Computer Engineering Commons^™

Cognitive Architectures And Autonomy: Commentary And Response, Włodzisław Duch, Ah-Hwee Tan, Stan Franklin

Research Collection School Of Computing and Information Systems

This paper provides a very useful and promising analysis and comparison of current architectures of autonomous intelligent systems acting in real time and specific contexts, with all their constraints. The chosen issue of Cognitive Architectures and Autonomy is really a challenge for AI current projects and future research. I appreciate and endorse not only that challenge but many specific choices and claims; in particular: (i) that “autonomy” is a key concept for general intelligent systems; (ii) that “a core issue in cognitive architecture is the integration of cognitive processes ....”; (iii) the analysis of features and capabilities missing in current …

Real-Time Mobile Stereo Vision, Bryan Hale Bodkin

Masters Theses

Computer stereo vision is used extract depth information from two aligned cameras and there are a number of hardware and software solutions to solve the stereo correspondence problem. However few solutions are available for inexpensive mobile platforms where power and hardware are major limitations. This Thesis will proposes a method that competes with an existing OpenCV stereo correspondence method in speed and quality, and is able to run on generic multi core CPU’s.

A Location-Aware Architecture Supporting Intelligent Real-Time Mobile Applications, Sean J. Barbeau

USF Tampa Graduate Theses and Dissertations

This dissertation presents LAISYC, a modular location-aware architecture for intelligent real-time mobile applications that is fully-implementable by third party mobile app developers and supports high-precision and high-accuracy positioning systems such as GPS. LAISYC significantly improves device battery life, provides location data authenticity, ensures security of location data, and significantly reduces the amount of data transferred between the phone and server. The design, implementation, and evaluation of LAISYC using real mobile phones include the following modules: the GPS Auto-Sleep module saves battery energy when using GPS, maintaining acceptable movement tracking (approximately 89% accuracy) with an approximate average doubling of battery life. …

Multi-Tier Exploration Concept Demonstration Mission, Jeremy Straub

Jeremy Straub

A multi-tier, multi-craft mission architecture has been proposed but, despite its apparent promise, limited use and testing of the architecture has been conducted. This paper proposes and details a mission concept and its implementation for testing this architecture in the terrestrial environment. It is expected that this testing will allow significant refinement of the proposed architecture as well as providing data on its suitability for use in both terrestrial and extra-terrestrial applications. Logistical and technical challenges with this testing are discussed.

Provable De-Anonymization Of Large Datasets With Sparse Dimensions, Anupam Datta, Divya Sharma, Arunesh Sinha

Research Collection School Of Computing and Information Systems

There is a significant body of empirical work on statistical de-anonymization attacks against databases containing micro-dataabout individuals, e.g., their preferences, movie ratings, or transactiondata. Our goal is to analytically explain why such attacks work. Specifically, we analyze a variant of the Narayanan-Shmatikov algorithm thatwas used to effectively de-anonymize the Netflix database of movie ratings. We prove theorems characterizing mathematical properties of thedatabase and the auxiliary information available to the adversary thatenable two classes of privacy attacks. In the first attack, the adversarysuccessfully identifies the individual about whom she possesses auxiliaryinformation (an isolation attack). In the second attack, the adversarylearns additional …

Adaptive Algorithms For Coverage Control And Space Partitioning In Mobile Robotic Networks, Jerome Le Ny, George J. Pappas

George J. Pappas

We consider deployment problems where a mobile robotic network must optimize its configuration in a distributed way in order to minimize a steady-state cost function that depends on the spatial distribution of certain probabilistic events of interest. Three classes of problems are discussed in detail: coverage control problems, spatial partitioning problems, and dynamic vehicle routing problems. Moreover, we assume that the event distribution is a priori unknown, and can only be progressively inferred from the observation of the location of the actual event occurrences. For each problem we present distributed stochastic gradient algorithms that optimize the performance objective. The stochastic …

Adaptive Algorithms For Coverage Control And Space Partitioning In Mobile Robotic Networks, Jerome Le Ny, George J. Pappas

George J. Pappas

We consider deployment problems where a mobile robotic network must optimize its configuration in a distributed way in order to minimize a steady-state cost function that depends on the spatial distribution of certain probabilistic events of interest. Three classes of problems are discussed in detail: coverage control problems, spatial partitioning problems, and dynamic vehicle routing problems. Moreover, we assume that the event distribution is a priori unknown, and can only be progressively inferred from the observation of the location of the actual event occurrences. For each problem we present distributed stochastic gradient algorithms that optimize the performance objective. The stochastic …

Adaptive Algorithms For Coverage Control And Space Partitioning In Mobile Robotic Networks, Jerome Le Ny, George J. Pappas

George J. Pappas

We consider deployment problems where a mobile robotic network must optimize its configuration in a distributed way in order to minimize a steady-state cost function that depends on the spatial distribution of certain probabilistic events of interest. Three classes of problems are discussed in detail: coverage control problems, spatial partitioning problems, and dynamic vehicle routing problems. Moreover, we assume that the event distribution is a priori unknown, and can only be progressively inferred from the observation of the location of the actual event occurrences. For each problem we present distributed stochastic gradient algorithms that optimize the performance objective. The stochastic …

Operating Software, Donovan Torgerson, Miyuru Arangala, Michael Hlas, David Bullock, Dayln Limesand, Cameron Kerbaugh, Daniel Schuler, Mitchell Fossen, Edwin Carlson, Atif Mohammad, Josh Berk, Jeremy Straub

Jeremy Straub

No abstract provided.

Cubesat Software Architecture, Christoffer Korvald, Atif Mohammad, Jeremy Straub, Josh Berk

Jeremy Straub

No abstract provided.

Payload Software, Christoffer Korvald, Jeremy Straub, Atif Mohammad, Josh Berk

Jeremy Straub

No abstract provided.

The Application Of Fuzzy Granular Computing For The Analysis Of Human Dynamic Behavior In 3d Space, Murad Mohammad Alaqtash

Open Access Theses & Dissertations

Human dynamic behavior in space is very complex in that it involves many physical, perceptual and motor aspects. It is tied together at a sensory level by linkages between vestibular, visual and somatosensory information that develop through experience of inertial and gravitational reaction forces. Coordinated movement emerges from the interplay among descending output from the central nervous system, sensory input from the body and environment, muscle dynamics, and the emergent dynamics of the whole neuromusculoskeletal system.

There have been many attempts to directly capture the activities of the neuronal system in human locomotion without the ability to clarify how the …

Preface: Trends In Natural And Machine Intelligence, Jonathan H. Chan, Ah-Hwee Tan

Research Collection School Of Computing and Information Systems

Trends in natural and machine intelligence are increasingly reflecting a convergence in these two well-established fields of study. The Third International Neural Network Society Winter Conference (INNS-WC 2012) was held in Bangkok, Thailand, on October 3-5, 2012. INNS-WC2012, with an aim to bring together scientists, practitioners, and students worldwide, to discuss the past, present, and future challenges and trends in the area of natural and machine intelligence. This event has been a bi-annual conference of the International Neural Network Society (INNS) to provide a forum for international researchers to exchange latest ideas and advances on neural networks and related discipline.