Physical Sciences and Mathematics Commons^™

Reputation-Aware Trajectory-Based Data Mining In The Internet Of Things (Iot), Samia Tasnim

FIU Electronic Theses and Dissertations

Internet of Things (IoT) is a critically important technology for the acquisition of spatiotemporally dense data in diverse applications, ranging from environmental monitoring to surveillance systems. Such data helps us improve our transportation systems, monitor our air quality and the spread of diseases, respond to natural disasters, and a bevy of other applications. However, IoT sensor data is error-prone due to a number of reasons: sensors may be deployed in hazardous environments, may deplete their energy resources, have mechanical faults, or maybe become the targets of malicious attacks by adversaries. While previous research has attempted to improve the quality of …

Trajectory Privacy Preservation And Lightweight Blockchain Techniques For Mobility-Centric Iot, Abdur Bin Shahid

FIU Electronic Theses and Dissertations

Various research efforts have been undertaken to solve the problem of trajectory privacy preservation in the Internet of Things (IoT) of resource-constrained mobile devices. Most attempts at resolving the problem have focused on the centralized model of IoT, which either impose high delay or fail against a privacy-invading attack with long-term trajectory observation. These proposed solutions also fail to guarantee location privacy for trajectories with both geo-tagged and non-geo-tagged data, since they are designed for geo-tagged trajectories only. While a few blockchain-based techniques have been suggested for preserving trajectory privacy in decentralized model of IoT, they require large storage capacity …

Augkit: An Augmented Drum Set System Designed For Live Performance, Mario A. Carvajal

FIU Electronic Theses and Dissertations

Augkit is an augmented drum set system designed for live performance. Augkit consists of a drum kit, microphone, audio interface, MIDI pad controller with foot switches, set of speakers, and a computer. I designed the processing audio engine in the visual programming language Max. Max processes the audio signal in a variety of ways that include delays, flanger, reverb, and synthesis that depend on the frequency content of the signal. Foot switches and MIDI pads toggle and modify the parameters of Augkit. This approach to playing drum set proves to be very flexible and offers new aesthetic possibilities for live …

A Privacy Framework For Decentralized Applications Using Blockchains And Zero Knowledge Proofs, David Gabay

FIU Electronic Theses and Dissertations

With the increasing interest in connected vehicles along with electrification opportunities, there is an ongoing effort to automate the charging process of electric vehicles (EVs) through their capabilities to communicate with the infrastructure and each other. However, charging EVs takes time and thus in-advance scheduling is needed. As this process is done frequently due to limited mileage of EVs, it may expose the locations and charging pattern of the EV to the service providers, raising privacy concerns for their users. Nevertheless, the EV still needs to be authenticated to charging providers, which means some information will need to be provided …

The Known Unknowns Of Diversity & Inclusion: Supporting Individuals With Hidden & Transitioning Identities, Stephen Secules, Cassandra Mccall

School of Universal Computing, Construction, and Engineering Education

The goal of this workshop is to create a safe and open space for people to learn about individuals with hidden and transitioning identities and ways to support them as community members and allies.

The Known Unknowns Of Diversity & Inclusion: Supporting Individuals With Hidden & Transitioning Identities, Stephen Secules, Cassandra Mccall

School of Universal Computing, Construction, and Engineering Education

The goal of this workshop is to create a safe and open space for people to learn about individuals with hidden and transitioning identities and ways to support them as community members and allies. Please only share information you are comfortable sharing and respectfully engage with and listen to others.

Implementing Facial Recognition Technology In A Municipal Archives Digitization Project, Rebecca Bakker

Works of the FIU Libraries

This poster at the 2019 annual meeting of the South Florida Archivists highlights a project where the facial recognition technology of Adobe Lightroom CC is used to identify individuals in photographs held by a local municipal archive. The photographs contain hundreds of images showing unnamed commissioners and city workers from the 1970s to the 1990s, with most of the images lacking metadata or information. Various strategies are employed to identify key city officials in the photographs, allowing their names to be added to the metadata of the records hosted in a digital repository. The poster demonstrates the potential and limitations …

Time Series Modeling Of Cell Cycle Exit Identifies Brd4 Dependent Regulation Of Cerebellar Neurogenesis, Clara Penas, Maria E. Maloof, Vasileios Stathias, Jun Long, Sze Kiat Tan, Jose Mier, Yin Fang, Camilo Valdes, Jezabel Rodriguez-Blanco, Cheng-Ming Chiang, David J. Robbins, Daniel J. Liebl, Jae K. Lee, Mary E. Hatten, Jennifer Clarke, Nagi G. Ayad

School of Computing and Information Sciences

No abstract provided.

Enlace: A Combination Of Layer-Based Architecture And Wireless Communication For Emotion Monitoring In Healthcare, Leandro Y. Mano, Vincicius A. Barros, Luiz H. Nunes, Luana O. Sawada, Julio C. Estrella, Jo Ueyama

School of Computing and Information Sciences

Owing to the increase in the number of people with disabilities, as a result of either accidents or old age, there has been an increase in research studies in the area of ubiquitous computing and the Internet of Things. They are aimed at monitoring health, in an efficient and easily accessible way, as a means of managing and improving the quality of life of this section of the public. It also involves adopting a Health Homes policy based on the Internet of Things and applied in smart home environments. This is aimed at providing connectivity between the patients and their …

Auto-Asd-Network: A Technique Based On Deep Learning And Support Vector Machines For Diagnosing Autism Spectrum Disorder Using Fmri Data, Taban Eslami, Fahad Saeed

School of Computing and Information Sciences

Quantitative analysis of brain disorders such as Autism Spectrum Disorder (ASD) is an ongoing field of research. Machine learning and deep learning techniques have been playing an important role in automating the diagnosis of brain disorders by extracting discriminative features from the brain data. In this study, we propose a model called Auto-ASD-Network in order to classify subjects with Autism disorder from healthy subjects using only fMRI data. Our model consists of a multilayer perceptron (MLP) with two hidden layers. We use an algorithm called SMOTE for performing data augmentation in order to generate artificial data and avoid overfitting, which …

Centralized And Distributed Detection Of Compromised Smart Grid Devices Using Machine Learning And Convolution Techniques, Cengiz Kaygusuz

FIU Electronic Theses and Dissertations

The smart grid concept has further transformed the traditional power grid into a massive cyber-physical system that depends on advanced two-way communication infrastructure. While the introduction of cyber components has improved the grid, it has also broadened the attack surface. In particular, the threat stemming from compromised devices pose a significant danger: An attacker can control the devices to change the behavior of the grid and can impact the measurements or damage the grid equipment. In this thesis, to detect such malicious smart grid devices, we propose a novel machine learning and convolution-based framework, named PowerWatch, that is able to …

A New Study Of Applying Complexity Theoretical Tools In Algorithm Design, Shuai Xu

FIU Electronic Theses and Dissertations

Given n vectors with dimension m in Boolean domain, how to find two vectors whose pairwise Hamming distance is minimum? This problem is known as the Closest Pair Problem. If these vectors are generated uniformly at random except two of them are correlated with Pearson-correlation coefficient, then the problem is called the Light Bulb Problem. In this work, we propose a novel coding-based scheme for the Closest Pair Problem. We design both randomized and deterministic algorithms, which achieve the best-known running time when the length of input vectors m is small and the minimum distance is very small compared to …

Analysis Of Flickr, Snapchat, And Twitter Use For The Modeling Of Visitor Activity In Florida State Parks, Hartwig H. Hochmair, Levente Juhasz

GIS Center

Spatio-temporal information attached to social media posts allows analysts to study human activity and travel behavior. This study analyzes contribution patterns to the Flickr, Snapchat, and Twitter platforms in over 100 state parks in Central and Northern Florida. The first part of the study correlates monthly visitor count data with the number of Flickr images, snaps, or tweets, contributed within the park areas. It provides insight into the suitability of these different social media platforms to be used as a proxy for the prediction of visitor numbers in state parks. The second part of the study analyzes the spatial distribution …

Spatio-Temporal Multimedia Big Data Analytics Using Deep Neural Networks, Samira Pouyanfar

FIU Electronic Theses and Dissertations

With the proliferation of online services and mobile technologies, the world has stepped into a multimedia big data era, where new opportunities and challenges appear with the high diversity multimedia data together with the huge amount of social data. Nowadays, multimedia data consisting of audio, text, image, and video has grown tremendously. With such an increase in the amount of multimedia data, the main question raised is how one can analyze this high volume and variety of data in an efficient and effective way. A vast amount of research work has been done in the multimedia area, targeting different aspects …

Multimodal Data Analytics And Fusion For Data Science, Haiman Tian

FIU Electronic Theses and Dissertations

Advances in technologies have rapidly accumulated a zettabyte of “new” data every two years. The huge amount of data have a powerful impact on various areas in science and engineering and generates enormous research opportunities, which calls for the design and development of advanced approaches in data analytics. Given such demands, data science has become an emerging hot topic in both industry and academia, ranging from basic business solutions, technological innovations, and multidisciplinary research to political decisions, urban planning, and policymaking. Within the scope of this dissertation, a multimodal data analytics and fusion framework is proposed for data-driven knowledge discovery …

Graph Theoretic And Pearson Correlation-Based Discovery Of Network Biomarkers For Cancer, Raihanul Bari Tanvir, Tasmia Aqila, Mona Maharjan, Abdullah Al Mamun, Ananda Mohan Mondal

School of Computing and Information Sciences

Two graph theoretic concepts—clique and bipartite graphs—are explored to identify the network biomarkers for cancer at the gene network level. The rationale is that a group of genes work together by forming a cluster or a clique-like structures to initiate a cancer. After initiation, the disease signal goes to the next group of genes related to the second stage of a cancer, which can be represented as a bipartite graph. In other words, bipartite graphs represent the cross-talk among the genes between two disease stages. To prove this hypothesis, gene expression values for three cancers— breast invasive carcinoma (BRCA), colorectal …

Ckmi: Comprehensive Key Management Infrastructure Design For Industrial Automation And Control Systems, T.C. Pramod, Thejas G.S., S.S. Iyengar, N. R. Sunitha

School of Computing and Information Sciences

Industrial Automation and Control Systems (IACS) are broadly utilized in critical infrastructures for monitoring and controlling the industrial processes remotely. The real-time transmissions in such systems provoke security breaches. Many security breaches have been reported impacting society severely. Hence, it is essential to achieve secure communication between the devices for creating a secure environment. For this to be effective, the keys used for secure communication must be protected against unauthorized disclosure, misuse, alteration or loss, which can be taken care of by a Key Management Infrastructure. In this paper, by considering the generic industrial automation network, a comprehensive key management …

How Middle School Boys From Underrepresented Communities Perceive Computer Science And Computer Science Careers, Cristal Kelly

Undergraduate Research at FIU (URFIU) Conference

Computer science (CS) as a field is characterized by significant disparities in the representation of people groups from minority populations. In this phenomenological study we sought to understand how middle school boys from minority groups perceive CS and related careers with the goal of identifying the factors that contribute to their career intentions. Specifically we sought to answer the following questions: How are salient factors reported by middle school boys related to CS career aspirations associated with their cultural values? How do perceived barriers shape their career intentions? And how do high CS interest and negative perceptions interact to affect …

Dynamic Interaction Network Inference From Longitudinal Microbiome Data, Jose Lugo-Martinez, Daniel Ruiz-Perez, Giri Narasimhan, Ziv Bar-Joseph

School of Computing and Information Sciences

Background

Several studies have focused on the microbiota living in environmental niches including human body sites. In many of these studies, researchers collect longitudinal data with the goal of understanding not only just the composition of the microbiome but also the interactions between the different taxa. However, analysis of such data is challenging and very few methods have been developed to reconstruct dynamic models from time series microbiome data.

Results

Here, we present a computational pipeline that enables the integration of data across individuals for the reconstruction of such models. Our pipeline starts by aligning the data collected for all …

Detection And Prevention Of Abuse In Online Social Networks, Sajedul Karim Talukder

FIU Electronic Theses and Dissertations

Adversaries leverage social networks to collect sensitive data about regular users and target them with abuse that includes fake news, cyberbullying, malware distribution, and propaganda. Such behavior is more effective when performed by the social network friends of victims. In two preliminary user studies we found that 71 out of 80 participants have at least 1 Facebook friend with whom (1) they never interact, either in Facebook or in real life, or whom they believe is (2) likely to abuse their posted photos or status updates, or (3) post offensive, false or malicious content. Such friend abuse is often considered …

Computational Analysis Of Large-Scale Trends And Dynamics In Eukaryotic Protein Family Evolution, Joseph Boehm Ahrens

FIU Electronic Theses and Dissertations

The myriad protein-coding genes found in present-day eukaryotes arose from a combination of speciation and gene duplication events, spanning more than one billion years of evolution. Notably, as these proteins evolved, the individual residues at each site in their amino acid sequences were replaced at markedly different rates. The relationship between protein structure, protein function, and site-specific rates of amino acid replacement is a topic of ongoing research. Additionally, there is much interest in the different evolutionary constraints imposed on sequences related by speciation (orthologs) versus sequences related by gene duplication (paralogs). A principal aim of this dissertation is to …

Cloud Workload Allocation Approaches For Quality Of Service Guarantee And Cybersecurity Risk Management, Soamar Homsi

FIU Electronic Theses and Dissertations

It has become a dominant trend in industry to adopt cloud computing --thanks to its unique advantages in flexibility, scalability, elasticity and cost efficiency -- for providing online cloud services over the Internet using large-scale data centers. In the meantime, the relentless increase in demand for affordable and high-quality cloud-based services, for individuals and businesses, has led to tremendously high power consumption and operating expense and thus has posed pressing challenges on cloud service providers in finding efficient resource allocation policies.

Allowing several services or Virtual Machines (VMs) to commonly share the cloud's infrastructure enables cloud providers to optimize resource …

Image-Based Authentication, Mozhgan Azimpourkivi

FIU Electronic Theses and Dissertations

Mobile and wearable devices are popular platforms for accessing online services. However, the small form factor of such devices, makes a secure and practical experience for user authentication, challenging. Further, online fraud that includes phishing attacks, has revealed the importance of conversely providing solutions for usable authentication of remote services to online users. In this thesis, we introduce image-based solutions for mutual authentication between a user and a remote service provider. First, we propose and develop Pixie, a two-factor, object-based authentication solution for camera-equipped mobile and wearable devices. We further design ai.lock, a system that reliably extracts from images, authentication …

Lbe: A Computational Load Balancing Algorithm For Speeding Up Parallel Peptide Search In Mass-Spectrometry Based Proteomics, Muhammad Haseeb, Fatima Afzali, Fahad Saeed

School of Computing and Information Sciences

The most commonly employed method for peptide identification in mass-spectrometry based proteomics involves comparing experimentally obtained tandem MS/MS spectra against a set of theoretical MS/MS spectra. The theoretical MS/MS spectra data are predicted using protein sequence database. Most state-of-the-art peptide search algorithms index theoretical spectra data to quickly filter-in the relevant (similar) indexed spectra when searching an experimental MS/MS spectrum. Data filtration substantially reduces the required number of computationally expensive spectrum-to-spectrum comparison operations. However, the number of predicted (and indexed) theoretical spectra grows exponentially with increase in posttranslational modifications creating a memory and I/O bottleneck. In this paper, we present …

Gpu-Dfc: A Gpu-Based Parallel Algorithm For Computing Dynamic-Functional Connectivity Of Big Fmri Data, Taban Eslami, Fahad Saeed

School of Computing and Information Sciences

Studying dynamic-functional connectivity (DFC) using fMRI data of the brain gives much richer information to neuroscientists than studying the brain as a static entity. Mining of dynamic connectivity graphs from these brain studies can be used to classify diseased versus healthy brains. However, constructing and mining dynamic-functional connectivity graphs of the brain can be time consuming due to size of fMRI data. In this paper, we propose a highly scalable GPU-based parallel algorithm called GPU-DFC for computing dynamic-functional connectivity of fMRI data both at region and voxel level. Our algorithm exploits sparsification of correlation matrix and stores them in CSR …

Context-Aware Personalized Point-Of-Interest Recommendation System, Ramesh Raj Baral

FIU Electronic Theses and Dissertations

The increasing volume of information has created overwhelming challenges to extract the relevant items manually. Fortunately, the online systems, such as e-commerce (e.g., Amazon), location-based social networks (LBSNs) (e.g., Facebook) among many others have the ability to track end users' browsing and consumption experiences. Such explicit experiences (e.g., ratings) and many implicit contexts (e.g., social, spatial, temporal, and categorical) are useful in preference elicitation and recommendation. As an emerging branch of information filtering, the recommendation systems are already popular in many domains, such as movies (e.g., YouTube), music (e.g., Pandora), and Point-of-Interest (POI) (e.g., Yelp).

The POI domain has many …