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Articles 331 - 360 of 499
Full-Text Articles in Engineering
Understanding Behavior Of System Of Systems Through Computational Intelligence Techniques, Nil H. Kilicay, Cihan H. Dagli
Understanding Behavior Of System Of Systems Through Computational Intelligence Techniques, Nil H. Kilicay, Cihan H. Dagli
Engineering Management and Systems Engineering Faculty Research & Creative Works
The world is facing an increasing level of systems integration leading towards systems of systems (SoS) that adapt to changing environmental conditions. The number of connections between components, the diversity of the components and the way the components are organized can lead to different emergent system behavior. Therefore, the need to focus on overall system behavior is becoming an unavoidable issue. The problem is to develop methodologies appropriate for better understanding behavior of system of systems before the design and implementation phase. This paper focuses on computational intelligence techniques used for analysis of complex adaptive systems with the aim of …
Adaptive Neural Network Based Stabilizing Controller Design For Single Machine Infinite Bus Power Systems, Wenxin Liu, Ganesh K. Venayagamoorthy, Donald C. Wunsch, David A. Cartes, Jagannathan Sarangapani, Mariesa Crow
Adaptive Neural Network Based Stabilizing Controller Design For Single Machine Infinite Bus Power Systems, Wenxin Liu, Ganesh K. Venayagamoorthy, Donald C. Wunsch, David A. Cartes, Jagannathan Sarangapani, Mariesa Crow
Engineering Management and Systems Engineering Faculty Research & Creative Works
Power system stabilizers are widely used to generate supplementary control signals for the excitation system in order to damp out the low frequency oscillations. In power system control literature, the performances of the proposed controllers were mostly demonstrated using simulation results without any rigorous stability analysis. This paper proposes a stabilizing neural network (NN) controller based on a sixth order single machine infinite bus power system model. The NN is used to approximate the complex nonlinear dynamics of power system. Unlike the other indirect adaptive NN control schemes, there is no offline training process and the NN can be directly …
An Evaluation Of Mahalanobis-Taguchi System And Neural Network For Multivariate Pattern Recognition, Jungeui Hong, Rajesh Jugulum, Kioumars Paryani, K. M. Ragsdell, Genichi Taguchi, Elizabeth A. Cudney
An Evaluation Of Mahalanobis-Taguchi System And Neural Network For Multivariate Pattern Recognition, Jungeui Hong, Rajesh Jugulum, Kioumars Paryani, K. M. Ragsdell, Genichi Taguchi, Elizabeth A. Cudney
Engineering Management and Systems Engineering Faculty Research & Creative Works
The Mahalanobis-Taguchi System is a diagnosis and predictive method for analyzing patterns in multivariate cases. The goal of this study is to compare the ability of the Mahalanobis- Taguchi System and a neural-network to discriminate using small data sets. We examine the discriminant ability as a function of data set size using an application area where reliable data is publicly available. The study uses the Wisconsin Breast Cancer study with nine attributes and one class.
Effective Use Of Process Capability Indices For Supplier Management, Elizabeth A. Cudney, David Drain
Effective Use Of Process Capability Indices For Supplier Management, Elizabeth A. Cudney, David Drain
Engineering Management and Systems Engineering Faculty Research & Creative Works
Process capability indices were originally invented to enable an organization to make economically sound decisions for process management. Process capability is a comparison of the voice of the process with the voice of the customer. Current practice is to use Cp and Cpk regardless of the validity of the underlying assumptions necessary for their use. Even if all necessary assumptions are satisfied, important problems can be missed if these indices are the sole process evaluation examined. Customer-supplier axioms are introduced to motivate more useful process evaluations and foster long-term harmonious relationships. This paper explores the alternative capability indices Cpm, Cpmk, …
Breaking The Cycle-Preventing Failures By Leveraging Historical Data During Conceptual Design, Daniel A. Krus, Katie Grantham
Breaking The Cycle-Preventing Failures By Leveraging Historical Data During Conceptual Design, Daniel A. Krus, Katie Grantham
Engineering Management and Systems Engineering Faculty Research & Creative Works
Major engineering accidents are often caused by seemingly minor failures propagating through complex systems. One example of this is an accident involving a Bell 206 Rotorcraft where a fuel pump failure led to the severing of the tail boom. Cataloguing and communicating the knowledge of potential failures and failure propagations is critical to prevent further accidents. The need for effective failure prevention tools is not specific to rotorcrafts, however. Failure reporting systems have been adopted by various industries to aid and promote failure prevention. The catalogued failures usually consist of narratives describing which part of a product failed, how it …
Near Optimal Neural Network-Based Output Feedback Control Of Affine Nonlinear Discrete-Time Systems, Qinmin Yang, Jagannathan Sarangapani
Near Optimal Neural Network-Based Output Feedback Control Of Affine Nonlinear Discrete-Time Systems, Qinmin Yang, Jagannathan Sarangapani
Electrical and Computer Engineering Faculty Research & Creative Works
In this paper, a novel online reinforcement learning neural network (NN)-based optimal output feedback controller, referred to as adaptive critic controller, is proposed for affine nonlinear discrete-time systems, to deliver a desired tracking performance. The adaptive critic design consist of three entities, an observer to estimate the system states, an action network that produces optimal control input and a critic that evaluates the performance of the action network. The critic is termed adaptive as it adapts itself to output the optimal cost-to-go function which is based on the standard Bellman equation. By using the Lyapunov approach, the uniformly ultimate boundedness …
Online Reinforcement Learning Neural Network Controller Design For Nanomanipulation, Qinmin Yang, Jagannathan Sarangapani
Online Reinforcement Learning Neural Network Controller Design For Nanomanipulation, Qinmin Yang, Jagannathan Sarangapani
Electrical and Computer Engineering Faculty Research & Creative Works
In this paper, a novel reinforcement learning neural network (NN)-based controller, referred to adaptive critic controller, is proposed for affine nonlinear discrete-time systems with applications to nanomanipulation. In the online NN reinforcement learning method, one NN is designated as the critic NN, which approximates the long-term cost function by assuming that the states of the nonlinear systems is available for measurement. An action NN is employed to derive an optimal control signal to track a desired system trajectory while minimizing the cost function. Online updating weight tuning schemes for these two NNs are also derived. By using the Lyapunov approach, …
Near Optimal Output-Feedback Control Of Nonlinear Discrete-Time Systems In Nonstrict Feedback Form With Application To Engines, Peter Shih, Brian C. Kaul, Jagannathan Sarangapani, J. A. Drallmeier
Near Optimal Output-Feedback Control Of Nonlinear Discrete-Time Systems In Nonstrict Feedback Form With Application To Engines, Peter Shih, Brian C. Kaul, Jagannathan Sarangapani, J. A. Drallmeier
Electrical and Computer Engineering Faculty Research & Creative Works
A novel reinforcement-learning based output-adaptive neural network (NN) controller, also referred as the adaptive-critic NN controller, is developed to track a desired trajectory for a class of complex nonlinear discrete-time systems in the presence of bounded and unknown disturbances. The controller includes an observer for estimating states and the outputs, critic, and two action NNs for generating virtual, and actual control inputs. The critic approximates certain strategic utility function and the action NNs are used to minimize both the strategic utility function and their outputs. All NN weights adapt online towards minimization of a performance index, utilizing gradient-descent based rule. …
Neural Network Control Of Robot Formations Using Rise Feedback, Jagannathan Sarangapani, Travis Alan Dierks
Neural Network Control Of Robot Formations Using Rise Feedback, Jagannathan Sarangapani, Travis Alan Dierks
Electrical and Computer Engineering Faculty Research & Creative Works
In this paper, a combined kinematic/torque control law is developed for leader-follower based formation control using backstepping in order to accommodate the dynamics of the robots and the formation in contrast with kinematic-based formation controllers that are widely reported in the literature. A neural network (NN) is introduced along with robust integral of the sign of the error (RISE) feedback to approximate the dynamics of the follower as well as its leader using online weight tuning. It is shown using Lyapunov theory that the errors for the entire formation are asymptotically stable and the NN weights are bounded as opposed …
Adaptive Critic Neural Network Force Controller For Atomic Force Microscope-Based Nanomanipulation, Qinmin Yang, Jagannathan Sarangapani
Adaptive Critic Neural Network Force Controller For Atomic Force Microscope-Based Nanomanipulation, Qinmin Yang, Jagannathan Sarangapani
Electrical and Computer Engineering Faculty Research & Creative Works
Automating the task of nanomanipulation is extremely important since it is tedious for humans. This paper proposes an atomic force microscope (AFM) based force controller to push nano particles on the substrates. A block phase correlation-based algorithm is embedded into the controller for the compensation of the thermal drift which is considered as the main external uncertainty during nanomanipulation. Then, the interactive forces and dynamics between the tip and the particle, particle and the substrate are modeled and analyzed. Further, an adaptive critic NN controller based on adaptive dynamic programming algorithm is designed and the task of pushing nano particles …
Neural Network Based Decentralized Excitation Control Of Large Scale Power Systems, Wenxin Liu, Ganesh K. Venayagamoorthy, Donald C. Wunsch, David A. Cartes, Jagannathan Sarangapani
Neural Network Based Decentralized Excitation Control Of Large Scale Power Systems, Wenxin Liu, Ganesh K. Venayagamoorthy, Donald C. Wunsch, David A. Cartes, Jagannathan Sarangapani
Electrical and Computer Engineering Faculty Research & Creative Works
This paper presents a neural network (NN) based decentralized excitation controller design for large scale power systems. The proposed controller design considers not only the dynamics of generators but also the algebraic constraints of the power flow equations. The control signals are calculated using only local signals. The transient stability and the coordination of the subsystem controllers can be guaranteed. NNs are used to approximate the unknown/imprecise dynamics of the local power system and the interconnections. All signals in the closed loop system are guaranteed to be uniformly ultimately bounded (UUB). Simulation results with a 3-machine power system demonstrate the …
Leadership In Student Distance Education Teams, Leroy Cox, Susan L. Murray, David Spurlock
Leadership In Student Distance Education Teams, Leroy Cox, Susan L. Murray, David Spurlock
Engineering Management and Systems Engineering Faculty Research & Creative Works
Interactive video technology has become a widely used medium for education. A prominent implementation of this technology, interactive distance learning, involves groups of students at local and remote sites connected by audio and video teleconferencing. This approach has made the task of delivering vital undergraduate and graduate engineering courses to distributed audiences much easier. As this approach has permeated more curricula, distance education instructors have increasingly assigned projects that require distance learners to work together as an element of the final course grade. This trend presents an interesting opportunity for researchers to understand the nature of interactions among course participants …
Patterns In Team Communication During A Simulation Game, David M. Baca, Ray Luechtefeld, Steve Eugene Watkins
Patterns In Team Communication During A Simulation Game, David M. Baca, Ray Luechtefeld, Steve Eugene Watkins
Engineering Management and Systems Engineering Faculty Research & Creative Works
The development of communication skills is a necessary preparation for effective engineering teamwork. Argyris' "Theory of Action" provides a framework for understanding patterns in team dialogue. Students can benefit from an awareness of these patterns. The theory highlights the detection and correction of errors by sharing information during group collaboration and interactions. Quality decision-making can be enhanced when members of a team develop high degrees of openness and interdependence. Quality decision-making can be diminished when members of a team regulate the information shared within the team. This work analyzes team interactions from simulation games used in an interdisciplinary engineering course …
Neuro Control Of Nonlinear Discrete Time Systems With Deadzone And Input Constraints, Pingan He, Wenzhi Gao, Jagannathan Sarangapani
Neuro Control Of Nonlinear Discrete Time Systems With Deadzone And Input Constraints, Pingan He, Wenzhi Gao, Jagannathan Sarangapani
Electrical and Computer Engineering Faculty Research & Creative Works
A neural network (NN) controller in discrete time is designed to deliver a desired tracking performance for a class of uncertain nonlinear systems with unknown deadzones and magnitude constraints on the input. The NN controller consists of two NNs: the first NN for compensating the unknown deadzones; and the second NN for compensating the uncertain nonlinear system dynamics. The magnitude constraints on the input are modeled as saturation nonlinearities and they are dealt with in the Lyapunov-based controller design. The uniformly ultimate boundedness (UUB) of the closed-loop tracking errors and the neural network weights estimation errors is demonstrated via Lyapunov …
Adaptive Distributed Fair Scheduling And Its Implementation In Wireless Sensor Networks, Maciej Jan Zawodniok, Jagannathan Sarangapani, Steve Eugene Watkins, James W. Fonda
Adaptive Distributed Fair Scheduling And Its Implementation In Wireless Sensor Networks, Maciej Jan Zawodniok, Jagannathan Sarangapani, Steve Eugene Watkins, James W. Fonda
Electrical and Computer Engineering Faculty Research & Creative Works
A novel adaptive and distributed fair scheduling (ADFS) scheme for wireless sensor networks is shown through hardware implementation. In contrast to simulation, hardware evaluation provides valuable feedback to protocol and hardware development process. The proposed protocol focuses on quality-of-service (QoS) issues to address flow prioritization. Thus, when nodes access a shared channel, the proposed ADFS allocates the channel bandwidth proportionally to the weight, or priority, of the packet flows. Moreover, ADFS allows for dynamic allocation of network resources with little added overhead. Weights are initially assigned using user specified QoS criteria. These weights are subsequently updated as a function of …
Decentralized Power Control With Implementation For Rfid Networks, Kainan Cha, Anil Ramachandran, David Pommerenke, Jagannathan Sarangapani
Decentralized Power Control With Implementation For Rfid Networks, Kainan Cha, Anil Ramachandran, David Pommerenke, Jagannathan Sarangapani
Electrical and Computer Engineering Faculty Research & Creative Works
In radio frequency identification (RFID) systems, the detection range and read rates will suffer from interference among high power reading devices. This problem grows severely and degrades system performance in dense RFID networks. In this paper, we investigate a suite of feasible power control schemes to ensure overall coverage area of the system while maintaining a desired read rate. The power control scheme and MAC protocol dynamically adjusts the RFID reader power output in response to the interference level seen locally during tag reading for an acceptable signal-to-noise ratio (SNR). We present novel distributed adaptive power control (DAPC) and probabilistic …
Development And Implementation Of Optimized Energy-Delay Sub-Network Routing Protocol For Wireless Sensor Networks, Maciej Jan Zawodniok, Jagannathan Sarangapani, Steve Eugene Watkins, James W. Fonda
Development And Implementation Of Optimized Energy-Delay Sub-Network Routing Protocol For Wireless Sensor Networks, Maciej Jan Zawodniok, Jagannathan Sarangapani, Steve Eugene Watkins, James W. Fonda
Electrical and Computer Engineering Faculty Research & Creative Works
The development and implementation of the optimized energy-delay sub-network routing (OEDSR) protocol for wireless sensor networks (WSN) is presented. This ondemand routing protocol minimizes a novel link cost factor which is defined using available energy, end-to-end (E2E) delay and distance from a node to the base station (BS), along with clustering, to effectively route information to the BS. Initially, the nodes are either in idle or sleep mode, but once an event is detected, the nodes near the event become active and start forming sub-networks. Formation of the inactive network into a sub-network saves energy because only a portion of …
Distributed Power Control For Cellular Networks In The Presence Of Channel Uncertainties, Maciej Jan Zawodniok, Q. Shang, Jagannathan Sarangapani
Distributed Power Control For Cellular Networks In The Presence Of Channel Uncertainties, Maciej Jan Zawodniok, Q. Shang, Jagannathan Sarangapani
Electrical and Computer Engineering Faculty Research & Creative Works
In this paper, a novel distributed power control (DPC) scheme for cellular network in the presence of radio channel uncertainties such as path loss, shadowing, and Rayleigh fading is presented. Since these uncertainties can attenuate the received signal strength and can cause variations in the received Signal-to-Interference ratio (SIR), a new DPC scheme, which can estimate the slowly varying channel uncertainty, is proposed so that a target SIR at the receiver can be maintained. Further, the standard assumption of a constant interference during a link's power update used in other works in the literature is relaxed. A CDMA-based cellular network …
Adaptive And Probabilistic Power Control Algorithms For Dense Rfid Reader Network, Kainan Cha, Anil Ramachandran, Jagannathan Sarangapani
Adaptive And Probabilistic Power Control Algorithms For Dense Rfid Reader Network, Kainan Cha, Anil Ramachandran, Jagannathan Sarangapani
Electrical and Computer Engineering Faculty Research & Creative Works
In radio frequency identification (RFID) systems, the detection range and read rates may suffer from interferences between high power devices such as readers. In dense networks, this problem grows severely and degrades system performance. In this paper, we investigate feasible power control schemes to ensure overall coverage area of the system while maintaining a desired data rate. The power control should dynamically adjust the output power of a RFID reader by adapting to the noise level seen during tag reading and acceptable signal-to-noise ratio (SNR). We present a novel distributed adaptive power control (DAPC) and probabilistic power control (PPC) as …
Forecasting Using The Mahalanobis-Taguchi System In The Presence Of Collinearity, Elizabeth A. Cudney, Kenneth M. Ragsdell
Forecasting Using The Mahalanobis-Taguchi System In The Presence Of Collinearity, Elizabeth A. Cudney, Kenneth M. Ragsdell
Engineering Management and Systems Engineering Faculty Research & Creative Works
The Mahalanobis Taguchi System is a diagnosis and forecasting method for multivariate data. Mahalanobis distance is a measure based on correlations between the variables and different patterns that can be identified and analyzed with respect to a base or reference group. the issue of multicollinearity is not adequately addressed in the MTS method. in cases where strong relationships exist between variables, the correlation matrix becomes almost singular, and the inverse matrix is not accurate. Multicollinearity can be handled by utilizing the adjoint matrix of the correlation matrix and Gram-Schmidt orthogonalization. This paper presents a case study of the MTS methodology …
Applying The Mahalanobis-Taguchi System To Vehicle Handling, Kioumars Paryani, Elizabeth A. Cudney, K. M. Ragsdell
Applying The Mahalanobis-Taguchi System To Vehicle Handling, Kioumars Paryani, Elizabeth A. Cudney, K. M. Ragsdell
Engineering Management and Systems Engineering Faculty Research & Creative Works
The Mahalanobis-Taguchi system (MTS) is a diagnosis and forecasting method using multivariate data. Mahalanobis distance (MD) is a measure based on correlations between the variables and patterns that can be identified and analyzed with respect to a base or reference group. The MTS is of interest because of its reported accuracy in forecasting using small, correlated data sets. This is the type of data that is encountered with consumer vehicle ratings. MTS enables a reduction in dimensionality and the ability to develop a scale based on MD values. MTS identifies a set of useful variables from the complete data set …
A Methodology For Deriving System Requirements Using Agent Based System Modeling, Karthik Gopalakrishnan, Sreeram Ramakrishnan, Cihan H. Dagli
A Methodology For Deriving System Requirements Using Agent Based System Modeling, Karthik Gopalakrishnan, Sreeram Ramakrishnan, Cihan H. Dagli
Engineering Management and Systems Engineering Faculty Research & Creative Works
In this paper, we duscuss a method to derive the requirements for developing an Industrial Automation and Constrol System (IACS). An IACS has software components and associated hardware, which together implement the required monitoring, supervision and control of operations an a production plant. The requirements of such a system are multi-dimensional and may require multiple layers of abstraction. For this domain, we propose an agent-based modeling adopting an agent-based modeling approach is the implicit flexibility afforded by agents and the negotiation techniques that can be implemented to streamline the change management process associated with requirements modeling and analysis. This paper …
A Simulation Framework For Real-Time Management And Control Of Inventory Routing Decisions, Shrikant Jarugumilli, Sreeram Ramakrishnan, Scott Erwin Grasman
A Simulation Framework For Real-Time Management And Control Of Inventory Routing Decisions, Shrikant Jarugumilli, Sreeram Ramakrishnan, Scott Erwin Grasman
Engineering Management and Systems Engineering Faculty Research & Creative Works
We consider a logistics network where a single warehouse distributes a single item to multiple retailers. Retailers in the network participate in a Vendor Managed Inventory (VMI) program with the warehouse, where the warehouse is responsible for tracking and replenishing the inventory at various retailer locations. The information update occurs every time a vehicle reaches a location and the decision on the delivery quantity and the next location to visit is made. For a small increase of locations in the network, the state space for the solution increases exponentially, making this problem NP-hard. Thus, we propose a solution methodology where …
Modeling Net-Centric System Of Systems Using The Dystems Modeling Language Sysml, Rao Madwaraj, Sreeram Ramakrishnan, Cihan H. Dagli
Modeling Net-Centric System Of Systems Using The Dystems Modeling Language Sysml, Rao Madwaraj, Sreeram Ramakrishnan, Cihan H. Dagli
Engineering Management and Systems Engineering Faculty Research & Creative Works
Understanding the operations of a large 'net-centric system-of-systems requires in-depth knowledge of the interfaces among the various systems, sub-systems and components. Architectural modeling can help in reducing the complexity involved in designing such large networked systems. An example of such a complex system is the Global Earth Observation System of Systems (GEOSS) - a system for monitoring and collecting information related to Earth's resources. This paper demonstrates the use of Systems Modeling Language (SysML), which supports specification, analysis, design, verification and validation of a broad range of complex systems, to model some aspects of the GEOSS. The paper discusses issues …
Heuristics And Genetic Algorithms, Michael D. Mobley, Cihan H. Dagli, David Enke
Heuristics And Genetic Algorithms, Michael D. Mobley, Cihan H. Dagli, David Enke
Engineering Management and Systems Engineering Faculty Research & Creative Works
Genetic algorithms are design tools used in generating optimal solutions. While they can often be shown to outperform various heuristic methods and hybrid approaches, using a combination of evolutionary algorithms and heuristic approaches can generate an optimal solution more quickly than either of the two methods independently. Our purpose is to provide an overview of genetic algorithms, to discuss the types of problems that lend themselves to being solved by genetic algorithms, and to identify heuristics that have been shown to aid genetic algorithms in their quest for optimal solutions. While the sample problems discussed in this paper are generally …
Neural Network-Based Output Feedback Controller For Lean Operation Of Spark Ignition Engines, Brian C. Kaul, Jagannathan Sarangapani, J. A. Drallmeier, Jonathan B. Vance, Pingan He
Neural Network-Based Output Feedback Controller For Lean Operation Of Spark Ignition Engines, Brian C. Kaul, Jagannathan Sarangapani, J. A. Drallmeier, Jonathan B. Vance, Pingan He
Electrical and Computer Engineering Faculty Research & Creative Works
Spark ignition (SI) engines running at very lean conditions demonstrate significant nonlinear behavior by exhibiting cycle-to-cycle dispersion of heat release even though such operation can significantly reduce NOx emissions and improve fuel efficiency by as much as 5-10%. A suite of neural network (NN) controller without and with reinforcement learning employing output feedback has shown ability to reduce the nonlinear cyclic dispersion observed under lean operating conditions. The neural network controllers consists of three NN: a) A NN observer to estimate the states of the engine such as total fuel and air; b) a second NN for generating virtual input; …
Unifying Value Methodology And Robust Design To Achieve Design For Six Sigma, Vivek K. Jikar, Elizabeth A. Cudney, Kenneth M. Ragsdell, Chuck T. Hui
Unifying Value Methodology And Robust Design To Achieve Design For Six Sigma, Vivek K. Jikar, Elizabeth A. Cudney, Kenneth M. Ragsdell, Chuck T. Hui
Engineering Management and Systems Engineering Faculty Research & Creative Works
The concept of product or system function is considered as described in the Taguchi System of Quality Engineering. the importance of transfer functions is also discussed, and a review of conventional value analysis techniques is given. This paper proposes a combination of the principles of robust design and value methodology to enable on-target functionality and direct cost allocation early in the product development process. the discussion on integration of value analysis principles in robust design methodology is provided considering the six-sigma environment. Copyright © 2006 SAE International.
Distributed Simulation Modeling For Manufacturing Systems Design Using Xml, Rawinkhan Srinon, Sreeram Ramakrishnan
Distributed Simulation Modeling For Manufacturing Systems Design Using Xml, Rawinkhan Srinon, Sreeram Ramakrishnan
Engineering Management and Systems Engineering Faculty Research & Creative Works
Discrete event simulations have been used to model manufacturing systems. Various decomposition methods such as distributed simulations have been employed for this modeling. in the context of distributed simulations, each federate must be able to share the embedded logic with the other federates, irrespective of the software used to design and build such systems. This paper provides an extensible Markup Language (XML)-Based representation for distributed models that can be shared across the federation of simulations. Specifically, the paper outlines three different model components that forms the basis of a design framework for distributed simulation models - object model (for simulation …
Harmony Search For Structural Design, Zong Woo Geem, Kang Seok Lee, Chung-Li Tseng
Harmony Search For Structural Design, Zong Woo Geem, Kang Seok Lee, Chung-Li Tseng
Engineering Management and Systems Engineering Faculty Research & Creative Works
Various algorithms have been developed and applied to structural optimization, in which cross-sectional areas of structure members are assumed to be continuous. in most cases of practical structure designs, however, decision variables (cross-sectional areas) are discrete. This paper proposes a combinatorial optimization model for structural design using a new nature-inspired algorithm, harmony search (HS). HS is also compared to genetic algorithms through a standard truss example. Numerical results reveal that the proposed HS is a powerful search algorithm for combinatorial structure optimization.
A Matter Of Priorities: Effects Of Increased Opportunities For Extracurricular And Non-Traditional Learning Experiences On Student Time Management And Attitudes, David Spurlock, Daniel J. Bailey, Susan L. Murray, Andrew S. Ricke
A Matter Of Priorities: Effects Of Increased Opportunities For Extracurricular And Non-Traditional Learning Experiences On Student Time Management And Attitudes, David Spurlock, Daniel J. Bailey, Susan L. Murray, Andrew S. Ricke
Engineering Management and Systems Engineering Faculty Research & Creative Works
Many schools are emphasizing non-traditional and extracurricular learning experiences for undergraduate engineering students. These include activities such as incorporating servicelearning projects into the classroom, involving students in design competitions (e.g., solar car, formula car races), and promoting involvement in traditional campus organizations. Often this emphasis is in response to changes in ABET requirements, desires of future employers, and needs to improve student retention. What are the effects of emphasizing these sorts of activities on student attitudes and time management decisions? We examine the influences on students' priorities for allocating their time and their perceptions of the relative importance of available …