Computer Engineering Commons^™

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

Department of Electrical and Computer Engineering: Faculty Publications

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 conductivity and …

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.

Advanced Security Analysis For Emergent Software Platforms, Mohannad Alhanahnah

School of Computing: Dissertations, Theses, 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 …

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 access to …

Low-Cost Near Infrared Diffuse Optical Imaging System, Mohammed Z. Shakil, Chen Xu

Publications and Research

Diffuse Optical Tomography (DOT) and Optical Spectroscopy using near-infrared (NIR) diffused light has demonstrated great potential for the initial diagnosis of tumors and in the assessment of tumor vasculature response to neoadjuvant chemotherapy. The NIR technique utilizes intrinsic hemoglobin contrast, which is directly related to tumor angiogenesis development, a key process required for tumor growth and metastasis. The NIR diffuse tomography holds great promise in distinguishing early-stage invasive breast cancers from benign lesions. This technique also provides insight into tumor metabolism and tumor hypoxia, important indicators of tumor response to various forms of therapy. Currently, the high cost of the …

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.

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 for specific …

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, …

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.

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.

Voice Controlled Augmented Reality: A Comparison Of Speech-Recognition Tools For Ar Applications, Juan Estrella

Publications and Research

Augmented Reality (AR) refers to the technologies that enhance the version of the physical environment with computer-generated sensory input such as sound and graphics overlaid on top of the user’s view of the real world. Artificial Intelligence (AI) studies how to make computer programs and machines "smart" and take decisions. Our research project focuses on exploring the Integration of AI in AR applications. Specifically, on using Speech Recognition or Natural Language Processing for controlling virtual AR objects and enhancing the human-computer interaction. It is obvious that integration of AI and AR is of great value. However, for developers, it is …

Influence Of Nh4f In Dextran Based Biopolymer Electrolytes: Conductivity And Electrical Analysis, Muhamad Hafiz Hamsan, Mohd Fakhrul Zamani Kadir, Shujahadeen Bakar Aziz, Muhammad Amirul Solihin Azha, Saifful Kamaluddin Muzakir

Makara Journal of Technology

Dextran polymer host was doped with different concentrations of ammonium fluoride (NH4F) via casting technique. In this present work, dextran-NH4F film has been employed to investigate the ionic conductivity using electrochemical impedance spectroscopy from 50 to 5 MHz. The highest room temperature conductivity is achieved at (2.33 ± 0.76) × 10-3 S cm-1 with 40 wt.% NH4F. The electrolyte is found to obey Arrhenius rule at high temperature with activation energy of 0.21 eV. Dielectric analysis has been performed to obtain better understanding on the conductivity pattern. The dielectric parameters e.g. ɛreal, ɛimag, Mreal, and Mimag have been tested as …

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. Both NFO and BTO precursors were manually mixed …

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 at (110), …

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 size. The crystallite size at 50% amplitude was the largest, and the diffusion …

Study On Antibacterial Of Chitosan/Hydroxyapatite Doped Magnesium Composite As A Material For Bone Graft Applications, Andromeda Dwi Laksono, Teodoro A. Amatosa, Jr., Hilda Pebrianti Octaviana Sitorus, Wentika Putri Kusuma Asih, Sulistijono Sulistijono

Makara Journal of Technology

Hydroxyapatite (HAp) is one of the constituent minerals of bone and teeth, that has been widely used for synthesizing bone graft. Due to the limitation on properties of the hydroxyapatite, it is doping with Magnesium (HAp-Mg). The addition of Chitosan (Chi) was expected to improve the antibacterial properties of HAp-Mg. The present research aims to study the influence of Chitosan with 0, 5, 15, and 25 wt% addition on biocompatibility properties of Chi/HAp-Mg composite. HAp-Mg was synthesized using the sol-gel method; meanwhile, Chi/HAp-Mg composite was manufactured by mixing Chitosan in acetic acid, and HAp-Mg was added into the mixture. The …

Evaluation Of Primal-Dual Splitting Algorithm For Mri Reconstruction Using Spatio-Temporal Structure Tensor And L1-2 Norm, Mia Rizkinia, Masahiro Okuda

Makara Journal of Technology

Magnetic resonance imaging (MRI) is an essential medical imaging technique which is widely used for medical research and diagnosis. Dynamic MRI provides the observed object visualization through time and results in a spatiotemporal signal. The image sequences often contain redundant information in both spatial and temporal domains. To utilize this characteristic, we propose a spatio-temporal reconstruction approach based on compressive sensing theory. We apply spatio-temporal structure tensor using nuclear norm, in addition to the wavelet sparsity regularization. The spatio-temporal structure tensor is a matrix that consists of gradient components of the MRI data w.r.t the spatial and temporal domains. For …

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 …

An Approach To Fast Multi-Robot Exploration In Buildings With Inaccessible Spaces, Matt Mcneill, Damian Lyons

Faculty Publications

The rapid exploration of unknown environments is a common application of autonomous multi-robot teams. For some types of exploration missions, a mission designer may possess some rudimentary knowledge about the area to be explored. For example, the dimensions of a building may be known, but not its floor layout or the location of furniture and equipment inside. For this type of mission, the Space- Based Potential Field (SBPF) method is an approach to multirobot exploration which leverages a priori knowledge of area bounds to determine robot motion. Explored areas and obstacles exert a repulsive force, and unexplored areas exert an …

Image-Driven Automated End-To-End Testing For Mobile Applications, Caleb Fritz

Computer Science and Computer Engineering Undergraduate Honors Theses

The increasing complexity and demand of software systems and the greater availability of test automation software is quickly rendering manual end-to-end (E2E) testing techniques for mobile platforms obsolete. This research seeks to explore the potential increase in automated test efficacy and maintainability through the use of computer vision algorithms when applied with Appium, a leading cross-platform mobile test automation framework. A testing framework written in a Node.js environment was created to support the development of E2E test scripts that examine and report the functional capabilities of a mobile test app. The test framework provides a suite of functions that connect …

Multiple Face Detection And Recognition System Design Applying Deep Learning In Web Browsers Using Javascript, Cristhian Gabriel Espinosa Sandoval

Computer Science and Computer Engineering Undergraduate Honors Theses

Deep learning has advanced progressively in the last years and now demonstrates state-of-the-art performance in various fields. In the era of big data, transformation of data into valuable knowledge has become one of the most important challenges in computing. Therefore, we will review multiple algorithms for face recognition that have been researched for a long time and are maturely developed, and analyze deep learning, presenting examples of current research.

To provide a useful and comprehensive perspective, in this paper we categorize research by deep learning architecture, including neural networks, convolutional neural networks, depthwise Separable Convolutions, densely connected convolutional networks, and …

Neural Network Classification Of Brainwave Alpha Signalsin Cognitive Activities, Ahmad Azhari, Adhi Susanto, Andri Pranolo, Yingchi Mao

Knowledge Engineering and Data Science

The signal produced by human brain waves is one unique feature. Signals carry information and are represented in electrical signals generated from the brain in a typical waveform. Human brain wave activity will always be active even when sleeping. Brain waves will produce different characteristics in different individuals. Physical and behavioral characteristics can be identified from patterns of brain wave activity. This study aims to distinguish signals from each individual based on the characteristics of alpha signals from brain waves produced. Brain wave signals are generated by giving several mental perception tasks measured using an Electroencephalogram (EEG). To get different …

Optimisation Of Rice Fertiliser Composition Using Genetic Algorithms, Retno Dewi Anissa, Wayan Firdaus Mahmudy, Agus Wahyu Widodo

Knowledge Engineering and Data Science

There are so many problems with food scarcity. One of them is not too good rice quality. So, an enhancement in rice production through an optimal fertiliser composition. Genetic algorithm is used to optimise the composition for a more affordable price. The process of genetic algorithm is done by using a representation of a real code chromosome. The reproduction process using a one-cut point crossover and random mutation, while for the selection using binary tournament selection process for each chromosome. The test results showed the optimum results are obtained on the size of the population of 10, the crossover rate …

Image Classification Using Fuzzy Fca, Niruktha Roy Gotoor

School of Computing: Dissertations, Theses, and Student Research

Formal concept analysis (FCA) is a mathematical theory based on lattice and order theory used for data analysis and knowledge representation. It has been used in various domains such as data mining, machine learning, semantic web, Sciences, for the purpose of data analysis and Ontology over the last few decades. Various extensions of FCA are being researched to expand it's scope over more departments. In this thesis,we review the theory of Formal Concept Analysis (FCA) and its extension Fuzzy FCA. Many studies to use FCA in data mining and text learning have been pursued. We extend these studies to include …

Formal Modeling And Analysis Of A Family Of Surgical Robots, Niloofar Mansoor

School of Computing: Dissertations, Theses, and Student Research

Safety-critical applications often use dependability cases to validate that specified properties are invariant, or to demonstrate a counterexample showing how that property might be violated. However, most dependability cases are written with a single product in mind. At the same time, software product lines (families of related software products) have been studied with the goal of modeling variability and commonality and building family-based techniques for both modeling and analysis. This thesis presents a novel approach for building an end to end dependability case for a software product line, where a property is formally modeled, a counterexample is found and then …

Domain Adaptation In Unmanned Aerial Vehicles Landing Using Reinforcement Learning, Pedro Lucas Franca Albuquerque

School of Computing: Dissertations, Theses, and Student Research

Landing an unmanned aerial vehicle (UAV) on a moving platform is a challenging task that often requires exact models of the UAV dynamics, platform characteristics, and environmental conditions. In this thesis, we present and investigate three different machine learning approaches with varying levels of domain knowledge: dynamics randomization, universal policy with system identification, and reinforcement learning with no parameter variation. We first train the policies in simulation, then perform experiments both in simulation, making variations of the system dynamics with wind and friction coefficient, then perform experiments in a real robot system with wind variation. We initially expected that providing …

Android And Web Application For Tracking Employees, Kaival Dholakia

Electronic Theses, Projects, and Dissertations

The purpose that this tracking system serves is to keep track of the employees of the company who have the nature of their job which involves a lot of traveling to various locations on a day to day basis. It is an amalgamation of Android as well as a Web application. The employee is supposed to pass the location and image as per the terms and conditions specified to use the Android application. The web application is used by the admin department to access the information which would help them monitor the location of the employee in a timely manner. …

Second-Order Fault Tolerant Extended Kalman Filter For Discrete Time Nonlinear Systems, Xin Wang, Edwin E. Yaz

Electrical and Computer Engineering Faculty Research and Publications

As missing sensor data may severely degrade the overall system performance and stability, reliable state estimation is of great importance in modern data-intensive control, computing, and power systems applications. Aiming at providing a more robust and resilient state estimation technique, this paper presents a novel second-order fault-tolerant extended Kalman filter estimation framework for discrete-time stochastic nonlinear systems under sensor failures, bounded observer-gain perturbation, extraneous noise, and external disturbances condition. The failure mechanism of multiple sensors is assumed to be independent of each other with various malfunction rates. The proposed approach is a locally unbiased, minimum estimation error covariance based nonlinear …

Comparison And Design Optimization Of A Five-Phase Flux-Switching Pm Machine For In-Wheel Traction Applications, Hao Chen, Xiangdong Liu, Nabeel Demerdash, Ayman M. El-Refaie, Jing Zhao, Jiangbiao He

Electrical and Computer Engineering Faculty Research and Publications

A comparative study of five-phase outer-rotor flux-switching permanent magnet (FSPM) machines with different topologies for in-wheel traction applications is presented in this paper. Those topologies include double-layer winding, single-layer winding, C-core, and E-core configurations. The electromagnetic performance in the low-speed region, the flux-weakening capability in the high-speed region, and the fault-tolerance capability are all investigated in detail. The results indicate that the E-core FSPM machine has performance advantages. Furthermore, two kinds of E-core FSPM machines with different stator and rotor pole combinations are optimized, respectively. In order to reduce the computational burden during the large-scale optimization process, a mathematical technique …

Design And Development Of A Comprehensive And Interactive Diabetic Parameter Monitoring System - Betictrack, Nusrat Chowdhury

Electronic Theses and Dissertations

A novel, interactive Android app has been developed that monitors the health of type 2 diabetic patients in real-time, providing patients and their physicians with real-time feedback on all relevant parameters of diabetes. The app includes modules for recording carbohydrate intake and blood glucose; for reminding patients about the need to take medications on schedule; and for tracking physical activity, using movement data via Bluetooth from a pair of wearable insole devices. Two machine learning models were developed to detect seven physical activities: sitting, standing, walking, running, stair ascent, stair descent and use of elliptical trainers. The SVM and decision …