Computer Engineering Commons^™

Domain-Specific Use Cases For Knowledge-Enabled Social Media Analysis, Soon Jye Kho, Swati Padhee, Goonmeet Bajaj, Krishnaprasad Thirunarayan, Amit Sheth

Publications

No abstract provided.

Tourism Review Sentiment Classification Using A Bidirectional Recurrent Neural Network With An Attention Mechanism And Topic-Enriched Word Vectors, Qin Li, Shaobo Li, Jie Hu, Sen Zhang, Jianjun Hu

Faculty Publications

Sentiment analysis of online tourist reviews is playing an increasingly important role in tourism. Accurately capturing the attitudes of tourists regarding different aspects of the scenic sites or the overall polarity of their online reviews is key to tourism analysis and application. However, the performances of current document sentiment analysis methods are not satisfactory as they either neglect the topics of the document or do not consider that not all words contribute equally to the meaning of the text. In this work, we propose a bidirectional gated recurrent unit neural network model (BiGRULA) for sentiment analysis by combining a topic …

Engaging Student Patrons With Traditional And Experimental Technology, Scott Russell, Joshua Enos, James Lane, Roy Zimmer

Academic Leadership Academy

No abstract provided.

A Framework For Detecting Injected Influence Attacks On Microblog Websites Using Change Detection Techniques, Vishnu S. Pendyala, Yuhong Liu, Silvia M. Figueira

Computer Science and Engineering

Presidential elections can impact world peace, global economics, and overall well-being. Recent news indicates that fraud on the Web has played a substantial role in elections, particularly in developing countries in South America and the public discourse, in general. To protect the trustworthiness of the Web, in this paper, we present a novel framework using statistical techniques to help detect veiled Web fraud attacks in Online Social Networks (OSN). Specific examples are used to demonstrate how some statistical techniques, such as the Kalman Filter and the modified CUSUM, can be applied to detect various attack scenarios. A hybrid data set, …

Cultivating Third Party Development In Platform-Centric Software Ecosystems: Extended Boundary Resources Model, Brown C. Msiska

The African Journal of Information Systems

Software ecosystems provide an effective way through which software solutions can be constructed by composing software components, typically applications, developed by internal and external developers on top of a software platform. Third party development increases the potential of a software ecosystem to effectively and quickly respond to context-specific software requirements. The boundary resources model gives a theoretical account for cultivation of third party development premised on the role of platform boundary resources such as application programming interfaces (API). However, from a longitudinal case study of the DHIS2 software ecosystem, this paper observes that no matter how good the boundary resources …

End-To-End Convolutional Neural Network Model For Gear Fault Diagnosis Based On Sound Signals, Yong Yao, Honglei Wang, Shaobo Li, Zhongnhao Liu, Gui Gui, Yabo Dan, Jianjun Hu

Faculty Publications

Currently gear fault diagnosis is mainly based on vibration signals with a few studies on acoustic signal analysis. However, vibration signal acquisition is limited by its contact measuring while traditional acoustic-based gear fault diagnosis relies heavily on prior knowledge of signal processing techniques and diagnostic expertise. In this paper, a novel deep learning-based gear fault diagnosis method is proposed based on sound signal analysis. By establishing an end-to-end convolutional neural network (CNN), the time and frequency domain signals can be fed into the model as raw signals without feature engineering. Moreover, multi-channel information from different microphones can also be fused …

Pfix: Fixing Concurrency Bugs Based On Memory Access Patterns, Huarui Lin, Zan Wang, Shuang Liu, Jun Sun, Dongdi Zhang, Guangning Wei

Research Collection School Of Computing and Information Systems

Concurrency bugs of a multi-threaded program may only manifest with certain scheduling, i.e., they are heisenbugs which are observed only from time to time if we execute the same program with the same input multiple times. They are notoriously hard to fix. In this work, we propose an approach to automatically fix concurrency bugs. Compared to previous approaches, our key idea is to systematically fix concurrency bugs by inferring locking policies from failure inducing memory-access patterns. That is, we automatically identify memory-access patterns which are correlated with the manifestation of the bug, and then conjecture what is the intended locking …

Enginews, September 2018, School Of Computer Science & Engineering Institution: Sacred Heart University

News, Magazines and Reports

No abstract provided.

Higher-Level Consistencies: Where, When, And How Much, Robert J. Woodward

School of Computing: Dissertations, Theses, and Student Research

Determining whether or not a Constraint Satisfaction Problem (CSP) has a solution is NP-complete. CSPs are solved by inference (i.e., enforcing consistency), conditioning (i.e., doing search), or, more commonly, by interleaving the two mechanisms. The most common consistency property enforced during search is Generalized Arc Consistency (GAC). In recent years, new algorithms that enforce consistency properties stronger than GAC have been proposed and shown to be necessary to solve difficult problem instances.

We frame the question of balancing the cost and the pruning effectiveness of consistency algorithms as the question of determining where, when, and how much of a higher-level …

Analysing Online User Activity To Implicitly Infer The Mental Workload Of Web-Based Tasks Using Defeasible Reasoning, Paul Mara

Dissertations

Mental workload can be considered the amount of cognitive load or effort used over time to complete a task in a complex system. Determining the limits of mental workload can assist in optimising designs and identify if user performance is affected by that design. Mental workload has also been presented as a defeasible concept, where one reason can defeat another and a 5-layer schema to represent domain knowledge to infer mental workload using defeasible reasoning has compared favourably to state-of-the-art inference techniques. Other previous work investigated using records of user activity for measuring mental workload at scale using web-based tasks …

Enhancing 3d Visual Odometry With Single-Camera Stereo Omnidirectional Systems, Carlos A. Jaramillo

Dissertations, Theses, and Capstone Projects

We explore low-cost solutions for efficiently improving the 3D pose estimation problem of a single camera moving in an unfamiliar environment. The visual odometry (VO) task -- as it is called when using computer vision to estimate egomotion -- is of particular interest to mobile robots as well as humans with visual impairments. The payload capacity of small robots like micro-aerial vehicles (drones) requires the use of portable perception equipment, which is constrained by size, weight, energy consumption, and processing power. Using a single camera as the passive sensor for the VO task satisfies these requirements, and it motivates the …

Blockchain Based Efficient And Robust Fair Payment For Outsourcing Services In Cloud Computing, Yinghui Zhang, Robert H. Deng, Ximeng Liu, Dong Zheng

Research Collection School Of Computing and Information Systems

As an attractive business model of cloud computing, outsourcing services usually involve online payment and security issues. The mutual distrust between users and outsourcing service providers may severely impede the wide adoption of cloud computing. Nevertheless, most existing payment solutions only consider a specific type of outsourcing service and rely on a trusted third-party to realize fairness. In this paper, in order to realize secure and fair payment of outsourcing services in general without relying on any third-party, trusted or not, we introduce BCPay, a blockchain based fair payment framework for outsourcing services in cloud computing. We first present the …

Vanishing Connections: Application Resiliency Through Cross-Network Tcp Migration, David Elliott

Theses and Dissertations

Computer applications are subject to a plethora of security challenges, ranging from concerns over network monitoring to avoiding expensive and damaging intrusion and compromise. A vast number of techniques exist to mitigate applications’ vulnerability to these threats: network policies can be adjusted, traffic can be rerouted, firewalls can be installed, hosts can be hardened, applications can be patched. A large body of research exists to improve the security of hosts in this context. However, for applications that have already been the subject of damaging attacks, we no longer focus primarily on security, but shift to resiliency, or the capacity of …

Androparse - An Android Feature Extraction Framework & Dataset, Robert Schmicker, Frank Breitinger, Ibrahim Baggili

Electrical & Computer Engineering and Computer Science Faculty Publications

Android malware has become a major challenge. As a consequence, practitioners and researchers spend a significant time analyzing Android applications (APK). A common procedure (especially for data scientists) is to extract features such as permissions, APIs or strings which can then be analyzed. Current state of the art tools have three major issues: (1) a single tool cannot extract all the significant features used by scientists and practitioners (2) Current tools are not designed to be extensible and (3) Existing parsers do not have runtime efficiency. Therefore, this work presents AndroParse which is an open-source Android parser written in Golang …

Decoupling Information And Connectivity Via Information-Centric Transport, Hila Ben Abraham, Jyoti Parwatikar, John Dehart, Adam Drescher, Patrick Crowley

Computer Science and Engineering Faculty Research

The power of Information-Centric Networking (ICN) architectures lies in their abstraction for communication --- the request for named data. This abstraction promises that applications can choose to operate only in the information plane, agnostic to the mechanisms implemented in the connectivity plane. However, despite this powerful promise, the information and connectivity planes are presently coupled in today's incarnations of leading ICNs by a core architectural component, the forwarding strategy. Presently, this component is not sustainable: it implements both the information and connectivity mechanisms without specifying who should choose a forwarding strategy --- an application developer or the network operator. In …

Digital Forensics In The Next Five Years, Laoise Luciano, Ibrahim Baggili, Mateusz Topor, Peter Casey, Frank Breitinger

Electrical & Computer Engineering and Computer Science Faculty Publications

Cyber forensics has encountered major obstacles over the last decade and is at a crossroads. This paper presents data that was obtained during the National Workshop on Redefining Cyber Forensics (NWRCF) on May 23-24, 2017 supported by the National Science Foundation and organized by the University of New Haven. Qualitative and quantitative data were analyzed from twenty-four cyber forensics expert panel members. This work identified important themes that need to be addressed by the community, focusing on (1) where the domain currently is; (2) where it needs to go and; (3) steps needed to improve it. Furthermore, based on the …

I Know What You Did Last Summer: Your Smart Home Internet Of Things And Your Iphone Forensically Ratting You Out, Gokila Dorai, Shiva Houshmand, Ibrahim Baggili

Electrical & Computer Engineering and Computer Science Faculty Publications

The adoption of smart home Internet of Things (IoT) devices continues to grow. What if your devices can snitch on you and let us know where you are at any given point in time? In this work we examined the forensic artifacts produced by Nest devices, and in specific, we examined the logical backup structure of an iPhone used to control a Nest thermostat, Nest Indoor Camera and a Nest Outdoor Camera. We also integrated the Google Home Mini as another method of controlling the studied Smart Home devices. Our work is the primary account for the examination of Nest …

Image Classification On Iot Edge Devices: Profiling And Modeling, Salma Abdel Magid

Computer Science and Engineering Master's Theses

With the advent of powerful, low-cost IoT systems, processing data closer to where the data originates, known as edge computing, has become an increasingly viable option. In addition to lowering the cost of networking infrastructures, edge computing reduces edge-cloud delay, which is essential for mission-critical applications. In this thesis, we show the feasibility and study the performance of image classification using IoT devices. Specifically, we explore the relationships between various factors of image classification algorithms that may affect energy consumption such as dataset size, image resolution, algorithm type, algorithm phase, and device hardware. Our experiments show a strong, positive linear …

Text Enhanced Recommendation System Model Based On Yelp Reviews, Peter Kouvaris, Ekaterina Pirogova, Hari Sanadhya, Albert Asuncion, Arun Rajagopal

SMU Data Science Review

In this paper, we introduce a useful natural language model for improving recommendation systems using collaborative filtering algorithms on ordinal ratings data. Since their inception, recommendation systems have evolved from simple user-business-rating matrices to complex systems that can consume multiple dimensions. Using Yelp's competition data set, we explore extending these dimensions to include natural language by leveraging a dual neural network architecture to produce a new and improved star rating system which offers potential improvements to collaborative filtering based recommendation systems.

Computational Thinking And Literacy, Sharin Rawhiya Jacob, Mark Warschauer

Journal of Computer Science Integration

Today’s students will enter a workforce that is powerfully shaped by computing. To be successful in a changing economy, students must learn to think algorithmically and computationally, to solve problems with varying levels of abstraction. These computational thinking skills have become so integrated into social function as to represent fundamental literacies. However, computer science has not been widely taught in K-12 schools. Efforts to create computer science standards and frameworks have yet to make their way into mandated course requirements. Despite a plethora of research on digital literacies, research on the role of computational thinking in the literature is sparse. …

Developing A New Storage Format And A Warp-Based Spmv Kernel For Configuration Interaction Sparse Matrices On The Gpu†, Mohammed Mahmoud, Mark Hoffmann, Hassan Reza

Computer Science Faculty Publications

Sparse matrix-vector multiplication (SpMV) can be used to solve diverse-scaled linear systems and eigenvalue problems that exist in numerous, and varying scientific applications. One of the scientific applications that SpMV is involved in is known as Configuration Interaction (CI). CI is a linear method for solving the nonrelativistic Schrödinger equation for quantum chemical multi-electron systems, and it can deal with the ground state as well as multiple excited states. In this paper, we have developed a hybrid approach in order to deal with CI sparse matrices. The proposed model includes a newly-developed hybrid format for storing CI sparse matrices on …

A Psychopathological Approach To Safety Engineering In Ai And Agi, Vahid Behzadan, Arslan Munir, Roman V. Yampolskiy

Faculty and Staff Scholarship

The complexity of dynamics in AI techniques is already approaching that of complex adaptive systems, thus curtailing the feasibility of formal controllability and reachability analysis in the context of AI safety. It follows that the envisioned instances of Artificial General Intelligence (AGI) will also suffer from challenges of complexity. To tackle such issues, we propose the modeling of deleterious behaviors in AI and AGI as psychological disorders, thereby enabling the employment of psychopathological approaches to analysis and control of misbehaviors. Accordingly, we present a discussion on the feasibility of the psychopathological approaches to AI safety, and propose general directions for …

From E-911 To Ng-911: Overview And Challenges In Ecuador, Danilo Corral-De-Witt, Enrique V. Carrera, Jose A. Matamoros-Vargas, Sergio Munoz-Romero, Jose Luis Rojo-Alvarez, Kemal Tepe

Department of Electrical and Computer Engineering: Faculty Publications

For years, emergency attendance institutions in Ecuador worked separately and not all of them had a 24/7 service, resulting in duplicated efforts, a waste of the scarce resources, and an absence of generalized technology. In 2012, Ecuador created an Integrated Security Service, called ECU 911, to address the need of an emergency service articulating all the first response institutions. The ECU 911 relies on the Enhanced 911 technology, having a countrywide presence. Since then, Ecuador has implemented 16 public-safety answering points and 11 decentralized operative rooms, covering all Ecuadorian territory and serving to a population of about 17 million people. …

Chaos Firefly Algorithm With Self-Adaptation Mutation Mechanism For Solving Large-Scale Economic Dispatch With Valve-Point Effects And Multiple Fuel Options, Yude Yang, Bori Wei, Hui Liu, Yiyi Zhang, Junhui Zhao, Emad Manla

Electrical & Computer Engineering and Computer Science Faculty Publications

This paper presents a new metaheuristic optimization algorithm, the firefly algorithm (FA), and an enhanced version of it, called chaos mutation FA (CMFA), for solving power economic dispatch problems while considering various power constraints, such as valve-point effects, ramp rate limits, prohibited operating zones, and multiple generator fuel options. The algorithm is enhanced by adding a new mutation strategy using self-adaptation parameter selection while replacing the parameters with fixed values. The proposed algorithm is also enhanced by a self-adaptation mechanism that avoids challenges associated with tuning the algorithm parameters directed against characteristics of the optimization problem to be solved. The …

Obtaining Chemical Selectivity From A Single, Nonselective Sensing Film: Two-Stage Adaptive Estimation Scheme With Multiparameter Measurement To Quantify Mixture Components And Interferents, Karthick Sothivelr, Florian Bender, Fabien Josse, Edwin E. Yaz, Antonio J. Ricco

Electrical and Computer Engineering Faculty Research and Publications

A new approach is reported to detect and quantify the members of a group of small-aromatic-molecule target analytes: benzene, toluene, ethylbenzene, and xylenes (BTEX), dissolved in water, in the presence of interferents, using only the data collected from a single polymer-coated SH-SAW (shear horizontal surface acoustic wave) device and a two-stage adaptive estimation scheme. This technique is composed of exponentially weighted recursive least-squares estimation (EW-RLSE) and a bank of Kalman filters (BKFs) and does not require any prior knowledge of the initial concentration range of the target analytes. The proposed approach utilizes the transient sensor response to sorption and/or desorption …

Dissipative Resilient Observer, M. Sami Fadali, Edwin E. Yaz

Electrical and Computer Engineering Faculty Research and Publications

Cybersecurity is a major concern for designers of control systems that can be directed against any of their components. Observers are an integral part of control systems that require state feedback. This paper considers an observer subject to errors in implementation or subject to cyberattacks. The errors and cyberattacks result in perturbations in the gain and in a finite-energy but unknown disturbance input. We obtain conditions for Q-S-R dissipativity and stability of the observer in the presence of the gain errors and disturbances in the form of linear matrix inequalities (LMIs). Three examples are presented to show how the LMIs …

Coupled State-Dependent Riccati Equation Control For Continuous Time Nonlinear Mechatronics Systems, Xin Wang, Edwin E. Yaz, Susan C. Schneider

Electrical and Computer Engineering Faculty Research and Publications

This manuscript considers the coupled state-dependent Riccati equation approach for systematically designing nonlinear quadratic regulator and H _∞ control of mechatronics systems. The state-dependent feedback control solutions can be obtained by solving a pair of coupled state-dependent Riccati equations, guaranteeing nonlinear quadratic optimality with inherent stability property in combination with robust ℓ ₂ type of disturbance reduction. The derivation of this control strategy is based on Nash's game theory. Both of finite and infinite horizon control problems are discussed. An underactuated robotic system, Furuta rotary pendulum, is used to examine the effectiveness and robustness of this novel nonlinear control approach.

Stator Resistance Estimation Using Adaptive Estimation Via A Bank Of Kalman Filters, Alia R. Strandt, Andrew Strandt, Susan C. Schneider, Edwin E. Yaz

Electrical and Computer Engineering Faculty Research and Publications

Accurate and efficient control of electric motors is dependent on knowledge of motor parameters such as the resistance and the inductance of the winding. However, these parameters are often unavailable to the control designer because they are dependent on the motor design and may change due to environmental effects such as temperature. An accurate real-time method to determine the values of these unknown parameters can improve motor performance over the entire operating range. In this work, a parameter estimation technique based on a bank of Kalman filters is used to adaptively estimate the motor winding resistance. Simulation results for a …

Aviation Cybersecurity: An Overview, Gary C. Kessler, J. Philip Craiger

National Training Aircraft Symposium (NTAS)

Information security—aka cybersecurity—is the most rapidly growing threat to critical infrastructures, including the aviation industry. Due to the plethora of digital devices, ubiquity of the Internet and other networks, and the rapid growth in the adoption of technology, everyone is an information system security manager. Every professional in the aviation and aeronautics industry use computers, mobile devices, tablets, GPS devices, and/or other hardware on a daily basis, as well as go online for a variety of reasons.

Attacks on information have been ongoing since the inception of the industry a hundred years ago, in such forms as intellectual property theft …

Self-Powered Time-Keeping And Time-Of-Occurrence Sensing, Liang Zhou

McKelvey School of Engineering Graduate Student Theses & Dissertations

Self-powered and passive Internet-of-Things (IoT) devices (e.g. RFID tags, financial assets, wireless sensors and surface-mount devices) have been widely deployed in our everyday and industrial applications. While diverse functionalities have been implemented in passive systems, the lack of a reference clock limits the design space of such devices used for applications such as time-stamping sensing, recording and dynamic authentication. Self-powered time-keeping in passive systems has been challenging because they do not have access to continuous power sources. While energy transducers can harvest power from ambient environment, the intermittent power cannot support continuous operation for reference clocks. The thesis of this …