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Abstract This paper presents a novel bolt looseness detection method for power transmission towers based on vibration signal analysis. The proposed method utilizes pulse excitation to extract the vibration signal of the tower, which is then adaptively decomposed using the Variational Mode Decomposition of Spider Wasp optimizer (SWVMD). This overcomes limitations of traditional Variational Mode Decomposition methods by leveraging bio‐inspired optimization to improve signal decomposition. Simulated signals processed with different optimization methods verify the superiority of the SWO approach. Field tests on a 110‐kV transmission tower further demonstrate the effectiveness of the proposed SWVMD technique for analyzing on‐site vibration data. A new improved intrinsic multiscale sample entropy feature is also introduced for bolt state characterization. A Spider Wasp Support Vector Machine classifier is developed to realize accurate bolt loosening monitoring using the extracted features. Dynamic response tests under varying bolt conditions show that the method can identify early loosening and reduce tower damage risks compared to conventional techniques. This novel vibration‐based detection framework presents an innovative application of nature‐inspired computing for power infrastructure health monitoring.

This paper presents a novel bolt looseness detection method for power transmission towers based on vibration signal analysis. The proposed method utilizes pulse excitation to extract the vibration signal of the tower, which is then adaptively decomposed using the Variational Mode Decomposition of Spider Wasp optimizer (SWVMD). This overcomes limitations of traditional Variational Mode Decomposition methods by leveraging bio‐inspired optimization to improve signal decomposition. Simulated signals processed with different optimization methods verify the superiority of the SWO approach. Field tests on a 110‐kV transmission tower further demonstrate the effectiveness of the proposed SWVMD technique for analyzing on‐site vibration data. A new improved intrinsic multiscale sample entropy feature is also introduced for bolt state characterization. A Spider Wasp Support Vector Machine classifier is developed to realize accurate bolt loosening monitoring using the extracted features. Dynamic response tests under varying bolt conditions show that the method can identify early loosening and reduce tower damage risks compared to conventional techniques. This novel vibration‐based detection framework presents an innovative application of nature‐inspired computing for power infrastructure health monitoring. [ABSTRACT FROM AUTHOR]

Even though achieving global connectivity represents one of the main goals of 5G and beyond wireless networks, exurban areas are still suffering frequent outages because of the lack of proper telecom infrastructures, which are often available only in urban areas. Indeed, cellular network design is usually capacity driven, and thus the densities of base stations (BSs) follow mostly population and especially revenue densities. Contextually, we focus on one of the most promising solutions to provide sufficient and reliable coverage in far-flung areas: aerial base stations (ABSs), which consist of unmanned aerial vehicles (UAVs) carrying cellular BS equipment. In this article, we extensively discuss the problem of bridging what is called the urban–rural digital divide (i.e., the connectivity gap between urban and rural areas) from various perspectives. First, we showcase various alternative solutions and compare conventional terrestrial networks with aerial networks from a techno-economic point of view. Then, we highlight the topological aspects of rural environments and explain how they can affect the actual design of cellular networks. In addition, we investigate both the coverage probability and the reliability of the communication links via simulations, proving that the integration of ABSs can be quite promising in a 6G perspective. Finally, we propose two original extensions of our case study as open problems. [ABSTRACT FROM AUTHOR]

Slow-moving landslides are destabilized by accumulated precipitation and consequent soil moisture. Yet, the continuous high-resolution soil-moisture measurements needed to aid the understanding of landslide processes are generally absent in steep terrain. Here, we produce soil-moisture time-series maps for a seasonally active grassland landslide in the northern California coast ranges, USA, using backscattering coefficients from NASA's uninhabited aerial vehicle synthetic aperture radar at 6-m resolution. A physically based radar scattering model is used to retrieve the near-surface (5-cm depth) soil moisture for the landslide. Both forward modeling (backscattering estimation) and the retrieval (soil-moisture validation) show good agreement. The root-mean-square errors (RMSE) for vertical transmit vertical receive (VV) and horizontal transmit horizontal receive (HH) polarizations in forward model comparison are 1.93 dB and 1.88 dB, respectively. The soil-moisture retrieval shows unbiased RMSE of 0.054 m3/m3. Our successful retrieval benefits from the surface and double-bounce scattering, which is common in grasslands. The retrieved maps show saturated wetness conditions within the active landslide boundaries. We also performed sensitivity tests for incidence angle and found that the retrieval is weakly dependent on the angle, especially while using copolarized HH and VV together. Using the two copolarized inputs, the retrieval is also not sensitive to the change of orientation angles of grass cylinders. The physical model inversion presented here can be generally applied for soil-moisture retrieval in areas with the same vegetation cover types in California.

As an emerging technique, P-band (0.3–1 GHz) may improve soil moisture remote sensing compared to L-band (1.4 GHz) Soil Moisture and Ocean Salinity (SMOS) and Soil Moisture Active Passive (SMAP) missions, because of its greater moisture retrieval depth resulting from its longer wavelength. Consequently, a number of tower-based experiments were undertaken in VIC, Australia, to understand and quantify potential improvements. The study reported here has extended the evaluation of the tau-omega model to a scenario with a dense corn canopy whose vegetation water content (VWC) reached ~20 kg/m2, and compared the soil moisture retrieval performance at P- and L-band. Based on the locally calibrated parameters, the results from both the single-channel algorithm (SCA) and dual-channel algorithm (DCA) approaches presented a clear reduction in vegetation impact at the P-band compared to L-band. While the root-mean-square error (RMSE) for the P-band did not achieve the 0.04- $\text{m}^{3}/\text{m}^{3}$ target accuracy of SMOS and SMAP, i.e., 0.054 $\text{m}^{3}/\text{m}^{3}$ for the SCA and 0.074 $\text{m}^{3}/\text{m}^{3}$ for the DCA, this performance can be regarded as acceptable considering the extremely high VWC. In comparison, the RMSEs at L-band were larger than 0.1 $\text{m}^{3}/\text{m}^{3}$ for both the SCA and the DCA approaches. Additionally, DCA performed better in correlation coefficient and unbiased RMSE, while SCA performed better in RMSE at the P-band due to the larger bias when using DCA. Moreover, the calibrated vegetation parameters at the P-band were found to apply to broader conditions than those at the L-band, likely due to the reduced vegetation impact. [ABSTRACT FROM AUTHOR]

Traditional deep-learning-based object detection networks often resize images during the data preprocessing stage to achieve a uniform size and scale in the feature map. Resizing is done to facilitate model propagation and fully connected classification. However, resizing inevitably leads to object deformation and loss of valuable information in the images. This drawback becomes particularly pronounced for tiny objects such as distribution towers (DTs) with linear shapes and few pixels. To address this issue, we propose abandoning the resizing operation. Instead, we introduce positional-encoding multihead criss-cross attention (CCA). This allows the model to capture contextual information and learn from multiple representation subspaces, effectively enriching the semantics of DTs. In addition, we enhance spatial pyramid pooling by reshaping three pooled feature maps into a new unified one while also reducing the computational burden. This approach allows images of different sizes and scales to generate feature maps with uniform dimensions and can be used in feature map propagation. Our SCAResNet incorporates these aforementioned improvements into the backbone network ResNet. We evaluated our SCAResNet using the electric transmission and distribution infrastructure imagery (ETDII) dataset from Duke University. Without any additional tricks, we used various object detection models with Gaussian receptive-field-based label assignment (RFLA) as the baseline. When incorporating the SCAResNet into the baseline model, we achieved a 2.1% improvement in mAPs. This demonstrates the advantages of our SCAResNet in detecting transmission and DTs and its value in tiny object detection (TOD). The source code is available at https://github.com/LisavilaLee/SCAResNet_mmdet. [ABSTRACT FROM AUTHOR]

Tower cranes with slender jib transporting bulky loads are commonly applied in the construction site. Human-operated commands induce vibrations of the cantilever jib, swing, and twisting of the suspended load. Coupled oscillations among jib deflection, load swing and load twisting exhibit complex dynamic behavior. Furthermore, coupled-system frequencies significantly differ from uncoupled frequencies of the jib and pendulum. Unfortunately, little attention has been directed at the coupled-oscillation dynamics and control of jib deflection, load swing, and load twisting. A dynamic model of a tower crane slewing a slender jib and moving a distributed-mass load is derived. The fully coupled effects among jib deflection, load swing, and load twisting are described in the model. Then, an equation for predicting coupled-system frequencies is presented from the analytical model. Meanwhile, a hybrid piecewise smoother is proposed to filter out coupled oscillations among jib deflection, load swing and load twisting. Many experiments validate the utility of frequency-estimation equation and verify the success of the smoother. [ABSTRACT FROM AUTHOR]

It is well known that for high voltage transmission lines in the range of 245 kV–525 kV, particularly in regions of high ground resistivity, lightning back flashover problems could be a major concern. Line arresters have been used successfully to address the problem. Underbuilt ground wires have been proposed as a viable alternative. The present paper shows that the full potential of additional ground wires could be achieved by optimizing their position on the tower. Such optimization often results in a preferred position at the level, or higher than the attachment height of the lower phase conductors; therefore the designation Embedded Ground Conductor. An essential requirement is that such positioning does not infringe in any way on the dielectric integrity of the electrical clearances and, under the influence of induced charge, does not become a source of positive streamers that may lead to additional radio or audible noise. It is found that a streamer- inhibited conductor, when properly placed, fully satisfies the above requirements. It is determined that for 245 kV, 345 kV and 420 kV lines, a streamer-inhibited embedded conductor could improve the back flashover rate by a factor of 10 or more [ABSTRACT FROM AUTHOR]

In actual line-commutated converter based high- voltage direct-current (LCC-HVDC) projects, multiple HVDC transmission lines are usually installed on the same tower to save transmission corridors and reduce construction costs. However, electromagnetic coupling effect between adjacent lines can cause commutation failure (CF) in the non-fault poles when a line or pole fails. Hence, this paper deeply investigates the mechanism and the prevention strategy of CFs caused by line coupling effect in single- and double-circuit HVDC systems. The influencing factors of line coupling effect and the coupling characteristics under fault conditions are analyzed first based on the modeling of parallel transmission lines and the traveling wave theory. Then the mechanism of CF caused by line coupling effect is investigated with the consideration of different fault conditions, different line structures, and different system operation modes. Based on the above analyses, prevention strategies for CFs of non-fault poles in single- and double-circuit systems are proposed. Finally, the simulation results verify the correctness of the theoretical analyses and the effectiveness of the proposed control strategies. [ABSTRACT FROM AUTHOR]

In this paper, the initial stage and the return stroke current waveform parameters of rocket-triggered lightning flashes to the ground and to the distribution line have been analyzed. The results show that the average current, the charge transferred and the action integral associated with the Initial Stage with return strokes are greater than the corresponding values without return strokes. For the initial stage, the presence of the distribution line greatly reduces the maximum current, average current, charge transfer, and action integral by a factor of 0.35, 0.42, 0.51, and 0.19, respectively. For the return stroke, the presence of the distribution line has little effect on the other parameters except for a 2.4-fold increase in the 10-90% risetime. The presence of the distribution line affects the initial stage parameters more significantly than the return stroke parameters, probably because the lightning channel equivalent impedance of the initial stage is much smaller than that of the return stroke. The lightning channel equivalent impedance of the initial stage estimated in this paper is about 145 ohms and the estimated lightning channel equivalent impedance for the return stroke is greater than 2000 ohms. [ABSTRACT FROM AUTHOR]

The tension insulator string is an important component for transferring the load of the conductor to the transmission tower. The damage of tension insulator strings may dramatically affect the operation safety of the grid power. In this paper, the dynamic response and fatigue life of the tension insulator strings under stochastic wind were systematically studied. Firstly, finite element models of conductors and the tension insulator string upon the actual transmission lines were established. The effects of height difference ratios on the dynamic tension of conductors and the dynamic response of tension insulator strings under a 10 m/s stochastic wind were investigated, respectively. Secondly, a simplified calculation method of stress time history is proposed to simplify the fatigue life analysis for tension insulator strings. Finally, based on the Rayleigh distribution, wind farms with the annual mean wind speed of 7 m/s were established to evaluate the fatigue life of tension insulator strings. The stress results revealed the at-risk parts in tension insulator strings and their failure modes. The fatigue life results showed 17.1 and 33.4 years for the GD (Guan Dian)-fittings and the upper U-shackles, respectively. This study can provide a useful guideline for optimization and safety evaluation of fittings. [ABSTRACT FROM AUTHOR]

Grover’s search algorithm allows a quantum adversary to find a $k$ k -bit secret key of a block cipher by making O($2^{k/2}$ 2 k / 2 ) block cipher queries. Resistance of a block cipher to such an attack is evaluated by quantum resources required to implement Grover’s oracle for the target cipher. The quantum resources are typically estimated by the $\textit {T}$ T -depth of its circuit implementation and the number of qubits used by the circuit (width). Since the AES S-box is the only component which requires $\textit {T}$ T -gates in a quantum implementation of AES, recent research has put its focus on efficient implementation of the AES S-box. However, any efficient implementation with low $\textit {T}$ T -depth will not be practical in the real world without considering qubit consumption of the implementation. In this work, we propose three methods of trade-off between time and space for the quantum implementation of the AES S-box. In particular, one of our methods turns out to use the smallest number of qubits among the existing methods, significantly reducing its $\textit {T}$ T -depth. [ABSTRACT FROM AUTHOR]

Several factors affect the electromagnetic environment changes generated underneath high-voltage transmission lines. This article carries out a study on the impact of the electromagnetic environment on high-voltage transmission lines based on different tower structures, voltage levels, conductor layouts, conductor parameters, and other full range of engineering factors. First, the model of wire three-phase phase sequence, ground height, horizontal phase spacing, wire splitting number, split spacing, and model values are built. By continuously adjusting and optimizing the parameters, the electromagnetic environment distribution curve at 1.8 m above the horizontal plane is obtained. Then, according to the characteristic analysis of the distribution law after optimization, the simulation results under some typical factors are compared with the standard limits. Simultaneously, the effect of this optimization is verified by comparison with relevant literature. Finally, some suggestions on the optimization of the pole tower structure, transmission line parameters, and the influence of electromagnetic radiation in transmission line corridors are proposed in high-voltage transmission line projects, which may potentially have constructive contributions and value. [ABSTRACT FROM AUTHOR]

In this article, we design a novel saturated proportional-derivative (PD) with sliding-mode control (SMC) method or saturated PD-SMC in short for 4-DOF tower crane systems under uncertain dynamics, external disturbances, as well as saturated control input constraints. The designed control method is model free, which can achieve accurate positioning and rapid swing suppression and elimination using only jib/trolly position/velocity and payload swing feedback with limited control inputs. Different from the existing control methods, the designed control method takes the advantages of simple structure and being easily realized in practical applications of the PD control, strong robustness of the SMC method with respect to model uncertainties and external disturbances, avoiding the requirements of accurate model knowledge associated with the SMC method, as well as rapid payload swing reduction of the swing suppression control. The stability of the controlled system is ensured by rigorous Lyapunov-based analysis. To the best of our knowledge, this is the first model-free control method without any linearization operations for tower crane systems with uncertain dynamics, external disturbances, and saturated control input constraints. Several experimental results are given to validate the superior control performance and strong robustness of the designed control method. [ABSTRACT FROM AUTHOR]

Wind turbines (WTs) can beseriously damaged by lightning strikes and they can be struck by a significant number of flashes. This should be taken into account when the WT lightning protection system is designed. Moreover, WTs represent a path for the lightning current that can modify the well-known effects of the lightning discharge in terms of radiated electromagnetic fields, which are a source of damage and interference for nearby structures and systems. In this paper, a WT struck by a lightning discharge is analyzed with a full-wave modelling approach, taking into account the details of the WT and its interactions with the lightning channel. The effects of first and subsequent return strokes are analyzed as well as that of the rotation angle of the struck blade. Results show that the lightning current along the WT is mainly affected by the ground reflection and by the reflection between the struck blade and the channel. The computed electromagnetic fields show that, for subsequent return strokes, the presence of a WT almost doubles their magnitude with respect to a lightning striking the ground. Such enhancement is emphasized when the inclined struck blade is considered. [ABSTRACT FROM AUTHOR]

All life on Earth is related, so that some molecular interactions are common across almost all living cells, with the number of common interactions increasing as we look at more closely related species. In particular, we expect the protein–protein interaction (PPI) networks of closely related species to share high levels of similarity. This similarity may facilitate the transfer of functional knowledge between model species and human. Multiple network alignment is the process of uncovering the connection similarity between three or more networks simultaneously. Existing algorithms for multiple network alignment rely on sequence similarities to help drive the alignments, and no comprehensive study has been done to determine the most effective ways to utilize network connectivity—network topology—to drive multiple network alignment. Here, we devise and empirically test the efficacy of several measures of topological similarity between three or more networks. To evolve the alignments toward optimal, we use simulated annealing as the search algorithm since it is agnostic to the objective being optimized. We test the measures both on the partially synthetic and highly similar PPI networks from the integrated interaction database, as well as on real PPI networks from a recent BioGRID release. [ABSTRACT FROM AUTHOR]

Abstract In this study, the rotor loss as well as the temperature variations due to the static air‐gap eccentricity (SAGE) and the rotor inter‐turn short circuit (RISC) in synchronous generators is presented. Different from the previous studies, this study investigates the loss/temperature changes under not only the single SAGE fault and the single RISC fault but also the combined faults (CF) that are composed of these two single faults. Detailed formula derivation on the hysteresis loss (HL) and the eddy current loss (ECL), together with the rotor temperature rise due to varied fault types and different operating conditions, are first carried out based on a theoretical analysis of the magnetic flux density (MFD) variation. Then, 3‐D finite element analysis (FEA) and experimental verifications are performed on a CS‐5 prototype generator that has two poles and a rated rotating speed of 3000 rpm. It shows that the occurrence of either SAGE or RISC will increase the rotor loss and temperature. Comparatively, the single RISC fault overweighs the single SAGE fault in the rotor temperature increment, while the combined fault overweighs both of these single faults. In the same fault cases, the rotor temperature will have the highest value under full‐load operation.

Currently, a set of scaled squat circular cylinders (SCCs) have been widely used for co-polarimetric radar cross section (RCS) calibration in various test ranges where low RCS metal pylons are used. The major drawback of a circular cylinder (CC) is its high sensitivity to elevation angle, as well as the frequency-dispersive theoretical RCS. In this work, we propose a new RCS calibrator, the metal ellipsoidal cylinder (EC), whose RCS characteristics are similar to a metal sphere, while it can be mounted on a metal pylon with little electromagnetic (EM) interactions as a CC does. A high-frequency RCS expression is derived using geometrical optics (GO) for the new calibrator. The scattering mechanisms are analyzed to establish the accurate parametric representation of the theoretical RCS. Based on surface current analysis and numerical calculation, the calibrator-pylon interaction (CPI), the angular sensitivity, and the bistatic RCS characteristics are discussed, enabling the calibration uncertainty evaluation for applying the proposed calibrator in the ground-plane range (GPR). Numerical and experimental results of a manufactured squat EC (SEC) are presented to demonstrate the excellent performance of the proposed EC calibrator for co-polarimetric RCS calibration. [ABSTRACT FROM AUTHOR]

Domain-independent planning decouples a planning task specification from planning engines. As the specification is usually describing only the physics of the environment, actions and a goal, the planning engines being generic solvers designed to solve any planning task tend to struggle with tasks that can be easily solved by domain-specific algorithms. Additional control knowledge can, to large extent, bridge such a performance gap. Instead of providing a specific planner supporting a given form of control knowledge, control knowledge can be directly encoded within the planning task specification and thus can be exploited by generic planners. In this paper, we propose Attributed Transition-Based Domain Control Knowledge (ATB-DCK) that is represented by a finite state automaton with attributed states, referring to specific states of objects, connected by transitions imposing constraints on action applicability. ATB-DCK, roughly speaking, represents the “grammar” of solution plans that guides the search. We show that ATB-DCK can be compiled into a classical planning task and thus it complements domain-independent planning techniques. Using several domains from the International Planning Competitions as benchmarks, we demonstrate that this approach often considerably improves efficiency of existing state-of-the-art planning engines. [ABSTRACT FROM AUTHOR]

In this article, we aim to address the following research question: How can a construction organization reduce and contain errors in its projects and mitigate rework and failures? We adopt an organizing sense-making perspective to acquire a sense of order of quality (e.g., rework) and to understand its relationship with safety (e.g., unsafe behavior) in construction. We undertook semistructured interviews from a range of employees involved with delivering a construction organization's projects. Also, documentary sources were accessed to supplement the rework and safety incidents that were referenced during the interviewing process. We found that the construction organization's prevailing culture focused on error prevention, which stymied its ability to learn and reduce rework in projects. The organization consciously enacted a trade-off between quality and safety. The upshot of this either/or framing of competing values was the suppression by senior management of nonconformances, which then led to deviant behavior manifesting in projects. We also revealed that safety incidents tended to arise when people engaged in unsafe behaviors while performing rework. The empirical evidence supports our call for construction organizations to engage in error management so that they can cultivate mindfulness where individuals and project teams can improvise and better handle errors, so they are not repeated. [ABSTRACT FROM AUTHOR]

In this article, we revised the commonly known engineering return stroke models for elevated objects, by taking into account the relativistic Doppler effect of the return stroke velocity shift. This revised model is applied to calculate the electromagnetic lightning field, struck by the Peissenberg tower using the finite difference time domain method in two-dimensions method. The simulation results are both compared with the results of the experimental measurements and with those obtained from the only two theoretical extending models existing in the literature that consider the presence of towers. Results show that the vertical lightning electric field is in perfect agreement with that measured experimentally, which means that this novel model was able to eliminate the nonphysical aspect of the transmitted current wave velocity from the tower top to the lightning channel observed in the hypothesis of the other authors and to reproduce in a more refined way the experimental measured electric field. The magnetic field behavior presents a concordance in the first peak and a slight difference in the tail waveform with that measured experimentally. These new formulations approximate the reality of the lightning radiation and, thus, allow to improve protection against its harmful effects. [ABSTRACT FROM AUTHOR]

In this study, we analyze a lightning event, which occurred on March 20, 2020 at 8:05 pm. Three other-triggered upward lightning developed simultaneously from the 150 m high Peissenberg Tower and from two small structures, a 35 m high mast and a 25 m high Church Tower. The velocity of the upward leaders ranged from 2.1 × 104 to 4.1 × 104 m/s. In addition, to these upward leaders, the total of 51 isolated leaders were observed. These leaders had no contact to the lightning channel or to other leaders or to objects at ground, i.e., most of them did not develop along a path of the decayed channel of a previous leader. Therefore, it is doubtful whether the isolated leaders may be recoil leaders. The lightning to the Peissenberg Tower was a bipolar flash with a current, which contained several (unusual) positive and negative components. The first component was a negative initial continuous current (ICC), followed by a strong negative current component, with a maximum of 4.1 kA and a duration of 40.2 ms. This current component was superimposed by a pulse train of 26 extremely strong current pulses with peak values up to 1.87 kA. The negative current component was followed by a positive current pulse with a peak value of 31 kA, a 10%–90% risetime of 1.80 ms, an action integral of 0.68 MJ/Ω, a full width on half maximum of 0.67 ms and a duration of 15.7 ms. The positive current pulse was superimposed by strong oscillations with the frequency of about 5 kHz and with amplitudes up to 10.2 kA. After its cessation, the positive current pulse turned into a negative continuing current with the duration of 217 ms, the maximum of 245 A, and the transferred charge of 18.0 C. The negative continuing current was followed by a negative return stroke which in turn was followed by a positive continuing current, which lasted 19.7 ms and had a maximum of 173 A. Finally, a second negative return stroke occurred, which was followed by a short negative continuing current with an M-component. [ABSTRACT FROM AUTHOR]

Unmanned Aerial Vehicle (UAV) inspection has gradually replaced manual inspection of transmission tower, which produces many images. While it is laborious and time-consuming to manually analyze these images, there are also challenges in automatically detecting small-size defective components such as bolts in transmission tower images, due to problems including complex background, small size, and many similar objects of bolts. In this paper, by virtue of multi-scale features and context information, we propose a deep neural network named Camp-Net (Context Information and Multi-Scale Pyramid Network) to identify bolts defect in transmission tower images. First, multi-scale feature fusion combines deep features and shallow features in convolutional networks to detect small-size bolts. Second, context information fusion puts the information around bolts into the detection network to remove the disturbance of complex background and similar objects. An image dataset containing defective bolts and normal bolts is constructed for model training and testing. Experimental results show that bolts with loose pins and bolts without pins among fittings in transmission tower can be accurately identified with the proposed model. The Average Precision (AP) of defective bolts detection of this model can be 11.4% higher than that of the commonly used high performance model, Faster R-CNN. [ABSTRACT FROM AUTHOR]

Trajectory prediction for mobile phone users is a cornerstone component to support many higher-level applications in LBSs (Location-Based Services). Most existing methods are designed based on the assumption that the explicit location information of the trajectories is available (e.g., GPS trajectories). However, collecting such kind of trajectories lays a heavy burden on the mobile phones and incurs privacy concerns. In this paper, we study the problem of trajectory prediction based on cell-id trajectories without explicit location information and propose a deep learning framework (called DeepCTP) to solve this problem. Specifically, we use a multi-graph embedding method to learn the latent spatial correlations between cell towers by exploiting handoff patterns. Then, we design a novel spatial-aware loss function for the encoder-decoder network to generate cell-id trajectory predictions. We conducted extensive experiments on real datasets. The experiment results show that DeepCTP outperforms the state-of-the-art cell-id trajectory prediction methods in terms of prediction error. [ABSTRACT FROM AUTHOR]

In this study, we propose an efficient optimization algorithm that is a hybrid of the iterated greedy and simulated annealing algorithms (hereinafter, referred to as IGSA) to solve the flexible job shop scheduling problem with crane transportation processes (CFJSP). Two objectives are simultaneously considered, namely, the minimization of the maximum completion time and the energy consumptions during machine processing and crane transportation. Different from the methods in the literature, crane lift operations have been investigated for the first time to consider the processing time and energy consumptions involved during the crane lift process. The IGSA algorithm is then developed to solve the CFJSPs considered. In the proposed IGSA algorithm, first, each solution is represented by a 2-D vector, where one vector represents the scheduling sequence and the other vector shows the assignment of machines. Subsequently, an improved construction heuristic considering the problem features is proposed, which can decrease the number of replicated insertion positions for the destruction operations. Furthermore, to balance the exploration abilities and time complexity of the proposed algorithm, a problem-specific exploration heuristic is developed. Finally, a set of randomly generated instances based on realistic industrial processes is tested. Through comprehensive computational comparisons and statistical analyses, the highly effective performance of the proposed algorithm is favorably compared against several efficient algorithms. Note to Practitioners—The flexible job shop scheduling problem (FJSP) can be extended and applied to many types of practical manufacturing processes. Many realistic production processes should consider the transportation procedures, especially for the limited crane resources and energy consumptions during the transportation operations. This study models a realistic production process as an FJSP with crane transportation, wherein two objectives, namely, the makespan and energy consumptions, are to be simultaneously minimized. This study first considers the height of the processing machines, and therefore, the crane lift operations and lift energy consumptions are investigated. A hybrid iterated greedy algorithm is proposed for solving the problem considered, and several problem-specific heuristics are embedded to balance the exploration and exploitation abilities of the proposed algorithm. In addition, the proposed algorithm can be generalized to solve other types of scheduling problems with crane transportations. [ABSTRACT FROM AUTHOR]

This paper encompasses various topics for 5G-involved broadcasting under the common context converged distribution of 5G media. Particularly, two primary subtopics are addressed: An overlaid coexistence of 5G terrestrial broadcast and Advanced Television Systems Committee (ATSC) 3.0; and dual connectivity applications built on top of the convergence between digital broadcasting and 5G unicasting. In the first part, a viable, time-sharing co-transmission system is introduced to overlay 5G Broadcast and ATSC 3.0 frames in the same radio spectrum. The system is carefully designed to comply with current 5G and ATSC 3.0 standards, so that it does not require modifications in either ATSC 3.0 or 5G specifications. To help the future planning in a technical aspect, the reliability performance is in-depth compared between 5G Broadcast and ATSC 3.0 frames, and the motivation of tower overlaying is discussed as well. Subsequently in the $2^{\mathrm{ nd}}$ part, the convergence is in parallel explored with respect to the dual connectivity. To settle a broad-ranged consensus for future convergence, various possible use cases are proposed in an application aspect. Technical, conceptual proposals and implementations are presented, specifically related to edge caching; 8K streaming (with a working prototype); large-scale software updating; data security; and location tracking. We hereby point out how dual connectivity can contribute to realistic scenarios. In turn, the scope of convergence use cases is desirably expanded, so that would encourage the initiatives bridging 5G and broadcasting into practice. [ABSTRACT FROM AUTHOR]

Due to lightning strikes, electric current with high power density flows through the ground grid or driven rod of power distribution line towers to the soil, which may threaten the safety of aquatic organisms in nearby ponds. In engineering practice, there is a lack of an effective risk assessment method for aquatic organisms around earthing devices of power distribution networks under impulse current dissipation caused by lightning strikes. To solve this problem, a method to assess the safety of grass carp is proposed. First, based on a method of equivalent conduction, the conductivity of a typical grass carp is measured, and current threshold values causing different reactions in grass carp are observed and recorded. Then, the steps for risk assessment are given, with consideration given to the probability distribution characteristics of lightning current amplitude. Finally, some protective measures to reduce the threat of lightning current are given. The performances of different protection methods are analyzed based on a case in Foshan city. The results show that implementing protective measures can effectively reduce adverse reactions of grass carp in thunderstorm weather. [ABSTRACT FROM AUTHOR]

The effect of the distribution of lightning strikes along the span on the performance of transmission lines was assessed following an advanced methodology, based on a Monte Carlo approach. First, considering typical features of 138-kV and 230-kV transmission lines, systematic simulations were performed, using an electromagnetic model to determine overvoltages and the disruptive effect method to assess backflashover occurrence. The influence of five variables was analyzed (tower-footing impedance, span length, waveform of the lightning return stroke current, insulation withstand and model of lightning attractiveness). The results indicated that a span factor is able to properly express the effect of the strikes distribution in the span and revealed trends: larger span factor with increasing tower-footing impedance and longer span length, smaller span factor with increasing critical flashover overvoltage and larger span factor for those models that assume larger attractiveness of the transmission line tower. Considering realistic distributions of tower-footing impedance along the line, a very narrow dispersion of the span factor was found. Assuming the same attractiveness for towers and shield wires, values of the span factor of about 0.8, 0.56, 0.53, and 0.37 were found, respectively for the 138-kV, 230-kV, 345-kV and 500-kV transmission lines. [ABSTRACT FROM AUTHOR]

Using 1.1 billion cellphone records collected in the city of Shanghai, this study evaluates the spatial and temporal movement of population during morning peak hours. The spatial autocorrelation of population density is quantitatively evaluated and visualized using Kriging models. We identify top traffic attraction zones (TTAZs) through population density change and evaluate the spatial and temporal characteristics of trip segments to TTAZs. The results show that the population density changes from a relatively homogenous pattern to a heterogeneous pattern during morning peak hours. Travelers are 10.65 to 17.2 times more likely to come from inside the TTAZs. Factors that affect the origins include the distance to a TTAZ, geographical separation, and metro lines. Approximately 85% of travelers arrive at their destination in a TTAZ after 8:00 a.m. The population density is higher along metro and expressway corridors and the impact increases over time during peak hours. The methodology provides a quantitative measure of the spatial and temporal characteristics of how population migrates. The study provides crucial information on the origin, arrival time, and route of trips to a TTAZ during morning peak hours. The results provide useful information to facilitate traffic management and planning in megacities and demonstrate the potential of using novel cellphone data for traffic planning and management. [ABSTRACT FROM AUTHOR]

We present FAST-Hex, a micro aerial hexarotor platform that allows to seamlessly transit from an underactuated to a fully actuated configuration with only one additional control input, a motor that synchronously tilts all propellers. The FAST-Hex adapts its configuration between the more efficient but underactuated, collinear multirotors, and the less efficient but full pose tracking, which is attained by noncollinear multirotors. On the basis of prior work on minimal input configurable micro aerial vehicle, we mainly stress three aspects: Mechanical design, motion control, and experimental validation. Specifically, we present the lightweight mechanical structure of the FAST-Hex that allows to only use one additional input to achieve configurability and full actuation in a vast state space. The motion controller receives as input any reference pose in $\mathbb {R}^3\times \mathrm{SO}(3)$ (3D position + 3D orientation). Full pose tracking is achieved if the reference pose is feasible with respect to actuator constraints. In case of unfeasibility, a new feasible desired trajectory is generated online giving priority to the position tracking over the orientation tracking. Finally, we present a large set of experimental results shading light on all aspects of the control of the FAST-Hex. [ABSTRACT FROM AUTHOR]

The article proposes maglev wind yaw system for wind turbine to yaw for wind. Two degrees-of-freedom (2-DOF) suspension model is constructed with the suspension current dynamics. A dual-loop cooperative suspension control including inverse system compensation, pseudo suspension control, and hybrid decoupling control is proposed to ensure nacelle stable suspension without pitching. The inverse system compensation gives the nominal current reference; and then the pseudo suspension control is designed from sliding mode controller with the nonlinear function to acquire two pseudo control input, and then 2-DOF disturbance observers based on two sliding mode surfaces and their sign function are proposed to get high-frequency interference, and cooperate with the linear relationship to decouple and give two sides current reference. The closed-loop stability of nacelle suspension has proved by the Lyapunov function, air gap asymptotic tracking can be reached in finite time. The state feedback controller with adaptive compensation is designed to enhance the current dynamic response. Finally, the simulation and experimental results show that the proposed strategy has faster suspension dynamic response, smaller steady-state error, and synchronization error. [ABSTRACT FROM AUTHOR]

In order to supply power wirelessly to reefer containers without constructing an extra power tower, this article proposed a novel multiload capacitive power transfer (CPT) system with an SP-CL isolation compensation topology. Unlike the traditional multiload CPT system, where receivers function solely as power consumers, in the proposed system, each receiver not only supplies power to the connected load but transfers power wirelessly to the next receivers. The coupler model with the cross-coupling of metal containers is established for reefer container application. Then, the SP-CL isolation compensation topology analysis based on the single circuit is carried out to achieve the load-independent characteristics with constant output voltage. The output characteristics and efficiency of the proposed CPT system are analyzed, considering the impact of the parasitic resistance. Besides, the voltage stress of passive components is optimized to design the experiment system. A 1.8-kW prototype with three loads is built to validate the effectiveness of the proposed CPT system. The equal power distribution (600 W and 600 W and 600 W) is achieved, and the system efficiency can reach 83.7%. [ABSTRACT FROM AUTHOR]

In this article, the influence of balun on the lighting electromagnetic coupling effects of planar dipole working at 890–954 MHz is investigated. The planar dipole is placed near the lightning channel. Based on the electromagnetic model of the lightning return stroke, the following two aspects are researched: first, the influence of the position of balun-cable to the lightning coupling effects, including the influence of the first return stroke and subsequent return stroke to the coupling effects of the planar dipole. Second, the influence of the distance between balun and coaxial cable to coupling effects of antenna. It can be found that the position of the balun-cable has great impacts on the lightning coupling effects of the planar dipole, even exceeding the impacts caused by the polarization of the antenna, which is installed on the communication tower and located near the lightning channel. Meanwhile, although the energy of the first return stroke is much greater than that of the subsequent return stroke, the energy of the subsequent return stroke coupling into the planar dipole is greater than that of the first return stroke. It is also found that the coupling effect of the antenna is approximately proportional to thedistance between the balun and the coaxial cable at the same height above the ground. [ABSTRACT FROM AUTHOR]

The aerosol liquid water content (ALWC) dictates the hygroscopicity of aerosol particles. To date, measurements of ALWC have been confined primarily to ground-based observations although vertical profiles of ALWC are crucial for understanding its interactions with meteorology. This study proposes a novel method for deriving profiles of ALWC using data acquired by a Light Detection and Ranging (LiDAR), a microwave radiometer, and a suite of aerosol instruments measuring aerosol physical and chemical properties, deployed during a five-month field experiment in Guangzhou, China. The retrieval approach is based on a machine-learning model named the gradient-boosted decision tree model. The inversion accuracy and stability are assessed through comparisons with ALWC data acquired on the ground and at the top of the Guangzhou tower of 532 m above ground. The agreements are encouraging: with the coefficient of determination $({R} ^{2}) = 0.870$ and root-mean-square error (RMSE) = $3.28 ~\mu \text{g} ~\cdot $ m−3 for all data; ${R} ^{2} = 0.776$ and RMSE = $2.18 ~\mu \text{g}~ \cdot $ m−3 for tower data; and ${R} ^{2} = 0.872$ and RMSE = $4.1~ \mu \text{g} ~\cdot $ m−3 for ground data. From the vertical distribution of the retrieved ALWC in Guangzhou, ALWC is higher in the lower boundary layer, especially when air pollution is severe. The proportion of liquid water in aerosol particles is closely related to the relative humidity in the environment, which will affect the morphology of aerosol particles (with about every 10% increase in liquid water, the depolarization ratio decreases by 0.02). The model may be of general use for studying air pollution and secondary aerosol generation. [ABSTRACT FROM AUTHOR]

A novel adaptive neural network tracking control method is systematically investigated for a unique double-pendulum tower crane system model in this article. Several critical and practical application-oriented control issues, including robustness, tracking error limitation, double-pendulum effects, and input dead zone nonlinearity, are considered simultaneously, which have never been well addressed in the existing literature. Technically, neural networks are employed to approximate the functions with uncertain/unknown dynamics and nonideal inputs. Several barrier Lyapunov functions are proposed that can circumvent the violation of tracking error limitations in the proposed control method. Importantly, based on the designed adaptive neural network tracking control method, the jib and trolley can track their desired trajectories very fast, and the hook and payload sway can be completely eliminated. The Lyapunov stability theory and Babalat’s lemma are utilized to theoretically prove the convergence and stability of the proposed control system. Finally, well-designed simulation studies are carried out to verify the excellent performance and strong robustness of the control method. This article should be the first work considering a double-pendulum tower crane system with guaranteed convergence and performance without any linearization for the original nonlinear dynamic model. [ABSTRACT FROM AUTHOR]

The ubiquitous expansion and transformation of the energy supply system involves large-scale power infrastructure construction projects. In view of investments of more than a million dollars per kilometre, planning authorities aim to minimize the resistances posed by multiple stakeholders. Mathematical optimization research offers efficient algorithms to compute globally optimal routes based on geographic input data. We propose a framework that utilizes a graph model where vertices represent possible locations of transmission towers, and edges are placed according to the feasible distance between neighbouring towers. In order to cope with the specific challenges arising in linear infrastructure layout, we first introduce a variant of the Bellman-Ford algorithm that efficiently computes the minimal-angle shortest path. Secondly, an iterative procedure is proposed that yields a locally optimal path at considerably lower memory requirements and runtime. Third, we discuss and analyse methods to output $k$ diverse path alternatives. Experiments on real data show that compared to previous work, our approach reduces the resistances by more than 10% in feasible time, while at the same time offering much more flexibility and functionality. Our methods are demonstrated in a simple and intuitive graphical user interface, and an open-source package (LION), available at https://pypi.org/project/lion-sp/ [ABSTRACT FROM AUTHOR]

For antiswing control of underactuated cranes, how to guarantee the converging speed of cranes through control design is essential but still remains unsolved. In this article, the adaptive antiswing control for underactuated gantry cranes with guaranteed transient performance under unmodeled dynamics and external disturbances is investigated. To sovle this problem, a set of filters are proposed to make the backstepping technique applicable for the control of crane systems. Then through variable transformation the position error and swing angel could be guaranteed converging to the origin with a given exponential speed. Hardware experiments are conducted to show that the proposed scheme achieves better control performance over existing methods, and it is illustrated that the proposed control scheme possesses strong robustness to unmodeled uncertainties and external disturbances. [ABSTRACT FROM AUTHOR]

This article presents an iterative learning control (ILC)-based approach for optimizing the flight path geometry of a tethered marine hydrokinetic (MHK) energy system. This type of system, which replaces the tower of a conventional system with a tether and a lifting body, can capture energy either through an on-board rotor or by driving a generator with tension in the tether. In the latter mode of operation, which represents the focal point of this effort, net positive energy is generated over one cycle of high-tension spool-out followed by low-tension spool-in. Because the net energy generation is sensitive to the shape of the flown path, we employ an iterative learning update law to adapt the path shape from one lap to the next. This update law is complemented with an iterative power take-off (PTO) controller, which adjusts the spooling profile at each iteration to ensure zero net spooling. We present and validate the proposed control approach in both uniform and spatiotemporally varying turbulent flow environments, based on a realistic ocean model detailed in this article. Finally, based on simulation results across a wide range of excitation levels, we perform a simulation-based assessment of convergence properties, comparing these results against bounds derived in the authors’ prior work. [ABSTRACT FROM AUTHOR]

A tower-based global navigation satellite system reflectometry (GNSS-R) experiment is set up in an Arctic wetland environment for investigating the possibility of monitoring wetland inundation and freeze/thaw (FT) dynamics which are additionally impacted by snow on the ground. Effects of inundation, snow cover, and soil FT state on observed GNSS-R signal-to-noise ratios (SNRs) are analyzed for horizontal (H) and vertical (V) polarizations. A simple classification approach is suggested to detect the inundated, frozen, or thawed soil state. A simple forward reflectivity model is formulated to evaluate the influence of snow cover, overlying frozen, or thawed soil, on the reflected GNSS signals. Reflectivity time series are simulated in H- and V-polarizations using in situ observations of the Arctic wetland site. The simulations are used to verify the tower-based observations, which show a significant impact of wet snow on reflectivity during melting conditions in spring. The observed SNR is strongly correlated with the Sentinel-1 backscatter coefficient. Generally, soil states detected by GNSS-R are in high agreement with ground truth soil states, especially for inundated and frozen soils. Wet snow conditions, however, complicate the correct timing estimation of soil thawing by inducing reflectivities of a similar order as thawing soil. It is recommended that GNSS-R land application models and retrieval algorithms consider snow cover effects to reduce false classification, especially in FT detection. Overall, the outcome of this study is relevant to the upcoming ESA HydroGNSS mission. [ABSTRACT FROM AUTHOR]

The impulse grounding performance of distribution lines tower is the key factor to lightning protection. Few field high-current impulse test researches are conducted on distribution line tower. In this paper, we used a mobile high-current impulse generator to conduct test on a 10 kV distribution line tower. The peak value of the current injection is 6 kA to 16 kA. The impulse impedance and the surface potential distribution are measured and analyzed. Based on the CDEGS software, an equivalent modeling of the experiment was carried out. The influence of soil ionization was taken into account by the method of changing the conductor radius through two rounds of calculation. The simulation and measured results were basically consistent. Experiments have shown that the soil ionization effect has an important impact on lightning performance of distribution line tower. The graphite earthing modules (GEMs) and pulling wires can significantly reduce the impulse impedance of the tower. The potential rise of the earth surface at a distance of 30 m from the tower can reach 1 kV at peak, under an injection of 7.15 kA. [ABSTRACT FROM AUTHOR]

The present study aims to provide a suitable approach to optimize transmission line towers with size, shape and panel design variables. MSTOWER software was used for modeling, analysis and design of the transmission tower. The design requirements applied to the structure were in accordance with ASCE10-97 standard. Transmission line towers are optimized in two ways. The first method combines Biogeography based Optimization (BBO) algorithm with MSTOWER software called BBO-MSTOWER and the second method, called BBO-ANFIS, uses an adaptive fuzzy neural inference system (ANFIS). To analyze the structure in the optimization process with the aim of reducing the computations and time of the optimization process. In order to evaluate the proposed method, two full-scale transmission towers were optimized as numerical models using the above two methods. Finally, the optimal design and time required in the two optimization methods were compared with each other as well as with the initial design of the tower and the results reported in previous studies. The results showed that with acceptable accuracy, ANFIS resulted in a significant reduction in the calculation time of the entire optimization process. [ABSTRACT FROM AUTHOR]

This paper presents an asset health index (HI) prediction methodology for high voltage transmission overhead lines (OHLs) using supervised machine learning and structured, unambiguous visual inspections. We propose a framework for asset HI predictions to determine the technical condition of individual OHL towers to improve grid reliability in a cost-effective manner. The paper focuses on asset HI prediction and the selection of the most parsimonious model. Based on the technical specifications and HI data, our methodology allows for the prediction of a HI for OHLs without HI data, and models asset aging behaviour. Technical specifications and the HI as defined in this paper are taken from the Estonian TSO periodical visual inspections implemented in 2018. The case study successfully demonstrates that the proposed methodology can predict tower HI values for a single OHL with nearly 80 percent accuracy without the need for additional measurements. [ABSTRACT FROM AUTHOR]

Minkowski proved that any $n$ -dimensional lattice of unit determinant has a nonzero vector of Euclidean norm at most $\sqrt {n}$ ; in fact, there are $2^{\Omega (n)}$ such lattice vectors. Lattices whose minimum distances come close to Minkowski’s bound provide excellent sphere packings and error-correcting codes in ${\mathbb {R}}^{n}$. The focus of this work is a certain family of efficiently constructible $n$ -dimensional lattices due to Barnes and Sloane, whose minimum distances are within an $O(\sqrt {\log n})$ factor of Minkowski’s bound. Our primary contribution is a polynomial-time algorithm that list decodes this family to distances approaching $1/\sqrt {2}$ of the minimum distance. The main technique is to decode Reed-Solomon codes under error measured in the Euclidean norm, using the Koetter-Vardy “soft decision” variant of the Guruswami-Sudan list-decoding algorithm. [ABSTRACT FROM AUTHOR]

Most existing cellular probe-based freeway congestion detection methods rely on on-call WLT (Wireless Location Technologies) signal transition data. However, these techniques facing difficulties such as small sample size, frequent road tests, safety, and privacy issues. This article presents a novel approach using the FCA data for traffic congestion detection on freeways. Two cellular activity features, the link pseudo speed and link probe activity, are defined and calculated. A rule-based algorithm is then developed to determine the traffic congestion state. The proposed method has been implemented and a prototype system has been deployed for a major freeway corridor in China. Validated by fixed-point detector data and incident records, the proposed method is able to identify real-time freeway traffic congestion accurately. [ABSTRACT FROM AUTHOR]

The growing commercial interest in indoor localization-based services has stimulated the development of many indoor positioning systems. Despite extensive research on localization, system requirements, such as site survey, user intervention, or specific hardware/software, place limitations on the widespread deployment of localization. To overcome these limitations, we propose a path estimation and localization system for indoor environments, termed PYLON, that runs on a smartphone and a server without any human intervention. PYLON uses an actual floor plan and measurements from widely deployed WiFi access points (APs) and Bluetooth Low Energy (BLE) beacons to estimate the user’s path. It creates virtual rooms according to received signal strength indicator (RSSI) values and matches them to actual rooms in the real-world floor plan. After room mapping, PYLON uses door passing times to precisely refine a user’s estimated path. Unlike conventional path estimation and localization systems, PYLON works independently of device types. We implement PYLON on five Android smartphones and conduct evaluation with three users in an office building. Our experimental results show that PYLON achieves 97 percent floor plan mapping accuracy with a localization error of 1.42 m. [ABSTRACT FROM AUTHOR]

Fostered by the upcoming BIOMASS mission, this article explores long-term trends of P-band temporal decorrelation over a tropical forest due to a time series of 617 days acquired during the TropiScat-2 experiment. The interest in this unique time series is twofold. First, it provides consistent statistics to monitor the yearly evolution of temporal coherences according to specific time scales of the BIOMASS tomographic and interferometric phases. Second, it provides key insights to explore new processing approaches with the combination of data from different orbit directions (ascending/descending) and different mission cycles separated by about seven months according to the current acquisition plan. For the first time, this study shows that 18-day coherences (corresponding to the time interval between the first and last acquisitions of the BIOMASS tomographic processing) can vary significantly according to rainy and dry seasons (medians from 0.3 to 0.9). The extension to time intervals of up to 90 days within both seasons and over two consecutive years puts forward the key role of the typical sporadic rainfalls occurring during dry periods in tropical rainforests, with a stronger impact on temporal coherence evolution compared to the more reproducible rainy seasons. Furthermore, outstanding values significantly above zero have been obtained for the 7- and 14-month coherences (medians of 0.35 and 0.2, respectively), opening the way to new methods of change detection. Overall, this study highlights the role of P-band temporal decorrelation not only as a disturbance factor for coherent applications but also as a relevant indicator of forest changes. [ABSTRACT FROM AUTHOR]

Extracting the power lines and pylons automatically and accurately from airborne LiDAR data is a critical step in inspecting the routine power line, especially in the remote mountainous areas. However, challenges arise in using existing methods to extract the targets from large scenarios of remote mountainous areas since the terrain is undulating, and the features are difficult to distinguish. In this article, to overcome these challenges, we propose a graph convolutional network (GCN)-based method to extract power lines and pylons from Airborne LiDAR point clouds. First, data augmentation and near-ground filtering methods are developed to overcome the problems of insufficient and imbalanced samples in the LiDAR data. Then, a GCN-based framework is proposed to extract the power lines and pylons, which consist of two main modules, i.e., the neighborhood dimension information (NDI) module and the neighborhood geometry information aggregation (NGIA) module. These two modules are designed to strengthen the model’s ability to portray local geometric details. Besides, an attention fusion module is investigated to further improve the NDI and NGIA features. Finally, a line structure constraint algorithm is proposed to identify individual power lines, where the power corridor is reconstructed using a polynomial-based algorithm. Numerical experiments are conducted based on two different power line scenarios acquired in mountainous areas. The results demonstrate the superior performances of the proposed method over several existing algorithms, where the $F_{1}$ score and quality of the power line are 99.3% and 98.6%, and the results of the pylon are 96% and 92.4%, respectively. The identification rate of power line identification is above 98%. [ABSTRACT FROM AUTHOR]

Accurate forecast of citywide passenger demand helps online car-hailing service providers to better schedule driver supplies. Previous research either uses only passenger order history and fails to capture the deep dependency of passenger demand, or is restricted on grid region partition that loses physical context. Recent advance in mobile traffic analysis has fostered understanding of city functions. In this article, we propose FlowFlexDP, a demand prediction model that integrates regional crowd flow and applies to flexible region partition. Analysis on a cellular dataset covering 1.5 million users in a major city in China reveals strong correlation between passenger demand and crowd flow. FlowFlexDP extracts both order history and crowd flow from cellular data, and adopts Graph Convolutional Neural Network to adapt prediction for regions of arbitrary shapes and sizes in a city. Evaluation on a large scale data set of 6 online car-hailing applications from cellular data shows that FlowFlexDP accurately predicts passenger demand and outperforms the state-of-the-art demand prediction methods. [ABSTRACT FROM AUTHOR]

In this article, we analyzed the difference in the estimated currents from the Foshan Total Lightning Location System (FTLLS) under two triggered lightning situations, i.e., triggered lightning to ground and triggered lightning to the distribution line. FTLLS underestimated the peak currents of triggered lightning to the distribution line, which is reflected in the peak far electric field. The peak far electric field of triggered lightning to the distribution line is about 12% lower than that of triggered lightning to ground. However, this difference in estimated current is not reflected in the far electric field waveform parameters, at least for the three field parameters: zero to peak risetime, 10%–90% risetime, and half-peak width time. The presence of distribution line will increase the risetime of the lightning return stroke current, the arithmetic mean of the current risetime of triggered lightning to distribution line is 0.46 μs, and that of triggered lightning to ground is 0.27 μs. Clarification of this underestimation phenomenon is beneficial for the application of the lightning location system in power systems. [ABSTRACT FROM AUTHOR]

The interaction of the lightning with a tall tower can be depicted by the electromagnetic field equations of a moving charge. When the equivalent moving charges are injected into the junction between the tip of tower and the bottom of lightning channel, they will travel both in the tall tower and in the channel. Along the channel, the charges will move with the return stoke speed and produce velocity field; but in the tower, they travel at the light speed without producing velocity field. At the both ends of a tower, the velocity of the moving charges will change, causing discontinuities here, and thus, the radiation fields will emit from the discontinuous ends. In such a process, the moving charges are experiencing repeatedly until the charges are fully exhausted by the channel and the ground. Based on this scenario, in this article, we proposed a method to derive the electromagnetic field radiate from the tall tower and also its current distribution by inputting the quantities of moving charges, the moving speed in the channel, the reflection and the transmission coefficient at the ends of the tower. To test the effectiveness of our method, we predict both the near-field and far-field from the tall tower struck by the lightning with three different return stroke models, i.e., transmission line (TL) model, modified TL model with exponential current decay with height (MTLE) and modified TL model with linear current decay with height (MTLL). Here, the TL model considers the velocity field and the radiation field, while MTLL and MTLE also incorporate quasi-electrostatic field produced by charges detained in the channel. Our predicted results are found to be consistent with the results from other methods. In general, our method avoids the need to incorporate the effect of current discontinuities at the return stroke frontwave compared to the extended engineering model, and could be more feasible than antenna theory method. [ABSTRACT FROM AUTHOR]