching the plan interactively. The user may draw and connect a variety of activities using different graphical metaphors as hints for uncertainty. The sketches are immediately interpreted and turned into a visualization to check and validate the resulting plan. To evaluate our new visualization and interactive approach, we conducted a quantitative user study. With an average correctness of 81%, the study shows that the visualization and interaction design work well together and that scheduling plans containing temporal uncertainties can be externalized by the majority of participants without major difficulties.
<i>LBiaP</i>

Abstract Overlapping bundles, that is, shorter lexical bundles that are totally or partially embedded in longer expressions, may prove problematic in the structural and functional classification of bundles. For example, many studies in the literature focus only on four-word lexical bundles and conduct extensive structural and functional analysis of those bundles. However, most scholars have not considered the fact that some 4-word expressions may be embedded in longer expressions. These longer expressions may not only have a different structure but may also carry out a different functional role. The present study introduces the Lexical Bundle Identification and Analysis Program ( LBiaP ), a software tool designed to facilitate lexical bundle research with independent observations of each lexical bundle identified. First, we describe complete overlapping, complete subsumption, and interlocking bundles in detail. We then explain how LBiaP deals with these types of bundles when detected.
Main concepts in immersive journalism

In this chapter, the main goal is to thoroughly examine the concepts of immersion and presence as fundamental definitions and phenomena within immersive journalism. This examination will assume a two-pronged approach. First, the authors use a systematic review approach to investigate how immersion and presence have been theoretically contextualised within key immersive journalism research since its beginnings in the early 2010s. Secondly, the authors connect results from their systematic examination to the wider fields of virtual reality and media studies. With this second step, the goal is to argue that the uses of terms such as immersion and presence in immersive journalism draw from rather old traditions. This, the authors suggest, means that after almost a decade of research, the field should be ready to arrive at a wider conceptual consensus about these terms. By adopting this two-pronged approach and by critically reflecting on the assembly of different sources, the goal of this chapter is to go beyond notions and definitions that are all too briefly presented in previous studies. The authors wish to provide an all-encompassing conceptual understanding of immersion and presence in immersive journalism – a conceptual landmark for immersive journalism as an emergent scientific field – which should serve as a solid basis for future immersive media research and practical endeavours.
Complexity of the Lambek Calculus with One Division and a Negative-Polarity Modality for Weakening

In this paper, we consider a variant of the Lambek calculus allowing empty antecedents. This variant uses two connectives: the left division and a unary modality that occurs only with negative polarity and allows weakening in antecedents of sequents. We define the notion of a proof net for this calculus, which is similar to those for the ordinary Lambek calculus and multiplicative linear logic. We prove that a sequent is derivable in the calculus under consideration if and only if there exists a proof net for it. We present a polynomial-time algorithm for deciding whether an arbitrary given sequent is derivable in this calculus.
On Possibilities for Sensory Research

"On Possibilities for Sensory Research." Material Religion, 19(1), pp. 87–88 Additional informationNotes on contributorsMicaela TerkMicaela Terk is a writer-publisher, designer, and facilitator based in Amsterdam, where she recently graduated from the Sandberg Instituut. Her practice and research stems from her commitment to movement research and somatic literacy as transformative forms of knowledge and perception. terkmicaela@gmail.com
Artistic into national way of life in the epresentation of the child

The content of artistic space as an objective basis for the formation of personality values is revealed. Shown coexistence in the artistic space of pedagogically managed and spontaneous information flows and their role in shaping the value sphere of the child. The definition of artistic intonation as a semantic feature of an artistic product (musical, plastic intonation, logosfery, visual image as rolled intonation) is substantiated and introduced into the pedagogical context. The interpretation of the artistic-intonational way of life as a subjective factor in the formation of a person's artistic value of a person is proposed. The contents of the artistic-intonational way of life in the representation of children are highlighted. The accent is made on the subjectivity of the child in the artistic space as a mechanism for the formation of its values in art. The logic of the change of the artistic-intonational image in the historical and cultural perspective is shown. The author's explanation of the peculiarities of the formation of artistic values of children as objective and deterministic by socio-cultural processes is presented. The objectivity of the formation of subcultures as personal semantic entities, as well as the tendency to deepen the closure of subcultures in the modern art space, which highlights the difficulties of pedagogical influence on the inner world of the child, is demonstrated.