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This paper proposes a specific algebraic structure and demonstrates its nature as an extension field, enabling the construction of Golomb Costas (GC) arrays. It provides detailed instructions and examples for constructing GC arrays using this extension field, along with a corresponding flowchart. Additionally, the paper conducts a thorough analysis, incorporating calculations and comparisons, to evaluate the autocorrelation of a GC array derived from the extension field compared to that of a diagonal frequency hopping array. The analysis reveals the superior autocorrelation properties of GC arrays based on the extension field. Furthermore, the paper establishes a mathematical model for the signal coded by the frequency hopping array and subsequently simulates and compares the ambiguity function of the signal coded by a GC array with that of a signal coded by a diagonal frequency hopping array. This comparison underscores the thumbtack ambiguity function of frequency hopping signal coded by a GC array. Moreover, the paper thoroughly investigates the relationship between the correlation function of GC arrays and the roots of an algebraic equation in a finite field, and strictly proves the ideal autocorrelation properties of Golomb Costas arrays. [ABSTRACT FROM AUTHOR]

This paper presents an edge‐based event‐triggered delay distributed algorithm for solving the economic dispatch problem (EDP) in smart grids. The objective of the EDP is to minimize the total generation cost by allocating power to individual generators, each with its local generation constraint. To save the overhead of communication resources between agents, an edge‐based event‐triggered mechanism is suggested. By setting distinct triggering thresholds for each communication edge, the agent may efficiently regulate the communication frequency among all neighbors. However, in practice, owing to the instability of the network, the agent may receive information regarding its neighbors, leading to communication lags for every communication link. The virtual agent technique and double‐stochastic matrix augmentation technique provide an equivalent delay‐free EDP. It is demonstrated that the proposed algorithm can asymptotically converge to the global optimal solution as long as the communication delay is arbitrary, time‐varying, and random, but bounded. Objective and clear evidence is provided through a case study in smart grids to verify the algorithm's feasibility. [ABSTRACT FROM AUTHOR]

It is now possible to detect dangerous arcing faults in the paper insulation of transformers and distinguish them from arcing faults in oil, using new sub-zones of Duval Pentagons 1 and 2. [ABSTRACT FROM AUTHOR]

Construction project delays can stem from a myriad of factors and pose significant challenges for owners and contractors. While numerous methods for analyzing delays exist, the majority are designed for network scheduling, lack contemporaneous tracking (i.e., do not allow for identifying and tracking delays as they occur), and struggle with attributing delays to specific stakeholders. Therefore, this paper introduces a novel graphical approach to monitor delays by comparing as-planned and as-built schedules at the activity level. Distinguished by its contemporaneous nature, the new method allows real-time tracking and quantification of delays. This facilitates identifying their origin and potential causes. Rules for constructing the graphs of various delay scenarios are demonstrated for typical activity combinations. The effectiveness of the proposed method is validated via a case study that showcases its practical application. Implementing it is straightforward, and while the method could be applied to network schedules, its relevance lies in linear and repetitive schedules. The cyclic nature of tasks in such schedules underscores the importance of contemporaneous delay tracking to facilitate swift remedial actions and pinpoint liability. Practical Applications: In this study, the authors present a new way to track delay using graphs by comparing starts, productivities, and finishes of as-planned and as-built schedules at the activity level. Because it is contemporaneous, the new approach tracks and measures delays in real time, currently manually, but easily implemented as computer code. This method makes it easier to find the source and possible causes of activity and project delays. Detailed rules are derived for common activity scenarios and interactions on how to create the respective graphs. A real-world study demonstrates how the proposed method can be used to substantiate its potential value to practitioners in industry. The proposed approach is practical, and while it could be used for network schedules, it is especially useful for linear and repetitive schedules. [ABSTRACT FROM AUTHOR]

Adaptive control and synchronization techniques have been extensively developed over the years due to their ability to operate without prior analytical knowledge of the system. However, their application in real-world systems necessitates the consideration of various factors such as delays and stochastic disturbances. Moreover, the conventional hypothesis of a global Lipschitzian condition is often overly restrictive for real-world systems. In this paper, we address these challenges by jointly incorporating these factors. We introduce a novel parameter θ in the algebraic power associated with the adaptive rule. This modification enhances the effectiveness of the adaptive scheme in more realistic systems. Additionally, we investigate how the power θ and the nonlinear degrees of vector fields affect the performance of the adaptive scheme. The adaptive scheme proves to be effective in controlling or synchronizing stochastic complex dynamics in ecosystems and biosystems, demonstrating its broad applicability in various fields. [ABSTRACT FROM AUTHOR]

Effective nonlinear control of manipulators with dynamically coupled arms, like those with direct drives, is the subject of the paper. Model-based predictive control (MPC) algorithms with nonlinear state-space models and most recent disturbance attenuation technique are proposed. This technique makes controller design and online calculations simpler, avoiding necessity of dynamic modeling of disturbances or resorting to additional techniques like SMC. The core of the paper are computationally effective MPC-NPL (Nonlinear Prediction and Linearization) algorithms, where computations at every sample are divided into two parts: prediction of initial trajectories using nonlinear model, then optimization using simplified linearized model. For a comparison, a known CTC-PID algorithm, which is also model-based, is considered. It is applied in standard form and also proposed in more advanced CTC-PID2dof version. For all algorithms a comprehensive comparative simulation study is performed, for a direct drive manipulator under disturbances. Additional contribution of the paper is investigation of influence of sampling period and of computational delay time on performance of the algorithms, which is practically important when using model-based algorithms with fast sampling. [ABSTRACT FROM AUTHOR]

This paper is concerned with the synchronization of stochastic uncertain complex dynamic networks with time‐varying delays. In contrast to existing synchronization network models, the current study considers both internal time‐varying delays and coupling time‐varying delays. By analyzing the two factors (i.e. time‐varying delays and uncertainties) on the synchronization performance of stochastic uncertain complex dynamic networks, a new inverse optimal adaptive control is proposed. The analysis tool developed in this paper is based on Lyapunov technique, algebraic graph theory and inverse optimality, which does not need to solve Hamilton‐Jacobi‐Bellman equation. Some sufficient conditions are established for the synchronization of stochastic uncertain complex dynamic networks with time‐varying delays. To demonstrate the effectiveness of the present approach, simulation results are illustrated. In this paper, we consider the synchronization of stochastic uncertain complex dynamic networks with time‐varying delays. Different from the existing synchronization of the networks model, we take the internal time‐varying delays and the coupling time‐varying delays into account. By analyzing the two factors (i.e. time‐varying delays and uncertainties) on the synchronization performance of stochastic uncertain complex dynamic networks, a novel inverse optimal adaptive control is proposed. The analysis tool developed in this paper is based on Lyapunov technique, algebraic graph theory and inverse optimality, which does not need to solve Hamilton‐Jacobi‐Bellman equation. Some sufficient conditions are established for the synchronization of stochastic uncertain complex dynamic networks with time‐varying delays. [ABSTRACT FROM AUTHOR]

Modifications to the design, quality, quantity of work, and standard of materials or goods to be utilized and the removal of any materials not in compliance with the contract from the site, are all considered variations in construction. The building industry is facing a significant problem with variation orders. This led to delays, cost overruns, and occasional disputes between the parties over contracts. This paper sought to determine the underlying reasons for variation, the implications of variations on Indian projects, and strategies for lessening the impact of variation orders. The study's methodology included a review of the literature, the collection of primary data, interviews, and closed-ended questionnaires. To determine whether there was a significant difference in the means of the professional groups, the analysis of variance test is employed. The collected data is reliable, the Cronbach alpha is greater than 0.70, and also the Pearson correlation coefficient is lying between -1 and 1. From this study, it is concluded that the correlation may or may not exist among the antecedents of variations, and their correlation may appear in any direction, and it is also in line with standard theory of statistics. [ABSTRACT FROM AUTHOR]

The current values of many populations depend on the past values of the population. In many cases, this dependence is caused by the time certain processes take. This dependence on the past can be introduced into mathematical models by adding delays. For example, the growth rate of a population depends on the population τ time units ago, where τ is the maturation time. For an epidemic, there is a time τ between the contact of an infected individual and a susceptible one, and the time the susceptible individual actually becomes infected. This time τ is also a delay. So, the number of infected individuals depends on the population at the time τ units ago. A second way of introducing this dependence on past values is to use non-local operators in the description of the model. Fractional derivatives have commonly been used to provide non-local effects. In population growth models, it can also be done by introducing a new compartment, the immature population, and in epidemic models, by introducing an additional exposed population. In this paper, we study and compare these methods of adding dependence on past values. For models of processes that involve delays, all three methods include dependence on past values, but fractional-order models do not justify the form of the dependence. Simulations show that for the models studied, the fractional differential equation method produces similar results to those obtained by explicitly incorporating the delay, but only for specific values of the fractional derivative order, which is an extra parameter. But in all three methods, the results are improved compared to using ordinary differential equations. [ABSTRACT FROM AUTHOR]

Delays and cost overruns in turnkey projects can lead to significant economic losses, disputes and even project abandonment. These facts negatively impact the environmental, social and governance (ESG) policies of companies involved in the project. In this paper, a bibliographic review was conducted to identify the leading causes of delays and cost overruns in turnkey industrial projects in the refining, gas and conventional electricity generation (RGE) sector and propose good practices to avoid or mitigate them. We identified 893 causes of delays and cost overruns and 147 mitigation measures. The causes and mitigation measures were grouped into eight categories based on the execution phases of an RGE project. A critical analysis was carried out to avoid duplication, and the result was evaluated by experts in turnkey project management, reducing the causes and mitigation measures to a final set of 103 and 49, respectively. The construction category showed the most significant influence on project delays and cost overruns, and this, together with the preliminary phase and project management categories, contributed to 60% of the identified causes. The findings of this study can help project managers improve the profitability of turnkey industrial projects, promoting innovation and sustainability within companies and society. [ABSTRACT FROM AUTHOR]

The aim of this paper is to develop and investigate a novel mathematical model of the dynamical behaviors of chronic hepatitis B virus infection. The model includes exposed infected hepatocytes, intracellular HBV DNA-containing capsids, uses a general incidence function for viral infection covering a variety of special cases available in the literature, and describes the interaction of cytotoxic T lymphocytes that kill the infected hepatocytes and the magnitude of B-cells that send antibody immune defense to neutralize free virions. Further, one time delay is incorporated to account for actual capsids production. The other time delays are used to account for maturation of capsids and free viruses. We start with the analysis of the proposed model by establishing the local and global existence, uniqueness, non-negativity and boundedness of solutions. After defined the threshold parameters, we discuss the stability properties of all possible steady state constants by using the crafty Lyapunov functionals, the LaSalle’s invariance principle and linearization methods. The impacts of the three time delays on the HBV infection transmission are discussed through local and global sensitivity analysis of the basic reproduction number and of the classes of infected states. Finally, an application is provided and numerical simulations are performed to illustrate and interpret the theoretical results obtained. It is suggested that, a good strategy to eradicate or to control HBV infection within a host should concentrate on any drugs that may prolong the values of the three delays. [ABSTRACT FROM AUTHOR]

Introduction: This study characterized the extent to which (1) financial barriers and (2) abortion care-seeking within a person's country of residence were associated with delays in abortion access among those travelling to England and the Netherlands for abortion care from European countries where abortion is legal on broad grounds in the first trimester but where access past the first trimester is limited to specific circumstances. Methodology: We drew on cross-sectional survey data collected at five abortion clinics in England and the Netherlands from 2017 to 2019 (n = 164). We assessed the relationship between difficulty paying for the abortion/travel, acute financial insecurity, and in-country care seeking on delays to abortion using multivariable discrete-time hazards models. Results: Participants who reported facing both difficulty paying for the abortion procedure and/or travel and difficulty covering basic living costs in the last month reported longer delays in accessing care than those who had no financial difficulty (adjusted hazard odds ratio: 0.39 95% CI 0.21–0.74). This group delayed paying other expenses (39%) or sold something of value (13%) to fund their abortion, resulting in ~ 60% of those with financial difficulty reporting it took them over a week to raise the funds needed for their abortion. Having contacted or visited an abortion provider in the country of residence was associated with delays in presenting abroad for an abortion. Discussion: These findings point to inequities in access to timely abortion care based on socioeconomic status. Legal time limits on abortion may intersect with individuals' interactions with the health care system to delay care. Plain Language Summary: This paper explores delays in accessing abortion care associated with financial and medical system barriers. We focus on residents of countries in Europe where abortion is available on broad grounds in the first trimester seeking abortion care outside of their country of residence. This study demonstrates an association between difficulty covering abortion costs for people facing financial insecurity and in-country care seeking and delays in accessing abortion abroad. Policy barriers, medical system barriers, as well as financial barriers may interact to delay access to care for people in European countries with broad grounds for abortion access in the first trimester but restrictions thereafter, especially for people later in pregnancy. [ABSTRACT FROM AUTHOR]

In this paper, we analyze the celebrated Haken--Kelso--Bunz model, describing the dynamics of bimanual coordination, in the presence of delay. We study the linear dynamics, stability, nonlinear behavior, and bifurcations of this model by both theoretical and numerical analysis. We calculate in-phase and antiphase limit cycles as well as quasi-periodic solutions via double Hopf bifurcation analysis and center manifold reduction. Moreover, we uncover further details on the global dynamic behavior by numerical continuation, including the occurrence of limit cycles in phase quadrature and 1-1 locking of quasi-periodic solutions. [ABSTRACT FROM AUTHOR]

This paper investigates the dynamic behavior of a class of delayed quaternion-valued neural networks (QVNNs) with impulses and parameter uncertainties. First, we assume that the activation function and connection matrices in the model are defined in the quaternion domain. Without decomposing the QVNNs into four equivalent neural networks in a real number domain or two equivalent neural networks in a complex number domain, the existence and uniqueness of the equilibrium point (EP) are studied based on the M-matrix and homeomorphism mapping theories. By combing the vector Lyapunov function with mathematical induction, theorems are given to ensure robust exponential stability of the system's EP. The results reflect the influence of connection matrices, delays, impulses, and the activation function on the convergence speed of the EP. Finally, the feasibility of the derived results is explained through three examples. [ABSTRACT FROM AUTHOR]

Our focus of this paper is on global Mittag-Leffler synchronization (GMLS) of the Caputotype Inertial Cohen-Grossberg Neural Networks (ICGNNs) with discrete and distributed delays. This model takes into account the inertial term as well as the two types of delays, which greatly reduces the conservatism with respect to the model. A change of variables transforms the 2β order inertial frame into β order ordinary frame in order to deal with the effect of the inertial term. In the following steps, two novel types of delay controllers are designed for the purpose of reaching the GMLS. In conjunction with the novel controllers, utilizing differential mean-value theorem and inequality techniques, several criteria are derived to determine the GMLS of ICGNNs within the framework of Caputo-type derivative and calculus properties. At length, the feasibility of the results is further demonstrated by two simulation examples. [ABSTRACT FROM AUTHOR]

This paper presents the first investigation of extended dissipative synchronization in a specific type of Takagi-Sugeno (T-S) fuzzy complex dynamical networks with interval hybrid coupling delays. First, the decoupling method is employed to reorganize the multiple communication dynamical system, which comprises discrete-time, partial and distributed coupling delays. Second, the non-fragile control, which allows for uncertainty management within predefined norm bounds, has been applied to networks. Moreover, it becomes possible to derive a less conservative condition by utilizing multiple integral Lyapunov functionals, a decoupling strategy, Jensen's inequality, Wirtinger's inequality, and mathematical inequality techniques. This condition ensures that the T-S fuzzy complex dynamical networks, with interval hybrid coupling delays, can attain asymptotic synchronization with the assistance of a non-fragile feedback controller. Additionally, we extended this system to the extended dissipativity analysis, including passivity, L2 - L∞, H∞ and dissipativity performance in a unified formulation. A set of strict linear matrix inequalities (LMIs) conditions is a sufficient criterion. Finally, two simulation examples are proposed to verify the merit of the obtained results. [ABSTRACT FROM AUTHOR]

The Cohen–Grossberg neural network is studied in the case when the dynamics of the neurons is modeled by a Riemann–Liouville fractional derivative with respect to another function and an appropriate initial condition is set up. Some inequalities about both the quadratic function and the absolute values functions and their fractional derivatives with respect to another function are proved and they are based on an appropriate modification of the Razumikhin method. These inequalities are applied to obtain the bounds of the norms of any solution of the model. In particular, we apply the squared norm and the absolute values norms. These bounds depend significantly on the function applied in the fractional derivative. We study the asymptotic behavior of the solutions of the model. In the case when the function applied in the fractional derivative is increasing without any bound, the norms of the solution of the model approach zero. In the case when the applied function in the fractional derivative is equal to the current time, the studied problem reduces to the model with the classical Riemann–Liouville fractional derivative and the obtained results gives us sufficient conditions for asymptotic behavior of the solutions for the corresponding model. In the case when the function applied in the fractional derivative is bounded, we obtain a finite bound for the solutions of the model. This bound depends on the initial function and the solution does not approach zero. An example is given illustrating the theoretical results. [ABSTRACT FROM AUTHOR]

The construction industry in New Zealand has undergone significant growth in recent years with an active commercial sector and ongoing infrastructure development projects. However, the industry has faced criticism due to failures, particularly in pipeline projects involving public infrastructure due to its underperformance, unnecessary postponement, and delay. This study, utilizing data from a ten-year plan of the Palmerston North City Council and employing document analysis techniques, examined the issues that have arisen in New Zealand's pipeline projects. The study identified government legislation, workforce, finance, and materials as major factors for the industry's underperformance. To address these issues, the study proposes various strategies and plans to improve the industry's stability; the proposal has practical implications for government and development agencies seeking the implementation of effective strategies for future projects. Furthermore, findings highlight the need for improved collaboration between the government and the industry's stakeholders, particularly in developing effective regulatory frameworks and ensuring a skilled workforce. The study provides valuable insights into the construction industry's challenges and opportunities in New Zealand, and underscores the importance of adopting a strategic approach to infrastructure development. The proposed strategies and plans can help to improve the industry's performance, thus contributing to sustainable growth and development in the sector. [ABSTRACT FROM AUTHOR]

This article aims to determine the causes of the delays in South African construction project planning, discussing the centralised hierarchical planning system factors, multiple agencies/spheres of government regarding building-permit approval factors, and systems and spheres of government/multiple agencies for improving preconstruction project planning in South Africa. It also describes a one-stop centre as a framework for improving South African preconstruction planning. The nature of planning in South Africa is influenced by many legislative measures. The delays being experienced in the educational infrastructure project have attributed to the backlogs currently existing in the delivery of basic education infrastructure. This study was conducted using a quantitative research design technique to assess the secondary data findings through primary data gathered on about 106 construction industry operatives. The primary data collected from the 106 construction operatives focused on architects, engineers, surveyors, and contractors. The researchers conducted a pilot survey with experts/professionals before an industry-wide survey as a questionnaire pretest. The finalised questionnaire was used as a data-gathering technique in the quantitative study approach. A focus group discussion was held to validate the findings. The collected information was then subjected to quantitative analysis in SPSS Version: 29.0.2.0 to verify the veracity of the research. According to the findings, a one-stop centre would enhance systems and sectors of government/multiple agencies and prevent preconstruction project-planning delays in South Africa. A centralised hierarchical planning system is essential for reducing preconstruction-planning delays and multiple agencies/sectors of the government delaying building-permit approvals. The critical research contribution is in that expanding on what is already known about preconstruction project planning in South Africa, this study shows how crucial it is to identify and understand the factors that influence preconstruction project planning in that country. The limitation, however, is that, regarding South Africa, the available literature indicates that there is a problem with systems responsible for approving construction projects. In conclusion, by proposing a structure known as the one-stop centre (OSC) to address the issues that lead to delays in preconstruction project planning in South Africa, this study offers a significant contribution. [ABSTRACT FROM AUTHOR]

In the literature, macroscopic fundamental diagram (MFD)- or network fundamental diagram-based perimeter control approaches have been demonstrated as cost-effective means to improve traffic efficiency for urban traffic networks. This article proposes a new perimeter control approach, which extends previous approaches in two aspects. First, the proposed approach optimizes the allocation of perimeter metered flow considering the heterogeneity of network traffic flow distribution, which is inversely related to network production. Second, queue management is considered by the proposed approach so as to prevent queue spillback induced by perimeter control. The proposed control approach is well advanced for field application using only loop detector data. It adopts a hierarchical framework, where the upper level controller determines the total flow entering the protected network through perimeter links based on an MFD-based feedback regulator, while the lower level controller optimizes the distribution of the total metered flow among the perimeter links based on real-time network heterogeneity and perimeter queues. The proposed approach is tested and compared with state-of-the-art perimeter control approaches, using a real traffic network developed in the microscopic simulation software VISSIM. Results demonstrate that the proposed approach significantly reduces the overall network delay. Moreover, it outperforms other perimeter control approaches by maintaining low network heterogeneity within the protected network and preventing (or delaying) queue spillback at perimeter links. [ABSTRACT FROM AUTHOR]

Stream processing is used in various fields. In the field of big data, stream aggregation is a popular processing technique, but it suffers serious setbacks when the order of events (e.g., stream elements) occurring is different from the order of events arriving to the systems. Such data streams are called “non-FIFO steams”. This phenomenon usually occurs in a distributed environment due to many factors, such as network disruptions, delays, etc. Many analyzing scenarios require efficient processing of such non-FIFO streams to meet various data processing requirements. This paper proposes an efficient scalable checkpoint-based bidirectional indexing approach, called $CPiX$ C P i X , for faster real-time analysis over non-FIFO streams. CPiX maintains the partial aggregation results in an on-demand manner per checkpoint. CPiX needs less time and space than the state-of-the-art approach. Extensive experiments confirm that CPiX can deal with out-of-order streams very efficiently and is, on average, about 3.8 times faster than the state-of-the-art approach while consuming less memory. [ABSTRACT FROM AUTHOR]

Time-domain indirect methods based on Lyapunov stability theory and linear matrix inequality techniques (LMIs) have been applied for delay-dependent stability analysis of large-scale load frequency control (LFC) schemes. This paper aims to enhance the numerical tractability of large-scale LMIs by exploiting the special characteristics of the LFC loops. First, in the typical LFC model, only a few delayed states that are directly influenced by transmission delays are distinguished from other normal system states. Hence, an improved reconstruction model is formed, based on which the delay-dependent stability condition is established with the decreased order of the LMIs and decision variables. Then, to further improve the numerical tractability of the developed stability criterion, all weighting matrices required in the augmented Lyapunov functional are enforced to have structural restrictions by proposing an extended symmetry-exploiting technique. Case studies show that the method proposed in this paper significantly improves the calculation efficiency of stability criterion established for multi-area power systems at the cost of only a minor reduction in computational accuracy. [ABSTRACT FROM AUTHOR]

Human-machine interactive systems show increasing demand for analysing fast moving objects in high-frame-rate videos. Robust foreground detection, which is able to reduce large amount of redundant background data from high-frame-rate video, becomes the essence to achieve ultra-high-speed human-machine interactions. This paper proposes a local spatial propagation based background model generation, a local linear illumination correction based background model update, and a regional central coordinates and edge keypoints constrained foreground region reselection. The three proposals make up a robust and hardware-friendly foreground detection method. Experimental results prove that the proposed hardware-friendly algorithm achieves high accuracy and robustness on various kinds of challenging cases. Meanwhile, the hardware implementation utilizes little hardware resources and achieves realtime processing of high-frame-rate (784 frame/second) video with the delay less than 1 ms/frame in image processing core. In addition, a practical system is implemented by combing a PC, a high-speed camera and a field programmable gate array (FPGA) for realworld applications. This work will significatively promote the development and application of high-speed human machine interaction. A demo of the proposed vision system working at 784 FPS is available at https://wcms.waseda.jp/em/5f84f75136a6. Note to Practitioners—This paper was motivated by the problem of high-frame-rate video contains large amount of redundant background pixels which makes ultra-high-speed human-machine interactions inaccessible. Existing approaches are mainly focused on designing complex background models, but processing speed, which is the most important issue for ultra-high-speed human-machine interactions, has received relatively little attention. This paper suggests a robust and hardware-friendly foreground detection algorithm which has been implemented as a hardware system by using an FPGA, a high-frame-rate camera, and a PC. We show that the hardware implementation utilizes less hardware resources and achieves real-time processing speed of 784 FPS with the delay less than 1 ms/frame in the image processing core. This work is a pioneering attempt of ultra-high-speed foreground detection, which will significatively speed up the wide applications of ultra-high-speed human machine interactions. [ABSTRACT FROM AUTHOR]

Owning to the sub-standards being developed by IEEE Time-Sensitive Networking (TSN) Task Group, the traditional IEEE 802.1 Ethernet is enhanced to support real-time dependable communications for future time- and safety-critical applications. Several sub-standards have been recently proposed that introduce various traffic shapers (e.g., Time-Aware Shaper (TAS), Asynchronous Traffic Shaper (ATS), Credit-Based Shaper (CBS), Strict Priority (SP)) for flow control mechanisms of queuing and scheduling, targeting different application requirements. These shapers can be used in isolation or combination and there is limited work that analyzes, evaluates, and compares their performance, which makes it challenging for end-users to choose the right combination for their applications. This paper aims at (i) quantitatively comparing various traffic shapers and their combinations, (ii) summarizing, classifying, and extending the architectures of individual and combined traffic shapers and their Network calculus (NC)-based performance analysis methods, and (iii) filling the gap in the timing analysis research on handling ATS and CBS used for different priority queues, and two novel hybrid architectures of combined traffic shapers, i.e., TAS+ATS+SP and TAS+ATS+CBS when ATS and CBS used at the same queue. A large number of experiments, using both synthetic and realistic test cases, are carried out for quantitative performance comparisons of various individual and combined traffic shapers, from the perspective of upper bounds of delay, backlog, and jitter. To the best of our knowledge, we are the first to quantitatively compare the performance of the main traffic shapers in TSN. The paper aims at supporting the researchers and practitioners in the selection of suitable TSN sub-protocols for their use cases. [ABSTRACT FROM AUTHOR]

State-of-charge (SoC) imbalance and bus voltage deviation are two of the main problems in autonomous dc microgrids. Based on this concern, this paper presents an improved dual-quadrant SoC weighted control strategy and a distributed optimization control method to achieve SoC balance, ensuring accurate power-sharing and bus voltage recovery. Firstly, this paper couples the injected/released power with the current SoC and observed average SoC value to weight the droop coefficient, which is based on the charge/discharge mode for the energy storage system. Then a secondary controller is designed based on distributed optimal control to eliminate the bus voltage deviation caused by the line impedance difference. The proposed optimal control method optimizes the average bus voltage to the nominal value and achieve accurate power-sharing by constructing the correlated variables and voltage independent intermediate variables exchanged among bulk energy storage units (ESUs). Since the voltage observer cannot accurately observe the true average bus voltage under the communication delay, the proposed distributed optimal control method without the voltage observer can ensure that the average bus voltage is optimized to the nominal value, thus improving the robustness of the control system. Finally, the correctness and effectiveness of the proposed method are verified in Simulink/MATLAB. [ABSTRACT FROM AUTHOR]

Highly active antiretroviral therapy (HAART) stands out as the most effective treatment for human immunodeficiency virus type-1 (HIV-1). While total eradication is still difficult, HAART can dramatically lower the virus's plasma viral level below the detection threshold. The activation of latently infected cells is considered to be the main obstacle to the total eradication of HIV-1 infection. This study investigates the dynamic characteristics of two generalized HIV-1 infection models taking into account the impairment of cytotoxic T lymphocytes (CTLs). These models include CD4+T cells that are latently infected and equipped with the capability to engage in cell-to-cell infection and elude immune responses. We introduce models featuring three infection pathways: virus-to-cell (VTC), latent cell-to-cell (L-CTC), and active cell-to-cell (A-CTC). The three pathways' infection rates are characterized by general functions, which cover the many types of infection rates documented in the literature. The second model integrates three distinct types of distributed-time delays. We demonstrate the validity of the suggested models, through their well-posedness. We determine the basic reproduction ratio (RO) of the systems. Lyapunov functions and LaSalle's invariance principle are employed to verify that the global stability of both the virus-free steady state (O0) and the virus-persistence steady state (Ο1). More precisely, O0 achieves global asymptotic stability when R0 ≤ 1 whereas Ο1 attains global asymptotic stability when R0 > 1-To demonstrate the impact of the parameter values on R0 we examine the sensitivity analysis. It is illustrated that R0 comprises three components, namely R0Ɛ, R0P, and R0K corresponding to the transmissions of VTC, L-CTC, and A-CTC, respectively. Thus, if the L-CTC pathway is disregarded in the HIV-1 infection model, R0 be underestimated, which could lead to inadequate or erroneous medication therapy focused on eradicating HIV-1 within the body. To demonstrate the associated mathematical outcomes, we conduct numerical simulations through an illustrative example. Specifically, we delve into how the dynamics of HIV-1 are influenced by both immune impairment and time delay. Our findings suggest a significant role of reduced immunity in the progression of the infection. Furthermore, time delays possess the potential to markedly reduce R0, thereby impeding the replication of HIV-1. [ABSTRACT FROM AUTHOR]

Connected and automated vehicles (CAVs) are being developed and designed to operate on existing roads. Their safe and efficient operation during roadworks, where traffic management measures are often introduced, is crucial. Two alternative measures are commonly applied during roadworks on motorways: (i) closing one or multiple lanes (ii) narrowing one or all lanes. The former can cause delays and increased emissions, while the latter can pose safety risks. This study uses a VISSIM‐based traffic microsimulation to compare the effectiveness of these two strategies on traffic efficiency and safety, considering various market penetration rates (MPR) of CAVs. The model was calibrated and validated with the data collected from M1 motorway in the United Kingdom. Results show that average delays per vehicle‐kilometre‐travelled decreased from 102.7 to 2.5 s (with lane closure) and 23.6 to 0.6 s (with narrow lanes) with 0% and 100% CAV MPR, respectively. Moreover, safety in narrow lanes improved by 4.8 times compared to 1.5 times improvement in lane closure with a 100% CAV MPR; indicating that narrow lanes would result in better safety performance. These findings could assist transport authorities in designing temporary traffic management measure that results in better CAV performance when navigating through roadworks. [ABSTRACT FROM AUTHOR]

Replacement policies have an important role in the functioning of the cache memory of processor cores. The implementation of a successful policy allows us to increase the performance of the processor core and the computer system as a whole. Replacement policies are most often evaluated by the percentage of cache hits during the cycles of the processor bus when accessing the cache memory. The policies that focus on replacing the Least Recently Used (LRU) or Least Frequently Used (LFU) elements, whether instructions or data, are relevant for use. It should be noted that in the paging cache buffer, the above replacement policies can also be used to replace address information. The pseudo LRU (PLRU) policy introduces replacing based on approximate information about the age of the elements in the cache memory. The hardware implementation of any replacement policy algorithm is the circuit. This hardware part of the processor core has certain characteristics: the latency of the search process for a candidate element for replacement, the gate complexity, and the reliability. The characteristics of the PLRUt and PLRUm replacement policies are synthesized and investigated. Both are the varieties of the PLRU replacement policy, which is close to the LRU policy in terms of the percentage of cache hits. In the current study, the hardware implementation of these policies is evaluated, and the possibility of adaptation to each of the policies in the processor core according to a selected priority characteristic is analyzed. The dependency of the rise in the delay and gate complexity in the case of an increase in the associativity of the cache memory is shown. The advantage of the hardware implementation of the PLRUt algorithm in comparison with the PLRUm algorithm for higher values of associativity is shown. [ABSTRACT FROM AUTHOR]

Concurrent multipath transfer (CMT) is a transport layer protocol used for transferring data over multiple paths concurrently. In the case of asymmetric paths, the dissimilarity of delay, bandwidth, and loss rate among paths leads to challenges such as out‐of‐order packets, receiver buffer blocking, and throughput reduction. A framework that uses the end‐to‐end delay of paths to distribute the packets over asymmetric paths in ordering policy is proposed. The proposed framework detects network congestion in the assigned path and reduces the congestion window. Furthermore, the proposed framework predicts receiver buffer blocking and deactivates the highest delay path that causes this problem. The simulation results show that the proposed framework achieves highest throughput, lower entropy and lower average application end‐to‐end delay than the previous algorithms. [ABSTRACT FROM AUTHOR]

This research investigates the edge-based asymptotic synchronization of delayed complex dynamical networks with reaction–diffusions and by an edge-based adaptive pinning control technique. Sufficient conditions for reaction–diffusion networks to realize synchronization are provided by Green's formula, Wirtinger inequality, inequality analysis techniques, and contradiction methods. The results show that network synchronization can be achieved by pinning any edge of the network (the choice of edge is arbitrary), which greatly reduces the difficulty of control. Lastly, a series of numerical examples illustrating the theoretical findings is provided. [ABSTRACT FROM AUTHOR]

This letter proposes novel approximate 4:2 compressors developed using input reordering circuits and input combination probabilities. The input reordering circuit is used to reduce the hardware complexity of the proposed designs. This letter proposes two designs of approximate 4:2 compressors. This compressor is used in designing an approximate multiplier. The proposed multiplier designs utilize less energy than the already published ones due to acceptable inaccurate output/precision, which are best suitable for image processing applications. The proposed multiplier designs MUL1, MUL2, MUL3, and MUL4 saves 22.75%, 21.95%, 11.57%, and 8.95% energy than the best of the existing design (Kong and Li, 2021). [ABSTRACT FROM AUTHOR]

In this paper, we formulate and study a fractional-order network model with four neurons, bidirectional ring structure and self-delay feedback. For the scenario of non-identical neurons, we develop a new algebraic technique to deal with the characteristic equation with e − 4 s τ (τ is the self-feedback delay) term and thus establish the easy-to-check criteria to determine the Hopf bifurcation point of self-feedback delay by fixing communication delay in its stable interval. For the scenario of identical neurons, we apply the crossing curves method to the fractional functional equations and thus procure the Hopf bifurcation curve. The obtained results accommodate the fact that the model cannot preserve its stability behavior when the self-feedback delay crosses the Hopf bifurcation point in the positive direction. Finally, we deliberate on the correctness of our methodology through two demonstration examples. [ABSTRACT FROM AUTHOR]

The general delay Hopfield neural network is studied. We consider the case of time-varying delay, continuously distributed delays, time-varying coefficients, and a special type of a Riemann–Liouville fractional derivative (GRLFD) with an exponential kernel. The kernels of the fractional integral and the fractional derivative in this paper are Sonine kernels and satisfy the first and the second fundamental theorems in calculus. The presence of delays and GRLFD in the model require a special type of initial condition. The applied GRLFD also requires a special definition of the equilibrium of the model. A constant equilibrium of the model is defined. An inequality for Lyapunov type of convex functions with the applied GRLFD is proved. It is combined with the Razumikhin method to study stability properties of the equilibrium of the model. As a partial case we apply quadratic Lyapunov functions. We prove some comparison results for Lyapunov function connected deeply with the applied GRLFD and use them to obtain exponential bounds of the solutions. These bounds are satisfied for intervals excluding the initial time. Also, the convergence of any solution of the model to the equilibrium at infinity is proved. An example illustrating the importance of our theoretical results is also included. [ABSTRACT FROM AUTHOR]

In this paper, we propose a class of octonion-valued neural networks with leakage delays and mixed delays. Considering that the multiplication of octonion algebras does not satisfy the associativity and commutativity, we can obtain the existence and global exponential stability of weighted pseudo almost periodic solutions for octonion-valued neural networks with leakage delays and mixed delays by using the Banach fixed point theorem, the proof by contradiction and the non-decomposition method. Finally, we will give one example to illustrate the feasibility and effectiveness of the main results. [ABSTRACT FROM AUTHOR]

The Chang'E‐5 (CE5) ascender achieved lunar orbit autonomous rendezvous and docking with orbiter‐returner successfully on 5 December 2020. Same‐beam Very Long Baseline Interferometry (VLBI) (SBI) observations were performed for the first time for autonomous rendezvous and docking in lunar orbit. In this paper, by studying the CE5 rendezvous and docking data observed by the Chinese VLBI network and analyzing the residual differential phase delay of the autonomous control phase, we successfully captured the maneuver of the 5 km holding of the orbiter‐returner. The differential phase delay (DPD) data of the far‐range guidance phase were used to perform orbit determination of the ascender and orbiter‐returner successfully. The results of orbit determination show that the DPD data can improve the relative position accuracy between the ascender and the orbiter‐returner, and the residual root mean square of the DPD data is 5 ps. Furthermore, when one of the probes has only DPD data, its orbit can also be determined. Key Points: The Chinese Very Long Baseline Interferometry (VLBI) network observes the autonomous rendezvous and docking of Chang'E‐5 in lunar orbit using Same‐beam VLBIThe residual differential phase delay monitors the maneuver of the orbiter‐returner in the autonomous control phaseThe differential phase delay improves the relative position accuracy between two probes in the far‐range guidance phase [ABSTRACT FROM AUTHOR]

Background Belize is a middle-income Caribbean country with poorly described cancer epidemiology and no comprehensive cancer care capacity. In 2018, GO, Inc., a US-based NGO, partnered with the Ministry of Health and the national hospital in Belize City to create the first public oncology clinic in the country. Here, we report demographics from the clinic and describe time intervals to care milestones to allow for public health targeting of gaps. Patients and Methods Using paper charts and a mobile health platform, we performed a retrospective chart review at the Karl Heusner Memorial Hospital (KHMH) clinic from 2018 to 2022. Results During this time period, 465 patients with cancer presented to the clinic. Breast cancer (28%) and cervical cancer (12%) were most common. Most patients (68%) presented with stage 3 or 4 disease and were uninsured (78%) and unemployed (79%). Only 21% of patients ever started curative intent treatment. Median time from patient-reported symptoms to a biopsy or treatment was 130 and 189 days. For the most common cancer, breast, similar times were seen at 140 and 178 days. Time intervals at the clinic: <30 days from initial visit to biopsy (if not previously performed) and <30 days to starting chemotherapy. Conclusion This study reports the first clinic-based cancer statistics for Belize. Many patients have months between symptom onset and treatment. In this setting, the clinic has built infrastructure allowing for minimal delays in care despite an underserved population. This further affirms the need for infrastructure investment and early detection programs to improve outcomes in Belize. [ABSTRACT FROM AUTHOR]

Absolute time synchronization is a basic issue in wireless communication. With the advent of 5G, many emerging vertical industry applications have put forward demands for timing accuracy over air interface. High Precision Timing method over Air Interface based on PHY Layer Signals (TAP) is proposed for mobile networks. It is designed to provide microsecond level timing accuracy at a relatively low cost compared to the existing timing methods, such as GNSS, NTP, PTP, etc. The purpose of this paper is to comprehensively improve TAP, including timing accuracy, stability and compatibility, so as to promote its practical application. This paper proposes improvements to TAP from four aspects: timing algorithm, timing pilot signal, terminal timing process and timing parameters determination. We improve the TAP’s deficiencies in delay estimation, delay compensation accuracy and real-time matching of timing information. We implement the workflow of TAPv2 for UE based on FPGA. Finally, we settle the problem of TAP parameters determination by applying a DQN method. The simulations and tests not only show that the DQN model can effectively determine the TAP parameters, but also show TAPv2 can achieve higher accuracy and stability than TAP in multiple scenarios based on the interaction with baseband. [ABSTRACT FROM AUTHOR]

Due to the non-uniform geographic distribution and time-varying characteristics of the ground traffic request, how to make full use of the limited beam resources to serve users flexibly and efficiently is a brand-new challenge for beam hopping satellite systems. The conventional greedy-based beam hopping methods do not consider the long-term reward, which is difficult to deal with the time-varying traffic demand. Meanwhile, the heuristic algorithms such as genetic algorithm have a slow convergence time, which can not achieve real-time scheduling. Furthermore, existing methods based on deep reinforcement learning (DRL) only make decisions on beam patterns, lack of the freedom of bandwidth. This paper proposes a dynamic beam pattern and bandwidth allocation scheme based on DRL, which flexibly uses three degrees of freedom of time, space and frequency. Considering that the joint allocation of bandwidth and beam pattern will lead to an explosion of action space, a cooperative multi-agents deep reinforcement learning (MADRL) framework is presented in this paper, where each agent is only responsible for the illumination allocation or bandwidth allocation of one beam. The agents can learn to collaborate by sharing the same reward to achieve the common goal, which refers to maximize the throughput and minimize the delay fairness between cells. Simulation results demonstrate that the offline trained MADRL model can achieve real-time beam pattern and bandwidth allocation to match the non-uniform and time-varying traffic request. Furthermore, when the traffic demand increases, our model has a good generalization ability. [ABSTRACT FROM AUTHOR]

In this work, the following stochastic Rayleigh-Stokes equations are considered ∂t[x(t) + f(t, xρ(t))] = (A + ...∂tβ A) [x(t) + f(t, xρ(t))] + g(t, xΤ (t)) + B(t, xξ(t)) ... (t), which involve the Riemann-Liouville fractional derivative in time, delays and standard Brownian motion. Under two different conditions for the non-linear external forcing terms, two existence and uniqueness results for the mild solution are established respectively, in the continuous space C([-h, T]; Lp(Ω, Vq)), p ≥ 2, q ≥ 0. Our study was motivated and inspired by a series of papers by T. Caraballo and his colleagues on stochastic differential equations containing delays. [ABSTRACT FROM AUTHOR]

With the rapid advancement of intelligent transportation systems (ITS) and vehicular communications, vehicular edge computing (VEC) is emerging as a promising technology to support low-latency ITS applications and services. In this paper, we consider the computation offloading problem from mobile vehicles/users in a heterogeneous VEC scenario, and focus on the network- and base station selection problems, where different networks have different traffic loads. In a fast-varying vehicular environment, computation offloading experience of users is strongly affected by the latency due to the congestion at the edge computing servers co-located with the base stations. However, as a result of the non-stationary property of such an environment and also information shortage, predicting this congestion is an involved task. To address this challenge, we propose an on-line learning algorithm and an off-policy learning algorithm based on multi-armed bandit theory. To dynamically select the least congested network in a piece-wise stationary environment, these algorithms predict the latency that the offloaded tasks experience using the offloading history. In addition, to minimize the task loss due to the mobility of the vehicles, we develop a method for base station selection. Moreover, we propose a relaying mechanism for the selected network, which operates based on the sojourn time of the vehicles. Through intensive numerical analysis, we demonstrate that the proposed learning-based solutions adapt to the traffic changes of the network by selecting the least congested network, thereby reducing the latency of offloaded tasks. Moreover, we demonstrate that the proposed joint base station selection and the relaying mechanism minimize the task loss in a vehicular environment. [ABSTRACT FROM AUTHOR]

In this paper, we propose a receiver architecture capable of compensating for a time-varying signal distortion induced by the transmitter analog components. In the proposed architecture, the novel transmitter distortion compensating (TDC) block is implemented outside of the feedback control loop of the adaptive equalizer to suppress the feedback delay by optimizing the parameter used in the least mean square (LMS) algorithm. The proposed TDC block is designed for compensating for the DC offset, the IQ amplitude imbalance, the IQ orthogonality error, and the IQ timing skew. Our simulation results show that the proposed scheme significantly reduces the required signal-to-noise ratio penalty from the theoretical limit, which is imposed due to the transmitter components distortion. Furthermore, our theoretical analysis confirms that the delay induced in the feedback loop of the adaptive equalizer determines the upper bound of the LMS step size under the stable condition, hence allowing us to maximize the tracking speed of our receiver. [ABSTRACT FROM AUTHOR]

Flight delay prediction has recently gained growing popularity due to the significant role it plays in efficient airline and airport operation. Most of the previous prediction works consider the single-airport scenario, which overlooks the time-varying spatial interactions hidden in airport networks. In this paper, the flight delay prediction problem is investigated from a network perspective (i.e., multi-airport scenario). To model the time-evolving and periodic graph-structured information in the airport network, a flight delay prediction approach based on the graph convolutional neural network (GCN) is developed in this paper. More specifically, regarding that GCN cannot take both delay time-series and time-evolving graph structures as inputs, a temporal convolutional block based on the Markov property is employed to mine the time-varying patterns of flight delays through a sequence of graph snapshots. Moreover, considering that unknown occasional air routes under emergency may result in incomplete graph-structured inputs for GCN, an adaptive graph convolutional block is embedded into the proposed method to expose spatial interactions hidden in airport networks. Through extensive experiments, it has been shown that the proposed approach outperforms benchmark methods with a satisfying accuracy improvement at the cost of acceptable execution time. The obtained results reveal that deep learning approach based on graph-structured inputs have great potentials in the flight delay prediction problem. [ABSTRACT FROM AUTHOR]

Spatial modulation (SM) is one special type of multiple-input multiple-output (MIMO) technique whose advantage is that only one radio-frequency (RF) chain is needed. Recently, the so-called cross Z-complementary pair (CZCP) was proposed as the SM training sequence. Optimal channel estimation performance over frequency-selective channels can be achieved since the CZCPs have the specific zero correlation zone (ZCZ) for auto-correlation and cross-correlation sums. However, the ZCZ width of the CZCP is theoretically upper bounded by half sequence length. In this paper, the CZCP is extended to the cross Z-complementary set (CZCS) to have larger ZCZ width which can be used in SM to combat larger delay spread. Several generic constructions of CZCSs with large ZCZ widths and flexible lengths are proposed in this paper. Even the perfect CZCS, whose ZCZ width has the maximum value, can be obtained. Numerical simulations demonstrate that the proposed CZCS-based training sequence can tolerate large delay spreads to improve the channel estimation performance in SM. [ABSTRACT FROM AUTHOR]

Future communication networksrequire higher bandwidth, greater coverage, and better throughput. The Space-Air-Ground Integrated Network (SAGIN) has the advantage of wide-area coverage and can cover global communications. It can meet the needs of network resources for maritime activities and remote mountainous areas, which is of great significance to the realization of a new generation of communications networks. With the development of the network and the emergence of delay-sensitive applications such as the Internet of Things, improving the delay performance of the system has received extensive attention. SAGIN involves multiple networks and is more complex than other networks. If there is no reasonable management between different networks, it is easy to lead to difficult link deployment and high time delay. On the basis of research and customization of SFC technology, it can provide a wide range of services and other advantages. It has significant performance in application scenarios involving multi network integration. In order to solve the above problems, this paper studies the SAGIN architecture of SFC based on business types. A service function chain mapping method based on delays prediction is proposed. Calculate the delay of the deployment path and select the path with the lowest delay as the SFC mapping path. The service model is constructed according to the mapping path, and the network slices are divided based on the service type. The simulation results show that the SFC mapping algorithm based on time delay prediction is compared with the traditional SFC mapping scheme. The algorithm does not affect other indicators, the CPU resource utilization rate is 27.8 $\%$ higher, and the link resource utilization rate is 22.7 $\%$ higher. The service acceptance rate increased by 21.5 $\%$ , the latency performance increased by 38.2 $\%$ , and the total resource consumption is reduced by 25.2 $\%$. [ABSTRACT FROM AUTHOR]

Connected automated driving technologies have shown substantial benefits to improve the safety and efficiency of traffic. However, connected mixed traffic, which involves both connected automated vehicles and connected human-driven vehicles, is more foreseen for the realistic case in the near future. This brings new challenges because of the complexity of human elements in the system. In addition, the communication constraints in realistic connectivity such as random delays and packet losses bring even more challenges to the system. Therefore, this paper proposes a new anticipative and predictive automated vehicle control approach in connected mixed traffic. The approach first anticipates the states of surrounding vehicles including human-driven vehicles, and then integrates the anticipation into the predictive control of automated vehicles, which can help improve the control performance and also handle the communication constraints. An inverse model predictive control (IMPC) based anticipation approach has been proposed. The proposed approach, together with constant speed (CS), intelligent driver model (IDM) and artificial neural network (ANN) based anticipation methods are integrated with model predictive control (MPC) for automated vehicle control. The approaches have been tested in human-in-the-loop experiments and the results show that the integration with a newly proposed IMPC based anticipation has shown the best performance in terms of accuracy, efficiency and scalability in connected mixed traffic with both ideal and constrained communications. [ABSTRACT FROM AUTHOR]

Motivated by applications in data center networks, in this paper, we study the problem of scheduling in an input queued switch. While throughput maximizing algorithms in a switch are well-understood, delay analysis was developed only recently. It was recently shown that the well-known MaxWeight algorithm achieves optimal scaling of mean queue lengths in steady state in the heavy-traffic regime, and is within a factor less than 2 of a universal lower bound. However, MaxWeight is not used in practice because of its high time complexity. In this paper, we study several low complexity algorithms and show that their heavy-traffic performance is identical to that of MaxWeight. We first present a negative result that picking a random schedule does not have optimal heavy-traffic scaling of queue lengths even under uniform traffic. We then show that if one picks the best among two matchings or modifies a random matching even a little, using the so-called flip operation, it leads to MaxWeight like heavy-traffic performance under uniform traffic. We then focus on the case of non-uniform traffic and show that a large class of low time complexity algorithms have the same heavy-traffic performance as MaxWeight, as long as it is ensured that a MaxWeight matching is picked often enough. We also briefly discuss the performance of these algorithms in the large scale heavy-traffic regime when the size of the switch increases simultaneously with the load. Finally, we perform empirical study on a new algorithm to compare its performance with some existing algorithms. [ABSTRACT FROM AUTHOR]

With the rapid growth of renewable energy and power electronic loads, voltage source converters (VSCs) have been commonly applied in different VSCs-based power systems, which also bring in stability issues due to their power electronic characteristics. The impedance-based stability theory and corresponding reshaping method can be used to analyze and solve system stability issue. However, dc stability issue in VSCs-based power systems becomes more complicated when considering ac/dc coupling relationship. This paper proposes an improved reshaping control strategy based on the detailed impedance model considering grid impedance and control delay. The influence of grid impedance, control delay and control parameters of VSC on dc stability are further analyzed to identify the cause of potential resonance risk. The proposed impedance reshaping method considers the trade-off between stability improvement and control performance, and compensates the impacts of grid impedance and control delay at the same time. The validity of stability analysis and reshaping method is further verified through the simulation and experimental results. [ABSTRACT FROM AUTHOR]

This paper analyzes the end-to-end delay performance in an edge-computing scenario where a set of Internet of Things devices (IoTDs) access the computation facilities of an Edge Node by means of a 5G based network. In particular, the paper deals with a two power levels slotted Aloha non-orthogonal-multiple-access (NOMA) scheme and formulates a stochastic end-to-end delay bound, in terms of complementary cumulative probability distribution, by resorting to the application of the martingale theory. In order to validate the proposed analysis, the paper proposes comparisons between the achieved analytical predictions and actual values derived by resorting to extensive computer simulations. Furthermore, the well known Boole bound has been formulated and compared with the proposed Martingale approach to highlight the better behavior of the proposed solution. [ABSTRACT FROM AUTHOR]

A scalar nonlinear impulsive differential equation with a delay and generalized proportional Caputo fractional derivatives (IDGFDE) is investigated. The linear boundary value problem (BVP) for the given fractional differential equation is set up. The explicit form of the unique solution of BVP in the special linear case is obtained. This formula is a generalization of the explicit solution of the case without any delay as well as the case of Caputo fractional derivatives. Furthermore, this integral form of the solution is used to define a special proportional fractional integral operator applied to the determination of a mild solution of the studied BVP for IDGFDE. The relation between the defined mild solution and the solution of the BVP for the IDGFDE is discussed. The existence and uniqueness results for BVP for IDGFDE are proven. The obtained results in this paper are a generalization of several known results. [ABSTRACT FROM AUTHOR]