This paper studies a fast optimization method considering both stopping accuracy and riding comfort in Automatic Train Operation (ATO) systems. ATO system plays an important role in the operation of ...a train, but stopping accuracy is a difficult problem. We use a predictive model and minimize the stopping error under the constraint of gear switches. The braking acceleration is a function of velocity and gear. We propose a multi-step method which makes each step solvable with limited computing resources on trains. The method computes a sequence of action outputs at each time interval, and only adopts the first output as the gear action of the next time interval. The experiment shows that the stopping accuracy and riding comfort are better than the traditional PID method. The problem is motivated by a practical project for the automatic control of Dongguan-Huizhou intercity railway. Various experiments are conducted based on the real data and scenarios. It is demonstrated that this method is robust and easy to use in different railway lines.
Due to the increasing integration of renewable resources and the deployment of energy storage units at the power distribution level, conventional deterministic approaches may not be suitable or ...effective for evaluating the reliability of active distribution networks anymore. This paper proposes a new method to evaluate the active distribution system reliability including microgrid and energy storage. The power output of distributed generator (DG) within the microgrid is first calculated based on the approach of generalized capacity outage tables (GCOTs). Then Monte Carlo Simulation (MCS) is utilized for performing power system reliability evaluation. The results obtained considering different energy storage capacities are compared. Furthermore, real-time pricing (RTP) strategy is considered in optimizing the control strategy of the energy storage device and the corresponding reliability indices are recalculated.
Ubuntu is an open source software platform that runs everywhere from the smartphone, the tablet and the PC to the server and the cloud. In Ubuntu, there are many self-contained or third-party ...software packages for different use, and a bug report in Ubuntu could affect one or more packages simultaneously. Identifying the common package bugs in Ubuntu can help both developers and users better understand the packages they are developing or using, and also provide further guidelines to developers of similar packages in the future. In this paper, we perform a large-scale empirical study of common package bugs on Ubuntu by leveraging topic modeling. By analyzing a total of 240,097 bug reports, we identify 3 general bugs that are common to all Ubuntu packages, i.e., Graphical User Interface (GUI), Maintenance, and Runtime bugs. Moreover, we categorize top-100 packages with most number of bug reports into 6 categories (i.e., graphics, internet, office, sound and video, system management, and kernel), and identify domain-specific bugs for each category.
Current state-of-the-art automatic software repair (ASR) techniques rely heavily on incomplete specifications, e.g., test suites, to generate repairs. This, however, may render ASR tools to generate ...incorrect repairs that do not generalize. To assess patch correctness, researchers have been following two typical ways separately: (1) Automated annotation, wherein patches are automatically labeled by an independent test suite (ITS) - a patch passing the ITS is regarded as correct or generalizable, and incorrect otherwise, (2) Author annotation, wherein authors of ASR techniques annotate correctness labels of patches generated by their and competing tools by themselves. While automated annotation fails to prove that a patch is actually correct, author annotation is prone to subjectivity. This concern has caused an on-going debate on appropriate ways to assess the effectiveness of numerous ASR techniques proposed recently. To address this concern, we propose to assess reliability of author and automated annotations on patch correctness assessment. We do this by first constructing a gold set of correctness labels for 189 randomly selected patches generated by 8 state-of-the-art ASR techniques through a user study involving 35 professional developers as independent annotators. By measuring inter-rater agreement as a proxy for annotation quality - as commonly done in the literature - we demonstrate that our constructed gold set is on par with other high-quality gold sets. We then compare labels generated by author and automated annotations with this gold set to assess reliability of the patch assessment methodologies. We subsequently report several findings and highlight implications for future studies.
As Android platform becomes more and more popular, a large amount of Android applications have been developed. When developers design and implement Android applications, power consumption management ...is an important factor to consider since it affects the usability of the applications. Thus, it is important to help developers adopt proper strategies to manage power consumption. Interestingly, today, there is a large number of Android application repositories made publicly available in sites such as GitHub. These repositories can be mined to help crystalize common power management activities that developers do. These in turn can be used to help other developers to perform similar tasks to improve their own Android applications.In this paper, we present an empirical study of power management commits in Android applications. Our study extends that of Moura et al. who perform an empirical studyon energy aware commits; however they do not focus on Android applications and only a few of the commits that they study come from Android applications. Android applications are often different from other applications (e.g., those running on a server) due to the issue of limited battery life and the use of specialized APIs. As subjects of our empirical study, we obtain a list of open source Android applications from F-Droid and crawl their commits from Github. We get 468 power management commits after we filter the commits using a set of keywords and by performing manual analysis. These 468 power management commits are from 154 different Android applications and belong to 15 different application categories. Furthermore, we use open card sort to categorize these power management commits and we obtain 6 groups which correspond to different power management activities. Our study also reveals that for different kinds of Android application (e.g., Games, Connectivity, Navigation, etc.), the dominant power management activities differ.For example, the percentageof power management commits belonging to Power Adaptation activity is larger for Navigation applications than those belonging to other categories.
Dual modality PET/CT has now essentially replaced PET in clinical practice and provided an opportunity to improve image segmentation through the high resolution, lower noise CT data. Thus far most ...research efforts have concentrated on segmentation of PET-only data. In this work we propose a systematic solution for the automated segmentation of brain PET/CT images into gray, white matter and CSF regions with the MAP-MRF model. Our approach takes advantage of the full information available from the combined scan. A PET/CT image pair and its segmentation result are modelled as a random field triplet, and segmentation is eventually achieved by solving a maximum a posteriori (MAP) problem using the expectation-maximization (EM) algorithm with simulated annealing. We compared the novel algorithm to two widely used PET-only based segmentation methods in the SPM5 toolbox and the VBM toolbox for simulation and patient data. Our results suggest that using the proposed approach substantially improves the accuracy of the delineation of brain structures.
Parametric FDG-PET data offer the potential for an automated identification of the different dementia syndromes. Principal component analysis (PCA) can be used for feature extraction in FDG-PET. ...However, standard PCA is not always successful in delineating the features that have the best discrimination ability. We report a genetic algorithm-based method to identify an optimal combination of eigenvectors so that the resultant features are capable of successfully separating patients with suspected Alzheimer's disease and frontotemporal dementia from normal controls. We compared our approach with standard PCA on a set of 210 clinical cases and improved the performance in separating the dementia types with an accuracy of 90.0% and a Kappa statistic of 0.849. There was very good agreement between the automated technique and the diagnosis given by clinicians.
The theory of microwave holography is introduced in the paper firstly. And then the measurement components and test results of Seshan 25m radio telescope (parabolic antenna) are described. And the ...system accuracy is also tested actually.
PDF
