scholarly journals Case Study of Drone Delivery Reliability for Time-Sensitive Medical Supplies With Stochastic Demand and Meteorological Conditions

2021 ◽  
pp. 036119812110366
Author(s):  
Travis B. Glick ◽  
Miguel A. Figliozzi ◽  
Avinash Unnikrishnan
Keyword(s):  
Probability Distributions ◽  
Real Data ◽  
Consumer Products ◽  
Meteorological Conditions ◽  
Modeling Framework ◽  
Fleet Size ◽  
Medical Supplies ◽  
Size Population ◽  
Delivery Reliability

Drones are increasingly being utilized to deliver medical supplies, and the COVID-19 pandemic has accelerated this trend. Drones arrive quickly by taking more direct paths and avoiding ground-based obstructions. However, drones are not completely reliable and may also experience failures and delays. For consumer products, delivery delays are an inconvenience, but for some medical supplies, delays may be fatal. This research focused on the drone reliability of one particular type of supply and event: automatic defibrillators for out-of-hospital cardiac arrests. A modeling framework was developed to analyze drone delivery reliability with stochastic demands and meteorological conditions. Using probability distributions based on real data from Portland, OR, this research quantified the failure rates as a function of drone range and meteorological conditions that included temperature, precipitation, and wind. Tradeoffs among drone reliability, fleet size, population size, and meteorological conditions were analyzed.

Investigation of a New Approach to Predict Water Quality Extremes with a Case Study of Chemical Determinands in Stream Water

1991 ◽  
Vol 24 (6) ◽  
pp. 25-33
Author(s):  
A. J. Jakeman ◽  
P. G. Whitehead ◽  
A. Robson ◽  
J. A. Taylor ◽  
J. Bai
Keyword(s):  
Water Quality ◽  
Stream Water ◽  
Probability Distributions ◽  
Management Strategies ◽  
Hybrid Modelling ◽  
Trend Model ◽  
Environmental Extremes ◽  
Modelling Approach

The paper illustrates analysis of the assumptions of the statistical component of a hybrid modelling approach for predicting environmental extremes. This shows how to assess the applicability of the approach to water quality problems. The analysis involves data on stream acidity from the Birkenes catchment in Norway. The modelling approach is hybrid in that it uses: (1) a deterministic or process-based description to simulate (non-stationary) long term trend values of environmental variables, and (2) probability distributions which are superimposed on the trend values to characterise the frequency of shorter term concentrations. This permits assessment of management strategies and of sensitivity to climate variables by adjusting the values of major forcing variables in the trend model. Knowledge of the variability about the trend is provided by: (a) identification of an appropriate parametric form of the probability density function (pdf) of the environmental attribute (e.g. stream acidity variables) whose extremes are of interest, and (b) estimation of pdf parameters using the output of the trend model.

scholarly journals Extreme avalanche cycles: Return levels and probability distributions depending on snow and meteorological conditions

2021 ◽  
pp. 100344
Author(s):  
Guillaume Evin ◽  
Pascal Dkengne Sielenou ◽  
Nicolas Eckert ◽  
Philippe Naveau ◽  
Pascal Hagenmuller ◽  
...  
Keyword(s):  
Probability Distributions ◽  
Meteorological Conditions ◽  
Return Levels

scholarly journals Towards DC Energy Efficient Homes

2021 ◽  
Vol 11 (13) ◽  
pp. 6005
Author(s):  
Daniel Villanueva ◽  
Moisés Cordeiro-Costas ◽  
Andrés E. Feijóo-Lorenzo ◽  
Antonio Fernández-Otero ◽  
Edelmiro Miguez-García
Keyword(s):  
Energy Efficiency ◽  
Electric Vehicles ◽  
Energy Efficient ◽  
Electricity Consumption ◽  
Real Data ◽  
Mean Values ◽  
Led Lighting ◽  
Shed Light

The aim of this paper is to shed light on the question regarding whether the integration of an electric battery as a part of a domestic installation may increase its energy efficiency in comparison with a conventional case. When a battery is included in such an installation, two types of electrical conversion must be considered, i.e., AC/DC and DC/AC, and hence the corresponding losses due to these converters must not be forgotten when performing the analysis. The efficiency of the whole system can be increased if one of the mentioned converters is avoided or simply when its dimensioning is reduced. Possible ways to achieve this goal can be: to use electric vehicles as DC suppliers, the use of as many DC home devices as possible, and LED lighting or charging devices based on renewables. With all this in mind, several scenarios are proposed here in order to have a look at all possibilities concerning AC and DC powering. With the aim of checking these scenarios using real data, a case study is analyzed by operating with electricity consumption mean values.

scholarly journals Scalable information-theoretic path planning for a rover-helicopter team in uncertain environments

2021 ◽  
Vol 18 (2) ◽  
pp. 172988142199958
Author(s):  
Larkin Folsom ◽  
Masahiro Ono ◽  
Kyohei Otsu ◽  
Hyoshin Park
Keyword(s):  
Path Planning ◽  
Lower Risk ◽  
Information Gain ◽  
Probability Distributions ◽  
Single Agent ◽  
Uncertain Environments ◽  
Information Theoretic ◽  
Highly Correlated ◽  
Naive Approach

Mission-critical exploration of uncertain environments requires reliable and robust mechanisms for achieving information gain. Typical measures of information gain such as Shannon entropy and KL divergence are unable to distinguish between different bimodal probability distributions or introduce bias toward one mode of a bimodal probability distribution. The use of a standard deviation (SD) metric reduces bias while retaining the ability to distinguish between higher and lower risk distributions. Areas of high SD can be safely explored through observation with an autonomous Mars Helicopter allowing safer and faster path plans for ground-based rovers. First, this study presents a single-agent information-theoretic utility-based path planning method for a highly correlated uncertain environment. Then, an information-theoretic two-stage multiagent rapidly exploring random tree framework is presented, which guides Mars helicopter through regions of high SD to reduce uncertainty for the rover. In a Monte Carlo simulation, we compare our information-theoretic framework with a rover-only approach and a naive approach, in which the helicopter scouts ahead of the rover along its planned path. Finally, the model is demonstrated in a case study on the Jezero region of Mars. Results show that the information-theoretic helicopter improves the travel time for the rover on average when compared with the rover alone or with the helicopter scouting ahead along the rover’s initially planned route.

Why Does Construct Validity Matter in Measuring Implementation Fidelity? A Methodological Case Study

2021 ◽  
pp. 153450842199877
Author(s):  
Wilhelmina van Dijk ◽  
A. Corinne Huggins-Manley ◽  
Nicholas A. Gage ◽  
Holly B. Lane ◽  
Michael Coyne
Keyword(s):  
Construct Validity ◽  
Reading Instruction ◽  
Model Building ◽  
Implementation Fidelity ◽  
Modeling Framework ◽  
Relative Rank ◽  
Rank Ordering ◽  
Adherence Data ◽  
Funded Project

In reading intervention research, implementation fidelity is assumed to be positively related to student outcomes, but the methods used to measure fidelity are often treated as an afterthought. Fidelity has been conceptualized and measured in many different ways, suggesting a lack of construct validity. One aspect of construct validity is the fidelity index of a measure. This methodological case study examined how different decisions in fidelity indices influence relative rank ordering of individuals on the construct of interest and influence our perception of the relation between the construct and intervention outcomes. Data for this study came from a large State-funded project to implement multi-tiered systems of support for early reading instruction. Analyses were conducted to determine whether the different fidelity indices are stable in relative rank ordering participants and if fidelity indices of dosage and adherence data influence researcher decisions on model building within a multilevel modeling framework. Results indicated that the fidelity indices resulted in different relations to outcomes with the most commonly used fidelity indices for both dosage and adherence being the worst performing. The choice of index to use should receive considerable thought during the design phase of an intervention study.

scholarly journals Life Cycle Assessment and Judgement

NanoEthics ◽  
2020 ◽  
Vol 14 (3) ◽  
pp. 271-283
Author(s):  
Christopher Nathan ◽  
Stuart Coles
Keyword(s):  
Life Cycle Assessment ◽  
Life Cycle ◽  
Academic Community ◽  
Consumer Products ◽  
Free Inquiry ◽  
Technology Project ◽  
Lively Debate ◽  
Technology Product

AbstractIt has become a standard for researchers carrying out biotechnology projects to do a life cycle assessment (LCA). This is a process for assessing the environmental impact of a technology, product or policy. Doing so is no simple matter, and in the last decades, a rich set of methodologies has developed around LCA. However, the proper methods and meanings of the process remain contested. Preceding the development of the international standard that now governs LCA, there was a lively debate in the academic community about the inclusion of ‘values’ within the process. We revisit this debate and reconsider the way forward for LCA. We set out ways in which those outside of science can provide input into LCAs by informing the value assumptions at stake. At the same time, we will emphasize that the role of those within the scientific community need not (and sometimes, will inevitably not) involve value-free inquiry. We carry out this exploration through a case study of a particular technology project that sought ways to produce industrial and consumer products from algal oils.

scholarly journals Spread of Epidemic Disease on Edge-Weighted Graphs from a Database: A Case Study of COVID-19

2021 ◽  
Vol 18 (9) ◽  
pp. 4432
Author(s):  
Ronald Manríquez ◽  
Camilo Guerrero-Nancuante ◽  
Felipe Martínez ◽  
Carla Taramasco
Keyword(s):  
Public Health ◽  
Infectious Diseases ◽  
Preventive Measures ◽  
Weighted Graph ◽  
Real Data ◽  
Sir Model ◽  
Weighted Graphs ◽  
Epidemic Disease ◽  
The Real

The understanding of infectious diseases is a priority in the field of public health. This has generated the inclusion of several disciplines and tools that allow for analyzing the dissemination of infectious diseases. The aim of this manuscript is to model the spreading of a disease in a population that is registered in a database. From this database, we obtain an edge-weighted graph. The spreading was modeled with the classic SIR model. The model proposed with edge-weighted graph allows for identifying the most important variables in the dissemination of epidemics. Moreover, a deterministic approximation is provided. With database COVID-19 from a city in Chile, we analyzed our model with relationship variables between people. We obtained a graph with 3866 vertices and 6,841,470 edges. We fitted the curve of the real data and we have done some simulations on the obtained graph. Our model is adjusted to the spread of the disease. The model proposed with edge-weighted graph allows for identifying the most important variables in the dissemination of epidemics, in this case with real data of COVID-19. This valuable information allows us to also include/understand the networks of dissemination of epidemics diseases as well as the implementation of preventive measures of public health. These findings are important in COVID-19’s pandemic context.

scholarly journals Macroscopic and Multi-Scale Models for Multi-Class Vehicular Dynamics with Uneven Space Occupancy: A Case Study

Axioms ◽  
2021 ◽  
Vol 10 (2) ◽  
pp. 102
Author(s):  
Maya Briani ◽  
Emiliano Cristiani ◽  
Paolo Ranut
Keyword(s):  
Road Network ◽  
Real Data ◽  
Second Order ◽  
Heavy Vehicles ◽  
First Order ◽  
Multi Scale ◽  
Stop And Go ◽  
Scale Models ◽  
Road Space

In this paper, we propose two models describing the dynamics of heavy and light vehicles on a road network, taking into account the interactions between the two classes. The models are tailored for two-lane highways where heavy vehicles cannot overtake. This means that heavy vehicles cannot saturate the whole road space, while light vehicles can. In these conditions, the creeping phenomenon can appear, i.e., one class of vehicles can proceed even if the other class has reached the maximal density. The first model we propose couples two first-order macroscopic LWR models, while the second model couples a second-order microscopic follow-the-leader model with a first-order macroscopic LWR model. Numerical results show that both models are able to catch some second-order (inertial) phenomena such as stop and go waves. Models are calibrated by means of real data measured by fixed sensors placed along the A4 Italian highway Trieste–Venice and its branches, provided by Autovie Venete S.p.A.

Co-localization analysis in fluorescence microscopy via maximum entropy copula

2020 ◽  
Vol 0 (0) ◽  
Author(s):  
Zahra Amini Farsani ◽  
Volker J. Schmid
Keyword(s):  
Fluorescence Microscopy ◽  
Maximum Entropy ◽  
Probability Distributions ◽  
Real Data ◽  
Bivariate Distribution ◽  
Entropy Method ◽  
Gaussian Copula ◽  
Microscopy Imaging ◽  
High Background ◽  
Localization Analysis

AbstractCo-localization analysis is a popular method for quantitative analysis in fluorescence microscopy imaging. The localization of marked proteins in the cell nucleus allows a deep insight into biological processes in the nucleus. Several metrics have been developed for measuring the co-localization of two markers, however, they depend on subjective thresholding of background and the assumption of linearity. We propose a robust method to estimate the bivariate distribution function of two color channels. From this, we can quantify their co- or anti-colocalization. The proposed method is a combination of the Maximum Entropy Method (MEM) and a Gaussian Copula, which we call the Maximum Entropy Copula (MEC). This new method can measure the spatial and nonlinear correlation of signals to determine the marker colocalization in fluorescence microscopy images. The proposed method is compared with MEM for bivariate probability distributions. The new colocalization metric is validated on simulated and real data. The results show that MEC can determine co- and anti-colocalization even in high background settings. MEC can, therefore, be used as a robust tool for colocalization analysis.

Sign in / Sign up

Export Citation Format

Share Document