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2022

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Articles 781 - 810 of 1255

Full-Text Articles in Computer Engineering

A Low-Cost And Low-Tech Solution To Test For Variations Between Multiple Offline Programming Software Packages., Steffen Wendell Bolz Apr 2022

A Low-Cost And Low-Tech Solution To Test For Variations Between Multiple Offline Programming Software Packages., Steffen Wendell Bolz

Masters Theses & Specialist Projects

This research paper chronicles the attempt to bring forth a low-cost and low-tech testing methodology whereby multiple offline programming (OLP) software packages’ generated programs may be compared when run on industrial robots. This research was initiated by the discovery that no real research exists to test between iterations of OLP software packages and that most research for positional accuracy and/or repeatability on industrial robots is expensive and technologically intensive. Despite this, many countries’ leaders are pushing for intensive digitalization of manufacturing and Small and Mediumsized Enterprises (SMEs) are noted to be lagging in adoption of such technologies. The research consisted …

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A Low-Cost, Long-Range, And Solar-Based Iot Soil Quality Monitor, Salvador Garcia, Trina Nguyen, Julian Wong Apr 2022

A Low-Cost, Long-Range, And Solar-Based Iot Soil Quality Monitor, Salvador Garcia, Trina Nguyen, Julian Wong

Interdisciplinary Design Senior Theses

The project objective is to create a low-cost, long-range, and solar-based IoT soil quality monitoring system. The system must transmit packages of data gathered from separate nodes, consisting of two dierent types of sensors, to a centralized gateway receiver to be displayed to the user in an elegant and readable manner. The end goal of the project is to supplement produce grown by large agricultural bodies around the United States without the misuse of water resources. This report presents the need for this system, details the components of the system, and the rationale behind design choices. It serves as a …

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Society Dilemma Of Computer Technology Management In Today's World, Iwasan D. Kejawa Ed.D Apr 2022

Society Dilemma Of Computer Technology Management In Today's World, Iwasan D. Kejawa Ed.D

School of Computing: Faculty Publications

Abstract - Is it true that some of the inhabitants of the world’s today are still hesitant in using computers? Research has shown that today many people are still against the use of computers. Computer technology management can be said to be obliterated by security problems. Research shows that some people in society feel reluctant or afraid to use computers because of errors and exposure of their privacy and their sophistication, which sometimes are caused by computer hackers and malfunction of the computers. The dilemma of not utilizing computer technology at all or, to its utmost, by certain people in …

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Cova Cci Undergrad Cyber Research, Nana Jeffrey Apr 2022

Cova Cci Undergrad Cyber Research, Nana Jeffrey

Cybersecurity Undergraduate Research Showcase

Is your digital assistant your worst enemy? Modern technology has impacted our lives in a positive way making tasks that were once time consuming become more convenient. For example a few years ago writing down your grocery list with a paper and pen was a norm, now with technology we have access to IoT devices such as smart fridges that can inform us on what items are low in stock, send a message to our digital assistants such as iOS Siri and Amazon's Alexa to remind us to buy those groceries. Although these digital assistants have helped make our daily …

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Verifiable Searchable Encryption Framework Against Insider Keyword-Guessing Attack In Cloud Storage, Yinbin Miao, Robert H. Deng, Kim-Kwang Raymond Choo, Ximeng Liu, Hongwei Li Apr 2022

Verifiable Searchable Encryption Framework Against Insider Keyword-Guessing Attack In Cloud Storage, Yinbin Miao, Robert H. Deng, Kim-Kwang Raymond Choo, Ximeng Liu, Hongwei Li

Research Collection School Of Computing and Information Systems

Searchable encryption (SE) allows cloud tenants to retrieve encrypted data while preserving data confidentiality securely. Many SE solutions have been designed to improve efficiency and security, but most of them are still susceptible to insider Keyword-Guessing Attacks (KGA), which implies that the internal attackers can guess the candidate keywords successfully in an off-line manner. Also in existing SE solutions, a semi-honest-but-curious cloud server may deliver incorrect search results by performing only a fraction of retrieval operations honestly (e.g., to save storage space). To address these two challenging issues, we first construct the basic Verifiable SE Framework (VSEF), which can withstand …

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Towards Improved Inertial Navigation By Reducing Errors Using Deep Learning Methodology, Hua Chen, Tarek M. Taha, Vamsy P. Chodavarapu Apr 2022

Towards Improved Inertial Navigation By Reducing Errors Using Deep Learning Methodology, Hua Chen, Tarek M. Taha, Vamsy P. Chodavarapu

Electrical and Computer Engineering Faculty Publications

Autonomous vehicles make use of an Inertial Navigation System (INS) as part of vehicular sensor fusion in many situations including GPS-denied environments such as dense urban places, multi-level parking structures, and areas with thick tree-coverage. The INS unit incorporates an Inertial Measurement Unit (IMU) to process the linear acceleration and angular velocity data to obtain orientation, position, and velocity information using mechanization equations. In this work, we describe a novel deep-learning-based methodology, using Convolutional Neural Networks (CNN), to reduce errors from MEMS IMU sensors. We develop a CNN-based approach that can learn from the responses of a particular inertial sensor …

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Ux/U-Eye: Designing Graphical User Interfaces For Exclusive Eye Gaze Control, Timothy Curol Apr 2022

Ux/U-Eye: Designing Graphical User Interfaces For Exclusive Eye Gaze Control, Timothy Curol

Honors Capstones

No abstract provided.

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Generative Adversarial Networks Take On Hand Drawn Sketches: An Application To Louisiana Culture And Mardi Gras Fashion, Stephanie Hines Apr 2022

Generative Adversarial Networks Take On Hand Drawn Sketches: An Application To Louisiana Culture And Mardi Gras Fashion, Stephanie Hines

Honors Capstones

No abstract provided.

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Development Of A Ppg Sensor Array As A Wearable Device For Monitoring Cardiovascular Metrics, Jose Ignacio Rodriguez-Labra Apr 2022

Development Of A Ppg Sensor Array As A Wearable Device For Monitoring Cardiovascular Metrics, Jose Ignacio Rodriguez-Labra

Masters Theses

Wearable devices with integrated sensors for tracking human vitals are widely used for a variety of applications, including exercise, wellness, and health monitoring. Photoplethysmography (PPG) sensors use pulse oximetry to measure pulse rate, cardiac cycle, oxygen saturation, and blood flow by passing a light beam of variable wavelength through the skin and measuring its reflection. A multi-channel PPG wearable system was developed to include multiple nodes of pulse oximeters, each capable of using different wavelengths of light. The system uses sensor fusion along with a machine learning model to perform feature extraction of relevant cardiovascular metrics across multiple pulse oximeters …

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Discovering Ways To Increase Inclusivity For Dyslexic Students In Computing Education, Felicia Hellems, Sajal Bhatia Apr 2022

Discovering Ways To Increase Inclusivity For Dyslexic Students In Computing Education, Felicia Hellems, Sajal Bhatia

School of Computer Science & Engineering Faculty Publications

The years accompanying entrance into the university system are often characterized by a period of great transformation. These years can also be wrought with difficulties for many students, difficulties which are often compounded in students with disabilities (SWD). Reports from the U.S. Department of Education show that as recently as 2015--16, 19% of undergraduate students experienced some form of disability1. Additionally, statistics show that SWD tend to have lower post secondary completion rates than their counterparts [3]. A review of pertinent literature has shown that there still exist gaps within the field of computing education (CE) for teaching cybersecurity concepts …

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An Overview Of The Potential For Blockchain Technology To Improve Cybersecurity, Stanley Mierzwa Apr 2022

An Overview Of The Potential For Blockchain Technology To Improve Cybersecurity, Stanley Mierzwa

Center for Cybersecurity

The purpose of this short research commentary is to provide a focused, semi-deep dive into the effort the industry places on cybersecurity defense and operations and the potential to integrate blockchain technology. As cybersecurity threats and incidents continue to rise, better procedures and strategies to protect our organizations’ data and systems are crucial to sustaining viable operations. Given that blockchain technology can potentially disrupt other industries (Moore, 2020), it is imperative to examine how it may improve our cybersecurity.

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Cybersecurity Best Practices For The Manufacturing Industry, David Ortiz, Stanley Mierzwa Apr 2022

Cybersecurity Best Practices For The Manufacturing Industry, David Ortiz, Stanley Mierzwa

Center for Cybersecurity

The manufacturing and industrial sectors have evolved with the introduction of technologies over the past many decades. Progress in improving processes, techniques, output, quality, and efficiencies have been gained with new emerging technologies, resulting in positive and fortuitous changes for organizations. With the rapid movement towards a modern-day manufacturing environment, new and connected technologies that employ greater cyber-connectedness continue to grow, but at the same time, introduce cybersecurity risks.

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Learning Domain Invariant Information To Enhance Presentation Attack Detection In Visible Face Recognition Systems, Jennifer Hamblin Apr 2022

Learning Domain Invariant Information To Enhance Presentation Attack Detection In Visible Face Recognition Systems, Jennifer Hamblin

Department of Electrical and Computer Engineering: Dissertations, Theses, and Student Research

Face signatures, including size, shape, texture, skin tone, eye color, appearance, and scars/marks, are widely used as discriminative, biometric information for access control. Despite recent advancements in facial recognition systems, presentation attacks on facial recognition systems have become increasingly sophisticated. The ability to detect presentation attacks or spoofing attempts is a pressing concern for the integrity, security, and trust of facial recognition systems. Multi-spectral imaging has been previously introduced as a way to improve presentation attack detection by utilizing sensors that are sensitive to different regions of the electromagnetic spectrum (e.g., visible, near infrared, long-wave infrared). Although multi-spectral presentation attack …

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Assessing Security Risks With The Internet Of Things, Faith Mosemann Apr 2022

Assessing Security Risks With The Internet Of Things, Faith Mosemann

Senior Honors Theses

For my honors thesis I have decided to study the security risks associated with the Internet of Things (IoT) and possible ways to secure them. I will focus on how corporate, and individuals use IoT devices and the security risks that come with their implementation. In my research, I found out that IoT gadgets tend to go unnoticed as a checkpoint for vulnerability. For example, often personal IoT devices tend to have the default username and password issued from the factory that a hacker could easily find through Google. IoT devices need security just as much as computers or servers …

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Pre-Training Graph Neural Networks For Link Prediction In Biomedical Networks, Yahui Long, Min Wu, Yong Liu, Yuan Fang, Chee Kong Kwoh, Jiawei Luo, Xiaoli Li Apr 2022

Pre-Training Graph Neural Networks For Link Prediction In Biomedical Networks, Yahui Long, Min Wu, Yong Liu, Yuan Fang, Chee Kong Kwoh, Jiawei Luo, Xiaoli Li

Research Collection School Of Computing and Information Systems

Motivation: Graphs or networks are widely utilized to model the interactions between different entities (e.g., proteins, drugs, etc) for biomedical applications. Predicting potential links in biomedical networks is important for understanding the pathological mechanisms of various complex human diseases, as well as screening compound targets for drug discovery. Graph neural networks (GNNs) have been designed for link prediction in various biomedical networks, which rely on the node features extracted from different data sources, e.g., sequence, structure and network data. However, it is challenging to effectively integrate these data sources and automatically extract features for different link prediction tasks. Results: In …

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Dynamics And Simulations Of Discretized Caputo-Conformable Fractional-Order Lotka–Volterra Models, Yousef Feras, Semmar Billel, Al Nasr Kamal Apr 2022

Dynamics And Simulations Of Discretized Caputo-Conformable Fractional-Order Lotka–Volterra Models, Yousef Feras, Semmar Billel, Al Nasr Kamal

Computer Science Faculty Research

In this article, a prey–predator system is considered in Caputo-conformable fractional-order derivatives. First, a discretization process, making use of the piecewise-constant approximation, is performed to secure discrete-time versions of the two fractional-order systems. Local dynamic behaviors of the two discretized fractional-order systems are investigated. Numerical simulations are executed to assert the outcome of the current work. Finally, a discussion is conducted to compare the impacts of the Caputo and conformable fractional derivatives on the discretized model.

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The Music Bluetooth Controller: An Intersection Between Technology And Music, Lydia Wu Apr 2022

The Music Bluetooth Controller: An Intersection Between Technology And Music, Lydia Wu

Senior Honors Theses

The modern musician faces a new challenge: how can technology be used to enhance a performance? This thesis documents the development of a Bluetooth remote controller that will aid today’s performing musicians by interacting with a digital display (e.g., an iPad) to flip musical score pages remotely. At its core, while mimicking a Bluetooth pedal (the current industry standard), this device attaches to the musician’s hand. In its pilot stages, the device has been referred to “MBC” (Music Bluetooth Controller).

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Privacy-Preserving Information Security For The Energy Grid Of Things, Mohammed Alsaid, Nirupama Bulusu, Abdullah Barghouti, N. Sonali Fernando, John M. Acken, Tylor E. Slay, Robert B. Bass Apr 2022

Privacy-Preserving Information Security For The Energy Grid Of Things, Mohammed Alsaid, Nirupama Bulusu, Abdullah Barghouti, N. Sonali Fernando, John M. Acken, Tylor E. Slay, Robert B. Bass

Electrical and Computer Engineering Faculty Publications and Presentations

Smart grid infrastructure relies on information exchange between multiple actors in order to ensure system reliability. These actors include but are not limited to smart loads, grid control, and energy management technologies. As information exchange between these actors is susceptible to cyber-attacks, security and privacy issues are indispensable to ensure a reliable and stable grid. This position paper proposes a privacy-preserving, trust-augmented secure scheme for a smart grid implementation.

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Quadratic Neural Network Architecture As Evaluated Relative To Conventional Neural Network Architecture, Reid Taylor Apr 2022

Quadratic Neural Network Architecture As Evaluated Relative To Conventional Neural Network Architecture, Reid Taylor

Senior Theses

Current work in the field of deep learning and neural networks revolves around several variations of the same mathematical model for associative learning. These variations, while significant and exceptionally applicable in the real world, fail to push the limits of modern computational prowess. This research does just that: by leveraging high order tensors in place of 2nd order tensors, quadratic neural networks can be developed and can allow for substantially more complex machine learning models which allow for self-interactions of collected and analyzed data. This research shows the theorization and development of mathematical model necessary for such an idea to …

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Improving Feature Generalizability With Multitask Learning In Class Incremental Learning, Dong Ma, Chi Ian Tang, Cecilia Mascolo Apr 2022

Improving Feature Generalizability With Multitask Learning In Class Incremental Learning, Dong Ma, Chi Ian Tang, Cecilia Mascolo

Research Collection School Of Computing and Information Systems

Many deep learning applications, like keyword spotting [1], [2], require the incorporation of new concepts (classes) over time, referred to as Class Incremental Learning (CIL). The major challenge in CIL is catastrophic forgetting, i.e., preserving as much of the old knowledge as possible while learning new tasks. Various techniques, such as regularization, knowledge distillation, and the use of exemplars, have been proposed to resolve this issue. However, prior works primarily focus on the incremental learning step, while ignoring the optimization during the base model training. We hypothesise that a more transferable and generalizable feature representation from the base model would …

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Conditional Variational Autoencoder (Cvae) For The Augmentation Of Ecl Biosensor Data, Matthew Dulcich Apr 2022

Conditional Variational Autoencoder (Cvae) For The Augmentation Of Ecl Biosensor Data, Matthew Dulcich

Honors Theses

Machine Learning (ML) is vastly improving the world, from computer vision to fully self-driving cars, we are now able accomplish objectives that were thought to only be dreams. In order to train ML models accurately, they require mountains of information to work with, but sometimes it becomes impossible to collect the data needed, so we turn to data augmentation. In this project we use a conditional variational auto encoder to supplement the original video electrochemiluminescence biosensor dataset, in order to increase the accuracy of a future classification model. In other words, using a cVAE we will create unique realistic videos …

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Exploring The Efficiency Of Neural Architecture Search (Nas) Modules, Joshua Dulcich Apr 2022

Exploring The Efficiency Of Neural Architecture Search (Nas) Modules, Joshua Dulcich

Honors Theses

Machine learning is obscure and expensive to develop. Neural architecture search (NAS) algorithms automate this process by learning to create premier ML networks, minimizing the bias and necessity of human experts. From this recently emerging field, most research has focused on optimizing a promisingly unique combination of NAS’s three segments. Despite regularly acquiring state of the art results, this practice sacrifices computing time and resources for slight increases in accuracy; this also obstructs performance comparison across papers. To resolve this issue, we use NASLib’s modular library to test the efficiency per module in a unique subset of combinations. Each NAS …

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On The Reliability Of Wearable Sensors For Assessing Movement Disorder-Related Gait Quality And Imbalance: A Case Study Of Multiple Sclerosis, Steven Díaz Hernández Mar 2022

On The Reliability Of Wearable Sensors For Assessing Movement Disorder-Related Gait Quality And Imbalance: A Case Study Of Multiple Sclerosis, Steven Díaz Hernández

USF Tampa Graduate Theses and Dissertations

Approximately 33 million American adults had a movement disorder associated with medication use, ear infections, injury, or neurological disorders in 2008, with over 18 million people affected by neurological disorders worldwide. Physical therapists assist people with movement disorders by providing interventions to reduce pain, improve mobility, avoid surgeries, and prevent falls and secondary complications of neurodegenerative disorders. Current gait assessments used by physical therapists, such as the Multiple Sclerosis Walking Scale, provide only semi-quantitative data, and cannot assess walking quality in detail or describe how one’s walking quality changes over time. As a result, quantitative systems have grownas useful tools …

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Seabem: An Artificial Intelligence Powered Web Application To Predict Cover Crop Biomass, Aime Christian Tuyishime, Andrea Basche Mar 2022

Seabem: An Artificial Intelligence Powered Web Application To Predict Cover Crop Biomass, Aime Christian Tuyishime, Andrea Basche

Honors Program: Senior Projects (Public)

SEABEM, the Stacked Ensemble Algorithms Biomass Estimator Model, is a web application with a stacked ensemble of Machine Learning (ML) algorithms running on the backend to predict cover crop biomass for locations in Sub-Saharan. The SEABEM model was developed using a previously developed database of crop growth and yield that included site characteristics such as latitude, longitude, soil texture (sand, silt, and clay percentages), temperature, and precipitation. The goal of SEABEM is to provide global farmers, mainly small-scale African farmers, the knowledge they need before practicing and benefiting from cover crops while avoiding the expensive and time-consuming operations that come …

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Mix Method Approach Of Measuring Vr As A Pedagogical Tool To Enhance Experimental Learning: Motivation From Literature Survey Of Previous Study, Muhammad Mujtaba Asad, Aisha Naz Ansari, Prathamesh Churi, Antonio José Moreno Guerrero, Anas A. Salameh Mar 2022

Mix Method Approach Of Measuring Vr As A Pedagogical Tool To Enhance Experimental Learning: Motivation From Literature Survey Of Previous Study, Muhammad Mujtaba Asad, Aisha Naz Ansari, Prathamesh Churi, Antonio José Moreno Guerrero, Anas A. Salameh

Institute for Educational Development, Karachi

This research has been experimented on our previous literature review. Technological advancement has prevailed in the modern era from the 20th century. Artificial intelligence and virtual worlds have been created for rapid technological development. This paper is aimed at exploring the effect of virtual reality as a pedagogical tool for enhancing experiential learning among undergraduate students. Considering this, it was a mixed-methods study following the design of sequential exploratory–which includes qualitative followed by quantitative part. The targeted population was undergraduate students taking education programs from Public Sector Universities of Sindh. For the qualitative part, the sample of eight undergraduate students …

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Barriers And Enablers For Older Adults Participating In A Home-Based Pragmatic Exercise Program Delivered And Monitored By Amazon Alexa: A Qualitative Study, Paul Jansons, Jackson Fyfe, Jack Dalla Via, Robin M. Daly, Eugene Gvozdenko, David Scott Mar 2022

Barriers And Enablers For Older Adults Participating In A Home-Based Pragmatic Exercise Program Delivered And Monitored By Amazon Alexa: A Qualitative Study, Paul Jansons, Jackson Fyfe, Jack Dalla Via, Robin M. Daly, Eugene Gvozdenko, David Scott

Research outputs 2022 to 2026

Background: The remote delivery and monitoring of individually-tailored exercise programs using voice-controlled intelligent personal assistants (VIPAs) that support conversation-based interactions may be an acceptable alternative model of digital health delivery for older adults. The aim of this study was to evaluate the enablers and barriers for older adults participating in a home-based exercise program delivered and monitored by VIPAs. Method: This qualitative study used videoconferencing to conduct semi-structured interviews following a 12-week, prospective single-arm pilot study in 15 adults aged 60 to 89 years living alone in the community. All participants were prescribed an individualized, brief (10 min, 2–4 times …

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A Combined Approach For Private Indexing Mechanism, Pranita Maruti Desai Ms., Vijay Maruti Shelake Mr. Mar 2022

A Combined Approach For Private Indexing Mechanism, Pranita Maruti Desai Ms., Vijay Maruti Shelake Mr.

Journal of Digital Forensics, Security and Law

Private indexing is a set of approaches for analyzing research data that are similar or resemble similar ones. This is used in the database to keep track of the keys and their values. The main subject of this research is private indexing in record linkage to secure the data. Because unique personal identification numbers or social security numbers are not accessible in most countries or databases, data linkage is limited to attributes such as date of birth and names to distinguish between the number of records and the real-life entities they represent. For security reasons, the encryption of these identifiers …

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Research On Algebraic Loop Of Synchronous Generator Simulation Based On Simulink, Shuang Wang, Zhaohui Gao, Siyu Chen, Xiao Tang, Zhan Xi Mar 2022

Research On Algebraic Loop Of Synchronous Generator Simulation Based On Simulink, Shuang Wang, Zhaohui Gao, Siyu Chen, Xiao Tang, Zhan Xi

Journal of System Simulation

Abstract: The problem of algebraic loop is common in Simulink simulation. The existence of algebraic loop will reduce the speed and accuracy of simulation, and even lead to errors in simulation results. Taking the simulation of synchronous generator as an example, the problem of algebraic loop and its elimination method in Simulink simulation are discussed. Starting from the analysis of the basic equations of synchronous generator, the cause of algebraic loop in simulation is discussed, the influence of the algebraic loop on the system simulation is pointed out, using disassembly method and transformation method, focusing on eliminating the algebraic loop, …

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Research On 3d Path Planning Algorithm Based On Fast Rrt Algorithm, Zhaoqiang Li, Shiyu Zhang Mar 2022

Research On 3d Path Planning Algorithm Based On Fast Rrt Algorithm, Zhaoqiang Li, Shiyu Zhang

Journal of System Simulation

Abstract: RRT (rapidly exploring random tree) algorithm is a sampling-based path planning algorithm, which can search a path in high-dimensional environment. The traditional RRT algorithm has the problems of low node utilization and large amount of calculation. To solve these problems, the fast RRT* (Quick RRT*) algorithm is improved by optimizing the strategy of reselection of parent node and pruning range, improving the sampling method and introducing adaptive step size, which makes the algorithm time-consuming and path length shorter. At the same time, the node connection screening strategy is added to eliminate the excessive turning angle in the path. …

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Simulation Of Robust Optimal Synchronization Control For Direct Drive H-Type Motion Platform, Limei Wang, Hongyan Yao, Kang Zhang Mar 2022

Simulation Of Robust Optimal Synchronization Control For Direct Drive H-Type Motion Platform, Limei Wang, Hongyan Yao, Kang Zhang

Journal of System Simulation

Abstract: Cell manufacturing is an important organizational form of modern production systems. In scheduling of cell manufacturing systems, machine failures or interruptions are very common in practice, meanwhile the waste due to energy consumption during machine idle time cannot be ignored. Hence the relevant research is with strong significance. This paper considers the problems of machine interruption and energy consumption in cell scheduling, and developed an integer programming model to minimize the makespan as well as the cost of energy consumption during machine idling and the interruption cost. A mixed optimization method is proposed based on improved wolf pack algorithm …

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