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Title: Low-power design of an ALU.
Creator: Agarwal, Ankur, Florida Atlantic University, Pandya, Abhijit S.
Abstract/Description: There is a mushrooming demand for battery operated applications that require intensive computation in portable environments. This has motivated the research and development of techniques that reduce power in CMOS digital circuits while maintaining their computational throughput. The two essentials to achieve a low power design are miniaturization and long battery life. Lowering the supply voltage is one of the most effective ways to achieve low-power performance as power dissipation in...
Show moreThere is a mushrooming demand for battery operated applications that require intensive computation in portable environments. This has motivated the research and development of techniques that reduce power in CMOS digital circuits while maintaining their computational throughput. The two essentials to achieve a low power design are miniaturization and long battery life. Lowering the supply voltage is one of the most effective ways to achieve low-power performance as power dissipation in digital CMOS circuits is approximately proportional to the square of supply voltage. The basic idea behind this thesis is that it proposes new designs of transfer gate based logical circuits, which use lower supply voltage and less number of transistors than the conventional designs. This work evaluates the obtained results from the proposed designs of the low-power ALU with that from the standard CMOS, other low power designs namely, Wang's XOR, XNOR and Inverter based gates. It was observed that the proposed designs perform better in terms of power consumption than the standard CMOS designs, and the other low power designs mentioned above.
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Date Issued: 2003
PURL: http://purl.flvc.org/fcla/dt/13017
Subject Headings: Metal oxide semiconductors, Complementary, Low voltage integrated circuits, Verilog (Computer hardware description language), Logic design
Format: Document (PDF)

Title: A Clinical Decision Support System for the Identification of Potential Hospital Readmission Patients.
Creator: Baechle, Christopher, Agarwal, Ankur, Florida Atlantic University, College of Engineering and Computer Science, Department of Computer and Electrical Engineering and Computer Science
Abstract/Description: Recent federal legislation has incentivized hospitals to focus on quality of patient care. A primary metric of care quality is patient readmissions. Many methods exist to statistically identify patients most likely to require hospital readmission. Correct identification of high-risk patients allows hospitals to intelligently utilize limited resources in mitigating hospital readmissions. However, these methods have seen little practical adoption in the clinical setting. This research attempts...
Show moreRecent federal legislation has incentivized hospitals to focus on quality of patient care. A primary metric of care quality is patient readmissions. Many methods exist to statistically identify patients most likely to require hospital readmission. Correct identification of high-risk patients allows hospitals to intelligently utilize limited resources in mitigating hospital readmissions. However, these methods have seen little practical adoption in the clinical setting. This research attempts to identify the many open research questions that have impeded widespread adoption of predictive hospital readmission systems. Current systems often rely on structured data extracted from health records systems. This data can be expensive and time consuming to extract. Unstructured clinical notes are agnostic to the underlying records system and would decouple the predictive analytics system from the underlying records system. However, additional concerns in clinical natural language processing must be addressed before such a system can be implemented. Current systems often perform poorly using standard statistical measures. Misclassification cost of patient readmissions has yet to be addressed and there currently exists a gap between current readmission system evaluation metrics and those most appropriate in the clinical setting. Additionally, data availability for localized model creation has yet to be addressed by the research community. Large research hospitals may have sufficient data to build models, but many others do not. Simply combining data from many hospitals often results in a model which performs worse than using data from a single hospital. Current systems often produce a binary readmission classification. However, patients are often readmitted for differing reasons than index admission. There exists little research into predicting primary cause of readmission. Furthermore, co-occurring evidence discovery of clinical terms with primary diagnosis has seen only simplistic methods applied. This research addresses these concerns to increase adoption of predictive hospital readmission systems.
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Date Issued: 2017
PURL: http://purl.flvc.org/fau/fd/FA00004880, http://purl.flvc.org/fau/fd/FA00004880
Subject Headings: Health services administration--Management., Medical care--Quality control--Statistical methods., Medical care--Quality control--Data processing., Medical care--Decision making., Evidence-based medicine., Outcome assessment (Medical care)
Format: Document (PDF)

Title: Development of a Wearable Device to Detect Epilepsy.
Creator: Khandnor Bakappa, Pradeepkumar, Agarwal, Ankur, Florida Atlantic University, College of Engineering and Computer Science, Department of Computer and Electrical Engineering and Computer Science
Abstract/Description: This paper evaluates the effectiveness of a wearable device, developed by the author, to detect different types of epileptic seizures and monitor epileptic patients. The device uses GSR, Pulse, EMG, body temperature and 3-axis accelerometer sensors to detect epilepsy. The device first learns the signal patterns of the epileptic patient in ideal condition. The signal pattern generated during the epileptic seizure, which are distinct from other signal patterns, are detected and analyzed by the...
Show moreThis paper evaluates the effectiveness of a wearable device, developed by the author, to detect different types of epileptic seizures and monitor epileptic patients. The device uses GSR, Pulse, EMG, body temperature and 3-axis accelerometer sensors to detect epilepsy. The device first learns the signal patterns of the epileptic patient in ideal condition. The signal pattern generated during the epileptic seizure, which are distinct from other signal patterns, are detected and analyzed by the algorithms developed by the author. Based on an analysis, the device successfully detected different types of epileptic seizures. The author conducted an experiment on himself to determine the effectiveness of the device and the algorithms. Based on the simulation results, the algorithms are 100 percent accurate in detecting different types of epileptic seizures.
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Date Issued: 2017
PURL: http://purl.flvc.org/fau/fd/FA00004937, http://purl.flvc.org/fau/fd/FA00004937
Subject Headings: Epilepsy--Diagnosis--Technological innovations., Patient monitoring., Signal processing--Digital techniques., Wearable computers--Industrial applications.
Format: Document (PDF)

Title: GAMIFICATION: A MONITORING SYSTEM FOR DIALYSIS PATIENTS.
Creator: Marella, Srivarsha, Agarwal, Ankur, Florida Atlantic University, College of Engineering and Computer Science, Department of Computer and Electrical Engineering and Computer Science
Abstract/Description: Dialysis patients are operated to have AV Fistula which is a joint junction of an artery and vein in the arm, operated to increase the blood flow through the dialyzer machine. AV- fistula is a type of vascular access which is a path into the body to connect/disconnect devices, but in this case, it is mainly Dialyzer. To reduce the failure rate during maturation period of AV Fistula, doctors recommend squeezing ball exercise as a necessary precaution for AV Fistula failure. Doing Squeezable...
Show moreDialysis patients are operated to have AV Fistula which is a joint junction of an artery and vein in the arm, operated to increase the blood flow through the dialyzer machine. AV- fistula is a type of vascular access which is a path into the body to connect/disconnect devices, but in this case, it is mainly Dialyzer. To reduce the failure rate during maturation period of AV Fistula, doctors recommend squeezing ball exercise as a necessary precaution for AV Fistula failure. Doing Squeezable interaction for about 3-4 times a day is recommended based on patient’s health condition. Hence, the proposed architecture adopts this squeezable exercise by embedding with sensor and measuring the angle at which the sensor is bent. The framework also proposes a new care coordination system having the hardware layer which has key components such as raspberry Pi, sensor which help in recording the pressure values when user presses the ball and software layer which solely focuses on data sync among the applications used by the user. It has been recorded that 53 % of patients having AV-Fistula fail because of negligence and lack of care. The maturation period is so critical and important which made us to build a gamification platform to monitor the exercise and track the activity through android application to keep users motivated and disciplined. In further chapters of the study will focus on different clinical like procedure around AV-Fistula and technical information such as different technologies used and implemented in the proposed system along with sensor circuit. This project goal is to present a way of monitoring patients and to keep track of the compliance whether the patient is active doing exercise daily. This way we are trying to present a care monitoring system for patients to help prevent AV Fistula failure.
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Date Issued: 2019
PURL: http://purl.flvc.org/fau/fd/FA00013331
Subject Headings: Gamification, Dialysis patients, Arteriovenous Fistula, Hemodialysis--Patients--Care, Patient monitoring
Format: Document (PDF)

Title: Big data driven co-occurring evidence discovery in chronic obstructive pulmonary disease patients.
Creator: Baechle, Christopher, Agarwal, Ankur, Zhu, Xingquan
Date Issued: 2017-12-04
PURL: http://purl.flvc.org/fau/flvc_fau_islandoraimporter_10.1186_s40537-017-0067-6_1629211082
Format: Citation

Title: Multi-method approach to wellness predictive modeling.
Creator: Agarwal, Ankur, Baechle, Christopher, Behara, Ravi S., Rao, Vinaya
Date Issued: 2016-12-24
PURL: http://purl.flvc.org/fau/flvc_fau_islandoraimporter_10.1186_s40537-016-0049-0_1628790858
Format: Citation

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)

Title: Predictive modeling for chronic conditions.
Creator: Jain, Ritesh, Agarwal, Ankur, Florida Atlantic University, College of Engineering and Computer Science, Department of Computer and Electrical Engineering and Computer Science
Abstract/Description: Chronic Diseases are the major cause of mortality around the world, accounting for 7 out of 10 deaths each year in the United States. Because of its adverse effect on the quality of life, it has become a major problem globally. Health care costs involved in managing these diseases are also very high. In this thesis, we will focus on two major chronic diseases Asthma and Diabetes, which are among the leading causes of mortality around the globe. It involves design and development of a...
Show moreChronic Diseases are the major cause of mortality around the world, accounting for 7 out of 10 deaths each year in the United States. Because of its adverse effect on the quality of life, it has become a major problem globally. Health care costs involved in managing these diseases are also very high. In this thesis, we will focus on two major chronic diseases Asthma and Diabetes, which are among the leading causes of mortality around the globe. It involves design and development of a predictive analytics based decision support system which uses five supervised machine learning algorithm to predict the occurrence of Asthma and Diabetes. This system helps in controlling the disease well in advance by selecting its best indicators and providing necessary feedback.
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Date Issued: 2015
PURL: http://purl.flvc.org/fau/fd/FA00004382, http://purl.flvc.org/fau/fd/FA00004382
Subject Headings: Biomedical engineering, Chronic diseases -- United States -- Prevention, Cloud computing, Medical informatics, Medicine, Preventive, Primary care (Medicine)
Format: Document (PDF)

Title: Virtualization techniques for mobile systems.
Creator: Jaramillo, David, Furht, Borko, Agarwal, Ankur, College of Engineering and Computer Science, Department of Computer and Electrical Engineering and Computer Science
Abstract/Description: In current mobile system environment there is a large gap in the use of smart phones for personal and enterprise use due to required enterprise security policies, privacy concerns as well as freedom of use. In the current environment, data-plans on mobile systems have become so wide spread that the rate of adaptation of data plans for every day customers has far outpaced the ability for enterprises to keep up with existing secure enterprise infrastructures. Most of the enterprises require...
Show moreIn current mobile system environment there is a large gap in the use of smart phones for personal and enterprise use due to required enterprise security policies, privacy concerns as well as freedom of use. In the current environment, data-plans on mobile systems have become so wide spread that the rate of adaptation of data plans for every day customers has far outpaced the ability for enterprises to keep up with existing secure enterprise infrastructures. Most of the enterprises require/provide the access of emails and other official information on smart platforms which presents a big challenge for the enterprise in securing their systems. Therefore due to the security issues and policies imposed by the enterprise in using the same device for dual purpose (personal and enterprise), the consumers often lose their individual freedom and convenience at the cost of security. Few solutions have been successful addressing this challenge. One effective way is to partition the mobile device such that the enterprise system access and its information are completely separated from the personal information. Several approaches are described and presented for mobile virtualization that creates a secure and secluded environment for enterprise information while allowing the user to access their personal information. A reference architecture is then presented that allows for integration with existing enterprise mobile device management systems and at the same time providing a light weight solution for containerizing mobile applications. This solution is then benchmarked with several of the existing mobile virtualization solutions.
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Date Issued: 2013
PURL: http://purl.flvc.org/fau/fd/FA0004028
Subject Headings: Mobile communication systems, Virtual computer systems
Format: Document (PDF)

Title: Prognostic COPD healthcare management system.
Creator: Jain, Piyush, Agarwal, Ankur, Florida Atlantic University, College of Engineering and Computer Science, Department of Computer and Electrical Engineering and Computer Science
Abstract/Description: Hospital readmission rates are considered to be an important indicator of quality of care because they may be a consequence of actions of commission or omission made during the initial hospitalization of the patient, or as a consequence of poorly managed transition of the patient back into the community. The negative impact on patient quality of life and huge burden on healthcare system have made reducing hospital readmissions a central goal of healthcare delivery and payment reform efforts....
Show moreHospital readmission rates are considered to be an important indicator of quality of care because they may be a consequence of actions of commission or omission made during the initial hospitalization of the patient, or as a consequence of poorly managed transition of the patient back into the community. The negative impact on patient quality of life and huge burden on healthcare system have made reducing hospital readmissions a central goal of healthcare delivery and payment reform efforts. In this project, we will focus on COPD (Chronic Obstructive Pulmonary Disease) which is one of the leading causes of disability and mortality worldwide. This project will design and develop a prognostic COPD healthcare management system which is a sustainable clinical decision-support system to reduce the number of readmissions by identifying those patients who need preventive interventions to reduce the probability of being readmitted. Based on patient’s clinical records and discharge summary, our system would be able to determine the readmission risk profile of patients treated for COPD. Suitable interventions could then be initiated with the objective of providing quality and timely care that helps prevent avoidable readmission.
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Date Issued: 2014
PURL: http://purl.flvc.org/fau/fd/FA00004125, http://purl.flvc.org/fau/fd/FA00004125
Subject Headings: Integrated delivery of health care, Lungs -- Diseases, Obstructive -- Treatment, Medical care -- Quality control
Format: Document (PDF)

Title: Remote monitoring and controlling of RF communication for a mobile device.
Creator: Gadipudi, Raviteja, Agarwal, Ankur, College of Engineering and Computer Science, Department of Computer and Electrical Engineering and Computer Science
Abstract/Description: In recent years there has been dramatic growth in mobile devices and technologies. According to reports from comScore [1], 47% users in the United States (aged more than 13) are using a smartphones as their primary phone. Smartphone offers more advanced computing ability and connectivity than contemporary phones. In today’s world, a user wants to keep their smartphones private, because of the personal information present in it. Among these users, some of them are minors. This thesis addresses...
Show moreIn recent years there has been dramatic growth in mobile devices and technologies. According to reports from comScore [1], 47% users in the United States (aged more than 13) are using a smartphones as their primary phone. Smartphone offers more advanced computing ability and connectivity than contemporary phones. In today’s world, a user wants to keep their smartphones private, because of the personal information present in it. Among these users, some of them are minors. This thesis addresses the functionality to track/control the mobile activities of minors by their parents using mobile phones. As a parent they want to know, whom his/her child is talking to and for what they are accessing browser for. Cellular network companies are providing number blocking services from the carrier side, but those are monthly paid services. In this thesis, we propose application architecture for remotely control the child phone and grant access to selected numbers for call and text. We use the emerging Android mobile platform and Google nexus phones to implement and test the application. This architecture will help developers to make more innovative applications in future which helps parent to access child phone information. We performed a study and reported the result using the proposal.
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Date Issued: 2013
PURL: http://purl.flvc.org/fau/fd/FA0004018
Subject Headings: Information technology -- Social aspects, Mobile communication devices -- Security measures, Technological innovations -- Social aspects
Format: Document (PDF)

Title: HPCC based Platform for COPD Readmission Risk Analysis with implementation of Dimensionality reduction and balancing techniques.
Creator: Jain, Piyush, Agarwal, Ankur, Florida Atlantic University, Department of Computer and Electrical Engineering and Computer Science, College of Engineering and Computer Science
Abstract/Description: Hospital readmission rates are considered to be an important indicator of quality of care because they may be a consequence of actions of commission or omission made during the initial hospitalization of the patient, or as a consequence of poorly managed transition of the patient back into the community. The negative impact on patient quality of life and huge burden on healthcare system have made reducing hospital readmissions a central goal of healthcare delivery and payment reform efforts....
Show moreHospital readmission rates are considered to be an important indicator of quality of care because they may be a consequence of actions of commission or omission made during the initial hospitalization of the patient, or as a consequence of poorly managed transition of the patient back into the community. The negative impact on patient quality of life and huge burden on healthcare system have made reducing hospital readmissions a central goal of healthcare delivery and payment reform efforts. In this study, we will be proposing a framework on how the readmission analysis and other healthcare models could be deployed in real world and a Machine learning based solution which uses patients discharge summaries as a dataset to train and test the machine learning model created. Current systems does not take into consideration one of the very important aspect of solving readmission problem by taking Big data into consideration. This study also takes into consideration Big data aspect of solutions which can be deployed in the field for real world use. We have used HPCC compute platform which provides distributed parallel programming platform to create, run and manage applications which involves large amount of data. We have also proposed some feature engineering and data balancing techniques which have shown to greatly enhance the machine learning model performance. This was achieved by reducing the dimensionality in the data and fixing the imbalance in the dataset. The system presented in this study provides a real world machine learning based predictive modeling for reducing readmissions which could be templatized for other diseases.
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Date Issued: 2020
PURL: http://purl.flvc.org/fau/fd/FA00013560
Subject Headings: Machine learning, Big data, Patient Readmission, Hospitals--Admission and discharge--Data processing, High performance computing
Format: Document (PDF)

Title: Smart campus.
Creator: Danda, Naga Prakash, Agarwal, Ankur, Florida Atlantic University, College of Engineering and Computer Science, Department of Computer and Electrical Engineering and Computer Science
Abstract/Description: The Smart Campus project envisions a university campus where technology assists faculty, staff, students and visitors to improve and more efficiently accomplish their daily activities. The objective of this project is to develop a smart phone application that assists users in finding a certain location on campus, locating their friends and professors, interacting with any student or professors of the campus, get the count of users at certain locations and remain updated about all the events...
Show moreThe Smart Campus project envisions a university campus where technology assists faculty, staff, students and visitors to improve and more efficiently accomplish their daily activities. The objective of this project is to develop a smart phone application that assists users in finding a certain location on campus, locating their friends and professors, interacting with any student or professors of the campus, get the count of users at certain locations and remain updated about all the events and campus news. Through this project, an idea of ‘Futuristic Social Network’ in a Campus is modeled and developed on Android platform.
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Date Issued: 2014
PURL: http://purl.flvc.org/fau/fd/FA00004098, http://purl.flvc.org/fau/fd/FA00004098
Subject Headings: Mobile communication systems -- Security measures, Technological innovations -- Social aspects, Ubiquitous computing, Universities and colleges -- Design
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).
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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: AN ARTIFICIAL INTELLIGENCE DRIVEN FRAMEWORK FOR MEDICAL IMAGING.
Creator: Sanghvi, Harshal A., Agarwal, Ankur, Florida Atlantic University, Department of Computer and Electrical Engineering and Computer Science, College of Engineering and Computer Science
Abstract/Description: The major objective of this dissertation was to create a framework which is used for medical image diagnosis. In this diagnosis, we brought classification and diagnosing of diseases through an Artificial Intelligence based framework, including COVID, Pneumonia, and Melanoma cancer through medical images. The algorithm ran on multiple datasets. A model was developed which detected the medical images through changing hyper-parameters. The aim of this work was to apply the new transfer learning...
Show moreThe major objective of this dissertation was to create a framework which is used for medical image diagnosis. In this diagnosis, we brought classification and diagnosing of diseases through an Artificial Intelligence based framework, including COVID, Pneumonia, and Melanoma cancer through medical images. The algorithm ran on multiple datasets. A model was developed which detected the medical images through changing hyper-parameters. The aim of this work was to apply the new transfer learning framework DenseNet-201 for the diagnosis of the diseases and compare the results with the other deep learning models. The novelty in the proposed work was modifying the Dense Net 201 Algorithm, changing hyper parameters (source weights, Batch Size, Epochs, Architecture (number of neurons in hidden layer), learning rate and optimizer) to quantify the results. The novelty also included the training of the model by quantifying weights and in order to get more accuracy. During the data selection process, the data were cleaned, removing all the outliers. Data augmentation was used for the novel architecture to overcome overfitting and hence not producing false absurd results the computational performance was also observed. The proposed model results were also compared with the existing deep learning models and the algorithm was also tested on multiple datasets.
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Date Issued: 2023
PURL: http://purl.flvc.org/fau/fd/FA00014274
Subject Headings: Diagnostic imaging, Artificial intelligence, Deep learning (Machine learning)
Format: Document (PDF)

Title: Predictive Models for Ebola using Machine Learning Algorithms.
Creator: Jain, Abhishek, Agarwal, Ankur, Furht, Borko, Florida Atlantic University, College of Engineering and Computer Science, Department of Computer and Electrical Engineering and Computer Science
Abstract/Description: Identifying and tracking individuals affected by this virus in densely populated areas is a unique and an urgent challenge in the public health sector. Currently, mapping the spread of the Ebola virus is done manually, however with the help of social contact networks we can model dynamic graphs and predictive diffusion models of Ebola virus based on the impact on either a specific person or a specific community. With the help of this model, we can make more precise forward predictions of the...
Show moreIdentifying and tracking individuals affected by this virus in densely populated areas is a unique and an urgent challenge in the public health sector. Currently, mapping the spread of the Ebola virus is done manually, however with the help of social contact networks we can model dynamic graphs and predictive diffusion models of Ebola virus based on the impact on either a specific person or a specific community. With the help of this model, we can make more precise forward predictions of the disease propagations and to identify possibly infected individuals which will help perform trace – back analysis to locate the possible source of infection for a social group. This model will visualize and identify the families and tightly connected social groups who have had contact with an Ebola patient and is a proactive approach to reduce the risk of exposure of Ebola spread within a community or geographic location.
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Date Issued: 2017
PURL: http://purl.flvc.org/fau/fd/FA00004919, http://purl.flvc.org/fau/fd/FA00004919
Subject Headings: Communicable diseases--Epidemiology., Public health surveillance., Ebola virus disease--Transmission., Machine learning., Computer algorithms., Virtual reality., Interactive multimedia., Computer graphics., History--Graphic methods., Historiography--Technological innovations.
Format: Document (PDF)

FAU Theses and Dissertations (14)	+ -
FAU College Collections (2)	+ -

Medicine, Preventive (2)	+ -
Technological innovations -- Social aspects (2)	+ -
Arteriovenous Fistula (1)	+ -
Artificial intelligence (1)	+ -
Bayesian statistical decision theory (1)	+ -

Big data (1)	+ -
Biomedical engineering (1)	+ -
Chronic diseases -- United States -- Prevention (1)	+ -
Cloud computing (1)	+ -
Communicable diseases--Epidemiology. (1)	+ -
Computer algorithms. (1)	+ -
Computer graphics. (1)	+ -
Computer networks--Quality control (1)	+ -
Data transmission systems (1)	+ -
Deep learning (Machine learning) (1)	+ -
Diagnostic imaging (1)	+ -
Dialysis patients (1)	+ -
Ebola virus disease--Transmission. (1)	+ -
Embedded computer systems--Quality control (1)	+ -
Epilepsy--Diagnosis--Technological innovations. (1)	+ -
Evidence-based medicine. (1)	+ -
Expert systems (Computer science) (1)	+ -
Gamification (1)	+ -
Health risk assessment (1)	+ -
Health services administration--Management. (1)	+ -
Hemodialysis--Patients--Care (1)	+ -
High performance computing (1)	+ -
Historiography--Technological innovations. (1)	+ -
History--Graphic methods. (1)	+ -
Hospitals--Admission and discharge--Data processing (1)	+ -

Electronic Thesis or Dissertation (14)	+ -
article (2)	+ -

Agarwal, Ankur (16)	+ -
College of Engineering and Computer Science (13)	+ -
Department of Computer and Electrical Engineering and Computer Science (13)	+ -
Florida Atlantic University (12)	+ -
Baechle, Christopher (3)	+ -

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