Proximity sensors are devices found in many fields of activity from the automotive area to robotics and beyond. Among them, proximity sensors occupy an important place due to their low price and ...reliable response. They are found in a wide range of sizes and detection distances. In this work, a comparative study was carried out on two constructive solutions - one shielded and one unshielded. The response provided by the sensor was followed through a 2D FEMM analysis varying a series of parameters: the material from which the target is made, the distance between the target and the sensor, as well as its operating frequency. The results highlight the influence of these parameters by changing some quantities of a magnetic nature such as the spectrum of the magnetic flux density, the magnetic energy stored by the target, respectively the inductance of the sensor coil.
Recently, electronic skins and flexible wearable devices have been developed for widespread applications in medical monitoring, artificial intelligence, human–machine interaction, and artificial ...prosthetics. Flexible proximity sensors can accurately perceive external objects without contact, introducing a new way to achieve an ultrasensitive perception of objects. This article reviews the progress of flexible capacitive proximity sensors, flexible triboelectric proximity sensors, and flexible gate-enhanced proximity sensors, focusing on their applications in the electronic skin field. Herein, their working mechanism, materials, preparation methods, and research progress are discussed in detail. Finally, we summarize the future challenges in developing flexible proximity sensors.
Measuring social networks in primates Gelardi, Valeria; Godard, Jeanne; Paleressompoulle, Dany ...
Proceedings of the Royal Society. A, Mathematical, physical, and engineering sciences,
04/2020, Letnik:
476, Številka:
2236
Journal Article
Recenzirano
Odprti dostop
Network analysis represents a valuable and flexible framework to understand the structure of individual interactions at the population level in animal societies. The versatility of network ...representations is moreover suited to different types of datasets describing these interactions. However, depending on the data collection method, different pictures of the social bonds between individuals could a priori emerge. Understanding how the data collection method influences the description of the social structure of a group is thus essential to assess the reliability of social studies based on different types of data. This is however rarely feasible, especially for animal groups, where data collection is often challenging. Here, we address this issue by comparing datasets of interactions between primates collected through two different methods: behavioural observations and wearable proximity sensors. We show that, although many directly observed interactions are not detected by the sensors, the global pictures obtained when aggregating the data to build interaction networks turn out to be remarkably similar. Moreover, sensor data yield a reliable social network over short time scales and can be used for long-term studies, showing their important potential for detailed studies of the evolution of animal social groups.
The most significant task aimed at maintaining the bridge is the “bridge deck crack inspection”. Conventionally, the inspector identifies the cracks utilizing eyes and notices the crack location ...manually. Nevertheless, accuracy of inspection outcome is less because of “subjective nature of human judgment”. And Suggested a “crack inspection system” which utilizes the mobile robot equipped with the camera to gather bridge deck pictures. And in this model, “Laplacian of Gaussian (LoG) algorithm” is utilized to identify cracks & “global crack map” is achieved by localization of robot and “camera calibration”. Ensuring that robot gathers entire bridge deck pictures, the “path planning algorithm” on the basis of genetic-algorithm will be improved. And the “path planning algorithm” identifies the solution that reduces the count of turns and moving distance. The evaluation is done on the suggested method by both experiments & simulations.
Sheep are highly social domesticated animals that evolved to live in large and structured groups. As in other group-living species, individuals differ in the level of association they have with ...others, and these associations often result in lasting and stable social bonds. However, there are substantial gaps in our knowledge of the temporal social dynamics in sheep, and how their social bonds vary in relation to environmental changes. Here, we aimed to assess the social relationships between ewes and lambs, collecting dyadic associations data of 41 ewes and 55 lambs through the use of proximity loggers on a commercial farm. We computed association indices between each pair of animals to estimate the proportion of time any two individuals associated. We first generated an aggregated network of the whole 13-day observation period, and we compared the values of association indices between different types of dyads (i.e., lamb-mother, lamb-ewe non-mother, lambs littermates, lambs non-littermates, ewe-ewe). We generated aggregated contact networks on a daily scale to compare the ego-networks of individuals obtained in successive time windows to determine how stable social associations were over time. As would be expected, the highest values of association indices were found in dyads formed by dams and lambs (0.17 ± 0.11) and by lambs of the same litter (0.32 ± 0.09). Both single-born and twin-born lambs showed high association values with their dams (single-born: 0.24 ± 0.11; twin-born: 0.1 ± 0.05), although twin-born lambs had stronger associations with their littermates compared with those with their mothers (p-value < 0.001). At a temporal level, the flock exhibited periods of high network stability at the beginning and at the end of the study period. However, periods of social instability occurred one-two days after management interventions, such as changes in field size. These transitory periods of social instability were driven by changes in the association patterns of ewes and single born lambs. In contrast, the ego-networks of twin-born lambs remained relatively stable, supported by strong association levels between twins. Thus, the social instability of the social network was not a global one, but some parts of the network remained stable while others underwent important changes. Our study represents a first step to track social associations within an ewe-lamb group using proximity tags and advances our understanding of the social organisation of sheep. We highlight the importance of detecting social network instability as a consequence of different types of perturbations in order to identify the presence of social rearrangements.
•Social relationships within the flock differed more than would be expected by chance.•The twin-born lambs had a greater association with siblings compared with the association with mothers.•The flock exhibited periods of social instability after management interventions such as changes in field size.•The network instability was transitory, by demonstrating a high selectivity in the social structure.•The twin-born lambs presented a stronger social stability over the entire study period.
•Domestic sheep formed non-random and highly heterogeneous social networks.•Sheep showed preferences in social ties based on characteristics similarity.•The factors that influenced the preferred ...social interactions between individuals changed over time.•Environmental and microclimate parameters were predictors for the tendency of sheep to form clusters.
Social structures of group-living farm animals can have important implications for animal welfare and productivity. Understanding which factors can have an effect on social behaviour is thus important in order to develop the best management strategies in livestock industries. Here, we studied the social network structure of a flock of 84 Poll Dorset ewes and collecting dyadic associations data through the use of proximity sensors during two study periods. First, we analysed the social structure of ewes at a group-level, by analysing the community structure, and at individual-level, by determining whether the ewes showed social differentiation in their association patterns. Second, we measured for the contribution of genetic relatedness, age, weight, reproductive status and previous management sub grouping on social associations to test for homophily effects. Lastly, we evaluated whether social clustering was influenced by the stocking density of individuals in a field, and by weather parameters, through the use of two climatic indices, the Temperature-Humidity Index (THI) and the Wind Chill Index (WCI). Our results showed that the pairwise associations between ewes are not-random and highly heterogeneous, both in total time spent in contact and in contacts duration. There was no evidence that ewes were subdivided into social communities, and at individual level, they showed markedly differentiated social relationships, demonstrating preferences in social ties. However, the factors that influenced the preferred social interactions between individuals changed over time. In the first study period ewes tended to maintain the social bonds formed in previous management sub grouping, most likely due to a social familiarization resulting from repeated interactions with the same individuals. In the second study period similarity in age influenced the strength of associations among ewes. We found no significant influence of reproductive status, weight (as an indicator of body size) and genetic relatedness on proximity associations in either study period. Moreover, our results showed the tendency of the ewes to form social clusters varied in relation to animals’ density, and Wind Chill Index (WCI). The identification of conditions that modify the social behaviour of sheep is critically important in order to implement management and productivity strategies and our results highlight how flock social structure can change depending on environmental and social contexts.
To mimic human touch sensing, robotics must be able to leverage multiple sensory inputs. Previously, to achieve both proximity and pressure sensing, most approaches have required using two separate ...sensors, each with their corresponding electronics, limiting the achievable density. More recently, sensors with multifunctional pressure and proximity capabilities have been realized at the cost of compromised pressure sensing. Presented here is a new design for a multifunctional interdigitated fringe field capacitive pressure sensor with a pyramid microstructured dielectric layer that has proximity‐sensing capabilities (noncontact mode) while also sensing pressure (contact mode) as strongly as an equivalent parallel plate capacitive sensor of the same size. In contact mode, both sensors have a response time of less than 20 ms and can respond to loads lighter than 0.5 Pa. Further, the interdigitated fringe field sensor can clearly distinguish between the two sensing modes, as well as between conductive and nonconductive materials in the noncontact mode. Finally, we use the interdigitated fringe field sensor to demonstrate both proximity and high‐sensitivity pressure sensing on a robotic gripper.
Multifunctional sensors are integral for high‐density sensing matrices to mimic human touch. To achieve this, a novel interdigitated fringe field sensor with pyramid microstructures enables proximity sensing without compromising on the pressure‐sensing performance. The sensor's pressure‐sensing performance is similar to an equivalent high‐sensitivity parallel plate capacitive pressure sensor and has the capability to distinguish between contact and noncontact sensing.
Easy and convenient reading for blinds is of great significance for lowering their learning, entertainment, and communication barrier, and improving their living quality. The general solution is to ...learn braille, far from satisfying the meet of the blinds’ daily learning and communication. Here, a new‐type conductor/insulator‐identifiable e‐tattoo proximity sensor is developed by simply depositing the circular interdigitated electrodes on organic semiconductor. The discriminable recognition toward conductors and insulators is realized only based on a single e‐tattoo device. The sensors not only enable recognition of the protruding characters like braille based on distance difference, but also enable recognition of the handwriting ink‐brush and pencil graphite characters based on the unique advantage of the sensors in distinguishing conduct and insulator. These results open a new route to realize the material category recognition, provide a user‐friendly way to help the visual impaired effectively reintegrate into society, and broaden the application field of proximity sensors.
The proximity sensor plays a role in character recognition. Based on the edge electric field and the gas dielectric, the discriminable recognition toward conductor and insulator is realized only based on a single e‐tattoo device. This work offers a new route to realize material category recognition, providing a user‐friendly solution to help the visual impaired reintegrate into society.
In the 34 developed and 156 developing countries, there are ~132 million disabled people who need a wheelchair, constituting 1.86% of the world population. Moreover, there are millions of people ...suffering from diseases related to motor disabilities, which cause inability to produce controlled movement in any of the limbs or even head. This paper proposes a system to aid people with motor disabilities by restoring their ability to move effectively and effortlessly without having to rely on others utilizing an eye-controlled electric wheelchair. The system input is images of the user's eye that are processed to estimate the gaze direction and the wheelchair was moved accordingly. To accomplish such a feat, four user-specific methods were developed, implemented, and tested; all of which were based on a benchmark database created by the authors. The first three techniques were automatic, employ correlation, and were variants of template matching, whereas the last one uses convolutional neural networks (CNNs). Different metrics to quantitatively evaluate the performance of each algorithm in terms of accuracy and latency were computed and overall comparison is presented. CNN exhibited the best performance (i.e., 99.3% classification accuracy), and thus it was the model of choice for the gaze estimator, which commands the wheelchair motion. The system was evaluated carefully on eight subjects achieving 99% accuracy in changing illumination conditions outdoor and indoor. This required modifying a motorized wheelchair to adapt it to the predictions output by the gaze estimation algorithm. The wheelchair control can bypass any decision made by the gaze estimator and immediately halt its motion with the help of an array of proximity sensors, if the measured distance goes below a well-defined safety margin. This work not only empowers any immobile wheelchair user, but also provides low-cost tools for the organization assisting wheelchair users.
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