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Knowledge-based expert system for selection and design of retaining structures
Title
Knowledge-based expert system for selection and design of retaining structures.
Creator
Sreenivasan, Giri., Florida Atlantic University, Arockiasamy, Madasamy, College of Engineering and Computer Science, Department of Ocean and Mechanical Engineering
Abstract/Description
This thesis describes the development of a microcomputer based prototype expert system, RETAININGEARTH, for the selection and design of earth retaining structures. RETAININGEARTH is an interactive menu-driven system and consists of two modules--the selection module, SELECTWALL and the design module. SELECTWALL is developed using the rule-based M.1 knowledge engineering shell and it makes a choice of the most appropriate retaining structure from a list of ten typical walls. The design module...
Show moreThis thesis describes the development of a microcomputer based prototype expert system, RETAININGEARTH, for the selection and design of earth retaining structures. RETAININGEARTH is an interactive menu-driven system and consists of two modules--the selection module, SELECTWALL and the design module. SELECTWALL is developed using the rule-based M.1 knowledge engineering shell and it makes a choice of the most appropriate retaining structure from a list of ten typical walls. The design module consists of five independent design programs which performs detailed designs of the concrete gravity and cantilever walls, gabions, reinforced earth and sheetpile structures. The SELECTWALL and the design module are linked by the M.1 external code EXT through a control program CALL. All the design procedures are coded using the C programming language.
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Date Issued
1991
PURL
http://purl.flvc.org/fcla/dt/14718
Subject Headings
Retaining walls--Data processing, Structural design--Computer programs, Expert systems (Computer science), Earthwork--Data processing
Format
Document (PDF)
Knowledge-based system for capacity rating of steel truss and skew bridges
Title
Knowledge-based system for capacity rating of steel truss and skew bridges.
Creator
Ponnuswamy, Sattanathan., Florida Atlantic University, Arockiasamy, Madasamy, College of Engineering and Computer Science, Department of Ocean and Mechanical Engineering
Abstract/Description
The Knowledge Based System CARAT is developed to rate any existing steel truss bridge. CARAT is capable of rating statically determinate and indeterminate truss bridges. Corrosion, temperature effects and the remaining fatigue life of the truss members can be evaluated using CARAT. The other expert system SKEWRAT is developed to determine the strength of skew bridges. Skew AASHTO girder and slab bridges can be analyzed using SKEWRAT. The architecture of both CARAT and SKEWRAT are based on...
Show moreThe Knowledge Based System CARAT is developed to rate any existing steel truss bridge. CARAT is capable of rating statically determinate and indeterminate truss bridges. Corrosion, temperature effects and the remaining fatigue life of the truss members can be evaluated using CARAT. The other expert system SKEWRAT is developed to determine the strength of skew bridges. Skew AASHTO girder and slab bridges can be analyzed using SKEWRAT. The architecture of both CARAT and SKEWRAT are based on production system model and set of IF-THEN rules are developed using EXSYS Professional Shell editor. The inference mechanism fire rules according to the built-in reasoning process. The suggestions given by Bakht and Jaeger (8) are incorporated to determine the strength characteristics of skewed AASHTO girder and slab bridges. Programming Languages FORTRAN and C are used extensively for the software development. The validity of both the softwares are verified and illustrated in detail with four examples.
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Date Issued
1996
PURL
http://purl.flvc.org/fcla/dt/15291
Subject Headings
Bridges, Truss--Evaluation--Computer programs, Bridges, Iron and steel--Evaluation--Computer programs, Bridges--Live loads--Evaluation--Computer programs, Expert systems (Computer science)
Format
Document (PDF)
Implementation of the IEEE 1609.2 WAVE Security Services Standard
Title
Implementation of the IEEE 1609.2 WAVE Security Services Standard.
Creator
Mandy, Chad Christopher Jr., Mahgoub, Imad, Florida Atlantic University, College of Engineering and Computer Science, Department of Computer and Electrical Engineering and Computer Science
Abstract/Description
This work presents the implementation of the the IEEE 1609.2 WAVE Security Services Standard. This implementation provides the ability to generate a message signature, along with the capability to verify that signature for wave short messages transmitted over an unsecured medium. Only the original sender of the message can sign it, allowing for the authentication of a message to be checked. As hashing is used during the generation and verification of signatures, message integrity can be...
Show moreThis work presents the implementation of the the IEEE 1609.2 WAVE Security Services Standard. This implementation provides the ability to generate a message signature, along with the capability to verify that signature for wave short messages transmitted over an unsecured medium. Only the original sender of the message can sign it, allowing for the authentication of a message to be checked. As hashing is used during the generation and verification of signatures, message integrity can be verified because a failed signature verification is a result of a compromised message. Also provided is the ability to encrypt and decrypt messages using AES-CCM to ensure that sensitive information remains safe and secure from unwanted recipients. Additionally this implementation provides a way for the 1609.2 specific data types to be encoded and decoded for ease of message transmittance. This implementation was built to support the Smart Drive initiative’s VANET testbed, supported by the National Science Foundation and is intended to run on the Vehicular Multi-technology Communication Device (VMCD) that is being developed. The VMCD runs on the embedded Linux operating system and this implementation will reside inside of the Linux kernel.
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Date Issued
2016
PURL
http://purl.flvc.org/fau/fd/FA00004693, http://purl.flvc.org/fau/fd/FA00004693
Subject Headings
Application software -- Security measures, Expert systems (Computer science), Vehicular ad hoc networks (Computer networks), Wireless LANs, Wireless communication systems -- Security measures, Wireless sensor networks
Format
Document (PDF)
Energy Efficient Cluster-Based Target Tracking Strategy
Title
Energy Efficient Cluster-Based Target Tracking Strategy.
Creator
AL-Ghanem, Waleed Khalid, Mahgoub, Imad, Florida Atlantic University
Abstract/Description
This research proposes a cluster-based target tracking strategy for one moving object using wireless sensor networks. The sensor field is organized in 3 hierarchal levels. 1-bit message is sent when a node detects the target. Otherwise the node stays silent. Since in wireless sensor network nodes have limited computational resources, limited storage resources, and limited battery, the code for predicting the target position should be simple, and fast to execute. The algorithm proposed in this...
Show moreThis research proposes a cluster-based target tracking strategy for one moving object using wireless sensor networks. The sensor field is organized in 3 hierarchal levels. 1-bit message is sent when a node detects the target. Otherwise the node stays silent. Since in wireless sensor network nodes have limited computational resources, limited storage resources, and limited battery, the code for predicting the target position should be simple, and fast to execute. The algorithm proposed in this research is simple, fast, and utilizes all available detection data for estimating the location of the target while conserving energy. lbis has the potential of increasing the network life time. A simulation program is developed to study the impact of the field size and density on the overall performance of the strategy. Simulation results show that the strategy saves energy while estimating the location of the target with an acceptable error margin.
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Date Issued
2008
PURL
http://purl.flvc.org/fau/fd/FA00012501
Subject Headings
Wireless communication systems--Technological innovations, Sensor networks--Security measures, High performance computing, Adaptive signal processing, Target acquisition, Expert systems (Computer science)
Format
Document (PDF)
Predictive modeling for wellness
Title
Predictive modeling for wellness.
Creator
Pulumati, Pranitha, Agarwal, Ankur, Florida Atlantic University, College of Engineering and Computer Science, Department of Computer and Electrical Engineering and Computer Science
Abstract/Description
Wellness and healthy life are the most common concerns for an individual to lead a happy life. A web-based approach known as Wellness Scoring is being developed taking into people’s concerns for their health issues. In this approach, four different classifiers are being investigated to predict the wellness. In this thesis, we investigated four different classifiers (a probabilistic graphical model, simple probabilistic classifier, probabilistic statistical classification and an artificial...
Show moreWellness and healthy life are the most common concerns for an individual to lead a happy life. A web-based approach known as Wellness Scoring is being developed taking into people’s concerns for their health issues. In this approach, four different classifiers are being investigated to predict the wellness. In this thesis, we investigated four different classifiers (a probabilistic graphical model, simple probabilistic classifier, probabilistic statistical classification and an artificial neural network) to predict the wellness outcome. An approach to calculate wellness score is also addressed. All these classifiers are trained on real data, hence giving more accurate results. With this solution, there is a better way of keeping track of an individuals’ health. In this thesis, we present the design and development of such a system and evaluate the performance of the classifiers and design considerations to maximize the end user experience with the application. A user experience model capable of predicting the wellness score for a given set of risk factors is developed.
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Date Issued
2014
PURL
http://purl.flvc.org/fau/fd/FA00004321, http://purl.flvc.org/fau/fd/FA00004321
Subject Headings
Bayesian statistical decision theory, Expert systems (Computer science), Health risk assessment, Medicine, Preventive, Patient self monitoring, Self care, Health, Well being
Format
Document (PDF)

Pages