Computer Engineering Commons^™

The Internet Of Energy: Architectures, Cyber Security, And Applications, Kun Wang, Yan Zhang, Song Guo, Mianxiong Dong, Rose Qingyang Hu, Lei He

Electrical and Computer Engineering Faculty Publications

The energy crisis and carbon emissions have become two critical concerns globally. As a very promising solution, the concept of Internet of Energy has appeared to tackle these challenges. The Internet of Energy is a new power generation paradigm developing a revolutionary vision of smart grids into the Internet. The communication infrastructure is an essential component for implementing the Internet of Energy. A scalable and robust communication infrastructure is crucial in both operating and maintaining smart energy systems. The wide-scale implementation and development of Internet of Energy into industrial applications should take into account the following challenges:

Paul Baran, Network Theory, And The Past, Present, And Future Of Internet, Christopher S. Yoo

All Faculty Scholarship

Paul Baran’s seminal 1964 article “On Distributed Communications Networks” that first proposed packet switching also advanced an underappreciated vision of network architecture: a lattice-like, distributed network, in which each node of the Internet would be homogeneous and equal in status to all other nodes. Scholars who have subsequently embraced the concept of a lattice-like network approach have largely overlooked the extent to which it is both inconsistent with network theory (associated with the work of Duncan Watts and Albert-László Barabási), which emphasizes the importance of short cuts and hubs in enabling networks to scale, and the actual way, the Internet …

Open Source Foundations For Spatial Decision Support Systems, Jochen Albrecht

Publications and Research

Spatial Decision Support Systems (SDSS) were a hot topic in the 1990s, when researchers tried to imbue GIS with additional decision support features. Successful practical developments such as HAZUS or CommunityViz have since been built, based on commercial desktop software and without much heed for theory other than what underlies their process models. Others, like UrbanSim, have been completely overhauled twice but without much external scrutiny. Both the practical and the theoretical foundations of decision support systems have developed considerably over the past 20 years. This article presents an overview of these developments and then looks at what corresponding tools …

Structure-Mediated Excitation Of Air Plasma And Silicon Plasma Expansion In Femtosecond Laser Pulses Ablation, Qingsong Wang, Lan Jiang, Changji Pan, Weina Han, Guoyan Wang, Feifei Wang, Kaihu Zhang, Ming Li, Yongfeng Lu

Department of Electrical and Computer Engineering: Faculty Publications

Femtosecond laser-induced surface structures upon multiple pulses irradiation are strongly correlated with the pulse number, which in turn significantly affects successive laser-material interactions. By recording the dynamics of femtosecond laser ablation of silicon using time-resolved shadowgraphy, here we present direct visualization of the excitation of air plasma induced by the reflected laser during the second pulse irradiation. The interaction of the air plasma and silicon plasma is found to enhance the shockwave expansion induced by silicon ablation in the longitudinal direction, showing anisotropic expansion dynamics in different directions. We further demonstrate the vanishing of air plasma as the pulse number …

Scalable Spatial Framework For Nosql Databases - Haslam Scholars Program Undergraduate Thesis, Daniel F. Enciso

Haslam Scholars Projects

The spatial frameworks used for knowledge discovery in “Big Data” areas such as urban information systems (UIS) are well- developed in SQL databases but are not as extensive within certain NoSQL databases. The focus of this project is to develop this framework for emerging search systems (ESS) in UIS by utilizing NoSQL databases, notably the document-based MongoDB. Such framework includes spatial functions for the most fundamental spatial queries. An ESS in UIS can take advantage of these new and attractive features of scalability within MongoDB to provide a robust approach to spatial search that differs from SQL relations and scalability. …

A Hierarchical Spectrum Access Scheme For Tv White Space Coexistence In Hetergeneous Networks, Mohammad Zaeri-Amirani, Fatemeh Afghah, Sherali Zeadally

Information Science Faculty Publications

Among current techniques for dynamic access to television (TV) white space (TVWS), geolocation database-based access provides a promising performance in protecting the TV-band incumbents from interference that cannot be efficiently achieved in other license-exempt models. However, in heterogeneous wireless networks, most portable devices do not have such access and may cause interference to TV incumbents. We propose a hierarchical model for spectrum sharing in TVWS that includes a wide range of fixed and portable devices. In the first tier, the TV broadcaster can lease the spectrum bands to local fixed users based on a soft license agreement. The fixed users …

Gmaim: An Analytical Pipeline For Microrna Splicing Profiling Using Generative Model, Kan Liu

Department of Computer Science and Engineering: Dissertations, Theses, and Student Research

MicroRNAs (miRNAs) are a class of short (~22 nt) single strand RNA molecules predominantly found in eukaryotes. Being involved in many major biological processes, miRNAs can regulate gene expression by targeting mRNAs to facilitate their degradation or translational inhibition. The imprecise splicing of miRNA splicing which introduces severe variability in terms of sequences of miRNA products and their corresponding downstream gene expression regulation. For example, to study biogenesis of miRNAs, usually, biologists can deplete a gene in the miRNA biogenesis pathway and study the change of miRNA sequences, which can cause impression of miRNAs. Although high-throughput sequencing technologies such as …

Smart Iot Sprinkler System, Galib F. Rahman

Publications and Research

The average family spends more than $1000 in water costs per year. One-way water is commonly wasted in many households is via inefficient sprinkler systems for lawns. Current technology has enabled the development of automatic sprinkler systems, which can be preconfigured to operate at desired times of day and intervals. Although these systems may reduce the amount of water utilized overall, they are not weather forecast aware. In situations when rainfall is upcoming the systems still water the lawn. In this project, we plan to implement a smart sprinkler system that has full awareness of upcoming weather and take account …

Facepet: Enhancing Bystanders' Facial Privacy With Smart Wearables/Internet Of Things, Alfredo J. Perez, Sherali Zeadally, Luis Y. Matos Garcia, Jaouad A. Mouloud, Scott Griffith

Information Science Faculty Publications

Given the availability of cameras in mobile phones, drones and Internet-connected devices, facial privacy has become an area of major interest in the last few years, especially when photos are captured and can be used to identify bystanders’ faces who may have not given consent for these photos to be taken and be identified. Some solutions to protect facial privacy in photos currently exist. However, many of these solutions do not give a choice to bystanders because they rely on algorithms that de-identify photos or protocols to deactivate devices and systems not controlled by bystanders, thereby being dependent on the …

Reasoning About Ideal Interruptible Moments: A Soft Computing Implementation Of An Interruption Classifier In Free-Form Task Environments, Edward R. Sykes

Publications and Scholarship

Current trends in society and technology make the concept of interruption a central human computer interaction problem. In this work, a novel soft computing implementation for an Interruption Classifier was designed, developed and evaluated that draws from a user model and real-time observations of the user's actions as s/he works on computer-based tasks to determine ideal times to interact with the user. This research is timely as the number of interruptions people experience daily has grown considerably over the last decade. Thus, systems are needed to manage interruptions by reasoning about ideal timings of interactions. This research shows: (1) the …

Distance-Based Cluster Head Election For Mobile Sensing, Ruairí De Fréin, Liam O'Farrell

Conference papers

Energy-efficient, fair, stochastic leader-selection algorithms are designed for mobile sensing scenarios which adapt the sensing strategy depending on the mobile sensing topology. Methods for electing a cluster head are crucially important when optimizing the trade-off between the number of peer-to- peer interactions between mobiles and client-server interactions with a cloud-hosted application server. The battery-life of mobile devices is a crucial constraint facing application developers who are looking to use the convergence of mobile computing and cloud computing to perform environmental sensing. We exploit the mobile network topology, specifically the location of mobiles with respect to the gateway device, to stochastically …

Teen Driver System Modeling: A Tool For Policy Analysis, Celestin Missikpode, Corrine Peek-Asa, Daniel V. Mcgehee, James Torner, Wayne Wakeland, Robert Wallace

Systems Science Faculty Publications and Presentations

Background: Motor vehicle crashes remain the leading cause of teen deaths in spite of preventive efforts. Prevention strategies could be advanced through new analytic approaches that allow us to better conceptualize the complex processes underlying teen crash risk. This may help policymakers design appropriate interventions and evaluate their impacts.

Methods: System Dynamics methodology was used as a new way of representing factors involved in the underlying process of teen crash risk. Systems dynamics modeling is relatively new to public health analytics and is a promising tool to examine relative influence of multiple interacting factors in predicting a health …

Scale-Out Algorithm For Apache Storm In Saas Environment, Ravi Kiran Puttaswamy

Department of Computer Science and Engineering: Dissertations, Theses, and Student Research

The main appeal of the Cloud is in its cost effective and flexible access to computing power. Apache Storm is a data processing framework used to process streaming data. In our work we explore the possibility of offering Apache Storm as a software service. Further, we take advantage of the cgroups feature in Storm to divide the computing power of worker machine into smaller units to be offered to users. We predict that the compute bounds placed on the cgroups could be used to approximate the state of the workflow. We discuss the limitations of the current schedulers in facilitating …

Reducing The Tail Latency Of A Distributed Nosql Database, Jun Wu

Department of Computer Science and Engineering: Dissertations, Theses, and Student Research

The request latency is an important performance metric of a distributed database, such as the popular Apache Cassandra, because of its direct impact on the user experience. Specifically, the latency of a read or write request is defined as the total time interval from the instant when a user makes the request to the instant when the user receives the request, and it involves not only the actual read or write time at a specific database node, but also various types of latency introduced by the distributed mechanism of the database. Most of the current work focuses only on reducing …

Evaluating Load Adjusted Learning Strategies For Client Service Levels Prediction From Cloud-Hosted Video Servers, Ruairí De Fréin, Obinna Izima, Mark Davis

Conference papers

Network managers that succeed in improving the accuracy of client video service level predictions, where the video is deployed in a cloud infrastructure, will have the ability to deliver responsive, SLA-compliant service to their customers. Meeting up-time guarantees, achieving rapid first-call resolution, and minimizing time-to-recovery af- ter video service outages will maintain customer loyalty.

To date, regression-based models have been applied to generate these predictions for client machines using the kernel metrics of a server clus- ter. The effect of time-varying loads on cloud-hosted video servers, which arise due to dynamic user requests have not been leveraged to improve prediction …

Deep Unsupervised Pixelization, Chu Han, Qiang Wen, Shengfeng He, Qianshu Zhu, Yinjie Tan, Guoqiang Han, Tien-Tsin Wong

Research Collection School Of Computing and Information Systems

In this paper, we present a novel unsupervised learning method for pixelization. Due to the difficulty in creating pixel art, preparing the paired training data for supervised learning is impractical. Instead, we propose an unsupervised learning framework to circumvent such difficulty. We leverage the dual nature of the pixelization and depixelization, and model these two tasks in the same network in a bi-directional manner with the input itself as training supervision. These two tasks are modeled as a cascaded network which consists of three stages for different purposes. GridNet transfers the input image into multi-scale grid-structured images with different aliasing …

Design And Analysis Of Binary Driven Coherent M-Ary Qam Transmitter For Next Generation Optical Networks, Naji Albakay

Department of Electrical and Computer Engineering: Dissertations, Theses, and Student Research

This work presents a design for a binary driven optical square M-ary quadrature amplitude modulation (QAM) transmitter for high speed optical networks. The transmitter applies tandem quadrature phase shift keying (QPSK) modulators to eliminate the need for linear broadband amplifiers and high-resolution digital to analog converters (DACs), which are both required by conventional transmitters. The transmitter design could be scaled to any order of square M-ary QAM by simply adding more QPSK modulators in tandem. It also provides a Gray coded symbol constellation, insuring the lowest bit error rate possible during symbol recovery. We also provide the design for the …

Automatically `Verifying’ Discrete-Time Complex Systems Through Learning, Abstraction And Refinement, Jingyi Wang, Jun Sun, Shengchao Qin, Cyrille Jegourel

Research Collection School Of Computing and Information Systems

Precisely modeling complex systems like cyber-physical systems is challenging, which often render model-based system verification techniques like model checking infeasible. To overcome this challenge, we propose a method called LAR to automatically ‘verify’ such complex systems through a combination of learning, abstraction and refinement from a set of system log traces. We assume that log traces and sampling frequency are adequate to capture ‘enough’ behaviour of the system. Given a safety property and the concrete system log traces as input, LAR automatically learns and refines system models, and produces two kinds of outputs. One is a counterexample with a bounded …

Co-Location Resistant Virtual Machine Placement In Cloud Data Centers, Amit Agarwal, Nguyen Binh Duong Ta

Research Collection School Of Computing and Information Systems

Due to increasing number of avenues for conducting cross-virtual machine (VM) side-channel attacks, the security of public IaaS cloud data centers is a growing concern. These attacks allow an adversary to steal private information from a target user whose VM instance is co-located with that of the adversary. To reduce the probability of malicious co-location, we propose a novel VM placement algorithm called “Previously Co-Located Users First”. We perform a theoretical and empirical analysis of our proposed algorithm to evaluate its resource efficiency and security. Our results, obtained using real-world cloud traces containing millions of VM requests and thousands of …

Early Prediction Of Merged Code Changes To Prioritize Reviewing Tasks, Yuanrui Fan, Xin Xia, David Lo, Shanping Li

Research Collection School Of Computing and Information Systems

Modern Code Review (MCR) has been widely used by open source and proprietary software projects. Inspecting code changes consumes reviewers much time and effort since they need to comprehend patches, and many reviewers are often assigned to review many code changes. Note that a code change might be eventually abandoned, which causes waste of time and effort. Thus, a tool that predicts early on whether a code change will be merged can help developers prioritize changes to inspect, accomplish more things given tight schedule, and not waste reviewing effort on low quality changes. In this paper, motivated by the above …

Building A Smart Nation: Singapore's Digital Journey, Siu Loon Hoe

Research Collection School Of Computing and Information Systems

Singapore’s smart nation journey began when the drive was officially announced by the country’s Prime Minister Lee Hsien Loong in November 2014 (Lee, 2014). The vision is to improve people’s lives and create more opportunities through information and communications technology (ICT). The smart nation drive is an effort by the government to co-create innovative, people-centric solutions with citizens and businesses. The three priority areas, underpinned by cyber security, are elderly, transportation and data. Since then, various digital strategies and policies have been further articulated, and digital programmes and projects implemented in the country.

“How Is My Child’S Asthma?” Digital Phenotype And Actionable Insights For Pediatric Asthma, Utkarshani Jaimini, Krishnaprasad Thirunarayan, Maninder Kalra, Revathy Venkataramanan, Dipesh Kadariya, Amit Sheth

Publications

Background: In the traditional asthma management protocol, a child meets with a clinician infrequently, once in 3 to 6 months, and is assessed using the Asthma Control Test questionnaire. This information is inadequate for timely determination of asthma control, compliance, precise diagnosis of the cause, and assessing the effectiveness of the treatment plan. The continuous monitoring and improved tracking of the child’s symptoms, activities, sleep, and treatment adherence can allow precise determination of asthma triggers and a reliable assessment of medication compliance and effectiveness. Digital phenotyping refers to moment-by-moment quantification of the individual-level human phenotype in situ using data from …

Asic Design To Support Low Power High Voltage Power Supply For Radiation Monitoring Applications, Daniel Rogge

Department of Electrical and Computer Engineering: Dissertations, Theses, and Student Research

A low power high voltage power supply is designed for use in a long duration radiation monitoring system. The supply employs a flexible pulse frequency modulation switching controller implemented in a 0.35 $\mu$m CMOS technology. The controller drives and regulates a flyback transformer driven 12-stage Cockroft-Walton voltage multiplier chain. The chain provides bias for the dynodes of a photomultiplier tube. The supply voltage is selectable via a 12-bit on-chip digital to analog converter. The system is designed for low power operation and immunity to supply voltage variation as the application is battery-powered.

Advisors: Sina Balkir and Michael Hoffman

Deploying, Improving And Evaluating Edge Bundling Methods For Visualizing Large Graphs, Jieting Wu

Department of Computer Science and Engineering: Dissertations, Theses, and Student Research

A tremendous increase in the scale of graphs has been witnessed in a wide range of fields, which demands efficient and effective visualization techniques to assist users in better understandings of large graphs. Conventional node-link diagrams are often used to visualize graphs, whereas excessive edge crossings can easily incur severe visual clutter in the node-link diagram of a large graph. Edge bundling can effectively remedy visual clutter and reveal high-level graph structures. Although significant efforts have been devoted to developing edge bundling, three challenging problems remain. First, edge bundling techniques are often computationally expensive and are not easy to deploy …

Controller Evolution And Divergence: A Software Perspective, Balaji Balasubramaniam

Department of Computer Science and Engineering: Dissertations, Theses, and Student Research

Successful controllers evolve as they are refined, extended, and adapted to new systems and contexts. This evolution occurs in the controller design and also in its software implementation. Model-based design and controller synthesis can help to synchronize this evolution of design and software, but such synchronization is rarely complete as software tends to also evolve in response to elements rarely present in a control model, leading to mismatches between the control design and the software.

In this thesis, we perform a first-of-its-kind study on the evolution of two popular open-source safety-critical autopilot control software -- ArduPilot, and Paparazzi, to better …

Evoalloy: An Evolutionary Approach For Analyzing Alloy Specifications, Jianghao Wang

Department of Computer Science and Engineering: Dissertations, Theses, and Student Research

Using mathematical notations and logical reasoning, formal methods precisely define a program’s specifications, from which we can instantiate valid instances of a system. With these techniques, we can perform a variety of analysis tasks to verify system dependability and rigorously prove the correctness of system properties. While there exist well-designed automated verification tools including ones considered lightweight, they still lack a strong adoption in practice. The essence of the problem is that when applied to large real world applications, they are not scalable and applicable due to the expense of thorough verification process. In this thesis, I present a new …

An Electron‐Rich Calix[4]Arene‐Based Receptor With Unprecedented Binding Affinity For Nitric Oxide, Denan Wang, Lena V. Ivanova, Maxim V. Ivanov, Saber Mirzaei, Qadir K. Timerghazin, Scott A. Reid, Rajendra Rathore

Electrical and Computer Engineering Faculty Research and Publications

Calixarenes have found widespread application as building blocks for the design and synthesis of functional materials in host–guest chemistry. The ongoing desire to develop a detailed understanding of the nature of NO bonding to multichromophoric π‐stacked assemblies led us to develop an electron‐rich methoxy derivative of calix[4]arene (3), which we show exists as a single conformer in solution at ambient temperature. Here, we examine the redox properties of this derivative, generate its cation radical (3^+.) using robust chemical oxidants, and determine the relative efficacy of its NO binding in comparison with model calixarenes. We find …

Best Trade-Off Point Method For Efficient Resource Provisioning In Spark, Peter P. Nghiem

Computer Science and Engineering

Considering the recent exponential growth in the amount of information processed in Big Data, the high energy consumed by data processing engines in datacenters has become a major issue, underlining the need for efficient resource allocation for more energy-efficient computing. We previously proposed the Best Trade-off Point (BToP) method, which provides a general approach and techniques based on an algorithm with mathematical formulas to find the best trade-off point on an elbow curve of performance vs. resources for efficient resource provisioning in Hadoop MapReduce. The BToP method is expected to work for any application or system which relies on a …

Deep Learning For Learning Representation And Its Application To Natural Language Processing, Shekoofeh Mokhtari

FIU Electronic Theses and Dissertations

As the web evolves even faster than expected, the exponential growth of data becomes overwhelming. Textual data is being generated at an ever-increasing pace via emails, documents on the web, tweets, online user reviews, blogs, and so on. As the amount of unstructured text data grows, so does the need for intelligently processing and understanding it. The focus of this dissertation is on developing learning models that automatically induce representations of human language to solve higher level language tasks.

In contrast to most conventional learning techniques, which employ certain shallow-structured learning architectures, deep learning is a newly developed machine learning …

A Validation Study Of Time Series Data Forecasting Using Neural Networks, Marco Martinez, Jeremy Evert

Student Research

Artificial Intelligence(AI) is a growing topic in Computer Science and has many uses in real world applications. One application is using Al, or more specifically Neural Networks to model data and predict outcomes. Neural Networks have been used in the past to predict weather changes, create facial recognition software , and to create self-driving cars. Our project is a validation study of, “Modeling Time Series Data With Deep Fourier Neural Networks” by Gashler and Ashmore, 2016. Here we show that a neural network can be trained to be an effective predictor of weather patterns in Alaska over several years. Our …