Time Performance Measures Research Articles

Internet-based measurement of visual assessment skill of trainee radiologists: developing a sensitive tool.

Expert radiologists exhibit high levels of visual diagnostic accuracy from review of radiological images, doing so after accumulating years of training and experience. To train new radiologists, learning interventions must focus on the development of these skills. By developing a web-based measure of image assessment, a key part of visual diagnosis, we aimed to capture differences in the performance of expert, trainee and non-radiologists. 12 consultant paediatric radiologists, 12 radiology registrars, and 39 medical students were recruited to the study. All participants completed a two-part, online task requiring them to visually assess 30 images (25 containing an abnormality) drawn from a library of 150 paediatric skeletal radiographs assessed prior to the study. Participants first identified whether an image contained an abnormality, and then clicked within the image to mark its location. Performance measures of identification accuracy, localisation precision, and task time were collected. Despite the difficulties of web-based testing, large differences in performance, both in terms of the accuracy of abnormality identification and in the precision of abnormality localisation were found between groups, with consultant radiologists the most accurate both at identifying images containing abnormalities (p < 0.001) and at localising abnormalities on the images (p < 0.001). Our data demonstrate that an online measurement of radiological skill is sufficiently sensitive to detect group level changes in performance consistent with the development of expertise. The developed tool will allow future studies assessing the impact of different training strategies on cognitive performance and diagnostic accuracy.

Assessment of the Physical Internet Enabled Urban Logistics Using Agent-Based Simulation

The physical internet (PI) is a new paradigm in logistics to aim for more efficiency and sustainability via the shared use of hubs and transports as well as the consolidation of shipments. This study investigates the potential of an open mobility web, designed on the principles of PI, in an urban area with e-commerce warehouses. Our motivation is to understand benefits gained by incorporating PI into existing logistics networks. To that aim, a multi-agent based simulation model is developed to demonstrate the efficacy of our proposed solution approach in this modelling framework. Four transportation scenarios simulate a range of advancements from the traditional logistics to PI. The computational results using real data indicate that the PI-enabled mobility web outperforms the traditional logistics on most performance measures of time and cost. We conclude with implications for logistics stakeholders, and discuss limitations and extensions of this study.

Multi-Stage assembly flow shop with setup time and release time

This article addresses multi-stage assembly flow shop for the first time. We propose several industrial applications of this system in which the opening stage has m parallel machines and the following stages (e.g. assembly, transportation, painting, packaging, etc.) complete and prepare products for delivery. We develop a mixed binary linear optimization model and a constraint-free mathematical presentation for this problem. We explore performance measures of makespan and total completion time and derive polynomial optimal solutions for special cases that are likely to occur in industry. We also propose lower bounds as well as nine efficient heuristics for solving the problem with the objective of minimizing makespan. The results reveal that the proposed lower bounds is tight enough. Moreover, the optimization models and derived polynomial algorithms can be applied to assembly flow shops without setup or release time. Finally, we implement General Variable Neighborhood Search (GVNS) and Grey Wolf Optimizer to improve the heuristic solutions. Comparison of employed algorithms on randomly generated instances indicates that GVNS outperforms other heuristics. The performance of proposed heuristics and meta-heuristics are confirmed with detailed statistical analysis.

The Assessment of Isometric, Dynamic, and Sports-Specific Upper-Body Strength in Male and Female Competitive Surfers.

The primary purpose of this study was to investigate gender differences in the dynamic strength index (DSI): an assessment of upper-body dynamic strength relative to maximal isometric strength. The secondary purpose was to investigate gender differences in the dynamic skill deficit (DSD): an assessment of sports-specific dynamic strength relative to maximal isometric strength, and its association with a sports-specific performance measure in surfers. Nine male (age = 30.3 ± 7.3 yrs) and eight female (age = 25.5 ± 5.2 yrs) surfers undertook three upper-body assessments: isometric push-up, dynamic push-up, and a force plate pop-up to determine the DSI and DSD. The performance measure of time taken to pop-up (TTP) was recorded. No gender differences for the DSI (d = 0.48, p = 0.33) or DSD (d = 0.69, p = 0.32) were observed. Normalized peak force (PF) of the isometric push-up, dynamic push-up, and force plate pop-up were significantly greater in males (p ≤ 0.05), with males recording significantly quicker TTP (d = 1.35, p < 0.05). The results suggest that male and female surfers apply a similar proportion of their maximal strength in sports-specific movements. However, greater normalized isometric and dynamic strength in males resulted in greater sports-specific PF application and a faster TTP. It would appear favorable that female surfers improve their maximal strength to facilitate sports-specific pop-up performance.

Off-Policy Reinforcement Learning: Optimal Operational Control for Two-Time-Scale Industrial Processes.

Industrial flow lines are composed of unit processes operating on a fast time scale and performance measurements known as operational indices measured at a slower time scale. This paper presents a model-free optimal solution to a class of two time-scale industrial processes using off-policy reinforcement learning (RL). First, the lower-layer unit process control loop with a fast sampling period and the upper-layer operational index dynamics at a slow time scale are modeled. Second, a general optimal operational control problem is formulated to optimally prescribe the set-points for the unit industrial process. Then, a zero-sum game off-policy RL algorithm is developed to find the optimal set-points by using data measured in real-time. Finally, a simulation experiment is employed for an industrial flotation process to show the effectiveness of the proposed method.

Validation of a Novel Inverted Peg Transfer Task: Advancing Beyond the Regular Peg Transfer Task for Surgical Simulation-Based Assessment

To evaluate the validity of a novel inverted peg transfer (iPT) task for assessing laparoscopic skills of novices and experts and compare iPT to the regular PT (rPT) task to ensure surgical trainee acquisition of an adequate advanced laparoscopic skills level for safe laparoscopic practice in the operating room. Prospective crossover study. Multidisciplinary simulation center and motion analysis laboratory, Mayo Clinic. Novices were medical students and surgical interns without laparoscopic experience. Experts were surgeons with at least 3 years of experience in laparoscopic surgery. This was the first exposure to iPT for both groups. Completion time and performance metrics were recorded. A scoring rubric was used to calculate a normalized performance score between 0 and 100. Wilcoxon rank sum and Mann-Whitney tests were performed with α = 0.05. Receiver-operating characteristic curves were graphed for the 2 task scores to assess the tasks' sensitivity and specificity in differentiating laparoscopic experience level. Performance measures of completion time, transferred triangles, dropped triangles (errors), and the overall performance score on both tasks between- and within-subjects (i.e., novices and experts). Thirty-six novices and eight experts participated. Both experts and novices had longer completion time and lower scores during iPT than rPT (p < 0.05). Within iPT, novice completion times were 144 seconds longer (p = 0.04), and performance score was 35 points lower than experts (p < 0.01). No differences between novices and experts were observed for completion time or performance scores (p > 0.05) for rPT. The iPT scores had a higher sensitivity and specificity than the rPT (area under the receiver-operating characteristic curve: iPT = 0.91; rPT = 0.69). iPT is a valid assessment of advanced laparoscopic skills for surgical trainees with higher specificity and sensitivity than rPT. As advanced minimally invasive surgery becomes more common, it is important that tasks such as iPT be included in surgical simulation curricula and training assessment.

Virtual interactive suturing for the Fundamentals of Laparoscopic Surgery (FLS)

BackgroundSuturing with intracorporeal knot-tying is one of the five tasks of the Fundamentals of Laparoscopic Surgery (FLS), which is a pre-requisite for board certification in general surgery. This task involves placing a short suture through two marks in a penrose drain and then tying a double-throw knot followed by two single-throw knots using two needle graspers operated by both hands. A virtual basic laparoscopic skill trainer (VBLaST©) is being developed to represent the virtual versions of the FLS tasks, including automated, real time performance measurement and feedback. In this paper, we present the development of a VBLaST suturing simulator (VBLaST-SS©). Developing such a simulator involves solving multiple challenges associated with fast collision detection, response and force feedback. MethodsIn this paper, we present a novel projection-intersection based knot detection method, which can identify the validity of different types of knots at haptic update rates. A simple and robust edge-edge based collision detection algorithm is introduced to support interactive knot tying and needle insertion operations. A bimanual hardware interface integrates actual surgical instruments with haptic devices enabling not only interactive rendering of force feedback but also realistic sensation of needle grasping, which realizes an immersive surgical suturing environment. ResultsExperiments on performing the FLS intracorporeal suturing task show that the simulator is able to run on a standard personal computer at interactive rates. ConclusionsVBLaST-SS© is a computer-based interactive virtual simulation system for FLS intracorporeal knot-tying suturing task that can provide real-time objective assessment for the user’s performance.

FIDOOP: PARALLEL MINING OF FREQUENT ITEM SETS USING MAPREDUCE

Due to the exponential increase of real-time data monitoring systems, the extraction of frequent item (Frequent item set mining) set from large uncertain database is the challenging task. The existing parallel mining algorithm for frequent item sets includes the limitations in terms of more memory usage and excessive run time even for less amount of data. To overcome this problem, the FiDoop based item set mining algorithm is proposed by using map reduce framework. It is used to improve the performance of load balancing operation in an uncertain database for computing frequent patterns. This system includes data uploading, preprocessing, threshold, find support and confidence, merge and result. Initially, the data is selected from the dataset and uploaded in the server. Afterwards, the preprocessing stage removes columns which contains unwanted entries. The information is analyzed and partitioned to compute threshold value. These data are classified depends on threshold values and the clustering algorithm is used to find high support and confidence values among clusters to discover frequent item. Finally, those frequent item sets are merged to acquire a frequent pattern. The proposed system is mainly developed for improving the accuracy and it is evaluated based on the performance measures of accuracy, memory usage and execution time.

Resting state intrinsic EEG impacts on go stimulus-response processes.

Neuropsychological research and practice rely on cognitive task performance measures as indicators of brain functioning. The neural activity underlying stimulus-response processes can be assessed with ERPs, but the relations between these cognitive processes and the brain's intrinsic resting state EEG activity are less understood. This study focused on the neurocognitive functioning of 20 healthy young adults in an equiprobable go/no-go task to map the ERP correlates of behavioral responses and examine contributions of the resting state intrinsic EEG to task-related outcomes. Continuous EEG was recorded during pretask eyes-closed (EC) and eyes-open (EO) conditions, and in the subsequent task. Delta, theta, alpha, and beta band amplitudes were assessed for the EC state and also for the reactive change to EO. Go/no-go ERPs were submitted to temporal principal components analysis, where the P2, N2, P3, and slow wave components of interest were extracted. The performance measure of reaction time (RT) variability was positively correlated with no-go and go errors, and also with go P2 amplitude, linking these to stimulus discrimination efforts involved in appropriate response selection. An N2c-P3b pairing was enhanced for shorter mean RTs, supporting their involvement in the decision to execute a response. A stepwise regression model identified EC midline delta as a predictor of P3b positivity, highlighting the relevance of delta in the neural mechanisms of attentional processes. These findings clarify the electrophysiology underlying decision-making processes in executive function, and provide a platform for further research assessing performance outcomes in larger samples and in developmental/clinical contexts.

Effect of routing flexibility and sequencing rules on performance of stochastic flexible job shop manufacturing system with setup times: Simulation approach

Routing flexibility is a major contributor towards flexibility of a flexible job shop manufacturing system. This article focuses on a simulation-based experimental study on the effect of routing flexibility and sequencing rules on the performance of a stochastic flexible job shop manufacturing system with sequence-dependent setup times while considering dynamic arrival of job types. Six route flexibility levels and six sequencing rules are considered for detailed study. The performance of manufacturing system is evaluated in terms of flow time related and due date–related measures. Results reveal that routing flexibility and sequencing rules have significant impact on system performance, and the performance of a system can be increased by incorporating routing flexibility. Furthermore, the system performance starts deteriorating as the level of route flexibility is increased beyond a particular limit for a specified sequencing rule. The statistical analysis of the results indicates that when flexibility exists, earliest due date rule emerges as a best sequencing rule for maximum flow time, mean tardiness and maximum tardiness performance measures. Furthermore, smallest setup time rule is better than other sequencing rules for mean flow time and number of tardy jobs performance measures. Route flexibility level two provides best performance for all considered measures.

An optimized protocol for generation and analysis of Ion Proton sequencing reads for RNA-Seq.

BackgroundPrevious studies compared running cost, time and other performance measures of popular sequencing platforms. However, comprehensive assessment of library construction and analysis protocols for Proton sequencing platform remains unexplored. Unlike Illumina sequencing platforms, Proton reads are heterogeneous in length and quality. When sequencing data from different platforms are combined, this can result in reads with various read length. Whether the performance of the commonly used software for handling such kind of data is satisfactory is unknown.ResultsBy using universal human reference RNA as the initial material, RNaseIII and chemical fragmentation methods in library construction showed similar result in gene and junction discovery number and expression level estimated accuracy. In contrast, sequencing quality, read length and the choice of software affected mapping rate to a much larger extent. Unspliced aligner TMAP attained the highest mapping rate (97.27 % to genome, 86.46 % to transcriptome), though 47.83 % of mapped reads were clipped. Long reads could paradoxically reduce mapping in junctions. With reference annotation guide, the mapping rate of TopHat2 significantly increased from 75.79 to 92.09 %, especially for long (>150 bp) reads. Sailfish, a k-mer based gene expression quantifier attained highly consistent results with that of TaqMan array and highest sensitivity.ConclusionWe provided for the first time, the reference statistics of library preparation methods, gene detection and quantification and junction discovery for RNA-Seq by the Ion Proton platform. Chemical fragmentation performed equally well with the enzyme-based one. The optimal Ion Proton sequencing options and analysis software have been evaluated.Electronic supplementary materialThe online version of this article (doi:10.1186/s12864-016-2745-8) contains supplementary material, which is available to authorized users.

Quantum speed problem: Theoretical hints for control

The transition time between states plays an important role in designing quantum devices as they are very sensitive to environmental influences. Decoherence phenomenon is responsible for possible destructions of the entanglement that is a fundamental requirement to implement quantum information processing systems. If the time between states is minimized, the decoherence effects can be reduced, thus, it is advantageous to the designer to develop expressions for time performance measures. Quantum speed limit (QSL) problem has been studied from the theoretical point of view, providing general results. Considering the implementation of quantum control systems, as the decoherence phenomenon is unavoidable, it is important to apply these general results to particular cases, developing expressions and performance measures, to assist control engineering designers. Here, a minimum time performance measure is defined for quantum control problems, for time-independent or time-dependent Hamiltonians, and applied to some practical examples, providing hints that may be useful for researchers pursuing optimization strategies for quantum control systems.

Are All Stroke Patients Eligible for Fast Alteplase Treatment? An Analysis of Unavoidable Delays.

The National Quality Forum recently endorsed a performance measure for time to intravenous thrombolytic therapy which allows exclusions for circumstances in which fast alteplase treatment may not be possible. However, the frequency and impact of unavoidable patient reasons for long door-to-needle time (DNT), such as need for medical stabilization, are largely unknown in clinical practice. As part of the Hurry Acute Stroke Treatment and Evaluation-2 (HASTE-2) project, we sought to identify patient and systems reasons associated with longer DNT. From June 2012 to June 2013 we collected data on DNT and potential reasons for delays from 102 consecutive patients presenting directly to the emergency department who were treated with alteplase within 4.5 hours of symptom onset. Mean age was 71 years, 56/113 (54%) were women, median NIH Stroke Scale score was 13, and median DNT was 53 minutes. Potential delays were noted in 59/102 (58%), of which 31/102 (31%) were unavoidable patient-related or eligibility reasons. Median DNT was longer when patient-related or eligibility reasons for delay were present (60 minutes) than when absent (45 minutes, p = 0.005). Multivariable modeling showed that need for urgent medical stabilization, presentation with seizure and inability to confirm eligibility were associated with 35%-50% longer DNT times. Up to 31% of patients have delays due to medical or eligibility-related causes that may be legitimate reasons for providing alteplase later than the benchmark time of 60 minutes.

Performance measure for reliable travel time of emergency vehicles

Travel time is very critical for emergency response and emergency vehicle (EV) operations. Compared to ordinary vehicles (OVs), EVs are permitted to break conventional road rules to reach the destination within shorter time. However, very few previous studies address the travel time performance of EVs. This study obtained nearly 4-year EV travel time data in Northern Virginia (NOVA) region using 76,000 preemption records at signalized intersections. First, the special characteristics of EV travel time are explored in mean, median, standard deviation and also the distribution, which display largely different characteristics from that of OVs in previous studies. Second, a utility-based model is proposed to quantify the travel time performance of EVs. Third, this paper further investigates two important components of the utility model: benchmark travel time and standardized travel time. The mode of the distribution is chosen as benchmark travel time, and its nonlinear decreasing relationship with the link length is revealed. At the same time, the distribution of standardized travel time is fitted with different candidate distributions and Inv. Gaussian distribution is proved to be the most suitable one. Finally, to validate the proposed model, we implement the model in case studies to estimate link and route travel time performance. The results of route comparisons also show that the proposed model can support EV route choice and eventually improve EV service and operations.

A mobile asset sharing policy for hospitals with real time locating systems.

Each year, hospitals lose a considerable amount of time and money due to misplaced mobile assets. In addition the assets which remain in departments that frequently use them depreciate early, while other assets of the same type in different departments are rarely used. A real time locating system can prevent these losses when used with appropriate asset sharing policies. This research quantifies the amount of time a medium size hospital saves by using real time locating system and proposes an asset selection rule to eliminate the asset usage imbalance problem. The asset selection rule proposed is based on multi objective optimization techniques. The effectiveness of this rule on asset to patient time and asset utilization rate variance performance measures were tested using discrete event simulation method. Results show that the proposed asset selection rule improved the usage balance significantly. Sensitivity analysis showed that the proposed rule is robust to changes in demand rates and user preferences. Real time locating systems enable saving considerable amount of time in hospitals, and they can still be improved by integrating decision support mechanisms. Combining tracking technology and asset selection rules helps improve healthcare services.

Performance analysis of dispatching rules in a stochastic dynamic job shop manufacturing system with sequence-dependent setup times: Simulation approach

Stochastic dynamic job shop scheduling problem with consideration of sequence-dependent setup times are among the most difficult classes of scheduling problems. This paper assesses the performance of nine dispatching rules in such shop from makespan, mean flow time, maximum flow time, mean tardiness, maximum tardiness, number of tardy jobs, total setups and mean setup time performance measures viewpoint. A discrete event simulation model of a stochastic dynamic job shop manufacturing system is developed for investigation purpose. Nine dispatching rules identified from literature are incorporated in the simulation model. The simulation experiments are conducted under different levels of shop utilization and setup time. The important aspects of the results of the simulation investigation are also discussed in detail.

The association between the transfer of emergency department admitted patients to inpatient hallways and outcomes of oncology patients

Objective: A protocol was implemented to ease Emergency Department (ED) crowding by moving suitable admitted patients into inpatient hallway beds (HALL) or off-service beds (OFF) when beds on an admitting service’s designated ward (ON) were not available. This study assessed the impact of hallway and off-service oncology admissions on ED patient flow, quality of care and patient satisfaction.Methods: Retrospective and prospective data were collected on patients admitted to the medical oncology service from Jan 1 to Dec 31, 2011. Data on clinician assessments and time performance measures were collected. Satisfaction surveys were prospectively administered to all patients. Results: Two hundred and ninty-seven patients (117 HALL, 90 OFF, 90 ON) were included in this study. There were no significant differences between groups for frequency of physician assessments, physical exam maneuvers at initial physician visit, time to complete vital signs or time to medication administration. The median (IQR) time spent admitted in the ED prior to departure from the ED was significantly longer for HALL patients (5.53 hrs [1.59-13.03 hrs]) compared to OFF patients (2.00 hrs [0.37-3.69 hrs]) and ON patients (2.18 hrs [0.15-5.57 hrs]) (p &lt; .01). Similarly, the median (IQR) total ED length of stay was significantly longer for HALL patients (13.82 hrs [7.43-20.72 hrs]) compared to OFF patients (7.18 hrs [5.72-11.42 hrs]) and ON patients (9.34 hrs [5.43-14.06 hrs]) (p &lt; .01). HALL patients gave significantly lower overall satisfaction scores with mean (SD) satisfaction scores for HALL, OFF and ON patients being 3.58 (1.20), 4.23 (0.58) and 4.29 (0.69) respectively (p &lt; .01). Among HALL patients, 58% were not comfortable being transferred into the hallway and 4% discharged themselves against medical advice. Conclusions: The protocol for transferring ED admitted patients to inpatient hallway beds did not reduce ED length of stay for oncology patients. The timeliness and frequency of clinical assessments were not compromised; however, patient satisfaction was decreased.

Performance Measures to Characterize Corridor Travel Time Delay Based on Probe Vehicle Data

Anonymous probe vehicle data are being collected on roadways throughout the United States. These data are incorporated into local and statewide mobility reports to measure the performance of highways and arterial systems. Predefined spatially located segments, known as traffic message channels (TMCs), are spatially and temporally joined with probe vehicle speed data. Through the analysis of these data, transportation agencies have been developing agencywide travel time performance measures. One widely accepted performance measure is travel time reliability, which is calculated along a series of TMCs. When reliable travel times are not achieved because of incidents and recurring congestion, it is desirable to understand the time and the location of these occurrences so that the corridor can be proactively managed. This research emphasizes a visually intuitive methodology that aggregates a series of TMC segments based on a cursory review of congestion hotspots within a corridor. Instead of a fixed congestion speed threshold, each TMC is assigned a congestion threshold based on the 70th percentile of the 15-min average speeds between 02:00 and 06:00. An analysis of approximately 90 million speed records collected in 2013 along I-80 in northern New Jersey was performed for this project. Travel time inflation, the time exceeding the expected travel time at 70% of measured free-flow speed, was used to evaluate each of the 166 directional TMC segments along 70 mi of I-80. This performance measure accounts for speed variability caused by roadway geometry and other Highway Capacity Manual speed-reducing friction factors associated with each TMC.

Stochastic Dynamic Job Shop Scheduling with Sequence-Dependent Setup Times: Simulation Experimentation

Stochastic dynamic job shop (SDJS) scheduling problems with sequence-dependent setup times are among the most difficult classes of scheduling problems. This paper assesses the performance of five dispatching rules (DRLs) in such shop from makespan, mean flow time, mean tardiness, number of tardy jobs, total setups, and mean setup time performance measures viewpoint. A discrete event simulation model of a SDJS manufacturing system is developed for investigation purpose. Five DRLs, that is, first come first serve (FCFS), shortest processing time (SPT), shortest setup time (SIMSET), earliest due date (EDD) and shortest sum of setup times and processing time (SSPT) are incorporated in the simulation model. The simulation experiments are conducted under due date tightness factor of 3, shop utilization percentage of 90 and setup time less than processing time. Results indicate that SIMSET rule provides best performance for mean flow time and number of tardy jobs performance measures. The SPT rule provides best performance for mean tardiness measure. The EDD rule is best-performing DRL for makespan, total setups and mean setup time measures.

A neural network-based methodology of quantifying the association between the design variables and the users’ performances

User performance is highly correlated with design variables of a system. Such association can be described as display–control relationship. In this study, a neural network-based methodology is proposed to identify and quantify the association among design variables (inputs) and to compute their relative influences (RIs) on the two performance measures (outputs) of user response time and response accuracy, using artificial neural network, generalised regression neural network, support vector regression (SVR), multiple linear regression and response surface model. Based on the results of the comparison, it is found that neural network-based methods are more reliable than SVR-based methods in computing the RI of design variables. As a result of our analysis, the best option for optimising each of the measures is suggested. Some useful observations about the design of man–machine systems are also presented, discussed and visualised. In the study of man–machine systems, quantitative methods are seldom adopted for examining the mappings between various displays and controls under a variety of operating conditions. The major contribution of this study is to provide some insights into the usefulness of quantitative methods in evaluating man–machine design in terms of display–control compatibility and to extract explanatory information from renowned black box systems such as neural networks.