Computer Sciences Commons^™

Smart Augmented Reality Instructional System For Mechanical Assembly, Ze-Hao Lai

Masters Theses

"Quality and efficiency are pivotal indicators of a manufacturing company. Many companies are suffering from shortage of experienced workers across the production line to perform complex assembly tasks such as assembly of an aircraft engine. This could lead to a significant financial loss. In order to further reduce time and error in an assembly, a smart system consisting of multi-modal Augmented Reality (AR) instructions with the support of a deep learning network for tool detection is introduced. The multi-modal smart AR is designed to provide on-site information including various visual renderings with a fine-tuned Region-based Convolutional Neural Network, which is …

Machine Learning Techniques Implementation In Power Optimization, Data Processing, And Bio-Medical Applications, Khalid Khairullah Mezied Al-Jabery

Doctoral Dissertations

"The rapid progress and development in machine-learning algorithms becomes a key factor in determining the future of humanity. These algorithms and techniques were utilized to solve a wide spectrum of problems extended from data mining and knowledge discovery to unsupervised learning and optimization. This dissertation consists of two study areas. The first area investigates the use of reinforcement learning and adaptive critic design algorithms in the field of power grid control. The second area in this dissertation, consisting of three papers, focuses on developing and applying clustering algorithms on biomedical data. The first paper presents a novel modelling approach for …

Perceptions Of Female Cybersecurity Professionals Toward Factors That Encourage Females To The Cybersecurity Field, Kembley Kay Lingelbach

CCAC Theses and Dissertations

Despite multiple national, educational, and industry initiatives, women continue to be underrepresented in the cybersecurity field. Only 11% of cybersecurity professionals, globally, are female. This contributes to the growing overall shortage of workers in the field. This research addressed the significant underrepresentation of females in the cybersecurity workforce. There are many practitioner and industry studies that suggest self-efficacy, discrimination and organizational culture play important roles in the low rate of women in the cybersecurity field. A limited number of scholarly studies identify causal factors; however, there is not a general consensus or framework to explain the problem thoroughly. Moreover, there …

Exploring Generational Differences In Text Messaging Usage And Habits, Daniel Wayne Long

CCAC Theses and Dissertations

Members of society today embrace multiple communication media for various purposes and intents. Text messaging has been identified as the medium of choice for continual relationship maintenance and text messaging from mobile devices overshadows all other media forms for the support of social connections. Text messaging is changing everything from how operators market their plans to how advertisers and service providers reach consumers. But just as technology usage of social media and internet access are different across generational boundaries, text messaging usage and habits may also be different for various generational groups. The majority of peer-reviewed research regarding text messaging …

Application Of Acoustic Emission And Machine Learning To Detect Codling Moth Infested Apples, Mengxing Li, Nader Ekramirad, Ahmed Rady, Akinbode A. Adedeji

Biosystems and Agricultural Engineering Faculty Publications

Incidence of codling moth (CM) (Cydia pomonella L.) infestation in apples has been a major concern in North America for decades. CM larvae bore deep into the fruit, making it unmarketable. An effective noninvasive method to detect larvae-infested apples is necessary to ensure that apples are CM-free in post-harvest processing. In this study, a novel approach using an acoustic emission (AE) system and subsequent machine learning methods was applied to classify larvae-infested apples from intact apples. 'GoldRush‘ apples were infested with CM neonates and stored at the same conditions as intact apples. The AE system was used to collect …

A Stochastic Petri Net Reverse Engineering Methodology For Deep Understanding Of Technical Documents, Giorgia Rematska

Browse all Theses and Dissertations

Systems Reverse Engineering has gained great attention over time and is associated with numerous different research areas. The importance of this research derives from several technological necessities. Security analysis and learning purposes are two of them and can greatly benefit from reverse engineering. More specifically, reverse engineering of technical documents for deeper automatic understanding is a research area where reverse engineering can contribute a lot. In this PhD dissertation we develop a novel reverse engineering methodology for deep understanding of architectural description of digital hardware systems that appear in technical documents. Initially, we offer a survey on reverse engineering of …

Building An Abstract-Syntax-Tree-Oriented Symbolic Execution Engine For Php Programs, Jin Huang

Browse all Theses and Dissertations

This thesis presents the design, implementation, and evaluation of an abstract-syntax-tree-oriented symbolic execution engine for the PHP programming language. As a symbolic execution engine, our system emulate the execution of a PHP program by assuming that all inputs are with symbolic rather than concrete values. While our system inherits the basic definition of symbolic execution, it fundamentally differs from existing symbolic execution implementations that mainly leverage intermediate representation (IRs) to operate. Specifically, our system directly takes the abstract syntax tree (AST) of a program as input and subsequently interprets this AST. Performing symbolic execution using AST offers unique advantages. First, …

Slim Embedding Layers For Recurrent Neural Language Models, Zhongliang Li

Browse all Theses and Dissertations

Recurrent neural language (RNN) models are the state-of-the-art method for language modeling. When the vocabulary size is large, the space taken to store the model parameters becomes the bottleneck for the use of these type of models. We introduce a simple space compression method that stochastically shares the structured parameters at both the input and output embedding layers of RNN models to significantly reduce the size of model parameters, but still compactly represents the original input and the output embedding layers. The method is easy to implement and tune. Experiments on several data sets show that the new method achieves …

New Dimensions For A Challenging Security Environment: Growing Exposure To Critical Space Infrastructure Disruption Risk, Adrian V. Gheorghe, Alexandru Georgescu, Olga Bucovetchi, Marilena Lazăr, Cezar Scarlat

Engineering Management & Systems Engineering Faculty Publications

Space systems have become a key enabler for a wide variety of applications that are vital to the functioning of advanced societies. The trend is one of quantitative and qualitative increase of this dependence, so much so that space systems have been described as a new example of critical infrastructure. This article argues that the existence of critical space infrastructures implies the emergence of a new category of disasters related to disruption risks. We inventory those risks and make policy recommendations for what is, ultimately, a resilience governance issue.

Automated Tree-Level Forest Quantification Using Airborne Lidar, Hamid Hamraz

Theses and Dissertations--Computer Science

Traditional forest management relies on a small field sample and interpretation of aerial photography that not only are costly to execute but also yield inaccurate estimates of the entire forest in question. Airborne light detection and ranging (LiDAR) is a remote sensing technology that records point clouds representing the 3D structure of a forest canopy and the terrain underneath. We present a method for segmenting individual trees from the LiDAR point clouds without making prior assumptions about tree crown shapes and sizes. We then present a method that vertically stratifies the point cloud to an overstory and multiple understory tree …

Analysis Of High Performance Scientific Programming Workflows, Withana Kankanamalage Umayanganie Klaassen

Open Access Theses & Dissertations

Substantial time is spent on building, optimizing and maintaining large-scale software that is run on supercomputers. However, little has been done to utilize overall resources efficiently when it comes to including expensive human resources. The community is beginning to acknowledge that optimizing the hardware performance such as speed and memory bottlenecks contributes less to the overall productivity than does the development lifecycle of high-performance scientific applications. Researchers are beginning to look at overall scientific workflows for high performance computing. Scientific programming productivity is measured by time and effort required to develop, configure, and maintain a simulation experiment and its constituent …

Automated Optical Mark Recognition Scoring System For Multiple-Choice Questions, Murtadha Alomran

Theses: Doctorates and Masters

Multiple-choice questions are one of the questions commonly used in assessments. It is widely used because this type of examination can be an effective and reliable way to examine the level of student’s knowledge. So far, this type of examination can either be marked by hand or with specialised answer sheets and scanning equipment. There are specialised answer sheets and scanning equipment to mark multiple-choice questions automatically. However, these are expensive, specialised and restrictive answer sheets and optical mark recognition scanners.

This research aims to design and implement a multiple-choice answer sheet and a reliable image processing-based scoring system that …

Hardware Implementation And Comparison Of Displacement Retrieval Algorithms For A Laser Diode-Based Optical Feedback Interferometric Sensor, Ghazi Rehman, Usman Zabit, Muhammad Obaid Ullah

Turkish Journal of Electrical Engineering and Computer Sciences

Optical feedback interferometer (OFI) lasers, also called self-mixing (SM) lasers, have been widely explored over the last couple of decades due to their low cost, compactness, and self-aligned nature and they provide a very good solution for measurements of displacement, vibration, distance, velocity, etc. The SM effect takes place when a part of the laser beam is fed back to the active laser cavity after reflecting from the target. The reflected beam interferes with the emitted beam and hence the optical and spectral characteristics of the laser get changed. To retrieve the vibration or displacement signal of the target from …

Field-Verified Integrated Eaf-Svc-Electrode Positioning Model Simulation And Anovel Hybrid Series Compensation Control For Eaf, Ahmed Hassan, Amr Abou-Ghazala, Ashraf Megahed

Turkish Journal of Electrical Engineering and Computer Sciences

In this paper, modeling and simulation of a typical steel-making network are realized using MATLAB Simulink environment and validated using trends collected from an actual steel plant. The models integrate different reactions between an electric arc furnace (EAF), a static Var compensator, and electrode positioning systems according to a previously introduced theory of operations. In addition, the conventional electrode positioning control performance is compared with the new hybrid series compensation control method to demonstrate the superiority of the new method regarding system response. With help of the proposed series compensation, the reference resistance value was restored 2.5 s faster than …

A Novel Efficient Tsv Built-In Test For Stacked 3d Ics, Badi Guibane, Belgacem Hamdi, Brahim Ben Salem, Abdellatif Mtibaa

Turkish Journal of Electrical Engineering and Computer Sciences

A through-silicon via (TSV) is established as the main enabler for a three-dimensional integrated circuit (3D IC) that increases system density and compactness. The exponential increase in TSV density led to TSV-induced catastrophic and parametric faults. We propose an original architecture that detects errors caused by TSV manufacturing defects. The proposed design for testability is a built-in technique that detects errors in an early manufacturing stage and is hence very economically attractive. The proposal is capable of testing each and every TSV in the network. The technique achieves high fault coverage and high observability.

“Woodlands” - A Virtual Reality Serious Game Supporting Learning Of Practical Road Safety Skills., Krzysztof Szczurowski, Matt Smith

Conference Papers

In developed societies road safety skills are taught early and often practiced under the supervision of a parent, providing children with a combination of theoretical and practical knowledge. At some point children will attempt to cross a road unsupervised, at that point in time their safety depends on the effectiveness of their road safety education. To date, various attempts to supplement road safety education with technology were made. Most common approach focus on addressing declarative knowledge, by delivering road safety theory in an engaging fashion. Apart from expanding on text based resources to include instructional videos and animations, some stakeholders …

Applying Machine Learning To Advance Cyber Security: Network Based Intrusion Detection Systems, Hassan Hadi Latheeth Al-Maksousy

Computer Science Theses & Dissertations

Many new devices, such as phones and tablets as well as traditional computer systems, rely on wireless connections to the Internet and are susceptible to attacks. Two important types of attacks are the use of malware and exploiting Internet protocol vulnerabilities in devices and network systems. These attacks form a threat on many levels and therefore any approach to dealing with these nefarious attacks will take several methods to counter. In this research, we utilize machine learning to detect and classify malware, visualize, detect and classify worms, as well as detect deauthentication attacks, a form of Denial of Service (DoS). …

Fast Identification Of High Utility Itemsets From Candidates, Jun-Feng Qu, Mengchi Liu, Chunsheng Xin, Zhongbo Wu

Electrical & Computer Engineering Faculty Publications

High utility itemsets (HUIs) are sets of items with high utility, like profit, in a database. Efficient mining of high utility itemsets is an important problem in the data mining area. Many mining algorithms adopt a two-phase framework. They first generate a set of candidate itemsets by roughly overestimating the utilities of all itemsets in a database, and subsequently compute the exact utility of each candidate to identify HUIs. Therefore, the major costs in these algorithms come from candidate generation and utility computation. Previous works mainly focus on how to reduce the number of candidates, without dedicating much attention to …

User-Friendly Deniable Storage For Mobile Devices, Bing Chang, Yao Cheng, Bo Chen, Fengwei Zhang, Wen-Tao Zhu, Yanju Liu, Zhan Wang

Research Collection School Of Computing and Information Systems

Mobile devices are prevalently used to process sensitive data, but traditional encryption may not work when an adversary is able to coerce the device owners to disclose the encryption keys. Plausibly Deniable Encryption (PDE) is thus designed to protect sensitive data against this powerful adversary. In this paper, we present MobiPluto, a user-friendly PDE scheme for denying the existence of sensitive data stored on mobile devices. A salient difference between MobiPluto and the existing PDE systems is that any block-based file systems can be deployed on top of it. To further improve usability and deniability of MobiPluto, we introduce a …

การปรับปรุงการแยกฉากหลังบนพื้นหลังสีเขียวไม่สม่ำเสมอแบบทันที, วรายุ จริยาวัฒนรัตน์

Chulalongkorn University Theses and Dissertations (Chula ETD)

วัตถุประสงค์หลักของงานวิจัยนี้คือปรับปรุงการแยกฉากหลังบนพื้นหลังสีเขียวที่ไม่สม่ำเสมอแบบทันที ในวิธีการพื้นฐาน แต่ละพิกเซลจะถูกคำนวณว่าเป็นฉากหลังโดยใช้ค่าขีดจำกัดเดียวกันทั้งภาพเพียง 2 ค่า แต่ในความเป็นจริง วิธีการนี้มีปัญหาในหลาย ๆ กรณี เช่น พื้นหลังไม่ได้เป็นสีเดียวกันทั้งหมด หรือมีเงาของนักแสดงทอดลงไปที่พื้นหลัง เป็นต้น ดังนั้นการใช้ค่าขีดจำกัดเดียวกันหมดทั้งภาพจึงไม่เหมาะสมสำหรับกรณีดังกล่าว งานวิจัยนี้จึงใช้การประมาณความหนาแน่นเคอร์เนลมาช่วยในการหาค่าขีดจำกัดของแต่ละพิกเซลในภาพ เพื่อให้ทุก ๆ พิกเซลในภาพมีขีดจำกัดที่เหมาะสม และยังมีความเร็วในการประมวลผลที่สามารถออกอากาศสดได้ที่ 60 เฟรมต่อวินาที สำหรับความละเอียดระดับ Full HD

ระบบนำทางหุ่นยนต์ด้วยหลายตัวนำทางย่อยและหลายแผนที่ย่อย, สุขุม สัตตรัตนามัย

Chulalongkorn University Theses and Dissertations (Chula ETD)

การใช้งานหุ่นยนต์อัตโนมัติในเขตเมืองที่มีความหลากหลายของลักษณะพื้นที่สูงเป็นงานท้าทายที่ต้องการโปรแกรมนำทางและรูปแบบแผนที่ที่แตกต่างกันในแต่ละบริเวณ การปฏิบัติงานของหุ่นยนต์ในโลกจริงต้องเจอกับสิ่งแวดล้อมที่มีการเปลี่ยนแปลงอย่างต่อเนื่อง เช่น ฝนตกหรือความคับคั่งของบริเวณที่ต้องนำทาง ส่งผลให้ต้องปรับแผนเส้นทาง ในงานวิจัยนี้นำเสนอระบบนำทางหุ่นยนต์ในโลกจริงซึ่งเป็นรูปแบบใหม่ของการสลับการทำงานระหว่างโปรแกรมนำทางหลายตัวอย่างเหมาะสม เพื่อให้สามารถจัดการกับพฤติกรรมของหุ่นยนต์และสภาพแวดล้อมที่ท้าทายได้ ระบบที่นำเสนอในงานวิจัยนี้เป็นผลลัพธ์ของการติดตั้งหุ่นยนต์จริงในระบบซึ่งมีผู้ใช้งานและสภาพแวดล้อมจริง

Knowing When Not To Answer: Positional Peptide Sequencing With Encoder-Decoder Networks, Korrawe Karunratanakul

Chulalongkorn University Theses and Dissertations (Chula ETD)

การถอดรหัสเปปไทด์นั้นเป็นองค์ประกอบสำคัญสำหรับการศึกษาโปรตีน โดยทั่วไปแล้วการวิเคราะห์ข้อมูล mass spectrum นั้นจะศึกษาเพียงสายของกรดอะมิโนที่ปรากฏอยู่ในฐานข้อมูลเท่านั้น ทำให้การค้นหาสายเปปไทด์แบบใหม่ที่อาจเกิดจากการกลายพันธุ์นั้นทำได้ยาก วิถีการถอดรหัสด้วยดีโนโวแก้ไขข้อจำกัดนี้ด้วยการถอดรหัสสายเปปไทด์โดยตรงจากข้อมูล mass spectrum โดยใช้ความรู้เกี่ยวกับกระบวนการแตกตัวของไอออน ทำให้ไม่จำเป็นต้องใช้ฐานข้อมูลโปรตีนช่วย อย่างไรก็ดี วิธีดังกล่าวยังมีข้อจำกัดด้านความแม่นยำและต้องการการตรวจทานโดยผู้เชี่ยวชาญ วิทยานิพนธ์ฉบับนี้นำเสนอวิธีการถอดรหัสเปปไทด์ด้วยวิธีการดีโนโวแบบใหม่ชื่อ SMSNet โดยใช้โมเดล deep learning เข้าช่วย โดยยังสามารถทำนายกรดอะมิโนได้อย่างครอบคลุมในระดับความแม่นยำของกรดอะมิโนที่ 95% งานฉบับนี้เสนอขั้นตอน ถอดรหัส ตัดออก และสืบค้น เพื่อตัดผลทำนายในตำแหน่งที่มีความกำกวมออกและใช้ข้อมูลจากฐานข้อมูลโปรตีนช่วยเพื่อให้ทำนายสายเปปไทด์ได้ถูกต้องทั้งเส้น นอกจากนี้ งานนี้ได้นำเสนอการใช้ rescorer ในการแก้ไขคะแนนความมั่นใจสำหรับผลทำนายในแต่ละตำแหน่ง ซึ่งส่งผลให้สามารถแยกกลุ่มคะแนนความมั่นใจสำหรับคำตอบที่ถูกต้องและคำตอบที่ผิดได้ดียิ่งขึ้น เมื่อประกอบทุกขั้นตอนวิธีในงานวิจัยฉบับนี้เข้าด้วยกันพบว่า SMSNet สามารถทำนายสายเปปไทด์ได้ในประสิทธิภาพที่ใกล้เคียงกับการทำนายด้วยฐานข้อมูลในการทดลองจริง

An Autonomous Intelligent Robotic Wheelchair To Assist People In Need: Standing-Up, Turning-Around And Sitting-Down, Iosif Papadakis Ktistakis

Browse all Theses and Dissertations

The world’s ageing population has significantly increased over the last decades, which will result in one of the most significant transformations of the twenty-first century. As people age, they become more vulnerable to diseases and their health may need constant monitoring. At the same time, the number of people who have some kind of disability is also increasing. These people with disabilities may need daily assistance and monitoring of their health condition that is provided by specialists (health providers) at a high cost. A possible solution to the aforementioned problem comes from the assistive and intelligent robotics research area. The …

Interactive Visualization Of Search Results Of Large Document Sets, James D. Anderson

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When presented with many search results, finding information or patterns within the data poses a challenge. This thesis presents the design, implementation and evaluation of a visualization enabling users to browse through voluminous information and comprehend the data. Implemented with the JavaScript library Data Driven Documents (D3), the visualization represents the search as clusters of similar documents grouped into bubbles with the contents depicted as word-clouds. Highly interactive features such as touch gestures and intuitive menu actions allow for expeditious exploration of the search results. Other features include drag-and-drop functionality for articles among bubbles, merging nodes, and refining the search …

Overwhelming The Saa System Of Delivery Uavs By Drone Swarming, Barry Lynn Pfaff

Browse all Theses and Dissertations

As the Internet continues to replace the brick-and-mortar store as the main place for purchasing goods, web-based companies are looking for ways to reduce the cost of delivering those goods. The use of Unmanned Aerial Vehicles, or UAVs, is one delivery method that is increasingly being used. These UAVs can be programmed with delivery routes and destinations and can complete the job while requiring limited intervention from human controllers. Sense and Avoidance (SAA) systems have recently been incorporated into these UAVs so that they can detect objects in their flight path, reroute the UAV accordingly and operate even more autonomously. …

Fully Transparent Computer Vision Framework For Ship Detection And Tracking In Satellite Imagery, Jason T. Gottweis

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Tracking of ships in satellite imagery is a challenging problem in remote sensing since it requires both object detection and object recognition. Most of the resources available only cover one of these problems and are often filled with machine learning techniques which are costly to train. Additionally, the techniques covered in these resources are often difficult to replicate or may be hard to combine with other solutions to get a full tracking algorithm. The proposed framework offers a transparent and efficient alternative to machine learning approaches and includes preprocessing, detection, and recognition needed for tracking. All components of the framework …

Augment The Multi-Modal Interaction Capabilities Of Hololens Through Networked Sensory Devices, Subhadra Tummalapally

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Augmented Reality (AR) places virtual contents along with real objects to enhance user perception in the physical environment. It is a technology that has shown great potential in many industries such as medicine, education and transportation. AR devices, such as Microsoft HoloLens, come with multi-modal interaction capabilities, such as voice, gesture and gaze, to support intuitive and reliable human-computer interactions. However, HoloLens gesture support is limited to simple gestures like tap, bloom and hold, it stops short to support meaningful interaction through full hand gesture and motion tracking, which may be critical in field operations of various industry practices in …

Identification Of Streptococcus Pyogenes Using Raman Spectroscopy, Ehsan Majidi

Wayne State University Dissertations

Despite the attention that Raman Spectroscopy has gained recently in the area of pathogen identification, the spectra analyses techniques are not well developed. In most scenarios, they rely on expert intervention to detect and assign the peaks of the spectra to specific molecular vibration. Although some investigators have used machine-learning techniques to classify pathogens, these studies are usually limited to a specific application, and the generalization of these techniques is not clear. Also, a wide range of algorithms have been developed for classification problems, however, there is less insight to applying such methods on Raman spectra. Furthermore, analyzing the Raman …

Dragline Excavation Simulation, Real-Time Terrain Recognition And Object Detection, Godfred Somua-Gyimah

Doctoral Dissertations

"The contribution of coal to global energy is expected to remain above 30% through 2030. Draglines are the preferred excavation equipment in most surface coal mines. Recently, studies toward dragline excavation efficiency have focused on two specific areas. The first area is dragline bucket studies, where the goal is to develop new designs which perform better than conventional buckets. Drawbacks in the current approach include operator inconsistencies and the inability to physically test every proposed design. Previous simulation models used Distinct Element Methods (DEM) but they over-predict excavation forces by 300% to 500%. In this study, a DEM-based simulation model …

A Twitter-Based Study For Understanding Public Reaction On Zika Virus, Roopteja Muppalla

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In recent times, social media platforms like Twitter have become more popular and people have become more interactive and responsive than before. People often react to every news in real-time and within no-time, the information spreads rapidly. Even with viral diseases like Zika, people tend to share their opinions and concerns on social media. This can be leveraged by the health officials to track the disease in real-time thereby reducing the time lag due to traditional surveys. A faster and accurate detection of the disease can allow health officials to understand people's opinion of the disease and take necessary precautions …