Call Admission Control Scheme for Arbitrary Traffic Distribution in CDMA Cellular Systems

Call Admission Control Scheme for Arbitrary Traffic Distribution in CDMA Cellular Systems

Date: September 2000
Creator: Akl, Robert G.; Hegde, Manju V.; Naraghi-Pour, Mort & Min, Paul S.
Description: This presentation discusses call admission control (CAC). The authors define a set of feasible call configurations that results in a CAC algorithm that captures the effect of having an arbitrary traffic distribution and whose complexity scales linearly with the number of cells.
Contributing Partner: UNT College of Engineering
CCAP: A Strategic Tool for Managing Capacity of CDMA Networks

CCAP: A Strategic Tool for Managing Capacity of CDMA Networks

Date: 1998
Creator: Akl, Robert G.
Description: This presentation discusses CCAP, a strategic tool for managing capacity of CDMA networks. CCAP is a graphical interactive tool for CDMA that calculates the coverage area, call capacity of a CDMA network, and subscriber network performance to optimize capacity.
Contributing Partner: UNT College of Engineering
Protein sequence classification using feature hashing

Protein sequence classification using feature hashing

Date: June 21, 2012
Creator: Caragea, Cornelia; Silvescu, Adrian & Mitra, Prasenjit
Description: Article discussing protein sequence classification using feature hashing.
Contributing Partner: UNT College of Engineering
Untangled: A scientific game to discover new mapping algorithms for domain-specific architectures

Untangled: A scientific game to discover new mapping algorithms for domain-specific architectures

Date: April 19, 2012
Creator: Rodgers, Brandon & Mehta, Gayatri
Description: This poster discusses untangled, a scientific game to discover new mapping algorithms for domain-specific architectures. This research has a broad impact on a wide range of next generation portable/wearable computing devices for health, multimedia, military, and aerospace purposes.
Contributing Partner: UNT Honors College
A Dual Dielectric Approach for Performance Aware Reduction of Gate Leakage in Combinational Circuits

A Dual Dielectric Approach for Performance Aware Reduction of Gate Leakage in Combinational Circuits

Date: May 2006
Creator: Mukherjee, Valmiki
Description: Design of systems in the low-end nanometer domain has introduced new dimensions in power consumption and dissipation in CMOS devices. With continued and aggressive scaling, using low thickness SiO2 for the transistor gates, gate leakage due to gate oxide direct tunneling current has emerged as the major component of leakage in the CMOS circuits. Therefore, providing a solution to the issue of gate oxide leakage has become one of the key concerns in achieving low power and high performance CMOS VLSI circuits. In this thesis, a new approach is proposed involving dual dielectric of dual thicknesses (DKDT) for the reducing both ON and OFF state gate leakage. It is claimed that the simultaneous utilization of SiON and SiO2 each with multiple thicknesses is a better approach for gate leakage reduction than the conventional usage of a single gate dielectric (SiO2), possibly with multiple thicknesses. An algorithm is developed for DKDT assignment that minimizes the overall leakage for a circuit without compromising with the performance. Extensive experiments were carried out on ISCAS'85 benchmarks using 45nm technology which showed that the proposed approach can reduce the leakage, as much as 98% (in an average 89.5%), without degrading the performance.
Contributing Partner: UNT Libraries
Tantra: A fast PRNG algorithm and its implementation

Tantra: A fast PRNG algorithm and its implementation

Date: June 2009
Creator: Gomathisankaran, Mahadevan & Lee, Ruby Bei-Loh
Description: This paper discusses Tantra. Tantra is a novel Pseudorandom number generator (PRNG) design that provides a long sequence high quality pseudorandom numbers at very high rate both in software and hardware implementations.
Contributing Partner: UNT College of Engineering
Temporal Connectionist Expert Systems Using a Temporal Backpropagation Algorithm

Temporal Connectionist Expert Systems Using a Temporal Backpropagation Algorithm

Date: December 1993
Creator: Civelek, Ferda N. (Ferda Nur)
Description: Representing time has been considered a general problem for artificial intelligence research for many years. More recently, the question of representing time has become increasingly important in representing human decision making process through connectionist expert systems. Because most human behaviors unfold over time, any attempt to represent expert performance, without considering its temporal nature, can often lead to incorrect results. A temporal feedforward neural network model that can be applied to a number of neural network application areas, including connectionist expert systems, has been introduced. The neural network model has a multi-layer structure, i.e. the number of layers is not limited. Also, the model has the flexibility of defining output nodes in any layer. This is especially important for connectionist expert system applications. A temporal backpropagation algorithm which supports the model has been developed. The model along with the temporal backpropagation algorithm makes it extremely practical to define any artificial neural network application. Also, an approach that can be followed to decrease the memory space used by weight matrix has been introduced. The algorithm was tested using a medical connectionist expert system to show how best we describe not only the disease but also the entire course of the disease. ...
Contributing Partner: UNT Libraries