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Articles 1 - 11 of 11
Full-Text Articles in Computer Engineering
On The Impact Of Gravity Compensation On Reinforcement Learning In Goal-Reaching Tasks For Robotic Manipulators, Jonathan Fugal, Hasan A. Poonawala, Jihye Bae
On The Impact Of Gravity Compensation On Reinforcement Learning In Goal-Reaching Tasks For Robotic Manipulators, Jonathan Fugal, Hasan A. Poonawala, Jihye Bae
Electrical and Computer Engineering Faculty Publications
Advances in machine learning technologies in recent years have facilitated developments in autonomous robotic systems. Designing these autonomous systems typically requires manually specified models of the robotic system and world when using classical control-based strategies, or time consuming and computationally expensive data-driven training when using learning-based strategies. Combination of classical control and learning-based strategies may mitigate both requirements. However, the performance of the combined control system is not obvious given that there are two separate controllers. This paper focuses on one such combination, which uses gravity-compensation together with reinforcement learning (RL). We present a study of the effects of gravity …
Influence Spread In Two-Layer Interdependent Networks: Designed Single-Layer Or Random Two-Layer Initial Spreaders?, Hana Khamfroush, Nathaniel Hudson, Samuel Iloo, Mahshid R. Naeini
Influence Spread In Two-Layer Interdependent Networks: Designed Single-Layer Or Random Two-Layer Initial Spreaders?, Hana Khamfroush, Nathaniel Hudson, Samuel Iloo, Mahshid R. Naeini
Computer Science Faculty Publications
Influence spread in multi-layer interdependent networks (M-IDN) has been studied in the last few years; however, prior works mostly focused on the spread that is initiated in a single layer of an M-IDN. In real world scenarios, influence spread can happen concurrently among many or all components making up the topology of an M-IDN. This paper investigates the effectiveness of different influence spread strategies in M-IDNs by providing a comprehensive analysis of the time evolution of influence propagation given different initial spreader strategies. For this study we consider a two-layer interdependent network and a general probabilistic threshold influence spread model …
Anonymous And Efficient Message Authentication Scheme For Smart Grid, Libing Wu, Jing Wang, Sherali Zeadally, Debiao He
Anonymous And Efficient Message Authentication Scheme For Smart Grid, Libing Wu, Jing Wang, Sherali Zeadally, Debiao He
Information Science Faculty Publications
Smart grid has emerged as the next-generation electricity grid with power flow optimization and high power quality. Smart grid technologies have attracted the attention of industry and academia in the last few years. However, the tradeoff between security and efficiency remains a challenge in the practical deployment of the smart grid. Most recently, Li et al. proposed a lightweight message authentication scheme with user anonymity and claimed that their scheme is provably secure. But we found that their scheme fails to achieve mutual authentication and mitigate some typical attacks (e.g., impersonation attack, denial of service attack) in the smart grid …
Facepet: Enhancing Bystanders' Facial Privacy With Smart Wearables/Internet Of Things, Alfredo J. Perez, Sherali Zeadally, Luis Y. Matos Garcia, Jaouad A. Mouloud, Scott Griffith
Facepet: Enhancing Bystanders' Facial Privacy With Smart Wearables/Internet Of Things, Alfredo J. Perez, Sherali Zeadally, Luis Y. Matos Garcia, Jaouad A. Mouloud, Scott Griffith
Information Science Faculty Publications
Given the availability of cameras in mobile phones, drones and Internet-connected devices, facial privacy has become an area of major interest in the last few years, especially when photos are captured and can be used to identify bystanders’ faces who may have not given consent for these photos to be taken and be identified. Some solutions to protect facial privacy in photos currently exist. However, many of these solutions do not give a choice to bystanders because they rely on algorithms that de-identify photos or protocols to deactivate devices and systems not controlled by bystanders, thereby being dependent on the …
Advanced Recurrent Network-Based Hybrid Acoustic Models For Low Resource Speech Recognition, Jian Kang, Wei-Qiang Zhang, Wei-Wei Liu, Jia Liu, Michael T. Johnson
Advanced Recurrent Network-Based Hybrid Acoustic Models For Low Resource Speech Recognition, Jian Kang, Wei-Qiang Zhang, Wei-Wei Liu, Jia Liu, Michael T. Johnson
Electrical and Computer Engineering Faculty Publications
Recurrent neural networks (RNNs) have shown an ability to model temporal dependencies. However, the problem of exploding or vanishing gradients has limited their application. In recent years, long short-term memory RNNs (LSTM RNNs) have been proposed to solve this problem and have achieved excellent results. Bidirectional LSTM (BLSTM), which uses both preceding and following context, has shown particularly good performance. However, the computational requirements of BLSTM approaches are quite heavy, even when implemented efficiently with GPU-based high performance computers. In addition, because the output of LSTM units is bounded, there is often still a vanishing gradient issue over multiple layers. …
Compact Hardware Implementation Of A Sha-3 Core For Wireless Body Sensor Networks, Yi Yang, Debiao He, Neeraj Kumar, Sherali Zeadally
Compact Hardware Implementation Of A Sha-3 Core For Wireless Body Sensor Networks, Yi Yang, Debiao He, Neeraj Kumar, Sherali Zeadally
Information Science Faculty Publications
One of the most important Internet of Things applications is the wireless body sensor network (WBSN), which can provide universal health care, disease prevention, and control. Due to large deployments of small scale smart sensors in WBSNs, security, and privacy guarantees (e.g., security and safety-critical data, sensitive private information) are becoming a challenging issue because these sensor nodes communicate using an open channel, i.e., Internet. We implement data integrity (to resist against malicious tampering) using the secure hash algorithm 3 (SHA-3) when smart sensors in WBSNs communicate with each other using the Internet. Due to the limited resources (i.e., storage, …
Fault Identification And Location For Distribution Network With Distributed Generations, Wen Fan, Yuan Liao
Fault Identification And Location For Distribution Network With Distributed Generations, Wen Fan, Yuan Liao
Electrical and Computer Engineering Faculty Publications
Power distribution networks with distributed generations may experience faults. It is essential to promptly locate the fault for fast repair and restoration. This paper presents a novel method for identifying the faulted section and accurate location of faults that occur on power distribution grid. Appropriate matrices are set up to represent meter locations on the grid and the topology of the grid. The voltage and current measurements obtained are utilized to decide the fault sections. Then fault location is determined by solving equations that link measurements and fault locations through bus impedance matrix. The method is applicable to both single …
A Fast And Robust Extrinsic Calibration For Rgb-D Camera Networks, Po-Chang Su, Ju Shen, Wanxin Xu, Sen-Ching S. Cheung, Ying Luo
A Fast And Robust Extrinsic Calibration For Rgb-D Camera Networks, Po-Chang Su, Ju Shen, Wanxin Xu, Sen-Ching S. Cheung, Ying Luo
Electrical and Computer Engineering Faculty Publications
From object tracking to 3D reconstruction, RGB-Depth (RGB-D) camera networks play an increasingly important role in many vision and graphics applications. Practical applications often use sparsely-placed cameras to maximize visibility, while using as few cameras as possible to minimize cost. In general, it is challenging to calibrate sparse camera networks due to the lack of shared scene features across different camera views. In this paper, we propose a novel algorithm that can accurately and rapidly calibrate the geometric relationships across an arbitrary number of RGB-D cameras on a network. Our work has a number of novel features. First, to cope …
Energy-Efficient Soft Real-Time Scheduling For Parameter Estimation In Wsns, Senlin Zhang, Zixiang Wang, Meikang Qiu, Meiqin Liu
Energy-Efficient Soft Real-Time Scheduling For Parameter Estimation In Wsns, Senlin Zhang, Zixiang Wang, Meikang Qiu, Meiqin Liu
Electrical and Computer Engineering Faculty Publications
In wireless sensor networks (WSNs), homogeneous or heterogenous sensor nodes are deployed at a certain area to monitor our curious target. The sensor nodes report their observations to the base station (BS), and the BS should implement the parameter estimation with sensors’ data. Best linear unbiased estimation (BLUE) is a common estimator in the parameter estimation. Due to the end-to-end packet delay, it takes some time for the BS to receive sufficient data for the estimation. In some soft real-time applications, we expect that the estimation can be completed before the deadline with a probability. The existing approaches usually guarantee …
An Probability-Based Energy Model On Cache Coherence Protocol With Mobile Sensor Network, Jihe Wang, Bing Guo, Meikang Qiu
An Probability-Based Energy Model On Cache Coherence Protocol With Mobile Sensor Network, Jihe Wang, Bing Guo, Meikang Qiu
Electrical and Computer Engineering Faculty Publications
Mobile sensor networks (MSNs) are widely used in various domains to monitor, record, compute, and interact the information within an environment. To prolong the life time of each node in MSNs, energy model and conservation should be considered carefully when designing the data communication mechanism in the network. The limited battery volume and high workload on channels worsen the life times of the busy nodes. In this paper, we propose a new energy evaluating methodology of packet transmissions in MSNs, which is based on redividing network layers and describing the synchronous data flow with matrix form. We first introduce the …
On Reducing Communication Energy Using Cross-Sensor Coding Technique, Kien Nguyen, Thinh Nguyen, Sen-Ching Cheung
On Reducing Communication Energy Using Cross-Sensor Coding Technique, Kien Nguyen, Thinh Nguyen, Sen-Ching Cheung
Electrical and Computer Engineering Faculty Publications
This paper addresses the uneven communication energy problem in data gathering sensor networks where the nodes closer to the sink tend to consume more energy than those of the farther nodes. Consequently, the lifetime of a network is significantly shortened. We propose a cross-sensor coding technique using On-Off keying which exploits (a) the tradeoff between delay and energy consumption and (b) the network topology in order to alleviate the problem of unequal energy consumption. We formulate our coding problem as an integer linear programming problem and show how to construct a number of codes based on different criteria. We show …