Physical Sciences and Mathematics Commons^™

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.

Topic Detection, Tracking, And Trend Analysis Using Self-Organizing Neural Networks, Kanagasabai Rajaraman, Ah-Hwee Tan

Research Collection School Of Computing and Information Systems

We address the problem of Topic Detection and Tracking (TDT) and subsequently detecting trends from a stream of text documents. Formulating TDT as a clustering problem in a class of self-organizing neural networks, we propose an incremental clustering algorithm. On this setup we show how trends can be identified. Through experimental studies, we observe that our method enables discovering interesting trends that are deducible only from reading all relevant documents.

Joachim Castella: Studien Zur Thematik "Kalkül Und Kreativität", Rudolf Kaehr

Rudolf Kaehr

Utopie der Zeichen – Zeichen der Utopie Vilém Flusser und Gotthard Günther als Komplement einer neuen Medienphilosophie Medientheorie als Theoriemedium Prolegomena einer allgemeinenMedientheorie Philosophie des LMR Joachim Castella 2000/2001

Distinguishing Natural Language Processes On The Basis Of Fmri-Measured Brain Activation, Francisco Pereira, Marcel Just, Tom Mitchell

Marcel Adam Just

No abstract provided.

Mental Rotation Of Objects Retrieved From Memory: An Fmri Study Of Spatial Processing, Marcel Just, Patricia Carpenter, Mandy Maguire, Vaibhav Diwadkar, Stephanie Mcmains

Marcel Adam Just

No abstract provided.

Interdependence Of Non-Overlapping Cortical Systems In Dual Cognitive Tasks, Marcel Adam Just, Patricia A. Carpenter, Timothy A. Keller, Lisa Emery, Holly Zajac, Keith R. Thulborn

Marcel Adam Just

No abstract provided.

A Service Paradigm For Reconfigurable Agents, Gary Holness, Deepak Karuppiah, Subramanya Uppala, Roderic Grupen, S. Chandu Ravela

Roderic Grupen

Applications of multiple processors embedded in the systems involved with entertainment, informatics, climate control, communication, transportation, and food preparation are already commonplace. A network of these embedded processors presents application development challenges since the state space grows exponentially as new devices attach to the network. The programming model for such systems will need to change if reliable systems are to be realized. By observing information about sensorimotor activity, such systems can gather information useful to programming the network. Through such interaction, a network can build hierarchies of shareable computational structures for representing various activities. This application domain presents additional challenges …

The Neural Bases Of Sentence Comprehension: A Fmri Examination Of Syntactic And Lexical Processing, Timothy A. Keller, Patricia A. Carpenter, Marcel Adam Just

Marcel Adam Just

No abstract provided.

An Fmri Investigation Of Sentence Comprehension By Eye And By Ear: Modality Fingerprints On Cognitive Processes, Erica B. Michael, Timothy A. Keller, Patricia A. Carpenter, Marcel Adam Just

Marcel Adam Just

No abstract provided.

Collaborative Model And Algorithms For Supporting Real-Time Distribution Logistics Systems, Hoong Chuin Lau, Qi Zhang Liu

Research Collection School Of Computing and Information Systems

We study a complex optimization problem that arises due to an emerging trend in distribution logistics. The problem involves the integration of an inventory management problem and the vehicle routing problem with time windows, both of which are known to be NP-hard. We describe a collaborative approach to solve this problem in real-time. The novelty of our approach lies in the tight algorithmic integration between two sub-problems, and suggests an elegant scheme to deal with other integrated optimization problems of the same nature. For first sub-problem, we will present two algorithms: a complete mathematical model integrating integer programming with constraint …

Side Collision Warning System For Transit Buses, Sue Mcneil, David Duggins, Christoph Mertz, Arne Suppe, Chuck Thorpe

Research Collection School Of Computing and Information Systems

Transit buses are involved in many more accidents than other vehicles. Collision warning systems (CWS) are therefore placed most efficiently on these buses. In our project, we investigate their operating environment and available technologies to develop performance specifications for such CWS. The paper discusses our findings of transit buses driving through very cluttered surroundings and being involved in many different types of accidents where currently available CWS no not work effectively. One of the focuses of our work is pedestrians around the bus and their detection.

Baldur's Gate Ii - Maps & Benchmark Problems, Nathan R. Sturtevant, Bioware Corp

Moving AI Lab: 2D Maps and Benchmark Problems

Maps extracted by Yngvi Björnsson from Baldur's Gate II with explicit permission from BioWare Corp. for use and distribution as benchmark problems.

Contains 75 maps and benchmark problem sets scaled to 512 x 512 and 120 original scale maps.

The Application And Performance Of A Generic Task Routine Decision Making Algorithm To Recipe Selection In Meal Planning, Michelle M. Cox

Theses and Dissertations - UTB/UTPA

A nutritional meal planning system was implemented to test the effectiveness of a previously developed routine decision making algorithm. The combinatorics involved in ordering recipes in all possible combinations to produce variability in a meal plan and provide sufficient nutrition is conceptually intensive. Meal planning involves selection of food to eat to fulfill a person's nutritional and personal preferences. This thesis demonstrates meal planning as a decision making problem and demonstrates the utility of the routine decision making algorithm by solving this problem. Generic Tasks, identified through artificial intelligence research, provides the basis for this algorithm. It uses user preferences …

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 …

Ria: Selecting Information To Include In Cooperative Task — Oriented Dialogues, Elise H. Turner

University of Maine Office of Research Administration: Grant Reports

The goal of this project was to delevop a technique for selecting information to volunteer in problem solving dialogues. The technique was to create usefulness ratings for information based on the problem solving of the agent that may communicate the information. Heuristics translate specific problem solving activities into contributions to the overall usefulness rating for the information. To this end, our objectives included determining the type of information that should be included in dialogues and implementing heuristics.

Fuzzy Neural Network Models For Classification, Arun D. Kulkarni, Charles D. Cavanaugh

Arun Kulkarni

Cataloging Expert Systems: Optimism And Frustrated Reality, William Olmstadt

E-JASL 1999-2009 (Volumes 1-10)

There is little question that computers have profoundly changed how information professionals work. The process of cataloging and classifying library materials was one of the first activities transformed by information technology. The introduction of the MARC format in the 1960s and the creation of national bibliographic utilities in the 1970s had a lasting impact on cataloging. In the 1980s, the affordability of microcomputers made the computer accessible for cataloging, even to small libraries. This trend toward automating library processes with computers parallels a broader societal interest in the use of computers to organize and store information. Following World War II, …

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 …

Ann As A Tool For Medical Prognosis, Sameem Abdul Kareem

Sameem Abdul Kareem

The analysis of cancer survival is used to determine the efficiency of treatment programmes and protocols; it is also used to determine the type of treatment. At the individual level a prediction of cancer survival can help patients make informed decisions with regards to their quality of life and future finances. Currently available prediction methods apply to groups of people, and may not be adequate to predict treatment outcome for individual patients. This paper presents a conceptual model of a cancer knowledge base incorporating a computer-based predictor for survival. It proposes the use of an artificial neural network (ANN) as …

An Inquiry Into The Development Of Expert Systems In Legal Reasoning, Trevor K. Sheeley

Presidential Scholars Theses (1990 – 2006)

The first goal of this paper is to review some of the steps necessary in developing a system that reasons effectively in some domain of law. The paper will begin by addressing the issues of domain selection, domain analysis and knowledge acquisition, knowledge representation, and selection of an inference method. After presenting a brief argument against using rule-based reasoning as the primary mode of inference, the paper will go on to expound the virtues of Kevin Ashley's HYPO, a software model of case based legal argument. It will conclude with a short description of my experience implementing part of a …

Masterpiece: Computer-Generated Music Through Fractals And Genetic Theory, Amanda Broyles

Honors Theses

A wide variety of computer-generated music exists. I have writ.ten a program which will generate music by using genetic theory and fractals. The genetic theory is used to mold input pieces into a musical motif. The motif is then elaborated by the fractal formula into a composition. A brief introduction to the world of genetic theory and fractals is given. Analysis of a musical work produced in this manner shows coherent patterns and also emotion.

Designing Electronic Casebooks That Talk Back: The Cato Program, Kevin D. Ashley

Articles

Electronic casebooks offer important benefits of flexibility in control of presentation, connectivity, and interactivity. These additional degrees of freedom, however, also threaten to overwhelm students. If casebook authors and instructors are to achieve their pedagogical goals, they will need new methods for guiding students. This paper presents three such methods developed in an intelligent tutoring environment for engaging students in legal role-playing, making abstract concepts explicit and manipulable, and supporting pedagogical dialogues. This environment is built around a program known as CATO, which employs artificial intelligence techniques to teach first-year law students how to make basic legal arguments with cases. …

Collaborative Activity Between Parietal And Dorso-Lateral Prefrontal Cortex In Dynamic Spatial Working Memory Revealed By Fmri, Vaibhav A. Diwadkar, Patricia A. Carpenter, Marcel Adam Just

Marcel Adam Just

No abstract provided.

The Neural Basis Of Strategy And Skill In Sentence-Picture Verification, Erik D. Reichle, Patricia A. A. Carpenter, Marcel Adam Just

Marcel Adam Just

No abstract provided.

Working Memory And Executive Function: Evidence From Neuroimaging, Patricia A. Carpenter, Marcel Adam Just, Erik D. Reichle

Marcel Adam Just

No abstract provided.

Grundlagenreflexionen Zur Thematik Anthropomorpher Schnittstellen, Rudolf Kaehr

Rudolf Kaehr

Report for the EMBASSI Project

Design Approaches To Model-Based Simulation In Intelligent Computer Assisted Instruction, Bjoern Helfesrieder, Venky Shankararaman

Research Collection School Of Computing and Information Systems

Model-based simulation systems have been created in various fields of engineering to train personnel or students in operation, maintenance and troubleshooting of complex devices and systems. A review of literature indicates a lack of good overviews of the approaches to system design of model-based training simulations in Intelligent Computer Assisted Instruction (ICAI). Though single systems have to some extent been evaluated with regard to their performance, an organised evaluation, especially a comparative evaluation of the systems that have been created within the field is lacking. To be able to successfully conduct an in-depth review under these conditions, we concentrate and …

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.

Structural Emergence And The Collaborative Behavior Of Autonomous Nano-Satellites, Daniel J. Petrovich

Theses and Dissertations

The collaborative behavior of nano-satellites in a zero-gravity environment is explored, and satellite characteristics are proposed that maximize constellation robustness and minimize manufacturing costs. Behavioral algorithms are proposed to facilitate both swarming and structural formation and are validated using the Structural Emergence Simulator (STEMS) Graphical User Interface (GUl). A payload of multiple satellites is placed in a zero-gravity environment and released to re-configure autonomously into a pre-designed structure. Data transmission between satellites is not permitted during the swarming phase of the structure formation mission. A binary behavior algorithm is invented that produces a direction and magnitude solution to the satellite …