The literature approaches, devoted to sensor improve network coverage, are deterministic in terms of deployment environment and node configuration parameters. Nevertheless, this type of approaches has not proven to be very successful in uncertain deployment environments. This paper aims to deal with this issue using theories of uncertainty. We consider deployment environment’s imperfections and the characteristics of the sensor nodes. The selection of a minimum number of nodes for a minimum number of clusters to guarantee coverage in wireless sensor networks (WSNs) is uncertain. As a consequence, this paper proposes a hybrid Fuzzy-Possibilistic model to Schedule the Active/Passive State of Sensor nodes Strategy (FP-3SNS). This model helps to plan the scheduling of node states (Active/Passive) based on possibilistic information fusion to make a possibilistic decision for the node activation at each period. We evaluated our model (FP-3SNS) with (a) a running example (that shows the best choice of the active node with a probability of 0.81215); (b) a statistical evaluation (calculation of the confidence interface), where the average coverage reliability at 95% of FP-3SNS use is between (92.94, 96.27); and (c) a comparison with maximum sensing coverage region problem (MSCR), coverage maximization with sleep scheduling (CMSS), Spider Canvas Strategy, Semi-Random Deployment Strategy (SRDP), Probing Environment and Adaptive Sleeping with Location Information Protocol (PEAS-LI), and Variable Length Particle Swarm Optimization Algorithm with a Weighted Sum Fitness Function (WS-VLPSO). The simulation results highlight the benefits of using the fuzzy and possibility theories for treating the area coverage problem and the proposed model maintained a coverage between 99.99 and 90.00% for a significant period of time.
In order to facilitate the development of wrist-worn vibrotactile devices, detailed knowledge about how vibrations are perceived by the users is needed. In particular, perceptual thresholds in amplitude are really important. Thresholds have been measured in the literature for other areas of the body, but given the variability reported between areas (shape of the threshold curve, position of maximum sensitivity), thresholds on the wrist can not be inferred from previous measurements and must be measured. The amplitude thresholds for vibrations normal to the skin surface were evaluated on 28 participants, with a three interval forced choice method. They were measured for 7 frequencies that are classical in the literature about vibrotactile perception (25, 40, 80, 160, 250, 320, and 640 Hz). The classical U-shape of the amplitude-threshold curve is observed, with a maximum sensitivity at around 160 Hz, which differs from other body areas, but confirms recent results obtained for vibrations parallel to the skin surface of the same body area. The sensitivity thresholds of vibrotactile signals appear to be in the micrometer range.
In this paper, a channel-level event-triggered communication scheme is investigated for path tracking control of autonomous ground vehicles via an in-vehicle network to ensure path tracking performance while reducing network resource utilization. First, a path tracking system is established considering the effect of norm bounded uncertainty on lateral vehicle dynamics, and a state feedback path tracking controller is designed within the Takagi-Sugeno fuzzy framework. Next, a decentralized event-triggered communication scheme is adopted between the sensors and controller, which makes it possible to save communication resources at the channel level. Finally, the results in the CarSim-Simulink joint-simulation environment show that the proposed controller can ensure a reliable path tracking performance in both lateral offset and heading error. At the same time, compared with the simple time-triggered scheme, the proposed method can effectively reduce the usage of communication resources by more than 80%.
Cooperative intelligent transport systems (C-ITSs) are being deployed all around the world. Shortly, in addition to vehicles, bicycles, pedestrians, buses, and all moving equipment will be compatible with C-ITS. These systems are connected through wireless local area networks based on WIFI IEEE 802.11p. The large number of C-ITSs and services will lead to a glut in the bandwidth of wireless networks. To overcome this limitation, we propose in this paper a new approach using the information-centric networking (ICN) paradigm which allows vehicles to communicate with the cloud environment. This scheme is denoted by vehicular central data networking (GeoVCDN). Our approach aims to reduce bandwidth consumption and improve data freshness by taking benefit from the existing application beacons and the geographical routing used by C-ITS actors. We have compared the performances (in terms of the network overhead and data freshness) of our solution to two other well-known ICN-based solutions. Each of them represents one of ICN categories, in particular, rendez-vous network (RENE) and named data networking (NDN). To do so, we have proposed a probabilistic model that allows us to evaluate the freshness and the load of the network. Furthermore, we have implemented these methods in a simulator. Our proposal outperforms the other methods in terms of network overhead and data freshness.
This paper proposes a new observer approach used to simultaneously estimate both vehicle lateral and longitudinal nonlinear dynamics, as well as their unknown inputs. Based on cascade observers, this robust virtual sensor is able to more precisely estimate not only the vehicle state but also human driver external inputs and road attributes, including acceleration and brake pedal forces, steering torque, and road curvature. To overcome the observability and the interconnection issues related to the vehicle dynamics coupling characteristics, tire effort nonlinearities, and the tire–ground contact behavior during braking and acceleration, the linear-parameter-varying (LPV) interconnected unknown inputs observer (UIO) framework was used. This interconnection scheme of the proposed observer allows us to reduce the level of numerical complexity and conservatism. To deal with the nonlinearities related to the unmeasurable real-time variation in the vehicle longitudinal speed and tire slip velocities in front and rear wheels, the Takagi–Sugeno (T-S) fuzzy form was undertaken for the observer design. The input-to-state stability (ISS) of the estimation errors was exploited using Lyapunov stability arguments to allow for more relaxation and an additional robustness guarantee with respect to the disturbance term of unmeasurable nonlinearities. For the design of the LPV interconnected UIO, sufficient conditions of the ISS property were formulated as an optimization problem in terms of linear matrix inequalities (LMIs), which can be effectively solved with numerical solvers. Extensive experiments were carried out under various driving test scenarios, both in interactive simulations performed with the well-known Sherpa dynamic driving simulator, and then using the LAMIH Twingo vehicle prototype, in order to highlight the effectiveness and the validity of the proposed observer design.
Reconfigurable manufacturing systems have been proposed over the last decades to deal with mass-customization problems and volatile markets. Issues regarding the physical design, control, or scheduling of these systems have been studied intensively but very few studies have investigated inherent safety problems. Yet this issue is crucial for reconfigurable assembly systems where manual and robotized workstations must cohabit. The present paper first presents the main safety issues inherent to this new type of manufacturing system. A methodological approach based on adaptable solutions (e.g. safety plans, movable barriers, and safety laser scanners) and comprising two phases (‘offline’ and ‘online’) is then proposed to address in a short time the previous issues. At each step of the ‘offline’ phase, dedicated software assists the safety manager (in charge of and responsible for safety) to design a ‘safe’ reconfigurable manufacturing system. Once this design is validated by the safety manager, the ‘online’ phase of the methodology is deployed.
We are interested in a reduced model for corrosion of iron, in which ferric cations and electrons evolve in a fixed oxide layer subject to a self-consistent electrostatic potential. Reactions at the boundaries are modeled thanks to Butler–Volmer formulas, whereas the boundary conditions on the electrostatic potential model capacitors located at the interfaces between the materials. Our model takes inspiration in existing papers, to which we bring slight modifications in order to make it consistent with thermodynamics and its second principle. Building on a free energy estimate, we establish the global in time existence of a solution to the problem without any restriction on the physical parameters, in opposition to previous works. The proof further relies on uniform estimates on the chemical potentials that are obtained thanks to Moser iterations. Numerical illustrations are finally provided to highlight the similarities and the differences between our new model and the one previously studied in the literature.
Cortical activity and walking speed are known to decline with age and can lead to an increased risk of falls in the elderly. Despite age being a known contributor to this decline, individuals age at different rates. This study aimed to analyse left and right cortical activity changes in elderly adults regarding their walking speed. Cortical activation and gait data were obtained from 50 healthy older individuals. Participants were then grouped into a cluster based on their preferred walking speed (slow or fast). Analyses on the differences of cortical activation and gait parameters between groups were carried out. Within-subject analyses on left and right-hemispheric activation were also performed. Results showed that individuals with a slower preferred walking speed required a higher increase in cortical activity. Individuals in the fast cluster presented greater changes in cortical activation in the right hemisphere. This work demonstrates that categorizing older adults by age is not necessarily the most relevant method, and that cortical activity can be a good indicator of performance with respect to walking speed (linked to fall risk and frailty in the elderly). Future work may wish to explore how physical activity training influences cortical activation over time in the elderly.
This article presents a solution to the leaderless formation control problem for first-order multiagent systems, which minimizes a global function composed of a sum of local strongly convex functions for each agent under weighted undirected graphs within a predefined time. The proposed distributed optimization process consists of two steps: 1) the controller initially leads each agent to the minimizer of its local function and 2) then guides all agents toward achieving leaderless formation and reaching the global function's minimizer. The proposed scheme requires fewer adjustable parameters than most existing methods in the literature without the need for auxiliary variables or time-variable gains. Additionally, one can consider highly nonlinear multivalued strongly convex cost functions, while the agents do not share the gradients and Hessians. Extensive simulations and comparisons with state-of-the-art algorithms demonstrate the effectiveness of our approach.
We study the stability of a class of discrete-time fuzzy systems with singleton consequents, called Mamdani-like fuzzy systems. The parametric expressions, specific to this class of fuzzy systems, are leveraged to derive stability analysis conditions via Finsler's lemma and Lyapunov stability tools. This allows avoiding the major challenge in dealing with high-dimensional cases, encountered in the related literature when using the classical state-space representation. Moreover, the information of the piecewise region partition can be fully taken into account in the stability analysis with the well-known $S-$ procedure to further reduce the stability conservatism. The stability of Mamdani-like fuzzy systems can be checked by solving a set of linear matrix inequalities (LMIs), that is numerically tractable with a suitable semidefinite programming software. Several numerical and physically motivated examples are provided to illustrate the effectiveness of the proposed stability analysis results.
High data rate coverage, security, and energy efficiency will play a key role in the continued performance scaling of next-generation mobile systems. Dense, small mobile cells based on a novel network architecture are part of the answer. Motivated by the recent mounting interest in free-space optical (FSO) technologies, this paper addresses a novel mobile fronthaul network architecture based on FSO, spread spectrum codes, and graphene modulators for the creation of dense small cells. The network uses an energy-efficient graphene modulator to send data bits to be coded with spread codes for achieving higher security before their transmission to remote units via high-speed FSO transmitters. Analytical results show the new fronthaul mobile network can accommodate up to 32 remote antennas under error-free transmissions with forward error correction. Furthermore, the modulator is optimized to provide maximum efficiency in terms of energy consumption per bit. The optimization procedure is carried out by optimizing both the amount of graphene used on the ring resonator and the modulator’s design. The optimized graphene modulator is used in the new fronthaul network and requires as low as 4.6 fJ/bit while enabling high-speed performance up to 42.6 GHz and remarkably using one-quarter of graphene only.
An original fully textile combiner is proposed to power supply sensors close to a body with only one centralized source of energy like a smartphone, for instance. A solution is provided for taking into account the requirements of an industrial production process that need to minimize needle movements during an embroidery process. Moreover, the paper shows how to support several wireless power transmission standards that already exist, i.e. NFC and A4WP, or will exist to satisfy the tremendous needs of energy for distributed systems in the IoT domain. In this paper, a new textile-based flexible wireless system enabling communication and energy harvesting is proposed. Analytical, numerical, and experimental studies have been conducted to demonstrate that the structure has two resonant frequencies at 6.8 MHz and 13.6 MHz, which make it suitable for NFC and A4WP standards. Moreover, the losses caused by the system are 2.76 dB and 1.91 dB for A4WP and NFC, respectively. The results are successively presented to highlight the specificities of such textile multi-coils combiners. A method for gaining a resonant structure without any solid electronic component is explained.
The harvesting energy from the vibration of piezoelectric beam or membrane producing an alternating voltage, requires a passive AC/DC converter to avoid energy losses, and to adapt the electrical signal to the input parameters (voltage, current). The objective of this work is to demonstrate a complete AC/DC converter autonomous system which is powered by a piezoelectric energy harvester. Accordingly, the proposed rectifier has several advantages in terms of efficiency, compatibility, circuit simplicity, and integration into various systems. The AC-DC converter for piezoelectric energy harvesting applications presented in this paper is an improved version of the Synchronized Switch Harvesting on Inductor Corrected (SSHIC) Converter. This modified version provides better results of up to 56% for technology parallel SSHIC-p and 51% for technology series SSHIC-s compared to input power. In addition, it is better in terms of efficiency more than 220% compared to the bridge rectifier with relatively stable output despite varying conditions. In addition, the structures vibrating in sinusoidal or pseudo sinusoidal mode, thus being able to be modeled by a second order. This model is well suited to broadband stresses of multimodal structures.
Real-time digital twin technology can enhance traffic safety of intelligent vehicular system and provide scientific strategies for intelligent traffic management. At the same time, real-time digital twin depends on strong computation from vehicle side to cloud side. Aiming at the problem of delay caused by the dual dependency of timing and data between computation tasks, and the problem of unbalanced load of mobile edge computing servers, a parallel intelligence-driven resource scheduling scheme for computation tasks with dual dependencies of timing and data in the intelligent vehicular systems (IVS) is proposed. First, the delay and energy consumption models of each computing platform are formulated by considering the dual dependence of sub-tasks. Then, based on the bidding idea of the auction algorithm, the allocation model of computing resources and communication resources is defined, and the load balance model of the mobile edge computing (MEC) server cluster is formulated according to the load status of each MEC server. Secondly, joint optimization problem for offloading, resource allocation, and load balance is formulated. Finally, an adaptive particle swarm with genetic algorithm is proposed to solve the optimization problem. The simulation results show that the proposed scheme can reduce the total cost of the system while satisfying the maximum tolerable delay, and effectively improve the load balance of the edge server cluster.
Cryptosporidium parvum is an enteric parasite and a major contributor to acute enteritis in calves worldwide, causing an important economic burden for farmers. This parasite poses a major public health threat through transmission between livestock and humans. Our previous pilot study in Western Europe revealed a high prevalence of Cryptosporidium in calves of dairy farms. In the sequel study herein, 936 faecal samples were collected from the same 51 dairy farms across Belgium, France, and the Netherlands. Following DNA extraction, Cryptosporidium screening was carried out using nested-PCR amplification targeting the SSU rRNA gene. All positive samples were sequenced, and phylogenetic analyses were used to identify the Cryptosporidium spp. present. The 60 kDa glycoprotein (gp60) gene was also sequenced to determine the C. parvum subtypes present. Prevalence of Cryptosporidium ranged from 23.3% to 25%, across the three countries surveyed. The parasite was found in most of the farms sampled, with 90.2% testing positive. Cryptosporidium parvum, C. bovis, C. ryanae and C. andersoni were all identified, with the former being the most predominant, representing 71.4% of all infections. Cryptosporidium parvum was associated with pre-weaned calves, while other species were associated with older animals. Subtyping of gp60 gene revealed nine subtypes, eight of which have previously been reported to cause clinical disease in humans. Similarly to the first study, vertical transmission was not a major contributor to Cryptosporidium spread. Our study highlights the need for further investigation into cryptosporidiosis transmission, and future studies will require a One Health approach to reduce the impact of this disease.
The nanoscale intrinsic electrical properties of in-plane InAs nanowires grown by selective area epitaxy are investigated using a process-free method involving a multi-probe scanning tunneling microscope. The resistance of oxide-free InAs nanowires grown on an InP(111)B substrate and the resistance of InAs/GaSb core-shell nanowires grown on an InP(001) substrate are measured using a collinear four-point probe arrangement in ultrahigh vacuum. They are compared with the resistance of two-dimensional electron gas reference samples measured using the same method and with the Van der Pauw geometry for validation. A significant improvement of the conductance is achieved when the InAs nanowires are fully embedded in GaSb, exhibiting an intrinsic sheet conductance close to the one of the quantum well counterpart.
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