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- Machine learning (2)
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Articles 1 - 10 of 10
Full-Text Articles in Electrical and Computer Engineering
A Framework For Stable Robot-Environment Interaction Based On The Generalized Scattering Transformation, Kanstantsin Pachkouski
A Framework For Stable Robot-Environment Interaction Based On The Generalized Scattering Transformation, Kanstantsin Pachkouski
Electronic Thesis and Dissertation Repository
This thesis deals with development and experimental evaluation of control algorithms for stabilization of robot-environment interaction based on the conic systems formalism and scattering transformation techniques. A framework for stable robot-environment interaction is presented and evaluated on a real physical system. The proposed algorithm fundamentally generalizes the conventional passivity-based approaches to the coupled stability problem. In particular, it allows for stabilization of not necessarily passive robot-environment interaction. The framework is based on the recently developed non-planar conic systems formalism and generalized scattering-based stabilization methods. A comprehensive theoretical background on the scattering transformation techniques, planar and non-planar conic systems is presented. …
Virtual Sensor Middleware: Managing Iot Data For The Fog-Cloud Platform, Fadi Almahamid, Hanan Lutfiyya, Katarina Grolinger
Virtual Sensor Middleware: Managing Iot Data For The Fog-Cloud Platform, Fadi Almahamid, Hanan Lutfiyya, Katarina Grolinger
Electrical and Computer Engineering Publications
This paper introduces the Virtual Sensor Middleware (VSM), which facilitates distributed sensor data processing on multiple fog nodes. VSM uses a Virtual Sensor as the core component of the middleware. The virtual sensor concept is redesigned to support functionality beyond sensor/device virtualization, such as deploying a set of virtual sensors to represent an IoT application and distributed sensor data processing across multiple fog nodes. Furthermore, the virtual sensor deals with the heterogeneous nature of IoT devices and the various communication protocols using different adapters to communicate with the IoT devices and the underlying protocol. VSM uses the publish-subscribe design pattern …
Agglomerative Hierarchical Clustering With Dynamic Time Warping For Household Load Curve Clustering, Fadi Almahamid, Katarina Grolinger
Agglomerative Hierarchical Clustering With Dynamic Time Warping For Household Load Curve Clustering, Fadi Almahamid, Katarina Grolinger
Electrical and Computer Engineering Publications
Energy companies often implement various demand response (DR) programs to better match electricity demand and supply by offering the consumers incentives to reduce their demand during critical periods. Classifying clients according to their consumption patterns enables targeting specific groups of consumers for DR. Traditional clustering algorithms use standard distance measurement to find the distance between two points. The results produced by clustering algorithms such as K-means, K-medoids, and Gaussian Mixture Models depend on the clustering parameters or initial clusters. In contrast, our methodology uses a shape-based approach that combines Agglomerative Hierarchical Clustering (AHC) with Dynamic Time Warping (DTW) to classify …
Optimal Inverter And Wire Selection For Solar Photovoltaic Fencing Applications, Koami Soulemane Hayibo, Joshua M. Pearce
Optimal Inverter And Wire Selection For Solar Photovoltaic Fencing Applications, Koami Soulemane Hayibo, Joshua M. Pearce
Electrical and Computer Engineering Publications
Despite the benefits and the economic advantages of agrivoltaics, capital costs limit deployment velocity. One recent potential solution to this challenge is to radically reduce the cost of racking materials by using existing farm fencing as vertical photovoltaic (PV) racking. This type of fenced-based PV system is inherently electrically challenging because of the relatively long distances between individual modules that are not present in more densely packed conventional solar PV farms. This study provides practical insights for inverter selection and wire sizing optimization for fence-based agrivoltaic systems. Numerical simulation sensitivities on the levelized cost of electricity (LCOE) were performed for …
Efficient Discovery And Utilization Of Radio Information In Ultra-Dense Heterogeneous 3d Wireless Networks, Mattaka Gamage Samantha Sriyananda
Efficient Discovery And Utilization Of Radio Information In Ultra-Dense Heterogeneous 3d Wireless Networks, Mattaka Gamage Samantha Sriyananda
Electronic Thesis and Dissertation Repository
Emergence of new applications, industrial automation and the explosive boost of smart concepts have led to an environment with rapidly increasing device densification and service diversification. This revolutionary upward trend has led the upcoming 6th-Generation (6G) and beyond communication systems to be globally available communication, computing and intelligent systems seamlessly connecting devices, services and infrastructure facilities. In this kind of environment, scarcity of radio resources would be upshot to an unimaginably high level compelling them to be very efficiently utilized. In this case, timely action is taken to deviate from approximate site-specific 2-Dimensional (2D) network concepts in radio resource utilization …
Autonomous Unmanned Aerial Vehicle Navigation Using Reinforcement Learning: A Systematic Review, Fadi Almahamid, Katarina Grolinger
Autonomous Unmanned Aerial Vehicle Navigation Using Reinforcement Learning: A Systematic Review, Fadi Almahamid, Katarina Grolinger
Electrical and Computer Engineering Publications
There is an increasing demand for using Unmanned Aerial Vehicle (UAV), known as drones, in different applications such as packages delivery, traffic monitoring, search and rescue operations, and military combat engagements. In all of these applications, the UAV is used to navigate the environment autonomously --- without human interaction, perform specific tasks and avoid obstacles. Autonomous UAV navigation is commonly accomplished using Reinforcement Learning (RL), where agents act as experts in a domain to navigate the environment while avoiding obstacles. Understanding the navigation environment and algorithmic limitations plays an essential role in choosing the appropriate RL algorithm to solve the …
Anonymization & Generation Of Network Packet Datasets Using Deep Learning, Spencer K. Vecile
Anonymization & Generation Of Network Packet Datasets Using Deep Learning, Spencer K. Vecile
Electronic Thesis and Dissertation Repository
Corporate networks are constantly bombarded by malicious actors trying to gain access. The current state of the art in protecting networks is deep learning-based intrusion detection systems (IDS). However, for an IDS to be effective it needs to be trained on a good dataset. The best datasets for training an IDS are real data captured from large corporate networks. Unfortunately, companies cannot release their network data due to privacy concerns creating a lack of public cybersecurity data. In this thesis I take a novel approach to network dataset anonymization using character-level LSTM models to learn the characteristics of a dataset; …
Introduction To Pub/Sub Systems Using Opcua, Mete Isiksalan
Introduction To Pub/Sub Systems Using Opcua, Mete Isiksalan
Undergraduate Student Research Internships Conference
The purpose of the project was to learn and implement the fundamental basics of OPCUA system architecture using pub/sub systems. The system allows the users to create multiple different publishers and subscribers while accessing data from a local server and a primary HTTP server. The system is designed to be a multi-client and multi-server system to simulate real-life scenarios while having two different sources of generated values to send via sockets in OPCUA protocols, multiple different APIs were used for the clients on how they retrieve data as well.
Deep Learning For Load Forecasting With Smart Meter Data: Online And Federated Learning, Mohammad Navid Fekri
Deep Learning For Load Forecasting With Smart Meter Data: Online And Federated Learning, Mohammad Navid Fekri
Electronic Thesis and Dissertation Repository
Electricity load forecasting has been attracting increasing attention because of its importance for energy management, infrastructure planning, and budgeting. In recent years, the proliferation of smart meters has created new opportunities for forecasting on the building and even individual household levels. Machine learning (ML) has achieved great successes in this domain; however, conventional ML techniques require data transfer to a centralized location for model training, therefore, increasing network traffic and exposing data to privacy and security risks. Also, traditional approaches employ offline learning, which means that they are only trained once and miss out on the possibility to learn from …
A New Approach For Grasp Quality Calculation Using Continuous Boundary Formulation Of Grasp Wrench Space, Shuwei Qiu, Mehrdad Kermani Ph.D., P.Eng.
A New Approach For Grasp Quality Calculation Using Continuous Boundary Formulation Of Grasp Wrench Space, Shuwei Qiu, Mehrdad Kermani Ph.D., P.Eng.
Electrical and Computer Engineering Publications
In this paper, we aim to use a continuous formulation to efficiently calculate the well-known wrench-based grasp metric proposed by Ferrari and Canny which is the minimum distance from the wrench space origin to the boundary of the grasp wrench space. Considering the L∞" role="presentation" style="box-sizing: border-box; margin: 0px; padding: 0px; display: inline-block; line-height: normal; font-size: 16.200000762939453px; word-spacing: normal; word-wrap: normal; white-space: nowrap; float: none; direction: ltr; max-width: none; max-height: none; min-width: 0px; min-height: 0px; border: 0px; position: relative;"> metric and the nonlinear friction cone model, the challenge of calculating this metric is to determine the boundary of the grasp …