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Articles 1 - 9 of 9
Full-Text Articles in Engineering
Convolutional Neural Network Based Localized Classification Of Uterine Cervical Cancer Digital Histology Images, Haidar A. Almubarak, R. Joe Stanley, Rodney Long, Sameer Antani, George Thoma, Rosemary Zuna, Shelliane R. Frazier
Convolutional Neural Network Based Localized Classification Of Uterine Cervical Cancer Digital Histology Images, Haidar A. Almubarak, R. Joe Stanley, Rodney Long, Sameer Antani, George Thoma, Rosemary Zuna, Shelliane R. Frazier
Electrical and Computer Engineering Faculty Research & Creative Works
In previous research, we introduced an automated localized, fusion-based algorithm to classify squamous epithelium into Normal, CIN1, CIN2, and CIN3 grades of cervical intraepithelial neoplasia (CIN). The approach partitioned the epithelium into 10 segments. Image processing and machine vision algorithms were used to extract features from each segment. The features were then used to classify the segment and the result was fused to classify the whole epithelium. This research extends the previous research by dividing each of the 10 segments into 3 parts and uses a convolutional neural network to classify the 3 parts. The result is then fused to …
Mechanism Design For Strategic Project Scheduling, Pradeep Varakantham, Na Fu
Mechanism Design For Strategic Project Scheduling, Pradeep Varakantham, Na Fu
Research Collection School Of Computing and Information Systems
Organizing large scale projects (e.g., Conferences, IT Shows, F1 race) requires precise scheduling of multiple dependent tasks on common resources where multiple selfish entities are competing to execute the individual tasks. In this paper, we consider a well studied and rich scheduling model referred to as RCPSP (Resource Constrained Project Scheduling Problem). The key change to this model that we consider in this paper is the presence of selfish entities competing to perform individual tasks with the aim of maximizing their own utility. Due to the selfish entities in play, the goal of the scheduling problem is no longer only …
Proactive And Reactive Coordination Of Non-Dedicated Agent Teams Operating In Uncertain Environments, Pritee Agrawal, Pradeep Varakantham
Proactive And Reactive Coordination Of Non-Dedicated Agent Teams Operating In Uncertain Environments, Pritee Agrawal, Pradeep Varakantham
Research Collection School Of Computing and Information Systems
Domains such as disaster rescue, security patrolling etc. often feature dynamic environments where allocations of tasks to agents become ineffective due to unforeseen conditions that may require agents to leave the team. Agents leave the team either due to arrival of high priority tasks (e.g., emergency, accident or violation) or due to some damage to the agent. Existing research in task allocation has only considered fixed number of agents and in some instances arrival of new agents on the team. However, there is little or no literature that considers situations where agents leave the team after task allocation. To that …
Real-Time Traffic State Estimation With Connected Vehicles, Sakib Mahmud Khan, Kaken Dey, Mashrur Chowdhury
Real-Time Traffic State Estimation With Connected Vehicles, Sakib Mahmud Khan, Kaken Dey, Mashrur Chowdhury
Publications
A novel framework is developed in this paper, to increase the real-time roadway traffic condition assessment accuracy, which integrates connected vehicle technology (CVT) with artificial intelligence (AI) paradigm forming a CVT-AI method. Traffic density is a major indicator of traffic conditions. In this paper, the traffic operational condition is assessed based on traffic density. A simulated network of Interstate 26 in South Carolina is developed to investigate the effectiveness of the method. The assumption is that the vehicle onboard units will forward the CV generated data to the edge devices (e.g., roadside units) for further processing. CV generated distance headway …
Regulating By Robot: Administrative Decision Making In The Machine-Learning Era, Cary Coglianese, David Lehr
Regulating By Robot: Administrative Decision Making In The Machine-Learning Era, Cary Coglianese, David Lehr
All Faculty Scholarship
Machine-learning algorithms are transforming large segments of the economy, underlying everything from product marketing by online retailers to personalized search engines, and from advanced medical imaging to the software in self-driving cars. As machine learning’s use has expanded across all facets of society, anxiety has emerged about the intrusion of algorithmic machines into facets of life previously dependent on human judgment. Alarm bells sounding over the diffusion of artificial intelligence throughout the private sector only portend greater anxiety about digital robots replacing humans in the governmental sphere. A few administrative agencies have already begun to adopt this technology, while others …
Models For Pedestrian Trajectory Prediction And Navigation In Dynamic Environments, Jeremy N. Kerfs
Models For Pedestrian Trajectory Prediction And Navigation In Dynamic Environments, Jeremy N. Kerfs
Master's Theses
Robots are no longer constrained to cages in factories and are increasingly taking on roles alongside humans. Before robots can accomplish their tasks in these dynamic environments, they must be able to navigate while avoiding collisions with pedestrians or other robots. Humans are able to move through crowds by anticipating the movements of other pedestrians and how their actions will influence others; developing a method for predicting pedestrian trajectories is a critical component of a robust robot navigation system. A current state-of-the-art approach for predicting pedestrian trajectories is Social-LSTM, which is a recurrent neural network that incorporates information about neighboring …
A Comparison On The Classification Of Short-Text Documents Using Latent Dirichlet Allocation And Formal Concept Analysis, Noel Rogers, Luca Longo
A Comparison On The Classification Of Short-Text Documents Using Latent Dirichlet Allocation And Formal Concept Analysis, Noel Rogers, Luca Longo
Books/Book Chapters
With the increasing amounts of textual data being collected online, automated text classification techniques are becoming increasingly important. However, a lot of this data is in the form of short-text with just a handful of terms per document (e.g. Text messages, tweets or Facebook posts). This data is generally too sparse and noisy to obtain satisfactory classification. Two techniques which aim to alleviate this problem are Latent Dirichlet Allocation (LDA) and Formal Concept Analysis (FCA). Both techniques have been shown to improve the performance of short-text classification by reducing the sparsity of the input data. The relative performance of classifiers …
Adapting The Search Space While Limiting Damage During Learning In A Simulated Flapping Wing Micro Air Vehicle, Monica Sam
Browse all Theses and Dissertations
Cyber-Physical Systems (CPS) are characterized by closely coupled physical and software components that operate simultaneously on different spatial and temporal scales; exhibit multiple and distinct behavioral modalities; and interact with one another in ways not entirely predictable at the time of design. A commonly appearing type of CPS are systems that contain one or more smart components that adapt locally in response to global measurements of whole system performance. An example of a smart component robotic CPS system is a Flapping Wing Micro Air Vehicle (FW-MAV) that contains wing motion oscillators that control their wing flapping patterns to enable the …
Human-Intelligence/Machine-Intelligence Decision Governance: An Analysis From Ontological Point Of View, Faisal Mahmud, Teddy Steven Cotter
Human-Intelligence/Machine-Intelligence Decision Governance: An Analysis From Ontological Point Of View, Faisal Mahmud, Teddy Steven Cotter
Engineering Management & Systems Engineering Faculty Publications
The increasing CPU power and memory capacity of computers, and now computing appliances, in the 21st century has allowed accelerated integration of artificial intelligence (AI) into organizational processes and everyday life. Artificial intelligence can now be found in a wide range of organizational processes including medical diagnosis, automated stock trading, integrated robotic production systems, telecommunications routing systems, and automobile fuzzy logic controllers. Self-driving automobiles are just the latest extension of AI. This thrust of AI into organizations and everyday life rests on the AI community’s unstated assumption that “…every aspect of human learning and intelligence could be so precisely described …