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CDMA Network Design

CDMA Network Design

Date: May 2002
Creator: Akl, Robert G.
Description: This presentation gives an overview of code-division multiple access (CDMA) and inter-cell effects, network capacities, sensitivity analysis of base station locations, pilot-signal power, and transmission power of the mobiles, and concludes with numerical results.
Contributing Partner: UNT College of Engineering
Cell Design to Maximize Capacity in CDMA Networks

Cell Design to Maximize Capacity in CDMA Networks

Date: April 2002
Creator: Akl, Robert G.
Description: This presentation discusses the code division multiple access (CDMA) inter-cell effects, capacity regions, maximizing network capacity, mobility, a call admission control algorithm, and network performance.
Contributing Partner: UNT College of Engineering
Cell Placement in a CDMA Network

Cell Placement in a CDMA Network

Date: September 1999
Creator: Akl, Robert G.; Hegde, Manju V.; Naraghi-Pour, Mort & Min, Paul S.
Description: This presentation discusses research on cell placement in a CDMA network. In order to enable iterative cell placement the authors use a computationally efficient iterative process to calculate the inter-cell and intra-cell interferences as a function of pilot-signal power and base station location.
Contributing Partner: UNT College of Engineering
Channel Assignment and Load Distribution in a Power-Managed WLAN

Channel Assignment and Load Distribution in a Power-Managed WLAN

Date: 2007
Creator: Haidar, Mohamad; Akl, Robert G.; Al-Rizzo, Hussain Mudhaffar Younis, 1957- & Chan, Yupo
Description: This paper discusses a proposed algorithm.
Contributing Partner: UNT College of Engineering
Channel Assignment in an IEEE 802.11 WLAN Based on Signal-to-Interference Ratio

Channel Assignment in an IEEE 802.11 WLAN Based on Signal-to-Interference Ratio

Date: May 2008
Creator: Haidar, Mohamad; Ghimire, Rabindra; Al-Rizzo, Hussain Mudhaffar Younis, 1957-; Akl, Robert G. & Chan, Yupo
Description: This article discusses channel assignment in an IEEE 802.11 WLAN based on signal-to-interference ratio.
Contributing Partner: UNT College of Engineering
Characterizing Humour: An Exploration of Features in Humorous Texts

Characterizing Humour: An Exploration of Features in Humorous Texts

Date: February 2007
Creator: Mihalcea, Rada, 1974- & Pulman, Stephen
Description: This paper investigates the problem of automatic humor recognition, and provides an in-depth analysis of two of the most frequently observed features of humorous text: human-centeredness and negative polarity. Through experiments performed on two collections of humorous texts, the authors show that these properties of verbal humor are consisted across different data sets.
Contributing Partner: UNT College of Engineering
Classification of Attributes and Behavior in Risk Management Using Bayesian Networks

Classification of Attributes and Behavior in Risk Management Using Bayesian Networks

Date: March 2007
Creator: Dantu, Ram; Kolan, Prakash; Loper, Kall & Akl, Robert G.
Description: This paper discusses issues in security.
Contributing Partner: UNT College of Engineering
Classifier Stacking and Voting for Text Filtering

Classifier Stacking and Voting for Text Filtering

Date: November 2002
Creator: Mihalcea, Rada, 1974-
Description: This article discusses classifier stacking and voting for text filtering.
Contributing Partner: UNT College of Engineering
Classifying Drug Resistance in the NCI60 Cancer Cell Lines Based on the mRNA Expression Levels of the 48 ABC Transporters

Classifying Drug Resistance in the NCI60 Cancer Cell Lines Based on the mRNA Expression Levels of the 48 ABC Transporters

Date: March 2014
Creator: Alshammari, Sultanah M.; Urity, Vinoo & Azad, Rajeev K.
Description: Poster for the 2014 MCBIOS Conference. This poster discusses classifying drug resistance in the NCI60 cancer cell lines based on the mRNA expression levels of the 48 ABC transporters.
Contributing Partner: UNT College of Engineering
Classifying genes to the correct Gene Ontology Slim term in Saccharomyces cerevisiae using neighbouring genes with classification learning

Classifying genes to the correct Gene Ontology Slim term in Saccharomyces cerevisiae using neighbouring genes with classification learning

Date: May 28, 2010
Creator: Amthauer, Heather A. & Tsatsoulis, C. (Costas), 1962-
Description: This article discusses classifying genes to the correct Gene Ontology Slim term in Saccharomyces cerevisiae using neighbouring genes with classification learning. This provides insight into a gene's functionality in the eukaryotic genome.
Contributing Partner: UNT College of Engineering