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Articles 1 - 24 of 24
Full-Text Articles in Engineering
Convolutional Spiking Neural Networks For Intent Detection Based On Anticipatory Brain Potentials Using Electroencephalogram, Nathan Lutes, V. Sriram Siddhardh Nadendla, K. Krishnamurthy
Convolutional Spiking Neural Networks For Intent Detection Based On Anticipatory Brain Potentials Using Electroencephalogram, Nathan Lutes, V. Sriram Siddhardh Nadendla, K. Krishnamurthy
Computer Science Faculty Research & Creative Works
Spiking neural networks (SNNs) are receiving increased attention because they mimic synaptic connections in biological systems and produce spike trains, which can be approximated by binary values for computational efficiency. Recently, the addition of convolutional layers to combine the feature extraction power of convolutional networks with the computational efficiency of SNNs has been introduced. This paper studies the feasibility of using a convolutional spiking neural network (CSNN) to detect anticipatory slow cortical potentials (SCPs) related to braking intention in human participants using an electroencephalogram (EEG). Data was collected during an experiment wherein participants operated a remote-controlled vehicle on a testbed …
Lrs: Enhancing Adversarial Transferability Through Lipschitz Regularized Surrogate, Tao Wu, Tony Tie Luo, Donald C. Wunsch
Lrs: Enhancing Adversarial Transferability Through Lipschitz Regularized Surrogate, Tao Wu, Tony Tie Luo, Donald C. Wunsch
Computer Science Faculty Research & Creative Works
The Transferability of Adversarial Examples is of Central Importance to Transfer-Based Black-Box Adversarial Attacks. Previous Works for Generating Transferable Adversarial Examples Focus on Attacking Given Pretrained Surrogate Models While the Connections between Surrogate Models and Adversarial Trasferability Have Been overlooked. in This Paper, We Propose Lipschitz Regularized Surrogate (LRS) for Transfer-Based Black-Box Attacks, a Novel Approach that Transforms Surrogate Models towards Favorable Adversarial Transferability. using Such Transformed Surrogate Models, Any Existing Transfer-Based Black-Box Attack Can Run Without Any Change, Yet Achieving Much Better Performance. Specifically, We Impose Lipschitz Regularization on the Loss Landscape of Surrogate Models to Enable a Smoother …
Cr-Sam: Curvature Regularized Sharpness-Aware Minimization, Tao Wu, Tony Tie Luo, Donald C. Wunsch
Cr-Sam: Curvature Regularized Sharpness-Aware Minimization, Tao Wu, Tony Tie Luo, Donald C. Wunsch
Computer Science Faculty Research & Creative Works
The Capacity to Generalize to Future Unseen Data Stands as One of the Utmost Crucial Attributes of Deep Neural Networks. Sharpness-Aware Minimization (SAM) Aims to Enhance the Generalizability by Minimizing Worst-Case Loss using One-Step Gradient Ascent as an Approximation. However, as Training Progresses, the Non-Linearity of the Loss Landscape Increases, Rendering One-Step Gradient Ascent Less Effective. on the Other Hand, Multi-Step Gradient Ascent Will Incur Higher Training Cost. in This Paper, We Introduce a Normalized Hessian Trace to Accurately Measure the Curvature of Loss Landscape on Both Training and Test Sets. in Particular, to Counter Excessive Non-Linearity of Loss Landscape, …
Demo-Abstract: A Dtn System For Tracking Miners Using Gae-Lstm And Contact Graph Routing In An Underground Mine, Abhay Goyal, Sanjay Kumar Madria, Samuel Frimpong
Demo-Abstract: A Dtn System For Tracking Miners Using Gae-Lstm And Contact Graph Routing In An Underground Mine, Abhay Goyal, Sanjay Kumar Madria, Samuel Frimpong
Computer Science Faculty Research & Creative Works
Localization and prediction of movement of miners in underground mines have been a constant problem more so during a mine disaster. Due to the unavailability of GPS signals, the pillars are used as a method to locate these miners, and thus, location prediction is also carried out with reference to these pillars. In this work, we demon- strate a Delay-tolerant Network (DTN) system called Miner-Finder that leverages Machine Learning (ML) framework (GAE-LSTM) that works on edge devices (e.g., mobile phones, tablets) to predict the location of miners in an underground mine. The information such as speed, angle, time, nearest pillar …
A Dtn-Based Spatio-Temporal Routing Using Location Prediction Model In Underground Mines, Abhay Goyal, Sanjay Kumar Madria, Samuel Frimpong
A Dtn-Based Spatio-Temporal Routing Using Location Prediction Model In Underground Mines, Abhay Goyal, Sanjay Kumar Madria, Samuel Frimpong
Computer Science Faculty Research & Creative Works
Situational awareness during any disaster depends on effective communication and location tracking. In the case of underground mines, where the communication methods are mostly central, the whole communication channel would be rendered unusable during a disaster. To this end, we propose the use of Delay Tolerant Networks (DTN) to allow the miners to function in a distributed manner and help in locating the injured miners and routing distress messages. Due to the unavailability of GPS signals, the pillar numbers are used to identify the locations of the miners. For spatio-temporal routing of messages, we formulate a new scheme using Contact …
Action Recognition In Manufacturing Assembly Using Multimodal Sensor Fusion, Md. Al-Amin, Wenjin Tao, David Doell, Ravon Lingard, Zhaozheng Yin, Ming-Chuan Leu, Ruwen Qin
Action Recognition In Manufacturing Assembly Using Multimodal Sensor Fusion, Md. Al-Amin, Wenjin Tao, David Doell, Ravon Lingard, Zhaozheng Yin, Ming-Chuan Leu, Ruwen Qin
Computer Science Faculty Research & Creative Works
Production innovations are occurring faster than ever. Manufacturing workers thus need to frequently learn new methods and skills. In fast changing, largely uncertain production systems, manufacturers with the ability to comprehend workers' behavior and assess their operation performance in near real-time will achieve better performance than peers. Action recognition can serve this purpose. Despite that human action recognition has been an active field of study in machine learning, limited work has been done for recognizing worker actions in performing manufacturing tasks that involve complex, intricate operations. Using data captured by one sensor or a single type of sensor to recognize …
Multicellular Models Bridging Intracellular Signaling And Gene Transcription To Population Dynamics, Mohammad Aminul Islam, Satyaki Roy, Sajal K. Das, Dipak Barua
Multicellular Models Bridging Intracellular Signaling And Gene Transcription To Population Dynamics, Mohammad Aminul Islam, Satyaki Roy, Sajal K. Das, Dipak Barua
Computer Science Faculty Research & Creative Works
Cell signaling and gene transcription occur at faster time scales compared to cellular death, division, and evolution. Bridging these multiscale events in a model is computationally challenging. We introduce a framework for the systematic development of multiscale cell population models. Using message passing interface (MPI) parallelism, the framework creates a population model from a single-cell biochemical network model. It launches parallel simulations on a single-cell model and treats each stand-alone parallel process as a cell object. MPI mediates cell-to-cell and cell-to-environment communications in a server-client fashion. In the framework, model-specific higher level rules link the intracellular molecular events to cellular …
Design The Capacity Of Onsite Generation System With Renewable Sources For Manufacturing Plant, Xiao Zhong, Md Monirul Islam, Haoyi Xiong, Zeyi Sun
Design The Capacity Of Onsite Generation System With Renewable Sources For Manufacturing Plant, Xiao Zhong, Md Monirul Islam, Haoyi Xiong, Zeyi Sun
Computer Science Faculty Research & Creative Works
The utilization of onsite generation system with renewable sources in manufacturing plants plays a critical role in improving the resilience, enhancing the sustainability, and bettering the cost effectiveness for manufacturers. When designing the capacity of onsite generation system, the manufacturing energy load needs to be met and the cost for building and operating such onsite system with renewable sources are two critical factors need to be carefully quantified. Due to the randomness of machine failures and the variation of local weather, it is challenging to determine the energy load and onsite generation supply at different time periods. In this paper, …
Distributed Power Balancing For The Freedm System, Rav Akella, Fanjun Meng, Derek Ditch, Bruce M. Mcmillin, Mariesa Crow
Distributed Power Balancing For The Freedm System, Rav Akella, Fanjun Meng, Derek Ditch, Bruce M. Mcmillin, Mariesa Crow
Computer Science Faculty Research & Creative Works
The FREEDM microgrid is a test bed for a smart grid integrated with Distributed Grid Intelligence (DGI) to efficiently manage the distribution and storage of renewable energy. Within the FREEDM system, DGI applies distributed algorithms in a unique way to achieve economically feasible utilization and storage of alternative energy sources in a distributed fashion. The FREEDM microgrid consists of residential or industrial nodes with each node running a portion of the DGI process called Intelligent Energy Management (IEM). Such IEM nodes within FREEDM coordinate among themselves to efficiently and economically manage their power generation, utility and storage. Among a variety …
Incentive Based Routing Protocol For Mobile Peer To Peer Networks, Anil Jade, Sanjay Kumar Madria, Mark Linderman
Incentive Based Routing Protocol For Mobile Peer To Peer Networks, Anil Jade, Sanjay Kumar Madria, Mark Linderman
Computer Science Faculty Research & Creative Works
Incentive models are becoming increasingly popular in Mobile Peer to Peer Networks (M-P2P) as these models entice node participation in return for a virtual currency to combat free riding and to effectively manage constraint resources in the network. Many routing protocols proposed are based on best effort data traffic policy, such as the shortest route selection (hop minimization). Using virtual currency to find a cost effective optimal route from the source to the destination, while considering Quality of Service (QoS) aspects such as bandwidth and service capacity constraints for data delivery, remains a challenging task due to the presence of …
An Open Framework For Highly Concurrent Real-Time Hardware-In-The-Loop Simulation, Ryan C. Underwood, Bruce M. Mcmillin, Mariesa Crow
An Open Framework For Highly Concurrent Real-Time Hardware-In-The-Loop Simulation, Ryan C. Underwood, Bruce M. Mcmillin, Mariesa Crow
Computer Science Faculty Research & Creative Works
Hardware-in-the-loop (HIL) real-time simulation is becoming a significant tool in prototyping complex, highly available systems. The HIL approach permits testing of hardware prototypes of components that would be extremely costly or difficult to test in the deployed environment. In power system simulation, key issues are the ability to wrap the systems of equations (such as Partial Differential Equations) describing the deployed environment into real-time software models, provide low synchronization overhead between the hardware and software, and reduce reliance on proprietary platforms. This paper introduces an open source HIL simulation framework that can be ported to any standard Unix-like system on …
Incorporation Of Evidences Into An Intelligent Computational Argumentation Network For A Web-Based Collaborative Engineering Design System, Xiaoqing Frank Liu, Ekta Khudkhudia, Ming-Chuan Leu
Incorporation Of Evidences Into An Intelligent Computational Argumentation Network For A Web-Based Collaborative Engineering Design System, Xiaoqing Frank Liu, Ekta Khudkhudia, Ming-Chuan Leu
Computer Science Faculty Research & Creative Works
Conflicts among the stakeholders are unavoidable in the process of collaborative engineering design. Resolution of these conflicts is a challenging task. In our previous research, a web based intelligent collaborative system was developed which provides decision-making support, using computational argumentation techniques. Enhancements were done to this system to incorporate the priorities of the stakeholders and to detect arguments that self conflict. As an effort to make this system more effective and more objective in the process of decision making, we develop a method to assess the effect of evidences in the argumentation network, using Dempster-Shafer theory of evidence and fuzzy …
Use Of Max-Flow On Facts Devices, Adam Lininger, Bruce M. Mcmillin, Badrul H. Chowdhury, Mariesa Crow
Use Of Max-Flow On Facts Devices, Adam Lininger, Bruce M. Mcmillin, Badrul H. Chowdhury, Mariesa Crow
Computer Science Faculty Research & Creative Works
FACTS devices can be used to mitigate cascading failures in a power grid by controlling the power flow in individual lines. Placement and control are significant issues. We present a procedure for determining whether a scenario can be mitigated using the concept of maximum flow. If it can be mitigated, we determine what placement and control setting will solve the scenario. This paper treats fourteen cascading failure scenarios and reports on the use of the max-flow algorithm both in determining the mitigation of each scenario and in finding FACTS settings that will mitigate the scenario.
Management Of An Intelligent Argumentation Network For A Web-Based Collaborative Engineering Design Environment, Xiaoqing Frank Liu, Man Zheng, Ganesh K. Venayagamoorthy, Ming-Chuan Leu
Management Of An Intelligent Argumentation Network For A Web-Based Collaborative Engineering Design Environment, Xiaoqing Frank Liu, Man Zheng, Ganesh K. Venayagamoorthy, Ming-Chuan Leu
Computer Science Faculty Research & Creative Works
Conflict resolution is one of the most challenging tasks in collaborative engineering design. In our previous research, a web-based intelligent collaborative system was developed to address this challenge based on intelligent computational argumentation. However, two important issues were not resolved in that system: priority of participants and self-conflicting arguments. In this paper, we develop two methods for incorporating priorities of participants into the computational argumentation network: 1) weighted summation and 2) re-assessment of strengths of arguments based on priority of owners of the argument using fuzzy logic inference. In addition, we develop a method for detection of self-conflicting arguments. Incorporation …
An Instance-Based Structured Object Oriented Method For Co-Analysis/Co-Design Of Concurrent Embedded Systems, Matt Ryan, Xiaoqing Frank Liu, Bruce M. Mcmillin, Ying Cheng, Sule Simsek
An Instance-Based Structured Object Oriented Method For Co-Analysis/Co-Design Of Concurrent Embedded Systems, Matt Ryan, Xiaoqing Frank Liu, Bruce M. Mcmillin, Ying Cheng, Sule Simsek
Computer Science Faculty Research & Creative Works
The current object-oriented class-based approaches to hardware/software co-analysis/co-design of embedded systems are limited in their abilities to properly capture the structure of individual instances of hardware and software components and their interactions. This paper discusses a methodology to extend a structured objectoriented hardware/software co-design methodology based on the High Order Object-oriented Modeling Technique (HOOMT) to incorporate instance-based object and behavioral models. The instance-based structured object-oriented methodology will enable description of a system's structure based on individual instances of hardware and software components and specification of the interactions among them. In addition, lattices are introduced to specify the concurrent behavior of …
An Internet Based Intelligent Argumentation System For Collaborative Engineering Design, Xiaoqing Frank Liu, Samir Raorane, Man Zheng, Ming-Chuan Leu
An Internet Based Intelligent Argumentation System For Collaborative Engineering Design, Xiaoqing Frank Liu, Samir Raorane, Man Zheng, Ming-Chuan Leu
Computer Science Faculty Research & Creative Works
Modern product design is a very complicated process which involves groups of designers, manufacturers, suppliers, and customer representatives. Conflicts are unavoidable in collaboration among multiple stakeholders, who have different objectives, requirements, and priorities. Unfortunately, current web-based collaborative engineering design systems do not support collaborative conflict resolution. In this paper, we will develop an intelligent computational argumentation model to enable management of a large scale argumentation network, and resolution of conflicts based on argumentation from many participants. A web-based intelligent argumentation tool is developed as a part of a web-based collaborative engineering design system based on the above model to resolve …
Structured Object-Oriented Co-Analysis/Co-Design Of Hardware/Software For The Facts Powers System, Matt Ryan, Sojan Markose, Xiaoqing Frank Liu, Bruce M. Mcmillin
Structured Object-Oriented Co-Analysis/Co-Design Of Hardware/Software For The Facts Powers System, Matt Ryan, Sojan Markose, Xiaoqing Frank Liu, Bruce M. Mcmillin
Computer Science Faculty Research & Creative Works
There are several approaches to the hardware/software design in embedded systems, ranging from the traditional sequential methods which focus on the determination of the hardware architecture prior to software design, to newer object-oriented approaches that attempt to apply software engineering methods to hardware design without a systematic process. This paper discusses a structured object-oriented methodology for the integrated co-analysis and co-design of hardware/software systems using an extended high order object-oriented modeling technique (HOOMT). This methodology offers a uniform method for hardware and software developers to jointly develop the specifications for and partitioning of the hardware and software components of a …
Power Transmission Control Using Distributed Max-Flow, Bruce M. Mcmillin, Austin Armbruster, Mariesa Crow, Michael R. Gosnell
Power Transmission Control Using Distributed Max-Flow, Bruce M. Mcmillin, Austin Armbruster, Mariesa Crow, Michael R. Gosnell
Computer Science Faculty Research & Creative Works
Existing maximum flow algorithms use one processor for all calculations or one processor per vertex in a graph to calculate the maximum possible flow through a graph's vertices. This is not suitable for practical implementation. We extend the max-flow work of Goldberg and Tarjan to a distributed algorithm to calculate maximum flow where the number of processors is less than the number of vertices in a graph. Our algorithm is applied to maximizing electrical flow within a power network where the power grid is modeled as a graph. Error detection measures are included to detect problems in a simulated power …
Adaptive Replication And Access Control Of Multimedia Data In A P2p Environment, Sanjay Kumar Madria, Sanjeev Agarwal
Adaptive Replication And Access Control Of Multimedia Data In A P2p Environment, Sanjay Kumar Madria, Sanjeev Agarwal
Computer Science Faculty Research & Creative Works
This paper explores some of the ideas and solutions related to replication and access control of multimedia data in a hierarchical P2P environment. We provided overview of the techniques to generate multiresolution of multimedia data and explored error recovery and access control issues.
A Distributed Discrete-Time Neural Network Architecture For Pattern Allocation And Control, A.T. Chronopoulos, Jagannathan Sarangapani
A Distributed Discrete-Time Neural Network Architecture For Pattern Allocation And Control, A.T. Chronopoulos, Jagannathan Sarangapani
Computer Science Faculty Research & Creative Works
No abstract provided.
Neural Network Diagnosis Of Malignant Melanoma From Color Images, Fikret Erçal, Hsi-Chieh Lee, William V. Stoecker, Randy Hays Moss, Anurag Chawla
Neural Network Diagnosis Of Malignant Melanoma From Color Images, Fikret Erçal, Hsi-Chieh Lee, William V. Stoecker, Randy Hays Moss, Anurag Chawla
Computer Science Faculty Research & Creative Works
Malignant melanoma is the deadliest form of all skin cancers. Approximately 32,000 new cases of malignant melanoma were diagnosed in 1991 in the United States, with approximately 80% of patients expected to survive 5 years. Fortunately, if detected early, even malignant melanoma may be treated successfully, Thus, in recent years, there has been rising interest in the automated detection and diagnosis of skin cancer, particularly malignant melanoma. Here, the authors present a novel neural network approach for the automated separation of melanoma from 3 benign categories of tumors which exhibit melanoma-like characteristics. The approach uses discriminant features, based on tumor …
Detection Of Skin Tumor Boundaries In Color Images, Fikret Erçal, M. Moganti, William V. Stoecker, Randy Hays Moss
Detection Of Skin Tumor Boundaries In Color Images, Fikret Erçal, M. Moganti, William V. Stoecker, Randy Hays Moss
Computer Science Faculty Research & Creative Works
A simple and yet effective method for finding the borders of tumors is presented as an initial step towards the diagnosis of skin tumors from their color images. The method makes use of an adaptive color metric from the red, green, and blue planes that contains information for discriminating the tumor from the background. Using this suitable coordinate transformation, the image is segmented. The tumor portion is then extracted from the segmented image and borders are drawn. Experimental results that verify the effectiveness of this approach are given
Composite Stock Cutting Through Simulated Annealing, Hanan Lutfiyya, Bruce M. Mcmillin, Pipatpong Poshyanonda, Cihan H. Dagli
Composite Stock Cutting Through Simulated Annealing, Hanan Lutfiyya, Bruce M. Mcmillin, Pipatpong Poshyanonda, Cihan H. Dagli
Computer Science Faculty Research & Creative Works
This paper explores the use of Simulated Annealing as an optimization technique for the problem of Composite Material Stock Cutting. The shapes are not constrained to be convex polygons or even regular shapes. However, due to the composite nature of the material, the orientation of the shapes on the stock is restricted. For placements of various shapes, we show how to determine a cost function, annealing parameters and performance. © 1992.
Parallel Implementation Of A Recursive Least Squares Neural Network Training Method On The Intel Ipsc/2, James Edward Steck, Bruce M. Mcmillin, K. Krishnamurthy, M. Reza Ashouri, Gary G. Leininger
Parallel Implementation Of A Recursive Least Squares Neural Network Training Method On The Intel Ipsc/2, James Edward Steck, Bruce M. Mcmillin, K. Krishnamurthy, M. Reza Ashouri, Gary G. Leininger
Computer Science Faculty Research & Creative Works
An algorithm based on the Marquardt-Levenberg least-square optimization method has been shown by S. Kollias and D. Anastassiou (IEEE Trans. on Circuits Syst. vol.36, no.8, p.1092-101, Aug. 1989) to be a much more efficient training method than gradient descent, when applied to some small feedforward neural networks. Yet, for many applications, the increase in computational complexity of the method outweighs any gain in learning rate obtained over current training methods. However, the least-squares method can be more efficiently implemented on parallel architectures than standard methods. This is demonstrated by comparing computation times and learning rates for the least-squares method implemented …