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Articles 421 - 450 of 501

Full-Text Articles in Engineering

A Java Framework For Computer Vision, Stephen Sheridan Nov 2015

A Java Framework For Computer Vision, Stephen Sheridan

The ITB Journal

This paper outlines a framework implemented entirely in Java that attempts to give students exposure to computer vision systems from a practical standpoint. Various tools and technologies are introduced that will allow a student to acquire an input image through a WebCam, extract useful information from that input image and finally, attempt to make sense of the input.

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Determination Of Rule Patterns In Complex Event Processing Using Machine Learning Techniques, Nijat Mehdiyev, Julian Krumeich, David Lee Enke, Dirk Werth, Peter Loos Nov 2015

Determination Of Rule Patterns In Complex Event Processing Using Machine Learning Techniques, Nijat Mehdiyev, Julian Krumeich, David Lee Enke, Dirk Werth, Peter Loos

Engineering Management and Systems Engineering Faculty Research & Creative Works

Complex Event Processing (CEP) is a novel and promising methodology that enables the real-time analysis of stream event data. The main purpose of CEP is detection of the complex event patterns from the atomic and semantically low-level events such as sensor, log, or RFID data. Determination of the rule patterns for matching these simple events based on the temporal, semantic, or spatial correlations is the central task of CEP systems. In the current design of the CEP systems, experts provide event rule patterns. Having reached maturity, the Big Data Systems and Internet of Things (IoT) technology require the implementation of …

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The Design And Implementation Of An Adaptive Chess Game, Mehdi Peiravi Sep 2015

The Design And Implementation Of An Adaptive Chess Game, Mehdi Peiravi

Electronic Theses, Projects, and Dissertations

In recent years, computer games have become a common form of entertainment. Fast advancement in computer technology and internet speed have helped entertainment software developers to create graphical games that keep a variety of players’ interest. The emergence of artificial intelligence systems has evolved computer gaming technology in new and profound ways. Artificial intelligence provides the illusion of intelligence in the behavior of NPCs (Non-Playable-Characters). NPCs are able to use the increased CPU, GPU, RAM, Storage and other bandwidth related capabilities, resulting in very difficult game play for the end user. In many cases, computer abilities must be toned down …

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Novelty Wins, “Straight Toward Objective” Loses! Or Book Review: Why Greatness Cannot Be Planned: The Myth Of The Objective, By Kenneth O. Stanley And Joel Lehman, Reuben Hersh Jul 2015

Novelty Wins, “Straight Toward Objective” Loses! Or Book Review: Why Greatness Cannot Be Planned: The Myth Of The Objective, By Kenneth O. Stanley And Joel Lehman, Reuben Hersh

Journal of Humanistic Mathematics

Experiments in evolutionary artificial intelligence demonstrate that progress toward an important, difficult goal is not best achieved by attempting to go directly toward that goal, but rather, by rewarding novelty.

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Probabilistic Inference Based Message-Passing For Resource Constrained Dcops, Supriyo Ghosh, Akshat Kumar, Pradeep Varakantham Jul 2015

Probabilistic Inference Based Message-Passing For Resource Constrained Dcops, Supriyo Ghosh, Akshat Kumar, Pradeep Varakantham

Research Collection School Of Computing and Information Systems

Distributed constraint optimization (DCOP) is an important framework for coordinated multiagent decision making. We address a practically useful variant of DCOP, called resource-constrained DCOP (RC-DCOP), which takes into account agents’ consumption of shared limited resources. We present a promising new class of algorithm for RC-DCOPs by translating the underlying co- ordination problem to probabilistic inference. Using inference techniques such as expectation- maximization and convex optimization machinery, we develop a novel convergent message-passing algorithm for RC-DCOPs. Experiments on standard benchmarks show that our approach provides better quality than previous best DCOP algorithms and has much lower failure rate. Comparisons against an …

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The Application Of Biomedical Engineering Techniques To The Diagnosis And Management Of Tropical Diseases: A Review, Fatimah Ibrahim, Tzer Hwai Gilbert Thio, Tarig Faisal, Michael Neuman Mar 2015

The Application Of Biomedical Engineering Techniques To The Diagnosis And Management Of Tropical Diseases: A Review, Fatimah Ibrahim, Tzer Hwai Gilbert Thio, Tarig Faisal, Michael Neuman

Michigan Tech Publications, Part 1

This paper reviews a number of biomedical engineering approaches to help aid in the detection and treatment of tropical diseases such as dengue, malaria, cholera, schistosomiasis, lymphatic filariasis, ebola, leprosy, leishmaniasis, and American trypanosomiasis (Chagas). Many different forms of non-invasive approaches such as ultrasound, echocardiography and electrocardiography, bioelectrical impedance, optical detection, simplified and rapid serological tests such as lab-on-chip and micro-/nano-fluidic platforms and medical support systems such as artificial intelligence clinical support systems are discussed. The paper also reviewed the novel clinical diagnosis and management systems using artificial intelligence and bioelectrical impedance techniques for dengue clinical applications.

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A Computational Intelligence Approach To System-Of-Systems Architecting Incorporating Multi-Objective Optimization, David M. Curry, Cihan H. Dagli Mar 2015

A Computational Intelligence Approach To System-Of-Systems Architecting Incorporating Multi-Objective Optimization, David M. Curry, Cihan H. Dagli

Engineering Management and Systems Engineering Faculty Research & Creative Works

A computational intelligence approach to system-of-systems architecting is developed using multi-objective optimization. Such an approach yields a set of optimal solutions (the Pareto set) which has both advantages and disadvantages. The primary benefit is that a set of solutions provides a picture of the optimal solution space that a single solution cannot. The primary difficulty is making use of a potentially infinite set of solutions. Therefore, a significant part of this approach is the development of a method to model the solution set with a finite number of points allowing the architect to intelligently choose a subset of optimal solutions …

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Designing A Portfolio Of Parameter Configurations For Online Algorithm Selection, Aldy Gunawan, Hoong Chuin Lau, Mustafa Misir Jan 2015

Designing A Portfolio Of Parameter Configurations For Online Algorithm Selection, Aldy Gunawan, Hoong Chuin Lau, Mustafa Misir

Research Collection School Of Computing and Information Systems

Algorithm portfolios seek to determine an effective set of algorithms that can be used within an algorithm selection framework to solve problems. A limited number of these portfolio studies focus on generating different versions of a target algorithm using different parameter configurations. In this paper, we employ a Design of Experiments (DOE) approach to determine a promising range of values for each parameter of an algorithm. These ranges are further processed to determine a portfolio of parameter configurations, which would be used within two online Algorithm Selection approaches for solving different instances of a given combinatorial optimization problem effectively. We …

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A Theory Of Name Resolution, Pierre Néron, Andrew Tolmach, Eelco Visser, Guido Wachsmuth Jan 2015

A Theory Of Name Resolution, Pierre Néron, Andrew Tolmach, Eelco Visser, Guido Wachsmuth

Computer Science Faculty Publications and Presentations

We describe a language-independent theory for name binding and resolution, suitable for programming languages with complex scoping rules including both lexical scoping and modules. We formulate name resolution as a two-stage problem. First a language-independent scope graph is constructed using language-specific rules from an abstract syntax tree. Then references in the scope graph are resolved to corresponding declarations using a language-independent resolution process. We introduce a resolution calculus as a concise, declarative, and language- independent specification of name resolution. We develop a resolution algorithm that is sound and complete with respect to the calculus. Based on the resolution calculus we …

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Autonomous Quadcopter Videographer, Quiquia Rey Coaguila Jan 2015

Autonomous Quadcopter Videographer, Quiquia Rey Coaguila

Electronic Theses and Dissertations

In recent years, the interest in quadcopters as a robotics platform for autonomous photography has increased. This is due to their small size and mobility, which allow them to reach places that are difficult or even impossible for humans. This thesis focuses on the design of an autonomous quadcopter videographer, i.e. a quadcopter capable of capturing good footage of a specific subject. In order to obtain this footage, the system needs to choose appropriate vantage points and control the quadcopter. Skilled human videographers can easily spot good filming locations where the subject and its actions can be seen clearly in …

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Modeling User Transportation Patterns Using Mobile Devices, Erfan Davami Jan 2015

Modeling User Transportation Patterns Using Mobile Devices, Erfan Davami

Electronic Theses and Dissertations

Participatory sensing frameworks use humans and their computing devices as a large mobile sensing network. Dramatic accessibility and affordability have turned mobile devices (smartphone and tablet computers) into the most popular computational machines in the world, exceeding laptops. By the end of 2013, more than 1.5 billion people on earth will have a smartphone. Increased coverage and higher speeds of cellular networks have given these devices the power to constantly stream large amounts of data. Most mobile devices are equipped with advanced sensors such as GPS, cameras, and microphones. This expansion of smartphone numbers and power has created a sensing …

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Sparse Coding Based Dense Feature Representation Model For Hyperspectral Image Classification, Ender Oguslu, Guoqing Zhou, Zezhong Zheng, Khan Iftekharuddin, Jiang Li Jan 2015

Sparse Coding Based Dense Feature Representation Model For Hyperspectral Image Classification, Ender Oguslu, Guoqing Zhou, Zezhong Zheng, Khan Iftekharuddin, Jiang Li

Electrical & Computer Engineering Faculty Publications

We present a sparse coding based dense feature representation model (a preliminary version of the paper was presented at the SPIE Remote Sensing Conference, Dresden, Germany, 2013) for hyperspectral image (HSI) classification. The proposed method learns a new representation for each pixel in HSI through the following four steps: sub-band construction, dictionary learning, encoding, and feature selection. The new representation usually has a very high dimensionality requiring a large amount of computational resources. We applied the l1/lq regularized multiclass logistic regression technique to reduce the size of the new representation. We integrated the method with a linear …

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Responses To Catastrophic Agi Risk: A Survey, Kaj Sotala, Roman V. Yampolskiy Dec 2014

Responses To Catastrophic Agi Risk: A Survey, Kaj Sotala, Roman V. Yampolskiy

Faculty and Staff Scholarship

Many researchers have argued that humanity will create artificial general intelligence (AGI) within the next twenty to one hundred years. It has been suggested that AGI may inflict serious damage to human well-being on a global scale ('catastrophic risk'). After summarizing the arguments for why AGI may pose such a risk, we review the fields proposed responses to AGI risk. We consider societal proposals, proposals for external constraints on AGI behaviors and proposals for creating AGIs that are safe due to their internal design.

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Bio-Inspired Optimization Of Ultra-Wideband Patch Antennas Using Graphics Processing Unit Acceleration, Brian Vyhnalek Jan 2014

Bio-Inspired Optimization Of Ultra-Wideband Patch Antennas Using Graphics Processing Unit Acceleration, Brian Vyhnalek

ETD Archive

Ultra-wideband (UWB) wireless systems have recently gained considerable attention as effective communications platforms with the properties of low power and high data rates. Applications of UWB such as wireless USB put size constraints on the antenna, however, which can be very dicult to meet using typical narrow band antenna designs. The aim of this thesis is to show how bio-inspired evolutionary optimization algorithms, in particular genetic algorithm (GA), particle swarm optimization (PSO) and biogeography-based optimization (BBO) can produce novel UWB planar patch antenna designs that meet a size constraint of a 10 mm 10 mm patch. Each potential antenna design …

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Intelligent Sensing Based On Low Cost Unmanned Aerial Vehicles (Uav) For Bridge Condition Assessment, Theodore Teates, Austin Boyd, Chung-Hao Chen Jan 2014

Intelligent Sensing Based On Low Cost Unmanned Aerial Vehicles (Uav) For Bridge Condition Assessment, Theodore Teates, Austin Boyd, Chung-Hao Chen

Electrical & Computer Engineering Faculty Publications

The eventual completion of this project envisions the use of an Unmanned Aerial Vehicle (UAV) to inspect bridge infrastructure. This project may also be expanded to encompass general object detection and inspection in order to unburden this technology so that it may reach its fullest potential. The project requires research and development in three distinct areas of image processing, control structures, and integration of systems. Initial undergraduate research sets the base knowledge for the overall project, explores the areas of concentration that are desired to expand upon in the future project, and provides a base UAV model that new researchers …

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Reasoning Across Language And Vision In Machines And Humans, Andrei Barbu Oct 2013

Reasoning Across Language And Vision In Machines And Humans, Andrei Barbu

Open Access Dissertations

Humans not only outperform AI and computer-vision systems, but use an unknown computational mechanism to perform tasks for which no suitable approaches exist. I present work investigating both novel tasks and how humans approach them in the context of computer vision and linguistics. I demonstrate a system which, like children, acquires high-level linguistic knowledge about the world. Robots learn to play physically-instantiated board games and use that knowledge to engage in physical play. To further integrate language and vision I develop an approach which produces rich sentential descriptions of events depicted in videos. I then show how to simultaneously detect …

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Towards Operations Excellence: Optimising Staff Scheduling For New Emergency Department, Amr Arisha, Waleed Abo Hamad Jun 2013

Towards Operations Excellence: Optimising Staff Scheduling For New Emergency Department, Amr Arisha, Waleed Abo Hamad

Conference papers

This paper presents a case study of an Emergency Department of a public hospital in Dublin, and uses an integrated approach to determine optimal staffing levels to meet the challenges of its dynamic patient demand levels. A comprehensive stochastic model is developed to incorporate patients care pathways and the resources required along their treatment journeys. Analytical Hierarchical Process is utilised to enable decision makers to set their preferences for the facility’s strategic objectives. Evolutionary algorithms are applied to optimise staff schedules. The resulted optimized schedules maintains continuity of care delivery for patients while ensuring a balanced equilibrium among available staff.

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Modeling Learner Mood In Realtime Through Biosensors For Intelligent Tutoring Improvements, Keith Brawner Jan 2013

Modeling Learner Mood In Realtime Through Biosensors For Intelligent Tutoring Improvements, Keith Brawner

Electronic Theses and Dissertations

Computer-based instructors, just like their human counterparts, should monitor the emotional and cognitive states of their students in order to adapt instructional technique. Doing so requires a model of student state to be available at run time, but this has historically been difficult. Because people are different, generalized models have not been able to be validated. As a person’s cognitive and affective state vary over time of day and seasonally, individualized models have had differing difficulties. The simultaneous creation and execution of an individualized model, in real time, represents the last option for modeling such cognitive and affective states. This …

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Cancer Risk Analysis By Fuzzy Logic Approach And Performance Status Of The Model, Atinç Yilmaz, Kürşat Ayan Jan 2013

Cancer Risk Analysis By Fuzzy Logic Approach And Performance Status Of The Model, Atinç Yilmaz, Kürşat Ayan

Turkish Journal of Electrical Engineering and Computer Sciences

Cancer is the leading life-threatening disease for people in today's world. Although cancer formation is different for each type of cancer, it has been determined by studies and research that stress also triggers cancer types. Early precaution is very important for people who have not fallen ill yet with a disease like cancer that has a high mortality rate and expensive treatment. With this study, we expound that the possibility of developing such disease may be decreased and people could take measures against it. For the 3 cancer types selected as pilot work by introducing a fuzzy logic model, the …

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A New Intelligent Classifier For Breast Cancer Diagnosis Based On A Rough Set And Extreme Learning Machine: Rs + Elm, Yilmaz Kaya Jan 2013

A New Intelligent Classifier For Breast Cancer Diagnosis Based On A Rough Set And Extreme Learning Machine: Rs + Elm, Yilmaz Kaya

Turkish Journal of Electrical Engineering and Computer Sciences

Breast cancer is one of the leading causes of death among women all around the world. Therefore, true and early diagnosis of breast cancer is an important problem. The rough set (RS) and extreme learning machine (ELM) methods were used collectively in this study for the diagnosis of breast cancer. The unnecessary attributes were discarded from the dataset by means of the RS approach. The classification process by means of ELM was performed using the remaining attributes. The Wisconsin Breast Cancer dataset (WBCD), derived from the University of California Irvine machine learning database, was used for the purpose of testing …

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Energy Efficiency Performance Improvements For Ant-Based Routing Algorithm In Wireless Sensor Networks, A. M. Zungeru, Kah Phooi Seng, Li-Minn Ang, W.C. Chia Jan 2013

Energy Efficiency Performance Improvements For Ant-Based Routing Algorithm In Wireless Sensor Networks, A. M. Zungeru, Kah Phooi Seng, Li-Minn Ang, W.C. Chia

Research outputs 2013

The main problem for event gathering in wireless sensor networks (WSNs) is the restricted communication range for each node. Due to the restricted communication range and high network density, event forwarding in WSNs is very challenging and requires multihop data forwarding. Currently, the energy-efficient ant based routing (EEABR) algorithm, based on the ant colony optimization (ACO) metaheuristic, is one of the state-of-the-art energy-aware routing protocols. In this paper, we propose three improvements to the EEABR algorithm to further improve its energy efficiency. The improvements to the original EEABR are based on the following: (1) a new scheme to intelligently initialize …

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Heuristic Methods For Optimization - Cornell University, Christine Shoemaker Oct 2012

Heuristic Methods For Optimization - Cornell University, Christine Shoemaker

All ECSTATIC Materials

Heuristic optimization algorithms are artificial intelligence search methods that can be used to find the optimal decisions for designing or managing a wide range of complex systems. This course describes a variety of (meta) heuristic search methods including simulated annealing, tabu search, genetic algorithms, genetic programming, dynamically dimensioned search, and multiobjective methods. Algorithms will be used to find values of discrete and/or continuous variables that optimize system performance or improve system reliability. Students can select application projects from a range of application areas. The advantages and disadvantages of heuristic search methods for both serial and parallel computation are discussed in …

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Novelty-Assisted Interactive Evolution Of Control Behaviors, Brian G. Woolley Jan 2012

Novelty-Assisted Interactive Evolution Of Control Behaviors, Brian G. Woolley

Electronic Theses and Dissertations

The field of evolutionary computation is inspired by the achievements of natural evolution, in which there is no final objective. Yet the pursuit of objectives is ubiquitous in simulated evolution because evolutionary algorithms that can consistently achieve established benchmarks are lauded as successful, thus reinforcing this paradigm. A significant problem is that such objective approaches assume that intermediate stepping stones will increasingly resemble the final objective when in fact they often do not. The consequence is that while solutions may exist, searching for such objectives may not discover them. This problem with objectives is demonstrated through an experiment in this …

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Object Retrieval From Secure Unknown Interior Spaces Using Autonomous Unmanned Aerial Vehicles, John Levous, Julie Hoven, Victor Habgood, Abdulrahman Alotaibi, Brandon Ordway, Garibe Mohammed-Jones, Haole Guo, Filip Cuckov, Chung-Hao Chen Jan 2012

Object Retrieval From Secure Unknown Interior Spaces Using Autonomous Unmanned Aerial Vehicles, John Levous, Julie Hoven, Victor Habgood, Abdulrahman Alotaibi, Brandon Ordway, Garibe Mohammed-Jones, Haole Guo, Filip Cuckov, Chung-Hao Chen

Electrical & Computer Engineering Faculty Publications

This paper describes an autonomous unmanned aerial vehicle (UAV) designed to participate in the 23rd annual International Aerial Robotics Competition. The UAV is equipped with onboard sensors and a Harvard architecture 8-bit RISC microcontroller to monitor and locally control its flight telemetry. Additional sensors (and an additional microcontroller) are used for detecting and mapping of structural and environmental objects while the UAV is in flight. The microcontrollers are interfaced with wireless communication modules for transmitting flight telemetry and structural/environmental data to a ground control station that sends the UAV command and control signals required for the mission objectives. The UAV …

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Performance Of Termite-Hill Routing Algorithm On Sink Mobility In Wireless Sensor Networks, Adamu M Zungeru, Li-Minn Ang, Kah Phooi Seng Jan 2012

Performance Of Termite-Hill Routing Algorithm On Sink Mobility In Wireless Sensor Networks, Adamu M Zungeru, Li-Minn Ang, Kah Phooi Seng

Research outputs 2012

High efficient and energy-aware routing is an important issue for the design of resource constrained environments like Wireless Sensor Networks (WSNs). Many protocols have been developed for WSN that try to overcome the constraints that characterized this type of networks. Termite based routing protocols can add a significant contribution to assist in the maximization of the network lifetime without performance degradation. But this is only possible by means of an adaptable and balanced algorithm that takes into account the main constraints of WSN. This paper presents a biological inspired self-organized routing protocol for WSN which is based on termite colony …

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Evolving Machine Morality Strategies Through Multiagent Simulations, David Burke Jun 2011

Evolving Machine Morality Strategies Through Multiagent Simulations, David Burke

Systems Science Friday Noon Seminar Series

There is a general consensus among robotics researchers that the world of the future will be filled with autonomous and semi-autonomous machines. There is less of a consensus, though, on the best approach to instilling a sense of 'machine morality' in these systems so that they will be able to have effective interactions with humans in an increasingly complex world. In my talk, we take a brief look at some existing approaches to computational ethics, and then describe work we've undertaken creating multiagent simulations involving moral decision-making during strategic interactions. In these simulations, agents make choices about whether to cooperate …

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Human-Computer Interaction And Human Mental Workload: Assessing Cognitive Engagement In The World Wide Web, Luca Longo Jan 2011

Human-Computer Interaction And Human Mental Workload: Assessing Cognitive Engagement In The World Wide Web, Luca Longo

Books/Book Chapters

Assessing the cognitive engagement of a user while seeking and consuming information over the World Wide Web is a key challenge for studying the quality of interactions. Indicators of cognitive engagement are useful for enhancing usability of interfaces, designing adaptable systems but also for analysing user behaviour and performance. For this purpose, we aim to adopt the multifaceted concept of Human Mental Workload, mainly applied in psychology and cognitive sciences, to study individual performance and user engagement in the context of Web. We aim to design a framework in which mental workload can be measured, analysed and explained. This will …

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Intelligent Controls For A Semi-Active Hydraulic Prosthetic Knee, Timothy Allen Wilmot Jan 2011

Intelligent Controls For A Semi-Active Hydraulic Prosthetic Knee, Timothy Allen Wilmot

ETD Archive

We discuss open loop control development and simulation results for a semi-active above-knee prosthesis. The control signal consists of two hydraulic valve settings. These valves control a rotary actuator that provides torque to the prosthetic knee. We develop open loop control using biogeography-based optimization (BBO), which is a recently developed evolutionary algorithm, and gradient descent. We use gradient descent to show that the control generated by BBO is locally optimal. This research contributes to the field of evolutionary algorithms by demonstrating that BBO is successful at finding optimal solutions to complex, real-world, nonlinear, time varying control problems. The research contributes …

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Spatio-Temporal Negotiation Protocols, Yi Luo Jan 2011

Spatio-Temporal Negotiation Protocols, Yi Luo

Electronic Theses and Dissertations

Canonical problems are simplified representations of a class of real world problems. They allow researchers to compare algorithms in a standard setting which captures the most important challenges of the real world problems being modeled. In this dissertation, we focus on negotiating a collaboration in space and time, a problem with many important real world applications. Although technically a multi-issue negotiation, we show that the problem can not be represented in a satisfactory manner by previous models. We propose the "Children in the Rectangular Forest" (CRF) model as a possible canonical problem for negotiating spatio-temporal collaboration. In the CRF problem, …

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Exploiting Opponent Modeling For Learning In Multi-Agent Adversarial Games, Kennard R. Laviers Jan 2011

Exploiting Opponent Modeling For Learning In Multi-Agent Adversarial Games, Kennard R. Laviers

Electronic Theses and Dissertations

An issue with learning effective policies in multi-agent adversarial games is that the size of the search space can be prohibitively large when the actions of both teammates and opponents are considered simultaneously. Opponent modeling, predicting an opponent’s actions in advance of execution, is one approach for selecting actions in adversarial settings, but it is often performed in an ad hoc way. In this dissertation, we introduce several methods for using opponent modeling, in the form of predictions about the players’ physical movements, to learn team policies. To explore the problem of decision-making in multi-agent adversarial scenarios, we use our …

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