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Agile, Steady Response of Inertial, Constrained Holonomic Robots Using Nonlinear, Anisotropic Dampening Forces
Get PDFIn this paper, the harmonic potential field (HPF) approach to motion planning is adapted to work with second order mechanical systems. The extension is based on a novel type of dampening forces called: nonlinear, anisotropic, dampening forces (NADFs). It is shown that NADFs are effective aids for planning spatially-constrained kinodynamic trajectories for mechanical systems. Theoretical developments and simulation results are provided in the pape
Infusing Critical Thinking Skill Compare and Contrast into Content of Data Structures Course
Get PDFThis paper describes some of our efforts in infusing the critical thinking skill of comparing and contrasting into a course on data structures. Comparing and contrasting is the process of looking at similarities and differences in order to reveal important characteristics of two objects, systems, organizations, events, processes or concepts. In comparing and contrasting two subjects, we 1- identify relevant factors for comparison, 2- discuss both similarities and differences between the two subjects with respect to each of these factors, 3- investigate if there are any patterns in the similarities and differences, and 4- make a conclusion based on this investigation. A skillful use of compare and contrast yields greater and deeper understanding of what is being taught. The conclusion drawn from compare and contrast can also help in designing a better system or process. Using a set of carefully chosen examples, we demonstrate that critical thinking skills can be naturally introduced in the course content of computer curricula at tertiary level. It is expected that infusion of critical thinking skills into course content and their explicit introduction stimulates students thinking and improves their learning ability
An Analytic Approach for Deploying Desktop Videoconferencing
Get PDFThe deployment of desktop videoconferencing, also known as Video and Voice over IP (VVoIP), over existing IP networks is gaining popularity these days. Such a deployment has become a major and challenging task for data network researchers and designers. This paper presents an analytic approach for deploying videoconferencing. The approach utilizes queueing network analysis and investigates two key performance bounds for videoconferencing: delay and bandwidth. The approach can be used to assess the support and readiness of an existing IP network. Prior to the purchase and deployment of desktop videoconferencing equipment, the approach predicts the number of videoconferencing sessions or calls that can be sustained by an existing network while satisfying QoS requirements of all network services and leaving adequate capacity for future growth. As a case study, we apply our approach to a typical network of a small enterprise. In addition, we use OPNET network simulator to verify and validate our analysis. Results obtained from analysis and simulation are in line and give a close match
"Particle Swarm Based Design of Variable Structure Stabilizer for a Nonlinear Model of SMIB System"
Get PDFIn this paper, a particle swarm-(PSO) based variable structure stabilizer (VSC) is proposed for enhancing the dynamic stability of a nonlinear model of synchronous machine infinite busbar system (SMIB). Unlike the methods reported in the literature which involve either linearizing the model of synchronous machine around a suitable operation point or applying nonlinear transformation techniques before linear control theory is used in designing a fixed parameter PSS, the present method formulates the design of VSC as an optimization problem and utilized the PSO algorithm to provide a simple and systematic way of arriving at the optimal feedback gains and switching vector values of the stabilizer. When compared to previous methods, simulation results showed the effectiveness of the proposed stabilizer design
"Design of Variable Structure Stabilizer for a Nonlinesr Mode of SMIB System: Particle Swarm Approach"
Get PDFIn this paper, a particle swarm-(PSO) based variable structure stabilizer (VSC) is proposed for enhancing the dynamic stability of a nonlinear model of synchronous machine infinite busbar system (SMIB). Unlike the methods reported in the literature which involve either linearizing the model of synchronous machine around a suitable operation point or applying nonlinear transformation techniques before linear control theory is used in designing a fixed parameter PSS, the present method formulates the design of VSC as an optimization problem and utilized the PSO algorithm to provide a simple and systematic way of arriving at the optimal feedback gains and switching vector values of the stabilizer. When compared to previous methods, simulation results showed the effectiveness of the proposed stabilizer design
Design and analysis of efficient and secure elliptic curve cryptoprocessors.
Get PDFElliptic Curve Cryptosystems have attracted many researchers and have been included in many standards such as IEEE, ANSI, NIST, SEC and WTLS. The ability to use smaller keys and computationally more efficient algorithms compared with earlier public key cryptosystems such as RSA and ElGamal are two main reasons why elliptic curve cryptosystems are becoming more popular. They are considered to be particularly suitable for implementation on smart cards or mobile devices. Power Analysis Attacks on such devices are considered serious threat due to the physical characteristics of these devices and their use in potentially hostile environments. This dissertation investigates elliptic curve cryptoprocessor architectures for curves defined over GF(2m) fields. In this dissertation, new architectures that are suitable for efficient computation of scalar multiplications with resistance against power analysis attacks are proposed and their performance evaluated. This is achieved by exploiting parallelism and randomized processing techniques. Parallelism and randomization are controlled at different levels to provide more efficiency and security. Furthermore, the proposed architectures are flexible enough to allow designers tailor performance and hardware requirements according to their performance and cost objectives. The proposed architectures have been modeled using VHDL and implemented on FPGA platform
Pathloss and Time Dispersion Parameters for Indoor UWB propagation
No full textThe propagation of ultra wideband (UWB) signals in indoor environments is an important issue with significant impacts on the future direction and scope of the UWB technology and its applications. The objective of this work is to obtain a better assessment of the potentials of UWB indoor communications by characterizing the UWB indoor communication channels. Channel characterization refers to extracting the channel parameters from measured data. An indoor UWB measurement campaign is undertaken. Time-domain indoor propagation measurements using pulses with less than 100 ps width are carried out. Typical indoor scenarios, including line-of-sight (LOS), non-line-of-sight (NLOS), room-to-room, within-the-room, and hallways, are considered. Results for indoor propagation measurements are presented for local power delay profiles (local PDP) and small-scale averaged power delay profiles (SSA-PDP). Site-specific trends and general observations are discussed. The results for path-loss exponent and time dispersion parameters are presented
An Efficient Iris Segmentation Technique based on a Multiscale Approach
Get PDFThe use of biometric signatures, instead of tokens such as identification cards or computer passwords, continues to gain increasing attention as an efficient means of identification and verification of individuals for controlling access to secured areas, materials, or systems and a wide variety of biometrics has been considered over the years in support of these challenges. Iris recognition is especially attractive due to the stability of the iris texture patterns with age and health conditions. Iris image segmentation and localisation is a key step in iris recognition and plays an essential role the accuracy of matching. In this paper, we propose a new iris segmentation technique using a multiscale approach for edge detection, which is a fundamental issue in image analysis. Due to the presence of speckles, which can be modelled as a a strong multiplicative noise, edge detection for iris segmentation is very important and methods developed so far are generally applied in one single scale. In our proposed method, we introduce the concept of multiscale edge detection to improve iris segmentation. The technique is effecient for edge detetcion, greatly reduces the search space for the Hough transform and at the same time is robust to noise thus improving the overall performance. Linear Hough transform has been used for eyelids isolation, and an adaptive thresholding has been used for isolating eyelashes. Once the iris is segmented, a normalization step has been carried out by converting an iris image from cartesien into polar coordinates which are more suitable to deal with rotation and translation problems. Extensive experiments have been carried out and results obtained have shown an effectiveness of the proposed method which provides a high segmentation success of 99.6%
Edge-Directed Invariant Shoeprint Image Retrieval
Get PDFIn this paper, we propose the use of image feature points for the classification of shoeprint images in a forensic setting. These feature points are quantified using wavelet maxima points extracted from a nonorthogonal wavelet decomposition of the shoeprint images. Wavelet transforms have been shown to be an effective analysis tool for image indexing, retrieval and characterization. This effectiveness is mainly attributed to the ability of the latter transforms to capture well the spatial information and visual features of the analyzed images using only few dominant subband coefficients. In this work, we propose the use of a nonorthogonal multiresolution representation to achieve shift-invariance. To reduce the content redundancy, we limit the feature space to wavelet maxima points. Such dimensionality reduction enables compact image representation while satisfying the requirements of the "information-preserving" rule. Based on the wavelet maxima representations, we suggest the use of a variance-weighted minimum distance measure as the similarity metric for image query, retrieval, and search purposes. As a result, each image is indexed by a vector in the wavelet maxima moment space. Finally, performance results are reported to illustrate the robustness of the extracted features in searching and retrieving of shoeprint images independently of position, size, orientation and image background
