Computer Engineering Commons^™

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 …

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.

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 …

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 …

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.

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 …

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), …

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 …

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 …

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

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 …

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 …

Extending The Capabilities Of Von Neumann With A Dataflow Sub-Isa, Martin Cowley

Masters Theses

Instruction set architectures (ISAs) such as x86, ARM, and RISC-V follow the control flow model of computation, where a program is defined as a sequence of instructions. Early processors executed instructions one-by-one based on the control flow of a program. Dataflow is an alternative model of computation that uses the availability of data to drive instruction execution. Any instruction can be chosen for execution, independent of the instruction order, as long as the data is available for that instruction. While modern processors incorporate concepts of the dataflow model in the microarchitecture, the implementation of the ISA, the amount of instruction …

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 …

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 …

Bitcoin Price Prediction Using Neural Networks, Vladislav Killiakov

Electrical Engineering

In this project, I will investigate the performance of several major neural network architectures for the task of Bitcoin price prediction. Bitcoin is a cryptocurrency that is recently becoming increasingly more popular, and more widely adopted as a financial instrument. As a result, more efforts have been made in the past several years to model and predict its price. However, to this moment a large portion of work on Bitcoin price modeling was done using statistical or classical machine learning techniques. At the same time, other artificial intelligence based prediction techniques, and specifically neural networks, have not been explored to …

Introducing Digital Content To Kclc, Chad Briesacher

Theses

No abstract provided.

Reasoning From Point Clouds, Joey Wilson

Computer Engineering

Over the past two years, 3D object detection has been a major area of focus across industry and academia. This is primarily due to the difficulty of learning data from point clouds. While camera images are fixed size and can therefore be easily trained on using convolution, point clouds are unstructured series of points in three dimensions. Therefore, there is no fixed number of features, or a structure to run convolution on. Instead, researchers have developed many ways of attempting to learn from this data, however there is no clear consensus on what is the best method, as each has …

Mobile Robot Platform, Sukhman S. Marok

Electrical Engineering

The Mobile Robot Platform is a research and development tool designed for researchers working in the field of robotics. The cost of existing mobile robot platforms can easily be in the thousands of dollars, leading many researchers to choose between spending the time to create their own platform or buying an expensive pre-existing solution. The Mobile Robot Platform proposed combines pre-existing open source software and hardware solutions, along with a strong mechanical base that is capable of navigating on flat surfaces. The robot is designed to have many of the necessary components needed for teleoperation as well as autonomous navigation. …

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 …

Handwriting Character Recognition Usingvector Quantization Technique, Haviluddin Haviluddin, Rayner Alfred, Ni’Mah Moham, Herman Santoso Pakpahan, Islamiyah Islamiyah, Hario Jati Setyadi

Knowledge Engineering and Data Science

This paper seeks to explore Learning Vector Quantization (LVQ) processing stage to recognize The Buginese Lontara script from Makassar as well as explaining its accuracy. The testing results of LVQ obtained an accuracy degree of 66.66 %. The most optimal variant of network architecture in the recognition process is a variation of learning rate of 0.02, a maximum epoch of 5000 and a hidden layer of 90 neurons which was the result of recognition based on feature 8. Based on these variations, the obtained performance with a mean square error (MSE) of 0.0306 and the time required during the learning …

Comparison Of Indonesian Imports Forecastingby Limited Period Using Sarima Method, Harits Ar Rosyid, Mutyara Whening Aniendya, Heru Wahyu Herwanto

Knowledge Engineering and Data Science

The development of Indonesia's imports fluctuate over years. Inability to anticipate such rapid changes can cause economic slump due to inappropriate policy. For instance, recent years imports in rice led to the extermination of rice reserves. The reason is to maintain the market price of rice in Indonesia. To overcome these changes, forecasting the amount of imports should assist the Government in determining the optimum policy. This can be done by utilizing an algorithm to forecast time series data, in this case the amount of imports in the next few months with a high degree of accuracy. This study uses …

Resource Allocation And Task Scheduling Optimization In Cloud-Based Content Delivery Networks With Edge Computing, Yang Peng

Operations Research and Engineering Management Theses and Dissertations

The extensive growth in adoption of mobile devices pushes global Internet protocol (IP) traffic to grow and content delivery network (CDN) will carry 72 percent of total Internet traffic by 2022, up from 56 percent in 2017. In this praxis, Interconnected Cache Edge (ICE) based on different public cloud infrastructures with multiple edge computing sites is considered to help CDN service providers (SPs) to maximize their operational profit. The problem of resource allocation and performance optimization is studied in order to maximize the cache hit ratio with available CDN capacity.

The considered problem is formulated as a multi-stage stochastic linear …

Involuntary Signal-Based Grounding Of Civilian Unmanned Aerial Systems (Uas) In Civilian Airspace, Keith Conley

Master's Theses

This thesis investigates the involuntary signal-based grounding of civilian unmanned aerial systems (UAS) in unauthorized air spaces. The technique proposed here will forcibly land unauthorized UAS in a given area in such a way that the UAS will not be harmed, and the pilot cannot stop the landing. The technique will not involuntarily ground authorized drones which will be determined prior to the landing. Unauthorized airspaces include military bases, university campuses, areas affected by a natural disaster, and stadiums for public events. This thesis proposes an early prototype of a hardware-based signal based involuntary grounding technique to handle the problem …

Mitigating Pilot Contamination Through Optimizing Pilot Allocation In Massive Mimo Systems, Rand Abdul Hussain

Theses and Dissertations

This dissertation has proposed several algorithms to optimize the allocation of pilots to the users’ equipment (UEs) to mitigate the effect of the pilot contamination problem in the massive MIMO systems. Pilot contamination reduces the performance of massive MIMO systems due to the reduction in the quality of the estimated channel between a UE and the serving base station (BS). The limitation of the number of samples in a coherence block limits the number of unique mutually orthogonal pilots, and hence, reusing the set of pilots across the cells causes inter-cell interference during pilot transmission, which is called pilot contamination. …