Delay Scenario Research Articles

Metro stop-skipping rescheduling optimization considering passenger waiting time fairness

ABSTRACT In urban metro systems, unexpected events often occur to cause discordance in the planned timetable and delay in passenger travel. Therefore, this study focuses on the timetable rescheduling problem by adopting a stop-skipping strategy during the off-peak period. In addition, there are a number of existing optimization models that minimize the total passenger waiting time, which can cause fairness issues for a small group of passengers having longer waiting time at some stations. In this study, a rescheduling model is proposed to consider passenger waiting time fairness and train travel time cost. This model is tested with a randomly designed delay scenario of Nanjing Metro Line 2, which can be efficiently solved by a designed iterative algorithm based on decomposition method. Compared to the standard stop pattern, the result shows that the stop-skipping pattern can better alleviate the impact of sudden delays, while simultaneously ensuring the passenger waiting time fairness.

Revenue Acceleration by Temporary Rental Pump Option in Plato Platform: Case Study in PT. Prominent Petro

This article explores the financial analysis and risk assessment of a company called PT. Prominent Petro, which is considering accelerating production in one of its production facilities, Plato Platform, by installing a temporary rental pump while waiting for the completion of a new permanent pump installation. The financial analysis used Capital Budgeting Technique with Discounted Cash Flow method. The risk analysis was performed by using Sensitivity Analysis and Monte Carlo analysis covering two timeframe scenarios of permanent pump installation, On Time Scenario and Delay Scenario. In On-Time Scenario, the results of the analysis showed that the temporary rental pump option would provide higher financial returns to the company, with an estimated NPV of 6.998 million USD, 7.7% higher than the baseline (no rental) option. Sensitivity analysis revealed that the most significant factor affecting the company's financial return was the realization of gas production. Monte Carlo analysis demonstrated that both Rental and No Rental investment proposals were low-risk and robust, with the rental option having higher risk and return. In Delay Scenario, without temporary rental pump, project financial return will decrease from 6.496 million USD to 5.907 million USD, with the discounted payback period delayed from 1.17 years to 1.80 years. However, the utilization of temporary rental pump option either for six- or twelve-months duration will improve the financial return to 6.4 million USD, similar with financial return of baseline option without delay. Furthermore, a decision tree analysis was developed to estimate the expected monetary value for the company. The analysis concluded that the rental pump option provided a better financial return, with an expected monetary value of $6.484 Million. Overall, the findings suggest that the temporary rental pump option give better financial result for the company.

Redefining Neurodevelopmental Impairment: Perspectives of Very Preterm Birth Stakeholders.

Children born very preterm are at risk of severe neurodevelopmental impairment, a composite endpoint that includes cerebral palsy, developmental delay, and hearing and visual impairment defined by medical professionals. We aimed to describe preterm birth stakeholders' perspectives on this classification. Ten clinical scenarios describing 18-month-old children with different components of severe neurodevelopmental impairment and one scenario of a typically developing child (control) were distributed to parents and stakeholders using a snowball sampling technique. For each scenario, participants rated health on a scale from 0 to 10 and whether the scenario represented a severe condition. Results were analyzed descriptively and mean differences from the control scenario were compared using a linear mixed-effects model. Stakeholders (number = 827) completed 4553 scenarios. Median health scores for each scenario varied from 6 to 10. The rating for the cerebral palsy and language delay scenario was significantly lower (mean difference -4.3; 95% confidence interval: -4.4, -4.1) than the control. The proportion of respondents rating a scenario as "severe" ranged from 5% for cognitive delay to 55% for cerebral palsy and language delay. Most participants disagreed with the rating used in research to describe severe neurodevelopmental impairment in preterm children. The term should be redefined to align with stakeholder perceptions.

Impact of timing to initiate adjuvant therapy on survival of elderly glioblastoma patients using the SEER-Medicare and national cancer databases

The optimal time to initiate adjuvant therapy (AT) in elderly patients with glioblastoma (GBM) remains unclear. We investigated the impact of timing to start AT on overall survival (OS) using two national-scale datasets covering elderly GBM populations in the United States. A total of 3159 and 8161 eligible elderly GBM patients were derived from the Surveillance, Epidemiology and End Results (SEER)—Medicare linked dataset (2004–2013) and the National Cancer Database (NCDB) (2004–2014), respectively. The intervals in days from the diagnosis to the initiation of AT were categorized based on two scenarios: Scenario I (quartiles), ≤ 15, 16–26, 27–37, and ≥ 38 days; Scenario II (median), < 27, and ≥ 27 days. The primary outcome was OS. We performed the Kaplan–Meier and Cox proportional hazards regression methods for survival analysis. A sensitivity analysis was performed using Propensity Score Matching (PSM) method to achieve well-balanced characteristics between early-timing and delayed-timing in Scenario II. Improved OS was observed among patients who underwent resection and initiated AT with either a modest delay (27–37 days) or a longer delay (≥ 38 days) compared to those who received AT immediately (≤ 15 days) from both the SEER-Medicare dataset [adjusted hazard ratio (aHR) 0.74, 95% CI 0.64–0.84, P < 0.001; and aHR 0.81, 95% CI 0.71–0.92, P = 0.002] and the NCDB (aHR 0.83, 95% CI 0.74–0.93, P = 0.001; and aHR 0.87, 95% CI 0.77–0.98, P = 0.017). The survival advantage is observed in delayed-timing group as well in Scenario II. For elderly patients who had biopsy only, improved OS was only detected in a longer delay (Scenario I: ≥ 38 days vs. ≤ 15 days) or the delayed-timing group (Scenario II: ≥ 27 days vs. < 27 days) in the NCDB while no survival difference was seen in SEER-Medicare population. For the best timing to start AT in elderly GBM patients, superior survivals were observed among those who had craniotomy and initiated AT with a modest (27–37 days) or longer delays (≥ 38 days) following diagnosis using both the SEER-Medicare and NCDB datasets (Scenario I). Such survival advantage was confirmed when categorizing delayed-timing vs. early-timing with the cut-off at 27 day in both datasets (Scenario II). The increased likelihood of receiving delayed AT (≥ 27 days) was significantly associated with tumor resection (STR/GTR), years of diagnosis after 2006, African American and Hispanics races, treatments at academic facilities, and being referred. There is no difference in timing of AT on survival among elderly GBM patients who had biopsy in the SEER-Medicare dataset. In conclusion, initiating AT with a modest delay (27–37 days) or a longer delay (≥ 38 days) after craniotomy may be the preferred timing in the elderly GBM population.

Development and validation of a framework for preventing and mitigating construction delay using 4D BIM platform in Bangladeshi construction sector

PurposeAs a developing nation, Bangladesh still has scarce technological applications in the construction sector, which results in construction delays. This paper aims to propose a framework that will diminish manual labor, reduce human error and apply four-dimensional (4D) building information modeling (BIM)-based solutions to mitigate and prevent construction project delays.Design/methodology/approachFirst, a systematic literature review was conducted on analyzing the construction delay scenario in the context of Bangladesh and other countries. Next, a 4D BIM-based framework was developed using Autodesk Navisworks Manage. Finally, it was used to run on-site simulations on an ongoing construction project which faced delays because of design errors and inefficient planning.FindingsAffirmative results were found from applying these methods through real-time project simulation. The current status of the project and the status after using BIM technology were compared. It was observed that during both the preconstruction and execution phases, the application of 4D BIM could reduce the delay posed by design error and inefficient planning.Practical implicationsThe project manager and the design engineers can use these frameworks to review their projects. For the design engineers, the preconstruction phase portion of the framework will help identify the probable errors in the design. For the project managers, keeping track of time using the execution phase portion of the framework will be resourceful.Originality/valueTo the best of the authors’ knowledge, this study is the first to assess the significant delay factors endemic in Bangladesh and develop a BIM-based technological solution. This study is solely dedicated to reforming the construction techniques in Bangladesh through the application of 4D BIM technology.

Timing of transition from open-pit to underground mining: A simultaneous optimisation model for open-pit and underground mine production schedules

Generally, shallow deposits are mined through open-pit mining and where the deposits are extended to a substantial depth, there is a potential for a combination of open-pit and underground mining methods. In this case, mine planning and optimisation play a significant role in the decision-making. This paper proposes a mixed-integer programming model to obtain the optimal transition point and the transition period from open-pit to underground mining, maximizing the project net present value considering crown pillar placement and development cost. An implementing at a three-dimensional case study generates the optimal transition point and period and an optimal production schedule for both open-pit and underground operations. The implementation considers three scenarios: transition point only (scenario 1), transition point and period without production delay (scenario 2), and transition point and period with two-period production delay during the transition (scenario 3). The optimal transition point for scenario 1 is 315 m and for scenarios 2 and 3 is 360 m below the surface.

Modelling cascade dynamics of passenger flow congestion in urban rail transit network induced by train delay

A research into congestion propagation mechanism of urban rail transit passenger flow in train delay scenario is of great significance to the formulation of coordinated limitation measures of passenger flow among the operation lines in urban rail transit networks. This paper presents a methodology for modelling cascade dynamics of passenger flow congestion. In this method, firstly, a computing method of network passenger flow states based on load entropy is proposed to describe the overall load conditions of passenger flow in the network. Secondly, a rail transit network is developed and the computation formulas of load and capacity of nodes have been established combining with a comprehensive consideration of nodes’ topological passenger flow attributes. Thirdly, Trip Betweenness Centrality of nodes is proposed and calculated. Considering the function of rail transit line capacity and load distribution strategy, the passenger flow congestion in train delay scenario is established to calculate cascade dynamics of congestion and the state transition of urban rail transit network. A real case study on Beijing Metro Line 10 is used to demonstrate the proposed methodology. The results show that the load values of nodes and the distances from the initial failure nodes can be determined for the spreading scope of passenger flow congestion in disrupted metro line and adjacent metro lines.

Bernoulli Trial in Gauging the Quantity Surveyors’ Standpoint on Concurrent Delays

It is not off beam to contend that concurrent delays are a contentious arena in construction claims where anecdotal experience-based approach has been evident among the practitioners. Assessing concurrent delay in relation to extension of time and delay damages is often complicated. The aim of the research is to recognize an industry-accepted precedent as to concurrent delays, from the quantity surveyor perspective. The objectives are to identify the ‘evaluators’ view on concurrent delay as a ‘phenomenon’ in the construction industry, gauge the industry practitioner’s view on the treatment on concurrent delay in terms of ratifying time extension and prolongation costs and finally to see whether a consensus is truly available. The authors in this paper offer a key insight into claims using a quantitative approach by effectively recommending a convincing solution in terms of either yes or no. This is done by encapsulating a concurrent delay scenario and asking consulting quantity surveyors to add their experience and offer their views through fully structured questionnaires. The questions were to examine, whether there exists a concurrent delay, time is excusable so that concurrent delay period once identified is added to the period of extension and finally, whether the costs on prolongation due to concurrent delays are compensable. Binomial distribution is used to model the probability and gauge the perception where a series of discrete trials in this research was conducted and each individual trial had either agreement or otherwise. In this way, a new insight into the attitudes of ‘evaluators’ to claims is obtained and common areas of agreement and disagreement are identified. It was found that claims consultants have a greater appreciation of the ways in which claims are eventually settled. Further, the authors have noted that assessing concurrent delay is often problematic. There is no single accepted definition of concurrent delay.&#x0D; Keywords: Claims; Concurrent delay; Scenario-based

Statistical Model Checking of Common Attack Scenarios on Blockchain

Blockchain technology has developed significantly over the last decade. One of the reasons for this is its sustainability architecture, which does not allow modification of the history of committed transactions. That means that developers should consider blockchain vulnerabilities and eliminate them before the deployment of the system. In this paper, we demonstrate a statistical model checking approach for the verification of blockchain systems on three real-world attack scenarios. We build and verify models of DNS attack, double-spending with memory pool flooding, and consensus delay scenario. After that, we analyze experimental results and propose solutions to avoid these kinds of attacks.

Impact of Coronavirus Disease 2019 Pandemic on Viral Hepatitis Elimination: What Is the Price?

In 2016, the World Health Organization developed a plan for viral hepatitis elimination by 2030. Globally, control of hepatitis B virus (HBV) and hepatitis C virus (HCV) are the most challenging aspects of viral hepatitis elimination. In many developed countries elimination of HBV could be targeted to special populations mostly immigrants from low resource settings. Elimination of HCV, however, remains a challenge globally. Barriers to HCV elimination include high cost of medications and the ability to engage specific at-risk populations as well as individuals who are out of medical care. In the context of the coronavirus disease 2019 (COVID-19) pandemic, treatment access and screening have been further negatively impacted by social distancing rules and COVID-19-related anxieties. This threatens to throw most countries off course in their elimination efforts. Before the pandemic, some states in the United States had scaled up their elimination efforts with plans to ramp up testing and treatment using Netflix-like payment models for HCV direct acting antiviral drugs. Most of these efforts have stalled on account of the health system's focus on COVID-19 control. To prevent further delays in achieving elimination targets, programs would need to explore new models of care that address COVID-19-related access hurdles. Systems that leverage technologies such as telemedicine and self-testing could help maintain treatment levels. Mathematical models estimate that COVID-19-related delays in 2020 could lead to 44,800 hepatocellular cancers and 72,300 liver-related deaths for the next decade.

Decision support system for the irregular flight recovery problem

In this paper, we describe a data-driven approach to the irregular flight recovery problem. By imitating the decision process of dispatchers, we develop a quantitative mechanism to evaluate the disrupted flight and to provide easily adopted recovery suggestions. Our method consists of two steps. The first step is to establish a scoring system based on interviews, questionnaires, and operational data. Specifically, an irregular flight will be assigned a real-time score representing the importance of the flight and the impact of its current status. This score is also used to evaluate the necessity of the immediate recovery of the irregular flight. The second step is to generate feasible adjustment plan, which decrease the total scores of the related flights. Having validated by 306 manually recorded recovery actions, the scoring system successfully explains most of the recovery actions from dispatchers, meaning that the scoring system is consistent with the airline recovery strategy. To further demonstrate the recovery method's feasibility and response time, we also conducted tests based on one-day flight schedule simulation containing 92 flights and 7 historical cases from one Chinese airline. These tests prove the feasible adjustment plans can be generated in real-time, help airlines mitigate disruption effects to the network and reduce their decision process by 5–10 min in each delay scenario.

Hierarchical Capacity Provisioning for Fog Computing

The concept of fog computing is centered around providing computation resources at the edge of the network, thereby reducing the latency and improving the quality of service. However, it is still desirable to investigate how and where at the edge of the network the computation capacity should be provisioned. To this end, we propose a hierarchical capacity provisioning scheme. In particular, we consider a two-tier network architecture consisting of shallow and deep cloudlets and explore the benefits of hierarchical capacity provisioning based on queuing analysis. Moreover, we explore two different network scenarios in which the network delay between the two tiers is negligible and the case that the deep cloudlet is located somewhere deeper in the network and thus the delay is significant. More importantly, we model the first network delay scenario with bufferless shallow cloudlets and the second scenario with finite-size buffer shallow cloudlets, and formulate an optimization problem for each model. We also use stochastic ordering to solve the optimization problem formulated for the first model and an upper bound-based technique is proposed for the second model. The performance of the proposed scheme is evaluated via simulations in which we show the accuracy of the proposed upper bound technique and the queue length estimation approach for both randomly generated input and real trace data.

Explicitly solvable eigenvalue problem and bifurcation delay in sub-diffusive Gierer–Meinhardt model

A spike solution is constructed on the infinite line for a sub-diffusive version of the Gierer–Meinhardt reaction – diffusion model. A non-local eigenvalue problem governs the spike's stability and is explicitly solvable for a certain choice of the kinetic parameters. Its solution generalises former results for the Gierer–Meinhardt model with regular diffusion, and the normal and anomalous systems' properties are juxtaposed. It is shown that a Hopf bifurcation occurs in the sub-diffusive system for larger values of the time parameter τo as compared to the normal counterpart, rendering the anomalous system more stable. Asymptotic solutions are obtained near important values of the diffusion anomaly index γ and collectively shown to be valid over most of the applicable range 0 &lt; γ &lt; 1. A bifurcation delay scenario is described for the sub-diffusive system, and the WKB exponent is computed analytically.

Ant colony optimization with immigrants schemes for the dynamic railway junction rescheduling problem with multiple delays

Train rescheduling after a perturbation is a challenging task and is an important concern of the railway industry as delayed trains can lead to large fines, disgruntled customers and loss of revenue. Sometimes not just one delay but several unrelated delays can occur in a short space of time which makes the problem even more challenging. In addition, the problem is a dynamic one that changes over time for, as trains are waiting to be rescheduled at the junction, more timetabled trains will be arriving, which will change the nature of the problem. The aim of this research is to investigate the application of several different ant colony optimization (ACO) algorithms to the problem of a dynamic train delay scenario with multiple delays. The algorithms not only resequence the trains at the junction but also resequence the trains at the stations, which is considered to be a first step towards expanding the problem to consider a larger area of the railway network. The results show that, in this dynamic rescheduling problem, ACO algorithms with a memory cope with dynamic changes better than an ACO algorithm that uses only pheromone evaporation to remove redundant pheromone trails. In addition, it has been shown that if the ant solutions in memory become irreparably infeasible it is possible to replace them with elite immigrants, based on the best-so-far ant, and still obtain a good performance.

Model Predictive Control for Space Teleoperation Systems Based on a Mixed-H2/H∞ Approach

In this paper a novel model predictive control (MPC) approach is proposed based on mixed-H2/Hi control for space teleoperation systems with unknown, large time-varying delays and input constraints. This novel approach only measures the online delay; it does not presume the delay bounds. In addition, Hi control has been incorporated into the original MPC, which compensates for large time-varying delays, handles input constraints, and provides the desired tracking performance. First, the space teleoperation system is built based on a type of control architecture and then converted into a discrete state-space equation. Next, a state-feedback controller is designed based on linear matrix inequality (LMI). Meanwhile, the corresponding sufficient conditions are derived for the controller, enabling the closed-loop system to be asymptotically stable and guaranteeing the prescribed mixed-H2/Hi performance under input constraints. The parameters of the controller are calculated online by updating the mixed-H2/Hi optimizing problem during each interval. Finally, comparative simulations reveal that the proposed approach can achieve better performance in terms of tracking ability than that of traditional MPC. Moreover, it can ensure the input constraints in the unknown, large time-varying delay scenario whereas the original Hi control approach cannot guarantee performance.

Handoff self-management based on SNR in mobile communication networks

In today’s high density wireless networks, delay is considered one of the main factors limiting the capacity and increasing the new call blocking probability of a cellular system. In this paper we discuss and analyse a delay scenario in cellular systems and we have proposed a novel handoff management based on cognitive radio scheme to reduce the latency that is caused by the repeated unnecessary handoff in the home cell. Using the cognitive radio in cellular systems will lead to a revolution in wireless communication with significant impacts on technology as well as regulation of spectrum usage to overcome existing lacks. The cognitive radio is a self-aware communication system that efficiently uses spectrum in an intelligent way. It autonomously coordinates the usage of spectrum in identifying unused radio spectrum based on observing spectrum usage.

Throughput of Networks With Large Propagation Delays

Propagation delays in underwater acoustic networks can be large as compared to the packet size. Conventional medium-access control (MAC) protocol design for such networks focuses on mitigation of the impact of propagation delay. Most proposed protocols to date achieve, at best, a throughput similar to that of the zero propagation delay scenario. In this paper, we systematically explore the possibility that propagation delays can be exploited to make throughput far exceed that of networks without propagation delay. Under the assumptions of the protocol model in a single collision domain for a half-duplex unicast network, we show that the upper bound of throughput in an <i xmlns:mml="http://www.w3.org/1998/Math/MathML" xmlns:xlink="http://www.w3.org/1999/xlink">N</i> -node wireless network with propagation delay is <i xmlns:mml="http://www.w3.org/1998/Math/MathML" xmlns:xlink="http://www.w3.org/1999/xlink">N</i> /2. We illustrate network geometries where this bound can be achieved and study transmission schedules that help achieve it. We show that for any network, the optimal schedule is periodic and present a computationally efficient algorithm to find good schedules. Finally, we show that <i xmlns:mml="http://www.w3.org/1998/Math/MathML" xmlns:xlink="http://www.w3.org/1999/xlink">N</i> -node network geometries that achieve throughput close to the <i xmlns:mml="http://www.w3.org/1998/Math/MathML" xmlns:xlink="http://www.w3.org/1999/xlink">N</i> /2 bound exist for any <i xmlns:mml="http://www.w3.org/1998/Math/MathML" xmlns:xlink="http://www.w3.org/1999/xlink">N</i> and present a lower bound on achievable maximum throughput for bounded geometries. This paper chiefly endeavors to explore the impact and potential of nonzero propagation delays on network throughput. We believe that the novel observations in this paper could motivate further research into this area, especially random access networks with large propagation delay, with a fundamentally changed outlook on maximum achievable throughput. This could lead to novel scheduling and network configuration approaches with applications in underwater and satellite networks.

Cellular automaton traffic flow model between the Fukui-Ishibashi and Nagel-Schreckenberg models.

We propose and study a one-dimensional traffic flow cellular automaton model of high-speed vehicles with the Fukui-Ishibashi-type acceleration for all cars, and the Nagel-Schreckenberg-type (NS) stochastic delay only for cars following the trail of the car ahead. The main difference in the delay scenario between our model and the NS model is that a car with spacing ahead longer than the velocity limit M may not be delayed in our model. By using a car-oriented mean-field theory, we analytically derive fundamental diagrams of the average speed as a function of the car density. Our theoretical results are in excellent agreement with numerical simulations.

THE GRADUAL ACCELERATING TRAFFIC FLOW GELLULAR AUTOMATON MODEL IN WHICH ONLY HIG H SPEED CAR CAN BE DELAYED

A new traffic flow cellular automaton (CA) model situated between Nagel-Schrecke nberg (NS) type and Fukui-Ishibashi (FI) type is defined and studied. This new m odel adopes the gradual acceleration scenario for all cars as NS model and the s tochastic delay scenario for only the car with speed limit as FI model. It is pr oved that the fundamental diagram of the average traffic flow speed as the funct ion of the car density for the new model is exactly the same as for FI model. Th is means that if the acceleration scenario of the FI traffic flow model in which a car may increase in velocity rapidly from zero to the velocity limit M or the maximum velocity permitted by empty spacing ahead, is changed to a gradual way in which the velocity of a car may increase by only one unit at most in one time step, the asymptotic steady state behavior of traffic flow will not be changed by interaction between cars and the self-organization evolution of the traffic flow.