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- Title
- Effects of Adaptive Antenna Array Beamforming and Power Management with Antenna Element Selection.
- Creator
- Abazari Aghdam, Sajjad, Bagby, Jonathan S., Florida Atlantic University, College of Engineering and Computer Science, Department of Computer and Electrical Engineering and Computer Science
- Abstract/Description
-
This research is the array processing help wireless communication techniques to increase the signal accuracy. This technique has an important part of prevalent applications. The wireless communication system, radar, and sonar. Beamforming is one of methods in array processing that filters signals based on their capture time at each element in an array of antennas spatially. Numerous studies in adaptive array processing have been proposed in the last several decades, which are divided in two...
Show moreThis research is the array processing help wireless communication techniques to increase the signal accuracy. This technique has an important part of prevalent applications. The wireless communication system, radar, and sonar. Beamforming is one of methods in array processing that filters signals based on their capture time at each element in an array of antennas spatially. Numerous studies in adaptive array processing have been proposed in the last several decades, which are divided in two parts. The first one related to non-adaptive beamforming techniques and the next one related to digitally adaptive Beamforming methods. The trade-off between computational complexity and performance make them different. In this thesis, we concentrate on the expansion of array processing algorithms in both non-adaptive and adaptive ones with application of beamforming in 4G mobile antenna and radar systems. The conventional and generalized side-lobe canceller (GSC) structures beamforming algorithms were employed with a phase array antenna that changed the phase of arrivals in array antenna with common phased array structure antennas. An eight-element uniform linear array (ULA), consisting of di-pole antennas, represented as the antenna array. An anechoic chamber measures the operation of beamforming algorithms performance. An extended modified Kaiser weighting function is proposed to make a semi-adaptive structure in phased array beamforming. This technique is extended to low complexity functions like hyperbolic cosine and exponential functions. Furthermore, these algorithms are used in GSC beamforming. The side-lobe levels were so lower than other algorithms in conventional beamforming around -10 dB. On the other hand, a uniform linear arrays for smart antenna purposes designed to utilize in implementing and testing the proposed algorithms. In this thesis, performance of smart antenna with rectangular aperture coupled microstrip linear array which experimental investigations carried out for obtaining X-band operation of rectangular microstrip antenna by using aperture coupled feeding technique. Frequency range set at approximately 8.6 to 10.9 GHz, by incorporating frequency range of the antenna resonates for single wideband with an impedance bandwidth of 23%. The enhancement of impedance bandwidth and gain does not affect the nature of broadside radiation characteristics. This thesis describes the design, operation, and realization of the beamforming such as Sidelobe level (SLL) control and null forming array antenna are examined with the prototype. An antenna radiation pattern beam maximum can be simultaneously placed towards the intended user or Signal of interest (SOl), and, ideally nulls can be positioned towards directions of interfering signals or signals not of interest (SNOIs). Finally, we focused on the adaptive digitally algorithms in compact antenna that faces with mutual coupling. The variable step-size normalized lease mean square (VS-NLMS) algorithm is implemented in beamforming. This algorithm utilizes continuous adaptation. The weights are attuned that the final weight vector to the most satisfied result. The gradient vector can be achieved by iterative beamforming algorithm from the available data. This algorithm is compared with LMS, NLMS, VSS-NLMS algorithms, it is determined that the VSS-NLMS algorithm is better performance to other algorithms. Finally, we introduced novel adaptive IP-NNLMS beamformer. This beamformer reaches to faster convergence and lower error floor than the previous adaptive beamformers even at low SNRs in presence of mutual coupling. The experimental results verified the simulation results that the proposed technique has better performance than other algorithms in various situations.
Show less - Date Issued
- 2016
- PURL
- http://purl.flvc.org/fau/fd/FA00004789, http://purl.flvc.org/fau/fd/FA00004789
- Subject Headings
- Global system for mobile communications., Long-Term Evolution (Telecommunications), Wireless communication systems., Antennas (Electronics), Antenna arrays., Array processors., Time-domain analysis.
- Format
- Document (PDF)
- Title
- Low latency and energy efficient MAC protocols for wireless sensor networks.
- Creator
- Abu-El Humos, Ali M., Florida Atlantic University, Alhalabi, Bassem A., Cardei, Mihaela, College of Engineering and Computer Science, Department of Computer and Electrical Engineering and Computer Science
- Abstract/Description
-
Energy consumption is a critical design issue in Wireless Sensor Networks (WSNs), since sensor nodes are battery operated, and replacing or recharging the battery is usually infeasible. Energy efficient solutions are sought at all network levels, especially at the medium access level. The IEEE 802.11 MAC protocol is optimized for Ad hoc Wireless Networks, but cannot be adopted for WSNs because it has the idle listening problem, which is a major source of energy waste. Several Medium Access...
Show moreEnergy consumption is a critical design issue in Wireless Sensor Networks (WSNs), since sensor nodes are battery operated, and replacing or recharging the battery is usually infeasible. Energy efficient solutions are sought at all network levels, especially at the medium access level. The IEEE 802.11 MAC protocol is optimized for Ad hoc Wireless Networks, but cannot be adopted for WSNs because it has the idle listening problem, which is a major source of energy waste. Several Medium Access Control (MAC) protocols have been proposed for WSNs to save the transceiver energy by introducing periodic listen/sleep cycles, and thus overcome the idle listing problem. The periodic listen sleep cycles, however, will increase the network latency and require extra overhead to establish and maintain synchronization among nodes in the network. This dissertation introduces a new MAC protocol for WSNs based on the SMAC protocol to improve its latency performance without compromising its energy consumption. The original SMAC provides an efficient solution for the energy consumption problem due to idle listening, but it increases latency especially in low duty cycle applications. TMAC was proposed to further reduce the energy consumption in SMAC and introduced the Forward Request-To-Send (FRTS) packet to solve the early sleep problem observed in TMAC. Later, Adaptive SMAC was proposed to reduce the latency problem in SMAC by at least 50% at light traffic load. Our new protocol, FASMAC, combines the advantages of both adaptive listening and the usage of FRTS packet in TMAC to further reduce the latency of SMAC. In FASMAC, a packet can travel at least three hops away from its source node within one time cycle. This results in at least 67% reduction in latency at light traffic when compared with the original SMAC. We also propose an energy model for performance evaluation of WSNs protocols using the network simulator NS2. The current energy model of NS2 was designed to handle Ad hoc Wireless Networks where the low power consumption sleep mode was not an issue. However, this is not the case in WSNs. We show that NS2 energy model is not suitable to evaluate the performance of WSNs protocols because it does not account for the low power sleep mode. This dissertation proposes a solution to this deficiency and provides simulation results that match real experimental results performed on the actual sensor motes.
Show less - Date Issued
- 2005
- PURL
- http://purl.flvc.org/fcla/dt/12149
- Subject Headings
- Wireless communication systems, Sensor networks, Power resources--Efficiency
- Format
- Document (PDF)
- Title
- Studies on nonlinear activity and cross-entropy considerations in neural networks.
- Creator
- Abusalah, Salahalddin Tawfiq., Florida Atlantic University, Neelakanta, Perambur S., College of Engineering and Computer Science, Department of Computer and Electrical Engineering and Computer Science
- Abstract/Description
-
The objectives of this research as deliberated in this dissertation are two-folded: (i) To study the nonlinear activity in the neural complex (real and artificial) and (ii) to analyze the learning processe(s) pertinent to an artificial neural network in the information-theoretic plane using cross-entropy error-metrics. The research efforts envisaged enclave the following specific tasks: (i) Obtaining a general solution for the Bernoulli-Riccati equation to represent a single parameter family...
Show moreThe objectives of this research as deliberated in this dissertation are two-folded: (i) To study the nonlinear activity in the neural complex (real and artificial) and (ii) to analyze the learning processe(s) pertinent to an artificial neural network in the information-theoretic plane using cross-entropy error-metrics. The research efforts envisaged enclave the following specific tasks: (i) Obtaining a general solution for the Bernoulli-Riccati equation to represent a single parameter family of S-shaped (sigmoidal) curves depicting the nonlinear activity in the neural network. (ii) Analysis of the logistic growth of output versus input values in the neural complex (real and artificial) under the consideration that the boundaries of the sets constituting the input and output entities are crisp and/or fuzzy. (iii) Construction of a set of cross-entropy error-metrics (known as Csiszar's measures) deduced in terms of the parameters pertinent to a perceptron topology and elucidation of their relative effectiveness in training the network optimally towards convergence. (iv) Presenting the methods of symmetrizing and balancing the aforesaid error-entropy measures (in the information-theoretic plane) so as to make them usable as error-metrics in the test domain. (v) Description and analysis of the dynamics of neural learning process in the information-theoretic plane for both crisp and fuzzy attributes of input values. Relevant to these topics portraying the studies on nonlinear activity and cross-entropy considerations vis-a-vis neural networks, newer and/or exploratory inferences are made, logical conclusions are enumerated and relative discussions are presented along with the scope for future research to be pursued.
Show less - Date Issued
- 1996
- PURL
- http://purl.flvc.org/fcla/dt/12447
- Subject Headings
- Neural networks (Computer science), Entropy (Information theory), Nonlinear control theory
- Format
- Document (PDF)
- Title
- Performance Analysis of Spectrum Sensing Schemes Based on Fractional Lower Order Moments for Cognitive Radios in Alpha- Stable Noise Environments.
- Creator
- Ackie, A-Bon Elfick, Aalo, Valentine A., Florida Atlantic University, College of Engineering and Computer Science, Department of Computer and Electrical Engineering and Computer Science
- Abstract/Description
-
Natural and manmade noise signals tend to exhibit impulsive behaviors. Therefore modeling those signals as α-stable processes is better suited towards the development of a practical spectrum sensing scheme. However, the performances of detectors operating in an α-stable noise environment are difficult to evaluate. This is because an α-stable random variable can usually only be modeled by the characteristic function since closed-form expressions are usually not available except for the special...
Show moreNatural and manmade noise signals tend to exhibit impulsive behaviors. Therefore modeling those signals as α-stable processes is better suited towards the development of a practical spectrum sensing scheme. However, the performances of detectors operating in an α-stable noise environment are difficult to evaluate. This is because an α-stable random variable can usually only be modeled by the characteristic function since closed-form expressions are usually not available except for the special values of the characteristic exponent that correspond to the Cauchy and Gaussian noise distributions. In this thesis, we derive a general closed-form expression for the probability density function (PDF) of symmetric alpha stable processes having rational characteristic exponent (0<α≤2). Consequently, we obtain analytical expressions for the PDF and corresponding complementary cumulative distribution function (CCDF) of the proposed fractional lower order moment (FLOM) detector. Utilizing false alarm and detection probabilities, the performance analysis of the proposed spectrum sensing scheme is conducted with the assumption that the cognitive radio (CR) users are operating in non-fading channels. We validate the analytical results with Monte Carlo simulations. The effect of the distribution parameters on the receiver operating characteristic (ROC) curves is verified.
Show less - Date Issued
- 2016
- PURL
- http://purl.flvc.org/fau/fd/FA00004561, http://purl.flvc.org/fau/fd/FA00004561
- Subject Headings
- Cognitive radio networks., Radio frequency allocation., Radio resource management (Wireless communications), Wireless communication systems.
- Format
- Document (PDF)
- Title
- Perceptual methods for video coding.
- Creator
- Adzic, Velibor, Kalva, Hari, Florida Atlantic University, College of Engineering and Computer Science, Department of Computer and Electrical Engineering and Computer Science
- Abstract/Description
-
The main goal of video coding algorithms is to achieve high compression efficiency while maintaining quality of the compressed signal at the highest level. Human visual system is the ultimate receiver of compressed signal and final judge of its quality. This dissertation presents work towards optimal video compression algorithm that is based on the characteristics of our visual system. Modeling phenomena such as backward temporal masking and motion masking we developed algorithms that are...
Show moreThe main goal of video coding algorithms is to achieve high compression efficiency while maintaining quality of the compressed signal at the highest level. Human visual system is the ultimate receiver of compressed signal and final judge of its quality. This dissertation presents work towards optimal video compression algorithm that is based on the characteristics of our visual system. Modeling phenomena such as backward temporal masking and motion masking we developed algorithms that are implemented in the state-of- the-art video encoders. Result of using our algorithms is visually lossless compression with improved efficiency, as verified by standard subjective quality and psychophysical tests. Savings in bitrate compared to the High Efficiency Video Coding / H.265 reference implementation are up to 45%.
Show less - Date Issued
- 2014
- PURL
- http://purl.flvc.org/fau/fd/FA00004074, http://purl.flvc.org/fau/fd/FA00004074
- Subject Headings
- Algorithms, Coding theory, Digital coding -- Data processing, Imaging systems -- Image quality, Perception, Video processing -- Data processing
- Format
- Document (PDF)
- Title
- QoS Driven Communication Backbone for NOC Based Embedded Systems.
- Creator
- Agarwal, Ankur, Shankar, Ravi, Florida Atlantic University, College of Engineering and Computer Science, Department of Computer and Electrical Engineering and Computer Science
- Abstract/Description
-
With the increasing complexity of the system design, it has become very critical to enhance system design productivity to meet with the time-to-market demands. Real Time embedded system designers are facing extreme challenges in underlying architectural design selection. It involves the selection of a programmable, concurrent, heterogeneous multiprocessor architecture platform. Such a multiprocessor system on chip (MPSoC) platform has set new innovative trends for the real-time systems and...
Show moreWith the increasing complexity of the system design, it has become very critical to enhance system design productivity to meet with the time-to-market demands. Real Time embedded system designers are facing extreme challenges in underlying architectural design selection. It involves the selection of a programmable, concurrent, heterogeneous multiprocessor architecture platform. Such a multiprocessor system on chip (MPSoC) platform has set new innovative trends for the real-time systems and system on Chip (SoC) designers. The consequences of this trend imply the shift in concern from computation and sequential algorithms to modeling concurrency, synchronization and communication in every aspect of hardware and software co-design and development. Some of the main problems in the current deep sub-micron technologies characterized by gate lengths in the range of 60-90 nm arise from non scalable wire delays, errors in signal integrity and un-synchronized communication. These problems have been addressed by the use of packet switched Network on Chip (NOC) architecture for future SoCs and thus, real-time systems. Such a NOC based system should be able to support different levels of quality of service (QoS) to meet the real time systems requirements. It will further help in enhancing the system productivity by providing a reusable communication backbone. Thus, it becomes extremely critical to properly design a communication backbone (CommB) for NOC. Along with offering different levels of QoS, CommB is responsible directing the flow of data from one node to another node through routers, allocators, switches, queues and links. In this dissertation I present a reusable component based, design of CommB, suitable for embedded applications, which supports three types of QoS (real-time, multi-media and control applications).
Show less - Date Issued
- 2006
- PURL
- http://purl.flvc.org/fau/fd/FA00012566
- Subject Headings
- Computer networks--Quality control, Data transmission systems, Embedded computer systems--Quality control, Interconnects (Integrated circuit technology)
- Format
- Document (PDF)
- Title
- A VLSI implementable handwritten digit recognition system using artificial neural networks.
- Creator
- Agba, Lawrence C., Florida Atlantic University, Shankar, Ravi, College of Engineering and Computer Science, Department of Computer and Electrical Engineering and Computer Science
- Abstract/Description
-
A VLSI implementable feature extraction scheme, and two VLSI implementable algorithms for feature classification that should lead to a practical handwritten digit recognition system are proposed. The feature extraction algorithm exploits the concept of holon dynamics. Holons can be regarded as a group of cooperative processors with self-organizing property. Two types of artificial neural network-based classifiers have been evolved to classify these features. The United States Post Office...
Show moreA VLSI implementable feature extraction scheme, and two VLSI implementable algorithms for feature classification that should lead to a practical handwritten digit recognition system are proposed. The feature extraction algorithm exploits the concept of holon dynamics. Holons can be regarded as a group of cooperative processors with self-organizing property. Two types of artificial neural network-based classifiers have been evolved to classify these features. The United States Post Office handwritten digit database was used to train and test these networks. The first type of classifier system used limited interconnect multi-layer perceptron (LIMP) modules in a hierarchical configuration. Each classifier in this system was independently trained and designated to recognize a particular digit. A maximum of sixty-one digits were used to train and 464 digits which included the training set were used to test the classifiers. A cumulative performance of 93.75% (correctly recognized digits) was recorded. The second classifier system consists of a cluster of small multi-layer perceptron (CLUMP) networks. Each cell in this system was independently trained to trace the boundary between two or more digits in the recognition plane. A combination of these cells distinguish a digit from the rest. This system was trained with 1796 digits and tested on 1918 different set of digits. On the training set a performance of 95.55% was recorded while 79.35% resulted from the test data. These results, which are expected to further improve, are superior to those obtained by other researchers on the same database. This technique of digit recognition is general enough for application in the development of a universal alphanumeric recognition system. A hybrid VLSI system consisting of both analog and digital circuitry, and utilizing both Bi-CMOS and switched capacitor technologies has been designed. The design is intended for implementation with the current MOSIS 2 $\mu$m, double poly, double metal, and p-well CMOS technology. The integrated circuit is such that both classifier systems can be realized using the same chip.
Show less - Date Issued
- 1990
- PURL
- http://purl.flvc.org/fcla/dt/12260
- Subject Headings
- Optical character recognition devices--Computer simulation, Pattern recognition systems--Computer simulation
- Format
- Document (PDF)
- Title
- Low Cost Robotic Car as a Way to Teach Mathematics.
- Creator
- Aguerrevere, Santiago Andres, Shankar, Ravi, Florida Atlantic University, College of Engineering and Computer Science, Department of Computer and Electrical Engineering and Computer Science
- Abstract/Description
-
This report describes the development of a low cost open source semiautonomous robotic car and a way to communicate with it. It is a continuation of prior research done by other students at FAU and published in recent ASEE conferences. The objective of this project was the development of a new robotic platform with improved precision over the original, while still keeping the cost down. It was developed with the aim to allow a hands-on approach to the teaching of mathematics topics that are...
Show moreThis report describes the development of a low cost open source semiautonomous robotic car and a way to communicate with it. It is a continuation of prior research done by other students at FAU and published in recent ASEE conferences. The objective of this project was the development of a new robotic platform with improved precision over the original, while still keeping the cost down. It was developed with the aim to allow a hands-on approach to the teaching of mathematics topics that are taught in the K-12 syllabus. Improved robustness and reliability of the robotic platform for visually solving math problems was achieved using a combination of PID loops to keep track of distance and rotation. The precision was increased by changing the position of the encoders to the shafts of each motor. A mobile application was developed to allow the student to draw the geometric shapes on the screen before the car draws them. The mobile application consists of two parts, the canvas that the user uses to draw the figure and the configure section that lets the user change the parameters of the controller. Results show that the robot can draw standard geometric and complex geometric shapes. It has high precision and sufficient accuracy, the accuracy can be improved with some mechanical adjustments. During testing a Pythagorean triangle was drawn to show visually the key mathematics concept. The eventual goal of this project will be a K-12 class room study to obtain the feedback of the teachers and students on the feasibility of using a robotic car to teach math. Subsequent to that necessary changes will be made to manufacture a unit that is easy to assemble by the teacher.
Show less - Date Issued
- 2016
- PURL
- http://purl.flvc.org/fau/fd/FA00004712, http://purl.flvc.org/fau/fd/FA00004712
- Subject Headings
- Adaptive control systems, Applied mathematics, Artificial intelligence, Computers, Special purpose, Mathematics -- Study and teaching, User interfaces (Computer systems)
- Format
- Document (PDF)
- Title
- Patterns for web services standards.
- Creator
- Ajaj, Ola, College of Engineering and Computer Science, Department of Computer and Electrical Engineering and Computer Science
- Abstract/Description
-
Web services intend to provide an application integration technology that can be successfully used over the Internet in a secure, interoperable and trusted manner. Policies are high-level guidelines defining the way an institution conducts its activities. The WS-Policy standard describes how to apply policies of security definition, enforcement of access control, authentication and logging. WS-Trust defines a security token service and a trust engine which are used by web services to...
Show moreWeb services intend to provide an application integration technology that can be successfully used over the Internet in a secure, interoperable and trusted manner. Policies are high-level guidelines defining the way an institution conducts its activities. The WS-Policy standard describes how to apply policies of security definition, enforcement of access control, authentication and logging. WS-Trust defines a security token service and a trust engine which are used by web services to authenticate other web services. Using the functions defined in WS-Trust, applications can engage in secure communication after establishing trust. BPEL is a language for web service composition that intends to provide convenient and effective means for application integration over the Internet. We address security considerations in BPEL and how to enforce them, as well as its interactions with other web services standards such as WS-Security and WS-Policy.
Show less - Date Issued
- 2010
- PURL
- http://purl.flvc.org/FAU/1927300
- Subject Headings
- Computational grids (Computer systems), Computer systems, Verification, Expert systems (Computer science), Computer network architectures, Web servers, Management, Electronic commerce, Computer programs
- Format
- Document (PDF)
- Title
- Modeling and analysis of security.
- Creator
- Ajaj, Ola, Fernandez, Eduardo B., College of Engineering and Computer Science, Department of Computer and Electrical Engineering and Computer Science
- Abstract/Description
-
Cloud Computing is a new computing model consists of a large pool of hardware and software resources on remote datacenters that are accessed through the Internet. Cloud Computing faces significant obstacles to its acceptance, such as security, virtualization, and lack of standardization. For Cloud standards, there is a long debate about their role, and more demands for Cloud standards are put on the table. The Cloud standardization landscape is so ambiguous. To model and analyze security...
Show moreCloud Computing is a new computing model consists of a large pool of hardware and software resources on remote datacenters that are accessed through the Internet. Cloud Computing faces significant obstacles to its acceptance, such as security, virtualization, and lack of standardization. For Cloud standards, there is a long debate about their role, and more demands for Cloud standards are put on the table. The Cloud standardization landscape is so ambiguous. To model and analyze security standards for Cloud Computing and web services, we have surveyed Cloud standards focusing more on the standards for security, and we classified them by groups of interests. Cloud Computing leverages a number of technologies such as: Web 2.0, virtualization, and Service Oriented Architecture (SOA). SOA uses web services to facilitate the creation of SOA systems by adopting different technologies despite their differences in formats and protocols. Several committees such as W3C and OASIS are developing standards for web services; their standards are rather complex and verbose. We have expressed web services security standards as patterns to make it easy for designers and users to understand their key points. We have written two patterns for two web services standards; WS-Secure Conversation, and WS-Federation. This completed an earlier work we have done on web services standards. We showed relationships between web services security standards and used them to solve major Cloud security issues, such as, authorization and access control, trust, and identity management. Close to web services, we investigated Business Process Execution Language (BPEL), and we addressed security considerations in BPEL and how to enforce them. To see how Cloud vendors look at web services standards, we took Amazon Web Services (AWS) as a case-study. By reviewing AWS documentations, web services security standards are barely mentioned. We highlighted some areas where web services security standards could solve some AWS limitations, and improve AWS security process. Finally, we studied the security guidance of two major Cloud-developing organizations, CSA and NIST. Both missed the quality of attributes offered by web services security standards. We expanded their work and added benefits of adopting web services security standards in securing the Cloud.
Show less - Date Issued
- 2013
- PURL
- http://purl.flvc.org/fau/fd/FA0004001
- Subject Headings
- Cloud Computing, Computational grids (Computer systems), Computer network architectures, Expert systems (Computer science), Web services -- Management
- Format
- Document (PDF)
- Title
- Cloud-based Skin Lesion Diagnosis System using Convolutional Neural Networks.
- Creator
- Akar, Esad, Furht, Borko, Florida Atlantic University, College of Engineering and Computer Science, Department of Computer and Electrical Engineering and Computer Science
- Abstract/Description
-
Skin cancer is a major medical problem. If not detected early enough, skin cancer like melanoma can turn fatal. As a result, early detection of skin cancer, like other types of cancer, is key for survival. In recent times, deep learning methods have been explored to create improved skin lesion diagnosis tools. In some cases, the accuracy of these methods has reached dermatologist level of accuracy. For this thesis, a full-fledged cloud-based diagnosis system powered by convolutional neural...
Show moreSkin cancer is a major medical problem. If not detected early enough, skin cancer like melanoma can turn fatal. As a result, early detection of skin cancer, like other types of cancer, is key for survival. In recent times, deep learning methods have been explored to create improved skin lesion diagnosis tools. In some cases, the accuracy of these methods has reached dermatologist level of accuracy. For this thesis, a full-fledged cloud-based diagnosis system powered by convolutional neural networks (CNNs) with near dermatologist level accuracy has been designed and implemented in part to increase early detection of skin cancer. A large range of client devices can connect to the system to upload digital lesion images and request diagnosis results from the diagnosis pipeline. The diagnosis is handled by a two-stage CNN pipeline hosted on a server where a preliminary CNN performs quality check on user requests, and a diagnosis CNN that outputs lesion predictions.
Show less - Date Issued
- 2018
- PURL
- http://purl.flvc.org/fau/fd/FA00013150
- Subject Headings
- Skin Diseases--diagnosis, Skin--Cancer--Diagnosis, Diagnosis--Methodology, Neural networks, Cloud computing
- Format
- Document (PDF)
- Title
- Adaptive hierarchical weighted fair queuing scheduling in WiMAX networks.
- Creator
- AL-Ghanem, Waleed Khalid, Ilyas, Mohammad, Mahgoub, Imad, Florida Atlantic University, College of Engineering and Computer Science, Department of Computer and Electrical Engineering and Computer Science
- Abstract/Description
-
The growing demand for faster connection to the Internet service and wireless multimedia applications has motivated the development of broadband wireless access technologies in recent years. WiMAX has enabled convergence of mobile and fixed broadband networks through a common wide-area radio-access technology and flexible network architecture. Scheduling is a fundamental component in resource management in WiMAX networks and plays the main role in meeting QoS requirements such as delay,...
Show moreThe growing demand for faster connection to the Internet service and wireless multimedia applications has motivated the development of broadband wireless access technologies in recent years. WiMAX has enabled convergence of mobile and fixed broadband networks through a common wide-area radio-access technology and flexible network architecture. Scheduling is a fundamental component in resource management in WiMAX networks and plays the main role in meeting QoS requirements such as delay, throughput and packet loss for different classes of service. In this dissertation work, the performance of uplink schedulers at the fixed WiMAX MAC layer has been considered, we proposed an Adaptive Hierarchical Weighted Fair Queuing Scheduling algorithm, the new scheduling algorithm adapts to changes in traffic, at the same time; it is able to heuristically enhance the performance of WiMAX network under most circumstances. The heuristic nature of this scheduling algorithm enables the MAC layer to meet the QoS requirements of the users. The performance of this adaptive WiMAX Uplink algorithm has been evaluated by simulation using MATLAB. Results indicate that the algorithm is efficient in scheduling the Base Stations’ traffic loads, and improves QoS. The utilization of relay stations is studied and simulation results are compared with the case without using relay stations. The results show that the proposed scheduling algorithm improves Quality of Service of WiMAX system.
Show less - Date Issued
- 2014
- PURL
- http://purl.flvc.org/fau/fd/FA00004178, http://purl.flvc.org/fau/fd/FA00004178
- Subject Headings
- Computer networks -- Technological innovations, Optical fiber communication, Wireless communication systems -- Technological innovations, Wireless metropolitan area networks -- Security measures
- Format
- Document (PDF)
- Title
- Real-time traffic incidents prediction in vehicular networks using big data analytics.
- Creator
- Al-Najada, Hamzah, Mahgoub, Imad, Florida Atlantic University, College of Engineering and Computer Science, Department of Computer and Electrical Engineering and Computer Science
- Abstract/Description
-
The United States has been going through a road accident crisis for many years. The National Safety Council estimates 40,000 people were killed and 4.57 million injured on U.S. roads in 2017. Direct and indirect loss from tra c congestion only is more than $140 billion every year. Vehicular Ad-hoc Networks (VANETs) are envisioned as the future of Intelligent Transportation Systems (ITSs). They have a great potential to enable all kinds of applications that will enhance road safety and...
Show moreThe United States has been going through a road accident crisis for many years. The National Safety Council estimates 40,000 people were killed and 4.57 million injured on U.S. roads in 2017. Direct and indirect loss from tra c congestion only is more than $140 billion every year. Vehicular Ad-hoc Networks (VANETs) are envisioned as the future of Intelligent Transportation Systems (ITSs). They have a great potential to enable all kinds of applications that will enhance road safety and transportation efficiency. In this dissertation, we have aggregated seven years of real-life tra c and incidents data, obtained from the Florida Department of Transportation District 4. We have studied and investigated the causes of road incidents by applying machine learning approaches to this aggregated big dataset. A scalable, reliable, and automatic system for predicting road incidents is an integral part of any e ective ITS. For this purpose, we propose a cloud-based system for VANET that aims at preventing or at least decreasing tra c congestions as well as crashes in real-time. We have created, tested, and validated a VANET traffic dataset by applying the connected vehicle behavioral changes to our aggregated dataset. To achieve the scalability, speed, and fault-tolerance in our developed system, we built our system in a lambda architecture fashion using Apache Spark and Spark Streaming with Kafka. We used our system in creating optimal and safe trajectories for autonomous vehicles based on the user preferences. We extended the use of our developed system in predicting the clearance time on the highway in real-time, as an important component of the traffic incident management system. We implemented the time series analysis and forecasting in our real-time system as a component for predicting traffic flow. Our system can be applied to use dedicated short communication (DSRC), cellular, or hybrid communication schema to receive streaming data and send back the safety messages. The performance of the proposed system has been extensively tested on the FAUs High Performance Computing Cluster (HPCC), as well as on a single node virtual machine. Results and findings confirm the applicability of the proposed system in predicting traffic incidents with low processing latency.
Show less - Date Issued
- 2018
- PURL
- http://purl.flvc.org/fau/fd/FA00013114
- Subject Headings
- Vehicular ad hoc networks (Computer networks), Big data, Intelligent transportation systems, Prediction, traffic incidents
- Format
- Document (PDF)
- Title
- INCORPORATING EMOTION RECOGNITION IN CO-ADAPTIVE SYSTEMS.
- Creator
- Al-Omair, Osamah M., Huang, Shihong, Florida Atlantic University, Department of Computer and Electrical Engineering and Computer Science, College of Engineering and Computer Science
- Abstract/Description
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The collaboration between human and computer systems has grown astronomically over the past few years. The ability of software systems adapting to human's input is critical in the symbiosis of human-system co-adaptation, where human and software-based systems work together in a close partnership to achieve synergetic goals. However, it is not always clear what kinds of human’s input should be considered to enhance the effectiveness of human and system co-adaptation. To address this issue,...
Show moreThe collaboration between human and computer systems has grown astronomically over the past few years. The ability of software systems adapting to human's input is critical in the symbiosis of human-system co-adaptation, where human and software-based systems work together in a close partnership to achieve synergetic goals. However, it is not always clear what kinds of human’s input should be considered to enhance the effectiveness of human and system co-adaptation. To address this issue, this research describes an approach that focuses on incorporating human emotion to improve human-computer co-adaption. The key idea is to provide a formal framework that incorporates human emotions as a foundation for explainability into co-adaptive systems, especially, how software systems recognize human emotions and adapt the system’s behaviors accordingly. Detecting and recognizing optimum human emotion is a first step towards human and computer symbiosis. As the first step of this research, we conduct a comparative review for a number of technologies and methods for emotion recognition. Specifically, testing the detection accuracy of facial expression recognition of different cloud-services, algorithms, and methods. Secondly, we study the application of emotion recognition within the areas of e-learning, robotics, and explainable artificial intelligence (XAI). We propose a formal framework that incorporates human emotions into an adaptive e-learning system, to create a more personalized learning experience for higher quality of learning outcomes. In addition, we propose a framework for a co-adaptive Emotional Support Robot. This human-centric framework adopts a reinforced learning approach where the system assesses its own emotional re-actions.
Show less - Date Issued
- 2022
- PURL
- http://purl.flvc.org/fau/fd/FA00013926
- Subject Headings
- Emotion recognition, Human-computer interaction, Affective Computing
- Format
- Document (PDF)
- Title
- AN EFFECTIVE ENSEMBLE LEARNING-BASED REAL-TIME INTRUSION DETECTION SCHEME FOR IN-VEHICLE NETWORK.
- Creator
- Alalwany, Easa, Mahgoub, Imadeldin, Florida Atlantic University, Department of Computer and Electrical Engineering and Computer Science, College of Engineering and Computer Science
- Abstract/Description
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Connectivity and automation have expanded with the development of autonomous vehicle technology. One of several automotive serial protocols that can be used in a wide range of vehicles is the controller area network (CAN). The growing functionality and connectivity of modern vehicles make them more vulnerable to cyberattacks aimed at vehicular networks. The CAN bus protocol is vulnerable to numerous attacks as it lacks security mechanisms by design. It is crucial to design intrusion detection...
Show moreConnectivity and automation have expanded with the development of autonomous vehicle technology. One of several automotive serial protocols that can be used in a wide range of vehicles is the controller area network (CAN). The growing functionality and connectivity of modern vehicles make them more vulnerable to cyberattacks aimed at vehicular networks. The CAN bus protocol is vulnerable to numerous attacks as it lacks security mechanisms by design. It is crucial to design intrusion detection systems (IDS) with high accuracy to detect attacks on the CAN bus. In this dissertation, to address all these concerns, we design an effective machine learning-based IDS scheme for binary classification that utilizes eight supervised ML algorithms, along with ensemble classifiers, to detect normal and abnormal activities in the CAN bus. Moreover, we design an effective ensemble learning-based IDS scheme for detecting and classifying DoS, fuzzing, replay, and spoofing attacks. These are common CAN bus attacks that can threaten the safety of a vehicle’s driver, passengers, and pedestrians. For this purpose, we utilize supervised machine learning in combination with ensemble methods. Ensemble learning aims to achieve better classification results through the use of different classifiers that are combined into a single classifier. Furthermore, in the pursuit of real-time attack detection and classification, we use the Kappa architecture for efficient data processing, enhancing the IDS’s accuracy and effectiveness. We build this system using the most recent CAN intrusion dataset provided by the IEEE DataPort. We carried out the performance evaluation of the proposed system in terms of accuracy, precision, recall, F1-score, and area under curve receiver operator characteristic (ROC-AUC). For the binary classification, the ensemble classifiers outperformed the individual supervised ML classifiers and improved the effectiveness of the classifier. For detecting and classifying CAN bus attacks, the ensemble learning methods resulted in a robust and accurate multiclassification IDS for common CAN bus attacks. The stacking ensemble method outperformed other recently proposed methods, achieving the highest performance. For the real-time attack detection and classification, the ensemble methods significantly enhance the accuracy the real-time CAN bus attack detection and classification. By combining the strengths of multiple models, the stacking ensemble technique outperformed individual supervised models and other ensembles.
Show less - Date Issued
- 2023
- PURL
- http://purl.flvc.org/fau/fd/FA00014298
- Subject Headings
- Automated vehicles, Controller Area Network (Computer network), Intrusion detection systems (Computer security)
- Format
- Document (PDF)
- Title
- Smart Adaptive Beaconing Schemes for VANET.
- Creator
- Alhameed, Mohammed, Mahgoub, Imad, Florida Atlantic University, College of Engineering and Computer Science, Department of Computer and Electrical Engineering and Computer Science
- Abstract/Description
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Vehicular Ad hoc Networks (VANET) is a wireless ad-hoc network that includes two types of communications, Vehicle-to-Vehicle (V2V) and Vehicle-to-Infrastructure (V2I). In VANET there are two types of messages. The first type is the event-driven messages that are only triggered in case of emergency. The second type is the periodical messages named beacons that are exchanged frequently between vehicles. A beacon message contains basic information about the sending vehicle such as id, location...
Show moreVehicular Ad hoc Networks (VANET) is a wireless ad-hoc network that includes two types of communications, Vehicle-to-Vehicle (V2V) and Vehicle-to-Infrastructure (V2I). In VANET there are two types of messages. The first type is the event-driven messages that are only triggered in case of emergency. The second type is the periodical messages named beacons that are exchanged frequently between vehicles. A beacon message contains basic information about the sending vehicle such as id, location and velocity. Beacons are frequently exchanged to increase the cooperative awareness between vehicles. Increasing beacon frequency helps increasing neighborhood awareness and improving information accuracy. However, this causes more congestion in the network, specially when the number of vehicles increases. On the other hand, reducing beacon frequency alleviates network congestion, but results in out-dated information. In this dissertation, we address the aforementioned challenges and propose a number of smart beaconing protocols and evaluate their performance in di↵erent environments and network densities. The four adaptive beaconing protocols are designed to increase the cooperative awareness and information freshness, while alleviating the network congestion. All the proposed protocols take into account the most important aspects, which are critical to beaconing rate adaptation. These aspects include channel status, traffic conditions and link quality. The proposed protocols employ fuzzy logic-based techniques to determine the congestion rank, which is used to adjust beacon frequency. The first protocol considers signal to interference-noise ratio (SINR), number of neighboring nodes and mobility to determine the congestion rank and adjust the beacon rate accordingly. This protocol works well in sparse conditions and highway environments. The second protocol works well in sparse conditions and urban environments. It uses channel busy time (CBT), mobility and packet delivery ratio (PDR) to determine the congestion rank and adjust the beacon rate. The third protocol utilizes CBT, SINR, PDR, number of neighbors and mobility as inputs for the fuzzy logic system to determine the congestion rank and adjust the beacon rate. This protocol works well in dense conditions in both highway and urban environments. Through extensive simulation experiments, we established that certain input parameters are more e↵ective in beacon rate adaptation for certain environments and conditions. Based on this, we propose a high awareness and channel efficient scheme that adapts to di↵erent environments and conditions. First, the protocol estimates the network density using adaptive threshold function. Then, it looks at the spatial distribution of nodes using the quadrat method to determine whether the environment is highway or urban. Based on the density conditions and nodes distribution, the protocol utilizes the appropriate fuzzy input parameters to adapt the beaconing rate. In addition, the protocol optimizes the performance by adapting the transmission power based on network density and nodes distribution. Finally, an investigation of the impact of adaptive beaconing on broadcasting is conducted. The simulation results confirm that our adaptive beaconing scheme can improve performance of the broadcast protocols in terms of reachability and bandwidth consumption when compared to a fixed rate scheme.
Show less - Date Issued
- 2018
- PURL
- http://purl.flvc.org/fau/fd/FA00013112
- Subject Headings
- Vehicular ad hoc networks (Computer networks), Beacons, Fuzzy logic, Adaptive computing systems
- Format
- Document (PDF)
- Title
- An Augmentative System with Facial and Emotion Recognition for Improving the Skills of Children with Autism Spectrum Disorders.
- Creator
- Alharbi, Mohammed N., Huang, Shihong, Florida Atlantic University, College of Engineering and Computer Science, Department of Computer and Electrical Engineering and Computer Science
- Abstract/Description
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Autism spectrum disorders (ASDs) are one of the complex, pervasive, and multifactorial neurodevelopmental conditions which affect one in 68 children. Scientific research has proven the efficiency of using technologies to improve communication and social skills of autistic children. The use of technological devices, such as mobile applications and multimedia, increase the interest of autistic children to learn while playing games. This thesis presents the re-engineering, extension, and...
Show moreAutism spectrum disorders (ASDs) are one of the complex, pervasive, and multifactorial neurodevelopmental conditions which affect one in 68 children. Scientific research has proven the efficiency of using technologies to improve communication and social skills of autistic children. The use of technological devices, such as mobile applications and multimedia, increase the interest of autistic children to learn while playing games. This thesis presents the re-engineering, extension, and evolution of an existing prototype Windows-based mobile application called Ying to become an Android mobile application which is augmented with facial and emotion recognition. This mobile app complements different approaches of traditional therapy, such as Applied Behavior Analysis (ABA). Ying integrates different computer-assisted technologies, including speech recognition, audio and visual interaction, and mobile applications to enhance autistic children’s social behavior and verbal communication skills. An evaluation of the efficacy of using Ying has been conducted and its results are presented in the thesis.
Show less - Date Issued
- 2018
- PURL
- http://purl.flvc.org/fau/fd/FA00005981
- Subject Headings
- Autism spectrum disorders, Human-computer interaction, Mobile apps
- Format
- Document (PDF)
- Title
- A PROBABILISTIC CHECKING MODEL FOR EFFECTIVE EXPLAINABILITY BASED ON PERSONALITY TRAITS.
- Creator
- Alharbi, Mohammed N., Huang, Shihong, Florida Atlantic University, Department of Computer and Electrical Engineering and Computer Science, College of Engineering and Computer Science
- Abstract/Description
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It is becoming increasingly important for an autonomous system to be able to explain its actions to humans in order to improve trust and enhance human-machine collaboration. However, providing the most appropriate kind of explanations – in terms of length, format, and presentation mode of explanations at the proper time – is critical to enhancing their effectiveness. Explanation entails costs, such as the time it takes to explain and for humans to comprehend and respond. Therefore, the actual...
Show moreIt is becoming increasingly important for an autonomous system to be able to explain its actions to humans in order to improve trust and enhance human-machine collaboration. However, providing the most appropriate kind of explanations – in terms of length, format, and presentation mode of explanations at the proper time – is critical to enhancing their effectiveness. Explanation entails costs, such as the time it takes to explain and for humans to comprehend and respond. Therefore, the actual improvement in human-system tasks from explanations (if any) is not always obvious, particularly given various forms of uncertainty in knowledge about humans. In this research, we propose an approach to address this issue. The key idea is to provide a structured framework that allows a system to model and reason about human personality traits as critical elements to guide proper explanation in human and system collaboration. In particular, we focus on the two concerns of modality and amount of explanation in order to optimize the explanation experience and improve overall system-human utility. Our models are based on probabilistic modeling and analysis (PRISM-games) to determine at run time what the most effective explanation under uncertainty is. To demonstrate our approach, we introduce a self-adaptative system called Grid – a virtual game – and the Stock Prediction Engine (SPE), which allows an automated system and a human to collaborate on the game and stock investments. Our evaluation of these exemplars, through simulation, demonstrates that a human subject’s performance and overall human-system utility is improved when considering the psychology of human personality traits in providing explanations.
Show less - Date Issued
- 2022
- PURL
- http://purl.flvc.org/fau/fd/FA00013894
- Subject Headings
- Human-computer interaction, Probabilistic modelling, Human-machine systems, Affective Computing
- Format
- Document (PDF)
- Title
- A Decision Support System for Sprint Planning in Scrum Practice.
- Creator
- Alhazmi, Alhejab Shawqi, Huang, Shihong, Florida Atlantic University, College of Engineering and Computer Science, Department of Computer and Electrical Engineering and Computer Science
- Abstract/Description
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Scrum is one of the Agile software development processes broadly adopted in industry. Scrum promotes frequent customer involvements and incremental short release. Sprint planning is a critical step in Scrum that sets up next release goals and lays out plans to achieve those goals. This thesis presents a Sprint Planning dEcision Support System (SPESS) which is a tool to assist the managers for Sprint planning. Among considering other Sprint planning factors, SPESS takes into consideration...
Show moreScrum is one of the Agile software development processes broadly adopted in industry. Scrum promotes frequent customer involvements and incremental short release. Sprint planning is a critical step in Scrum that sets up next release goals and lays out plans to achieve those goals. This thesis presents a Sprint Planning dEcision Support System (SPESS) which is a tool to assist the managers for Sprint planning. Among considering other Sprint planning factors, SPESS takes into consideration developer competency, developer seniority and task dependency. The results are that the assignments of the tasks of each Sprint to developers guarantee that each team member contributes to their fullest potential, and project planning is optimized for the shortest possible time. Keywords—Scrum, Sprint planning, planning poker, competence, task dependence, Hungarian algorithm, Essence.
Show less - Date Issued
- 2018
- PURL
- http://purl.flvc.org/fau/fd/FA00005970
- Subject Headings
- Scrum (Computer software development), Project management, Agile software development
- Format
- Document (PDF)
- Title
- INTEGRATING DESIGN THINKING MODEL AND ITEMS PRIORITIZATION DECISION SUPPORT SYSTEMS INTO REQUIREMENTS MANAGEMENT IN SCRUM.
- Creator
- Alhazmi, Alhejab Shawqi, Huang, Shihong, Florida Atlantic University, Department of Computer and Electrical Engineering and Computer Science, College of Engineering and Computer Science
- Abstract/Description
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The Agile methodologies have attracted the software development industry's attention due to their capability to overcome the limitations of the traditional software development approaches and to cope with increasing complexity in system development. Scrum is one of the Agile software development processes broadly adopted by industry. Scrum promotes frequent customer involvement and incremental short releases. Despite its popular use, Scrum’s requirements engineering stage is inadequately...
Show moreThe Agile methodologies have attracted the software development industry's attention due to their capability to overcome the limitations of the traditional software development approaches and to cope with increasing complexity in system development. Scrum is one of the Agile software development processes broadly adopted by industry. Scrum promotes frequent customer involvement and incremental short releases. Despite its popular use, Scrum’s requirements engineering stage is inadequately defined which can lead to increase development time and cost, along with low quality or failure for the end products. This research shows the importance of activity planning of requirements engineering in improving the product quality, cost, and scheduling as well as it points out some drawbacks of Agile practices and available solutions. To improve the Scrum requirements engineering by overcoming its challenges in cases, such as providing a comprehensive understanding of the customer’s needs and addressing the effects of the challenges in other cases, such as frequent changes of requirements, the Design Thinking model is integrated into the Scrum framework in the context of requirements engineering management. The use of the Design Thinking model, in the context of requirements engineering management, is validated through an in-depth scientific study of the IBM Design Thinking framework. In addition, this research presents an Items Prioritization dEcision Support System (IPESS) which is a tool to assist the Product Owners for requirements prioritization. IPESS is built on information collected in the Design Thinking model. The IPESS tool adopts Analytic Hierarchy Process (AHP) technique and PageRank algorithm to deal with the specified factors and to achieve the optimal order for requirements items based on the prioritization score. IPESS is a flexible and comprehensive tool that focuses on different important aspects including customer satisfaction and product quality. The IPESS tool is validated through an experiment that was conducted in a real-world project
Show less - Date Issued
- 2021
- PURL
- http://purl.flvc.org/fau/fd/FA00013699
- Subject Headings
- Scrum (Computer software development), Computer software--Development--Management, Software engineering
- Format
- Document (PDF)