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2019

Theses/Dissertations

Computer Sciences

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Full-Text Articles in Engineering

Efficient Detection Of Diseases By Feature Engineering Approach From Chest Radiograph, Avishek Mukherjee Jan 2019

Efficient Detection Of Diseases By Feature Engineering Approach From Chest Radiograph, Avishek Mukherjee

Legacy Theses & Dissertations (2009 - 2024)

Deep Learning is the new state-of-the-art technology in Image Processing. We applied Deep Learning techniques for identification of diseases from Radiographs made publicly available by NIH. We applied some Feature Engineering approach to augment the data from Anterior-Posterior position to Posterior-Anterior position and vice-versa for all the diseases, at the same point we suppressed ‘No Finding’ radiographs which contributed to more than 50% (approximately 60,000) of the dataset to top 1000 images. We also prepared a model by adding a huge amount of noise to the augmented data, which if need be can be deployed at rural locations which lack …

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Emotion Forecasting In Dyadic Conversation : Characterizing And Predicting Future Emotion With Audio-Visual Information Using Deep Learning, Sadat Shahriar Jan 2019

Emotion Forecasting In Dyadic Conversation : Characterizing And Predicting Future Emotion With Audio-Visual Information Using Deep Learning, Sadat Shahriar

Legacy Theses & Dissertations (2009 - 2024)

Emotion forecasting is the task of predicting the future emotion of a speaker, i.e., the emotion label of the future speaking turn–based on the speaker’s past and current audio-visual cues. Emotion forecasting systems require new problem formulations that differ from traditional emotion recognition systems. In this thesis, we first explore two types of forecasting windows(i.e., analysis windows for which the speaker’s emotion is being forecasted): utterance forecasting and time forecasting. Utterance forecasting is based on speaking turns and forecasts what the speaker’s emotion will be after one, two, or three speaking turns. Time forecasting forecasts what the speaker’s emotion will …

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Autonomous Spectrum Enforcement : A Blockchain Approach, Maqsood Ahamed Abdul Careem Jan 2019

Autonomous Spectrum Enforcement : A Blockchain Approach, Maqsood Ahamed Abdul Careem

Legacy Theses & Dissertations (2009 - 2024)

A core limitation in existing wireless technologies is the scarcity of spectrum, to support the exponential increase in Internet-connected and multimedia-capable mobile devices and the increasing demand for bandwidth-intensive services. As a solution, Dynamic Spectrum Access policies are being ratified to promote spectrum sharing for various spectrum bands and to improve the spectrum utilization. This poses an equally challenging problem of enforcing these spectrum policies. The distributed and dynamic nature of policy violations necessitates the use of autonomous agents to implement efficient and agile enforcement systems. The design of such a fully autonomous enforcement system is complicated due to the …

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Instance Segmentation And Object Detection In Road Scenes Using Inverse Perspective Mapping Of 3d Point Clouds And 2d Images, Chungyup Lee Jan 2019

Instance Segmentation And Object Detection In Road Scenes Using Inverse Perspective Mapping Of 3d Point Clouds And 2d Images, Chungyup Lee

Electronic Theses and Dissertations

The instance segmentation and object detection are important tasks in smart car applications. Recently, a variety of neural network-based approaches have been proposed. One of the challenges is that there are various scales of objects in a scene, and it requires the neural network to have a large receptive field to deal with the scale variations. In other words, the neural network must have deep architectures which slow down computation. In smart car applications, the accuracy of detection and segmentation of vehicle and pedestrian is hugely critical. Besides, 2D images do not have distance information but enough visual appearance. On …

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Controlled Switching In Kalman Filtering And Iterative Learning Controls, He Li Jan 2019

Controlled Switching In Kalman Filtering And Iterative Learning Controls, He Li

Masters Theses

“Switching is not an uncommon phenomenon in practical systems and processes, for examples, power switches opening and closing, transmissions lifting from low gear to high gear, and air planes crossing different layers in air. Switching can be a disaster to a system since frequent switching between two asymptotically stable subsystems may result in unstable dynamics. On the contrary, switching can be a benefit to a system since controlled switching is sometimes imposed by the designers to achieve desired performance. This encourages the study of system dynamics and performance when undesired switching occurs or controlled switching is imposed. In this research, …

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Static Evaluation Of Type Inference And Propagation On Global Variables With Varying Context, Ivan Frasure Jan 2019

Static Evaluation Of Type Inference And Propagation On Global Variables With Varying Context, Ivan Frasure

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Software reverse engineering (SRE) is a broad field with motivations ranging from verifying or documenting gordian source code files to understanding and reimplementing binary object files and executables. SRE of binaries is exceptionally compelling and challenging due to large amounts of information that can be lost in the compilation progress. A central area in SRE is type inference. Type inference is built around a fundamental step in understanding the behavior of a binary, recovering the types of data in the program. Type inference has many unique techniques in both static and dynamic type inference systems that have been implemented in …

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Securing Modern Cyberspace Using A Multi-Faceted Approach, Yu Li Jan 2019

Securing Modern Cyberspace Using A Multi-Faceted Approach, Yu Li

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Security has become one of the most significant concerns for our cyberspace. Securing the cyberspace, however, becomes increasingly challenging. This can be attributed to the rapidly growing diversities and complexity of the modern cyberspace. Specifically, it is not any more dominated by connected personal computers (PCs); instead, it is greatly characterized by cyber-physical systems (CPS), embedded systems, dynamic services, and human-computer interactions. Securing modern cyberspace therefore calls for a multi-faceted approach capable of systematically integrating these emerging characteristics. This dissertation presents our novel and significant solutions towards this direction. Specifically, we have devised automated, systematic security solutions to three critical …

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Recognition Of Incomplete Objects Based On Synthesis Of Views Using A Geometric Based Local-Global Graphs, Michael Christopher Robbeloth Jan 2019

Recognition Of Incomplete Objects Based On Synthesis Of Views Using A Geometric Based Local-Global Graphs, Michael Christopher Robbeloth

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The recognition of single objects is an old research field with many techniques and robust results. The probabilistic recognition of incomplete objects, however, remains an active field with challenging issues associated to shadows, illumination and other visual characteristics. With object incompleteness, we mean missing parts of a known object and not low-resolution images of that object. The employment of various single machine-learning methodologies for accurate classification of the incomplete objects did not provide a robust answer to the challenging problem. In this dissertation, we present a suite of high-level, model-based computer vision techniques encompassing both geometric and machine learning approaches …

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Islands Of Fitness Compact Genetic Algorithm For Rapid In-Flight Control Learning In A Flapping-Wing Micro Air Vehicle: A Search Space Reduction Approach, Kayleigh E. Duncan Jan 2019

Islands Of Fitness Compact Genetic Algorithm For Rapid In-Flight Control Learning In A Flapping-Wing Micro Air Vehicle: A Search Space Reduction Approach, Kayleigh E. Duncan

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On-going effective control of insect-scale Flapping-Wing Micro Air Vehicles could be significantly advantaged by active in-flight control adaptation. Previous work demonstrated that in simulated vehicles with wing membrane damage, in-flight recovery of effective vehicle attitude and vehicle position control precision via use of an in-flight adaptive learning oscillator was possible. Most recent approaches to this problem employ an island-of-fitness compact genetic algorithm (ICGA) for oscillator learning. The work presented provides the details of a domain specific search space reduction approach implemented with existing ICGA and its effect on the in-flight learning time. Further, it will be demonstrated that the proposed …

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Knowledge-Enabled Entity Extraction, Hussein S. Al-Olimat Jan 2019

Knowledge-Enabled Entity Extraction, Hussein S. Al-Olimat

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Information Extraction (IE) techniques are developed to extract entities, relationships, and other detailed information from unstructured text. The majority of the methods in the literature focus on designing supervised machine learning techniques, which are not very practical due to the high cost of obtaining annotations and the difficulty in creating high quality (in terms of reliability and coverage) gold standard. Therefore, semi-supervised and distantly-supervised techniques are getting more traction lately to overcome some of the challenges, such as bootstrapping the learning quickly. This dissertation focuses on information extraction, and in particular entities, i.e., Named Entity Recognition (NER), from multiple domains, …

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Thai Spelling Correction And Word Normalization On Social Text Using A Two-Stage Pipeline With Neural Contextual Attention, Anuruth Lertpiya Jan 2019

Thai Spelling Correction And Word Normalization On Social Text Using A Two-Stage Pipeline With Neural Contextual Attention, Anuruth Lertpiya

Chulalongkorn University Theses and Dissertations (Chula ETD)

Text correction systems (e.g., spell checkers) have been used to improve the quality of computerized text by detecting and correcting errors. However, the task of performing spelling correction and word normalization (text correction) for Thai social media text has remained largely unexplored. In this thesis, we investigated how current text correction systems perform on correcting errors and word variances in Thai social texts and propose a method designed for this task. We have found that currently available Thai text correction systems are insufficiently robust for correcting spelling errors and word variances, while the text correctors designed for English grammatical error …

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Quantum Comparator Circuit On Superconducting Quantum Computer, Naphan Benchasattabuse Jan 2019

Quantum Comparator Circuit On Superconducting Quantum Computer, Naphan Benchasattabuse

Chulalongkorn University Theses and Dissertations (Chula ETD)

In this thesis, we present an optimised quantum comparator circuit based on Cuccaro's ripple-carry quantum adder using relative phase techniques from Maslov's multiple control Toffoli optimisation. We extend the cost function from simply counting C-Not and Toffoli gate to Qiskit cost which defines arbitrary single qubit gate cost as unity and C-Not as the only two qubit gate cost as ten. We report the comparison result between our comparator circuit with previous comparator circuits from literature using optimal Toffoli implementation with Qiskit cost, C-Not count, and circuit depth. We also report our experiment of implementing a two-bit comparator on IBM …

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Thai Scene Text Recognition, Thananop Kobchaisawat Jan 2019

Thai Scene Text Recognition, Thananop Kobchaisawat

Chulalongkorn University Theses and Dissertations (Chula ETD)

Automatic scene text detection and recognition can benefit a large number of daily life applications such as reading signs and labels, and helping visually impaired persons. Reading scene text images becomes more challenging than reading scanned documents in many aspects due to many factors such as variations of font styles and unpredictable lighting conditions. The problem can be decomposed into two sub-problems: text localization and text recognition. The proposed scene text localization works at the pixel level combined with a new text representation and a fully-convolutional neural network. This method is capable of detecting arbitrary shape texts without language limitations. …

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Knowledge Graph Reasoning Over Unseen Rdf Data, Bhargavacharan Reddy Kaithi Jan 2019

Knowledge Graph Reasoning Over Unseen Rdf Data, Bhargavacharan Reddy Kaithi

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In recent years, the research in deep learning and knowledge engineering has made a wide impact on the data and knowledge representations. The research in knowledge engineering has frequently focused on modeling the high level human cognitive abilities, such as reasoning, making inferences, and validation. Semantic Web Technologies and Deep Learning have an interest in creating intelligent artifacts. Deep learning is a set of machine learning algorithms that attempt to model data representations through many layers of non-linear transformations. Deep learning is in- creasingly employed to analyze various knowledge representations mentioned in Semantic Web and provides better results for Semantic …

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Leveraging Blockchain To Mitigate The Risk Of Counterfeit Microelectronics In Its Supply Chain, Aman Ali Pogaku Jan 2019

Leveraging Blockchain To Mitigate The Risk Of Counterfeit Microelectronics In Its Supply Chain, Aman Ali Pogaku

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System on Chip (SoC) is the backbone component of the electronics industry nowadays. ASIC and FPGA-based SoCs are the two most popular methods of manufacturing SoCs. However, both ASIC and FPGA industries are plagued with risks of counterfeits due to the limitations in Security, Accountability, Complexity, and Governance of their supply chain management. As a result, the current practices of these microelectronics supply chain suffer from performance and efficiency bottlenecks. In this research, we are incorporating blockchain technology into the FPGA and ASIC microelectronic supply chain to help mitigate the risk of counterfeit microelectronics through a secure and decentralized solution …

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Design And Development Of An Immersive Simulation For Social Determinants Of Health Training, Lahari Surapaneni Jan 2019

Design And Development Of An Immersive Simulation For Social Determinants Of Health Training, Lahari Surapaneni

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This thesis research project focuses on design and development of an immersion simulation-based training tool that help raise the social determinants of health (SDOH) awareness among the health care providers. Compared to existing classroom lecture and/or role-play based SDOH education approach, our immersion-simulation based approach provides an easy access and highly realistic experience to such training curriculum at anytime and anywhere with an Internet connection. Such an interactive and immersive exposure is critical to raise SDOH awareness and maintain long-lasting empathy towards actual patients in practice, and thus help providers to be better prepared when encountering with those patients. Particularly, …

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Data-Driven And Knowledge-Based Strategies For Realizing Crowd Wisdom On Social Media, Shreyansh Bhatt Jan 2019

Data-Driven And Knowledge-Based Strategies For Realizing Crowd Wisdom On Social Media, Shreyansh Bhatt

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The wisdom of the crowd is a well-known example of collective intelligence wherein an aggregated judgment of a group of individuals is superior to that of an individual. The aggregated judgment is surprisingly accurate for predicting the outcome of a range of tasks from geopolitical forecasting to the stock price prediction. Recent research has shown that participants' previous performance data contributes to the identification of a subset of participants that can collectively predict an accurate outcome. In the absence of such performance data, researchers have explored the role of human-perceived diversity, i.e., whether a human considers a crowd as a …

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Speech Enabled Navigation In Virtual Environments, Raksha Rajashekar Jan 2019

Speech Enabled Navigation In Virtual Environments, Raksha Rajashekar

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Navigating in a Virtual Environment with traditional input devices such as mouse, joysticks and keyboards provide limited maneuverability and is also time consuming. While working in a virtual environment, changing parameters to obtain the desired visualization requires time to achieve by manually entering parameter values in an algorithm to test outcomes. The following thesis presents an alternate user interface to reduce user efforts, while navigating within the Virtual Environment. The user interface is an Android application which is designed to accommodate spoken commands. This Speech Enabled User Interface termed as the Speech Navigation Application (SNA), provides the user with an …

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Towards Data And Model Confidentiality In Outsourced Machine Learning, Sagar Sharma Jan 2019

Towards Data And Model Confidentiality In Outsourced Machine Learning, Sagar Sharma

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With massive data collections and needs for building powerful predictive models, data owners may choose to outsource storage and expensive machine learning computations to public cloud providers (Cloud). Data owners may choose cloud outsourcing due to the lack of in-house storage and computation resources or the expertise of building models. Similarly, users, who subscribe to specialized services such as movie streaming and social networking, voluntarily upload their data to the service providers' site for storage, analytics, and better services. The service provider, in turn, may also choose to benefit from ubiquitous cloud computing. However, outsourcing to a public cloud provider …

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Abusive And Hate Speech Tweets Detection With Text Generation, Abhishek Nalamothu Jan 2019

Abusive And Hate Speech Tweets Detection With Text Generation, Abhishek Nalamothu

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According to a Pew Research study, 41% of Americans have personally experienced online harassment and two-thirds of Americans have witnessed harassment in 2017. Hence, online harassment detection is vital for securing and sustaining the popularity and viability of online social networks. Machine learning techniques play a crucial role in automatic harassment detection. One of the challenges of using supervised approaches is training data imbalance. Existing text generation techniques can help augment the training data, but they are still inadequate and ineffective. This research explores the role of domain-specific knowledge to complement the limited training data available for training a text …

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Kbot: Knowledge-Enabled Personalized Chatbot For Self-Management Of Asthma In Pediatric Population, Dipesh Kadariya Jan 2019

Kbot: Knowledge-Enabled Personalized Chatbot For Self-Management Of Asthma In Pediatric Population, Dipesh Kadariya

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Asthma, chronic pulmonary disease, is one of the major health issues in the United States. Given its chronic nature, the demand for continuous monitoring of patient’s adherence to the medication care plan, assessment of their environment triggers, and management of asthma control level can be challenging in traditional clinical settings and taxing on clinical professionals. A shift from a reactive to a proactive asthma care can improve health outcomes and reduce expenses. On the technology spectrum, smart conversational systems and Internet-of-Things (IoTs) are rapidly gaining popularity in the healthcare industry. By leveraging such technological prevalence, it is feasible to design …

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Detecting Malicious Behavior In Openwrt With Qemu Tracing, Jeremy Porter Jan 2019

Detecting Malicious Behavior In Openwrt With Qemu Tracing, Jeremy Porter

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In recent years embedded devices have become more ubiquitous than ever before and are expected to continue this trend. Embedded devices typically have a singular or more focused purpose, a smaller footprint, and often interact with the physical world. Some examples include routers, wearable heart rate monitors, and thermometers. These devices are excellent at providing real time data or completing a specific task quickly, but they lack many features that make security issues more obvious. Generally, Embedded devices are not easily secured. Malware or rootkits in the firmware of an embedded system are difficult to detect because embedded devices do …

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Leveraging Schema Information For Improved Knowledge Graph Navigation, Rama Someswar Chittella Jan 2019

Leveraging Schema Information For Improved Knowledge Graph Navigation, Rama Someswar Chittella

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Over the years, the semantic web has emerged as a new generation of the world wide web featuring advanced technologies and research contributions. It has revolutionized the usage of information by allowing users to capture and publish machine-understandable data and expedite methods such as ontologies to perform the same. These ontologies help in the formal representation of a specified domain and foster comprehensive machine understanding. Although, the engineering of ontologies and usage of logic have been an integral part of the web semantics, new areas of research such as the semantic web search, linking and usage of open data on …

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Conditional Dilated Attention Tracking Model - C-Datm, Tyler Clayton Highlander Jan 2019

Conditional Dilated Attention Tracking Model - C-Datm, Tyler Clayton Highlander

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Current commercial tracking systems do not process images fast enough to perform target-tracking in real- time. State-of-the-art methods use entire scenes to locate objects frame-by-frame and are commonly computationally expensive because they use image convolutions. Alternatively, attention mechanisms track more efficiently by mimicking human optical cognitive interaction to only process small portions of an image. Thus, in this work we use an attention-based approach to create a model called C-DATM (Conditional Dilated Attention tracking Model) that learns to compare target features in a sequence of image-frames using dilated convolutions. The C-DATM is tested using the Modified National Institute of Standards …

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Virtual Reality And Analysis Framework For Studying Different Layout Designs, Madison Glines Jan 2019

Virtual Reality And Analysis Framework For Studying Different Layout Designs, Madison Glines

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This thesis describes the tools for studying different design prototypes. The goal was to develop effective tools to study these designs using a data-driven approach. “Proof of concept” experiments were conducted, in which participants were allowed to interact with a virtual environment depicting different designs as data pertaining to their virtual location and orientation was recorded for later analysis. The designs included “flat” store racks, as opposed to racks with more varied shapes, as well as “curved” racks. Focus of the design studies was to assist in identifying optimal locations for different product types. The automated data collection mechanisms required …

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Llvm-Ir Based Decompilation, Ilsoo Jeon Jan 2019

Llvm-Ir Based Decompilation, Ilsoo Jeon

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Decompilation is a process of transforming an executable program into a source-like high-level language code, which plays an important role in malware analysis, and vulnerability detection. In this thesis, we design and implement the middle end of a decompiler framework, focusing on Low Level Language properties reduction using the optimization techniques, propagation and elimination. An open-source software tool, dagger, is used to translate binary code to LLVM (Low Level Virtual Machine) Intermediate Representation code. We perform data flow analysis and control flow analysis on the LLVM format code to generate high-level code using a Functional Programming Langauge (FPL), Haskell. The …

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Anticipation In Dynamic Environments: Deciding What To Monitor, Zohreh A. Dannenhauer Jan 2019

Anticipation In Dynamic Environments: Deciding What To Monitor, Zohreh A. Dannenhauer

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In dynamic environments, external changes may occur that may affect planning decisions and goal choices. We claim that an intelligent agent should actively watch for what can go wrong and anticipate changes in the environment that allows the changing of its plan or changing of a given goal. In this thesis, we focus on the relationship between perception, act, interpretation, and planning. We claim that these components are not independent and need to interact with each other to help the agent succeed in achieving its goals and plans. If newly encountered world information affects the plan, the agent adapts to …

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Software Implementations And Applications Of Elliptic Curve Cryptography, Kirill Kultinov Jan 2019

Software Implementations And Applications Of Elliptic Curve Cryptography, Kirill Kultinov

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Elliptic Curve Cryptography (ECC) is a public-key cryptography system. Elliptic Curve Cryptography (ECC) can achieve the same level of security as the public-key cryptography system, RSA, with a much smaller key size. It is a promising public key cryptography system with regard to time efficiency and resource utilization. This thesis focuses on the software implementations of ECC over finite field GF(p) with two distinct implementations of the Big Integer classes using character arrays, and bit sets in C++ programming language. Our implementation works on the ECC curves of the form y^2 = x^3 + ax + b (mod p). The …

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Rules With Right Hand Existential Or Disjunction With Rowltab, Sri Jitendra Satpathy Jan 2019

Rules With Right Hand Existential Or Disjunction With Rowltab, Sri Jitendra Satpathy

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One hotly debated research topic is, “What is the best approach for modeling ontologies?”. In the earlier stages of modeling ontologies, researchers have favored the usage of description logic to capture knowledge. One such choice is the Web Ontology Language (OWL) that is based on description logic. Many tools were designed around this principle and are still widely being used to model and explore ontologies. However, not all users find description logic to be intuitive, at least not without an extensive background in formal logics. Due to this, researchers have tried to explore other ways that will enable such users …

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Automated Vehicle Electronic Control Unit (Ecu) Sensor Location Using Feature-Vector Based Comparisons, Gregory S. Buthker Jan 2019

Automated Vehicle Electronic Control Unit (Ecu) Sensor Location Using Feature-Vector Based Comparisons, Gregory S. Buthker

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In the growing world of cybersecurity, being able to map and analyze how software and hardware interact is key to understanding and protecting critical embedded systems like the Engine Control Unit (ECU). The aim of our research is to use our understanding of the ECU's control flow attained through manual analysis to automatically map and identify sensor functions found within the ECU. We seek to do this by generating unique sets of feature vectors for every function within the binary file of a car ECU, and then using those feature sets to locate functions within each binary similar to their …

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