Search results for "Benchmark"
showing 10 items of 310 documents
Assessing Sustainability: Research Directions and Relevant Issues
2016
The growing research debate concerning sustainability and its applications in interdisciplinary domain represents a conjunction point where basic and applied science (scientific computation and applications in all areas of sciences, engineering, technology, industry, economics, life sciences and social sciences), but also qualified practitioners, compare and discuss advances in order to substance what we consider a the future perspective: “applied sustainability”. A relevant issue in order to compare and benchmark different position is the “sustainability performance assessment”. It means to discuss in a general view critical aspects and general issues in order to propose research direction…
Status of ceramic breeder pebble bed thermo-mechanics R&D and impact on breeder material mechanical strength
2012
Abstract Among the international fusion solid breeder blanket community, there exists steady progress on the experimental, phenomenological, and numerical characterizations of the pebble bed effective thermo physical and mechanical properties, and of thermomechanic state of the bed under prototypical operating conditions. This paper summarizes recent achievements in pebble bed thermomechanics that were carried out by members of the IEA Fusion Nuclear Technology Subtask I Solid Breeding Blanket. A major goal is on developing predictive capability while identifying a pre-conditioned equilibrium stress state that would warrant pebble bed integrity during operations. The paper reviews and synth…
A random-walk benchmark for single-electron circuits
2021
Mesoscopic integrated circuits aim for precise control over elementary quantum systems. However, as fidelities improve, the increasingly rare errors and component crosstalk pose a challenge for validating error models and quantifying accuracy of circuit performance. Here we propose and implement a circuit-level benchmark that models fidelity as a random walk of an error syndrome, detected by an accumulating probe. Additionally, contributions of correlated noise, induced environmentally or by memory, are revealed as limits of achievable fidelity by statistical consistency analysis of the full distribution of error counts. Applying this methodology to a high-fidelity implementation of on-dema…
Visual Marker Guided Point Cloud Registration in a Large Multi-Sensor Industrial Robot Cell
2018
This paper presents a benchmark and accuracy analysis of 3D sensor calibration in a large industrial robot cell. The sensors used were the Kinect v2 which contains both an RGB and an IR camera measuring depth based on the time-of-flight principle. The approach taken was based on a novel procedure combining Aruco visual markers, methods using region of interest and iterative closest point. The calibration of sensors is performed pairwise, exploiting the fact that time-of-flight sensors can have some overlap in the generated point cloud data. For a volume measuring 10m × 14m × 5m a typical accuracy of the generated point cloud data of 5–10cm was achieved using six sensor nodes.
A Structural $\mathcal{ SHOIN(D)}$ Ontology Model for Change Modelling
2013
This paper presents a complete structural ontology model suited for change modelling on \(\mathcal{ SHOIN(D)}\) ontologies. The application of this model is illustrated along the paper through the description of an ontology example inspired by the UOBM ontology benchmark and its evolution.
Robust Hand Gestures Recognition Using a Deep CNN and Thermal Images
2021
Medical systems and assistive technologies, human-computer interaction, human-robot interaction, industrial automation, virtual environment control, sign language translation, crisis and disaster management, entertainment and computer games, and so on all use RGB cameras for hand gesture recognition. However, their performance is limited especially in low-light conditions. In this paper, we propose a robust hand gesture recognition system based on high-resolution thermal imaging that is light-independent. A dataset of 14,400 thermal hand gestures is constructed, separated into two color tones. We also propose using a deep CNN to classify high-resolution hand gestures accurately. The propose…
Feature selection using support vector machines and bootstrap methods for ventricular fibrillation detection
2012
Early detection of ventricular fibrillation (VF) is crucial for the success of the defibrillation therapy in automatic devices. A high number of detectors have been proposed based on temporal, spectral, and time-frequency parameters extracted from the surface electrocardiogram (ECG), showing always a limited performance. The combination ECG parameters on different domain (time, frequency, and time-frequency) using machine learning algorithms has been used to improve detection efficiency. However, the potential utilization of a wide number of parameters benefiting machine learning schemes has raised the need of efficient feature selection (FS) procedures. In this study, we propose a novel FS…
An Empirical Investigation of Performance Overhead in Cross-Platform Mobile Development Frameworks
2020
AbstractThe heterogeneity of the leading mobile platforms in terms of user interfaces, user experience, programming language, and ecosystem have made cross-platform development frameworks popular. These aid the creation of mobile applications – apps – that can be executed across the target platforms (typically Android and iOS) with minimal to no platform-specific code. Due to the cost- and time-saving possibilities introduced through adopting such a framework, researchers and practitioners alike have taken an interest in the underlying technologies. Examining the body of knowledge, we, nonetheless, frequently encounter discussions on the drawbacks of these frameworks, especially with regard…
Vectors of Pairwise Item Preferences
2019
Neural embedding has been widely applied as an effective category of vectorization methods in real-world recommender systems. However, its exploration of users’ explicit feedback on items, to create good quality user and item vectors is still limited. Existing neural embedding methods only consider the items that are accessed by the users, but neglect the scenario when a user gives high or low rating to a particular item. In this paper, we propose Pref2Vec, a method to generate vector representations of pairwise item preferences, users and items, which can be directly utilized for machine learning tasks. Specifically, Pref2Vec considers users’ pairwise item preferences as elementary units. …
The Ground State Electronic Energy of Benzene.
2020
We report on the findings of a blind challenge devoted to determining the frozen-core, full configuration interaction (FCI) ground state energy of the benzene molecule in a standard correlation-consistent basis set of double-$\zeta$ quality. As a broad international endeavour, our suite of wave function-based correlation methods collectively represents a diverse view of the high-accuracy repertoire offered by modern electronic structure theory. In our assessment, the evaluated high-level methods are all found to qualitatively agree on a final correlation energy, with most methods yielding an estimate of the FCI value around $-863$ m$E_{\text{H}}$. However, we find the root-mean-square devia…