Search results for "Artificial"
showing 10 items of 7394 documents
Visualization of Memory Map Information in Embedded System Design
2018
Data compression is a common requirement for displaying large amounts of information. The goal is to reduce visual clutter. The approach given in this paper uses an analysis of a data set to construct a visual representation. The visualization is compressed using the address ranges of the memory structure. This method produces a compressed version of the initial visualization, retaining the same information as the original. The presented method has been implemented as a Memory Designer tool for ASIC, FPGA and embedded systems using IP-XACT. The Memory Designer is a user-friendly tool for model based embedded system design, providing access and adjustment of the memory layout from a single v…
Automating statistical diagrammatic representations with data characterization
2017
The search for an efficient method to enhance data cognition is especially important when managing data from multidimensional databases. Open data policies have dramatically increased not only the volume of data available to the public, but also the need to automate the translation of data into efficient graphical representations. Graphic automation involves producing an algorithm that necessarily contains inputs derived from the type of data. A set of rules are then applied to combine the input variables and produce a graphical representation. Automated systems, however, fail to provide an efficient graphical representation because they only consider either a one-dimensional characterizat…
Mesh Visual Quality based on the combination of convolutional neural networks
2019
Blind quality assessment is a challenging issue since the evaluation is done without access to the reference nor any information about the distortion. In this work, we propose an objective blind method for the visual quality assessment of 3D meshes. The method estimates the perceived visual quality using only information from the distorted mesh to feed pre-trained deep convolutional neural networks. The input data is prepared by rendering 2D views from the 3D mesh and the corresponding saliency map. The views are split into small patches of fixed size that are filtered using a saliency threshold. Only the salient patches are selected as input data. After that, three pre-trained deep convolu…
Multiple Classifiers and Data Fusion for Robust Diagnosis of Gearbox Mixed Faults
2019
Detection and isolation of single and mixed faults in a gearbox are very important to enhance the system reliability, lifetime, and service availability. This paper proposes a hybrid learning algorithm, consisting of multilayer perceptron (MLP)- and convolutional neural network (CNN)-based classifiers, for diagnosis of gearbox mixed faults. Domain knowledge features are required to train the MLP classifier, while the CNN classifier can learn features itself, allowing to reduce the required knowledge features for the counterpart. Vibration data from an experimental setup with gearbox mixed faults is used to validate the effectiveness of the algorithms and compare them with conventional metho…
Fusion of CNN and sparse representation for threat estimation near power lines and poles infrastructure using aerial stereo imagery
2021
Abstract Fires or electrical hazards and accidents can occur if vegetation is not controlled or cleared around overhead power lines, resulting in serious risks to people and property and significant costs to the community. There are numerous blackouts due to interfering the trees with the power transmission lines in hilly and urban areas. Power distribution companies are facing a challenge to monitor the vegetation to avoid blackouts and flash-over threats. Recently, several methods have been developed for vegetation monitoring; however, existing methods are either not accurate or could not provide better disparity map in the textureless region. Moreover, are not able to handle depth discon…
Exploiting Semantic Trajectories Using HMMs and BIM for Worker Safety in Dynamic Environments
2020
International audience; Understanding dynamic behaviors of moving objects using positioning technologies for construction safety monitoring is still an open research issue. One task; that is a small subset in the widespread field of objects dynamics is the enrichment of the location data of users with the semantic information for studying their mobility patterns in the context of the environment. However, incorporating the semantics related to the environment gets complex in case of the dynamic construction sites where the site spaces are kept evolving with time. For instance, new walls and infrastructure supports are added often on sites, while others are detached. Similar situations open …
Data lakes in business intelligence: reporting from the trenches
2018
Abstract The data lake approach has emerged as a promising way to handle large volumes of structured and unstructured data. This big data technology enables enterprises to profoundly improve their Business Intelligence. However, there is a lack of empirical studies on the use of the data lake approach in enterprises. This paper provides the results of an exploratory study designed to improve the understanding of the use of the data lake approach in enterprises. I interviewed 12 experts who had implemented this approach in various enterprises and identified three important purposes of implementing data lakes: (1) as staging areas or sources for data warehouses, (2) as a platform for experime…
Gui-driven intelligent tutoring system with affective support to help learning the algebraic method
2017
Despite many research efforts focused on the development of algebraic reasoning and the resolution of story problems, several investigations have reported that relatively advanced students experience serious difficulties in symbolizing certain meaningful relations by using algebraic equations. In this paper, we describe and justify the Graphical User Interface of an Intelligent Tutoring System that allows learning and practising the procedural aspects involved in translating the information contained in a story problem into a symbolic representation. The application design has been driven by cognitive findings from several previous investigations. First, the process of translating a word pr…
WiHAR : From Wi-Fi Channel State Information to Unobtrusive Human Activity Recognition
2020
A robust and unobtrusive human activity recognition system is essential to a multitude of applications, such as health care, active assisted living, robotics, sports, and tele-immersion. Existing well-performing activity recognition methods are either vision- or wearable sensor-based. However, they are not fully passive. In this paper, we develop WiHAR—an unobtrusive Wi-Fi-based activity recognition system. WiHAR uses the Wi-Fi network interface card to capture the channel state information (CSI) data. These CSI data are effectively processed, and then amplitude and phase information is used to obtain the spectrogram. In the subsequent step, the time-variant mean Doppler shift (MDS) caused …
An Ontology Model for Interoperability and Multi-organization Data Exchange
2020
Progress in the uptake and use of technologies such as Artificial Intelligence and the Internet of Things seems to be stalled by the colossal fragmentation of information and data standards. This complexity is compounded by issues of inter-organisational differences, hindering effective collaboration. There is a growing demand for cross-organizational integrations in regulated but decentralized environments. This paper introduces an ontology architecture where information is sliced into independent semantic layers, each focusing on a specific aspect of the data. By dissolving traditional monolithic data structures into layered, light semantic components, the necessity to maintain contextual…