The Community Collaboration Stakeholder Project

ERIC Educational Resources Information Center

Heath, Renee Guarriello

2010-01-01

Today's increasingly complex and diverse world demands 21st century communication skills to solve community and social justice problems. Interorganizational collaboration is at the heart of much community activism, such as that focused on solving environmental disputes, eradicating racially discriminating real estate practices, and bringing early…

Engineering Problem-Solving Knowledge: The Impact of Context

ERIC Educational Resources Information Center

Wolff, Karin

2017-01-01

Employer complaints of engineering graduate inability to "apply knowledge" suggests a need to interrogate the complex theory-practice relationship in twenty-first century real world contexts. Focussing specifically on the application of mathematics, physics and logic-based disciplinary knowledge, the research examines engineering…

Beyond rules: The next generation of expert systems

NASA Technical Reports Server (NTRS)

Ferguson, Jay C.; Wagner, Robert E.

1987-01-01

The PARAGON Representation, Management, and Manipulation system is introduced. The concepts of knowledge representation, knowledge management, and knowledge manipulation are combined in a comprehensive system for solving real world problems requiring high levels of expertise in a real time environment. In most applications the complexity of the problem and the representation used to describe the domain knowledge tend to obscure the information from which solutions are derived. This inhibits the acquisition of domain knowledge verification/validation, places severe constraints on the ability to extend and maintain a knowledge base while making generic problem solving strategies difficult to develop. A unique hybrid system was developed to overcome these traditional limitations.

Developing a new stochastic competitive model regarding inventory and price

NASA Astrophysics Data System (ADS)

Rashid, Reza; Bozorgi-Amiri, Ali; Seyedhoseini, S. M.

2015-09-01

Within the competition in today's business environment, the design of supply chains becomes more complex than before. This paper deals with the retailer's location problem when customers choose their vendors, and inventory costs have been considered for retailers. In a competitive location problem, price and location of facilities affect demands of customers; consequently, simultaneous optimization of the location and inventory system is needed. To prepare a realistic model, demand and lead time have been assumed as stochastic parameters, and queuing theory has been used to develop a comprehensive mathematical model. Due to complexity of the problem, a branch and bound algorithm has been developed, and its performance has been validated in several numerical examples, which indicated effectiveness of the algorithm. Also, a real case has been prepared to demonstrate performance of the model for real world.

Tabu Search enhances network robustness under targeted attacks

NASA Astrophysics Data System (ADS)

Sun, Shi-wen; Ma, Yi-lin; Li, Rui-qi; Wang, Li; Xia, Cheng-yi

2016-03-01

We focus on the optimization of network robustness with respect to intentional attacks on high-degree nodes. Given an existing network, this problem can be considered as a typical single-objective combinatorial optimization problem. Based on the heuristic Tabu Search optimization algorithm, a link-rewiring method is applied to reconstruct the network while keeping the degree of every node unchanged. Through numerical simulations, BA scale-free network and two real-world networks are investigated to verify the effectiveness of the proposed optimization method. Meanwhile, we analyze how the optimization affects other topological properties of the networks, including natural connectivity, clustering coefficient and degree-degree correlation. The current results can help to improve the robustness of existing complex real-world systems, as well as to provide some insights into the design of robust networks.

Collaborative Service Learning: A Winning Proposition for Industry and Education

ERIC Educational Resources Information Center

Crutsinger, Christy A.; Pookulangara, Sanjukta; Tran, Gina; Duncan, Kim

2004-01-01

Collaboration between industry and academia creates a win-win situation for individuals and communities. Through innovative partnering, students apply knowledge to real-world situations, institutions increase program visibility, and businesses receive innovative solutions to complex problems. This article provides a roadmap for implementing a…

Building a Greener Future

ERIC Educational Resources Information Center

Baldwin, Blake; Koenig, Kathleen; Van der Bent, Andries

2016-01-01

Integrating engineering and science in the classroom can be challenging, and creating authentic experiences that address real-world problems is often even more difficult. "A Framework for K-12 Science Education" (NRC 2012), however, calls for high school graduates to be able to undertake more complex engineering design projects related…

Teaching Pre-Service Teachers to Make Digital Stories That Explain Complex Mathematical Concepts in a Real-World Context: The "Math-eo" Project, Creating "Cool New Tools"

ERIC Educational Resources Information Center

Walters, Lynne Masel; Green, Martha R.; Goldsby, Dianne; Walters, Timothy N.; Wang, Liangyan

2016-01-01

This mixed methods study examines whether engaging in a problem-solving project to create Math-eos (digital videos) increases pre-service teachers' understanding of the relationship between visual, auditory, and verbal representation and critical thinking in mathematics. Additionally, the study looks at what aspects of a digital problem solving…

Applications of Evolutionary Technology to Manufacturing and Logistics Systems : State-of-the Art Survey

NASA Astrophysics Data System (ADS)

Gen, Mitsuo; Lin, Lin

Many combinatorial optimization problems from industrial engineering and operations research in real-world are very complex in nature and quite hard to solve them by conventional techniques. Since the 1960s, there has been an increasing interest in imitating living beings to solve such kinds of hard combinatorial optimization problems. Simulating the natural evolutionary process of human beings results in stochastic optimization techniques called evolutionary algorithms (EAs), which can often outperform conventional optimization methods when applied to difficult real-world problems. In this survey paper, we provide a comprehensive survey of the current state-of-the-art in the use of EA in manufacturing and logistics systems. In order to demonstrate the EAs which are powerful and broadly applicable stochastic search and optimization techniques, we deal with the following engineering design problems: transportation planning models, layout design models and two-stage logistics models in logistics systems; job-shop scheduling, resource constrained project scheduling in manufacturing system.

Putting the puzzle together: the role of ‘problem definition’ in complex clinical judgement

PubMed Central

Cristancho, Sayra; Lingard, Lorelei; Forbes, Thomas; Ott, Michael; Novick, Richard

2017-01-01

CONTEXT We teach judgement in pieces; that is, we talk about each aspect separately (patient, plan, resources, technique, etc.). We also let trainees figure out how to put the pieces together. In complex situations, this might be problematic. Using data from a drawing-based study on surgeons’ experiences with complex situations, we explore the notion of ‘problem definition’ in real-world clinical judgement using the theoretical lens of systems engineering. METHODS ‘Emergence’, the sensitising concept for analysis, is rooted in two key systems premises: that person and context are inseparable and that what emerges is an act of choice. Via a ‘gallery walk’ we used these premises to perform analysis on individual drawings as well as cross-comparisons of multiple drawings. Our focus was to understand similarities and differences among the vantage points used by multiple surgeons. RESULTS In this paper we challenge two assumptions from current models of clinical judgement: that experts hold a fixed and static definition of the problem and that consequently the focus of the expert’s work is on solving the problem. Each situation described by our participants revealed different but complementary perspectives of what a surgical problem might come to be: from concerns about ensuring standard of care, to balancing personal emotions versus care choices, to coordinating resources, and to maintaining control while in the midst of personality clashes. CONCLUSION We suggest that it is only at the situation and system level, not at the individual level, that we are able to appreciate the nuances of defining the problem when experts make judgements during real-world complex situations. PMID:27943366

Putting the puzzle together: the role of 'problem definition' in complex clinical judgement.

PubMed

Cristancho, Sayra; Lingard, Lorelei; Forbes, Thomas; Ott, Michael; Novick, Richard

2017-02-01

We teach judgement in pieces; that is, we talk about each aspect separately (patient, plan, resources, technique, etc.). We also let trainees figure out how to put the pieces together. In complex situations, this might be problematic. Using data from a drawing-based study on surgeons' experiences with complex situations, we explore the notion of 'problem definition' in real-world clinical judgement using the theoretical lens of systems engineering. 'Emergence', the sensitising concept for analysis, is rooted in two key systems premises: that person and context are inseparable and that what emerges is an act of choice. Via a 'gallery walk' we used these premises to perform analysis on individual drawings as well as cross-comparisons of multiple drawings. Our focus was to understand similarities and differences among the vantage points used by multiple surgeons. In this paper we challenge two assumptions from current models of clinical judgement: that experts hold a fixed and static definition of the problem and that consequently the focus of the expert's work is on solving the problem. Each situation described by our participants revealed different but complementary perspectives of what a surgical problem might come to be: from concerns about ensuring standard of care, to balancing personal emotions versus care choices, to coordinating resources, and to maintaining control while in the midst of personality clashes. We suggest that it is only at the situation and system level, not at the individual level, that we are able to appreciate the nuances of defining the problem when experts make judgements during real-world complex situations. © 2016 John Wiley & Sons Ltd and The Association for the Study of Medical Education.

A Cost Assessment of the Dayton Public Schools Vehicle Routing Problem

DTIC Science & Technology

2009-03-01

known problems: the Traveling Salesman Problem (TSP) and the Bin Packing Problem ( BPP ) (Ralphs, 2003). The VRP has a plethora of real world...well known problems: the Traveling Salesman Problem (TSP) and the Bin Packing Problem ( BPP ) (Ralphs, 2003). The VRP has a plethora of real world

Mentoring Undergraduate Scholars: A Pathway to Interdisciplinary Research?

ERIC Educational Resources Information Center

Davis, Shannon N.; Mahatmya, Duhita; Garner, Pamela W.; Jones, Rebecca M.

2015-01-01

Interdisciplinary research is a valuable approach to addressing complex real-world problems. However, undergraduate research mentoring is discussed as an activity that happens in disciplinary silos where the mentor and student scholar share a disciplinary background. By transcending traditional academic divisions, we argue that mentors can train a…

Getting It Together: Gerontological Research and the Real World.

ERIC Educational Resources Information Center

Bikson, Tora Kay

This paper presents a critical review of recent empirical and theoretical literature on information dissemination and utilization, incorporating key concepts from that body of literature into a model of effective knowledge transfer in gerontology. It assumes that the urgency and complexity of rapidly growing age-linked problems demand informed…

Integrative Learning: Making Liberal Education Purposeful, Personal, and Practical

ERIC Educational Resources Information Center

Ferren, Ann S.; Anderson, Chad B.

2016-01-01

This chapter explores three key features of integrative learning practice that play a vital role in fostering student success: guidance and support through critical transitions; entire development of the student; and engagement in project-based learning that connects learning to complex, real-world problems, and opportunities that can have…

A tabu search evalutionary algorithm for multiobjective optimization: Application to a bi-criterion aircraft structural reliability problem

NASA Astrophysics Data System (ADS)

Long, Kim Chenming

Real-world engineering optimization problems often require the consideration of multiple conflicting and noncommensurate objectives, subject to nonconvex constraint regions in a high-dimensional decision space. Further challenges occur for combinatorial multiobjective problems in which the decision variables are not continuous. Traditional multiobjective optimization methods of operations research, such as weighting and epsilon constraint methods, are ill-suited to solving these complex, multiobjective problems. This has given rise to the application of a wide range of metaheuristic optimization algorithms, such as evolutionary, particle swarm, simulated annealing, and ant colony methods, to multiobjective optimization. Several multiobjective evolutionary algorithms have been developed, including the strength Pareto evolutionary algorithm (SPEA) and the non-dominated sorting genetic algorithm (NSGA), for determining the Pareto-optimal set of non-dominated solutions. Although numerous researchers have developed a wide range of multiobjective optimization algorithms, there is a continuing need to construct computationally efficient algorithms with an improved ability to converge to globally non-dominated solutions along the Pareto-optimal front for complex, large-scale, multiobjective engineering optimization problems. This is particularly important when the multiple objective functions and constraints of the real-world system cannot be expressed in explicit mathematical representations. This research presents a novel metaheuristic evolutionary algorithm for complex multiobjective optimization problems, which combines the metaheuristic tabu search algorithm with the evolutionary algorithm (TSEA), as embodied in genetic algorithms. TSEA is successfully applied to bicriteria (i.e., structural reliability and retrofit cost) optimization of the aircraft tail structure fatigue life, which increases its reliability by prolonging fatigue life. A comparison for this application of the proposed algorithm, TSEA, with several state-of-the-art multiobjective optimization algorithms reveals that TSEA outperforms these algorithms by providing retrofit solutions with greater reliability for the same costs (i.e., closer to the Pareto-optimal front) after the algorithms are executed for the same number of generations. This research also demonstrates that TSEA competes with and, in some situations, outperforms state-of-the-art multiobjective optimization algorithms such as NSGA II and SPEA 2 when applied to classic bicriteria test problems in the technical literature and other complex, sizable real-world applications. The successful implementation of TSEA contributes to the safety of aeronautical structures by providing a systematic way to guide aircraft structural retrofitting efforts, as well as a potentially useful algorithm for a wide range of multiobjective optimization problems in engineering and other fields.

Generative model selection using a scalable and size-independent complex network classifier

NASA Astrophysics Data System (ADS)

Motallebi, Sadegh; Aliakbary, Sadegh; Habibi, Jafar

2013-12-01

Real networks exhibit nontrivial topological features, such as heavy-tailed degree distribution, high clustering, and small-worldness. Researchers have developed several generative models for synthesizing artificial networks that are structurally similar to real networks. An important research problem is to identify the generative model that best fits to a target network. In this paper, we investigate this problem and our goal is to select the model that is able to generate graphs similar to a given network instance. By the means of generating synthetic networks with seven outstanding generative models, we have utilized machine learning methods to develop a decision tree for model selection. Our proposed method, which is named "Generative Model Selection for Complex Networks," outperforms existing methods with respect to accuracy, scalability, and size-independence.

DOE Office of Scientific and Technical Information (OSTI.GOV)

Moore, Thomas W.; Quach, Tu-Thach; Detry, Richard Joseph

Complex Adaptive Systems of Systems, or CASoS, are vastly complex ecological, sociological, economic and/or technical systems which we must understand to design a secure future for the nation and the world. Perturbations/disruptions in CASoS have the potential for far-reaching effects due to pervasive interdependencies and attendant vulnerabilities to cascades in associated systems. Phoenix was initiated to address this high-impact problem space as engineers. Our overarching goals are maximizing security, maximizing health, and minimizing risk. We design interventions, or problem solutions, that influence CASoS to achieve specific aspirations. Through application to real-world problems, Phoenix is evolving the principles and discipline ofmore » CASoS Engineering while growing a community of practice and the CASoS engineers to populate it. Both grounded in reality and working to extend our understanding and control of that reality, Phoenix is at the same time a solution within a CASoS and a CASoS itself.« less

Community detection in complex networks by using membrane algorithm

NASA Astrophysics Data System (ADS)

Liu, Chuang; Fan, Linan; Liu, Zhou; Dai, Xiang; Xu, Jiamei; Chang, Baoren

Community detection in complex networks is a key problem of network analysis. In this paper, a new membrane algorithm is proposed to solve the community detection in complex networks. The proposed algorithm is based on membrane systems, which consists of objects, reaction rules, and a membrane structure. Each object represents a candidate partition of a complex network, and the quality of objects is evaluated according to network modularity. The reaction rules include evolutionary rules and communication rules. Evolutionary rules are responsible for improving the quality of objects, which employ the differential evolutionary algorithm to evolve objects. Communication rules implement the information exchanged among membranes. Finally, the proposed algorithm is evaluated on synthetic, real-world networks with real partitions known and the large-scaled networks with real partitions unknown. The experimental results indicate the superior performance of the proposed algorithm in comparison with other experimental algorithms.

Iterative repair for scheduling and rescheduling

NASA Technical Reports Server (NTRS)

Zweben, Monte; Davis, Eugene; Deale, Michael

1991-01-01

An iterative repair search method is described called constraint based simulated annealing. Simulated annealing is a hill climbing search technique capable of escaping local minima. The utility of the constraint based framework is shown by comparing search performance with and without the constraint framework on a suite of randomly generated problems. Results are also shown of applying the technique to the NASA Space Shuttle ground processing problem. These experiments show that the search methods scales to complex, real world problems and reflects interesting anytime behavior.

On unified modeling, theory, and method for solving multi-scale global optimization problems

NASA Astrophysics Data System (ADS)

Gao, David Yang

2016-10-01

A unified model is proposed for general optimization problems in multi-scale complex systems. Based on this model and necessary assumptions in physics, the canonical duality theory is presented in a precise way to include traditional duality theories and popular methods as special applications. Two conjectures on NP-hardness are proposed, which should play important roles for correctly understanding and efficiently solving challenging real-world problems. Applications are illustrated for both nonconvex continuous optimization and mixed integer nonlinear programming.

The Proposal of the Model for Developing Dispatch System for Nationwide One-Day Integrative Planning

NASA Astrophysics Data System (ADS)

Kim, Hyun Soo; Choi, Hyung Rim; Park, Byung Kwon; Jung, Jae Un; Lee, Jin Wook

The problems of dispatch planning for container truck are classified as the pickup and delivery problems, which are highly complex issues that consider various constraints in the real world. However, in case of the current situation, it is developed by the control system so that it requires the automated planning system under the view of nationwide integrative planning. Therefore, the purpose of this study is to suggest model to develop the automated dispatch system through the constraint satisfaction problem and meta-heuristic technique-based algorithm. In the further study, the practical system is developed and evaluation is performed in aspect of various results. This study suggests model to undergo the study which promoted the complexity of the problems by considering the various constraints which were not considered in the early study. However, it is suggested that it is necessary to add the study which includes the real-time monitoring function for vehicles and cargos based on the information technology.

Perceiving and Acting on Complex Affordances: How Children and Adults Bicycle across Two Lanes of Opposing Traffic

ERIC Educational Resources Information Center

Grechkin, Timofey Y.; Chihak, Benjamin J.; Cremer, James F.; Kearney, Joseph K.; Plumert, Jodie M.

2013-01-01

This investigation examined how children and adults negotiate a challenging perceptual-motor problem with significant real-world implications--bicycling across two lanes of opposing traffic. Twelve- and 14-year-olds and adults rode a bicycling simulator through an immersive virtual environment. Participants crossed intersections with continuous…

Designing a Better Experience: A Qualitative Investigation of Student Engineering Internships

ERIC Educational Resources Information Center

Paknejad, Mohammad R.

2016-01-01

Science, Technology, Engineering and Mathematics (STEM) education play a very important role in preparing students with skills necessary to obtain better jobs, solve real-world challenges, and compete in the global economy. STEM education develops critical thinking and the ability to solve complex problems. Research showed that 8 out of 10 most…

Dialysis, Albumin Binding, and Competitive Binding: A Laboratory Lesson Relating Three Chemical Concepts to Healthcare

ERIC Educational Resources Information Center

Domingo, Jennifer P.; Abualia, Mohammed; Barragan, Diana; Schroeder, Lianne; Wink, Donald J.; King, Maripat; Clark, Ginevra A.

2017-01-01

Introductory Chemistry laboratories must go beyond "cookbook" methods to illustrate how chemistry concepts apply to complex, real-world problems. In our case, we are preparing students to use their chemistry knowledge in the healthcare profession. The experiment described here explicitly models three important chemical concepts: dialysis…

Understanding Introductory Students' Application of Integrals in Physics from Multiple Perspectives

ERIC Educational Resources Information Center

Hu, Dehui

2013-01-01

Calculus is used across many physics topics from introductory to upper-division level college courses. The concepts of differentiation and integration are important tools for solving real world problems. Using calculus or any mathematical tool in physics is much more complex than the straightforward application of the equations and algorithms that…

Riding Alone on the Elevator: A Class Experiment in Interdisciplinary Education

ERIC Educational Resources Information Center

Frank, Anna M.; Froese, Rebecca; Hof, Barbara C.; Scheffold, Maike I. E.; Schreyer, Felix; Zeller, Mathias; Rödder, Simone

2017-01-01

The ability to conduct interdisciplinary research is crucial to address complex real-world problems that require the collaboration of different scientific fields, with global warming being a case in point. To produce integrated climate-related knowledge, climate researchers should be trained early on to work across boundaries and gain an…

Memetic Algorithms, Domain Knowledge, and Financial Investing

ERIC Educational Resources Information Center

Du, Jie

2012-01-01

While the question of how to use human knowledge to guide evolutionary search is long-recognized, much remains to be done to answer this question adequately. This dissertation aims to further answer this question by exploring the role of domain knowledge in evolutionary computation as applied to real-world, complex problems, such as financial…

Contribution of Emotional Intelligence towards Graduate Students' Critical Thinking Disposition

ERIC Educational Resources Information Center

Kang, Fong-Luan

2015-01-01

Good critical thinkers possess a core set of cognitive thinking skills, and a disposition towards critical thinking. They are able to think critically to solve complex, real-world problems effectively. Although personal emotion is important in critical thinking, it is often a neglected issue. The emotional intelligence in this study concerns our…

Integrating Six Sigma Concepts in an MBA Quality Management Class

ERIC Educational Resources Information Center

Weinstein, Larry B.; Petrick, Joseph; Castellano, Joseph; Vokurka, Robert J.

2008-01-01

Instructors face enormous challenges in presenting effective instruction on concepts and tools of quality management. Most textbooks focus on presenting individual concepts or tools and fail to address complex issues confronted in real-world problem-solving situations. The supplementary use of cases does not help students to understand the dynamic…

A Framework and a Methodology for Developing Authentic Constructivist e-Learning Environments

ERIC Educational Resources Information Center

Zualkernan, Imran A.

2006-01-01

Semantically rich domains require operative knowledge to solve complex problems in real-world settings. These domains provide an ideal environment for developing authentic constructivist e-learning environments. In this paper we present a framework and a methodology for developing authentic learning environments for such domains. The framework is…

The Social Process of Analyzing Real Water Resource Systems Plans and Management Policies

NASA Astrophysics Data System (ADS)

Loucks, Daniel

2016-04-01

Developing and applying systems analysis methods for improving the development and management of real world water resource systems, I have learned, is primarily a social process. This talk is a call for more recognition of this reality in the modeling approaches we propose in the papers and books we publish. The mathematical models designed to inform planners and managers of water systems that we see in many of our journals often seem more complex than they need be. They also often seem not as connected to reality as they could be. While it may be easier to publish descriptions of complex models than simpler ones, and while adding complexity to models might make them better able to mimic or resemble the actual complexity of the real physical and/or social systems or processes being analyzed, the usefulness of such models often can be an illusion. Sometimes the important features of reality that are of concern or interest to those who make decisions can be adequately captured using relatively simple models. Finding the right balance for the particular issues being addressed or the particular decisions that need to be made is an art. When applied to real world problems or issues in specific basins or regions, systems modeling projects often involve more attention to the social aspects than the mathematical ones. Mathematical models addressing connected interacting interdependent components of complex water systems are in fact some of the most useful methods we have to study and better understand the systems we manage around us. They can help us identify and evaluate possible alternative solutions to problems facing humanity today. The study of real world systems of interacting components using mathematical models is commonly called applied systems analyses. Performing such analyses with decision makers rather than of decision makers is critical if the needed trust between project personnel and their clients is to be developed. Using examples from recent and ongoing modeling projects in different parts of the world, this talk will attempt to show the dependency on the degree of project success with the degree of attention given to the communication between project personnel, the stakeholders and decision making institutions. It will also highlight how initial project terms-of-reference and expected outcomes can change, sometimes in surprising ways, during the course of such projects. Changing project objectives often result from changing stakeholder values, emphasizing the need for analyses that can adapt to this uncertainty.

The way adults with orientation to mathematics teaching cope with the solution of everyday real-world problems

NASA Astrophysics Data System (ADS)

Gazit, Avikam; Patkin, Dorit

2012-03-01

The article aims to check the way adults, some who are practicing mathematics teachers at elementary school, some who are academicians making a career change to mathematics teachers at junior high school and the rest who are pre-service mathematics teachers at elementary school, cope with the solution of everyday real-world problems of buying and selling. The findings show that even adults with mathematical background tend to make mistakes in solving everyday real-world problems. Only about 70% of the adults who have an orientation to mathematics solved the sample problem correctly. The lowest percentage of success was demonstrated by the academicians making a career change to junior high school mathematics teachers whereas the highest percentage of success was manifested by pre-service elementary school mathematics teachers. Moreover, the findings illustrate that life experience of the practicing mathematics teachers and, mainly, of the academicians making a career change, who were older than the pre-service teachers, did not facilitate the solution of such a real-world problem. Perhaps the reason resides in the process of mathematics teaching at school, which does not put an emphasis on the solution of everyday real-world problems.

Generative model selection using a scalable and size-independent complex network classifier

DOE Office of Scientific and Technical Information (OSTI.GOV)

Motallebi, Sadegh, E-mail: motallebi@ce.sharif.edu; Aliakbary, Sadegh, E-mail: aliakbary@ce.sharif.edu; Habibi, Jafar, E-mail: jhabibi@sharif.edu

2013-12-15

Real networks exhibit nontrivial topological features, such as heavy-tailed degree distribution, high clustering, and small-worldness. Researchers have developed several generative models for synthesizing artificial networks that are structurally similar to real networks. An important research problem is to identify the generative model that best fits to a target network. In this paper, we investigate this problem and our goal is to select the model that is able to generate graphs similar to a given network instance. By the means of generating synthetic networks with seven outstanding generative models, we have utilized machine learning methods to develop a decision tree formore » model selection. Our proposed method, which is named “Generative Model Selection for Complex Networks,” outperforms existing methods with respect to accuracy, scalability, and size-independence.« less

BI-sparsity pursuit for robust subspace recovery

DOE PAGES

Bian, Xiao; Krim, Hamid

2015-09-01

Here, the success of sparse models in computer vision and machine learning in many real-world applications, may be attributed in large part, to the fact that many high dimensional data are distributed in a union of low dimensional subspaces. The underlying structure may, however, be adversely affected by sparse errors, thus inducing additional complexity in recovering it. In this paper, we propose a bi-sparse model as a framework to investigate and analyze this problem, and provide as a result , a novel algorithm to recover the union of subspaces in presence of sparse corruptions. We additionally demonstrate the effectiveness ofmore » our method by experiments on real-world vision data.« less

Set as an Instance of a Real-World Visual-Cognitive Task

ERIC Educational Resources Information Center

Nyamsuren, Enkhbold; Taatgen, Niels A.

2013-01-01

Complex problem solving is often an integration of perceptual processing and deliberate planning. But what balances these two processes, and how do novices differ from experts? We investigate the interplay between these two in the game of SET. This article investigates how people combine bottom-up visual processes and top-down planning to succeed…

The Power of Numbers. A Teacher's Guide to Mathematics in a Social Studies Context. An Interdisciplinary Curriculum.

ERIC Educational Resources Information Center

Gross, Fred E.; And Others

This document is the teacher's guide for a curriculum designed to teach mathematics in a social studies context. It provides mathematical experiences in real world contexts that help students interpret, experiment, communicate, and look for multiple solutions to complex problems. The curriculum uses mathematics in context to help students develop…

Classroom Literacy Assessment. Making Sense of What Students Know and Do. Solving Problems in the Teaching of Literacy Series

ERIC Educational Resources Information Center

Paratore, Jeanne R. Ed.; McCormack, Rachel L. Ed.; Block, Cathy, Collins Ed.

2007-01-01

Showcasing assessment practices that can help teachers plan effective instruction, this book addresses the real-world complexities of teaching literacy in grades K-8. Leading contributors present trustworthy approaches that examine learning processes as well as learning products, that yield information on how the learning environment can be…

Integrated Concentration in Science (iCons): Undergraduate Education Through Interdisciplinary, Team-Based, Real-World Problem Solving

NASA Astrophysics Data System (ADS)

Tuominen, Mark

2013-03-01

Attitude, Skills, Knowledge (ASK) - In this order, these are fundamental characteristics of scientific innovators. Through first-hand practice in using science to unpack and solve complex real-world problems, students can become self-motivated scientific leaders. This presentation describes the pedagogy of a recently developed interdisciplinary undergraduate science education program at the University of Massachusetts Amherst focused on addressing global challenges with scientific solutions. Integrated Concentration in Science (iCons) is an overarching concentration program that supplements the curricula provided within each student's chosen major. iCons is a platform for students to perform student-led research in interdisciplinary collaborative teams. With a schedule of one course per year over four years, the cohort of students move through case studies, analysis of real-world problems, development of potential solutions, integrative communication, laboratory practice, and capstone research projects. In this presentation, a track emphasizing renewable energy science is used to illustrate the iCons pedagogical methods. This includes discussion of a third-year laboratory course in renewable energy that is educationally scaffolded: beginning with a boot camp in laboratory techniques and culminating with student-designed research projects. Among other objectives, this course emphasizes the practice of using reflection and redesign, as a means of generating better solutions and embedding learning for the long term. This work is supported in part by NSF grant DUE-1140805.

Boosting medical diagnostics by pooling independent judgments

PubMed Central

Kurvers, Ralf H. J. M.; Herzog, Stefan M.; Hertwig, Ralph; Krause, Jens; Carney, Patricia A.; Bogart, Andy; Argenziano, Giuseppe; Zalaudek, Iris; Wolf, Max

2016-01-01

Collective intelligence refers to the ability of groups to outperform individual decision makers when solving complex cognitive problems. Despite its potential to revolutionize decision making in a wide range of domains, including medical, economic, and political decision making, at present, little is known about the conditions underlying collective intelligence in real-world contexts. We here focus on two key areas of medical diagnostics, breast and skin cancer detection. Using a simulation study that draws on large real-world datasets, involving more than 140 doctors making more than 20,000 diagnoses, we investigate when combining the independent judgments of multiple doctors outperforms the best doctor in a group. We find that similarity in diagnostic accuracy is a key condition for collective intelligence: Aggregating the independent judgments of doctors outperforms the best doctor in a group whenever the diagnostic accuracy of doctors is relatively similar, but not when doctors’ diagnostic accuracy differs too much. This intriguingly simple result is highly robust and holds across different group sizes, performance levels of the best doctor, and collective intelligence rules. The enabling role of similarity, in turn, is explained by its systematic effects on the number of correct and incorrect decisions of the best doctor that are overruled by the collective. By identifying a key factor underlying collective intelligence in two important real-world contexts, our findings pave the way for innovative and more effective approaches to complex real-world decision making, and to the scientific analyses of those approaches. PMID:27432950

Derivative with two fractional orders: A new avenue of investigation toward revolution in fractional calculus

NASA Astrophysics Data System (ADS)

Atangana, Abdon

2016-10-01

In order to describe more complex problems using the concept of fractional derivatives, we introduce in this paper the concept of fractional derivatives with orders. The new definitions are based upon the concept of power law together with the generalized Mittag-Leffler function. The first order is included in the power law function and the second one is in the generalized Mittag-Leffler function. Each order therefore plays an important role while modeling, for instance, problems with two layers with different properties. This is the case, for instance, in thermal science for a reaction diffusion within a media with two different layers with different properties. Another case is that of groundwater flowing within an aquifer where geological formation is formed with two layers with different properties. The paper presents new fractional operators that will open new doors for research and investigations in modeling real world problems. Some useful properties of the new operators are presented, in particular their relationship with existing integral transforms, namely the Laplace, Sumudu, Mellin and Fourier transforms. The numerical approximation of the new fractional operators are presented. We apply the new fractional operators on the model of groundwater plume with degradation and limited sorption and solve the new model numerically with some numerical simulations. The numerical simulation leaves no doubt in believing that the new fractional operators are powerfull mathematical tools able to portray complexes real world problems.

A design rationale for NASA TileWorld

NASA Technical Reports Server (NTRS)

Philips, Andrew B.; Swanson, Keith J.; Drummond, Mark E.; Bresina, John L.

1991-01-01

Automated systems that can operate in unrestricted real-world domains are still well beyond current computational capabilities. This paper argues that isolating essential problem characteristics found in real-world domains allows for a careful study of how particular control systems operate. By isolating essential problem characteristics and studying their impact on autonomous system performance, we should be able to more quickly deliver systems for practical real-world problems. For our research on planning, scheduling, and control, we have selected three particular domain attributes to study: exogenous events, uncertain action outcome, and metric time. We are not suggesting that studies of these attributes in isolation are sufficient to guarantee the obvious goals of good methodology, brilliant architectures, or first-class results; however, we are suggesting that such isolation facilitates the achievement of these goals. To study these attributes, we have developed the NASA TileWorld. We describe the NASA TileWorld simulator in general terms, present an example NASA TileWorld problem, and discuss some of our motivations and concerns for NASA TileWorld.

A brief historical introduction to Euler's formula for polyhedra, topology, graph theory and networks

NASA Astrophysics Data System (ADS)

Debnath, Lokenath

2010-09-01

This article is essentially devoted to a brief historical introduction to Euler's formula for polyhedra, topology, theory of graphs and networks with many examples from the real-world. Celebrated Königsberg seven-bridge problem and some of the basic properties of graphs and networks for some understanding of the macroscopic behaviour of real physical systems are included. We also mention some important and modern applications of graph theory or network problems from transportation to telecommunications. Graphs or networks are effectively used as powerful tools in industrial, electrical and civil engineering, communication networks in the planning of business and industry. Graph theory and combinatorics can be used to understand the changes that occur in many large and complex scientific, technical and medical systems. With the advent of fast large computers and the ubiquitous Internet consisting of a very large network of computers, large-scale complex optimization problems can be modelled in terms of graphs or networks and then solved by algorithms available in graph theory. Many large and more complex combinatorial problems dealing with the possible arrangements of situations of various kinds, and computing the number and properties of such arrangements can be formulated in terms of networks. The Knight's tour problem, Hamilton's tour problem, problem of magic squares, the Euler Graeco-Latin squares problem and their modern developments in the twentieth century are also included.

The Role of Problem-Based Learning in Developing Creative Expertise

ERIC Educational Resources Information Center

Gallagher, Shelagh A.

2015-01-01

Contemporary real-world problems require creative solutions, necessitating the preparation of a new generation of creative experts capable of finding original solutions to ill-structured problems. Although much school-based training in creativity focuses on discrete skills, real-world creativity results from a multidimensional interaction between…

Robot, computer problem solving system

NASA Technical Reports Server (NTRS)

Becker, J. D.

1972-01-01

The development of a computer problem solving system is reported that considers physical problems faced by an artificial robot moving around in a complex environment. Fundamental interaction constraints with a real environment are simulated for the robot by visual scan and creation of an internal environmental model. The programming system used in constructing the problem solving system for the simulated robot and its simulated world environment is outlined together with the task that the system is capable of performing. A very general framework for understanding the relationship between an observed behavior and an adequate description of that behavior is included.

Effective real-time vehicle tracking using discriminative sparse coding on local patches

NASA Astrophysics Data System (ADS)

Chen, XiangJun; Ye, Feiyue; Ruan, Yaduan; Chen, Qimei

2016-01-01

A visual tracking framework that provides an object detector and tracker, which focuses on effective and efficient visual tracking in surveillance of real-world intelligent transport system applications, is proposed. The framework casts the tracking task as problems of object detection, feature representation, and classification, which is different from appearance model-matching approaches. Through a feature representation of discriminative sparse coding on local patches called DSCLP, which trains a dictionary on local clustered patches sampled from both positive and negative datasets, the discriminative power and robustness has been improved remarkably, which makes our method more robust to a complex realistic setting with all kinds of degraded image quality. Moreover, by catching objects through one-time background subtraction, along with offline dictionary training, computation time is dramatically reduced, which enables our framework to achieve real-time tracking performance even in a high-definition sequence with heavy traffic. Experiment results show that our work outperforms some state-of-the-art methods in terms of speed, accuracy, and robustness and exhibits increased robustness in a complex real-world scenario with degraded image quality caused by vehicle occlusion, image blur of rain or fog, and change in viewpoint or scale.

Informatics in radiology: an information model of the DICOM standard.

PubMed

Kahn, Charles E; Langlotz, Curtis P; Channin, David S; Rubin, Daniel L

2011-01-01

The Digital Imaging and Communications in Medicine (DICOM) Standard is a key foundational technology for radiology. However, its complexity creates challenges for information system developers because the current DICOM specification requires human interpretation and is subject to nonstandard implementation. To address this problem, a formally sound and computationally accessible information model of the DICOM Standard was created. The DICOM Standard was modeled as an ontology, a machine-accessible and human-interpretable representation that may be viewed and manipulated by information-modeling tools. The DICOM Ontology includes a real-world model and a DICOM entity model. The real-world model describes patients, studies, images, and other features of medical imaging. The DICOM entity model describes connections between real-world entities and the classes that model the corresponding DICOM information entities. The DICOM Ontology was created to support the Cancer Biomedical Informatics Grid (caBIG) initiative, and it may be extended to encompass the entire DICOM Standard and serve as a foundation of medical imaging systems for research and patient care. RSNA, 2010

Diving into Real World Challenges

ERIC Educational Resources Information Center

Saldana, Matt; Rodden, Leslie

2012-01-01

In this article, the authors discuss how educators can engage students in real world learning using their academic knowledge and technical skills. They describe how school districts have discovered that the world of robotics can help students use technical skills to solve simulated problems found in the real world, while understanding the…

The Phenomenon of Collaboration: A Phenomenologic Study of Collaboration between Family Medicine and Obstetrics and Gynecology Departments at an Academic Medical Center

ERIC Educational Resources Information Center

Brown, David R.; Brewster, Cheryl D.; Karides, Marina; Lukas, Lou A.

2011-01-01

Collaboration is essential to manage complex real world problems. We used phenomenologic methods to elaborate a description of collaboration between two departments at an academic medical center who considered their relationship to represent a model of effective collaboration. Key collaborative structures included a shared vision and commitment by…

The Future of Psychology: Connecting Mind to Brain

PubMed Central

Barrett, Lisa Feldman

2009-01-01

Psychological states such as thoughts and feelings are real. Brain states are real. The problem is that the two are not real in the same way, creating the mind–brain correspondence problem. In this article, I present a possible solution to this problem that involves two suggestions. First, complex psychological states such as emotion and cognition an be thought of as constructed events that can be causally reduced to a set of more basic, psychologically primitive ingredients that are more clearly respected by the brain. Second, complex psychological categories like emotion and cognition are the phenomena that require explanation in psychology, and, therefore, they cannot be abandoned by science. Describing the content and structure of these categories is a necessary and valuable scientific activity. Physical concepts are free creations of the human mind, and are not, however it may seem, uniquely determined by the external world.—Einstein & Infeld (1938, p. 33) The cardinal passions of our life, anger, love, fear, hate, hope, and the most comprehensive divisions of our intellectual activity, to remember, expect, think, know, dream (and he goes on to say, feel) are the only facts of a subjective order…—James (1890, p. 195) PMID:19844601

Hierarchical Spatio-Temporal Probabilistic Graphical Model with Multiple Feature Fusion for Binary Facial Attribute Classification in Real-World Face Videos.

PubMed

Demirkus, Meltem; Precup, Doina; Clark, James J; Arbel, Tal

2016-06-01

Recent literature shows that facial attributes, i.e., contextual facial information, can be beneficial for improving the performance of real-world applications, such as face verification, face recognition, and image search. Examples of face attributes include gender, skin color, facial hair, etc. How to robustly obtain these facial attributes (traits) is still an open problem, especially in the presence of the challenges of real-world environments: non-uniform illumination conditions, arbitrary occlusions, motion blur and background clutter. What makes this problem even more difficult is the enormous variability presented by the same subject, due to arbitrary face scales, head poses, and facial expressions. In this paper, we focus on the problem of facial trait classification in real-world face videos. We have developed a fully automatic hierarchical and probabilistic framework that models the collective set of frame class distributions and feature spatial information over a video sequence. The experiments are conducted on a large real-world face video database that we have collected, labelled and made publicly available. The proposed method is flexible enough to be applied to any facial classification problem. Experiments on a large, real-world video database McGillFaces [1] of 18,000 video frames reveal that the proposed framework outperforms alternative approaches, by up to 16.96 and 10.13%, for the facial attributes of gender and facial hair, respectively.

Introducing the MCHF/OVRP/SDMP: Multicapacitated/Heterogeneous Fleet/Open Vehicle Routing Problems with Split Deliveries and Multiproducts

PubMed Central

Yilmaz Eroglu, Duygu; Caglar Gencosman, Burcu; Cavdur, Fatih; Ozmutlu, H. Cenk

2014-01-01

In this paper, we analyze a real-world OVRP problem for a production company. Considering real-world constrains, we classify our problem as multicapacitated/heterogeneous fleet/open vehicle routing problem with split deliveries and multiproduct (MCHF/OVRP/SDMP) which is a novel classification of an OVRP. We have developed a mixed integer programming (MIP) model for the problem and generated test problems in different size (10–90 customers) considering real-world parameters. Although MIP is able to find optimal solutions of small size (10 customers) problems, when the number of customers increases, the problem gets harder to solve, and thus MIP could not find optimal solutions for problems that contain more than 10 customers. Moreover, MIP fails to find any feasible solution of large-scale problems (50–90 customers) within time limits (7200 seconds). Therefore, we have developed a genetic algorithm (GA) based solution approach for large-scale problems. The experimental results show that the GA based approach reaches successful solutions with 9.66% gap in 392.8 s on average instead of 7200 s for the problems that contain 10–50 customers. For large-scale problems (50–90 customers), GA reaches feasible solutions of problems within time limits. In conclusion, for the real-world applications, GA is preferable rather than MIP to reach feasible solutions in short time periods. PMID:25045735

On the break down of reality at superluminal velocities, Quantum entanglement and Singularities (Complex Universe)

NASA Astrophysics Data System (ADS)

Estakhr, Ahmad Reza

2017-09-01

In the real world nothing can move faster than the speed of light. But what convinces you that our world is all real? I realized that reality break down at superluminal velocities (By studying the physics of tachyonic neutrinos), Quantum entanglement and Singularities of Black Holes, I realized that infact our world is complex and has two parts, one part of the world is real (the part that nothing can move faster than the speed of light) but the other part of the world is imaginary. z = a + ib Einstein was wrong because he thought our world is completely real (Of course he was not alone in this belief almost all physicists believe that our world is completely real) Eventually his false interpretation of reality censored imaginary part of the universe. Einstein's Second Postulate of special theory of relativity was a misleading guide to the true nature of reality. He `expected' the true nature of reality will follow to his (false) postulate, But the true nature of reality is unlike what anyone ever `expected'!. Einstein twist facts to suit his theory of relativity instead of theories to suit facts!. This is a dramatic revisions to our conception of the theory of relativity, Reality is complex but We always perceive its real part.

Leadership emergence in engineering design teams.

PubMed

Guastello, Stephen J

2011-01-01

Leaders emerge from leaderless groups as part of a more complex emerging social structure. Several studies have shown that the emerging structure is aptly described by a swallowtail catastrophe model where the control parameters differ depending on whether creative problem solving, production, coordination-intensive, or emergency management groups are involved. The present study explored creative problem solving further where the participants were engaged in real-world tasks extending over several months rather than short laboratory tasks. Participants were engineering students who were organized into groups of to people who designed, built, and tested a prototype product that would solve a real-world problem. At the th week of work they completed a questionnaire indicating who was most like the leader of their group, second most like the leader, along with other questions about individuals' contributions to the group process. Results showed that the swallowtail model (R = .) exhibited a strong advantage over the linear alternative model (R = .) for predicting leadership emergence. The three control variables were control of the task, creative contributions to the group's work, and facilitating the creative contributions of others.

System Identification for the Clipper Liberty C96 Wind Turbine

NASA Astrophysics Data System (ADS)

Showers, Daniel

System identification techniques are powerful tools that help improve modeling capabilities of real world dynamic systems. These techniques are well established and have been successfully used on countless systems in many areas. However, wind turbines provide a unique challenge for system identification because of the difficulty in measuring its primary input: wind. This thesis first motivates the problem by demonstrating the challenges with wind turbine system identification using both simulations and real data. It then suggests techniques toward successfully identifying a dynamic wind turbine model including the notion of an effective wind speed and how it might be measured. Various levels of simulation complexity are explored for insights into calculating an effective wind speed. In addition, measurements taken from the University of Minnesota's Clipper Liberty C96 research wind turbine are used for a preliminary investigation into the effective wind speed calculation and system identification of a real world wind turbine.

Food for Thought: Cross-Classification and Category Organization in a Complex Real-World Domain.

ERIC Educational Resources Information Center

Ross, Brian H.; Murphy, Gregory L.

1999-01-01

Seven studies involving 256 undergraduates examined how people represent, access, and make inferences about the real-world category domain, foods. Results give a detailed picture of the use of cross-classification in a complex domain. (SLD)

Complex fuzzy soft expert sets

NASA Astrophysics Data System (ADS)

Selvachandran, Ganeshsree; Hafeed, Nisren A.; Salleh, Abdul Razak

2017-04-01

Complex fuzzy sets and its accompanying theory although at its infancy, has proven to be superior to classical type-1 fuzzy sets, due its ability in representing time-periodic problem parameters and capturing the seasonality of the fuzziness that exists in the elements of a set. These are important characteristics that are pervasive in most real world problems. However, there are two major problems that are inherent in complex fuzzy sets: it lacks a sufficient parameterization tool and it does not have a mechanism to validate the values assigned to the membership functions of the elements in a set. To overcome these problems, we propose the notion of complex fuzzy soft expert sets which is a hybrid model of complex fuzzy sets and soft expert sets. This model incorporates the advantages of complex fuzzy sets and soft sets, besides having the added advantage of allowing the users to know the opinion of all the experts in a single model without the need for any additional cumbersome operations. As such, this model effectively improves the accuracy of representation of problem parameters that are periodic in nature, besides having a higher level of computational efficiency compared to similar models in literature.

Evaluation of the cognitive effects of travel technique in complex real and virtual environments.

PubMed

Suma, Evan A; Finkelstein, Samantha L; Reid, Myra; V Babu, Sabarish; Ulinski, Amy C; Hodges, Larry F

2010-01-01

We report a series of experiments conducted to investigate the effects of travel technique on information gathering and cognition in complex virtual environments. In the first experiment, participants completed a non-branching multilevel 3D maze at their own pace using either real walking or one of two virtual travel techniques. In the second experiment, we constructed a real-world maze with branching pathways and modeled an identical virtual environment. Participants explored either the real or virtual maze for a predetermined amount of time using real walking or a virtual travel technique. Our results across experiments suggest that for complex environments requiring a large number of turns, virtual travel is an acceptable substitute for real walking if the goal of the application involves learning or reasoning based on information presented in the virtual world. However, for applications that require fast, efficient navigation or travel that closely resembles real-world behavior, real walking has advantages over common joystick-based virtual travel techniques.

Ensuring the Quality of Outreach: The Critical Role of Evaluating Individual and Collective Initiatives and Performance

ERIC Educational Resources Information Center

Lynton, Ernest A.

2016-01-01

New knowledge is created in the course of the application of outreach. Each complex problem in the real world is likely to have unique aspects and thus it requires some modification of standard approaches. Hence, each engagement in outreach is likely to have an element of inquiry and discovery, leading to new knowledge. The flow of knowledge is in…

Page Oriented Holographic Memories And Optical Pattern Recognition

NASA Astrophysics Data System (ADS)

Caulfield, H. J.

1987-08-01

In the twenty-two years since VanderLugt's introduction of holographic matched filtering, the intensive research carried out throughout the world has led to no applications in complex environment. This leads one to the suspicion that the VanderLugt filter technique is insufficiently complex to handle truly complex problems. Therefore, it is of great interest to increase the complexity of the VanderLugt filtering operation. We introduce here an approach to the real time filter assembly: use of page oriented holographic memories and optically addressed SLMs to achieve intelligent and fast reprogramming of the filters using a 10 4 to 10 6 stored pattern base.

Tracking dynamic team activity

DOE Office of Scientific and Technical Information (OSTI.GOV)

Tambe, M.

1996-12-31

AI researchers are striving to build complex multi-agent worlds with intended applications ranging from the RoboCup robotic soccer tournaments, to interactive virtual theatre, to large-scale real-world battlefield simulations. Agent tracking - monitoring other agent`s actions and inferring their higher-level goals and intentions - is a central requirement in such worlds. While previous work has mostly focused on tracking individual agents, this paper goes beyond by focusing on agent teams. Team tracking poses the challenge of tracking a team`s joint goals and plans. Dynamic, real-time environments add to the challenge, as ambiguities have to be resolved in real-time. The central hypothesismore » underlying the present work is that an explicit team-oriented perspective enables effective team tracking. This hypothesis is instantiated using the model tracing technology employed in tracking individual agents. Thus, to track team activities, team models are put to service. Team models are a concrete application of the joint intentions framework and enable an agent to track team activities, regardless of the agent`s being a collaborative participant or a non-participant in the team. To facilitate real-time ambiguity resolution with team models: (i) aspects of tracking are cast as constraint satisfaction problems to exploit constraint propagation techniques; and (ii) a cost minimality criterion is applied to constrain tracking search. Empirical results from two separate tasks in real-world, dynamic environments one collaborative and one competitive - are provided.« less

Optimizing a realistic large-scale frequency assignment problem using a new parallel evolutionary approach

NASA Astrophysics Data System (ADS)

Chaves-González, José M.; Vega-Rodríguez, Miguel A.; Gómez-Pulido, Juan A.; Sánchez-Pérez, Juan M.

2011-08-01

This article analyses the use of a novel parallel evolutionary strategy to solve complex optimization problems. The work developed here has been focused on a relevant real-world problem from the telecommunication domain to verify the effectiveness of the approach. The problem, known as frequency assignment problem (FAP), basically consists of assigning a very small number of frequencies to a very large set of transceivers used in a cellular phone network. Real data FAP instances are very difficult to solve due to the NP-hard nature of the problem, therefore using an efficient parallel approach which makes the most of different evolutionary strategies can be considered as a good way to obtain high-quality solutions in short periods of time. Specifically, a parallel hyper-heuristic based on several meta-heuristics has been developed. After a complete experimental evaluation, results prove that the proposed approach obtains very high-quality solutions for the FAP and beats any other result published.

A novel multilayer model for missing link prediction and future link forecasting in dynamic complex networks

NASA Astrophysics Data System (ADS)

Yasami, Yasser; Safaei, Farshad

2018-02-01

The traditional complex network theory is particularly focused on network models in which all network constituents are dealt with equivalently, while fail to consider the supplementary information related to the dynamic properties of the network interactions. This is a main constraint leading to incorrect descriptions of some real-world phenomena or incomplete capturing the details of certain real-life problems. To cope with the problem, this paper addresses the multilayer aspects of dynamic complex networks by analyzing the properties of intrinsically multilayered co-authorship networks, DBLP and Astro Physics, and presenting a novel multilayer model of dynamic complex networks. The model examines the layers evolution (layers birth/death process and lifetime) throughout the network evolution. Particularly, this paper models the evolution of each node's membership in different layers by an Infinite Factorial Hidden Markov Model considering feature cascade, and thereby formulates the link generation process for intra-layer and inter-layer links. Although adjacency matrixes are useful to describe the traditional single-layer networks, such a representation is not sufficient to describe and analyze the multilayer dynamic networks. This paper also extends a generalized mathematical infrastructure to address the problems issued by multilayer complex networks. The model inference is performed using some Markov Chain Monte Carlo sampling strategies, given synthetic and real complex networks data. Experimental results indicate a tremendous improvement in the performance of the proposed multilayer model in terms of sensitivity, specificity, positive and negative predictive values, positive and negative likelihood ratios, F1-score, Matthews correlation coefficient, and accuracy for two important applications of missing link prediction and future link forecasting. The experimental results also indicate the strong predictivepower of the proposed model for the application of cascade prediction in terms of accuracy.

Teaching Real-World Applications of Business Statistics Using Communication to Scaffold Learning

ERIC Educational Resources Information Center

Green, Gareth P.; Jones, Stacey; Bean, John C.

2015-01-01

Our assessment research suggests that quantitative business courses that rely primarily on algorithmic problem solving may not produce the deep learning required for addressing real-world business problems. This article illustrates a strategy, supported by recent learning theory, for promoting deep learning by moving students gradually from…

Teaching Molecular Phylogenetics through Investigating a Real-World Phylogenetic Problem

ERIC Educational Resources Information Center

Zhang, Xiaorong

2012-01-01

A phylogenetics exercise is incorporated into the "Introduction to biocomputing" course, a junior-level course at Savannah State University. This exercise is designed to help students learn important concepts and practical skills in molecular phylogenetics through solving a real-world problem. In this application, students are required to identify…

A VIKOR Technique with Applications Based on DEMATEL and ANP

NASA Astrophysics Data System (ADS)

Ou Yang, Yu-Ping; Shieh, How-Ming; Tzeng, Gwo-Hshiung

In multiple criteria decision making (MCDM) methods, the compromise ranking method (named VIKOR) was introduced as one applicable technique to implement within MCDM. It was developed for multicriteria optimization of complex systems. However, few papers discuss conflicting (competing) criteria with dependence and feedback in the compromise solution method. Therefore, this study proposes and provides applications for a novel model using the VIKOR technique based on DEMATEL and the ANP to solve the problem of conflicting criteria with dependence and feedback. In addition, this research also uses DEMATEL to normalize the unweighted supermatrix of the ANP to suit the real world. An example is also presented to illustrate the proposed method with applications thereof. The results show the proposed method is suitable and effective in real-world applications.

Motif formation and industry specific topologies in the Japanese business firm network

NASA Astrophysics Data System (ADS)

Maluck, Julian; Donner, Reik V.; Takayasu, Hideki; Takayasu, Misako

2017-05-01

Motifs and roles are basic quantities for the characterization of interactions among 3-node subsets in complex networks. In this work, we investigate how the distribution of 3-node motifs can be influenced by modifying the rules of an evolving network model while keeping the statistics of simpler network characteristics, such as the link density and the degree distribution, invariant. We exemplify this problem for the special case of the Japanese Business Firm Network, where a well-studied and relatively simple yet realistic evolving network model is available, and compare the resulting motif distribution in the real-world and simulated networks. To better approximate the motif distribution of the real-world network in the model, we introduce both subgraph dependent and global additional rules. We find that a specific rule that allows only for the merging process between nodes with similar link directionality patterns reduces the observed excess of densely connected motifs with bidirectional links. Our study improves the mechanistic understanding of motif formation in evolving network models to better describe the characteristic features of real-world networks with a scale-free topology.

An Investigation of Problem Solving Approaches, Strategies, and Models Used by the 7th and 8th Grade Students When Solving Real-World Problems

ERIC Educational Resources Information Center

Bayazit, Ibrahim

2013-01-01

This study scrutinises approaches and thinking processes displayed by the elementary school students when solving real-world problems. It employed a qualitative inquiry to produce rich and realistic data about the case at hand. The research sample included 116 students. The data were obtained from written exam and semistructured interviews, and…

Learning to Predict Social Influence in Complex Networks

DTIC Science & Technology

2012-03-29

03/2010 – 17/03/2012 Abstract: First, we addressed the problem of analyzing information diffusion process in a social network using two kinds...algorithm which avoids the inner loop optimization during the search. We tested the performance using the structures of four real world networks, and...result of information diffusion that starts from the node. 2 We use “infected” and “activated” interchangeably. Efficient Discovery of Influential

Engineering Encounters: The Tightrope Challenge

ERIC Educational Resources Information Center

Burton, Bill

2014-01-01

In order to prepare students to become the next innovators, teachers need to provide real-world challenges that allow children to exercise their innovation muscles. Innovation starts with a problem and innovators work to solve a problem by planning, creating, and testing. The real-world innovation process does not happen on a worksheet, and it…

Using Real World Experience to Teach Science and Environmental Writing.

ERIC Educational Resources Information Center

Friedman, Sharon M.

The use of interpretive reporting techniques and programs offering real world training to writers may provide solutions to the problems encountered in writing about science for the mass media. Both science and environmental writers have suggested that the problems they face would be decreased by the use of more interpretive and investigative…

The Mathematics of High School Physics

NASA Astrophysics Data System (ADS)

Kanderakis, Nikos

2016-10-01

In the seventeenth and eighteenth centuries, mathematicians and physical philosophers managed to study, via mathematics, various physical systems of the sublunar world through idealized and simplified models of these systems, constructed with the help of geometry. By analyzing these models, they were able to formulate new concepts, laws and theories of physics and then through models again, to apply these concepts and theories to new physical phenomena and check the results by means of experiment. Students' difficulties with the mathematics of high school physics are well known. Science education research attributes them to inadequately deep understanding of mathematics and mainly to inadequate understanding of the meaning of symbolic mathematical expressions. There seem to be, however, more causes of these difficulties. One of them, not independent from the previous ones, is the complex meaning of the algebraic concepts used in school physics (e.g. variables, parameters, functions), as well as the complexities added by physics itself (e.g. that equations' symbols represent magnitudes with empirical meaning and units instead of pure numbers). Another source of difficulties is that the theories and laws of physics are often applied, via mathematics, to simplified, and idealized physical models of the world and not to the world itself. This concerns not only the applications of basic theories but also all authentic end-of-the-chapter problems. Hence, students have to understand and participate in a complex interplay between physics concepts and theories, physical and mathematical models, and the real world, often without being aware that they are working with models and not directly with the real world.

Making Math Real: Effective Qualities of Guest Speaker Presentations and the Impact of Speakers on Student Attitude and Achievement in the Algebra Classroom

ERIC Educational Resources Information Center

McKain, Danielle R.

2012-01-01

The term real world is often used in mathematics education, yet the definition of real-world problems and how to incorporate them in the classroom remains ambiguous. One way real-world connections can be made is through guest speakers. Guest speakers can offer different perspectives and share knowledge about various subject areas, yet the impact…

Steady-State ALPS for Real-Valued Problems

NASA Technical Reports Server (NTRS)

Hornby, Gregory S.

2009-01-01

The two objectives of this paper are to describe a steady-state version of the Age-Layered Population Structure (ALPS) Evolutionary Algorithm (EA) and to compare it against other GAs on real-valued problems. Motivation for this work comes from our previous success in demonstrating that a generational version of ALPS greatly improves search performance on a Genetic Programming problem. In making steady-state ALPS some modifications were made to the method for calculating age and the method for moving individuals up layers. To demonstrate that ALPS works well on real-valued problems we compare it against CMA-ES and Differential Evolution (DE) on five challenging, real-valued functions and on one real-world problem. While CMA-ES and DE outperform ALPS on the two unimodal test functions, ALPS is much better on the three multimodal test problems and on the real-world problem. Further examination shows that, unlike the other GAs, ALPS maintains a genotypically diverse population throughout the entire search process. These findings strongly suggest that the ALPS paradigm is better able to avoid premature convergence then the other GAs.

Identifying and characterizing key nodes among communities based on electrical-circuit networks.

PubMed

Zhu, Fenghui; Wang, Wenxu; Di, Zengru; Fan, Ying

2014-01-01

Complex networks with community structures are ubiquitous in the real world. Despite many approaches developed for detecting communities, we continue to lack tools for identifying overlapping and bridging nodes that play crucial roles in the interactions and communications among communities in complex networks. Here we develop an algorithm based on the local flow conservation to effectively and efficiently identify and distinguish the two types of nodes. Our method is applicable in both undirected and directed networks without a priori knowledge of the community structure. Our method bypasses the extremely challenging problem of partitioning communities in the presence of overlapping nodes that may belong to multiple communities. Due to the fact that overlapping and bridging nodes are of paramount importance in maintaining the function of many social and biological networks, our tools open new avenues towards understanding and controlling real complex networks with communities accompanied with the key nodes.

A Probabilistic Ontology Development Methodology

DTIC Science & Technology

2014-06-01

Test, and Evaluation; Acquisition; and Planning and Marketing ," in Handbook of Systems Engineering and Management .: John Wiley & Sons, 2009, pp...Intelligence and knowledge management . However, many real world problems in these disciplines are burdened by incomplete information and other sources...knowledge engineering, Artificial Intelligence and knowledge management . However, many real world problems in these disciplines are burdened by

Mathematical Self-Efficacy and Understanding: Using Geographic Information Systems to Mediate Urban High School Students' Real-World Problem Solving

ERIC Educational Resources Information Center

DeBay, Dennis J.

2013-01-01

To explore student mathematical self-efficacy and understanding of graphical data, this dissertation examines students solving real-world problems in their neighborhood, mediated by professional urban planning technologies. As states and schools are working on the alignment of the Common Core State Standards for Mathematics (CCSSM), traditional…

Problem-Based Learning Pedagogies: Psychological Processes and Enhancement of Intelligences

ERIC Educational Resources Information Center

Tan, Oon-Seng

2007-01-01

Education in this 21st century is concerned with developing intelligences. Problem solving in real-world contexts involves multiple ways of knowing and learning. Intelligence in the real world involves not only learning how to do things effectively but also more importantly the ability to deal with novelty and growing our capacity to adapt, select…

Prospective Primary School Teachers' Proficiencies in Solving Real-World Problems: Approaches, Strategies and Models

ERIC Educational Resources Information Center

Aksoy, Yilmaz; Bayazit, Ibrahim; Dönmez, S. Merve Kirnap

2015-01-01

This study investigates approaches, strategies and models used by prospective primary school teachers in responding to real-world problems. The research was carried out with 82 participants. Data were collected through written-exam and semi-structured interviews; and they were analysed using content and discourse analysis methods. Most of the…

Game theory and extremal optimization for community detection in complex dynamic networks.

PubMed

Lung, Rodica Ioana; Chira, Camelia; Andreica, Anca

2014-01-01

The detection of evolving communities in dynamic complex networks is a challenging problem that recently received attention from the research community. Dynamics clearly add another complexity dimension to the difficult task of community detection. Methods should be able to detect changes in the network structure and produce a set of community structures corresponding to different timestamps and reflecting the evolution in time of network data. We propose a novel approach based on game theory elements and extremal optimization to address dynamic communities detection. Thus, the problem is formulated as a mathematical game in which nodes take the role of players that seek to choose a community that maximizes their profit viewed as a fitness function. Numerical results obtained for both synthetic and real-world networks illustrate the competitive performance of this game theoretical approach.

Interacting complex systems: Theory and application to real-world situations

NASA Astrophysics Data System (ADS)

Piccinini, Nicola

The interest in complex systems has increased exponentially during the past years because it was found helpful in addressing many of today's challenges. The study of the brain, biology, earthquakes, markets and social sciences are only a few examples of the fields that have benefited from the investigation of complex systems. Internet, the increased mobility of people and the raising energy demand are among the factors that brought in contact complex systems that were isolated till a few years ago. A theory for the interaction between complex systems is becoming more and more urgent to help mankind in this transition. The present work builds upon the most recent results in this field by solving a theoretical problem that prevented previous work to be applied to important complex systems, like the brain. It also shows preliminary laboratory results of perturbation of in vitro neural networks that were done to test the theory. Finally, it gives a preview of the studies that are being done to create a theory that is even closer to the interaction between real complex systems.

Fault Identification Based on Nlpca in Complex Electrical Engineering

NASA Astrophysics Data System (ADS)

Zhang, Yagang; Wang, Zengping; Zhang, Jinfang

2012-07-01

The fault is inevitable in any complex systems engineering. Electric power system is essentially a typically nonlinear system. It is also one of the most complex artificial systems in this world. In our researches, based on the real-time measurements of phasor measurement unit, under the influence of white Gaussian noise (suppose the standard deviation is 0.01, and the mean error is 0), we used mainly nonlinear principal component analysis theory (NLPCA) to resolve fault identification problem in complex electrical engineering. The simulation results show that the fault in complex electrical engineering is usually corresponding to the variable with the maximum absolute value coefficient in the first principal component. These researches will have significant theoretical value and engineering practical significance.

Canonical Duality Theory and Algorithms for Solving Some Challenging Problems in Global Optimization and Decision Science

DTIC Science & Technology

2015-09-24

algorithms for solving real- world problems. Within the past five years, 2 books, 5 journal special issues, and about 60 papers have been published...Four international conferences have been organized, including the 3rd World Congress of Global Optimization. A unified methodology and algorithm have...been developed with real- world applications. This grant has been used to support and co-support three post-doctors, three PhD students, one part

Effective Capital Provision Within Government. Methodologies for Right-Sizing Base Infrastructure

DTIC Science & Technology

2005-01-01

unknown distributions, since they more accurately represent the complexity of real -world problems. Forecasting uncertain future demand flows is critical to...ordering system with no time lags and no additional costs for instantaneous delivery, shortage and holding costs would be eliminated, because the...order a fixed quantity, Q. 4.1.4 Analyzed Time Step Time is an important dimension in inventory models, since the way the system changes over time affects

The James Webb Space Telescope RealWorld-InWorld Design Challenge: Involving Professionals in a Virtual Classroom

NASA Astrophysics Data System (ADS)

Masetti, Margaret; Bowers, S.

2011-01-01

Students around the country are becoming experts on the James Webb Space Telescope by designing solutions to two of the design challenges presented by this complex mission. RealWorld-InWorld has two parts; the first (the Real World portion) has high-school students working face to face in their classroom as engineers and scientists. The InWorld phase starts December 15, 2010 as interested teachers and their teams of high school students register to move their work into a 3D multi-user virtual world environment. At the start of this phase, college students from all over the country choose a registered team to lead InWorld. Each InWorld team is also assigned an engineer or scientist mentor. In this virtual world setting, each team refines their design solutions and creates a 3D model of the Webb telescope. InWorld teams will use 21st century tools to collaborate and build in the virtual world environment. Each team will learn, not only from their own team members, but will have the opportunity to interact with James Webb Space Telescope researchers through the virtual world setting, which allows for synchronous interactions. Halfway through the challenge, design solutions will be critiqued and a mystery problem will be introduced for each team. The top five teams will be invited to present their work during a synchronous Education Forum April 14, 2011. The top team will earn scholarships and technology. This is an excellent opportunity for professionals in both astronomy and associated engineering disciplines to become involved with a unique educational program. Besides the chance to mentor a group of interested students, there are many opportunities to interact with the students as a guest, via chats and presentations.

Collaborative learning in networks.

PubMed

Mason, Winter; Watts, Duncan J

2012-01-17

Complex problems in science, business, and engineering typically require some tradeoff between exploitation of known solutions and exploration for novel ones, where, in many cases, information about known solutions can also disseminate among individual problem solvers through formal or informal networks. Prior research on complex problem solving by collectives has found the counterintuitive result that inefficient networks, meaning networks that disseminate information relatively slowly, can perform better than efficient networks for problems that require extended exploration. In this paper, we report on a series of 256 Web-based experiments in which groups of 16 individuals collectively solved a complex problem and shared information through different communication networks. As expected, we found that collective exploration improved average success over independent exploration because good solutions could diffuse through the network. In contrast to prior work, however, we found that efficient networks outperformed inefficient networks, even in a problem space with qualitative properties thought to favor inefficient networks. We explain this result in terms of individual-level explore-exploit decisions, which we find were influenced by the network structure as well as by strategic considerations and the relative payoff between maxima. We conclude by discussing implications for real-world problem solving and possible extensions.

Collaborative learning in networks

PubMed Central

Mason, Winter; Watts, Duncan J.

2012-01-01

Complex problems in science, business, and engineering typically require some tradeoff between exploitation of known solutions and exploration for novel ones, where, in many cases, information about known solutions can also disseminate among individual problem solvers through formal or informal networks. Prior research on complex problem solving by collectives has found the counterintuitive result that inefficient networks, meaning networks that disseminate information relatively slowly, can perform better than efficient networks for problems that require extended exploration. In this paper, we report on a series of 256 Web-based experiments in which groups of 16 individuals collectively solved a complex problem and shared information through different communication networks. As expected, we found that collective exploration improved average success over independent exploration because good solutions could diffuse through the network. In contrast to prior work, however, we found that efficient networks outperformed inefficient networks, even in a problem space with qualitative properties thought to favor inefficient networks. We explain this result in terms of individual-level explore-exploit decisions, which we find were influenced by the network structure as well as by strategic considerations and the relative payoff between maxima. We conclude by discussing implications for real-world problem solving and possible extensions. PMID:22184216

Linking Project-Based Interdisciplinary Learning and Recommended Professional Competencies with Business Management, Digital Media, Distance Learning, Engineering Technology, and English

ERIC Educational Resources Information Center

Bender, Melinda; Fulwider, Miles; Stemkoski, Michael J.

2008-01-01

This paper encourages the investigation of real world problems by students and faculty and links recommended student competencies with project based learning. In addition to the traditional course objectives, project-based learning (PBL) uses real world problems for classroom instruction and fieldwork to connect students, instructors, and industry…

Use of Common-Sense Knowledge, Language and Reality in Mathematical Word Problem Solving

ERIC Educational Resources Information Center

Sepeng, Percy

2014-01-01

The study reported in this article sought to explore and observe how grade 9 learners solve real-wor(l)d problems (a) without real context and (b) without real meaning. Learners' abilities to make sense of the decontextualised word problems set in the real world were investigated with regard to learners' use of common sense in relation to problem…

Hybrid Metaheuristics for Solving a Fuzzy Single Batch-Processing Machine Scheduling Problem

PubMed Central

Molla-Alizadeh-Zavardehi, S.; Tavakkoli-Moghaddam, R.; Lotfi, F. Hosseinzadeh

2014-01-01

This paper deals with a problem of minimizing total weighted tardiness of jobs in a real-world single batch-processing machine (SBPM) scheduling in the presence of fuzzy due date. In this paper, first a fuzzy mixed integer linear programming model is developed. Then, due to the complexity of the problem, which is NP-hard, we design two hybrid metaheuristics called GA-VNS and VNS-SA applying the advantages of genetic algorithm (GA), variable neighborhood search (VNS), and simulated annealing (SA) frameworks. Besides, we propose three fuzzy earliest due date heuristics to solve the given problem. Through computational experiments with several random test problems, a robust calibration is applied on the parameters. Finally, computational results on different-scale test problems are presented to compare the proposed algorithms. PMID:24883359

Real-World Executive Functions in Adults with Autism Spectrum Disorder: Profiles of Impairment and Associations with Adaptive Functioning and Co-Morbid Anxiety and Depression

ERIC Educational Resources Information Center

Wallace, Gregory L.; Kenworthy, Lauren; Pugliese, Cara E.; Popal, Haroon S.; White, Emily I.; Brodsky, Emily; Martin, Alex

2016-01-01

Although executive functioning (EF) difficulties are well documented among children and adolescents with autism spectrum disorder (ASD), little is known about real-world measures of EF among adults with ASD. Therefore, this study examined parent-reported real-world EF problems among 35 adults with ASD without intellectual disability and their…

Fixing Ganache: Another Real-Life Use for Algebra

ERIC Educational Resources Information Center

Kalman, Adam M.

2011-01-01

This article presents a real-world application of proportional reasoning and equation solving. The author describes how students adjust ingredient amounts in a recipe for chocolate ganache. Using this real-world scenario provided students an opportunity to solve a difficult and nonstandard algebra problem, a lot of practice with fractions, a…

A Real-Life Case Study of Audit Interactions--Resolving Messy, Complex Problems

ERIC Educational Resources Information Center

Beattie, Vivien; Fearnley, Stella; Hines, Tony

2012-01-01

Real-life accounting and auditing problems are often complex and messy, requiring the synthesis of technical knowledge in addition to the application of generic skills. To help students acquire the necessary skills to deal with these problems effectively, educators have called for the use of case-based methods. Cases based on real situations (such…

Concept Systems and Ontologies: Recommendations for Basic Terminology

NASA Astrophysics Data System (ADS)

Klein, Gunnar O.; Smith, Barry

This essay concerns the problems surrounding the use of the term ``concept'' in current ontology and terminology research. It is based on the constructive dialogue between realist ontology on the one hand and the world of formal standardization of health informatics on the other, but its conclusions are not restricted to the domain of medicine. The term ``concept'' is one of the most misused even in literature and technical standards which attempt to bring clarity. In this paper we propose to use the term ``concept'' in the context of producing defined professional terminologies with one specific and consistent meaning which we propose for adoption as the agreed meaning of the term in future terminological research, and specifically in the development of formal terminologies to be used in computer systems. We also discuss and propose new definitions of a set of cognate terms. We describe the relations governing the realm of concepts, and compare these to the richer and more complex set of relations obtaining between entities in the real world. On this basis we also summarize an associated terminology for ontologies as representations of the real world and a partial mapping between the world of concepts and the world of reality.

Predicting the evolution of complex networks via similarity dynamics

NASA Astrophysics Data System (ADS)

Wu, Tao; Chen, Leiting; Zhong, Linfeng; Xian, Xingping

2017-01-01

Almost all real-world networks are subject to constant evolution, and plenty of them have been investigated empirically to uncover the underlying evolution mechanism. However, the evolution prediction of dynamic networks still remains a challenging problem. The crux of this matter is to estimate the future network links of dynamic networks. This paper studies the evolution prediction of dynamic networks with link prediction paradigm. To estimate the likelihood of the existence of links more accurate, an effective and robust similarity index is presented by exploiting network structure adaptively. Moreover, most of the existing link prediction methods do not make a clear distinction between future links and missing links. In order to predict the future links, the networks are regarded as dynamic systems in this paper, and a similarity updating method, spatial-temporal position drift model, is developed to simulate the evolutionary dynamics of node similarity. Then the updated similarities are used as input information for the future links' likelihood estimation. Extensive experiments on real-world networks suggest that the proposed similarity index performs better than baseline methods and the position drift model performs well for evolution prediction in real-world evolving networks.

Popularity and Novelty Dynamics in Evolving Networks.

PubMed

Abbas, Khushnood; Shang, Mingsheng; Abbasi, Alireza; Luo, Xin; Xu, Jian Jun; Zhang, Yu-Xia

2018-04-20

Network science plays a big role in the representation of real-world phenomena such as user-item bipartite networks presented in e-commerce or social media platforms. It provides researchers with tools and techniques to solve complex real-world problems. Identifying and predicting future popularity and importance of items in e-commerce or social media platform is a challenging task. Some items gain popularity repeatedly over time while some become popular and novel only once. This work aims to identify the key-factors: popularity and novelty. To do so, we consider two types of novelty predictions: items appearing in the popular ranking list for the first time; and items which were not in the popular list in the past time window, but might have been popular before the recent past time window. In order to identify the popular items, a careful consideration of macro-level analysis is needed. In this work we propose a model, which exploits item level information over a span of time to rank the importance of the item. We considered ageing or decay effect along with the recent link-gain of the items. We test our proposed model on four various real-world datasets using four information retrieval based metrics.

The Motivation of Problem-Based Teaching and Learning in Translation

ERIC Educational Resources Information Center

Yingxue, Zheng

2013-01-01

Problem-Based Learning (PBL) has been one of the popular pedagogical strategies these years. PBL is about students connecting disciplinary knowledge to real-world problems--the motivation to solve a problem. To recognize general elements and typological differences of language in translation is the motivation to solve real problems such as…

A Framework for Dynamic Constraint Reasoning Using Procedural Constraints

NASA Technical Reports Server (NTRS)

Jonsson, Ari K.; Frank, Jeremy D.

1999-01-01

Many complex real-world decision and control problems contain an underlying constraint reasoning problem. This is particularly evident in a recently developed approach to planning, where almost all planning decisions are represented by constrained variables. This translates a significant part of the planning problem into a constraint network whose consistency determines the validity of the plan candidate. Since higher-level choices about control actions can add or remove variables and constraints, the underlying constraint network is invariably highly dynamic. Arbitrary domain-dependent constraints may be added to the constraint network and the constraint reasoning mechanism must be able to handle such constraints effectively. Additionally, real problems often require handling constraints over continuous variables. These requirements present a number of significant challenges for a constraint reasoning mechanism. In this paper, we introduce a general framework for handling dynamic constraint networks with real-valued variables, by using procedures to represent and effectively reason about general constraints. The framework is based on a sound theoretical foundation, and can be proven to be sound and complete under well-defined conditions. Furthermore, the framework provides hybrid reasoning capabilities, as alternative solution methods like mathematical programming can be incorporated into the framework, in the form of procedures.

Hypertext-based design of a user interface for scheduling

NASA Technical Reports Server (NTRS)

Woerner, Irene W.; Biefeld, Eric

1993-01-01

Operations Mission Planner (OMP) is an ongoing research project at JPL that utilizes AI techniques to create an intelligent, automated planning and scheduling system. The information space reflects the complexity and diversity of tasks necessary in most real-world scheduling problems. Thus the problem of the user interface is to present as much information as possible at a given moment and allow the user to quickly navigate through the various types of displays. This paper describes a design which applies the hypertext model to solve these user interface problems. The general paradigm is to provide maps and search queries to allow the user to quickly find an interesting conflict or problem, and then allow the user to navigate through the displays in a hypertext fashion.

Strategic planning for disaster recovery with stochastic last mile distribution

DOE Office of Scientific and Technical Information (OSTI.GOV)

Bent, Russell Whitford; Van Hentenryck, Pascal; Coffrin, Carleton

2010-01-01

This paper considers the single commodity allocation problem (SCAP) for disaster recovery, a fundamental problem faced by all populated areas. SCAPs are complex stochastic optimization problems that combine resource allocation, warehouse routing, and parallel fleet routing. Moreover, these problems must be solved under tight runtime constraints to be practical in real-world disaster situations. This paper formalizes the specification of SCAPs and introduces a novel multi-stage hybrid-optimization algorithm that utilizes the strengths of mixed integer programming, constraint programming, and large neighborhood search. The algorithm was validated on hurricane disaster scenarios generated by Los Alamos National Laboratory using state-of-the-art disaster simulation toolsmore » and is deployed to aid federal organizations in the US.« less

A new decision sciences for complex systems.

PubMed

Lempert, Robert J

2002-05-14

Models of complex systems can capture much useful information but can be difficult to apply to real-world decision-making because the type of information they contain is often inconsistent with that required for traditional decision analysis. New approaches, which use inductive reasoning over large ensembles of computational experiments, now make possible systematic comparison of alternative policy options using models of complex systems. This article describes Computer-Assisted Reasoning, an approach to decision-making under conditions of deep uncertainty that is ideally suited to applying complex systems to policy analysis. The article demonstrates the approach on the policy problem of global climate change, with a particular focus on the role of technology policies in a robust, adaptive strategy for greenhouse gas abatement.

Approximation of Nash equilibria and the network community structure detection problem

PubMed Central

2017-01-01

Game theory based methods designed to solve the problem of community structure detection in complex networks have emerged in recent years as an alternative to classical and optimization based approaches. The Mixed Nash Extremal Optimization uses a generative relation for the characterization of Nash equilibria to identify the community structure of a network by converting the problem into a non-cooperative game. This paper proposes a method to enhance this algorithm by reducing the number of payoff function evaluations. Numerical experiments performed on synthetic and real-world networks show that this approach is efficient, with results better or just as good as other state-of-the-art methods. PMID:28467496

Research in the Real World: Improving Adult Learners Web Search and Evaluation Skills through Motivational Design and Problem-Based Learning

ERIC Educational Resources Information Center

Roberts, Lindsay

2017-01-01

How can we better engage adult learners during information literacy sessions? How do we increase students' perception of the relevance and importance of information literacy skills for academic work and life in the real world? To explore these questions, the ARCS Model of Motivational Design and Problem-Based Learning were used to develop…

Ranking in evolving complex networks

NASA Astrophysics Data System (ADS)

Liao, Hao; Mariani, Manuel Sebastian; Medo, Matúš; Zhang, Yi-Cheng; Zhou, Ming-Yang

2017-05-01

Complex networks have emerged as a simple yet powerful framework to represent and analyze a wide range of complex systems. The problem of ranking the nodes and the edges in complex networks is critical for a broad range of real-world problems because it affects how we access online information and products, how success and talent are evaluated in human activities, and how scarce resources are allocated by companies and policymakers, among others. This calls for a deep understanding of how existing ranking algorithms perform, and which are their possible biases that may impair their effectiveness. Many popular ranking algorithms (such as Google's PageRank) are static in nature and, as a consequence, they exhibit important shortcomings when applied to real networks that rapidly evolve in time. At the same time, recent advances in the understanding and modeling of evolving networks have enabled the development of a wide and diverse range of ranking algorithms that take the temporal dimension into account. The aim of this review is to survey the existing ranking algorithms, both static and time-aware, and their applications to evolving networks. We emphasize both the impact of network evolution on well-established static algorithms and the benefits from including the temporal dimension for tasks such as prediction of network traffic, prediction of future links, and identification of significant nodes.

Characterization of topological structure on complex networks.

PubMed

Nakamura, Ikuo

2003-10-01

Characterizing the topological structure of complex networks is a significant problem especially from the viewpoint of data mining on the World Wide Web. "Page rank" used in the commercial search engine Google is such a measure of authority to rank all the nodes matching a given query. We have investigated the page-rank distribution of the real Web and a growing network model, both of which have directed links and exhibit a power law distributions of in-degree (the number of incoming links to the node) and out-degree (the number of outgoing links from the node), respectively. We find a concentration of page rank on a small number of nodes and low page rank on high degree regimes in the real Web, which can be explained by topological properties of the network, e.g., network motifs, and connectivities of nearest neighbors.

Context sensitivity and ambiguity in component-based systems design

DOE Office of Scientific and Technical Information (OSTI.GOV)

Bespalko, S.J.; Sindt, A.

1997-10-01

Designers of components-based, real-time systems need to guarantee to correctness of soft-ware and its output. Complexity of a system, and thus the propensity for error, is best characterized by the number of states a component can encounter. In many cases, large numbers of states arise where the processing is highly dependent on context. In these cases, states are often missed, leading to errors. The following are proposals for compactly specifying system states which allow the factoring of complex components into a control module and a semantic processing module. Further, the need for methods that allow for the explicit representation ofmore » ambiguity and uncertainty in the design of components is discussed. Presented herein are examples of real-world problems which are highly context-sensitive or are inherently ambiguous.« less

A tool for modeling concurrent real-time computation

NASA Technical Reports Server (NTRS)

Sharma, D. D.; Huang, Shie-Rei; Bhatt, Rahul; Sridharan, N. S.

1990-01-01

Real-time computation is a significant area of research in general, and in AI in particular. The complexity of practical real-time problems demands use of knowledge-based problem solving techniques while satisfying real-time performance constraints. Since the demands of a complex real-time problem cannot be predicted (owing to the dynamic nature of the environment) powerful dynamic resource control techniques are needed to monitor and control the performance. A real-time computation model for a real-time tool, an implementation of the QP-Net simulator on a Symbolics machine, and an implementation on a Butterfly multiprocessor machine are briefly described.

Sequential Test Strategies for Multiple Fault Isolation

NASA Technical Reports Server (NTRS)

Shakeri, M.; Pattipati, Krishna R.; Raghavan, V.; Patterson-Hine, Ann; Kell, T.

1997-01-01

In this paper, we consider the problem of constructing near optimal test sequencing algorithms for diagnosing multiple faults in redundant (fault-tolerant) systems. The computational complexity of solving the optimal multiple-fault isolation problem is super-exponential, that is, it is much more difficult than the single-fault isolation problem, which, by itself, is NP-hard. By employing concepts from information theory and Lagrangian relaxation, we present several static and dynamic (on-line or interactive) test sequencing algorithms for the multiple fault isolation problem that provide a trade-off between the degree of suboptimality and computational complexity. Furthermore, we present novel diagnostic strategies that generate a static diagnostic directed graph (digraph), instead of a static diagnostic tree, for multiple fault diagnosis. Using this approach, the storage complexity of the overall diagnostic strategy reduces substantially. Computational results based on real-world systems indicate that the size of a static multiple fault strategy is strictly related to the structure of the system, and that the use of an on-line multiple fault strategy can diagnose faults in systems with as many as 10,000 failure sources.

Virtual School, Real Experience: Simulations Replicate the World of Practice for Aspiring Principals

ERIC Educational Resources Information Center

Mann, Dale; Shakeshaft, Charol

2013-01-01

A web-enabled computer simulation program presents real-world opportunities, problems, and challenges for aspiring principals. The simulation challenges areas that are not always covered in lectures, textbooks, or workshops. For example, using the simulation requires dealing--on-screen and in real time--with demanding parents, observing…

Culture & Cognition Laboratory

DTIC Science & Technology

2011-05-01

life: Real world social-interaction cooperative tasks are inherently unequal in difficulty. Re-scoring performance on unequal tasks in order to enable...real- world situations to which this model is intended to apply, it is possible for calls for help to not be heard, or for a potential help-provider to...not have clear, well-defined objectives. Since many complex real- worlds tasks are not well-defined, defining a realistic objective can be considered a

Alice in the Real World

ERIC Educational Resources Information Center

Parker, Tom

2012-01-01

As a fifth-grade mathematics teacher, the author tries to create authentic problem-solving activities that connect to the world in which his students live. He discovered a natural connection to his students' real world at a computer camp. A friend introduced him to Alice, a computer application developed at Carnegie Mellon, under the leadership of…

Evaluation of Process Science Skills: From the Real World to the Ideal World.

ERIC Educational Resources Information Center

Lipowich, Shelley A.

State legislatures and others are recommending and, in some cases, mandating reforms in education including evaluating students' ability to meet stated objectives. This "ideal" situation poses a major problem concerning instruments needed to assess process skills. In the real world, educators do not yet have nationally recognized, valid,…

External Prior Guided Internal Prior Learning for Real-World Noisy Image Denoising

NASA Astrophysics Data System (ADS)

Xu, Jun; Zhang, Lei; Zhang, David

2018-06-01

Most of existing image denoising methods learn image priors from either external data or the noisy image itself to remove noise. However, priors learned from external data may not be adaptive to the image to be denoised, while priors learned from the given noisy image may not be accurate due to the interference of corrupted noise. Meanwhile, the noise in real-world noisy images is very complex, which is hard to be described by simple distributions such as Gaussian distribution, making real noisy image denoising a very challenging problem. We propose to exploit the information in both external data and the given noisy image, and develop an external prior guided internal prior learning method for real noisy image denoising. We first learn external priors from an independent set of clean natural images. With the aid of learned external priors, we then learn internal priors from the given noisy image to refine the prior model. The external and internal priors are formulated as a set of orthogonal dictionaries to efficiently reconstruct the desired image. Extensive experiments are performed on several real noisy image datasets. The proposed method demonstrates highly competitive denoising performance, outperforming state-of-the-art denoising methods including those designed for real noisy images.

On Teaching Energy: Preparing Students Better for their Role as Citizens

NASA Astrophysics Data System (ADS)

Myers, J. D.; Lyford, M. E.; Buss, A.

2009-12-01

Supplying energy to an expanding population with a rising standard of living and maintaining human and natural systems is an increasingly difficult task. Thus, energy is often listed as one of the grand challenges facing humankind. Energy‘s grand challenges are many, complex, multifaceted and of variable scale. It is not surprising then that their solutions must be multi-dimensional as well. Historically, energy solutions have focused on energy science (a multidisciplinary topic spanning biology, chemistry, Earth science, physics, and math), technology or economics. In the real world, focusing solely on these aspects of energy has rarely produced energy projects that are just and fair. Sustainable, equitable and effective energy projects are only created when additional perspectives are considered, e.g. environment, culture, social institutions, politics, etc. The natures of these other perspectives are determined largely by the social context of any particular energy issue. For example, petroleum production has had vastly different impacts in Norway than it does in Nigeria. Thus, solutions to energy issues are, in fact, multidimensional functions. Given this complexity, preparing students to deal with the energy issues they will face in the future requires an instructional approach that integrates a multidisciplinary science approach with technology and social context. Yet this alone will not ensure that students leave the classroom with the skills necessary to equitably, effectively and logically deal with energy issues. Rather, teaching energy also requires sound pedagogy. Effective pedagogy ensures student success in the classroom and facilitates transfer of classroom knowledge to real world situations. It includes, but also goes beyond, employing classroom strategies that promote deep and lasting learning. In this arena, it fosters the development of a skill set that enables students to transfer classroom knowledge to real world issues. It prepares students to handle the uncertainty and ambiguity of the real world while promoting critical thinking and problem solving. Fundamental literacies, a type of QR, prepare students to handle data, perform simple calculations and evaluate critically quantitative claims. They are crucial to working in the real world as well as the scientific realm. Understanding and using scientific content also requires mastering a series of technical literacies. Although they may vary between scientific disciplines, some technical literacies are shared by a number of sciences. Although most science courses assume students can transfer what they have learned to societal applications without further assistance, this is rare, even for the best students. Rather, this classroom-to-real world transfer skill set, i.e. citizenship literacies, must be explicitly taught and practiced. Mastering critical thinking, understanding social context and practicing informed engagement provides students the skills to use their scientific understanding to address energy problems in meaningful and effective ways while enabling them to communicate effectively their ideas to others and work co-operatively with stakeholders with different views.

End-User Applications of Real-Time Earthquake Information in Europe

NASA Astrophysics Data System (ADS)

Cua, G. B.; Gasparini, P.; Giardini, D.; Zschau, J.; Filangieri, A. R.; Reakt Wp7 Team

2011-12-01

The primary objective of European FP7 project REAKT (Strategies and Tools for Real-Time Earthquake Risk Reduction) is to improve the efficiency of real-time earthquake risk mitigation methods and their capability of protecting structures, infrastructures, and populations. REAKT aims to address the issues of real-time earthquake hazard and response from end-to-end, with efforts directed along the full spectrum of methodology development in earthquake forecasting, earthquake early warning, and real-time vulnerability systems, through optimal decision-making, and engagement and cooperation of scientists and end users for the establishment of best practices for use of real-time information. Twelve strategic test cases/end users throughout Europe have been selected. This diverse group of applications/end users includes civil protection authorities, railway systems, hospitals, schools, industrial complexes, nuclear plants, lifeline systems, national seismic networks, and critical structures. The scale of target applications covers a wide range, from two school complexes in Naples, to individual critical structures, such as the Rion Antirion bridge in Patras, and the Fatih Sultan Mehmet bridge in Istanbul, to large complexes, such as the SINES industrial complex in Portugal and the Thessaloniki port area, to distributed lifeline and transportation networks and nuclear plants. Some end-users are interested in in-depth feasibility studies for use of real-time information and development of rapid response plans, while others intend to install real-time instrumentation and develop customized automated control systems. From the onset, REAKT scientists and end-users will work together on concept development and initial implementation efforts using the data products and decision-making methodologies developed with the goal of improving end-user risk mitigation. The aim of this scientific/end-user partnership is to ensure that scientific efforts are applicable to operational, real-world problems.

Inquiry and Problem Solving.

ERIC Educational Resources Information Center

Thorson, Annette, Ed.

1999-01-01

This issue of ENC Focus focuses on the topic of inquiry and problem solving. Featured articles include: (1) "Inquiry in the Everyday World of Schools" (Ronald D. Anderson); (2) "In the Cascade Reservoir Restoration Project Students Tackle Real-World Problems" (Clint Kennedy with Advanced Biology Students from Cascade High…

Exploring the Role of Intrinsic Nodal Activation on the Spread of Influence in Complex Networks

DOE Office of Scientific and Technical Information (OSTI.GOV)

Visweswara Sathanur, Arun; Halappanavar, Mahantesh; Shi, Yi

In many complex networked systems such as online social networks, at any given time, activity originates at certain nodes and subsequently spreads on the network through influence. To model the spread of influence in such a scenario, we consider the problem of identification of influential entities in a complex network when nodal activation can happen through two different mechanisms. The first mode of activation is due mechanisms intrinsic to the node. The second mechanism is through the influence of connected neighbors. In this work, we present a simple probabilistic formulation that models such self-evolving systems where information diffusion occurs primarilymore » because of the intrinsic activity of users and the spread of activity occurs due to influence. We provide an algorithm to mine for the influential seeds in such a scenario by modifying the well-known influence maximization framework with the independent cascade diffusion model. We provide small motivating examples to provide an intuitive understanding of the effect of including the intrinsic activation mechanism. We sketch a proof of the submodularity of the influence function under the new formulation and demonstrate the same with larger graphs. We then show by means of additional experiments on a real-world twitter dataset how the formulation can be applied to real-world social media datasets. Finally we derive a computationally efficient centrality metric that takes into account, both the mechanisms of activation and provides for an accurate as well as computationally efficient alternative approach to the problem of identifying influencers under intrinsic activation.« less

A community detection algorithm using network topologies and rule-based hierarchical arc-merging strategies

PubMed Central

2017-01-01

The authors use four criteria to examine a novel community detection algorithm: (a) effectiveness in terms of producing high values of normalized mutual information (NMI) and modularity, using well-known social networks for testing; (b) examination, meaning the ability to examine mitigating resolution limit problems using NMI values and synthetic networks; (c) correctness, meaning the ability to identify useful community structure results in terms of NMI values and Lancichinetti-Fortunato-Radicchi (LFR) benchmark networks; and (d) scalability, or the ability to produce comparable modularity values with fast execution times when working with large-scale real-world networks. In addition to describing a simple hierarchical arc-merging (HAM) algorithm that uses network topology information, we introduce rule-based arc-merging strategies for identifying community structures. Five well-studied social network datasets and eight sets of LFR benchmark networks were employed to validate the correctness of a ground-truth community, eight large-scale real-world complex networks were used to measure its efficiency, and two synthetic networks were used to determine its susceptibility to two resolution limit problems. Our experimental results indicate that the proposed HAM algorithm exhibited satisfactory performance efficiency, and that HAM-identified and ground-truth communities were comparable in terms of social and LFR benchmark networks, while mitigating resolution limit problems. PMID:29121100

Self-consistent adjoint analysis for topology optimization of electromagnetic waves

NASA Astrophysics Data System (ADS)

Deng, Yongbo; Korvink, Jan G.

2018-05-01

In topology optimization of electromagnetic waves, the Gâteaux differentiability of the conjugate operator to the complex field variable results in the complexity of the adjoint sensitivity, which evolves the original real-valued design variable to be complex during the iterative solution procedure. Therefore, the self-inconsistency of the adjoint sensitivity is presented. To enforce the self-consistency, the real part operator has been used to extract the real part of the sensitivity to keep the real-value property of the design variable. However, this enforced self-consistency can cause the problem that the derived structural topology has unreasonable dependence on the phase of the incident wave. To solve this problem, this article focuses on the self-consistent adjoint analysis of the topology optimization problems for electromagnetic waves. This self-consistent adjoint analysis is implemented by splitting the complex variables of the wave equations into the corresponding real parts and imaginary parts, sequentially substituting the split complex variables into the wave equations with deriving the coupled equations equivalent to the original wave equations, where the infinite free space is truncated by the perfectly matched layers. Then, the topology optimization problems of electromagnetic waves are transformed into the forms defined on real functional spaces instead of complex functional spaces; the adjoint analysis of the topology optimization problems is implemented on real functional spaces with removing the variational of the conjugate operator; the self-consistent adjoint sensitivity is derived, and the phase-dependence problem is avoided for the derived structural topology. Several numerical examples are implemented to demonstrate the robustness of the derived self-consistent adjoint analysis.

DOE Office of Scientific and Technical Information (OSTI.GOV)

Erfle, Stephen; Pound, John; Kalt, Joseph

An analysis of the response of American markets to supply crises in world oil markets is presented. It addresses four main issues: the efficiency of the operation of American oil markets during oil supply crises; the problems of both economic efficiency and social equity which arise during the American adaptation process; the propriety of the Federal government's past policy responses to these problems; and the relationship between perceptions of the problems caused by world oil crises and the real economic natures of these problems. Specifically, Chapter 1 presents a theoretical discussion of the effects of a world supply disruption onmore » the price level and supply availability of the world market oil to any consuming country including the US Chapter 2 provides a theoretical and empirical analysis of the efficiency of the adaptations of US oil product markets to higher world oil prices. Chapter 3 examines the responses of various groups of US oil firms to the alterations observed in world markets, while Chapter 4 presents a theoretical explanation for the price-lagging behavior exhibited by firms in the US oil industry. Chapter 5 addresses the nature of both real and imagined oil market problems in the US during periods of world oil market transition. (MCW)« less

Impact of Cognitive Abilities and Prior Knowledge on Complex Problem Solving Performance - Empirical Results and a Plea for Ecologically Valid Microworlds.

PubMed

Süß, Heinz-Martin; Kretzschmar, André

2018-01-01

The original aim of complex problem solving (CPS) research was to bring the cognitive demands of complex real-life problems into the lab in order to investigate problem solving behavior and performance under controlled conditions. Up until now, the validity of psychometric intelligence constructs has been scrutinized with regard to its importance for CPS performance. At the same time, different CPS measurement approaches competing for the title of the best way to assess CPS have been developed. In the first part of the paper, we investigate the predictability of CPS performance on the basis of the Berlin Intelligence Structure Model and Cattell's investment theory as well as an elaborated knowledge taxonomy. In the first study, 137 students managed a simulated shirt factory ( Tailorshop ; i.e., a complex real life-oriented system) twice, while in the second study, 152 students completed a forestry scenario ( FSYS ; i.e., a complex artificial world system). The results indicate that reasoning - specifically numerical reasoning (Studies 1 and 2) and figural reasoning (Study 2) - are the only relevant predictors among the intelligence constructs. We discuss the results with reference to the Brunswik symmetry principle. Path models suggest that reasoning and prior knowledge influence problem solving performance in the Tailorshop scenario mainly indirectly. In addition, different types of system-specific knowledge independently contribute to predicting CPS performance. The results of Study 2 indicate that working memory capacity, assessed as an additional predictor, has no incremental validity beyond reasoning. We conclude that (1) cognitive abilities and prior knowledge are substantial predictors of CPS performance, and (2) in contrast to former and recent interpretations, there is insufficient evidence to consider CPS a unique ability construct. In the second part of the paper, we discuss our results in light of recent CPS research, which predominantly utilizes the minimally complex systems (MCS) measurement approach. We suggest ecologically valid microworlds as an indispensable tool for future CPS research and applications.

Solving a real-world problem using an evolving heuristically driven schedule builder.

PubMed

Hart, E; Ross, P; Nelson, J

1998-01-01

This work addresses the real-life scheduling problem of a Scottish company that must produce daily schedules for the catching and transportation of large numbers of live chickens. The problem is complex and highly constrained. We show that it can be successfully solved by division into two subproblems and solving each using a separate genetic algorithm (GA). We address the problem of whether this produces locally optimal solutions and how to overcome this. We extend the traditional approach of evolving a "permutation + schedule builder" by concentrating on evolving the schedule builder itself. This results in a unique schedule builder being built for each daily scheduling problem, each individually tailored to deal with the particular features of that problem. This results in a robust, fast, and flexible system that can cope with most of the circumstances imaginable at the factory. We also compare the performance of a GA approach to several other evolutionary methods and show that population-based methods are superior to both hill-climbing and simulated annealing in the quality of solutions produced. Population-based methods also have the distinct advantage of producing multiple, equally fit solutions, which is of particular importance when considering the practical aspects of the problem.

Exploiting Bounded Signal Flow for Graph Orientation Based on Cause-Effect Pairs

NASA Astrophysics Data System (ADS)

Dorn, Britta; Hüffner, Falk; Krüger, Dominikus; Niedermeier, Rolf; Uhlmann, Johannes

We consider the following problem: Given an undirected network and a set of sender-receiver pairs, direct all edges such that the maximum number of "signal flows" defined by the pairs can be routed respecting edge directions. This problem has applications in communication networks and in understanding protein interaction based cell regulation mechanisms. Since this problem is NP-hard, research so far concentrated on polynomial-time approximation algorithms and tractable special cases. We take the viewpoint of parameterized algorithmics and examine several parameters related to the maximum signal flow over vertices or edges. We provide several fixed-parameter tractability results, and in one case a sharp complexity dichotomy between a linear-time solvable case and a slightly more general NP-hard case. We examine the value of these parameters for several real-world network instances. For many relevant cases, the NP-hard problem can be solved to optimality. In this way, parameterized analysis yields both deeper insight into the computational complexity and practical solving strategies.

Multiple Choice Knapsack Problem: example of planning choice in transportation.

PubMed

Zhong, Tao; Young, Rhonda

2010-05-01

Transportation programming, a process of selecting projects for funding given budget and other constraints, is becoming more complex as a result of new federal laws, local planning regulations, and increased public involvement. This article describes the use of an integer programming tool, Multiple Choice Knapsack Problem (MCKP), to provide optimal solutions to transportation programming problems in cases where alternative versions of projects are under consideration. In this paper, optimization methods for use in the transportation programming process are compared and then the process of building and solving the optimization problems is discussed. The concepts about the use of MCKP are presented and a real-world transportation programming example at various budget levels is provided. This article illustrates how the use of MCKP addresses the modern complexities and provides timely solutions in transportation programming practice. While the article uses transportation programming as a case study, MCKP can be useful in other fields where a similar decision among a subset of the alternatives is required. Copyright 2009 Elsevier Ltd. All rights reserved.

Dynamic vehicle routing with time windows in theory and practice.

PubMed

Yang, Zhiwei; van Osta, Jan-Paul; van Veen, Barry; van Krevelen, Rick; van Klaveren, Richard; Stam, Andries; Kok, Joost; Bäck, Thomas; Emmerich, Michael

2017-01-01

The vehicle routing problem is a classical combinatorial optimization problem. This work is about a variant of the vehicle routing problem with dynamically changing orders and time windows. In real-world applications often the demands change during operation time. New orders occur and others are canceled. In this case new schedules need to be generated on-the-fly. Online optimization algorithms for dynamical vehicle routing address this problem but so far they do not consider time windows. Moreover, to match the scenarios found in real-world problems adaptations of benchmarks are required. In this paper, a practical problem is modeled based on the procedure of daily routing of a delivery company. New orders by customers are introduced dynamically during the working day and need to be integrated into the schedule. A multiple ant colony algorithm combined with powerful local search procedures is proposed to solve the dynamic vehicle routing problem with time windows. The performance is tested on a new benchmark based on simulations of a working day. The problems are taken from Solomon's benchmarks but a certain percentage of the orders are only revealed to the algorithm during operation time. Different versions of the MACS algorithm are tested and a high performing variant is identified. Finally, the algorithm is tested in situ: In a field study, the algorithm schedules a fleet of cars for a surveillance company. We compare the performance of the algorithm to that of the procedure used by the company and we summarize insights gained from the implementation of the real-world study. The results show that the multiple ant colony algorithm can get a much better solution on the academic benchmark problem and also can be integrated in a real-world environment.

A Heuristic Algorithm for Planning Personalized Learning Paths for Context-Aware Ubiquitous Learning

ERIC Educational Resources Information Center

Hwang, Gwo-Jen; Kuo, Fan-Ray; Yin, Peng-Yeng; Chuang, Kuo-Hsien

2010-01-01

In a context-aware ubiquitous learning environment, learning systems can detect students' learning behaviors in the real-world with the help of context-aware (sensor) technology; that is, students can be guided to observe or operate real-world objects with personalized support from the digital world. In this study, an optimization problem that…

Handbook of Research on Technology Tools for Real-World Skill Development (2 Volumes)

ERIC Educational Resources Information Center

Rosen, Yigel, Ed.; Ferrara, Steve, Ed.; Mosharraf, Maryam, Ed.

2016-01-01

Education is expanding to include a stronger focus on the practical application of classroom lessons in an effort to prepare the next generation of scholars for a changing world economy centered on collaborative and problem-solving skills for the digital age. "The Handbook of Research on Technology Tools for Real-World Skill Development"…

DEB modeling for nanotoxicology, microbial ecology, and environmental engineering. Comment on: ;Physics of metabolic organization; by Marko Jusup et al.

NASA Astrophysics Data System (ADS)

Holden, Patricia A.

2017-03-01

Jusup et al. [1] appeal to mathematical physicists, and to biologists, by providing the theoretical basis for dynamic energy budget (DEB) modeling of individual organisms and populations, while emphasizing model simplicity, universality, and applicability to real world problems. Comments herein regard the disciplinary tensions proposed by the authors and suggest that-in addition to important applications in eco- and specifically nano-toxicology-there are opportunities for DEB frameworks to inform relative complexity in microbial ecological process modeling. This commentary also suggests another audience for bridging DEB theory and application-engineers solving environmental problems.

Network community-detection enhancement by proper weighting

NASA Astrophysics Data System (ADS)

Khadivi, Alireza; Ajdari Rad, Ali; Hasler, Martin

2011-04-01

In this paper, we show how proper assignment of weights to the edges of a complex network can enhance the detection of communities and how it can circumvent the resolution limit and the extreme degeneracy problems associated with modularity. Our general weighting scheme takes advantage of graph theoretic measures and it introduces two heuristics for tuning its parameters. We use this weighting as a preprocessing step for the greedy modularity optimization algorithm of Newman to improve its performance. The result of the experiments of our approach on computer-generated and real-world data networks confirm that the proposed approach not only mitigates the problems of modularity but also improves the modularity optimization.

Multi-Objective Hybrid Optimal Control for Multiple-Flyby Interplanetary Mission Design Using Chemical Propulsion

NASA Technical Reports Server (NTRS)

Englander, Jacob A.; Vavrina, Matthew A.

2015-01-01

Preliminary design of high-thrust interplanetary missions is a highly complex process. The mission designer must choose discrete parameters such as the number of flybys and the bodies at which those flybys are performed. For some missions, such as surveys of small bodies, the mission designer also contributes to target selection. In addition, real-valued decision variables, such as launch epoch, flight times, maneuver and flyby epochs, and flyby altitudes must be chosen. There are often many thousands of possible trajectories to be evaluated. The customer who commissions a trajectory design is not usually interested in a point solution, but rather the exploration of the trade space of trajectories between several different objective functions. This can be a very expensive process in terms of the number of human analyst hours required. An automated approach is therefore very desirable. This work presents such an approach by posing the impulsive mission design problem as a multiobjective hybrid optimal control problem. The method is demonstrated on several real-world problems.

Non-linear molecular pattern classification using molecular beacons with multiple targets.

PubMed

Lee, In-Hee; Lee, Seung Hwan; Park, Tai Hyun; Zhang, Byoung-Tak

2013-12-01

In vitro pattern classification has been highlighted as an important future application of DNA computing. Previous work has demonstrated the feasibility of linear classifiers using DNA-based molecular computing. However, complex tasks require non-linear classification capability. Here we design a molecular beacon that can interact with multiple targets and experimentally shows that its fluorescent signals form a complex radial-basis function, enabling it to be used as a building block for non-linear molecular classification in vitro. The proposed method was successfully applied to solving artificial and real-world classification problems: XOR and microRNA expression patterns. Copyright © 2013 Elsevier Ireland Ltd. All rights reserved.

DOE Office of Scientific and Technical Information (OSTI.GOV)

Sanfilippo, Antonio P.; Riensche, Roderick M.; Haack, Jereme N.

“Gamification”, the application of gameplay to real-world problems, enables the development of human computation systems that support decision-making through the integration of social and machine intelligence. One of gamification’s major benefits includes the creation of a problem solving environment where the influence of cognitive and cultural biases on human judgment can be curtailed through collaborative and competitive reasoning. By reducing biases on human judgment, gamification allows human computation systems to exploit human creativity relatively unhindered by human error. Operationally, gamification uses simulation to harvest human behavioral data that provide valuable insights for the solution of real-world problems.

Models, Data, and War: a Critique of the Foundation for Defense Analyses.

DTIC Science & Technology

1980-03-12

scientific formulation 6 An "objective" solution 8 Analysis of a squishy problem 9 A judgmental formulation 9 A potential for distortion 11 A subjective...inextricably tied to those judgments. Different analysts, with apparently identical knowledge of a real world problem, may develop plausible formulations ...configured is a concrete theoretical statement." 2/ The formulation of a computer model--conceiving a mathematical representation of the real world

Using Generative Representations to Evolve Robots. Chapter 1

NASA Technical Reports Server (NTRS)

Hornby, Gregory S.

2004-01-01

Recent research has demonstrated the ability of evolutionary algorithms to automatically design both the physical structure and software controller of real physical robots. One of the challenges for these automated design systems is to improve their ability to scale to the high complexities found in real-world problems. Here we claim that for automated design systems to scale in complexity they must use a representation which allows for the hierarchical creation and reuse of modules, which we call a generative representation. Not only is the ability to reuse modules necessary for functional scalability, but it is also valuable for improving efficiency in testing and construction. We then describe an evolutionary design system with a generative representation capable of hierarchical modularity and demonstrate it for the design of locomoting robots in simulation. Finally, results from our experiments show that evolution with our generative representation produces better robots than those evolved with a non-generative representation.

Exploring the complexity of inquiry learning in an open-ended problem space

NASA Astrophysics Data System (ADS)

Clarke, Jody

Data-gathering and problem identification are key components of scientific inquiry. However, few researchers have studied how students learn these skills because historically this required a time-consuming, complicated method of capturing the details of learners' data-gathering processes. Nor are classroom settings authentic contexts in which students could exhibit problem identification skills parallel to those involved in deconstructing complex real world situations. In this study of middle school students, because of my access to an innovative technology, I simulated a disease outbreak in a virtual community as a complicated, authentic problem. As students worked through the curriculum in the virtual world, their time-stamped actions were stored by the computer in event-logs. Using these records, I tracked in detail how the student scientists made sense of the complexity they faced and how they identified and investigated the problem using science-inquiry skills. To describe the degree to which students' data collection narrowed and focused on a specific disease over time, I developed a rubric and automated the coding of records in the event-logs. I measured the ongoing development of the students' "systematicity" in investigating the disease outbreak. I demonstrated that coding event-logs is an effective yet non-intrusive way of collecting and parsing detailed information about students' behaviors in real time in an authentic setting. My principal research question was "Do students who are more thoughtful about their inquiry prior to entry into the curriculum demonstrate increased systematicity in their inquiry behavior during the experience, by narrowing the focus of their data-gathering more rapidly than students who enter with lower levels of thoughtfulness about inquiry?" My sample consisted of 403 middle-school students from public schools in the US who volunteered to participate in the River City Project in spring 2008. Contrary to my hypothesis, I found that prior thoughtfulness of inquiry was not a predictor of the subsequent development of systematicity. However, all students did indeed become more systematic in their scientific behavior over time. On average, boys were generally more systematic than girls, but the rates at which systematicity increased with time was identical across the genders.

The 'Practice Entrepreneur' - An Australian case study of a systems thinking inspired health promotion initiative.

PubMed

Joyce, A; Green, C; Carey, G; Malbon, E

2017-01-23

The potential of systems science concepts to inform approaches for addressing complex public health problems, such as obesity prevention, has been attracting significant attention over the last decade. Despite its recent popularity, there are very few studies examining the application of systems science concepts, termed systems thinking, in practice and whether (if at all) it influences the implementation of health promotion in real world settings and in what ways. Healthy Together Victoria (HTV) was based on a systems thinking approach to address obesity prevention alongside other chronic health problems and was implemented across 14 local government areas. This paper examines the experience of practitioners from one of those intervention sites. In-depth interviews with eight practitioners revealed that there was a rigidity with which they had experienced previous health promotion jobs relative to the flexibility and fluidity of HTV. While the health promotion literature does not indicate that health promotion should be overly prescriptive, the experience of these practitioners suggests it is being applied as such in real world settings. Within HTV, asking people to work with 'systems thinking', without giving a prescription about what systems thinking is, enabled practitioners to be 'practice entrepreneurs' by choosing from a variety of systems thinking methods (mapping, reflection) to engage actively in their positions. This highlights the importance of understanding how key concepts, both traditional planning approaches and systems science concepts, are interpreted and then implemented in real world settings. © The Author 2017. Published by Oxford University Press. All rights reserved. For Permissions, please email: journals.permissions@oup.com.

The way to uncover community structure with core and diversity

NASA Astrophysics Data System (ADS)

Chang, Y. F.; Han, S. K.; Wang, X. D.

2018-07-01

Communities are ubiquitous in nature and society. Individuals that share common properties often self-organize to form communities. Avoiding the shortages of computation complexity, pre-given information and unstable results in different run, in this paper, we propose a simple and efficient method to deepen our understanding of the emergence and diversity of communities in complex systems. By introducing the rational random selection, our method reveals the hidden deterministic and normal diverse community states of community structure. To demonstrate this method, we test it with real-world systems. The results show that our method could not only detect community structure with high sensitivity and reliability, but also provide instructional information about the hidden deterministic community world and the real normal diverse community world by giving out the core-community, the real-community, the tide and the diversity. Thizs is of paramount importance in understanding, predicting, and controlling a variety of collective behaviors in complex systems.

A Bayesian state-space approach for damage detection and classification

NASA Astrophysics Data System (ADS)

Dzunic, Zoran; Chen, Justin G.; Mobahi, Hossein; Büyüköztürk, Oral; Fisher, John W.

2017-11-01

The problem of automatic damage detection in civil structures is complex and requires a system that can interpret collected sensor data into meaningful information. We apply our recently developed switching Bayesian model for dependency analysis to the problems of damage detection and classification. The model relies on a state-space approach that accounts for noisy measurement processes and missing data, which also infers the statistical temporal dependency between measurement locations signifying the potential flow of information within the structure. A Gibbs sampling algorithm is used to simultaneously infer the latent states, parameters of the state dynamics, the dependence graph, and any changes in behavior. By employing a fully Bayesian approach, we are able to characterize uncertainty in these variables via their posterior distribution and provide probabilistic estimates of the occurrence of damage or a specific damage scenario. We also implement a single class classification method which is more realistic for most real world situations where training data for a damaged structure is not available. We demonstrate the methodology with experimental test data from a laboratory model structure and accelerometer data from a real world structure during different environmental and excitation conditions.

Techniques for Single System Integration of Elastic Simulation Features

NASA Astrophysics Data System (ADS)

Mitchell, Nathan M.

Techniques for simulating the behavior of elastic objects have matured considerably over the last several decades, tackling diverse problems from non-linear models for incompressibility to accurate self-collisions. Alongside these contributions, advances in parallel hardware design and algorithms have made simulation more efficient and affordable than ever before. However, prior research often has had to commit to design choices that compromise certain simulation features to better optimize others, resulting in a fragmented landscape of solutions. For complex, real-world tasks, such as virtual surgery, a holistic approach is desirable, where complex behavior, performance, and ease of modeling are supported equally. This dissertation caters to this goal in the form of several interconnected threads of investigation, each of which contributes a piece of an unified solution. First, it will be demonstrated how various non-linear materials can be combined with lattice deformers to yield simulations with behavioral richness and a high potential for parallelism. This potential will be exploited to show how a hybrid solver approach based on large macroblocks can accelerate the convergence of these deformers. Further extensions of the lattice concept with non-manifold topology will allow for efficient processing of self-collisions and topology change. Finally, these concepts will be explored in the context of a case study on virtual plastic surgery, demonstrating a real-world problem space where these ideas can be combined to build an expressive authoring tool, allowing surgeons to record procedures digitally for future reference or education.

The real-world navigator

NASA Technical Reports Server (NTRS)

Balabanovic, Marko; Becker, Craig; Morse, Sarah K.; Nourbakhsh, Illah R.

1994-01-01

The success of every mobile robot application hinges on the ability to navigate robustly in the real world. The problem of robust navigation is separable from the challenges faced by any particular robot application. We offer the Real-World Navigator as a solution architecture that includes a path planner, a map-based localizer, and a motion control loop that combines reactive avoidance modules with deliberate goal-based motion. Our architecture achieves a high degree of reliability by maintaining and reasoning about an explicit description of positional uncertainty. We provide two implementations of real-world robot systems that incorporate the Real-World Navigator. The Vagabond Project culminated in a robot that successfully navigated a portion of the Stanford University campus. The Scimmer project developed successful entries for the AIAA 1993 Robotics Competition, placing first in one of the two contests entered.

Tuning Out the World with Noise-Canceling Headphones

ERIC Educational Resources Information Center

McCulloch, Allison W.; Whitehead, Ashley; Lovett, Jennifer N.; Whitley, Blake

2017-01-01

Context is what makes mathematical modeling tasks different from more traditional textbook word problems. Math problems are sometimes stripped of context as they are worked on. For modeling problems, however, context is important for making sense of the mathematics. The task should be brought back to its real-world context as often as possible. In…

The coral reefs optimization algorithm: a novel metaheuristic for efficiently solving optimization problems.

PubMed

Salcedo-Sanz, S; Del Ser, J; Landa-Torres, I; Gil-López, S; Portilla-Figueras, J A

2014-01-01

This paper presents a novel bioinspired algorithm to tackle complex optimization problems: the coral reefs optimization (CRO) algorithm. The CRO algorithm artificially simulates a coral reef, where different corals (namely, solutions to the optimization problem considered) grow and reproduce in coral colonies, fighting by choking out other corals for space in the reef. This fight for space, along with the specific characteristics of the corals' reproduction, produces a robust metaheuristic algorithm shown to be powerful for solving hard optimization problems. In this research the CRO algorithm is tested in several continuous and discrete benchmark problems, as well as in practical application scenarios (i.e., optimum mobile network deployment and off-shore wind farm design). The obtained results confirm the excellent performance of the proposed algorithm and open line of research for further application of the algorithm to real-world problems.

The Coral Reefs Optimization Algorithm: A Novel Metaheuristic for Efficiently Solving Optimization Problems

PubMed Central

Salcedo-Sanz, S.; Del Ser, J.; Landa-Torres, I.; Gil-López, S.; Portilla-Figueras, J. A.

2014-01-01

This paper presents a novel bioinspired algorithm to tackle complex optimization problems: the coral reefs optimization (CRO) algorithm. The CRO algorithm artificially simulates a coral reef, where different corals (namely, solutions to the optimization problem considered) grow and reproduce in coral colonies, fighting by choking out other corals for space in the reef. This fight for space, along with the specific characteristics of the corals' reproduction, produces a robust metaheuristic algorithm shown to be powerful for solving hard optimization problems. In this research the CRO algorithm is tested in several continuous and discrete benchmark problems, as well as in practical application scenarios (i.e., optimum mobile network deployment and off-shore wind farm design). The obtained results confirm the excellent performance of the proposed algorithm and open line of research for further application of the algorithm to real-world problems. PMID:25147860

Data Literacy: Real-World Learning through Problem-Solving with Data Sets

ERIC Educational Resources Information Center

Erwin, Robin W., Jr.

2015-01-01

The achievement of deep learning by secondary students requires teaching approaches that draw students into task commitment, integrated curricula, and analytical thinking. By using real-world data sets in project based instructional units, teachers can guide students in analyzing, interpreting, and reporting quantitative data. Working with…

Using mathematics to solve real world problems: the role of enablers

NASA Astrophysics Data System (ADS)

Geiger, Vincent; Stillman, Gloria; Brown, Jill; Galbriath, Peter; Niss, Mogens

2018-03-01

The purpose of this article is to report on a newly funded research project in which we will investigate how secondary students apply mathematical modelling to effectively address real world situations. Through this study, we will identify factors, mathematical, cognitive, social and environmental that "enable" year 10/11 students to successfully begin the modelling process, that is, formulate and mathematise a real world problem. The 3-year study will take a design research approach in working intensively with six schools across two educational jurisdictions. It is anticipated that this research will generate new theoretical and practical insights into the role of "enablers" within the process of mathematisation, leading to the development of principles for the design and implementation for tasks that support students' development as modellers.

A Multitasking General Executive for Compound Continuous Tasks

ERIC Educational Resources Information Center

Salvucci, Dario D.

2005-01-01

As cognitive architectures move to account for increasingly complex real-world tasks, one of the most pressing challenges involves understanding and modeling human multitasking. Although a number of existing models now perform multitasking in real-world scenarios, these models typically employ customized executives that schedule tasks for the…

Stress Training and Simulator Complexity: Why Sometimes More Is Less

ERIC Educational Resources Information Center

Tichon, Jennifer G.; Wallis, Guy M.

2010-01-01

Through repeated practice under conditions similar to those in real-world settings, simulator training prepares an individual to maintain effective performance under stressful work conditions. Interfaces offering high fidelity and immersion can more closely reproduce real-world experiences and are generally believed to result in better learning…

New optical museum at Saint-Petersburg for education and training

NASA Astrophysics Data System (ADS)

Vasil'ev, V. N.; Stafeef, S. K.; Tomilin, M. G.

2009-06-01

Nowadays the educational problem of teaching optics and photonics is to attract the young generation to the wonderful and magic world of light, optical science, technology and systems. The main issue is to explain that in the course of last several hundred years optics has been representing the most clear world view for humanity. In fact, the optics itself is a multidisciplinary complex of independent scientific directions, and, moreover, it has always been a generator of new fields of knowledge. Besides, optics and photonics are the fields within which the most fundamental problems of today's reality are to be resolved. It is absolutely necessary to encourage our scholars in getting optics and photonics education as an alternative physical basis to gaining solely computer knowledge. The main obstacle is the poor connection between program of optical education and the real optical researches, disintegration of different branches of the optical science, the demographic situation, some problems with teaching mathematics and physics at schools, and the collision between traditional educational methods and the mentality of the new generation. In Russia the Saint-Petersburg State University of Information Technologies, Mechanics and Optics offers partial solution to these problems: the organization of a real place for interactive optical science in a form of a new museum of optics, intended for education and training, seems to be the most effective way. This was the main reason for establishing such a museum in Saint-Petersburg at the end of 2008.

Language Problems in Applied Linguistics: Limiting the Scope

ERIC Educational Resources Information Center

Kadarisman, A. Effendi

2014-01-01

This article critically discusses the paradigmatic shift in applied linguistics, resulting in a claim that countless real-world language problems fall within its scope, but in reality they weaken the discipline and make it lack a focus. Then it takes a closer look at the nature of these language problems, and picks out, for analysis, real examples…

Current trends in geomathematics

USGS Publications Warehouse

Griffiths, J.C.

1970-01-01

Geoscience has extended its role and improved its applications by the development of geophysics since the nineteen-thirties, geochemistry since the nineteen-fifties and now, in the late nineteen-sixties, a new synergism leads to geomathematics; again the greatest pressure for change arises from areas of application of geoscience and, as the problems to which geoscience is applied increase in complexity, the analytical tools become more sophisticated, a development which is accelerated by growth in the use of computers in geological problem-solving. In the next decade the problems with greatest public impact appear to be the ones which will receive greatest emphasis and support. This will require that the geosciences comprehend exceedingly complex probabilistic systems and these, in turn, demand the use of operations research, cybernetics and systems analysis. Such a development may well lead to a change in the paradigms underlying geoscience; they will certainly include more realistic models of "real-world" systems and the tool of simulation with cybernetic models may well become the basis for rejuvenation of experimentation in the geosciences. ?? 1970.

Compound Event Barrier Coverage in Wireless Sensor Networks under Multi-Constraint Conditions.

PubMed

Zhuang, Yaoming; Wu, Chengdong; Zhang, Yunzhou; Jia, Zixi

2016-12-24

It is important to monitor compound event by barrier coverage issues in wireless sensor networks (WSNs). Compound event barrier coverage (CEBC) is a novel coverage problem. Unlike traditional ones, the data of compound event barrier coverage comes from different types of sensors. It will be subject to multiple constraints under complex conditions in real-world applications. The main objective of this paper is to design an efficient algorithm for complex conditions that can combine the compound event confidence. Moreover, a multiplier method based on an active-set strategy (ASMP) is proposed to optimize the multiple constraints in compound event barrier coverage. The algorithm can calculate the coverage ratio efficiently and allocate the sensor resources reasonably in compound event barrier coverage. The proposed algorithm can simplify complex problems to reduce the computational load of the network and improve the network efficiency. The simulation results demonstrate that the proposed algorithm is more effective and efficient than existing methods, especially in the allocation of sensor resources.

Compound Event Barrier Coverage in Wireless Sensor Networks under Multi-Constraint Conditions

PubMed Central

Zhuang, Yaoming; Wu, Chengdong; Zhang, Yunzhou; Jia, Zixi

2016-01-01

It is important to monitor compound event by barrier coverage issues in wireless sensor networks (WSNs). Compound event barrier coverage (CEBC) is a novel coverage problem. Unlike traditional ones, the data of compound event barrier coverage comes from different types of sensors. It will be subject to multiple constraints under complex conditions in real-world applications. The main objective of this paper is to design an efficient algorithm for complex conditions that can combine the compound event confidence. Moreover, a multiplier method based on an active-set strategy (ASMP) is proposed to optimize the multiple constraints in compound event barrier coverage. The algorithm can calculate the coverage ratio efficiently and allocate the sensor resources reasonably in compound event barrier coverage. The proposed algorithm can simplify complex problems to reduce the computational load of the network and improve the network efficiency. The simulation results demonstrate that the proposed algorithm is more effective and efficient than existing methods, especially in the allocation of sensor resources. PMID:28029118

Bridging STEM in a Real World Problem

ERIC Educational Resources Information Center

English, Lyn D.; Mousoulides, Nicholas G.

2015-01-01

Engineering-based modeling activities provide a rich source of meaningful situations that capitalize on and extend students' routine learning. By integrating such activities within existing curricula, students better appreciate how their school learning in mathematics and science applies to problems in the outside world. Furthermore, modeling…

A Comparison of Genetic Programming Variants for Hyper-Heuristics

DOE Office of Scientific and Technical Information (OSTI.GOV)

Harris, Sean

Modern society is faced with ever more complex problems, many of which can be formulated as generate-and-test optimization problems. General-purpose optimization algorithms are not well suited for real-world scenarios where many instances of the same problem class need to be repeatedly and efficiently solved, such as routing vehicles over highways with constantly changing traffic flows, because they are not targeted to a particular scenario. Hyper-heuristics automate the design of algorithms to create a custom algorithm for a particular scenario. Hyper-heuristics typically employ Genetic Programming (GP) and this project has investigated the relationship between the choice of GP and performance inmore » Hyper-heuristics. Results are presented demonstrating the existence of problems for which there is a statistically significant performance differential between the use of different types of GP.« less

Combining fuzzy mathematics with fuzzy logic to solve business management problems

NASA Astrophysics Data System (ADS)

Vrba, Joseph A.

1993-12-01

Fuzzy logic technology has been applied to control problems with great success. Because of this, many observers fell that fuzzy logic is applicable only in the control arena. However, business management problems almost never deal with crisp values. Fuzzy systems technology--a combination of fuzzy logic, fuzzy mathematics and a graphical user interface--is a natural fit for developing software to assist in typical business activities such as planning, modeling and estimating. This presentation discusses how fuzzy logic systems can be extended through the application of fuzzy mathematics and the use of a graphical user interface to make the information contained in fuzzy numbers accessible to business managers. As demonstrated through examples from actual deployed systems, this fuzzy systems technology has been employed successfully to provide solutions to the complex real-world problems found in the business environment.

Technology transfer from the science of medicine to the real world: the potential role played by artificial adaptive systems.

PubMed

Grossi, Enzo

2007-01-01

The author describes a refiguration of medical thought that originates from nonlinear dynamics and chaos theory. The coupling of computer science and these new theoretical bases coming from complex systems mathematics allows the creation of "intelligent" agents capable of adapting themselves dynamically to problems of high complexity: the artificial neural networks (ANNs). ANNs are able to reproduce the dynamic interaction of multiple factors simultaneously, allowing the study of complexity; they can also draw conclusions on an individual basis and not as average trends. These tools can allow a more efficient technology transfer from the science of medicine to the real world, overcoming many obstacles responsible for the present translational failure. They also contribute to a new holistic vision of the human subject person, contrasting the statistical reductionism that tends to squeeze or even delete the single subject, sacrificing him to his group of belongingness. A remarkable contribution to this individual approach comes from fuzzy logic, according to which there are no sharp limits between opposite things, such as wealth and disease. This approach allows one to partially escape from the probability theory trap in situations where it is fundamental to express a judgement based on a single case and favor a novel humanism directed to the management of the patient as an individual subject person.

Traffic light detection and intersection crossing using mobile computer vision

NASA Astrophysics Data System (ADS)

Grewei, Lynne; Lagali, Christopher

2017-05-01

The solution for Intersection Detection and Crossing to support the development of blindBike an assisted biking system for the visually impaired is discussed. Traffic light detection and intersection crossing are key needs in the task of biking. These problems are tackled through the use of mobile computer vision, in the form of a mobile application on an Android phone. This research builds on previous Traffic Light detection algorithms with a focus on efficiency and compatibility on a resource-limited platform. Light detection is achieved through blob detection algorithms utilizing training data to detect patterns of Red, Green and Yellow in complex real world scenarios where multiple lights may be present. Also, issues of obscurity and scale are addressed. Safe Intersection crossing in blindBike is also discussed. This module takes a conservative "assistive" technology approach. To achieve this blindBike use's not only the Android device but, an external bike cadence Bluetooth/Ant enabled sensor. Real world testing results are given and future work is discussed.

A Comparison of Techniques for Scheduling Fleets of Earth-Observing Satellites

NASA Technical Reports Server (NTRS)

Globus, Al; Crawford, James; Lohn, Jason; Pryor, Anna

2003-01-01

Earth observing satellite (EOS) scheduling is a complex real-world domain representative of a broad class of over-subscription scheduling problems. Over-subscription problems are those where requests for a facility exceed its capacity. These problems arise in a wide variety of NASA and terrestrial domains and are .XI important class of scheduling problems because such facilities often represent large capital investments. We have run experiments comparing multiple variants of the genetic algorithm, hill climbing, simulated annealing, squeaky wheel optimization and iterated sampling on two variants of a realistically-sized model of the EOS scheduling problem. These are implemented as permutation-based methods; methods that search in the space of priority orderings of observation requests and evaluate each permutation by using it to drive a greedy scheduler. Simulated annealing performs best and random mutation operators outperform our squeaky (more intelligent) operator. Furthermore, taking smaller steps towards the end of the search improves performance.

Tuning self-motion perception in virtual reality with visual illusions.

PubMed

Bruder, Gerd; Steinicke, Frank; Wieland, Phil; Lappe, Markus

2012-07-01

Motion perception in immersive virtual environments significantly differs from the real world. For example, previous work has shown that users tend to underestimate travel distances in virtual environments (VEs). As a solution to this problem, researchers proposed to scale the mapped virtual camera motion relative to the tracked real-world movement of a user until real and virtual motion are perceived as equal, i.e., real-world movements could be mapped with a larger gain to the VE in order to compensate for the underestimation. However, introducing discrepancies between real and virtual motion can become a problem, in particular, due to misalignments of both worlds and distorted space cognition. In this paper, we describe a different approach that introduces apparent self-motion illusions by manipulating optic flow fields during movements in VEs. These manipulations can affect self-motion perception in VEs, but omit a quantitative discrepancy between real and virtual motions. In particular, we consider to which regions of the virtual view these apparent self-motion illusions can be applied, i.e., the ground plane or peripheral vision. Therefore, we introduce four illusions and show in experiments that optic flow manipulation can significantly affect users' self-motion judgments. Furthermore, we show that with such manipulations of optic flow fields the underestimation of travel distances can be compensated.

COVARIANCE ESTIMATION USING CONJUGATE GRADIENT FOR 3D CLASSIFICATION IN CRYO-EM.

PubMed

Andén, Joakim; Katsevich, Eugene; Singer, Amit

2015-04-01

Classifying structural variability in noisy projections of biological macromolecules is a central problem in Cryo-EM. In this work, we build on a previous method for estimating the covariance matrix of the three-dimensional structure present in the molecules being imaged. Our proposed method allows for incorporation of contrast transfer function and non-uniform distribution of viewing angles, making it more suitable for real-world data. We evaluate its performance on a synthetic dataset and an experimental dataset obtained by imaging a 70S ribosome complex.

Ordinal optimization and its application to complex deterministic problems

NASA Astrophysics Data System (ADS)

Yang, Mike Shang-Yu

1998-10-01

We present in this thesis a new perspective to approach a general class of optimization problems characterized by large deterministic complexities. Many problems of real-world concerns today lack analyzable structures and almost always involve high level of difficulties and complexities in the evaluation process. Advances in computer technology allow us to build computer models to simulate the evaluation process through numerical means, but the burden of high complexities remains to tax the simulation with an exorbitant computing cost for each evaluation. Such a resource requirement makes local fine-tuning of a known design difficult under most circumstances, let alone global optimization. Kolmogorov equivalence of complexity and randomness in computation theory is introduced to resolve this difficulty by converting the complex deterministic model to a stochastic pseudo-model composed of a simple deterministic component and a white-noise like stochastic term. The resulting randomness is then dealt with by a noise-robust approach called Ordinal Optimization. Ordinal Optimization utilizes Goal Softening and Ordinal Comparison to achieve an efficient and quantifiable selection of designs in the initial search process. The approach is substantiated by a case study in the turbine blade manufacturing process. The problem involves the optimization of the manufacturing process of the integrally bladed rotor in the turbine engines of U.S. Air Force fighter jets. The intertwining interactions among the material, thermomechanical, and geometrical changes makes the current FEM approach prohibitively uneconomical in the optimization process. The generalized OO approach to complex deterministic problems is applied here with great success. Empirical results indicate a saving of nearly 95% in the computing cost.

Real-World Learning Opportunities in Sustainability: From Classroom into the Real World

ERIC Educational Resources Information Center

Brundiers, Katja; Wiek, Arnim; Redman, Charles L.

2010-01-01

Purpose--Academic sustainability programs aim to develop key competencies in sustainability, including problem-solving skills and the ability to collaborate successfully with experts and stakeholders. These key competencies may be most fully developed in new teaching and learning situations. The purpose of this paper is to analyze the kind of, and…

Using Mathematics to Solve Real World Problems: The Role of Enablers

ERIC Educational Resources Information Center

Geiger, Vincent; Stillman, Gloria; Brown, Jill; Galbriath, Peter; Niss, Mogens

2018-01-01

The purpose of this article is to report on a newly funded research project in which we will investigate how secondary students apply mathematical modelling to effectively address real world situations. Through this study, we will identify factors, mathematical, cognitive, social and environmental that "enable" year 10/11 students to…

Uniting Community and University through Service Learning

ERIC Educational Resources Information Center

Arney, Janna B.; Jones, Irma

2006-01-01

At its core, service-learning is about creating opportunities for students to apply theory they learn in the classroom to real-world problems and real-world needs. A service-learning project was initiated with the CEO of the Brownsville Chamber of Commerce. The project required 2nd-year business communication students to interview community…

A Community of Practice Approach to Learning Programming

ERIC Educational Resources Information Center

Chen, Gwo-Dong; Li, Liang-Yi; Wang, Chin-Yea

2012-01-01

In programming courses, teaching students who have varied levels of knowledge and skills the requisite competencies to perform in real-world software development teams is indeed difficult. To address this problem, this paper proposes a community of practice (CoP) approach and provides some guidelines to simulate a real-world CoP in a blended…

Real World Projects, Real World Problems: Capstones for External Clients

ERIC Educational Resources Information Center

Reinicke, Bryan; Janicki, Thomas

2011-01-01

Capstones form an important part of the curriculum in many undergraduate and graduate programs in Information Systems. These projects give the students a chance to synthesize and apply the skills they have been acquiring throughout their academic program. These projects can be integrated with another recent initiative in higher education: service…

Social Justice and Proportional Reasoning

ERIC Educational Resources Information Center

Simic-Muller, Ksenija

2015-01-01

Ratio and proportional reasoning tasks abound that have connections to real-world situations. Examples in this article demonstrate how textbook tasks can easily be transformed into authentic real-world problems that shed light on issues of equity and fairness, such as population growth and crime rates. A few ideas are presented on how teachers can…

A New Approach to Teaching Biomechanics Through Active, Adaptive, and Experiential Learning.

PubMed

Singh, Anita

2017-07-01

Demand of biomedical engineers continues to rise to meet the needs of healthcare industry. Current training of bioengineers follows the traditional and dominant model of theory-focused curricula. However, the unmet needs of the healthcare industry warrant newer skill sets in these engineers. Translational training strategies such as solving real world problems through active, adaptive, and experiential learning hold promise. In this paper, we report our findings of adding a real-world 4-week problem-based learning unit into a biomechanics capstone course for engineering students. Surveys assessed student perceptions of the activity and learning experience. While students, across three cohorts, felt challenged to solve a real-world problem identified during the simulation lab visit, they felt more confident in utilizing knowledge learned in the biomechanics course and self-directed research. Instructor evaluations indicated that the active and experiential learning approach fostered their technical knowledge and life-long learning skills while exposing them to the components of adaptive learning and innovation.

Sparse dynamical Boltzmann machine for reconstructing complex networks with binary dynamics

NASA Astrophysics Data System (ADS)

Chen, Yu-Zhong; Lai, Ying-Cheng

2018-03-01

Revealing the structure and dynamics of complex networked systems from observed data is a problem of current interest. Is it possible to develop a completely data-driven framework to decipher the network structure and different types of dynamical processes on complex networks? We develop a model named sparse dynamical Boltzmann machine (SDBM) as a structural estimator for complex networks that host binary dynamical processes. The SDBM attains its topology according to that of the original system and is capable of simulating the original binary dynamical process. We develop a fully automated method based on compressive sensing and a clustering algorithm to construct the SDBM. We demonstrate, for a variety of representative dynamical processes on model and real world complex networks, that the equivalent SDBM can recover the network structure of the original system and simulates its dynamical behavior with high precision.

Sparse dynamical Boltzmann machine for reconstructing complex networks with binary dynamics.

PubMed

Chen, Yu-Zhong; Lai, Ying-Cheng

2018-03-01

Revealing the structure and dynamics of complex networked systems from observed data is a problem of current interest. Is it possible to develop a completely data-driven framework to decipher the network structure and different types of dynamical processes on complex networks? We develop a model named sparse dynamical Boltzmann machine (SDBM) as a structural estimator for complex networks that host binary dynamical processes. The SDBM attains its topology according to that of the original system and is capable of simulating the original binary dynamical process. We develop a fully automated method based on compressive sensing and a clustering algorithm to construct the SDBM. We demonstrate, for a variety of representative dynamical processes on model and real world complex networks, that the equivalent SDBM can recover the network structure of the original system and simulates its dynamical behavior with high precision.

Enabling Controlling Complex Networks with Local Topological Information.

PubMed

Li, Guoqi; Deng, Lei; Xiao, Gaoxi; Tang, Pei; Wen, Changyun; Hu, Wuhua; Pei, Jing; Shi, Luping; Stanley, H Eugene

2018-03-15

Complex networks characterize the nature of internal/external interactions in real-world systems including social, economic, biological, ecological, and technological networks. Two issues keep as obstacles to fulfilling control of large-scale networks: structural controllability which describes the ability to guide a dynamical system from any initial state to any desired final state in finite time, with a suitable choice of inputs; and optimal control, which is a typical control approach to minimize the cost for driving the network to a predefined state with a given number of control inputs. For large complex networks without global information of network topology, both problems remain essentially open. Here we combine graph theory and control theory for tackling the two problems in one go, using only local network topology information. For the structural controllability problem, a distributed local-game matching method is proposed, where every node plays a simple Bayesian game with local information and local interactions with adjacent nodes, ensuring a suboptimal solution at a linear complexity. Starring from any structural controllability solution, a minimizing longest control path method can efficiently reach a good solution for the optimal control in large networks. Our results provide solutions for distributed complex network control and demonstrate a way to link the structural controllability and optimal control together.

Global Coverage Measurement Planning Strategies for Mobile Robots Equipped with a Remote Gas Sensor

PubMed Central

Arain, Muhammad Asif; Trincavelli, Marco; Cirillo, Marcello; Schaffernicht, Erik; Lilienthal, Achim J.

2015-01-01

The problem of gas detection is relevant to many real-world applications, such as leak detection in industrial settings and landfill monitoring. In this paper, we address the problem of gas detection in large areas with a mobile robotic platform equipped with a remote gas sensor. We propose an algorithm that leverages a novel method based on convex relaxation for quickly solving sensor placement problems, and for generating an efficient exploration plan for the robot. To demonstrate the applicability of our method to real-world environments, we performed a large number of experimental trials, both on randomly generated maps and on the map of a real environment. Our approach proves to be highly efficient in terms of computational requirements and to provide nearly-optimal solutions. PMID:25803707

Global coverage measurement planning strategies for mobile robots equipped with a remote gas sensor.

PubMed

Arain, Muhammad Asif; Trincavelli, Marco; Cirillo, Marcello; Schaffernicht, Erik; Lilienthal, Achim J

2015-03-20

The problem of gas detection is relevant to many real-world applications, such as leak detection in industrial settings and landfill monitoring. In this paper, we address the problem of gas detection in large areas with a mobile robotic platform equipped with a remote gas sensor. We propose an algorithm that leverages a novel method based on convex relaxation for quickly solving sensor placement problems, and for generating an efficient exploration plan for the robot. To demonstrate the applicability of our method to real-world environments, we performed a large number of experimental trials, both on randomly generated maps and on the map of a real environment. Our approach proves to be highly efficient in terms of computational requirements and to provide nearly-optimal solutions.

Simulating and mapping spatial complexity using multi-scale techniques

USGS Publications Warehouse

De Cola, L.

1994-01-01

A central problem in spatial analysis is the mapping of data for complex spatial fields using relatively simple data structures, such as those of a conventional GIS. This complexity can be measured using such indices as multi-scale variance, which reflects spatial autocorrelation, and multi-fractal dimension, which characterizes the values of fields. These indices are computed for three spatial processes: Gaussian noise, a simple mathematical function, and data for a random walk. Fractal analysis is then used to produce a vegetation map of the central region of California based on a satellite image. This analysis suggests that real world data lie on a continuum between the simple and the random, and that a major GIS challenge is the scientific representation and understanding of rapidly changing multi-scale fields. -Author

Aging and autism spectrum disorder: Evidence from the broad autism phenotype.

PubMed

Wallace, Gregory L; Budgett, Jessica; Charlton, Rebecca A

2016-12-01

This study investigated for the first time the broad autism phenotype (BAP) in the context of older adulthood and its associations with real-world executive function, social support, and both depression and anxiety symptomatology. Based on self-ratings of autistic traits, 66 older adults (60+ years old, range = 61-88) were split into BAP (n = 20) and control (n = 46) groups. Individuals in the BAP group, even after controlling for age, education level, sex, and health problems, exhibited more real-world executive function problems in multiple domains, reported lower levels of social support, and self-rated increased depression and anxiety symptomatology compared to the control group. Regression analysis revealed that level of social support was the strongest predictor of BAP traits across both groups, although real-world executive function problems and depression symptomatology were also significant predictors. Moreover, when predicting anxiety and depression symptomatology, BAP traits were the strongest predictors above and beyond the effects of demographic factors, real-world executive function problems, and social support levels. These findings suggest that the BAP in older adulthood imparts additional risks to areas of functioning that are known to be crucial to aging-related outcomes in the context of typical development. These results might in turn inform aging in autism spectrum disorder, which has been largely unexplored to date. Autism Res 2016, 9: 1294-1303. © 2016 International Society for Autism Research, Wiley Periodicals, Inc. © 2016 International Society for Autism Research, Wiley Periodicals, Inc.

Enhancing implementation science by applying best principles of systems science.

PubMed

Northridge, Mary E; Metcalf, Sara S

2016-10-04

Implementation science holds promise for better ensuring that research is translated into evidence-based policy and practice, but interventions often fail or even worsen the problems they are intended to solve due to a lack of understanding of real world structures and dynamic complexity. While systems science alone cannot possibly solve the major challenges in public health, systems-based approaches may contribute to changing the language and methods for conceptualising and acting within complex systems. The overarching goal of this paper is to improve the modelling used in dissemination and implementation research by applying best principles of systems science. Best principles, as distinct from the more customary term 'best practices', are used to underscore the need to extract the core issues from the context in which they are embedded in order to better ensure that they are transferable across settings. Toward meaningfully grappling with the complex and challenging problems faced in adopting and integrating evidence-based health interventions and changing practice patterns within specific settings, we propose and illustrate four best principles derived from our systems science experience: (1) model the problem, not the system; (2) pay attention to what is important, not just what is quantifiable; (3) leverage the utility of models as boundary objects; and (4) adopt a portfolio approach to model building. To improve our mental models of the real world, system scientists have created methodologies such as system dynamics, agent-based modelling, geographic information science and social network simulation. To understand dynamic complexity, we need the ability to simulate. Otherwise, our understanding will be limited. The practice of dynamic systems modelling, as discussed herein, is the art and science of linking system structure to behaviour for the purpose of changing structure to improve behaviour. A useful computer model creates a knowledge repository and a virtual library for internally consistent exploration of alternative assumptions. Among the benefits of systems modelling are iterative practice, participatory potential and possibility thinking. We trust that the best principles proposed here will resonate with implementation scientists; applying them to the modelling process may abet the translation of research into effective policy and practice.

The real-world problem of care coordination: a longitudinal qualitative study with patients living with advanced progressive illness and their unpaid caregivers.

PubMed

Daveson, Barbara A; Harding, Richard; Shipman, Cathy; Mason, Bruce L; Epiphaniou, Eleni; Higginson, Irene J; Ellis-Smith, Clare; Henson, Lesley; Munday, Dan; Nanton, Veronica; Dale, Jeremy R; Boyd, Kirsty; Worth, Allison; Barclay, Stephen; Donaldson, Anne; Murray, Scott

2014-01-01

To develop a model of care coordination for patients living with advanced progressive illness and their unpaid caregivers, and to understand their perspective regarding care coordination. A prospective longitudinal, multi-perspective qualitative study involving a case-study approach. Serial in-depth interviews were conducted, transcribed verbatim and then analyzed through open and axial coding in order to construct categories for three cases (sites). This was followed by continued thematic analysis to identify underlying conceptual coherence across all cases in order to produce one coherent care coordination model. Fifty-six purposively sampled patients and 27 case-linked unpaid caregivers. Three cases from contrasting primary, secondary and tertiary settings within Britain. Coordination is a deliberate cross-cutting action that involves high-quality, caring and well-informed staff, patients and unpaid caregivers who must work in partnership together across health and social care settings. For coordination to occur, it must be adequately resourced with efficient systems and services that communicate. Patients and unpaid caregivers contribute substantially to the coordination of their care, which is sometimes volunteered at a personal cost to them. Coordination is facilitated through flexible and patient-centered care, characterized by accurate and timely information communicated in a way that considers patients' and caregivers' needs, preferences, circumstances and abilities. Within the midst of advanced progressive illness, coordination is a shared and complex intervention involving relational, structural and information components. Our study is one of the first to extensively examine patients' and caregivers' views about coordination, thus aiding conceptual fidelity. These findings can be used to help avoid oversimplifying a real-world problem, such as care coordination. Avoiding oversimplification can help with the development, evaluation and implementation of real-world coordination interventions for patients and their unpaid caregivers in the future.

The Effects of Duration of Exposure to the REAPS Model in Developing Students' General Creativity and Creative Problem Solving in Science

ERIC Educational Resources Information Center

Alhusaini, Abdulnasser Alashaal F.

2016-01-01

The Real Engagement in Active Problem Solving (REAPS) model was developed in 2004 by C. June Maker and colleagues as an intervention for gifted students to develop creative problem solving ability through the use of real-world problems. The primary purpose of this study was to examine the effects of the REAPS model on developing students' general…

Programming and Tuning a Quantum Annealing Device to Solve Real World Problems

NASA Astrophysics Data System (ADS)

Perdomo-Ortiz, Alejandro; O'Gorman, Bryan; Fluegemann, Joseph; Smelyanskiy, Vadim

2015-03-01

Solving real-world applications with quantum algorithms requires overcoming several challenges, ranging from translating the computational problem at hand to the quantum-machine language to tuning parameters of the quantum algorithm that have a significant impact on the performance of the device. In this talk, we discuss these challenges, strategies developed to enhance performance, and also a more efficient implementation of several applications. Although we will focus on applications of interest to NASA's Quantum Artificial Intelligence Laboratory, the methods and concepts presented here apply to a broader family of hard discrete optimization problems, including those that occur in many machine-learning algorithms.

Fast and robust curve skeletonization for real-world elongated objects

USDA-ARS?s Scientific Manuscript database

These datasets were generated for calibrating robot-camera systems. In an extension, we also considered the problem of calibrating robots with more than one camera. These datasets are provided as a companion to the paper, "Solving the Robot-World Hand-Eye(s) Calibration Problem with Iterative Meth...

Impact of Cognitive Abilities and Prior Knowledge on Complex Problem Solving Performance – Empirical Results and a Plea for Ecologically Valid Microworlds

PubMed Central

Süß, Heinz-Martin; Kretzschmar, André

2018-01-01

The original aim of complex problem solving (CPS) research was to bring the cognitive demands of complex real-life problems into the lab in order to investigate problem solving behavior and performance under controlled conditions. Up until now, the validity of psychometric intelligence constructs has been scrutinized with regard to its importance for CPS performance. At the same time, different CPS measurement approaches competing for the title of the best way to assess CPS have been developed. In the first part of the paper, we investigate the predictability of CPS performance on the basis of the Berlin Intelligence Structure Model and Cattell’s investment theory as well as an elaborated knowledge taxonomy. In the first study, 137 students managed a simulated shirt factory (Tailorshop; i.e., a complex real life-oriented system) twice, while in the second study, 152 students completed a forestry scenario (FSYS; i.e., a complex artificial world system). The results indicate that reasoning – specifically numerical reasoning (Studies 1 and 2) and figural reasoning (Study 2) – are the only relevant predictors among the intelligence constructs. We discuss the results with reference to the Brunswik symmetry principle. Path models suggest that reasoning and prior knowledge influence problem solving performance in the Tailorshop scenario mainly indirectly. In addition, different types of system-specific knowledge independently contribute to predicting CPS performance. The results of Study 2 indicate that working memory capacity, assessed as an additional predictor, has no incremental validity beyond reasoning. We conclude that (1) cognitive abilities and prior knowledge are substantial predictors of CPS performance, and (2) in contrast to former and recent interpretations, there is insufficient evidence to consider CPS a unique ability construct. In the second part of the paper, we discuss our results in light of recent CPS research, which predominantly utilizes the minimally complex systems (MCS) measurement approach. We suggest ecologically valid microworlds as an indispensable tool for future CPS research and applications. PMID:29867627

Control system of water flow and casting speed in continuous steel casting

NASA Astrophysics Data System (ADS)

Tirian, G. O.; Gheorghiu, C. A.; Hepuţ, T.; Chioncel, C.

2017-05-01

This paper presents the results of research based on real data taken from the installation process at Arcelor Mittal Hunedoara. Using Matlab Simulink an intelligent system is made that takes in data from the process and makes real time adjustments in the rate of flow of the cooling water and the speed of casting that eliminates fissures in the poured material from the secondary cooling of steel. Using Matlab Simulink simulation environment allowed for qualitative analysis for various real world situations. Thus, compared to the old method of approach for the problem of cracks forming in the crust of the steel in the continuous casting, this new method, proposed and developed, brings safety and precision in this complex process, thus removing any doubt on the existence or non-existence of cracks and takes the necessary steps to prevent and correct them.

A Structured Approach to Teaching Applied Problem Solving through Technology Assessment.

ERIC Educational Resources Information Center

Fischbach, Fritz A.; Sell, Nancy J.

1986-01-01

Describes an approach to problem solving based on real-world problems. Discusses problem analysis and definitions, preparation of briefing documents, solution finding techniques (brainstorming and synectics), solution evaluation and judgment, and implementation. (JM)

Students without Borders: Global Collaborative Learning Connects School to the Real World

ERIC Educational Resources Information Center

Bickley, Mali; Carleton, Jim

2009-01-01

Kids can't help but get engaged when they're collaborating with peers across the globe to solve real-life problems. Global collaborative learning is about connecting students in communities of learners around the world so they can work together on projects that make a difference locally and globally. It is about building relationships and…

Kids Are Consumers, Too! Real-World Reading and Language Arts.

ERIC Educational Resources Information Center

Fair, Jan; Melvin, Mary; Bantz, Carol; Vause, Kate

Designed to help youngsters with real-world learning, and with being a smart consumer, this book focuses on having students participate in decisions facing consumers every day. The book contends that this is the best way to help students think critically and solve problems. Activities in the book require students to make consumer decisions related…

How to Make a Math Modeling Class from Scratch in Six (Not-So) Easy Steps

ERIC Educational Resources Information Center

Gerhardt, Ira

2017-01-01

The recent introduction of a new course in mathematical modeling at Manhattan College has provided students with a valuable opportunity to gain practical experience utilizing tools in applying their mathematical abilities to a real-world problem. This paper describes the steps taken to create this class, from obtaining a real-world partner…

Investigating Comprehension in Real World Tasks: Understanding Jury Instructions.

ERIC Educational Resources Information Center

Charrow, Veda R.; Charrow, Robert

This paper discusses the results of part of an ongoing project studying an aspect of real world language usage, the comprehension of standard jury instructions. Problems in the comprehension of these instructions include the memory load that they impose, the fact that most instructions are read only once, and the fact that instructions are written…

Effective use of integrated hydrological models in basin-scale water resources management: surrogate modeling approaches

NASA Astrophysics Data System (ADS)

Zheng, Y.; Wu, B.; Wu, X.

2015-12-01

Integrated hydrological models (IHMs) consider surface water and subsurface water as a unified system, and have been widely adopted in basin-scale water resources studies. However, due to IHMs' mathematical complexity and high computational cost, it is difficult to implement them in an iterative model evaluation process (e.g., Monte Carlo Simulation, simulation-optimization analysis, etc.), which diminishes their applicability for supporting decision-making in real-world situations. Our studies investigated how to effectively use complex IHMs to address real-world water issues via surrogate modeling. Three surrogate modeling approaches were considered, including 1) DYCORS (DYnamic COordinate search using Response Surface models), a well-established response surface-based optimization algorithm; 2) SOIM (Surrogate-based Optimization for Integrated surface water-groundwater Modeling), a response surface-based optimization algorithm that we developed specifically for IHMs; and 3) Probabilistic Collocation Method (PCM), a stochastic response surface approach. Our investigation was based on a modeling case study in the Heihe River Basin (HRB), China's second largest endorheic river basin. The GSFLOW (Coupled Ground-Water and Surface-Water Flow Model) model was employed. Two decision problems were discussed. One is to optimize, both in time and in space, the conjunctive use of surface water and groundwater for agricultural irrigation in the middle HRB region; and the other is to cost-effectively collect hydrological data based on a data-worth evaluation. Overall, our study results highlight the value of incorporating an IHM in making decisions of water resources management and hydrological data collection. An IHM like GSFLOW can provide great flexibility to formulating proper objective functions and constraints for various optimization problems. On the other hand, it has been demonstrated that surrogate modeling approaches can pave the path for such incorporation in real-world situations, since they can dramatically reduce the computational cost of using IHMs in an iterative model evaluation process. In addition, our studies generated insights into the human-nature water conflicts in the specific study area and suggested potential solutions to address them.

The Origin of Complex Quantum Amplitudes

NASA Astrophysics Data System (ADS)

Goyal, Philip; Knuth, Kevin H.; Skilling, John

2009-12-01

Physics is real. Measurement produces real numbers. Yet quantum mechanics uses complex arithmetic, in which √-1 is necessary but mysteriously relates to nothing else. By applying the same sort of symmetry arguments that Cox [1, 2] used to justify probability calculus, we are now able to explain this puzzle. The dual device/object nature of observation requires us to describe the world in terms of pairs of real numbers about which we never have full knowledge. These pairs combine according to complex arithmetic, using Feynman's rules.

A Ranking Approach on Large-Scale Graph With Multidimensional Heterogeneous Information.

PubMed

Wei, Wei; Gao, Bin; Liu, Tie-Yan; Wang, Taifeng; Li, Guohui; Li, Hang

2016-04-01

Graph-based ranking has been extensively studied and frequently applied in many applications, such as webpage ranking. It aims at mining potentially valuable information from the raw graph-structured data. Recently, with the proliferation of rich heterogeneous information (e.g., node/edge features and prior knowledge) available in many real-world graphs, how to effectively and efficiently leverage all information to improve the ranking performance becomes a new challenging problem. Previous methods only utilize part of such information and attempt to rank graph nodes according to link-based methods, of which the ranking performances are severely affected by several well-known issues, e.g., over-fitting or high computational complexity, especially when the scale of graph is very large. In this paper, we address the large-scale graph-based ranking problem and focus on how to effectively exploit rich heterogeneous information of the graph to improve the ranking performance. Specifically, we propose an innovative and effective semi-supervised PageRank (SSP) approach to parameterize the derived information within a unified semi-supervised learning framework (SSLF-GR), then simultaneously optimize the parameters and the ranking scores of graph nodes. Experiments on the real-world large-scale graphs demonstrate that our method significantly outperforms the algorithms that consider such graph information only partially.

Principles for fostering the transdisciplinary development of assistive technologies.

PubMed

Boger, Jennifer; Jackson, Piper; Mulvenna, Maurice; Sixsmith, Judith; Sixsmith, Andrew; Mihailidis, Alex; Kontos, Pia; Miller Polgar, Janice; Grigorovich, Alisa; Martin, Suzanne

2017-07-01

Developing useful and usable assistive technologies often presents complex (or "wicked") challenges that require input from multiple disciplines and sectors. Transdisciplinary collaboration can enable holistic understanding of challenges that may lead to innovative, impactful and transformative solutions. This paper presents generalised principles that are intended to foster transdisciplinary assistive technology development. The paper introduces the area of assistive technology design before discussing general aspects of transdisciplinary collaboration followed by an overview of relevant concepts, including approaches, methodologies and frameworks for conducting and evaluating transdisciplinary working and assistive technology design. The principles for transdisciplinary development of assistive technologies are presented and applied post hoc to the COACH project, an ambient-assisted living technology for guiding completion of activities of daily living by older adults with dementia as an illustrative example. Future work includes the refinement and validation of these principles through their application to real-world transdisciplinary assistive technology projects. Implications for rehabilitation Transdisciplinarity encourages a focus on real world 'wicked' problems. A transdisciplinary approach involves transcending disciplinary boundaries and collaborating with interprofessional and community partners (including the technology's intended users) on a shared problem. Transdisciplinarity fosters new ways of thinking about and doing research, development, and implementation, expanding the scope, applicability, and commercial viability of assistive technologies.

Spontaneous mentalizing during an interactive real world task: an fMRI study.

PubMed

Spiers, Hugo J; Maguire, Eleanor A

2006-01-01

There are moments in everyday life when we need to consider the thoughts and intentions of other individuals in order to act in a socially appropriate manner. Most of this mentalizing occurs spontaneously as we go about our business in the complexity of the real world. As such, studying the neural basis of spontaneous mentalizing has been virtually impossible. Here we devised a means to achieve this by employing a unique combination of functional magnetic resonance imaging (fMRI), a detailed and interactive virtual reality simulation of a bustling familiar city, and a retrospective verbal report protocol. We were able to provide insights into the content of spontaneous mentalizing events and identify the brain regions that underlie them. We found increased activity in a number of regions, namely the right posterior superior temporal sulcus, the medial prefrontal cortex and the right temporal pole associated with spontaneous mentalizing. Furthermore, we observed the right posterior superior temporal sulcus to be consistently active during several different subtypes of mentalizing events. By contrast, medial prefrontal cortex seemed to be particularly involved in thinking about agents that were visible in the environment. Our findings show that it is possible to investigate the neural basis of mentalizing in a manner closer to its true context, the real world, opening up intriguing possibilities for making comparisons with those who have mentalizing problems.

Decision-making deficits in normal elderly persons associated with executive personality disturbances.

PubMed

Nguyen, Christopher M; Barrash, Joseph; Koenigs, Anna L; Bechara, Antoine; Tranel, Daniel; Denburg, Natalie L

2013-11-01

The problems that some community-dwelling elderly persons develop in real-world decision-making may have disastrous consequences for their health and financial well-being. Investigations across the adult life span have identified personality as an important individual differences variable that is related to decision-making ability. The aim of this study was to investigate the relationship between personality characteristics, as rated by an informant, and complex decision-making performance among elderly persons. It was hypothesized that deficits in decision-making would be associated with personality characteristics reflecting weak executive functioning (Lack of Planning, Poor Judgment, Lack of Persistence, Perseveration, Lack of Initiative, Impulsivity, and Indecisiveness). Fifty-eight elderly persons participated. Their health and cognitive status were deemed intact via comprehensive neuropsychological evaluation. The Iowa Scales of Personality, completed by an informant, was used to assess personality characteristics, and the Iowa Gambling Task, completed by the participant, was used to assess complex decision-making abilities. Longstanding disturbances in executive personality characteristics were found to be associated with poor decision-making, and these disturbances remained predictive of poor decision-making even after taking into consideration demographic, neuropsychological, and mood factors. Acquired personality disturbances did not add significantly to prediction after longstanding disturbances were taken into account. Disturbances in other dimensions of personality were not significantly associated with poor decision-making. Our study suggests that attentiveness to the personality correlates of difficulties with aspects of executive functioning over the adult years could enhance the ability to identify older individuals at risk for problems with real-world decision-making.

Decision-Making Deficits in Normal Elderly Persons Associated with Executive Personality Disturbances

PubMed Central

Nguyen, Christopher M.; Barrash, Joseph; Koenigs, Anna L.; Bechara, Antoine; Tranel, Daniel; Denburg, Natalie L.

2014-01-01

Background The problems that some community-dwelling elderly develop in real-world decision-making may have disastrous consequences for their health and financial well-being. Investigations across the adult life span have identified personality as an important individual differences variable that is related to decision-making ability. The aim of this study was to investigate the relationship between personality characteristics, as rated by an informant, and complex decision-making performance among elders. It was hypothesized that deficits in decision-making would be associated with personality characteristics reflecting weak executive functioning (Lack of Planning, Poor Judgment, Lack of Persistence, Perseveration, Lack of Initiative, Impulsivity, and Indecisiveness). Methods Fifty-eight elderly persons participated. Their health and cognitive status were deemed intact via comprehensive neuropsychological evaluation. The Iowa Scales of Personality, completed by an informant, was used to assess personality characteristics, and the Iowa Gambling Task, completed by the participant, was used to assess complex decision-making abilities. Results Longstanding disturbances in executive personality characteristics were found to be associated with poor decision-making, and these disturbances remained predictive of poor decision-making even after taking into consideration demographic, neuropsychological, and mood factors. Acquired personality disturbances did not add significantly to prediction after longstanding disturbances were taken into account. Disturbances in other dimensions of personality were not significantly associated with poor decision-making. Conclusions Our study suggests that attentiveness to the personality correlates of difficulties with aspects of executive functioning over the adult years could enhance the ability to identify older individuals at risk for problems with real-world decision-making. PMID:23906413

Earth System Science Education Modules

NASA Astrophysics Data System (ADS)

Hall, C.; Kaufman, C.; Humphreys, R. R.; Colgan, M. W.

2009-12-01

The College of Charleston is developing several new geoscience-based education modules for integration into the Earth System Science Education Alliance (ESSEA). These three new modules provide opportunities for science and pre-service education students to participate in inquiry-based, data-driven experiences. The three new modules will be discussed in this session. Coastal Crisis is a module that analyzes rapidly changing coastlines and uses technology - remotely sensed data and geographic information systems (GIS) to delineate, understand and monitor changes in coastal environments. The beaches near Charleston, SC are undergoing erosion and therefore are used as examples of rapidly changing coastlines. Students will use real data from NASA, NOAA and other federal agencies in the classroom to study coastal change. Through this case study, learners will acquire remotely sensed images and GIS data sets from online sources, utilize those data sets within Google Earth or other visualization programs, and understand what the data is telling them. Analyzing the data will allow learners to contemplate and make predictions on the impact associated with changing environmental conditions, within the context of a coastal setting. To Drill or Not To Drill is a multidisciplinary problem based module to increase students’ knowledge of problems associated with nonrenewable resource extraction. The controversial topic of drilling in the Arctic National Wildlife Refuge (ANWR) examines whether the economic benefit of the oil extracted from ANWR is worth the social cost of the environmental damage that such extraction may inflict. By attempting to answer this question, learners must balance the interests of preservation with the economic need for oil. The learners are exposed to the difficulties associated with a real world problem that requires trade-off between environmental trust and economic well-being. The Citizen Science module challenges students to translate scientific information into words that are understandable and useful for policy makers and other stakeholders. The inability of scientists to effectively communicate with the public has been highlighted as a major reason for the anti-science attitude of a large segment of the public. This module, unlike other ESSEA modules, addresses this problem by first, investigating a global change environmental problem using Earth System Science methodologies, then developing several solutions to that problem, and finally writing a position paper for the policy makers to use. These three hands-on, real-world modules that engage students in authentic research share similar goals: 1) to use global change data sets to examine controversial environmental problems; 2) to use an earth system science approach to understand the complexity of global problems; and 3) to help students understand the political complexity of environmental problems where there is a clash between economic and ecological problems. The curriculum will meet National Standards in science, geography, math, etc.

Confronting Analytical Dilemmas for Understanding Complex Human Interactions in Design-Based Research from a Cultural-Historical Activity Theory (CHAT) Framework

ERIC Educational Resources Information Center

Yamagata-Lynch, Lisa C.

2007-01-01

Understanding human activity in real-world situations often involves complicated data collection, analysis, and presentation methods. This article discusses how Cultural-Historical Activity Theory (CHAT) can inform design-based research practices that focus on understanding activity in real-world situations. I provide a sample data set with…

Planning perception and action for cognitive mobile manipulators

NASA Astrophysics Data System (ADS)

Gaschler, Andre; Nogina, Svetlana; Petrick, Ronald P. A.; Knoll, Alois

2013-12-01

We present a general approach to perception and manipulation planning for cognitive mobile manipulators. Rather than hard-coding single purpose robot applications, a robot should be able to reason about its basic skills in order to solve complex problems autonomously. Humans intuitively solve tasks in real-world scenarios by breaking down abstract problems into smaller sub-tasks and use heuristics based on their previous experience. We apply a similar idea for planning perception and manipulation to cognitive mobile robots. Our approach is based on contingent planning and run-time sensing, integrated in our knowledge of volumes" planning framework, called KVP. Using the general-purpose PKS planner, we model information-gathering actions at plan time that have multiple possible outcomes at run time. As a result, perception and sensing arise as necessary preconditions for manipulation, rather than being hard-coded as tasks themselves. We demonstrate the e ectiveness of our approach on two scenarios covering visual and force sensing on a real mobile manipulator.

DART - LTQ ORBITRAP as an expedient tool for the identification of synthetic cannabinoids.

PubMed

Habala, Ladislav; Valentová, Jindra; Pechová, Iveta; Fuknová, Mária; Devínsky, Ferdinand

2016-05-01

Synthetic cannabinoids as designer drugs constitute a major problem due to their rapid increase in number and the difficulties connected with their identification in complex mixtures. DART (Direct Analysis in Real Time) has emerged as an advantageous tool for the direct and rapid analysis of complex samples by mass spectrometry. Here we report on the identification of six synthetic cannabinoids originating from seized material in various matrices, employing the combination of ambient pressure ion source DART and hybrid ion trap - LTQ ORBITRAP mass spectrometer. This report also describes the sampling techniques for the provided herbal material containing the cannabinoids, either directly as plant parts or as an extract in methanol and their influence on the outcome of the analysis. The high resolution mass spectra supplied by the LTQ ORBITRAP instrument allowed for an unambiguous assignment of target compounds. The utilized instrumental coupling proved to be a convenient way for the identification of synthetic cannabinoids in real-world samples. Copyright © 2016 Elsevier Ireland Ltd. All rights reserved.

Interreality in practice: bridging virtual and real worlds in the treatment of posttraumatic stress disorders.

PubMed

Riva, Giuseppe; Raspelli, Simona; Algeri, Davide; Pallavicini, Federica; Gorini, Alessandra; Wiederhold, Brenda K; Gaggioli, Andrea

2010-02-01

The use of new technologies, particularly virtual reality, is not new in the treatment of posttraumatic stress disorders (PTSD): VR is used to facilitate the activation of the traumatic event during exposure therapy. However, during the therapy, VR is a new and distinct realm, separate from the emotions and behaviors experienced by the patient in the real world: the behavior of the patient in VR has no direct effects on the real-life experience; the emotions and problems experienced by the patient in the real world are not directly addressed in the VR exposure. In this article, we suggest that the use of a new technological paradigm, Interreality, may improve the clinical outcome of PTSD. The main feature of Interreality is a twofold link between the virtual and real worlds: (a) behavior in the physical world influences the experience in the virtual one; (b) behavior in the virtual world influences the experience in the real one. This is achieved through 3D shared virtual worlds; biosensors and activity sensors (from the real to the virtual world); and personal digital assistants and/or mobile phones (from the virtual world to the real one). We describe different technologies that are involved in the Interreality vision and its clinical rationale. To illustrate the concept of Interreality in practice, a clinical scenario is also presented and discussed: Rosa, a 55-year-old nurse, involved in a major car accident.

Attention in the real world: toward understanding its neural basis

PubMed Central

Peelen, Marius V.; Kastner, Sabine

2016-01-01

The efficient selection of behaviorally relevant objects from cluttered environments supports our everyday goals. Attentional selection has typically been studied in search tasks involving artificial and simplified displays. Although these studies have revealed important basic principles of attention, they do not explain how the brain efficiently selects familiar objects in complex and meaningful real-world scenes. Findings from recent neuroimaging studies indicate that real-world search is mediated by ‘what’ and ‘where’ attentional templates that are implemented in high-level visual cortex. These templates represent target-diagnostic properties and likely target locations, respectively, and are shaped by object familiarity, scene context, and memory. We propose a framework for real-world search that incorporates these recent findings and specifies directions for future study. PMID:24630872

Approximate l-fold cross-validation with Least Squares SVM and Kernel Ridge Regression

DOE Office of Scientific and Technical Information (OSTI.GOV)

Edwards, Richard E; Zhang, Hao; Parker, Lynne Edwards

2013-01-01

Kernel methods have difficulties scaling to large modern data sets. The scalability issues are based on computational and memory requirements for working with a large matrix. These requirements have been addressed over the years by using low-rank kernel approximations or by improving the solvers scalability. However, Least Squares Support VectorMachines (LS-SVM), a popular SVM variant, and Kernel Ridge Regression still have several scalability issues. In particular, the O(n^3) computational complexity for solving a single model, and the overall computational complexity associated with tuning hyperparameters are still major problems. We address these problems by introducing an O(n log n) approximate l-foldmore » cross-validation method that uses a multi-level circulant matrix to approximate the kernel. In addition, we prove our algorithm s computational complexity and present empirical runtimes on data sets with approximately 1 million data points. We also validate our approximate method s effectiveness at selecting hyperparameters on real world and standard benchmark data sets. Lastly, we provide experimental results on using a multi-level circulant kernel approximation to solve LS-SVM problems with hyperparameters selected using our method.« less

Estimating Classifier Accuracy Using Noisy Expert Labels

DTIC Science & Technology

estimators to real -world problems is limited. We applythe estimators to labels simulated from three models of the expert labeling process and also four real ...thatconditional dependence between experts negatively impacts estimator performance. On two of the real datasets, the estimatorsclearly outperformed the

Comparing Evolutionary Programs and Evolutionary Pattern Search Algorithms: A Drug Docking Application

DOE Office of Scientific and Technical Information (OSTI.GOV)

Hart, W.E.

1999-02-10

Evolutionary programs (EPs) and evolutionary pattern search algorithms (EPSAS) are two general classes of evolutionary methods for optimizing on continuous domains. The relative performance of these methods has been evaluated on standard global optimization test functions, and these results suggest that EPSAs more robustly converge to near-optimal solutions than EPs. In this paper we evaluate the relative performance of EPSAs and EPs on a real-world application: flexible ligand binding in the Autodock docking software. We compare the performance of these methods on a suite of docking test problems. Our results confirm that EPSAs and EPs have comparable performance, and theymore » suggest that EPSAs may be more robust on larger, more complex problems.« less

Autonomous stair-climbing with miniature jumping robots.

PubMed

Stoeter, Sascha A; Papanikolopoulos, Nikolaos

2005-04-01

The problem of vision-guided control of miniature mobile robots is investigated. Untethered mobile robots with small physical dimensions of around 10 cm or less do not permit powerful onboard computers because of size and power constraints. These challenges have, in the past, reduced the functionality of such devices to that of a complex remote control vehicle with fancy sensors. With the help of a computationally more powerful entity such as a larger companion robot, the control loop can be closed. Using the miniature robot's video transmission or that of an observer to localize it in the world, control commands can be computed and relayed to the inept robot. The result is a system that exhibits autonomous capabilities. The framework presented here solves the problem of climbing stairs with the miniature Scout robot. The robot's unique locomotion mode, the jump, is employed to hop one step at a time. Methods for externally tracking the Scout are developed. A large number of real-world experiments are conducted and the results discussed.

Attitudes about high school physics in relationship to gender and ethnicity: A mixed method analysis

NASA Astrophysics Data System (ADS)

Hafza, Rabieh Jamal

There is an achievement gap and lack of participation in science, technology, engineering, and math (STEM) by minority females. The number of minority females majoring in STEM related fields and earning advanced degrees in these fields has not significantly increased over the past 40 years. Previous research has evaluated the relationship between self-identity concept and factors that promote the academic achievement as well the motivation of students to study different subject areas. This study examined the interaction between gender and ethnicity in terms of physics attitudes in the context of real world connections, personal interest, sense making/effort, problem solving confidence, and problem solving sophistication. The Colorado Learning Attitudes about Science Survey (CLASS) was given to 131 students enrolled in physics classes. There was a statistically significant Gender*Ethnicity interaction for attitude in the context of Real World Connections, Personal Interest, Sense Making/Effort, Problem Solving Confidence, and Problem Solving Sophistication as a whole. There was also a statistically significant Gender*Ethnicity interaction for attitude in the context of Real World Connections, Personal Interest, and Sense Making/Effort individually. Five Black females were interviewed to triangulate the quantitative results and to describe the experiences of minority females taking physics classes. There were four themes that emerged from the interviews and supported the findings from the quantitative results. The data supported previous research done on attitudes about STEM. The results reported that Real World Connections and Personal Interest could be possible factors that explain the lack of participation and achievement gaps that exists among minority females.

Working with Missing Data in Higher Education Research: A Primer and Real-World Example

ERIC Educational Resources Information Center

Cox, Bradley E.; McIntosh, Kadian; Reason, Robert D.; Terenzini, Patrick T.

2014-01-01

Nearly all quantitative analyses in higher education draw from incomplete datasets-a common problem with no universal solution. In the first part of this paper, we explain why missing data matter and outline the advantages and disadvantages of six common methods for handling missing data. Next, we analyze real-world data from 5,905 students across…

Image-based aircraft pose estimation: a comparison of simulations and real-world data

NASA Astrophysics Data System (ADS)

Breuers, Marcel G. J.; de Reus, Nico

2001-10-01

The problem of estimating aircraft pose information from mono-ocular image data is considered using a Fourier descriptor based algorithm. The dependence of pose estimation accuracy on image resolution and aspect angle is investigated through simulations using sets of synthetic aircraft images. Further evaluation shows that god pose estimation accuracy can be obtained in real world image sequences.

PuLP/XtraPuLP : Partitioning Tools for Extreme-Scale Graphs

DOE Office of Scientific and Technical Information (OSTI.GOV)

Slota, George M; Rajamanickam, Sivasankaran; Madduri, Kamesh

2017-09-21

PuLP/XtraPulp is software for partitioning graphs from several real-world problems. Graphs occur in several places in real world from road networks, social networks and scientific simulations. For efficient parallel processing these graphs have to be partitioned (split) with respect to metrics such as computation and communication costs. Our software allows such partitioning for massive graphs.

Bridging the Particle Physics and Big Data Worlds

NASA Astrophysics Data System (ADS)

Pivarski, James

2017-09-01

For decades, particle physicists have developed custom software because the scale and complexity of our problems were unique. In recent years, however, the ``big data'' industry has begun to tackle similar problems, and has developed some novel solutions. Incorporating scientific Python libraries, Spark, TensorFlow, and machine learning tools into the physics software stack can improve abstraction, reliability, and in some cases performance. Perhaps more importantly, it can free physicists to concentrate on domain-specific problems. Building bridges isn't always easy, however. Physics software and open-source software from industry differ in many incidental ways and a few fundamental ways. I will show work from the DIANA-HEP project to streamline data flow from ROOT to Numpy and Spark, to incorporate ideas of functional programming into histogram aggregation, and to develop real-time, query-style manipulations of particle data.

Generic Entity Resolution in Relational Databases

NASA Astrophysics Data System (ADS)

Sidló, Csaba István

Entity Resolution (ER) covers the problem of identifying distinct representations of real-world entities in heterogeneous databases. We consider the generic formulation of ER problems (GER) with exact outcome. In practice, input data usually resides in relational databases and can grow to huge volumes. Yet, typical solutions described in the literature employ standalone memory resident algorithms. In this paper we utilize facilities of standard, unmodified relational database management systems (RDBMS) to enhance the efficiency of GER algorithms. We study and revise the problem formulation, and propose practical and efficient algorithms optimized for RDBMS external memory processing. We outline a real-world scenario and demonstrate the advantage of algorithms by performing experiments on insurance customer data.

Sampling from complex networks using distributed learning automata

NASA Astrophysics Data System (ADS)

Rezvanian, Alireza; Rahmati, Mohammad; Meybodi, Mohammad Reza

2014-02-01

A complex network provides a framework for modeling many real-world phenomena in the form of a network. In general, a complex network is considered as a graph of real world phenomena such as biological networks, ecological networks, technological networks, information networks and particularly social networks. Recently, major studies are reported for the characterization of social networks due to a growing trend in analysis of online social networks as dynamic complex large-scale graphs. Due to the large scale and limited access of real networks, the network model is characterized using an appropriate part of a network by sampling approaches. In this paper, a new sampling algorithm based on distributed learning automata has been proposed for sampling from complex networks. In the proposed algorithm, a set of distributed learning automata cooperate with each other in order to take appropriate samples from the given network. To investigate the performance of the proposed algorithm, several simulation experiments are conducted on well-known complex networks. Experimental results are compared with several sampling methods in terms of different measures. The experimental results demonstrate the superiority of the proposed algorithm over the others.

Directed Bee Colony Optimization Algorithm to Solve the Nurse Rostering Problem.

PubMed

Rajeswari, M; Amudhavel, J; Pothula, Sujatha; Dhavachelvan, P

2017-01-01

The Nurse Rostering Problem is an NP-hard combinatorial optimization, scheduling problem for assigning a set of nurses to shifts per day by considering both hard and soft constraints. A novel metaheuristic technique is required for solving Nurse Rostering Problem (NRP). This work proposes a metaheuristic technique called Directed Bee Colony Optimization Algorithm using the Modified Nelder-Mead Method for solving the NRP. To solve the NRP, the authors used a multiobjective mathematical programming model and proposed a methodology for the adaptation of a Multiobjective Directed Bee Colony Optimization (MODBCO). MODBCO is used successfully for solving the multiobjective problem of optimizing the scheduling problems. This MODBCO is an integration of deterministic local search, multiagent particle system environment, and honey bee decision-making process. The performance of the algorithm is assessed using the standard dataset INRC2010, and it reflects many real-world cases which vary in size and complexity. The experimental analysis uses statistical tools to show the uniqueness of the algorithm on assessment criteria.

Directed Bee Colony Optimization Algorithm to Solve the Nurse Rostering Problem

PubMed Central

Amudhavel, J.; Pothula, Sujatha; Dhavachelvan, P.

2017-01-01

The Nurse Rostering Problem is an NP-hard combinatorial optimization, scheduling problem for assigning a set of nurses to shifts per day by considering both hard and soft constraints. A novel metaheuristic technique is required for solving Nurse Rostering Problem (NRP). This work proposes a metaheuristic technique called Directed Bee Colony Optimization Algorithm using the Modified Nelder-Mead Method for solving the NRP. To solve the NRP, the authors used a multiobjective mathematical programming model and proposed a methodology for the adaptation of a Multiobjective Directed Bee Colony Optimization (MODBCO). MODBCO is used successfully for solving the multiobjective problem of optimizing the scheduling problems. This MODBCO is an integration of deterministic local search, multiagent particle system environment, and honey bee decision-making process. The performance of the algorithm is assessed using the standard dataset INRC2010, and it reflects many real-world cases which vary in size and complexity. The experimental analysis uses statistical tools to show the uniqueness of the algorithm on assessment criteria. PMID:28473849

A computer-based training system combining virtual reality and multimedia

NASA Technical Reports Server (NTRS)

Stansfield, Sharon A.

1993-01-01

Training new users of complex machines is often an expensive and time-consuming process. This is particularly true for special purpose systems, such as those frequently encountered in DOE applications. This paper presents a computer-based training system intended as a partial solution to this problem. The system extends the basic virtual reality (VR) training paradigm by adding a multimedia component which may be accessed during interaction with the virtual environment. The 3D model used to create the virtual reality is also used as the primary navigation tool through the associated multimedia. This method exploits the natural mapping between a virtual world and the real world that it represents to provide a more intuitive way for the student to interact with all forms of information about the system.

Addressing Data Veracity in Big Data Applications

DOE Office of Scientific and Technical Information (OSTI.GOV)

Aman, Saima; Chelmis, Charalampos; Prasanna, Viktor

Big data applications such as in smart electric grids, transportation, and remote environment monitoring involve geographically dispersed sensors that periodically send back information to central nodes. In many cases, data from sensors is not available at central nodes at a frequency that is required for real-time modeling and decision-making. This may be due to physical limitations of the transmission networks, or due to consumers limiting frequent transmission of data from sensors located at their premises for security and privacy concerns. Such scenarios lead to partial data problem and raise the issue of data veracity in big data applications. We describemore » a novel solution to the problem of making short term predictions (up to a few hours ahead) in absence of real-time data from sensors in Smart Grid. A key implication of our work is that by using real-time data from only a small subset of influential sensors, we are able to make predictions for all sensors. We thus reduce the communication complexity involved in transmitting sensory data in Smart Grids. We use real-world electricity consumption data from smart meters to empirically demonstrate the usefulness of our method. Our dataset consists of data collected at 15-min intervals from 170 smart meters in the USC Microgrid for 7 years, totaling 41,697,600 data points.« less

Discovering Link Communities in Complex Networks by an Integer Programming Model and a Genetic Algorithm

PubMed Central

Li, Zhenping; Zhang, Xiang-Sun; Wang, Rui-Sheng; Liu, Hongwei; Zhang, Shihua

2013-01-01

Identification of communities in complex networks is an important topic and issue in many fields such as sociology, biology, and computer science. Communities are often defined as groups of related nodes or links that correspond to functional subunits in the corresponding complex systems. While most conventional approaches have focused on discovering communities of nodes, some recent studies start partitioning links to find overlapping communities straightforwardly. In this paper, we propose a new quantity function for link community identification in complex networks. Based on this quantity function we formulate the link community partition problem into an integer programming model which allows us to partition a complex network into overlapping communities. We further propose a genetic algorithm for link community detection which can partition a network into overlapping communities without knowing the number of communities. We test our model and algorithm on both artificial networks and real-world networks. The results demonstrate that the model and algorithm are efficient in detecting overlapping community structure in complex networks. PMID:24386268

Pattern Formation and Complexity Emergence

NASA Astrophysics Data System (ADS)

Berezin, Alexander A.

2001-03-01

Success of nonlinear modelling of pattern formation and self-organization encourages speculations on informational and number theoretical foundations of complexity emergence. Pythagorean "unreasonable effectiveness of integers" in natural processes is perhaps extrapolatable even to universal emergence "out-of-nothing" (Leibniz, Wheeler). Because rational numbers (R = M/N) are everywhere dense on real axis, any digital string (hence any "book" from "Library of Babel" of J.L.Borges) is "recorded" infinitely many times in arbitrary many rationals. Furthermore, within any arbitrary small interval there are infinitely many Rs for which (either or both) integers (Ms and Ns) "carry" any given string of any given length. Because any iterational process (such as generation of fractal features of Mandelbrot Set) is arbitrary closely approximatable with rational numbers, the infinite pattern of integers expresses itself in generation of complexity of the world, as well as in emergence of the world itself. This "tunnelling" from Platonic World ("Platonia" of J.Barbour) to a real (physical) world is modern recast of Leibniz's motto ("for deriving all from nothing there suffices a single principle").

Multimedia: The Brave New World of Buckytubes | ScienceCinema

Science.gov Websites

Multimedia: The Brave New World of Buckytubes Citation Details Title: The Brave New World of Buckytubes In a talk titled "The Brave New World of Buckytubes," Smalley discusses the basic science , anmore »alysis, and assembly of buckytubes for solving real-world technological problems.« less Title

Real-world navigation in amnestic mild cognitive impairment: The relation to visuospatial memory and volume of hippocampal subregions.

PubMed

Peter, Jessica; Sandkamp, Richard; Minkova, Lora; Schumacher, Lena V; Kaller, Christoph P; Abdulkadir, Ahmed; Klöppel, Stefan

2018-01-31

Spatial disorientation is a frequent symptom in Alzheimer's disease and in mild cognitive impairment (MCI). In the clinical routine, spatial orientation is less often tested with real-world navigation but rather with 2D visuoconstructive tasks. However, reports about the association between the two types of tasks are sparse. Additionally, spatial disorientation has been linked to volume of the right hippocampus but it remains unclear whether right hippocampal subregions have differential involvement in real-world navigation. Yet, this would help uncover different functional roles of the subregions, which would have important implications for understanding the neuronal underpinnings of navigation skills. We compared patients with amnestic MCI (aMCI; n = 25) and healthy elderly controls (HC; n = 25) in a real-world navigation task that engaged different spatial processes. The association between real-world navigation and different visuoconstructive tasks was tested (i.e., figures from the Consortium to Establish a Registry for Alzheimer's Disease; CERAD, the Rey-Osterrieth Complex Figure task; and clock drawing). Furthermore, the relation between spatial navigation and volume of right hippocampal subregions was examined. Linear regression and relative weight analysis were applied for statistical analyses. Patients with aMCI were significantly less able to correctly navigate through a route compared to HC but had comparable map drawing and landmark recognition skills. The association between visuoconstructive tasks and real-world navigation was only significant when using the visuospatial memory component of the Rey figure. In aMCI, more volume of the right hippocampal tail was significantly associated with better navigation skills, while volume of the right CA2/3 region was a significant predictor in HC. Standard visuoconstructive tasks (e.g., the CERAD figures or clock drawing) are not sufficient to detect real-world spatial disabilities in aMCI. Consequently, more complex visuoconstructive tasks (i.e., the Rey figure) should be routinely included in the assessment of cognitive functions in the context of AD. Moreover, in those elderly individuals with impaired complex visuospatial memory, route finding behaviour should be evaluated in detail. Regarding the contribution of hippocampal subregions to spatial navigation, the right hippocampal tail seems to be particularly important for patients with aMCI, while the CA2/3 region appears to be more relevant in HC. Copyright © 2017 Elsevier Ltd. All rights reserved.

Quantifying uncertainty in high-resolution coupled hydrodynamic-ecosystem models

NASA Astrophysics Data System (ADS)

Allen, J. I.; Somerfield, P. J.; Gilbert, F. J.

2007-01-01

Marine ecosystem models are becoming increasingly complex and sophisticated, and are being used to estimate the effects of future changes in the earth system with a view to informing important policy decisions. Despite their potential importance, far too little attention has been, and is generally, paid to model errors and the extent to which model outputs actually relate to real-world processes. With the increasing complexity of the models themselves comes an increasing complexity among model results. If we are to develop useful modelling tools for the marine environment we need to be able to understand and quantify the uncertainties inherent in the simulations. Analysing errors within highly multivariate model outputs, and relating them to even more complex and multivariate observational data, are not trivial tasks. Here we describe the application of a series of techniques, including a 2-stage self-organising map (SOM), non-parametric multivariate analysis, and error statistics, to a complex spatio-temporal model run for the period 1988-1989 in the Southern North Sea, coinciding with the North Sea Project which collected a wealth of observational data. We use model output, large spatio-temporally resolved data sets and a combination of methodologies (SOM, MDS, uncertainty metrics) to simplify the problem and to provide tractable information on model performance. The use of a SOM as a clustering tool allows us to simplify the dimensions of the problem while the use of MDS on independent data grouped according to the SOM classification allows us to validate the SOM. The combination of classification and uncertainty metrics allows us to pinpoint the variables and associated processes which require attention in each region. We recommend the use of this combination of techniques for simplifying complex comparisons of model outputs with real data, and analysis of error distributions.

Finding Out Critical Points For Real-Time Path Planning

NASA Astrophysics Data System (ADS)

Chen, Wei

1989-03-01

Path planning for a mobile robot is a classic topic, but the path planning under real-time environment is a different issue. The system sources including sampling time, processing time, processes communicating time, and memory space are very limited for this type of application. This paper presents a method which abstracts the world representation from the sensory data and makes the decision as to which point will be a potentially critical point to span the world map by using incomplete knowledge about physical world and heuristic rule. Without any previous knowledge or map of the workspace, the robot will determine the world map by roving through the workspace. The computational complexity for building and searching such a map is not more than O( n2 ) The find-path problem is well-known in robotics. Given an object with an initial location and orientation, a goal location and orientation, and a set of obstacles located in space, the problem is to find a continuous path for the object from the initial position to the goal position which avoids collisions with obstacles along the way. There are a lot of methods to find a collision-free path in given environment. Techniques for solving this problem can be classified into three approaches: 1) the configuration space approach [1],[2],[3] which represents the polygonal obstacles by vertices in a graph. The idea is to determine those parts of the free space which a reference point of the moving object can occupy without colliding with any obstacles. A path is then found for the reference point through this truly free space. Dealing with rotations turns out to be a major difficulty with the approach, requiring complex geometric algorithms which are computationally expensive. 2) the direct representation of the free space using basic shape primitives such as convex polygons [4] and overlapping generalized cones [5]. 3) the combination of technique 1 and 2 [6] by which the space is divided into the primary convex region, overlap region and obstacle region, then obstacle boundaries with attribute values are represented by the vertices of the hypergraph. The primary convex region and overlap region are represented by hyperedges, the centroids of overlap form the critical points. The difficulty is generating segment graph and estimating of minimum path width. The all techniques mentioned above need previous knowledge about the world to make path planning and the computational cost is not low. They are not available in an unknow and uncertain environment. Due to limited system resources such as CPU time, memory size and knowledge about the special application in an intelligent system (such as mobile robot), it is necessary to use algorithms that provide the good decision which is feasible with the available resources in real time rather than the best answer that could be achieved in unlimited time with unlimited resources. A real-time path planner should meet following requirements: - Quickly abstract the representation of the world from the sensory data without any previous knowledge about the robot environment. - Easily update the world model to spell out the global-path map and to reflect changes in the robot environment. - Must make a decision of where the robot must go and which direction the range sensor should point to in real time with limited resources. The method presented here assumes that the data from range sensors has been processed by signal process unite. The path planner will guide the scan of range sensor, find critical points, make decision where the robot should go and which point is poten- tial critical point, generate the path map and monitor the robot moves to the given point. The program runs recursively until the goal is reached or the whole workspace is roved through.

Measuring the Complexity of Seismicity Pattern Evolution

NASA Astrophysics Data System (ADS)

Goltz, C.

2004-12-01

``Complexity'' has become an ubiquitous term in science. However, there is, much as with ``fractality'', no clear definition of what complexity actually means. Yet, it is important to distinguish between what is merely complicated and what is complex in the sense that simple rules can give rise to very rich behaviour. Seismicity is certainly a complicated phenomenon (difficult to understand) but simple models such as cellular automata indicate that earthquakes are truly complex. From the observational point of view, there exists the problem of quantification of complexity in real world seismicity patterns (in the absence of even a rigid definition of complexity). Such a measurement is desirable, however, not only for fundamental understanding but also for monitoring and possibly for prediction purposes. Maybe the most workable definitions of complexity exist in informatics, summarised under the topic of algorithmic complexity. Here, after introducing the concepts, I apply such measures of complexity to temporally evolving seismicity patterns from different geographic regions. Finally, I discuss the usefulness of the approach and discuss results in view of the occurrence of large earthquakes.

Parameter Optimization for Turbulent Reacting Flows Using Adjoints

NASA Astrophysics Data System (ADS)

Lapointe, Caelan; Hamlington, Peter E.

2017-11-01

The formulation of a new adjoint solver for topology optimization of turbulent reacting flows is presented. This solver provides novel configurations (e.g., geometries and operating conditions) based on desired system outcomes (i.e., objective functions) for complex reacting flow problems of practical interest. For many such problems, it would be desirable to know optimal values of design parameters (e.g., physical dimensions, fuel-oxidizer ratios, and inflow-outflow conditions) prior to real-world manufacture and testing, which can be expensive, time-consuming, and dangerous. However, computational optimization of these problems is made difficult by the complexity of most reacting flows, necessitating the use of gradient-based optimization techniques in order to explore a wide design space at manageable computational cost. The adjoint method is an attractive way to obtain the required gradients, because the cost of the method is determined by the dimension of the objective function rather than the size of the design space. Here, the formulation of a novel solver is outlined that enables gradient-based parameter optimization of turbulent reacting flows using the discrete adjoint method. Initial results and an outlook for future research directions are provided.

Interactive physically-based sound simulation

NASA Astrophysics Data System (ADS)

Raghuvanshi, Nikunj

The realization of interactive, immersive virtual worlds requires the ability to present a realistic audio experience that convincingly compliments their visual rendering. Physical simulation is a natural way to achieve such realism, enabling deeply immersive virtual worlds. However, physically-based sound simulation is very computationally expensive owing to the high-frequency, transient oscillations underlying audible sounds. The increasing computational power of desktop computers has served to reduce the gap between required and available computation, and it has become possible to bridge this gap further by using a combination of algorithmic improvements that exploit the physical, as well as perceptual properties of audible sounds. My thesis is a step in this direction. My dissertation concentrates on developing real-time techniques for both sub-problems of sound simulation: synthesis and propagation. Sound synthesis is concerned with generating the sounds produced by objects due to elastic surface vibrations upon interaction with the environment, such as collisions. I present novel techniques that exploit human auditory perception to simulate scenes with hundreds of sounding objects undergoing impact and rolling in real time. Sound propagation is the complementary problem of modeling the high-order scattering and diffraction of sound in an environment as it travels from source to listener. I discuss my work on a novel numerical acoustic simulator (ARD) that is hundred times faster and consumes ten times less memory than a high-accuracy finite-difference technique, allowing acoustic simulations on previously-intractable spaces, such as a cathedral, on a desktop computer. Lastly, I present my work on interactive sound propagation that leverages my ARD simulator to render the acoustics of arbitrary static scenes for multiple moving sources and listener in real time, while accounting for scene-dependent effects such as low-pass filtering and smooth attenuation behind obstructions, reverberation, scattering from complex geometry and sound focusing. This is enabled by a novel compact representation that takes a thousand times less memory than a direct scheme, thus reducing memory footprints to fit within available main memory. To the best of my knowledge, this is the only technique and system in existence to demonstrate auralization of physical wave-based effects in real-time on large, complex 3D scenes.

Effects of Integrating an Active Learning-Promoting Mechanism into Location-Based Real-World Learning Environments on Students' Learning Performances and Behaviors

ERIC Educational Resources Information Center

Hwang, Gwo-Jen; Chang, Shao-Chen; Chen, Pei-Ying; Chen, Xiang-Ya

2018-01-01

Engaging students in real-world learning contexts has been identified by educators as being an important way of helping them learn to apply what they have learned from textbooks to practical problems. The advancements in mobile and image-processing technologies have enabled students to access learning resources and receive learning guidance in…

Working memory training may increase working memory capacity but not fluid intelligence.

PubMed

Harrison, Tyler L; Shipstead, Zach; Hicks, Kenny L; Hambrick, David Z; Redick, Thomas S; Engle, Randall W

2013-12-01

Working memory is a critical element of complex cognition, particularly under conditions of distraction and interference. Measures of working memory capacity correlate positively with many measures of real-world cognition, including fluid intelligence. There have been numerous attempts to use training procedures to increase working memory capacity and thereby performance on the real-world tasks that rely on working memory capacity. In the study reported here, we demonstrated that training on complex working memory span tasks leads to improvement on similar tasks with different materials but that such training does not generalize to measures of fluid intelligence.

More stereotypes, please! The limits of 'theory of mind' and the need for further studies on the complexity of real world social interactions.

PubMed

Andrews, Kristin

2017-01-01

I suggest that the Stereotype Rationality Hypothesis (Jussim 2012) is only partially right. I agree it is rational to rely on stereotypes, but in the complexity of real world social interactions, most of our individuating information invokes additional stereotypes. Despite assumptions to the contrary, there is reason to think theory of mind is not accurate, and social psychology's denial of stereotype accuracy led us toward mindreading/theory of mind - a less accurate account of how we understand other people.

Park Forest Middle School STEM Education Fair 2010

ERIC Educational Resources Information Center

Hughes, Bill

2010-01-01

Innovations from the United States have often led the world to new discoveries and solutions to complex problems. However, there are alarming indications that the United States is falling behind other countries in the ability to apply science, technology, engineering, and math to complex problems facing our world. In order for the country to…

A Human Proximity Operations System test case validation approach

NASA Astrophysics Data System (ADS)

Huber, Justin; Straub, Jeremy

A Human Proximity Operations System (HPOS) poses numerous risks in a real world environment. These risks range from mundane tasks such as avoiding walls and fixed obstacles to the critical need to keep people and processes safe in the context of the HPOS's situation-specific decision making. Validating the performance of an HPOS, which must operate in a real-world environment, is an ill posed problem due to the complexity that is introduced by erratic (non-computer) actors. In order to prove the HPOS's usefulness, test cases must be generated to simulate possible actions of these actors, so the HPOS can be shown to be able perform safely in environments where it will be operated. The HPOS must demonstrate its ability to be as safe as a human, across a wide range of foreseeable circumstances. This paper evaluates the use of test cases to validate HPOS performance and utility. It considers an HPOS's safe performance in the context of a common human activity, moving through a crowded corridor, and extrapolates (based on this) to the suitability of using test cases for AI validation in other areas of prospective application.

Non-stationary noise estimation using dictionary learning and Gaussian mixture models

NASA Astrophysics Data System (ADS)

Hughes, James M.; Rockmore, Daniel N.; Wang, Yang

2014-02-01

Stationarity of the noise distribution is a common assumption in image processing. This assumption greatly simplifies denoising estimators and other model parameters and consequently assuming stationarity is often a matter of convenience rather than an accurate model of noise characteristics. The problematic nature of this assumption is exacerbated in real-world contexts, where noise is often highly non-stationary and can possess time- and space-varying characteristics. Regardless of model complexity, estimating the parameters of noise dis- tributions in digital images is a difficult task, and estimates are often based on heuristic assumptions. Recently, sparse Bayesian dictionary learning methods were shown to produce accurate estimates of the level of additive white Gaussian noise in images with minimal assumptions. We show that a similar model is capable of accu- rately modeling certain kinds of non-stationary noise processes, allowing for space-varying noise in images to be estimated, detected, and removed. We apply this modeling concept to several types of non-stationary noise and demonstrate the model's effectiveness on real-world problems, including denoising and segmentation of images according to noise characteristics, which has applications in image forensics.

The Streetboard Rider: An Appealing Problem in Non-Holonomic Mechanics

ERIC Educational Resources Information Center

Janova, J.; Musilova, J.

2010-01-01

This paper enlarges the reservoir of solved tutor problems in non-holonomic mechanics at the undergraduate level of physics education. Unlike other, rather artificial, solved problems typically used, the streetboard-rider locomotion problem presented here represents an appealing contemporary real-world problem with interesting applications in a…

Beyond Problem-Based Learning: Using Dynamic PBL in Chemistry

ERIC Educational Resources Information Center

Overton, Tina L.; Randles, Christopher A.

2015-01-01

This paper describes the development and implementation of a novel pedagogy, dynamic problem-based learning. The pedagogy utilises real-world problems that evolve throughout the problem-based learning activity and provide students with choice and different data sets. This new dynamic problem-based learning approach was utilised to teach…

Problems as Possibilities: Problem-Based Learning for K-12 Education.

ERIC Educational Resources Information Center

Torp, Linda; Sage, Sara

Problem-based learning (PBL) is an experiential form of learning centered around the collaborative investigation and resolution of "messy, real-world" problems. This book offers opportunities to learn about problem-based learning from the perspectives of teachers, students, parents, administrators, and curriculum developers. Chapter 1 tells…

SCOUT: simultaneous time segmentation and community detection in dynamic networks

PubMed Central

Hulovatyy, Yuriy; Milenković, Tijana

2016-01-01

Many evolving complex real-world systems can be modeled via dynamic networks. An important problem in dynamic network research is community detection, which finds groups of topologically related nodes. Typically, this problem is approached by assuming either that each time point has a distinct community organization or that all time points share a single community organization. The reality likely lies between these two extremes. To find the compromise, we consider community detection in the context of the problem of segment detection, which identifies contiguous time periods with consistent network structure. Consequently, we formulate a combined problem of segment community detection (SCD), which simultaneously partitions the network into contiguous time segments with consistent community organization and finds this community organization for each segment. To solve SCD, we introduce SCOUT, an optimization framework that explicitly considers both segmentation quality and partition quality. SCOUT addresses limitations of existing methods that can be adapted to solve SCD, which consider only one of segmentation quality or partition quality. In a thorough evaluation, SCOUT outperforms the existing methods in terms of both accuracy and computational complexity. We apply SCOUT to biological network data to study human aging. PMID:27881879

Explicitly solvable complex Chebyshev approximation problems related to sine polynomials

NASA Technical Reports Server (NTRS)

Freund, Roland

1989-01-01

Explicitly solvable real Chebyshev approximation problems on the unit interval are typically characterized by simple error curves. A similar principle is presented for complex approximation problems with error curves induced by sine polynomials. As an application, some new explicit formulae for complex best approximations are derived.

Identification of a Threshold Value for the DEMATEL Method: Using the Maximum Mean De-Entropy Algorithm

NASA Astrophysics Data System (ADS)

Chung-Wei, Li; Gwo-Hshiung, Tzeng

To deal with complex problems, structuring them through graphical representations and analyzing causal influences can aid in illuminating complex issues, systems, or concepts. The DEMATEL method is a methodology which can be used for researching and solving complicated and intertwined problem groups. The end product of the DEMATEL process is a visual representation—the impact-relations map—by which respondents organize their own actions in the world. The applicability of the DEMATEL method is widespread, ranging from analyzing world problematique decision making to industrial planning. The most important property of the DEMATEL method used in the multi-criteria decision making (MCDM) field is to construct interrelations between criteria. In order to obtain a suitable impact-relations map, an appropriate threshold value is needed to obtain adequate information for further analysis and decision-making. In this paper, we propose a method based on the entropy approach, the maximum mean de-entropy algorithm, to achieve this purpose. Using real cases to find the interrelationships between the criteria for evaluating effects in E-learning programs as an examples, we will compare the results obtained from the respondents and from our method, and discuss that the different impact-relations maps from these two methods.

Algebraic criteria for positive realness relative to the unit circle.

NASA Technical Reports Server (NTRS)

Siljak, D. D.

1973-01-01

A definition is presented of the circle positive realness of real rational functions relative to the unit circle in the complex variable plane. The problem of testing this kind of positive reality is reduced to the algebraic problem of determining the distribution of zeros of a real polynomial with respect to and on the unit circle. Such reformulation of the problem avoids the search for explicit information about imaginary poles of rational functions. The stated algebraic problem is solved by applying the polynomial criteria of Marden (1966) and Jury (1964), and a completely recursive algorithm for circle positive realness is obtained.

CROSS-DISCIPLINARY PHYSICS AND RELATED AREAS OF SCIENCE AND TECHNOLOGY: The Fractal Dimensions of Complex Networks

NASA Astrophysics Data System (ADS)

Guo, Long; Cai, XU

2009-08-01

It is shown that many real complex networks share distinctive features, such as the small-world effect and the heterogeneous property of connectivity of vertices, which are different from random networks and regular lattices. Although these features capture the important characteristics of complex networks, their applicability depends on the style of networks. To unravel the universal characteristics many complex networks have in common, we study the fractal dimensions of complex networks using the method introduced by Shanker. We find that the average 'density' (ρ(r)) of complex networks follows a better power-law function as a function of distance r with the exponent df, which is defined as the fractal dimension, in some real complex networks. Furthermore, we study the relation between df and the shortcuts Nadd in small-world networks and the size N in regular lattices. Our present work provides a new perspective to understand the dependence of the fractal dimension df on the complex network structure.

Field balancing in the real world

DOE Office of Scientific and Technical Information (OSTI.GOV)

Bracher, B.

Field balancing can achieve significant results when other problems are present in the frequency spectrum and multiple vibrations are evident in the waveform. Many references suggest eliminating other problems before attempting to balance. That`s great - if you can do it. There are valid reasons for this approach, and it would be much easier to balance machinery when other problems have been corrected. It is the theoretical ideal in field balancing. However, in the real world of machinery maintained for years by reacting to immediate problems, the classic vibration signature for unbalance is rarely seen. Maintenance personnel make most ofmore » their decisions with limited information. The decision to balance or not to balance is usually made the same way. This paper will demonstrate significant results of field balancing in the presence of multiple problems. By examining the data available and analyzing the probabilities, a reasonable chance for success can be assured.« less

Experimental quantum annealing: case study involving the graph isomorphism problem.

PubMed

Zick, Kenneth M; Shehab, Omar; French, Matthew

2015-06-08

Quantum annealing is a proposed combinatorial optimization technique meant to exploit quantum mechanical effects such as tunneling and entanglement. Real-world quantum annealing-based solvers require a combination of annealing and classical pre- and post-processing; at this early stage, little is known about how to partition and optimize the processing. This article presents an experimental case study of quantum annealing and some of the factors involved in real-world solvers, using a 504-qubit D-Wave Two machine and the graph isomorphism problem. To illustrate the role of classical pre-processing, a compact Hamiltonian is presented that enables a reduced Ising model for each problem instance. On random N-vertex graphs, the median number of variables is reduced from N(2) to fewer than N log2 N and solvable graph sizes increase from N = 5 to N = 13. Additionally, error correction via classical post-processing majority voting is evaluated. While the solution times are not competitive with classical approaches to graph isomorphism, the enhanced solver ultimately classified correctly every problem that was mapped to the processor and demonstrated clear advantages over the baseline approach. The results shed some light on the nature of real-world quantum annealing and the associated hybrid classical-quantum solvers.

Improving extreme-scale problem solving: assessing electronic brainstorming effectiveness in an industrial setting.

PubMed

Dornburg, Courtney C; Stevens, Susan M; Hendrickson, Stacey M L; Davidson, George S

2009-08-01

An experiment was conducted to compare the effectiveness of individual versus group electronic brainstorming to address difficult, real-world challenges. Although industrial reliance on electronic communications has become ubiquitous, empirical and theoretical understanding of the bounds of its effectiveness have been limited. Previous research using short-term laboratory experiments have engaged small groups of students in answering questions irrelevant to an industrial setting. The present experiment extends current findings beyond the laboratory to larger groups of real-world employees addressing organization-relevant challenges during the course of 4 days. Employees and contractors at a national laboratory participated, either in a group setting or individually, in an electronic brainstorm to pose solutions to a real-world problem. The data demonstrate that (for this design) individuals perform at least as well as groups in producing quantity of electronic ideas, regardless of brainstorming duration. However, when judged with respect to quality along three dimensions (originality, feasibility, and effectiveness), the individuals significantly (p < .05) outperformed the group. When quality is used to benchmark success, these data indicate that work-relevant challenges are better solved by aggregating electronic individual responses rather than by electronically convening a group. This research suggests that industrial reliance on electronic problem-solving groups should be tempered, and large nominal groups may be more appropriate corporate problem-solving vehicles.

Experimental quantum annealing: case study involving the graph isomorphism problem

PubMed Central

Zick, Kenneth M.; Shehab, Omar; French, Matthew

2015-01-01

Quantum annealing is a proposed combinatorial optimization technique meant to exploit quantum mechanical effects such as tunneling and entanglement. Real-world quantum annealing-based solvers require a combination of annealing and classical pre- and post-processing; at this early stage, little is known about how to partition and optimize the processing. This article presents an experimental case study of quantum annealing and some of the factors involved in real-world solvers, using a 504-qubit D-Wave Two machine and the graph isomorphism problem. To illustrate the role of classical pre-processing, a compact Hamiltonian is presented that enables a reduced Ising model for each problem instance. On random N-vertex graphs, the median number of variables is reduced from N2 to fewer than N log2 N and solvable graph sizes increase from N = 5 to N = 13. Additionally, error correction via classical post-processing majority voting is evaluated. While the solution times are not competitive with classical approaches to graph isomorphism, the enhanced solver ultimately classified correctly every problem that was mapped to the processor and demonstrated clear advantages over the baseline approach. The results shed some light on the nature of real-world quantum annealing and the associated hybrid classical-quantum solvers. PMID:26053973

A neuromorphic network for generic multivariate data classification

PubMed Central

Schmuker, Michael; Pfeil, Thomas; Nawrot, Martin Paul

2014-01-01

Computational neuroscience has uncovered a number of computational principles used by nervous systems. At the same time, neuromorphic hardware has matured to a state where fast silicon implementations of complex neural networks have become feasible. En route to future technical applications of neuromorphic computing the current challenge lies in the identification and implementation of functional brain algorithms. Taking inspiration from the olfactory system of insects, we constructed a spiking neural network for the classification of multivariate data, a common problem in signal and data analysis. In this model, real-valued multivariate data are converted into spike trains using “virtual receptors” (VRs). Their output is processed by lateral inhibition and drives a winner-take-all circuit that supports supervised learning. VRs are conveniently implemented in software, whereas the lateral inhibition and classification stages run on accelerated neuromorphic hardware. When trained and tested on real-world datasets, we find that the classification performance is on par with a naïve Bayes classifier. An analysis of the network dynamics shows that stable decisions in output neuron populations are reached within less than 100 ms of biological time, matching the time-to-decision reported for the insect nervous system. Through leveraging a population code, the network tolerates the variability of neuronal transfer functions and trial-to-trial variation that is inevitably present on the hardware system. Our work provides a proof of principle for the successful implementation of a functional spiking neural network on a configurable neuromorphic hardware system that can readily be applied to real-world computing problems. PMID:24469794

Prediction of competitive diffusion on complex networks

NASA Astrophysics Data System (ADS)

Zhao, Jiuhua; Liu, Qipeng; Wang, Lin; Wang, Xiaofan

2018-10-01

In this paper, we study the prediction problem of diffusion process on complex networks in competitive circumstances. With this problem solved, the competitors could timely intervene the diffusion process if needed such that an expected outcome might be obtained. We consider a model with two groups of competitors spreading opposite opinions on a network. A prediction method based on the mutual influences among the agents is proposed, called Influence Matrix (IM for short), and simulations on real-world networks show that the proposed IM method has quite high accuracy on predicting both the preference of any normal agent and the final competition result. For comparison purpose, classic centrality measures are also used to predict the competition result. It is shown that PageRank, Degree, Katz Centrality, and the IM method are suitable for predicting the competition result. More precisely, in undirected networks, the IM method performs better than these centrality measures when the competing group contains more than one agent; in directed networks, the IM method performs only second to PageRank.

EDITORIAL: Sixth World Congress on Industrial Process Tomography (WCIPT6) Sixth World Congress on Industrial Process Tomography (WCIPT6)

NASA Astrophysics Data System (ADS)

Takei, Masahiro; Xu, Lijun

2011-10-01

We are pleased to publish this special feature on the Sixth World Congress on Industrial Process Tomography (WCIPT6) in Measurement Science and Technology. The international congress was successfully held in the campus of Beihang University, Beijing, China, from 6-9 September 2010. It was jointly organized by International Society for Industrial Process Tomography (ISIPT), North China Electric Power University (NCEPU) and Beihang University (BUAA). Process tomography is a tangible tool to visualize and determine the material distribution inside a process non-intrusively in real time. The internal features that can be monitored by process tomography are frequently encountered and required in the design of processes and industrial plants in the fields of chemical, oil, power and metallurgical engineering as well as many other activities such as food, material handling and combustion systems. One of the key characteristics of process tomography is to provide a direct impression and instant and clear understanding of a complex phenomenon. From the viewpoint of practical applications, industries all over the world are currently facing a number of daunting challenges including many wide-range and complex technical problems. The innovative technology of process tomography consistently contributes to providing better and better solutions to the problems as 'seeing is believing'. As a regular event, WCIPT is playing a more and more important role in addressing the challenges to overcome these problems. We are glad to see that this special feature provides a great opportunity for world-wide top-level researchers to discuss and make further developments in process tomography and its applications. The 20 articles included in this issue cover a wide range of relevant topics including sensors and sensing mechanisms, data acquisition systems and instrumentation, electrical, optical, acoustic and hybrid systems, image reconstruction and system evaluation, data and sensor fusion, data processing, other emerging technologies, and their industrial applications such as in multi-phase systems, combustion and chemical reaction, etc. The Seventh World Congress on Industrial Process Tomography (WCIPT7) will take place in Krakow, Poland, from 2-5 September 2013. We look forward to meeting you in Poland!

GAIA - a generalizable, extensible structure for integrating games, models and social networking to support decision makers

NASA Astrophysics Data System (ADS)

Paxton, L. J.; Schaefer, R. K.; Nix, M.; Fountain, G. H.; Weiss, M.; Swartz, W. H.; Parker, C. L.; MacDonald, L.; Ihde, A. G.; Simpkins, S.; GAIA Team

2011-12-01

In this paper we describe the application of a proven methodology for modeling the complex social and economic interactions embodied in real-world decision making to water scarcity and water resources. We have developed a generalizable, extensible facility we call "GAIA" - Global Assimilation of Information for Action - and applied it to different problem sets. We describe the use of the "Green Country Model" and other gaming/simulation tools to address the impacts of climate and climate disruption issues at the intersection of science, economics, policy, and society. There is a long history in the Defense community of using what are known as strategic simulations or "wargames" to model the complex interactions between the environment, people, resources, infrastructure and the economy in a competitive environment. We describe in this paper, work that we have done on understanding how this heritage can be repurposed to help us explore how the complex interplay between climate disruption and our socio/political and economic structures will affect our future. Our focus here is on a fundamental and growing issue - water and water availability. We consider water and the role of "virtual water" in the system. Various "actors" are included in the simulations. While these simulations cannot definitively predict what will happen, they do illuminate non-linear feedbacks between, for example, treaty agreement, the environment, the economy, and the government. These simulations can be focused on the global, regional, or local environment. We note that these simulations are not "zero sum" games - there need not be a winner and a loser. They are, however, competitive influence games: they represent the tools that a nation, state, faction or group has at its disposal to influence policy (diplomacy), finances, industry (economy), infrastructure, information, etc to achieve their particular goals. As in the real world the problem is competitive - not everyone shares the same definition of a successful or favorable outcome.

Processor farming in two-level analysis of historical bridge

NASA Astrophysics Data System (ADS)

Krejčí, T.; Kruis, J.; Koudelka, T.; Šejnoha, M.

2017-11-01

This contribution presents a processor farming method in connection with a multi-scale analysis. In this method, each macro-scopic integration point or each finite element is connected with a certain meso-scopic problem represented by an appropriate representative volume element (RVE). The solution of a meso-scale problem provides then effective parameters needed on the macro-scale. Such an analysis is suitable for parallel computing because the meso-scale problems can be distributed among many processors. The application of the processor farming method to a real world masonry structure is illustrated by an analysis of Charles bridge in Prague. The three-dimensional numerical model simulates the coupled heat and moisture transfer of one half of arch No. 3. and it is a part of a complex hygro-thermo-mechanical analysis which has been developed to determine the influence of climatic loading on the current state of the bridge.

Simultaneous personnel and vehicle shift scheduling in the waste management sector.

PubMed

Ghiani, Gianpaolo; Guerriero, Emanuela; Manni, Andrea; Manni, Emanuele; Potenza, Agostino

2013-07-01

Urban waste management is becoming an increasingly complex task, absorbing a huge amount of resources, and having a major environmental impact. The design of a waste management system consists in various activities, and one of these is related to the definition of shift schedules for both personnel and vehicles. This activity has a great incidence on the tactical and operational cost for companies. In this paper, we propose an integer programming model to find an optimal solution to the integrated problem. The aim is to determine optimal schedules at minimum cost. Moreover, we design a fast and effective heuristic to face large-size problems. Both approaches are tested on data from a real-world case in Southern Italy and compared to the current practice utilized by the company managing the service, showing that simultaneously solving these problems can lead to significant monetary savings. Copyright © 2013 Elsevier Ltd. All rights reserved.

A quantile-based scenario analysis approach to biomass supply chain optimization under uncertainty

DOE PAGES

Zamar, David S.; Gopaluni, Bhushan; Sokhansanj, Shahab; ...

2016-11-21

Supply chain optimization for biomass-based power plants is an important research area due to greater emphasis on renewable power energy sources. Biomass supply chain design and operational planning models are often formulated and studied using deterministic mathematical models. While these models are beneficial for making decisions, their applicability to real world problems may be limited because they do not capture all the complexities in the supply chain, including uncertainties in the parameters. This study develops a statistically robust quantile-based approach for stochastic optimization under uncertainty, which builds upon scenario analysis. We apply and evaluate the performance of our approach tomore » address the problem of analyzing competing biomass supply chains subject to stochastic demand and supply. Finally, the proposed approach was found to outperform alternative methods in terms of computational efficiency and ability to meet the stochastic problem requirements.« less

A Novel Biobjective Risk-Based Model for Stochastic Air Traffic Network Flow Optimization Problem.

PubMed

Cai, Kaiquan; Jia, Yaoguang; Zhu, Yanbo; Xiao, Mingming

2015-01-01

Network-wide air traffic flow management (ATFM) is an effective way to alleviate demand-capacity imbalances globally and thereafter reduce airspace congestion and flight delays. The conventional ATFM models assume the capacities of airports or airspace sectors are all predetermined. However, the capacity uncertainties due to the dynamics of convective weather may make the deterministic ATFM measures impractical. This paper investigates the stochastic air traffic network flow optimization (SATNFO) problem, which is formulated as a weighted biobjective 0-1 integer programming model. In order to evaluate the effect of capacity uncertainties on ATFM, the operational risk is modeled via probabilistic risk assessment and introduced as an extra objective in SATNFO problem. Computation experiments using real-world air traffic network data associated with simulated weather data show that presented model has far less constraints compared to stochastic model with nonanticipative constraints, which means our proposed model reduces the computation complexity.

A quantile-based scenario analysis approach to biomass supply chain optimization under uncertainty

DOE Office of Scientific and Technical Information (OSTI.GOV)

Zamar, David S.; Gopaluni, Bhushan; Sokhansanj, Shahab

Supply chain optimization for biomass-based power plants is an important research area due to greater emphasis on renewable power energy sources. Biomass supply chain design and operational planning models are often formulated and studied using deterministic mathematical models. While these models are beneficial for making decisions, their applicability to real world problems may be limited because they do not capture all the complexities in the supply chain, including uncertainties in the parameters. This study develops a statistically robust quantile-based approach for stochastic optimization under uncertainty, which builds upon scenario analysis. We apply and evaluate the performance of our approach tomore » address the problem of analyzing competing biomass supply chains subject to stochastic demand and supply. Finally, the proposed approach was found to outperform alternative methods in terms of computational efficiency and ability to meet the stochastic problem requirements.« less

Modified artificial bee colony algorithm for reactive power optimization

NASA Astrophysics Data System (ADS)

Sulaiman, Noorazliza; Mohamad-Saleh, Junita; Abro, Abdul Ghani

2015-05-01

Bio-inspired algorithms (BIAs) implemented to solve various optimization problems have shown promising results which are very important in this severely complex real-world. Artificial Bee Colony (ABC) algorithm, a kind of BIAs has demonstrated tremendous results as compared to other optimization algorithms. This paper presents a new modified ABC algorithm referred to as JA-ABC3 with the aim to enhance convergence speed and avoid premature convergence. The proposed algorithm has been simulated on ten commonly used benchmarks functions. Its performance has also been compared with other existing ABC variants. To justify its robust applicability, the proposed algorithm has been tested to solve Reactive Power Optimization problem. The results have shown that the proposed algorithm has superior performance to other existing ABC variants e.g. GABC, BABC1, BABC2, BsfABC dan IABC in terms of convergence speed. Furthermore, the proposed algorithm has also demonstrated excellence performance in solving Reactive Power Optimization problem.

Learning Time-Varying Coverage Functions

PubMed Central

Du, Nan; Liang, Yingyu; Balcan, Maria-Florina; Song, Le

2015-01-01

Coverage functions are an important class of discrete functions that capture the law of diminishing returns arising naturally from applications in social network analysis, machine learning, and algorithmic game theory. In this paper, we propose a new problem of learning time-varying coverage functions, and develop a novel parametrization of these functions using random features. Based on the connection between time-varying coverage functions and counting processes, we also propose an efficient parameter learning algorithm based on likelihood maximization, and provide a sample complexity analysis. We applied our algorithm to the influence function estimation problem in information diffusion in social networks, and show that with few assumptions about the diffusion processes, our algorithm is able to estimate influence significantly more accurately than existing approaches on both synthetic and real world data. PMID:25960624

Learning Time-Varying Coverage Functions.

PubMed

Du, Nan; Liang, Yingyu; Balcan, Maria-Florina; Song, Le

2014-12-08

Coverage functions are an important class of discrete functions that capture the law of diminishing returns arising naturally from applications in social network analysis, machine learning, and algorithmic game theory. In this paper, we propose a new problem of learning time-varying coverage functions, and develop a novel parametrization of these functions using random features. Based on the connection between time-varying coverage functions and counting processes, we also propose an efficient parameter learning algorithm based on likelihood maximization, and provide a sample complexity analysis. We applied our algorithm to the influence function estimation problem in information diffusion in social networks, and show that with few assumptions about the diffusion processes, our algorithm is able to estimate influence significantly more accurately than existing approaches on both synthetic and real world data.

Identifying important nodes by adaptive LeaderRank

NASA Astrophysics Data System (ADS)

Xu, Shuang; Wang, Pei

2017-03-01

Spreading process is a common phenomenon in complex networks. Identifying important nodes in complex networks is of great significance in real-world applications. Based on the spreading process on networks, a lot of measures have been proposed to evaluate the importance of nodes. However, most of the existing measures are appropriate to static networks, which are fragile to topological perturbations. Many real-world complex networks are dynamic rather than static, meaning that the nodes and edges of such networks may change with time, which challenge numerous existing centrality measures. Based on a new weighted mechanism and the newly proposed H-index and LeaderRank (LR), this paper introduces a variant of the LR measure, called adaptive LeaderRank (ALR), which is a new member of the LR-family. Simulations on six real-world networks reveal that the new measure can well balance between prediction accuracy and robustness. More interestingly, the new measure can better adapt to the adjustment or local perturbations of network topologies, as compared with the existing measures. By discussing the detailed properties of the measures from the LR-family, we illustrate that the ALR has its competitive advantages over the other measures. The proposed algorithm enriches the measures to understand complex networks, and may have potential applications in social networks and biological systems.

A combinatorial framework to quantify peak/pit asymmetries in complex dynamics.

PubMed

Hasson, Uri; Iacovacci, Jacopo; Davis, Ben; Flanagan, Ryan; Tagliazucchi, Enzo; Laufs, Helmut; Lacasa, Lucas

2018-02-23

We explore a combinatorial framework which efficiently quantifies the asymmetries between minima and maxima in local fluctuations of time series. We first showcase its performance by applying it to a battery of synthetic cases. We find rigorous results on some canonical dynamical models (stochastic processes with and without correlations, chaotic processes) complemented by extensive numerical simulations for a range of processes which indicate that the methodology correctly distinguishes different complex dynamics and outperforms state of the art metrics in several cases. Subsequently, we apply this methodology to real-world problems emerging across several disciplines including cases in neurobiology, finance and climate science. We conclude that differences between the statistics of local maxima and local minima in time series are highly informative of the complex underlying dynamics and a graph-theoretic extraction procedure allows to use these features for statistical learning purposes.

Video Analysis and Remote Digital Ethnography: Approaches to understanding user perspectives and processes involving healthcare information technology.

PubMed

Kushniruk, Andre W; Borycki, Elizabeth M

2015-01-01

Innovations in healthcare information systems promise to revolutionize and streamline healthcare processes worldwide. However, the complexity of these systems and the need to better understand issues related to human-computer interaction have slowed progress in this area. In this chapter the authors describe their work in using methods adapted from usability engineering, video ethnography and analysis of digital log files for improving our understanding of complex real-world healthcare interactions between humans and technology. The approaches taken are cost-effective and practical and can provide detailed ethnographic data on issues health professionals and consumers encounter while using systems as well as potential safety problems. The work is important in that it can be used in techno-anthropology to characterize complex user interactions with technologies and also to provide feedback into redesign and optimization of improved healthcare information systems.

Acute myeloid leukemia in the real world: why population-based registries are needed

PubMed Central

Lazarevic, Vladimir; Hörstedt, Ann-Sofi; Hagberg, Oskar; Höglund, Martin

2012-01-01

Population-based registries may provide data complementary to that from basic science and clinical intervention studies, all of which are essential for establishing recommendations for the management of patients in the real world. The same quality criteria apply for the evidence-based label, and both high representation and good data quality are crucial in registry studies. Registries with high coverage of the target population reduce the impact of selection on outcome and the subsequent problem with extrapolating data to nonstudied populations. Thus, data useful for clinical decision in situations not well covered by clinical studies can be provided. The potential clinical impact of data from population-based studies is exemplified with analyses from the Swedish Acute Leukemia Registry containing more than 3300 acute myeloid leukemia (AML) patients diagnosed between 1997 and 2006 with a median follow-up of 6.2 years on (1) the role of intensive combination chemotherapy for older patients with AML, (2) the impact of allogeneic stem cell transplantation on survival of younger patients with AML, and (3) the continuing problem with early deaths in acute promyelocytic leukemia. We also present the first Web-based dynamic graph showing the complex interaction between age, performance status, the proportion of patients given intensive treatment, early death rate, complete remission rate, use of allogeneic transplants, and overall survival in AML (non-AML). PMID:22383796

Using student feedback to improve student attitudes and mathematical confidence in a first year interdisciplinary quantitative course: from the ashes of disaster!

NASA Astrophysics Data System (ADS)

Everingham, Yvette; Gyuris, Emma; Sexton, Justin

2013-09-01

Today's scientist is faced with complex problems that require interdisciplinary solutions. Consequently, tertiary science educators have had to develop and deliver interdisciplinary science courses to equip students with the skills required to solve the evolving real-world challenges of today and tomorrow. There are few reported studies of the lessons learned from designing and delivering first year compulsory interdisciplinary science subjects at regional universities. Even fewer studies assess the impact that teaching interventions within interdisciplinary courses have on students' attitudes towards mathematics and technology, and mathematics anxiety. This paper discusses the feedback received from the first student cohort of a new compulsory, first year interdisciplinary science subject at a regional Australian university which resulted in curricular revisions. These revisions included a greater emphasis on the subject relevance and increased student support in tutorials. Assessment practices were also dramatically modified. The change in student attitudes and anxiety levels a priori and a posteriori to the interventions was measured quantitatively and qualitatively. Post-intervention, female and non-mathematics major students had grown in mathematical confidence and were less anxious. It is important that positive and negative research findings are reported, so science educators can learn from one another, and can better prepare their students for the challenges they will face in bringing interdisciplinary solutions to contemporary real-world problems.

Acute myeloid leukemia in the real world: why population-based registries are needed.

PubMed

Juliusson, Gunnar; Lazarevic, Vladimir; Hörstedt, Ann-Sofi; Hagberg, Oskar; Höglund, Martin

2012-04-26

Population-based registries may provide data complementary to that from basic science and clinical intervention studies, all of which are essential for establishing recommendations for the management of patients in the real world. The same quality criteria apply for the evidence-based label, and both high representation and good data quality are crucial in registry studies. Registries with high coverage of the target population reduce the impact of selection on outcome and the subsequent problem with extrapolating data to nonstudied populations. Thus, data useful for clinical decision in situations not well covered by clinical studies can be provided. The potential clinical impact of data from population-based studies is exemplified with analyses from the Swedish Acute Leukemia Registry containing more than 3300 acute myeloid leukemia (AML) patients diagnosed between 1997 and 2006 with a median follow-up of 6.2 years on (1) the role of intensive combination chemotherapy for older patients with AML, (2) the impact of allogeneic stem cell transplantation on survival of younger patients with AML, and (3) the continuing problem with early deaths in acute promyelocytic leukemia. We also present the first Web-based dynamic graph showing the complex interaction between age, performance status, the proportion of patients given intensive treatment, early death rate, complete remission rate, use of allogeneic transplants, and overall survival in AML (non-AML).

A hybrid neural learning algorithm using evolutionary learning and derivative free local search method.

PubMed

Ghosh, Ranadhir; Yearwood, John; Ghosh, Moumita; Bagirov, Adil

2006-06-01

In this paper we investigate a hybrid model based on the Discrete Gradient method and an evolutionary strategy for determining the weights in a feed forward artificial neural network. Also we discuss different variants for hybrid models using the Discrete Gradient method and an evolutionary strategy for determining the weights in a feed forward artificial neural network. The Discrete Gradient method has the advantage of being able to jump over many local minima and find very deep local minima. However, earlier research has shown that a good starting point for the discrete gradient method can improve the quality of the solution point. Evolutionary algorithms are best suited for global optimisation problems. Nevertheless they are cursed with longer training times and often unsuitable for real world application. For optimisation problems such as weight optimisation for ANNs in real world applications the dimensions are large and time complexity is critical. Hence the idea of a hybrid model can be a suitable option. In this paper we propose different fusion strategies for hybrid models combining the evolutionary strategy with the discrete gradient method to obtain an optimal solution much quicker. Three different fusion strategies are discussed: a linear hybrid model, an iterative hybrid model and a restricted local search hybrid model. Comparative results on a range of standard datasets are provided for different fusion hybrid models.

The Performance of Chinese Primary School Students on Realistic Arithmetic Word Problems

ERIC Educational Resources Information Center

Xin, Ziqiang; Lin, Chongde; Zhang, Li; Yan, Rong

2007-01-01

Compared with standard arithmetic word problems demanding only the direct use of number operations and computations, realistic problems are harder to solve because children need to incorporate "real-world" knowledge into their solutions. Using the realistic word problem testing materials developed by Verschaffel, De Corte, and Lasure…

LEGO Robotics: An Authentic Problem Solving Tool?

ERIC Educational Resources Information Center

Castledine, Alanah-Rei; Chalmers, Chris

2011-01-01

With the current curriculum focus on correlating classroom problem solving lessons to real-world contexts, are LEGO robotics an effective problem solving tool? This present study was designed to investigate this question and to ascertain what problem solving strategies primary students engaged with when working with LEGO robotics and whether the…

Problem Solving by Design

ERIC Educational Resources Information Center

Capobianco, Brenda M.; Tyrie, Nancy

2009-01-01

In a unique school-university partnership, methods students collaborated with fifth graders to use the engineering design process to build their problem-solving skills. By placing the problem in the context of a client having particular needs, the problem took on a real-world appeal that students found intriguing and inviting. In this article, the…

Examining Problem Solving in Physics-Intensive Ph.D. Research

ERIC Educational Resources Information Center

Leak, Anne E.; Rothwell, Susan L.; Olivera, Javier; Zwickl, Benjamin; Vosburg, Jarrett; Martin, Kelly Norris

2017-01-01

Problem-solving strategies learned by physics undergraduates should prepare them for real-world contexts as they transition from students to professionals. Yet, graduate students in physics-intensive research face problems that go beyond problem sets they experienced as undergraduates and are solved by different strategies than are typically…

Recent trends in robot-assisted therapy environments to improve real-life functional performance after stroke.

PubMed

Johnson, Michelle J

2006-12-18

Upper and lower limb robotic tools for neuro-rehabilitation are effective in reducing motor impairment but they are limited in their ability to improve real world function. There is a need to improve functional outcomes after robot-assisted therapy. Improvements in the effectiveness of these environments may be achieved by incorporating into their design and control strategies important elements key to inducing motor learning and cerebral plasticity such as mass-practice, feedback, task-engagement, and complex problem solving. This special issue presents nine articles. Novel strategies covered in this issue encourage more natural movements through the use of virtual reality and real objects and faster motor learning through the use of error feedback to guide acquisition of natural movements that are salient to real activities. In addition, several articles describe novel systems and techniques that use of custom and commercial games combined with new low-cost robot systems and a humanoid robot to embody the " supervisory presence" of the therapy as possible solutions to exercise compliance in under-supervised environments such as the home.

Recent trends in robot-assisted therapy environments to improve real-life functional performance after stroke

PubMed Central

Johnson, Michelle J

2006-01-01

Upper and lower limb robotic tools for neuro-rehabilitation are effective in reducing motor impairment but they are limited in their ability to improve real world function. There is a need to improve functional outcomes after robot-assisted therapy. Improvements in the effectiveness of these environments may be achieved by incorporating into their design and control strategies important elements key to inducing motor learning and cerebral plasticity such as mass-practice, feedback, task-engagement, and complex problem solving. This special issue presents nine articles. Novel strategies covered in this issue encourage more natural movements through the use of virtual reality and real objects and faster motor learning through the use of error feedback to guide acquisition of natural movements that are salient to real activities. In addition, several articles describe novel systems and techniques that use of custom and commercial games combined with new low-cost robot systems and a humanoid robot to embody the " supervisory presence" of the therapy as possible solutions to exercise compliance in under-supervised environments such as the home. PMID:17176474

Case Study on Optimal Routing in Logistics Network by Priority-based Genetic Algorithm

NASA Astrophysics Data System (ADS)

Wang, Xiaoguang; Lin, Lin; Gen, Mitsuo; Shiota, Mitsushige

Recently, research on logistics caught more and more attention. One of the important issues on logistics system is to find optimal delivery routes with the least cost for products delivery. Numerous models have been developed for that reason. However, due to the diversity and complexity of practical problem, the existing models are usually not very satisfying to find the solution efficiently and convinently. In this paper, we treat a real-world logistics case with a company named ABC Co. ltd., in Kitakyusyu Japan. Firstly, based on the natures of this conveyance routing problem, as an extension of transportation problem (TP) and fixed charge transportation problem (fcTP) we formulate the problem as a minimum cost flow (MCF) model. Due to the complexity of fcTP, we proposed a priority-based genetic algorithm (pGA) approach to find the most acceptable solution to this problem. In this pGA approach, a two-stage path decoding method is adopted to develop delivery paths from a chromosome. We also apply the pGA approach to this problem, and compare our results with the current logistics network situation, and calculate the improvement of logistics cost to help the management to make decisions. Finally, in order to check the effectiveness of the proposed method, the results acquired are compared with those come from the two methods/ software, such as LINDO and CPLEX.

Mathematics at Work in Alberta.

ERIC Educational Resources Information Center

Glanfield, Florence, Ed.; Tilroe, Daryle, Ed.

This document is designed to assist teachers by providing practical examples of real world applications of high school mathematics. Fifteen problems are presented that individuals in industry and business solve using mathematics. Each problem provides the contributor's name, suggested skills required to solve the problem, background information…

The Real-World Problem of Care Coordination: A Longitudinal Qualitative Study with Patients Living with Advanced Progressive Illness and Their Unpaid Caregivers

PubMed Central

Daveson, Barbara A.; Harding, Richard; Shipman, Cathy; Mason, Bruce L.; Epiphaniou, Eleni; Higginson, Irene J.; Ellis-Smith, Clare; Henson, Lesley; Munday, Dan; Nanton, Veronica; Dale, Jeremy R.; Boyd, Kirsty; Worth, Allison; Barclay, Stephen; Donaldson, Anne; Murray, Scott

2014-01-01

Objectives To develop a model of care coordination for patients living with advanced progressive illness and their unpaid caregivers, and to understand their perspective regarding care coordination. Design A prospective longitudinal, multi-perspective qualitative study involving a case-study approach. Methods Serial in-depth interviews were conducted, transcribed verbatim and then analyzed through open and axial coding in order to construct categories for three cases (sites). This was followed by continued thematic analysis to identify underlying conceptual coherence across all cases in order to produce one coherent care coordination model. Participants Fifty-six purposively sampled patients and 27 case-linked unpaid caregivers. Settings Three cases from contrasting primary, secondary and tertiary settings within Britain. Results Coordination is a deliberate cross-cutting action that involves high-quality, caring and well-informed staff, patients and unpaid caregivers who must work in partnership together across health and social care settings. For coordination to occur, it must be adequately resourced with efficient systems and services that communicate. Patients and unpaid caregivers contribute substantially to the coordination of their care, which is sometimes volunteered at a personal cost to them. Coordination is facilitated through flexible and patient-centered care, characterized by accurate and timely information communicated in a way that considers patients’ and caregivers’ needs, preferences, circumstances and abilities. Conclusions Within the midst of advanced progressive illness, coordination is a shared and complex intervention involving relational, structural and information components. Our study is one of the first to extensively examine patients’ and caregivers’ views about coordination, thus aiding conceptual fidelity. These findings can be used to help avoid oversimplifying a real-world problem, such as care coordination. Avoiding oversimplification can help with the development, evaluation and implementation of real-world coordination interventions for patients and their unpaid caregivers in the future. PMID:24788451

Creation of the Naturalistic Engagement in Secondary Tasks (NEST) distracted driving dataset.

PubMed

Owens, Justin M; Angell, Linda; Hankey, Jonathan M; Foley, James; Ebe, Kazutoshi

2015-09-01

Distracted driving has become a topic of critical importance to driving safety research over the past several decades. Naturalistic driving data offer a unique opportunity to study how drivers engage with secondary tasks in real-world driving; however, the complexities involved with identifying and coding relevant epochs of naturalistic data have limited its accessibility to the general research community. This project was developed to help address this problem by creating an accessible dataset of driver behavior and situational factors observed during distraction-related safety-critical events and baseline driving epochs, using the Strategic Highway Research Program 2 (SHRP2) naturalistic dataset. The new NEST (Naturalistic Engagement in Secondary Tasks) dataset was created using crashes and near-crashes from the SHRP2 dataset that were identified as including secondary task engagement as a potential contributing factor. Data coding included frame-by-frame video analysis of secondary task and hands-on-wheel activity, as well as summary event information. In addition, information about each secondary task engagement within the trip prior to the crash/near-crash was coded at a higher level. Data were also coded for four baseline epochs and trips per safety-critical event. 1,180 events and baseline epochs were coded, and a dataset was constructed. The project team is currently working to determine the most useful way to allow broad public access to the dataset. We anticipate that the NEST dataset will be extraordinarily useful in allowing qualified researchers access to timely, real-world data concerning how drivers interact with secondary tasks during safety-critical events and baseline driving. The coded dataset developed for this project will allow future researchers to have access to detailed data on driver secondary task engagement in the real world. It will be useful for standalone research, as well as for integration with additional SHRP2 data to enable the conduct of more complex research. Copyright © 2015 Elsevier Ltd and National Safety Council. All rights reserved.

Stream computing for biomedical signal processing: A QRS complex detection case-study.

PubMed

Murphy, B M; O'Driscoll, C; Boylan, G B; Lightbody, G; Marnane, W P

2015-01-01

Recent developments in "Big Data" have brought significant gains in the ability to process large amounts of data on commodity server hardware. Stream computing is a relatively new paradigm in this area, addressing the need to process data in real time with very low latency. While this approach has been developed for dealing with large scale data from the world of business, security and finance, there is a natural overlap with clinical needs for physiological signal processing. In this work we present a case study of streams processing applied to a typical physiological signal processing problem: QRS detection from ECG data.

Size does Matter

NASA Astrophysics Data System (ADS)

Vespignani, Alessandro

From schools of fish and flocks of birds, to digital networks and self-organizing biopolymers, our understanding of spontaneously emergent phenomena, self-organization, and critical behavior is in large part due to complex systems science. The complex systems approach is indeed a very powerful conceptual framework to shed light on the link between the microscopic dynamical evolution of the basic elements of the system and the emergence of oscopic phenomena; often providing evidence for mathematical principles that go beyond the particulars of the individual system, thus hinting to general modeling principles. By killing the myth of the ant queen and shifting the focus on the dynamical interaction across the elements of the systems, complex systems science has ushered our way into the conceptual understanding of many phenomena at the core of major scientific and social challenges such as the emergence of consensus, social opinion dynamics, conflicts and cooperation, contagion phenomena. For many years though, these complex systems approaches to real-world problems were often suffering from being oversimplified and not grounded on actual data...

Meet Mai-Anh Ha | NREL

Science.gov Websites

find the best versions of the materials to guide experimentalists. "The world is complex," specifics," she says, "and then you can go from modeling into real-world applications." All to then choke me in my car," she says. Instead, she envisions a world filled with fuel cell cars

New fuzzy support vector machine for the class imbalance problem in medical datasets classification.

PubMed

Gu, Xiaoqing; Ni, Tongguang; Wang, Hongyuan

2014-01-01

In medical datasets classification, support vector machine (SVM) is considered to be one of the most successful methods. However, most of the real-world medical datasets usually contain some outliers/noise and data often have class imbalance problems. In this paper, a fuzzy support machine (FSVM) for the class imbalance problem (called FSVM-CIP) is presented, which can be seen as a modified class of FSVM by extending manifold regularization and assigning two misclassification costs for two classes. The proposed FSVM-CIP can be used to handle the class imbalance problem in the presence of outliers/noise, and enhance the locality maximum margin. Five real-world medical datasets, breast, heart, hepatitis, BUPA liver, and pima diabetes, from the UCI medical database are employed to illustrate the method presented in this paper. Experimental results on these datasets show the outperformed or comparable effectiveness of FSVM-CIP.

Are We Ready for Real-world Neuroscience?

PubMed

Matusz, Pawel J; Dikker, Suzanne; Huth, Alexander G; Perrodin, Catherine

2018-06-19

Real-world environments are typically dynamic, complex, and multisensory in nature and require the support of top-down attention and memory mechanisms for us to be able to drive a car, make a shopping list, or pour a cup of coffee. Fundamental principles of perception and functional brain organization have been established by research utilizing well-controlled but simplified paradigms with basic stimuli. The last 30 years ushered a revolution in computational power, brain mapping, and signal processing techniques. Drawing on those theoretical and methodological advances, over the years, research has departed more and more from traditional, rigorous, and well-understood paradigms to directly investigate cognitive functions and their underlying brain mechanisms in real-world environments. These investigations typically address the role of one or, more recently, multiple attributes of real-world environments. Fundamental assumptions about perception, attention, or brain functional organization have been challenged-by studies adapting the traditional paradigms to emulate, for example, the multisensory nature or varying relevance of stimulation or dynamically changing task demands. Here, we present the state of the field within the emerging heterogeneous domain of real-world neuroscience. To be precise, the aim of this Special Focus is to bring together a variety of the emerging "real-world neuroscientific" approaches. These approaches differ in their principal aims, assumptions, or even definitions of "real-world neuroscience" research. Here, we showcase the commonalities and distinctive features of the different "real-world neuroscience" approaches. To do so, four early-career researchers and the speakers of the Cognitive Neuroscience Society 2017 Meeting symposium under the same title answer questions pertaining to the added value of such approaches in bringing us closer to accurate models of functional brain organization and cognitive functions.

Solving multi-objective job shop scheduling problems using a non-dominated sorting genetic algorithm

NASA Astrophysics Data System (ADS)

Piroozfard, Hamed; Wong, Kuan Yew

2015-05-01

The efforts of finding optimal schedules for the job shop scheduling problems are highly important for many real-world industrial applications. In this paper, a multi-objective based job shop scheduling problem by simultaneously minimizing makespan and tardiness is taken into account. The problem is considered to be more complex due to the multiple business criteria that must be satisfied. To solve the problem more efficiently and to obtain a set of non-dominated solutions, a meta-heuristic based non-dominated sorting genetic algorithm is presented. In addition, task based representation is used for solution encoding, and tournament selection that is based on rank and crowding distance is applied for offspring selection. Swapping and insertion mutations are employed to increase diversity of population and to perform intensive search. To evaluate the modified non-dominated sorting genetic algorithm, a set of modified benchmarking job shop problems obtained from the OR-Library is used, and the results are considered based on the number of non-dominated solutions and quality of schedules obtained by the algorithm.

Contextualized Mathematics Problems and Transfer of Knowledge: Establishing Problem Spaces and Boundaries

ERIC Educational Resources Information Center

McGraw, Rebecca; Patterson, Cody L.

2017-01-01

In this study, we examine how inservice secondary mathematics teachers working together on a contextualized problem negotiate issues arising from the ill-structured nature of the problem such as what assumptions one may make, what real-world considerations should be taken into account, and what constitutes a satisfactory solution. We conceptualize…

Elements of Problem-Based Learning: Suggestions for Implementation in the Asynchronous Environment

ERIC Educational Resources Information Center

Nelson, Erik

2010-01-01

Problem-based learning, or PBL, is a student-centered instructional approach that is derived from constructivist epistemology. It is based upon ill-structured real-world problems with the goal of strengthening and developing critical thinking and problem-solving skills in learners. Initially utilized in medical schools to strengthen diagnostic…

Learning and Parallelization Boost Constraint Search

ERIC Educational Resources Information Center

Yun, Xi

2013-01-01

Constraint satisfaction problems are a powerful way to abstract and represent academic and real-world problems from both artificial intelligence and operations research. A constraint satisfaction problem is typically addressed by a sequential constraint solver running on a single processor. Rather than construct a new, parallel solver, this work…

A geostatistical approach to the change-of-support problem and variable-support data fusion in spatial analysis

NASA Astrophysics Data System (ADS)

Wang, Jun; Wang, Yang; Zeng, Hui

2016-01-01

A key issue to address in synthesizing spatial data with variable-support in spatial analysis and modeling is the change-of-support problem. We present an approach for solving the change-of-support and variable-support data fusion problems. This approach is based on geostatistical inverse modeling that explicitly accounts for differences in spatial support. The inverse model is applied here to produce both the best predictions of a target support and prediction uncertainties, based on one or more measurements, while honoring measurements. Spatial data covering large geographic areas often exhibit spatial nonstationarity and can lead to computational challenge due to the large data size. We developed a local-window geostatistical inverse modeling approach to accommodate these issues of spatial nonstationarity and alleviate computational burden. We conducted experiments using synthetic and real-world raster data. Synthetic data were generated and aggregated to multiple supports and downscaled back to the original support to analyze the accuracy of spatial predictions and the correctness of prediction uncertainties. Similar experiments were conducted for real-world raster data. Real-world data with variable-support were statistically fused to produce single-support predictions and associated uncertainties. The modeling results demonstrate that geostatistical inverse modeling can produce accurate predictions and associated prediction uncertainties. It is shown that the local-window geostatistical inverse modeling approach suggested offers a practical way to solve the well-known change-of-support problem and variable-support data fusion problem in spatial analysis and modeling.

Complexity management theory: motivation for ideological rigidity and social conflict.

PubMed

Peterson, Jordan B; Flanders, Joseph L

2002-06-01

We are doomed to formulate conceptual structures that are much simpler than the complex phenomena they are attempting to account for. These simple conceptual structures shield us, pragmatically, from real-world complexity, but also fail, frequently, as some aspect of what we did not take into consideration makes itself manifest. The failure of our concepts dysregulates our emotions and generates anxiety, necessarily, as the unconstrained world is challenging and dangerous. Such dysregulation can turn us into rigid, totalitarian dogmatists, as we strive to maintain the structure of our no longer valid beliefs. Alternatively, we can face the underlying complexity of experience, voluntarily, gather new information, and recast and reconfigure the structures that underly our habitable worlds.

Complex Problem Solving: What It Is and What It Is Not

PubMed Central

Dörner, Dietrich; Funke, Joachim

2017-01-01

Computer-simulated scenarios have been part of psychological research on problem solving for more than 40 years. The shift in emphasis from simple toy problems to complex, more real-life oriented problems has been accompanied by discussions about the best ways to assess the process of solving complex problems. Psychometric issues such as reliable assessments and addressing correlations with other instruments have been in the foreground of these discussions and have left the content validity of complex problem solving in the background. In this paper, we return the focus to content issues and address the important features that define complex problems. PMID:28744242

Investigating the Wicked Problems of (Un)sustainability Through Three Case Studies Around the Water-Energy-Food Nexus

NASA Astrophysics Data System (ADS)

Metzger, E. P.; Curren, R. R.

2016-12-01

Effective engagement with the problems of sustainability begins with an understanding of the nature of the challenges. The entanglement of interacting human and Earth systems produces solution-resistant dilemmas that are often portrayed as wicked problems. As introduced by urban planners Rittel and Webber (1973), wicked problems are "dynamically complex, ill-structured, public problems" arising from complexity in both biophysical and socio-economic systems. The wicked problem construct is still in wide use across diverse contexts, disciplines, and sectors. Discourse about wicked problems as related to sustainability is often connected to discussion of complexity or complex systems. In preparation for life and work in an uncertain, dynamic and hyperconnected world, students need opportunities to investigate real problems that cross social, political and disciplinary divides. They need to grapple with diverse perspectives and values, and collaborate with others to devise potential solutions. Such problems are typically multi-casual and so intertangled with other problems that they cannot be resolved using the expertise and analytical tools of any single discipline, individual, or organization. We have developed a trio of illustrative case studies that focus on energy, water and food, because these resources are foundational, interacting, and causally connected in a variety of ways with climate destabilization. The three interrelated case studies progress in scale from the local and regional, to the national and international and include: 1) the 2010 Gulf of Mexico oil spill with examination of the multiple immediate and root causes of the disaster, its ecological, social, and economic impacts, and the increasing risk and declining energy return on investment associated with the relentless quest for fossil fuels; 2) development of Australia's innovative National Water Management System; and 3) changing patterns of food production and the intertwined challenge of managing transnational water resources in the rapidly growing Mekong Region of Southeast Asia. .

A Hybrid Constraint Representation and Reasoning Framework

NASA Technical Reports Server (NTRS)

Golden, Keith; Pang, Wanlin

2004-01-01

In this paper, we introduce JNET, a novel constraint representation and reasoning framework that supports procedural constraints and constraint attachments, providing a flexible way of integrating the constraint system with a runtime software environment and improving its applicability. We describe how JNET is applied to a real-world problem - NASA's Earth-science data processing domain, and demonstrate how JNET can be extended, without any knowledge of how it is implemented, to meet the growing demands of real-world applications.

Agent-based modeling: Methods and techniques for simulating human systems

PubMed Central

Bonabeau, Eric

2002-01-01

Agent-based modeling is a powerful simulation modeling technique that has seen a number of applications in the last few years, including applications to real-world business problems. After the basic principles of agent-based simulation are briefly introduced, its four areas of application are discussed by using real-world applications: flow simulation, organizational simulation, market simulation, and diffusion simulation. For each category, one or several business applications are described and analyzed. PMID:12011407

From random microstructures to representative volume elements

NASA Astrophysics Data System (ADS)

Zeman, J.; Šejnoha, M.

2007-06-01

A unified treatment of random microstructures proposed in this contribution opens the way to efficient solutions of large-scale real world problems. The paper introduces a notion of statistically equivalent periodic unit cell (SEPUC) that replaces in a computational step the actual complex geometries on an arbitrary scale. A SEPUC is constructed such that its morphology conforms with images of real microstructures. Here, the appreciated two-point probability function and the lineal path function are employed to classify, from the statistical point of view, the geometrical arrangement of various material systems. Examples of statistically equivalent unit cells constructed for a unidirectional fibre tow, a plain weave textile composite and an irregular-coursed masonry wall are given. A specific result promoting the applicability of the SEPUC as a tool for the derivation of homogenized effective properties that are subsequently used in an independent macroscopic analysis is also presented.

Real-World Evidence In Support Of Precision Medicine: Clinico-Genomic Cancer Data As A Case Study.

PubMed

Agarwala, Vineeta; Khozin, Sean; Singal, Gaurav; O'Connell, Claire; Kuk, Deborah; Li, Gerald; Gossai, Anala; Miller, Vincent; Abernethy, Amy P

2018-05-01

The majority of US adult cancer patients today are diagnosed and treated outside the context of any clinical trial (that is, in the real world). Although these patients are not part of a research study, their clinical data are still recorded. Indeed, data captured in electronic health records form an ever-growing, rich digital repository of longitudinal patient experiences, treatments, and outcomes. Likewise, genomic data from tumor molecular profiling are increasingly guiding oncology care. Linking real-world clinical and genomic data, as well as information from other co-occurring data sets, could create study populations that provide generalizable evidence for precision medicine interventions. However, the infrastructure required to link, ensure quality, and rapidly learn from such composite data is complex. We outline the challenges and describe a novel approach to building a real-world clinico-genomic database of patients with cancer. This work represents a case study in how data collected during routine patient care can inform precision medicine efforts for the population at large. We suggest that health policies can promote innovation by defining appropriate uses of real-world evidence, establishing data standards, and incentivizing data sharing.

Incorporating Problem-Based Experiential Teaching in the Agricultural Curriculum.

ERIC Educational Resources Information Center

Salvador, R. J.; And Others

1995-01-01

A forestry and agronomy course at Iowa State University incorporates problem-based team projects on real-world situations as a means of providing students with integrative and meaningful experiential learning. Student evaluations of these courses indicate that students recognize and appreciate the integrative nature of the problem-based team…

Effectiveness of Problem-Based Learning in Introductory Business Courses

ERIC Educational Resources Information Center

Hartman, Katherine B.; Moberg, Christopher R.; Lambert, Jamie M.

2013-01-01

Problem-based learning (PBL) is an instructional approach that provides learners with opportunities to identify solutions to ill-structured, real-world problems. Previous research provides evidence to support claims about the positive effects of PBL on cognitive skill development and knowledge retention. This study contributes to existing…

Caffeine enhances real-world language processing: evidence from a proofreading task.

PubMed

Brunyé, Tad T; Mahoney, Caroline R; Rapp, David N; Ditman, Tali; Taylor, Holly A

2012-03-01

Caffeine has become the most prevalently consumed psychostimulant in the world, but its influences on daily real-world functioning are relatively unknown. The present work investigated the effects of caffeine (0 mg, 100 mg, 200 mg, 400 mg) on a commonplace language task that required readers to identify and correct 4 error types in extended discourse: simple local errors (misspelling 1- to 2-syllable words), complex local errors (misspelling 3- to 5-syllable words), simple global errors (incorrect homophones), and complex global errors (incorrect subject-verb agreement and verb tense). In 2 placebo-controlled, double-blind studies using repeated-measures designs, we found higher detection and repair rates for complex global errors, asymptoting at 200 mg in low consumers (Experiment 1) and peaking at 400 mg in high consumers (Experiment 2). In both cases, covariate analyses demonstrated that arousal state mediated the relationship between caffeine consumption and the detection and repair of complex global errors. Detection and repair rates for the other 3 error types were not affected by caffeine consumption. Taken together, we demonstrate that caffeine has differential effects on error detection and repair as a function of dose and error type, and this relationship is closely tied to caffeine's effects on subjective arousal state. These results support the notion that central nervous system stimulants may enhance global processing of language-based materials and suggest that such effects may originate in caffeine-related right hemisphere brain processes. Implications for understanding the relationships between caffeine consumption and real-world cognitive functioning are discussed. PsycINFO Database Record (c) 2012 APA, all rights reserved.

Review of battery powered embedded systems design for mission-critical low-power applications

NASA Astrophysics Data System (ADS)

Malewski, Matthew; Cowell, David M. J.; Freear, Steven

2018-06-01

The applications and uses of embedded systems is increasingly pervasive. Mission and safety critical systems relying on embedded systems pose specific challenges. Embedded systems is a multi-disciplinary domain, involving both hardware and software. Systems need to be designed in a holistic manner so that they are able to provide the desired reliability and minimise unnecessary complexity. The large problem landscape means that there is no one solution that fits all applications of embedded systems. With the primary focus of these mission and safety critical systems being functionality and reliability, there can be conflicts with business needs, and this can introduce pressures to reduce cost at the expense of reliability and functionality. This paper examines the challenges faced by battery powered systems, and then explores at more general problems, and several real-world embedded systems.

Power law-based local search in spider monkey optimisation for lower order system modelling

NASA Astrophysics Data System (ADS)

Sharma, Ajay; Sharma, Harish; Bhargava, Annapurna; Sharma, Nirmala

2017-01-01

The nature-inspired algorithms (NIAs) have shown efficiency to solve many complex real-world optimisation problems. The efficiency of NIAs is measured by their ability to find adequate results within a reasonable amount of time, rather than an ability to guarantee the optimal solution. This paper presents a solution for lower order system modelling using spider monkey optimisation (SMO) algorithm to obtain a better approximation for lower order systems and reflects almost original higher order system's characteristics. Further, a local search strategy, namely, power law-based local search is incorporated with SMO. The proposed strategy is named as power law-based local search in SMO (PLSMO). The efficiency, accuracy and reliability of the proposed algorithm is tested over 20 well-known benchmark functions. Then, the PLSMO algorithm is applied to solve the lower order system modelling problem.

Quantum optimization for training support vector machines.

PubMed

Anguita, Davide; Ridella, Sandro; Rivieccio, Fabio; Zunino, Rodolfo

2003-01-01

Refined concepts, such as Rademacher estimates of model complexity and nonlinear criteria for weighting empirical classification errors, represent recent and promising approaches to characterize the generalization ability of Support Vector Machines (SVMs). The advantages of those techniques lie in both improving the SVM representation ability and yielding tighter generalization bounds. On the other hand, they often make Quadratic-Programming algorithms no longer applicable, and SVM training cannot benefit from efficient, specialized optimization techniques. The paper considers the application of Quantum Computing to solve the problem of effective SVM training, especially in the case of digital implementations. The presented research compares the behavioral aspects of conventional and enhanced SVMs; experiments in both a synthetic and real-world problems support the theoretical analysis. At the same time, the related differences between Quadratic-Programming and Quantum-based optimization techniques are considered.

Scalable Nonparametric Low-Rank Kernel Learning Using Block Coordinate Descent.

PubMed

Hu, En-Liang; Kwok, James T

2015-09-01

Nonparametric kernel learning (NPKL) is a flexible approach to learn the kernel matrix directly without assuming any parametric form. It can be naturally formulated as a semidefinite program (SDP), which, however, is not very scalable. To address this problem, we propose the combined use of low-rank approximation and block coordinate descent (BCD). Low-rank approximation avoids the expensive positive semidefinite constraint in the SDP by replacing the kernel matrix variable with V(T)V, where V is a low-rank matrix. The resultant nonlinear optimization problem is then solved by BCD, which optimizes each column of V sequentially. It can be shown that the proposed algorithm has nice convergence properties and low computational complexities. Experiments on a number of real-world data sets show that the proposed algorithm outperforms state-of-the-art NPKL solvers.

Task directed sensing

NASA Technical Reports Server (NTRS)

Firby, R. James

1990-01-01

High-level robot control research must confront the limitations imposed by real sensors if robots are to be controlled effectively in the real world. In particular, sensor limitations make it impossible to maintain a complete, detailed world model of the situation surrounding the robot. To address the problems involved in planning with the resulting incomplete and uncertain world models, traditional robot control architectures must be altered significantly. Task-directed sensing and control is suggested as a way of coping with world model limitations by focusing sensing and analysis resources on only those parts of the world relevant to the robot's active goals. The RAP adaptive execution system is used as an example of a control architecture designed to deploy sensing resources in this way to accomplish both action and knowledge goals.

Input Devices and Interaction Techniques for VR-Enhanced Medicine

NASA Astrophysics Data System (ADS)

Gallo, Luigi; Pietro, Giuseppe De

Virtual Reality (VR) technologies make it possible to reproduce faithfully real life events in computer-generated scenarios. This approach has the potential to simplify the way people solve problems, since they can take advantage of their real life experiences while interacting in synthetic worlds.

Eating behavior: lessons from the real world of humans.

PubMed

de Castro, J M

2000-10-01

Food intake by normal humans has been investigated both in the laboratory and under free-living conditions in the natural environment. For measurement of real-world intake, the diet-diary technique is imperfect and tends to underestimate actual intakes but it appears to be sensitive, can detect subtle influences on eating behavior, and produces reliable and valid measures. Research studies in the real world show the multivariate richness of the natural environment, which allows investigation of the complexities of intake regulation, and even causation can be investigated. Real-world research can overcome some of the weaknesses of laboratory studies, where constraints on eating are often removed or missing, facilitatory influences on eating are often controlled or eliminated, the importance of variables can be overestimated, and important influences can be missed because of the short durations of the studies. Real-world studies have shown a wide array of physiologic, psychological, and social variables that can have potent and immediate effects on intake. Compensatory mechanisms, including some that operate with a 2- to 3-d delay, adjust for prior excesses. Heredity affects all aspect of food-intake regulation, from the determination of body size to the subtleties of the individual preferences and social proclivities and the extent to which environmental factors affect the individual. Hence, real-world research teaches valuable lessons, and much more is needed to complement laboratory studies.

An Efficient Pattern Mining Approach for Event Detection in Multivariate Temporal Data

PubMed Central

Batal, Iyad; Cooper, Gregory; Fradkin, Dmitriy; Harrison, James; Moerchen, Fabian; Hauskrecht, Milos

2015-01-01

This work proposes a pattern mining approach to learn event detection models from complex multivariate temporal data, such as electronic health records. We present Recent Temporal Pattern mining, a novel approach for efficiently finding predictive patterns for event detection problems. This approach first converts the time series data into time-interval sequences of temporal abstractions. It then constructs more complex time-interval patterns backward in time using temporal operators. We also present the Minimal Predictive Recent Temporal Patterns framework for selecting a small set of predictive and non-spurious patterns. We apply our methods for predicting adverse medical events in real-world clinical data. The results demonstrate the benefits of our methods in learning accurate event detection models, which is a key step for developing intelligent patient monitoring and decision support systems. PMID:26752800

The Role of Temporal Trends in Growing Networks

PubMed Central

Ruppin, Eytan; Shavitt, Yuval

2016-01-01

The rich get richer principle, manifested by the Preferential attachment (PA) mechanism, is widely considered one of the major factors in the growth of real-world networks. PA stipulates that popular nodes are bound to be more attractive than less popular nodes; for example, highly cited papers are more likely to garner further citations. However, it overlooks the transient nature of popularity, which is often governed by trends. Here, we show that in a wide range of real-world networks the recent popularity of a node, i.e., the extent by which it accumulated links recently, significantly influences its attractiveness and ability to accumulate further links. We proceed to model this observation with a natural extension to PA, named Trending Preferential Attachment (TPA), in which edges become less influential as they age. TPA quantitatively parametrizes a fundamental network property, namely the network’s tendency to trends. Through TPA, we find that real-world networks tend to be moderately to highly trendy. Networks are characterized by different susceptibilities to trends, which determine their structure to a large extent. Trendy networks display complex structural traits, such as modular community structure and degree-assortativity, occurring regularly in real-world networks. In summary, this work addresses an inherent trait of complex networks, which greatly affects their growth and structure, and develops a unified model to address its interaction with preferential attachment. PMID:27486847

Toward a Model for Intercultural Communication in Simulations

ERIC Educational Resources Information Center

Wiggins, Bradley E.

2012-01-01

The growing need for intercultural literacy in an increasingly interconnected and computer-mediated world contrasts with the dearth of investigation in best practices when designing simulations aimed at improving intercultural communication. Synthetic cultures inspired by real-world cultural traits, problem-based learning, and a social…

Real change in the real world: an achievable goal.

PubMed

Friedman, Robert M

2010-03-01

This commentary builds on the papers presented at the Vanderbilt Conference by emphasizing the importance of better understanding the process of change-making if real change in the real world is to be achieved. The commentary reviews several frameworks and research findings related to achieving large-scale sustainable change that benefits children and families. It calls for the application of systems thinking as a complement to the more micro-level research that was presented at the Vanderbilt conference. Such an approach would have implications for framing of the issue, for the strategies that are taken to try to achieve change, and for research/evaluation methods for studying complex, dynamic, nonlinear systems.

Building an intelligent tutoring system for procedural domains

NASA Technical Reports Server (NTRS)

Warinner, Andrew; Barbee, Diann; Brandt, Larry; Chen, Tom; Maguire, John

1990-01-01

Jobs that require complex skills that are too expensive or dangerous to develop often use simulators in training. The strength of a simulator is its ability to mimic the 'real world', allowing students to explore and experiment. A good simulation helps the student develop a 'mental model' of the real world. The closer the simulation is to 'real life', the less difficulties there are transferring skills and mental models developed on the simulator to the real job. As graphics workstations increase in power and become more affordable they become attractive candidates for developing computer-based simulations for use in training. Computer based simulations can make training more interesting and accessible to the student.

Using Video Prompting to Teach Mathematical Problem Solving of Real-World Video-Simulation Problems

ERIC Educational Resources Information Center

Saunders, Alicia F.; Spooner, Fred; Ley Davis, Luann

2018-01-01

Mathematical problem solving is necessary in many facets of everyday life, yet little research exists on how to teach students with more severe disabilities higher order mathematics like problem solving. Using a multiple probe across participants design, three middle school students with moderate intellectual disability (ID) were taught to solve…

Laboratory Based Case Studies: Closer to the Real World

ERIC Educational Resources Information Center

Dinan, Frank J.

2005-01-01

Case-based laboratories offer students the chance to approximate real science. Based on interesting stories that pose problems requiring experimental solutions, they avoid the cookbook approach characteristic of traditional undergraduate laboratory instruction. Instead, case-based laboratories challenge students to develop, as much as possible,…

Object classification for obstacle avoidance

NASA Astrophysics Data System (ADS)

Regensburger, Uwe; Graefe, Volker

1991-03-01

Object recognition is necessary for any mobile robot operating autonomously in the real world. This paper discusses an object classifier based on a 2-D object model. Obstacle candidates are tracked and analyzed false alarms generated by the object detector are recognized and rejected. The methods have been implemented on a multi-processor system and tested in real-world experiments. They work reliably under favorable conditions but sometimes problems occur e. g. when objects contain many features (edges) or move in front of structured background.

United Space Alliance LLC Parachute Refurbishment Facility Model

NASA Technical Reports Server (NTRS)

Esser, Valerie; Pessaro, Martha; Young, Angela

2007-01-01

The Parachute Refurbishment Facility Model was created to reflect the flow of hardware through the facility using anticipated start and delivery times from a project level IV schedule. Distributions for task times were built using historical build data for SFOC work and new data generated for CLV/ARES task times. The model currently processes 633 line items from 14 SFOC builds for flight readiness, 16 SFOC builds returning from flight for defoul, wash, and dry operations, 12 builds for CLV manufacturing operations, and 1 ARES 1X build. Modeling the planned workflow through the PRF is providing a reliable way to predict the capability of the facility as well as the manpower resource need. Creating a real world process allows for real world problems to be identified and potential workarounds to be implemented in a safe, simulated world before taking it to the next step, implementation in the real world.

How far we are from the complete knowledge: Complexity of knowledge acquisition in Dempster-Shafer approach

NASA Technical Reports Server (NTRS)

Chokr, Bassam A.; Kreinovich, Vladik YA.

1991-01-01

When a knowledge base represents the experts' uncertainty, then it is reasonable to ask how far we are from the complete knowledge, that is, how many more questions do we have to ask (to these experts, to nature by means of experimenting, etc) in order to attain the complete knowledge. Of course, since we do not know what the real world is, we cannot get the precise number of questions from the very beginning: it is quite possible, for example, that we ask the right question first and thus guess the real state of the world after the first question. So we have to estimate this number and use this estimate as a natural measure of completeness for a given knowledge base. We give such estimates for Dempster-Shafer formalism. Namely, we show that this average number of questions can be obtained by solving a simple mathematical optimization problem. In principle this characteristic is not always sufficient to express the fact that sometimes we have more knowledge. For example, it has the same value if we have an event with two possible outcomes and nothing else is known, and if there is an additional knowledge that the probability of every outcome is 0.5. We'll show that from the practical viewpoint this is not a problem, because the difference between the necessary number of questions in both cases is practically negligible.

Efficiently modeling neural networks on massively parallel computers

NASA Technical Reports Server (NTRS)

Farber, Robert M.

1993-01-01

Neural networks are a very useful tool for analyzing and modeling complex real world systems. Applying neural network simulations to real world problems generally involves large amounts of data and massive amounts of computation. To efficiently handle the computational requirements of large problems, we have implemented at Los Alamos a highly efficient neural network compiler for serial computers, vector computers, vector parallel computers, and fine grain SIMD computers such as the CM-2 connection machine. This paper describes the mapping used by the compiler to implement feed-forward backpropagation neural networks for a SIMD (Single Instruction Multiple Data) architecture parallel computer. Thinking Machines Corporation has benchmarked our code at 1.3 billion interconnects per second (approximately 3 gigaflops) on a 64,000 processor CM-2 connection machine (Singer 1990). This mapping is applicable to other SIMD computers and can be implemented on MIMD computers such as the CM-5 connection machine. Our mapping has virtually no communications overhead with the exception of the communications required for a global summation across the processors (which has a sub-linear runtime growth on the order of O(log(number of processors)). We can efficiently model very large neural networks which have many neurons and interconnects and our mapping can extend to arbitrarily large networks (within memory limitations) by merging the memory space of separate processors with fast adjacent processor interprocessor communications. This paper will consider the simulation of only feed forward neural network although this method is extendable to recurrent networks.

Making the Most of Modeling Tasks

ERIC Educational Resources Information Center

Wernet, Jamie L.; Lawrence, Kevin A.; Gilbertson, Nicholas J.

2015-01-01

While there is disagreement among mathematics educators about some aspects of its meaning, mathematical modeling generally involves taking a real-world scenario and translating it into the mathematical world (Niss, Blum, and Galbraith 2007). The complete modeling process involves describing situations posed in problems with mathematical concepts,…

Seven Billion People: Fostering Productive Struggle

ERIC Educational Resources Information Center

Murawska, Jaclyn M.

2018-01-01

How can a cognitively demanding real-world task such as the Seven Billion People problem promote productive struggle "and" help shape students' mathematical dispositions? Driving home from school one evening, Jaclyn Murawska heard a commentator on the radio announce three statements: (1) experts had determined that the world population…

Walkable Worlds give a Rich Self-Similar Structure to the Real Line

NASA Astrophysics Data System (ADS)

Rosinger, Elemér E.

2010-05-01

It is a rather universal tacit and unquestioned belief—and even more so among physicists—that there is one and only one real line, namely, given by the coodinatisation of Descartes through the usual field R of real numbers. Such a dramatically limiting and thus harmful belief comes, unknown to equally many, from the similarly tacit acceptance of the ancient Archimedean Axiom in Euclid's Geometry. The consequence of that belief is a similar belief in the uniqueness of the coordinatization of the plane by the usual field C of complex numbers, and therefore, of the various spaces, manifolds, etc., be they finite or infinite dimensional, constructed upon the real or complex numbers, including the Hilbert spaces used in Quantum Mechanics. A near total lack of awareness follows therefore about the rich self-similar structure of other possible coordinatisations of the real line, possibilities given by various linearly ordered scalar fields obtained through the ultrapower construction. Such fields contain as a rather small subset the usual field R of real numbers. The concept of walkable world, which has highly intuitive and pragmatic algebraic and geometric meaning, illustrates the mentioned rich self-similar structure.

Learning Activity Predictors from Sensor Data: Algorithms, Evaluation, and Applications.

PubMed

Minor, Bryan; Doppa, Janardhan Rao; Cook, Diane J

2017-12-01

Recent progress in Internet of Things (IoT) platforms has allowed us to collect large amounts of sensing data. However, there are significant challenges in converting this large-scale sensing data into decisions for real-world applications. Motivated by applications like health monitoring and intervention and home automation we consider a novel problem called Activity Prediction , where the goal is to predict future activity occurrence times from sensor data. In this paper, we make three main contributions. First, we formulate and solve the activity prediction problem in the framework of imitation learning and reduce it to a simple regression learning problem. This approach allows us to leverage powerful regression learners that can reason about the relational structure of the problem with negligible computational overhead. Second, we present several metrics to evaluate activity predictors in the context of real-world applications. Third, we evaluate our approach using real sensor data collected from 24 smart home testbeds. We also embed the learned predictor into a mobile-device-based activity prompter and evaluate the app for 9 participants living in smart homes. Our results indicate that our activity predictor performs better than the baseline methods, and offers a simple approach for predicting activities from sensor data.

Right-side-stretched multifractal spectra indicate small-worldness in networks

NASA Astrophysics Data System (ADS)

Oświȩcimka, Paweł; Livi, Lorenzo; Drożdż, Stanisław

2018-04-01

Complex network formalism allows to explain the behavior of systems composed by interacting units. Several prototypical network models have been proposed thus far. The small-world model has been introduced to mimic two important features observed in real-world systems: i) local clustering and ii) the possibility to move across a network by means of long-range links that significantly reduce the characteristic path length. A natural question would be whether there exist several ;types; of small-world architectures, giving rise to a continuum of models with properties (partially) shared with other models belonging to different network families. Here, we take advantage of the interplay between network theory and time series analysis and propose to investigate small-world signatures in complex networks by analyzing multifractal characteristics of time series generated from such networks. In particular, we suggest that the degree of right-sided asymmetry of multifractal spectra is linked with the degree of small-worldness present in networks. This claim is supported by numerical simulations performed on several parametric models, including prototypical small-world networks, scale-free, fractal and also real-world networks describing protein molecules. Our results also indicate that right-sided asymmetry emerges with the presence of the following topological properties: low edge density, low average shortest path, and high clustering coefficient.

Reinventing the Wheel: Design and Problem Solving

ERIC Educational Resources Information Center

Blasetti, Sean M.

2010-01-01

This article describes a design problem that not only takes students through the technological design process, but it also provides them with real-world problem-solving experience as it relates to the manufacturing and engineering fields. It begins with a scenario placing the student as a custom wheel designer for an automotive manufacturing…

Theme: The 21st Century Adult Learner

ERIC Educational Resources Information Center

Lopez Brown, P.

2017-01-01

Problem-based learning is an innovative educational approach that is gaining prominence in higher education using "real world" problems or situations as a context for learning. The present study explored the use of problem-based learning with teacher trainees of the University of Belize. Using a concurrent mixed method design with 74…

A General Chemistry Assignment Analyzing Environmental Contamination for the Depue, IL, National Superfund Site

ERIC Educational Resources Information Center

Saslow Gomez, Sarah A.; Faurie-Wisniewski, Danielle; Parsa, Arlen; Spitz, Jeff; Spitz, Jennifer Amdur; Loeb, Nancy C.; Geiger, Franz M.

2015-01-01

The classroom exercise outlined here is a self-directed assignment that connects students to the environmental contamination problem surrounding the DePue Superfund site. By connecting chemistry knowledge gained in the classroom with a real-world problem, students are encouraged to personally connect with the problem while simultaneously…

Preservice Middle and High School Mathematics Teachers' Strategies When Solving Proportion Problems

ERIC Educational Resources Information Center

Arican, Muhammet

2018-01-01

The purpose of this study was to investigate eight preservice middle and high school mathematics teachers' solution strategies when solving single and multiple proportion problems. Real-world missing-value word problems were used in an interview setting to collect information about preservice teachers' (PSTs) reasoning about proportional…

Just-in-Time Algebra: A Problem Solving Approach Including Multimedia and Animation.

ERIC Educational Resources Information Center

Hofmann, Roseanne S.; Hunter, Walter R.

2003-01-01

Describes a beginning algebra course that places stronger emphasis on learning to solve problems and introduces topics using real world applications. Students learn estimating, graphing, and algebraic algorithms for the purpose of solving problems. Indicates that applications motivate students by appearing to be a more relevant topic as well as…

Engaging At-Risk Students with Technology.

ERIC Educational Resources Information Center

Duttweiler, Patricia Cloud

1992-01-01

Educational technology can be used to engage students in interesting activities through which teachers can present skills, concepts, and problems to be solved. At-risk students benefit from the investigation of relevant real world problems and the immediate feedback and privacy that technology affords. (EA)

Research on the man in the loop control system of the robot arm based on gesture control

NASA Astrophysics Data System (ADS)

Xiao, Lifeng; Peng, Jinbao

2017-03-01

The Man in the loop control system of the robot arm based on gesture control research complex real-world environment, which requires the operator to continuously control and adjust the remote manipulator, as the background, completes the specific mission human in the loop entire system as the research object. This paper puts forward a kind of robot arm control system of Man in the loop based on gesture control, by robot arm control system based on gesture control and Virtual reality scene feedback to enhance immersion and integration of operator, to make operator really become a part of the whole control loop. This paper expounds how to construct a man in the loop control system of the robot arm based on gesture control. The system is a complex system of human computer cooperative control, but also people in the loop control problem areas. The new system solves the problems that the traditional method has no immersion feeling and the operation lever is unnatural, the adjustment time is long, and the data glove mode wears uncomfortable and the price is expensive.

Extracting Depth From Motion Parallax in Real-World and Synthetic Displays

NASA Technical Reports Server (NTRS)

Hecht, Heiko; Kaiser, Mary K.; Aiken, William; Null, Cynthia H. (Technical Monitor)

1994-01-01

In psychophysical studies on human sensitivity to visual motion parallax (MP), the use of computer displays is pervasive. However, a number of potential problems are associated with such displays: cue conflicts arise when observers accommodate to the screen surface, and observer head and body movements are often not reflected in the displays. We investigated observers' sensitivity to depth information in MP (slant, depth order, relative depth) using various real-world displays and their computer-generated analogs. Angle judgments of real-world stimuli were consistently superior to judgments that were based on computer-generated stimuli. Similar results were found for perceived depth order and relative depth. Perceptual competence of observers tends to be underestimated in research that is based on computer generated displays. Such findings cannot be generalized to more realistic viewing situations.

Network Community Detection based on the Physarum-inspired Computational Framework.

PubMed

Gao, Chao; Liang, Mingxin; Li, Xianghua; Zhang, Zili; Wang, Zhen; Zhou, Zhili

2016-12-13

Community detection is a crucial and essential problem in the structure analytics of complex networks, which can help us understand and predict the characteristics and functions of complex networks. Many methods, ranging from the optimization-based algorithms to the heuristic-based algorithms, have been proposed for solving such a problem. Due to the inherent complexity of identifying network structure, how to design an effective algorithm with a higher accuracy and a lower computational cost still remains an open problem. Inspired by the computational capability and positive feedback mechanism in the wake of foraging process of Physarum, which is a large amoeba-like cell consisting of a dendritic network of tube-like pseudopodia, a general Physarum-based computational framework for community detection is proposed in this paper. Based on the proposed framework, the inter-community edges can be identified from the intra-community edges in a network and the positive feedback of solving process in an algorithm can be further enhanced, which are used to improve the efficiency of original optimization-based and heuristic-based community detection algorithms, respectively. Some typical algorithms (e.g., genetic algorithm, ant colony optimization algorithm, and Markov clustering algorithm) and real-world datasets have been used to estimate the efficiency of our proposed computational framework. Experiments show that the algorithms optimized by Physarum-inspired computational framework perform better than the original ones, in terms of accuracy and computational cost. Moreover, a computational complexity analysis verifies the scalability of our framework.

Using an Algorithm When Solving Hardy-Weinberg Problems in Biology.

ERIC Educational Resources Information Center

Stencel, John E.

1991-01-01

A real world sample of actual data that students can use to see the application of the Hardy-Weinberg law to a real population is provided. The directions for using a six-step algorithmic procedure to determine Hardy-Weinberg percentages on the data given are described. (KR)

Development of a cost-effective and flexible vibration DAQ system for long-term continuous structural health monitoring

NASA Astrophysics Data System (ADS)

Nguyen, Theanh; Chan, Tommy H. T.; Thambiratnam, David P.; King, Les

2015-12-01

In the structural health monitoring (SHM) field, long-term continuous vibration-based monitoring is becoming increasingly popular as this could keep track of the health status of structures during their service lives. However, implementing such a system is not always feasible due to on-going conflicts between budget constraints and the need of sophisticated systems to monitor real-world structures under their demanding in-service conditions. To address this problem, this paper presents a comprehensive development of a cost-effective and flexible vibration DAQ system for long-term continuous SHM of a newly constructed institutional complex with a special focus on the main building. First, selections of sensor type and sensor positions are scrutinized to overcome adversities such as low-frequency and low-level vibration measurements. In order to economically tackle the sparse measurement problem, a cost-optimized Ethernet-based peripheral DAQ model is first adopted to form the system skeleton. A combination of a high-resolution timing coordination method based on the TCP/IP command communication medium and a periodic system resynchronization strategy is then proposed to synchronize data from multiple distributed DAQ units. The results of both experimental evaluations and experimental-numerical verifications show that the proposed DAQ system in general and the data synchronization solution in particular work well and they can provide a promising cost-effective and flexible alternative for use in real-world SHM projects. Finally, the paper demonstrates simple but effective ways to make use of the developed monitoring system for long-term continuous structural health evaluation as well as to use the instrumented building herein as a multi-purpose benchmark structure for studying not only practical SHM problems but also synchronization related issues.

Remembering a visit to the psychology lab: Implications of Mild Cognitive Impairment.

PubMed

Davidson, Patrick S R; Cooper, Lara; Taler, Vanessa

2016-09-01

Morris Moscovitch has emphasized the importance of sensitively and carefully measuring cognition in the real world. With this lesson in mind, we examined the real-world episodic memory problems of older adults with Mild Cognitive Impairment (MCI). MCI patients often complain of episodic memory problems and perform poorly on standardized neuropsychological measures, but we still do not know enough about their actual difficulties remembering real experiences. A few days after their visit to the laboratory for an experimental session, we telephoned 19 MCI patients and 34 healthy participants without warning to ask what they could recollect about 16 elements of their visit. The patients had difficulty remembering the details of their visit, and reported lower ratings of memory vividness compared to healthy participants. Patients' memory for the visit was commensurate with their performance on three standard clinical memory assessment measures (delayed 5 word recall from the Montreal Cognitive Assessment, long delay free recall from the California Verbal Learning Test-II and recall of the details of the Wechsler Memory Scale-III Logical Memory stories), providing evidence for the generalizability of the clinical measures. Putting these findings together with those from Moscovitch and colleagues (Murphy et al., 2008) can help us better understand the real-world memory implications of Mild Cognitive Impairment. Copyright © 2016 Elsevier Ltd. All rights reserved.

Spatial cognition

NASA Technical Reports Server (NTRS)

Kaiser, Mary Kister; Remington, Roger

1988-01-01

Spatial cognition is the ability to reason about geometric relationships in the real (or a metaphorical) world based on one or more internal representations of those relationships. The study of spatial cognition is concerned with the representation of spatial knowledge, and our ability to manipulate these representations to solve spatial problems. Spatial cognition is utilized most critically when direct perceptual cues are absent or impoverished. Examples are provided of how human spatial cognitive abilities impact on three areas of space station operator performance: orientation, path planning, and data base management. A videotape provides demonstrations of relevant phenomena (e.g., the importance of orientation for recognition of complex, configural forms). The presentation is represented by abstract and overhead visuals only.

Fuzzy pharmacology: theory and applications.

PubMed

Sproule, Beth A; Naranjo, Claudio A; Türksen, I Burhan

2002-09-01

Fuzzy pharmacology is a term coined to represent the application of fuzzy logic and fuzzy set theory to pharmacological problems. Fuzzy logic is the science of reasoning, thinking and inference that recognizes and uses the real world phenomenon that everything is a matter of degree. It is an extension of binary logic that is able to deal with complex systems because it does not require crisp definitions and distinctions for the system components. In pharmacology, fuzzy modeling has been used for the mechanical control of drug delivery in surgical settings, and work has begun evaluating its use in other pharmacokinetic and pharmacodynamic applications. Fuzzy pharmacology is an emerging field that, based on these initial explorations, warrants further investigation.

3D reconstruction from non-uniform point clouds via local hierarchical clustering

NASA Astrophysics Data System (ADS)

Yang, Jiaqi; Li, Ruibo; Xiao, Yang; Cao, Zhiguo

2017-07-01

Raw scanned 3D point clouds are usually irregularly distributed due to the essential shortcomings of laser sensors, which therefore poses a great challenge for high-quality 3D surface reconstruction. This paper tackles this problem by proposing a local hierarchical clustering (LHC) method to improve the consistency of point distribution. Specifically, LHC consists of two steps: 1) adaptive octree-based decomposition of 3D space, and 2) hierarchical clustering. The former aims at reducing the computational complexity and the latter transforms the non-uniform point set into uniform one. Experimental results on real-world scanned point clouds validate the effectiveness of our method from both qualitative and quantitative aspects.

A Direct Comparison of Real-World and Virtual Navigation Performance in Chronic Stroke Patients.

PubMed

Claessen, Michiel H G; Visser-Meily, Johanna M A; de Rooij, Nicolien K; Postma, Albert; van der Ham, Ineke J M

2016-04-01

An increasing number of studies have presented evidence that various patient groups with acquired brain injury suffer from navigation problems in daily life. This skill is, however, scarcely addressed in current clinical neuropsychological practice and suitable diagnostic instruments are lacking. Real-world navigation tests are limited by geographical location and associated with practical constraints. It was, therefore, investigated whether virtual navigation might serve as a useful alternative. To investigate the convergent validity of virtual navigation testing, performance on the Virtual Tubingen test was compared to that on an analogous real-world navigation test in 68 chronic stroke patients. The same eight subtasks, addressing route and survey knowledge aspects, were assessed in both tests. In addition, navigation performance of stroke patients was compared to that of 44 healthy controls. A correlation analysis showed moderate overlap (r = .535) between composite scores of overall real-world and virtual navigation performance in stroke patients. Route knowledge composite scores correlated somewhat stronger (r = .523) than survey knowledge composite scores (r = .442). When comparing group performances, patients obtained lower scores than controls on seven subtasks. Whereas the real-world test was found to be easier than its virtual counterpart, no significant interaction-effects were found between group and environment. Given moderate overlap of the total scores between the two navigation tests, we conclude that virtual testing of navigation ability is a valid alternative to navigation tests that rely on real-world route exposure.

Student Curators: Becoming Lifelong Learners.

ERIC Educational Resources Information Center

Koetsch, Peg; And Others

1994-01-01

Fifth graders at a Virginia school are applying new knowledge about world cultures by constructing artifacts for an Egyptian legacy exhibit. Exhibitions are a key facet of Museums-in-Progress (MIP), a program that links problem-solving activities with the real world. Students learn to develop, install, and interpret an exhibition by touring local…

Problem Solving with Workstations. Program Description, Teacher Materials, and Student Information. Teacher Developed Technology Education for the Nineties (TD-TEN).

ERIC Educational Resources Information Center

Garey, Robert W.

The Randolph, New Jersey Intermediate School updated its industrial arts program to reflect the challenges and work force of the Twentieth Century in which students apply a design/problem-solving process to solve real-world problems. In the laboratory portion of the program, students circulate between workstations to define problems, complete…

Improving Teaching Quality and Problem Solving Ability through Contextual Teaching and Learning in Differential Equations: A Lesson Study Approach

ERIC Educational Resources Information Center

Khotimah, Rita Pramujiyanti; Masduki

2016-01-01

Differential equations is a branch of mathematics which is closely related to mathematical modeling that arises in real-world problems. Problem solving ability is an essential component to solve contextual problem of differential equations properly. The purposes of this study are to describe contextual teaching and learning (CTL) model in…

Evaluation of the nephrotoxicity of complex mixtures containing organics and metals: advantages and disadvantages of the use of real-world complex mixtures.

PubMed

Simmons, J E; Yang, R S; Berman, E

1995-02-01

As part of a multidisciplinary health effects study, the nephrotoxicity of complex industrial waste mixtures was assessed. Adult, male Fischer 344 rats were gavaged with samples of complex industrial waste and nephrotoxicity evaluated 24 hr later. Of the 10 tested samples, 4 produced increased absolute or relative kidney weight, or both, coupled with a statistically significant alteration in at least one of the measured serum parameters (urea nitrogen (BUN), creatinine (CREAT), and BUN/CREAT ratio). Although the waste samples had been analyzed for a number of organic chemicals and 7 of the 10 samples were analyzed also for 12 elemental metals and metalloids, their nephrotoxicity was not readily predicted from the partial chemical characterization data. Because the chemical form or speciation of the metals was unknown, it was not possible to estimate their contribution to the observed biological response. Various experimental approaches, including use of real-world complex mixtures, chemically defined synthetic mixtures, and simple mixtures, will be necessary to adequately determine the potential human health risk from exposure to complex chemical mixtures.

Dynamic simulation modelling of policy responses to reduce alcohol-related harms: rationale and procedure for a participatory approach.

PubMed

Atkinson, Jo-An; O'Donnell, Eloise; Wiggers, John; McDonnell, Geoff; Mitchell, Jo; Freebairn, Louise; Indig, Devon; Rychetnik, Lucie

2017-02-15

Development of effective policy responses to address complex public health problems can be challenged by a lack of clarity about the interaction of risk factors driving the problem, differing views of stakeholders on the most appropriate and effective intervention approaches, a lack of evidence to support commonly implemented and acceptable intervention approaches, and a lack of acceptance of effective interventions. Consequently, political considerations, community advocacy and industry lobbying can contribute to a hotly contested debate about the most appropriate course of action; this can hinder consensus and give rise to policy resistance. The problem of alcohol misuse and its associated harms in New South Wales (NSW), Australia, provides a relevant example of such challenges. Dynamic simulation modelling is increasingly being valued by the health sector as a robust tool to support decision making to address complex problems. It allows policy makers to ask 'what-if' questions and test the potential impacts of different policy scenarios over time, before solutions are implemented in the real world. Participatory approaches to modelling enable researchers, policy makers, program planners, practitioners and consumer representatives to collaborate with expert modellers to ensure that models are transparent, incorporate diverse evidence and perspectives, are better aligned to the decision-support needs of policy makers, and can facilitate consensus building for action. This paper outlines a procedure for embedding stakeholder engagement and consensus building in the development of dynamic simulation models that can guide the development of effective, coordinated and acceptable policy responses to complex public health problems, such as alcohol-related harms in NSW.

The Ocean: Our Future

NASA Astrophysics Data System (ADS)

Independent World Commission On The Oceans; Soares, Mario

1998-09-01

The Ocean, Our Future is the official report of the Independent World Commission on the Oceans, chaired by Mário Soares, former President of Portugal. Its aim is to summarize the very real problems affecting the ocean and its future management, and to provide imaginative solutions to these various and interlocking problems. The oceans have traditionally been taken for granted as a source of wealth, opportunity and abundance. Our growing understanding of the oceans has fundamentally changed this perception. We now know that in some areas, abundance is giving way to real scarcity, resulting in severe conflicts. Territorial disputes that threaten peace and security, disruptions to global climate, overfishing, habitat destruction, species extinction, indiscriminate trawling, pollution, the dumping of hazardous and toxic wastes, piracy, terrorism, illegal trafficking and the destruction of coastal communities are among the problems that today form an integral part of the unfolding drama of the oceans. Based on the deliberations, experience and input of more than 100 specialists from around the world, this timely volume provides a powerful overview of the state of our water world.

A prediction model to forecast the cost impact from a break in the production schedule

NASA Technical Reports Server (NTRS)

Delionback, L. M.

1977-01-01

The losses which are experienced after a break or stoppage in sequence of a production cycle portends an extremely complex situation and involves numerous variables, some of uncertain quantity and quality. There are no discrete formulas to define the losses during a gap in production. The techniques which are employed are therefore related to a prediction or forecast of the losses that take place, based on the conditions which exist in the production environment. Such parameters as learning curve slope, number of predecessor units, and length of time the production sequence is halted are utilized in formulating a prediction model. The pertinent current publications related to this subject are few in number, but are reviewed to provide an understanding of the problem. Example problems are illustrated together with appropriate trend curves to show the approach. Solved problems are also given to show the application of the models to actual cases or production breaks in the real world.

Visualization for Hyper-Heuristics. Front-End Graphical User Interface

DOE Office of Scientific and Technical Information (OSTI.GOV)

Kroenung, Lauren

Modern society is faced with ever more complex problems, many of which can be formulated as generate-and-test optimization problems. General-purpose optimization algorithms are not well suited for real-world scenarios where many instances of the same problem class need to be repeatedly and efficiently solved because they are not targeted to a particular scenario. Hyper-heuristics automate the design of algorithms to create a custom algorithm for a particular scenario. While such automated design has great advantages, it can often be difficult to understand exactly how a design was derived and why it should be trusted. This project aims to address thesemore » issues of usability by creating an easy-to-use graphical user interface (GUI) for hyper-heuristics to support practitioners, as well as scientific visualization of the produced automated designs. My contributions to this project are exhibited in the user-facing portion of the developed system and the detailed scientific visualizations created from back-end data.« less

Evaluating the performance of parallel subsurface simulators: An illustrative example with PFLOTRAN

PubMed Central

Hammond, G E; Lichtner, P C; Mills, R T

2014-01-01

[1] To better inform the subsurface scientist on the expected performance of parallel simulators, this work investigates performance of the reactive multiphase flow and multicomponent biogeochemical transport code PFLOTRAN as it is applied to several realistic modeling scenarios run on the Jaguar supercomputer. After a brief introduction to the code's parallel layout and code design, PFLOTRAN's parallel performance (measured through strong and weak scalability analyses) is evaluated in the context of conceptual model layout, software and algorithmic design, and known hardware limitations. PFLOTRAN scales well (with regard to strong scaling) for three realistic problem scenarios: (1) in situ leaching of copper from a mineral ore deposit within a 5-spot flow regime, (2) transient flow and solute transport within a regional doublet, and (3) a real-world problem involving uranium surface complexation within a heterogeneous and extremely dynamic variably saturated flow field. Weak scalability is discussed in detail for the regional doublet problem, and several difficulties with its interpretation are noted. PMID:25506097

Evaluating the performance of parallel subsurface simulators: An illustrative example with PFLOTRAN.

PubMed

Hammond, G E; Lichtner, P C; Mills, R T

2014-01-01

[1] To better inform the subsurface scientist on the expected performance of parallel simulators, this work investigates performance of the reactive multiphase flow and multicomponent biogeochemical transport code PFLOTRAN as it is applied to several realistic modeling scenarios run on the Jaguar supercomputer. After a brief introduction to the code's parallel layout and code design, PFLOTRAN's parallel performance (measured through strong and weak scalability analyses) is evaluated in the context of conceptual model layout, software and algorithmic design, and known hardware limitations. PFLOTRAN scales well (with regard to strong scaling) for three realistic problem scenarios: (1) in situ leaching of copper from a mineral ore deposit within a 5-spot flow regime, (2) transient flow and solute transport within a regional doublet, and (3) a real-world problem involving uranium surface complexation within a heterogeneous and extremely dynamic variably saturated flow field. Weak scalability is discussed in detail for the regional doublet problem, and several difficulties with its interpretation are noted.

Virtual Reality for Artificial Intelligence: human-centered simulation for social science.

PubMed

Cipresso, Pietro; Riva, Giuseppe

2015-01-01

There is a long last tradition in Artificial Intelligence as use of Robots endowing human peculiarities, from a cognitive and emotional point of view, and not only in shape. Today Artificial Intelligence is more oriented to several form of collective intelligence, also building robot simulators (hardware or software) to deeply understand collective behaviors in human beings and society as a whole. Modeling has also been crucial in the social sciences, to understand how complex systems can arise from simple rules. However, while engineers' simulations can be performed in the physical world using robots, for social scientist this is impossible. For decades, researchers tried to improve simulations by endowing artificial agents with simple and complex rules that emulated human behavior also by using artificial intelligence (AI). To include human beings and their real intelligence within artificial societies is now the big challenge. We present an hybrid (human-artificial) platform where experiments can be performed by simulated artificial worlds in the following manner: 1) agents' behaviors are regulated by the behaviors shown in Virtual Reality involving real human beings exposed to specific situations to simulate, and 2) technology transfers these rules into the artificial world. These form a closed-loop of real behaviors inserted into artificial agents, which can be used to study real society.

Rivaroxaban real-world evidence: Validating safety and effectiveness in clinical practice.

PubMed

Beyer-Westendorf, Jan; Camm, A John; Coleman, Craig I; Tamayo, Sally

2016-09-28

Randomised controlled trials (RCTs) are considered the gold standard of clinical research as they use rigorous methodologies, detailed protocols, pre-specified statistical analyses and well-defined patient cohorts. However, RCTs do not take into account the complexity of real-world clinical decision-making. To tackle this, real-world data are being increasingly used to evaluate the long-term safety and effectiveness of a given therapy in routine clinical practice and in patients who may not be represented in RCTs, addressing key clinical questions that may remain. Real-world evidence plays a substantial role in supporting the use of non-vitamin K antagonist (VKA) oral anticoagulants (NOACs) in clinical practice. By providing data on patient profiles and the use of anticoagulation therapies in routine clinical practice, real-world evidence expands the current awareness of NOACs, helping to ensure that clinicians are well-informed on their use to implement patient-tailored clinical decisions. There are various issues with current anticoagulation strategies, including under- or overtreatment and frequent monitoring with VKAs. Real-world studies have demonstrated that NOAC use is increasing (Dresden NOAC registry and Global Anticoagulant Registry in the FIELD-AF [GARFIELD-AF]), as well as reaffirming the safety and effectiveness of rivaroxaban previously observed in RCTs (XArelto on preveNtion of sTroke and non-central nervoUS system systemic embolism in patients with non-valvular atrial fibrillation [XANTUS] and IMS Disease Analyzer). This article will describe the latest updates in real-world evidence across a variety of methodologies, such as non-interventional studies (NIS), registries and database analyses studies. It is anticipated that these studies will provide valuable clinical insights into the management of thromboembolism, and enhance the current knowledge on anticoagulant use and outcomes for patients.

Additional Crime Scenes for Projectile Motion Unit

NASA Astrophysics Data System (ADS)

Fullerton, Dan; Bonner, David

2011-12-01

Building students' ability to transfer physics fundamentals to real-world applications establishes a deeper understanding of underlying concepts while enhancing student interest. Forensic science offers a great opportunity for students to apply physics to highly engaging, real-world contexts. Integrating these opportunities into inquiry-based problem solving in a team environment provides a terrific backdrop for fostering communication, analysis, and critical thinking skills. One such activity, inspired jointly by the museum exhibit "CSI: The Experience"2 and David Bonner's TPT article "Increasing Student Engagement and Enthusiasm: A Projectile Motion Crime Scene,"3 provides students with three different crime scenes, each requiring an analysis of projectile motion. In this lesson students socially engage in higher-order analysis of two-dimensional projectile motion problems by collecting information from 3-D scale models and collaborating with one another on its interpretation, in addition to diagramming and mathematical analysis typical to problem solving in physics.

Active Learning with Irrelevant Examples

NASA Technical Reports Server (NTRS)

Mazzoni, Dominic; Wagstaff, Kiri L.; Burl, Michael

2006-01-01

Active learning algorithms attempt to accelerate the learning process by requesting labels for the most informative items first. In real-world problems, however, there may exist unlabeled items that are irrelevant to the user's classification goals. Queries about these points slow down learning because they provide no information about the problem of interest. We have observed that when irrelevant items are present, active learning can perform worse than random selection, requiring more time (queries) to achieve the same level of accuracy. Therefore, we propose a novel approach, Relevance Bias, in which the active learner combines its default selection heuristic with the output of a simultaneously trained relevance classifier to favor items that are likely to be both informative and relevant. In our experiments on a real-world problem and two benchmark datasets, the Relevance Bias approach significantly improved the learning rate of three different active learning approaches.

TUNS/TCIS information model/process model

NASA Technical Reports Server (NTRS)

Wilson, James

1992-01-01

An Information Model is comprised of graphical and textual notation suitable for describing and defining the problem domain - in our case, TUNS or TCIS. The model focuses on the real world under study. It identifies what is in the problem and organizes the data into a formal structure for documentation and communication purposes. The Information Model is composed of an Entity Relationship Diagram (ERD) and a Data Dictionary component. The combination of these components provide an easy to understand methodology for expressing the entities in the problem space, the relationships between entities and the characteristics (attributes) of the entities. This approach is the first step in information system development. The Information Model identifies the complete set of data elements processed by TUNS. This representation provides a conceptual view of TUNS from the perspective of entities, data, and relationships. The Information Model reflects the business practices and real-world entities that users must deal with.

Uncertainty Reduction for Stochastic Processes on Complex Networks

NASA Astrophysics Data System (ADS)

Radicchi, Filippo; Castellano, Claudio

2018-05-01

Many real-world systems are characterized by stochastic dynamical rules where a complex network of interactions among individual elements probabilistically determines their state. Even with full knowledge of the network structure and of the stochastic rules, the ability to predict system configurations is generally characterized by a large uncertainty. Selecting a fraction of the nodes and observing their state may help to reduce the uncertainty about the unobserved nodes. However, choosing these points of observation in an optimal way is a highly nontrivial task, depending on the nature of the stochastic process and on the structure of the underlying interaction pattern. In this paper, we introduce a computationally efficient algorithm to determine quasioptimal solutions to the problem. The method leverages network sparsity to reduce computational complexity from exponential to almost quadratic, thus allowing the straightforward application of the method to mid-to-large-size systems. Although the method is exact only for equilibrium stochastic processes defined on trees, it turns out to be effective also for out-of-equilibrium processes on sparse loopy networks.

Distributed Cooperation Solution Method of Complex System Based on MAS

NASA Astrophysics Data System (ADS)

Weijin, Jiang; Yuhui, Xu

To adapt the model in reconfiguring fault diagnosing to dynamic environment and the needs of solving the tasks of complex system fully, the paper introduced multi-Agent and related technology to the complicated fault diagnosis, an integrated intelligent control system is studied in this paper. Based on the thought of the structure of diagnostic decision and hierarchy in modeling, based on multi-layer decomposition strategy of diagnosis task, a multi-agent synchronous diagnosis federation integrated different knowledge expression modes and inference mechanisms are presented, the functions of management agent, diagnosis agent and decision agent are analyzed, the organization and evolution of agents in the system are proposed, and the corresponding conflict resolution algorithm in given, Layered structure of abstract agent with public attributes is build. System architecture is realized based on MAS distributed layered blackboard. The real world application shows that the proposed control structure successfully solves the fault diagnose problem of the complex plant, and the special advantage in the distributed domain.

How to use MPI communication in highly parallel climate simulations more easily and more efficiently.

NASA Astrophysics Data System (ADS)

Behrens, Jörg; Hanke, Moritz; Jahns, Thomas

2014-05-01

In this talk we present a way to facilitate efficient use of MPI communication for developers of climate models. Exploitation of the performance potential of today's highly parallel supercomputers with real world simulations is a complex task. This is partly caused by the low level nature of the MPI communication library which is the dominant communication tool at least for inter-node communication. In order to manage the complexity of the task, climate simulations with non-trivial communication patterns often use an internal abstraction layer above MPI without exploiting the benefits of communication aggregation or MPI-datatypes. The solution for the complexity and performance problem we propose is the communication library YAXT. This library is built on top of MPI and takes high level descriptions of arbitrary domain decompositions and automatically derives an efficient collective data exchange. Several exchanges can be aggregated in order to reduce latency costs. Examples are given which demonstrate the simplicity and the performance gains for selected climate applications.

Understanding real-world implementation quality and "active ingredients" of PBIS.

PubMed

Molloy, Lauren E; Moore, Julia E; Trail, Jessica; Van Epps, John James; Hopfer, Suellen

2013-12-01

Programs delivered in the "real world" often look substantially different from what was originally intended by program developers. Depending on which components of a program are being trimmed or altered, such modifications may seriously undermine the effectiveness of a program. In the present study, these issues are explored within a widely used school-based, non-curricular intervention, Positive Behavioral Intervention and Supports. The present study takes advantage of a uniquely large dataset to gain a better understanding of the "real-world" implementation quality of PBIS and to take a first step toward identifying the components of PBIS that "matter most" for student outcomes. Data from 27,689 students and 166 public primary and secondary schools across seven states included school and student demographics, indices of PBIS implementation quality, and reports of problem behaviors for any student who received an office discipline referral during the 2007-2008 school year. Results of the present study identify three key components of PBIS that many schools are failing to implement properly, three program components that were most related to lower rates of problem behavior (i.e., three "active ingredients" of PBIS), and several school characteristics that help to account for differences across schools in the quality of PBIS implementation. Overall, findings highlight the importance of assessing implementation quality in "real-world" settings, and the need to continue improving understanding of how and why programs work. Findings are discussed in terms of their implications for policy.

Generating realistic environments for cyber operations development, testing, and training

NASA Astrophysics Data System (ADS)

Berk, Vincent H.; Gregorio-de Souza, Ian; Murphy, John P.

2012-06-01

Training eective cyber operatives requires realistic network environments that incorporate the structural and social complexities representative of the real world. Network trac generators facilitate repeatable experiments for the development, training and testing of cyber operations. However, current network trac generators, ranging from simple load testers to complex frameworks, fail to capture the realism inherent in actual environments. In order to improve the realism of network trac generated by these systems, it is necessary to quantitatively measure the level of realism in generated trac with respect to the environment being mimicked. We categorize realism measures into statistical, content, and behavioral measurements, and propose various metrics that can be applied at each level to indicate how eectively the generated trac mimics the real world.

A Systems Approach to Research in Vocational Education.

ERIC Educational Resources Information Center

Miller, Larry E.

1991-01-01

A methodology to address "soft system" problems (those that are unstructured or fuzzy) has these steps: (1) mapping the problem; (2) constructing a root definition; (3) applying conceptual models; (4) comparing models to the real world; and (5) finding and implementing feasible solutions. (SK)

Design optimization of steel frames using an enhanced firefly algorithm

NASA Astrophysics Data System (ADS)

Carbas, Serdar

2016-12-01

Mathematical modelling of real-world-sized steel frames under the Load and Resistance Factor Design-American Institute of Steel Construction (LRFD-AISC) steel design code provisions, where the steel profiles for the members are selected from a table of steel sections, turns out to be a discrete nonlinear programming problem. Finding the optimum design of such design optimization problems using classical optimization techniques is difficult. Metaheuristic algorithms provide an alternative way of solving such problems. The firefly algorithm (FFA) belongs to the swarm intelligence group of metaheuristics. The standard FFA has the drawback of being caught up in local optima in large-sized steel frame design problems. This study attempts to enhance the performance of the FFA by suggesting two new expressions for the attractiveness and randomness parameters of the algorithm. Two real-world-sized design examples are designed by the enhanced FFA and its performance is compared with standard FFA as well as with particle swarm and cuckoo search algorithms.

Problem-Based Learning and Earth System Science - The ESSEA High School Earth System Science Online Course

NASA Astrophysics Data System (ADS)

Myers, R.; Botti, J.

2002-12-01

The high school Earth system science course is web based and designed to meet the professional development needs of science teachers in grades 9-12. Three themes predominate this course: Earth system science (ESS) content, collaborative investigations, and problem-based learning (PBL) methodology. PBL uses real-world contexts for in-depth investigations of a subject matter. Participants predict the potential impacts of the selected event on Earth's spheres and the subsequent feedback and potential interactions that might result. PBL activities start with an ill-structured problem that serves as a springboard to team engagement. These PBL scenarios contain real-world situations. Teams of learners conduct an Earth system science analysis of the event and make recommendations or offer solutions regarding the problem. The course design provides an electronic forum for conversations, debate, development, and application of ideas. Samples of threaded discussions built around ESS thinking in science and PBL pedagogy will be presented.

Problem-Based Learning and Earth System Science - The ESSEA High School Earth System Science Online Course

NASA Astrophysics Data System (ADS)

Myers, R. J.; Botti, J. A.

2001-12-01

The high school Earth system science course is web based and designed to meet the professional development needs of science teachers in grades 9-12. Three themes predominate this course: Earth system science (ESS) content, collaborative investigations, and problem-based learning (PBL) methodology. PBL uses real-world contexts for in-depth investigations of a subject matter. Participants predict the potential impacts of the selected event on Earth's spheres and the subsequent feedback and potential interactions that might result. PBL activities start with an ill-structured problem that serves as a springboard to team engagement. These PBL scenarios contain real-world situations. Teams of learners conduct an Earth system science analysis of the event and make recommendations or offer solutions regarding the problem. The course design provides an electronic forum for conversations, debate, development, and application of ideas. Samples of threaded discussions built around ESS thinking in science and PBL pedagogy will be presented.

Sowing the Seeds of Creativity

ERIC Educational Resources Information Center

Briten, Elizabeth

2006-01-01

The exciting world of plants may be something of a mystery to many children, and the often-dry content of a curriculum taught indoors inhibits real understanding of many complex biological processes. Moving outdoors opens up an unexplored world and presents rich opportunities for imaginative learning. The "Life processes and living…

Hierarchical Event Descriptors (HED): Semi-Structured Tagging for Real-World Events in Large-Scale EEG

PubMed Central

Bigdely-Shamlo, Nima; Cockfield, Jeremy; Makeig, Scott; Rognon, Thomas; La Valle, Chris; Miyakoshi, Makoto; Robbins, Kay A.

2016-01-01

Real-world brain imaging by EEG requires accurate annotation of complex subject-environment interactions in event-rich tasks and paradigms. This paper describes the evolution of the Hierarchical Event Descriptor (HED) system for systematically describing both laboratory and real-world events. HED version 2, first described here, provides the semantic capability of describing a variety of subject and environmental states. HED descriptions can include stimulus presentation events on screen or in virtual worlds, experimental or spontaneous events occurring in the real world environment, and events experienced via one or multiple sensory modalities. Furthermore, HED 2 can distinguish between the mere presence of an object and its actual (or putative) perception by a subject. Although the HED framework has implicit ontological and linked data representations, the user-interface for HED annotation is more intuitive than traditional ontological annotation. We believe that hiding the formal representations allows for a more user-friendly interface, making consistent, detailed tagging of experimental, and real-world events possible for research users. HED is extensible while retaining the advantages of having an enforced common core vocabulary. We have developed a collection of tools to support HED tag assignment and validation; these are available at hedtags.org. A plug-in for EEGLAB (sccn.ucsd.edu/eeglab), CTAGGER, is also available to speed the process of tagging existing studies. PMID:27799907

Genetic Algorithm and Tabu Search for Vehicle Routing Problems with Stochastic Demand

DOE Office of Scientific and Technical Information (OSTI.GOV)

Ismail, Zuhaimy, E-mail: zuhaimyi@yahoo.com, E-mail: irhamahn@yahoo.com; Irhamah, E-mail: zuhaimyi@yahoo.com, E-mail: irhamahn@yahoo.com

2010-11-11

This paper presents a problem of designing solid waste collection routes, involving scheduling of vehicles where each vehicle begins at the depot, visits customers and ends at the depot. It is modeled as a Vehicle Routing Problem with Stochastic Demands (VRPSD). A data set from a real world problem (a case) is used in this research. We developed Genetic Algorithm (GA) and Tabu Search (TS) procedure and these has produced the best possible result. The problem data are inspired by real case of VRPSD in waste collection. Results from the experiment show the advantages of the proposed algorithm that aremore » its robustness and better solution qualities.« less

An Intuitionistic Fuzzy Logic Models for Multicriteria Decision Making Under Uncertainty

NASA Astrophysics Data System (ADS)

Jana, Biswajit; Mohanty, Sachi Nandan

2017-04-01

The purpose of this paper is to enhance the applicability of the fuzzy sets for developing mathematical models for decision making under uncertainty, In general a decision making process consist of four stages, namely collection of information from various sources, compile the information, execute the information and finally take the decision/action. Only fuzzy sets theory is capable to quantifying the linguistic expression to mathematical form in complex situation. Intuitionistic fuzzy set (IFSs) which reflects the fact that the degree of non membership is not always equal to one minus degree of membership. There may be some degree of hesitation. Thus, there are some situations where IFS theory provides a more meaningful and applicable to cope with imprecise information present for solving multiple criteria decision making problem. This paper emphasis on IFSs, which is help for solving real world problem in uncertainty situation.

Facility Layout Problems Using Bays: A Survey

NASA Astrophysics Data System (ADS)

Davoudpour, Hamid; Jaafari, Amir Ardestani; Farahani, Leila Najafabadi

2010-06-01

Layout design is one of the most important activities done by industrial Engineers. Most of these problems have NP hard Complexity. In a basic layout design, each cell is represented by a rectilinear, but not necessarily convex polygon. The set of fully packed adjacent polygons is known as a block layout (Asef-Vaziri and Laporte 2007). Block layout is divided by slicing tree and bay layout. In bay layout, departments are located in vertical columns or horizontal rows, bays. Bay layout is used in real worlds especially in concepts such as semiconductor and aisles. There are several reviews in facility layout; however none of them focus on bay layout. The literature analysis given here is not limited to specific considerations about bay layout design. We present a state of art review for bay layout considering some issues such as the used objectives, the techniques of solving and the integration methods in bay.

A Temporal Pattern Mining Approach for Classifying Electronic Health Record Data

PubMed Central

Batal, Iyad; Valizadegan, Hamed; Cooper, Gregory F.; Hauskrecht, Milos

2013-01-01

We study the problem of learning classification models from complex multivariate temporal data encountered in electronic health record systems. The challenge is to define a good set of features that are able to represent well the temporal aspect of the data. Our method relies on temporal abstractions and temporal pattern mining to extract the classification features. Temporal pattern mining usually returns a large number of temporal patterns, most of which may be irrelevant to the classification task. To address this problem, we present the Minimal Predictive Temporal Patterns framework to generate a small set of predictive and non-spurious patterns. We apply our approach to the real-world clinical task of predicting patients who are at risk of developing heparin induced thrombocytopenia. The results demonstrate the benefit of our approach in efficiently learning accurate classifiers, which is a key step for developing intelligent clinical monitoring systems. PMID:25309815

Data reliability in complex directed networks

NASA Astrophysics Data System (ADS)

Sanz, Joaquín; Cozzo, Emanuele; Moreno, Yamir

2013-12-01

The availability of data from many different sources and fields of science has made it possible to map out an increasing number of networks of contacts and interactions. However, quantifying how reliable these data are remains an open problem. From Biology to Sociology and Economics, the identification of false and missing positives has become a problem that calls for a solution. In this work we extend one of the newest, best performing models—due to Guimerá and Sales-Pardo in 2009—to directed networks. The new methodology is able to identify missing and spurious directed interactions with more precision than previous approaches, which renders it particularly useful for analyzing data reliability in systems like trophic webs, gene regulatory networks, communication patterns and several social systems. We also show, using real-world networks, how the method can be employed to help search for new interactions in an efficient way.

Aerodynamic Design of Complex Configurations Using Cartesian Methods and CAD Geometry

NASA Technical Reports Server (NTRS)

Nemec, Marian; Aftosmis, Michael J.; Pulliam, Thomas H.

2003-01-01

The objective for this paper is to present the development of an optimization capability for the Cartesian inviscid-flow analysis package of Aftosmis et al. We evaluate and characterize the following modules within the new optimization framework: (1) A component-based geometry parameterization approach using a CAD solid representation and the CAPRI interface. (2) The use of Cartesian methods in the development Optimization techniques using a genetic algorithm. The discussion and investigations focus on several real world problems of the optimization process. We examine the architectural issues associated with the deployment of a CAD-based design approach in a heterogeneous parallel computing environment that contains both CAD workstations and dedicated compute nodes. In addition, we study the influence of noise on the performance of optimization techniques, and the overall efficiency of the optimization process for aerodynamic design of complex three-dimensional configurations. of automated optimization tools. rithm and a gradient-based algorithm.

Receiver Operating Characteristic Analysis of Eyewitness Memory: Comparing the Diagnostic Accuracy of Simultaneous versus Sequential Lineups

ERIC Educational Resources Information Center

Mickes, Laura; Flowe, Heather D.; Wixted, John T.

2012-01-01

A police lineup presents a real-world signal-detection problem because there are two possible states of the world (the suspect is either innocent or guilty), some degree of information about the true state of the world is available (the eyewitness has some degree of memory for the perpetrator), and a decision is made (identifying the suspect or…

Decolonisation of fractional calculus rules: Breaking commutativity and associativity to capture more natural phenomena

NASA Astrophysics Data System (ADS)

Atangana, Abdon; Gómez-Aguilar, J. F.

2018-04-01

To answer some issues raised about the concept of fractional differentiation and integration based on the exponential and Mittag-Leffler laws, we present, in this paper, fundamental differences between the power law, exponential decay, Mittag-Leffler law and their possible applications in nature. We demonstrate the failure of the semi-group principle in modeling real-world problems. We use natural phenomena to illustrate the importance of non-commutative and non-associative operators under which the Caputo-Fabrizio and Atangana-Baleanu fractional operators fall. We present statistical properties of generator for each fractional derivative, including Riemann-Liouville, Caputo-Fabrizio and Atangana-Baleanu ones. The Atangana-Baleanu and Caputo-Fabrizio fractional derivatives show crossover properties for the mean-square displacement, while the Riemann-Liouville is scale invariant. Their probability distributions are also a Gaussian to non-Gaussian crossover, with the difference that the Caputo Fabrizio kernel has a steady state between the transition. Only the Atangana-Baleanu kernel is a crossover for the waiting time distribution from stretched exponential to power law. A new criterion was suggested, namely the Atangana-Gómez fractional bracket, that helps describe the energy needed by a fractional derivative to characterize a 2-pletic manifold. Based on these properties, we classified fractional derivatives in three categories: weak, mild and strong fractional differential and integral operators. We presented some applications of fractional differential operators to describe real-world problems and we proved, with numerical simulations, that the Riemann-Liouville power-law derivative provides a description of real-world problems with much additional information, that can be seen as noise or error due to specific memory properties of its power-law kernel. The Caputo-Fabrizio derivative is less noisy while the Atangana-Baleanu fractional derivative provides an excellent description, due to its Mittag-Leffler memory, able to distinguish between dynamical systems taking place at different scales without steady state. The study suggests that the properties of associativity and commutativity or the semi-group principle are just irrelevant in fractional calculus. Properties of classical derivatives were established for the ordinary calculus with no memory effect and it is a failure of mathematical investigation to attempt to describe more complex natural phenomena using the same notions.

Performance in Mathematical Problem Solving as a Function of Comprehension and Arithmetic Skills

ERIC Educational Resources Information Center

Voyer, Dominic

2011-01-01

Many factors influence a student's performance in word (or textbook) problem solving in class. Among them is the comprehension process the pupils construct during their attempt to solve the problem. The comprehension process may include some less formal representations, based on pupils' real-world knowledge, which support the construction of a…

Fostering Modeling Competencies: Benefits of Worked Examples, Problems to Be Solved, and Fading Procedures

ERIC Educational Resources Information Center

Große, Cornelia S.

2015-01-01

The application of mathematics to real-world problems is moving more and more in the focus of attention of mathematics education; however, many learners experience huge difficulties in relating "pure" mathematics to everyday contents. In order to solve "modeling problems", it is first necessary to find a transition from a…

A Critical Discourse Analysis of Practical Problems in a Foundation Mathematics Course at a South African University

ERIC Educational Resources Information Center

le Roux, Kate; Adler, Jill

2016-01-01

Mathematical problems that make links to the everyday and to disciplines other than mathematics--variously referred to as practical, realistic, real-world or applied problems in the literature--feature in school and undergraduate mathematics reforms aimed at increasing mathematics participation in contexts of inequity and diversity. In this…

Integrating Problem-Based Learning with Community-Engaged Learning in Teaching Program Development and Implementation

ERIC Educational Resources Information Center

Hou, Su-I

2014-01-01

Purpose: Problem-based learning (PBL) challenges students to learn and work in groups to seek solutions to real world problems. Connecting academic study with community-engaged learning (CEL) experience can deeper learning and thinking. This paper highlights the integration of PBL with CEL in the Implementation Course to engage graduate students…

A Tiny Adventure: The Introduction of Problem Based Learning in an Undergraduate Chemistry Course

ERIC Educational Resources Information Center

Williams, Dylan P.; Woodward, Jonathan R.; Symons, Sarah L.; Davies, David L.

2010-01-01

Year 1 of the chemistry degree at the University of Leicester has been significantly changed by the integration of a problem based learning (PBL) component into the introductory inorganic/physical chemistry module, "Chemical Principles". Small groups of 5-6 students were given a series of problems with real world scenarios and were then…

"What's so Terrible about Swallowing an Apple Seed?" Problem-Based Learning in Kindergarten

ERIC Educational Resources Information Center

Zhang, Meilan; Parker, Joyce; Eberhardt, Jan; Passalacqua, Susan

2011-01-01

Problem-Based Learning (PBL), an instructional approach originated in medical education, has gained increasing attention in K-12 science education because of its emphasis on self-directed learning and real-world problem-solving. Yet few studies have examined how PBL can be adapted for kindergarten. In this study, we examined how a veteran…

Problem-Based Learning in an Online Course: A Case Study

ERIC Educational Resources Information Center

Cheaney, James D.; Ingebritsen, Thomas S.

2005-01-01

Problem-based learning (PBL) is the use of a "real world" problem or situation as a context for learning. The present study explores the use of PBL in an online biotechnology course. In the PBL unit, student groups dealt with the ethical, legal, social, and human issues surrounding pre-symptomatic DNA testing for a genetic disease. Issues…

Convex relaxations for gas expansion planning

DOE PAGES

Borraz-Sanchez, Conrado; Bent, Russell Whitford; Backhaus, Scott N.; ...

2016-01-01

Expansion of natural gas networks is a critical process involving substantial capital expenditures with complex decision-support requirements. Here, given the non-convex nature of gas transmission constraints, global optimality and infeasibility guarantees can only be offered by global optimisation approaches. Unfortunately, state-of-the-art global optimisation solvers are unable to scale up to real-world size instances. In this study, we present a convex mixed-integer second-order cone relaxation for the gas expansion planning problem under steady-state conditions. The underlying model offers tight lower bounds with high computational efficiency. In addition, the optimal solution of the relaxation can often be used to derive high-quality solutionsmore » to the original problem, leading to provably tight optimality gaps and, in some cases, global optimal solutions. The convex relaxation is based on a few key ideas, including the introduction of flux direction variables, exact McCormick relaxations, on/off constraints, and integer cuts. Numerical experiments are conducted on the traditional Belgian gas network, as well as other real larger networks. The results demonstrate both the accuracy and computational speed of the relaxation and its ability to produce high-quality solution« less

Solution of a Complex Least Squares Problem with Constrained Phase.

PubMed

Bydder, Mark

2010-12-30

The least squares solution of a complex linear equation is in general a complex vector with independent real and imaginary parts. In certain applications in magnetic resonance imaging, a solution is desired such that each element has the same phase. A direct method for obtaining the least squares solution to the phase constrained problem is described.

A simple model clarifies the complicated relationships of complex networks

PubMed Central

Zheng, Bojin; Wu, Hongrun; Kuang, Li; Qin, Jun; Du, Wenhua; Wang, Jianmin; Li, Deyi

2014-01-01

Real-world networks such as the Internet and WWW have many common traits. Until now, hundreds of models were proposed to characterize these traits for understanding the networks. Because different models used very different mechanisms, it is widely believed that these traits origin from different causes. However, we find that a simple model based on optimisation can produce many traits, including scale-free, small-world, ultra small-world, Delta-distribution, compact, fractal, regular and random networks. Moreover, by revising the proposed model, the community-structure networks are generated. By this model and the revised versions, the complicated relationships of complex networks are illustrated. The model brings a new universal perspective to the understanding of complex networks and provide a universal method to model complex networks from the viewpoint of optimisation. PMID:25160506

Discrete particle swarm optimization for identifying community structures in signed social networks.

PubMed

Cai, Qing; Gong, Maoguo; Shen, Bo; Ma, Lijia; Jiao, Licheng

2014-10-01

Modern science of networks has facilitated us with enormous convenience to the understanding of complex systems. Community structure is believed to be one of the notable features of complex networks representing real complicated systems. Very often, uncovering community structures in networks can be regarded as an optimization problem, thus, many evolutionary algorithms based approaches have been put forward. Particle swarm optimization (PSO) is an artificial intelligent algorithm originated from social behavior such as birds flocking and fish schooling. PSO has been proved to be an effective optimization technique. However, PSO was originally designed for continuous optimization which confounds its applications to discrete contexts. In this paper, a novel discrete PSO algorithm is suggested for identifying community structures in signed networks. In the suggested method, particles' status has been redesigned in discrete form so as to make PSO proper for discrete scenarios, and particles' updating rules have been reformulated by making use of the topology of the signed network. Extensive experiments compared with three state-of-the-art approaches on both synthetic and real-world signed networks demonstrate that the proposed method is effective and promising. Copyright © 2014 Elsevier Ltd. All rights reserved.

Generalized Hough Transform for Object Classification in the Maritime Domain

DTIC Science & Technology

2015-12-01

and memory storage problems of the GHT in this work . Neural networks have been used to provide excellent solutions to real-world problems in many...1 A. THESIS OBJECTIVE ...............................................................................1 B. RELATED WORK ...SIGNIFICANT CONTRIBUTIONS ......................................................47  B.  RECOMMENDATIONS FOR FUTURE WORK ................................48

The Real World of the Beginning Teacher.

ERIC Educational Resources Information Center

National Education Association, Washington, DC. National Commission on Teacher Education and Professional Standards.

Problems and goals of beginning teachers are the subject of these speeches presented by both experienced and beginning teachers at the 1965 national conference of the National Commission on Teacher Education and Professional Standards. The problems include the differences between teacher expectations and encounters, unrealistic teaching and…

Strategies to Support Students' Mathematical Modeling

ERIC Educational Resources Information Center

Jung, Hyunyi

2015-01-01

An important question for mathematics teachers is this: "How can we help students learn mathematics to solve everyday problems, rather than teaching them only to memorize rules and practice mathematical procedures?" Teaching students using modeling activities can help them learn mathematics in real-world problem-solving situations that…

Mathematics and Water in the Garden: Weaving Mathematics into the Students' Lived Environment

ERIC Educational Resources Information Center

Clarkson, Philip

2010-01-01

In an earlier issue of "Australian Primary Mathematics Classroom," Sparrow discussed the concept of real-world mathematics and the use of mathematics to explore problems in real-life situations. Environmental issues have provided a context that some teachers have used for teaching mathematics. An example of a particular environmental…

Using Technology to Facilitate and Enhance Project-based Learning in Mathematical Physics

NASA Astrophysics Data System (ADS)

Duda, Gintaras

2011-04-01

Problem-based and project-based learning are two pedagogical techniques that have several clear advantages over traditional instructional methods: 1) both techniques are active and student centered, 2) students confront real-world and/or highly complex problems, and 3) such exercises model the way science and engineering are done professionally. This talk will present an experiment in project/problem-based learning in a mathematical physics course. The group project in the course involved modeling a zombie outbreak of the type seen in AMC's ``The Walking Dead.'' Students researched, devised, and solved their mathematical models for the spread of zombie-like infection. Students used technology in all stages; in fact, since analytical solutions to the models were often impossible, technology was a necessary and critical component of the challenge. This talk will explore the use of technology in general in problem and project-based learning and will detail some specific examples of how technology was used to enhance student learning in this course. A larger issue of how students use the Internet to learn will also be explored.

Towards a Framework of Using Knowledge Tools for Teaching by Solving Problems in Technology-Enhanced Learning Environment

ERIC Educational Resources Information Center

Kostousov, Sergei; Kudryavtsev, Dmitry

2017-01-01

Problem solving is a critical competency for modern world and also an effective way of learning. Education should not only transfer domain-specific knowledge to students, but also prepare them to solve real-life problems--to apply knowledge from one or several domains within specific situation. Problem solving as teaching tool is known for a long…

Complex eigenvalue extraction in NASTRAN by the tridiagonal reduction (FEER) method

NASA Technical Reports Server (NTRS)

Newman, M.; Mann, F. I.

1977-01-01

An extension of the Tridiagonal Reduction (FEER) method to complex eigenvalue analysis in NASTRAN is described. As in the case of real eigenvalue analysis, the eigensolutions closest to a selected point in the eigenspectrum are extracted from a reduced, symmetric, tridiagonal eigenmatrix whose order is much lower than that of the full size problem. The reduction process is effected automatically, and thus avoids the arbitrary lumping of masses and other physical quantities at selected grid points. The statement of the algebraic eigenvalue problem admits mass, damping and stiffness matrices which are unrestricted in character, i.e., they may be real, complex, symmetric or unsymmetric, singular or non-singular.

An intelligent telecardiology system using a wearable and wireless ECG to detect atrial fibrillation.

PubMed

Lin, Chin-Teng; Chang, Kuan-Cheng; Lin, Chun-Ling; Chiang, Chia-Cheng; Lu, Shao-Wei; Chang, Shih-Sheng; Lin, Bor-Shyh; Liang, Hsin-Yueh; Chen, Ray-Jade; Lee, Yuan-Teh; Ko, Li-Wei

2010-05-01

This study presents a novel wireless, ambulatory, real-time, and autoalarm intelligent telecardiology system to improve healthcare for cardiovascular disease, which is one of the most prevalent and costly health problems in the world. This system consists of a lightweight and power-saving wireless ECG device equipped with a built-in automatic warning expert system. This device is connected to a mobile and ubiquitous real-time display platform. The acquired ECG signals are instantaneously transmitted to mobile devices, such as netbooks or mobile phones through Bluetooth, and then, processed by the expert system. An alert signal is sent to the remote database server, which can be accessed by an Internet browser, once an abnormal ECG is detected. The current version of the expert system can identify five types of abnormal cardiac rhythms in real-time, including sinus tachycardia, sinus bradycardia, wide QRS complex, atrial fibrillation (AF), and cardiac asystole, which is very important for both the subjects who are being monitored and the healthcare personnel tracking cardiac-rhythm disorders. The proposed system also activates an emergency medical alarm system when problems occur. Clinical testing reveals that the proposed system is approximately 94% accurate, with high sensitivity, specificity, and positive prediction rates for ten normal subjects and 20 AF patients. We believe that in the future a business-card-like ECG device, accompanied with a mobile phone, can make universal cardiac protection service possible.

A brief history of the most remarkable numbers e, i and γ in mathematical sciences with applications

NASA Astrophysics Data System (ADS)

Debnath, Lokenath

2015-08-01

This paper deals with a brief history of the most remarkable Euler numbers e, i and γ in mathematical sciences. Included are many properties of the constants e, i and γ and their applications in algebra, geometry, physics, chemistry, ecology, business and industry. Special attention is given to the growth and decay phenomena in many real-world problems including stability and instability of their solutions. Some specific and modern applications of logarithms, complex numbers and complex exponential functions to electrical circuits and mechanical systems are presented with examples. Included are the use of complex numbers and complex functions in the description and analysis of chaos and fractals with the aid of modern computer technology. In addition, the phasor method is described with examples of applications in engineering science. The major focus of this paper is to provide basic information through historical approach to mathematics teaching and learning of the fundamental knowledge and skills required for students and teachers at all levels so that they can understand the concepts of mathematics, and mathematics education in science and technology.

On mining complex sequential data by means of FCA and pattern structures

NASA Astrophysics Data System (ADS)

Buzmakov, Aleksey; Egho, Elias; Jay, Nicolas; Kuznetsov, Sergei O.; Napoli, Amedeo; Raïssi, Chedy

2016-02-01

Nowadays data-sets are available in very complex and heterogeneous ways. Mining of such data collections is essential to support many real-world applications ranging from healthcare to marketing. In this work, we focus on the analysis of "complex" sequential data by means of interesting sequential patterns. We approach the problem using the elegant mathematical framework of formal concept analysis and its extension based on "pattern structures". Pattern structures are used for mining complex data (such as sequences or graphs) and are based on a subsumption operation, which in our case is defined with respect to the partial order on sequences. We show how pattern structures along with projections (i.e. a data reduction of sequential structures) are able to enumerate more meaningful patterns and increase the computing efficiency of the approach. Finally, we show the applicability of the presented method for discovering and analysing interesting patient patterns from a French healthcare data-set on cancer. The quantitative and qualitative results (with annotations and analysis from a physician) are reported in this use-case which is the main motivation for this work.

Iterative Minimum Variance Beamformer with Low Complexity for Medical Ultrasound Imaging.

PubMed

Deylami, Ali Mohades; Asl, Babak Mohammadzadeh

2018-06-04

Minimum variance beamformer (MVB) improves the resolution and contrast of medical ultrasound images compared with delay and sum (DAS) beamformer. The weight vector of this beamformer should be calculated for each imaging point independently, with a cost of increasing computational complexity. The large number of necessary calculations limits this beamformer to application in real-time systems. A beamformer is proposed based on the MVB with lower computational complexity while preserving its advantages. This beamformer avoids matrix inversion, which is the most complex part of the MVB, by solving the optimization problem iteratively. The received signals from two imaging points close together do not vary much in medical ultrasound imaging. Therefore, using the previously optimized weight vector for one point as initial weight vector for the new neighboring point can improve the convergence speed and decrease the computational complexity. The proposed method was applied on several data sets, and it has been shown that the method can regenerate the results obtained by the MVB while the order of complexity is decreased from O(L 3 ) to O(L 2 ). Copyright © 2018 World Federation for Ultrasound in Medicine and Biology. Published by Elsevier Inc. All rights reserved.

Enhancing Navigation Skills through Audio Gaming.

PubMed

Sánchez, Jaime; Sáenz, Mauricio; Pascual-Leone, Alvaro; Merabet, Lotfi

2010-01-01

We present the design, development and initial cognitive evaluation of an Audio-based Environment Simulator (AbES). This software allows a blind user to navigate through a virtual representation of a real space for the purposes of training orientation and mobility skills. Our findings indicate that users feel satisfied and self-confident when interacting with the audio-based interface, and the embedded sounds allow them to correctly orient themselves and navigate within the virtual world. Furthermore, users are able to transfer spatial information acquired through virtual interactions into real world navigation and problem solving tasks.

Analytical Chemistry: A Literary Approach

NASA Astrophysics Data System (ADS)

Lucy, Charles A.

2000-04-01

The benefits of incorporating real-world examples of chemistry into lectures and lessons is reflected by the recent inclusion of the Teaching with Problems and Case Studies column in this Journal. However, these examples lie outside the experience of many students, and so much of the impact of "real-world" examples is lost. This paper provides an anthology of references to analytical chemistry techniques from history, popular fiction, and film. Such references are amusing to both instructor and student. Further, the fictional descriptions can serve as a focal point for discussions of a technique's true capabilities and limitations.

In the DNA Exoneration Cases, Eyewitness Memory Was Not the Problem: A Reply to Berkowitz and Frenda (2018) and Wade, Nash, and Lindsay (2018).

PubMed

Wixted, John T; Mickes, Laura; Fisher, Ronald P

2018-05-01

The available real-world evidence suggests that, on an initial test, eyewitness memory is often reliable. Ironically, even the DNA exoneration cases-which generally involved nonpristine testing conditions and which are usually construed as an indictment of eyewitness memory-show how reliable an initial test of eyewitness memory can be in the real world. We endorse the use of pristine testing procedures, but their absence does not automatically imply that eyewitness memory is unreliable.

Enhancing Navigation Skills through Audio Gaming

PubMed Central

Sánchez, Jaime; Sáenz, Mauricio; Pascual-Leone, Alvaro; Merabet, Lotfi

2014-01-01

We present the design, development and initial cognitive evaluation of an Audio-based Environment Simulator (AbES). This software allows a blind user to navigate through a virtual representation of a real space for the purposes of training orientation and mobility skills. Our findings indicate that users feel satisfied and self-confident when interacting with the audio-based interface, and the embedded sounds allow them to correctly orient themselves and navigate within the virtual world. Furthermore, users are able to transfer spatial information acquired through virtual interactions into real world navigation and problem solving tasks. PMID:25505796

"Fast" Is Not "Real-Time": Designing Effective Real-Time AI Systems

NASA Astrophysics Data System (ADS)

O'Reilly, Cindy A.; Cromarty, Andrew S.

1985-04-01

Realistic practical problem domains (such as robotics, process control, and certain kinds of signal processing) stand to benefit greatly from the application of artificial intelligence techniques. These problem domains are of special interest because they are typified by complex dynamic environments in which the ability to select and initiate a proper response to environmental events in real time is a strict prerequisite to effective environmental interaction. Artificial intelligence systems developed to date have been sheltered from this real-time requirement, however, largely by virtue of their use of simplified problem domains or problem representations. The plethora of colloquial and (in general) mutually inconsistent interpretations of the term "real-time" employed by workers in each of these domains further exacerbates the difficul-ties in effectively applying state-of-the-art problem solving tech-niques to time-critical problems. Indeed, the intellectual waters are by now sufficiently muddied that the pursuit of a rigorous treatment of intelligent real-time performance mandates the redevelopment of proper problem perspective on what "real-time" means, starting from first principles. We present a simple but nonetheless formal definition of real-time performance. We then undertake an analysis of both conventional techniques and AI technology with respect to their ability to meet substantive real-time performance criteria. This analysis provides a basis for specification of problem-independent design requirements for systems that would claim real-time performance. Finally, we discuss the application of these design principles to a pragmatic problem in real-time signal understanding.

Global World: A Problem of Governance

ERIC Educational Resources Information Center

Chumakov, Alexander Nikolayevich

2014-01-01

Purpose: The purpose of this paper is to include the following items: to show the absolute necessity of managing the international community, to explore the fundamental possibility of managing the global world, to prove or disprove such a possibility, to determine the real background of global governance in modern conditions and to show the…

An Investigation into Cooperative Learning in a Virtual World Using Problem-Based Learning

ERIC Educational Resources Information Center

Parson, Vanessa; Bignell, Simon

2017-01-01

Three-dimensional multi-user virtual environments (MUVEs) have the potential to provide experiential learning qualitatively similar to that found in the real world. MUVEs offer a pedagogically-driven immersive learning opportunity for educationalists that is cost-effective and enjoyable. A family of digital virtual avatars was created within…

Design of a Prototype Mobile Application to Make Mathematics Education More Realistic

ERIC Educational Resources Information Center

Jordaan, Dawid B.; Laubscher, Dorothy J.; Blignaut, A. Seugnet

2017-01-01

To enter the world of work, students require skills which include flexibility, critical thinking, problem solving, collaboration and communication. The use of mobile technologies which are specifically created for a context could stimulate motivation in students to recognise the relevance of Mathematics in the real world. South Africa in…

Performance of a Modern Glucose Meter in ICU and General Hospital Inpatients: 3 Years of Real-World Paired Meter and Central Laboratory Results.

PubMed

Zhang, Ray; Isakow, Warren; Kollef, Marin H; Scott, Mitchell G

2017-09-01

Due to accuracy concerns, the Food and Drug Administration issued guidances to manufacturers that resulted in Center for Medicare and Medicaid Services stating that the use of meters in critically ill patients is "off-label" and constitutes "high complexity" testing. This is causing significant workflow problems in ICUs nationally. We wished to determine whether real-world accuracy of modern glucose meters is worse in ICU patients compared with non-ICU inpatients. We reviewed glucose results over the preceding 3 years, comparing results from paired glucose meter and central laboratory tests performed within 60 minutes of each other in ICU versus non-ICU settings. Seven ICU and 30 non-ICU wards at a 1,300-bed academic hospital in the United States. A total of 14,763 general medicine/surgery inpatients and 20,970 ICU inpatients. None. Compared meter results with near simultaneously performed laboratory results from the same patient by applying the 2016 U.S. Food and Drug Administration accuracy criteria, determining mean absolute relative difference and examining where paired results fell within the Parkes consensus error grid zones. A higher percentage of glucose meter results from ICUs than from non-ICUs passed 2016 Food and Drug Administration accuracy criteria (p < 10) when comparing meter results with laboratory results. At 1 minute, no meter result from ICUs posed dangerous or significant risk by error grid analysis, whereas at 10 minutes, less than 0.1% of ICU meter results did, which was not statistically different from non-ICU results. Real-world accuracy of modern glucose meters is at least as accurate in the ICU setting as in the non-ICU setting at our institution.

GODDESS: A Goal-Directed Decision Structuring System.

DTIC Science & Technology

1980-06-01

differ- ent support techniques. From a practical viewpoint, though, the major drawback of manual interviews is their length and cost. Since real - time ...conducting his future inquiries. A direct man-machine interface could provide three distinct advantages. First, it offers the capability of real - time ...knowledge in tree form. In many real -world applications, the decision maker may not perceive a problem in the form of a time sequence of decision

Advanced biologically plausible algorithms for low-level image processing

NASA Astrophysics Data System (ADS)

Gusakova, Valentina I.; Podladchikova, Lubov N.; Shaposhnikov, Dmitry G.; Markin, Sergey N.; Golovan, Alexander V.; Lee, Seong-Whan

1999-08-01

At present, in computer vision, the approach based on modeling the biological vision mechanisms is extensively developed. However, up to now, real world image processing has no effective solution in frameworks of both biologically inspired and conventional approaches. Evidently, new algorithms and system architectures based on advanced biological motivation should be developed for solution of computational problems related to this visual task. Basic problems that should be solved for creation of effective artificial visual system to process real world imags are a search for new algorithms of low-level image processing that, in a great extent, determine system performance. In the present paper, the result of psychophysical experiments and several advanced biologically motivated algorithms for low-level processing are presented. These algorithms are based on local space-variant filter, context encoding visual information presented in the center of input window, and automatic detection of perceptually important image fragments. The core of latter algorithm are using local feature conjunctions such as noncolinear oriented segment and composite feature map formation. Developed algorithms were integrated into foveal active vision model, the MARR. It is supposed that proposed algorithms may significantly improve model performance while real world image processing during memorizing, search, and recognition.

Nonlinearly Activated Neural Network for Solving Time-Varying Complex Sylvester Equation.

PubMed

Li, Shuai; Li, Yangming

2013-10-28

The Sylvester equation is often encountered in mathematics and control theory. For the general time-invariant Sylvester equation problem, which is defined in the domain of complex numbers, the Bartels-Stewart algorithm and its extensions are effective and widely used with an O(n³) time complexity. When applied to solving the time-varying Sylvester equation, the computation burden increases intensively with the decrease of sampling period and cannot satisfy continuous realtime calculation requirements. For the special case of the general Sylvester equation problem defined in the domain of real numbers, gradient-based recurrent neural networks are able to solve the time-varying Sylvester equation in real time, but there always exists an estimation error while a recently proposed recurrent neural network by Zhang et al [this type of neural network is called Zhang neural network (ZNN)] converges to the solution ideally. The advancements in complex-valued neural networks cast light to extend the existing real-valued ZNN for solving the time-varying real-valued Sylvester equation to its counterpart in the domain of complex numbers. In this paper, a complex-valued ZNN for solving the complex-valued Sylvester equation problem is investigated and the global convergence of the neural network is proven with the proposed nonlinear complex-valued activation functions. Moreover, a special type of activation function with a core function, called sign-bi-power function, is proven to enable the ZNN to converge in finite time, which further enhances its advantage in online processing. In this case, the upper bound of the convergence time is also derived analytically. Simulations are performed to evaluate and compare the performance of the neural network with different parameters and activation functions. Both theoretical analysis and numerical simulations validate the effectiveness of the proposed method.

Enabling complex genetic circuits to respond to extrinsic environmental signals.

PubMed

Hoynes-O'Connor, Allison; Shopera, Tatenda; Hinman, Kristina; Creamer, John Philip; Moon, Tae Seok

2017-07-01

Genetic circuits have the potential to improve a broad range of metabolic engineering processes and address a variety of medical and environmental challenges. However, in order to engineer genetic circuits that can meet the needs of these real-world applications, genetic sensors that respond to relevant extrinsic and intrinsic signals must be implemented in complex genetic circuits. In this work, we construct the first AND and NAND gates that respond to temperature and pH, two signals that have relevance in a variety of real-world applications. A previously identified pH-responsive promoter and a temperature-responsive promoter were extracted from the E. coli genome, characterized, and modified to suit the needs of the genetic circuits. These promoters were combined with components of the type III secretion system in Salmonella typhimurium and used to construct a set of AND gates with up to 23-fold change. Next, an antisense RNA was integrated into the circuit architecture to invert the logic of the AND gate and generate a set of NAND gates with up to 1168-fold change. These circuits provide the first demonstration of complex pH- and temperature-responsive genetic circuits, and lay the groundwork for the use of similar circuits in real-world applications. Biotechnol. Bioeng. 2017;114: 1626-1631. © 2017 Wiley Periodicals, Inc. © 2017 Wiley Periodicals, Inc.

The influence of professional expertise and task complexity upon the potency of the contextual interference effect.

PubMed

Ollis, Stewart; Button, Chris; Fairweather, Malcolm

2005-03-01

The contextual interference (CI) effect has been investigated through practice schedule manipulations within both basic and applied studies. Despite extensive research activity there is little conclusive evidence regarding the optimal practice structure of real world manipulative tasks in professional training settings. The present study therefore assessed the efficacy of practising simple and complex knot-tying skills in professional fire-fighters training. Forty-eight participants were quasi-randomly assigned to various practice schedules along the CI continuum. Twenty-four participants were students selected for their novice knot-tying capabilities and 24 were experienced fire-fighters who were more 'experienced knot-tiers'. They were assessed for skill acquisition, retention and transfer effects having practiced tying knots classified as simple or complex. Surprisingly, high levels of CI scheduling enhance learning for novices even when practising a complex task. The findings also revealed that CI benefits are most apparent as learners engage in tasks high in transfer distality. In conclusion, complexity and experience are mediating factors influencing the potency of the CI training effect in real-world settings.

Problems and Trends Regarding Vocational Teachers in China

ERIC Educational Resources Information Center

Kuang, Ying

2014-01-01

At present, China's vocational education system is undergoing a transition process from growing in size to improving in quality. Teacher and teaching force issues are a bottleneck and critical factor that will determine whether the transformation will be successful. The real-world problems of the number, deployment, capacity, and training systems…

A Laboratory Exercise with Related Rates.

ERIC Educational Resources Information Center

Sworder, Steven C.

A laboratory experiment, based on a simple electric circuit that can be used to demonstrate the existence of real-world "related rates" problems, is outlined and an equation for voltage across the capacitor terminals during discharge is derived. The necessary materials, setup methods, and experimental problems are described. A student laboratory…

Ingenuity in Action: Connecting Tinkering to Engineering Design Processes

ERIC Educational Resources Information Center

Wang, Jennifer; Werner-Avidon, Maia; Newton, Lisa; Randol, Scott; Smith, Brooke; Walker, Gretchen

2013-01-01

The Lawrence Hall of Science, a science center, seeks to replicate real-world engineering at the "Ingenuity in Action" exhibit, which consists of three open-ended challenges. These problems encourage children to engage in engineering design processes and problem-solving techniques through tinkering. We observed and interviewed 112…

Guide to Mathematics Released Items: Understanding Scoring

ERIC Educational Resources Information Center

Partnership for Assessment of Readiness for College and Careers, 2017

2017-01-01

The Partnership for Assessment of Readiness for College and Careers (PARCC) mathematics items measure critical thinking, mathematical reasoning, and the ability to apply skills and knowledge to real-world problems. Students are asked to solve problems involving the key knowledge and skills for their grade level as identified by the Common Core…

Weather Tamers

ERIC Educational Resources Information Center

Frazier, Wendy M.; Sterling, Donna R.

2007-01-01

Problem-based learning experiences that extend at least two weeks provide an opportunity for students to investigate a real-world problem while learning science content and skills in an exciting way. In this article, students are challenged by the president of the United States to serve as employees of the Federal Emergency Management Agency to…

Toying with Technology.

ERIC Educational Resources Information Center

Foster, Patrick; Kirkwood, James

1993-01-01

Suggests that technology education is much more than simply computer literacy and must emphasize real-world problem solving and hands-on learning. Provides examples of activities, such as the construction of a model city out of scrap wood, that can be carried out with students in grades one through four to develop problem-solving skills. (MDM)

Connecting Learning & Technology for Effective Lesson Plan Design.

ERIC Educational Resources Information Center

Seamon, Mary P.

This paper focuses on the design of effective lesson plans using the Internet. Effective lesson design helps students to explore ideas, acquire and synthesize information, and frame and solve problems. The creative problem solving which depends upon context, interrelationships, and real-world activities is available through Internet projects.…

Prizes in Cereal Boxes: An Application of Probability.

ERIC Educational Resources Information Center

Litwiller, Bonnie H.; Duncan, David R.

1992-01-01

Presents four cases of real-world probabilistic situations to promote more effective teaching of probability. Calculates the probability of obtaining six of six different prizes successively in six, seven, eight, and nine boxes of cereal, generalizes the problem to n boxes of cereal, and offers suggestions to extend the problem. (MDH)

Camera calibration correction in shape from inconsistent silhouette

USDA-ARS?s Scientific Manuscript database

The use of shape from silhouette for reconstruction tasks is plagued by two types of real-world errors: camera calibration error and silhouette segmentation error. When either error is present, we call the problem the Shape from Inconsistent Silhouette (SfIS) problem. In this paper, we show how sm...

Sustainable Schools through Science Across the World

ERIC Educational Resources Information Center

Cutler, Marianne

2007-01-01

Children need new skills if they are to become part of the solution to challenges such as climate change rather than part of the problem. So states the UK's National Framework for Sustainable Schools. Skills include expressing points of view, weighing up evidence, cooperating, thinking critically, tackling real problems, participating in…

Bringing Management Reality into the Classroom--The Development of Interactive Learning.

ERIC Educational Resources Information Center

Nicholson, Alastair

1997-01-01

Effective learning in management education can be enhanced by reproducing the real-world need to solve problems under pressure of time, inadequate information, and group interaction. An interactive classroom communication system involving problems in decision making and continuous improvement is one method for bridging theory and practice. (SK)

Small-world bias of correlation networks: From brain to climate

NASA Astrophysics Data System (ADS)

Hlinka, Jaroslav; Hartman, David; Jajcay, Nikola; Tomeček, David; Tintěra, Jaroslav; Paluš, Milan

2017-03-01

Complex systems are commonly characterized by the properties of their graph representation. Dynamical complex systems are then typically represented by a graph of temporal dependencies between time series of state variables of their subunits. It has been shown recently that graphs constructed in this way tend to have relatively clustered structure, potentially leading to spurious detection of small-world properties even in the case of systems with no or randomly distributed true interactions. However, the strength of this bias depends heavily on a range of parameters and its relevance for real-world data has not yet been established. In this work, we assess the relevance of the bias using two examples of multivariate time series recorded in natural complex systems. The first is the time series of local brain activity as measured by functional magnetic resonance imaging in resting healthy human subjects, and the second is the time series of average monthly surface air temperature coming from a large reanalysis of climatological data over the period 1948-2012. In both cases, the clustering in the thresholded correlation graph is substantially higher compared with a realization of a density-matched random graph, while the shortest paths are relatively short, showing thus distinguishing features of small-world structure. However, comparable or even stronger small-world properties were reproduced in correlation graphs of model processes with randomly scrambled interconnections. This suggests that the small-world properties of the correlation matrices of these real-world systems indeed do not reflect genuinely the properties of the underlying interaction structure, but rather result from the inherent properties of correlation matrix.

Small-world bias of correlation networks: From brain to climate.

PubMed

Hlinka, Jaroslav; Hartman, David; Jajcay, Nikola; Tomeček, David; Tintěra, Jaroslav; Paluš, Milan

2017-03-01

Complex systems are commonly characterized by the properties of their graph representation. Dynamical complex systems are then typically represented by a graph of temporal dependencies between time series of state variables of their subunits. It has been shown recently that graphs constructed in this way tend to have relatively clustered structure, potentially leading to spurious detection of small-world properties even in the case of systems with no or randomly distributed true interactions. However, the strength of this bias depends heavily on a range of parameters and its relevance for real-world data has not yet been established. In this work, we assess the relevance of the bias using two examples of multivariate time series recorded in natural complex systems. The first is the time series of local brain activity as measured by functional magnetic resonance imaging in resting healthy human subjects, and the second is the time series of average monthly surface air temperature coming from a large reanalysis of climatological data over the period 1948-2012. In both cases, the clustering in the thresholded correlation graph is substantially higher compared with a realization of a density-matched random graph, while the shortest paths are relatively short, showing thus distinguishing features of small-world structure. However, comparable or even stronger small-world properties were reproduced in correlation graphs of model processes with randomly scrambled interconnections. This suggests that the small-world properties of the correlation matrices of these real-world systems indeed do not reflect genuinely the properties of the underlying interaction structure, but rather result from the inherent properties of correlation matrix.

Modes of Interaction between Individuals Dominate the Topologies of Real World Networks

PubMed Central

Lee, Insuk; Kim, Eiru; Marcotte, Edward M.

2015-01-01

We find that the topologies of real world networks, such as those formed within human societies, by the Internet, or among cellular proteins, are dominated by the mode of the interactions considered among the individuals. Specifically, a major dichotomy in previously studied networks arises from modeling networks in terms of pairwise versus group tasks. The former often intrinsically give rise to scale-free, disassortative, hierarchical networks, whereas the latter often give rise to single- or broad-scale, assortative, nonhierarchical networks. These dependencies explain contrasting observations among previous topological analyses of real world complex systems. We also observe this trend in systems with natural hierarchies, in which alternate representations of the same networks, but which capture different levels of the hierarchy, manifest these signature topological differences. For example, in both the Internet and cellular proteomes, networks of lower-level system components (routers within domains or proteins within biological processes) are assortative and nonhierarchical, whereas networks of upper-level system components (internet domains or biological processes) are disassortative and hierarchical. Our results demonstrate that network topologies of complex systems must be interpreted in light of their hierarchical natures and interaction types. PMID:25793969

Local spatial frequency analysis for computer vision

NASA Technical Reports Server (NTRS)

Krumm, John; Shafer, Steven A.

1990-01-01

A sense of vision is a prerequisite for a robot to function in an unstructured environment. However, real-world scenes contain many interacting phenomena that lead to complex images which are difficult to interpret automatically. Typical computer vision research proceeds by analyzing various effects in isolation (e.g., shading, texture, stereo, defocus), usually on images devoid of realistic complicating factors. This leads to specialized algorithms which fail on real-world images. Part of this failure is due to the dichotomy of useful representations for these phenomena. Some effects are best described in the spatial domain, while others are more naturally expressed in frequency. In order to resolve this dichotomy, we present the combined space/frequency representation which, for each point in an image, shows the spatial frequencies at that point. Within this common representation, we develop a set of simple, natural theories describing phenomena such as texture, shape, aliasing and lens parameters. We show these theories lead to algorithms for shape from texture and for dealiasing image data. The space/frequency representation should be a key aid in untangling the complex interaction of phenomena in images, allowing automatic understanding of real-world scenes.

Efficient weighting strategy for enhancing synchronizability of complex networks

NASA Astrophysics Data System (ADS)

Wang, Youquan; Yu, Feng; Huang, Shucheng; Tu, Juanjuan; Chen, Yan

2018-04-01

Networks with high propensity to synchronization are desired in many applications ranging from biology to engineering. In general, there are two ways to enhance the synchronizability of a network: link rewiring and/or link weighting. In this paper, we propose a new link weighting strategy based on the concept of the neighborhood subgroup. The neighborhood subgroup of a node i through node j in a network, i.e. Gi→j, means that node u belongs to Gi→j if node u belongs to the first-order neighbors of j (not include i). Our proposed weighting schema used the local and global structural properties of the networks such as the node degree, betweenness centrality and closeness centrality measures. We applied the method on scale-free and Watts-Strogatz networks of different structural properties and show the good performance of the proposed weighting scheme. Furthermore, as model networks cannot capture all essential features of real-world complex networks, we considered a number of undirected and unweighted real-world networks. To the best of our knowledge, the proposed weighting strategy outperformed the previously published weighting methods by enhancing the synchronizability of these real-world networks.

Breakdown of interdependent directed networks.

PubMed

Liu, Xueming; Stanley, H Eugene; Gao, Jianxi

2016-02-02

Increasing evidence shows that real-world systems interact with one another via dependency connectivities. Failing connectivities are the mechanism behind the breakdown of interacting complex systems, e.g., blackouts caused by the interdependence of power grids and communication networks. Previous research analyzing the robustness of interdependent networks has been limited to undirected networks. However, most real-world networks are directed, their in-degrees and out-degrees may be correlated, and they are often coupled to one another as interdependent directed networks. To understand the breakdown and robustness of interdependent directed networks, we develop a theoretical framework based on generating functions and percolation theory. We find that for interdependent Erdős-Rényi networks the directionality within each network increases their vulnerability and exhibits hybrid phase transitions. We also find that the percolation behavior of interdependent directed scale-free networks with and without degree correlations is so complex that two criteria are needed to quantify and compare their robustness: the percolation threshold and the integrated size of the giant component during an entire attack process. Interestingly, we find that the in-degree and out-degree correlations in each network layer increase the robustness of interdependent degree heterogeneous networks that most real networks are, but decrease the robustness of interdependent networks with homogeneous degree distribution and with strong coupling strengths. Moreover, by applying our theoretical analysis to real interdependent international trade networks, we find that the robustness of these real-world systems increases with the in-degree and out-degree correlations, confirming our theoretical analysis.

What to Do Until the Money Runs Out: A Refinement Framework for Cognitive Engineering in the Real World

NASA Technical Reports Server (NTRS)

Shafto, Michael G.; Remington, Roger W.; Trimble, Jay W.

1994-01-01

A case study is presented to illustrate some of the problems of applying cognitive science to complex human-machine systems. Disregard for facts about human cognition often undermines the safety, reliability, and cost-effectiveness of complex systems. Yet single-point methods (for example, better user-interface design), whether rooted in computer science or in experimental psychology, fall far short of addressing systems-level problems in a timely way using realistic resources. A model-based methodology is proposed for organizing and prioritizing the cognitive engineering effort, focusing appropriate expertise on major problems first, then moving to more sophisticated refinements if time and resources permit. This case study is based on a collaborative effort between the Human Factors Division at NASA-Ames and the Spaceborne Imaging Radar SIR-C/X-Band Synthetic Aperture Radar (SIR-C/X-SAR) Project at the Jet Propulsion Laboratory (JPL), California institute of Technology. The first SIR-C/X-SAR Shuttle mission flew successfully in April, 1994. A series of such missions is planned to provide radar data to study Earth's ecosystems, climatic and geological processes, hydrologic cycle, and ocean circulation. In addition to JPL and NASA personnel, the SIR-C/X-SAR operations team included Scientists and engineers from the German and Italian space agencies.

Balancing Bologna: opportunities for university teaching that integrates academic and practical learning outcomes

NASA Astrophysics Data System (ADS)

Probst, Lorenz; Pflug, Verena; Brandenburg, Christiane; Guggenberger, Thomas; Mentler, Axel; Wurzinger, Maria

2014-05-01

In the course of the Bologna Process, the quality of university teaching has become more prominent in the discourse on higher education. More attention is now paid to didactics and methods and learner-oriented modes of teaching are introduced. The application of knowledge, practical skills and in consequence the employability of university graduates have become requirements for university teaching. Yet, the lecture-style approach still dominates European universities, although empirical evidence confirms that student-centred, interdisciplinary and experiential learning is more effective. Referring to the learning taxonomy introduced by Bloom, we argue that standard approaches rarely move beyond the learning level of comprehension and fail to reach the levels of application, analysis, synthesis and evaluation. Considering the rapid changes and multiple challenges society faces today, responsible practitioners and scientists who can improve the current management of natural resources are urgently needed. Universities are expected to equip their graduates with the necessary skills to reflect and evaluate their actions when addressing 'real world' problems in order to improve impact and relevance of their work. Higher education thus faces the challenge of providing multi-level learning opportunities for students with diverse practical and theoretical learning needs. In this study, we reflect on three cases of university teaching attempting to bridge theory and practice and based on the principles of systemic, problem based learning. The described courses focus on organic farming, rural development and landscape planning and take place in Uganda, Nicaragua and Italy. We show that being part of a real-world community of stakeholders requires hands-on learning and the reflection and evaluation of actions. This prepares students in a more effective and realistic way for their future roles as responsible decision makers in complex social, economic and ecological systems. We thus conclude that in order (1) to meet the goals of the Bologna process; and (2) to bridge the gap between theory and practice in higher education, university teaching needs to radically reconsider its standard forms of teaching. We propose a fundamental shift towards action learning in real-world settings, empowering students to become responsible actors.

Science Classroom Inquiry (SCI) Simulations: A Novel Method to Scaffold Science Learning

PubMed Central

Peffer, Melanie E.; Beckler, Matthew L.; Schunn, Christian; Renken, Maggie; Revak, Amanda

2015-01-01

Science education is progressively more focused on employing inquiry-based learning methods in the classroom and increasing scientific literacy among students. However, due to time and resource constraints, many classroom science activities and laboratory experiments focus on simple inquiry, with a step-by-step approach to reach predetermined outcomes. The science classroom inquiry (SCI) simulations were designed to give students real life, authentic science experiences within the confines of a typical classroom. The SCI simulations allow students to engage with a science problem in a meaningful, inquiry-based manner. Three discrete SCI simulations were created as website applications for use with middle school and high school students. For each simulation, students were tasked with solving a scientific problem through investigation and hypothesis testing. After completion of the simulation, 67% of students reported a change in how they perceived authentic science practices, specifically related to the complex and dynamic nature of scientific research and how scientists approach problems. Moreover, 80% of the students who did not report a change in how they viewed the practice of science indicated that the simulation confirmed or strengthened their prior understanding. Additionally, we found a statistically significant positive correlation between students’ self-reported changes in understanding of authentic science practices and the degree to which each simulation benefitted learning. Since SCI simulations were effective in promoting both student learning and student understanding of authentic science practices with both middle and high school students, we propose that SCI simulations are a valuable and versatile technology that can be used to educate and inspire a wide range of science students on the real-world complexities inherent in scientific study. PMID:25786245

Science classroom inquiry (SCI) simulations: a novel method to scaffold science learning.

PubMed

Peffer, Melanie E; Beckler, Matthew L; Schunn, Christian; Renken, Maggie; Revak, Amanda

2015-01-01

Science education is progressively more focused on employing inquiry-based learning methods in the classroom and increasing scientific literacy among students. However, due to time and resource constraints, many classroom science activities and laboratory experiments focus on simple inquiry, with a step-by-step approach to reach predetermined outcomes. The science classroom inquiry (SCI) simulations were designed to give students real life, authentic science experiences within the confines of a typical classroom. The SCI simulations allow students to engage with a science problem in a meaningful, inquiry-based manner. Three discrete SCI simulations were created as website applications for use with middle school and high school students. For each simulation, students were tasked with solving a scientific problem through investigation and hypothesis testing. After completion of the simulation, 67% of students reported a change in how they perceived authentic science practices, specifically related to the complex and dynamic nature of scientific research and how scientists approach problems. Moreover, 80% of the students who did not report a change in how they viewed the practice of science indicated that the simulation confirmed or strengthened their prior understanding. Additionally, we found a statistically significant positive correlation between students' self-reported changes in understanding of authentic science practices and the degree to which each simulation benefitted learning. Since SCI simulations were effective in promoting both student learning and student understanding of authentic science practices with both middle and high school students, we propose that SCI simulations are a valuable and versatile technology that can be used to educate and inspire a wide range of science students on the real-world complexities inherent in scientific study.

Multi-layered reasoning by means of conceptual fuzzy sets

NASA Technical Reports Server (NTRS)

Takagi, Tomohiro; Imura, Atsushi; Ushida, Hirohide; Yamaguchi, Toru

1993-01-01

The real world consists of a very large number of instances of events and continuous numeric values. On the other hand, people represent and process their knowledge in terms of abstracted concepts derived from generalization of these instances and numeric values. Logic based paradigms for knowledge representation use symbolic processing both for concept representation and inference. Their underlying assumption is that a concept can be defined precisely. However, as this assumption hardly holds for natural concepts, it follows that symbolic processing cannot deal with such concepts. Thus symbolic processing has essential problems from a practical point of view of applications in the real world. In contrast, fuzzy set theory can be viewed as a stronger and more practical notation than formal, logic based theories because it supports both symbolic processing and numeric processing, connecting the logic based world and the real world. In this paper, we propose multi-layered reasoning by using conceptual fuzzy sets (CFS). The general characteristics of CFS are discussed along with upper layer supervision and context dependent processing.

Real-world effectiveness of 8 weeks treatment with ledipasvir/sofosbuvir in chronic hepatitis C.

PubMed

Buggisch, Peter; Zeuzem, Stefan

2018-05-11

We thank Ojha and Steyerberg for making a good point. Indeed, defining analyses populations of real-life observational studies as ITT or PP is problematic as this wording may suggest a higher comparability to clinical trials as is adequate. In principle, even refined methods for adjusting confounders and minimizing bias cannot fully resolve the inherent problem of confounders in such trials. In our paper the wording (ITT and PP) was chosen for comparability with similar previous observational studies (e.g. Zeng et al) and a lot of effort was made to make the definitions transparent by illustrating them in a Figure and mentioning them several times in the article. Furthermore, the results were carefully discussed and, overall, highly comparable with those from clinical trials. Therefore, potential overestimation of sustained response rates as illustrated and discussed in the letter by Ojha and Steyerberg seems to be a limited problem in our article about this real world data. Copyright © 2018. Published by Elsevier B.V.

Why Do They Stay: Factors Influencing Teacher Retention in Rural Zimbabwe

ERIC Educational Resources Information Center

Gomba, Clifford

2015-01-01

The attraction and retention of teachers in Zimbabwe is a problem not only unique to Zimbabwean schools, but all over the world. The problem is more pronounced in rural areas where resources are scarce, hence the tendency to repel teachers. Although the problem of teacher turnover is real, there are teachers who have remained in the profession for…

Hypercube technology

NASA Technical Reports Server (NTRS)

Parker, Jay W.; Cwik, Tom; Ferraro, Robert D.; Liewer, Paulett C.; Patterson, Jean E.

1991-01-01

The JPL designed MARKIII hypercube supercomputer has been in application service since June 1988 and has had successful application to a broad problem set including electromagnetic scattering, discrete event simulation, plasma transport, matrix algorithms, neural network simulation, image processing, and graphics. Currently, problems that are not homogeneous are being attempted, and, through this involvement with real world applications, the software is evolving to handle the heterogeneous class problems efficiently.

Distributed Cognition as a Lens to Understand the Effects of Scaffolds: The Role of Transfer of Responsibility

ERIC Educational Resources Information Center

Belland, Brian R.

2011-01-01

Problem solving is an important skill in the knowledge economy. Research indicates that the development of problem solving skills works better in the context of instructional approaches centered on real-world problems. But students need scaffolding to be successful in such instruction. In this paper I present a conceptual framework for…

Are Individual Differences in Performance on Perceptual and Cognitive Optimization Problems Determined by General Intelligence?

ERIC Educational Resources Information Center

Burns, Nicholas R.; Lee, Michael D.; Vickers, Douglas

2006-01-01

Studies of human problem solving have traditionally used deterministic tasks that require the execution of a systematic series of steps to reach a rational and optimal solution. Most real-world problems, however, are characterized by uncertainty, the need to consider an enormous number of variables and possible courses of action at each stage in…

Adapting Experiential Learning to Develop Problem-Solving Skills in Deaf and Hard-of-Hearing Engineering Students.

PubMed

Marshall, Matthew M; Carrano, Andres L; Dannels, Wendy A

2016-10-01

Individuals who are deaf and hard-of-hearing (DHH) are underrepresented in science, technology, engineering, and mathematics (STEM) professions, and this may be due in part to their level of preparation in the development and retention of mathematical and problem-solving skills. An approach was developed that incorporates experiential learning and best practices of STEM instruction to give first-year DHH students enrolled in a postsecondary STEM program the opportunity to develop problem-solving skills in real-world scenarios. Using an industrial engineering laboratory that provides manufacturing and warehousing environments, students were immersed in real-world scenarios in which they worked on teams to address prescribed problems encountered during the activities. The highly structured, Plan-Do-Check-Act approach commonly used in industry was adapted for the DHH student participants to document and communicate the problem-solving steps. Students who experienced the intervention realized a 14.6% improvement in problem-solving proficiency compared with a control group, and this gain was retained at 6 and 12 months, post-intervention. © The Author 2016. Published by Oxford University Press. All rights reserved. For Permissions, please email: journals.permissions@oup.com.

Notes about COOL: Analysis and Highlights of Complex View in Education

ERIC Educational Resources Information Center

de Oliveira, C. A.

2012-01-01

Purpose: The purpose of this paper is to present principles from the complex approach in education and describe some practical pedagogic experiences enhancing how "real world" perspectives have influenced and contributed to curriculum development. Design/methodology/approach: Necessity of integration in terms of knowledge modeling is an…

Measuring societal effects of transdisciplinary research projects: design and application of an evaluation method.

PubMed

Walter, Alexander I; Helgenberger, Sebastian; Wiek, Arnim; Scholz, Roland W

2007-11-01

Most Transdisciplinary Research (TdR) projects combine scientific research with the building of decision making capacity for the involved stakeholders. These projects usually deal with complex, societally relevant, real-world problems. This paper focuses on TdR projects, which integrate the knowledge of researchers and stakeholders in a collaborative transdisciplinary process through structured methods of mutual learning. Previous research on the evaluation of TdR has insufficiently explored the intended effects of transdisciplinary processes on the real world (societal effects). We developed an evaluation framework for assessing the societal effects of transdisciplinary processes. Outputs (measured as procedural and product-related involvement of the stakeholders), impacts (intermediate effects connecting outputs and outcomes) and outcomes (enhanced decision making capacity) are distinguished as three types of societal effects. Our model links outputs and outcomes of transdisciplinary processes via the impacts using a mediating variables approach. We applied this model in an ex post evaluation of a transdisciplinary process. 84 out of 188 agents participated in a survey. The results show significant mediation effects of the two impacts "network building" and "transformation knowledge". These results indicate an influence of a transdisciplinary process on the decision making capacity of stakeholders, especially through social network building and the generation of knowledge relevant for action.

Preschoolers' Quarantining of Fantasy Stories

ERIC Educational Resources Information Center

Richert, Rebekah A.; Smith, Erin I.

2011-01-01

Preschool-aged children are exposed to fantasy stories with the expectation that they will learn messages in those stories that are applied to real-world situations. We examined children's transfer from fantastical and real stories. Over the course of 2 studies, 3 1/2- to 5 1/2-year-old children were less likely to transfer problem solutions from…

Collaborative Invention in Computer Prototype Design: Negotiating Group Processes and Artifacts.

ERIC Educational Resources Information Center

Werner, Mark

A study looked at four groups of mostly senior graphic and industrial design students in their final semester capstone course--a collaborative studio project intended to give them the opportunity to apply their design expertise to real-world problems for real clients. The study examined the ways in which one of these groups used arguments to…

University Facilities as Real-World Foci of Multidisciplinary Science Learning

ERIC Educational Resources Information Center

Wojdak, Jeremy; Guinan, Judy; Wirgau, Joseph; Kugler, Charles; Hammond, Georgia; Small, Christine; Manyara, Charles; Singer, Frederick; Watts, Chester; Bodo, Bethany; Baldwin, Andrew

2010-01-01

The authors sought to better approximate the practice of "real" science in our classrooms by having students study a newly built storm-water remediation wetland on campus. The wetland was meant to gather and clean storm water running off of student parking lots--thus students had ownership in the problem and potential solution. Participating…

Using Student Agencies to Produce Mini-Campaigns in the Principles of Advertising Course.

ERIC Educational Resources Information Center

Lynn, Jerry R.; Gagnard, Alice L.

The use of mini-campaign projects in an introductory course in advertising can (1) provide students with actual experience in dealing with real advertising problems; (2) bring classroom lectures and laboratory assignments into a "real-world" perspective; (3) give students a broader perspective of advertising; (4) bring students into contact with…

Learning and Teaching Mathematics through Real Life Models

ERIC Educational Resources Information Center

Takaci, Djurdjica; Budinski, Natalija

2011-01-01

This paper proposes modelling based learning as a tool for learning and teaching mathematics in high school. We report on an example of modelling real world problems in two high schools in Serbia where students were introduced for the first time to the basic concepts of modelling. Student use of computers and educational software, GeoGebra, was…

Comparative analysis of two discretizations of Ricci curvature for complex networks.

PubMed

Samal, Areejit; Sreejith, R P; Gu, Jiao; Liu, Shiping; Saucan, Emil; Jost, Jürgen

2018-06-05

We have performed an empirical comparison of two distinct notions of discrete Ricci curvature for graphs or networks, namely, the Forman-Ricci curvature and Ollivier-Ricci curvature. Importantly, these two discretizations of the Ricci curvature were developed based on different properties of the classical smooth notion, and thus, the two notions shed light on different aspects of network structure and behavior. Nevertheless, our extensive computational analysis in a wide range of both model and real-world networks shows that the two discretizations of Ricci curvature are highly correlated in many networks. Moreover, we show that if one considers the augmented Forman-Ricci curvature which also accounts for the two-dimensional simplicial complexes arising in graphs, the observed correlation between the two discretizations is even higher, especially, in real networks. Besides the potential theoretical implications of these observations, the close relationship between the two discretizations has practical implications whereby Forman-Ricci curvature can be employed in place of Ollivier-Ricci curvature for faster computation in larger real-world networks whenever coarse analysis suffices.

On parameterization of the inverse problem for estimating aquifer properties using tracer data

NASA Astrophysics Data System (ADS)

Kowalsky, M. B.; Finsterle, S.; Williams, K. H.; Murray, C.; Commer, M.; Newcomer, D.; Englert, A.; Steefel, C. I.; Hubbard, S. S.

2012-06-01

In developing a reliable approach for inferring hydrological properties through inverse modeling of tracer data, decisions made on how to parameterize heterogeneity (i.e., how to represent a heterogeneous distribution using a limited number of parameters that are amenable to estimation) are of paramount importance, as errors in the model structure are partly compensated for by estimating biased property values during the inversion. These biased estimates, while potentially providing an improved fit to the calibration data, may lead to wrong interpretations and conclusions and reduce the ability of the model to make reliable predictions. We consider the estimation of spatial variations in permeability and several other parameters through inverse modeling of tracer data, specifically synthetic and actual field data associated with the 2007 Winchester experiment from the Department of Energy Rifle site. Characterization is challenging due to the real-world complexities associated with field experiments in such a dynamic groundwater system. Our aim is to highlight and quantify the impact on inversion results of various decisions related to parameterization, such as the positioning of pilot points in a geostatistical parameterization; the handling of up-gradient regions; the inclusion of zonal information derived from geophysical data or core logs; extension from 2-D to 3-D; assumptions regarding the gradient direction, porosity, and the semivariogram function; and deteriorating experimental conditions. This work adds to the relatively limited number of studies that offer guidance on the use of pilot points in complex real-world experiments involving tracer data (as opposed to hydraulic head data).

A Series of MATLAB Learning Modules to Enhance Numerical Competency in Applied Marine Sciences

NASA Astrophysics Data System (ADS)

Fischer, A. M.; Lucieer, V.; Burke, C.

2016-12-01

Enhanced numerical competency to navigate the massive data landscapes are critical skills students need to effectively explore, analyse and visualize complex patterns in high-dimensional data for addressing the complexity of many of the world's problems. This is especially the case for interdisciplinary, undergraduate applied marine science programs, where students are required to demonstrate competency in methods and ideas across multiple disciplines. In response to this challenge, we have developed a series of repository-based data exploration, analysis and visualization modules in MATLAB for integration across various attending and online classes within the University of Tasmania. The primary focus of these modules is to teach students to collect, aggregate and interpret data from large on-line marine scientific data repositories to, 1) gain technical skills in discovering, accessing, managing and visualising large, numerous data sources, 2) interpret, analyse and design approaches to visualise these data, and 3) to address, through numerical approaches, complex, real-world problems, that the traditional scientific methods cannot address. All modules, implemented through a MATLAB live script, include a short recorded lecture to introduce the topic, a handout that gives an overview of the activities, an instructor's manual with a detailed methodology and discussion points, a student assessment (quiz and level-specific challenge task), and a survey. The marine science themes addressed through these modules include biodiversity, habitat mapping, algal blooms and sea surface temperature change and utilize a series of marine science and oceanographic data portals. Through these modules students, with minimal experience in MATLAB or numerical methods are introduced to array indexing, concatenation, sorting, and reshaping, principal component analysis, spectral analysis and unsupervised classification within the context of oceanographic processes, marine geology and marine community ecology.

Learning to see, seeing to learn: visual aspects of sensemaking

NASA Astrophysics Data System (ADS)

Russell, Daniel M.

2003-06-01

When one says "I see," what is usually meant is "I understand." But what does it mean to create a sense of understanding a large, complex, problem, one with many interlocking pieces, sometimes ill-fitting data and the occasional bit of contradictory information? The traditional computer science perspective on helping people towards understanding is to provide an armamentarium of tools and techniques - databases, query tools and a variety of graphing methods. As a field, we have an overly simple perspective on what it means to grapple with real information. In practice, people who try to make sense of some thing (say, the life sciences, the Middle East, the large scale structure of the universe, their taxes) are faced with a complex collection of information, some in easy-to-digest structured forms, but with many relevant parts scattered hither and yon, in forms and shapes too difficult to manage. To create an understanding, we find that people create representations of complex information. Yet using representations relies on fairly sophisticated perceptual practices. These practices are in no way preordained, but subject to the kinds of perceptual and cognitive phenomena we see in every day life. In order to understand our information environments, we need to learn to perceive these perceptual elements, and understand when they do, and do not, work to our advantage. A more powerful approach to the problem of supporting realistic sensemaking practice is to design information environments that accommodate both the world"s information realities and people"s cognitive characteristics. This paper argues that visual aspects of representation use often dominate sensemaking behavior, and illustrates this by showing three sensemaking tools we have built that take advantage of this property.

An improved game-theoretic approach to uncover overlapping communities

NASA Astrophysics Data System (ADS)

Sun, Hong-Liang; Ch'Ng, Eugene; Yong, Xi; Garibaldi, Jonathan M.; See, Simon; Chen, Duan-Bing

How can we uncover overlapping communities from complex networks to understand the inherent structures and functions? Chen et al. firstly proposed a community game (Game) to study this problem, and the overlapping communities have been discovered when the game is convergent. It is based on the assumption that each vertex of the underlying network is a rational game player to maximize its utility. In this paper, we investigate how similar vertices affect the formation of community game. The Adamic-Adar Index (AA Index) has been employed to define the new utility function. This novel method has been evaluated on both synthetic and real-world networks. Experimental study shows that it has significant improvement of accuracy (from 4.8% to 37.6%) compared with the Game on 10 real networks. It is more efficient on Facebook networks (FN) and Amazon co-purchasing networks than on other networks. This result implicates that “friend circles of friends” of Facebook are valuable to understand the overlapping community division.

Multiclass Posterior Probability Twin SVM for Motor Imagery EEG Classification.

PubMed

She, Qingshan; Ma, Yuliang; Meng, Ming; Luo, Zhizeng

2015-01-01

Motor imagery electroencephalography is widely used in the brain-computer interface systems. Due to inherent characteristics of electroencephalography signals, accurate and real-time multiclass classification is always challenging. In order to solve this problem, a multiclass posterior probability solution for twin SVM is proposed by the ranking continuous output and pairwise coupling in this paper. First, two-class posterior probability model is constructed to approximate the posterior probability by the ranking continuous output techniques and Platt's estimating method. Secondly, a solution of multiclass probabilistic outputs for twin SVM is provided by combining every pair of class probabilities according to the method of pairwise coupling. Finally, the proposed method is compared with multiclass SVM and twin SVM via voting, and multiclass posterior probability SVM using different coupling approaches. The efficacy on the classification accuracy and time complexity of the proposed method has been demonstrated by both the UCI benchmark datasets and real world EEG data from BCI Competition IV Dataset 2a, respectively.

Adaptive Management: From More Talk to Real Action

NASA Astrophysics Data System (ADS)

Williams, Byron K.; Brown, Eleanor D.

2014-02-01

The challenges currently facing resource managers are large-scale and complex, and demand new approaches to balance development and conservation goals. One approach that shows considerable promise for addressing these challenges is adaptive management, which by now is broadly seen as a natural, intuitive, and potentially effective way to address decision-making in the face of uncertainties. Yet the concept of adaptive management continues to evolve, and its record of success remains limited. In this article, we present an operational framework for adaptive decision-making, and describe the challenges and opportunities in applying it to real-world problems. We discuss the key elements required for adaptive decision-making, and their integration into an iterative process that highlights and distinguishes technical and social learning. We illustrate the elements and processes of the framework with some successful on-the-ground examples of natural resource management. Finally, we address some of the difficulties in applying learning-based management, and finish with a discussion of future directions and strategic challenges.

JPRS Report, China.

DTIC Science & Technology

1989-02-23

February 1989 facing complex problems in need of solution, and there is no excuse for us to congratulate ourselves." Firstly, because of continuous...problem of development to be placed on the top of the international agenda. History has proven that the world needs the existence of a United Nations...and the United Nations needs support from the world’s nations. A changing and multi-polar- ized world further needs a United Nations that can

Scope of Gradient and Genetic Algorithms in Multivariable Function Optimization

NASA Technical Reports Server (NTRS)

Shaykhian, Gholam Ali; Sen, S. K.

2007-01-01

Global optimization of a multivariable function - constrained by bounds specified on each variable and also unconstrained - is an important problem with several real world applications. Deterministic methods such as the gradient algorithms as well as the randomized methods such as the genetic algorithms may be employed to solve these problems. In fact, there are optimization problems where a genetic algorithm/an evolutionary approach is preferable at least from the quality (accuracy) of the results point of view. From cost (complexity) point of view, both gradient and genetic approaches are usually polynomial-time; there are no serious differences in this regard, i.e., the computational complexity point of view. However, for certain types of problems, such as those with unacceptably erroneous numerical partial derivatives and those with physically amplified analytical partial derivatives whose numerical evaluation involves undesirable errors and/or is messy, a genetic (stochastic) approach should be a better choice. We have presented here the pros and cons of both the approaches so that the concerned reader/user can decide which approach is most suited for the problem at hand. Also for the function which is known in a tabular form, instead of an analytical form, as is often the case in an experimental environment, we attempt to provide an insight into the approaches focusing our attention toward accuracy. Such an insight will help one to decide which method, out of several available methods, should be employed to obtain the best (least error) output. *

The Calculus of Friendship

ERIC Educational Resources Information Center

Strogatz, Steven

2009-01-01

Many academics like to isolate a piece of the world to study: an important social issue, a central philosophical problem, a key moment in history. They know they're oversimplifying but they do it anyway--it's the only way to make progress, and what's more, their little worlds are often more beautiful than the real one. This paper shares a story of…

Probability & Statistics: Modular Learning Exercises. Teacher Edition

ERIC Educational Resources Information Center

Actuarial Foundation, 2012

2012-01-01

The purpose of these modules is to provide an introduction to the world of probability and statistics to accelerated mathematics students at the high school level. The modules also introduce students to real world math concepts and problems that property and casualty actuaries come across in their work. They are designed to be used by teachers and…

Humanities in the Aftermath: An Interview with Gary Olson

ERIC Educational Resources Information Center

Taylor, Todd

2010-01-01

This article presents an interview with Gary Olson on the changing contexts of the humanities in this modern world. He emphasizes that the humanities are absolutely essential when it comes to the very real-world problems. He explains that what he is saying not just applies to terrorism and economic crisis; the humanities equip everyone to deal…

The positive impacts of Real-World Data on the challenges facing the evolution of biopharma.

PubMed

Wise, John; Möller, Angeli; Christie, David; Kalra, Dipak; Brodsky, Elia; Georgieva, Evelina; Jones, Greg; Smith, Ian; Greiffenberg, Lars; McCarthy, Marie; Arend, Michael; Luttringer, Olivier; Kloss, Sebastian; Arlington, Steve

2018-04-01

Demand for healthcare services is unprecedented. Society is struggling to afford the cost. Pricing of biopharmaceutical products is under scrutiny, especially by payers and Health Technology Assessment agencies. As we discuss here, rapidly advancing technologies, such as Real-World Data (RWD), are being utilized to increase understanding of disease. RWD, when captured and analyzed, produces the Real-World Evidence (RWE) that underpins the economic case for innovative medicines. Furthermore, RWD can inform the understanding of disease, help identify new therapeutic intervention points, and improve the efficiency of research and development (R&D), especially clinical trials. Pursuing precompetitive collaborations to define shared requirements for the use of RWD would equip service-providers with the specifications needed to implement cloud-based solutions for RWD acquisition, management and analysis. Only this approach would deliver cost-effective solutions to an industry-wide problem. Copyright © 2018 Elsevier Ltd. All rights reserved.

Impact on Learning Awards, 2001.

ERIC Educational Resources Information Center

School Planning & Management, 2001

2001-01-01

Recognizes 14 architectural firms for their innovative designs, which helped solve real-world problems in K-12 school facilities. Designs for retrofits, safety and security, and specialized learning environments are profiled and critiqued. (GR)

Developing Graduate Attributes in an Open Online Course

ERIC Educational Resources Information Center

Rowe, Michael

2016-01-01

In an increasingly connected world where solving complex problems is not possible by solitary experts, educators and learners need opportunities to develop ways of thinking that allow them to engage with the dynamic and complex situations that arise in the world. The development of graduate attributes has been suggested as one way in which…

Ubiquitousness of link-density and link-pattern communities in real-world networks

NASA Astrophysics Data System (ADS)

Šubelj, L.; Bajec, M.

2012-01-01

Community structure appears to be an intrinsic property of many complex real-world networks. However, recent work shows that real-world networks reveal even more sophisticated modules than classical cohesive (link-density) communities. In particular, networks can also be naturally partitioned according to similar patterns of connectedness among the nodes, revealing link-pattern communities. We here propose a propagation based algorithm that can extract both link-density and link-pattern communities, without any prior knowledge of the true structure. The algorithm was first validated on different classes of synthetic benchmark networks with community structure, and also on random networks. We have further applied the algorithm to different social, information, technological and biological networks, where it indeed reveals meaningful (composites of) link-density and link-pattern communities. The results thus seem to imply that, similarly as link-density counterparts, link-pattern communities appear ubiquitous in nature and design.

Seamless Connection between Learning and Assessment--Applying Progressive Learning Tasks in Mobile Ecology Inquiry

ERIC Educational Resources Information Center

Hung, Pi-Hsia; Hwang, Gwo-Jen; Lin, Yu-Fen; Wu, Tsung-Hsun; Su, I-Hsiang

2013-01-01

Mobile learning has been recommended for motivating students on field trips; nevertheless, owing to the complexity and the richness of the learning resources from both the real-world and the digital-world environments, information overload remains one of the major concerns. Most mobile learning designs provide feedback only for multiple choice…

Learning Algebra by Example in Real-World Classrooms

ERIC Educational Resources Information Center

Booth, Julie L.; Oyer, Melissa H.; Paré-Blagoev, E. Juliana; Elliot, Andrew J.; Barbieri, Christina; Augustine, Adam; Koedinger, Kenneth R.

2015-01-01

Math and science textbook chapters invariably supply students with sets of problems to solve, but this widely used approach is not optimal for learning; instead, more effective learning can be achieved when many problems to solve are replaced with correct and incorrect worked examples for students to study and explain. In the present study, the…

The Geometric Construction Abilities of Gifted Students in Solving Real-World Problems: A Case from Turkey

ERIC Educational Resources Information Center

Yildiz, Avni

2016-01-01

Geometric constructions have already been of interest to mathematicians. However, studies on geometric construction are not adequate in the relevant literature. Moreover, these studies generally focus on how secondary school gifted students solve non-routine mathematical problems. The present study aims to examine the geometric construction…

"Merds That Laugh Don't Like Mushrooms": Evidence for Deductive Reasoning by Preschoolers.

ERIC Educational Resources Information Center

Hawkins, J.; And Others

1984-01-01

Examines the relationship between development of logical processes required in deductive reasoning and their use by preschoolers, also considering possible explanations for children's deductive reasoning. The relationship of problem content to real-world knowledge and the sequence of presentation of problem types were found to affect the display…

Approaches to Interactive Video Anchors in Problem-Based Science Learning

ERIC Educational Resources Information Center

Kumar, David Devraj

2010-01-01

This paper is an invited adaptation of the IEEE Education Society Distinguished Lecture Approaches to Interactive Video Anchors in Problem-Based Science Learning. Interactive video anchors have a cognitive theory base, and they help to enlarge the context of learning with information-rich real-world situations. Carefully selected movie clips and…

Sparse Measurement Systems: Applications, Analysis, Algorithms and Design

ERIC Educational Resources Information Center

Narayanaswamy, Balakrishnan

2011-01-01

This thesis deals with "large-scale" detection problems that arise in many real world applications such as sensor networks, mapping with mobile robots and group testing for biological screening and drug discovery. These are problems where the values of a large number of inputs need to be inferred from noisy observations and where the…

Does What I Eat and Drink Affect My Teeth?

ERIC Educational Resources Information Center

Brown, Sherri Lynne

2013-01-01

"A Framework for K-12 Science Education" (NRC 2012) recommends that science teachers provide experiences for students to see "how science and engineering pertain to real-world problems and to explore opportunities to apply their scientific knowledge to engineering design problems once this linkage is made" (NRC 2012, p. 32). To…

Problem Solving in All Seasons: Prekindergarten-Grade 2

ERIC Educational Resources Information Center

Markworth, Kim; McCool, Jenni; Kosiak, Jennifer

2015-01-01

Holidays and seasonal activities provide excitement and a change of pace for teachers and students alike. They also offer perfect backdrops for mathematical tasks that can be related to other topics and themes in the classroom. "Problem Solving in All Seasons, Prekindergarten-Grade 2" delivers thirty-two appealing, real-world situations,…

Multitasking capacities in persons diagnosed with schizophrenia: a preliminary examination of their neurocognitive underpinnings and ability to predict real world functioning.

PubMed

Laloyaux, Julien; Van der Linden, Martial; Levaux, Marie-Noëlle; Mourad, Haitham; Pirri, Anthony; Bertrand, Hervé; Domken, Marc-André; Adam, Stéphane; Larøi, Frank

2014-07-30

Difficulties in everyday life activities are core features of persons diagnosed with schizophrenia and in particular during multitasking activities. However, at present, patients׳ multitasking capacities have not been adequately examined in the literature due to the absence of suitable assessment strategies. We thus recently developed a computerized real-life activity task designed to take into account the complex and multitasking nature of certain everyday life activities where participants are required to prepare a room for a meeting. Twenty-one individuals diagnosed with schizophrenia and 20 matched healthy controls completed the computerized task. Patients were also evaluated with a cognitive battery, measures of symptomatology and real world functioning. To examine the ecological validity, 14 other patients were recruited and were given the computerized version and a real version of the meeting preparation task. Results showed that performance on the computerized task was significantly correlated with executive functioning, pointing to the major implication of these cognitive processes in multitasking situations. Performance on the computerized task also significantly predicted up to 50% of real world functioning. Moreover, the computerized task demonstrated good ecological validity. These findings suggest the importance of evaluating multitasking capacities in patients diagnosed with schizophrenia in order to predict real world functioning. Copyright © 2014 Elsevier Ireland Ltd. All rights reserved.

A comparison of fitness-case sampling methods for genetic programming

NASA Astrophysics Data System (ADS)

Martínez, Yuliana; Naredo, Enrique; Trujillo, Leonardo; Legrand, Pierrick; López, Uriel

2017-11-01

Genetic programming (GP) is an evolutionary computation paradigm for automatic program induction. GP has produced impressive results but it still needs to overcome some practical limitations, particularly its high computational cost, overfitting and excessive code growth. Recently, many researchers have proposed fitness-case sampling methods to overcome some of these problems, with mixed results in several limited tests. This paper presents an extensive comparative study of four fitness-case sampling methods, namely: Interleaved Sampling, Random Interleaved Sampling, Lexicase Selection and Keep-Worst Interleaved Sampling. The algorithms are compared on 11 symbolic regression problems and 11 supervised classification problems, using 10 synthetic benchmarks and 12 real-world data-sets. They are evaluated based on test performance, overfitting and average program size, comparing them with a standard GP search. Comparisons are carried out using non-parametric multigroup tests and post hoc pairwise statistical tests. The experimental results suggest that fitness-case sampling methods are particularly useful for difficult real-world symbolic regression problems, improving performance, reducing overfitting and limiting code growth. On the other hand, it seems that fitness-case sampling cannot improve upon GP performance when considering supervised binary classification.

Creating Impact with Operations Research in Health: Making Room for Practice in Academia

PubMed Central

Brandeau, Margaret L.

2015-01-01

Operations research (OR)-based analyses have the potential to improve decision making for many important, real-world health care problems. However, junior scholars often avoid working on practical applications in health because promotion and tenure processes tend to value theoretical studies more highly than applied studies. This paper discusses the author's experiences in using OR to inform and influence decisions in health and provides a blueprint for junior researchers who wish to find success by taking a similar path. This involves selecting good problems to study, forming productive collaborations with domain experts, developing appropriate models, identifying the most salient results from an analysis, and effectively disseminating findings to decision makers. The paper then suggests how journals, funding agencies, and senior academics can encourage such work by taking a broader and more informed view of the potential role and contributions of OR to solving health care problems. Making room in academia for the application of OR in health follows in the tradition begun by the founders of operations research: to work on important real-world problems where operations research can contribute to better decision making. PMID:26003321

Reasoning and planning in dynamic domains: An experiment with a mobile robot

NASA Technical Reports Server (NTRS)

Georgeff, M. P.; Lansky, A. L.; Schoppers, M. J.

1987-01-01

Progress made toward having an autonomous mobile robot reason and plan complex tasks in real-world environments is described. To cope with the dynamic and uncertain nature of the world, researchers use a highly reactive system to which is attributed attitudes of belief, desire, and intention. Because these attitudes are explicitly represented, they can be manipulated and reasoned about, resulting in complex goal-directed and reflective behaviors. Unlike most planning systems, the plans or intentions formed by the system need only be partly elaborated before it decides to act. This allows the system to avoid overly strong expectations about the environment, overly constrained plans of action, and other forms of over-commitment common to previous planners. In addition, the system is continuously reactive and has the ability to change its goals and intentions as situations warrant. Thus, while the system architecture allows for reasoning about means and ends in much the same way as traditional planners, it also posseses the reactivity required for survival in complex real-world domains. The system was tested using SRI's autonomous robot (Flakey) in a scenario involving navigation and the performance of an emergency task in a space station scenario.

Lessons Learned from Crowdsourcing Complex Engineering Tasks.

PubMed

Staffelbach, Matthew; Sempolinski, Peter; Kijewski-Correa, Tracy; Thain, Douglas; Wei, Daniel; Kareem, Ahsan; Madey, Gregory

2015-01-01

Crowdsourcing is the practice of obtaining needed ideas, services, or content by requesting contributions from a large group of people. Amazon Mechanical Turk is a web marketplace for crowdsourcing microtasks, such as answering surveys and image tagging. We explored the limits of crowdsourcing by using Mechanical Turk for a more complicated task: analysis and creation of wind simulations. Our investigation examined the feasibility of using crowdsourcing for complex, highly technical tasks. This was done to determine if the benefits of crowdsourcing could be harnessed to accurately and effectively contribute to solving complex real world engineering problems. Of course, untrained crowds cannot be used as a mere substitute for trained expertise. Rather, we sought to understand how crowd workers can be used as a large pool of labor for a preliminary analysis of complex data. We compared the skill of the anonymous crowd workers from Amazon Mechanical Turk with that of civil engineering graduate students, making a first pass at analyzing wind simulation data. For the first phase, we posted analysis questions to Amazon crowd workers and to two groups of civil engineering graduate students. A second phase of our experiment instructed crowd workers and students to create simulations on our Virtual Wind Tunnel website to solve a more complex task. With a sufficiently comprehensive tutorial and compensation similar to typical crowd-sourcing wages, we were able to enlist crowd workers to effectively complete longer, more complex tasks with competence comparable to that of graduate students with more comprehensive, expert-level knowledge. Furthermore, more complex tasks require increased communication with the workers. As tasks become more complex, the employment relationship begins to become more akin to outsourcing than crowdsourcing. Through this investigation, we were able to stretch and explore the limits of crowdsourcing as a tool for solving complex problems.

Cognitive and Motivational Impacts of Learning Game Design on Middle School Children

ERIC Educational Resources Information Center

Akcaoglu, Mete

2013-01-01

In today`s complex and fast-evolving world, problem solving is an important skill to possess. For young children to be successful at their future careers, they need to have the "skill" and the "will" to solve complex problems that are beyond the well-defined problems that they learn to solve at schools. One promising approach…

The benefits of adaptive parametrization in multi-objective Tabu Search optimization

NASA Astrophysics Data System (ADS)

Ghisu, Tiziano; Parks, Geoffrey T.; Jaeggi, Daniel M.; Jarrett, Jerome P.; Clarkson, P. John

2010-10-01

In real-world optimization problems, large design spaces and conflicting objectives are often combined with a large number of constraints, resulting in a highly multi-modal, challenging, fragmented landscape. The local search at the heart of Tabu Search, while being one of its strengths in highly constrained optimization problems, requires a large number of evaluations per optimization step. In this work, a modification of the pattern search algorithm is proposed: this modification, based on a Principal Components' Analysis of the approximation set, allows both a re-alignment of the search directions, thereby creating a more effective parametrization, and also an informed reduction of the size of the design space itself. These changes make the optimization process more computationally efficient and more effective - higher quality solutions are identified in fewer iterations. These advantages are demonstrated on a number of standard analytical test functions (from the ZDT and DTLZ families) and on a real-world problem (the optimization of an axial compressor preliminary design).

A Theoretical Analysis: Physical Unclonable Functions and The Software Protection Problem

DOE Office of Scientific and Technical Information (OSTI.GOV)

Nithyanand, Rishab; Solis, John H.

2011-09-01

Physical Unclonable Functions (PUFs) or Physical One Way Functions (P-OWFs) are physical systems whose responses to input stimuli (i.e., challenges) are easy to measure (within reasonable error bounds) but hard to clone. This property of unclonability is due to the accepted hardness of replicating the multitude of uncontrollable manufacturing characteristics and makes PUFs useful in solving problems such as device authentication, software protection, licensing, and certified execution. In this paper, we focus on the effectiveness of PUFs for software protection and show that traditional non-computational (black-box) PUFs cannot solve the problem against real world adversaries in offline settings. Our contributionsmore » are the following: We provide two real world adversary models (weak and strong variants) and present definitions for security against the adversaries. We continue by proposing schemes secure against the weak adversary and show that no scheme is secure against a strong adversary without the use of trusted hardware. Finally, we present a protection scheme secure against strong adversaries based on trusted hardware.« less

Debating complexity in modeling

USGS Publications Warehouse

Hunt, Randall J.; Zheng, Chunmiao

1999-01-01

As scientists trying to understand the natural world, how should our effort be apportioned? We know that the natural world is characterized by complex and interrelated processes. Yet do we need to explicitly incorporate these intricacies to perform the tasks we are charged with? In this era of expanding computer power and development of sophisticated preprocessors and postprocessors, are bigger machines making better models? Put another way, do we understand the natural world better now with all these advancements in our simulation ability? Today the public's patience for long-term projects producing indeterminate results is wearing thin. This increases pressure on the investigator to use the appropriate technology efficiently. On the other hand, bringing scientific results into the legal arena opens up a new dimension to the issue: to the layperson, a tool that includes more of the complexity known to exist in the real world is expected to provide the more scientifically valid answer.

Workshop on Fielded Applications of Machine Learning

DTIC Science & Technology

1994-05-11

This report summaries the talks presented at the Workshop on Fielded Applications of Machine Learning , and draws some initial conclusions about the state of machine learning and its potential for solving real-world problems.

Graph Theory and the High School Student.

ERIC Educational Resources Information Center

Chartrand, Gary; Wall, Curtiss E.

1980-01-01

Graph theory is presented as a tool to instruct high school mathematics students. A variety of real world problems can be modeled which help students recognize the importance and difficulty of applying mathematics. (MP)

Seeing the Landscape and the Forest Floor: Changes Made to Improve the Connectivity of Concepts in a Hybrid Problem-Based Learning Curriculum

ERIC Educational Resources Information Center

O'Neill, Geraldine; Hung, Woei

2010-01-01

Problem-based learning (PBL) curricula utilise authentic problems that are based in the real-world of practice. This very characteristic enables students to develop an intimate knowledge about the intricacies of practice, metaphorically, seeing the details of the forest floor. However, it is equally important for students to develop an overall…

Effects of Modified Schema-Based Instruction on Real-World Algebra Problem Solving of Students with Autism Spectrum Disorder and Moderate Intellectual Disability

ERIC Educational Resources Information Center

Root, Jenny Rose

2016-01-01

The current study evaluated the effects of modified schema-based instruction (SBI) on the algebra problem solving skills of three middle school students with autism spectrum disorder and moderate intellectual disability (ASD/ID). Participants learned to solve two types of group word problems: missing-whole and missing-part. The themes of the word…

Statistical Mechanics of Temporal and Interacting Networks

NASA Astrophysics Data System (ADS)

Zhao, Kun

In the last ten years important breakthroughs in the understanding of the topology of complexity have been made in the framework of network science. Indeed it has been found that many networks belong to the universality classes called small-world networks or scale-free networks. Moreover it was found that the complex architecture of real world networks strongly affects the critical phenomena defined on these structures. Nevertheless the main focus of the research has been the characterization of single and static networks. Recently, temporal networks and interacting networks have attracted large interest. Indeed many networks are interacting or formed by a multilayer structure. Example of these networks are found in social networks where an individual might be at the same time part of different social networks, in economic and financial networks, in physiology or in infrastructure systems. Moreover, many networks are temporal, i.e. the links appear and disappear on the fast time scale. Examples of these networks are social networks of contacts such as face-to-face interactions or mobile-phone communication, the time-dependent correlations in the brain activity and etc. Understanding the evolution of temporal and multilayer networks and characterizing critical phenomena in these systems is crucial if we want to describe, predict and control the dynamics of complex system. In this thesis, we investigate several statistical mechanics models of temporal and interacting networks, to shed light on the dynamics of this new generation of complex networks. First, we investigate a model of temporal social networks aimed at characterizing human social interactions such as face-to-face interactions and phone-call communication. Indeed thanks to the availability of data on these interactions, we are now in the position to compare the proposed model to the real data finding good agreement. Second, we investigate the entropy of temporal networks and growing networks , to provide a new framework to quantify the information encoded in these networks and to answer a fundamental problem in network science: how complex are temporal and growing networks. Finally, we consider two examples of critical phenomena in interacting networks. In particular, on one side we investigate the percolation of interacting networks by introducing antagonistic interactions. On the other side, we investigate a model of political election based on the percolation of antagonistic networks. The aim of this research is to show how antagonistic interactions change the physics of critical phenomena on interacting networks. We believe that the work presented in these thesis offers the possibility to appreciate the large variability of problems that can be addressed in the new framework of temporal and interacting networks.

Controlling herding in minority game systems

NASA Astrophysics Data System (ADS)

Zhang, Ji-Qiang; Huang, Zi-Gang; Wu, Zhi-Xi; Su, Riqi; Lai, Ying-Cheng

2016-02-01

Resource allocation takes place in various types of real-world complex systems such as urban traffic, social services institutions, economical and ecosystems. Mathematically, the dynamical process of resource allocation can be modeled as minority games. Spontaneous evolution of the resource allocation dynamics, however, often leads to a harmful herding behavior accompanied by strong fluctuations in which a large majority of agents crowd temporarily for a few resources, leaving many others unused. Developing effective control methods to suppress and eliminate herding is an important but open problem. Here we develop a pinning control method, that the fluctuations of the system consist of intrinsic and systematic components allows us to design a control scheme with separated control variables. A striking finding is the universal existence of an optimal pinning fraction to minimize the variance of the system, regardless of the pinning patterns and the network topology. We carry out a generally applicable theory to explain the emergence of optimal pinning and to predict the dependence of the optimal pinning fraction on the network topology. Our work represents a general framework to deal with the broader problem of controlling collective dynamics in complex systems with potential applications in social, economical and political systems.

Master-slave system with force feedback based on dynamics of virtual model

NASA Technical Reports Server (NTRS)

Nojima, Shuji; Hashimoto, Hideki

1994-01-01

A master-slave system can extend manipulating and sensing capabilities of a human operator to a remote environment. But the master-slave system has two serious problems: one is the mechanically large impedance of the system; the other is the mechanical complexity of the slave for complex remote tasks. These two problems reduce the efficiency of the system. If the slave has local intelligence, it can help the human operator by using its good points like fast calculation and large memory. The authors suggest that the slave is a dextrous hand with many degrees of freedom able to manipulate an object of known shape. It is further suggested that the dimensions of the remote work space be shared by the human operator and the slave. The effect of the large impedance of the system can be reduced in a virtual model, a physical model constructed in a computer with physical parameters as if it were in the real world. A method to determine the damping parameter dynamically for the virtual model is proposed. Experimental results show that this virtual model is better than the virtual model with fixed damping.

Cross-Dependency Inference in Multi-Layered Networks: A Collaborative Filtering Perspective.

PubMed

Chen, Chen; Tong, Hanghang; Xie, Lei; Ying, Lei; He, Qing

2017-08-01

The increasingly connected world has catalyzed the fusion of networks from different domains, which facilitates the emergence of a new network model-multi-layered networks. Examples of such kind of network systems include critical infrastructure networks, biological systems, organization-level collaborations, cross-platform e-commerce, and so forth. One crucial structure that distances multi-layered network from other network models is its cross-layer dependency, which describes the associations between the nodes from different layers. Needless to say, the cross-layer dependency in the network plays an essential role in many data mining applications like system robustness analysis and complex network control. However, it remains a daunting task to know the exact dependency relationships due to noise, limited accessibility, and so forth. In this article, we tackle the cross-layer dependency inference problem by modeling it as a collective collaborative filtering problem. Based on this idea, we propose an effective algorithm Fascinate that can reveal unobserved dependencies with linear complexity. Moreover, we derive Fascinate-ZERO, an online variant of Fascinate that can respond to a newly added node timely by checking its neighborhood dependencies. We perform extensive evaluations on real datasets to substantiate the superiority of our proposed approaches.

APFiLoc: An Infrastructure-Free Indoor Localization Method Fusing Smartphone Inertial Sensors, Landmarks and Map Information

PubMed Central

Shang, Jianga; Gu, Fuqiang; Hu, Xuke; Kealy, Allison

2015-01-01

The utility and adoption of indoor localization applications have been limited due to the complex nature of the physical environment combined with an increasing requirement for more robust localization performance. Existing solutions to this problem are either too expensive or too dependent on infrastructure such as Wi-Fi access points. To address this problem, we propose APFiLoc—a low cost, smartphone-based framework for indoor localization. The key idea behind this framework is to obtain landmarks within the environment and to use the augmented particle filter to fuse them with measurements from smartphone sensors and map information. A clustering method based on distance constraints is developed to detect organic landmarks in an unsupervised way, and the least square support vector machine is used to classify seed landmarks. A series of real-world experiments were conducted in complex environments including multiple floors and the results show APFiLoc can achieve 80% accuracy (phone in the hand) and around 70% accuracy (phone in the pocket) of the error less than 2 m error without the assistance of infrastructure like Wi-Fi access points. PMID:26516858

Integrated human-machine intelligence in space systems

NASA Technical Reports Server (NTRS)

Boy, Guy A.

1992-01-01

The integration of human and machine intelligence in space systems is outlined with respect to the contributions of artificial intelligence. The current state-of-the-art in intelligent assistant systems (IASs) is reviewed, and the requirements of some real-world applications of the technologies are discussed. A concept of integrated human-machine intelligence is examined in the contexts of: (1) interactive systems that tolerate human errors; (2) systems for the relief of workloads; and (3) interactive systems for solving problems in abnormal situations. Key issues in the development of IASs include the compatibility of the systems with astronauts in terms of inputs/outputs, processing, real-time AI, and knowledge-based system validation. Real-world applications are suggested such as the diagnosis, planning, and control of enginnered systems.

Object-oriented integrated approach for the design of scalable ECG systems.

PubMed

Boskovic, Dusanka; Besic, Ingmar; Avdagic, Zikrija

2009-01-01

The paper presents the implementation of Object-Oriented (OO) integrated approaches to the design of scalable Electro-Cardio-Graph (ECG) Systems. The purpose of this methodology is to preserve real-world structure and relations with the aim to minimize the information loss during the process of modeling, especially for Real-Time (RT) systems. We report on a case study of the design that uses the integration of OO and RT methods and the Unified Modeling Language (UML) standard notation. OO methods identify objects in the real-world domain and use them as fundamental building blocks for the software system. The gained experience based on the strongly defined semantics of the object model is discussed and related problems are analyzed.

Spatio-temporal networks: reachability, centrality and robustness.

PubMed

Williams, Matthew J; Musolesi, Mirco

2016-06-01

Recent advances in spatial and temporal networks have enabled researchers to more-accurately describe many real-world systems such as urban transport networks. In this paper, we study the response of real-world spatio-temporal networks to random error and systematic attack, taking a unified view of their spatial and temporal performance. We propose a model of spatio-temporal paths in time-varying spatially embedded networks which captures the property that, as in many real-world systems, interaction between nodes is non-instantaneous and governed by the space in which they are embedded. Through numerical experiments on three real-world urban transport systems, we study the effect of node failure on a network's topological, temporal and spatial structure. We also demonstrate the broader applicability of this framework to three other classes of network. To identify weaknesses specific to the behaviour of a spatio-temporal system, we introduce centrality measures that evaluate the importance of a node as a structural bridge and its role in supporting spatio-temporally efficient flows through the network. This exposes the complex nature of fragility in a spatio-temporal system, showing that there is a variety of failure modes when a network is subject to systematic attacks.