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Articles 121 - 150 of 341
Full-Text Articles in Computer Engineering
Context-Centric Affect Recognition From Paralinguistic Features Of Speech, Andreas Marpaung
Context-Centric Affect Recognition From Paralinguistic Features Of Speech, Andreas Marpaung
Electronic Theses and Dissertations
As the field of affect recognition has progressed, many researchers have shifted from having unimodal approaches to multimodal ones. In particular, the trends in paralinguistic speech affect recognition domain have been to integrate other modalities such as facial expression, body posture, gait, and linguistic speech. Our work focuses on integrating contextual knowledge into paralinguistic speech affect recognition. We hypothesize that a framework to recognize affect through paralinguistic features of speech can improve its performance by integrating relevant contextual knowledge. This dissertation describes our research to integrate contextual knowledge into the paralinguistic affect recognition process from acoustic features of speech. We …
Improvement Of Data-Intensive Applications Running On Cloud Computing Clusters, Ibrahim Adel Ibrahim
Improvement Of Data-Intensive Applications Running On Cloud Computing Clusters, Ibrahim Adel Ibrahim
Electronic Theses and Dissertations
MapReduce, designed by Google, is widely used as the most popular distributed programming model in cloud environments. Hadoop, an open-source implementation of MapReduce, is a data management framework on large cluster of commodity machines to handle data-intensive applications. Many famous enterprises including Facebook, Twitter, and Adobe have been using Hadoop for their data-intensive processing needs. Task stragglers in MapReduce jobs dramatically impede job execution on massive datasets in cloud computing systems. This impedance is due to the uneven distribution of input data and computation load among cluster nodes, heterogeneous data nodes, data skew in reduce phase, resource contention situations, and …
Simulation, Analysis, And Optimization Of Heterogeneous Cpu-Gpu Systems, Christopher Giles
Simulation, Analysis, And Optimization Of Heterogeneous Cpu-Gpu Systems, Christopher Giles
Electronic Theses and Dissertations
With the computing industry's recent adoption of the Heterogeneous System Architecture (HSA) standard, we have seen a rapid change in heterogeneous CPU-GPU processor designs. State-of-the-art heterogeneous CPU-GPU processors tightly integrate multicore CPUs and multi-compute unit GPUs together on a single die. This brings the MIMD processing capabilities of the CPU and the SIMD processing capabilities of the GPU together into a single cohesive package with new HSA features comprising better programmability, coherency between the CPU and GPU, shared Last Level Cache (LLC), and shared virtual memory address spaces. These advancements can potentially bring marked gains in heterogeneous processor performance and …
Rethinking Routing And Peering In The Era Of Vertical Integration Of Network Functions, Prasun Kanti Dey
Rethinking Routing And Peering In The Era Of Vertical Integration Of Network Functions, Prasun Kanti Dey
Electronic Theses and Dissertations
Content providers typically control the digital content consumption services and are getting the most revenue by implementing an "all-you-can-eat" model via subscription or hyper-targeted advertisements. Revamping the existing Internet architecture and design, a vertical integration where a content provider and access ISP will act as unibody in a sugarcane form seems to be the recent trend. As this vertical integration trend is emerging in the ISP market, it is questionable if existing routing architecture will suffice in terms of sustainable economics, peering, and scalability. It is expected that the current routing will need careful modifications and smart innovations to ensure …
Scalable Map Information Dissemination For Connected And Automated Vehicle Systems, S. M. Osman Gani
Scalable Map Information Dissemination For Connected And Automated Vehicle Systems, S. M. Osman Gani
Electronic Theses and Dissertations
Situational awareness in connected and automated vehicle (CAV) systems becomes particularly challenging in the presence of non-line of sight objects and/or objects beyond the sensing range of local onboard sensors. Despite the fact that fully autonomous driving requires the use of multiple redundant sensor systems, primarily including camera, radar, and LiDAR, the non-line of sight object detection problem still persists due to the inherent limitations of those sensing techniques. To tackle this challenge, the inter-vehicle communication system is envisioned that allows vehicles to exchange self-status updates aiming to extend their effective field of view and thus compensate for the limitations …
Guided Autonomy For Quadcopter Photography, Saif Alabachi
Guided Autonomy For Quadcopter Photography, Saif Alabachi
Electronic Theses and Dissertations
Photographing small objects with a quadcopter is non-trivial to perform with many common user interfaces, especially when it requires maneuvering an Unmanned Aerial Vehicle (C) to difficult angles in order to shoot high perspectives. The aim of this research is to employ machine learning to support better user interfaces for quadcopter photography. Human Robot Interaction (HRI) is supported by visual servoing, a specialized vision system for real-time object detection, and control policies acquired through reinforcement learning (RL). Two investigations of guided autonomy were conducted. In the first, the user directed the quadcopter with a sketch based interface, and periods of …
Modeling And Simulation Methodologies For Spinal Cord Stimulation., Saliya Kumara Kirigeeganage
Modeling And Simulation Methodologies For Spinal Cord Stimulation., Saliya Kumara Kirigeeganage
Electronic Theses and Dissertations
The use of neural prostheses to improve health of paraplegics has been a prime interest of neuroscientists over the last few decades. Scientists have performed experiments with spinal cord stimulation (SCS) to enable voluntary motor function of paralyzed patients. However, the experimentation on the human spinal cord is not a trivial task. Therefore, modeling and simulation techniques play a significant role in understanding the underlying concepts and mechanics of the spinal cord stimulation. In this work, simulation and modeling techniques related to spinal cord stimulation were investigated. The initial work was intended to visualize the electric field distribution patterns in …
A Transfer Learning Approach For Sentiment Classification., Omar Abdelwahab
A Transfer Learning Approach For Sentiment Classification., Omar Abdelwahab
Electronic Theses and Dissertations
The idea of developing machine learning systems or Artificial Intelligence agents that would learn from different tasks and be able to accumulate that knowledge with time so that it functions successfully on a new task that it has not seen before is an idea and a research area that is still being explored. In this work, we will lay out an algorithm that allows a machine learning system or an AI agent to learn from k different domains then uses some or no data from the new task for the system to perform strongly on that new task. In order …
Autonomous Discovery And Maintenance Of Mobile Frees-Space-Optical Links, Mahmudur Khan
Autonomous Discovery And Maintenance Of Mobile Frees-Space-Optical Links, Mahmudur Khan
Electronic Theses and Dissertations
Free-Space-Optical (FSO) communication has the potential to play a significant role in future generation wireless networks. It is advantageous in terms of improved spectrum utilization, higher data transfer rate, and lower probability of interception from unwanted sources. FSO communication can provide optical-level wireless communication speeds and can also help solve the wireless capacity problem experienced by the traditional RF-based technologies. Despite these advantages, communications using FSO transceivers require establishment and maintenance of line-of-sight (LOS). We consider autonomous mobile nodes (Unmanned Ground Vehicles or Unmanned Aerial Vehicles), each with one FSO transceiver mounted on a movable head capable of scanning in …
Spam Elimination And Bias Correction : Ensuring Label Quality In Crowdsourced Tasks., Lingyu Lyu
Spam Elimination And Bias Correction : Ensuring Label Quality In Crowdsourced Tasks., Lingyu Lyu
Electronic Theses and Dissertations
Crowdsourcing is proposed as a powerful mechanism for accomplishing large scale tasks via anonymous workers online. It has been demonstrated as an effective and important approach for collecting labeled data in application domains which require human intelligence, such as image labeling, video annotation, natural language processing, etc. Despite the promises, one big challenge still exists in crowdsourcing systems: the difficulty of controlling the quality of crowds. The workers usually have diverse education levels, personal preferences, and motivations, leading to unknown work performance while completing a crowdsourced task. Among them, some are reliable, and some might provide noisy feedback. It is …
Horse Racing Prediction Using Graph-Based Features., Mehmet Akif Gulum
Horse Racing Prediction Using Graph-Based Features., Mehmet Akif Gulum
Electronic Theses and Dissertations
This thesis presents an applied horse racing prediction using graph based features on a set of horse races data. We used artificial neural network and logistic regression models to train then test to prediction without graph based features and with graph based features. This thesis can be explained in 4 main parts. Collect data from a horse racing website held from 2015 to 2017. Train data to using predictive models and make a prediction. Create a global directed graph of horses and extract graph-based features (Core Part) . Add graph based features to basic features and train to using same …
Machine Learning For Omics Data Analysis., Ameni Trabelsi
Machine Learning For Omics Data Analysis., Ameni Trabelsi
Electronic Theses and Dissertations
In proteomics and metabolomics, to quantify the changes of abundance levels of biomolecules in a biological system, multiple sample analysis steps are involved. The steps include mass spectrum deconvolution and peak list alignment. Each analysis step introduces a certain degree of technical variation in the abundance levels (i.e. peak areas) of those molecules. Some analysis steps introduce technical variations that affect the peak areas of all molecules equally while others affect the peak areas of a subset of molecules with varying degrees. To correct these technical variations, some existing normalization methods simply scale the peak areas of all molecules detected …
Maintainability Analysis Of Mining Trucks With Data Analytics., Abdulgani Kahraman
Maintainability Analysis Of Mining Trucks With Data Analytics., Abdulgani Kahraman
Electronic Theses and Dissertations
The mining industry is one of the biggest industries in need of a large budget, and current changes in global economic challenges force the industry to reduce its production expenses. One of the biggest expenditures is maintenance. Thanks to the data mining techniques, available historical records of machines’ alarms and signals might be used to predict machine failures. This is crucial because repairing machines after failures is not as efficient as utilizing predictive maintenance. In this case study, the reasons for failures seem to be related to the order of signals or alarms, called events, which come from trucks. The …
End-To-End Learning Framework For Circular Rna Classification From Other Long Non-Coding Rnas Using Multi-Modal Deep Learning., Mohamed Chaabane
End-To-End Learning Framework For Circular Rna Classification From Other Long Non-Coding Rnas Using Multi-Modal Deep Learning., Mohamed Chaabane
Electronic Theses and Dissertations
Over the past two decades, a circular form of RNA (circular RNA) produced from splicing mechanism has become the focus of scientific studies due to its major role as a microRNA (miR) ac tivity modulator and its association with various diseases including cancer. Therefore, the detection of circular RNAs is a vital operation for continued comprehension of their biogenesis and purpose. Prediction of circular RNA can be achieved by first distinguishing non-coding RNAs from protein coding gene transcripts, separating short and long non-coding RNAs (lncRNAs), and finally pre dicting circular RNAs from other lncRNAs. However, available tools to distinguish circular …
Robust Fuzzy Clustering For Multiple Instance Regression., Mohamed Trabelsi
Robust Fuzzy Clustering For Multiple Instance Regression., Mohamed Trabelsi
Electronic Theses and Dissertations
Multiple instance regression (MIR) operates on a collection of bags, where each bag contains multiple instances sharing an identical real-valued label. Only few instances, called primary instances, contribute to the bag labels. The remaining instances are noise and outliers observations. The goal in MIR is to identify the primary instances within each bag and learn a regression model that can predict the label of a previously unseen bag. In this thesis, we introduce an algorithm that uses robust fuzzy clustering with an appropriate distance to learn multiple linear models from a noisy feature space simultaneously. We show that fuzzy memberships …
A Framework For Cardio-Pulmonary Resuscitation (Cpr) Scene Retrieval From Medical Simulation Videos Based On Object And Activity Detection., Anju Panicker Madhusoodhanan Sathik
A Framework For Cardio-Pulmonary Resuscitation (Cpr) Scene Retrieval From Medical Simulation Videos Based On Object And Activity Detection., Anju Panicker Madhusoodhanan Sathik
Electronic Theses and Dissertations
In this thesis, we propose a framework to detect and retrieve CPR activity scenes from medical simulation videos. Medical simulation is a modern training method for medical students, where an emergency patient condition is simulated on human-like mannequins and the students act upon. These simulation sessions are recorded by the physician, for later debriefing. With the increasing number of simulation videos, automatic detection and retrieval of specific scenes became necessary. The proposed framework for CPR scene retrieval, would eliminate the conventional approach of using shot detection and frame segmentation techniques. Firstly, our work explores the application of Histogram of Oriented …
Network Science Algorithms For Mobile Networks., Heba Mohamed Elgazzar
Network Science Algorithms For Mobile Networks., Heba Mohamed Elgazzar
Electronic Theses and Dissertations
Network Science is one of the important and emerging fields in computer science and engineering that focuses on the study and analysis of different types of networks. The goal of this dissertation is to design and develop network science algorithms that can be used to study and analyze mobile networks. This can provide essential information and knowledge that can help mobile networks service providers to enhance the quality of the mobile services. We focus in this dissertation on the design and analysis of different network science techniques that can be used to analyze the dynamics of mobile networks. These techniques …
Studying Facial Expression Recognition And Imitation Ability Of Children With Autism Spectrum Disorder In Interaction With A Social Robot, Farzaneh Askari
Studying Facial Expression Recognition And Imitation Ability Of Children With Autism Spectrum Disorder In Interaction With A Social Robot, Farzaneh Askari
Electronic Theses and Dissertations
Children with Autism Spectrum Disorder (ASD) experience limited abilities in recognizing non-verbal elements of social interactions such as facial expressions [1]. They also show deficiencies in imitating facial expressions in social situations. In this Master thesis, we focus on studying the ability of children with ASD in recognizing facial expressions and imitating the expressions using a rear-projected expressive humanoid robot, called Ryan. Recent studies show that social robots such as Ryan have great potential for autism therapy. We designed and developed three studies, first to evaluate the ability of children with ASD in recognizing facial expressions that are presented to …
Developing An Affect-Aware Rear-Projected Robotic Agent, Ali Mollahosseini
Developing An Affect-Aware Rear-Projected Robotic Agent, Ali Mollahosseini
Electronic Theses and Dissertations
Social (or Sociable) robots are designed to interact with people in a natural and interpersonal manner. They are becoming an integrated part of our daily lives and have achieved positive outcomes in several applications such as education, health care, quality of life, entertainment, etc. Despite significant progress towards the development of realistic social robotic agents, a number of problems remain to be solved. First, current social robots either lack enough ability to have deep social interaction with human, or they are very expensive to build and maintain. Second, current social robots have yet to reach the full emotional and social …
Force-Canceling Mixer Algorithm For Vehicles With Fully-Articulated Radially Symmetric Thruster Arrays, Joseph Nicholas Casabona
Force-Canceling Mixer Algorithm For Vehicles With Fully-Articulated Radially Symmetric Thruster Arrays, Joseph Nicholas Casabona
Electronic Theses and Dissertations
A new type of fully-holonomic aerial vehicle is identified and developed that can optionally utilize automatic cancellation of excessive thruster forces to maintain precise control despite little or no throttle authority. After defining the physical attributes of the new vehicle, a flight control mixer algorithm is defined and presented. This mixer is an input/output abstraction that grants a flight control system (or pilot) full authority of the vehicle's position and orientation by means of an input translation vector and input torque vector. The mixer is shown to be general with respect to the number of thrusters in the system provided …
Security Of Autonomous Systems Under Physical Attacks: With Application To Self-Driving Cars, Raj Gautam Dutta
Security Of Autonomous Systems Under Physical Attacks: With Application To Self-Driving Cars, Raj Gautam Dutta
Electronic Theses and Dissertations
The drive to achieve trustworthy autonomous cyber-physical systems (CPS), which can attain goals independently in the presence of significant uncertainties and for long periods of time without any human intervention, has always been enticing. Significant progress has been made in the avenues of both software and hardware for fulfilling these objectives. However, technological challenges still exist and particularly in terms of decision making under uncertainty. In an autonomous system, uncertainties can arise from the operating environment, adversarial attacks, and from within the system. As a result of these concerns, human-beings lack trust in these systems and hesitate to use them …
Service Integration Design Patterns In Microservices, Meng Wang
Service Integration Design Patterns In Microservices, Meng Wang
Electronic Theses and Dissertations
“Microservices” is a new term in software architecture that was defined in 2014 [1]. It is a method to build a software application with a set of small services. Each service has its process to serve a single purpose and communicates with other services through lightweight mechanisms. Because of a great deal of independently distributed services, it is a challenge to integrate the loose services fully. Too many trivial relationships can be messed up easily during deployment. Also, it is hard to modify the relationships if the services are updated as the source codes need to be re-edited and tested. …
Localization Of Microcalcification On The Mammogram Using Deep Convolutional Neural Network, Jieun Jhang
Localization Of Microcalcification On The Mammogram Using Deep Convolutional Neural Network, Jieun Jhang
Electronic Theses and Dissertations
Breast cancer is the most common cancer in women worldwide, and the mammogram is the most widely used screening technique for breast cancer. To make a diagnosis in the early stage of breast cancer, the appearance of masses and microcalcifications on the mammogram are two crucial indicators. Notably, the early detection of malignant microcalcifications can facilitate the diagnosis and the treatment of breast cancer at the appropriate time. Making an accurate evaluation on microcalcifications is a timeconsuming and challenging task for the radiologists due to the small size and the low contrast of microcalcification. Compared to the background and mammogram …
An Approach To Finding Parking Space Using The Csi-Based Wifi Technology, Yunfan Zhang
An Approach To Finding Parking Space Using The Csi-Based Wifi Technology, Yunfan Zhang
Electronic Theses and Dissertations
With ever-increasing number of vehicles and shortages of parking spaces, parking has always been a very important issue in transportation. It is necessary to use advanced intelligent technologies to help drivers find parking spaces, quickly. In this thesis, an approach to finding empty spaces in parking lots using the CSI-based WiFi technology is presented. First, the channel state information (CSI) of received WiFi signals is analyzed. The features of CSI data that are strongly correlated with the number of empty slots in parking lots are identified and extracted. A machine learning technique to perform multi-class classification that categorizes the input …
Wi-Fi Finger-Printing Based Indoor Localization Using Nano-Scale Unmanned Aerial Vehicles, Appala Narasimha Raju Chekuri
Wi-Fi Finger-Printing Based Indoor Localization Using Nano-Scale Unmanned Aerial Vehicles, Appala Narasimha Raju Chekuri
Electronic Theses and Dissertations
Explosive growth in the number of mobile devices like smartphones, tablets, and smartwatches has escalated the demand for localization-based services, spurring development of numerous indoor localization techniques. Especially, widespread deployment of wireless LANs prompted ever increasing interests in WiFi-based indoor localization mechanisms. However, a critical shortcoming of such localization schemes is the intensive time and labor requirements for collecting and building the WiFi fingerprinting database, especially when the system needs to cover a large space. In this thesis, we propose to automate the WiFi fingerprint survey process using a group of nano-scale unmanned aerial vehicles (NAVs). The proposed system significantly …
Design, Implementation And A Pilot Study Of Mobile Framework For Pedestrian Safety Using Smartphone Sensors, Aawesh Man Shrestha
Design, Implementation And A Pilot Study Of Mobile Framework For Pedestrian Safety Using Smartphone Sensors, Aawesh Man Shrestha
Electronic Theses and Dissertations
Pedestrian distraction from smartphones is a serious social problem that caused an ever increasing number of fatalities especially as virtual reality (VR) games have gained popularity recently. In this thesis, we present the design, implementation, and a pilot study of WiPedCross, a WiFi direct-based pedestrian safety system that senses and evaluates a risk, and alerts accordingly the user to prevent traffic accidents. In order to develop a non-intrusive, accurate, and energy-efficient pedestrian safety system, a number of technical challenges are addressed: to enhance the positioning accuracy of the user for precise risk assessment, a map-matching algorithm based on a Hidden …
Chronic Risk And Disease Management Model Using Structured Query Language And Predictive Analysis, Mamata Ojha
Chronic Risk And Disease Management Model Using Structured Query Language And Predictive Analysis, Mamata Ojha
Electronic Theses and Dissertations
Individuals with chronic conditions are the ones who use health care most frequently and more than 50% of top ten causes of death are chronic diseases in United States and these members always have health high risk scores. In the field of population health management, identifying high risk members is very important in terms of patient health care, disease management and cost management. Disease management program is very effective way of monitoring and preventing chronic disease and health related complications and risk management allows physicians and healthcare companies to reduce patient’s health risk, help identifying members for care/disease management along …
Low Power Wide Area Networks (Lpwan): Technology Review And Experimental Study On Mobility Effect, Dhaval Patel
Low Power Wide Area Networks (Lpwan): Technology Review And Experimental Study On Mobility Effect, Dhaval Patel
Electronic Theses and Dissertations
In the past decade, we have witnessed explosive growth in the number of low-power embedded and Internet-connected devices, reinforcing the new paradigm, Internet of Things (IoT). IoT devices like smartphones, home security systems, smart electric meters, garage parking indicators, etc., have penetrated deeply into our daily lives. These IoT devices are increasingly attached and operated in mobile objects like unmanned vehicles, trains, airplanes, etc. The low power wide area network (LPWAN), due to its long-range, low-power and low-cost communication capability, is actively considered by academia and industry as the future wireless communication standard for IoT. However, despite the increasing popularity …
Enabling Low Cost Wifi-Based Traffic Monitoring System Using Deep Learning, Sayan Sahu
Enabling Low Cost Wifi-Based Traffic Monitoring System Using Deep Learning, Sayan Sahu
Electronic Theses and Dissertations
A traffic monitoring system (TMS) is an integral part of Intelligent Transportation Systems (ITS) for traffic analysis and planning. However, covering huge miles of rural highways (119,247 miles in U.S.) with a large number of TMSs is a very challenging problem due to the cost issue. This paper aims to address the problem by developing a low-cost and portable TMS called DeepWiTraffic based on COTs WiFi devices. The proposed system enables accurate vehicle detection (counting) and classification by exploiting the unique WiFi Channel State Information (CSI) of passing vehicles. Spatial and temporal correlations of CSI amplitude and phase data are …
Enhancing Cognitive Algorithms For Optimal Performance Of Adaptive Networks, Hector Lugo-Cordero
Enhancing Cognitive Algorithms For Optimal Performance Of Adaptive Networks, Hector Lugo-Cordero
Electronic Theses and Dissertations
This research proposes to enhance some Evolutionary Algorithms in order to obtain optimal and adaptive network configurations. Due to the richness in technologies, low cost, and application usages, we consider Heterogeneous Wireless Mesh Networks. In particular, we evaluate the domains of Network Deployment, Smart Grids/Homes, and Intrusion Detection Systems. Having an adaptive network as one of the goals, we consider a robust noise tolerant methodology that can quickly react to changes in the environment. Furthermore, the diversity of the performance objectives considered (e.g., power, coverage, anonymity, etc.) makes the objective function non-continuous and therefore not have a derivative. For these …