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Articles 1 - 30 of 277
Full-Text Articles in Engineering
Generalized Conditional Feedback System With Model Uncertainty, Chengbo Dai, Zhiqiang Gao, Yangquan Chen, Donghai Li
Generalized Conditional Feedback System With Model Uncertainty, Chengbo Dai, Zhiqiang Gao, Yangquan Chen, Donghai Li
Electrical and Computer Engineering Faculty Publications
Model uncertainty creates a largely open challenge for industrial process control, which causes a trade-off between robustness and performance optimality. In such a case, we propose a generalized conditional feedback (GCF) system to largely eliminate conflicts between robustness and performance optimality. This approach leverages a nominal model to design an optimal control in the virtual domain and defines an ancillary feedback controller to drive the physical process to track the trajectory of the virtual domain. The effectiveness of the proposed GCF scheme is demonstrated in a simulation for six typical industrial processes and three model-based control methods, and in a …
Blockchain-Based Applications For Smart Grids: An Umbrella Review, Wenbing Zhao, Quan Qi, Jiong Zhou, Xiong Luo Qi
Blockchain-Based Applications For Smart Grids: An Umbrella Review, Wenbing Zhao, Quan Qi, Jiong Zhou, Xiong Luo Qi
Electrical and Computer Engineering Faculty Publications
This article presents an umbrella review of blockchain-based smart grid applications. By umbrella review, we mean that our review is based on systematic reviews of this topic. We aim to synthesize the findings from these systematic reviews and gain deeper insights into this discipline. After studying the systematic reviews, we find it imperative to provide a concise and authoritative description of blockchain technology because many technical inaccuracies permeate many of these papers. This umbrella review is guided by five research questions. The first research question concerns the types of blockchain-based smart grid applications. Existing systematic reviews rarely used a systematic …
Towards An Evolved Immersive Experience: Exploring 5g-And Beyond-Enabled Ultra-Low-Latency Communications For Augmented And Virtual Reality, Ananya Hazarika, Mehdi Rahmati
Towards An Evolved Immersive Experience: Exploring 5g-And Beyond-Enabled Ultra-Low-Latency Communications For Augmented And Virtual Reality, Ananya Hazarika, Mehdi Rahmati
Electrical and Computer Engineering Faculty Publications
Augmented reality and virtual reality technologies are witnessing an evolutionary change in the 5G and Beyond (5GB) network due to their promising ability to enable an immersive and interactive environment by coupling the virtual world with the real one. However, the requirement of low-latency connectivity, which is defined as the end-to-end delay between the action and the reaction, is very crucial to leverage these technologies for a high-quality immersive experience. This paper provides a comprehensive survey and detailed insight into various advantageous approaches from the hardware and software perspectives, as well as the integration of 5G technology, towards 5GB, in …
An Ultrasensitive Bacterial Detection Platform For Culture-Free Diagnosis Of Infections, Xuyang Shi
An Ultrasensitive Bacterial Detection Platform For Culture-Free Diagnosis Of Infections, Xuyang Shi
ETD Archive
The current methods of the diagnosis of bloodstream infections are based on bacterial culture growth, a process that requires considerable time, e.g., 12-16 hours, to obtain a result. This long wait time for the result creates many problems, including the generation of multi-drug resistant organisms (MDROs). At the same time, infected bloodstream usually contains a very low concentration of bacteria, i.e., lower than 5 CFU/mL. The long diagnosis time and the extremely low concentration of bacteria in the infected bloodstream make such infections difficult to diagnose. Here, we demonstrate a culture-free approach for the diagnosis of bloodstream infections using a …
Effective Short Text Classification Via The Fusion Of Hybrid Features For Iot Social Data, Xiong Luo, Zhijian Yu, Zhigang Zhao, Wenbing Zhao, Jenq-Haur Wang
Effective Short Text Classification Via The Fusion Of Hybrid Features For Iot Social Data, Xiong Luo, Zhijian Yu, Zhigang Zhao, Wenbing Zhao, Jenq-Haur Wang
Electrical and Computer Engineering Faculty Publications
Nowadays short texts can be widely found in various social data in relation to the 5G-enabled Internet of Things (IoT). Short text classification is a challenging task due to its sparsity and the lack of context. Previous studies mainly tackle these problems by enhancing the semantic information or the statistical information individually. However, the improvement achieved by a single type of information is limited, while fusing various information may help to improve the classification accuracy more effectively. To fuse various information for short text classification, this article proposes a feature fusion method that integrates the statistical feature and the comprehensive …
Machine Learning Used In Biomedical Computing And Intelligence Healthcare, Volume Ii, Honghao Gao, Ying Li, Zijian Zhang, Wenbing Zhao
Machine Learning Used In Biomedical Computing And Intelligence Healthcare, Volume Ii, Honghao Gao, Ying Li, Zijian Zhang, Wenbing Zhao
Electrical and Computer Engineering Faculty Publications
No abstract provided.
An Analytical Methodology To Security Constraints Management In Power System Operation, Shubo Zhang
An Analytical Methodology To Security Constraints Management In Power System Operation, Shubo Zhang
ETD Archive
In a deregulated electricity market, Independent System Operators (ISOs) are responsible for dispatching power to the load securely, efficiently, and economically. ISO performs Security Constrained Unit Commitment (SCUC) to guarantee sufficient generation commitment, maximized social welfare and facilitating market-driven economics. A large number of security constraints would render the model impossible to solve under time requirements. Developing a method to identify the minimum set of security constraints without overcommitting is necessary to reduce Mixed Integer Linear Programming (MILP) solution time. To overcome this challenge, we developed a powerful tool called security constraint screening. The proposed approach effectively filters out non-dominating …
Research And Simulation Of Dc Microgrid Three-Phase Ac-Dc Converter Control Strategy Based On Double Loop, Boning Wu, Zhiqiang Gao, Xuesong Zhou, Youjie Ma, Chenglong Wang
Research And Simulation Of Dc Microgrid Three-Phase Ac-Dc Converter Control Strategy Based On Double Loop, Boning Wu, Zhiqiang Gao, Xuesong Zhou, Youjie Ma, Chenglong Wang
Electrical and Computer Engineering Faculty Publications
The new voltage and current double loop control strategy is proposed to solve the DC microgrid bus voltage fluctuation caused by loads fluctuation, parameters perturbation and unbalanced three-phase power supply. Firstly, the dq axis mathematical model of three-phase AC-DC bidirectional converter in DC microgrid is analyzed and established, and then the controllers are designed according to the dq axis mathematical model. The outer loop is a voltage loop based on variable gain linear extended state observer (VGLESO) and sliding mode theory. VGLESO can not only effectively overcome the problem of peak output of traditional high-gain LESO in the initial stage …
On The Conceptualization Of Total Disturbance And Its Profound Implications, Sen Chen, Wenyan Bai, Yu Hu, Yi Huang, Wenbing Zhao
On The Conceptualization Of Total Disturbance And Its Profound Implications, Sen Chen, Wenyan Bai, Yu Hu, Yi Huang, Wenbing Zhao
Electrical and Computer Engineering Faculty Publications
No abstract provided.
An Extensive Set Of Kinematic And Kinetic Data For Individuals With Intact Limbs And Transfemoral Prosthesis Users, Seyed Abolfazl Fakoorian, Arash Roshanineshat, Poya Khalaf, Vahid Azimi, Daniel J. Simon, Elizabeth Hardin
An Extensive Set Of Kinematic And Kinetic Data For Individuals With Intact Limbs And Transfemoral Prosthesis Users, Seyed Abolfazl Fakoorian, Arash Roshanineshat, Poya Khalaf, Vahid Azimi, Daniel J. Simon, Elizabeth Hardin
Electrical and Computer Engineering Faculty Publications
This paper introduces an extensive human motion data set for typical activities of daily living. These data are crucial for the design and control of prosthetic devices for transfemoral prosthesis users. This data set was collected from seven individuals, including five individuals with intact limbs and two transfemoral prosthesis users. These data include the following types of movements: (1) walking at three different speeds; (2) walking up and down a 5-degree ramp; (3) stepping up and down; (4) sitting down and standing up. We provide full-body marker trajectories and ground reaction forces (GRFs) as well as joint angles, joint velocities, …
Control Of Rigid Robots With Large Uncertainties Using The Function Approximation Technique, Donald Ebeigbe
Control Of Rigid Robots With Large Uncertainties Using The Function Approximation Technique, Donald Ebeigbe
ETD Archive
This dissertation focuses on the control of rigid robots that cannot easily be modeled due to complexity and large uncertainties. The function approximation technique (FAT), which represents uncertainties as finite linear combinations of orthonormal basis functions, provides an alternate form of robot control - in situations where the dynamic equation cannot easily be modeled - with no dependency on the use of model information or training data. This dissertation has four aims - using the FAT - to improve controller efficiency and robustness in scenarios where reliable mathematical models cannot easily be derived or are otherwise unavailable. The first aim …
Co-Optimization Approach To Post-Storm Recovery For Interdependent Power And Transportation Systems, Yinyin Ge, Lili Du, Hongzing Ye
Co-Optimization Approach To Post-Storm Recovery For Interdependent Power And Transportation Systems, Yinyin Ge, Lili Du, Hongzing Ye
Electrical and Computer Engineering Faculty Publications
The power and transportation systems are urban interdependent critical infrastructures (CIs). During the post-disaster restoration process, transportation mobility and power restoration process are interdependent, and their functionalities significantly affect other well-beings of other urban CIs. Therefore, to enhance the resilience of urban CIs, successful recovery strategies should promote CI function cooperatively and synergistically to distribute goods and services efficiently. This paper develops an integrative framework that addresses the challenges of enhancing the recovery efficiency of urban power and transportation systems in short-term recovery period. Specifically, the post-storm recovery process is considered as a scheduling problem under the constraints representing crew …
Robust Impedance Control Of A Four Degree Of Freedom Exercise Robot, Santino Joseph Bianco
Robust Impedance Control Of A Four Degree Of Freedom Exercise Robot, Santino Joseph Bianco
ETD Archive
The CSU 4OptimX exercise robot provides a platform for future research into advanced exercise and rehabilitation. The robot and its control system will autonomously modify reference trajectories and impedances on the basis of an optimization criterion and physiological feedback. To achieve this goal, a robust impedance control system with trajectory tracking must be implemented as the foundational control scheme. Two control laws will be compared, sliding mode and H-infinity control. The above robust control laws are combined with underlying impedance control laws to overcome uncertain plant model parameters and disturbance anomalies affecting the input signal. The sliding mode control law …
State Estimation For An Agonistic‐Antagonistic Muscle System, Thang Tien Nguyen, Holly Warner, Hung La, Hanieh Mohammadi, Daniel J. Simon, Hanz Richter
State Estimation For An Agonistic‐Antagonistic Muscle System, Thang Tien Nguyen, Holly Warner, Hung La, Hanieh Mohammadi, Daniel J. Simon, Hanz Richter
Electrical and Computer Engineering Faculty Publications
Research on assistive technology, rehabilitation, and prosthetics requires the understanding of human machine interaction, in which human muscular properties play a pivotal role. This paper studies a nonlinear agonistic‐antagonistic muscle system based on the Hill muscle model. To investigate the characteristics of the muscle model, the problem of estimating the state variables and activation signals of the dual muscle system is considered. In this work, parameter uncertainty and unknown inputs are taken into account for the estimation problem. Three observers are presented: a high gain observer, a sliding mode observer, and an adaptive sliding mode observer. Theoretical analysis shows the …
High Order Volumetric Directional Pattern For Video-Based Face Recognition, Almabrok Essa, Vijayan Asari
High Order Volumetric Directional Pattern For Video-Based Face Recognition, Almabrok Essa, Vijayan Asari
Electrical and Computer Engineering Faculty Publications
Describing the dynamic textures has attracted growing attention in the field of computer vision and pattern recognition. In this paper, a novel approach for recognizing dynamic textures, namely, high order volumetric directional pattern (HOVDP), is proposed. It is an extension of the volumetric directional pattern (VDP) which extracts and fuses the temporal information (dynamic features) from three consecutive frames. HOVDP combines the movement and appearance features together considering the nth order volumetric directional variation patterns of all neighboring pixels from three consecutive frames. In experiments with two challenging video face databases, YouTube Celebrities and Honda/UCSD, HOVDP clearly outperformed a set …
Intelligent Sensing And Decision Making In Smart Technologies, Wenbing Zhao, Jinsong Wu, Peng Shi, Hongqiao Wang
Intelligent Sensing And Decision Making In Smart Technologies, Wenbing Zhao, Jinsong Wu, Peng Shi, Hongqiao Wang
Electrical and Computer Engineering Faculty Publications
No abstract provided.
Short-Term Wind Speed Forecasting Via Stacked Extreme Learning Machine With Generalized Correntropy, Xiong Luo, Jiankun Sun, Long Wang, Weiping Wang, Wenbing Zhao, Jinsong Wu, Jenq-Haur Wang, Zijun Zhang
Short-Term Wind Speed Forecasting Via Stacked Extreme Learning Machine With Generalized Correntropy, Xiong Luo, Jiankun Sun, Long Wang, Weiping Wang, Wenbing Zhao, Jinsong Wu, Jenq-Haur Wang, Zijun Zhang
Electrical and Computer Engineering Faculty Publications
Recently, wind speed forecasting as an effective computing technique plays an important role in advancing industry informatics, while dealing with these issues of control and operation for renewable power systems. However, it is facing some increasing difficulties to handle the large-scale dataset generated in these forecasting applications, with the purpose of ensuring stable computing performance. In response to such limitation, this paper proposes a more practical approach through the combination of extreme-learning machine (ELM) method and deep-learning model. ELM is a novel computing paradigm that enables the neural network (NN) based learning to be achieved with fast training speed and …
Active Disturbance Rejection Control Of Lcl-Filtered Grid-Connected Inverter Using Pade Approximation, Abdeldjabar Benrabah, Dianguo Xu, Zhiqiang Gao
Active Disturbance Rejection Control Of Lcl-Filtered Grid-Connected Inverter Using Pade Approximation, Abdeldjabar Benrabah, Dianguo Xu, Zhiqiang Gao
Electrical and Computer Engineering Faculty Publications
In this paper, a simplified robust control is proposed to improve the performance of a three-phase current controlled voltage source inverter connected to the grid through an inductive-capacitive-inductive ( LCL) filter. The presence of the LCL-filter resonance complicates the dynamics of the control system and limits its overall performance, particularly when disturbances and parametric uncertainty are considered. To solve this problem, a robust active damping method based on the linear active disturbance rejection control (LADRC) is proposed. The simplification is made possible by order reduction in the plant transfer function using Padé approximation. Simulation results show that the proposed LADRC-based …
Resource Allocation In The Cognitive Radio Network-Aided Internet Of Things For The Cyber-Physical-Social System: An Efficient Jaya Algorithm, Xiong Luo, Zhijie He, Zhigang Zhao, Long Wang, Weiping Wang, Huansheng Ning, Jenq-Haur Wang, Wenbing Zhao, Jun Zhang
Resource Allocation In The Cognitive Radio Network-Aided Internet Of Things For The Cyber-Physical-Social System: An Efficient Jaya Algorithm, Xiong Luo, Zhijie He, Zhigang Zhao, Long Wang, Weiping Wang, Huansheng Ning, Jenq-Haur Wang, Wenbing Zhao, Jun Zhang
Electrical and Computer Engineering Faculty Publications
Currently, there is a growing demand for the use of communication network bandwidth for the Internet of Things (IoT) within the cyber-physical-social system (CPSS), while needing progressively more powerful technologies for using scarce spectrum resources. Then, cognitive radio networks (CRNs) as one of those important solutions mentioned above, are used to achieve IoT effectively. Generally, dynamic resource allocation plays a crucial role in the design of CRN-aided IoT systems. Aiming at this issue, orthogonal frequency division multiplexing (OFDM) has been identified as one of the successful technologies, which works with a multi-carrier parallel radio transmission strategy. In this article, through …
Finite-Time Anti-Synchronization Of Memristive Stochastic Bam Neural Networks With Probabilistic Time-Varying Delays, Manman Yuan, Weiping Wang, Xiong Luo, Linlin Liu, Wenbing Zhao
Finite-Time Anti-Synchronization Of Memristive Stochastic Bam Neural Networks With Probabilistic Time-Varying Delays, Manman Yuan, Weiping Wang, Xiong Luo, Linlin Liu, Wenbing Zhao
Electrical and Computer Engineering Faculty Publications
This paper investigates the drive-response finite-time anti-synchronization for memristive bidirectional associative memory neural networks (MBAMNNs). Firstly, a class of MBAMNNs with mixed probabilistic time-varying delays and stochastic perturbations is first formulated and analyzed in this paper. Secondly, an nonlinear control law is constructed and utilized to guarantee drive-response finite-time anti-synchronization of the neural networks. Thirdly, by employing some inequality technique and constructing an appropriate Lyapunov function, some anti-synchronization criteria are derived. Finally, a number simulation is provided to demonstrate the effectiveness of the proposed mechanism.
Surrogate Affine Approximation Based Co-Optimization Of Transactive Flexibility, Uncertainty, And Energy, Hongzing Ye
Surrogate Affine Approximation Based Co-Optimization Of Transactive Flexibility, Uncertainty, And Energy, Hongzing Ye
Electrical and Computer Engineering Faculty Publications
This study presents an approach to co-optimization of transactive flexibility, energy, and optimal injection-range of Variable Energy Resource (VER). Flexibility receives immense attention, as it is the essential resource to accommodate VERs in modern power systems. With a novel concept of transactive flexibility, the proposed approach proactively positions the flexible resources and optimizes the demand of flexibility. A surrogate affine approximation (SAA) method is proposed to solve the problem with variable infinite-constraint range in polynomial time. It is shown that SAA is more optimistic than the traditional affine policy in the power literature. The SAA method is also applicable to …
Correction To: Dependability Enhancing Mechanisms For Integrated Clinical Environments (Vol 73, Pg 4207, 2017), Wenbing Zhao, Mary Q. Yang
Correction To: Dependability Enhancing Mechanisms For Integrated Clinical Environments (Vol 73, Pg 4207, 2017), Wenbing Zhao, Mary Q. Yang
Electrical and Computer Engineering Faculty Publications
No abstract provided.
Human Activity Tracking And Recognition Using Kinect Sensor, Roanna Lun
Human Activity Tracking And Recognition Using Kinect Sensor, Roanna Lun
ETD Archive
The objective of this dissertation research is to use Kinect sensor, a motion sensing input device, to develop an integrated software system that can be used for tracking non-compliant activity postures of consented health-care workers for assisting the workers' compliance to best practices, allowing individualized gestures for privacy-aware user registration, movement recognition using rule-based algorithm, real-time feedback, and exercises data collection. The research work also includes developing a graphical user interface and data visualization program for illustrating statistical information for administrator, as well as utilizing cloud based database system used for data resource.
A Transformative Process Control Solution, Simone Castanho Nobrega De Almedia Soares
A Transformative Process Control Solution, Simone Castanho Nobrega De Almedia Soares
ETD Archive
Knowing that a technology invented almost hundred years ago (PID controller) is still dominating industrial process control, a historical review was done to understand how the control field evolved. Model dependency and high level of mathematics appear as the main reasons that prevent other technologies from penetrating the engineering practice. A relatively novel methodology introduced by J. Han in 1998 called Active Disturbance Rejection Control (ADRC) came with characteristics that matches process control needs and restrictions on model dependency. This study will present a transformative solution for process control based on that. The control algorithm is designed and discretized for …
School Logo Cleveland State University Logo Title Evolutionary Optimization For Safe Navigation Of An Autonomous Robot In Cluttered Dynamic Unknown Environments, Arash Roshanineshat
School Logo Cleveland State University Logo Title Evolutionary Optimization For Safe Navigation Of An Autonomous Robot In Cluttered Dynamic Unknown Environments, Arash Roshanineshat
ETD Archive
We present a path planning approach based on probabilistic methods for a robot to navigate in a cluttered, dynamic, unknown environment. There are dynamic obstacles moving around and static obstacles located in the map. The robot does not have any prior information about them but should be able to navigate through the map beginning from a known starting point and safely ending at a known target point. The only information the robot has is the location of the starting point and the target point and it uses sensory information to collect information about its surroundings. Our method is compared to …
Evolutionary Optimization For Safe Navigation Of An Autonomous Robot In Cluttered Dynamic Unknown Environments, Arash Roshanineshat
Evolutionary Optimization For Safe Navigation Of An Autonomous Robot In Cluttered Dynamic Unknown Environments, Arash Roshanineshat
ETD Archive
We present a path planning approach based on probabilistic methods for a robot to navigate in a cluttered, dynamic, unknown environment. There are dynamic obstacles moving around and static obstacles located in the map. The robot does not have any prior information about them but should be able to navigate through the map beginning from a known starting point and safely ending at a known target point. The only information the robot has is the location of the starting point and the target point and it uses sensory information to collect information about its surroundings. Our method is compared to …
Virtual Reality Based Serious Games For Stna Training, Ryan Thomas Kall
Virtual Reality Based Serious Games For Stna Training, Ryan Thomas Kall
Undergraduate Research Posters 2018
In this project, exploratory steps have been taken towards the development of a set of serious games for state tested nursing assistants (STNAs) education and training, which promises to make the training more engaging and effective. Tasks include getting familiar with developing 3D scenes with Unity, human activity recognition with Microsoft Kinect, creating holograms with Microsoft HoloLens, and help implement a gaze-based mechanism for performance assessment in patient transfer skills.
Dependability Enhancing Mechanisms For Integrated Clinical Environments, Wenbing Zhao, Mary Q. Yang
Dependability Enhancing Mechanisms For Integrated Clinical Environments, Wenbing Zhao, Mary Q. Yang
Electrical and Computer Engineering Faculty Publications
In this article, we present a set of lightweight mechanisms to enhance the dependability of a safety-critical real-time distributed system referred to as an integrated clinical environment (ICE). In an ICE, medical devices are interconnected and work together with the help of a supervisory computer system to enhance patient safety during clinical operations. Inevitably, there are strong dependability requirements on the ICE. We introduce a set of mechanisms that essentially make the supervisor component a trusted computing base, which can withstand common hardware failures and malicious attacks. The mechanisms rely on the replication of the supervisor component and employ only …
Design Optimization Of A High Power Led Matrix Luminaire, Jose Luiz F. Barbosa, Daniel J. Simon, Wesley P. Calixto
Design Optimization Of A High Power Led Matrix Luminaire, Jose Luiz F. Barbosa, Daniel J. Simon, Wesley P. Calixto
Electrical and Computer Engineering Faculty Publications
This work presents a methodology for optimizing the layout and geometry of an m x n high power (HP) light emitting diode (LED) luminaire. Two simulators are used to analyze an LED luminaire model. The first simulator uses the finite element method (FEM) to analyze the thermal dissipation, and the second simulator uses the ray tracing method for lighting analysis. The thermal and lighting analysis of the luminaire model is validated with an error of less than 10%. The goal of the optimization process is to find a solution that satisfies both thermal dissipation and light efficiency. The optimization goal …
Maintaining Parallel Realities In Cqrs And Event Sourcing, Ehren Thomas Eschmann
Maintaining Parallel Realities In Cqrs And Event Sourcing, Ehren Thomas Eschmann
ETD Archive
In today’s distributed software ecosystem, we have witnessed a broad exhibition of notable approaches to software architecture. Traditionally, these approaches have centered around persisting a system’s current state. Rather than adhere to these criteria, two modern architectures, Command Query Responsibility Segregation (CQRS) and Event Sourcing have inspired us to persist the interactions of the software actor as replayable events which describe the history of their input data.
While CQRS and Event Sourcing allow for considerable benefits in many types of
systems, maintaining parallel realities (multiple snapshots of history deriving from a single parent history) is generally regarded as too complex …