Time Coordinates Research Articles

The ‘situatedness’ of security in postcolonial spaces: Examining the historical and spatial trajectories of localised practices in Tunisia

Preventing and countering violent extremism programmes (P/CVE) programmes in western and postcolonial countries present several differences as well as similarities. The differences are a consequence of specific coordinates of time and space in which security programmes are situated. This article builds on a growing scholarship focusing on the dimension of time, highlighting how the investigation of global and local historical trajectories brings to light postcolonial processes of security policymaking and their role in shaping local security measures. Through interviews carried out in Tunisia with local and international NGOs working on P/CVE, this research examines the agency of international and local actors, and their role in implementing or challenging global and local security narratives. The objective of this research is to show the connection between global and local security narratives and practices, and the role of colonial historical trajectories in the evolution of security.

Multi time scale management and coordination strategy for stationary super capacitor energy storage in urban rail transit power supply system

The application of stationary super capacitor energy storage systems (SCESS) is an effective way to recover the regenerative braking energy of urban rail transit vehicles. The benefits of these systems’ application largely depend on the design of the energy management strategy (EMS). In this paper, the EMS core demand of SCESS is analyzed and divided into different levels based on the considered time scale. On this basis, control objectives and mathematical models were analyzed considering different time scales. Then, an EMS based on a genetic and fuzzy algorithm was presented. The feasibility and effectiveness of the proposed EMS were verified through the simulation of actual line parameters. The results indicated that the EMS can satisfy the control requirements of multiple time scales of SCESS. It is capable of effectively achieving energy management and coordinated control of multiple SCESS. As a result, it also for energy savings in the urban rail transit power supply system.

Protection Relay Setting based on Overcurrent Phenomena in Commercial Building

Nowadays, every single distribution system needs to install an appropriate relay to keep the system safe. The operational and commonly recommended relay for distribution systems is the overcurrent (OC) relay. Throughout the distribution system, the protective relay is one of the methods that can detect and protect the location according to its observation from any fault from abnormal activity. Note that time coordination between the protective equipment relay needs to be a minimum of time interruption to prevent faults occurs. The ideal setting for all coordination protection relays is necessary to protect the device against electrical failure and interference. This paper analyzes the real results data collected for the selected commercial building of an OC relay implemented in a distribution board for high voltage and low voltage downward at a commercial building. All the parameters need to be clarified first before testing has been made and measurement is carried out using the MICROTEST 860 set. Based on the analysis, it proves that according to the IEC Standard of 0.10-time multiplier Setting (TMS) is practical to be used to obtain the operation time in seconds for the current curve set. Other than that, the results show that the normal inverse curve from manual calculation results is more accurate compared to the service setting (SS) made based on the incoming setting in a real commercial building. The case study for OC relay setting is related between current injection and time-tripping, which complies with the IEC 60255-3 standard using its formula. This method was applied to determine the characteristics of the curve. Hence, this research successfully determined the proper methods for the OC relay setting for the power distribution system. Besides, the feasibility and efficiency of OC relay data transmission are tested and checked successfully to implement the measurement method in the relay coordination study.

Reconstruction of GPS Coordinate Time Series Based on Low-Rank Hankel Matrix Recovery

Reconstruction of GPS Coordinate Time Series Based on Low-Rank Hankel Matrix Recovery

Relationships Between Task Constraints, Visual Constraints, Joint Coordination and Football-Specific Performance in Talented Youth Athletes: An Ecological Dynamics Approach.

Individual performance in team sports is a multifactorial reflection of how well a player can cope and accomplish tasks in varied playing situations. Thus, performance analysis should not only focus on outcomes, but also on underlying mechanisms of those outcomes. We adopted principles of the ecological dynamics approach (EDA) to investigate the effect of introducing constraints on players' joint coordination responses for a football-specific performance drill outcome. Seventeen talented youth football (soccer) players performed a football-specific drill under different conditions: basic constraints, additional defender dummies, stroboscopic glasses, and a combination of the latter two constraints. We recorded these players' execution time, passing accuracy, and lower extremity joint kinematics. We calculated joint coordination for hip-knee, knee-ankle, and trunk-hip couplings. The added constraints negatively affected execution time and passing accuracy, and caused changes in joint coordination. Furthermore, we identified a relationship between execution time and joint coordination. This study serves as an example how the EDA can be adopted to investigate mechanisms that underlie individual performance in team sports.

Heteroclinic networks for brain dynamics.

Heteroclinic networks are a mathematical concept in dynamic systems theory that is suited to describe metastable states and switching events in brain dynamics. The framework is sensitive to external input and, at the same time, reproducible and robust against perturbations. Solutions of the corresponding differential equations are spatiotemporal patterns that are supposed to encode information both in space and time coordinates. We focus on the concept of winnerless competition as realized in generalized Lotka-Volterra equations and report on results for binding and chunking dynamics, synchronization on spatial grids, and entrainment to heteroclinic motion. We summarize proposals of how to design heteroclinic networks as desired in view of reproducing experimental observations from neuronal networks and discuss the subtle role of noise. The review is on a phenomenological level with possible applications to brain dynamics, while we refer to the literature for a rigorous mathematical treatment. We conclude with promising perspectives for future research.

The LHCb RICH upgrade for the high luminosity LHC era

The hadron particle identification provided by the RICH system in LHCb over a momentum range of 2.6–100 GeV/c has been a key element of the success of the experiment and will remain equally important for Upgrade II. With luminosities expected up to 7.5 times those expected for Upgrade I and 75 times those realised in the past, maintaining the current excellent particle identification performance demands a substantial improvement in the precision of the measurements of the space and time coordinates of the photons detected in the RICH. It will require a readout strategy with high-resolution timing information and making significant improvements in the resolution of the reconstructed Cherenkov angle.

Wyprowadzenie fenomenologicznych równań hydromechaniki przepływów wielofazowych

In the article, a multi-phase (non-homogeneous, heterogeneous) medium is considered as a macrosystem (continuum) composed of several (at least two) phases, such as a carrier phase (liquid, vapor or gas) and a carried phase (solid particles, bubbles or drops).The masses and mixtures of these phases undergo continuous changes over time due to the addition or separation of new masses to or from both phases. The model takes into account interphase transitions, discontinuities inside the mixture, and the possibility of phases being either continuous or discrete, depending on their location. A method for preliminary smoothing of discontinuities has been developed, leveraging the fact that the location in space, as well as the shape and size of the discrete phase are random. A function, denoted as φi (x, y, z, t), has been introduced, which indicates the probability of the presence of the i-th phase in the vicinity of a given point in space at time t, or that the given point of space x, y, z at time t belongs to the set of points of the i-th phase. On the other hand, this probability can be interpreted as the volumetric concentration of the i-th phase at a given point in space (i.e., the ratio of the measure of the set of points belonging to the i-th phase in the vicinity of the point under consideration at time t to the measure of the entire set of points in the surrounding area). This hypothetical medium, being equivalent to the original one, serves as a model for a multi-phase (inhomogeneous, heterogeneous, two-phase) medium. The uniqueness of the model arises from its construction. In addition, this paper considers several main areas of theoretical and experimental research concerning the hydrodynamics of a multi-phase (two-phase suspension-carrying) flow of a continuous medium. It also discusses the most important results achieved in existing works. A critical analysis of known theories for mathematically describing the motion of multi-phase (two-phase) systems and methods for averaging the hydrodynamic characteristics of a turbulent flow are given. The procedure for closing the equations systems of hydromechanics of multi-phase flows proposed in existing works is carried out within the framework of semi-empirical theories of turbulence. In nature, the vast majority of multi-phase (two-phase, inhomogeneous) mixtures exhibit turbulent behavior, making its study a crucial practical task. The mathematical description of the motion of a turbulent multi-phase flow relies on stylized laws of mechanics. The methods of operational analysis proposed at various times by different researchers for the mathematical description of the motion of a multi-phase (two-phase) flow have varying degrees of approximation and certain limited areas of application. One of the main challenges in formulating differential equations for the motion of a turbulent multi-phase (two-phase, suspension-carrying) flow is the fact that in a turbulent flow of a mixture, where the characteristics of the flow change chaotically and randomly over time and at each point in space, both in magnitude and in direction, there are surfaces with weak and strong discontinuities. Consequently, the actual values of velocity and pressure of a multi-phase flow, strictly speaking, cannot be considered continuous functions of the coordinates of space and time throughout the entire region occupied by the mixture.

LoRaWAN-based IoT protocol for three levels central protection scheme in MT-HVDC networks with ANFIS-PSO restoration algorithm

A new three-level adaptive central protection scheme has been introduced for multi-terminal high voltage direct current (MT-HVDC) transmission grids. The primary protection is based on a differential relay, while two backup protection levels are proposed: a local dv/dt under-voltage relay and a centralized overcurrent relay at the AC grid side. The coordination of these three protection levels is managed based on a convenient coordination time. The communication between the central protection unit and the Fault Isolation Devices (FIDs) is established using the LoRaWAN-based Internet of Things (IoT) protocol. In case of fault clearance triggered by the third protection level, the faulty line is detected and isolated using the adaptive neuro-fuzzy inference system (ANFIS) algorithm. The restoration process of the healthy lines focuses on minimizing load shedding and line power loss. The protection scheme proposed in this article has been implemented and tested under various fault conditions using the MATLAB/Simulink® environment. The results demonstrate the effectiveness and efficiency of the proposed protection scheme in detecting and isolating faulty lines in MT-HVDC transmission grids, along with a rapid restoration technique.

Understanding and optimizing fish counting techniques based on electrical impedance measurements.

Sustainable aquatic resources management requires reliable methods for fish detection in various environmental conditions. Herein, we study fundamental mechanisms underlying the application of electrical impedance measurements in this regard. We present results of experimental studies conducted in laboratory conditions using a low-cost impedance measurement circuit, as well as the corresponding numerical models. We also present evaluation results of a newly developed, real-time detection algorithm based on adaptive thresholding. The numerical model was validated by extracting fish tracks in 3D space from the experimental datasets, and then comparing the calculated versus measured impedance values as functions of fish coordinates in time. Numerical predictions closely resemble the experimental data. The detection sensitivity and specificity values determined for various settings exceeded 90%. Electrode width to spacing ratio is demonstrated to be a crucial parameter influencing the system sensitivity distribution. The introduced approach can constitute a framework for designing electrical impedance-based fish counting systems.

Physics-informed neural networks for solving forward and inverse Vlasov–Poisson equation via fully kinetic simulation

The Vlasov–Poisson equation is one of the most fundamental models in plasma physics. It has been widely used in areas such as confined plasmas in thermonuclear research and space plasmas in planetary magnetospheres. In this study, we explore the feasibility of the physics-informed neural networks for solving forward and inverse Vlasov–Poisson equation (PINN-Vlasov). The PINN-Vlasov method employs a multilayer perceptron (MLP) to represent the solution of the Vlasov–Poisson equation. The training dataset comprises the randomly sampled time, space, and velocity coordinates and the corresponding distribution function. We generate training data using the fully kinetic PIC simulation rather than the analytical solution to the Vlasov–Poisson equation to eliminate the correlation between data and equations. The Vlasov equation and Poisson equation are concurrently integrated into the PINN-Vlasov framework using automatic differentiation and the trapezoidal rule, respectively. By minimizing the residuals between the reconstructed distribution function and labeled data, and the physically constrained residuals of the Vlasov–Poisson equation, the PINN-Vlasov method is capable of dealing with both forward and inverse problems. For forward problems, the PINN-Vlasov method can solve the Vlasov–Poisson equation with given initial and boundary conditions. For inverse problems, the completely unknown electric field and equation coefficients can be predicted with the PINN-Vlasov method using little particle distribution data.

A fast coordination approach for large-scale drone swarm

With the advances in artificial intelligence, robotics, and data fusion, large numbers of drones operating in a coordinated manner will become commonplace for a wide range of commercial and military uses. At present, the application methods of drone swarms are mainly divided into fully autonomous methods and controlled methods with human participation. Because of the limited level of artificial intelligence, controlled drone swarms will be the main way for the application of large-scale drone swarms for a long time. However, there is less research on achieving global coordination in a limited time for a controlled large-scale drone swarm. Therefore, a new large-scale drone swarm framework is proposed firstly in this paper, which achieves global coordination through local interaction and reduces the impact of limited channel resources. Secondly, this paper proposes a local interaction-based fast coordination method and introduces a prediction mechanism, to ensure that large-scale drone swarms can quickly achieve coordination even in the presence of node loss. Moreover, the numerical integration method is used to update the consensus state, so that the drones can increase the iteration period, reduce the number of packets, and further reduce the channel burden. Finally, considering that large-scale drones swarm are usually composed of drone swarms launched at different locations and times, a consensus algorithm considering the merging behavior of drone swarms is also proposed. The simulation results show that the large-scale drone swarm using the proposed architecture can achieve the leader–follower consensus in a very short time and even in a confrontational environment with poor communication conditions. Besides, after the merger of multiple drone swarms, the consensus problem can still be solved in very few iteration cycles.

Autonomous ship navigation with an enhanced safety collision avoidance technique

The motion of an autonomous ship is different from that of ground and aerial robots due to its maneuvering and environmental constraints. As a result, many techniques have been introduced for autonomous ship path planning. This paper presents a novel technique for global and local navigation planning of autonomous ships under complex static and dynamic constraints. Our technique, termed safety-enhanced path planning (SPP), has been developed to avoid potential collisions with underwater obstacles near seaside areas. SPP pre-processes the map to preserve the shape of visible obstacles and mark a safety-outline around the shores. Subsequently, an offset safety line (OSL) is drawn about the original shore to protect the ship when passing close to threat-defined offshore areas. The global path is produced with an enhanced A* multi-directional algorithm, considering the kinematic constraint of the ship. To ensure optimal path quality, the global path is further refined with a smoothing filter to improve consistency and smoothness. Additionally, local navigation is introduced to help the autonomous ship avoid collisions with other obstacle ships. Local offset trajectories are produced with 4th and 5th degree polynomials along longitudinal and lateral coordinates in time t. Distance closest point approach (DCPA) is utilized for early obstacle prediction to help the ship maneuver in complex dynamic obstacle avoidance scenarios. The trajectory set is filtered with an efficient cost policy to obtain the best trajectory for dynamic collision avoidance. We conduct simulations in MATLAB and compared with other maritime path planning methods to verify the effectiveness of our approach.

Spatially homogeneous teleparallel spacetimes with four-dimensional groups of motions

In this paper, we study metric teleparallel geometries, which can either be defined through a Lorentzian metric and flat, metric-compatible affine connection, or a tetrad and a flat Lorentz spin connection, which are invariant under the transitive action of a four-dimensional Lie group on their spatial equal-time hypersurfaces. There are three such group actions, and their corresponding spatial hypersurfaces belong to the Bianchi types II, III and IX, respectively. For each of these three symmetry groups, we determine the most general teleparallel geometry, and find that it is parametrized by six functions of time, one of which can be eliminated by the choice of the time coordinate. We further show that these geometries are unique up to global Lorentz transformations, coordinate transformations and changes of the choice of the parameter functions.

A new deep self-attention neural network for GNSS coordinate time series prediction

A new deep self-attention neural network for GNSS coordinate time series prediction

Effects of partial passive ownership in a successive endogenous timing game with R&D spillovers

AbstractThis study explores the effect of partial passive ownership (PPO) in a successive two‐round endogenous timing game wherein firms choose research and development (R&D) investments in the first round and then subsequently choose quantities in the second round. We show that each firm prefers to be a quantity leader independent of the timing of R&D decisions, but the welfare‐inferior Cournot competition is an equilibrium of an endogenous production timing game. Moreover, we discover that the equilibrium of an endogenous R&D timing game crucially depends on the PPO level and R&D spillovers rate, while the R&D timing coordination may not be socially desirable unless both are low or high. Our findings suggest that the R&D leadership position of a PPO holder can play an anticompetitive role in the coordination of R&D competition with higher R&D spillovers rates and PPO levels.

Photo-thermo-piezo-elastic waves in semiconductor medium subject to distinct two temperature models with higher order memory dependencies

PurposeThis study aims to examine the impacts of higher memory dependencies on a novel semiconductor material that exhibits generalized photo-piezo-thermo-elastic properties. Specifically, the research focuses on analyzing the behavior of the semiconductor under three distinct temperature models.Design/methodology/approachThe study assumes a homogeneous and orthotropic piezo-semiconductor medium during photo-thermal excitation. The field equations have been devised to encompass higher order parameters, temporal delays and a specifically tailored kernel function to address the problem. The eigenmode technique is used to solve these equations and derive analytical expressions.FindingsThe research presents graphical representations of the physical field distribution across different temperatures, higher order plasma heat conduction models and time. The results reveal that the amplitude of the distribution profile is markedly affected by factors such as the memory effect, time, conductive temperature and spatial coordinates. These factors cannot be overlooked in the analysis and design of the semiconductor.Research limitations/implicationsSpecific cases are also discussed in detail, offering the potential to advance the creation of precise models and facilitate future simulations.Practical implicationsThe research offers valuable information on the physical field distribution across various temperatures, allowing engineers and designers to optimize the design of semiconductor devices. Understanding the impact of memory effect, time, conductive temperature and spatial coordinates enables device performance and efficiency improvement.Originality/valueThis manuscript is the result of the joint efforts of the authors, who independently initiated and contributed equally to this study.

Three-Dimensional Modeling of Sound Field Holograms of a Moving Source in the Presence of Internal Waves Causing Horizontal Refraction

In this paper, we study the variations of holograms of a moving source in an inhomogeneous ocean waveguide. It is assumed that intense internal waves (internal solitons) are the reason for the inhomogeneities of the shallow water waveguide. The results of 3D modeling of the sound field considering horizontal refraction by internal waves are presented. In the context of 3D modeling, the interferogram (sound intensity distributions in frequency–time coordinates) and hologram (2D Fourier transform of the interferogram) of moving sources are analyzed. The hologram consists of two disjoint regions corresponding to the unperturbed field and the field perturbed by internal waves. This structure of the hologram allows for the reconstruction of the interferogram of the unperturbed field in a waveguide in the absence of intense internal waves. The error in the reconstruction of the unperturbed interferogram is estimated.

A new method for coseismic offset detection from GPS coordinate time series

Currently, the extraction of coseismic offset signals primarily relies on earthquake catalog data to determine the occurrence time of earthquakes. This is followed by the process of differencing the average GPS coordinate time series data, with a time interval of 3 to 5 days before and after the earthquake. In the face of the huge amount of GPS coordinate time series data today, the conventional approach of relying on earthquake catalog data to assist in obtaining coseismic offset signals has become increasingly burdensome. To address this problem, we propose a new method for automatically detecting coseismic offset signals in GPS coordinate time series without an extra earthquake catalog for reference. Firstly, we pre-process the GPS coordinate time series data for filtering out stations with significant observations missing and detecting and removing outliers. Secondly, we eliminate other signals and errors in the GPS coordinate time series, such as trend and seasonal signals, leaving the coseismic offset signals as the primary signal. The resulting coordinate time series is then modeled using the first-order difference and data stacking method. The modeling method enables automatic detection of the coseismic offset signals in the GPS coordinate time series. The aforementioned method is applied to automatically detect coseismic offset signals using simulated data and the Searles Valley GPS data in California, USA. The results demonstrate the efficacy of our proposed method, successfully detecting coseismic offsets from vast amounts of GPS coordinate time series data.

Slow Slip Events Associated with Seismic Activity in the Hikurangi Subduction Zone, New Zealand, from 2019 to 2022

Slow slip events (SSEs) are geophysical phenomena primarily occurring in subduction zones. These events are often associated with seismic activity and can be detected by Global Positioning System (GPS). However, the relationship between SSEs and seismic activity remains unclear. To further investigate SSEs associated with seismic activity, we conducted SSE detection and inversion for the period from 2019 to 2022 on New Zealand’s North Island, where both SSEs and seismic activity frequently occur. By modeling daily GPS coordinate time series from 40 GPS stations and applying the Network Inversion Filter (NIF) method, we obtain surface displacements, cumulative slips, and slip rates for eight shallow SSEs. Subsequently, we conduct a statistical analysis of seismic activity concerning its spatial distribution and frequency before, during, and after SSE occurrences. The results indicate that SSE1 and SSE7 exhibited larger cumulative slips, at 14.35 and 7.20 cm, and surface displacements, at 4.97 and 2.53 cm, respectively. During their occurrences, the seismic frequency noticeably increased to 6.5 and 5.6 events per day in the Eastern Coastal Region (ECR) of New Zealand’s North Island. However, the other six SSEs, characterized by cumulative slips of less than 6 cm and maximum surface displacements of less than 2 cm, did not lead to a noticeable increase in seismic frequency during their occurrences in the ECR. In the Main Slip Regions (MSR) of these eight SSEs, a significant upward trend in seismic frequency was observed during their occurrences. Therefore, it can be inferred that in the ECR of New Zealand’s North Island, all SSEs result in an increased seismic frequency within their respective MSRs, but only significant SSEs impact the seismic frequency of the ECR. Monitoring shallow SSEs may contribute to the identification and recording of seismic activity.