Mathematical models of self-propelled particles

2017 ◽  
Vol 27 (06) ◽  
pp. 997-1004 ◽  
Author(s):  
N. Bellomo ◽  
F. Brezzi
Keyword(s):  
Mathematical Models ◽  
General Framework ◽  
Future Research ◽  
Large Systems

This paper presents the papers published in two special issues devoted to the modeling of large systems of self-propelled particles. The contents of these papers are presented in the general framework of the conceptual analytic difficulties and of the computational problems that are met when dealing with this class of systems. In addition, some perspective ideas on possible objectives of future research are extracted from the contents of this issue and brought to the reader’s attention.

What every mathematician should know about modelling crime

2010 ◽  
Vol 21 (4-5) ◽  
pp. 275-281 ◽  
Author(s):  
MARCUS FELSON
Keyword(s):  
Mathematical Models ◽  
Real Data ◽  
Future Research ◽  
Data Modelling

This paper by a criminologist explains why it makes more sense to model criminal acts than to model criminals, how many preconceptions about crime can mislead modellers and offers some simple crime modelling ideas. Many opportunities for simulation now exist, and new opportunities for real-data modelling are emerging. The author suggests mathematical models of crime, including offender foraging for crime targets, as a rich area for future research.

Mismanagement or Mismeasurement

2015 ◽  
pp. 276-322
Author(s):  
Abdel Latef Anouze ◽  
Ibrahim H. Osman
Keyword(s):  
General Framework ◽  
Evaluation Process ◽  
Future Research ◽  
Data Envelopment ◽  
Analytical Evaluation ◽  
Valuation Method ◽  
Multiple Input ◽  
Overall Performance ◽  
Five Phases ◽  
Decision Making Units

Data Envelopment Analysis (DEA) is a well-known frontier valuation method to assess the performance of set of Decision Making Units (DMUs). It derives an overall performance for each DMU based on its efficiency relative to others. All DMUs use the same production function that transfers multiple-input into multiple-output of qualitative and quantitative values. Such big data necessitates the provision of a general framework to guide both researchers and practitioners in the analytical evaluation process for better insights. This chapter proposes a new roadmap to guide future research to implement rigorous and relevant DEA applications. This roadmap consists of five phases: Understand, Prepare, Analyze, Implement, and Monitor (AIM-UP). This roadmap could be used to evaluate the efficiency of resource utilization and the effectiveness of production by the operating processes. Finally, three case studies are used to illustrate DEA implementation, and an up-to-date review of DEA applications is conducted.

Online Machine Learning

2013 ◽  
pp. 27-54 ◽  
Author(s):  
Óscar Fontenla-Romero ◽  
Bertha Guijarro-Berdiñas ◽  
David Martinez-Rego ◽  
Beatriz Pérez-Sánchez ◽  
Diego Peteiro-Barral
Keyword(s):  
Machine Learning ◽  
Online Learning ◽  
Mathematical Models ◽  
General Framework ◽  
Current Application ◽  
Data Set

Machine Learning (ML) addresses the problem of adjusting those mathematical models which can accurately predict a characteristic of interest from a given phenomenon. They achieve this by extracting information from regularities contained in a data set. From its beginnings two visions have always coexisted in ML: batch and online learning. The former assumes full access to all data samples in order to adjust the model whilst the latter overcomes this limiting assumption thus expanding the applicability of ML. In this chapter, we review the general framework and methods of online learning since its inception are reviewed and its applicability in current application areas is explored.

Online Collaboration

2012 ◽  
pp. 403-411 ◽  
Author(s):  
Charalampos Z. Patrikakis ◽  
Lemonia Argyriou ◽  
Agis Papantoniou
Keyword(s):  
Social Networking ◽  
General Framework ◽  
Work Group ◽  
Collaborative Work ◽  
Online Collaboration ◽  
Future Research ◽  
The Internet ◽  
Group Behaviour ◽  
Collaborative Innovation ◽  
Diffusion Curves

In this chapter, the authors present the general framework for assessing collaborative work group behaviour over the Internet and their social or asocial behaviour based on previous studies. Following this approach, the authors first give reference to a related study on social and asocial learning and how they can be distinguished through the analysis of data diffusion curves and other mathematical models. As a next step, a used method on group collaboration over a digital content publication platform is presented. Finally, the authors state a new direction on collaborative work groups, and the idea of Collaborative Innovation Networks is presented. The paper ends with directions for future research on social networking and human-machine collaboration.

Modelling post‐acquisition employee behavior: typology and determining factors

1998 ◽  
Vol 20 (1) ◽  
pp. 73-91 ◽  
Author(s):  
Dimitris Bourantas ◽  
Irene I. Nicandrou
Keyword(s):  
Human Resource ◽  
General Framework ◽  
Future Research ◽  
Employee Behavior ◽  
Determining Factors ◽  
Employee Behaviors ◽  
Employee Reactions ◽  
The Relationship ◽  
Employee Responses

Understanding employee reactions to acquisitions is important in assessing the dynamics of acquisitions and their possible success or failure. Proposes a typology of employee behaviors in acquisitions. Moreover, describes the general framework for studying employee responses, by showing the relationship between the factors contributing to the formation of attitudes which can lead to a certain behavior. Finally, discusses directions for future research regarding human resource issues.

scholarly journals A Survey and Perspectives on Mathematical Models for Quantitative Precipitation Estimation Using Lightning

2017 ◽  
Vol 2017 ◽  
pp. 1-11
Author(s):  
Carlos Manuel Minjarez-Sosa ◽  
Julio Waissman
Keyword(s):  
Mathematical Models ◽  
Convective Precipitation ◽  
Future Research ◽  
The Novel ◽  
Mathematical Methods ◽  
Simple Observation ◽  
Quantitative Precipitation Estimation ◽  
Precipitation Estimation ◽  
Cloud To Ground Lightning ◽  
Electrically Charged

Lightning is one of the most spectacular phenomena in nature. It is produced when there is a breakdown in the resistance in the electric field between the ground and an electrically charged cloud. By simple observation, we observe that precipitation, especially the most intense, is often accompanied by lightning. Given this observation, lightning has been employed to estimate convective precipitation since 1969. In early studies, mathematical models were deduced to quantify this relationship and used to estimate precipitation. Currently, the use of several techniques to estimate precipitation is gaining momentum, and lightning is one of the novel techniques to complement the traditional techniques for Quantitative Precipitation Estimation. In this paper, the authors provide a survey of the mathematical methods employed to estimate precipitation through the use of cloud-to-ground lightning. We also offer a perspective on the future research to this end.

Unexpected Plural Inflections in Spanish: Reduplication and Metathesis

2005 ◽  
Vol 36 (2) ◽  
pp. 195-222 ◽  
Author(s):  
James Harris ◽  
Morris Halle
Keyword(s):  
Recent Work ◽  
General Framework ◽  
Future Research ◽  
Special Cases ◽  
Spanish Dialects

We examine the puzzling displacement in various Spanish dialects of a plural suffix from a verb where it is motivated semantically, syntactically, and morphologically onto a following clitic. We present previously unreported data and a new analysis of this material that succeeds where earlier efforts fail to provide a unified account of related phenomena. Our solution, which employs recent work on reduplication and metathesis, allows us to account for seemingly disparate phenomena as special cases of a single general framework and demonstrates that these operations are more versatile than previously thought. Directions for future research are indicated.

Mathematical Models to Discriminate Between Benign and Malignant Adnexal Masses: Potential Diagnostic Improvement Using Ovarian HistoScanning

2011 ◽  
Vol 21 (1) ◽  
pp. 35-43 ◽  
Author(s):  
Evelien Vaes ◽  
Ranjit Manchanda ◽  
Rina Nir ◽  
Dror Nir ◽  
Harry Bleiberg ◽  
...  
Keyword(s):  
Mathematical Models ◽  
New Technology ◽  
Characteristic Curve ◽  
Model Performance ◽  
Diagnostic Value ◽  
Ca 125 ◽  
Transvaginal Sonography ◽  
Future Research ◽  
Initial Report ◽  
Adnexal Masses

Purpose:Accurate preoperative clinical assessment of adnexal masses can optimize outcomes by ensuring appropriate and timely surgery. This article addresses whether a new technology, ovarian HistoScanning, has an additional diagnostic value in mathematical models developed for the differential diagnosis of adnexal masses.Patients and Methods:Transvaginal sonography-based morphological variables were obtained through blinded analysis of archived images in 199 women enrolled in a prospective study to assess the performance of ovarian HistoScanning. Logistic regression (LR) and neural network (NN) models including these variables and clinical and patient data along with the HistoScanning score (HSS) (range, 0-125; based on mathematical algorithms) were developed in a learning set (60% patients). The remaining 40% patients (evaluation set) were used to assess model performance.Results:Of all morphological and clinical variables tested, serum CA-125, presence of a solid component, and HSS were most significant and used to develop the LR model. The NN model included all variables. The novel variable, HSS, offered significant improvement in the LR and NN models' performance. The LR and NN models in an independent evaluation set were found to have area under the receiver operating characteristic curve = 0.97 (95% confidence interval [CI], 94-99) and 0.93 (95% CI, 88-98), sensitivities = 83% (95% CI, 71%-91%) and 80% (95% CI, 67%-89%), and specificities = 98% (95% CI, 89%-99%) and 86% (95% CI, 72%-95%), respectively. In addition, these models showed an improved performance when compared with 3 other existing models (allP< 0.05).Conclusions:This initial report shows a clear benefit of including ovarian HistoScanning into mathematical models used for discriminating benign from malignant ovarian masses. These models may be specifically helpful to the less experienced examiner. Future research should assess performance of these models in prospective clinical trials in different populations.

MODELLING VASCULAR MORPHOGENESIS: CURRENT VIEWS ON BLOOD VESSELS DEVELOPMENT

2009 ◽  
Vol 19 (supp01) ◽  
pp. 1483-1537 ◽  
Author(s):  
MIGUEL Á. HERRERO ◽  
ÁLVARO KÖHN ◽  
JOSÉ M. PÉREZ-POMARES
Keyword(s):  
Blood Vessel ◽  
Mathematical Models ◽  
Structure Function ◽  
Blood Vessels ◽  
Biological Process ◽  
Current Knowledge ◽  
Point Of View ◽  
Future Research ◽  
Signalling Molecules ◽  
Vascular Morphogenesis

In this work we present a comprehensive account of our current knowledge on vascular morphogenesis, both from a biological and a mathematical point of view. To this end, we first describe the basic steps in the known mechanisms of blood vessel morphogenesis, whose structure, function and unfolding properties are examined. We then provide a wide, although by no means exhaustive, account of mathematical models which are used to describe and discuss particular aspects of the overall biological process considered. We finally summarize the approaches presented, and suggest possible directions for future research. Details about some of the major signalling molecules involved are included in a first Appendix at the end of the paper. A second Appendix provides a brief overview of design principles for vascular nets, a subject that has deserved considerable attention over the years.

Mathematics, complexity and multiscale features of large systems of self-propelled particles

2015 ◽  
Vol 26 (02) ◽  
pp. 207-214 ◽  
Author(s):  
N. Bellomo ◽  
F. Brezzi
Keyword(s):  
Complex Systems ◽  
Mathematical Theory ◽  
Life Sciences ◽  
Living Systems ◽  
Future Research ◽  
Large Systems

This issue is devoted to complex systems in life sciences. Some perspective ideas on possible objectives of future research are extracted from the contents of this issue and brought to the reader’s attention. The final ambitious aim is the development of a mathematical theory for complex living systems.

Sign in / Sign up

Export Citation Format

Share Document