scholarly journals Uncovering the fragility of large-scale engineering projects

2021 ◽  
Vol 10 (1) ◽  
Author(s):  
Marc Santolini ◽  
Christos Ellinas ◽  
Christos Nicolaides
Keyword(s):  
Empirical Evidence ◽  
Large Scale ◽  
Network Science ◽  
Project Completion ◽  
Activity Networks ◽  
Large Perturbation ◽  
Network Properties ◽  
Science Framework ◽  
Engineering Projects ◽  
Timely Project Completion

AbstractEngineering projects are notoriously hard to complete on-time, with project delays often theorised to propagate across interdependent activities. Here, we use a novel dataset consisting of activity networks from 14 diverse, large-scale engineering projects to uncover network properties that impact timely project completion. We provide empirical evidence of perturbation cascades, where perturbations in the delivery of a single activity can impact the delivery of up to 4 activities downstream, leading to large perturbation cascades. We further show that perturbation clustering significantly affects project overall delays. Finally, we find that poorly performing projects have their highest perturbations in high reach nodes, which can lead to largest cascades, while well performing projects have perturbations in low reach nodes, resulting in localised cascades. Altogether, these findings pave the way for a network-science framework that can materially enhance the delivery of large-scale engineering projects.

scholarly journals Controllable and decomposable multidirectional synchronizations

2021 ◽  
Author(s):  
Gábor Bergmann
Keyword(s):  
Systems Engineering ◽  
Large Scale ◽  
Mathematical Framework ◽  
Collaborative Systems ◽  
Consistency Constraints ◽  
Restoration Mechanism ◽  
Common Goals ◽  
Access Privileges ◽  
Novel Concept ◽  
Engineering Projects

AbstractStudying large-scale collaborative systems engineering projects across teams with differing intellectual property clearances, or healthcare solutions where sensitive patient data needs to be partially shared, or similar multi-user information systems over databases, all boils down to a common mathematical framework. Updateable views (lenses) and more generally bidirectional transformations are abstractions to study the challenge of exchanging information between participants with different read access privileges. The view provided to each participant must be different due to access control or other limitations, yet also consistent in a certain sense, to enable collaboration towards common goals. A collaboration system must apply bidirectional synchronization to ensure that after a participant modifies their view, the views of other participants are updated so that they are consistent again. While bidirectional transformations (synchronizations) have been extensively studied, there are new challenges that are unique to the multidirectional case. If complex consistency constraints have to be maintained, synchronizations that work fine in isolation may not compose well. We demonstrate and characterize a failure mode of the emergent behaviour, where a consistency restoration mechanism undoes the work of other participants. On the other end of the spectrum, we study the case where synchronizations work especially well together: we characterize very well-behaved multidirectional transformations, a non-trivial generalization from the bidirectional case. For the former challenge, we introduce a novel concept of controllability, while for the latter one, we propose a novel formal notion of faithful decomposition. Additionally, the paper proposes several novel properties of multidirectional transformations.

scholarly journals Genetic and Transcriptomic Biomarkers in Neurodegenerative Diseases: Current Situation and the Road Ahead

Cells ◽  
2021 ◽  
Vol 10 (5) ◽  
pp. 1030
Author(s):  
Julie Lake ◽  
Catherine S. Storm ◽  
Mary B. Makarious ◽  
Sara Bandres-Ciga
Keyword(s):  
Neurodegenerative Diseases ◽  
Large Scale ◽  
Disease Diagnosis ◽  
Open Science ◽  
Future Directions ◽  
The Road ◽  
Current State ◽  
Molecular Complexity ◽  
Science Framework ◽  
Lateral Sclerosis

Neurodegenerative diseases are etiologically and clinically heterogeneous conditions, often reflecting a spectrum of disease rather than well-defined disorders. The underlying molecular complexity of these diseases has made the discovery and validation of useful biomarkers challenging. The search of characteristic genetic and transcriptomic indicators for preclinical disease diagnosis, prognosis, or subtyping is an area of ongoing effort and interest. The next generation of biomarker studies holds promise by implementing meaningful longitudinal and multi-modal approaches in large scale biobank and healthcare system scale datasets. This work will only be possible in an open science framework. This review summarizes the current state of genetic and transcriptomic biomarkers in Parkinson’s disease, Alzheimer’s disease, and amyotrophic lateral sclerosis, providing a comprehensive landscape of recent literature and future directions.

A Scalable Redefined Stochastic Blockmodel

2021 ◽  
Vol 15 (3) ◽  
pp. 1-28
Author(s):  
Xueyan Liu ◽  
Bo Yang ◽  
Hechang Chen ◽  
Katarzyna Musial ◽  
Hongxu Chen ◽  
...  
Keyword(s):  
Large Scale ◽  
Network Science ◽  
Learning Algorithm ◽  
State Of The Art ◽  
Real World Data ◽  
Computational Overhead ◽  
Stochastic Blockmodel ◽  
Np Hard Problem ◽  
Large Scale Networks ◽  
The Cost

Stochastic blockmodel (SBM) is a widely used statistical network representation model, with good interpretability, expressiveness, generalization, and flexibility, which has become prevalent and important in the field of network science over the last years. However, learning an optimal SBM for a given network is an NP-hard problem. This results in significant limitations when it comes to applications of SBMs in large-scale networks, because of the significant computational overhead of existing SBM models, as well as their learning methods. Reducing the cost of SBM learning and making it scalable for handling large-scale networks, while maintaining the good theoretical properties of SBM, remains an unresolved problem. In this work, we address this challenging task from a novel perspective of model redefinition. We propose a novel redefined SBM with Poisson distribution and its block-wise learning algorithm that can efficiently analyse large-scale networks. Extensive validation conducted on both artificial and real-world data shows that our proposed method significantly outperforms the state-of-the-art methods in terms of a reasonable trade-off between accuracy and scalability. 1

scholarly journals On the origin of variable structures in the winds of hot luminous stars

2013 ◽  
Vol 440 (1) ◽  
pp. 2-9 ◽  
Author(s):  
Yannick J. L. Michaux ◽  
Anthony F. J. Moffat ◽  
André-Nicolas Chené ◽  
Nicole St-Louis
Keyword(s):  
Magnetic Field ◽  
Empirical Evidence ◽  
Temporal Variability ◽  
Large Scale ◽  
Small Scale ◽  
Ionization Zone ◽  
Corotating Interaction Regions ◽  
Wind Variability ◽  
Global Magnetic Field ◽  
Interaction Regions

Abstract Examination of the temporal variability properties of several strong optical recombination lines in a large sample of Galactic Wolf–Rayet (WR) stars reveals possible trends, especially in the more homogeneous WC than the diverse WN subtypes, of increasing wind variability with cooler subtypes. This could imply that a serious contender for the driver of the variations is stochastic, magnetic subsurface convection associated with the 170 kK partial-ionization zone of iron, which should occupy a deeper and larger zone of greater mass in cooler WR subtypes. This empirical evidence suggests that the heretofore proposed ubiquitous driver of wind variability, radiative instabilities, may not be the only mechanism playing a role in the stochastic multiple small-scaled structures seen in the winds of hot luminous stars. In addition to small-scale stochastic behaviour, subsurface convection guided by a global magnetic field with localized emerging loops may also be at the origin of the large-scale corotating interaction regions as seen frequently in O stars and occasionally in the winds of their descendant WR stars.

Software Testing Strategy

2014 ◽  
Vol 6 (2) ◽  
pp. 23-36
Author(s):  
Fatma Molu
Keyword(s):  
Life Cycle ◽  
Large Scale ◽  
Critical Role ◽  
Real Life ◽  
Banking System ◽  
System Transformation ◽  
Financial Systems ◽  
Project Completion ◽  
Basic Features ◽  
Project Life

Complex financial conversion projects with large budgets have many different challenges. For companies that want to survive in conditions of tough competition, legacy (old) systems must continue to provide the required service throughout the project life cycle and in some circumstances even after project completion partly. In this case, the term coexistence comes into prominence. During this period, testing phase takes more critical role while integration systems' complexity and risk amount increase. Determining testing approach to use is essential to make sure both transformed and legacy systems provide service synchronously. In this paper, testing practices applied in the long conversion processes are discussed. Primarily, the basic features of the critical financial systems are addressed and then the main adoption methods in the literature are summarized. Then a variety of testing methodologies are presented depending on those adoption methods. These samples based on real-life experiences of transformation project. The most extensive example of real-time online financial systems is core banking systems. This paper covers the testing life cycle process of the large scale project of core banking system transformation project of a bank in Turkey.

A Case Study of the Effects of Design Project Length on Team Collaboration and Leadership in Senior Mechanical Engineering Projects

2017 ◽  
Author(s):  
James Righter ◽  
Andy Blanton ◽  
Hallie Stidham ◽  
Doug Chickarello ◽  
Joshua D. Summers
Keyword(s):  
Exploratory Research ◽  
Design Teams ◽  
Team Collaboration ◽  
Project Completion ◽  
Communication Structures ◽  
Senior Design ◽  
Design Projects ◽  
The Impact ◽  
Engineering Projects

This paper describes exploratory research regarding leadership and communication within undergraduate engineering design teams. The case study was performed on student design projects of one and two semester duration to begin to assess the impact of project length on leadership and communication within the design teams. Data was collected using a survey that was given to the participants in three capstone design projects in Clemson University’s senior design course. The survey was administered within one month of course and project completion. While there were differences in the communication and leadership patterns between the teams, there were other possible influences beyond the project length such as team size and organization, organizational and geographic distribution, and the nature of the product. As a result, further research is proposed to study leadership and communication structures within undergraduate teams and multi-team systems (MTS).

scholarly journals Iterations as the result of social and technical factors: empirical evidence from a large-scale design project

2018 ◽  
Vol 30 (2) ◽  
pp. 251-270 ◽  
Author(s):  
Sebastiano A. Piccolo ◽  
Anja M. Maier ◽  
Sune Lehmann ◽  
Chris A. McMahon
Keyword(s):  
Empirical Evidence ◽  
Large Scale ◽  
Design Project ◽  
Technical Factors ◽  
Scale Design

scholarly journals Fooled by facts: quantifying anchoring bias through a large-scale experiment

2022 ◽  
Author(s):  
Taha Yasseri ◽  
Jannie Reher
Keyword(s):  
Decision Making ◽  
Treatment Group ◽  
Field Experiment ◽  
Empirical Evidence ◽  
Large Scale ◽  
Complex Relationship ◽  
Great Care ◽  
The Future ◽  
Anchoring Bias ◽  
Scale Experiment

AbstractThrough a large-scale online field experiment, we provide new empirical evidence for the presence of the anchoring bias in people’s judgement due to irrational reliance on a piece of information that they are initially given. The comparison of the anchoring stimuli and respective responses across different tasks reveals a positive, yet complex relationship between the anchors and the bias in participants’ predictions of the outcomes of events in the future. Participants in the treatment group were equally susceptible to the anchors regardless of their level of engagement, previous performance, or gender. Given the strong and ubiquitous influence of anchors quantified here, we should take great care to closely monitor and regulate the distribution of information online to facilitate less biased decision making.

scholarly journals Multi-Site Bilingual Team-Based Grounded Theory Research: A Retrospective Methodological Review

2018 ◽  
Author(s):  
Annie Pullen Sansfaçon ◽  
Amy Fulton ◽  
Marion Brown ◽  
John Graham ◽  
Stéphanie Ethier
Keyword(s):  
Grounded Theory ◽  
Large Scale ◽  
Successful Management ◽  
Methodological Review ◽  
Virtual Spaces ◽  
Grounded Theory Study ◽  
Project Completion ◽  
Grounded Theory Research ◽  
University Systems ◽  
Theory Research

Successful management of a multi-site bilingual team-based grounded theory study requires overcoming key challenges associated with implementation of a large-scale, multi-faceted project. This article retrospectively reviews the methodological strategies employed during a multi-site bilingual team-based grounded theory study that investigated the professional adaptation experiences of migrant social workers in Canada. The article presents the strategies that the research team engaged to overcome numerous challenges and successfully work together across a variety of contexts and systems, including (a) provincial contexts, (b) languages, (c) university systems, (d) virtual spaces, and (e) epistemological perspectives. The findings highlight the importance of leadership and teamwork as central to successful project completion.

The Intersection of Data Analytics and Data-Driven Innovation

2020 ◽  
pp. 317-343
Author(s):  
Marcus Tanque ◽  
Harry J. Foxwell
Keyword(s):  
Private Sector ◽  
Data Analytics ◽  
Large Scale ◽  
Data Driven ◽  
Public And Private ◽  
Managerial Practices ◽  
Project Completion ◽  
Technological Advances ◽  
Private Sector Organizations ◽  
Public And Private Sector

This chapter discusses businesses, key technology implementations, case studies, limitations, and trends. It also presents recommendations to improve data analysis, data-driven innovation, and big data project implementation. Small-to-large-scale project inefficiencies present unique challenges to both public and private sector institutions and their management. Data analytics management, data-driven innovation, and related project initiatives have grown in scope, scale, and frequency. This evolution is due to continued technological advances in analytical methods and computing technologies. Most public and private sector organizations do not deliver on project benefits and results. Many organizational and managerial practices emphasize these technical limitations. Specialized human and technical resources are essential for an organization's effective project completion. Functional and practical areas affecting analytics domain and ability requirements, stakeholder expectations, solution infrastructure choices, legal and ethical concerns will also be discussed in this chapter.

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