890 resultados para Reference sensors


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Active optical sensing (LIDAR and light curtain transmission) devices mounted on a mobile platform can correctly detect, localize, and classify trees. To conduct an evaluation and comparison of the different sensors, an optical encoder wheel was used for vehicle odometry and provided a measurement of the linear displacement of the prototype vehicle along a row of tree seedlings as a reference for each recorded sensor measurement. The field trials were conducted in a juvenile tree nursery with one-year-old grafted almond trees at Sierra Gold Nurseries, Yuba City, CA, United States. Through these tests and subsequent data processing, each sensor was individually evaluated to characterize their reliability, as well as their advantages and disadvantages for the proposed task. Test results indicated that 95.7% and 99.48% of the trees were successfully detected with the LIDAR and light curtain sensors, respectively. LIDAR correctly classified, between alive or dead tree states at a 93.75% success rate compared to 94.16% for the light curtain sensor. These results can help system designers select the most reliable sensor for the accurate detection and localization of each tree in a nursery, which might allow labor-intensive tasks, such as weeding, to be automated without damaging crops.

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The solutions to cope with new challenges that societies have to face nowadays involve providing smarter daily systems. To achieve this, technology has to evolve and leverage physical systems automatic interactions, with less human intervention. Technological paradigms like Internet of Things (IoT) and Cyber-Physical Systems (CPS) are providing reference models, architectures, approaches and tools that are to support cross-domain solutions. Thus, CPS based solutions will be applied in different application domains like e-Health, Smart Grid, Smart Transportation and so on, to assure the expected response from a complex system that relies on the smooth interaction and cooperation of diverse networked physical systems. The Wireless Sensors Networks (WSN) are a well-known wireless technology that are part of large CPS. The WSN aims at monitoring a physical system, object, (e.g., the environmental condition of a cargo container), and relaying data to the targeted processing element. The WSN communication reliability, as well as a restrained energy consumption, are expected features in a WSN. This paper shows the results obtained in a real WSN deployment, based on SunSPOT nodes, which carries out a fuzzy based control strategy to improve energy consumption while keeping communication reliability and computational resources usage among boundaries.

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Point-probe optical fiber chem-sensors have been implemented using cladding etched fiber Bragg gratings. The sensors possess refractive index sensing capability that can be utilized to measure chemical concentrations. The Bragg wavelength shift reaches 8 nm when the index of surrounding medium changes from 1.33 to 1.44, giving maximum sensitivity more than 10 times higher than that of previously reported devices. More importantly, the dual-grating configuration of the point-probe sensors offers a temperature reference function, permitting accurate measurement of refractive index encoded chemical concentrations.

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Point-probe optical fiber chem-sensors have been implemented using cladding etched fiber Bragg gratings. The sensors possess refractive index sensing capability that can be utilized to measure chemical concentrations. The Bragg wavelength shift reaches 8 nm when the index of surrounding medium changes from 1.33 to 1.44, giving maximum sensitivity more than 10 times higher than that of previously reported devices. More importantly, the dual-grating configuration of the point-probe sensors offers a temperature reference function, permitting accurate measurement of refractive index encoded chemical concentrations.

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This article demonstrates the use of embedded fibre Bragg gratings as vector bending sensor to monitor two-dimensional shape deformation of a shape memory polymer plate. The shape memory polymer plate was made by using thermal-responsive epoxy-based shape memory polymer materials, and the two fibre Bragg grating sensors were orthogonally embedded, one on the top and the other on the bottom layer of the plate, in order to measure the strain distribution in both longitudinal and transverse directions separately and also with temperature reference. When the shape memory polymer plate was bent at different angles, the Bragg wavelengths of the embedded fibre Bragg gratings showed a red-shift of 50 pm/°caused by the bent-induced tensile strain on the plate surface. The finite element method was used to analyse the stress distribution for the whole shape recovery process. The strain transfer rate between the shape memory polymer and optical fibre was also calculated from the finite element method and determined by experimental results, which was around 0.25. During the experiment, the embedded fibre Bragg gratings showed very high temperature sensitivity due to the high thermal expansion coefficient of the shape memory polymer, which was around 108.24 pm/°C below the glass transition temperature (Tg) and 47.29 pm/°C above Tg. Therefore, the orthogonal arrangement of the two fibre Bragg grating sensors could provide a temperature compensation function, as one of the fibre Bragg gratings only measures the temperature while the other is subjected to the directional deformation. © The Author(s) 2013.

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A novel interrogation technique for fully distributed linearly chirped fiber Bragg grating (LCFBG) strain sensors with simultaneous high temporal and spatial resolution based on optical time-stretch frequency-domain reflectometry (OTS-FDR) is proposed and experimentally demonstrated. LCFBGs is a promising candidate for fully distributed sensors thanks to its longer grating length and broader reflection bandwidth compared to normal uniform FBGs. In the proposed system, two identical LCFBGs are employed in a Michelson interferometer setup with one grating serving as the reference grating whereas the other serving as the sensing element. Broadband spectral interferogram is formed and the strain information is encoded into the wavelength-dependent free spectral range (FSR). Ultrafast interrogation is achieved based on dispersion-induced time stretch such that the target spectral interferogram is mapped to a temporal interference waveform that can be captured in real-Time using a single-pixel photodector. The distributed strain along the sensing grating can be reconstructed from the instantaneous RF frequency of the captured waveform. High-spatial resolution is also obtained due to high-speed data acquisition. In a proof-of-concept experiment, ultrafast real-Time interrogation of fully-distributed grating sensors with various strain distributions is experimentally demonstrated. An ultrarapid measurement speed of 50 MHz with a high spatial resolution of 31.5 μm over a gauge length of 25 mm and a strain resolution of 9.1 μϵ have been achieved.

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The Smart Grid needs a large amount of information to be operated and day by day new information is required to improve the operation performance. It is also fundamental that the available information is reliable and accurate. Therefore, the role of metrology is crucial, especially if applied to the distribution grid monitoring and the electrical assets diagnostics. This dissertation aims at better understanding the sensors and the instrumentation employed by the power system operators in the above-mentioned applications and studying new solutions. Concerning the research on the measurement applied to the electrical asset diagnostics: an innovative drone-based measurement system is proposed for monitoring medium voltage surge arresters. This system is described, and its metrological characterization is presented. On the other hand, the research regarding the measurements applied to the grid monitoring consists of three parts. The first part concerns the metrological characterization of the electronic energy meters’ operation under off-nominal power conditions. Original test procedures have been designed for both frequency and harmonic distortion as influence quantities, aiming at defining realistic scenarios. The second part deals with medium voltage inductive current transformers. An in-depth investigation on their accuracy behavior in presence of harmonic distortion is carried out by applying realistic current waveforms. The accuracy has been evaluated by means of the composite error index and its approximated version. Based on the same test setup, a closed-form expression for the measured current total harmonic distortion uncertainty estimation has been experimentally validated. The metrological characterization of a virtual phasor measurement unit is the subject of the third and last part: first, a calibrator has been designed and the uncertainty associated with its steady-state reference phasor has been evaluated; then this calibrator acted as a reference, and it has been used to characterize the phasor measurement unit implemented within a real-time simulator.

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The design process of any electric vehicle system has to be oriented towards the best energy efficiency, together with the constraint of maintaining comfort in the vehicle cabin. Main aim of this study is to research the best thermal management solution in terms of HVAC efficiency without compromising occupant’s comfort and internal air quality. An Arduino controlled Low Cost System of Sensors was developed and compared against reference instrumentation (average R-squared of 0.92) and then used to characterise the vehicle cabin in real parking and driving conditions trials. Data on the energy use of the HVAC was retrieved from the car On-Board Diagnostic port. Energy savings using recirculation can reach 30 %, but pollutants concentration in the cabin builds up in this operating mode. Moreover, the temperature profile appeared strongly nonuniform with air temperature differences up to 10° C. Optimisation methods often require a high number of runs to find the optimal configuration of the system. Fast models proved to be beneficial for these task, while CFD-1D model are usually slower despite the higher level of detail provided. In this work, the collected dataset was used to train a fast ML model of both cabin and HVAC using linear regression. Average scaled RMSE over all trials is 0.4 %, while computation time is 0.0077 ms for each second of simulated time on a laptop computer. Finally, a reinforcement learning environment was built in OpenAI and Stable-Baselines3 using the built-in Proximal Policy Optimisation algorithm to update the policy and seek for the best compromise between comfort, air quality and energy reward terms. The learning curves show an oscillating behaviour overall, with only 2 experiments behaving as expected even if too slow. This result leaves large room for improvement, ranging from the reward function engineering to the expansion of the ML model.

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The increasing number of extreme rainfall events, combined with the high population density and the imperviousness of the land surface, makes urban areas particularly vulnerable to pluvial flooding. In order to design and manage cities to be able to deal with this issue, the reconstruction of weather phenomena is essential. Among the most interesting data sources which show great potential are the observational networks of private sensors managed by citizens (crowdsourcing). The number of these personal weather stations is consistently increasing, and the spatial distribution roughly follows population density. Precisely for this reason, they perfectly suit this detailed study on the modelling of pluvial flood in urban environments. The uncertainty associated with these measurements of precipitation is still a matter of research. In order to characterise the accuracy and precision of the crowdsourced data, we carried out exploratory data analyses. A comparison between Netatmo hourly precipitation amounts and observations of the same quantity from weather stations managed by national weather services is presented. The crowdsourced stations have very good skills in rain detection but tend to underestimate the reference value. In detail, the accuracy and precision of crowd- sourced data change as precipitation increases, improving the spread going to the extreme values. Then, the ability of this kind of observation to improve the prediction of pluvial flooding is tested. To this aim, the simplified raster-based inundation model incorporated in the Saferplaces web platform is used for simulating pluvial flooding. Different precipitation fields have been produced and tested as input in the model. Two different case studies are analysed over the most densely populated Norwegian city: Oslo. The crowdsourced weather station observations, bias-corrected (i.e. increased by 25%), showed very good skills in detecting flooded areas.

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Lawsonia inermis mediated synthesis of silver nanoparticles (Ag-NPs) and its efficacy against Candida albicans, Microsporum canis, Propioniabacterium acne and Trichophyton mentagrophytes is reported. A two-step mechanism has been proposed for bioreduction and formation of an intermediate complex leading to the synthesis of capped nanoparticles was developed. In addition, antimicrobial gel for M. canis and T. mentagrophytes was also formulated. Ag-NPs were synthesized by challenging the leaft extract of L. inermis with 1 mM AgNO₃. The Ag-NPs were characterized by Ultraviolet-Visible (UV-Vis) spectrophotometer and Fourier transform infrared spectroscopy (FTIR). Transmission electron microscopy (TEM), nanoparticle tracking and analysis sytem (NTA) and zeta potential was measured to detect the size of Ag-NPs. The antimicrobial activity of Ag-NPs was evaluated by disc diffusion method against the test organisms. Thus these Ag-NPs may prove as a better candidate drug due to their biogenic nature. Moreover, Ag-NPs may be an answer to the drug-resistant microorganisms.

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The genera Cochliomyia and Chrysomya contain both obligate and saprophagous flies, which allows the comparison of different feeding habits between closely related species. Among the different strategies for comparing these habits is the use of qPCR to investigate the expression levels of candidate genes involved in feeding behavior. To ensure an accurate measure of the levels of gene expression, it is necessary to normalize the amount of the target gene with the amount of a reference gene having a stable expression across the compared species. Since there is no universal gene that can be used as a reference in functional studies, candidate genes for qPCR data normalization were selected and validated in three Calliphoridae (Diptera) species, Cochliomyia hominivorax Coquerel, Cochliomyia macellaria Fabricius, and Chrysomya albiceps Wiedemann . The expression stability of six genes ( Actin, Gapdh, Rp49, Rps17, α -tubulin, and GstD1) was evaluated among species within the same life stage and between life stages within each species. The expression levels of Actin, Gapdh, and Rp49 were the most stable among the selected genes. These genes can be used as reliable reference genes for functional studies in Calliphoridae using similar experimental settings.

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By comparing the SEED and Pfam functional profiles of metagenomes of two Brazilian coral species with 29 datasets that are publicly available, we were able to identify some functions, such as protein secretion systems, that are overrepresented in the metagenomes of corals and may play a role in the establishment and maintenance of bacteria-coral associations. However, only a small percentage of the reads of these metagenomes could be annotated by these reference databases, which may lead to a strong bias in the comparative studies. For this reason, we have searched for identical sequences (99% of nucleotide identity) among these metagenomes in order to perform a reference-independent comparative analysis, and we were able to identify groups of microbial communities that may be under similar selective pressures. The identification of sequences shared among the metagenomes was found to be even better for the identification of groups of communities with similar niche requirements than the traditional analysis of functional profiles. This approach is not only helpful for the investigation of similarities between microbial communities with high proportion of unknown reads, but also enables an indirect overview of gene exchange between communities.

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Current data indicate that the size of high-density lipoprotein (HDL) may be considered an important marker for cardiovascular disease risk. We established reference values of mean HDL size and volume in an asymptomatic representative Brazilian population sample (n=590) and their associations with metabolic parameters by gender. Size and volume were determined in HDL isolated from plasma by polyethyleneglycol precipitation of apoB-containing lipoproteins and measured using the dynamic light scattering (DLS) technique. Although the gender and age distributions agreed with other studies, the mean HDL size reference value was slightly lower than in some other populations. Both HDL size and volume were influenced by gender and varied according to age. HDL size was associated with age and HDL-C (total population); non- white ethnicity and CETP inversely (females); HDL-C and PLTP mass (males). On the other hand, HDL volume was determined only by HDL-C (total population and in both genders) and by PLTP mass (males). The reference values for mean HDL size and volume using the DLS technique were established in an asymptomatic and representative Brazilian population sample, as well as their related metabolic factors. HDL-C was a major determinant of HDL size and volume, which were differently modulated in females and in males.

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To describe maternal and neonatal outcomes in pregnant women undergoing hemodialysis in a referral center in Brazilian Southeast side. Retrospective and descriptive study, with chart review of all pregnancies undergoing hemodialysis that were followed-up at an outpatient clinic of high- risk prenatal care in Southeast Brazil. Among the 16 women identified, 2 were excluded due to follow-up loss. In 14 women described, hypertension was the most frequent cause of chronic renal failure (half of cases). The majority (71.4%) had performed hemodialysis treatment for more than one year and all of them underwent 5 to 6 hemodialysis sessions per week. Eleven participants had chronic hypertension, 1 of which was also diabetic, and 6 of them were smokers. Regarding pregnancy complications, 1 of the hypertensive women developed malignant hypertension (with fetal growth restriction and preterm delivery at 29 weeks), 2 had acute pulmonary edema and 2 had abruption placenta. The mode of delivery was cesarean section in 9 women (64.3%). All neonates had Apgar score at five minutes above 7. To improve perinatal and maternal outcomes of women undergoing hemodialysis, it is important to ensure multidisciplinary approach in referral center, strict control of serum urea, hemoglobin and maternal blood pressure, as well as close monitoring of fetal well-being and maternal morbidities. Another important strategy is suitable guidance for contraception in these women.

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The objective of this work was to compare the soybean crop mapping in the western of Parana State by MODIS/Terra and TM/Landsat 5 images. Firstly, it was generated a soybean crop mask using six TM images covering the crop season, which was used as a reference. The images were submitted to Parallelepiped and Maximum Likelihood digital classification algorithms, followed by visual inspection. Four MODIS images, covering the vegetative peak, were classified using the Parallelepiped method. The quality assessment of MODIS and TM classification was carried out through an Error Matrix, considering 100 sample points between soybean or not soybean, randomly allocated in each of the eight municipalities within the study area. The results showed that both the Overall Classification (OC) and the Kappa Index (KI) have produced values ranging from 0.55 to 0.80, considered good to very good performances, either in TM or MODIS images. When OC and KI, from both sensors were compared, it wasn't found no statistical difference between them. The soybean mapping, using MODIS, has produced 70% of reliance in terms of users. The main conclusion is that the mapping of soybean by MODIS is feasible, with the advantage to have better temporal resolution than Landsat, and to be available on the internet, free of charge.