Collaboration monitoring in software process is important to check if the collaboration is indeed happening as planned, but there are few approaches that define how to measure and monitor collaboration. By assessing c...
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In a mixed environment of autonomous driverless vehicles and human driven vehicles operating on the same road, identifying intentions of human drivers and interacting with them in a compliant and responsible manner be...
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In a mixed environment of autonomous driverless vehicles and human driven vehicles operating on the same road, identifying intentions of human drivers and interacting with them in a compliant and responsible manner becomes a challenging problem for the driverless vehicles. In this paper, the problem of vehicle interaction at an intersection merging scenario is formulated as an Intention-Aware motion planning problem using the tools from Mixed Observability Markov Decision Process (MOMDP). We utilize the tools from recent intention aware planning framework to demonstrate a merging behavior in the presence of human drivers by trying to infer and act according to the intentions of the human drivers. A driver behavior model for T-junction intersections is developed in order to calculate the probabilistic state transition functions of the MOMDP model. With proposed solution, it is demonstrated that using intention aware planning improves performance in comparison to present time to merge approach by lowering accident probability and intersection navigation duration. The proposed method is tested on a real autonomous vehicle (AV) in the presence of human driven vehicles to validate our approach.
In this paper we carried out designing and implementing of a target tracking data fusion algorithm based on a two stages graph solution using the computational model Gamma (General Abstract Model for Multiset mAnipula...
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In this paper we carried out designing and implementing of a target tracking data fusion algorithm based on a two stages graph solution using the computational model Gamma (General Abstract Model for Multiset mAnipulation). The proposed solution is the first parallel implementation of the method PPTS (Pairs of Plots in Two Stages). For this, we employed three Gamma implementations, where two of them exploited the resources of a parallel hardware environment, one using the MPI (Message Passing Interface) and the other one GPU (Graphics Processing Unit). Thus, the studied algorithm was evaluated from the parallelism exploited and finally was carried out a performance analysis of this algorithm in the three Gamma implementations used. The aim of this study is to provide an implementation on a real problem using for this the paradigm Gamma, which contributes to the implementations of the Gamma computational model, since it enables the performance analysis of these implementations and provides some suggestions for possible improvements. In addition, this work contributes to the PPTS method since it provides the parallelization of the first stage.
High Performance Computing (HPC) aggregates computing power in order to solve large and complex problems in different knowledge areas. Nowadays, HPC users can utilize virtualized infrastructures as a low-cost alternat...
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ISBN:
(纸本)9781479986989
High Performance Computing (HPC) aggregates computing power in order to solve large and complex problems in different knowledge areas. Nowadays, HPC users can utilize virtualized infrastructures as a low-cost alternative to deploy their applications. However, virtualization brings some challenges for HPC, specially in regard to overhead caused by hyper visors. In this work, our main goal is to analyze the performance of two hyper visors (KVM and Virtual Box) under HPC activities, considering full virtualization, and Para virtualization approaches. We used the HPC Challenge Benchmark (HPCC) to evaluate processor, RAM, inter-process communication and network communication performance. Our results show KVM in Para virtualization mode has a similar performance of a native cluster.
PepExplorer aids in the biological interpretation of de novo sequencing results;this is accomplished by assembling a list of homolog proteins obtained by aligning results from widely adopted de novo sequencing tools a...
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The rapid change of trading values from tangible assets to Intelectual Property has put both businesses and academia in a race to acquire and protect the rights to exploit such property. This is mainly accomplished in...
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The rapid change of trading values from tangible assets to Intelectual Property has put both businesses and academia in a race to acquire and protect the rights to exploit such property. This is mainly accomplished in the form of patent issuing by the governments, being time consuming and complicated due to the vast amount of documents that need to be analyzed in order to assert the novelty or validity of a patent application. Patent information retrieval research is thus growing quickly to support document analysis across multiple domains and information systems. One of the big challenges in patent analysis is the identification of the elements of innovation (concepts, processes, materials) and the relations between them, in the patent text. This paper presents a method for extracting semantic information from patent claims by using semantic annotations on phrasal structures, abstracting domain ontology information and outputting ontology-friendly structures to achieve generalization. An extraction system built upon the method is briefly evaluated on a document sample from INPI, the Brazilian patent office, a challenging information source.
Purpose: A calibrationless parallel imaging reconstruction method, termed simultaneous autocalibrating and k-space estimation (SAKE), is presented. It is a data-driven, coil-by-coil reconstruction method that does not...
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Heart rate variability (HRV) is known to be one of the representative ECG-derived features that are useful for diverse pervasive healthcare applications. The advancement in daily physiological monitoring technology is...
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ISBN:
(纸本)9781424479276
Heart rate variability (HRV) is known to be one of the representative ECG-derived features that are useful for diverse pervasive healthcare applications. The advancement in daily physiological monitoring technology is enabling monitoring of HRV in people's everyday lives. In this study, we evaluate the feasibility of measuring ECG-derived features such as HRV, only using the smartphone-integrated ECG sensors system named Sinabro. We conducted the evaluation with 13 subjects in five predetermined smartphone use cases. The result shows the potential that the smartphone-based sensing system can support daily monitoring of ECG-derived features;The average errors of HRV over all participants ranged from 1.65% to 5.83% (SD: 2.54～10.87) for five use cases. Also, all of individual HRV parameters showed less than 5% of average errors for the three reliable cases.
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