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With the development of smart meters and other intelligent electronic devices, more and more data‐driven fault location methods based on wide area measurement are emerging. However, these diagnostic methods for dealing with the whole tested system often appear complex. This paper presents an innovative subsystems‐based fault location strategy in distribution grid by the sparsity promoted Bayesian learning algorithm. To avoid taking measurement for the whole distribution system, the fault‐included subsystem is selected according to the distribution characteristics of negative sequence voltage. Then the data for fault location is measured by allocating meters in subsystem, which can reduce the number of required meters. For accurately estimating the fault location, a sparse prior is proposed for the Bayesian learning, which could improve the accuracy of the fault location algorithm by about 4%. The performance is tested on a 12.66‐kV, 69‐bus distribution system in response to various fault scenarios. The results show that the accuracy of the proposed method for the fault section location can reach 90%. It also verifies the robustness and accuracy for fault line location, faced different fault types, fault resistance, noise, etc. [ABSTRACT FROM AUTHOR]

In two previous papers, we calculated the dielectrophoresis (DEP) force and corresponding trajectories of high- and low-conductance 200-µm 2D spheres in a square 1 × 1-mm chamber with plane-versus-pointed, plane-versus-plane and pointed-versus-pointed electrode configurations by applying the law of maximum entropy production (LMEP) to the system. Here, we complete these considerations for configurations with four-pointed electrodes centered on the chamber edges. The four electrodes were operated in either object-shift mode (two adjacent electrodes opposite the other two adjacent electrodes), DEP mode (one electrode versus the other three electrodes), or field-cage mode (two electrodes on opposite edges versus the two electrodes on the other two opposite edges). As in previous work, we have assumed DC properties for the object and the external media for simplicity. Nevertheless, every possible polarization ratio of the two media can be modeled this way. The trajectories of the spherical centers and the corresponding DEP forces were calculated from the gradients of the system's total energy dissipation, described by numerically-derived conductance fields. In each of the three drive modes, very high attractive and repulsive forces were found in front of pointed electrodes for the high and low-conductance spheres, respectively. The conductance fields predict bifurcation points, watersheds, and trajectories with multiple endpoints. The high and low-conductance spheres usually follow similar trajectories, albeit with reversed orientations. In DEP drive mode, the four-point electrode chamber provides a similar area for DEP measurements as the classical plane-versus-pointed electrode chamber. [ABSTRACT FROM AUTHOR]

State estimation has a special role in the real-time control and monitoring of smart distribution networks. State estimation process is typically based on network topology and measurements sent from meters. Employing an accurate state estimation algorithm as well as transferring high volumes of measurements are serious challenges in large scale grids. In this paper, compressive sensing is used to reduce the measurement data volume, before transmission, to alleviate problems such as lack of storage space, interference and delay. In this paper, a modified extended Kalman filter algorithm is proposed which estimates states from compressed data directly without applying the reconstruction procedure. The main differences between the proposed method and EKF are the network dynamic modeling approach and the states correction mechanism. The IEEE 33-node distribution network with two DGs is employed to illustrate the effective performance of the proposed method. Results show that the states of the test feeder are accurately estimated even with only 50% compressed measurements. [ABSTRACT FROM AUTHOR]

This paper presents a cost-effective and efficient closed-loop calibration method to enhance the absolute positioning accuracy of industrial robots. The method utilizes an economical and highly accurate set of simple measurement devices, including a device mounted on the robot's end effector and a spherical constraint device positioned within the robot's workspace. A novel local area measurement method is employed for the spherical constraint device, effectively converting position errors into the errors in the sphere center position of the constraint device. Furthermore, the error model considers both kinematic parameter deviations of the robot itself as well as those of the measurement device, along with non-kinematic errors caused by link self-weight. The closed-loop calibration model relies on position constraints, enabling identification and compensation of all error parameters using Levenberg Marquardt method after substituting measured data. The effectiveness of this proposed method is demonstrated through simulation and experimentation. In simulations, average position error reduces from 8.249 mm to 0.8384 mm, while absolute mean difference in sphere center positions obtained using our measurement equipment decreases from 1.206 mm to 0.1027 mm. Significant reductions in both position error and difference in sphere center position are indicated after calibration. This proves that the absolute mean value of the sphere center position difference can be used as the basis for judging the size of the robot's end position error. Experimental results show that absolute mean difference in sphere center position decreases from 0.4319 mm to 0.02869 mm, leading to substantial improvement in overall positioning accuracy. • Calibration model incorporates both kinematic and non-kinematic deviation. • Local area measurement data effectively reflects the robot's end position error. • Closed-loop calibration method exhibits robustness in the presence of noise. [ABSTRACT FROM AUTHOR]

Non-destructive and destructive leaf area estimation are critical in plant physiological and ecological experiments. In modern agriculture, ubiquitous digital cameras and scanners are primarily replacing traditional leaf area measurements. Thus, measuring the leaflet's dimension is integral in analysing plant photosynthesis and growth. Leaf dimension assessment with image processing is widely used nowadays. In this investigation employed an image segmentation algorithm to classify the ice plant (Mesembryanthemum crystallinum L.) canopy image with a threshold segmentation technique by grey colour model and calculating the degree of green colour in the HSV (hue, saturation, value) model. Notably, the segmentation technique is used to separate suitable surfaces from a defective noisy background. In this work, the canopy area was measured by pixel number statistics relevant to the known reference area. Furthermore, this paper proposed total leaf area estimation in a destructive method by a computer coordinating area curvimeter and lastly evaluated the overlapping percentage using the total leaf area and canopy area measurements. To assess the overlapping percentage using the proposed algorithm, the curvimeter method experiment was performed on 24 images of ice plants. The obtained results reveal that the overlapping percentage is less than 10%, as evidenced by a difference in the curvimeter and the proposed algorithm's results with the canopy leaf area approach. Furthermore, the results show a strong correlation between the canopy and total leaf area (R2: 0.99) calculated by our proposed method. This overlapping leaf area finding offers a significant contribution to crop evolution by using computational techniques to make monitoring easier. [ABSTRACT FROM AUTHOR]

The low-altitude photogrammetry technology of unmanned aerial vehicles (UAVs) is widely used in many fields, but the absence of analysis and research affects the accuracy of its data products. At the same time, low-altitude photogrammetry faces the problem of low elevation positioning accuracy. The network space triangulation adjustment in the beam technique region is considered to eliminate perspective distortion in non-overlapping areas. This paper explains the key technologies of low-altitude photography and remote sensing mapping of UAVs, rectifies the distortion difference of remote sensing images, and then carries out grid division on the image according to the improved APAP (as-projective-as-possible warp) matching method. Next, it solves each grid homography matrix, linearizes the homography matrix, and carries out image matching according to the linearized homography matrix, which can effectively weaken the ghosting phenomenon during image matching. The network space triangulation adjustment in the beam technique region is considered to eliminate perspective distortion in non-overlapping areas. The two measurement areas' accuracy level is analyzed using digital line drawing and digital orthophoto images (DOIs). Finally, the experimental results indicate that the image matching algorithm proposed in this paper has strong reliability and can substantially increase photogrammetric elevation positioning. [ABSTRACT FROM AUTHOR]

Automated driving is now possible in diverse road and traffic conditions. However, there are still situations that automated vehicles cannot handle safely and efficiently. In this case, a Transition of Control (ToC) is necessary so that the driver takes control of the driving. Executing a ToC requires the driver to get full situation awareness of the driving environment. If the driver fails to get back the control in a limited time, a Minimum Risk Maneuver (MRM) is executed to bring the vehicle into a safe state (e.g., decelerating to full stop). The execution of ToCs requires some time and can cause traffic disruption and safety risks that increase if several vehicles execute ToCs/MRMs at similar times and in the same area. This study proposes to use novel C-ITS traffic management measures where the infrastructure exploits V2X communications to assist Connected and Automated Vehicles (CAVs) in the execution of ToCs. The infrastructure can suggest a spatial distribution of ToCs, and inform vehicles of the locations where they could execute a safe stop in case of MRM. This paper reports the first field operational tests that validate the feasibility and quantify the benefits of the proposed infrastructure-assisted ToC and MRM management. The paper also presents the CAV and roadside infrastructure prototypes implemented and used in the trials. The conducted field trials demonstrate that infrastructure-assisted traffic management solutions can reduce safety risks and traffic disruptions. [ABSTRACT FROM AUTHOR]

Free-form surface matching that aligns measured points with a design model is a common problem in manufacturing automation. In this paper, an iterative variance-minimization matching (VMM) method is proposed to address measured points that have measuring defects, such as uneven/open point distributions and measuring noise. The basic idea is that the objective function is defined as the variance of the closest distance from each measured point to the design model, and the measuring defects are considered by incorporating an average distance item into the objective function. Using the defined average distance item, a strategy for analyzing the effect of measuring defects on VMM and existing methods is presented. It is shown that the VMM method does not easily become trapped in a local optimum when measuring defects exist. To consider convergence speed and convergence stability, a new distance based on the first-order point-to-point distance and point-to-tangent distance is developed and used in the objective function. To demonstrate the availability of the proposed method, quadratic convergence and positive definiteness are theoretically analyzed. The proposed method is efficient and insensitive to measuring defects and is useful for shape matching tasks involving free-form surface features. Note to Practitioners—This paper is motivated by the problem of matching measured points with a design model to automate manufacturing processes such as geometric inspection, workpiece localization, and allowance distribution. Measured points are obtained by applying a scanning device where measuring defects usually appear. Existing matching methods suffer from the drawback that the measured points may incline toward dense data and become trapped in a local optimum, due to measuring defects. To address this practical issue, this paper proposes a new method called variance-minimization matching (VMM), in which the objective function is optimized to weaken the effect of measuring defects. By examining the differences between VMM and existing methods, it is found that VMM can achieve quadratic convergence speed. Most importantly, the method is insensitive to uneven/open point distributions. In summary: 1) this method allows us to improve the matching accuracy in the presence of measuring defects; 2) there is no need to obtain a high-quality scan of the entire workpiece, potentially reducing scanning difficulty and improving scanning efficiency; and 3) the requirement of uniform sampling for measured points is reduced. [ABSTRACT FROM AUTHOR]

The conventional terrain and ground object data acquisition methods of the channel mainly include RTK land terrain measurement and single-beam underwater terrain depth measurement. The surveying and mapping results can only be reflected on the drawings in the form of coordinate points and vector lines, and the intuitive image data of the survey area cannot be obtained. Restricted by field measurement techniques and conditions, it is difficult to fully meet the needs of timeliness, consistency and integrity of underwater measurement objects in large, special or dangerous areas with tight measurement time, heavy tasks, navigation or busy construction. In this paper, combined with a variety of high-tech surveying and mapping technologies such as UAV low-altitude photogrammetry, high-precision single-machine RTK positioning, 3D laser and image scanning, multi-beam scanning and single-beam measurement, and comprehensive application of unmanned measurement ships, the multi-platform multi-directional collaborative acquisition and multi-source data fusion processing suitable for the Yangtze River waterway were studied. The cooperative fusion processing technology of multi-source data was studied for the type, format and data volume of various data obtained. According to the unified data standard, processing and fusion were carried out for data fusion display and analysis. Based on the method, a set of multi-source data fusion processing and result visualization display platform which can meet the application requirements of various waterway surveying and mapping was developed. Combined with the practical application case of the Yangtze River waterway, the results show that the accuracy of the multi-beam sounding reaches 0.3 m, and the plane accuracy and elevation accuracy of the laser point cloud reach 0.4 cm, which meets the accuracy level required by the specification. [ABSTRACT FROM AUTHOR]

While many studies have been used onboard monitoring methods to detect train wheel defects, this paper aims to extract damage features from vibrational signals obtained by the wayside monitoring system. To provide an appropriate tool for the decomposition of experimental nonstationary vibration signals containing impacts, an analytical amplitude-based signal decomposition method is provided. A two-axle motor car with a flat wheel defect is studied at different operating conditions. Vibrational signals arising from wheel-rail interactions are gathered by the Wayside Data Collection Setup (WDCS) with five piezoelectric accelerometers. The tests are performed at the constant speeds of 10, 20, 30, and 40 km/h. The acquired signals are decomposed by the Multi-channel Singular Spectrum Analysis (MSSA) into the contributing components. Based on the results, increases in the amplitudes of the second reconstructed components (RCs) of the vibrational signals sensed by all the accelerometers can be observed at a specific time instance as a repeating pattern. Similar patterns are obtained at different motor car positions relative to the measurement area, as well as different motor car speeds. To verify the consistency of the second RCs, the crest factors are obtained for all the angular positions. The results show sudden increases in the crest factor at a fixed angular position that indicate the existence of a defect at that specific angular position of the wheel. [ABSTRACT FROM AUTHOR]

The paper focuses on the area of experimental measurements for monitoring the impact of decarbonization on the technical and environmental parameters of the ICE. The condition for the implementation of the measurements was the selection of an ICE that had driven more than 300,790 km. During the laboratory tests, several test methods were used to assess the technical and emission conditions of the tested ICE with the code designation ALH, which is used in VOLKSWAGEN BORA vehicles. The technical parameters of the tested ICE (corrected power PNorm and torque MMom), emission parameters (absorption coefficient k and NOx emission) and fuel consumption parameters (specific fuel consumption bsfc) were compared and evaluated in the results. The results show that the decarbonization process on the tested vehicle VOLKSVWAGEN BORA 1.9 TDi affected the emission parameters but did not affect the technical parameters and specific fuel consumption. [ABSTRACT FROM AUTHOR]

Discussions about teaching area measurement in primary school have been ongoing over some decades. However, investigations that thoroughly examine the current research on conceptual understanding in area measuring in elementary schools are still lacking. The objective of this paper is to review whether conceptual knowledge in area measurement may support students to obtain better results in primary schools. This study is to gain insight into how conceptual knowledge in area measurement has been portrayed for primary school students, and reveal possible omissions and gaps in the synthesized literature on the subject. To gather information, two databases were used: Scopus and Web of Science. Primary searches pulled up many studies on the subject of investigation. After analyzing abstracts and eliminating duplicates, our systematic review indicates that there seems a direct link between conceptual understanding and area measurement in primary school mathematics. Hence, teaching children the principle of area measurement rather than a procedure for solving problems seems to be the most effective way of improving problem-solving skills and conceptual understanding for primary students. [ABSTRACT FROM AUTHOR]

The ecological footprint basically aims to measure the impact of humans on the ecosystem. The measurements include the area required to produce the materials consumed in terms of the consumption footprint and the area required to absorb the carbon dioxide emissions. No distinction is made between domestic and foreign producers in the production by the countries. The countries with the most developed industry and the highest impact on the ecosystem in this sense appear as the countries with the highest footprint in the ecosystem. This study, based on the ecological footprint data of seven industrialized countries (G7) between 1984 and 2019, aims to reveal the effect of ecological footprints on trade openness. Panel data analysis and ARDL Boundary Test / PMG method was used to obtain the results. DOLS and FMOLS methods were also used to compare both economic and empirical results and for consistency. As a result of the analysis, as the impact of industrialized countries on the ecosystem increases, their trade openness also increases in the short and long term. This effect could be seen most clearly in the United States (USA), which has the most developed industry. This research paper points out these important issues. [ABSTRACT FROM AUTHOR]

Two large earthquakes (Mw = 7.7 and Mw = 7.6) that occurred in Turkey on February 6, 2023, affected a very extent region and caused a lot of loss of life and property. This paper presents preliminary results from geophysical measurements (Seismic Refraction Tomography-SRT, Multi-Channel Surface Wave Analysis-MASW and Microtremor-MT) on eight profiles in four provinces (Kahramanmaraş, Hatay, Malatya, Gaziantep) to understand the relationship between subsurface properties and the destruction that occurs immediately after earthquakes. By analyzing the geophysical data, the dynamic-elastic properties of ground and the soil classification according to Vs30 were determined. It is generally understood that the near-surface (< ~ 10–15 m) units in the measurement areas are very loose, and the deeper ones (≥ ~ 15–20 m) have a very porous/fractured structure. Soil classes were defined as ZD (Malatya-1, Hatay-1 and Kahramanmaraş-1) and ZC (Malatya-2, Hatay-2, Gaziantep-1,2 and Kahramanmaraş-2). In addition, by evaluating the information of strong ground motion station closest to the measurement profiles, it is observed that the PGA values versus epicenter distances are higher at stations in the zone parallel to the direction of both faults than those in the perpendicular zones. This leads directivity effect in the propagation of earthquake waves. The results indicate that one of the basic reasons for the damages is that the earthquake-ground-structure relationship has not been fully and accurately reflected in building designs. Therefore, future researches involving more geophysical data and PGA values will provide more information about the structural, physical and geotechnical properties of subsurface and definitive results. [ABSTRACT FROM AUTHOR]

In energy-constrained wireless sensor network, one way is to the maximize network lifetime to cover all the targets (full coverage) is to group sensor nodes proficiently in such a way that each subset (called cover set) is capable enough of monitoring all the targets in the given area of interest. In some of WSNs applications, such as average temperature or humidity measurement in an area, neglecting some of the targets do not affects the outcome of the network. By excluding a fraction of targets, network lifetime increases considerably because fewer sensors are required to monitor targets in each cover set. This variant of coverage is called α-Coverage (0 < α < 1) or partial coverage. This paper proposes an energy-proficient heuristic to maximize the network lifetime under α–Coverage scenario. Under α–Coverage constraint, while neglecting a fraction (1-α) of targets, a set of neglected targets may never change. Due to this, some of the targets may face negligible or zero coverage. In order to avoid neglecting the same set of targets over subsequent cover sets, we further propose a minimum coverage bound for each target in the given networks. Simulation results show that the proposed heuristic achieves better solution as compared to the existing approaches while calculating the network lifetime. [ABSTRACT FROM AUTHOR]

Image analysis is a promising method for in situ leaf area measurement. However, as leaves are three-dimensional, the use of two-dimensional images captured using a digital camera can result in underestimation. To overcome this problem, we tested a clear folder method. Before photographing leaves with a digital camera, we flattened the leaves by sandwiching them between a pair of transparent plastic clear file folder sheets, which are stationery implements for carrying documents. Although similar methods have been previously proposed, their applicability to species with different leaf shapes has never been investigated. We tested the efficacy of this method using 12 species from various taxa (monocots, magnoliids, and basal and core eudicots) and leaf morphology (entire vs. lobed, simple vs. compound leaves, small and large leaves). Individual leaf areas and the Montgomery parameters obtained using this method were then compared with those obtained using the standard method, which employs a flatbed digital scanner. We observed strong correlations (R2 > 0.98) between the camera and scanner data. The regression slopes were close to unity (0.96–1.01) and the intercepts were close to zero. These findings suggest that the clear folder method can be used as an inexpensive alternative method to estimate the area of leaves in situ with acceptable accuracy. An introductory manual for readers unfamiliar with image analysis using ImageJ is presented in the end of the paper. [ABSTRACT FROM AUTHOR]

With the fast development of cyber‐physical power systems, coordinated cyber‐physical attacks have become one of the main threats to the security of modern power grid. Considering that it is difficult for attackers to obtain full information of the entire power grid, the coordinated cyber‐physical attack problem for partitioned power grid is studied in this paper, and a tri‐level defender‐attacker‐dispatcher optimization model with consideration of wind power uncertainty in a specific coordinated cyber‐physical attack mode is proposed. The Karush‐Kuhn‐Tucker (KKT) condition and an improved implicit enumeration algorithm are applied to obtain the solution of the complicated optimization problem effectively. In addition, two risk assessment indices pertinent to the physical lines and load measurements are proposed according to the obtained total amount of optimized load shedding and coordinated attack‐defense strategy under valid attack‐defense scenarios. Taking a partitioned IEEE 39‐bus test system as example, the risks of physical transmission lines and load measurements in different areas under attacks are elaborately studied, and the impact of wind power uncertainty on attack‐defense strategies is discussed as well. Numerical simulation results illustrate the effectiveness of the proposed optimization model and risk assessment indices, and some significant conclusions are drawn. [ABSTRACT FROM AUTHOR]

More than 29 years of altimeter data have been recently reprocessed by the multi-satellite Data Unification and Altimeter Combination System (DUACS) and made available under the name of DT2021 through the Copernicus Marine Service (CMEMS) and the Copernicus Climate Change Service (C3S). New standards have been applied and various geophysical correction parameters have been updated compared to the previous release in order to improve the product quality. This paper describes the assessment of this new release through the comparison of both the all satellites and the two satellites product with external in situ tide gauge measurements in the coastal areas of the European seas for a time period from 1 January 1993 to 31 May 2020. The aim is to quantify the improvements on the previous DT2018 processing version for the retrieval of sea level in the coastal zone. The results confirmed that the CMEMS product in the new DT2021 processing version better solves the signal in the coastal band. The all satellites dataset showed a reduction of 3 % in errors when compared with tide gauges and of 5 % in the variance of the differences between the datasets compared to DT2018 reprocessing. Moreover, the all satellites dataset provided more accurate sea level measurements when making a comparison with tide gauges with respect to the climatic two satellites dataset due to the better performance of the former for the assessment of higher than climatic frequency signals. By contrast, the two satellite dataset is the most suitable product for the assessment of long-term sea level sea surface height (SSH) trends in the coastal zone due to its larger stability to the detriment of the all satellites dataset. [ABSTRACT FROM AUTHOR]

In anthropological sciences, the areas of the bones where muscles or ligaments attach ("entheses" or "muscle attachments") are routinely used for reconstructing habitual physical activity based on skeletal remains. However, several previous studies have argued against this practice, considering the low measuring repeatability of most traditional evaluation techniques and the former lack of supportive experimental evidence for an actual effect of physical activity on entheseal morphology. In 2016, I proposed a repeatable virtual approach for reconstructing habitual physical activity using entheseal morphology, which has been validated based on several experimental studies on laboratory animal species and human skeletons with uniquely detailed and longitudinal occupational documentation. This method, which was later named the "Validated Entheses‐based Reconstruction of Activity" (VERA) method, relies on a precise protocol for virtually delineating and quantifying entheseal areas on three‐dimensional bone models. The obtained area measurements are then subjected to size adjustment and multivariate statistical analyses, which have been experimentally shown to reveal group correlations among entheses that reflect habitual coordination among muscle groups. This paper presents the first critical review of all the various statistical approaches previously employed for analyzing entheses using VERA (so far), providing the first coherent step‐by‐step protocol for the complete univariate and multivariate analysis of entheseal three‐dimensional data. These include the introduction of a new, simple, and fast plotting technique for the initial screening of group entheseal patterns prior to multivariate analysis (i.e., the "VERA Bar‐Chart"), followed by the calculation of the "group entheseal patterning index" (hereafter GEPI%). [ABSTRACT FROM AUTHOR]

Delamination in the interlayers of multi-layer systems can cause a degradation in functionality, stability and life span of such systems. This is even more pertinent for systems at high temperatures. Laser flash analysis (LFA) has long been used for thermophysical properties measurements at high temperatures. In the European Metrology Programme for Innovation and Research (EMPIR) funded JRP 17IND11 Hi-TRACE project, the National Physical Laboratory (NPL) is developing multi-layer reference artefacts, including both fully bonded and partially de-bonded systems for validating thermal characterisation of multi-layer systems at temperatures from room temperature to above 1000 °C using LFA. The sensitivity studies carried out before creating the partially debonded artefacts have shown that the measurement area of the detector is one the important parameters that affect the accuracy of the thermal characterisation using LFA. However, this parameter is unknown to users of the early version of the Netzsch LFA 427, as it has negligible effect on radially homogenous samples which LFA is typically used for. This paper details the effect of measurement area on thermal characterisation of artefacts with partial debonding in the interface using LFA. For a bi-layer IG-210 grade graphite-hafnium foil system with a 6 mm diameter defect at the centre of the foil interface, variation in the measurement area can change the heat pulse transmission half-rise time by up to ~ 40%. Three methods to determine the system measurement area are discussed. The physical measurement diameter for the LFA 427 at NPL was estimated to be 7.7 mm ± 0.3 mm, independent of temperature. Within the uncertainty range of the measurement diameter, the thermal conductance of the defect region and the average heat transfer coefficient (HTC) can vary by ± 36% and ± 3.5% respectively. It is important to remember that this change is for a defect of 6 mm diameter which is a significant portion of the measurement area. For much smaller defects a much smaller change can be expected. [ABSTRACT FROM AUTHOR]

This paper is Part II of specific digital need of a small open pit exploitation. Using several intersections extracted from Copernicus of European Union's Copernicus Land Monitoring Service information, and also the provided GIS Protected Area shapes of the Romanian Ministry of Environment [1], an open pit/quarry project is analyzed concerning the Protected Area Measurements in order to minimize the environmental impact and the investments costs. An ArcGIS Pro License of the Technical University of Cluj Napoca, North University Center of Baia Mare owned in the Faculty of Engineering was used combined with the Commercial License of Rhinoceros 3D. [ABSTRACT FROM AUTHOR]

Background: The characteristics of light source have an important influence on the measurement performance of canopy reflectance spectrometer. The size of the effective irradiation area and the uniformity of the light intensity distribution in the irradiation area determine the ability of the spectrometer to express the group characteristics of the measured objects. Methods: In this paper, an evaluation method was proposed to theoretically analyze the influence of the light intensity distribution characteristics of the light source irradiation area on the measurement results. The light intensity distribution feature vector and the reflectance feature vector of the measured object were constructed to design reflectance difference coefficient, which could effectively evaluate the measurement performance of the canopy reflectance spectrometer. By using self-design light intensity distribution test system and GreenSeeker RT100, the evaluation method was applied to evaluate the measurement results. Results: The evaluation results showed that the vegetation indices based on the arithmetic average reflectance of the measured object could be obtained theoretically only when the light intensity distribution of the light source detected by the spectrometer was uniform, which could fully express the group characteristics of the object. When the light intensity distribution of the active light source was not uniform, the measure value was difficult to fully express the group characteristics of the object. And the measured object reflectance was merely the weighted average value based on the light intensity distribution characteristics. Conclusions: According to the research results of this paper, sunlight is the most ideal detection light source. If the passive light source spectrometer can improve the measurement method to adapt to the change of sunlight intensity, its measurement performance will be better than any active-light spectrometer. [ABSTRACT FROM AUTHOR]

Food systems are not sustainable, and efforts to address this are paralyzed by the complex networks of food system actors and factors that interact across sectoral and geographic scales. Actions at the community level can positively contribute toward globally sustainable food systems (SFS). Assessing such contributions has two central challenges: 1) a lack of methods that support alignment between communities and across scales, balanced against the need to involve the community in developing relevant indicators; and 2) the absence of adequate, fine grained data relevant to the community. Addressing these two challenges, this paper illustrates a proposed procedure that supports community engagement with, and assessment of, their contributions. Engaged by a community of Canadian dietitians, researchers used the Delphi Inquiry method, guided by the Framework for Strategic Sustainable Development, to address the first challenge, and causal loop diagrams informed by the Cultural Adaptation Template to address the second. Indicators were developed for dietitian-identified actions and outcomes for SFS. Modeling indicator interactions provide insight into how some actions are influenced by and reinforce the value placed on SFS within the professional cultural paradigm, as well as priority areas for action and measurement. Process-oriented assessment is useful in the context of partial and subjective understandings of a dynamic system, and supports continual adjustment in action. This article offers theoretical and practical insight for community engagement in addressing some of the systemic challenges in food systems. It accommodates community-based knowledge, applies process-indicators, and emphasizes the importance of cultural paradigms as a driving force of community-level actions, and overall system change. Under current conditions, facilitating SFS literacy among dietitians can amplify adaptations for broader SFS development. [ABSTRACT FROM AUTHOR]

A new hierarchical multi-area power system state estimation method is proposed in this paper. Instead of exchanging boundary measurements or state estimates, the proposed technique is based on exchanging the sensitivity functions of local state estimators. The main benefit of the proposed scheme is the improved convergence speed, which also reduces the amount of information exchange required. Extensive numerical results involving IEEE standard systems and a utility scale system are presented. [ABSTRACT FROM AUTHOR]

This paper proposes a transient stability constrained controlled islanding (TSC-CI) approach against cascading events in power systems. Using the wide area measurements, the proposed islanding algorithm is implemented regarding the actual dynamic conditions of the resulted islands. Since the main concern, right after the execution of controlled network splitting, is the transient stability of synchronous machines, a transient energy function is utilized for proper network partitioning. The proposed transient stability criterion is expressed as a function of the transfer impedance between each pair of generators in the resulted islands. Transfer impedance between each pair of coherent generators determines the direction of network splitting for transient stability improvement. A multi-objective function is then introduced to provide the transient stability with least possible power imbalance, as a resilience measure, over the created islands considering operational and structural constraints. Based on the wide-area measurements, a proper weighting procedure is utilized to prioritize the critical islands, avoiding the unnecessary power imbalance in favor of transient stability improvement. The proposed TSC-CI model is formulated as a mixed integer linear programming (MILP) multi-objective model and is solved using CPLEX in GAMS. The obtained results are compared with the conventional islanding scheme using the IEEE 118-bus system. [ABSTRACT FROM AUTHOR]

Cyber-attacks on smart-grid systems have become increasingly more complicated, and there is a need for taking detection and mitigation measures to combat their adverse effects on the smart-grid infrastructure. Wide area measurement system (WAMS) infrastructure comprising of phasor measurement units (PMUs) has recently shown remarkable progress in solving complex power system problems and avoiding blackouts. However, WAMS is vulnerable to cyber-attacks. This paper presents a novel cyber-attack resilient WAMS framework incorporating both attack detection and mitigation modules that ensure the resiliency of PMU data-based supervisory protection applications. It includes deep learning-based Long Short Term Memory (LSTM) model for real-time detection of anomalies in time-series PMU measurements and isolating the compromised PMUs followed by Generative Adversarial Imputation Nets (GAIN) for the reconstruction of the compromised PMU's data. The corrected PDC data-stream is then forwarded to the decision-making end application, making it resilient against attacks. A Random Forrest classifier is used in the end application to distinguish fault events from other disturbances and supervise the third zone of distance relay for backup protection of transmission lines. The efficacy of the proposed framework for different attack scenarios has been verified on the WSCC 9-Bus System modeled on a developed real-time digital simulator (RTDS)-based integrated cyber-physical WAMS testbed. Experimental analysis shows that the proposed model successfully detects and mitigates attacks' adverse effects on the end application. [ABSTRACT FROM AUTHOR]

In this paper, we use a recent Lipschitz-type condition, called L condition, to state different area formulas in the context of metric measure spaces. We first provide area formulas for mappings between general metric measure spaces and appropriate Euclidean space. That includes area formulas for the graph mapping of a function between a metric measure space and the Euclidean space R n , and for metric-valued mappings with domain R n . Finally, and under the assumption of n-rectifiable domains, we provide a general area formula for functions between metric measure spaces. [ABSTRACT FROM AUTHOR]

Over the last few years, light-emitting diodes have completely dominated the lighting field. In road lighting, high-power LEDs have replaced traditional light sources. That is why various technical aspects of LEDs have been researched extensively worldwide. However, little research has been conducted in the area of luminance measurement. This paper reviews the methods for measuring the luminance of high-power LEDs. Particular attention is paid to the influence of the measurement distance on the measurement results. Next, the results of the tests using a modern image luminance measuring device (ILMD) for luminance measurements are presented. It is concluded that it is necessary to redefine the photometric test distance. The conducted research demonstrates that an incorrectly selected test distance can lead to the huge errors of several hundred per cent or more. In addition, the possible impact of the incorrect measurements on the design of road lighting installations is presented. It is shown that a road lighting installation can use over 300% more electrical energy compared to the installation based on the correct luminance measurements of single LEDs. In the final stage of the research, the definition of the photometric test distance for LED measurements using ILMD is proposed. The results of the research can also be useful for the luminance measurements of other types of LEDs. [ABSTRACT FROM AUTHOR]

Purpose: The purpose of this study is to reflect upon the feasibility of agile methodologies, Scrum in particular, to supplement the procedural design and implementation of performance measurement systems (PMS). Design/methodology/approach: The study is an interventionist case study that applied agile methodologies in the PMS development. Researchers actively participated in the PMS development, e.g. researchers designed some of the performance measurement prototypes in order to facilitate the agile development. Findings: The study outlines an agile approach suitable for PMS development. The paper answers the topical needs for adaptability and agility in management accounting, by applying agile methodologies into PMS development. PMS development does not take place only as a project or process that systematically progresses from the measure selection to measure implementation. Instead, as the requirements for the PMS change during the development project, management may reject some measures and new measures emerge as the understanding about changing situations increase. Agile methodologies are a methodological way to respond to the inevitable change and to enhance management accounting adaptability. Research limitations/implications: This study contributes to the PMS literature by proposing that agile development methodologies can advance organizational features that increase management accounting adaptability. As a result, the study proposes a new approach for PMS development to supplement existing ones. Agile methodologies are especially suitable for extending the PMS in new, yet relatively immature areas of performance measurement. The new approach applies Scrum principles in PMS development. By drawing from the theories of performance measurement (system) development and enabling PMS, the paper furthers academic understanding about agile development of accounting information systems. Practical implications: Companies can use the proposed approach in PMS development, particularly after the initial system implementation in redesigning the system. The approach may increase the PMS impact in organizations and prevent PMS implementation failures. Originality/value: The paper identifies the potential of using agile methodologies to enhance PMS adaptability and provides preliminary evidence of the potential of such approach in supplementing processual PMS development frameworks. [ABSTRACT FROM AUTHOR]

The recent surge of machine learning (ML) has impacted many disciplines, including educational and psychological measurement (hereafter shortened as measurement). The measurement literature has seen rapid growth in applications of ML to solve measurement problems. However, as we emphasize in this article, it is imperative to critically examine the potential risks associated with involving ML in measurement. The MxML project aims to explore the relationship between measurement and ML, so as to identify and address the risks and better harness the power of ML to serve measurement missions. This paper describes the first study of the MxML project, in which we summarize the state of the field of applications, extensions, and discussions about ML in measurement contexts with a systematic review of the recent 10 years' literature. We provide a snapshot of the literature in (1) areas of measurement where ML is discussed, (2) types of articles (e.g., applications, conceptual, etc.), (3) ML methods discussed, and (4) potential risks associated with involving ML in measurement, which result from the differences between what measurement tasks need versus what ML techniques can provide. [ABSTRACT FROM AUTHOR]

The study of the area of circles is an important component of mathematics education for students of all ages; however, evidence suggests that many middle school students struggle to interpret and apply the area formula of a circle. In this article, I report the findings of a classroom design study conducted to investigate the collective establishment and justification for the area formula of a circle. An instructional sequence comprising paper-based decomposition and recomposition measurement tasks situated on a grid was implemented in a Year 8 classroom (n = 18) and the collective mathematical practices that emerged from an analysis of the argumentation of students during whole-class discussion were documented. The findings extend the existing literature by illustrating how decomposition/recomposition tasks can be leveraged in a classroom context by grounding students’ reasoning in measurement strategies and opportunities to examine alternative strategies and justifications through whole-class discussions. [ABSTRACT FROM AUTHOR]

In this paper, we performed an analysis of the areas of sunspot groups of various classes according to the Zurich group classification. To do this, observations of sunspots at the Locarno Observatory (Locarno, Switzerland) for 21–24 activity cycles were digitized. In the Zurich classification of sunspot groups, there are classes from A to J. The classes correspond to the process of development and decay of sunspot groups. We combined the Locarno data with the measurements of the areas of sunspot groups performed at the Kislovodsk mountain astronomical station of the GAO RAS. Average areas were obtained for groups of different classes. In counting the number of sunspot groups, the contribution of groups of classes A and B, consisting of pores, is 34% and only 5.1% in the total area. It is shown that groups of classes A + B form a separate distribution of areas from groups of other classes. The areas separately of class A and class B, in turn, are also divided into two independent distributions. This indicates different physical mechanisms for the formation of pores and regular spots. The H + J unipolar sunspots make up ~19% of the total sunspot area, and the H and J classes can be described by a single distribution. [ABSTRACT FROM AUTHOR]

In this paper, a novel point cloud segmentation and completion framework is proposed to achieve high-quality leaf area measurement of melon seedlings. In particular, the input of our algorithm is the point cloud data collected by an Azure Kinect camera from the top view of the seedlings, and our method can enhance measurement accuracy from two aspects based on the acquired data. On the one hand, we propose a neighborhood space-constrained method to effectively filter out the hover points and outlier noise of the point cloud, which can enhance the quality of the point cloud data significantly. On the other hand, by leveraging the purely linear mixer mechanism, a new network named MIX-Net is developed to achieve segmentation and completion of the point cloud simultaneously. Different from previous methods that separate these two tasks, the proposed network can better balance these two tasks in a more definite and effective way, leading to satisfactory performance on these two tasks. The experimental results prove that our methods can outperform other competitors and provide more accurate measurement results. Specifically, for the seedling segmentation task, our method can obtain a 3.1% and 1.7% performance gain compared with PointNet++ and DGCNN, respectively. Meanwhile, the R 2 of leaf area measurement improved from 0.87 to 0.93 and M S E decreased from 2.64 to 2.26 after leaf shading completion. [ABSTRACT FROM AUTHOR]

This paper proposes a hierarchical active power differential signal-based generalized backup protection algorithm using Wide Area Measurement System (WAMS) data for Flexible AC Transmission System (FACTS)-compensated transmission networks. The proposed algorithm can be used for backup protection of transmission systems with any shunt and series-type FACTS devices. The increased number of FACT compensators affects the reliable operation of primary and backup protection of the transmission lines. Both shunt and series compensated lines cause malfunctioning of existing backup protection schemes. The proposed algorithm utilizes the sequence components of bus voltages and active power differential signals of lines to identify the faulty line. The algorithm is validated on a modified 9-bus system under MATLAB/SIMULINK platform. It is observed that the algorithm is suitable for identifying a faulty line in transmission systems containing both uncompensated and compensated lines with series or shunt-type FACTS controllers. This algorithm has the advantage that it uses a generalized backup protection logic and can be used for the accurate identification of a faulty line irrespective of the type of compensation devices. [ABSTRACT FROM AUTHOR]

With the rapid increase of the penetration rate of renewable energy sources in power system, the decrease of system inertia will threaten the frequency stability, and the dispersion of frequency response cannot be ignored. This paper proposes a method to estimate area inertia of power system containing wind power considering dispersion of frequency response. Firstly, the impact of inertia distribution between areas on the frequency stability and the inter‐area oscillation are analysed. Secondly, the system is divided based on the spectral clustering algorithm and the frequency similarity index is defined according to the Pearson correlation coefficient to determine the measurement locations for area frequency. Thirdly, the measured tie‐line power and frequency deviation are used to estimate the area inertia based on the numerical integration method. Finally, the case study is conducted based on the modified IEEE 39‐bus system. The simulation results revealed that the proposed method is accurate and reliable in different scenarios. [ABSTRACT FROM AUTHOR]

A computerized bone age assessment requires segmentation of the X-ray carpal bones from other undesired tissue regions. This paper presents segmentation and area measurement of carpal bones in X-ray images. The locally weighted K-means variational level set was applied in segmenting 67 X-ray carpal bone datasets. Dice coefficient and Hausdorff distance measures show mean values above 0.7 and around 3 pixels, respectively. These satisfying segmentation outcomes enable the carpal bone areas to be measured on the segmented images. The carpal bone area measurement ranged from 4.24 mm to 48.96 mm with a mean value of 20.70 ± 10.51 mm and various values of the Pearson's correlation coefficient implies that the segmentation method is insensitive to different carpal bone areas and locations. These results suggest that the methods can be applied in the bone age assessment by quantifying changes in the carpal bone area over certain time intervals. [ABSTRACT FROM AUTHOR]

Premise: With modern advances in genetic sequencing technology, plant phenotyping has become a substantial bottleneck in crop improvement programs. Traditionally, researchers have manually measured phenotypic traits to help determine genotype–phenotype relationships, but manual measurements can be time consuming and expensive. Recently, automated phenotyping systems have increased the spatial and temporal density of measurements, but most of these systems are extremely expensive and require specialized expertise. In the present paper, we develop and validate a low‐cost, scalable, high‐throughput phenotyping (HTP) system for automating the measurement of foliar area and greenness. Methods: During a greenhouse experiment on the effects of abiotic stress on Brassica rapa, we collected images of hundreds of plants every hour for over a month with a system that cost approximately US$1000. Results: In comparison with manually acquired images, this HTP system was able to produce similar estimates of foliar area and greenness, developmental trends, and treatment effects. Foliar area was correlated between the two image sets, but greenness was not. Discussion: These findings highlight the potential of HTP systems built from low‐cost hardware and freely available software. Future work can use this system to investigate genotype–environment interactions and the genetic loci underlying morphological changes resulting from abiotic stress. [ABSTRACT FROM AUTHOR]

This paper proposes a model-free distribution system state estimation method based on tensor completion using canonical polyadic decomposition. In particular, we consider a setting where the network is divided into multiple areas. The measured physical quantities at buses located in the same area are processed by an area controller. A three-way tensor is constructed to collect these measured quantities. The measurements are analyzed locally to recover the full state information of the network. A distributed closed-form iterative algorithm based on the alternating direction method of multipliers is developed to obtain the low-rank factors of the whole network state tensor where information exchange happens only between neighboring areas. The convergence properties of the distributed algorithm and the sufficient conditions on the number of samples for each smaller network that guarantee the identifiability of the factors of the state tensor are presented. To demonstrate the efficacy of the proposed algorithm and to check the identifiability conditions, numerical simulations are carried out using the IEEE 123-bus system and a large-scale real utility feeder. [ABSTRACT FROM AUTHOR]

The electrical properties of many biological tissues are freely available from the INRC and the IT'IS databases. However, particularly in lower frequency ranges, few studies have investigated the optimal measurement protocol or the key confounders that need to be controlled, monitored, and reported. However, preliminary work suggests that the contact force of the measurement probe on the tissue sample can affect the measurements. The aim of this paper is to investigate the conductivity change due to the probe contact force in detail. Twenty ex vivo bovine heart samples are used, and conductivity measurements are taken in the Left Atrial Appendage, a common target for medical device developments. The conductivity measurements reported in this work (between 0.14 S/m and 0.24 S/m) align with the literature. The average conductivity is observed to change by −21% as the contact force increases from 2 N to 10 N. In contrast, in conditions where the fluid concentration in the measurement area is expected to be lower, very small changes are observed (less than 2.5%). These results suggest that the LAA conductivity is affected by the contact force due to the fluid concentration in the tissue. This work suggests that contact force should be controlled for in all future experiments. [ABSTRACT FROM AUTHOR]

Abstract—The paper addresses two issues. The first is the validity of the plane wave model when applied in the MT soundings (MT) collected in polar latitudes. The second is the validity of using two-component stations when survey in the conditions of a close ionospheric signal source in polar latitudes. To answer these questions, we consider the data from 5000 MT sites collected within a 120 × 80 km area in the north of Yakutia. The MT measurements in this area were conducted during half a year. During the three summer months, electromagnetic field was continuously recorded by the base station (remote reference) at the center of the area. This record is used to solve the first question. To answer the second question, we analyze the horizontal magnetic tensor yielded by processing the magnetic field records from the survey sites relative to the remote reference site. [ABSTRACT FROM AUTHOR]

Reduced external networks supplied with real-time data are employed in this paper to solve the state estimation problem in interconnected systems. We propose a method to obtain a composed single system state of different monitored areas with local estimations and external equivalent models, which neither require the use of a coordination agent nor requires extensive data interchange. Phasor measurement unit (PMU) measurements taken from system boundaries are used to provide updated equivalent networks as well as an inter-area synchronism. The approach allows testing erroneous external models directly in the state estimation framework. The detectability of bad data in interconnection measurements are also preserved. Tests with the IEEE 118-bus and IEEE 300-bus systems show robustness and accuracy of the model under different area decomposition schemes with low computational requirements compared to similar conventional approaches. [ABSTRACT FROM AUTHOR]

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This paper presents a computationally efficient and statistically robust linear state estimator for very large scale interconnected power grids that are made observable by synchronized phasor measurements. The developed estimator has some desirable properties such as robustness against gross errors in phasor measurements (bad data), computational performance that remains minimally affected by growing system size or bad data as long as the size of the largest control area remains bounded, and the fact that independent system operators associated with control areas do not have to share majority of their real-time data or measurements while the estimator solves for the entire system. The estimator is implemented and tested on a small (30-bus) and a large (2917-bus) utility test systems and results are provided. [ABSTRACT FROM AUTHOR]

Jang, W.S.; Park, H.S, and Park, S.G., 2018. Analysis of Positioning Accuracy of PPP, VRS, DGPS in Coast and Inland Water Area of South Korea. In: Shim, J.-S.; Chun, I., and Lim, H.S. (eds.), Proceedings from the International Coastal Symposium (ICS) 2018 (Busan, Republic of Korea). Journal of Coastal Research, Special Issue No. 85, pp. 1276–1280. Coconut Creek (Florida), ISSN 0749-0208. Various research activities are being conducted every year in the coastal and inland water areas of Korea. Among them, location accuracy is very important for coastline change survey, depth survey, and coastal route analysis. VRS and DGPS are commonly used in coastal and inland areas. VRS is a type of Network RTK that offers high location accuracy and ease of use. However, due to the limitations of the Network RTK method, VRS is not able to significantly degrade or use its location accuracy unless the survey area is located within the network. On the other hand, DGPS has a position accuracy of about 1m, which is lower than that of VRS. However, DGPS is widely used for location measurement in the coastal area due to its wide service range. PPP is the most recently developed satellite positioning method. PPP can be used anywhere in Korea, like DGPS, while providing accuracy similar to VRS's positioning accuracy. However, PPP is still an early stage positioning technology and has a long convergence time to show high positioning accuracy and high complexity of use. Therefore, it is not used for research activities in actual coastal and inland water. In this paper, we present our PPP positioning system and analyze the results of PPP using our PPP positioning system, VRS and DGPS positioning presented in coastal and inland areas of Korea. In this paper, we compare and analyze the accuracy of three positioning methods and present the results. [ABSTRACT FROM AUTHOR]

As a type of earth observation technology, interferometric synthetic aperture radar (InSAR) is increasingly widely used in the field of geological disaster detection. However, the application of InSAR in low-coherence areas, such as alpine canyon areas and vegetation coverage areas, is subject to considerable limitations. How to accurately identify landslides from InSAR measurement data in these areas remains the subject of several challenges and shortcomings. Based on statistical analysis and spatial cluster analysis, in this paper, we propose an automatic landslide identification and gradation method suitable for low-coherence areas. The proposed method combines the small baseline subset InSAR (SBAS-InSAR) method and the interferogram stacking (stacking-InSAR) method to obtain a deformation map in the study area, using statistical analysis and spatial cluster analysis to extract deformation regions and landslide polygons to propose a landslide screening model (LSM) based on multivariate features to screen landslides and reduce the interference of noise in landslide identification, in addition to proposing a landslide gradation model (LGM) based on signum function to grade the identified landslides and provide support to distinguish landslides with different deformation degrees. The method was applied to landslide identification in the upper section of the Jinsha River basin, and 47 potential landslides were identified, including 15 high-risk landslides and 13 landslides endangering villages. The experimental results show that the proposed method can identify landslides accurately and hierarchically in low-coherence areas, providing support for geological hazard investigation agencies and local departments. [ABSTRACT FROM AUTHOR]