Estimation and Error Analysis for Optomechanical Inertial Sensors

A sensor model and methodology to estimate the forcing accelerations measured using a novel optomechanical inertial sensor with the inclusion of stochastic bias and measurement noise processes is presented. A Kalman filter for the estimation of instantaneous sensor bias is developed; the outputs from this calibration step are then employed in two different approaches for the estimation of external accelerations applied to the sensor. The performance of the system is demonstrated using simulated measurements and representative values corresponding to a bench-tested 3.76 Hz oscillator. It is shown that the developed methods produce accurate estimates of the bias over a short calibration step. This information enables precise estimates of acceleration over an extended operation period. These results establish the feasibility of reliably precise acceleration estimates using the presented methods in conjunction with state of the art optomechanical sensing technology.

Voltammetric E-Tongue for Honey Adulteration Detection

The aim of this study is to establish the usefulness of an electronic tongue based on cyclic voltammetry e-tongue using five working electrodes (gold, silver, copper, platinum and glass) in honey adulteration detection. Authentic honey samples of different botanical origin (acacia, tilia, sunflower, polyfloral and raspberry) were adulterated with agave, maple, inverted sugar, corn and rice syrups in percentages of 5%, 10%, 20% and 50%. The silver and copper electrodes provided the clearest voltammograms, the differences between authentic and adulterated honey samples being highlighted by the maximum current intensity. The electronic tongue results have been correlated with physicochemical parameters (pH, free acidity, hydroxymethylfurfural content—5 HMF and electrical conductivity—EC). Using statistical methods such as Linear discriminant analysis (LDA) and Support vector machines (SVM), an accuracy of 94.87% and 100% respectively was obtained in the calibration step and 89.65% and 100% respectively in the validation step. The PLS-R (Partial Least Squares Regression) model (constructed from the minimum and maximum current intensity obtained for all electrodes) was used in physicochemical parameters prediction; EC reached the highest regression coefficients (0.840 in the calibration step and 0.842 in the validation step, respectively), being followed by pH (0.704 in the calibration step and 0.516 in the validation step, respectively).

A comparison between coincident laser and Ku radar versus S- to C-band 'snow radar' data for airborne retrievals of snow depth on sea ice

<p>Snow depth estimates remain a large uncertainty for constraining the accuracy of sea ice thickness retrievals from polar altimetry. There have been several recent investigations into methods for estimating snow depth from airborne observations over sea ice; this poster outlines a comparison between two different methods applied to Operation IceBridge data from the Spring 2016 campaign. The first co-locates visible-band laser scanner data from the Airborne Topographic Mapper with Ku-band data from the CReSIS radar, using a fixed threshold first-maximum retracker algorithm for retracking radar waveforms and applying a calibration step to remove the vertical offset between sensors at leads. This method represents an airborne proxy for the newly-aligned ICESat-2 and CryoSat-2 orbits of the Cryo2Ice campaign. The second method uses the conventional CReSIS ultrawide-band frequency‐modulated continuous‐wave ‘snow radar’ system, that ranges between S- and C-band, applying the retracker algorithm described by Newman et al 2014. We evaluate properties of the estimated snow depth distribution, and alignment of air-snow and snow-ice interfaces, along the aircraft track and the scale of correlation between sensors.</p>

The New Method To Calibrate Iso/cie General Skies modelled In Artificial Skies

Recently sky luminance distributions under fifteen ISO/CIE sky types were standardised in relative terms, i.e. all elementary sky luminance are normalised by the zenith luminance in nature. However, these standard sky luminance patterns can be characterised also in their physical units, see in CIE215:20014 which can be reduced by suitable intensity scales to simulate the very high natural sky luminance in laboratory under artificial sky domes. For the design of the electric illumination system of the artificial sky the appropriate zenith luminance for each sky type has to be derived respecting the indicatrix and gradation functions of each sky type. Thus, the sky patterns simulated in the artificial sky can be calibrated either by luminance measurements or by analysing fish-eye photos taken from the sky centre showing the smoothness and gradual changes of homogeneous sky type luminance patterns. The sky luminance images can be utilised to proceed with the adjustment or dimming of the LED electrical system to the final calibration check containing zenith luminance and exterior illuminance in the second calibration step.

State-level COVID-19 Trend Forecasting Using Mobility and Policy Data

The importance of pandemic forecast cannot be overemphasized. We propose an interpretable machine learning approach for forecasting pandemic transmission rates by utilizing local mobility statistics and government policies. A calibration step is introduced to deal with time-varying relationships between transmission rates and predictors. Experimental results demonstrate that our approach is able to make accurate two-week ahead predictions of the state-level COVID-19 infection trends in the US. Moreover, the models trained by our approach offer insights into the spread of COVID-19, such as the association between the baseline transmission rate and the state-level demographics, the effectiveness of local policies in reducing COVID-19 infections, and so on. This work provides a good understanding of COVID-19 evolution with respect to state-level characteristics and can potentially inform local policymakers in devising customized response strategies.

In-process calibration of smart structures produced by incremental forming

Smart load-bearing structures are created by forming integration of functional materials into passive metallic components with target-oriented pre-stress conditions by rotary swaging. Their sensory capability cannot only be used during the utilization but also during the manufacturing phase. Previous works demonstrated how this capability paves the way for efficient monitoring and controlling of the used integration process. In search of an even higher overall efficiency of the manufacturing chain, the subsequent costly calibration step deserves closer attention. Therefore, a cost- and time-efficient approach for the process-integrated calibration of a sensor-integrated structure is proposed in this paper. During the in-process calibration, the acting process forces are measured both in the integrated sensor and in a special-built clamping fixture. The measured data can be transferred into calibration slopes of the sensory structures. A suitable signal processing based on the process characteristics is performed to compensate interference effects on the raw signals. As a result, an accuracy of the calibration better than 2% of the nominal value compared to an offline standardized calibration is achieved with the in-line calibration method. Consequently, efficiency in the manufacturing of sensory structures is further boosted by avoidance of setup or logistical operations.

USING THE TOTAL EXPLORATORY FACTOR ANALYSIS (T-EFA) AS A CALIBRATION TECHNIQUE FOR SLEUTH MODEL

Developments in information technologies (IT) allow to modelling dynamic and complex form of cities and several studies have been implemented since 1990s. The cellular automata based urban growth simulation model, SLEUTH is the most well-known one among the simulation models. Calibration is the most important stage of the model created in three stages such as test, calibration, prediction. The more precise the calibration is completed, the more accurate the model generates. Several methods have been developed for the calibration step in which growth coefficients values are calculated by metrics. The study aims to investigate success of the Total Exploratory Factor Analysis (T-EFA) technique, which provides using the 13 metrics all together, in rapid grown settlement areas using high resolution data. In this context, the Sancaktepe district of Istanbul was selected as the study area and a simulation model was generated for the year 2050. The obtained results are promising to apply the T-EFA method in different studies.

Development and validation of GC/MS method for simultaneous determination of 16 polycyclic aromatic hydrocarbons (PAHs) in pork meat matrix

The major processes for introducing polycyclic aromatic hydrocarbons (PAHs) in food are smoking and grilling of different products. But in addition, PAHs can permeate in the food chain due to their high lipophilicity and ability to be accumulated in specific tissue, through contaminated animal feed. Further, when some parts of these animals are marketed as food, the accumulated PAHs can go to the human organism. Some of them are classified as highly toxic, carcinogenic and mutagenic for animal and human organisms so they are under consideration of International and European legislation. This work reports development and validation of simple and fast GC/MS method for 16 PAHs determination. Comparison of two methods for sample preparation in pork meat matrix standard extraction/saponification procedure and modified QuEChERS method is also done. In addition, this paper report the calibration step of instrument and a recovery study for 16 PAHs in model pork meat, using modified QuEChERS procedure for sample pretreatment. The calibration step with accessible and suitable for use in real laboratory conditions internal standard (chrysene D12) is done in the range 10–100 ppb using toluene as solvent. The obtained results show very good linearity (R2 = 0.99 to 1.00). For the recovery study six model samples were spiked with 16 PAHs and they all are subjected to QuEChERS procedure. The recovery is calculated and the obtained data (71–120%) is in a good correlation with requirements of international legislation. Finally, LOD values for all 16 investigated compounds of modified GC/MS method and for the instrument were determined.

Dense point cloud acquisition with a low-cost Velodyne VLP-16

This study develops a method to acquire dense point clouds with a low-cost Velodyne VLP-16 lidar system, without using expensive GNSS positioning or IMU. Our setting consists in mounting the lidar on a motor to continuously change the scan direction, which leads to a significant increase in the point cloud density. A post-treatment reconstructs the position of each point accounting for the motor angle at the time of acquisition, and a calibration step accounts for inaccuracies in the hardware assemblage. The system is tested in indoors settings such as buildings and abandoned mines, but is also expected to give good results outdoors. It is also compared with a more expensive system based on IMU registration and a SLAM algorithm. The alignment between acquisitions with those two systems is within a distance of 2 cm.

Optimization of a gas chromatographic unit for measuring biogenic volatile organic compounds in ambient air

A new online gas chromatographic method dedicated to biogenic volatile organic compound (BVOC) analysis was developed for the measurement of a 20 BVOC gaseous mixture (isoprene; β-pinene; α-pinene; limonene; ocimene; myrcene; sabinene; Δ3-carene; camphene; 1,8 cineole; terpinolene; linalool; α-phellandrene; nopinone; citral; α-terpinene; β-caryophyllene; p-cymene; γ-terpinene; and 2-carene) at a time resolution of 90 min. The optimized method includes an online Peltier-cooled thermodesorption system sample trap made of Carbopack B coupled to a gas chromatographic system equipped with a 60 m, 0.25 mm internal diameter (i.d.) BPX5 column. Eluent was analysed using flame ionization detection (FID). Potassium iodide was identified as the best ozone scrubber for the 20 BVOC mixture. In order to obtain an accurate quantification of BVOC concentrations, the development of a reliable standard mixture was also required. Quantification of BVOCs was reported with a detection limit ranging from 4 ppt for α-pinene to 19 ppt for sabinene. The main source of uncertainty was the calibration step, stressing the need for certified gaseous standards for a wider panel of BVOCs. This new method was applied for the first time to measure BVOCs in a pine forest during the LANDEX episode 1 field campaign (summer 2017). All target BVOCs were detected at least once during the campaign. The two major monoterpenes observed were β-pinene and α-pinene, representing 60 % of the measured terpenoid concentration on average, while isoprene represented only 17 %. The uncertainties determined were always below 13 % for the six major terpenes.