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2019

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Computer Engineering

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Full-Text Articles in Engineering

Fiber-Optic Temperature And Flow Sensory System And Methods, Ming Han, Guigen Liu, Weilin Hou, Qiwen Shen Dec 2019

Fiber-Optic Temperature And Flow Sensory System And Methods, Ming Han, Guigen Liu, Weilin Hou, Qiwen Shen

Faculty Publications from the Department of Electrical and Computer Engineering

A fiber optic sensor, a process for utilizing a fiber optic sensor, and a process for fabricating a fiber optic sensor are described, where a double-side-polished silicon pillar is attacked to an optical fiber tip and forms, a Fabry-Perot cavity. In an implementation, a fiber optic sensor in accordance with an examplary embodiment includes an optical fiber configured to be coupled to a light source and a spectrometer; and a single silicon layer or multiple silicon layers disposed on an end face of the optical fiber, where each of the silicon layer(s) defines a Fabry-Perot interferometer, and where the ...


Quantitative Metrics For Mutation Testing, Amani M. Ayad Dec 2019

Quantitative Metrics For Mutation Testing, Amani M. Ayad

Dissertations

Program mutation is the process of generating versions of a base program by applying elementary syntactic modifications; this technique has been used in program testing in a variety of applications, most notably to assess the quality of a test data set. A good test set will discover the difference between the original program and mutant except if the mutant is semantically equivalent to the original program, despite being syntactically distinct.

Equivalent mutants are a major nuisance in the practice of mutation testing, because they introduce a significant amount of bias and uncertainty in the analysis of test results; indeed, mutants ...


Generating Energy Data For Machine Learning With Recurrent Generative Adversarial Networks, Mohammad Navid Fekri, Ananda M. Ghosh, Katarina Grolinger Dec 2019

Generating Energy Data For Machine Learning With Recurrent Generative Adversarial Networks, Mohammad Navid Fekri, Ananda M. Ghosh, Katarina Grolinger

Electrical and Computer Engineering Publications

The smart grid employs computing and communication technologies to embed intelligence into the power grid and, consequently, make the grid more efficient. Machine learning (ML) has been applied for tasks that are important for smart grid operation including energy consumption and generation forecasting, anomaly detection, and state estimation. These ML solutions commonly require sufficient historical data; however, this data is often not readily available because of reasons such as data collection costs and concerns regarding security and privacy. This paper introduces a recurrent generative adversarial network (R-GAN) for generating realistic energy consumption data by learning from real data. Generativea adversarial ...


Interpretable Deep Neural Network For Cancer Survival Analysis By Integrating Genomic And Clinical Data, Jie Hao, Youngsoon Kim, Tejaswini Mallavarapu, Jung Hun Oh, Mingon Kang Dec 2019

Interpretable Deep Neural Network For Cancer Survival Analysis By Integrating Genomic And Clinical Data, Jie Hao, Youngsoon Kim, Tejaswini Mallavarapu, Jung Hun Oh, Mingon Kang

Computer Science Faculty Publications

Background: Understanding the complex biological mechanisms of cancer patient survival using genomic and clinical data is vital, not only to develop new treatments for patients, but also to improve survival prediction. However, highly nonlinear and high-dimension, low-sample size (HDLSS) data cause computational challenges to applying conventional survival analysis. Results: We propose a novel biologically interpretable pathway-based sparse deep neural network, named Cox-PASNet, which integrates high-dimensional gene expression data and clinical data on a simple neural network architecture for survival analysis. Cox-PASNet is biologically interpretable where nodes in the neural network correspond to biological genes and pathways, while capturing the nonlinear ...


Design And Implementation Of Anomaly Detections For User Authentication Framework, Iman Abu Sulayman Dec 2019

Design And Implementation Of Anomaly Detections For User Authentication Framework, Iman Abu Sulayman

Electronic Thesis and Dissertation Repository

Anomaly detection is quickly becoming a very significant tool for a variety of applications such as intrusion detection, fraud detection, fault detection, system health monitoring, and event detection in IoT devices. An application that lacks a strong implementation for anomaly detection is user trait modeling for user authentication purposes. User trait models expose up-to-date representation of the user so that changes in their interests, their learning progress or interactions with the system are noticed and interpreted. The reason behind the lack of adoption in user trait modeling arises from the need of a continuous flow of high-volume data, that is ...


Identifying Customer Churn In After-Market Operations Using Machine Learning Algorithms, Vitaly Briker, Richard Farrow, William Trevino, Brent Allen Dec 2019

Identifying Customer Churn In After-Market Operations Using Machine Learning Algorithms, Vitaly Briker, Richard Farrow, William Trevino, Brent Allen

SMU Data Science Review

This paper presents a comparative study on machine learning methods as they are applied to product associations, future purchase predictions, and predictions of customer churn in aftermarket operations. Association rules are used help to identify patterns across products and find correlations in customer purchase behaviour. Studying customer behaviour as it pertains to Recency, Frequency, and Monetary Value (RFM) helps inform customer segmentation and identifies customers with propensity to churn. Lastly, Flowserve’s customer purchase history enables the establishment of churn thresholds for each customer group and assists in constructing a model to predict future churners. The aim of this model ...


Analysis Of The Duration And Energy Consumption Of Aes Algorithms On A Contiki-Based Iot Device, Brandon Tsao Dec 2019

Analysis Of The Duration And Energy Consumption Of Aes Algorithms On A Contiki-Based Iot Device, Brandon Tsao

Computer Science and Engineering Master's Theses

With the growing prevalence of the Internet of Things, securing the sheer abundance of devices is critical. The current IoT and security landscapes lack empirical metrics on encryption algorithm implementations that are optimized for constrained devices, such as encryption/decryption duration and energy consumption. In this paper, we achieve two things. First, we survey for optimized implementations of symmetric encryption algorithms. Seconds, we study the performance of various symmetric encryption algorithms on a Contiki-based IoT device. This paper provides encryption and decryption durations and energy consumption results on three implementations of AES: TinyAES, B-Con’s AES, and Contiki’s own ...


Non-Trivial Off-Path Network Measurements Without Shared Side-Channel Resource Exhaustion, Geoffrey I. Alexander Dec 2019

Non-Trivial Off-Path Network Measurements Without Shared Side-Channel Resource Exhaustion, Geoffrey I. Alexander

Computer Science ETDs

Most traditional network measurement scans and attacks are carried out through the use of direct, on-path network packet transmission. This requires that a machine be on-path (i.e, involved in the packet transmission process) and as a result have direct access to the data packets being transmitted. This limits network scans and attacks to situations where access can be gained to an on-path machine. If, for example, a researcher wanted to measure the round trip time between two machines they did not have access to, traditional scans would be of little help as they require access to an on-path machine ...


Point Cloud Processing With Neural Networks, Stephanie Miller, Jiahao Li Dec 2019

Point Cloud Processing With Neural Networks, Stephanie Miller, Jiahao Li

All Computer Science and Engineering Research

In this project, we explore new techniques and architectures for applying deep neural networks when the input is point cloud data. We first consider applying convolutions on regular pixel and voxel grids, using polynomials of point coordinates and Fourier transforms to get a rich feature representation for all points mapped to the same pixel or voxel. We also apply these ideas to generalize the recently proposed "interpolated convolution", by learning continuous-space kernels as a combination of polynomial and Fourier basis kernels. Experiments on the ModelNet40 dataset demonstrate that our methods have superior performance over the baselines in 3D object recognition.


Cluster-Based Chained Transfer Learning For Energy Forecasting With Big Data, Yifang Tian Dec 2019

Cluster-Based Chained Transfer Learning For Energy Forecasting With Big Data, Yifang Tian

Electronic Thesis and Dissertation Repository

Smart meter popularity has resulted in the ability to collect big energy data and has created opportunities for large-scale energy forecasting. Machine Learning (ML) techniques commonly used for forecasting, such as neural networks, involve computationally intensive training typically with data from a single building/group to predict future consumption for that same building/group. With hundreds of thousands of smart meters, it becomes impractical or even infeasible to individually train a model for each meter. Consequently, this paper proposes Cluster-Based Chained Transfer Learning (CBCTL), an approach for building neural network-based models for many meters by taking advantage of already trained ...


Localized Dielectric Loss Heating In Dielectrophoresis Devices, Tae Joon Kwak, Imtiaz Hossen, Rashid Bashir, Woo-Jin Chang, Chung-Hoon Lee Dec 2019

Localized Dielectric Loss Heating In Dielectrophoresis Devices, Tae Joon Kwak, Imtiaz Hossen, Rashid Bashir, Woo-Jin Chang, Chung-Hoon Lee

Electrical and Computer Engineering Faculty Research and Publications

Temperature increases during dielectrophoresis (DEP) can affect the response of biological entities, and ignoring the effect can result in misleading analysis. The heating mechanism of a DEP device is typically considered to be the result of Joule heating and is overlooked without an appropriate analysis. Our experiment and analysis indicate that the heating mechanism is due to the dielectric loss (Debye relaxation). A temperature increase between interdigitated electrodes (IDEs) has been measured with an integrated micro temperature sensor between IDEs to be as high as 70 °C at 1.5 MHz with a 30 Vpp applied voltage to our ...


Using Machine Learning Classification Methods To Detect The Presence Of Heart Disease, Nestor Pereira Dec 2019

Using Machine Learning Classification Methods To Detect The Presence Of Heart Disease, Nestor Pereira

Dissertations

Cardiovascular disease (CVD) is the most common cause of death in Ireland, and probably, worldwide. According to the Health Service Executive (HSE) cardiovascular disease accounting for 36% of all deaths, and one important fact, 22% of premature deaths (under age 65) are from CVD.

Using data from the Heart Disease UCI Data Set (UCI Machine Learning), we use machine learning techniques to detect the presence or absence of heart disease in the patient according to 14 features provide for this dataset. The different results are compared based on accuracy performance, confusion matrix and area under the Receiver Operating Characteristics (ROC ...


Factor Analysis Of Mixed Data (Famd) And Multiple Linear Regression In R, Nestor Pereira Dec 2019

Factor Analysis Of Mixed Data (Famd) And Multiple Linear Regression In R, Nestor Pereira

Dissertations

In the previous projects, it has been worked to statistically analysis of the factors to impact the score of the subjects of Mathematics and Portuguese for several groups of the student from secondary school from Portugal.

In this project will be interested in finding a model, hypothetically multiple linear regression, to predict the final score, dependent variable G3, of the student according to some features divide into two groups. One group, analyses the features or predictors which impact in the final score more related to the performance of the students, means variables like study time or past failures. The second ...


A Wearable Mechatronic Device For Hand Tremor Monitoring And Suppression: Development And Evaluation, Yue Zhou Dec 2019

A Wearable Mechatronic Device For Hand Tremor Monitoring And Suppression: Development And Evaluation, Yue Zhou

Electronic Thesis and Dissertation Repository

Tremor, one of the most disabling symptoms of Parkinson's disease (PD), significantly affects the quality of life of the individuals who suffer from it. These people live with difficulties with fine motor tasks, such as eating and writing, and suffer from social embarrassment. Traditional medicines are often ineffective, and surgery is highly invasive and risky. The emergence of wearable technology facilitates an externally worn mechatronic tremor suppression device as a potential alternative approach for tremor management. However, no device has been developed for the suppression of finger tremor that has been validated on a human.

It has been reported ...


Amodal Instance Segmentation And Multi-Object Tracking With Deep Pixel Embedding, Yanfeng Liu Dec 2019

Amodal Instance Segmentation And Multi-Object Tracking With Deep Pixel Embedding, Yanfeng Liu

Theses, Dissertations, and Student Research from Electrical & Computer Engineering

This thesis extends upon the representational output of semantic instance segmentation by explicitly including both visible and occluded parts. A fully convolutional network is trained to produce consistent pixel-level embedding across two layers such that, when clustered, the results convey the full spatial extent and depth ordering of each instance. Results demonstrate that the network can accurately estimate complete masks in the presence of occlusion and outperform leading top-down bounding-box approaches.

The model is further extended to produce consistent pixel-level embeddings across two consecutive image frames from a video to simultaneously perform amodal instance segmentation and multi-object tracking. No post-processing ...


Hardware Implementation Of Assistive Technology Robot, Joycephine Li Dec 2019

Hardware Implementation Of Assistive Technology Robot, Joycephine Li

Publications and Research

SuperHERO is an on-going research project in Computer Engineering Technology department which involves upgrading Heathkit Education Robot (HERO) hardware circuits and features by using modern hardware devices and sensors. The current phase of the project will focus on upgrading the motor drive system hardware as well as implementation and testing of features such as mobile robot obstacle detection and other assistive technologies to help people with disabilities. This involves the reattachment of the robot arm after repairing and updating with 3D printing and using modern hardware and software technology. We observed that the robotic arm has rotary and translation movements ...


Hardware-Entangled Software Execution Using Dynamic Pufs, Wenjie Xiong Dec 2019

Hardware-Entangled Software Execution Using Dynamic Pufs, Wenjie Xiong

Yale Day of Data

Low-end computing devices are becoming increasingly ubiquitous, especially due to the widespread deployment of Internet-of-Things products. There is, however, much concern about sensitive data being processed on these low-end devices which have limited protection mechanisms in place. This paper proposes a Hardware-Entangled Software Protection (HESP) scheme that leverages hardware features to protect software code from malicious modification before or during run-time. It also enables implicit hardware authentication. Thus, the software will execute correctly only on an authorized device and if the timing of the software, e.g., control flow, was not changed through malicious modifications. The proposed ideas are based ...


Static Taint Analysis Of Binary Executables Using Architecture-Neutral Intermediate Representation, Elaine Cole Dec 2019

Static Taint Analysis Of Binary Executables Using Architecture-Neutral Intermediate Representation, Elaine Cole

All Computer Science and Engineering Research

Ghidra, National Security Agency’s powerful reverse engineering framework, was recently released open-source in April 2019 and is capable of lifting instructions from a wide variety of processor architectures into its own register transfer language called p-code. In this project, we present a new tool which leverages Ghidra’s specific architecture-neutral intermediate representation to construct a control flow graph modeling all program executions of a given binary and apply static taint analysis. This technique is capable of identifying the information flow of malicious input from untrusted sources that may interact with key sinks or parts of the system without needing ...


Aluminum/Carbon Composites Materials Fabricated By The Powder Metallurgy Process, Amélie Veillère, Hiroki Kurita, Akira Kawasaki, Yongfeng Lu, Jean-Marc Heintz, Jean-François Silvain Dec 2019

Aluminum/Carbon Composites Materials Fabricated By The Powder Metallurgy Process, Amélie Veillère, Hiroki Kurita, Akira Kawasaki, Yongfeng Lu, Jean-Marc Heintz, Jean-François Silvain

Faculty Publications from the Department of Electrical and Computer Engineering

Aluminum matrix composites reinforced with carbon fibers or diamond particles have been fabricated by a powder metallurgy process and characterized for thermal management applications. Al/C composite is a nonreactive system (absence of chemical reaction between the metallic matrix and the ceramic reinforcement) due to the presence of an alumina layer on the surface of the aluminum powder particles. In order to achieve fully dense materials and to enhance the thermo-mechanical properties of the Al/C composite materials, a semi-liquid method has been carried out with the addition of a small amount of Al-Si alloys in the Al matrix. Thermal ...


Advanced Security Analysis For Emergent Software Platforms, Mohannad Alhanahnah Dec 2019

Advanced Security Analysis For Emergent Software Platforms, Mohannad Alhanahnah

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

Emergent software ecosystems, boomed by the advent of smartphones and the Internet of Things (IoT) platforms, are perpetually sophisticated, deployed into highly dynamic environments, and facilitating interactions across heterogeneous domains. Accordingly, assessing the security thereof is a pressing need, yet requires high levels of scalability and reliability to handle the dynamism involved in such volatile ecosystems.

This dissertation seeks to enhance conventional security detection methods to cope with the emergent features of contemporary software ecosystems. In particular, it analyzes the security of Android and IoT ecosystems by developing rigorous vulnerability detection methods. A critical aspect of this work is the ...


Chapman Ambassador Tour Robot, Alexandra Lewandowski, Yanni Parissis, Khiry Carter, Hilary Lee Dec 2019

Chapman Ambassador Tour Robot, Alexandra Lewandowski, Yanni Parissis, Khiry Carter, Hilary Lee

Student Scholar Symposium Abstracts and Posters

Being a student ambassador improves a student's confidence and leadership skills. With an increasing demand for technology skills, our project will display how the ambassador robot can assist student ambassadors while improving upon their efficiency, by discussing information during college campus tours and familiarizing students with robot applications and their technology. The ambassador robot can support students during tours by answering a question about specific knowledge that may have slipped an ambassador's mind. The robot will also be able to create a group-focused atmosphere that will allow ambassadors to have the opportunity to lean on a dependable teammate ...


The Trolley Problem In Virtual Reality, Jungsu Pak, Ariane Guirguis, Nicholas Mirchandani, Scott Cummings, Uri Maoz Dec 2019

The Trolley Problem In Virtual Reality, Jungsu Pak, Ariane Guirguis, Nicholas Mirchandani, Scott Cummings, Uri Maoz

Student Scholar Symposium Abstracts and Posters

Would people react to the Trolley problem differently based on the medium? Immersive Virtual Reality Driving Simulator was used to examine participants respond to the trolley problem in a realistic and controlled simulated environment.


The Fog Development Kit: A Platform For The Development And Management Of Fog Systems, Colton Powell Dec 2019

The Fog Development Kit: A Platform For The Development And Management Of Fog Systems, Colton Powell

Computer Science and Engineering Master's Theses

With the rise of the Internet of Things (IoT), fog computing has emerged to help traditional cloud computing in meeting scalability demands. Fog computing makes it possible to fulfill real-time requirements of applications by bringing more processing, storage, and control power geographically closer to end-devices. How- ever, since fog computing is a relatively new field, there is no standard platform for research and development in a realistic environment, and this dramatically inhibits innovation and development of fog-based applications. In response to these challenges, we propose the Fog Development Kit (FDK). By providing high-level interfaces for allocating computing and networking resources ...


How Degrees Of Freedom Affects Sense Of Agency, Akima Connelly, Jungsu Pak, Tian Lan, Uri Maoz Dec 2019

How Degrees Of Freedom Affects Sense Of Agency, Akima Connelly, Jungsu Pak, Tian Lan, Uri Maoz

Student Scholar Symposium Abstracts and Posters

Can the rubber-hand illusion be extended to a moving robotic arm in different degrees of freedom (DOF), inducing sense of ownership & agency over the arm? We hypothesize that DOF closer to what humans possess will result in a stronger sense of ownership and agency.


Self-Driving Toy Car Using Deep Learning, Fahim Ahmed, Suleyman Turac, Mubtasem Ali Dec 2019

Self-Driving Toy Car Using Deep Learning, Fahim Ahmed, Suleyman Turac, Mubtasem Ali

Publications and Research

Our research focuses on building a student affordable platform for scale model self-driving cars. The goal of this project is to explore current developments of Open Source hardware and software to build a low-cost platform consisting of the car chassis/framework, sensors, and software for the autopilot. Our research will allow other students with low budget to enter into the world of Deep Learning, self-driving cars, and autonomous cars racing competitions.


International Space Object Orbit Tracker, Nicole Navarro Dec 2019

International Space Object Orbit Tracker, Nicole Navarro

Publications and Research

This software engineering project involves development of machine learning algorithms for embedded applications. High speed 32-bit hardware devices such as Raspberry Pi and ARM microcontrollers has become inexpensive and readily available. Machine learning algorithms for applications such as image processing and image recognition are computationally intensive. But with the availability of low cost 32-bit embedded computing devices, it is now feasible to implement then on embedded hardware. This project will explore embedded applications of machine learning algorithms by following a software engineering design and test approach.


Acute Toxicitystudy Of Choline Based Ionic Liquids Towards Danio Rerio Fish And The Aggregation Behavior Of Their Binary Mixtures, Mansoor Ul Hassan Shah, Nasruddin Nasruddin, Suzana Bt Yusup, Muhammad Moniruzzaman Dec 2019

Acute Toxicitystudy Of Choline Based Ionic Liquids Towards Danio Rerio Fish And The Aggregation Behavior Of Their Binary Mixtures, Mansoor Ul Hassan Shah, Nasruddin Nasruddin, Suzana Bt Yusup, Muhammad Moniruzzaman

Makara Journal of Technology

Marine oil spills are effectively controlled by chemical dispersants. However, the toxicity associated with it reduce its employment in marine environment. To overcome this limitation, the acute toxicity of choline based ionic liquids was evaluated as a potential low toxic variant for oil spill remediation. Further, the aggregation behavior of the individual as well as their binary mixtures was also evaluated by employing tensiometry technique. The half-lethal concentration, LC50on zebrafish (Danio rerio) of three choline based ionic liquids showed that the studied ionic liquids (ILs) fall in the range of “practically nontoxic” ( 100-1000 mg L-1).Various micellar properties showed that ...


Neutron Diffraction Study Of Multiferroic 0.6nife2o4/0.4batio3 Composite, Engkir Sukirman, Yosef Sarwanto, Syahfandi Ahda, Andon Insani Dec 2019

Neutron Diffraction Study Of Multiferroic 0.6nife2o4/0.4batio3 Composite, Engkir Sukirman, Yosef Sarwanto, Syahfandi Ahda, Andon Insani

Makara Journal of Technology

Neutron diffraction study on the 0.6NiFe2O4/0.4BaTiO3 multiferroic composite has been carried out. The 0.6NiFe2O4/0.4BaTiO3 multiferroic composites have been synthesized by solid reaction method. In this study, 20 g of BaTiO3 (BTO) and 20 g of NiFe2O4 (NFO) compounds were prepared from the powder raw materials of BaO3 and TiO2 for BTO, and NiO and Fe2O3 for NFO. Furthermore, both BTO and NFO were each crushed for 5 hours using High Energy Milling (HEM). Then the BTO and NFO were calcined in the furnace at 950 °C/5 hours and 900 °C/5 hours, respectively ...


Comprehensive Inspection On The Experimental Ferritic Stainless Steel By Means Of Transmission Electron Microscopy And Neutron Diffraction Techniques, Parikin Parikin, Mohammad Dani, Riza Iskandar, Aziz Khan Jahja, Andon Insani, Joachim Mayer Dec 2019

Comprehensive Inspection On The Experimental Ferritic Stainless Steel By Means Of Transmission Electron Microscopy And Neutron Diffraction Techniques, Parikin Parikin, Mohammad Dani, Riza Iskandar, Aziz Khan Jahja, Andon Insani, Joachim Mayer

Makara Journal of Technology

The field of physical metallurgy is one of the primary beacons that guide alloy developments for multipurpose materials such as the in-core structure materials for pressure vessel components and heat exchangers. The surface microstructure of new ferritic steel with significant local constituent materials was characterized by high resolution powder neutron diffractometer (HRPD) and transmission electron microscope (TEM), combined with the energy dispersive X-ray spectroscopy (EDX). The alloy contains73% Fe, 24% Cr, 2% Si, 0.8% Mn, and 0.1% Ni, in %wt. The charge materials were melted by the casting techniques. The neutron diffractograms obtained shows five dominant diffraction peaks ...


A New Synthesized Microalloys Steel Ods Of High Amplitude Ultrasonically Irradiation, Marzuki Silalahi, Hanif Abdurrahman Wicaksana, Ferhat Aziz, Syahfandi Ahda, Mohamad Riza Iskandar Dec 2019

A New Synthesized Microalloys Steel Ods Of High Amplitude Ultrasonically Irradiation, Marzuki Silalahi, Hanif Abdurrahman Wicaksana, Ferhat Aziz, Syahfandi Ahda, Mohamad Riza Iskandar

Makara Journal of Technology

Micropowders of oxide-dispersion-strengthened (ODS) steel have been synthesized using the ultrasonic irradiation method with variations in amplitude. The ultrasonic irradiation process is performed for 50 h at a frequency of 20 kHz with 40%, 50%, and 60% amplitudes in toluene solution. The formation of Fe-Cr microalloys in the preparation of Fe- 15Cr-0.5Y2O3 powder was analyzed using SEM-EDS, X-ray diffraction (XRD), and TEM-EDS. The percentage of Fe- Cr phase mass fraction of ODS steel micropowder formed during ultrasonic irradiation with 40%:50%:60% amplitude was 12.2%:34.1%:22.1%, with 25.67:77.02:38.51 nm crystallite ...