Current Issue : April - June Volume : 2018 Issue Number : 2 Articles : 5 Articles
In this paper, a circular microstrip antenna for stress evaluation is studied. This kind of\nmicrostrip sensor can be utilized in structural health monitoring systems. Reflection coefficient S11\nis measured to determine deformation/strain value. The proposed sensor is adhesively connected\nto the studied sample. Applied strain causes a change in patch geometry and influences current\ndistribution both in patch and ground plane. Changing the current flow in patch influences the\nvalue of resonant frequency. In this paper, two different resonant frequencies were analysed because\nin each case, different current distributions in patch were obtained. The sensor was designed for\noperating frequency of 2.5 GHz (at fundamental mode), which results in a diameter less than 55 mm.\nObtained sensitivity was up to 1 MHz/100 MPa, resolution depends on utilized vector network\nanalyser. Moreover, the directional characteristics for both resonant frequencies were defined, studied\nusing numerical model and verified by measurements. Thus far, microstrip antennas have been\nused in deformation measurement only if the direction of external force was well known. Obtained\ndirectional characteristics of the sensor allow the determination of direction and value of stress by\none sensor. This method of measurement can be an alternative to the rosette strain gauge....
Energy efficiency is still the obstacle for long-term real-time wireless ECG monitoring. In this paper, a digital compressed sensing-\n(CS-) based single-spot Bluetooth ECG node is proposed to deal with the challenge in wireless ECG application. A periodic\nsleep/wake-up scheme and a CS-based compression algorithm are implemented in a node, which consists of ultra-low-power\nanalog front-end, microcontroller, Bluetooth 4.0 communication module, and so forth. The efficiency improvement and the\nnode�s specifics are evidenced by the experiments using the ECG signals sampled by the proposed node under daily activities of\nlay, sit, stand, walk, and run. Under using sparse binary matrix (SBM), block sparse Bayesian learning (BSBL) method, and\ndiscrete cosine transform (DCT) basis, all ECG signals were essentially undistorted recovered with root-mean-square differences\n(PRDs) which are less than 6%. The proposed sleep/wake-up scheme and data compression can reduce the airtime over energyhungry\nwireless links, the energy consumption of proposed node is 6.53 mJ, and the energy consumption of radio decreases\n77.37%. Moreover, the energy consumption increase caused by CS code execution is negligible, which is 1.3% of the total\nenergy consumption...
The proliferation of mobile devices has facilitated the prevalence of participatory sensing applications in which participants collect\nand share information in their environments. The design of a participatory sensing application confronts two challenges: ââ?¬Å?privacyââ?¬Â\nand ââ?¬Å?incentiveââ?¬Â which are two conflicting objectives and deserve deeper attention. Inspired by physical currency circulation system,\nthis paper introduces the notion of E-cent, an exchangeable unit bearer currency. Participants can use the E-cent to take part in\ntasks anonymously. By employing E-cent, we propose an E-cent-based privacy-preserving incentive mechanism, called EPPI. As a\ndynamic balance regulatorymechanism, EPPI can not only protect the privacy of participant, but also adjust thewhole systemto the\nideal situation, under which the rated tasks can be finished at minimal cost. To the best of our knowledge, EPPI is the first attempt\nto build an incentive mechanism while maintaining the desired privacy in participatory sensing systems. Extensive simulation and\nanalysis results show that EPPI can achieve high anonymity level and remarkable incentive effects....
This paper studies the notion of hierarchical (chained) structure of stochastic tracking of marked feature points while a person is\nmoving in the field of view of a RGB and depth sensor.The objective is to explore how the information between the two sensing\nmodalities (namely, RGB sensing and depth sensing) can be cascaded in order to distribute and share the implicit knowledge\nassociated with the tracking environment. In the first layer, the prior estimate of the state of the object is distributed based on the\nnovel expected motion constraints approach associated with the movements. For the second layer, the segmented output resulting\nfrom the RGB image is used for tracking marked feature points of interest in the depth image of the person. Here we proposed two\napproaches for associating a measure (weight) for the distribution of the estimates (particles) of the tracking feature points using\ndepth data. The first measure is based on the notion of spin-image and the second is based on the geodesic distance. The paper\npresents the overall implementation of the proposed method combined with some case study results....
In this paper, a new approach for modeling the static force characteristic of Festo pneumatic\nmuscle actuators (PMAs) will be presented. The model is physically motivated and therefore gives\na deeper understanding of the Festo PMA. After introducing the new model, it will be validated\nthrough a comparison to a measured force map of a Festo DMSP-10-250 and a DMSP-20-300,\nrespectively. It will be shown that the error between the new model and the measured data is\nbelow 4.4% for the DMSP-10-250 and below 2.35% for the DMSP-20-300. In addition, the quality of\nthe presented model will be compared to the quality of existing models by comparing the maximum\nerror. It can be seen that the newly introduced model is closer to the measured force characteristic of\na Festo PMA than any existing model....
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