A multimodal and adaptive real-time human -computer interface for peoples with severe motor disability

This dissertation introduces the design of a multimodal, adaptive real-time assistive system as an alternate human computer interface that can be used by individuals with severe motor disabilities. The proposed design is based on the integration of a remote eye-gaze tracking system, voice recognition software, and a virtual keyboard. The methodology relies on a user profile that customizes eye gaze tracking using neural networks. The user profiling feature facilitates the notion of universal access to computing resources for a wide range of applications such as web browsing, email, word processing and editing. ^ The study is significant in terms of the integration of key algorithms to yield an adaptable and multimodal interface. The contributions of this dissertation stem from the following accomplishments: (a) establishment of the data transport mechanism between the eye-gaze system and the host computer yielding to a significantly low failure rate of 0.9%; (b) accurate translation of eye data into cursor movement through congregate steps which conclude with calibrated cursor coordinates using an improved conversion function; resulting in an average reduction of 70% of the disparity between the point of gaze and the actual position of the mouse cursor, compared with initial findings; (c) use of both a moving average and a trained neural network in order to minimize the jitter of the mouse cursor, which yield an average jittering reduction of 35%; (d) introduction of a new mathematical methodology to measure the degree of jittering of the mouse trajectory; (e) embedding an onscreen keyboard to facilitate text entry, and a graphical interface that is used to generate user profiles for system adaptability. ^ The adaptability nature of the interface is achieved through the establishment of user profiles, which may contain the jittering and voice characteristics of a particular user as well as a customized list of the most commonly used words ordered according to the user's preferences: in alphabetical or statistical order. This allows the system to successfully provide the capability of interacting with a computer. Every time any of the sub-system is retrained, the accuracy of the interface response improves even more. ^

Signal processing of physiological signals for automated assessment of stress in computer users

The need to provide computers with the ability to distinguish the affective state of their users is a major requirement for the practical implementation of affective computing concepts. This dissertation proposes the application of signal processing methods on physiological signals to extract from them features that can be processed by learning pattern recognition systems to provide cues about a person's affective state. In particular, combining physiological information sensed from a user's left hand in a non-invasive way with the pupil diameter information from an eye-tracking system may provide a computer with an awareness of its user's affective responses in the course of human-computer interactions. In this study an integrated hardware-software setup was developed to achieve automatic assessment of the affective status of a computer user. A computer-based "Paced Stroop Test" was designed as a stimulus to elicit emotional stress in the subject during the experiment. Four signals: the Galvanic Skin Response (GSR), the Blood Volume Pulse (BVP), the Skin Temperature (ST) and the Pupil Diameter (PD), were monitored and analyzed to differentiate affective states in the user. Several signal processing techniques were applied on the collected signals to extract their most relevant features. These features were analyzed with learning classification systems, to accomplish the affective state identification. Three learning algorithms: Naïve Bayes, Decision Tree and Support Vector Machine were applied to this identification process and their levels of classification accuracy were compared. The results achieved indicate that the physiological signals monitored do, in fact, have a strong correlation with the changes in the emotional states of the experimental subjects. These results also revealed that the inclusion of pupil diameter information significantly improved the performance of the emotion recognition system. ^

Multinational enterprises and technological effort by local firms:a case study of the Malaysian electronics and electrical industry

It is often assumed that foreign MNEs are the driving force behind technological development in developing economies but it has become evident in recent years that the actions of MNEs in isolation from the domestic economy. The study, therefore, examines the determinants of local firms' decisions to undertake technological effort, not only in isolation, but also in the context of linkages between domestic firms and MNEs. There is evidence that linkages between MNEs and local firms are important in explaining technological effort by local firms but direct technological assistance from MNEs does not seem to play a major role in fostering increased technological effort by local firms.

On Software Engineering Repositories and Their Open Problems

In the last decade, a large number of software repositories have been created for different purposes. In this paper we present a survey of the publicly available repositories and classify the most common ones as well as discussing the problems faced by researchers when applying machine learning or statistical techniques to them.

Field programmable gate array based target detection and gesture recognition

The move from Standard Definition (SD) to High Definition (HD) represents a six times increases in data, which needs to be processed. With expanding resolutions and evolving compression, there is a need for high performance with flexible architectures to allow for quick upgrade ability. The technology advances in image display resolutions, advanced compression techniques, and video intelligence. Software implementation of these systems can attain accuracy with tradeoffs among processing performance (to achieve specified frame rates, working on large image data sets), power and cost constraints. There is a need for new architectures to be in pace with the fast innovations in video and imaging. It contains dedicated hardware implementation of the pixel and frame rate processes on Field Programmable Gate Array (FPGA) to achieve the real-time performance. ^ The following outlines the contributions of the dissertation. (1) We develop a target detection system by applying a novel running average mean threshold (RAMT) approach to globalize the threshold required for background subtraction. This approach adapts the threshold automatically to different environments (indoor and outdoor) and different targets (humans and vehicles). For low power consumption and better performance, we design the complete system on FPGA. (2) We introduce a safe distance factor and develop an algorithm for occlusion occurrence detection during target tracking. A novel mean-threshold is calculated by motion-position analysis. (3) A new strategy for gesture recognition is developed using Combinational Neural Networks (CNN) based on a tree structure. Analysis of the method is done on American Sign Language (ASL) gestures. We introduce novel point of interests approach to reduce the feature vector size and gradient threshold approach for accurate classification. (4) We design a gesture recognition system using a hardware/ software co-simulation neural network for high speed and low memory storage requirements provided by the FPGA. We develop an innovative maximum distant algorithm which uses only 0.39% of the image as the feature vector to train and test the system design. Database set gestures involved in different applications may vary. Therefore, it is highly essential to keep the feature vector as low as possible while maintaining the same accuracy and performance^

Network construction and graph theoretical analysis of functional language networks in pediatric epilepsy

This dissertation introduces a new approach for assessing the effects of pediatric epilepsy on the language connectome. Two novel data-driven network construction approaches are presented. These methods rely on connecting different brain regions using either extent or intensity of language related activations as identified by independent component analysis of fMRI data. An auditory description decision task (ADDT) paradigm was used to activate the language network for 29 patients and 30 controls recruited from three major pediatric hospitals. Empirical evaluations illustrated that pediatric epilepsy can cause, or is associated with, a network efficiency reduction. Patients showed a propensity to inefficiently employ the whole brain network to perform the ADDT language task; on the contrary, controls seemed to efficiently use smaller segregated network components to achieve the same task. To explain the causes of the decreased efficiency, graph theoretical analysis was carried out. The analysis revealed no substantial global network feature differences between the patient and control groups. It also showed that for both subject groups the language network exhibited small-world characteristics; however, the patient's extent of activation network showed a tendency towards more random networks. It was also shown that the intensity of activation network displayed ipsilateral hub reorganization on the local level. The left hemispheric hubs displayed greater centrality values for patients, whereas the right hemispheric hubs displayed greater centrality values for controls. This hub hemispheric disparity was not correlated with a right atypical language laterality found in six patients. Finally it was shown that a multi-level unsupervised clustering scheme based on self-organizing maps, a type of artificial neural network, and k-means was able to fairly and blindly separate the subjects into their respective patient or control groups. The clustering was initiated using the local nodal centrality measurements only. Compared to the extent of activation network, the intensity of activation network clustering demonstrated better precision. This outcome supports the assertion that the local centrality differences presented by the intensity of activation network can be associated with focal epilepsy.^

Optical and electrical characterization of samaria-doped ceria

Ce(0.8)SM(0.2)O(1.9) and CeO(2) nanomaterials were prepared by a solution technique to produce an ultrafine particulate material with high sinterability. In this work, the structural characteristics, the photoluminescent behavior and the ionic conductivity of the synthesized materials are focused. The thermally decomposed material consists of less than 10 nm in diameter nanoparticles. The Raman spectrum of pure CeO(2) consists of a single triple degenerate F(2g) model characteristic of the fluorite-like structure. The full width at half maximum of this band decreases linearly with increasing calcination temperature. The photoluminescence spectra show a broadened emission band assigned to the ligand-to-metal charge-transfer states O -> Ce(4+). The emission spectra of the Ce(0.8)Sm(0.2)O(1.9) specimens present narrow bands arising from the 4G(5/2) -> (6)H(J) transitions (J = 5/2, 7/2, 9/2 and 11/2) of Sm(3+) ion due to the efficient energy transfer from the O -> Ce(4+) transitions to the emitter 4G(5/2) level. The ionic conductivity of sintered specimens shows a significant dependence on density. (C) 2009 Elsevier B.V. All rights reserved.

Fuzzy distributed artificial intelligence systems

In this paper, we introduce a DAI approach called hereinafter Fuzzy Distributed Artificial Intelligence (FDAI). Through the use of fuzzy logic, we have been able to develop mechanisms that we feel may effectively improve current DAI systems, giving much more flexibility and providing the subsidies which a formal theory can bring. The appropriateness of the FDAI approach is explored in an important application, a fuzzy distributed traffic-light control system, where we have been able to aggregate and study several issues concerned with fuzzy and distributed artificial intelligence. We also present a number of current research directions necessary to develop the FDAI approach more fully.

Hardness and Electrical Resistivity of Copper-Iron Powder Metal Compacts

Although powder metallurgical methods have been used for years to fabricate tungsten and platinum, very little scientific data have been recorded until the beginning of this century. A large percentage of all commercial production at present is based upon past practice rather than upon scientific knowledge.

ASIC microcontroller design of a radiation monitoring system using VHDL modeling and FPGA implementation

Three new technologies have been brought together to develop a miniaturized radiation monitoring system. The research involved (1) Investigation a new HgI$\sb2$ detector. (2) VHDL modeling. (3) FPGA implementation. (4) In-circuit Verification. The packages used included an EG&G's crystal(HgI$\sb2$) manufactured at zero gravity, the Viewlogic's VHDL and Synthesis, Xilinx's technology library, its FPGA implementation tool, and a high density device (XC4003A). The results show: (1) Reduced cycle-time between Design and Hardware implementation; (2) Unlimited Re-design and implementation using the static RAM technology; (3) Customer based design, verification, and system construction; (4) Well suited for intelligent systems. These advantages excelled conventional chip design technologies and methods in easiness, short cycle time, and price in medium sized VLSI applications. It is also expected that the density of these devices will improve radically in the near future. ^

Ionized cluster beam deposition, and thin film analysis

In 1972 the ionized cluster beam (ICB) deposition technique was introduced as a new method for thin film deposition. At that time the use of clusters was postulated to be able to enhance film nucleation and adatom surface mobility, resulting in high quality films. Although a few researchers reported singly ionized clusters containing 10$\sp2$-10$\sp3$ atoms, others were unable to repeat their work. The consensus now is that film effects in the early investigations were due to self-ion bombardment rather than clusters. Subsequently in recent work (early 1992) synthesis of large clusters of zinc without the use of a carrier gas was demonstrated by Gspann and repeated in our laboratory. Clusters resulted from very significant changes in two source parameters. Crucible pressure was increased from the earlier 2 Torr to several thousand Torr and a converging-diverging nozzle 18 mm long and 0.4 mm in diameter at the throat was used in place of the 1 mm x 1 mm nozzle used in the early work. While this is practical for zinc and other high vapor pressure materials it remains impractical for many materials of industrial interest such as gold, silver, and aluminum. The work presented here describes results using gold and silver at pressures of around 1 and 50 Torr in order to study the effect of the pressure and nozzle shape. Significant numbers of large clusters were not detected. Deposited films were studied by atomic force microscopy (AFM) for roughness analysis, and X-ray diffraction.^ Nanometer size islands of zinc deposited on flat silicon substrates by ICB were also studied by atomic force microscopy and the number of atoms/cm$\sp2$ was calculated and compared to data from Rutherford backscattering spectrometry (RBS). To improve the agreement between data from AFM and RBS, convolution and deconvolution algorithms were implemented to study and simulate the interaction between tip and sample in atomic force microscopy. The deconvolution algorithm takes into account the physical volume occupied by the tip resulting in an image that is a more accurate representation of the surface.^ One method increasingly used to study the deposited films both during the growth process and following, is ellipsometry. Ellipsometry is a surface analytical technique used to determine the optical properties and thickness of thin films. In situ measurements can be made through the windows of a deposition chamber. A method for determining the optical properties of a film, that is sensitive only to the growing film and accommodates underlying interfacial layers, multiple unknown underlayers, and other unknown substrates was developed. This method is carried out by making an initial ellipsometry measurement well past the real interface and by defining a virtual interface in the vicinity of this measurement. ^

Extended principal component analysis and its applications to image analysis

The objectives of this research are to analyze and develop a modified Principal Component Analysis (PCA) and to develop a two-dimensional PCA with applications in image processing. PCA is a classical multivariate technique where its mathematical treatment is purely based on the eigensystem of positive-definite symmetric matrices. Its main function is to statistically transform a set of correlated variables to a new set of uncorrelated variables over $\IR\sp{n}$ by retaining most of the variations present in the original variables.^ The variances of the Principal Components (PCs) obtained from the modified PCA form a correlation matrix of the original variables. The decomposition of this correlation matrix into a diagonal matrix produces a set of orthonormal basis that can be used to linearly transform the given PCs. It is this linear transformation that reproduces the original variables. The two-dimensional PCA can be devised as a two successive of one-dimensional PCA. It can be shown that, for an $m\times n$ matrix, the PCs obtained from the two-dimensional PCA are the singular values of that matrix.^ In this research, several applications for image analysis based on PCA are developed, i.e., edge detection, feature extraction, and multi-resolution PCA decomposition and reconstruction. ^

Ionized cluster beam deposition: Modeling, cluster size measurement and applications

Clusters are aggregations of atoms or molecules, generally intermediate in size between individual atoms and aggregates that are large enough to be called bulk matter. Clusters can also be called nanoparticles, because their size is on the order of nanometers or tens of nanometers. A new field has begun to take shape called nanostructured materials which takes advantage of these atom clusters. The ultra-small size of building blocks leads to dramatically different properties and it is anticipated that such atomically engineered materials will be able to be tailored to perform as no previous material could.^ The idea of ionized cluster beam (ICB) thin film deposition technique was first proposed by Takagi in 1972. It was based upon using a supersonic jet source to produce, ionize and accelerate beams of atomic clusters onto substrates in a vacuum environment. Conditions for formation of cluster beams suitable for thin film deposition have only recently been established following twenty years of effort. Zinc clusters over 1,000 atoms in average size have been synthesized both in our lab and that of Gspann. More recently, other methods of synthesizing clusters and nanoparticles, using different types of cluster sources, have come under development.^ In this work, we studied different aspects of nanoparticle beams. The work includes refinement of a model of the cluster formation mechanism, development of a new real-time, in situ cluster size measurement method, and study of the use of ICB in the fabrication of semiconductor devices.^ The formation process of the vaporized-metal cluster beam was simulated and investigated using classical nucleation theory and one dimensional gas flow equations. Zinc cluster sizes predicted at the nozzle exit are in good quantitative agreement with experimental results in our laboratory.^ A novel in situ real-time mass, energy and velocity measurement apparatus has been designed, built and tested. This small size time-of-flight mass spectrometer is suitable to be used in our cluster deposition systems and does not suffer from problems related to other methods of cluster size measurement like: requirement for specialized ionizing lasers, inductive electrical or electromagnetic coupling, dependency on the assumption of homogeneous nucleation, limits on the size measurement and non real-time capability. Measured ion energies using the electrostatic energy analyzer are in good accordance with values obtained from computer simulation. The velocity (v) is measured by pulsing the cluster beam and measuring the time of delay between the pulse and analyzer output current. The mass of a particle is calculated from m = (2E/v$\sp2).$ The error in the measured value of background gas mass is on the order of 28% of the mass of one N$\sb2$ molecule which is negligible for the measurement of large size clusters. This resolution in cluster size measurement is very acceptable for our purposes.^ Selective area deposition onto conducting patterns overlying insulating substrates was demonstrated using intense, fully-ionized cluster beams. Parameters influencing the selectivity are ion energy, repelling voltage, the ratio of the conductor to insulator dimension, and substrate thickness. ^

Remote learning and laboratory center over Internet and ISDN

Recent advances in telecommunications technologies have transformed the modes of learning and teaching. One potentially vital component in the equation will be Remote Education or Remote Learning, the ability to compress time and space between teachers and students through the judicious application of technology. The purpose of this thesis is to develop a Remote Learning and Laboratory Center over the Internet and ISDN, which provide education and access to resources to those living in remote areas, children in hospitals and traveling families, with audio, video and data.^ Remote Learning and Laboratory Center (RLLC) is not restricted to merely traditional education processes such as universities or colleges, it can be very useful for companies to train their engineers, via networks. This capability will facilitate the best use of scarce, high quality educational resources and will bring equity of services to students as well as will be helpful to the Industries to train their engineers. The RLLC over the Internet and ISDN has been described in details and implemented successfully. For the Remote Laboratory, the experiment procedure has been demonstrated on reprogrammable CPLD design using ISR Kit. ^

Nonlinear dynamics and chaos simulation system analysis for improved design

Small errors proved catastrophic. Our purpose to remark that a very small cause which escapes our notice determined a considerable effect that we cannot fail to see, and then we say that the effect is due to chance. Small differences in the initial conditions produce very great ones in the final phenomena. A small error in the former will produce an enormous error in the latter. When dealing with any kind of electrical device specification, it is important to note that there exists a pair of test conditions that define a test: the forcing function and the limit. Forcing functions define the external operating constraints placed upon the device tested. The actual test defines how well the device responds to these constraints. Forcing inputs to threshold for example, represents the most difficult testing because this put those inputs as close as possible to the actual switching critical points and guarantees that the device will meet the Input-Output specifications. ^ Prediction becomes impossible by classical analytical analysis bounded by Newton and Euclides. We have found that non linear dynamics characteristics is the natural state of being in all circuits and devices. Opportunities exist for effective error detection in a nonlinear dynamics and chaos environment. ^ Nowadays there are a set of linear limits established around every aspect of a digital or analog circuits out of which devices are consider bad after failing the test. Deterministic chaos circuit is a fact not a possibility as it has been revived by our Ph.D. research. In practice for linear standard informational methodologies, this chaotic data product is usually undesirable and we are educated to be interested in obtaining a more regular stream of output data. ^ This Ph.D. research explored the possibilities of taking the foundation of a very well known simulation and modeling methodology, introducing nonlinear dynamics and chaos precepts, to produce a new error detector instrument able to put together streams of data scattered in space and time. Therefore, mastering deterministic chaos and changing the bad reputation of chaotic data as a potential risk for practical system status determination. ^