Service Time Estimation Research Articles

Prediction of the residual lifetime of bitumen coatings on urban gas pipelines from the change in their mechanical characteristics during thermal-oxidative aging

Residual life of bitumen insulation is an important parameter of urban gas pipelines. Its fast and reliable estimation is necessary for timely health monitoring and coating restoration. In this study, we propose to define lifespan of bitumen insulation in situ from the mechanical characteristics measured during its thermal-oxidative aging. For evaluation of elastic and viscous properties, micro-impact dynamic indentation was applied. We determined the values of activation energy under thermal destruction and the dependence of transient electrical resistance on the critical values of coating's mechanical properties. Obtained experimental data foster real-time estimation of service time of insulation without coating removal.

A Conceptual Model for Coeval Time Estimation of Virtual Reference Service

The objective of this paper is to propose a conceptual model of a virtual reference service (VRS) time estimation system that can estimate and display the time required to complete a transaction. The system will start estimating the duration before initiation of a transaction and update the estimated duration with the changing complexity of the transaction. Literature on industrial time estimation techniques and artificial-intelligence based VRS programs are reviewed to identify the gap. Four flowcharts are constructed with the aid of machine learning techniques like random forest regression and speech recognition, and natural language processing techniques like intent and entity recognition, and weighting. The pre-estimating, estimating, and post-estimating stages of the system are vividly explained with an example to enlighten the time-estimation process. The limitation of the paper is that the system is not practically developed and tested. However, developing such a system will help in transparent and unbiased transaction time estimation and assist the library professionals to manage queue time and maintain consistent timeliness. The estimated time may be used as a benchmark for evaluating different aspects of VRS. Providing quality service within the estimated time may increase the reliability and loyalty of the patrons toward the library professionals.

Analytics for labor planning in systems with load-dependent service times

This paper presents a generalized framework for labor planning in systems with load-dependent service times. Our approach integrates customer arrival forecasting, service time estimation, and staffing into an end to end process. More specifically, (i) we propose a hybrid model to forecast customer arrivals, that combines a traditional time-series technique with a state-of-the-art machine learning algorithm, thereby allowing to incorporate a rich set of predictors; (ii) we develop a methodology to estimate the distribution of load-dependent service times from past transactions data; and (iii) we present a stochastic programming formulation to determine staffing levels under quality-of-service constraints. Finally, we develop a heuristic solution algorithm that utilizes an embedded discrete event simulation to evaluate system performance.To demonstrate the practical applicability of our approach, we conduct a case study at a franchisee of a major international fast food chain. Our data set includes the number of transactions, average order value, average service times, and staffing levels recorded at the restaurant on an hourly level, as well as information on marketing activities of the fast food chain on a daily level for nine consecutive years. We show that by applying our approach, the personnel expenses could be reduced by 4.4%, which would translate into an increase in earnings before interest and taxes by 13% at the collaborating restaurant.

Dynamic Estimation of Hospital Reservation Registration Service Time in the Basis of Dual Attribute Similarity

Considering the particularity, complexity and uncertainty of influencing factors, a dynamic estimation model of reservation registration service time based on binary attribute similarity in the hospital is proposed to solve the problem of hospital reservation registration service time estimation. The model combines hospital process expert knowledge with machine learning of historical data, and uses binary attribute similarity to construct the model of hospital data object. The results show that the proposed method can effectively estimate the booking service time and have high accuracy.

Heuristics for tactical time slot management: a periodic vehicle routing problem view

AbstractIn this study, we consider a tactical problem where a time slot schedule for delivery service over a given planning horizon must be selected in each zone of a geographical area. A heuristic search evaluates each schedule selection by constructing a corresponding tactical routing plan of minimum cost based on demand and service time estimates. At the end, the schedule selection leading to the best tactical routing plan is selected. The latter can then be used as a blueprint when addressing the operational problem (i.e., when real customer orders are received and operational routes are constructed). We propose two heuristics to address the tactical problem. The first heuristic is a three‐phase approach: a periodic vehicle routing problem (PVRP) is first solved, followed by a repair phase and a final improvement phase where a vehicle routing problem (VRP) with time windows is solved for each period of the planning horizon. The second heuristic tackles the problem as a whole by directly solving a PVRP with time windows. Computational results compare the two heuristics under various settings, based on instances derived from benchmark instances for the VRP with time windows.

Waiting‐time estimation in walk‐in clinics

AbstractMedical assistance is offered by walk‐in clinics (WC). These clinics must keep track of patients’ turn in line. Some private companies offer an extra follow‐up service to WC patients, which notifies them when their consultation approaches, so patients can use their free time elsewhere than in the waiting room. This paper aims to develop an applied forecasting approach for consultation service time estimation and waiting‐time estimation. A model based on particle filters and mixture models helps to estimate the waiting time for each consultation, using historical and new incoming data from patient consultations. The system considers two types of patients, namely, regular and follow‐up. Our method gives an estimate of the waiting time for consultation better than simple statistics.

Bus service time estimation model for a curbside bus stop

The bus service time at bus stop areas occupies a large proportion of the total on-road bus operational time. Curbside bus stops are very common in urban transit systems, and the occurrence of bus queues forming at the entry and departure area of bus stop is quite frequent. To estimate the service time at a curbside bus stop, a compound Poisson service time estimation model (CPSTM) is proposed. The CPSTM considers the interactions among arriving buses and number of boarding and alighting passengers. Realistic observational data are acquired for a representative bus stop. Four different scenarios are presented to estimate the total expected service time. The service time estimation of each bus line is obtained via the CPSTM, and the effectiveness of the proposed CPSTM is demonstrated. The results show that the employment of real-time data is not required for accurate service time estimation.

Annual patient time costs associated with medical care among cancer survivors in the United States.

Although patient time costs are recommended for inclusion in cost-effectiveness analyses, these data are not routinely collected. We used nationally representative data and a medical service-based approach to estimate the annual patient time costs among cancer survivors. We identified adult 6699 cancer survivors and 86,412 individuals without a cancer history ages 18 years or more from 2008-2011 Medical Expenditure Panel Survey (MEPS). Service use was categorized as hospitalizations, emergency room use, provider visits, ambulatory surgery, chemotherapy, and radiation therapy. Service time estimates were applied to frequencies for each service category and the US median wage rate in 2011 was used to value time. We evaluated the association between cancer survivorship and service use frequencies and patient time costs with multivariable regression models, stratified by age group (18-64 and 65+ y). Sensitivity analyses evaluated different approaches for valuing time. Cancer survivors were more likely to have hospitalizations, emergency room visits, ambulatory surgeries, and provider visits in the past year than individuals without a cancer history in adjusted analyses (P<0.05). Annual patient time was higher for cancer survivors than individuals without a cancer history among those aged 18-64 years (30.2 vs. 13.6 h; P<0.001) and 65+ years (55.1 vs. 36.6 h; P<0.001), as were annual patient time costs (18-64 y: $500 vs. $226; P<0.001 and 65+ y: $913 vs. $607; P<0.001). Cancer survivors had greater annual medical service use and patient time costs than individuals without a cancer history. This medical service-based approach for estimating annual time costs can also be applied to other conditions.

On the Value Function of the M/G/1 FCFS and LCFS Queues

We consider a single-server queue with Poisson input operating under first-come–first-served (FCFS) or last-come–first-served (LCFS) disciplines. The service times of the customers are independent and obey a general distribution. The system is subject to costs for holding a customer per unit of time, which can be customer specific or customer class specific. We give general expressions for the corresponding value functions, which have elementary compact forms, similar to the Pollaczek–Khinchine mean value formulae. The results generalize earlier work where similar expressions have been obtained for specific service time distributions. The obtained value functions can be readily applied to develop nearly optimal dispatching policies for a broad range of systems with parallel queues, including multiclass scenarios and the cases where service time estimates are available.

On the Value Function of the M/G/1 FCFS and LCFS Queues

We consider a single-server queue with Poisson input operating under first-come–first-served (FCFS) or last-come–first-served (LCFS) disciplines. The service times of the customers are independent and obey a general distribution. The system is subject to costs for holding a customer per unit of time, which can be customer specific or customer class specific. We give general expressions for the corresponding value functions, which have elementary compact forms, similar to the Pollaczek–Khinchine mean value formulae. The results generalize earlier work where similar expressions have been obtained for specific service time distributions. The obtained value functions can be readily applied to develop nearly optimal dispatching policies for a broad range of systems with parallel queues, including multiclass scenarios and the cases where service time estimates are available.

Research on Service Time Estimation and Service Selection Based on Grey System Theory for Web of Things

Research on Service Time Estimation and Service Selection Based on Grey System Theory for Web of Things

ASIdE: Using Autocorrelation-Based Size Estimation for Scheduling Bursty Workloads

Temporal dependence in workloads creates peak congestion that can make service unavailable and reduce system performance. To improve system performability under conditions of temporal dependence, a server should quickly process bursts of requests that may need large service demands. In this paper, we propose and evaluateASIdE, an Autocorrelation-based SIze Estimation, that selectively delays requests which contribute to the workload temporal dependence. ASIdE implicitly approximates the shortest job first (SJF) scheduling policy but without any prior knowledge of job service times. Extensive experiments show that (1) ASIdE achieves good service time estimates from the temporal dependence structure of the workload to implicitly approximate the behavior of SJF; and (2) ASIdE successfully counteracts peak congestion in the workload and improves system performability under a wide variety of settings. Specifically, we show that system capacity under ASIdE is largely increased compared to the first-come first-served (FCFS) scheduling policy and is highly-competitive with SJF.

An Adaptive Traffic-Aware Polling and Scheduling Algorithm for Bluetooth Piconets

According to Bluetooth specifications, communications between slave devices within a piconet are controlled by its master node. In other words, a master node has to be involved in all packet exchange activities in its associated piconet. Consequently, how to determine the polling sequence and how to estimate service time for individual slave nodes are two critical intrapiconet missions to a master and are usually categorized as the intrapiconet polling and scheduling problem. Obviously, a good polling sequence can reduce the average packet delay, whereas accurate service time estimation would result in better throughput performance. Furthermore, the packet delay of intrapiconet transmission is mostly caused by the inadequate behavior in which the master node polls an idle slave since other nonidle slaves belonging to the same piconet have to wait for the completion of such POLL/NULL packet transmissions. Certainly, unnecessary pollings would cause bandwidth utilization reduction as well. Therefore, the adaptability to traffic pattern is a necessary condition to a good intrapiconet polling and scheduling algorithm. In this paper, we proposed a traffic-aware algorithm to deal with the polling and scheduling issue within a piconet. The objective of our work is to maximize the throughput performance and to reduce the average intrapiconet packet delay as simultaneously as possible. As expected, the simulation results verify that our work designs an intrapiconet scheduling scheme with low delay and high throughput, which is adaptive to various traffic scenarios as well.

Online feedback-based estimation of dynamic page service time

We present a framework for estimating the service time of a dynamic HTTP request by using the service times of past requests to the same URL. Our framework tags incoming requests with a timestamp. As the request is processed, server state relevant to the estimation mechanism, such as the number of threads servicing incoming requests, is stored with each request. When a request is handled, it is timestamped again, allowing us to calculate its service time. This service time is added to the history table and used in the computation of future estimates. The estimators we evaluated do not produce accurate predictions when server resources change, leaving room for further work in estimator design.

Analysis of the transport flows service time of the veidcles and the assessment of the ideterminancy of external impact

Abstract To increase the attraction of Lithuania as a transit country striving to promote carriers' border crossing activities and facilitate customs clearance procedures as well as freight delivery to clients it is necessary to identify the main obstacles, to analyse them and to select adequate measures and means for their elimination. Therefore, on the basis of the analysis of the transport flows service time, as well as basing on the assessment of indeterminacy of external impacts, it would be possible to deduce the main causes of idle time of transport means at customs, to estimate the dependence of service time in proportion to transport flows. Basing on theoretical estimation in this article the estimation of service time of international transport and the management of transport flows are described.

ANALYSIS OF THE TRANSPORT FLOWS SERVICE TIME OF THE VEIDCLES AND THE ASSESSMENT OF THE IDETERMINANCY OF EXTERNAL IMPACT

To increase the attraction of Lithuania as a transit country striving to promote carriers' border crossing activities and facilitate customs clearance procedures as well as freight delivery to clients it is necessary to identify the main obstacles, to analyse them and to select adequate measures and means for their elimination. Therefore, on the basis of the analysis of the transport flows service time, as well as basing on the assessment of indeterminacy of external impacts, it would be possible to deduce the main causes of idle time of transport means at customs, to estimate the dependence of service time in proportion to transport flows. Basing on theoretical estimation in this article the estimation of service time of international transport and the management of transport flows are described.

Strain based service time estimation for angle-ply laminates

The long term behaviour of ±45°-angle-ply laminates of carbon/epoxy was studied. Due to the absence of 0°-layers angle-ply laminates are subject to cyclic creep. To investigate the time dependent behaviour, creep tests and constant amplitude fatigue tests at different stress ratios were performed. The assumption that the extent of creep depends on the fatigue mean stress was verified and the interaction between creep and fatigue was determined. Based on creep strain data a general fatigue damage metric was defined and conservative service times were estimated.