Engineering Commons^™

Integrating Local Search And Network Flow To Solve The Inventory Routing Problem, Hoong Chuin Lau, Q Liu, H. Ono

Research Collection School Of Computing and Information Systems

The inventory routing problem is one of important and practical problems in logistics. It involves the integration of inventory management and vehicle routing, both of which are known to be NP-hard. In this paper, we combine local search and network flows to solve the inventory management problem, by utilizing the minimum cost flow sub-solutions as a guiding measure for local search. We then integrate with a standard VRPTW solver to present experimental results for the overall inventory routing problem, based on instances extended from the Solomon benchmark problems.

Modular Machine Learning Methods For Computer-Aided Diagnosis Of Breast Cancer, Mia Kathleen Markey '94

Doctoral Dissertations

The purpose of this study was to improve breast cancer diagnosis by reducing the number of benign biopsies performed. To this end, we investigated modular and ensemble systems of machine learning methods for computer-aided diagnosis (CAD) of breast cancer. A modular system partitions the input space into smaller domains, each of which is handled by a local model. An ensemble system uses multiple models for the same cases and combines the models' predictions.

Five supervised machine learning techniques (LDA, SVM, BP-ANN, CBR, CART) were trained to predict the biopsy outcome from mammographic findings (BIRADS™) and patient age based on a …

A New Approach For Weighted Constraint Satisfaction, Hoong Chuin Lau

Research Collection School Of Computing and Information Systems

We consider the Weighted Constraint Satisfaction Problem which is an important problem in Artificial Intelligence. Given a set of variables, their domains and a set of constraints between variables, our goal is to obtain an assignment of the variables to domain values such that the weighted sum of satisfied constraints is maximized. In this paper, we present a new approach based on randomized rounding of semidefinite programming relaxation. Besides having provable worst-case bounds for domain sizes 2 and 3, our algorithm is simple and efficient in practice, and produces better solutions than some other polynomial-time algorithms such as greedy and …

Investigation Of Cooperative Behavior In Autonomous Wide Search Munitions, Robert E. Dunkel Iii

Theses and Dissertations

The purpose of this research is to investigate the effectiveness of wide-area search munitions in various scenarios using different cooperative behavior algorithms. The general scenario involves multiple autonomous munitions searching for an unknown number of targets of different priority in unknown locations. Three cooperative behavior algorithms are used in each scenario: no cooperation, cooperative attack only, and cooperative classification and attack. In the cooperative cases, the munitions allocate tasks on-line as a group, using linear programming techniques to determine the optimum allocation. Each munition provides inputs to the task allocation routine in the form of probabilities of successfully being able …

Level Set Segmentation Of Mr Images For Extraction Of Femur Bone And Tissues, Christina Shanti Nayagam

Student Works (2000-2009)

This research explores a potentially useful segmentation algorithm, known as the level set method. It is suitable for images obtained from the Magnetic Resonance Imaging (MRJ) modality, despite the fact that MR images have low contrast between bone and tissue. The level set method is a numerical technique designed to track the evolution of an interface. The fast marching version of the method is implemented for two-dimensional (2-D) and three-dimensional (3-D) segmentation in this research. Femur segmentation is the main thrust of this thesis, however brain and heart images are also presented. Pre-processing steps are first performed for the 2-0 …

A Genetic Algorithm Solution To The Shortest Path Problem In Ospf And Mpls, Wee Jing Tee Wee Jing

Student Works (2000-2009)

This project studies and explores the potential of using genetic algorithm to solve the shortest path problem in Open Shortest Path First (OSPF) and Multiprotocol Label Switching (MPLS). The most critical task for developing a genetic algorithm to the shortest path problem is to how to encode a path in a network. In this project, two genetic algorithm solutions arc developed for the above two problem domains, i.e. Previous-node-based Encoding to solve the shortest path problem in OSPF and Priority-based Encoding to solve the shortest path problem in MPLS. For each of the shortest path problem domains, the proposed solution …

Pickup And Delivery Problem With Time Windows: Algorithms And Test Case Generation, Hoong Chuin Lau, Zhe Liang

Research Collection School Of Computing and Information Systems

In the pickup and delivery problem with time windows (PDPTW), vehicles have to transport loads from origins to destinations respecting capacity and time constraints. In this paper, we present a two-phase method to solve the PDPTW. In the first phase, we apply a novel construction heuristics to generate an initial solution. In the second phase, a tabu search method is proposed to improve the solution. Another contribution of this paper is a strategy to generate good problem instances and benchmarking solutions for PDPTW, based on Solomon's benchmark test cases for VRPTW. Experimental results show that our approach yields very good …

A Multi-Agent Framework For Supporting Intelligent Fourth-Party Logistics, Hoong Chuin Lau, G. Lo

Research Collection School Of Computing and Information Systems

A distributed intelligent agent-based framework that supports fourth-party logistics optimization under a web-based e-Commerce environment has been proposed in this paper. In the framework, customer job requests come through an e-Procurement service. These requests are consolidated and pushed to the e-Market Place service periodically. The e-Market Place then serves as a broker that allows intelligent agents to bid to serve these requests optimally in real-time by solving multiple instances of underlying logistics optimization problem. The resulting system was implemented based on the Java 2 Enterprise Edition (J2EE) platform using distributed system technology for communication between objects.

Aurora Working Group: Dsr Front End Lvcsr Evaluation — Baseline Recognition System Description, Naveen Parihar, Joseph Picone

Publications

In this document we describe the features of the baseline system to be used in the Distributed Speech Recognition (DSR) front end large vocabulary continuous speech recognition (LVCSR) evaluations being conducted by the Aurora Working Group of the European Telecommunications Standards Institute (ETSI). The objective of these evaluations is to determine the robustness of different front ends for use in client/server type telecommunications applications. As such, our experiments are designed to test the following focus conditions on the DARPA Wall Street Journal (WSJ0) corpus using a 5000-word closed-loop vocabulary and a bigram language model:

1. Additive Noise: six noise conditions …

Comparison Of Two Distributed Fuzzy Logic Controllers For Flexible-Link Manipulators, Linda Z. Shi, Mohamed Trabia

Mechanical Engineering Faculty Presentations

The paper suggests that fuzzy logic controllers present a computationally efficient and robust alternative to conventional controllers. The paper presents two possible structures for the distributed fuzzy logic controller of a single-link flexible manipulator. A linear quadratic regulator method is used to prove the effectiveness of fuzzy logic controllers.

Fingerprint Recognition Using Neural Networks, Eng Hoe Kennie Yeoh

Student Works (2000-2009)

Traditional methods of fingerprint verification uses either complicated feature detection algorithms that are not specific to each fingerprint, or compare two fingerprint images directly using image processing toots. The former involves very complicated calculations and tedious algorithms, and the latter tend to work poorly. In this paper it is described a new method which takes the middle ground. This paper studies the implementation of the Fast Fourier Transform and Artificial Neural Networks into the recognition of fingerprints. With tests conducted on the implementation of the Fourier Transform as a method of fingerprint feature extraction, the use of the Fourier Transform …

Dynamic Bandwidth Allocation Using Neural-Fuzzy In Atm Network, Yan Sing Chua

Student Works (2000-2009)

Dynamic bandwidth allocation is becoming one of the crucial issues in the design and research in the computer network. This is due to the continuous increasing demand of intensive applications that require more bandwidth while retaining higher quality. Dynamic bandwidth allocation utilises the current network state information to optimise the bandwidth distribution. The state information can be gathered through prediction using past data and measurement on current state. Agility and flexibility of dynamic bandwidth allocation using Neural-Fuzzy has the advantage that it can adapt to the state changes of the network. ATM network carries heterogeneous traffic and this causes the …

Hopfield Model For Shortest Path Computation And Routing In Atm Network, Chee Weng Lee

Student Works (2000-2009)

This research focuses on the application of Hopfield neural network and Boltmann machine in solving the shortest path routing problem in the ATM network environment. Hopfield neural network and Boltzmann machine are two types of neural network which are commonly used for solving optimization problem such as the shortest path routing problem. The objectives of this research are to construct a Hopfield neural network and a Boltzmann machine for solving the shortest path routing problem in the ATM network. Both of these two types of neural network are built based on a chosen example of an A TM network. The …

Design Of Adaptive Sliding Mode Fuzzy Control For Robot Manipulator Based On Extended Kalman Filter, Abdelrahman Aledhaibi

Mechanical & Aerospace Engineering Theses & Dissertations

In this work, a new adaptive motion control scheme for robust performance control of robot manipulators is presented. The proposed scheme is designed by combining the fuzzy logic control with the sliding mode control based on extended Kalman filter. Fuzzy logic controllers have been used successfully in many applications and were shown to be superior to the classical controllers for some nonlinear systems. Sliding mode control is a powerful approach for controlling nonlinear and uncertain systems. It is a robust control method and can be applied in the presence of model uncertainties and parameter disturbances, provided that the bounds of …

Bottom-Up Design Of Artificial Neural Network For Single-Lead Electrocardiogram Beat And Rhythm Classification, Srikanth Thiagarajan

Doctoral Dissertations

Performance improvement in computerized Electrocardiogram (ECG) classification is vital to improve reliability in this life-saving technology. The non-linearly overlapping nature of the ECG classification task prevents the statistical and the syntactic procedures from reaching the maximum performance. A new approach, a neural network-based classification scheme, has been implemented in clinical ECG problems with much success. The focus, however, has been on narrow clinical problem domains and the implementations lacked engineering precision. An optimal utilization of frequency information was missing. This dissertation attempts to improve the accuracy of neural network-based single-lead (lead-II) ECG beat and rhythm classification. A bottom-up approach defined …

Application Of Vibrational Techniques In Determination Of Dynamic Properties Of Agricultural Products-State Of The Arton Of Vibrational Techniques In Determination Of Dynamic Properties Of Agricultural Products-State Of The Art, Silas Kajuna

Tanzania Journal of Engineering and Technology (TJET)

Vibration is one of the techniques employed in the determination of dynamic properties of fruits and vegetables. It entails generation of a mechanical or acoustic vibrational signal which is propagated through the flesh of the agricultural material. A transducer is either attached or held close to the specimen to monitor the propagation of the signal through the specimen. The manner in which the signal is transmitted through the material is analyzed, and the dynamic properties of the specimen which relate to its firmness or its internal being are derived. The technique has been around for the past 30 years or …

Newton Parameter Update Algorithm For Recurrent Neural Networks Applied To Adaptive System Identification And Control, Donald Allen Gates

Electrical & Computer Engineering Theses & Dissertations

This paper shows that the combination of a second-order neural network parameter update algorithm and internal network feedback can be effectively used for adaptive, nonlinear, dynamical system identification and control. Adaptive neural identification and control algorithms are typically utilized for real-time applications where the rate of adaptation is often critical. A fast, adaptive network parameter update algorithm is presented.

Simulation results show that this algorithm is capable of quickly identifying and adapting to changes in system parameters, making it feasible to use for real-time control and fault accommodation applications.

Multiple Stochastic Learning Automata For Vehicle Path Control In An Automated Highway System, Cem Unsal, Pushkin Kachroo, John S. Bay

Electrical & Computer Engineering Faculty Research

This paper suggests an intelligent controller for an automated vehicle planning its own trajectory based on sensor and communication data. The intelligent controller is designed using the learning stochastic automata theory. Using the data received from on-board sensors, two automata (one for lateral actions, one for longitudinal actions) can learn the best possible action to avoid collisions. The system has the advantage of being able to work in unmodeled stochastic environments, unlike adaptive control methods or expert systems. Simulations for simultaneous lateral and longitudinal control of a vehicle provide encouraging results

Fuzzy Logic Applied To System Control To Enhance Commercial Appliance Performance, Glenn Moffett

Doctoral Dissertations

The purpose of this research is to determine the usefulness of fuzzy logic and fuzzy control when applied to a commercial appliance. Fuzzy logic is a structured, model-free estimator that approximates a function through linguistic input/output associations. Fuzzy rule-based systems apply these methods to solve many types of "real-world" problems, especially where a system is difficult to model, is controlled by a human operator or expert, or where ambiguity or vagueness is common.

This dissertation presents fuzzy sets, fuzzy systems, and fuzzy control, with an example conveying the use of fuzzy control of a consumer product and an overview of …

Singularity Avoidance Strategies For Satellite Mounted Manipulators Using Attitude Control, Nathan A. Titus

Theses and Dissertations

Control concepts for satellite mounted manipulators (SMM) are examined. The primary focus is on base actuated concepts, which eliminate singularity problems associated with free floating SMMs. A new form of the equations of motion for an n-link SMM is developed using a quasi coordinate form of Lagrange's Equation. Alternative free floating SMM designs are presented which eliminate dynamic singularities, but still experience difficulties due to the unactuated base. A new generic SMM controller is developed as a framework for various control concepts with and without base actuation. Momentum constrained Jacobians are shown to produce better SMM tracking than fixed base …

Study Of Human Factors Variables In Battle Outcome Prediction Models, David Andrew Glovier

Engineering Management & Systems Engineering Theses & Dissertations

Over time there have been many improvements in models that are used to predict the outcome of battles. Currently there is much supposition and speculation surrounding the use of human performance related factors as additional inputs to battle simulation models to improve their accuracy. However there is no conclusive scientific evidence which shows that these factors do make a significant difference. This study investigates the use of factors that may impact on the human performance directly or indirectly in battle prediction models. These factors consist of traditional human factors and external factors that may influence the human performance. The research …

Design And Design Centers In Engineering Education, Clive L. Dym

All HMC Faculty Publications and Research

This paper is intended to be the opening salvo of the workshop, Computing Futures in Engineering Design (Dym, 1997). Thus, I want to take this privileged moment to ask you to think with me about the role of design in engineering. In particular, I want to reflect upon how design is articulated and how design is taught; about the role of design in engineering education and in the practice of engineering; and about the role that could be played locally and, perhaps, nationally by a center devoted to design education. Because I teach here at Harvey Mudd College (HMC), …

Virtual Reality Modelling Of A Cnc Machine, Damian O'Sullivan

Theses

The increasing importance of training and upgrading skills has led to the use of new interactive technologies in the development of more effective training tools. Previous techniques for training Computer Numerical Control (CNC) machine operators, while excellent for their time, varied from brief inexpensive tutorials to expensive on the job training. A CNC machine uses a computer to perform the functions of the machine using a part program stored in the memory of the computer. This thesis describes a Virtual Reality (VR) model of a CNC milling machine, implemented within a VR environment representing a CNC workshop. Its development and …

Simulation Study Of Learning Automata Games In Automated Highway Systems, Cem Unsal, Pushkin Kachroo, John S. Bay

Electrical & Computer Engineering Faculty Research

One of the most important issues in Automated Highway System (AHS) deployment is intelligent vehicle control. While the technology to safely maneuver vehicles exists, the problem of making intelligent decisions to improve a single vehicle’s travel time and safety while optimizing the overall traffic flow is still a stumbling block. We propose an artificial intelligence technique called stochastic learning automata to design an intelligent vehicle path controller. Using the information obtained by on-board sensors and local communication modules, two automata are capable of learning the best possible (lateral and longitudinal) actions to avoid collisions. This learning method is capable of …

A Synthesized Methodology For Eliciting Expert Judgment For Addressing Uncertainty In Decision Analysis, Richard W. Monroe

Engineering Management & Systems Engineering Theses & Dissertations

This dissertation describes the development, refinement, and demonstration of an expert judgment elicitation methodology. The methodology has been developed by synthesizing the literature across several social science and scientific fields. The foremost consideration in the methodology development has been to incorporate elements that are based on reasonable expectations for the human capabilities of the user, the expert in this case.

Many methodologies exist for eliciting assessments for uncertain events. These are frequently elicited in probability form. This methodology differs by incorporating a qualitative element as a beginning step for the elicitation process. The qualitative assessment is a more reasonable way …

Development Of Object-Based Teleoperator Control For Unstructured Applications, Hyunki Cho

Theses and Dissertations

For multi-fingered end effectors in unstructured applications, the main issues are control in the presence of uncertainties and providing grasp stability and object manipulability. The suggested concept in this thesis is object based teleoperator control which provides an intuitive way to control the robot in terms of the grasped object and reduces the operator's conceptual constraints. The general control law is developed using a hierarchical control structure, i.e., human interface I gross motion control level in teleoperation control and fine motion control/object grasp stability in autonomous control. The gross motion control is required to provide the position/orientation of the Super …

Exploring Knowledge Processes For Technology Assimilation, Rochelle K. Young

Engineering Management & Systems Engineering Theses & Dissertations

In the emerging knowledge society, the ability to make the experience and expertise of those involved in and affected by new technology unconditionally available to all members of an organization is becoming increasingly important. One of the problems in developing such knowledge processes for technology assimilation is that current social structures do not easily accommodate unconditional participation. Since the implementation of modern information technology is changing the workplace and the nature of work itself, alternative social structures are needed. This research takes as given that deep questions concerning knowledge processes and social transformation are in principle undecidable; and, only questions …

Combinatorial Approaches For Hard Problems In Manpower Scheduling, Hoong Chuin Lau

Research Collection School Of Computing and Information Systems

Manpower scheduling is concerned with the construction of a workers' schedule which meets demands while satisfying given constraints. We consider a manpower scheduling Problem, called the Change Shift Assignment Problem(CSAP). In previous work, we proved that CSAP is NP-hard and presented greedy methods to solve some restricted versions. In this paper, we present combinatorial algorithms to solve more general and realistic versions of CSAP which are unlikely solvable by greedy methods. First, we model CSAP as a fixed-charge network and show that a feasible schedule can be obtained by finding disjoint paths in the network, which can be derived from …

Randomized Approximation Of The Constraint Satisfaction Problem, Hoong Chuin Lau, Osamu Watanabe

Research Collection School Of Computing and Information Systems

We consider the Weighted Constraint Satisfaction Problem (W-CSP) which is a fundamental problem in Artificial Intelligence and a generalization of important combinatorial problems such as MAX CUT and MAX SAT. In this paper, we prove non-approximability properties of W-CSP and give improved approximations of W-CSP via randomized rounding of linear programming and semidefinite programming relaxations. Our algorithms are simple to implement and experiments show that they are run-time efficient.

Intelligent Control Of Vehicles: Preliminary Results On The Application Of Learning Automata Techniques To Automated Highway System, Cem Unsal, John S. Bay, Pushkin Kachroo

Electrical & Computer Engineering Faculty Research

We suggest an intelligent controller for an automated vehicle to plan its own trajectory based on sensor and communication data received. Our intelligent controller is based on an artificial intelligence technique called learning stochastic automata. The automaton can learn the best possible action to avoid collisions using the data received from on-board sensors. The system has the advantage of being able to work in unmodeled stochastic environments. Simulations for the lateral control of a vehicle using this AI method provides encouraging results.