Computer Engineering Commons^™

Modeling Adversarial Insider Vehicles In Mix Zones, Nicholas Plewtong

Master's Theses

Security is a necessity when dealing with new forms of technology that may not have been analyzed from a security perspective. One of the latest growing technological advances are Vehicular Ad-Hoc Networks (VANETs). VANETs allow vehicles to communicate information to each other wirelessly which allows for an increase in safety and efficiency for vehicles. However, with this new type of computerized system comes the need to maintain security on top of it.

In order to try to protect location privacy of the vehicles in the system, vehicles change pseudonyms or identifiers at areas known as mix zones. This thesis implements …

Sentiment Analysis Of Twitter Data, Evan L. Munson

Theses and Dissertations

The rapid expansion and acceptance of social media has opened doors into users’ opinions and perceptions that were never as accessible as they are with today's prevalence of mobile technology. Harvested data, analyzed for opinions and sentiment can provide powerful insight into a population. This research utilizes Twitter data due to its widespread global use, in order to examine the sentiment associated with tweets. An approach utilizing Twitter #hashtags and Latent Dirichlet Allocation topic modeling were utilized to differentiate between tweet topics. A lexicographical dictionary was then utilized to classify sentiment. This method provides a framework for an analyst to …

Skylux Smartphone Controlled Skylight, James A. Green Vi

Computer Engineering

There are numerous electric skylight openers available for purchase for home-use, but the majority of them are remote based, or operated by a wall-unit. Furthermore, these devices are in hard to reach places, so if one were to lose the remote on a remote operated system, the only option is to contact the manufacturer for a new device. As such, my senior project, in collaboration with Colton Sundstrom’s senior project, build upon our existing capstone project in order to allow operation of the Internet of Things (IoT) device over the internet. Our client, Richard Murray, was unsatisfied with the current …

A Novel Evolutionary Algorithm For Designing Robust Analog Filters, Shaobo Li, Wang Zou, Jianjun Hu

Faculty Publications

Designing robust circuits that withstand environmental perturbation and device degradation is critical for many applications. Traditional robust circuit design is mainly done by tuning parameters to improve system robustness. However, the topological structure of a system may set a limit on the robustness achievable through parameter tuning. This paper proposes a new evolutionary algorithm for robust design that exploits the open-ended topological search capability of genetic programming (GP) coupled with bond graph modeling. We applied our GP-based robust design (GPRD) algorithm to evolve robust lowpass and highpass analog filters. Compared with a traditional robust design approach based on a state-of-the-art …

Cru Android App, Dylan Sun

Computer Science and Software Engineering

The Cru app is focused on connecting students and faculty to one of the many Cru ministries here in San Luis Obispo. The app is capable of connecting individuals to a specific community group and ministry teams, gathering information about upcoming Cru events and gatherings, and direct rideshare capabilities. The Cru Android App utilizes Java and other industry standard technologies to fully deliver a well-rounded user experience and to be connected with Cru. In this project, I increased Cru app’s access control abilities and updated the app overall to be ready for an alpha release.

Predicting The Vote Using Legislative Speech, Aditya Budhwar

Master's Theses

As most dedicated observers of voting bodies like the U.S. Supreme Court can attest, it is possible to guess vote outcomes based on statements made during deliberations or questioning by the voting members. In most forms of representative democracy, citizens can actively petition or lobby their representatives, and that often means understanding their intentions to vote for or against an issue of interest. In some U.S. state legislators, professional lobby groups and dedicated press members are highly informed and engaged, but the process is basically closed to ordinary citizens because they do not have enough background and familiarity with the …

Hiddencode: Hidden Acoustic Signal Capture With Vibration Energy Harvesting, Guohao Lan, Dong Ma, Mahbub Hassan, Wen Hu

Research Collection School Of Computing and Information Systems

The feasibility of using vibration energy harvesting (VEH) as an energy-efficient receiver for short-range acoustic data communication has been investigated recently. When data was encoded in acoustic signal within the energy harvesting frequency band and transmitted through a speaker, a VEH receiver was capable of decoding the data by processing the harvested energy signal. Although previous work created new opportunities for simultaneous energy harvesting and communication using the same hardware, the communication makes annoying sounds as the energy harvesting frequency band lies within the sensitive region of human auditory system. In this work, we present a novel modulation scheme to …

Scaling Human Activity Recognition Via Deep Learning-Based Domain Adaptation, Md Abdullah Hafiz Khan, Nirmalya Roy, Archan Misra

Research Collection School Of Computing and Information Systems

We investigate the problem of making human activityrecognition (AR) scalable–i.e., allowing AR classifiers trainedin one context to be readily adapted to a different contextualdomain. This is important because AR technologies can achievehigh accuracy if the classifiers are trained for a specific individualor device, but show significant degradation when the sameclassifier is applied context–e.g., to a different device located ata different on-body position. To allow such adaptation withoutrequiring the onerous step of collecting large volumes of labeledtraining data in the target domain, we proposed a transductivetransfer learning model that is specifically tuned to the propertiesof convolutional neural networks (CNNs). Our model, …

A New Revocable And Re-Delegable Proxy Signature And Its Application, Shengmin Xu, Guomin Yang, Yi Mu

Research Collection School Of Computing and Information Systems

With the popularity of cloud computing and mobile Apps, on-demand services such as on-line music or audio streaming and vehicle booking are widely available nowadays. In order to allow efficient delivery and management of the services, for large-scale on-demand systems, there is usually a hierarchy where the service provider can delegate its service to a top-tier (e.g., countrywide) proxy who can then further delegate the service to lower level (e.g., region-wide) proxies. Secure (re-)delegation and revocation are among the most crucial factors for such systems. In this paper, we investigate the practical solutions for achieving re-delegation and revocation utilizing proxy …

Fixation And Confusion: Investigating Eye-Tracking Participants' Exposure To Information In Personas, Joni Salminen, Bernard J. Jansen, Jisun An, Soon-Gyo Jung, Lene Nielsen, Haewoon Kwak

Research Collection School Of Computing and Information Systems

To more effectively convey relevant information to end users of persona profiles, we conducted a user study consisting of 29 participants engaging with three persona layout treatments. We were interested in confusion engendered by the treatments on the participants, and conducted a within-subjects study in the actual work environment, using eye-tracking and talk-aloud data collection. We coded the verbal data into classes of informativeness and confusion and correlated it with fixations and durations on the Areas of Interests recorded by the eye-tracking device. We used various analysis techniques, including Mann-Whitney, regression, and Levenshtein distance, to investigate how confused users differed …

Constant-Size Ciphertexts In Threshold Attribute-Based Encryption Without Dummy Attributes, Willy Susilo, Guomin Yang, Fuchun Guo, Qiong Huang

Research Collection School Of Computing and Information Systems

Attribute-based encryption (ABE) is an augmentation of public key encryption that allows users to encrypt and decrypt messages based on users' attributes. In a (t, s) threshold ABE, users who can decrypt a ciphertext must hold at least t attributes among the s attributes specified by the encryptor. At PKC 2010, Herranz, Laguillaumie and Raft& proposed the first threshold ABE with constant-size ciphertexts. In order to ensure the encryptor can flexibly select the attribute set and a threshold value, they use dummy attributes to satisfy the decryption requirement. The advantage of their scheme is that any addition or removal of …

Electron Effective Mass In In0.33ga0.67n Determined By Mid- Infrared Optical Hall Effect, Nerijus Armakavicius, Vallery Stanishev, Sean Knight, Mathias Schubert, Vanya Darakchieva

Department of Electrical and Computer Engineering: Faculty Publications

Mid-infrared optical Hall effect measurements are used to determine the free charge carrier parameters of an unintentionally doped wurtzite-structure c-plane oriented In_0.33Ga_0.67N epitaxial layer. Room temperature electron effective mass parameters of m_ ¼ ð0:20560:013Þm0 andm_k ¼ ð0:20460:016Þm0 for polarization perpendicular and parallel to the c-axis, respectively,were determined. The free electron concentration was obtained as (1.760.2)_1019 cm^-3. Within our uncertainty limits, we detect no anisotropy for the electron effective mass parameter and we estimate the upper limit of the possible effective mass anisotropy as 7%. We discuss the influence of conduction band nonparabolicity on …

H.264 Video Decoder Implemented On Fpgas Using 3×3 And 2×2 Networks-On-Chip, Ian Barge, Cristinel Ababei

Electrical and Computer Engineering Faculty Research and Publications

In this paper, we present the design and verification of the H.264 video decoder algorithm on FPGAs. The primary difference compared to previously reported designs is that the communication between the decoder modules is done via a network-on-chip in our case. The proposed design is a complete system level hardware design described in VHDL and Verilog. We report experimental results for two different implementations. The first implementation uses a 3×3 network-on-chip and is validated on the DE4 development board, which uses Altera's Stratix IV GX FPGA chip. The second implementation uses a 2×2 network-on-chip and is validated on the Cyclone …

Patent Keyword Extraction Algorithm Based On Distributed Representation For Patent Classification, Jie Hu, Shaobo Li, Yong Yao, Liya Yu, Guanci Yang, Jianjun Hu

Faculty Publications

Many text mining tasks such as text retrieval, text summarization, and text comparisons depend on the extraction of representative keywords from the main text. Most existing keyword extraction algorithms are based on discrete bag-of-words type of word representation of the text. In this paper, we propose a patent keyword extraction algorithm (PKEA) based on the distributed Skip-gram model for patent classification. We also develop a set of quantitative performance measures for keyword extraction evaluation based on information gain and cross-validation, based on Support Vector Machine (SVM) classification, which are valuable when human-annotated keywords are not available. We used a standard …

Condensation And Subsequent Freezing Delays As A Result Of Using Femtosecond Laser Functionalized Surfaces, Chongji Huang, Ryan Bell, Alfred Tsubaki, Craig Zuhlke, Dennis Alexander

Department of Electrical and Computer Engineering: Faculty Publications

In this paper, the authors report on the use of femtosecond laser surface processing (FLSP) to enhance the anti-icing properties of a commonly used aircraft alloy, Al 7075-O Clad. By changing the surface morphology through FLSP and the surface chemistry through siloxane vapor deposition, the wettability of Al 7075-O Clad was altered. Tall mound and short mound FLSP functionalized surfaces were created through two sets of laser parameters. Condensation and the subsequent freezing of condensates on FLSP Al 7075-O Clad was studied. Both structure height and surface wettability were shown to play a role in the delay of freezing. Freezing …

Unified Framework For Spam Detection And Risk Assessment In Short Message Communication Media, Sakariyah Adewole Kayode

Student Works (2010-2019)

Short message communication media (SMCM), such as mobile and microblogging social networks, have become essential part of many people daily routine. Despite the benefits offered by these communication media, they have become the popular platforms for distributing spam contents. Research in spam message and spam account detection in SMCM has received growing interests in the recent years, mainly focusing on introducing separate frameworks that can identify spam message or spam account. There are hundreds of published works related to spam message and spam account detection that aim to identify effective detection methods. While spam message and spam account studies have …

Internet Of Underground Things: Sensing And Communications On The Field For Precision Agriculture, Mehmet C. Vuran, Abdul Salam, Rigoberto Wong, Suat Irmak

School of Computing: Conference and Workshop Papers

The projected increases in World population and need for food have recently motivated adoption of information technology solutions in crop fields within precision agriculture approaches. Internet of underground things (IOUT), which consists of sensors and communication devices, partly or completely buried underground for real-time soil sensing and monitoring, emerge from this need. This new paradigm facilitates seamless integration of underground sensors, machinery, and irrigation systems with the complex social network of growers, agronomists, crop consultants, and advisors. In this paper, state-of-the-art communication architectures are reviewed, and underlying sensing technology and communication mechanisms for IOUT are presented. Recent advances in the …

Scheduling In Mapreduce Clusters, Chen He

School of Computing: Dissertations, Theses, and Student Research

MapReduce is a framework proposed by Google for processing huge amounts of data in a distributed environment. The simplicity of the programming model and the fault-tolerance feature of the framework make it very popular in Big Data processing.

As MapReduce clusters get popular, their scheduling becomes increasingly important. On one hand, many MapReduce applications have high performance requirements, for example, on response time and/or throughput. On the other hand, with the increasing size of MapReduce clusters, the energy-efficient scheduling of MapReduce clusters becomes inevitable. These scheduling challenges, however, have not been systematically studied.

The objective of this dissertation is to …

Collaborative Appearance-Based Place Recognition And Improving Place Recognition Using Detection Of Dynamic Objects, Juan Pablo Munoz

Dissertations, Theses, and Capstone Projects

This dissertation makes contributions to the problem of Long-Term Appearance-Based Place Recognition. We present a framework for place recognition in a collaborative scheme and a method to reduce the impact of dynamic objects on place representations. We demonstrate our findings using a state-of-the-art place recognition approach.

We begin in Part I by describing the general problem of place recognition and its importance in applications where accurate localization is crucial. We discuss feature detection and description and also explain the functioning of several place recognition frameworks.

In Part II, we present a novel framework for collaboration between agents from a pure …

Vision-Based Assistive Indoor Localization, Feng Hu

Dissertations, Theses, and Capstone Projects

An indoor localization system is of significant importance to the visually impaired in their daily lives by helping them localize themselves and further navigate an indoor environment. In this thesis, a vision-based indoor localization solution is proposed and studied with algorithms and their implementations by maximizing the usage of the visual information surrounding the users for an optimal localization from multiple stages. The contributions of the work include the following: (1) Novel combinations of a daily-used smart phone with a low-cost lens (GoPano) are used to provide an economic, portable, and robust indoor localization service for visually impaired people. (2) …

Artificial Intelligence(Ai) Application In Library Systems In Iran: A Taxonomy Study, Asefeh Asemi, Adeleh Asemi

Library Philosophy and Practice (e-journal)

With introducing and developing AI logic, this science as a branch of computer science could impact and improve all sciences which used computer systems. LIS also could get benefit from AI in many areas. This paper survey applications of AI in library and information science and introduce the potential of library system to apply AI techniques. Intelligent systems have contributed for many librarian purposes like cataloging, indexing, information retrieval, reference, and other purposes. We applied Exploratory Factor Analysis (EFA) as a primer method for identification of the most applicable AI techniques categories in LIS. ESs are the most usable intelligent …

Sparse Modeling-Based Sequential Ensemble Learning For Effective Outlier Detection In High-Dimensional Numeric Data, Guansong Pang, Longbing Cao, Ling Chen, Defu Lian, Huan Liu

Research Collection School Of Computing and Information Systems

The large proportion of irrelevant or noisy features in reallife high-dimensional data presents a significant challenge to subspace/feature selection-based high-dimensional outlier detection (a.k.a. outlier scoring) methods. These methods often perform the two dependent tasks: relevant feature subset search and outlier scoring independently, consequently retaining features/subspaces irrelevant to the scoring method and downgrading the detection performance. This paper introduces a novel sequential ensemble-based framework SEMSE and its instance CINFO to address this issue. SEMSE learns the sequential ensembles to mutually refine feature selection and outlier scoring by iterative sparse modeling with outlier scores as the pseudo target feature. CINFO instantiates SEMSE …

A Real-Time Wireless Sweat Rate Measurement System For Physical Activity Monitoring, Andrew Brueck, Tashfin Iftekhar, Alicja B. Stannard, Kumar Yelamarthi, Tolga Kaya

Exercise Science Faculty Publications

There has been significant research on the physiology of sweat in the past decade, with one of the main interests being the development of a real-time hydration monitor that utilizes sweat. The contents of sweat have been known for decades; sweat provides significant information on the physiological condition of the human body. However, it is important to know the sweat rate as well, as sweat rate alters the concentration of the sweat constituents, and ultimately affects the accuracy of hydration detection. Towards this goal, a calorimetric based flow-rate detection system was built and tested to determine sweat rate in real …

Electronically Tuned Phase Transition In Germanium Telluride (Gete) Cells For Memory And Rf Switch Applications, Dushyant Tomer, Ronald A. Coutu Jr.

Electrical and Computer Engineering Faculty Research and Publications

Germanium telluride (GeTe) is a phase change material that undergoes an amorphous to crystalline transition upon heating to ~ 200oC. This transition is reversible in nature and results in ~ six orders of magnitude difference in GeTe resistivity which makes it a suitable candidate for data storage and other functional devices. In this work, micro-size phase change test cells were fabricated by RF sputtering GeTe thin films onto silicon (Si) wafers and Si wafers coated with silicon dioxide (SiO2), silicon nitride (Si3N4), and alumina (Al2O3) films. Two different heating methods, conductive and electrical (i.e. Joule heating), were applied to induce …

Analytical Formulas For Mean Gain And Excess Noise Factor In Inas Avalanche Photodiodes, Erum Jamil, Majeed M. Hayat, Gordon A. Keeler

Electrical and Computer Engineering Faculty Research and Publications

It has been known that McIntyre's local multiplication theory for avalanche photodiodes (APDs) does not fully explain the experimental results for single-carrier InAs APDs, which exhibit excess noise factor values below 2. While it has been established that the inclusion of the dead-space effect in the nonlocal multiplication theory resolves this discrepancy, no closed-form formulas for the mean gain and excess noise factor have been specialized to InAs APDs in a nonlocal setting. Upon utilizing prior analytical formulation of single-carrier avalanche multiplication based on age-dependent branching theory in conjunction with nonlocal ionization coefficients and thresholds for InAs, closed-form solutions of …

Employing A User-Centered Design Process For Cybersecurity Awareness In The Power Grid, Jean C. Scholtz, Lyndsey Franklin, Aditya Ashok, Katya Leblanc, Christopher Bonebrake, Eric Andersen, Michael Cassiadoro

Journal of Human Performance in Extreme Environments

In this paper, we discuss the process we are using in the design and implementation of a tool to improve the situation awareness of cyberattacks in the power grid. We provide details of the steps we have taken to date and describe the steps that still need to be accomplished. The focus of this work is to provide situation awareness of the power grid to staff from different, non-overlapping roles in an electrical transmission organization in order to facilitate an understanding of a possible occurrence of a cyberattack. Our approach follows a user-centered design process and includes determining the types …

Analytical Approaches To Improve Accuracy In Solving The Protein Topology Problem, Kamal Al Nasr, Feras Yousef, Ruba Jebril, Christopher Jones

Computer Science Faculty Research

To take advantage of recent advances in genomics and proteomics it is critical that the three-dimensional physical structure of biological macromolecules be determined. Cryo-Electron Microscopy (cryo-EM) is a promising and improving method for obtaining this data, however resolution is often not sufficient to directly determine the atomic scale structure. Despite this, information for secondary structure locations is detectable. De novo modeling is a computational approach to modeling these macromolecular structures based on cryo-EM derived data. During de novo modeling a mapping between detected secondary structures and the underlying amino acid sequence must be identified. DP-TOSS (Dynamic Programming for determining the …

Silicon Compilation And Test For Dataflow Implementations In Gasp And Click, Swetha Mettala Gilla

Dissertations and Theses

Many modern computer systems are distributed over space. Well-known examples are the Internet of Things and IBM's TrueNorth for deep learning applications. At the Asynchronous Research Center (ARC) at Portland State University we build distributed hardware systems using self-timed computation and delay-insensitive communication. Where appropriate, self-timed hardware operations can reduce average and peak power, energy, latency, and electromagnetic interference. Alternatively, self-timed operations can increase throughput, tolerance to delay variations, scalability, and manufacturability.

The design of complex hardware systems requires design automation and support for test, debug, and product characterization.

This thesis focuses on design compilation and test support for dataflow …

A Hierarchical Feature Extraction Model For Multi-Label Mechanical Patent Classification, Jie Hu, Shaobo Li, Jianjun Hu, Guanci Yang

Faculty Publications

Various studies have focused on feature extraction methods for automatic patent classification in recent years. However, most of these approaches are based on the knowledge from experts in related domains. Here we propose a hierarchical feature extraction model (HFEM) for multi-label mechanical patent classification, which is able to capture both local features of phrases as well as global and temporal semantics. First, a n-gram feature extractor based on convolutional neural networks (CNNs) is designed to extract salient local lexical-level features. Next, a long dependency feature extraction model based on the bidirectional long–short-term memory (BiLSTM) neural network model is proposed to …

A Fast And Robust Extrinsic Calibration For Rgb-D Camera Networks, Po-Chang Su, Ju Shen, Wanxin Xu, Sen-Ching S. Cheung, Ying Luo

Electrical and Computer Engineering Faculty Publications

From object tracking to 3D reconstruction, RGB-Depth (RGB-D) camera networks play an increasingly important role in many vision and graphics applications. Practical applications often use sparsely-placed cameras to maximize visibility, while using as few cameras as possible to minimize cost. In general, it is challenging to calibrate sparse camera networks due to the lack of shared scene features across different camera views. In this paper, we propose a novel algorithm that can accurately and rapidly calibrate the geometric relationships across an arbitrary number of RGB-D cameras on a network. Our work has a number of novel features. First, to cope …