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Being an offline measurement technique, Polarization Depolarization Current (PDC) data is conventionally measured after the oil-paper insulation of the equipment reaches thermal equilibrium. Depending on the condition of the insulation, PDC data measurement time typically ranges from several minutes to few hours. It is understood that atmospheric conditions controls the value of ambient temperature. During field measurement, these conditions may not remain constant throughout the PDC recording process. Variation in ambient temperature disturbs the thermal equilibrium that the equipment may have attained at the start of the measurement procedure. Such a condition invariably affects the recorded dielectric response data. However, methods that are available for analyzing relaxation current assume that temperature equilibrium is maintained throughout the measurement period. Results presented in this paper show that dielectric response data is indeed affected if the ambient temperature increases/decreases monotonically. A method is also proposed in this paper using which the effect of such temperature variation on the recorded relaxation current data can be eliminated. This also ensures correct interpretation of PDC data for condition assessment. Analysis presented shows that the value of the equilibrium temperature does not affect the performance of the proposed technique. The applicability of the proposed methodology is first tested on laboratory samples. Thereafter, it is applied to data collected from a real life power transformer. [ABSTRACT FROM AUTHOR]

In this paper, we report the development of an oxygen sensor using a simple device made from a film of ZnO crystals dispersed over a paper surface. Due to the high porosity of this kind of device made from paper and ZnO, a large photoconductive effect is observed as result of the fast absorption and desorption of oxygen from the ZnO surface. To detect oxygen, we propose to use ultraviolet (UV) illumination over the photoconductive surface of the sensor, the applied UV light produces oxygen desorption causing current variations through the sensor that are proportional to the oxygen presence nearby the sensor surface. The sensor developed in this paper is attractive because it is remarkably easy to fabricate, employs only very low-cost materials for its construction, and shows a better sensitivity at low concentration of oxygen at partial vacuum environments. [ABSTRACT FROM PUBLISHER]

The adoption of prognostics for critical assets has the potential to advance asset management in the power industry significantly. Whereas diagnostic techniques can identify the presence of incipient faults, prognostics aims to predict the future state of a given asset [1], [2]. Prognostics can therefore be used to estimate the remaining useful life (RUL) of the asset, and help plan maintenance while minimizing the risk of failure in service. Prognostics requires a good model of the process of deterioration, from inception through to failure [1]?[3]. Deterioration may be due to aging, as in the case of paper insulation, or it may be due to a fault. Regardless of the cause of deterioration, prognostics is useful only if the deterioration is slow enough that maintenance (repair or replacement) can be scheduled during the predicted RUL. Thus, prognostics is not superior to diagnostics if the deterioration is so rapid that failure cannot be prevented. [ABSTRACT FROM PUBLISHER]

This paper proposes an approach to determine the participation of algebraic variables in power system modes. The approach is based on a new interpretation of the classical participation factors, as well as on the definition of adequate output variables of the system's state-space representation. The paper considers both the linear and generalized eigenvalue problems for the calculation of the participation factors and presents a theorem to cope with eigenvalue multiplicities. An illustrative example on the two-area system, as well as a study on a 1479-bus dynamic model of the all-Irish transmission system are carried out to support the theory and illustrate the features of the proposed approach. [ABSTRACT FROM AUTHOR]

Quantitative analysis is a solid, well established mathematical technique that can be used to analyze the result of survey(s) in a specific field. Survey analysis is usually based on the study of the effect of independent variables on a dependent variable. Although quantitative analysis can use an R-Squared value as a method to measure the strength of the relationship between the independent and dependent variables, it does not capture the effect of participants’ ambiguity when answering questionnaires. The source of such ambiguity stems from the process of completing the survey, whereby the respondent may have answered most of the independent questions with ease, but has difficulty in responding to the overall dependent question (or vice versa). The objective of this paper is to demonstrate the use of fuzzy logic as a mechanism to measure the uncertainty faced by participants when filling a questionnaire. Based on the participants’ responses to the independent variables, the proposed technique uses fuzzy logic inference to measure the subjectivity (qualitative aspect) of the participants’ response to the dependent variable. Beyond quantitative analysis, augmentation with such a fuzzy module can provide clearer picture to analysts when analyzing the survey results. In this paper, Cloud acceptance survey will be used as a vehicle to provide step-by-step explanation of the proposed augmentation technique to unleash the hidden knowledge in similar cases to cloud computing long survey questionnaire where participants may change their mind at the end of the survey causing uncertainty represented in discrepancy of the collected data. The proposed technique would only be valid for long surveys like the presented Cloud computing acceptability where uncertainty in the data is inevitable. [ABSTRACT FROM AUTHOR]

Using the barometer for height estimation often requires the use of external reference to correct biases in measurement. These biases are often caused by the change of the ambient pressure environment. The barometric height estimation is especially challenging in tactical and rescue applications where high temperatures or sudden large pressure shocks can change the pressure rapidly. We assess the suitability of barometers for infrastructure-free navigation in tactical applications. First, this paper investigates the effect of transition in seamless indoor/outdoor navigation. Second, we measure the effects of pressure shocks, caused by explosions or firearms, on low-cost and lightweight micro-electromechanical barometers to ensure that the sensors are capable of operating under these conditions. Finally, we investigate the use of sonar measurement to estimate the vertical speed as an alternative to the reference barometer for infrastructure-free navigation. The fusion of barometer and sonar achieved on average 0.46-m root-mean-square error (RMSE) while simple barometric height estimation had a RMSE of 0.65 m. The fusion method had no errors over 1.5 m during the test. This accuracy is generally sufficient to find the correct floor level which is crucial for tactical situational awareness. The goal of this paper is to develop the methods for seamless indoor/outdoor navigation, and therefore the most important result of this paper is that the error caused when transitioning between outdoor and indoor environments is visibly reduced. [ABSTRACT FROM AUTHOR]

While formal and rigorous procedures are adopted to ensure the reliability of measurement results, the decision-making activities based on the information returned by measurement are often poorly structured and based on vague assumptions and reasoning, thus negatively impacting the reliability of the achieved conclusion. To overcome this problem, a structured multicriteria decision-making approach based on the analytic hierarchy process was recently proposed in the literature to properly support decision-making activities by exploiting the information provided by measurement results related to heterogeneous properties and its application was demonstrated in a case study. Using the same case study, this paper analyses the sensitivity of the obtained conclusion to various uncertainty sources that are embedded in that approach. In particular, the impact of uncertainties on both measurement and pairwise comparisons of the criteria is analyzed and their combined effect is evaluated by considering a worst case situation. Moreover, the effect of the formula adopted to aggregate the information returned by the measurement of heterogeneous properties on the final decision is considered. The performed analysis contributes to support a disciplined and methodologically sound implementation of decision-making activities, significantly improving both the repeatability and reproducibility of the whole evaluation process, as well as the confidence in the achieved conclusions. [ABSTRACT FROM AUTHOR]

This paper discusses the design and implementation of a biomimetic, flexible antenna system consisting of flexible dipoles on Pyralux AP. They are implemented into a novel, airborne atmospheric sensor system. The antennas and substrate serve a secondary function as a rotor system, forcing the sensor nodes to autorotate when falling to maximize drag and decrease their fall speed. The designed antenna system works both in the industrial, scientific, and medical band and the GPS L1 band with the designed antennas having bandwidths of 100 and 130 MHz, respectively. This paper also presents a test procedure to characterize the antenna performance at different bend angles. [ABSTRACT FROM AUTHOR]

In prior work, we have shown how the basic concepts and terms of quantum mechanics relate to factorizations and marginals of complex-valued quantum mass functions, which are generalizations of joint probability mass functions. In this paper, using quantum mass functions, we discuss the realization of measurements in terms of unitary interactions and marginalizations. It follows that classical measurement results strictly belong to local models, i.e., marginals of more detailed models. Classical variables that are created by marginalization do not exist in the unmarginalized model, and different marginalizations may yield incompatible classical variables. These observations are illustrated by the Frauchiger–Renner paradox, which is analyzed (and resolved) in terms of quantum mass functions. Throughout, the paper uses factor graphs to represent quantum systems/models with multiple measurements at different points in time. [ABSTRACT FROM AUTHOR]

The increasing deployment of distribution-level phasor measurement units (PMUs) calls for dynamic distribution state estimation (DDSE) approaches that tap into high-rate measurements to maintain a comprehensive view of the distribution-system state in real time. Accordingly, this paper explores the development of a fast algorithmic framework by casting the DDSE task within the time-varying optimization realm. The time-varying formulation involves a time-varying robustified least-squares approach, and it naturally models optimal trajectories for the estimated states under streaming of measurements. The formulation is based on a linear surrogate of the AC power-flow equations, and it includes an element of robustness with respect to measurement outliers. The paper then leverages a first-order prediction-correction method to achieve simple online updates that can provably track the state variables from heterogeneous measurements. This online algorithm is computationally efficient as it relies on the Hessian of the cost function without computing matrix-inverse. Convergence and bounds on the estimation errors of proposed algorithm can be analytically established. [ABSTRACT FROM AUTHOR]

Most fundamental research on thermal perception focuses on the fingers or the hand. Also most existing and proposed thermal devices are meant to be applied to hand or fingers. However, if the hands are needed for other tasks, application of thermal stimulation to other body regions should be considered. This paper surveys the literature on thermal perception and thermal devices relevant to such other body regions. It starts with a short description of the experimental methods used in the various studies, such as the methods of limits, the two-alternative forced choice method, and magnitude estimation. This is followed by thermal psychophysical studies on detection, adaptation, spatial summation, and resolution. Next some striking thermal illusions are presented, such as a thermal grill and a seemingly continuously warming or cooling stimulus. Finally, the few studies on thermal communication and applications are summarized. These latter studies mainly focus on communicating emotions or playing computer games. The overall conclusion of this survey is that thermal devices should not focus on conveying complex messages, but especially in the areas of gaming or communication there seem to be interesting possibilities for further developments. [ABSTRACT FROM AUTHOR]

This paper is concerned with estimating remaining useful life (RUL) for a class of stochastic degrading systems with surviving degradation paths and uncertain measurements. The motivation comes from two engineering facts: the system's degradation state is discretely monitored and the measured degradation signals are taken from a survival degradation path, i.e., its lifetime is greater than the latest observation time, and the underlying degradation state cannot be perfectly observed due to the noise, disturbance, nonideal instruments, etc. Thus, the measured degradation signals are uncertain, but related to the underlying degradation state. Toward this end, we first present a general stochastic degradation modeling approach to account for the abovementioned facts. Then, a non-Gaussian degradation state transition equation is derived considering the constraint of the survival path and thus the particle filtering algorithm is used to estimate the underlying degradation state in real time from uncertain measurements. Furthermore, we derive the RUL distribution based on the first-passage time concept which incorporates the uncertainty of the estimation for the degradation state and can be real-time updated based on the available surviving yet uncertain measurements. The novelty of this paper is to allow us to exclude the probability of failure between discrete monitoring times and to account for the impacts of surviving and uncertain measurements on estimating both the degradation state and the RUL. To apply the presented methodology, a maximum likelihood estimation framework is provided to determine the model parameters based on the expectation maximization algorithm together with particle filtering and smoothing methods. As a special case fallen into the presented framework, a linear degradation modeling and prognostic realization is discussed. Finally, we demonstrate the proposed approach by a case study. [ABSTRACT FROM AUTHOR]

Despite the large number of privacy-preserving aggregation protocols in the smart grid, there is no common methodology for evaluating and comparing their privacy guarantees. Protocol discussion often lacks a formal evaluation of the proposed privacy guarantees. In order to transfer the well-established formal methodology of game-based proofs to the smart grid domain, in this paper we: 1) present a game-based privacy definition which addresses the privacy requirement to be captured in an aggregation protocol (the definition may be used or extended for other protocols); 2) exemplify our game-based proof technique for two aggregation protocols; and 3) provide a novel and compact way to visualize and easily compare the privacy guarantees of different protocols. We employ two sample protocols that reflect the basis of the most common approaches currently found in the energy aggregation literature. In summary, we contribute a guideline on how to conduct formal evaluations for protocol developers as well as an easy-to-understand way to assess the privacy guarantees of different aggregation protocols for non-experts. [ABSTRACT FROM AUTHOR]

This paper addresses the evaluation of object detection performance for non-contact safety-related sensors in low-visibility environments due to adverse weather conditions. An evaluation metric, MOT (Minimum Object-detectable Transmittance), is proposed to quantitatively evaluate the influence of the low-visibility environments on the object detection performance. Traditionally, the Meteorological Optical Range (MOR) has been used for this purpose. However, MOR is not appropriate for the sensor evaluation because it is a meteorological metric which is optimized for human eyes to estimate the distance at which a person can see clearly through an atmosphere. On the other hand, MOT is a physical and optical measure that quantifies the relationship between the spatial transmittance and the distance at which a sensor can detect a specified object. It is specialized for the sensor evaluation and can express the sensor characteristics in the low-visibility environments at each measurement distance. The usefulness of MOT will be demonstrated by presenting the experimental results of MOT measurements for various sensor devices in a fog space reproduced with environmental simulator equipment. [ABSTRACT FROM AUTHOR]

This paper addresses the performance in the retrieval of 3-D mean deformation maps by exploiting simultaneous or quasi-simultaneous squinted synthetic aperture radar (SAR) interferometric acquisitions in a repeat-pass scenario. In multisatellite or multibeam low earth observation missions, the availability of two (or more) lines of sight (LOSs) allows the simultaneous acquisition of SAR images with different squint angles, hence improving the sensitivity to the north–south component of the deformation. Due to the simultaneity of the acquisitions, the troposphere will be highly correlated and, therefore, will tend to cancel out when performing the differential measurement between the interferograms obtained with the different LOSs, hence resulting in a practically troposphere-free estimation of the along-track deformation measurement. In practice, however, the atmospheric noise in the differential measurement will increase for increasing angular separations. This paper expounds the mathematical framework to derive the performance by properly considering the correlation of the atmospheric delays between the simultaneous acquisitions. To that aim, the hybrid Cramér–Rao bound is exploited making use of the autocorrelation function of the troposphere. Some performance examples are presented in the frame of future spaceborne SAR missions at C and L band. [ABSTRACT FROM AUTHOR]

The interest of industry and academia in medical measurements continues to increase, due to technology advancements that allow new sensors, measurement systems, and methodologies, supporting a wide number of medical applications. [ABSTRACT FROM PUBLISHER]

Infrared thermal imager is an important means of temperature measurement. However, the measurement results of infrared thermal imagers are easily affected by interference factors, resulting in non-negligible temperature measurement errors, and the infrared thermal imager may be affected by multiple factors at the same time. To research the influence of multiple interference factors on infrared temperature measurement, this paper takes two common interference factors in actual temperature measurement processes, dust and measuring distance, as examples. Firstly, this paper analyzed the influence of dust and measuring distance and carried out the temperature measurement experiments under multi-factor interference and the experiments under single-factor interference respectively. Then, based on nonlinear polynomial regression, a compensation method is proposed to compensate for the measurement errors caused by dust and measuring distance. Results demonstrate that the proposed compensation method can significantly reduce the measurement errors caused by multiple interference factors, which is essential to promote the application of infrared thermal imagers in complex scenes with multiple interferences. [ABSTRACT FROM AUTHOR]

Contractures are generally assessed by a physician or physical therapist through palpation. However, contracture palpation requires skill and experience. The frictional vibration, which has a pulse-like vibration due to sliding disturbances around the affected area during palpation, is important in assessing the degree of contracture progression. This paper aims to enhance the perceptual sensitivity of frictional vibration for contracture palpation using a vibrotactile feedback system. We previously proposed an evaluation system for palpation with a wearable skin vibration sensor that detects skin-propagated vibration, allowing touch with a bare fingertip. In this paper, we propose the vibrotactile feedback system that presents the tactile information of the fingertip detected by the wearable tactile sensor to the temples with a vibrotactile display. A stimulator that gives vibrations similar to those during the palpation, which include pulse-like vibration and small vibration, was assembled. Then, psychophysical experiments on the vibrotactile feedback system were conducted using this stimulator. The results showed that the detection sensitivity of the pulse-like vibration was significantly enhanced with the feedback. [ABSTRACT FROM AUTHOR]

Location-aware networks enable new services and applications in fields such as autonomous driving, smart cities, and the Internet-of-Things. Network localization and navigation (NLN) is a recently proposed paradigm for accurate ubiquitous localization without the need for extensive infrastructure. In NLN, devices form an interconnected network for the purpose of cooperatively localizing one another. This paper introduces Peregrine, a system that combines real-time distributed NLN algorithms with ultra-wideband (UWB) sensing and communication. The Peregrine software integrates three NLN algorithms to jointly perform 3-D localization and network operation in a technology agnostic manner, leveraging both spatial and temporal cooperation. Peregrine hardware is composed of compact low-cost devices that comprise a microprocessor and a UWB radio. The contribution of each algorithmic component is characterized through indoor network experimentation. Results show that Peregrine is robust, scalable, and capable of sub-meter accuracy in challenging wireless environments. [ABSTRACT FROM AUTHOR]

The availability of novel materials is one of the bases of the development of science and technology. During the last decades, the research on artificial materials exhibiting novel electrical and magnetic properties received significant attention from the scientific and industrial communities. In particular, the so-called metamaterials represent an interdisciplinary field of investigation nowadays and offer promising applications in many fields, such as electromagnetism, optics, thermal, and acoustics. Metamaterials are engineered composite structures which can exhibit physical properties not readily observed in common materials available in nature. Their crucial aspect is to reproduce structured materials, whose repeated elementary cell represents the “metamolecule.” The linear dimensions of the cells are sub-wavelength. As a consequence, the material behaves uniformly. Special attention was received by metamaterials showing negative values of the effective permittivity and permeability in a given frequency range. In this paper, we revisit the concept of such macroscopic parameters, in particular, from the measurement point of view on a macroscopic scale. Indeed, an accurate characterization of such material properties is a key issue for paving new technological applications. Thus, we start from the very definition of the quantities of interest at a macroscopic level. We focus on the meaning of measurement of magnetism in composite magnetic materials, deriving the relevant measurement models. [ABSTRACT FROM AUTHOR]

Terrain-based vehicle localization is a valuable alternative to GPS when the signal is blocked or dynamic occlusions exist. However, braking events can induce the slips and vibrations of the vehicle and, thus, increase the errors of terrain-based position estimations. This paper develops a terrain-based localization approach which is robust to braking events. First, the terrain map is generated and stored before localization, which includes distance measurements, terrain feature data, and the geographic locations. The terrain feature data are pitch differences to eliminate the accumulated error. Next, particle-filter-based and acceleration-considered vehicle localization is proposed for position estimation. It takes into account the influence of braking in the vehicle model and the inference process. Experimental results demonstrate the repeatability of pitch difference measurements and the robustness of the proposed approach in the cases of smooth driving and braking. [ABSTRACT FROM AUTHOR]

Land surface temperature and emissivity (LST&E) are key variables for a wide variety of surface–atmosphere studies, and it is very important to validate the accuracy of different LST&E retrieval algorithms. In this paper, the accuracy of the Advanced Spaceborne Thermal Emission and Reflection (ASTER) temperature emissivity separation (TES) algorithm with the water vapor scaling (WVS) method and the ASTER standard LSE&E products (without WVS) was validated using 12 ASTER scenes from May 2012 to September 2012 with concurrent ground LST and emissivity measurements collected in an arid area in northwest China during the Heihe Watershed Allied Telemetry Experimental Research experiment. Both the National Center for Environmental Prediction (NCEP) and MOD07 atmospheric profile products were employed to perform the atmospheric correction. The results showed that the WVSTES LSTs retrieved from the two profiles both demonstrate good accuracies, with average biases of 0.34 and 0.24 K and average root-mean-square errors (RMSEs) of 1.52 and 1.46 K for the NCEP and MOD07 profiles, respectively. When the WVS was not applied, we obtained an average bias of 1.26 K and an average RMSE of 2.05 K for the AST08 product. The emissivities from the WVSTES algorithm with the two profiles both showed good agreements with the ground CE312 measurements, with mean differences of the five ASTER bands that were less than 0.01. AST05 showed anomalous emissivity spectra and underestimated the emissivity values of graybody surfaces when compared with the ground data, with mean differences of greater than 0.015, which were more obvious for cases with high water vapor. This paper demonstrated that the WVS method is critical for retrieving ASTER TES LST with accuracies within 1.5 K and emissivity within 0.015 for a wide range of atmospheric conditions and land surface types. [ABSTRACT FROM AUTHOR]

Air-borne micrometer and submicrometer particles produced by anthropogenic sources contaminate atmospheric air, especially in large cities where both population and industrial activities are higher leading to a reduced air quality. Recent research has pointed out particles less than 2.5 \mum in diameter (PM2.5) as a potential health hazard. To address this issue, stricter legislation has been put into force to reduce PM2.5 emissions. This paper is focused on the development of an impulsive microelectrostatic precipitation technology for charging and removal of fine air-borne particles in an economically feasible way. In this paper, a compact coaxial precipitator has been developed for possible indoor air cleaning applications. High-voltage impulses together with dc voltage have been used for energization of the reactor as it has been shown to enhance the precipitation efficiency. This precipitation system has been used for removal of fumes and fine air-borne particles from ambient air. In addition to the experimental part, analytical work has been conducted to optimize the electrostatic precipitation process and to reduce its power consumption. [ABSTRACT FROM PUBLISHER]

This paper describes the preflight spectral calibration methods and results for the Orbiting Carbon Observatory 2 (OCO-2), following the approach developed for the first OCO. The instrument line shape (ILS) function and dispersion parameters were determined through laser-based spectroscopic measurements, and then further optimized by comparing solar spectra recorded simultaneously on the ground by the OCO-2 flight instrument and a collocated high-resolution Fourier transform spectrometer (FTS). The resulting ILS profiles and dispersion parameters, when applied to the FTS solar data, showed agreement between the spectra recorded by the spectrometers and FTS to approximately 0.2% RMS, satisfying the preflight spectral calibration accuracy requirement of <0.25% RMS. Specific changes to the OCO-2 instrument and calibration process, compared to the original OCO, include stray-light protection; improved laser setup; increased spectral sampling; enhanced data screening, and incremental improvements in the ILS, dispersion, and FTS optimization analyses. [ABSTRACT FROM PUBLISHER]

Testability analysis is a fundamental prerequisite to any fault location or parameter identification technique (FLPIT) for analog circuits. However, differently from the linear time-invariant field, this topic has been poorly investigated with regard to nonlinear circuits. In this paper, for the first time, to the best of our knowledge, the question is addressed with reference to periodically switched networks with dc stimuli (PSNDSs), a class of inherently nonlinear time-varying circuits that subsumes dc-dc converters as noteworthy members. A rigorous testability measure at both a circuit and a component level is thereby obtained, which provides information as to how many and which components can be unambiguously diagnosed or estimated from time-domain measurements. Consequently, it yields an upper bound, independent of the parameter values and the test instants, to the performance of whatever method actually employed as an FLPIT. This theoretical testability metric has been converted into an efficient computer program for the fully automated testability analysis of PSNDSs presented herein. Such a computer program represents the first practical testability gauge for PSNDSs: it can be employed by both test engineers and circuit designers as a guide to properly selecting injection and measurement points as well as estimating the number of necessary measurement instants, so as to shape their own FLPITs. Several examples are provided for which an in-depth pencil-and-paper testability analysis is contrasted with its automated counterpart provided by the aforementioned software: in particular, popular dc-dc converter topologies are thoroughly analyzed. Comparisons with a previously proposed frequency-domain testability measure are also considered. [ABSTRACT FROM PUBLISHER]

This paper presents the analysis of all driving during 1 year by 14 older drivers from the Candrive study. Data analytic techniques have been applied to this unique big data set that includes global positioning system and geographic information system data with an average of 1567 trips and 20 200 km for each driver. The drivers have stable general, cognitive, and physical health over the year. This paper identifies trip features and tests their potential to be used to distinguish between driver pairs and shows that trip length and duration allow 90.1% and 90.1% of the 91 driver pairs (14 drivers) to be distinguished ( $p<5$ %). Driver velocity histograms are also shown to allow driver pairs to be distinguished. This paper explores the deceleration habits of the drivers by locating all deceleration events with a net velocity drop of >=4 km/h (average of 30 156 events per driver) and finds that the event mean and minimum deceleration values have different two-phase relationships for each driver. Trips taken by a driver are compared with the drivers’ two-phase relationships and this paper shows that the measures achieve their maximum performance for trips with >=8 events. The minimum measure is better (correlation of 0.74) than the mean measure (0.54). These relationships provide a measure of a driver’s unique behaviors and could allow more personalized autonomous driving systems and capture features of the deceleration habits for the driver that can be used to distinguish between drivers. [ABSTRACT FROM PUBLISHER]

We evaluated whether a vibrotactile breathing pacer would influence two measures of affect during a cognitive stressor. In particular, we examined whether changes in breathing would be evident, and if so, whether these would mediate the effects of breathing pacer on self-report anxiety and skin conductance. Our results were surprising: although we observed the expected effects on breathing, we were unable to demonstrate that changes in breathing parameters were responsible for the observed changes in self-report anxiety. In addition, we failed to show that the pacer had an impact on skin conductance. In this paper, we investigate why we did not observe the expected effects. We believe our negative results have implications for evaluating technological interventions for affect regulation. [ABSTRACT FROM AUTHOR]

Stellar atmospheric refraction imaging error, as the optical imaging variation of starlight before and after passing through Earth’s atmosphere, is one of the key issues for terrestrial star trackers to obtain accurate attitude measurement results. To resolve the problem, a refraction surface-based stellar atmospheric refraction correction method is presented in this paper. Different from existing correction methods, a new atmospheric refraction feature, i.e., stellar atmospheric refraction surface, is proposed to represent the random irregular optical phenomena of starlight, and avoids the limitations of theoretical atmospheric models and empirical formulas. On the basis of the principles of “collinear refraction surfaces”, “invariable refraction surface”, the proposed model successfully realizes the accuracy atmospheric refraction correction by the sensor itself, without external atmospheric parameters. Then, by analyzing the error factors parallel and perpendicular to the atmospheric refraction surface, the atmospheric refraction correction error estimation model is established to forecast the attitude accuracy after correction. Numerical simulations and night sky experiments validate the reliability of our atmospheric refraction correction method and error estimation model. The average angular distance error of the test star tracker is reduced from $31.1310''$ into $1.7705''$ , which is significantly decreased by 94.31%. [ABSTRACT FROM AUTHOR]

Objective: This paper aims to analyse the human musculoskeletal and energetic adaptation mechanisms when physically interacting with a unilateral knee orthosis during treadmill walking. Methods: Test subjects participated in two walking trials, whereby the orthosis was controlled to deliver five predefined torque profiles of different duration (as % of a gait cycle). The adaptations to assistive torques of different duration were analysed in terms of gait parameters, metabolic effort, and muscle activity. Results: Orthotic assistance’s kinematic effects remain local to the assisted leg and joint, unlike the muscles spanning the knee joint, which engage in a balancing-out action to retain stability. Duration of assistive torque significantly affects only the timing of the knee joint’s peak flexion angle in the stance phase, while the observed joint kinematics and muscle activity demonstrate different recovery times upon changing robotic support (washout effects). Conclusion: Human body adaptations to external robotic knee joint assistance during walking take place on multiple levels and to a different extent in a joint effort to keep the gait stable. Significance: This paper provides important insights into the human body’s multiple adaptation mechanisms in the presence of external robotic assistance. [ABSTRACT FROM AUTHOR]

The increasing presence of photovoltaic (PV) generation in the energy mix demands improved forecasting tools which can be updated in an almost continuous basis. Satellite-based information lends itself naturally to this purpose and here it is used to nowcast hourly PV energy production for horizons up to six hours over Peninsular Spain and two islands, Majorca in the Mediterranean Sea and Tenerife in the Atlantic Ocean. This paper compares a single model-based on same-day numerical weather prediction (NWP) with hourly refreshed models which either only use satellite-based measurements or which combine both NWP same-day forecasts and satellite data. As shown in the experiments, the satellite–NWP combination gives very good nowcasting results, clearly superior to those achievable separately by either approach. [ABSTRACT FROM AUTHOR]

A stochastic gradient (SG)-based particle filter (SG-PF) algorithm is developed for an ARX model with nonlinear communication output in this paper. This ARX model consists of two submodels, one is a linear ARX model and the other is a nonlinear output model. The process outputs (outputs of the linear submodel) transmitted over a communication channel are unmeasurable, while the communication outputs (outputs of the nonlinear submodel) are available, and both of the two-type outputs are contaminated by white noises. Based on the rich input data and the available communication output data, a SG-PF algorithm is proposed to estimate the unknown process outputs and parameters of the ARX model. Furthermore, a direct weight optimization method and the Epanechnikov kernel method are extended to modify the particle filter when the measurement noise is a Gaussian noise with unknown variance and the measurement noise distribution is unknown. The simulation results demonstrate that the SG-PF algorithm is effective. [ABSTRACT FROM AUTHOR]

The ability to monitor the quality of the metal forming process as well as the machine's condition is of significant importance in modern industrial processes. In the case where a physical device (i.e., sensor) cannot be deployed due to the characteristics of the system, models that rely on the estimation of both the applied force and the dynamic behavior of the machine (i.e., system) are adopted. The development of such models and the corresponding algorithms used to estimate the above-mentioned quantities has attracted the interest of the community. The main contribution of this paper is the estimation of a servo press force by employing a novel dual particle filter based algorithm, achieving a maximum relative error in the force estimation of 3.6%. Moreover, to address real-time performance requirements, this paper proposes a field programmable gate array based accelerator that improves the sampling rate by a factor of 200 compared to a processor-based solution, thus enabling the deployment of the system in many realistic scenarios. [ABSTRACT FROM AUTHOR]

The problem of recovering a pair of signals from their blind phaseless short-time Fourier transform measurements arises in several important phase retrieval applications, including ptychography and ultra-short pulse characterization. In this paper, we prove that in order to determine a pair of generic signals uniquely, up to trivial ambiguities, the number of phaseless measurements one needs to collect is, at most, five times the number of parameters required to describe the signals. This result improves significantly upon previous papers, which required the number of measurements to be quadratic in the number of parameters rather than linear. In addition, we consider the simpler problem of recovering a pair of generic signals from their blind short-time Fourier transform, when the phases are known. In this setting, which can be understood as a special case of the blind deconvolution problem, we show that the number of measurements required to determine the two signals, up to trivial ambiguities, equals exactly the number of parameters to be recovered. As a side result, we study the classical phase retrieval problem—that is, recovering a signal from its Fourier magnitudes—when some entries of the signal are known a priori. We derive a bound on the number of required measurements as a function of the size of the set of known entries. Specifically, we show that if most of the signal’s entries are known, then only a few Fourier magnitudes are necessary to determine a signal uniquely. [ABSTRACT FROM AUTHOR]

Rapid population growth, urbanization and motorization have brought about secondary effects that have gradually damaged the atmosphere, whose importance is vital for both the survival of all living beings and the climate balance. In this sense, air pollution is a problem that affects current society and is much more critical in developing countries. In this context, in the present paper non-parametric statistical inference techniques are used to carry out the analysis of measurements of health concerning fine particulate matter concentration, PM2.5, in an urban park of Quito, Ecuador. In short, the data collected during the measurements were stored in random variables and the Kruskal-Wallis test was used to test if these random variables come from populations with identical distributions. Also, the Wilcoxon signed rank test was used to test if the numerical values collected in the samples of the random variables of interest represent a level of contamination that could be dangerous for human beings. The experimental results show that urban parks and, specifically, trees are a natural filter between the pollution generated in the road and the center of the park. Therefore, the role of trees in the face of vehicular pollution will depend on two variables: the amount and compactness of the vegetation, and the emission levels recorded in the border roads. [ABSTRACT FROM AUTHOR]

In this paper, a new analytical model is proposed to describe the behavior of uncertainty for a generic vision-based measurement system applied to mechanical vibration measurement. In particular, this paper proposes a novel way to evaluate the effects of motion blur. The theoretical framework presented here takes into account the camera acquisition parameters, the dynamics of the measurand (in terms of instantaneous speed), and the image scaling factor to develop a physical model of uncertainty when measuring a mainly monomodal vibration. Uncertainty is evaluated starting from the normalized discrepancy between a measured position and the actual one. The analytical model proposed here has been validated extensively with the help of a test stand that can generate biaxial monomodal vibrations. The motion of a target mounted on the test stand has been simultaneously monitored by a stereo vision rig and a set of triangulation lasers. Model validation has been carried out using two measurement techniques: stereo vision blob analysis and digital image correlation. The experimental results show that the proposed model is able to represent the behavior of uncertainty for both the techniques. After the model has been validated, it is shown how it is possible to exploit it to estimate the uncertainty of a vision rig starting from the nominal characteristics of both the vision system and the target. This can be a tool to facilitate the design of vision-based measurement systems. [ABSTRACT FROM AUTHOR]

This paper presents a comprehensive study of the impact of visual-haptic spatial discrepancies on human performance in a targeting task conducted in a visual-haptic virtual and augmented environment. Moreover, it explores whether the impact of this effect varies with two additional variables: 1) haptic wall stiffness and 2) visual cursor diameter. Finally, we discuss the relative dominance of visual and haptic cues during a targeting task. The results indicate that while the spatial discrepancies studied exerted a small effect on the time required to perform targeting, they impacted the absolute errors considerably. Additionally, we report that haptic wall stiffness has a significant effect on absolute errors while the visual cursor diameter has a significant effect on movement time. Finally, we conclude that while both visual and haptic cues are important during targeting tasks, haptic cues played a more dominant role than visual cues. The results of this paper can be used to predict how human targeting performance will vary between systems, such as those using haptically enabled virtual reality or augmented reality technologies that feature visual-haptic spatial discrepancies. [ABSTRACT FROM PUBLISHER]

We analyze the movement of particles in an electric paper that consists of upper and lower electrodes. Particles inserted in a fluid move under the influence of an electric field when voltage is applied to the electrodes. The movement of particles is determined by the intensity of the electric field, the viscosity of the fluid, and the q/m of the particles. Each factor has an impact on the independent particles. Considering these factors, we analyze the characteristics of the particles’ movements. We analyze the behavior of the electric paper with experiments based on Stokes’ Law. [ABSTRACT FROM PUBLISHER]

This paper describes an equipment for continuous measurement and identification of gamma radioactivity in aerosols developed by the Nuclear Engineering Research Group (NERG) at the Technical University of Catalonia (UPC) and Raditel Serveis i Subministraments Tecnològics, Ltd. A spectrometric analysis code has been specially designed for it. Spectrum analysis identifies and determines activity concentration of aerosol emitters captured by a fiberglass paper filter. This new equipment is currently operating in three radioactivity monitoring stations of the Environmental Radiological Surveillance Network of the Generalitat of Catalunya (local Catalan government): two near Ascó and Vandellòs Nuclear Power Plants in the province of Tarragona and one in the city of Barcelona. Two more monitors are expected to be deployed at Roses, Girona, Spain, and Puigcerdà, Barcelona, Spain. Measurements and evolution analysis results of emitters identified at these stations were also provided. [ABSTRACT FROM PUBLISHER]

This paper comprehensively presents key issues in design of an original optoelectronic measurement device built to assess amount of suspended particulate matter. The paper is introduced with a short explanation of concerns with a suspended particulate matter, what role it has in the air quality and how it affects health of human population. Then, problems of construction of the measurement device supported by a theoretical explanation on the basis of Mie theory are discussed. Subsequently, it is followed by an analysis of the device operation both in laboratory and in real conditions. Results obtained with the presented device are compared with the professional measurement equipment and an expensive, outdoor measurement station. Paper is concluded with observations of differences in spatio-temporal PM change at very close but significantly different city locations. [ABSTRACT FROM AUTHOR]

It is known that particle size obtained from Brownian motion of a particle is called the diffusion coefficient equivalent size (DCES) and is close to the geometric size independent of the physical properties of a particle. In this paper, it is described that real time measurement of the particle size and particle number concentration by observing the Brownian motion of the particles from which the influence of the flow field has been eliminated by the instrument combining the flow particle tracking (FPT) method and the L-shaped flow cell. Furthermore, we realized in evaluating the refractive index, which is the physical property information of the particles, from the DCES, the Rayleigh scattering equation and the light scattering intensity of particle that physical properties are known. In this paper, we also discuss that improvement of particle size accuracy and refractive index accuracy in the measurement of DCES. [ABSTRACT FROM AUTHOR]

Despite elegance being universally recognized as a goal for system design, there is little guidance in the related research and literature that is relevant to the design, development, or evaluation of elegant systems. This paper begins by reviewing the rather loose usage of elegance as a property of a system and shows that there are both abstract and practical views. Further, from analysis of the practical views of elegance in systems, it is clear that most current definitions of elegance are focused on the sufficiency of the system as a solution to the stated problem, rather than on elegance, perse. This paper disambiguates the usage of sufficiency and elegance, offers a formal definition of the two terms, and then provides several simple examples by way of illustration. Elegance and sufficiency must be considered as separate properties of a system, if only because the essential act of validation is an examination of the sufficiency of a solution, not its elegance. Any system attribute desired by the customer must be included as part of the solution's sufficiency and designed into the solution, not be a serendipitous unintended outcome of that design. Sufficiency is shown to be binary—a solution is either sufficient or it is not—and there may be more than one sufficient solution. Elegance is then defined to be the least complex sufficient solution. Furthermore, an elegant solution must be sufficient, but a sufficient system does not have to be (and is not always desirable to be) elegant. [ABSTRACT FROM AUTHOR]

We consider the probabilistic group testing problem where $d$ random defective items in a large population of $N$ items are identified with high probability by applying binary tests. It is known that the $\Theta (d \log N)$ tests are necessary and sufficient to recover the defective set with vanishing probability of error when $d = O(N^{\alpha })$ for some $\alpha \in (0, 1)$. However, to the best of our knowledge, there is no explicit (deterministic) construction achieving $\Theta (d \log N)$ tests in general. In this paper, we show that a famous construction introduced by Kautz and Singleton for the combinatorial group testing problem (which is known to be suboptimal for combinatorial group testing for moderate values of $d$) achieves the order optimal $\Theta (d \log N)$ tests in the probabilistic group testing problem when $d = \Omega (\log ^{2}\,\,N)$. This provides a strongly explicit construction achieving the order optimal result in the probabilistic group testing setting for a wide range of values of $d$. To prove the order-optimality of Kautz and Singleton’s construction in the probabilistic setting, we provide a novel analysis of the probability of a non-defective item being covered by a random defective set directly, rather than arguing from combinatorial properties of the underlying code, which has been the main approach in the literature. Furthermore, we use a recursive technique to convert this construction into one that can also be efficiently decoded with only a log-log factor increase in the number of tests. [ABSTRACT FROM AUTHOR]

In this paper, we propose a method for vehicle tracking on roadways using measurements of magnetometers and accelerometers. The measurements are used to build a low-cost, low-complexity vehicle tracking sensor platform for highway traffic monitoring. First, the problem is formulated by introducing the process model for the motion of the vehicle on the road and two measurement models: one for each of the sensors. Second, it is shown how the measurements of the sensors can be fused using particle filtering. The standard sampling importance resampling (SIR) particle filter is extended for processing of multirate sensor measurements and models that employ unknown static parameters. The latter are treated by Rao–Blackwellization. The performance of the method is demonstrated by computer simulations. It is found that it is feasible to fuse the two sensors for vehicle tracking and that the proposed multirate particle filter performs better than particle filters that process only measurements of one of the sensors. The main contribution of this paper is the novel approach of fusing the measurements of road-mounted magnetometers and accelerometers for vehicle tracking and traffic monitoring. [ABSTRACT FROM AUTHOR]

This paper presents a method that has been developed to determine the quantity of accumulated magnetic particles in mice tissues using magnetization measurements. Dispersions of platelet Fe3O4 particles with the size of 30–50 nm and a saturation magnetization of $\sim 80$ Am2/kg were intravenously administered to mice. Primary tissues were dried to measure the magnetization. The amounts of Fe3O4 particles accumulated in the tissues were obtained by dividing the magnetization of tissues by the magnetization of Fe3O4 particles under a magnetic field of 39.8 kA/m. A remarkable accumulation of particles was observed in the liver and the spleen, being supported by the observation of tissues using Prussian blue staining. Total Fe3O4 particles accumulated in primary tissues were $\sim 38$ –40 and 40–44 wt% against the particles in administered dispersions with 3 and 0.4 wt% contents, respectively. The method developed in this paper is considered to be effective for verifying magnetic hyperthermia and thermoablation therapies, in which the quantity of accumulated particles directly reflects the heating power required for those therapies. [ABSTRACT FROM AUTHOR]

This paper presents the results from a one-year study of 12 patients with moderate dementia in an adult day program who played a novel whack-a-mole game-based measurement instrument for cognitive behavior and performance. The ongoing measurement of cognition and changes associated with dementia is a challenge for healthcare providers. Measurement methods based on a tablet-based instrument are proposed. Partnership with the adult day program greatly eased recruitment: all but 1 eligible participant joined our study, compared to one in five, or lower, for previous studies with similar populations. There are three unique aspects to the design of our game: first, it has two distinct targets requiring different actions, which increases the cognitive processing for the users; second, each level is systematically more difficult; third, it records and analyzes player performance. The results show that the patients’ game performance improves over the first few weeks; this indicates that they are learning the game and retaining ability gains from week-to-week, suggesting some procedural learning is still intact. Over the year, 4 participants showed cognitive decline, 4 were stable and 3 improved based on their Minimental State Exam (MMSE) score. Two measures are proposed based on level progression within the sessions and mole hit performance. The level progression measure identifies declining participants with one false negative (FN) and one false positive error. The mole hit performance measure identifies declining participants with one FN error. These results demonstrate the potential for the proposed instrument to provide an ongoing measurement as an alternative for the repeated application of the MMSE. [ABSTRACT FROM AUTHOR]

Accommodation of a situation when a prior map is not available in an indoor localization system is valuable to cost-effective operations by removing a need for map drawing and map updating. This paper suggests a trajectory learning method using crowdsourced measurements in order to support the absence of map. A localization framework based on a particle filter is formalized by machine-learning-based feature extraction and Gaussian process (GP) regression. The feature extraction algorithm reduces dimensionality of sparse measurement vector, and it is applied to detect floor level and designated landmarks. Also, the combination of the feature extraction and the GP regression is used for modeling nonlinear relationship between location and measurement. By this combination, locations of Wi-Fi access points are not required to be known. From the field experimental results, we confirm that the detections of floor level and landmarks are accurate, the learned trajectories are close to the true map, and positioning accuracy is improved thanks to the learning-aided localization. [ABSTRACT FROM PUBLISHER]

Measurement of total ionizing dose in a radiation field is efficiently carried out by ionisation chambers. The paper details the design of a mixed-signal ASIC for the front-end electronics of ionisation chambers. A single chip solution for ultra-low current measurement is designed by combining the current processing analog section realized using low leakage thick gate transistors and the data handling digital section implemented using fast thin gate transistors. The design succeeds in limiting the cross coupling between the two circuit domains using deep n-wells and guard rings. The ASIC fabricated in 130 nm technology attains a wide dynamic range of −7 fA to $- 20\,\,\mu \text{A}$ with maximum error in measurement less than ±4 %. The ASIC occupies an area of 3.52 mm2 and has a total power consumption of 17.4 mW. The femtoampere range input leakage current of the ASIC contributed primarily by the ESD diodes was found to be varying exponentially with temperature. Dose rate measurements from $5 ~\mu $ Sv/h to 7.4 Sv/h is demonstrated by interfacing the ASIC to an ionisation chamber. [ABSTRACT FROM AUTHOR]

The position is one of the foremost imperative properties of an object. The Inertial Measurement Unit (IMU) development has enabled the system to continuously decrease in size, reduce power consumption, and become more and more universal. Although IMU meets the real-time needs of the localization system, it faces accumulative error and drifting problems. This paper presents an error constraint enhanced particle filter algorithm using quantum particle swarm optimization (EC-QPF), which achieves high-precision position estimation of target tracking with IMU. First, we proposed a quantum particle swarm optimization-based resampling method taking the place of the traditional weight-based resampling method in the particle filter, which avoids the particle impoverishment problem and keeps the particles’ diversity. The theoretical foundation of error constraint was raised applied to enhance the performance of the proposed particle filter. The error constraint is established utilizing the known estimated center and confidence scale to achieve particle screening based on the geometrical position of particles. Numerical experimental results show that the proposed EC-QPF has a 67% improvement instead of other modified particle filters and more efficiently eliminates the cumulative error. Furthermore, higher accuracy and stability are obtained under the exact condition, demonstrating better performance than traditional particle filter methods. [ABSTRACT FROM AUTHOR]

City-wide package delivery becomes popular due to the dramatic rise of online shopping. In order to speed up the package delivery process without increasing the delivery cost, a promising system has been proposed, which leverages the crowdsourced taxis. Many efforts have been done on this novel system in recent literature. However, a fundamental problem still remains open, i.e., measuring the maximum capacity of taxi-based logistics at the urban scale. In this paper, we first propose an accurate and efficient measurement mechanism to tackle this problem in the Non-stop package delivery method. The basic idea is to construct a spatial-temporal graph according to the passenger demands and calculate the maximum urban capacity by combining the results of several carefully designed max-flow problems. Then, we expand our measurement mechanism to be used in other taxi-based package delivery methods after a few adaptations, including the One-hop method and the Stop-and-wait method. At last, we evaluate our measurement mechanism and compare the maximum urban capacity of various package delivery methods with a real-world dataset from an online taxi-taking platform. [ABSTRACT FROM AUTHOR]

In this paper, we extend the notion of Cauchy–Schwarz divergence to point processes and establish that the Cauchy–Schwarz divergence between the probability densities of two Poisson point processes is half the squared L^2 -distance between their intensity functions. Extension of this result to mixtures of Poisson point processes and, in the case where the intensity functions are Gaussian mixtures, closed form expressions for the Cauchy–Schwarz divergence are presented. Our result also implies that the Bhattacharyya distance between the probability distributions of two Poisson point processes is equal to the square of the Hellinger distance between their intensity measures. We illustrate the result via a sensor management application where the system states are modeled as point processes. [ABSTRACT FROM PUBLISHER]