Adel L. Ali

Image restoration based on the fast marching method and block based sampling

In this dissertation, a novel image restoration method is described, validated and compared with other available image restoration methods. The presented image restoration method combines the advantages of High Accuracy Fast Marching Method and non-parametric texture synthesis. The technique described from the method can handle both homogeneous and non-homogeneous natural images. The algorithm for the method can be elaborated in two sections. The first section of the algorithm is based on the High Accuracy Fast Marching Method to decide the filling order of the pixels in the target regions. The second section of the algorithm implicitly assumes a Markov random field model for textured image regions and blocks of texture are produced through an efficient searching process. The algorithm is easy to implement and requires only searching range of sample textures and a block size as user inputs. It restores the target regions with visually plausible quality equal to or better than those produced by previous techniques, with much less execution cost.

The undeterministic manipulation of solid models for robot program synthesis

Abstract In automatic robot program synthesis the number of variables that should be taken into consideration become prohibitively numerous. Due to the ambiguity and sheer size of items to be considered conventional computation methods cannot satisfactorily solve the problem. A Neural Network model that acquires data from a Solid Modeling data base, combines the completeness of information provided by solid modeling with the uncertainty encountered in the grouping process to perform geometrical classification of objects. The capabilities of Neural Networks to learn non-geometrical patterns in the grasping process, are yet to be achieved. Much progress needs to be made in both the neural model complexity and the computing machinery power before real intelligent program synthesis can be achieved.

Launching: university partnership for health informatics

The University Partnership for Health Informatics (UP-HI) is a private-public partnership between the University of Minnesota and the College of St. Scholastica that builds on 11 existing health information technology (HIT) certificates and degrees. It is a newly funded University-Based Training Program enabled by the ARRA HITECH Act. The overall goals and objectives of this partnership are to: 1) rapidly train students to serve in all six HIT professional roles identified by the Office of the National Coordinator for HIT requiring university-level training, including: a) Clinical/Public Health Leaders; b) Health Information Management/Exchange Specialists; c) Health Information Privacy/Security Specialists; d) Research and Development Specialists; e) Programmers/Software Engineers; and f) Health Information Technology Sub-Specialists; and 2) enhance existing HIT certificates and degrees with unique features, including: program access, communication, and asset management through a shared web portal; improved alignment of course content and assignments with role-specific competencies; enhanced online delivery of courses, and enhanced training/mentoring through work context immersion and a journal club. This paper reports on the innovative features of this newly-launched program.

Embedded Image Coding Using Zerotrees of Wavelet Coefficients for Visible Human Dataset

A lossless to lossy medical color image compression algorithm based on three-dimensional wavelet transform and zerotree coding (EZW) is presented. The algorithm (3D-CEZW) efficiently encodes color image volume by exploiting the dependencies in all three dimensions, decorrelating the original RGB color space to YCC color space, while enabling lossy and near lossless compression from the same bit stream and maintaining the fully embeddedness required by color image encoder. An application to visible human datasets shows that the 3D algorithm produces 3-5 dB higher PSNR than 2D algorithm. Compared to adaptive arithmetic coding, 3D-CEZW is superior in lossless compression which is desired for many medical applications

Neural net—fuzzy logic rules mapping for dynamic of fuzzy sets boundaries

Abstract Beauty, quality, performance, shape, or form are just a few characteristics that are hard to quantify. Expecting a computer to deal with such ambiguous properties is complicated since even humans sometimes have trouble agreeing on their meanings. L. A. Zadeh in 1965 at the University of California at Berkeley introduced the concept of “Fuzzy Sets”. It is not the intent of the author of this paper to evaluate Fuzzy Logic as a whole due to its broadness. Rather by analyzing a few characteristics about fuzzy logic considered weaknesses, the author wishes to provide information about current solutions as well as offer other innovations. It is well known that if a fuzzy system is tweaked optimally and assigned set values to the truths, then the system ceases to become fuzzy. In other words, the fuzzy system lacks adaptability. The possibility of using neural networks to adjust fuzzy logic sets is studied. The results are accomlished by comparing three different systems: one with fuzzy logic only, one with neural networks only, and finally one with a combination of fuzzy logic and neural networks. The basis of the problem on all three models involves balancing a weight on an inverted pendulum balance.

Application specific integrated circuit design on a PC platform

Application Specific Integrated Circuits (ASICs) are most commonly designed on high end computer platforms, such as the SUN workstation. This paper describes a cost-effective method of designing ASICs on PCS. With the rapidly increasing power of the PC, and the ease of communication through the Internet, today it is possible to run some of popular VLSI CAD packages at a much lower cost. Today, at the University of Southern Mississippi the software package MAGIC has been used for that purpose on PC based stations. This paper starts with an overview of ASIC design on PC platforms and its impact on industry and academia. The software and hardware requirements and the techniques needed to acquire VLSI capabilities on a PC are examined. This is followed by a comparison of the available VLSI software in the market and its suitability for the class environment.

A man-machine approach for robot grasp planning

Abstract Grasping is a key operation in manipulator programs since it affects all subsequent motions. The role of grasping in programming, however, is not limited only to defining the grip points, but should extend to include path planning to reach and leave these points from suitable approach and departure positions. The selection process is complicated and requires manipulation of many geometrical and functional constraints. In this paper we introduce an interactive system for grasp analysis. The main strategy in our design is to build a grasp analyzer that is based on man-machine interaction. In such system a CAD based geometric analyzer develops a list of candidate grips. The user can then override or change these grips according to functional constraints. Users modifications are still monitored by the system to avoid geometrical and interference violations. New concepts regarding functional constraints and geometrical were introduced. The system was implemented using a boundary representation solid modelers and it can be interfaced with a Graphical and/or Language Programming modules.

Community engagement and outreach as curricular and pedagogical tools for consortial delivery of health informatics curricula

The objective of this paper is to identify and characterise two grand challenges in the consortial delivery of health informatics curricula: (a) challenges of curriculum and pedagogy and (b) challenges of community engagement. We discovered that we could broadly depict the first challenge along four dimensions and the second challenge along six dimensions. Solutions to these challenges are provided along with a depiction of how the solutions have been successfully implemented in the University Partnership for Health Informatics, a university-based training programme funded by the Office of the National Coordinator for Health Information Technology.

An energy efficient framework using non-volatile flash memory for networked storage systems

In the past decade parallel disk systems have been highly scalable and able to alleviate the problem of disk I/O bottleneck, thereby being widely used to support a wide range of data- intensive applications. Optimizing energy consumption in parallel disk systems has strong impacts on the cost of backup power-generation and cooling equipment, because a significant fraction of the operation cost of data centres is due to energy consumption and cooling. Although a variety of parallel disk systems were developed to achieve high performance and energy efficiency, most existing parallel disk systems lack an adaptive way to conserve energy in dynamically changing workload conditions. To remedy this deficiency, we proposed an energy efficient framework. In the framework, we developed an adaptive energy conservation mechanism that makes use of the Dynamic Voltage Scaling Mechanism to conserve energy in parallel disk systems without sacrificing performance. The framework leverages the adaptor to dynamically choose the most appropriate voltage supplies for parallel disks while guaranteeing specified performance for example disk request’s desired response time. We conduct extensive experiments to quantitatively evaluate the performance of the proposed framework. To validate our framework, we developed an energy aware algorithm that integrates DVS with flash (DCAPS for short).

Employing mutual-exclusion algorithms for collaborative immersive visualization--CTHRU-C: a case study

CTHRU is a high performance visualization tool that is used to visualize temporal 3D datasets in an immersion environment. It was developed by Mississippi State University to visualize ocean models. This paper describes the design, development, and implementation of an enhanced version of CTHRU in order to add new collaborative capabilities. The CTHRU-C software package allows remote users to view and manipulate temporal datasets in real-time. Developing a multi-collaborative package with homogeneous software on both sides may run a risk of message duplication, which would lead to every message being repeatedly sent over the network and since, the options work in a toggled manner this would wreck havoc on the systems. To solve this problem a new mutual exclusion algorithms was developed. The paper also describes the network design scheme including propagation techniques. To implement a multi-user environment one master is needed that everyone would connect to. The paper also describes the network design scheme including propagation techniques. To implement a multi-user environment one mater is needed that everyone would connect to. The master would farm out all connections. This connection was implemented in CTHRU-C as a floating master. The software is designed around OpenGL, CAVERNsoft and CAVElibs to interface to the immersion environment. The tool was successfully tested on local machines at the Central of Higher Learning and Mississippi State University. The paper also addresses the guidelines that should \be taken into consideration while designing similar packages if one the design objectives is to add collaborative mode in the future.