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Articles 5431 - 5460 of 25750
Full-Text Articles in Computer Engineering
Continuous Simulation Technology For Multi-State Evolution Of Urban Road Traffic, Qinglu Ma, Lin Zhang, Xinxin Yuan, Fengjie Liu
Continuous Simulation Technology For Multi-State Evolution Of Urban Road Traffic, Qinglu Ma, Lin Zhang, Xinxin Yuan, Fengjie Liu
Journal of System Simulation
Abstract: Arming at the decreased positioning accuracy caused by the environment dynamic change of indoor positioning system, an error compensation algorithm based on XGBoost fusion elastic net is proposed. XGBoost positioning model is used to make a preliminary prediction on the target position. When the indoor environment changes, the elastic net algorithm is used to construct an error compensation model to correct the positioning error of XGBoost positioning model. The experimental results show that when only 15% of the fingerprint database samples need to be updated, the positioning accuracy of the proposed algorithm is controlled in 0.73m at the 80% …
Microscopic Nuclei Classification, Segmentation, And Detection With Improved Deep Convolutional Neural Networks (Dcnn), Md Zahangir Alom, Vijayan K. Asari, Anil Parwani, Tarek M. Taha
Microscopic Nuclei Classification, Segmentation, And Detection With Improved Deep Convolutional Neural Networks (Dcnn), Md Zahangir Alom, Vijayan K. Asari, Anil Parwani, Tarek M. Taha
Electrical and Computer Engineering Faculty Publications
Background Nuclei classification, segmentation, and detection from pathological images are challenging tasks due to cellular heterogeneity in the Whole Slide Images (WSI). Methods In this work, we propose advanced DCNN models for nuclei classification, segmentation, and detection tasks. The Densely Connected Neural Network (DCNN) and Densely Connected Recurrent Convolutional Network (DCRN) models are applied for the nuclei classification tasks. The Recurrent Residual U-Net (R2U-Net) and the R2UNet-based regression model named the University of Dayton Net (UD-Net) are applied for nuclei segmentation and detection tasks respectively. The experiments are conducted on publicly available datasets, including Routine Colon Cancer (RCC) classification and …
Optimal Operation For Park Integrated Energy System Considering Interruptible Loads, Lixin Ma, Ying Cheng
Optimal Operation For Park Integrated Energy System Considering Interruptible Loads, Lixin Ma, Ying Cheng
Journal of System Simulation
Abstract: The operating mode of thermal power generation units has certain limitations in peak shaving capacity. Interruptible load (IL), as a power resource to be tapped, can be applied to the park integrated energy management and microgrid systems to guide users to reduce peak electricity consumption. The IL function is introduced into the park integrated energy system with combined heat and power units to improve the system's peak shaving ability, and the corresponding model is established with the optimization goal of economy. Taking an ecological park of northern region as the example, the adaptive chaotic particle swarm algorithm is used …
Radar Remote Sensing Data Augmentation Method Based On Generative Adversarial Network, Xu Kang, Xiaofeng Zhang
Radar Remote Sensing Data Augmentation Method Based On Generative Adversarial Network, Xu Kang, Xiaofeng Zhang
Journal of System Simulation
Abstract: In the research field of radar remote sensing, both the completeness and diversity of radar data samples cannot meet the requirement of effective training of deep learning models, and the models are prone to over-fitting, which significantly limits the wide application of deep learning techniques in this field. Targeting on the needs of intelligent application in radar remote sensing, a microwave imaging radar suited data augmentation method is proposed to solve the issue of insufficient radar data samples by leveraging the general framework of generative adversarial network. Aiming at the features of radar samples being not obvious, the label …
A Devs-Based Formal Description Method For Complex Product Behavior Models, Qingquan Lin, Jiaran Yang, Heming Zhang
A Devs-Based Formal Description Method For Complex Product Behavior Models, Qingquan Lin, Jiaran Yang, Heming Zhang
Journal of System Simulation
Abstract: For the online optimization of pedestrian flow control in subway station, an algorithm frame for pedestrian flow control in subway station based on machine learning is designed. The pedestrian flow control process of a subway station during morning rush hour is selected,and the agent-based model is built to simulate the control process. The training data is collected through the multiple runs of the model, which is used as the input of deep reinforcement learning network, and the mature net is obtained through adequate training to provide the optimizing scheduling policy. Linking the actual data with the mature net …
Research On Space Launch Visualization Simulation Analysis Technology And Application, Feng Wu, Xiuluo Liu, Jia Wang, Yang Liu, Sujiang Li, Yan Zhong
Research On Space Launch Visualization Simulation Analysis Technology And Application, Feng Wu, Xiuluo Liu, Jia Wang, Yang Liu, Sujiang Li, Yan Zhong
Journal of System Simulation
Abstract: Through the typical cases in the field of military, society, manufacturing etc., this paper introduces the concept and features of complex engineering system of systems as well as the significance of modeling and simulation for the study of complex engineering system of systems. Taking complex product manufacturing as an example, the evolution process from systems engineering to model-based systems engineering (MBSE) and then to modeling and simulation-based system of systems engineering is analyzed. The characteristics and challenges of modeling and simulation of complex engineering system of systems is discussed. Some research topics in filed of MSBS2E is introduced, which …
Hybrid Variable Neighborhood Search Algorithm For The Multi-Trip And Heterogeneous-Fleet Electric Vehicle Routing Problem, Weiquan Wang, Ding Ding, Shuyan Cao
Hybrid Variable Neighborhood Search Algorithm For The Multi-Trip And Heterogeneous-Fleet Electric Vehicle Routing Problem, Weiquan Wang, Ding Ding, Shuyan Cao
Journal of System Simulation
Abstract: Based on the real business practice, the multi-trip and heterogeneous-fleet electric vehicle routing problem (MTHF-EVRP) with time windows in green logistics is studied. A path-based mixed-integer linear model is built for the precise solution to the small-scale instances. A hybrid variable neighborhood search algorithm (Hybrid VNS) combined the variable neighborhood search algorithm with the labeling algorithm is proposed for the large-scale instances. The algorithm generates a modified insertion heuristic with random factor to construct the initial solution, allows the time window and range violation, adopts the neighborhood operators for the local search, and applies a labeling algorithm to solve …
Design And Implementation Of A Hybrid Solver On Cpu And Gpu Multi-Target Machines, Lin Ma, Xuesong Zhang, Xinlin Lei, Tie Bao
Design And Implementation Of A Hybrid Solver On Cpu And Gpu Multi-Target Machines, Lin Ma, Xuesong Zhang, Xinlin Lei, Tie Bao
Journal of System Simulation
Abstract: The traditional parallel solving methods for the ordinary differential equations mainly include the task-oriented parallelism and the method-oriented parallelism. However, these two solving algorithms have serious shortcomings, which can only use CPU resource or just design for the homogeneous form of ODE(ordinary differential equations) clusters. By using RIDC(revisionist integral deferred correction) algorithm, a hybrid solver based on CPU and GPU multi-target machine is designed, which solves the differential equation system based on the pipeline form. Meanwhile, the parallel calculation within a single equation group and between the different equation groups is realized, which can give full play to the …
Motion Simulation And Performance Analysis Of 2d Variable Stiffness Snake-Like Robot, Yanqin Long, Guifang Qiao, Guangming Song, Ying Zhang, Linlin Cheng
Motion Simulation And Performance Analysis Of 2d Variable Stiffness Snake-Like Robot, Yanqin Long, Guifang Qiao, Guangming Song, Ying Zhang, Linlin Cheng
Journal of System Simulation
Abstract: Mutual interference of vehicular laser radar causes serious performance reduction of target detection and tracking. From spatial, time and modulation frequency, various possible interference of lidars of pulse and frequency modulated continuous wave method in road environments are studied by simulation. The possibility of the interference is calculated, the features and performance reduction of the interference are analyzed. For the possible interference, using a method of pseudo random noise code to modulate the output amplitude of the continuous wave laser can effectively reduce the probability of interference and ensure the reliable operation of lidar in road environments.
Optimization Of Dynamic Post-Disaster Emergency Distribution Network Under Perspective Of Rescue Efficiency, Xinyu Gao, Jing Ni
Optimization Of Dynamic Post-Disaster Emergency Distribution Network Under Perspective Of Rescue Efficiency, Xinyu Gao, Jing Ni
Journal of System Simulation
Abstract: Aiming at the emergency rescue, a dynamic directed rescue network is established with the dynamic changes of the location, demand, and affected population of disaster site, and a mathematical model is constructed with the maximum rescue efficiency. A data envelope analysis model is applied to evaluate the efficiency of each rescue route segment. An efficiency-based dynamic routing model is established to transform the dynamic routes into the multi-stage static routes through the time slice division. An improved hybrid greedy-ant colony optimization algorithm is designed to solve the model, and the proposed algorithm is compared with the genetic algorithm, particle …
Idea Of Infinitesimal Method-Introduced Hybrid Tt&C Resources Joint Scheduling, Naiyang Xue, Dan Ding, Hongmin Wang, Yile Fan, Zhongqian Liu
Idea Of Infinitesimal Method-Introduced Hybrid Tt&C Resources Joint Scheduling, Naiyang Xue, Dan Ding, Hongmin Wang, Yile Fan, Zhongqian Liu
Journal of System Simulation
Abstract: Aiming at the study on the motion performance of a two-dimensional variable stiffness snake-robot, a Simulink/Adams co-simulation model is established, and the effects of the damping coefficient, the stiffness parameters and the angular frequency of the variable stiffness actuator on the motion energy consumption are analyzed. To realize the synchronous control of joint trajectory and stiffness, a motion controller based on two-layer CPG is proposed. The results show that the damping coefficient can effectively reduce the proportion of starting energy consumption of the variable stiffness snake-like robot, and the ratio of starting energy consumption increases with the stiffness parameter …
Research On Multi-Depot Half-Open Vehicle Routing Problem With Time-Varying Speed, Kaiqing Zhang, Qichun Ji
Research On Multi-Depot Half-Open Vehicle Routing Problem With Time-Varying Speed, Kaiqing Zhang, Qichun Ji
Journal of System Simulation
Abstract: Based on the analysis of operation concept and its elements, this paper proposes a framework of operation effectiveness simulation evaluation under the guidance of operation concept. Based on this framework, the basic idea of operation effectiveness simulation evaluation index construction under the guidance of operation concept is put forward. The specific methods of operation task modeling based on description, operation activity modeling based on decomposition, and operation effectiveness index selection based on effect are studied. The operation effectiveness simulation evaluation index system is constructed by taking the ground assault unit mountain key point capture and attack operation task guided …
Simulation On Critical Conditions Of Delay Diffusion In Scale-Free Logistics Network, Hongguang Yao, Huihui Xiao, Hang Zhang
Simulation On Critical Conditions Of Delay Diffusion In Scale-Free Logistics Network, Hongguang Yao, Huihui Xiao, Hang Zhang
Journal of System Simulation
Abstract: Aiming at the critical condition of delay diffusion in scale-free logistics network, a susceptible-infected-susceptible(SIS) model based on the density of delay nodes is established by mean field theory, and the critical value is solved. By designing the delay diffusion simulation system in logistics network, a virtual network with scale-free attribute is generated, and the critical condition is verified by simulation. The results show that there are a few key nodes with high value in scale-free logistics network. Once these nodes have service obstades, compared with other nodes, it will lead to a larger range of delay and faster …
Real-Time Illumination Capture And Rendering On Mobile Devices, Snehal Padhye, James A. Ferwerda
Real-Time Illumination Capture And Rendering On Mobile Devices, Snehal Padhye, James A. Ferwerda
Frameless
We present our efforts to develop methods for rendering 3D objects on mobile devices using real-world dynamic illumination from the user’s environment. To achieve this, we use the front and back cameras on the mobile device to estimate the light distribution in the environment in real time. We then create a dynamic illumination map and render the object at interactive rates in a browser on the device using a web-based graphics API. This project achieves one of the goals of our related work on realistic visualization of virtual objects: to make virtual objects appear to be situated within the scene …
Mixed Reality Prototype Device Showcase: Using Smart Glasses To Enhance Language Access, Aaron Parker, Connor Switenky, Roshan Mathew, Wendy Dannels
Mixed Reality Prototype Device Showcase: Using Smart Glasses To Enhance Language Access, Aaron Parker, Connor Switenky, Roshan Mathew, Wendy Dannels
Frameless
While the use of American Sign Language (ASL) interpreters and real-time captioning significantly increases deaf individuals’ ability to participate in a wide variety of functions, there are some limitations. The major problem is that current ways of providing communication and information access to deaf people require them to split their attention between the visual focus of the specific content and the interpreter/captioning display. At any given point in time, deaf people are forced to decide what explanation to miss with subsequent effects on topic comprehension and perceptions of the interaction and environments.
Novel 360-Degree Camera, Ian Gauger, Andrew Kurtz, Zakariya Niazi
Novel 360-Degree Camera, Ian Gauger, Andrew Kurtz, Zakariya Niazi
Frameless
Circle Optics is developing novel technology for low-parallax, real time, panoramic image capture using an integrated array of multiple adjacent polygonal-edged cameras. This technology can be optimized and deployed for a variety of markets, including cinematic VR. Circle Optics’ existing prototype, Hydra Alpha, will be demonstrated.
Warehouse And Logistics: Smart Picking With Vuzix Smart Glasses, Elise Hemink
Warehouse And Logistics: Smart Picking With Vuzix Smart Glasses, Elise Hemink
Frameless
Vuzix is an industry leader in augmented reality (AR) technology. We provide innovative products to an array of industries, a few being defense, security, enterprise, and consumers. Our AR technology provides a perfect balance of engagement in the digital and real worlds thanks to their innovative optics, AI apps and 5G capability.
Creating A Virtual Reality Experience In Service To A Non-Profit Agency, Frank Deese, Susan Lakin, Isabelle Anderson
Creating A Virtual Reality Experience In Service To A Non-Profit Agency, Frank Deese, Susan Lakin, Isabelle Anderson
Frameless
In the summer of 2018, RIT Professors Susan Lakin and Frank Deese discussed with the principal officers of the Society for the Protection and Care of Children (SPCC) in Rochester how the new technology of Virtual Reality might be used to not only impart information to viewers, but generate empathy for those receiving services from the organization as well as those performing those services. Their ultimate goal was to create an experience that could be viewed with VR headsets at fundraising events and on a website using low-cost Google Cardboard.
Exploring The Psychological Consequences Of Distances In Virtual Reality, Gary D. Jacobs
Exploring The Psychological Consequences Of Distances In Virtual Reality, Gary D. Jacobs
Frameless
This presentation will examine common concepts of traveling between formalized spaces inside virtual reality (VR) experiences.
The common method for traveling in virtual reality is to click on an area or trigger and be transported to that location. These “teleportations”, however, remove the notion of distances from our virtual worlds. This is akin to a magic wand that eliminates the consequences of travel in VR. Often heralded as a boon for the virtual worlds we can create, wherein we can travel to far away lands without lag in time and without effort on the part of the participant. We posit …
Vr Sound Mapping: Make Sound Accessible For Dhh People In Virtual Reality Environments, Ziming Li, Roshan Peiris
Vr Sound Mapping: Make Sound Accessible For Dhh People In Virtual Reality Environments, Ziming Li, Roshan Peiris
Frameless
In-game audio plays an important role in enhancing the sense of reality and immersion in the gaming experience. In many games, sounds are also used to provide notifications and clues which are essential to the gameplay. However, in this case, the DHH (deaf and hard of hearing) players may fail to access the information conveyed by sounds, which degrades their gaming experience (Jain et al. 2021).
A Deep Reinforcement Learning Approach With Prioritized Experience Replay And Importance Factor For Makespan Minimization In Manufacturing, Jose Napoleon Martinez
A Deep Reinforcement Learning Approach With Prioritized Experience Replay And Importance Factor For Makespan Minimization In Manufacturing, Jose Napoleon Martinez
LSU Doctoral Dissertations
In this research, we investigated the application of deep reinforcement learning (DRL) to a common manufacturing scheduling optimization problem, max makespan minimization. In this application, tasks are scheduled to undergo processing in identical processing units (for instance, identical machines, machining centers, or cells). The optimization goal is to assign the jobs to be scheduled to units to minimize the maximum processing time (i.e., makespan) on any unit.
Machine learning methods have the potential to "learn" structures in the distribution of job times that could lead to improved optimization performance and time over traditional optimization methods, as well as to adapt …
Development Of A Compliant Gripper Driven By 3 Dof Soft Robot, Derek M. Price Ii, Ricardo Ramirez, Pt Angel Tran
Development Of A Compliant Gripper Driven By 3 Dof Soft Robot, Derek M. Price Ii, Ricardo Ramirez, Pt Angel Tran
Symposium of Student Scholars
Industrial robots are moving toward automation, which makes it increasingly necessary to replace the functions traditionally performed by humans with robotics. Pick and place operation is a prime example of such automation. Robots that pick up and place objects mimic the human action of picking an object up and placing it in a targeted location. It has led to the development of robotic end-effectors that have a human-like feel. Grippers can be articulated in various ways depending on their application area and well-defined desired tasks. As compliant and soft links deflect more under the same load than their rigid body …
Iot Clusters Platform For Data Collection, Analysis, And Visualization Use Case, Soin Abdoul Kassif Baba M Traore
Iot Clusters Platform For Data Collection, Analysis, And Visualization Use Case, Soin Abdoul Kassif Baba M Traore
Symposium of Student Scholars
Climate change is happening, and many countries are already facing devastating consequences. Populations worldwide are adapting to the season's unpredictability they relay to lands for agriculture. Our first research was to develop an IoT Clusters Platform for Data Collection, analysis, and visualization. The platform comprises hardware parts with Raspberry Pi and Arduino's clusters connected to multiple sensors. The clusters transmit data collected in real-time to microservices-based servers where the data can be accessed and processed. Our objectives in developing this platform were to create an efficient data collection system, relatively cheap to implement and easy to deploy in any part …
Analysis Of The Internal Delays Of Various Wireless Technologies For Autonomous Vehicle Applications, Luanne Seaman
Analysis Of The Internal Delays Of Various Wireless Technologies For Autonomous Vehicle Applications, Luanne Seaman
Symposium of Student Scholars
Analysis of the Internal Delays of Various Wireless Technologies for Autonomous Vehicle Applications
Poster Presentation Undergraduate Student: Luanne Seaman
Research Mentor: Dr. Billy Kihei
Autonomous vehicles use VANETs (vehicular ad-hoc networks) to communicate with the world around them. Despite the simple premise, VANETs rely on a variety of wireless technologies depending on range, internal delay, urgency of information, and other factors. Therefore, VANET algorithms will need to weigh these elements accordingly. Through this research, I hope to contribute reliable measurements of internal delay to reduce the algorithms’ complexity. To calculate internal delay, I connected two Arduinos to a STM32 Nucleo …
A Brief Literature Review For Machine Learning In Autonomous Robotic Navigation, Jake Biddy, Jeremy Evert
A Brief Literature Review For Machine Learning In Autonomous Robotic Navigation, Jake Biddy, Jeremy Evert
Student Research
Machine learning is becoming very popular in many technological aspects worldwide, including robotic applications. One of the unique aspects of using machine learning in robotics is that it no longer requires the user to program every situation. The robotic application will be able to learn and adapt from its mistakes. In most situations, robotics using machine learning is designed to fulfill a task better than a human could, and with the machine learning aspect, it can function at the highest level of efficiency and quality. However, creating a machine learning program requires extensive coding and programming knowledge that can be …
Computational Analysis Of The Synthesis Of Hydrogels Using The Diels Alder Reaction, Avery Boley
Computational Analysis Of The Synthesis Of Hydrogels Using The Diels Alder Reaction, Avery Boley
Honors Theses
No abstract provided.
Putin And Putnam: Interpreting Russian Military Activity Through A Three Player, Two-Level Game, Nathan M. Colvin
Putin And Putnam: Interpreting Russian Military Activity Through A Three Player, Two-Level Game, Nathan M. Colvin
Modeling, Simulation and Visualization Student Capstone Conference
Is Vladimir Putin a bad strategist, perhaps irrational? Previous military activity by Russia, such as the annexation of Crimea of 2014, yielded limited international gains, at a significant economic and reputational cost. Yet as the 2022 invasion of Ukraine shows, Putin is willing to commit military power, despite the cost of sanctions and other possible retaliation. This three-player simultaneous game, originally created in June, 2021, demonstrates how domestic and international considerations of President Vladimir Putin might lead to otherwise unpredictable Russian military behavior. In this extended version of Robert Putnam’s “two-level game,” President Putin rationally uses the international venue as …
Deapsecure Computational Training For Cybersecurity: Third-Year Improvements And Impacts, Bahador Dodge, Jacob Strother, Rosby Asiamah, Karina Arcaute, Wirawan Purwanto, Masha Sosonkina, Hongyi Wu
Deapsecure Computational Training For Cybersecurity: Third-Year Improvements And Impacts, Bahador Dodge, Jacob Strother, Rosby Asiamah, Karina Arcaute, Wirawan Purwanto, Masha Sosonkina, Hongyi Wu
Modeling, Simulation and Visualization Student Capstone Conference
The Data-Enabled Advanced Training Program for Cybersecurity Research and Education (DeapSECURE) was introduced in 2018 as a non-degree training consisting of six modules covering a broad range of cyberinfrastructure techniques, including high performance computing, big data, machine learning and advanced cryptography, aimed at reducing the gap between current cybersecurity curricula and requirements needed for advanced research and industrial projects. By its third year, DeapSECURE, like many other educational endeavors, experienced abrupt changes brought by the COVID-19 pandemic. The training had to be retooled to adapt to fully online delivery. Hands-on activities were reformatted to accommodate self-paced learning. In this paper, …
Real-Time External Labeling For Interactive Visualization In Virtual Environments, Shan Liu, Yuzhong Shen
Real-Time External Labeling For Interactive Visualization In Virtual Environments, Shan Liu, Yuzhong Shen
Modeling, Simulation and Visualization Student Capstone Conference
A real-time external labeling algorithm has been developed to explore the potential for applying annotation and visualization to virtual reality environments, which manages label placement in the projections of virtual 3D models on the view plane. The approach intends to place labels with visual constraints, such as no overlapping, intersections, and occlusions, close proximity to the model parts, by adjusting external annotations' positions concerning available space in the view plane. This algorithm is based on the projected model's contour and adapts to camera viewpoint changes within interactive frame rates. It solves the visibility problem of annotations and operates in real-time …
Multi-Modality Breast Mri Segmentation Using Nn-Unet For Preoperative Planning Of Robotic Surgery Navigation, Motaz Alqaoud, John Plemmons Md, Eric Feliberti Md, Facs, Krishnanand Kaipa, Siqin Dong, Gabor Fichtinger, Yimming Xiao, Michel Audette
Multi-Modality Breast Mri Segmentation Using Nn-Unet For Preoperative Planning Of Robotic Surgery Navigation, Motaz Alqaoud, John Plemmons Md, Eric Feliberti Md, Facs, Krishnanand Kaipa, Siqin Dong, Gabor Fichtinger, Yimming Xiao, Michel Audette
Modeling, Simulation and Visualization Student Capstone Conference
Segmentation of the chest region and breast tissues is essential for surgery planning and navigation. This paper proposes the foundation for preoperative segmentation based on two cascaded architectures of deep neural networks (DNN) based on the state-of-the-art nnU-Net. Additionally, this study introduces a polyvinyl alcohol cryogel (PVA-C) breast phantom based on the segmentation of the DNN automated approach, enabling the experiments of navigation system for robotic breast surgery. Multi-modality breast MRI datasets of T2W and STIR images were acquired from 10 patients. Segmentation evaluation utilized the Dice Similarity Coefficient (DSC), segmentation accuracy, sensitivity, and specificity. First, a single class labeling …