Search results for "artificial intelligence"
showing 10 items of 6122 documents
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…
Anomaly‐based intrusion detection systems: The requirements, methods, measurements, and datasets
2021
International audience; With the Internet's unprecedented growth and nations' reliance on computer networks, new cyber‐attacks are created every day as means for achieving financial gain, imposing political agendas, and developing cyberwarfare arsenals. Network security is thus acquiring increasing attention among researchers, practitioners, network architects, policy makers, and others. To defend organizations' networks from existing, foreseen, and future threats, intrusion detection systems (IDSs) are becoming a must. Existing surveys on anomaly‐based IDS (AIDS) focus on specific components such as detection mechanisms and lack many others. In contrast to existing surveys, this article co…
WITHDRAWN: An efficient multiscale algorithm
2016
The publisher regrets that this article has been temporarily removed. The reason for the overturn of the decision on ACHA-16-25 from Acceptance to Rejection is: One of the colleagues of the authors, Elisa Francomano, claims that the authors submitted the manuscript to ACHA without her knowledge and omitting her as one of the authors. The full Elsevier Policy on Article Withdrawal can be found at http://www.elsevier.com/locate/withdrawalpolicy .
Arbiter Meta-Learning with Dynamic Selection of Classifiers and its Experimental Investigation
1999
In data mining, the selection of an appropriate classifier to estimate the value of an unknown attribute for a new instance has an essential impact to the quality of the classification result. Recently promising approaches using parallel and distributed computing have been presented. In this paper, we consider an approach that uses classifiers trained on a number of data subsets in parallel as in the arbiter meta-learning technique. We suggest that information is collected during the learning phase about the performance of the included base classifiers and arbiters and that this information is used during the application phase to select the best classifier dynamically. We evaluate our techn…
Prediction of Temperature in Buildings Using Machine Learning Techniques
2017
Energy efficiency is a trend due to ecological and economic benefits. Within this field, energy efficiency in buildings sector constitutes one of the main concerns due to the fact that approximately 40% of total world energy consumption corresponds to this sector. Climate control in buildings has the potential to increase its energy efficiency planning strategies for the heating, ventilation and air conditioning (HVAC) machines. These planning strategies may include a stage for long term indoor temperature forecasting. This chapter entails the use of four prediction models (NAÏVE, MLR, MLP, FIS and ANFIS) to forecast temperature in an office building using a temporal horizon of several hour…