Hot spotting in photovoltaic (PV) panels causes physical damage, power loss, reduced lifetime reliability, and increased manufacturing costs. The problem arises routinely in defect-free standard panels; any string of cells that receives uneven illumination can develop hot spots, and the temperature rise often exceeds 100°C in conventional silicon panels despite on-panel bypass diodes, the standard mitigation technique. Bypass diodes limit the power dissipated in a cell subjected to reverse bias, but they do not prevent hot spots from forming. An alternative control method has been suggested by Kernahan [1] that senses in real time the dynamic conductance |dI/dV| of a string of cells and adjusts its operating current so that a partially shaded cell is never forced into reverse bias. We start by exploring the behavior of individual illuminated PV cells when externally forced into reverse bias. We observe that cells can suffer significant heating and structural damage, with desoldering of cell-tabbing and discolorations on the front cell surface. Then we test PV panels and confirm Kernahan’s proposed panel-level solution that anticipates and prevents hot spots in real time. Simulations of cells and panels confirm our experimental observations and provide insights into both the operation of Kernahan’s method and panel performance.

Interior point methods (IPMs) are popular and powerful methods for solving large-scale nonlinear and nonconvex optimization problems, such as AC optimal power flow (ACOPF). There are various ways to model ACOPF, depending on the objective and the physical components that need to be optimized. This paper models shunt flexible AC transmission systems (FACTS). Shunt FACTS devices such as static VAR compensators (SVCs) are sources for reactive power compensations and addressing voltage stability issues. The co-optimization of SVCs with power dispatch can impact the computational performance of ACOPF. In this paper, we evaluate the performance of different ACOPF formulations with approximated active-set interior point (AASIP) algorithm and co-optimization of SVC set points alongside other decision variables. Our numerical results suggest that both AASIP and SVCs alone improves the computation performance of almost all formulations. The gain in performance, however, depends on the sparsity of the formulation. The most spares formulation, such as branch power flow rectangular voltages (BPFRV), shows the highest gain in performance. In the event of co-optimizing SVCs with power dispatch using AASIP, the performance gain is minimal. Finally, the results are verified using various test cases ranging from 500-bus systems to 9591-bus systems.

In most practical adaptive signal processing systems, e.g., active noise control, active vibration control, and acoustic echo cancellation, substantial nonlinearities that cannot be neglected exist. In this paper, we analyze the behaviors of an adaptive system in which the output of the adaptive filter has the clipping saturation-type nonlinearity by a statistical-mechanical method. We discuss the dynamical and steady-state behaviors of the adaptive system by asymptotic analysis, steady-state analysis, and numerical calculation. As a result, it has become clear that the saturation value has the critical point at which the system’s mean-square stability and instability switch. The obtained theory well explains the strange behaviors around the critical point observed in the computer simulation. Finally, the exact value of the critical point is also derived.

The 3D position estimation of pedestrians is a vital problem in the development of virtual reality, augmented reality, and the internet of things. The learning-based inertial odometry is a very potential auxiliary method of pedestrian positioning due to its low position drift and immunity to external environmental influences. However, in many cases, the drift error of the heading is still the main factor that causes the rapid divergence of the position estimated by the learning based inertial odometry. This paper proposed a graph optimization-based estimation method to fusing learned based inertial odometry and magnetometer measurements for obtaining lower drift position. The proposed algorithm does not need to calibrate the magnetometer bias, and effectively resist the influence of magnetic interference in the indoor environment, and can provide a very reliable absolute magnetic heading correction. Test results show that the proposed method can obtain better positioning performance than other methods using calibrated magnetometer observations.

In this research, we discuss the possibility of incorrect prediction of the double-bounce scattering (DBS) power in model-based decomposition (MBD) algorithms applied to polarimetric synthetic aperture radar (SAR) images of vegetated terrain. In most of the MBD schemes, the estimation of the DBS component is based on the assumption that the co-polarized phase difference (CPD) of the DBS is similar to those of backscattering from a pair of orthogonal planer conducting surfaces. However, for dielectric surfaces such as soil or vegetation trunks, this assumption is only valid within a certain range of radar incidence angle, which is dictated by the Brewster angles of the dielectric surfaces. If the incidence angle is out of this range, the DBS contribution is incorrectly estimated as the surface scattering. Moreover, because the Brewster angle is a function of surface permittivity, the angular range depends on moisture contents of the surfaces; therefore, correctness of the MBD results also depend on the surface moisture contents. To demonstrate this problem, we provide a simple numerical model of vegetated terrain, and we validate theoretical results by a series of controlled experiments carried out in an anechoic chamber with a simplified vegetation model.

Current hole matching pixel detector (HMPD) collimators for SPECT imaging exist in two configurations: one hole per pixel (1HMPD) or four holes per pixel (4HMPD). The aim of this study was to assess the performance of a dual-layer collimator made by stacking up these two collimator types (1H/4HMDP) for low and medium-energy gamma emitters. Analytical equations describing 1H/4HMDP collimator geometrical efficiency and full width at half maximum (FWHM) were derived. In addition, a fast dedicated gamma ray-tracing Monte Carlo (MC) code was developed to assess the collimator’s point spread function (PSF) and to simulate planar and SPECT acquisitions. A relative agreement between analytical equations and MC simulations better than 3% was observed for the efficiency and better than 1% for the FWHM. The length of the two layers was optimized to get the best spatial resolution while keeping the geometrical efficiency equal to that of the 45mm-length 1HMPD collimator. An optimized combination of the 1H/4HMPD configuration with respective hole lengths of 20mm and 12.95mm has been derived. For source-collimator distances above 5 cm and equal collimator geometrical efficiency, the spatial resolution of this optimal 1H/4HMDP collimator supersedes that of the 45mm-length 1HMPD collimator, and that of the 19.1mm-length 4HMPD collimator. This improvement was observed in simulations of bar phantoms planar images and of hot rods phantom SPECT. Remarkably, the spatial resolution was preserved along the depth of the Jaszczak phantom slices. The 1H/4HMDP collimator is a promising solution for CZT SPECT imaging of low- and medium-energy emitters.

Our aim is to understand technological and socio-economic barriers to blockchain solutions that are intrinsic in the blockchain technology stack itself (permissionless as well as permissioned). On the basis of that, we want to understand the future potentioal impact of blockchain technology. We provide an argumentation against the theoretical background of Williamson’s instutional analysis framework, and triangulate the insights with results from four design science research efforts. We (i) characterize cryptocurrency as one-tiered collateralized money. We (ii) review potential blockchain solutions against defined essential modes of communications. We review (iii) well-known scalability issues and potential denial-of-service attacks through a new probabilistic model. We (iv) characterize a typical neglection of physical network infrastructure in blockchain technology discussions. We (v) describe four successful blockchain solutions and explain their design. There is (vi) no evidence that the proclaimed “blockchain revolution” can disrupt our institutional stack; instead, it can only happen in the boundaries of the current institutional stack. Nevertheless, it is possible to (vii) design useful blockchain solutions. The findings of this research enable policy makers, decision makers and information systems architects alike to make informed decisions about blockchain technology and its application. Given its theoretic foundation in new institutional economics, triangulated with comprehensive results from design science efforts, this study is the first of its kind in the area of blockchain technology research.

Due to the rapid and widespread growth of the Internet-of-Things (IoT) paradigm, present days witness an exponential increase in the number of connected devices. In this regard, the orthogonal transmission techniques featured by conventional 4G and 5G systems can only support a limited number of simultaneously active users, due to their low spectral efficiency and poorly flexible resource allocation. To overcome such limitations, the 6G framework will include novel Next Generation Multiple Access (NGMA) solutions that will efficiently and flexibly connect a significantly larger number of devices over the same portion of spectrum. Under the NGMA umbrella, the Power-Domain Non-Orthogonal Multiple Access (PD-NOMA) technology is able to accommodate multiple users on the same frequencies by carefully assigning different power levels to the active users and employing Successive Interference Cancellation (SIC) receivers. In this work, we put forth a novel analytical approach to evaluate the performance that PD-NOMA achieves on the uplink of a single cell when a dynamic-ordered SIC receiver is considered. With respect to other existing works, the fundamental limits on the system performance are assessed analytically for an arbitrary number $n$ of simultaneously transmitting users, and both the case of Rayleigh and lognormal-shadowed Rayleigh fading are examined. The closed-form expressions presented in this work, whose correctness and excellent accuracy are validated through Monte Carlo simulations, disclose the impact of lognormal shadowing and an increasingly larger number of active users on the PD-NOMA performance.

This article has been accepted for publication in IEEE Transactions on Antennas and Propagation. Citation information: T. Watanabe and H. Yamada, “Far-Field Radar Cross-Section Determination From Near-Field 3-D Synthetic Aperture Imaging With Arbitrary Antenna-Scanning Surfaces,” IEEE Transactions on Antennas and Propagation, doi: 10.1109/TAP.2022.3161491. © 2022 IEEE. Personal use of this material is permitted. Permission from IEEE must be obtained for all other uses, in any current or future media, including reprinting/republishing this material for advertising or promotional purposes, creating new collective works, for resale or redistribution to servers or lists, or reuse of any copyrighted component of this work in other works. In this study, we propose a generalized algorithm for far-field radar cross-section determination by using 3-D synthetic aperture imaging with arbitrary antenna-scanning surfaces. This method belongs to a class of techniques called image-based near-field-to-far-field transformation. The previous image-based approaches have been formulated based on a specific antenna-scanning trajectory or surface, such as a line, plane, circle, cylinder, and sphere; majority of these approaches consider 2-D radar images to determine the azimuth radar cross-section. We generalize the conventional image-based technique to accommodate an arbitrary antenna-scanning surface and consider a 3-D radar image for radar cross-section prediction in both the azimuth and zenith directions. We validate the proposed algorithm by performing numerical simulations and anechoic chamber measurements.

The use of an eigenstate based equivalent circuit topology is proposed for the analysis and modeling of lossless and lossy bi-periodic scatterers. It can significantly simplify the design of this kind of surfaces, since it reduces the number of elements with respect to other general circuits. It contains at most only two admittances and two transformers depending on one unique transformation ratio. The real parts of these admittances can be assured to be non-negative, an interesting aspect in the modeling of lossy surfaces such as those present in asorbers. Moreover, due to the capability of decomposition into the eigenexcitations of the structure, the circuit provides important physical insight. Different cases of scatterers have been analyzed: symmetric and asymmetric, lossy and lossless. In all these cases, the modeling of the circuit admittances has been successfully achieved with a few RLC elements, positive and frequency independent. In the case of structures with symmetries, the transformation ratio directly reflects the physical orientation of the eigenexcitations of the scatterer. Furthermore, in the case of lossy scatterers but without symmetries, the resulting equivalent circuit reveals that their eigenexcitations are not linear polarizations, but elliptic polarizations whose properties are described by the complex transformation ratio.

The induction motor is considered the workhorse of the industry as it is used in most of the engineering applications. It is essential to ensure a safe and reliable operation of the induction motor in every system. Among the various types of induction motor faults, stator winding insulation fault accounts for a high percentage of it. As such, being able to detect early stages of insulation faults within the equipment using the method proposed in this paper would prove to be useful in providing timely maintenance. The proposed method in this paper is the non-intrusive impedance extraction method for online stator winding fault detection of induction motor. By observing the health condition of the motor in relation with its impedance, early stages of faults can be detected and rectified. Hence, eliminating potential safety hazards, reducing motor downtime as well as lowering the cost of maintenance. Experimental results shown will prove the reliability and accuracy in which the method proposed would provide. At the same time, its installation and removal are less complicated as compared to other methods hence is cost and time efficient.

Internet of Things (IoT) are the most commonly used devices today, that provide services that have become widely prevalent. With their success and growing need, the number of threats and attacks against IoT devices and services have been increasing exponentially. With the increase in knowledge of IoT related threats and adequate monitoring technologies, the potential to detect these threats is becoming a reality. There have been various studies consisting of fingerprinting based approaches on device identification but none have taken into account the full protocol spectrum. IPAssess is a novel fingerprinting based model which takes a feature set based on the correlation between the device characteristics and the protocols and then applies various machine learning models to perform device identification and classification. We have also used aggregation and augmentation to enhance the algorithm. In our experimental study, IPAssess performs IoT device identification with a 99.6\% classification accuracy.

This work sheds light on a novel learning-based optimization framework for heterogeneous backscatter vehicular networks. More specifically, the article presents a resource allocation and user association scheme for large-scale heterogeneous backscatter vehicular networks by considering a collaboration centric spectrum sharing mechanism. In the considered network setup, multiple network service providers (NSPs) own the resources to serve several legacy and backscatter vehicular users in the network. For each NSP, the legacy vehicle user operates under the macro cell, whereas, the backscatter vehicle user operates under small private cells using leased spectrum resources. A joint power allocation, user association, and spectrum sharing problem has been formulated with an objective to maximize the utility of NSPs. In order to overcome challenges of high dimensionality and non-convexity, the problem is divided into two subproblems. Subsequently, a reinforcement learning and a supervised deep learning approach have been used to solve both subproblems in an efficient and effective manner.

In pedestrian inertial navigation, one possible placement of Inertial Measurement Units (IMUs) is on a footwear. This placement allows to limit the accumulation of navigation errors due to the bias drift of inertial sensors and is generally a preferable placement of sensors to achieve the highest precision of pedestrian inertial navigation. However, inertial sensors mounted on footwear experience significantly higher accelerations and angular velocities during regular pedestrian activities than during more conventional navigation tasks, which could exceed Full Scale Range (FSR) of many commercial-off-the-shelf IMUs, therefore degrading accuracy of pedestrian navigation systems. This paper proposes a reconstruction filter to mitigate localization error in pedestrian navigation due to insufficient FSR of inertial sensors. The proposed reconstruction filter approximates immeasurable accelerometer’s signals with a triangular function and estimates the size of the triangles using a Gaussian Process regression. To evaluate performance of the proposed reconstruction filter, we conducted two series of indoor pedestrian navigation experiments with a VectorNav VN-200 IMU and an Analog Device ADIS16497-3 IMU. In the first series of experiments, forces experienced by the IMUs did not exceed the FSRs of the sensors, while in the second series, the forces surpassed the FSR of the VN-200 IMU and saturated the accelerometer’s readings. The saturated readings reduced the accuracy of estimated positions using the VN-200 by 1.34× and 3.37× along horizontal and vertical directions. When applying our proposed reconstruction filter to the saturated measurements, the navigation accuracy was increased by 5% horizontally and 50% vertically, as compared to using unreconstructed signals.

Foldable robotics is accepted as one of the leading technologies in the soft robotics field. Integrating the sensing components, including hinge angle proprioception, into the robot with a single fabrication method is a part of the field’s ultimate goal. Here we present a cheap single-step method for angle sensing integration into the hinges, with an accurate and reproducible performance. We use silver nanoparticle inkjet printing on the flexible structural layer (PET) of the foldable robot (i.e. Delta robot), using an office-type printer. Silver printed sensors were studied for slight bending applications; however, we report their behavior under a 1 mm minimum radius of curvature, an advanced range both for silver strain sensors and any printed hinge position sensors. Among the three patterns studied, one gave a mean absolute dynamic hysteresis error below 1 degree. Reproducibility of a printed angle sensor behavior is reported for the first time, with three prototypes of each pattern (2degree standard deviation). Printed sensor feedback is tested with proportional control for the first time, via set-point and tracking tasks. On-off control law is also implemented and errors below 1 degree are achieved. Proportional control performances are compared with encoder feedback control and the difference between the realized trajectories are found to be under 1 mm in the task plane.

This article has been accepted for publication in IEEE Transactions on Human-Machine Systems (DOI: 10.1109/THMS.2023.3274916). The experiment reported in this paper provides a first experimental evaluation of human-machine cooperation on decision level: It explicitly focuses on the interaction of human and machine in cooperative decision making situations for which a suitable experimental design is introduced. Furthermore, it challenges conventional leader-follower approaches by comparing them to newly proposed automation designs based on cooperative decision making models. These models originate from negotiation theory and game theory and allow for an investigation of cooperative decision making between equal partners. This equality is motivated by similar approaches on the action level of human-machine cooperation. The experiment’s results indicate an added value of the proposed automation designs in terms of objective cooperative performance as well as human trust in and satisfaction with the cooperation. Hence, the experiment yields the same insight on decision level as already observed on action level: it may be beneficial to design machines as equal cooperation partners and in accordance to models of emancipated human-machine cooperation.

In this paper, we propose a heuristic algorithm for rate-profile construction of Arikan’s Polarization Assisted Convolutional (PAC) codes. This method can be used for any blocklength, rate and convolutional precoding polynomial. The proposed algorithm tries to create a rate-profile for which the corresponding PAC code is, in a sense, locally optimized for having maximum possible minimum distance. Simulation results show that PAC codes constructed with the proposed algorithm perform better in terms of frame erasure rate (FER) compared to the PAC codes constructed with rate profiling designs in existing literature for various list lengths. Further, by using a (64, 32) PAC code as an example, it is shown that the choice of convolutional precoding polynomial can have a significant impact on FER performance. Finally, we demonstrate that for a target FER of $\mathbf{10^{-5}}$, (128, 72) PAC codes constructed with our proposed algorithm is just 0.35 dB away from the information theoretic limit at this blocklength.

This paper is about using diffusion equation to enhance noisy images.