Optimized reduction of uncertainty in bursty human dynamics

Waiting time is an important transport quantity that is complementary to average current and its fluctuation. So far all the studies of waiting time distribution (WTD) are limited to steady state transport (either dc or ac). In this work, we present a theory to calculate WTD for coherent electronic systems in transient regime. We express the generating function of full counting statistics using Keldysh non-equilibrium Green's functions formalism. Our analysis goes beyond the wideband approximation and is suitable for first principles calculation on realistic systems. Analytic solution has been obtained for short and long time behaviors of waiting times. At short times, the WTD shows a linear dependence on the waiting time while in the long time limit, WTD follows Poisson distribution. We have applied this theory to a quantum dot connected by two leads and calculated cumulants of transferred charge as well as WTD in the transient regime. We have demonstrated how to relate WTD to experimental measured data.

In this paper, we describe an elementary combinatorial approach for deriving the waiting and response time distributions in a few classical priority queueing models. By making use of lattice paths that are linked in a natural way to the stochastic processes analyzed, the proposed method offers new insights and complements the results previously obtained by inverting the associated Laplace transforms.

Racial/ethnic disparities in emergency department wait times in the United States, 2013-2017.

For a class of renewal process waiting time distributions defined herein, one may describe the distribution of asymptotic residual waiting times. The relationship between the two distributions characterizes the class, which includes the gamma distribution. Possible consequences for hypothesis testing are discussed.

Nonmetastatic cervical cancer is a highly curable malignancy, and radiotherapy (RT) remains the mainstay treatment. Early initiation is critical, and the optimal time to initiate RT for cure is 6 weeks, with a reported 15% decrease in 3-year overall survival for those who wait 40 days. There is considerable variation in the waiting time to initiate RT between countries, with a median time of 27.2 days in Ontario, Canada and 108 days in South Africa. Real-world evidence of cancer progression because of treatment delay is scarce in low-income countries. Ethiopia, a country of 120 million, had a single machine at Tikur Anbessa Specialized Hospital (TASH) until it acquired a linear accelerator very recently. This study aimed to assess the extent of delay in receiving RT and the effect of delay on the natural disease court in patients with cervical cancer treated at TASH. This study was conducted at TASH between January 2019 and May 2020 and evaluated patients at different time points before and after RT. All individuals who were diagnosed with cervical cancer (stage IIB to stage IVA) and booked for RT at TASH were included. Concurrent chemoradiotherapy was administered for cervical cancer with weekly cisplatin as a chemotherapy agent. A total of 115 patients were included in this study. The median time between pathologic diagnosis and booking RT was 19 days, and the median time from booking to RT initiation was 458 days. The total median time from diagnosis to treatment was 477 days, and the median time to disease progression was 51 days. During the waiting period for RT, the stage was reassessed for 105 patients. The number of patients in stage IIB, IIA, and IIIB decreased during this period, whereas the number of patients in stage IVA increased from 20 (17.4%) to 30 (26.1%), 2 (1.8%) developed distant metastasis to the lungs (stage IVB), and 37 died before receiving a phone call for RT. Of 115 patients booked to receive CCRT, only 9 (7.8%) received CCRT, 80 (69.9%) received a single shot of palliative RT due to disease progression, and 25 (21.7%) did not receive RT at all. The mean and median survival times were 20.1 months (95% confidence interval [CI], 18.3–22.7) and 21 months (95% CI, 18.3–23.8), respectively. Waiting time, stage at presentation, distant metastasis during the waiting time, hydronephrosis during the waiting time, and type of treatment were significantly associated with survival. Multivariate cox regression using these variables found that patients with stage IIIB were 2.2 times more likely to die than those with stage IIB (adjusted hazards ratio, 2.2; 95% CI, 1.07–4.48), and patients with stage IVA were 20.95 times more likely to die than patients with stage IIB (adjusted hazards ratio, 20.95; 95% CI, 6.26–70.03). Prolonged waiting time increased the mortality rate of cervical cancer by 2.9 (95% CI, 1.07–4.5). This study provides a significant advancement in our understanding of cervical cancer care in low-income countries. The median waiting time diagnosis to treatment was 477 days, whereas the median waiting period for disease progression was 51 days, resulting in unnecessary disease progression, change in treatment intent from curative to palliative, and increased mortality. These findings highlight the need to increase access to RT services in lower-income nations to reduce wait times and provide better cancer care.

In the application of probabilistic models to waiting time problems it is sometimes necessary to compare two or more different service patterns to determine which pattern is most effective in decreasing waiting times. In many cases the mean waiting time of the customer is the criterion used to measure the effectiveness of the service because it is the easiest property of the waiting time distribution to calculate. It is the purpose of this note to give an example of a simple waiting time problem in which it is intuitively clear that the mean waiting time gives a misleading indication of the effectiveness of the service and that some other measure should be considered. Suppose there are N independent bus routes passing a particular bus stop A which by different paths arrive at a particular destination point B. Let T,,(') (i = 1, 2, . . . N; n1, 2, . . .) be the instant at which the nth arrival of a bus on the ith route occurs at point A. We will assume that On(i) = T1+1'i'Tn), (n = 1 2 . . .) are independent identically distributed positive random variables such that

A single-server subject to random breakdowns (or preemptive interruptions) insure the service of customers who arrive in the system according to a homogeneous Poisson process. The customer who arrive when the server is blocked (out of order or busy) is admitted to repeat his call until the server can provide his service. The purpose of this paper is to provide a simple approach to compute the stationary probability distribution of the customer's sojourn time in the system. We also obtain the probability distribution of the work which is different from the sojourn time contrary to the classical FIFO discipline. We show how mean performance measures such as mean waiting time and mean sojourn time can be obtained. Finally, we obtain asymptotic distributions of the waiting and sojourn times in heavy traffic and in the case of low retrial rate.

Optimal timing of hepatitis C treatment among HIV/HCV coinfected ESRD patients: Pre- vs posttransplant.

Through analysis and experiments, this paper investigates two-phase waiting algorithms to minimize the cost of waiting for synchronization in large-scale multiprocessors. In a two-phase algorithm, a thread first waits by polling a synchronization variable. If the cost of polling reaches a limit L poll and further waiting is necessary, the thread is blocked, incurring an additional fixed cost, B . The choice of L poll is a critical determinant of the performance of two-phase algorithms. We focus on methods for statically determining L poll because the run-time overhead of dynamically determining L poll can be comparable to the cost of blocking in large-scale multiprocessor systems with lightweight threads. Our experiments show that always-block ( L poll = 0) is a good waiting algorithm with performance that is usually close to the best of the algorithms compared. We show that even better performance can be achieved with a static choice of L poll based on knowledge of likely wait-time distributions. Motivated by the observation that different synchronization types exhibit different wait-time distributions, we prove that a static choice of L poll can yield close to optimal on-line performance against an adversary that is restricted to choosing wait times from a fixed family of probability distributions. This result allows us to make an optimal static choice of L poll based on synchronization type. For exponentially distributed wait times, we prove that setting L poll = 1n(e-1) B results in a waiting cost that is no more than e/(e-1) times the cost of an optimal off-line algorithm. For uniformly distributed wait times, we prove that setting L poll =1/2(square root of 5 -1) B results in a waiting cost that is no more than (square root of 5 + 1)/2 (the golden ratio) times the cost of an optimal off-line algorithm. Experimental measurements of several parallel applications on the Alewife multiprocessor simulator corroborate our theoretical findings.

We consider the stationary waiting time distribution under the FIFO discipline for multi-server queues with (possibly heterogeneous) phase type servers and renewal arrivals, and for queues which can be represented as a quasi-birth-and-death process. It is shown that the complementary distribution function of the stationary waiting time in these queues is of the form where θ is positive and the dj are probabilities. A complete characterization of θ and dj , which lends itself to interesting probabilistic interpretations, is given for all these cases. Except in the case of the multiserver GI/PH/c queue which is to be discussed in detail elsewhere, we provide an efficient algorithm to compute the waiting time distribution.

In this paper, the waiting time analysis for an OFDMA wireless cellular system with finite buffering and Adaptive Modulation and Coding (AMC) is addressed. When AMC is considered, several concentric regions within cells serving users with different data rates are differentiated. Phase type (PHT) distribution functions are used to model the conditional cumulative distribution function of the waiting time for users in the different coverage regions. The representation of the conditional waiting time distribution through PHT distributions allows expressing cumulative distribution function (CDF) as a linear combination of negative exponential distributions. The analytical method proposed here captures the exact behavior of the waiting time and the obtained solution is based on matrix analytic derivation, which allows evaluating system performance for any size of buffer and any number of coverage regions.

One crossroad of ​​Surabaya whose high level of congestion is the crossing of Jemur Andayani – Ahmad Yani Street. It needs to Improve traffic management, geometric, and signal time to obtain optimal traffic performance. The purpose of this study is to make a model of traffic flow and determine the optimal total waiting time at the crossing of Jemur Andayani – Ahmad Yani using Compatible Graph. Compatible graphs are two sets where vertices indicate objects to be arranged and edges indicate compatible pairs of objects. Compatible traffic flow is two traffic flows which if both of them run simultaneously can run safely and not collide. The results of the optimal waiting time calculation using a compatible graph assuming the left turn following the lamp is 75 seconds. While the optimal total waiting time by assuming the left turn not following the lights is 60 seconds. The optimal total waiting time is smaller than the actual total waiting time currently applied at Frontage Ahmad Yani street, which is 170 seconds by assuming turn left following the lights.

We present the timing solutions for three radio pulsars discovered with the Green Bank North Celestial Cap and 350 MHz Green Bank Telescope drift-scan surveys. These pulsars were initially discovered through their single-pulse emissions and are therefore designated as rotating radio transients (RRATs). Follow-up timing campaigns yielded a number of higher signal-to-noise summed pulse profiles for each pulsar, allowing us to obtain timing solutions both through single pulses as well as the standard method of time-integrating the pulsar’s emission. We find that the two methods return timing parameters that are usually in agreement within two standard deviations and have similar-sized error bars. The single-pulse timing solutions have significantly higher rms errors and reduced chi-squared values, likely due to pulse jitter. The distribution of wait times between detected single pulses indicates a significant amount of pulse clustering in time on short timescales from all three sources. For all sources, the presence of low-level emissions outside of the sparse bright pulses and the lack of giant pulses is more reminiscent of highly nulling canonical radio pulsars than extremely transient RRATs, highlighting the diversity of emission behavior observed from sources published as RRATs.

In a Fork-Join (FJ) queueing system an upstream fork station splits incoming jobs into N tasks to be further processed by N parallel servers, each with its own queue; the response time of one job is determined, at a downstream join station, by the maximum of the corresponding tasks' response times. This queueing system is useful to the modelling of multi-service systems subject to synchronization constraints, such as MapReduce clusters or multipath routing. Despite their apparent simplicity, FJ systems are hard to analyze. This paper provides the first computable stochastic bounds on the waiting and response time distributions in FJ systems. We consider four practical scenarios by combining 1a) renewal and 1b) non-renewal arrivals, and 2a) non-blocking and 2b) blocking servers. In the case of non blocking servers we prove that delays scale as O(logN), a law which is known for first moments under renewal input only. In the case of blocking servers, we prove that the same factor of log N dictates the stability region of the system. Simulation results indicate that our bounds are tight, especially at high utilizations, in all four scenarios. A remarkable insight gained from our results is that, at moderate to high utilizations, multipath routing 'makes sense' from a queueing perspective for two paths only, i.e., response times drop the most when N = 2; the technical explanation is that the resequencing (delay) price starts to quickly dominate the tempting gain due to multipath transmissions.

A discrete time single-line queueing system with independent geometric streams of regular and negative claims, infinite buffer, and geometric service is considered. A negative claim pushes a regular claim out of the buffer queue and moves it to a bunker of infinite capacity. If the buffer is empty, a negative claim leaves the system without any effect. After servicing a claim, the system receives the next claim from the buffer, if it is not empty, or from the bunker. We obtain relations for stationary waiting and sojourn time distributions of the regular claim.