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Articles 1 - 8 of 8
Full-Text Articles in Engineering
Reliability Models For Smartphone Applications, Sonia Meskini, Ali Bou Nassif, Luiz Fernando Capretz
Reliability Models For Smartphone Applications, Sonia Meskini, Ali Bou Nassif, Luiz Fernando Capretz
Electrical and Computer Engineering Publications
Smartphones have become the most used electronic devices. They carry out most of the functionalities of desktops, offering various useful applications that suit the user’s needs. Therefore, instead of the operator, the user has been the main controller of the device and its applications, therefore its reliability has become an emergent requirement. As a first step, based on collected smartphone applications failure data, we investigated and evaluated the efficacy of Software Reliability Growth Models (SRGMs) when applied to these smartphone data in order to check whether they achieve the same accuracy as in the desktop/laptop area. None of the selected …
Precision Grasp Using An Arm-Hand System As A Hybrid Parallel-Serial System: A Novel Inverse Kinematics Solution, Shuwei Qiu, Shuwei Qiu Ph.D., P.Eng.
Precision Grasp Using An Arm-Hand System As A Hybrid Parallel-Serial System: A Novel Inverse Kinematics Solution, Shuwei Qiu, Shuwei Qiu Ph.D., P.Eng.
Electrical and Computer Engineering Publications
In this letter, we present a novel inverse kinematics (IK) solution for a robotic arm-hand system to achieve precision grasp. This problem is kinematically over-constrained and to address the issue and to solve the problem, we propose a new approach with three key insights. First, we propose a human-inspired thumb-first strategy and consider one finger of the robotic hand as the “thumb” to narrow down the search space and increase the success rate of our algorithm. Second, we formulate the arm-thumb serial chain as a closed chain such that the entire arm-hand system is controlled as a hybrid parallel-serial system. …
Reinforcement Learning Algorithms: An Overview And Classification, Fadi Almahamid, Katarina Grolinger
Reinforcement Learning Algorithms: An Overview And Classification, Fadi Almahamid, Katarina Grolinger
Electrical and Computer Engineering Publications
The desire to make applications and machines more intelligent and the aspiration to enable their operation without human interaction have been driving innovations in neural networks, deep learning, and other machine learning techniques. Although reinforcement learning has been primarily used in video games, recent advancements and the development of diverse and powerful reinforcement algorithms have enabled the reinforcement learning community to move from playing video games to solving complex real-life problems in autonomous systems such as self-driving cars, delivery drones, and automated robotics. Understanding the environment of an application and the algorithms’ limitations plays a vital role in selecting the …
Dynamic Planning Networks, Norman Tasfi, Miriam A M Capretz
Dynamic Planning Networks, Norman Tasfi, Miriam A M Capretz
Electrical and Computer Engineering Publications
We introduce Dynamic Planning Networks (DPN), a novel architecture for deep reinforcement learning, that combines model-based and model-free aspects for online planning. Our architecture learns to dynamically construct plans using a learned state-transition model by selecting and traversing between simulated states and actions to maximize information before acting. DPN learns to efficiently form plans by expanding a single action conditional state transition at a time instead of exhaustively evaluating each action, reducing the number of state-transitions used during planning. We observe emergent planning patterns in our agent, including classical search methods such as breadth-first and depth-first search. DPN shows improved …
Arm-Hand Systems As Hybrid Parallel-Serial Systems: A Novel Inverse Kinematics Solution, Shuwei Qiu, Mehrdad Kermani Ph.D., P.Eng.
Arm-Hand Systems As Hybrid Parallel-Serial Systems: A Novel Inverse Kinematics Solution, Shuwei Qiu, Mehrdad Kermani Ph.D., P.Eng.
Electrical and Computer Engineering Publications
No abstract provided.
Transfer Learning By Similarity Centred Architecture Evolution For Multiple Residential Load Forecasting, Santiago Gomez-Rosero, Miriam A M Capretz, Syed Mir
Transfer Learning By Similarity Centred Architecture Evolution For Multiple Residential Load Forecasting, Santiago Gomez-Rosero, Miriam A M Capretz, Syed Mir
Electrical and Computer Engineering Publications
The development from traditional low voltage grids to smart systems has become extensive and adopted worldwide. Expanding the demand response program to cover the residential sector raises a wide range of challenges. Short term load forecasting for residential consumers in a neighbourhood could lead to a better understanding of low voltage consumption behaviour. Nevertheless, users with similar characteristics can present diversity in consumption patterns. Consequently, transfer learning methods have become a useful tool to tackle differences among residential time series. This paper proposes a method combining evolutionary algorithms for neural architecture search with transfer learning to perform short term load …
‘Digits’ App - Smartphone Augmented Reality For Hand Telerehabilitation, Hongdao Dong, Edward Ho, Herbert Shin, Tania Banerjee, Geoffrey Masschelein, Jacob Davidson, Sandrine De Ribaupierre, Roy Eagleson, Caitlin Symonette
‘Digits’ App - Smartphone Augmented Reality For Hand Telerehabilitation, Hongdao Dong, Edward Ho, Herbert Shin, Tania Banerjee, Geoffrey Masschelein, Jacob Davidson, Sandrine De Ribaupierre, Roy Eagleson, Caitlin Symonette
Electrical and Computer Engineering Publications
Hand telerehabilitation currently has limitations for accurate and remote assessment of range of motion (ROM) in small finger joints. ‘DIGITS’ application utilises the front smartphone camera to measure finger ROM in a reliable and rapid assessment protocol. Our initial beta-phase testing examined the consistency of our software measurements to in-person goniometry. 6 to 9 degrees of difference existed between the smartphone application recorded data versus the in-person measurements. This range is within acceptable 7 to 9 degree tolerance for interrater goniometry measurements. The effect of environmental factors such as hand distance, lightings and hand orientation was evaluated. The intraclass correlation …
A Systematic Review Of Convolutional Neural Network-Based Structural Condition Assessment Techniques, Sandeep Sony, Kyle Dunphy, Ayan Sadhu, Miriam A M Capretz
A Systematic Review Of Convolutional Neural Network-Based Structural Condition Assessment Techniques, Sandeep Sony, Kyle Dunphy, Ayan Sadhu, Miriam A M Capretz
Electrical and Computer Engineering Publications
With recent advances in non-contact sensing technology such as cameras, unmanned aerial and ground vehicles, the structural health monitoring (SHM) community has witnessed a prominent growth in deep learning-based condition assessment techniques of structural systems. These deep learning methods rely primarily on convolutional neural networks (CNNs). The CNN networks are trained using a large number of datasets for various types of damage and anomaly detection and post-disaster reconnaissance. The trained networks are then utilized to analyze newer data to detect the type and severity of the damage, enhancing the capabilities of non-contact sensors in developing autonomous SHM systems. In recent …