Allocation Problems in Ride-sharing Platforms

2021 ◽  
Vol 9 (3) ◽  
pp. 1-17
Author(s):  
John P. Dickerson ◽  
Karthik A. Sankararaman ◽  
Aravind Srinivasan ◽  
Pan Xu
Keyword(s):  
Adaptive Algorithm ◽  
Competitive Ratio ◽  
Data Driven ◽  
Matching Markets ◽  
Prior Work ◽  
Bipartite Matching ◽  
New Model ◽  
Ride Sharing ◽  
Online Matching ◽  
Over Time

Bipartite-matching markets pair agents on one side of a market with agents, items, or contracts on the opposing side. Prior work addresses online bipartite-matching markets, where agents arrive over time and are dynamically matched to a known set of disposable resources. In this article, we propose a new model, Online Matching with (offline) Reusable Resources under Known Adversarial Distributions ( OM-RR-KAD ) , in which resources on the offline side are reusable instead of disposable; that is, once matched, resources become available again at some point in the future. We show that our model is tractable by presenting an LP-based non-adaptive algorithm that achieves an online competitive ratio of ½-ϵ for any given constant ϵ > 0. We also show that no adaptive algorithm can achieve a ratio of ½ + o (1) based on the same benchmark LP. Through a data-driven analysis on a massive openly available dataset, we show our model is robust enough to capture the application of taxi dispatching services and ride-sharing systems. We also present heuristics that perform well in practice.

scholarly journals Deferred On-Line Bipartite Matching

10.37236/5756 ◽  
2018 ◽  
Vol 25 (2) ◽  
Author(s):  
Jakub Kozik ◽  
Grzegorz Matecki
Keyword(s):  
Competitive Ratio ◽  
Bipartite Graphs ◽  
Deterministic Algorithm ◽  
The Other ◽  
Bipartite Matching ◽  
Classical Version ◽  
New Model ◽  
On Line

We present a new model for the problem of on-line matching on bipartite graphs. Suppose that one part of a graph is given, but the vertices of the other part are presented in an on-line fashion. In the classical version, each incoming vertex is either irrevocably matched to a vertex from the other part or stays unmatched forever. In our version, an algorithm is allowed to match the new vertex to a group of elements (possibly empty). Later on, the algorithm can decide to remove some vertices from the group and assign them to another (just presented) vertex, with the restriction that each element belongs to at most one group. We present an optimal (deterministic) algorithm for this problem and prove that its competitive ratio equals $1-\pi/\cosh(\frac{\sqrt{3}}{2}\pi)\approx 0.588$.

scholarly journals The Importance of Studying Health Behavior in Older Adults

2020 ◽  
Vol 4 (Supplement_1) ◽  
pp. 827-827
Author(s):  
Jaime Hughes ◽  
Susan Hughes ◽  
Mina Raj ◽  
Janet Bettger
Keyword(s):  
Social Support ◽  
Older Adults ◽  
Behavior Change ◽  
Chronic Conditions ◽  
Population Level ◽  
Multiple Chronic Conditions ◽  
Prior Work ◽  
Time Changes ◽  
The Impact ◽  
Over Time

Abstract Behavior change is an inherent aspect of routine geriatric care. However, most research and clinical programs emphasis how to initiate behavior change with less emphasis placed on skills and strategies to maintain behaviors over time, including after an intervention has concluded. This presentation will provide an introduction to the symposium, including a review of prior work and our rationale for studying the critical yet overlooked construct of maintenance in older adults. Several key considerations in our work include the impact of multiple chronic conditions, declines in cognitive and functional capacity over time, changes in environmental context and/or social support, and sustainability of community and population-level programs and services.

scholarly journals An Exploratory Study of COVID-19 Information on Twitter in the Greater Region

2021 ◽  
Vol 5 (1) ◽  
pp. 5
Author(s):  
Ninghan Chen ◽  
Zhiqiang Zhong ◽  
Jun Pang
Keyword(s):  
Machine Learning ◽  
Social Networks ◽  
Online Social Networks ◽  
Exploratory Study ◽  
Representation Learning ◽  
Data Driven ◽  
Learning Methods ◽  
Twitter Users ◽  
Over Time

The outbreak of the COVID-19 led to a burst of information in major online social networks (OSNs). Facing this constantly changing situation, OSNs have become an essential platform for people expressing opinions and seeking up-to-the-minute information. Thus, discussions on OSNs may become a reflection of reality. This paper aims to figure out how Twitter users in the Greater Region (GR) and related countries react differently over time through conducting a data-driven exploratory study of COVID-19 information using machine learning and representation learning methods. We find that tweet volume and COVID-19 cases in GR and related countries are correlated, but this correlation only exists in a particular period of the pandemic. Moreover, we plot the changing of topics in each country and region from 22 January 2020 to 5 June 2020, figuring out the main differences between GR and related countries.

scholarly journals Machine Learning the Phenomenology of COVID-19 From Early Infection Dynamics

2020 ◽  
Author(s):  
Malik Magdon-Ismail
Keyword(s):  
Public Health ◽  
Machine Learning ◽  
Early Infection ◽  
Data Driven ◽  
Infection Dynamics ◽  
Serious Infection ◽  
Specific Virus ◽  
Different Populations ◽  
Learning Analysis ◽  
Over Time

AbstractWe present a robust data-driven machine learning analysis of the COVID-19 pandemic from its early infection dynamics, specifically infection counts over time. The goal is to extract actionable public health insights. These insights include the infectious force, the rate of a mild infection becoming serious, estimates for asymtomatic infections and predictions of new infections over time. We focus on USA data starting from the first confirmed infection on January 20 2020. Our methods reveal significant asymptomatic (hidden) infection, a lag of about 10 days, and we quantitatively confirm that the infectious force is strong with about a 0.14% transition from mild to serious infection. Our methods are efficient, robust and general, being agnostic to the specific virus and applicable to different populations or cohorts.

scholarly journals More alike than different: Novel methods for measuring and modeling executive function development

2021 ◽  
Author(s):  
Jessica Younger ◽  
Kristine O'Laughlin ◽  
Joaquin Anguera ◽  
Silvia Bunge ◽  
Emilio Ferrer ◽  
...  
Keyword(s):  
Executive Function ◽  
Executive Functions ◽  
Middle Childhood ◽  
Analytic Approach ◽  
Data Driven ◽  
Positive Outcomes ◽  
Novel Methods ◽  
Students Success ◽  
Over Time ◽  
Longitudinal Dataset

Abstract Executive functions (EFs) are linked to positive outcomes across the lifespan. Yet, methodological challenges have prevented rigorous understanding of the precise ways EFs are organized in childhood and how they develop over time. We introduce novel methods to address these challenges for both measuring and modeling EFs using a large, accelerated longitudinal dataset from a diverse sample of students in middle childhood (approximately ages 8 to 14; N = 1,286). Adaptive assessments allowed us to equate EF challenge across ages and a data-driven, network analytic approach revealed the evolving diversity of EFs while accounting for their unity. Our results suggest EF organization stabilizes around age 10, but continues refining through at least age 14. This approach brings new precision to EFs’ development by removing interpretative ambiguities associated with previous methodologies. By improving EF measurement, the field can move towards improving EF training, to provide a strong foundation for students’ success.

A BEST POSSIBLE ONLINE ALGORITHM FOR SCHEDULING TO MINIMIZE MAXIMUM FLOW-TIME ON BOUNDED BATCH MACHINES

2014 ◽  
Vol 31 (04) ◽  
pp. 1450030 ◽  
Author(s):  
CHENGWEN JIAO ◽  
WENHUA LI ◽  
JINJIANG YUAN
Keyword(s):  
Competitive Ratio ◽  
Completion Time ◽  
Online Algorithm ◽  
Unit Length ◽  
Maximum Flow ◽  
Flow Time ◽  
Release Time ◽  
Batch Machine ◽  
The Difference ◽  
Over Time

We consider online scheduling of unit length jobs on m identical parallel-batch machines. Jobs arrive over time. The objective is to minimize maximum flow-time, with the flow-time of a job being the difference of its completion time and its release time. A parallel-batch machine can handle up to b jobs simultaneously as a batch. Here, the batch capacity is bounded, that is b < ∞. In this paper, we provide a best possible online algorithm for the problem with a competitive ratio of [Formula: see text].

Designing Dynamic Logotypes to Represent Data

2019 ◽  
Vol 8 (1) ◽  
pp. 16-30
Author(s):  
Jéssica Parente ◽  
Tiago Martins ◽  
João Bicker ◽  
Penousal Machado
Keyword(s):  
Female Students ◽  
Design Approach ◽  
Data Driven ◽  
Male And Female ◽  
The Creation ◽  
Academic Information ◽  
The University ◽  
Over Time

This work explores how data can influence the design of logotypes and how they can convey information. The authors use the University of Coimbra, in Portugal, as a case study to develop data-driven logotypes for its faculties and, subsequently, for its students. The proposed logotypes are influenced by the current number of students in each faculty, the number of male and female students, and the nationality of the students. The resulting logotypes are able to portray the diversity of students in each faculty. The authors also test this design approach in the creation of logotypes for the students according to their academic information, namely the course and number of credits done. The resulting logotypes are able to adapt to the current students, evolving over time with the departure of students and admission of new ones.

Data-driven state detection algorithm for multi-scale systems and its application

2013 ◽  
Vol 228 (7) ◽  
pp. 1223-1234 ◽  
Author(s):  
Zeng Deliang ◽  
Liu Jiwei ◽  
Liu Jizhen
Keyword(s):  
Failure Rate ◽  
Detection Algorithm ◽  
Data Driven ◽  
Simulation Experiments ◽  
Multi Scale ◽  
State Detection ◽  
Security And Reliability ◽  
Roller Ring ◽  
Technical Basis ◽  
Over Time

To improve the security and reliability of equipment and reduce their failure rate, a data-driven state detection algorithm was proposed. The concepts of multi-scale system, multi-scale entropy and multi-scale exergy were defined. The algorithm is used for multi-scale systems whose state parameters change over time and have the characteristic of increasing monotonically on a dominant scale. An abrasion index for the middle speed roller ring mill was constructed, which was used to monitor the states of the instruments. Noise that affected the accuracy of the results was analyzed. The results of simulation experiments demonstrate the effectiveness of the algorithm, which can provide a technical basis for condition maintenance.

scholarly journals The Effect of Chronic Wasting Disease on Resident Deer Hunting Permit Demand in Wisconsin

Animals ◽  
2019 ◽  
Vol 9 (12) ◽  
pp. 1096
Author(s):  
Dane Erickson ◽  
Carson Reeling ◽  
John G. Lee
Keyword(s):  
Chronic Wasting Disease ◽  
Negative Impact ◽  
The State ◽  
Prior Work ◽  
Wasting Disease ◽  
Deer Hunting ◽  
On Demand ◽  
Permit Price ◽  
Over Time ◽  
Hunter Recruitment

Chronic wasting disease (CWD) has had a negative impact on deer license demand in Wisconsin since it was first found in the state in 2002. Prior work evaluates the effect of CWD on hunting permit sales, but only in the period immediately after the disease was discovered. We use data on hunting permit sales, permit price, and other demand shifters to estimate a model of deer permit demand for the period 1966–2015. We use the estimated model to quantify the effect of CWD on (1) hunter demand for deer permits; (2) hunter surplus from hunting; and (3) lost hunting permit revenues. Hunter participation declined by 5.4% after CWD was detected in 2002. Hunter surplus decreased by $96 million over this period, while permit revenues declined by nearly $17 million. The effect of CWD was greater on demand for firearm permits than for archery permits. We also find that the effects of CWD diminish over time in absolute terms. This is because permit demand would have started to decline in 2008 even in the absence of CWD. This finding implies efforts to control CWD and efforts at hunter recruitment are economic complements and should be pursued jointly to maximize hunter welfare.

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