Survey of Distributed Decision

We survey the recent distributed computing literature on checking whether a given distributed system configuration satisfies a given boolean predicate, i.e., whether the configuration is legal or illegal w.r.t. that predicate. We consider classical distributed computing environments, including mostly synchronous fault-free network computing (LOCAL and CONGEST models), but also asynchronous crash-prone shared-memory computing (WAIT-FREE model), and mobile computing (FSYNC model)

Experimental Verification of Inertial Navigation with MEMS for Forensic Investigation of Vehicle Collision

This paper studies whether low-grade inertial sensors can be adequate source of data for the accident characterization and the estimation of vehicle trajectory near crash. Paper presents outcomes of an experiment carried out in accredited safety performance assessment facility in which full-size passenger car was crashed and the recordings of different types of motion sensors were compared to investigate practical level of accuracy of consumer grade sensors versus reference equipment and cameras. Inertial navigation system was developed by combining motion sensors of different dynamic ranges to acquire and process vehicle crash data. Vehicle position was reconstructed in three-dimensional space using strap-down inertial mechanization. Difference between the computed trajectory and the ground-truth position acquired by cameras was on decimeter level within short time window of 750 ms. Experiment findings suggest that inertial sensors of this grade, despite significant stochastic variations and imperfections, can be valuable for estimation of velocity vector change, crash severity, direction of impact force, and for estimation of vehicle trajectory in crash proximity

SAT and CP: Parallelisation and Applications

This thesis is considered with the parallelisation of solvers which search for either an arbitrary, or an optimum, solution to a problem stated in some formal way. We discuss the parallelisation of two solvers, and their application in three chapters.In the first chapter, we consider SAT, the decision problem of propositional logic, and algorithms for showing the satisfiability or unsatisfiability of propositional formulas. We sketch some proof-theoretic foundations which are related to the strength of different algorithmic approaches. Furthermore, we discuss details of the implementations of SAT solvers, and show how to improve upon existing sequential solvers. Lastly, we discuss the parallelisation of these solvers with a focus on clause exchange, the communication of intermediate results within a parallel solver. The second chapter is concerned with Contraint Programing (CP) with learning. Contrary to classical Constraint Programming techniques, this incorporates learning mechanisms as they are used in the field of SAT solving. We present results from parallelising CHUFFED, a learning CP solver. As this is both a kind of CP and SAT solver, it is not clear which parallelisation approaches work best here. In the final chapter, we will discuss Sorting networks, which are data oblivious sorting algorithms, i. e., the comparisons they perform do not depend on the input data. Their independence of the input data lends them to parallel implementation. We consider the question how many parallel sorting steps are needed to sort some inputs, and present both lower and upper bounds for several cases

Self-Stabilizing Supervised Publish-Subscribe Systems

In this paper we present two major results: First, we introduce the first self-stabilizing version of a supervised overlay network by presenting a self-stabilizing supervised skip ring. Secondly, we show how to use the self-stabilizing supervised skip ring to construct an efficient self-stabilizing publish-subscribe system. That is, in addition to stabilizing the overlay network, every subscriber of a topic will eventually know all of the publications that have been issued so far for that topic. The communication work needed to processes a subscribe or unsubscribe operation is just a constant in a legitimate state, and the communication work of checking whether the system is still in a legitimate state is just a constant on expectation for the supervisor as well as any process in the system

How much body is there in the voice? The comparative analysis of Maria Callas’s and Sondra Radvanovsky’s portrayals of Luigi Cherubini’s Medea

Staging Luigi Cherubini’s opera Medea is a venture that has rarely been taken on even by major opera houses. The main reason is an extremely demanding leading role, in terms of its vocal, physical, and psychological aspects. Known for uniting these aspects in her portrayals of tragic opera heroines, it is no surprise that Maria Callas was one of the few ideal exponents of this role. To assess her performance of Medea, we had at our disposal one studio recording, several live audio recordings, some short video excerpts, and photos. However, no integral video of the opera staging is commercially available. Deciding to use a lack of visual trace of Callas’s performance to our advantage, we came to the core idea for this paper. We propose a question: is the body aspect missing in the audio performance or is it even more present? In order to answer this question we explored the relationship between implicit gestures in music and their correspondence with the corporeality of the voice, i.e. gestures in vocal performance. The starting point of our methodological frame is Robert Hatten’s theory of musical gesture and Arnie Cox’s exploration in the field of the embodied experience of music perception. The embodiment of the psychological-archetypal dimension of Medea’s character is analyzed on two levels – that of musical gestures and that of performative gestures, with an additional aim to observe how their synchronicity affects voice corporeality. Missing the complete video leads the research further, posing the question: how does the experience of voice-corporeality change with the visual aspect of the performance? Therefore, we chose Sondra Radvanovsky’s body-engaging performance of Medea in the 2022 production of Metropolitan Opera. We submitted it to the same analytical process, for the purpose of determining how the additional layer of body gestures enhances or diminishes the effect of voice corporeality

Machine learning computational tools to assist the performance of systematic reviews : A mapping review

Within evidence-based practice (EBP), systematic reviews (SR) are considered the highest level of evidence in that they summarize the best available research and describe the progress in a determined field. Due its methodology, SR require significant time and resources to be performed; they also require repetitive steps that may introduce biases and human errors. Machine learning (ML) algorithms therefore present a promising alternative and a potential game changer to speed up and automate the SR process. This review aims to map the current availability of computational tools that use ML techniques to assist in the performance of SR, and to support authors in the selection of the right software for the performance of evidence synthesis. The mapping review was based on comprehensive searches in electronic databases and software repositories to obtain relevant literature and records, followed by screening for eligibility based on titles, abstracts, and full text by two reviewers. The data extraction consisted of listing and extracting the name and basic characteristics of the included tools, for example a tool's applicability to the various SR stages, pricing options, open-source availability, and type of software. These tools were classified and graphically represented to facilitate the description of our findings. A total of 9653 studies and 585 records were obtained from the structured searches performed on selected bibliometric databases and software repositories respectively. After screening, a total of 119 descriptions from publications and records allowed us to identify 63 tools that assist the SR process using ML techniques. This review provides a high-quality map of currently available ML software to assist the performance of SR. ML algorithms are arguably one of the best techniques at present for the automation of SR. The most promising tools were easily accessible and included a high number of user-friendly features permitting the automation of SR and other kinds of evidence synthesis reviews. The online version contains supplementary material available at 10.1186/s12874-022-01805-4

Historical and Heritage Sustainability for the Revival of Ancient Wine-Making Techniques and Wine Styles

ReviewThe purpose of this review is to provide a general description of ancient winemaking techniques and wine styles that were most lauded in antiquity, in support of their revival and dissemination today. From the first fully excavated winery, dating from the late fifth to the early fourth millennium BC, the gentle crushing of grapes by foot and the probable absence of maceration indicate that most wines were made with the aim of reducing astringency. The oxidative nature of winemaking would have resulted in rapid browning, so that wines made from red grapes would have had a similar color to those made from white grapes after being aged in clay vats for several years. The difficulty in preventing the wine surface contact with the air would have resulted in biological ageing under the yeast pellicle being a common occurrence. This phenomenon was not considered a flaw, but a characteristic feature of highly prized wines. Dried grapes were used to make sweet wines, which were also highly prized, therefore justifying the construction of dedicated facilities. The addition of boiled juices, salt, resins, mixtures of herbs, spices, fruit juices, flowers, or honey to the wines would have increased their taste pleasantness while improving their preservability and medicinal properties. Indeed, today’s preference for flavored wines with a soft mouthfeel seems to have been representative of the ancient elite consumers. Overall, the technical interpretation of winemaking described in this review will provide solid historical support for the current rebirth of ancient production methods, particularly those using pottery vesselsinfo:eu-repo/semantics/publishedVersio

Search for Dark Matter and Supersymmetry with a Compressed Mass Spectrum in the Vector Boson Fusion Topology in Proton-Proton Collisions at √s = 8 TeV

A first search for pair production of dark matter candidates through vector boson fusion in proton-proton collisions at √s = 8  TeV is performed with the CMS detector. The vector boson fusion topology enhances missing transverse momentum, providing a way to probe supersymmetry, even in the case of a compressed mass spectrum. The data sample corresponds to an integrated luminosity of 18.5  fb^(−1), recorded by the CMS experiment. The observed dijet mass spectrum is consistent with the standard model expectation. In an effective field theory, dark matter masses are explored as a function of contact interaction strength. The most stringent limit on bottom squark production with mass below 315 GeV is also reported, assuming a 5 GeV mass difference with respect to the lightest neutralino