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Articles 331 - 360 of 6813
Full-Text Articles in Entire DC Network
Four Faculty Members Retire, Sarah Moss
Learning Visuomotor Policies With Deep Movement Primitives, Michail Theofanidis, Asil Kaan Bozcuoglu, Michael Neumann, Fillia Makedon, Maria Kyrarini, Michael Beetz, Jeo Cloud
Learning Visuomotor Policies With Deep Movement Primitives, Michail Theofanidis, Asil Kaan Bozcuoglu, Michael Neumann, Fillia Makedon, Maria Kyrarini, Michael Beetz, Jeo Cloud
Association of Computing Machinery Open Access Agreement Publications-Archive
In this paper, we present a novel method to learn end-to-end visuomotor policies for robotic manipulators. The method computes state-action mappings in a supervised learning manner from video demonstrations and robot trajectories. We show that the robot learns to perform different tasks by associating image features with the corresponding movement primitives of different grasp poses. To evaluate the effectiveness of the proposed learning method, we conduct experiments with a PR2 robot in a simulation environment. The purpose of these experiments is to evaluate the system’s ability to perform manipulation tasks.
Mina: A Multitasking Intelligent Nurse Aid Robot, Harish Ram Nambiappan, Krishna Chaitanya Kodur, Maria Kyrarini, Nicholas Gans, Fillia Makedon
Mina: A Multitasking Intelligent Nurse Aid Robot, Harish Ram Nambiappan, Krishna Chaitanya Kodur, Maria Kyrarini, Nicholas Gans, Fillia Makedon
Association of Computing Machinery Open Access Agreement Publications-Archive
Nurses have to carry out a myriad of tasks, which is one of the main reasons for burnout. In this paper, a robotic Multitasking Intelligent Nurse Aid (MINA) is proposed to assist nurses with everyday tasks and tackle nurse burnout. MINA uses Simultaneous Localization And Mapping (SLAM) to map shelves in a storage room and pointcloud using an RGB-Depth camera. The barcode of the item is first detected using zbar library, and then the pointcloud is generated in ROS and saved accordingly. Preliminary experiments with respect to the creation of a pointcloud map with barcode detection are presented. The preliminary …
“I’M Better Off On My Own”: Understanding How A Tutorial’S Medium Affects Physical Skill Development, Shreyosi Endow, Cesar Torres
“I’M Better Off On My Own”: Understanding How A Tutorial’S Medium Affects Physical Skill Development, Shreyosi Endow, Cesar Torres
Association of Computing Machinery Open Access Agreement Publications-Archive
The shift towards distance learning brought forth by the pandemic has highlighted the shortcomings of teaching physical skills at a distance. With the emergence of new augmented and connected mediums, new opportunities arise for transferring physical skills that have resisted traditional documentation methods. However, there lacks a framework that allows tutorial authors to capitalize on a new medium’s unique affordances rather than remediating existing tutorial conventions. Our work analyzes a body of tutorials rendered in various mediums for centering clay on a pottery wheel — a foundational skill that exemplifies the difficulties of physical skill transfer. Through the lens of …
Interfacing With Robots Without The Use Of Touch Or Speech, Addison Clark, Ahmad Ishfaq
Interfacing With Robots Without The Use Of Touch Or Speech, Addison Clark, Ahmad Ishfaq
Association of Computing Machinery Open Access Agreement Publications-Archive
As the field of robotics develops, so do the methods of interfacing with and controlling those robots. Many modern robots can be communicated with using commands that require neither speech nor touch. The two main motivations behind this trend are the assistance of people with disabilities and the desire for more natural Human-Robot Interaction (HRI). In allowing nonverbal communication with robots, accessibility of the systems increases to allow more people to interact with and benefit from robotics systems. Additionally, nonverbal communication provides more natural communication, which can lead to many benefits in HRI. This paper provides an overview of existing …
Weakly-Supervised Hand Part Segmentation From Depth Images, Mohammad Rezaei, Farnaz Farahanipad, Alex Dilhoff, Vassilis Athitos, Ramez Elmasri
Weakly-Supervised Hand Part Segmentation From Depth Images, Mohammad Rezaei, Farnaz Farahanipad, Alex Dilhoff, Vassilis Athitos, Ramez Elmasri
Association of Computing Machinery Open Access Agreement Publications-Archive
Existing learning-based methods require a large number of labeled data to produce accurate part segmentation labels. However, acquiring ground truth labels is costly, giving rise to a need for methods that either require fewer labels or can utilize other currently available labels as a form of weak supervision for training. In this paper, in order to mitigate the burden of labeled-data acquisition, we propose a data-driven method for hand part segmentation on depth maps without any need for extra effort to obtain segmentation labels. The proposed method uses the labels already provided by public datasets in terms of major 3D …
Attacking Audio Event Detection Deep Learning Classifiers With White Noise, Rodrigo Dos Santos, Ashwitha Kassetty, Shirin Nilizadeh
Attacking Audio Event Detection Deep Learning Classifiers With White Noise, Rodrigo Dos Santos, Ashwitha Kassetty, Shirin Nilizadeh
Association of Computing Machinery Open Access Agreement Publications-Archive
We develop deep learning-based classifiers for Audio Event Detection (AED), attacking them next with some white noise disturbances. We show that an attacker can use such simple disturbances to potentially fully avoid detection by AED systems. Prior work has shown that attackers can mislead image classification tasks, however this work focuses on attacks against AED systems, by tampering the audio and not image. This work brings awareness to the designers and manufacturers of AED systems and devices, as these solutions are becoming more ubiquitous by the day.
A Simulated Environment For Traversability Estimation Experiments In Field Robotics Applications, Christos Sevastopoulos, Stasinos Konstantopoulos
A Simulated Environment For Traversability Estimation Experiments In Field Robotics Applications, Christos Sevastopoulos, Stasinos Konstantopoulos
Association of Computing Machinery Open Access Agreement Publications-Archive
We present an environment for simulated experiments in field robotics, and especially in experiments on estimating the traversability of foliage and other objects that appear as obstacles but that can be overcome by the robot without circumventing them. The simulated environment is developed in the Unity real-time development platform, integrated with the ROS middleware. In the preliminary experiments presented here, we demonstrate that our environment is able to simulate the sensory input needed in order to train supervised traversability estimation models.
Classification Of Mild Cognitive Impairment By Fusing Neuroimaging And Gene Expression Data, Yanjun Lyu, Xiaowei Yu, Lu Zhang, Dajiang Zhu
Classification Of Mild Cognitive Impairment By Fusing Neuroimaging And Gene Expression Data, Yanjun Lyu, Xiaowei Yu, Lu Zhang, Dajiang Zhu
Association of Computing Machinery Open Access Agreement Publications-Archive
As reversing the pathology of Alzheimer’s disease (AD) is impossible, the diagnosis of mild cognitive impairment (MCI), which is considered as the precursor of AD, has become a more tractable goal. Because both brain structural and functional alterations have been observed in MCI patients, many multimodal fusion approaches have been proposed to classify MCI from normal controls (NC) in clinical studies. Given the complex relationships between brain structure and function, deep learning based models can be helpful in revealing potential non-linear relationships buried in multimodal neuroimaging data. Meanwhile, RNA expression microarray profile can be a complementary feature in brain diseases …
Web Scraping Of Covid-19 News Stories To Create Datasets For Sentiment And Emotion Analysis, Poojitha Thota, Ramez Elmasri
Web Scraping Of Covid-19 News Stories To Create Datasets For Sentiment And Emotion Analysis, Poojitha Thota, Ramez Elmasri
Association of Computing Machinery Open Access Agreement Publications-Archive
Over the past few years, the ubiquitous usage of internet to broadcast information worldwide, has proved to be one of the best methods in making people aware about their surroundings. This has also led towards storage of vast amount of data in user interactive websites. Several news channels apart from live streaming, are using internet in such ways to convey their information. And these methods have not only benefited people to acquire regular updates but have also impacted their lives in many ways during the world awakening pandemic like COVID-19. Currently, in this pandemic situation, many leaders including federal and …
Sequential Late Fusion Technique For Multi-Modal Sentiment Analysis, Debapriya Banerjee, Fotios Lygerakis, Fillia Makedon
Sequential Late Fusion Technique For Multi-Modal Sentiment Analysis, Debapriya Banerjee, Fotios Lygerakis, Fillia Makedon
Association of Computing Machinery Open Access Agreement Publications-Archive
Multi-modal sentiment analysis plays an important role for providing better interactive experiences to users. Each modality in multi-modal data can provide different viewpoints or reveal unique aspects of a user’s emotional state. In this work, we use text, audio and visual modalities from MOSI dataset and we propose a novel fusion technique using a multi-head attention LSTM network. Finally, we perform a classification task and evaluate its performance.
Viiis: A Vocational Intelligent Interactive Immersive Storytelling Framework To Support Task Performance, Sanika Doolani, Callen Wessels, Fillia Makedon
Viiis: A Vocational Intelligent Interactive Immersive Storytelling Framework To Support Task Performance, Sanika Doolani, Callen Wessels, Fillia Makedon
Association of Computing Machinery Open Access Agreement Publications-Archive
This paper presents a framework for developing Intelligent, Interactive, and Immersive Storytelling systems for vocational training by improving task performance. We present a systematic framework that can be used to personalize training for a worker in a factory environment. We also present a system implementation that builds upon the vIIIS framework and also describes the design decisions made throughout the system. In this paper, we focus on improving a user’s episodic and working memory by employing picture sequence and object sorting tasks taken from the NIH toolbox and presenting an intelligent Augmented Reality system. A major advantage of using an …
Map Visualization Using Spatial And Spatio-Temporal Data: Application To Covid-19 Data, Mohammad A. Shaito, Ramez Elmasri
Map Visualization Using Spatial And Spatio-Temporal Data: Application To Covid-19 Data, Mohammad A. Shaito, Ramez Elmasri
Association of Computing Machinery Open Access Agreement Publications-Archive
Currently, spatial geographic data can be collected for many applications that involve data on the planet earth. These collected data typically have coordinates (x, y), or longitude and latitude in map space, and thus can be located and displayed on maps. Data alone represents facts and has no meaning on its own but becomes meaningful when it is associated with application knowledge, such as elections, crimes, disease, etc. For example, there is no meaning behind those numbers (1, 23, 125, 355, . . .), yet they are data that can get meaning when correlated with the total number of cases …
Z-Fuzzer: Device-Agnostic Fuzzing Of Zigbee Protocol Implementation, Mengfei Ren, Xiaolei Ren, Huadong Feng, Jiang Ming, Yu Lei
Z-Fuzzer: Device-Agnostic Fuzzing Of Zigbee Protocol Implementation, Mengfei Ren, Xiaolei Ren, Huadong Feng, Jiang Ming, Yu Lei
Association of Computing Machinery Open Access Agreement Publications-Archive
With the proliferation of the Internet of Things (IoT) devices, Zigbee is widely adopted as a resource-efficient wireless protocol. Recently, severe vulnerabilities in Zigbee protocol implementations have compromised IoT devices from different manufacturers. It becomes imperative to perform security testing on Zigbee protocol implementations. However, it is not a trivial task to apply the existing vulnerability detection techniques such as fuzzing to Zigbee protocol implementations. In particular, it remains a significant obstacle to deal with low-level hardware events. Many existing protocol fuzzing tools lack a proper execution environment for the Zigbee protocol, which communicates via a radio channel instead of …
End-User Framework For Robot Control, Kaustubh Rajpathak, Krishna Chaitanya Kodur, Maria Kyrarini, Fillia Makedon
End-User Framework For Robot Control, Kaustubh Rajpathak, Krishna Chaitanya Kodur, Maria Kyrarini, Fillia Makedon
Association of Computing Machinery Open Access Agreement Publications-Archive
This paper showcases a developed end-user framework for a humanrobot collaborative system for common tasks, such as pick and place. The system is designed for semi-automated pick and place tasks as well as manual operation making it flexible for multiple use-case scenarios. The goal of the system is to make the robot multi-functional, easy to use with a graphical user interface and to perform common tasks with the help of a human teammate. Integration with object recognition neural network (YoloV3) and an RGB-Depth camera helps automate pick and place tasks with a wide variety of objects.
A Pipeline For Hand 2-D Keypoint Localization Using Unpaired Image To Image Translation, Farnaz Farahanipad, Mohammad Rezaei, Alex Dilhoff, Farhad Kamangar, Vassilis Athitos
A Pipeline For Hand 2-D Keypoint Localization Using Unpaired Image To Image Translation, Farnaz Farahanipad, Mohammad Rezaei, Alex Dilhoff, Farhad Kamangar, Vassilis Athitos
Association of Computing Machinery Open Access Agreement Publications-Archive
Hand pose estimation is getting a lot of attention in many areas such as Human-Computer Interaction and Sign Language Recognition. A fundamental step to accurately estimate the hand pose involves detecting and localizing fingertips in an image. Despite the progress of 2-D hand pose estimation in recent studies, accurate and robust detection and localization of fingertips still remains a challenging task due to low resolution of a fingertip in images and varying lightning condition. Inspired by the progress of the Generative Adversarial Network (GAN) and image-style transfer, we propose a two-stage pipeline to accurately localize the fingertip position even in …
Self-Supervised Human Activity Recognition By Augmenting Generative Adversarial Networks, Mohammad Zaki Zahed, Ashish Jaiswal, Ramesh Babu Ashwin, Maria Kyrarini, Fillia Makedon
Self-Supervised Human Activity Recognition By Augmenting Generative Adversarial Networks, Mohammad Zaki Zahed, Ashish Jaiswal, Ramesh Babu Ashwin, Maria Kyrarini, Fillia Makedon
Association of Computing Machinery Open Access Agreement Publications-Archive
This article proposes a novel approach for augmenting generative adversarial network (GAN) with a self-supervised task in order to improve its ability for encoding video representations that are useful in downstream tasks such as human activity recognition. In the proposed method, input video frames are randomly transformed by different spatial transformations, such as rotation, translation and shearing or temporal transformations such as shuffling temporal order of frames. Then discriminator is encouraged to predict the applied transformation by introducing an auxiliary loss. Subsequently, results prove superiority of the proposed method over baseline methods for providing a useful representation of videos used …
Designing A Vocational Immersive Storytelling Training And Support System To Evaluate Impact On Working And Episodic Memory, Sanika Doolani, Callen Wessels, Fillia Makedon
Designing A Vocational Immersive Storytelling Training And Support System To Evaluate Impact On Working And Episodic Memory, Sanika Doolani, Callen Wessels, Fillia Makedon
Association of Computing Machinery Open Access Agreement Publications-Archive
Working memory and episodic memory are mainly responsible for the storage and recollection of information, whereas Storytelling is the most ancient and effective way of relaying this information to the user. We have designed an interactive and immersive storytelling system using Augmented Reality to improve episodic and working memory. This paper presents an overview of the tasks we used to improve these 2 sections of memory and also presents a study design on how we plan to evaluate our system to prove its effectiveness in comparison to desktop 2D-based training.
Manifolk: A 3d T-Sne Visualizer, Krishna Chaitanya Kodur, Ramesh Babu Ashwin, Fillia Makedon
Manifolk: A 3d T-Sne Visualizer, Krishna Chaitanya Kodur, Ramesh Babu Ashwin, Fillia Makedon
Association of Computing Machinery Open Access Agreement Publications-Archive
Manifolk is a tool to visualize the output of dimensionality reduction algorithms like t-SNE, PCA etc. One of this tool’s main uses is that it de-clutters graphs by plotting data points pertaining to a subset of labels. The subset of labels to be plotted can be selected using the provided checkboxes. A case study on data from a publicly available action recognition dataset like UCF101 shows how this tool can help find outliers. With the rise in self-supervised methods for training deep neural networks, this tool helps researchers better visualize the embeddings learned by the model.
Estimation Of Heart Rate Variability Measures Using Apple Watch And Evaluating Their Accuracy, Ahmad Turki, Kan Ding, Rong Zhang, Ming Li, Kathleen Bell, Khosrow Behbehani
Estimation Of Heart Rate Variability Measures Using Apple Watch And Evaluating Their Accuracy, Ahmad Turki, Kan Ding, Rong Zhang, Ming Li, Kathleen Bell, Khosrow Behbehani
Association of Computing Machinery Open Access Agreement Publications-Archive
In a pandemic crisis such as the one that the world has been experiencing since January 2020, utilizing remote mobile health monitoring can help monitor the cardiac health of healthy individuals as well as chronically ill patients. Apple Watch is a fitness tracker that measures heart rate and can facilitate this need due to its availability worldwide and relative affordability. Hence, it has the potential of being useful in assessing and monitoring one’s cardiac health. This paper reports the preliminary results from an ongoing study aimed at assessing the accuracy of the Apple Watch in measuring heart rate variability. To …
Automated System To Measure Tandem Gait To Assess Executive Functions In Children, Mohammad Zaki Zahed, Ramesh Babu Ashwin, Ashish Jaiswal, Maria Kyrarini, Morris Bell, Fillia Makedon
Automated System To Measure Tandem Gait To Assess Executive Functions In Children, Mohammad Zaki Zahed, Ramesh Babu Ashwin, Ashish Jaiswal, Maria Kyrarini, Morris Bell, Fillia Makedon
Association of Computing Machinery Open Access Agreement Publications-Archive
As mobile technologies have become ubiquitous in recent years, computer-based cognitive tests have become more popular and efficient. In this work, we focus on assessing motor function in children by analyzing their gait movements. Although there has been a lot of research on designing automated assessment systems for gait analysis, most of these efforts use obtrusive wearable sensors for measuring body movements. We have devised a computer visionbased assessment system that only requires a camera which makes it easier to employ in school or home environments. A dataset has been created with 27 children performing the test. Furthermore, in order …
Accelerating Human-Agent Collaborative Reinforcement Learning, Fotios Lygerakis, Maria Dagioglou, Vangelis Karkaletsis
Accelerating Human-Agent Collaborative Reinforcement Learning, Fotios Lygerakis, Maria Dagioglou, Vangelis Karkaletsis
Association of Computing Machinery Open Access Agreement Publications-Archive
In domains such as Human-Robot Collaboration artificial agents must be able to support mutual adaptation and learning. Towards this direction, we use a discrete Soft Actor-Critic agent on a realtime collaborative game with humans. We examine how different allocations of on-line and off-line gradient updates impact the game performance and the total training time. Our results suggest that early allocation of a high number of off-line g/u can accelerate learning while shortening training duration.
Lirs2: An Improved Lirs Replacement Algorithm, Chen Zhong, Xingsheng Zhao, Song Jiang
Lirs2: An Improved Lirs Replacement Algorithm, Chen Zhong, Xingsheng Zhao, Song Jiang
Association of Computing Machinery Open Access Agreement Publications-Archive
A block replacement algorithm keeps receiving attention on improvement of its hit ratio. Many replacement algorithms have been proposed, among which LIRS stands out with its consistently higher hit ratio across various workloads with low time and space overheads. However, there are still access patterns where LIRS produces sub-optimal hit ratio and has room for further improvement. In this paper, we replace the locality measure used by LIRS, the reuse distance, with a more stable and thus more reliable measure, to predict future access time. The new measure is the sum of a block’s two recent consecutive reuse distances. It …
Empowering Pandemic Narratives: Transitioning From In-Person To Virtual Blog Training, Alexandra Pirkle, Krystal Schenk
Empowering Pandemic Narratives: Transitioning From In-Person To Virtual Blog Training, Alexandra Pirkle, Krystal Schenk
UTA Libraries Staff Publications - Archive
When UTA Libraries launched its new website in January 2020, one of the goals for Marketing and Communications was to provide comprehensive and accessible blog training to Libraries staff. What began as pre-scheduled, in-person training sessions in computer labs quickly transitioned to more fluid, virtual offerings as the COVID-19 pandemic swept the United States and staff began to work from home. This presentation will describe the original development of our blog training, including documentation, branding, and overall curricular structure, and how we translated that to the more nebulous Microsoft Teams-based sessions we continue to offer to staff today. We will …
Responding To The Call: Building A Training Program To Diversify The Academy In Alzheimer's Disease Research, Lucy Annang Ingram Phd, Mph, Marvella E. Ford, Christiana L. Johnson, Brianna Ashford-Carroll, Quentun Mccollum, Daniela B. Friedman Ph.D., Sue Ellen Levkoff
Responding To The Call: Building A Training Program To Diversify The Academy In Alzheimer's Disease Research, Lucy Annang Ingram Phd, Mph, Marvella E. Ford, Christiana L. Johnson, Brianna Ashford-Carroll, Quentun Mccollum, Daniela B. Friedman Ph.D., Sue Ellen Levkoff
Faculty and Staff Publications
Alzheimer's disease and related dementias (ADRD) are at the forefront of the United States (US) public health agenda due to their tremendous human and financial burden. Further, disproportionately high ADRD rates among racial/ethnic minorities require incorporating the unique perspectives of racially and ethnically diverse scientists, which will necessitate diversifying the scientific workforce that investigates disparities in aging. The purpose of this paper is to describe the training and mentorship initiatives of the National Institute on Aging (NIA)-funded Carolina Center on Alzheimer's Disease and Minority Research, emphasizing lessons learned from our engagement with underrepresented minority and minoritized (URM) Scientists. We highlight …
Slgpt: Using Transfer Learning To Directly Generate Simulink Model Files And Find Bugs In The Simulink Toolchain, Lal Shrestha Sohil, Christoph Csallner
Slgpt: Using Transfer Learning To Directly Generate Simulink Model Files And Find Bugs In The Simulink Toolchain, Lal Shrestha Sohil, Christoph Csallner
Association of Computing Machinery Open Access Agreement Publications-Archive
Finding bugs in a commercial cyber-physical system (CPS) development tool such as Simulink is hard as its codebase contains millions of lines of code and complete formal language specifications are not available. While deep learning techniques promise to learn such language specifications from sample models, deep learning needs a large number of training data to work well. SLGPT addresses this problem by using transfer learning to leverage the powerful Generative Pre-trained Transformer 2 (GPT-2) model, which has been pre-trained on a large set of training data. SLGPT adapts GPT-2 to Simulink with both randomly generated models and models mined from …
The Effect Of Room-Temperature Aging On Enthalpy And Dielectric Property Of Carbon-Fiber/Epoxy Composite Prepreg And The Mechanical Property Of Manufactured Composite, Monjur Morshed Rabby, Minhazur Rahman, Partha Pratim Das, Muthu Ram Prabhu Elenchezhian, Relebohile George Qhobosheane, Vamsee Vadlamudi
The Effect Of Room-Temperature Aging On Enthalpy And Dielectric Property Of Carbon-Fiber/Epoxy Composite Prepreg And The Mechanical Property Of Manufactured Composite, Monjur Morshed Rabby, Minhazur Rahman, Partha Pratim Das, Muthu Ram Prabhu Elenchezhian, Relebohile George Qhobosheane, Vamsee Vadlamudi
Institute of Predictive Performance Methodologies (IPPM-UTARI)-Archive
Fiber-based reinforced plastics are widely used materials in different industries - e.g., Automotive, Aerospace, Defense- because of their various advantages. The most reliable raw materials for manufacturing fiber-based composites are pre-impregnated reinforcing fiber (prepreg). However, the limitation of using prepreg lies in its instability at room temperature. Prepregs have a specific out-life which sometimes makes the manufacturing process difficult. The objective of this study is to find out a way to investigate the room temperature aging effect on prepreg by analyzing the enthalpy and dielectric properties. In this study, differential scanning calorimetry (DSC) was used to measure the reaction enthalpy …
Unleashing The Hidden Power Of Compiler Optimization On Binary Code Difference: An Empirical Study, Xialei Ren, Michael Ho, Jiang Ming, Yu Lei, Li Li
Unleashing The Hidden Power Of Compiler Optimization On Binary Code Difference: An Empirical Study, Xialei Ren, Michael Ho, Jiang Ming, Yu Lei, Li Li
Association of Computing Machinery Open Access Agreement Publications-Archive
Hunting binary code difference without source code (i.e., binary diffing) has compelling applications in software security. Due to the high variability of binary code, existing solutions have been driven towards measuring semantic similarities from syntactically different code. Since compiler optimization is the most common source contributing to binary code differences in syntax, testing the resilience against the changes caused by different compiler optimization settings has become a standard evaluation step for most binary diffing approaches. For example, 47 top-venue papers in the last 12 years compared different program versions compiled by default optimization levels (e.g., -Ox in GCC and LLVM). …
A Generalized Approach For Reducing Expensive Distance Calls For A Broad Class Of Proximity Problems, Jees Augustine, Suraj Shetiya, Mohammadreza Esfandiari, Senjuti Basu Roy, Gautam Das
A Generalized Approach For Reducing Expensive Distance Calls For A Broad Class Of Proximity Problems, Jees Augustine, Suraj Shetiya, Mohammadreza Esfandiari, Senjuti Basu Roy, Gautam Das
Association of Computing Machinery Open Access Agreement Publications-Archive
In this paper, we revisit a suite of popular proximity problems (such as, KNN, clustering, minimum spanning tree) that repeatedly perform distance computations to compare distances during their execution. Our effort here is to design principled solutions to minimize distance computations for such problems in general metric spaces, especially for the scenarios where calling an expensive oracle to resolve unknown distances are the dominant cost of the algorithms for these problems. We present a suite of techniques, including a novel formulation of the problem, that studies how distance comparisons between objects could be modelled as a system of linear inequalities …
Artificial Intelligence In Real-Time Diagnostics And Prognostics Of Composite Materials And Its Uncertainties – A Review, Muthu Ram Prabhu Elenchezhian, Vamsee Vadlamudi, Rassel Raihan, Kenneth Reifsnider, Erick Reifsnider
Artificial Intelligence In Real-Time Diagnostics And Prognostics Of Composite Materials And Its Uncertainties – A Review, Muthu Ram Prabhu Elenchezhian, Vamsee Vadlamudi, Rassel Raihan, Kenneth Reifsnider, Erick Reifsnider
UTARI Researcher Publications-Archive
In the era of the 4th industrial revolution of big data, Artificial Intelligence (AI) is widely used in each and every field of composite materials which includes design and analysis, material storage, manufacturing, non-destructive testing (NDT), Structural Health Monitoring (SHM) and Prognostics of its Remaining Useful Life (RUL), Material State (MS) and damage modes. While these AI models are rapidly developed and integrated into the Industrial Internet of Things (IIoT) to keep track of the health of a composite material from its birth to death, these integrations remain uncertain for prognostics without the certainty of its previous material state. This …