Competing Swarms of Autonomous Vehicles: Intruders Versus Guardians

2017 ◽  
Author(s):  
Daigo Shishika ◽  
Katarina Sherman ◽  
Derek A. Paley
Keyword(s):  
Protected Area ◽  
Autonomous Vehicles ◽  
Payoff Function ◽  
Time Interval ◽  
Design Strategies ◽  
Time Intervals ◽  
Aerial Vehicles ◽  
Zero Sum ◽  
The Impact ◽  
Probability Of Capture

We consider a competition between two swarms of aerial vehicles, where multiple intruder vehicles try to approach and then leave an area that multiple guardian vehicles are protecting. Pre-existing swarming strategies for the guardians to maximize the probability of capturing a single intruder are summarized. This work considers the case where multiple intruders approach the protected area sequentially with varied time intervals, to study the impact of intrusion frequency on the probability of capture. In addition, we formulate a payoff function treating the competition as a zero-sum game, and use this function to design strategies for the intruders, i.e., how to optimize the time interval between intrusions. We propose an intrusion strategy and demonstrate its performance with numerical simulations.

Abstract 13248: The Impact of Instructions for Covering the Mouth and the Nose on Dispatch-Assisted Cardiopulmonary Resuscitation

Circulation ◽  
2021 ◽  
Vol 144 (Suppl_2) ◽  
Author(s):  
Hidetada Fukushima ◽  
Hideki Asai ◽  
Koji Yamamoto ◽  
Yasuyuki Kawai
Keyword(s):  
Cardiopulmonary Resuscitation ◽  
Median Time ◽  
Chest Compression ◽  
Fire Department ◽  
Emergency Call ◽  
Time Interval ◽  
Time Intervals ◽  
Median Time Interval ◽  
Study Results ◽  
The Impact

Introduction: Under the SARS-CoV-2 pandemic, rescuers are recommended to cover their mouth and nose with a facemask or a cloth as well as victim’s mouth and nose when performing cardiopulmonary resuscitation (CPR). However, its impact on dispatch-assisted CPR (DACPR) has not been investigated well. Hypothesis: DACPR including the instruction for covering the rescuer’s and the victim’s mouth and nose can significantly delay the start of the first chest compression. Methods: We retrospectively analyzed DACPR records of the Nara Wide Area Fire Department, covering population of 853,000/3361km 2 , in Japan. We investigated the key time intervals of 505 DACPR records between May 2020 and March 2021. We also compared the results to that of the same period in 2019 (535 records). Results: Dispatchers failed to provide mask instruction in 322 cases (63.8%). The median time interval from the emergency call and the start of CPR instruction was longer in 2020 (197 seconds vs 190 seconds, p=0.641). The time to the first chest compression was also delayed in 2020 (264 seconds vs 246 seconds, p=0.015). Among the cases that dispatchers successfully provided mask instruction (183 cases, 36.2%), median time intervals to the start of instruction and the first chest compression were relatively faster than cases without mask instruction (177 seconds vs 211 seconds and 254 seconds vs 269.5 seconds, respectively). Conclusions: Dispatchers failed to provide mask instruction in the majority of CA cases. However, our study results indicate that the impact of mask instruction on DACPR can be minor in terms of immediate CPR provision.

scholarly journals Clinical Outcome of Spine Surgery Complicated by Accidental Dural Tears: Meta-Analysis of the Literature

2020 ◽  
pp. 219256822091487
Author(s):  
Zeiad A. F. Alshameeri ◽  
El-Nasri Ahmed ◽  
Vinay Jasani
Keyword(s):  
Back Pain ◽  
Clinical Outcome ◽  
Spinal Surgery ◽  
Short Form ◽  
Meta Analysis ◽  
Systemic Review ◽  
Time Interval ◽  
Time Intervals ◽  
Dural Tears ◽  
The Impact

Study Design: Systemic review and meta-analysis. Objectives: Several studies have reported the impact of accidental dural tears (DT) on the outcome of spinal surgery, some with conflicting results. Therefore, the aim of this study was to carry out a systemic review and meta-analysis of the literature to establish the overall clinical outcome of spinal surgery following accidental DT. Method: A systemic literature search was carried out. Postoperative improvement in Oswestry Disability Index (ODI), Short-Form 36 survey (SF36), leg pain visual analogue scale (VAS), and back pain VAS were compared between patients with and without DT at different time intervals. Results: Eleven studies were included in this meta-analysis. There was a slightly better improvement in ODI and leg VAS score (standardized mean difference of −0.06, 95% confidence interval [CI] −0.12 to −0.01, and −0.06, 95% CI −0.09 to −0.02, respectively) in patients without DT at 12 months postsurgery, but this effect was not demonstrated at any other time intervals up to 4 years. There were no differences in the overall SF36 (function) score at any time interval or back pain VAS at 12 months. Conclusion: Based on this study, accidental DT did not have an overall significant adverse impact on the short-term clinical outcome of spinal surgery. More studies are needed to address the long-term impact and other outcome measures including other immediate complications of DT.

Controlling Grass Weeds on Hard Surfaces: Effect of Time Intervals between Flame Treatments

2012 ◽  
Vol 26 (1) ◽  
pp. 83-88 ◽  
Author(s):  
Anne M. Rask ◽  
Palle Kristoffersen ◽  
Christian Andreasen
Keyword(s):  
Perennial Ryegrass ◽  
Aboveground Biomass ◽  
Plant Biomass ◽  
Time Interval ◽  
Time Intervals ◽  
Short Treatment ◽  
Annual Bluegrass ◽  
Treatment Interval ◽  
Effect Of Treatment ◽  
The Impact

An experiment was conducted on a specially designed hard surface to study the impact of time interval between flaming treatments on the regrowth and flower production of two grass weeds. The goal of this experiment was to optimize the control of annual bluegrass and perennial ryegrass, both species that are very difficult to control without herbicides. Aboveground biomass from 72 plants per treatment was harvested and dry weights were recorded at regular intervals to investigate how the plants responded to flaming. Regrowth of the grasses was measured by harvesting aboveground biomass 2 wk after the second flaming treatments that were implemented at different time intervals. Flaming treatments decreased plant biomass of both species and also the ratio of flowering annual bluegrass plants. However, few plants were killed. The first flaming treatment affected aboveground biomass more than the second flaming treatment. A treatment interval of 7 d provided the greatest reduction in regrowth of perennial ryegrass, whereas the effect of treatment interval varied between the first and second repetitions of this experiment for annual bluegrass. In general, short treatment intervals (3 d) should be avoided, as they did not increase the reduction of aboveground biomass compared with the 7-d treatment interval. Knowledge on the regrowth of grass weeds after flaming treatments provided by this study can help improve recommendations given to road keepers and park managers for management on these weeds.

scholarly journals Spatiotemporal variability of water vapor investigated using lidar and FTIR vertical soundings above the Zugspitze

2015 ◽  
Vol 15 (6) ◽  
pp. 3135-3148 ◽  
Author(s):  
H. Vogelmann ◽  
R. Sussmann ◽  
T. Trickl ◽  
A. Reichert
Keyword(s):  
Water Vapor ◽  
Spatiotemporal Variability ◽  
Time Interval ◽  
Short Time Interval ◽  
Horizontal Distance ◽  
Free Troposphere ◽  
Time Intervals ◽  
Matching Criteria ◽  
The Impact ◽  
Relative Variability

Abstract. Water vapor is the most important greenhouse gas and its spatiotemporal variability strongly exceeds that of all other greenhouse gases. However, this variability has hardly been studied quantitatively so far. We present an analysis of a 5-year period of water vapor measurements in the free troposphere above the Zugspitze (2962 m a.s.l., Germany). Our results are obtained from a combination of measurements of vertically integrated water vapor (IWV), recorded with a solar Fourier transform infrared (FTIR) spectrometer on the summit of the Zugspitze and of water vapor profiles recorded with the nearby differential absorption lidar (DIAL) at the Schneefernerhaus research station. The special geometrical arrangement of one zenith-viewing and one sun-pointing instrument and the temporal resolution of both instruments allow for an investigation of the spatiotemporal variability of IWV on a spatial scale of less than 1 km and on a timescale of less than 1 h. The standard deviation of differences between both instruments σIWV calculated for varied subsets of data serves as a measure of variability. The different subsets are based on various spatial and temporal matching criteria. Within a time interval of 20 min, the spatial variability becomes significant for horizontal distances above 2 km, but only in the warm season (σIWV =0.35 mm). However, it is not sensitive to the horizontal distance during the winter season. The variability of IWV within a time interval of 30 min peaks in July and August (σIWV > 0.55 mm, mean horizontal distance = 2.5 km) and has its minimum around midwinter (σIWV < 0.2 mm, mean distance > 5 km). The temporal variability of IWV is derived by selecting subsets of data from both instruments with optimal volume matching. For a short time interval of 5 min, the variability is 0.05 mm and increases to more than 0.5 mm for a time interval of 15 h. The profile variability of water vapor is determined by analyzing subsets of water vapor profiles recorded by the DIAL within time intervals from 1 to 5 h. For all altitudes, the variability increases with widened time intervals. The lowest relative variability is observed in the lower free troposphere around an altitude of 4.5 km. Above 5 km, the relative variability increases continuously up to the tropopause by about a factor of 3. Analysis of the covariance of the vertical variability reveals an enhanced variability of water vapor in the upper troposphere above 6 km. It is attributed to a more coherent flow of heterogeneous air masses, while the variability at lower altitudes is also driven by local atmospheric dynamics. By studying the short-term variability of vertical water vapor profiles recorded within a day, we come to the conclusion that the contribution of long-range transport and the advection of heterogeneous layer structures may exceed the impact of local convection by 1 order of magnitude even in the altitude range between 3 and 5 km.

Impact of delta check time intervals on error detection capability

2020 ◽  
Vol 58 (3) ◽  
pp. 384-389 ◽  
Author(s):  
Rui Zhen Tan ◽  
Corey Markus ◽  
Tze Ping Loh
Keyword(s):  
Error Detection ◽  
False Positive ◽  
Time Window ◽  
Laboratory Data ◽  
Absolute Difference ◽  
Time Interval ◽  
Time Intervals ◽  
Patient Will ◽  
Mean Corpuscular Haemoglobin ◽  
The Impact

AbstractBackgroundThe delta check time interval limit is the maximum time window within which two sequential results of a patient will be evaluated by the delta check rule. The impact of time interval on delta check performance is not well studied.MethodsDe-identified historical laboratory data were extracted from the laboratory information system and divided into children (≤18 years) and adults (>21 years). The relative and absolute differences of the original pair of results from each patient were compared against the delta check limits associated with 90% specificity. The data were then randomly reshuffled to simulate a switched (misidentified) sample scenario. The data were divided into 1-day, 3-day, 7-day, 14-day, 1-month, 3-month, 6-month and 1-year time interval bins. The true positive- and false-positive rates at different intervals were examined.ResultsOverall, 24 biochemical and 20 haematological tests were analysed. For nearly all the analytes, there was no statistical evidence of any difference in the true- or false-positive rates of the delta check rules at different time intervals when compared to the overall data. The only exceptions to this were mean corpuscular volume (using both relative- and absolute-difference delta check) and mean corpuscular haemoglobin (only absolute-difference delta check) in the children population, where the false-positive rates became significantly lower at 1-year interval.ConclusionsThis study showed that there is no optimal delta check time interval. This fills an important evidence gap for future guidance development.

scholarly journals Spatiotemporal access to emergency medical services in Wuhan, China: accounting for scene and transport time intervals

2020 ◽  
Vol 19 (1) ◽  
Author(s):  
Weicong Luo ◽  
Jing Yao ◽  
Richard Mitchell ◽  
Xiaoxiang Zhang
Keyword(s):  
Travel Time ◽  
Medical Service ◽  
Time Interval ◽  
Time Intervals ◽  
Transport Time ◽  
Emergency Medical ◽  
Hospital Access ◽  
Administrative Unit ◽  
Peripheral Areas ◽  
The Impact

Abstract Background Access as a primary indicator of Emergency Medical Service (EMS) efficiency has been widely studied over the last few decades. Most previous studies considered one-way trips, either getting ambulances to patients or transporting patients to hospitals. This research assesses spatiotemporal access to EMS at the shequ (the smallest administrative unit) level in Wuhan, China, attempting to fill a gap in literature by considering and comparing both trips in the evaluation of EMS access. Methods Two spatiotemporal access measures are adopted here: the proximity-based travel time obtained from online map services and the enhanced two-step floating catchment area (E-2SFCA) which is a gravity-based model. First, the travel time is calculated for the two trips involved in one EMS journey: one is from the nearest EMS station to the scene (i.e. scene time interval (STI)) and the other is from the scene to the nearest hospital (i.e. transport time interval (TTI)). Then, the predicted travel time is incorporated into the E-2SFCA model to calculate the access measure considering the availability of the service provider as well as the population in need. For both access measures, the calculation is implemented for peak hours and off-peak hours. Results Both methods showed a marked decrease in EMS access during peak traffic hours, and differences in spatial patterns of ambulance and hospital access. About 73.9% of shequs can receive an ambulance or get to the nearest hospital within 10 min during off-peak periods, and this proportion decreases to about 45.5% for peak periods. Most shequs with good ambulance access but poor hospital access are in the south of the study area. In general, the central areas have better ambulance, hospital and overall access than peripheral areas, particularly during off-peak periods. Conclusions In addition to the impact of peak traffic periods on EMS access, we found that good ambulance access does not necessarily guarantee good hospital access nor the overall access, and vice versa.

Impact of Timing Between Insulin Administration and Meal Consumption on Glycemic Fluctuation and Outcomes in Hospitalized Patients With Type 2 Diabetes

2018 ◽  
Vol 33 (4) ◽  
pp. 449-456 ◽  
Author(s):  
Shu Fang Lim ◽  
Michelle Jong ◽  
Daniel Ek Kwang Chew ◽  
Joyce Yu-Chia Lee
Keyword(s):  
Type 2 Diabetes ◽  
Insulin Injection ◽  
Hospitalized Patients ◽  
Time Interval ◽  
Time Intervals ◽  
Sliding Scale ◽  
Meal Time ◽  
The Impact ◽  
Meal Consumption

Background The effect of time interval from insulin injection to meal consumption (“insulin-meal”) on glycemic fluctuation and outcomes is not well understood. Objective This study aims to investigate the impact of coordinated versus mismatched insulin-meal administration on glycemic fluctuation and outcomes among hospitalized patients with type 2 diabetes (T2D). Methods Hospitalized patients with T2D who received at least 1 dose of insulin as part of sliding scale regimen were included. Data such as capillary blood glucose values and insulin-meal time intervals were collected. Results A total of 215 patients with 840 insulin-meal encounters were eligible for the study. Compared to the insulin-meal mismatch group (n = 206), the coordinated insulin-meal administration group (n = 9) had lower mean glycemic fluctuation (6.5 [2.6] mmol/L vs 5.6 [2.5] mmol/L or 117 [47] mg/dL vs 100 [45] mg/dL). Encounters with the insulin-meal time interval of 30 to 45 minutes (n = 172) were associated with the lowest percentage of severe hyperglycemia occurrences (13%) as compared to encounters with time interval of 0 to 29 minutes (n = 280, 15%) and more than 45 minutes (n = 246, 16%). Conclusion Coordinated insulin-meal administration was associated with lower glycemic fluctuation among hospitalized patients with T2D.

scholarly journals On selection of the optimal data time interval for real-time hydrological forecasting

2013 ◽  
Vol 17 (9) ◽  
pp. 3639-3659 ◽  
Author(s):  
J. Liu ◽  
D. Han
Keyword(s):  
Real Time ◽  
Case Studies ◽  
Time Interval ◽  
Rainfall Runoff ◽  
Time Intervals ◽  
Hydrological Forecasting ◽  
Forecast Lead Time ◽  
The Future ◽  
The Impact ◽  
Selection Of

Abstract. With the advancement in modern telemetry and communication technologies, hydrological data can be collected with an increasingly higher sampling rate. An important issue deserving attention from the hydrological community is which suitable time interval of the model input data should be chosen in hydrological forecasting. Such a problem has long been recognised in the control engineering community but is a largely ignored topic in operational applications of hydrological forecasting. In this study, the intrinsic properties of rainfall–runoff data with different time intervals are first investigated from the perspectives of the sampling theorem and the information loss using the discrete wavelet transform tool. It is found that rainfall signals with very high sampling rates may not always improve the accuracy of rainfall–runoff modelling due to the catchment low-pass-filtering effect. To further investigate the impact of a data time interval in real-time forecasting, a real-time forecasting system is constructed by incorporating the probability distributed model (PDM) with a real-time updating scheme, the autoregressive moving-average (ARMA) model. Case studies are then carried out on four UK catchments with different concentration times for real-time flow forecasting using data with different time intervals of 15, 30, 45, 60, 90 and 120 min. A positive relation is found between the forecast lead time and the optimal choice of the data time interval, which is also highly dependent on the catchment concentration time. Finally, based on the conclusions from the case studies, a hypothetical pattern is proposed in three-dimensional coordinates to describe the general impact of the data time interval and to provide implications of the selection of the optimal time interval in real-time hydrological forecasting. Although nowadays most operational hydrological systems still have low data sampling rates (daily or hourly), the future is that higher sampling rates will become more widespread, and there is an urgent need for hydrologists both in academia and in the field to realise the significance of the data time interval issue. It is important that more case studies in different catchments with various hydrological forecasting systems are explored in the future to further verify and improve the proposed hypothetical pattern.

scholarly journals On selection of the optimal data time interval for real-time hydrological forecasting

2012 ◽  
Vol 9 (9) ◽  
pp. 10829-10875
Author(s):  
J. Liu ◽  
D. Han
Keyword(s):  
Real Time ◽  
Case Studies ◽  
Time Interval ◽  
Rainfall Runoff ◽  
Time Intervals ◽  
Hydrological Forecasting ◽  
Forecast Lead Time ◽  
The Future ◽  
The Impact ◽  
Selection Of

Abstract. With the advancement in modern telemetry and communication technologies, hydrological data can be collected with an increasingly higher sampling rate. An important issue deserving attention from the hydrological community is what suitable time interval of the model input data should be chosen in hydrological forecasting. Such a problem has long been recognised in the control engineering community but is a largely ignored topic in operational applications of hydrological forecasting. In this study, the intrinsic properties of rainfall-runoff data with different time intervals are first investigated from the perspectives of the sampling theorem and the information loss using the discrete wavelet decomposition tool. It is found that rainfall signals with very high sampling rates may not always improve the accuracy of rainfall-runoff modelling due to the catchment low-pass filtering effect. To further investigate the impact of data time interval in real-time forecasting, a real-time forecasting system is constructed by incorporating the Probability Distributed Model (PDM) with a real-time updating scheme, the autoregressive-moving average (ARMA) model. Case studies are then carried out on four UK catchments with different concentration times for real-time flow forecasting using data with different time intervals of 15 min, 30 min, 45 min, 60 min, 90 min and 120 min. A positive relation is found between the forecast lead time and the optimal choice of the data time interval, which is also highly dependent on the catchment concentration time. Finally, based on the conclusions from the case studies, a hypothetical pattern is proposed in three-dimensional coordinates to describe the general impact of the data time interval and to provide implications on the selection of the optimal time interval in real-time hydrological forecasting. Although nowadays most operational hydrological systems still have low data sampling rates (daily or hourly), the trend in the future is that higher sampling rates will become widespread and there is an urgent need for both academic and practising hydrologists to realise the significance of the data time interval issue. It is important that more case studies in different catchments with various hydrological forecasting models should be explored in the future to further verify and improve the proposed hypothetical pattern.

scholarly journals New Mobility Model for Mobile and Geographic Cross-layer Architecture for Mobile IoT Networks

2021 ◽  
Author(s):  
Ridouane El Mezouary ◽  
Abdelmoghit Souissi
Keyword(s):  
Mathematical Model ◽  
Mobility Model ◽  
Service Differentiation ◽  
Mobile Internet ◽  
Cross Layer ◽  
Time Interval ◽  
Mac Layer ◽  
Time Intervals ◽  
The Impact ◽  
The Mathematical Model

Abstract In this article, we propose a new mobility model, for a mobile and geographic cross-layer architecture. This cross-layer architecture allows service differentiation between real-time and best-effort traffic, for a mobile internet of things ( IoT ) network. We present a mathematical model, which works on the parameters of the MAC layer and the network layer. The mathematical model makes it possible to calculate the throughput between a source object and a destination object (gateway), under conditions of stable queues. We use the positional (geographic) information in the mathematical model of the proposed cross-layer architecture, to study the impact of mobility on the performance of the proposed mathematical model. The proposed mobility model defines two time intervals, the first interval for communication (transmission and reception of data without mobility at the same time), and the second time interval for the mobility of objects of the IoT network (without communication at the same time). The results show that the calculated throughput depends on the position of the objects, as well as the probability of transmission. Finally, we study the effect of distance and speed on the performance of the proposed cross-layer architecture.

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