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Articles 2071 - 2100 of 14409
Full-Text Articles in Entire DC Network
Distributed Intermittent Fault Diagnosis In Wireless Sensor Network Using Likelihood Ratio Test, Bhabani Sankar Gouda, Meenakshi Panda, Trilochan Panigrahi, Sudhakar Das, Bhargav Appasani, Omprakash Acharya, Hossam Zawbaa, Salah Kamel
Distributed Intermittent Fault Diagnosis In Wireless Sensor Network Using Likelihood Ratio Test, Bhabani Sankar Gouda, Meenakshi Panda, Trilochan Panigrahi, Sudhakar Das, Bhargav Appasani, Omprakash Acharya, Hossam Zawbaa, Salah Kamel
Articles
In current days, sensor nodes are deployed in hostile environments for various military and commercial applications. Sensor nodes are becoming faulty and having adverse effects in the network if they are not diagnosed and inform the fault status to other nodes. Fault diagnosis is difficult when the nodes behave faulty some times and provide good data at other times. The intermittent disturbances may be random or kind of spikes either in regular or irregular intervals. In literature, the fault diagnosis algorithms are based on statistical methods using repeated testing or machine learning. To avoid more complex and time consuming repeated …
Lightnet: A Novel Lightweight Convolutional Network For Brain Tumor Segmentation In Healthcare, Dongyuan Wu, Junyi Tao, Zhen Qin, Rao Asad Mumtaz, Jin Qin, Linfang Yu, Jane Courtney
Lightnet: A Novel Lightweight Convolutional Network For Brain Tumor Segmentation In Healthcare, Dongyuan Wu, Junyi Tao, Zhen Qin, Rao Asad Mumtaz, Jin Qin, Linfang Yu, Jane Courtney
Articles
Diagnosis, treatment planning, surveillance, and the monitoring of clinical trials for brain diseases all benefit greatly from neuroimaging-based tumor segmentation. Recently, Convolutional Neural Networks (CNNs) have demonstrated promising results in enhancing the efficiency of image-based brain tumor segmentation. Most current work on CNNs, however, is devoted to creating increasingly complicated convolution modules to improve performance, which in turn raises the computing cost of the model. This work proposes a simple and effective feed-forward CNN, LightNet (Light Network). Based on multi-path and multi-level, it replaces traditional convolutional methods with light operations, which reduces network parameters and redundant feature maps. In the …
Turbo Receivers For Multiple-Input Multiple-Output Underwater Acoustic Communications, Yahong Rosa Zheng, Weimin Duan, Chengshan Xiao
Turbo Receivers For Multiple-Input Multiple-Output Underwater Acoustic Communications, Yahong Rosa Zheng, Weimin Duan, Chengshan Xiao
Patents
Aspects of the present disclosure include methods for communication using a MIMO channel, such as an acoustic channel for underwater communication. An acoustic receiver may receive a signal comprising information encoded in at least one transmitted symbol. Using a twolayer iterative process, the at least one transmitted symbol is estimated. The first layer of the two-layer process uses iterative exchanges of soft-decisions between an adaptive turbo equalizer and a MAP decoder. The second layer of the two-layer process uses a data-reuse procedure that adapts an equalizer vector of both a feedforward filter and a serial interference cancellation filter of the …
Setransformer: A Transformer-Based Code Semantic Parser For Code Comment Generation, Zheng Li, Yonghao Wu, Bin Peng, Xiang Chen, Zeyu Sun, Yong Liu, Paul Doyle
Setransformer: A Transformer-Based Code Semantic Parser For Code Comment Generation, Zheng Li, Yonghao Wu, Bin Peng, Xiang Chen, Zeyu Sun, Yong Liu, Paul Doyle
Conference Papers
Automated code comment generation technologies can help developers understand code intent, which can significantly reduce the cost of software maintenance and revision. The latest studies in this field mainly depend on deep neural networks, such as convolutional neural networks and recurrent neural network. However, these methods may not generate high-quality and readable code comments due to the long-term dependence problem, which means that the code blocks used to summarize information are far from each other. Owing to the long-term dependence problem, these methods forget the previous input data’s feature information during the training process. In this article, to solve the …
Detection Of Pause In A Pedestrian’S Movement On A Linear Walkway Using Bluetooth Low Energy Received Signal Strength Indicator, Mayank Parmar, Paula Kelly, Damon Berry
Detection Of Pause In A Pedestrian’S Movement On A Linear Walkway Using Bluetooth Low Energy Received Signal Strength Indicator, Mayank Parmar, Paula Kelly, Damon Berry
Conference papers
In recent years, Bluetooth Low Energy (BLE) has amassed significant attention in several applications. Its potential, however, remains largely unexplored for understanding pedestrian behaviour. This study focuses on investigating the potential of BLE in identifying pedestrian activity in an outdoor linear walkway. We specifically examine the likelihood of detecting pauses in the movement of pedestrians on a linear walkway using the strength of the signals obtained from a BLE device carried by the pedestrian. To accomplish this, a volunteer pedestrian intentionally pauses at selected points on the chosen walkway for varying predetermined intervals. The obtained data was conditioned using a …
Real-Time Air Gap And Thickness Measurement Of Continuous Caster Mold Flux By Extrinsic Fabry-Perot Interferometer, Abhishek Prakash Hungund, Hanok Tekle, Bohong Zhang, Ronald J. O'Malley, Jeffrey D. Smith, Rex E. Gerald, Jie Huang
Real-Time Air Gap And Thickness Measurement Of Continuous Caster Mold Flux By Extrinsic Fabry-Perot Interferometer, Abhishek Prakash Hungund, Hanok Tekle, Bohong Zhang, Ronald J. O'Malley, Jeffrey D. Smith, Rex E. Gerald, Jie Huang
Materials Science and Engineering Faculty Research & Creative Works
Mold Flux plays a critical role in continuous casting of steel. Along with many other functions, the mold flux in the gap between the solidifying steel shell and the mold serves as a medium for controlling heat transfer and as a barrier to prevent shell sticking to the mold. This manuscript introduces a novel method of monitoring the structural features of a mold flux film in real-time in a simulated mold gap. A 3-part stainless-steel mold was designed with a 2 mm, 4 mm and, 6 mm step profile to contain mold flux films of varying thickness. An Extrinsic Fabry-Perot …
Heart Disease Prediction Using Stacking Model With Balancing Techniques And Dimensionality Reduction, Ayesha Noor, Nadeem Javaid, Nabil Alrajeh, Babar Mansoor, Ali Khaqan, Safdar Hussain Bouk
Heart Disease Prediction Using Stacking Model With Balancing Techniques And Dimensionality Reduction, Ayesha Noor, Nadeem Javaid, Nabil Alrajeh, Babar Mansoor, Ali Khaqan, Safdar Hussain Bouk
School of Cybersecurity Faculty Publications
Heart disease is a serious worldwide health issue with wide-reaching effects. Since heart disease is one of the leading causes of mortality worldwide, early detection is crucial. Emerging technologies like Machine Learning (ML) are currently being actively used by the biomedical, healthcare, and health prediction industries. PaRSEL, a new stacking model is proposed in this research, that combines four classifiers, Passive Aggressive Classifier (PAC), Ridge Classifier (RC), Stochastic Gradient Descent Classifier (SGDC), and eXtreme Gradient Boosting (XGBoost), at the base layer, and LogitBoost is deployed for the final predictions at the meta layer. The imbalanced and irrelevant features in the …
Mwirgan: Unsupervised Visible-To Mwir Image Translation With Generative Adversarial Network, Mohammad Shahab Uddin, Chiman Kwan, Jiang Li
Mwirgan: Unsupervised Visible-To Mwir Image Translation With Generative Adversarial Network, Mohammad Shahab Uddin, Chiman Kwan, Jiang Li
Electrical & Computer Engineering Faculty Publications
Unsupervised image-to-image translation techniques have been used in many applications, including visible-to-Long-Wave Infrared (visible-to-LWIR) image translation, but very few papers have explored visible-to-Mid-Wave Infrared (visible-to-MWIR) image translation. In this paper, we investigated unsupervised visible-to-MWIR image translation using generative adversarial networks (GANs). We proposed a new model named MWIRGAN for visible-to-MWIR image translation in a fully unsupervised manner. We utilized a perceptual loss to leverage shape identification and location changes of the objects in the translation. The experimental results showed that MWIRGAN was capable of visible-to-MWIR image translation while preserving the object’s shape with proper enhancement in the translated images and …
The Effect Of The Width Of The Incident Pulse To The Dielectric Transition Layer In The Scattering Of An Electromagnetic Pulse — A Qubit Lattice Algorithm Simulation, George Vahala, Linda Vahala, Abhay K. Ram, Min Soe
The Effect Of The Width Of The Incident Pulse To The Dielectric Transition Layer In The Scattering Of An Electromagnetic Pulse — A Qubit Lattice Algorithm Simulation, George Vahala, Linda Vahala, Abhay K. Ram, Min Soe
Electrical & Computer Engineering Faculty Publications
The effect of the thickness of the dielectric boundary layer that connects a material of refractive index n1 to another of index n2is considered for the propagation of an electromagnetic pulse. A qubit lattice algorithm (QLA), which consists of a specially chosen non-commuting sequence of collision and streaming operators acting on a basis set of qubits, is theoretically determined that recovers the Maxwell equations to second-order in a small parameter ϵ. For very thin boundary layer the scattering properties of the pulse mimics that found from the Fresnel jump conditions for a plane wave - except that …
Deep-Learning-Based Classification Of Digitally Modulated Signals Using Capsule Networks And Cyclic Cumulants, John A. Snoap, Dimitrie C. Popescu, James A. Latshaw, Chad M. Spooner
Deep-Learning-Based Classification Of Digitally Modulated Signals Using Capsule Networks And Cyclic Cumulants, John A. Snoap, Dimitrie C. Popescu, James A. Latshaw, Chad M. Spooner
Electrical & Computer Engineering Faculty Publications
This paper presents a novel deep-learning (DL)-based approach for classifying digitally modulated signals, which involves the use of capsule networks (CAPs) together with the cyclic cumulant (CC) features of the signals. These were blindly estimated using cyclostationary signal processing (CSP) and were then input into the CAP for training and classification. The classification performance and the generalization abilities of the proposed approach were tested using two distinct datasets that contained the same types of digitally modulated signals, but had distinct generation parameters. The results showed that the classification of digitally modulated signals using CAPs and CCs proposed in the paper …
A Survey Of Using Machine Learning In Iot Security And The Challenges Faced By Researchers, Khawlah M. Harahsheh, Chung-Hao Chen
A Survey Of Using Machine Learning In Iot Security And The Challenges Faced By Researchers, Khawlah M. Harahsheh, Chung-Hao Chen
Electrical & Computer Engineering Faculty Publications
The Internet of Things (IoT) has become more popular in the last 15 years as it has significantly improved and gained control in multiple fields. We are nowadays surrounded by billions of IoT devices that directly integrate with our lives, some of them are at the center of our homes, and others control sensitive data such as military fields, healthcare, and datacenters, among others. This popularity makes factories and companies compete to produce and develop many types of those devices without caring about how secure they are. On the other hand, IoT is considered a good insecure environment for cyber …
An Adaptive Multiple-Object Tracking Architecture For Long-Duration Videos With Variable Target Density, Joachim Lohn-Jaramillo
An Adaptive Multiple-Object Tracking Architecture For Long-Duration Videos With Variable Target Density, Joachim Lohn-Jaramillo
Dartmouth College Ph.D Dissertations
Multiple-Object Tracking (MOT) methods are used to detect targets in individual video frames, e.g., vehicles, people, and other objects, and then record each unique target’s path over time. Current state-of-the-art approaches are extremely complex because most rely on extracting and comparing visual features at every frame to track each object. These approaches are geared toward high-difficulty-tracking scenarios, e.g., crowded airports, and require expensive dedicated hardware, e.g., Graphics Processing Units. In hardware-constrained applications, researchers are turning to older, less complex MOT methods, which reveals a serious scalability issue within the state-of-the-art. Crowded environments are a niche application for MOT, i.e., there …
Design Of Next-Generation Neural Interfaces For Decoding The Brain, Yi Qiang
Design Of Next-Generation Neural Interfaces For Decoding The Brain, Yi Qiang
Dartmouth College Ph.D Dissertations
The primary goal of neural interface technology is to establish a connection between the nervous system and the external world by recording and modulating neural signals. Over the past few decades, microelectrode array (MEA) technology has played an essential role in the acquisition of electrophysiological signals, with impressive progress being made towards developing high-density, large-throughput, and ultra-flexible MEAs. However, despite these advancements, there remain long-standing limitations in current neural interfaces. For example, electrophysiology is limited in its ability to distinguish cell types and has limited spatial resolution due to its electrical recording nature. Furthermore, conventional neural MEAs are limited to …
Advancing Vehicular Communication Systems: An Evolution From Dsrc To 5g Nr C-V2x Technology For Enhanced Safety, Reliability, And Efficiency In Intelligent Transportation Systems, Mehnaz Tabassum
Dissertations, Master's Theses and Master's Reports
This work focuses on the evolution of connected vehicles communication technologies and performance evaluation of vehicular communication systems, specifically in the context of Cellular Vehicle-to-Everything (C-V2X) technology and the Third Generation Partnership Project (3GPP) specifications. The dissertation also discusses the evolution of vehicle communication systems from Dedicated Short-Range Communication (DSRC) through 5G technologies. It examines the motivation for this shift, which are the growing demand for transportation safety, low latency, high data rate, low energy use, and seamless inter connectivity. The research delves into the greater capabilities and improved performance that 5G offers for direct V2V communications by analyzing the …
Wireless Environmental Weather Monitor, Joel Christie-Millett, Nathan Schroeder, Sylvester Wilson, Matthew Szijarto
Wireless Environmental Weather Monitor, Joel Christie-Millett, Nathan Schroeder, Sylvester Wilson, Matthew Szijarto
Williams Honors College, Honors Research Projects
The goal of this senior design/honors project is to create a device that monitors environmental conditions in order to detect a wildfire. This device should notify a user of the status of the environment. The device should also last for 6 months without any human interaction. My role on the team is to design the power supply system that maximizes efficiency and uses renewable energy.
Chemical Classification By Monitoring Liquid Evaporation Using Extrinsic Fabry-Perot Interferometer With Microwave Photonics, Abhishek Prakash Hungund, Bohong Zhang, Anand Nambisan, Wassana Naku, Rex E. Gerald, Jie Huang
Chemical Classification By Monitoring Liquid Evaporation Using Extrinsic Fabry-Perot Interferometer With Microwave Photonics, Abhishek Prakash Hungund, Bohong Zhang, Anand Nambisan, Wassana Naku, Rex E. Gerald, Jie Huang
Electrical and Computer Engineering Faculty Research & Creative Works
Identification of liquids is essential in chemical analysis, safety, environmental protection, quality control, and research. A novel liquid identification system based on Microwave Photonics (MWP) measured time transient evaporation signals is investigated. An extrinsic Fabry-Perot Interferometer (EFPI) based optical probe using single-mode fiber (SMF) is proposed to monitor evaporation of different liquids. The MWP system is used to measure the optical path changes during liquid evaporation due to its high sensitivity, selectivity, and Signal-to-Noise Ratio (SNR). The measured S21 continuous wave (CW) time Magnitude and Phase signals were processed to extract features such as histogram and Fast Fourier Transform (FFT) …
Esd Events To Wearable Medical Devices In Healthcare Environments—Part 1: Current Measurements, Mehdi Kohani, Javad Meiguni, David J. Pommerenke, Michael G. Pecht
Esd Events To Wearable Medical Devices In Healthcare Environments—Part 1: Current Measurements, Mehdi Kohani, Javad Meiguni, David J. Pommerenke, Michael G. Pecht
Electrical and Computer Engineering Faculty Research & Creative Works
Wearable medical devices are widely used for monitoring and treatment of patients. Electrostatic discharge can render these devices unreliable and cause a temporary or permanent disturbance in their operation. In a healthcare environment, severe electrostatic discharge (ESD) can occur while a patient, lying down or sitting on a hospital bed with a wearable device, discharges the device via a grounded bedframe. To protect the devices from ESD damage, the worst-case discharge conditions in the usage environment need to be identified. Previous studies by authors revealed that such events could be more severe than the conventional human metal model (HMM). However, …
Development Of A Matlab-Based Structural Analysis Toolbox For Sensor Placement In A Multi-Domain Physical System, Arnold A. Fernandes, Kartikeya J.P. Veeramraju, Jonathan W. Kimball
Development Of A Matlab-Based Structural Analysis Toolbox For Sensor Placement In A Multi-Domain Physical System, Arnold A. Fernandes, Kartikeya J.P. Veeramraju, Jonathan W. Kimball
Electrical and Computer Engineering Faculty Research & Creative Works
This paper discusses a Bond Graph (BG) Structural Analysis Toolbox developed in MATLAB® (MATSAT) that performs causal analysis on the BG and assists the user in the sensor selection process for a multi-domain physical system. MATSAT contains modules for performing the Sequential Causality Assignment Procedure (SCAP) and Causal Path Search (CaPS). The modules can be combined to check for structural properties such as structural observability (SO) for any sensor set. The working of MATSAT is shown for standard systems. Verification of SCAP, CaPS, and necessary and sufficient SO conditions is shown.
A Physics-Based Model For Snapback-Type Esd Protection Devices, Xin Yan, Seyed Mostafa Mousavi, Li Shen, Yang Xu, Wei Zhang, Sergej Bub, Steffen Holland, Daryl G. Beetner
A Physics-Based Model For Snapback-Type Esd Protection Devices, Xin Yan, Seyed Mostafa Mousavi, Li Shen, Yang Xu, Wei Zhang, Sergej Bub, Steffen Holland, Daryl G. Beetner
Electrical and Computer Engineering Faculty Research & Creative Works
A simplified physical-based model for deep-snapback transient voltage suppressors (TVS) is developed in this article. While based on physics, the number of parameters and components is minimized, so the model can be tuned easily from available measurements of the packaged TVS. SPICE convergence issues seen in previous snapback device models are eliminated by adding nonlinear damping components to the model. No convergence issues were seen among any of the simulations performed for this study, which includes transmission-line pulse tests with multiple levels and rise times. The proposed model was used to represent two different TVS devices and was validated in …
System Level Pdn Impedance Optimization Utilizing The Zeros Of The Decoupling Capacitors, Yifan Ding, Shuang Liang, Francesco De Paulis, Matteo Cocchini, Samuel Connor, Matthew Doyle, Albert E. Ruehli, Chulsoon Hwang, James L. Drewniak
System Level Pdn Impedance Optimization Utilizing The Zeros Of The Decoupling Capacitors, Yifan Ding, Shuang Liang, Francesco De Paulis, Matteo Cocchini, Samuel Connor, Matthew Doyle, Albert E. Ruehli, Chulsoon Hwang, James L. Drewniak
Electrical and Computer Engineering Faculty Research & Creative Works
System-Level Power Distribution Network (PDN) Impedance Optimization Utilizing the Zeros of the Decoupling Capacitors (Decaps) is Discussed in This Paper. an Example of a Practical PDN Application is Proposed to Validate the Poles and Zeros Algorithm (P&Z) Presented. the System-Level PDN is with the Printed Circuit Board (PCB), Package (PKG), and Chip, as Well as the Low-Frequency Decaps on the PCB and the On-PKG Decoupling Capacitors. the PDN Optimization Results Are Compared with Those from the Genetic Algorithm (GA) to Show the Reasonableness and Validity of the P&Z Algorithm.
On Finding An Equivalent Force To Mimic The Multilayer Ceramic Capacitor Vibration, Yifan Ding, Jianmin Zhang, Mingfeng Xue, Shengyin Ding, Benjamin Leung, Eric A. Macintosh, Chulsoon Hwang
On Finding An Equivalent Force To Mimic The Multilayer Ceramic Capacitor Vibration, Yifan Ding, Jianmin Zhang, Mingfeng Xue, Shengyin Ding, Benjamin Leung, Eric A. Macintosh, Chulsoon Hwang
Electrical and Computer Engineering Faculty Research & Creative Works
The Multilayer Ceramic Capacitor (MLCC) Can Vibrate Due to the Piezoelectric Effect When There is AC Noise on the Power Rail. the Vibration of the Capacitor Will Generate a Force on the PCB and Thus Cause the PCB Vibration and Audible Problems May Occur. the Work in This Paper Finds an Equivalent Force with Similar Behavior to the MLCC-Generated Force. the Force is Controllable and Knowable and Thus Can Mimic the Capacitor Vibration on the PCB.
Decomposition Measurement For Antenna Gain And Radio Sensitivity Of Wireless Receiving System, Chaoqiang Zang, Lidong Chi, Fuhai Li, James L. Drewniak, Gang Feng, Yihong Qi
Decomposition Measurement For Antenna Gain And Radio Sensitivity Of Wireless Receiving System, Chaoqiang Zang, Lidong Chi, Fuhai Li, James L. Drewniak, Gang Feng, Yihong Qi
Electrical and Computer Engineering Faculty Research & Creative Works
A General Procedure for Decomposition Measurements for Receiver Antenna Gain and Radio Sensitivity based on Received Signal Strength Indicator (RSSI) Reporting is Proposed in This Paper. This Procedure Standardizes the Measurement Steps for Eliminating Nonlinear Error in RSSI Reporting. after Path Loss Calibration and RSSI Uncertainty Calibration, the Real Performance of the Antenna and the Radio Working in the Actual Environment of Wireless Receiving System Can Be Measured. the Antenna Gain is Obtained from the Difference between RSSI Reporting and Transmit Power, and the Radio Sensitivity is Obtained from the Transmit Power. This Method Helps to Improve the Development Efficiency …
A Statistical Shmoo For A Decision Feedback Equalizer (Dfe), Junyong Park, Donghyun Kim
A Statistical Shmoo For A Decision Feedback Equalizer (Dfe), Junyong Park, Donghyun Kim
Electrical and Computer Engineering Faculty Research & Creative Works
This article proposes a statistical shmoo for a Decision Feedback Equalizer (DFE). A statistical shmoo shows a Bit-Error Rate (BER) distribution of a system depending on conditions such as a threshold voltage and sampling time. The previous statistical eye diagram can be converted to a statistical shmoo except for the case of a DFE. In the shmoo, rows and columns represent different threshold voltages and sampling times, respectively. Thus, the DFE operation also depends on each row and column. Furthermore, a DFE may have error propagations because of substantial noise. Therefore, this article proposes a statistical shmoo for an ideal …
Accelerated Statistical Eye Diagram Estimation Method For Efficient Signal Integrity Analysis, Junyong Park, Youngwoo Kim, Donghyun Kim
Accelerated Statistical Eye Diagram Estimation Method For Efficient Signal Integrity Analysis, Junyong Park, Youngwoo Kim, Donghyun Kim
Electrical and Computer Engineering Faculty Research & Creative Works
This article proposes an accelerated statistical eye diagram estimation method for efficient signal integrity (SI) analysis. An eye diagram is a critical metric in the SI analysis, however obtaining an eye diagram is time-consuming in simulation. The required time might be a few weeks depending on the complexity. Because the eye diagram is obtained by superposition of the received waveforms. Statistical eye diagram estimation methods were proposed to make the eye diagram acquisition efficient, however, it still has a limited improvement due to a large number of convolution operations. To address this limitation, the proposed method includes two approaches: (i) …
A Throughput Fast Measurement Method For Two-Antenna Equipped Wireless Mimo Terminals, Penghui Shen, Quan Yu, Daryl G. Beetner, Yihong Qi
A Throughput Fast Measurement Method For Two-Antenna Equipped Wireless Mimo Terminals, Penghui Shen, Quan Yu, Daryl G. Beetner, Yihong Qi
Electrical and Computer Engineering Faculty Research & Creative Works
According to the Third Generation Partnership Project Specification, a Period of 8-12.8 H is Required to Evaluate the Multiple-Input-Multiple-Output (MIMO) Performance of a Wireless Terminal for a Single Frequency Point and Channel Model Combination. the Following Article Proposes a Semi-Simulation, Semi-Measurement-Based MIMO throughput Modeling Scheme Which Can Reduce the 8-12.8-H Measurement Time to 40-60 Min, Corresponding to More Than a Ten Times Improvement of the Test Efficiency, Without Loss of the Test Accuracy.
Atlas-Based Shared-Boundary Deformable Multi-Surface Models Through Multi-Material And Two-Manifold Dual Contouring, Tanweer Rashid, Sharmin Sultana, Mallar Chakravarty, Michel Albert Audette
Atlas-Based Shared-Boundary Deformable Multi-Surface Models Through Multi-Material And Two-Manifold Dual Contouring, Tanweer Rashid, Sharmin Sultana, Mallar Chakravarty, Michel Albert Audette
Electrical & Computer Engineering Faculty Publications
This paper presents a multi-material dual “contouring” method used to convert a digital 3D voxel-based atlas of basal ganglia to a deformable discrete multi-surface model that supports surgical navigation for an intraoperative MRI-compatible surgical robot, featuring fast intraoperative deformation computation. It is vital that the final surface model maintain shared boundaries where appropriate so that even as the deep-brain model deforms to reflect intraoperative changes encoded in ioMRI, the subthalamic nucleus stays in contact with the substantia nigra, for example, while still providing a significantly sparser representation than the original volumetric atlas consisting of hundreds of millions of voxels. The …
View Synthesis With Scene Recognition For Cross-View Image Localization, Uddom Lee, Peng Jiang, Hongyi Wu, Chunsheng Xin
View Synthesis With Scene Recognition For Cross-View Image Localization, Uddom Lee, Peng Jiang, Hongyi Wu, Chunsheng Xin
Electrical & Computer Engineering Faculty Publications
Image-based localization has been widely used for autonomous vehicles, robotics, augmented reality, etc., and this is carried out by matching a query image taken from a cell phone or vehicle dashcam to a large scale of geo-tagged reference images, such as satellite/aerial images or Google Street Views. However, the problem remains challenging due to the inconsistency between the query images and the large-scale reference datasets regarding various light and weather conditions. To tackle this issue, this work proposes a novel view synthesis framework equipped with deep generative models, which can merge the unique features from the outdated reference dataset with …
Toward Real-Time, Robust Wearable Sensor Fall Detection Using Deep Learning Methods: A Feasibility Study, Haben Yhdego, Christopher Paolini, Michel Audette
Toward Real-Time, Robust Wearable Sensor Fall Detection Using Deep Learning Methods: A Feasibility Study, Haben Yhdego, Christopher Paolini, Michel Audette
Electrical & Computer Engineering Faculty Publications
Real-time fall detection using a wearable sensor remains a challenging problem due to high gait variability. Furthermore, finding the type of sensor to use and the optimal location of the sensors are also essential factors for real-time fall-detection systems. This work presents real-time fall-detection methods using deep learning models. Early detection of falls, followed by pneumatic protection, is one of the most effective means of ensuring the safety of the elderly. First, we developed and compared different data-segmentation techniques for sliding windows. Next, we implemented various techniques to balance the datasets because collecting fall datasets in the real-time setting has …
Special Section Editorial: Artificial Intelligence For Medical Imaging In Clinical Practice, Claudia Mello-Thoms, Karen Drukker, Sian Taylor-Phillips, Khan Iftekharuddin, Marios Gavrielides
Special Section Editorial: Artificial Intelligence For Medical Imaging In Clinical Practice, Claudia Mello-Thoms, Karen Drukker, Sian Taylor-Phillips, Khan Iftekharuddin, Marios Gavrielides
Electrical & Computer Engineering Faculty Publications
This editorial introduces the JMI Special Section on Artificial Intelligence for Medical Imaging in Clinical Practice.
Proknow: Process Knowledge For Safety Constrained And Explainable Question Generation For Mental Health Diagnostic Assistance, Kaushik Roy, Manas Gaur, Misagh Soltani, Vipula Rawte, Ashwin Kalyan, Amit Sheth
Proknow: Process Knowledge For Safety Constrained And Explainable Question Generation For Mental Health Diagnostic Assistance, Kaushik Roy, Manas Gaur, Misagh Soltani, Vipula Rawte, Ashwin Kalyan, Amit Sheth
Publications
Current Virtual Mental Health Assistants (VMHAs) provide counseling and suggestive care. They refrain from patient diagnostic assistance because of a lack of training on safety-constrained and specialized clinical process knowledge (Pro-Know). In this work, we define ProKnow as an ordered set of information that maps to evidence-based guidelines or categories of conceptual understanding to experts in a domain. We also introduce a new dataset of diagnostic conversations guided by safety constraints and ProKnow that healthcare professionals use (ProKnow-data). We develop a method for natural language question generation (NLG) that collects diagnostic information from the patient interactively (ProKnow-algo). We demonstrate the …