Modeling and Analyzing Adaptive User-Centric Systems in Real-Time Maude

Pervasive user-centric applications are systems which are meant to sense the presence, mood, and intentions of users in order to optimize user comfort and performance. Building such applications requires not only state-of-the art techniques from artificial intelligence but also sound software engineering methods for facilitating modular design, runtime adaptation and verification of critical system requirements. In this paper we focus on high-level design and analysis, and use the algebraic rewriting language Real-Time Maude for specifying applications in a real-time setting. We propose a generic component-based approach for modeling pervasive user-centric systems and we show how to analyze and prove crucial properties of the system architecture through model checking and simulation. For proving time-dependent properties we use Metric Temporal Logic (MTL) and present analysis algorithms for model checking two subclasses of MTL formulas: time-bounded response and time-bounded safety MTL formulas. The underlying idea is to extend the Real-Time Maude model with suitable clocks, to transform the MTL formulas into LTL formulas over the extended specification, and then to use the LTL model checker of Maude. It is shown that these analyses are sound and complete for maximal time sampling. The approach is illustrated by a simple adaptive advertising scenario in which an adaptive advertisement display can react to actions of the users in front of the display.Comment: In Proceedings RTRTS 2010, arXiv:1009.398

Timed Automata Semantics for Analyzing Creol

We give a real-time semantics for the concurrent, object-oriented modeling language Creol, by mapping Creol processes to a network of timed automata. We can use our semantics to verify real time properties of Creol objects, in particular to see whether processes can be scheduled correctly and meet their end-to-end deadlines. Real-time Creol can be useful for analyzing, for instance, abstract models of multi-core embedded systems. We show how analysis can be done in Uppaal.Comment: In Proceedings FOCLASA 2010, arXiv:1007.499

A Study of Realtime Summarization Metrics

Unexpected news events, such as natural disasters or other human tragedies, create a large volume of dynamic text data from official news media as well as less formal social media. Automatic real-time text summarization has become an important tool for quickly transforming this overabundance of text into clear, useful information for end-users including affected individuals, crisis responders, and interested third parties. Despite the importance of real-time summarization systems, their evaluation is not well understood as classic methods for text summarization are inappropriate for real-time and streaming conditions. The TREC 2013-2015 Temporal Summarization (TREC-TS) track was one of the first evaluation campaigns to tackle the challenges of real-time summarization evaluation, introducing new metrics, ground-truth generation methodology and dataset. In this paper, we present a study of TREC-TS track evaluation methodology, with the aim of documenting its design, analyzing its effectiveness, as well as identifying improvements and best practices for the evaluation of temporal summarization systems

Wearable Fall Detector Using Recurrent Neural Networks

Falls have become a relevant public health issue due to their high prevalence and negative effects in elderly people. Wearable fall detector devices allow the implementation of continuous and ubiquitous monitoring systems. The effectiveness for analyzing temporal signals with low energy consumption is one of the most relevant characteristics of these devices. Recurrent neural networks (RNNs) have demonstrated a great accuracy in some problems that require analyzing sequential inputs. However, getting appropriate response times in low power microcontrollers remains a difficult task due to their limited hardware resources. This work shows a feasibility study about using RNN-based deep learning models to detect both falls and falls’ risks in real time using accelerometer signals. The effectiveness of four different architectures was analyzed using the SisFall dataset at different frequencies. The resulting models were integrated into two different embedded systems to analyze the execution times and changes in the model effectiveness. Finally, a study of power consumption was carried out. A sensitivity of 88.2% and a specificity of 96.4% was obtained. The simplest models reached inference times lower than 34 ms, which implies the capability to detect fall events in real-time with high energy efficiency. This suggests that RNN models provide an effective method that can be implemented in low power microcontrollers for the creation of autonomous wearable fall detection systems in real-time

Fuzzy approach to multimedia faulty module replacement

For non-real time multimedia systems, we present a fuzzy approach to replacing the faulty module. After analyzing the nature of the random and pseudo-random test sequences applied to a module under test, we obtain the aliasing fault coverage between the random and pseudo-random sequences. The activity probability features of intermittent faults in the module under test are discussed based on the Markov chain model. Results on real examples are presented to demonstrate the effectiveness of the proposed fuzzy replacement approac

SHARP: Automated monitoring of spacecraft health and status

Briefly discussed here are the spacecraft and ground systems monitoring process at the Jet Propulsion Laboratory (JPL). Some of the difficulties associated with the existing technology used in mission operations are highlighted. A new automated system based on artificial intelligence technology is described which seeks to overcome many of these limitations. The system, called the Spacecraft Health Automated Reasoning Prototype (SHARP), is designed to automate health and status analysis for multi-mission spacecraft and ground data systems operations. The system has proved to be effective for detecting and analyzing potential spacecraft and ground systems problems by performing real-time analysis of spacecraft and ground data systems engineering telemetry. Telecommunications link analysis of the Voyager 2 spacecraft was the initial focus for evaluation of the system in real-time operations during the Voyager spacecraft encounter with Neptune in August 1989

Analyzing the effect of gain time on soft task scheduling policies in real-time systems

In hard real-time systems, gain time is defined as the difference between the Worst Case Execution Time (WCET) of a hard task and its actual processor consumption at runtime. This paper presents the results of an empirical study about how the presence of a significant amount of gain time in a hard real-time system questions the advantages of using the most representative scheduling algorithms or policies for aperiodic or soft tasks in fixed-priority preemptive systems. The work presented here refines and complements many other studies in this research area in which such policies have been introduced and compared. This work has been performed by using the authors' testing framework for soft scheduling policies, which produces actual, synthetic, randomly generated applications, executes them in an instrumented Real-Time Operating System (RTOS), and finally processes this information to obtain several statistical outcomes. The results show that, in general, the presence of a significant amount of gain time reduces the performance benefit of the scheduling policies under study when compared to serving the soft tasks in background, which is considered the theoretical worst case. In some cases, this performance benefit is so small that the use of a specific scheduling policy for soft tasks is questionable. © 2012 IEEE.This work is partially funded by research projects PROMETEO/2008/051, CSD2007-022, and TIN2008-04446.Búrdalo Rapa, LA.; Terrasa Barrena, AM.; Espinosa Minguet, AR.; García Fornes, AM. (2012). Analyzing the effect of gain time on soft task scheduling policies in real-time systems. IEEE Transactions on Software Engineering. 38(6):1305-1318. https://doi.org/10.1109/TSE.2011.95S1305131838