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Articles 1 - 8 of 8
Full-Text Articles in Engineering
Traffic Control And Collision Resolution For Random Access In M2m Communication, Changwei Zhang
Traffic Control And Collision Resolution For Random Access In M2m Communication, Changwei Zhang
Electronic Thesis and Dissertation Repository
Internet-of-Things (IoT), which aims to integrate machines, industrial process, and people together, has become one of the most critical technology for the next wave of industrial revolution. Among many related technical fields of IoT, machine-to-machine (M2M) communication is the most important paradigm to realize the seamless information exchange between different machine-type devices (MTDs) with minimal human interference and has experienced rapid development in the past few decades. However, features of M2M communication such as diverse applications, small data packets, and large connections, would cause quality-of-service (QoS) dissatisfaction, channel utilization deterioration and severe collisions to the random access procedure, which is …
Optimized And Automated Machine Learning Techniques Towards Iot Data Analytics And Cybersecurity, Li Yang
Optimized And Automated Machine Learning Techniques Towards Iot Data Analytics And Cybersecurity, Li Yang
Electronic Thesis and Dissertation Repository
The Internet-of-Things (IoT) systems have emerged as a prevalent technology in our daily lives. With the wide spread of sensors and smart devices in recent years, the data generation volume and speed of IoT systems have increased dramatically. In most IoT systems, massive volumes of data must be processed, transformed, and analyzed on a frequent basis to enable various IoT services and functionalities. Machine Learning (ML) approaches have shown their capacity for IoT data analytics. However, applying ML models to IoT data analytics tasks still faces many difficulties and challenges. The first challenge is to process large amounts of dynamic …
Machine Learning And Operations Research For Intelligence Engines In Future Networks, Ali Chouman
Machine Learning And Operations Research For Intelligence Engines In Future Networks, Ali Chouman
Electronic Thesis and Dissertation Repository
The evolution of fifth-generation (5G) and Beyond mobile technologies is spurred by the rapid demands and high-end requirements of next-generation mobile networks. It is imperative that advanced intelligence and machine learning techniques address these dynamic requirements by supporting network operations in terms of maintenance, servicing, and performance. The Third Generation Partnership Project (3GPP) has outlined a Network Data Analytics Function (NWDAF) for 5G Core (5GC) networks that should provide predictive network maintenance and improve network performance in these dynamic networks, and which must leverage the capabilities of artificial intelligence, machine learning, and advanced data analytics methods to satisfy its specification …
Machine Learning With Big Data For Electrical Load Forecasting, Alexandra L'Heureux
Machine Learning With Big Data For Electrical Load Forecasting, Alexandra L'Heureux
Electronic Thesis and Dissertation Repository
Today, the amount of data collected is exploding at an unprecedented rate due to developments in Web technologies, social media, mobile and sensing devices and the internet of things (IoT). Data is gathered in every aspect of our lives: from financial information to smart home devices and everything in between. The driving force behind these extensive data collections is the promise of increased knowledge. Therefore, the potential of Big Data relies on our ability to extract value from these massive data sets. Machine learning is central to this quest because of its ability to learn from data and provide data-driven …
Automated Segmentation Of The Inner Ear And Round Window In Computed Tomography Scans Using Convolutional Neural Networks, Kyle A. Rioux
Automated Segmentation Of The Inner Ear And Round Window In Computed Tomography Scans Using Convolutional Neural Networks, Kyle A. Rioux
Electronic Thesis and Dissertation Repository
Computed tomography (CT) scans are acquired prior to cochlear implant (CI) surgery. Three-dimensional segmentations of the inner ear (IE) and round window (RW) based on clinical CTs can improve the CI procedure. Software pipelines are presented here which employ convolutional neural networks to automatically segment the IE and RW. The first pipeline produces high resolution segmentations of the IE and RW in tightly cropped CTs. Mean IE Dice score and RW centroid error were 0.88, 0.57mm and 0.93, 0.18mm in implanted and non-implanted samples, respectively. The second pipeline automatically segments the IE in large field of view CTs of any …
The Role Of Transient Vibration Of The Skull On Concussion, Rodrigo Dalvit Carvalho Da Silva
The Role Of Transient Vibration Of The Skull On Concussion, Rodrigo Dalvit Carvalho Da Silva
Electronic Thesis and Dissertation Repository
Concussion is a traumatic brain injury usually caused by a direct or indirect blow to the head that affects brain function. The maximum mechanical impedance of the brain tissue occurs at 450±50 Hz and may be affected by the skull resonant frequencies. After an impact to the head, vibration resonance of the skull damages the underlying cortex. The skull deforms and vibrates, like a bell for 3 to 5 milliseconds, bruising the cortex. Furthermore, the deceleration forces the frontal and temporal cortex against the skull, eliminating a layer of cerebrospinal fluid. When the skull vibrates, the force spreads directly to …
Design Of A Capability And Maturity Model For The Development Of Trustworthy Adm Systems Based On Principled Ai, Daniel Varona Cordero
Design Of A Capability And Maturity Model For The Development Of Trustworthy Adm Systems Based On Principled Ai, Daniel Varona Cordero
Electronic Thesis and Dissertation Repository
Automatic decision-making (ADM) systems have permeated every sphere of society where a large amount of data is managed to fulfill prediction/classification needs. The enhanced capabilities ADM systems have brought into their applied sciences conditioned their evolution to more complex and less transparent machine learning algorithms and models (MLA & M). Nowadays, dissimilar predictions, or suggested decisions supported by MLA & M are found to be misleading, or discriminatory resulting in heated academic and public debates since these MLA & M are being applied in socially and politically sensitive areas such as crime prevention, justice management, among others. Thus, there exists …
Autonomous Rock Segmentation From Lidar Point Clouds Using Machine Learning Approaches, Lauren E. Flanagan
Autonomous Rock Segmentation From Lidar Point Clouds Using Machine Learning Approaches, Lauren E. Flanagan
Electronic Thesis and Dissertation Repository
Rover navigation on planetary surfaces currently uses a method called blind drive which requires a navigation goal as input from operators on Earth and uses camera images to autonomously detect obstacles. Images can be affected by lighting conditions, are not highly accurate from far distances, and will not work in the dark; these factors negatively impact the autonomous capabilities of rovers. By improving a rover's ability to autonomously detect obstacles, the capabilities of rovers in future missions would improve; for example, enabling exploration of permanently shadowed regions, and allowing faster driving speeds and farther travel distances. This thesis demonstrates how …