Narrow Results

We study a MAP/M/c queueing system in which a group of servers take a simultaneous phase type vacation. The queueing model is studied as a QBD process. The steady-state analysis of the model including the waiting time distribution is presented. Interesting numerical results are discussed.

We consider a type of correlated queue in which the inter-arrival time between two consecutive customers linearly depends on the service time of the first customer. We first derive infinite systems of linear equations for the moments of the waiting time in two special cases, based on which we then develop several methods to calculate the moments of the waiting time by using MacLaurin series approximation, Padé approximation and truncation method. In addition, we show how the moments and covariances of the inter-departure times of the correlated queue can be calculated based on the moments of the waiting time. Finally, extensive numerical examples are provided to validate our methods.

This paper describes the experimental results of the levitation force of single-grained YBaCuO bulk superconductors preparing by the top-seeded melt-growth method with different waiting time t_w below an NdFeB permanent magnet. It was found that waiting time has large effects on the zero-field-cooled (ZFC) and field-cooled (FC) levitation force, and the levitation force shows aging characteristics at the liquid nitrogen temperature.

Cloud providers face the challenge of managing large amounts of heterogeneous resources in real time. It is usually very costly to conduct experiments with real cloud systems. Therefore, tools to analyze and evaluate cloud scenarios and experimental studies are very useful for them. In this paper, we model cloud systems and the user interactions with the cloud provider using the UML2Cloud profile. In general, users request virtual machines according to their needs, but they can also subscribe to the cloud provider and wait to be notified when the requested resources are not available. In this case, users indicate a maximum subscription time, so once this time elapses without being notified, users leave the system unattended. Thus, we present an exhaustive experimental study to measure how the user subscription times affect the overall system responsiveness. To this end, four different cloud configurations are analyzed, and the workloads for these studies are produced by using three distribution functions for the user arrivals, namely, a uniform, a normal, and a cyclic normal distribution. Furthermore, we also analyze the cloud performance with a workload obtained from a real trace. The purpose of this study is to find out the inflection point for the waiting time of the users, from which the cloud responsiveness and its performance do not improve. The obtained information is, therefore, useful for the cloud provider to improve the configuration of the cloud.

The heat equation with homogeneous Dirichlet boundary conditions is well known to preserve non-negativity. Besides, due to infinite velocity of propagation, the heat equation is null controllable within arbitrary small time, with controls supported in any arbitrarily open subset of the domain (or its boundary) where heat diffuses. The following question then arises naturally: can the heat dynamics be controlled from a positive initial steady state to a positive final one, requiring that the state remains non-negative along the controlled time-dependent trajectory? We show that this state-constrained controllability property can be achieved if the control time is large enough, but that it fails to be true in general if the control time is too short, thus showing the existence of a positive minimal controllability time. In other words, in spite of infinite velocity of propagation, realizing controllability under the unilateral non-negativity state constraint requires a positive minimal time. We establish similar results for unilateral control constraints. We give some explicit bounds on the minimal controllability time, first in 1D by using the sinusoidal spectral expansion of solutions, and then in the multi-dimensional case. We illustrate our results with numerical simulations, and we discuss similar issues for other control problems with various boundary conditions.

As new energy technology has advanced to a respectable level, Electric Vehicles (EV) have gained recognition from people all over the world and have become increasingly popular in a number of nations. Effective charging station placement is critical for the rapid growth of electric vehicles, as it is vital to provide convenience for electric vehicles while also ensuring the effectiveness of traffic networks. The location of an EV charging station is simply an application situation for the facility location problem. Traditional works often pay attention to the mileage concerns of electric vehicle customers while ignoring their competitive and strategic charging tactics. This research aims to frame the allocation of charging stations issue as a multi-faceted venture by assessing the aspects economically along with the characteristics of the power grid like “cost, Voltage stability, Reliability, and Power loss (VRP) index, waiting time, and accessibility index”. Further, we proposed a hybrid artificial intelligence to resolve the allocation issue. The proposed new Artificial Intelligence (AI) based algorithm is termed as Hybridized Salp and Harris Algorithm (HS-HA). The effectiveness and scalability of the presented algorithm for the charging station placement issue are also assessed through different plans in the IEEE 33-bus distribution systems. Finally, the efficiency of the presented approach is proved over the existing approaches with respect to various measures.

ATOZET® a New Combination Treatment Option for High-Risk Patients to Lower LDL Cholesterol, is Now Approved in Singapore.

ASEAN+ Rare Disease Network Established.

Luye Medical Joins Forces with OncoCare To Expand Its Integrated Healthcare Services Platform for Their Patients.

NUS Pharmacy Team Develops Online “Calculator” to Predict Risk of Early Hospital Readmission.

The Bare Essentials: Ensuring Affordable Access to Insulin.

AstraZeneca’s CVD-REAL Study Shows SGLT-2 Inhibitors Significantly Reduced Death and Hospitalisations for Heart Failure Versus Other Type-2 Diabetes Medicines.

The aim of this paper is to analyse the total length of time spent by a group of patients in an Accident and Emergency (A&E) department using a multi-stage Markov model. A patient's pathway through A&E consists of a sequence of stages, such as triage, examination, and a decision of whether to admit to hospital or not. Using Coxian phase-type distributions, this paper models these stages and illustrates the difference in the distribution of the time spent in A&E for those patients who are admitted to hospital, and those patients who are not. A theoretical approach to modelling the costs accumulated by a group of patients in A&E is also presented. The data analysed refers to the time spent by 53,213 patients in the A&E department of a hospital in Northern Ireland over a one year period.