Search results for " image processing."
showing 10 items of 2265 documents
Comparison of WSN and IoT approaches for a real-time monitoring system of meal distribution trolleys: A case study
2018
Abstract International regulations determine that food in hospitals and elderly homes must be served at given temperature ranges. However, the real-time surveillance of the meal distribution trolleys along all the institutions facilities, guaranteeing conformity to rules from the instant when all the meals are put in the distribution trolley until they are delivered to the patients, is still a challenge. In this paper, we present a comparison of two approaches based on Wireless Sensor Networks (WSN) and Internet of Things (IoT) technologies for implementing a Real-Time Monitoring System of Meal Distribution Trolleys in a hospital. The performance evaluation results show that the IoT impleme…
SAUCE: A web application for interactive teaching and learning of parallel programming
2017
Abstract Prevalent hardware trends towards parallel architectures and algorithms create a growing demand for graduate students familiar with the programming of concurrent software. However, learning parallel programming is challenging due to complex communication and memory access patterns as well as the avoidance of common pitfalls such as dead-locks and race conditions. Hence, the learning process has to be supported by adequate software solutions in order to enable future computer scientists and engineers to write robust and efficient code. This paper discusses a selection of well-known parallel algorithms based on C++11 threads, OpenMP, MPI, and CUDA that can be interactively embedded i…
A holistic modeling for QoE estimation in live video streaming applications over LTE Advanced technologies with Full and Non Reference approaches
2018
Abstract Current mobile networks are providing high speed access to Internet at a rate of Gigabits per second. In this scenario, traditional services over wired networks are an alternative, in particular those based on live video streaming. But in the transition, different issues should be considered due to the rapid changing network conditions and the limited resources of the mobile devices. These issues should be taken into account to keep a good Quality of Experience (QoE) of the video in terms of a high Mean Opinion Score (MOS), a subjective video quality. Our goal is to estimate and predict this subjective metric in a holistic manner. Thus, we have analyzed and measured different varia…
Enabling early sleeping and early data transmission in wake-up radio-enabled IoT networks
2019
Abstract Wireless sensor networks (WSNs) are one of the key enabling technologies for the Internet of things (IoT). In such networks, wake-up radio (WuR) is gaining its popularity thanks to its on-demand transmission feature and overwhelming energy consumption superiority. Despite this advantage, overhearing still occurs when a wake-up receiver decodes the address of a wake-up call (WuC) which is not intended to it, causing a certain amount of extra energy waste in the network. Moreover, long latency may occur due to WuC address decoding since WuCs are transmitted at a very low data rate. In this paper, we propose two schemes, i.e., early sleeping (ES) and early data transmission (EDT), to …
A Predictive Approach for the Efficient Distribution of Agent-Based Systems on a Hybrid-Cloud
2018
International audience; Hybrid clouds are increasingly used to outsource non-critical applications to public clouds. However, the main challenge within such environments, is to ensure a cost-efficient distribution of the systems between the resources that are on/off premises. For Multi Agent Systems (MAS), this challenge is deepened due to irregular workload progress and intensive communication between the agents, which may result in high computing and data transfer costs. Thus, in this paper we propose a generic framework for adaptive cost-efficient deployment of MAS with a special focus on hybrid clouds. The framework is based mainly on the use of a performance evaluation process that con…
Learning by the Process of Elimination
2002
AbstractElimination of potential hypotheses is a fundamental component of many learning processes. In order to understand the nature of elimination, herein we study the following model of learning recursive functions from examples. On any target function, the learning machine has to eliminate all, save one, possible hypotheses such that the missing one correctly describes the target function. It turns out that this type of learning by the process of elimination (elm-learning, for short) can be stronger, weaker or of the same power as usual Gold style learning.While for usual learning any r.e. class of recursive functions can be learned in all of its numberings, this is no longer true for el…
DRESS: A Distributed RMS Evaluation Simulation Software
2020
Distributed environments consist of a huge number of entities that cooperate to achieve complex goals. When interactions occur between unknown parties, intelligent techniques for estimating agent reputations are required. Reputation management systems (RMS's) allow agents to perform such estimation in a cooperative way. In particular, distributed RMS's exploit feedbacks provided after each interaction and allow prediction of future behaviors of agents. Such systems, in contrast to centralized RMSs, are sensitive to fake information injected by malicious users; thus, predicting the performance of a distributed RMS is a very challenging task. Although many existing works have addressed some c…
Detection of developmental dyslexia with machine learning using eye movement data
2021
Dyslexia is a common neurocognitive learning disorder that can seriously hinder individuals’ aspirations if not detected and treated early. Instead of costly diagnostic assessment made by experts, in the near future dyslexia might be identified with ease by automated analysis of eye movements during reading provided by embedded eye tracking technology. However, the diagnostic machine learning methods need to be optimized first. Previous studies with machine learning have been quite successful in identifying dyslexic readers, however, using contrasting groups with large performance differences between diagnosed and good readers. A practical challenge is to identify also individuals with bord…
Collaborative body sensor networks: Taxonomy and open challenges
2018
International audience; Single Body Sensor Networks (BSNs) have gained a lot of interest during the past few years. However, the need to monitor the activity of many individuals to assess the group status and take action accordingly has created a new research domain called Collaborative Body Sensor Network (CBSN). In such a new field, understanding CBSN's concept and challenges over the roots requires investigation to allow the development of suitable algorithms and protocols. Although there are many research studies in BSN, CBSN is still in its early phases and studies around it are very few. In this paper, we define and taxonomize CBSN, describe its architecture, and discuss its applicati…
Fast fringe pattern phase demodulation using FIR Hilbert transformers
2016
This paper suggests the use of FIR Hilbert transformers to extract the phase of fringe patterns. This method is computationally faster than any known spatial method that produces wrapped phase maps. Also, the algorithm does not require any parameters to be adjusted which are dependent upon the specific fringe pattern that is being processed, or upon the particular setup of the optical fringe projection system that is being used. It is therefore particularly suitable for full algorithmic automation. The accuracy and validity of the suggested method has been tested using both computer-generated and real fringe patterns. This novel algorithm has been proposed for its advantages in terms of com…