A systematic literature review of machine learning applications in IoT

The Internet of Things (IoT) is a network of interconnected smart objects having capabilities that collectively form an ecosystem and enable the delivery of smart services to users. The IoT is providing several benefits into people's lives through the environment. The various applications that are run in the IoT environment offer facilities and services. The most crucial services provided by IoT applications are quick decision for efficient management. Recently, machine learning (ML) techniques have been successfully used to maximize the potential of IoT systems. This paper presents a systematic review of the literature on the integration of ML methods in the IoT. The challenges of IoT systems are split into two categories: fundamental operation and performance. We also look at how ML is assisting in the resolution of fundamental system operation challenges such as security, big data, clustering, routing, and data aggregation.     

The actuation efficiency,a measure of acceleration capability for nonredundant robotic manipulators

This article presents a performance measure, the actuation efficiency, which describes the imbalance between the end‐effector accelerations achievable in different directions of nonredundant robotic manipulators. A key feature of the proposed measure is that in its development the differences in units between translational and rotational accelerations are treated in a physically meaningful manner. The measure also indicates oversized actuators, since this contributes to the imbalance in achievable accelerations. The development of this measure is based on the formulation of the dynamic capability equations. The shape of the dynamic capability hypersurface, which is defined by the dynamic capability equations, is a weak indicator of the level of imbalance in achievable end‐effector accelerations. © 2005 Wiley Periodicals, Inc.     

Effect of amyl acetate sorption on mechanical and thermal properties of polypropylene packaging

Sorption kinetics of amyl acetate in polypropylene is studied at 23, 40 and 55°C. Diffusion (D) and partition (Kp) coefficients were determined by fitting the sorption curves with a theoretical curve calculated from Fick's diffusion equation. The role of temperature and concentration of amyl acetate was investigated. The results show that D is not affected and Kp decreases with increasing concentration of amyl acetate in the solution. The sorption rate or total amount absorbed increased considerably with temperature. Concentration profiles were calculated by using a numerical algorithm based on a finite element method. The effect of amyl acetate concentration on the mechanical and thermal properties of the polymer was investigated. Copyright © 2007 John Wiley & Sons, Ltd.     

Minimisation de la consommation d’Énergie dans les réseaux ad hoc

An ad hoc network is a collection of wireless devices forming a temporary network independently of any administration or fixed infrastructure. The main benefits of this new generation of mobile networks are flexibility and their low cost. Wireless devices have maximum utility when they can be used “anywhere at anytime “. However, one of the greatest limitations to that goal is the finite power supplies. Since batteries provide limited power, a general constraint of wireless communication is the short continuous operation time of mobile terminals. This constraint is more important for the ad hoc networks, since every terminal has to perform the functions of a router. Therefore, energy consumption should be a crucial issue while designing new communication protocols and particularly ad hoc routing protocols. We propose, in this paper, some extensions to the most important on-demand routing algorithm,Aodv (Ad hoc On demand Distance Vector). The discovery mechanism in these extensions uses energy as a routing metric. These algorithms improve the network survivability by maintaining the network connectivity, which is the strong requirement for a high-quality communication. They carry out this objective with low message overhead for computing routes and without affecting the other network protocol layers.     

Resource Scheduling Using Neural Dynamics Model of Adeli and Park

This paper presents a mathematical model for resource scheduling considering project scheduling characteristics generally ignored in prior research, including precedence relationships, multiple crew-strategies, and time cost trade-off. Previous resource scheduling formulations have traditionally focused on project duration minimization. The proposed model considers the total project cost minimization. Furthermore, resource leveling and resource-constrained scheduling have traditionally been solved independently. In the new formulation, resource leveling and resource-constrained scheduling are performed simultaneously. The proposed model is solved using the patented neural dynamics model of Adeli and Park. A case study is presented to demonstrate the performance of the method under various resource availability profiles.     

Adaptation of a routing algorithm in wireless video sensor network for disaster scenarios using JPEG 2000

In this work we will develop an extension of one of existing routing algorithm in wireless sensor network. This new adaptation will permit the sensor node to save more energy and transmit images in wireless mode. This situation will be strategic and helpful especially in disaster scenario, where groups of rescuers must be on site to accomplish emergency tasks; therefore it’s very important and necessary to establish a wireless communication in real time between individuals or groups. The nature of wireless video sensor network makes it suitable to be used in the context of emergencies because introducing a video give more information in precise time and this is very advantageous when the existing infrastructure is down or severely overloaded. In emergencies the network topology may change rapidly and randomly. The increasing mobility of terminals makes them progressively dependent on their autonomy from the power source. This is illustrated by introducing many mobility models and using many scenarios of mobility in emergency situation, where image transmission via sensor node is used. Low complexity algorithm in image processing in order to reduce time transfer of selected data by this way allows saving energy. Efficiency in emergency scenario is the main objective of this work, achieved by the combination of three strategies: low-power mode algorithm, a power-aware routing strategy and compression technique in image processing used in sensor node. A selected set of simulations studies and real test bed on sensor node platform (Telos-B) indicate a reduction in energy consumption and a significant increase in node lifetime whereas network performance is not affected significantly. This is the big interest of our work in emergency situation, by increasing life time of node, individual can communicate longer and give more chance to rescuers to find them.     

Bright unidirectional fluorescence emission of molecules in a nanoaperture with plasmonic corrugations

Controlling the fluorescence emission from nanoscale quantum emitters is a key element for a wide range of applications, from efficient analytical sensing to quantum information processing. Enhancing the fluorescence intensity and narrowing the emission directivity are both essential features to achieve a full control of fluorescence, yet this is rarely obtained simultaneously with optical nanoantennas. Here we report that gold nanoapertures surrounded by periodic corrugations transform standard fluorescent molecules into bright unidirectional sources. We obtain enhancement factors of the fluorescence count rate per molecule up to 120 fold simultaneously with a directional emission of the fluorescence into a narrow angular cone in the direction normal to the sample plane. The bright emission and narrow directionality enable the detection of single molecules with a low numerical aperture objective, and improve the effectiveness of fluorescence-based applications. We thoroughly quantify the increased light-matter coupling as well as the radiation pattern intensity. These results are highly relevant for the development of single molecule sensing, single-photon sources, and light emitting devices.     

Evaluation of model compounds–polypropylene film interactions by Fourier transformed infrared spectroscopy (FTIR) method

The interactions of methyl esters, methyl ketones and aldehyde compounds with polypropylene (PP) film were investigated. PP film, placed on a glass vial, was immersed in aqueous solution containing a model flavour compound. After a determined time at 45°C, the PP film was analysed by Fourier transform infrared spectroscopy (FTIR), allowing us to follow the speed of sorption and to quantify its relative rate. For PP films, we observed that the sorption strongly depended on the structure of sorbed molecules. For each functional group of flavour compounds, the sorption increased as the carbon chain number increased. A linear chain of 12–14 carbons favours the sorption more than a linear chain of eight carbons. Concerning functions, the rate of sorption usually decreases from esters to ketones and to aldehydes. High sorption was observed for flavour compounds with a low difference of solubility parameter (SP) value between the film and flavour [(δ_polymer ? δ_flavour)² value]. Furthermore, by using the proposed thermodynamic affinity concept, represented as the contribution of three interactive molecular forces [dispersion (d_d), polar (d_p) and hydrogen bonding (d_h)] between two SP values of film and flavour, packaging materials with high flavour preservation against sorption can be designed. We have a good correlation between the kinetic sorption by FTIR and the SP concept. Copyright © 2007 John Wiley & Sons, Ltd.     

Transported-PDF (IEM, EMST) micromixing models in a hydrogen-air nonpremixed turbulent flame

The topic of this study is the numerical simulation of a turbulent non-premixed hydrogen flame with different micromixing models in order to investigate their predictive capability. The two micromixing models are compared. The first model is the interaction by exchange with the mean (IEM) model (Dopazo and O’Brien Acta Astronaut 1(9–10):1239, 1974). The second one is the Euclidean minimum spanning tree (EMST) model (Subramaniam and Pope Combust Flame 115(4):487, 1998). The dynamic model for the mixing time-scale is handled, by computing the individual time-scales for the reactive scalars in each cell during the simulation course using the Fluent/MM-INTAS CFD code. The predictions are validated against experimental data provided by Raman and Laser Doppler anemometry measurements for a turbulent jet Hydrogen-air diffusion flame. The interaction of turbulence-chemistry is handled with TPDF method. The chemical model used here consists of 11 chemical species and 23 reactions. Comparisons with experimental data demonstrate that predictions based on the EMST model are slightly better. The EMST improves largely the precision of the results to the detriment of the RAM and the CPU performances. Overall, profile predictions of mixture fraction, flame temperature and major species are in reasonable agreement with experimental data.