Ionospheric Neutral Mass Spectroscopy

Understanding neutral masses in the ionosphere, especially in the E- and D-regions, is a very challenging endeavor. This is due to the high density of neutral masses at this height and the speed at which sounding rockets travel. These factors limit the ability to understand the quantity and quality of neutral masses in these regions; the density of these masses and the percentage of different masses present is not well resolved. Therefore, there exists a need to further investigate neutral mass in the ionosphere, and this research aims at presenting a possible instrument for doing so. We conducted experiments to evaluate whether a residual gas analyzer (RGA) could be used as a neutral mass spectrometer for application in the E- and D-region ionosphere. The basic experimental configuration was a roughing vacuum pump attached to a turbo vacuum which together brought the configuration to a pressure between 5 × 10−9 to 2 × 10−8 Torr. With the RGA within the vacuum, data was collected on the trends found, accuracy, and scanning speed of the instrument. Ultimately, the RGA was able to collect at a rate of 9 seconds per AMU studied with a deviation of around ±10−10 Torr when running in secondary electron multiplier mode (SEM). The results did not support the potential flight of a RGA on future sounding rocket campaigns for studying neutral masses within the ionosphere, however solutions around the limitations of the device are offered

On the CALM principle for BSP computation

In recent times, considerable emphasis has been given to two apparently disjoint research topics: data-parallel and eventually consistent, distributed systems. In this paper we propose a study on an eventually consistent, dataparallel computational model, the keystone of which is provided by the recent finding that a class of programs exists that can be computed in an eventually consistent, coordination-free way: monotonic programs. This principle is called CALM and has been proven by Ameloot et al. for distributed, asynchronous settings. We advocate that CALM should be employed as a basic theoretical tool also for data-parallel systems, wherein computation usually proceeds synchronously in rounds and where communication is assumed to be reliable. We deem this problem relevant and interesting, especially for what concerns parallel workflow optimization, and make the case that CALM does not hold in general for dataparallel systems if the techniques developed by Ameloot et al. are directly used. In this paper we sketch how, using novel techniques, the satisfiability of the if direction of the CALM principle can still be obtained, although just for a subclass of monotonic queries

State-of-the-art on evolution and reactivity

This report starts by, in Chapter 1, outlining aspects of querying and updating resources on the Web and on the Semantic Web, including the development of query and update languages to be carried out within the Rewerse project. From this outline, it becomes clear that several existing research areas and topics are of interest for this work in Rewerse. In the remainder of this report we further present state of the art surveys in a selection of such areas and topics. More precisely: in Chapter 2 we give an overview of logics for reasoning about state change and updates; Chapter 3 is devoted to briefly describing existing update languages for the Web, and also for updating logic programs; in Chapter 4 event-condition-action rules, both in the context of active database systems and in the context of semistructured data, are surveyed; in Chapter 5 we give an overview of some relevant rule-based agents frameworks

On Web-based Domain-Specific Language for Internet of Things

This paper discusses the challenges of the Internet of Things programming. Sensing and data gathering from the various sources are often the key elements of applications for Smart Cities. So, the effective programming models for them are very important. In this article, we discuss system software models and solutions, rather than network related aspects. In our paper, we present the web-based domain-specific language for Internet of Things applications. Our goal is to present the modern models for data processing in Internet of Things and Smart Cities applications. In our view, the use of this kind of tools should seriously reduce the time to develop new applications.Comment: submitted to ICUMT 201

Extracting time-frequency feature of single-channel vastus medialis EMG signals for knee exercise pattern recognition

© 2017 Zhang et al. This is an open access article distributed under the terms of the Creative Commons Attribution License, which permits unrestricted use, distribution, and reproduction in any medium, provided the original author and source are credited. The EMG signal indicates the electrophysiological response to daily living of activities, particularly to lower-limb knee exercises. Literature reports have shown numerous benefits of the Wavelet analysis in EMG feature extraction for pattern recognition. However, its application to typical knee exercises when using only a single EMG channel is limited. In this study, three types of knee exercises, i.e., flexion of the leg up (standing), hip extension from a sitting position (sitting) and gait (walking) are investigated from 14 healthy untrained subjects, while EMG signals from the muscle group of vastus medialis and the goniometer on the knee joint of the detected leg are synchronously monitored and recorded. Four types of lower-limb motions including standing, sitting, stance phase of walking, and swing phase of walking, are segmented. The Wavelet Transform (WT) based Singular Value Decomposition (SVD) approach is proposed for the classification of four lower-limb motions using a single-channel EMG signal from the muscle group of vastus medialis. Based on lower-limb motions from all subjects, the combination of five-level wavelet decomposition and SVD is used to comprise the feature vector. The Support Vector Machine (SVM) is then configured to build a multiple-subject classifier for which the subject independent accuracy will be given across all subjects for the classification of four types of lower-limb motions. In order to effectively indicate the classification performance, EMG features from time-domain (e.g., Mean Absolute Value (MAV), Root-Mean-Square (RMS), integrated EMG (iEMG), Zero Crossing (ZC)) and frequency-domain (e.g., Mean Frequency (MNF) and Median Frequency (MDF)) are also used to classify lower-limb motions. The five-fold cross validation is performed and it repeats fifty times in order to acquire the robust subject independent accuracy. Results show that the proposed WT-based SVD approach has the classification accuracy of 91.85% ±0.88% which outperforms other feature models

(I) A Declarative Framework for ERP Systems(II) Reactors: A Data-Driven Programming Model for Distributed Applications

To those who can be swayed by argument and those who know they do not have all the answers This dissertation is a collection of six adapted research papers pertaining to two areas of research. (I) A Declarative Framework for ERP Systems: • POETS: Process-Oriented Event-driven Transaction Systems. The paper describes an ontological analysis of a small segment of the enterprise domain, namely the general ledger and accounts receivable. The result is an event-based approach to designing ERP systems and an abstract-level sketch of the architecture. • Compositional Specification of Commercial Contracts. The paper de-scribes the design, multiple semantics, and use of a domain-specific lan-guage (DSL) for modeling commercial contracts. • SMAWL: A SMAll Workflow Language Based on CCS. The paper show

Algorithm Diversity for Resilient Systems

Diversity can significantly increase the resilience of systems, by reducing the prevalence of shared vulnerabilities and making vulnerabilities harder to exploit. Work on software diversity for security typically creates variants of a program using low-level code transformations. This paper is the first to study algorithm diversity for resilience. We first describe how a method based on high-level invariants and systematic incrementalization can be used to create algorithm variants. Executing multiple variants in parallel and comparing their outputs provides greater resilience than executing one variant. To prevent different parallel schedules from causing variants' behaviors to diverge, we present a synchronized execution algorithm for DistAlgo, an extension of Python for high-level, precise, executable specifications of distributed algorithms. We propose static and dynamic metrics for measuring diversity. An experimental evaluation of algorithm diversity combined with implementation-level diversity for several sequential algorithms and distributed algorithms shows the benefits of algorithm diversity

Counter Machines and Distributed Automata: A Story about Exchanging Space and Time

We prove the equivalence of two classes of counter machines and one class of distributed automata. Our counter machines operate on finite words, which they read from left to right while incrementing or decrementing a fixed number of counters. The two classes differ in the extra features they offer: one allows to copy counter values, whereas the other allows to compute copyless sums of counters. Our distributed automata, on the other hand, operate on directed path graphs that represent words. All nodes of a path synchronously execute the same finite-state machine, whose state diagram must be acyclic except for self-loops, and each node receives as input the state of its direct predecessor. These devices form a subclass of linear-time one-way cellular automata.Comment: 15 pages (+ 13 pages of appendices), 5 figures; To appear in the proceedings of AUTOMATA 2018