scholarly journals Training for the Next Wave

2012 ◽  
Vol 134 (03) ◽  
pp. 34-37 ◽  
Author(s):  
Ahmed K. Noor
Keyword(s):  
Complex Systems ◽  
Workforce Development ◽  
System Integration ◽  
Large Scale ◽  
High Tech ◽  
Engineering Practice ◽  
Engineering Programs ◽  
Large Numbers ◽  
And Mathematics ◽  
Workforce Needs

This article focuses on various aspects of an ecosystem that can accelerate the training, which the engineering workforce needs to realize and sustain complex systems. Several science, technology, engineering, and mathematics (STEM) improvement and pilot academic engineering programs have been proposed to address some of the needs and challenges of the high-tech workforce. Companies have launched their own educational programs to address some of the reskilling and large-scale system integration needs of complex systems. A step towards the implementation of the comprehensive strategy is the development of Intelligent Cyber-Physical Engineering Ecosystems to advance collaboration among engineering and research institutions, industry, professional societies, and other stakeholders working on complex systems. The ecosystems will consist of large numbers of distributed interacting components that are continually updated and expanded. The ecosystems are expected to grow and to reach unanticipated levels of complexity because of the relations among the continually expanding individual components. The ecosystems are expected to provide knowledge-rich, immersive environments for integrating engineering practice with learning, training, and workforce development needed for complex systems.

Introduction: Adaptation, Evolution, and Intelligence

2005 ◽  
Author(s):  
Lashon Booker ◽  
Stephanie Forrest
Keyword(s):  
Complex Systems ◽  
Complex Adaptive Systems ◽  
Adaptive Systems ◽  
Insect Behavior ◽  
Global Behavior ◽  
Large Numbers ◽  
Simple Rules ◽  
Complex Adaptive ◽  
And Mathematics ◽  
Interdisciplinary Study

It has long been known that the repeated or collective application of very simple rules can produce surprisingly complex organized behavior. In recent years several compelling examples have caught the public's eye, including chaos, fractals, cellular automata, self-organizing systems, and swarm intelligence. These kinds of approaches and models have been applied to phenomena in fields as diverse as immunology, neuroscience, cardiology, social insect behavior, and economics. The interdisciplinary study of how such complex behavior arises has developed into a new scientific field called "complex systems." The complex systems that most challenge our understanding are those whose behavior involves learning or adaptation; these have been named "complex adaptive systems." Examples of complex adaptive behavior include the brain's ability, through the collective actions of large numbers of neurons, to alter the strength of its own connections in response to experiences in an environment; the immune system's continual and dynamic protection against an onslaught of ever-changing invaders; the ability of evolving species to produce, maintain, and reshape traits useful to their survival, even as environments change; and the power of economic systems to reflect, in the form of prices, supplies, and other market characteristics, the collective preferences and desires of millions of distributed, independent individuals engaged in buying and selling. What is similar in these diverse examples is that global behavior arises from the semi-independent actions of many players obeying relatively simple rules, with little or no central control. Moreover, this global behavior exhibits learning or adaptation in some form, which allows individual agents or the system as a whole to maintain or improve the ability to make predictions about the future and act in accordance with these predictions. Traditional methods of science and mathematics have had limited success explaining (and predicting) such phenomena, and an increasingly common view in the scientific community is that novel approaches are needed, particularly those involving computer simulation. Understanding complex adaptive systems is difficult for several reasons. One reason is that in such systems the lowest level components (often called agents) not only change their behavior in response to the environment, but, through learning, they can also change the underlying rules used to generate their behavior.

Education for Professional Engineering Practice

2014 ◽  
Vol 28 (3) ◽  
pp. 193-199
Author(s):  
Mike D. Bramhall ◽  
Chris Short
Keyword(s):  
Large Scale ◽  
Project Work ◽  
Engineering Practice ◽  
Curriculum Innovation ◽  
Collaborative Project ◽  
Management Learning ◽  
Project Outcomes ◽  
And Mathematics ◽  
Project Objectives ◽  
Education Science

This paper reports on a funded collaborative large-scale curriculum innovation and enhancement project undertaken as part of a UK National Higher Education Science, Technology Engineering and Mathematics (STEM) programme. Its aim was to develop undergraduate curricula to teach appropriate skills for professional engineering practice more effectively. Sheffield Hallam University (SHU) led the project with Loughborough and London South Bank Universities as partners. Project advisers included Imperial College London and Coventry University. The four collaborative project objectives were to: develop an approach to interdisciplinary cross-year integration and professional team practice, project management, learning, teaching and assessment; develop cross-year student support systems to aid the above; develop the assessment of professional skills; and evaluate and disseminate the project outcomes to the wider STEM community. The activity allowed partners to trial and test a rounded implementation in each institution involving academic taught material, practical laboratory-based project work, together with an appropriate support structure for operation across a range of undergraduate courses.

A Decision-Centric Framework for Modeling Evolutionary Complex Systems

2021 ◽  
pp. 499-531
Author(s):  
Zhenghui Sha ◽  
Jitesh H. Panchal
Keyword(s):  
Complex Systems ◽  
Cyber Security ◽  
Large Scale ◽  
Environmental Safety ◽  
Human Society ◽  
Energy Sustainability ◽  
Engineering Product ◽  
Human Needs ◽  
Large Numbers ◽  
New Challenges

The human society is facing new challenges, such as cyber-security, environmental safety, and energy sustainability, which cannot be solved by a single engineering product or system. When seeking ways to address the challenges in order to meet fundamental human needs, the solutions often lead to large-scale complex systems. In complex systems, there are large numbers of interactive entities that work together to form a system of value greater than the sum of the individuals.

Computer Analyses in Preventive Health Research

1967 ◽  
Vol 06 (01) ◽  
pp. 8-14 ◽  
Author(s):  
M. F. Collen
Keyword(s):  
Medical Research ◽  
Preventive Medicine ◽  
Health Research ◽  
Large Scale ◽  
Preventive Health ◽  
New Era ◽  
Large Numbers ◽  
Normal Test ◽  
Computer Analyses

The utilization of an automated multitest laboratory as a data acquisition center and of a computer for trie data processing and analysis permits large scale preventive medical research previously not feasible. Normal test values are easily generated for the particular population studied. Long-term epidemiological research on large numbers of persons becomes practical. It is our belief that the advent of automation and computers has introduced a new era of preventive medicine.

Introduction to the Section on Workforce Development

2010 ◽  
Vol 14 (3) ◽  
Author(s):  
David Sachs
Keyword(s):  
Community Colleges ◽  
Workforce Development ◽  
Large Scale ◽  
Job Skills ◽  
Development Programs ◽  
Blended Education

When unemployment is high and education budgets are shrinking, people flock to community colleges and other providers to learn new job skills. Asynchronous and blended education provide solutions for meeting large scale demand, thus this issue features four cases about innovative workforce development programs. Each one of them advances the possibilities and provides replicable practices for expanding access.

scholarly journals Improving Undergraduate Life Science Education for the Biosciences Workforce: Overcoming the Disconnect between Educators and Industry

2018 ◽  
Vol 17 (3) ◽  
pp. es12 ◽  
Author(s):  
Christopher Thompson ◽  
Joseph Sanchez ◽  
Michael Smith ◽  
Judy Costello ◽  
Amrita Madabushi ◽  
...  
Keyword(s):  
United States ◽  
Workforce Development ◽  
The United States ◽  
University Graduates ◽  
Washington Dc ◽  
College And University ◽  
Highly Educated ◽  
Undergraduate Institutions ◽  
And Mathematics ◽  
Undergraduate Programs

The BioHealth Capital Region (Maryland, Virginia, and Washington, DC; BHCR) is flush with colleges and universities training students in science, technology, engineering, and mathematics disciplines and has one of the most highly educated workforces in the United States. However, current educational approaches and business recruitment tactics are not drawing sufficient talent to sustain the bioscience workforce pipeline. Surveys conducted by the Mid-Atlantic Biology Research and Career Network identified a disconnect between stakeholders who are key to educating, training, and hiring college and university graduates, resulting in several impediments to workforce development in the BHCR: 1) students are underinformed or unaware of bioscience opportunities before entering college and remain so at graduation; 2) students are not job ready at the time of graduation; 3) students are mentored to pursue education beyond what is needed and are therefore overqualified (by degree) for most of the available jobs in the region; 4) undergraduate programs generally lack any focus on workforce development; and 5) few industry–academic partnerships with undergraduate institutions exist in the region. The reality is that these issues are neither surprising nor restricted to the BHCR. Recommendations are presented to facilitate improvement in the preparation of graduates for today’s bioscience industries throughout the United States.

scholarly journals Development of a Radar Reflector Kit for Older Adults to Use to Signal Their Location and Needs in a Large-Scale Earthquake Disaster

2021 ◽  
Vol 13 (10) ◽  
pp. 1883
Author(s):  
Yuma Morisaki ◽  
Makoto Fujiu ◽  
Ryoichi Furuta ◽  
Junichi Takayama
Keyword(s):  
Older Adults ◽  
Synthetic Aperture Radar ◽  
Satellite Imagery ◽  
Disaster Response ◽  
Large Scale ◽  
Synthetic Aperture ◽  
Earthquake Disaster ◽  
Large Numbers ◽  
The World ◽  
Vulnerable People

In Japan, older adults account for the highest proportion of the population of any country in the world. When large-scale earthquake disasters strike, large numbers of casualties are known to particularly occur among seniors. Many are physically or mentally vulnerable and require assistance during the different phases of disaster response, including rescue, evacuation, and living in an evacuation center. However, the growing number of older adults has made it difficult, after a disaster, to quickly gather information on their locations and assess their needs. The authors are developing a proposal to enable vulnerable people to signal their location and needs in the aftermath of a disaster to response teams by deploying radar reflectors that can be detected in synthetic aperture radar (SAR) satellite imagery. The purpose of this study was to develop a radar reflector kit that seniors could easily assemble in order to make this proposal feasible in practice. Three versions of the reflector were tested for detectability, and a sample of older adults was asked to assemble the kits and provide feedback regarding problems they encountered and regarding their interest in using the reflectors in the event of a large-scale disaster.

scholarly journals System design for inferring colony-level pollination activity through miniature bee-mounted sensors

2021 ◽  
Vol 11 (1) ◽  
Author(s):  
Haron M. Abdel-Raziq ◽  
Daniel M. Palmer ◽  
Phoebe A. Koenig ◽  
Alyosha C. Molnar ◽  
Kirstin H. Petersen
Keyword(s):  
Data Acquisition ◽  
Honey Bees ◽  
Large Scale ◽  
Physical World ◽  
Cluttered Environments ◽  
Robotic Mapping ◽  
Large Scale Data ◽  
Trade Offs ◽  
Large Numbers ◽  
Engineered Systems

AbstractIn digital agriculture, large-scale data acquisition and analysis can improve farm management by allowing growers to constantly monitor the state of a field. Deploying large autonomous robot teams to navigate and monitor cluttered environments, however, is difficult and costly. Here, we present methods that would allow us to leverage managed colonies of honey bees equipped with miniature flight recorders to monitor orchard pollination activity. Tracking honey bee flights can inform estimates of crop pollination, allowing growers to improve yield and resource allocation. Honey bees are adept at maneuvering complex environments and collectively pool information about nectar and pollen sources through thousands of daily flights. Additionally, colonies are present in orchards before and during bloom for many crops, as growers often rent hives to ensure successful pollination. We characterize existing Angle-Sensitive Pixels (ASPs) for use in flight recorders and calculate memory and resolution trade-offs. We further integrate ASP data into a colony foraging simulator and show how large numbers of flights refine system accuracy, using methods from robotic mapping literature. Our results indicate promising potential for such agricultural monitoring, where we leverage the superiority of social insects to sense the physical world, while providing data acquisition on par with explicitly engineered systems.

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