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Articles 2671 - 2700 of 17318
Full-Text Articles in Computer Sciences
Auxiliary Decision-Making Method For Flight Support Force Allocation Based On Dbn, Junyang Liu, Shisong Zhu
Auxiliary Decision-Making Method For Flight Support Force Allocation Based On Dbn, Junyang Liu, Shisong Zhu
Journal of System Simulation
Abstract: In order to make up for the deficiency of decision-making methods of full deployment and proportional allocation in airport flight support activities, an auxiliary decision-making model for airport flight support force allocation based on a dynamic Bayesian network (DBN) is constructed.On the basis of quantifying the strength of the support force, thehidden Markov model and Hausdorff distance algorithm are introduced to make auxiliary decisions for flight support activities under different conditions and define relevant decision evaluation indexes as the basis for model verification. Simulation tests are carried out on airport flight support activities under two …
Two-Stage Distributed Robust Optimal Dispatching For A Combined Heat And Power Virtual Power Plant, Yaqian Fan, Songyuan Yu, Fang Fang
Two-Stage Distributed Robust Optimal Dispatching For A Combined Heat And Power Virtual Power Plant, Yaqian Fan, Songyuan Yu, Fang Fang
Journal of System Simulation
Abstract: Combined heat and power virtual power plant (CHP-VPP) aggregates various electrical and thermal output units and takes into account the uncertainty of wind and solar output, dynamic electricity prices, thermal comfort of users, and other influences to achieve optimal dispatching of overall output. A two-stage distributed robust optimal dispatching method is proposed. In the first stage, planned dispatching is considered, so as to maximize the benefit of CHP-VPP. In the second stage, a fuzzy set of wind and solar output uncertainties is constructed based on the distributed robust method of moment uncertainty, and …
Multi-Camera Vehicle Recognition Method Based On Feature Robustness Enhancement, Huicheng Luo, Shujuan Wang
Multi-Camera Vehicle Recognition Method Based On Feature Robustness Enhancement, Huicheng Luo, Shujuan Wang
Journal of System Simulation
Abstract: Due to factors such as viewpoint changes, complex environments, and pose differences under multiple cameras, the images of the same vehicle in different scenes show huge appearance ambiguity, which brings challenges to vehicle identity matching. In order to solve this problem, a feature robustness enhancement method for vehicle recognition is proposed under the transformer framework. Based on the fact that the structural information of the vehicle is invariant under multiple cameras, a module for enhancing structural information guided by contour features is designed, and a structural feature perception loss is proposed to promote the fusion …
Picking Path Planning Of Container Robots Based On Improved Genetic Algorithm, Yuwen Wu, Zhiyue Niu, Zhenping Li
Picking Path Planning Of Container Robots Based On Improved Genetic Algorithm, Yuwen Wu, Zhiyue Niu, Zhenping Li
Journal of System Simulation
Abstract: Under the new "container-to-person" picking mode in intelligent warehouses, a new optimization model and its improved genetic algorithm are proposed to solve the picking path planning problem of multiple container robots. According to the picking mode and characteristics of container robots, the picking path planning problem is transformed into an asymmetric vehicle routing problem, and a mixed integer programming model is established with bi-objectives of the shortest total picking path and the least completion time. A hybrid genetic algorithm is designed to solve this model, and the effectiveness and stability of the algorithm are verified …
Simulation Platform For Optimization And Decision Making Of Flexible Manufacturing Process Of Automatic Production Lines, Chao Fu, Dongyue Wang, Xinxin Li, Min Xue
Simulation Platform For Optimization And Decision Making Of Flexible Manufacturing Process Of Automatic Production Lines, Chao Fu, Dongyue Wang, Xinxin Li, Min Xue
Journal of System Simulation
Abstract: In order to simulate a flexible manufacturing process to verify the correctness of theoretical computation and analysis and find other important factors for optimization and decision making in the manufacturing process, a simulation platform for the optimization and decision making of the flexible manufacturing process of automatic production lines is designed and developed. The framework of the simulation platform is constructed with four hierarchies, including the enterprise production hierarchy, optimization and decision making hierarchy, data resource hierarchy, and function module hierarchy. On this basis, the functional implementation of the modules of production allocation …
Modeling And Simulation Of Spaceborne, Near-Spaceborne, And Airborne Integrated Collaborative Remote Sensing System Based On Dodaf, Lili An, Tian Xia, Wenbin Yang, Xinbo Wu
Modeling And Simulation Of Spaceborne, Near-Spaceborne, And Airborne Integrated Collaborative Remote Sensing System Based On Dodaf, Lili An, Tian Xia, Wenbin Yang, Xinbo Wu
Journal of System Simulation
Abstract: Spaceborne, near-spaceborne, and airborne integrated collaborative remote sensing system (SNA-ICRSS) makes comprehensive use of modern information technology to aggregate multiple and heterogeneous data in spaceborne, near-spaceborne, and airborne domains, so as to realize accurate emergency service and command decision-making. SNA-ICRSS is huge and complex, and there is a lack of research on its architecture modeling and simulation. According to the architecture characteristics of the SNA-ICRSS, the minimum prototype of the SNA-ICRSS is constructed; through the department of defense architecture framework (DoDAF) and activity based methodology (ABM) methods, the minimal prototype of the SNA-ICRSS is modeled, and the operational resource …
An Algorithm For Obtaining Interception Guidance Routes Weighted By Threat Indexes, Shuyuan Liu
An Algorithm For Obtaining Interception Guidance Routes Weighted By Threat Indexes, Shuyuan Liu
Journal of System Simulation
Abstract: Interception guidance and threat assessment are two inseparable parts of command and control. The former implements specific command and guidance through guidance solutions, and the latter provides basis for threat assessment and situation advantage to command and control. Taking threat indexes as the weight, a kind of optimal interception route index is proposed to obtain the guidance solution with the least threat. Simulation results show that the proposed algorithm can effectively provide routing solutions for interception with the least threat, and is reliable under different situations, or with different weights of threat indexes. The algorithm provides a new idea …
Partial Task Offloading Strategy Of Cloud Robots Based On Game Theory Under Cloud-Edge Coordination, Chunmao Jiang, Zhenxing Yang
Partial Task Offloading Strategy Of Cloud Robots Based On Game Theory Under Cloud-Edge Coordination, Chunmao Jiang, Zhenxing Yang
Journal of System Simulation
Abstract: How to rationally utilize the resources of central and edge clouds to reduce energy consumption of system equipment and shorten average task completion time is a fundamental challenge for computational task offloading of cloud robots. In this paper, we transform the computational task offloading problem of multiple cloud robots into a multi-actor game model by using the computational task completion time and energy consumption of cloud robots as cost measurement indicators and setting different cost weights according to actual needs. We also develop a game theory-based partial task offloading algorithm (GT-PTO). With the Nash equilibrium state …
Fixed-Wing Uav Detection Based On Simulated Data Transfer Learning, Yu Fu, Yao Zhang, Meng Zhao, Mianzhao Wang, Jiangpeng Zheng, Chen Jia, Shengyong Chen
Fixed-Wing Uav Detection Based On Simulated Data Transfer Learning, Yu Fu, Yao Zhang, Meng Zhao, Mianzhao Wang, Jiangpeng Zheng, Chen Jia, Shengyong Chen
Journal of System Simulation
Abstract: Data play an important role in visual inspection tasks, but it is difficult to obtain a sufficient amount of real fixed-wing UAV data. Therefore, a data set containing a large number of simulated fixed-wing UAV data and a small number of real fixed-wing UAV data is constructed, and the real fixed-wing UAV data are detected by training simulated fixed-wing UAV data based on the idea of weight transfer. On this basis, a two-stage learning strategy is proposed to further reduce the missed detection rate of UAVs by using multi-scale feature fusion.The simulation results show that …
Research On No-Wait Flow Shop Scheduling Based On Discrete State Transition Algorithm, Jiaying Yu, Hongli Zhang, Yingchao Dong
Research On No-Wait Flow Shop Scheduling Based On Discrete State Transition Algorithm, Jiaying Yu, Hongli Zhang, Yingchao Dong
Journal of System Simulation
Abstract: In view of the no-wait flow shop problem (NWFSP) widely existing in the manufacturing industry, an improved discrete state transition algorithm (IDSTA) is proposed to solve the problem. The coding mode of the workpiece is designed based on the characteristics of the flow shop scheduling problem (FSSP). The initial solution is constructed by the Nawaz-Enscore-Ham (NEH) method with the standard deviation of the processing time of the workpiece as the priority, and a multi-neighborhood combinatorial search strategy based on insertion and exchange is designed to improve the quality of the initial solution. A discrete state transition algorithm ( …
Action Recognition Method Based On Projection Subspace Views Under Single Viewing Angle, Benyue Su, Manzhen Sun, Qing Ma, Min Sheng
Action Recognition Method Based On Projection Subspace Views Under Single Viewing Angle, Benyue Su, Manzhen Sun, Qing Ma, Min Sheng
Journal of System Simulation
Abstract: In view of the self-occlusion problem of joint action tracking by a depth camera under a single viewing angle, a new human action recognition method based on projection subspace views is proposed. Without adding data acquisition equipment, the method projects the three-dimensional(3D) action sequences obtained under a single viewing angle into multiple two-dimensional subspacesand then seeks the maximum distance between classes in the two-dimensional subspaces, so as to increase the distance between 3D actions based on the fusion of multiple subspace views as much as possible. The recognition rate in the self-built AQNU …
Vitreoscilla Globin Promoter Cloning And Testing In Escherichia Coli, Lauren J. Coffey
Vitreoscilla Globin Promoter Cloning And Testing In Escherichia Coli, Lauren J. Coffey
Rose-Hulman Undergraduate Research Publications
No abstract provided.
A Neutrosophic Framework For Assessment Of Distributed Circular Water To Give Neighborhoods Analysis To Prepare For Unexpected Stressor Events, Mohamed Abouhawwash, Mohammed Jameel, Sameh S. Askar
A Neutrosophic Framework For Assessment Of Distributed Circular Water To Give Neighborhoods Analysis To Prepare For Unexpected Stressor Events, Mohamed Abouhawwash, Mohammed Jameel, Sameh S. Askar
Neutrosophic Systems with Applications
The global water issue is caused by a number of factors, including extreme weather, population increase, and industrial activity. One of the reasons we're running out of water as a planet is because of the outdated take-make-use-throw-away linear paradigm of handling water. It has been suggested that the circular economy may help alleviate water shortages by inspiring a fundamental change in municipal water infrastructure. Reduced consumption, recovered natural resources, and minimal waste are the three pillars of a circular water supply. A dispersed water supply is more adaptable and robust than a centralized one because it gives communities more time …
A Neutrosophic Framework For Assessment Of Distributed Circular Water To Give Neighborhoods Analysis To Prepare For Unexpected Stressor Events, Mohamed Abouhawwash, Mohammed Jameel, Sameh S. Askar
A Neutrosophic Framework For Assessment Of Distributed Circular Water To Give Neighborhoods Analysis To Prepare For Unexpected Stressor Events, Mohamed Abouhawwash, Mohammed Jameel, Sameh S. Askar
Neutrosophic Systems with Applications
The global water issue is caused by a number of factors, including extreme weather, population increase, and industrial activity. One of the reasons we're running out of water as a planet is because of the outdated take-make-use-throw-away linear paradigm of handling water. It has been suggested that the circular economy may help alleviate water shortages by inspiring a fundamental change in municipal water infrastructure. Reduced consumption, recovered natural resources, and minimal waste are the three pillars of a circular water supply. A dispersed water supply is more adaptable and robust than a centralized one because it gives communities more time …
Identifying Key Activity Indicators In Rats' Neuronal Data Using Lasso Regularized Logistic Regression, Avery Woods
Identifying Key Activity Indicators In Rats' Neuronal Data Using Lasso Regularized Logistic Regression, Avery Woods
Honors Theses
This thesis aims to identify timestamps of rats’ neuronal activity that best determine behavior using a machine learning model. Neuronal data is a complex and high-dimensional dataset, and identifying the most informative features is crucial for understanding the underlying neuronal processes. The Lasso regularization technique is employed to select the most relevant features of the data to the model’s prediction. The results of this study provide insights into the key activity indicators that are associated with specific behaviors or cognitive processes in rats, as well as the effect that stress can have on neuronal activity and behavior. Ultimately, it was …
Integrated Neutrosophic Best-Worst Method For Comprehensive Analysis And Ranking Of Flood Risks: A Case Study Approach From Aswan, Egypt, Safa Al-Saeed, Nabil M. Abdelaziz
Integrated Neutrosophic Best-Worst Method For Comprehensive Analysis And Ranking Of Flood Risks: A Case Study Approach From Aswan, Egypt, Safa Al-Saeed, Nabil M. Abdelaziz
Neutrosophic Systems with Applications
This paper presents a comprehensive framework for the analysis and ranking of flood risks with respect to regional variations and data uncertainties under a Neutrosophic environment. The research introduces a novel approach to flood risk mitigation and management, bringing together the scientifically robust Best-Worst Method (BWM) and single-valued Neutrosophic set for the first time. The unique application of a single-valued Neutrosophic set allows us to better illustrate and manage uncertainty, imprecision, and vagueness in data. Additionally, we employ BWM, a multi-factor decision-making method, for discerning and ranking the most influential flood risk factors. Together, the integrated methodologies provide a balanced, …
Integrated Neutrosophic Best-Worst Method For Comprehensive Analysis And Ranking Of Flood Risks: A Case Study Approach From Aswan, Egypt, Safa Al-Saeed, Nabil M. Abdelaziz
Integrated Neutrosophic Best-Worst Method For Comprehensive Analysis And Ranking Of Flood Risks: A Case Study Approach From Aswan, Egypt, Safa Al-Saeed, Nabil M. Abdelaziz
Neutrosophic Systems with Applications
This paper presents a comprehensive framework for the analysis and ranking of flood risks with respect to regional variations and data uncertainties under a Neutrosophic environment. The research introduces a novel approach to flood risk mitigation and management, bringing together the scientifically robust Best-Worst Method (BWM) and single-valued Neutrosophic set for the first time. The unique application of a single-valued Neutrosophic set allows us to better illustrate and manage uncertainty, imprecision, and vagueness in data. Additionally, we employ BWM, a multi-factor decision-making method, for discerning and ranking the most influential flood risk factors. Together, the integrated methodologies provide a balanced, …
Secure And Efficient Federated Learning, Xingyu Li
Secure And Efficient Federated Learning, Xingyu Li
Theses and Dissertations
In the past 10 years, the growth of machine learning technology has been significant, largely due to the availability of large datasets for training. However, gathering a sufficient amount of data on a central server can be challenging. Additionally, with the rise of mobile networking and the large amounts of data generated by IoT devices, privacy and security issues have become a concern, resulting in government regulations such as GDPR, HIPAA, CCPA, and ADPPA. Under these circumstances, traditional centralized machine learning methods face a problem in that sensitive data must be kept locally for privacy reasons, making it difficult to …
Eddy Current Defect Response Analysis Using Sum Of Gaussian Methods, James William Earnest
Eddy Current Defect Response Analysis Using Sum Of Gaussian Methods, James William Earnest
Theses and Dissertations
This dissertation is a study of methods to automatedly detect and produce approximations of eddy current differential coil defect signatures in terms of a summed collection of Gaussian functions (SoG). Datasets consisting of varying material, defect size, inspection frequency, and coil diameter were investigated. Dimensionally reduced representations of the defect responses were obtained utilizing common existing reduction methods and novel enhancements to them utilizing SoG Representations. Efficacy of the SoG enhanced representations were studied utilizing common Machine Learning (ML) interpretable classifier designs with the SoG representations indicating significant improvement of common analysis metrics.
Du Undergraduate Showcase: Research, Scholarship, And Creative Works, Caitlyn Aldersea, Justin Bravo, Sam Allen, Anna Block, Connor Block, Emma Buechler, Maria De Los Angeles Bustillos, Arianna Carlson, William Christensen, Olivia Kachulis, Noah Craver, Kate Dillon, Muskan Fatima, Angel Fernandes, Emma Finch, Colleen Cassidy, Amy Fishman, Andrea Francis, Stacia Fritz, Simran Gill, Emma Gries, Rylie Hansen, Shannon Powers, Jacqueline Martinez, Zachary Harker, Ashley Hasty, Mykaela Tanino-Springsteen, Kathleen Hopps, Adelaide Kerenick, Colin Kleckner, Ci Koehring, Elijah Kruger, Braden Krumholz, Maddie Leake, Lyneé Alves, Seraphina Loukas, Yatzari Lozano Vazquez, Haley Maki, Emily Martinez, Sierra Mckinney, Audrey Mitchell, Kipling Newman, Audrey Ng, Megan Lucyshyn, Andrew Nguyen, Stevie Ostman, Casandra Pearson, Alexandra Penney, Julia Gielczynski, Tyler Ball, Anna Rini, Christina Rorres, Simon Ruland, Helayna Schafer, Emma Sellers, Sarah Schuller, Claire Shaver, Kevin Summers, Isabella Shaw, Madison Sinar, Claudia Pena, Apshara Siwakoti, Carter Sorensen, Madi Sousa, Anna Sparling, Alexandra Revier, Brandon Thierry, Dylan Tyree, Maggie Williams, Lauren Wols
Du Undergraduate Showcase: Research, Scholarship, And Creative Works, Caitlyn Aldersea, Justin Bravo, Sam Allen, Anna Block, Connor Block, Emma Buechler, Maria De Los Angeles Bustillos, Arianna Carlson, William Christensen, Olivia Kachulis, Noah Craver, Kate Dillon, Muskan Fatima, Angel Fernandes, Emma Finch, Colleen Cassidy, Amy Fishman, Andrea Francis, Stacia Fritz, Simran Gill, Emma Gries, Rylie Hansen, Shannon Powers, Jacqueline Martinez, Zachary Harker, Ashley Hasty, Mykaela Tanino-Springsteen, Kathleen Hopps, Adelaide Kerenick, Colin Kleckner, Ci Koehring, Elijah Kruger, Braden Krumholz, Maddie Leake, Lyneé Alves, Seraphina Loukas, Yatzari Lozano Vazquez, Haley Maki, Emily Martinez, Sierra Mckinney, Audrey Mitchell, Kipling Newman, Audrey Ng, Megan Lucyshyn, Andrew Nguyen, Stevie Ostman, Casandra Pearson, Alexandra Penney, Julia Gielczynski, Tyler Ball, Anna Rini, Christina Rorres, Simon Ruland, Helayna Schafer, Emma Sellers, Sarah Schuller, Claire Shaver, Kevin Summers, Isabella Shaw, Madison Sinar, Claudia Pena, Apshara Siwakoti, Carter Sorensen, Madi Sousa, Anna Sparling, Alexandra Revier, Brandon Thierry, Dylan Tyree, Maggie Williams, Lauren Wols
DU Undergraduate Research Journal Archive
DU Undergraduate Showcase: Research, Scholarship, and Creative Works
When Ai Moves Downstream, Frances S. Grodzinsky, Keith W. Miller, Marty J. Wolf
When Ai Moves Downstream, Frances S. Grodzinsky, Keith W. Miller, Marty J. Wolf
School of Computer Science & Engineering Faculty Publications
After computing professionals design, develop, and deploy software, what is their responsibility for subsequent uses of that software “downstream” by others? Furthermore, does it matter ethically if the software in question is considered to be artificial intelligent (AI)? The authors have previously developed a model to explore downstream accountability, called the Software Responsibility Attribution System (SRAS). In this paper, we explore three recent publications relevant to downstream accountability, and focus particularly on examples of AI software. Based on our understanding of the three papers, we suggest refinements of SRAS.
Leveraging Neutrosophic Uncertainty Theory Toward Choosing Biodegradable Dynamic Plastic Product In Various Arenas, Mona Mohamed, Karam M. Sallam
Leveraging Neutrosophic Uncertainty Theory Toward Choosing Biodegradable Dynamic Plastic Product In Various Arenas, Mona Mohamed, Karam M. Sallam
Neutrosophic Systems with Applications
Numerous studies in recent years have documented the negative effects of plastic waste on the environment and human wellness. Due to their widespread usage in daily life, particularly in packaging, and their rising direct or indirect discharge into the environment, plastics are recognized as an emerging environmental hazard. Thus, this point is considered the first problem in this study. As a result, efforts to replace traditional plastics with bioplastics have intensified. However, studies regarding the effects of conventional and bioplastics (BioPs) are also important. Hence, biodegradable polymers for industrial and commercial usage are essential in the present day as an …
Leveraging Neutrosophic Uncertainty Theory Toward Choosing Biodegradable Dynamic Plastic Product In Various Arenas, Mona Mohamed, Karam M. Sallam
Leveraging Neutrosophic Uncertainty Theory Toward Choosing Biodegradable Dynamic Plastic Product In Various Arenas, Mona Mohamed, Karam M. Sallam
Neutrosophic Systems with Applications
Numerous studies in recent years have documented the negative effects of plastic waste on the environment and human wellness. Due to their widespread usage in daily life, particularly in packaging, and their rising direct or indirect discharge into the environment, plastics are recognized as an emerging environmental hazard. Thus, this point is considered the first problem in this study. As a result, efforts to replace traditional plastics with bioplastics have intensified. However, studies regarding the effects of conventional and bioplastics (BioPs) are also important. Hence, biodegradable polymers for industrial and commercial usage are essential in the present day as an …
Blockchain Security: Double-Spending Attack And Prevention, William Henry Scott Iii
Blockchain Security: Double-Spending Attack And Prevention, William Henry Scott Iii
Electronic Theses and Dissertations
This thesis shows that distributed consensus systems based on proof of work are vulnerable to hashrate-based double-spending attacks due to abuse of majority rule. Through building a private fork of Litecoin and executing a double-spending attack this thesis examines the mechanics and principles behind the attack. This thesis also conducts a survey of preventative measures used to deter double-spending attacks, concluding that a decentralized peer-to-peer network using proof of work is best protected by the addition of an observer system whether internal or external.
Do Plants Have The Cognitive Complexity For Sentience?, Ricard V. Solé
Do Plants Have The Cognitive Complexity For Sentience?, Ricard V. Solé
Animal Sentience
Are plants sentient? Like other aspects of the cognitive potential of plants, this is a controversial issue, often driven by analogies and seldom supported on solid theoretical grounds. Sentience is understood in cognitive sciences as the capacity to feel. I suggest that because of plants’ evolved adaptations to morphological plasticity, sessile nature and ecological constraints, they are unlikely to have the requisite cognitive complexity for sentience.
What Senior U.S. Leaders Say We Should Know About Cyber, Dr. Joseph H. Schafer
What Senior U.S. Leaders Say We Should Know About Cyber, Dr. Joseph H. Schafer
Military Cyber Affairs
On April 6, 2023, the Atlantic Council’s Cyber Statecraft Initiative hosted a panel discussion on the new National Cybersecurity Strategy. The panel featured four senior officials from the Office of the National Cyber Director (ONCD), the Department of State (DoS), the Department of Justice (DoJ), and the Department of Homeland Security (DHS). The author attended and asked each official to identify the most important elements that policymakers and strategists must understand about cyber. This article highlights historical and recent struggles to express cyber policy, the responses from these officials, and the author’s ongoing research to improve national security cyber policy.
Effects Of Factors On The Market Price Of The Shares Using Design Of Experiment, Amir Ahmad Dar, Mohammad Shahfaraz Khan, Imran Azad, Tanveer Ahmad Tarray, N. Anuradha, Qaiser Farroq Dar
Effects Of Factors On The Market Price Of The Shares Using Design Of Experiment, Amir Ahmad Dar, Mohammad Shahfaraz Khan, Imran Azad, Tanveer Ahmad Tarray, N. Anuradha, Qaiser Farroq Dar
Applied Mathematics & Information Sciences
When the cost of capital, dividends and the price of the share at the beginning is known, Modigliani and Miller’s model can be used to estimate the price of the share at the end of the period. A design of experiment (Taguchi’s orthogonal array) is used in order to investigate the impact of three parameters on the price of the share at the end of the period. The main aim of this research article is to find which parameter is more significant on the price of the share at the end of the period. Taguchi’s methodology of design of the …
Reverse Engineering Post-Quantum Cryptography Schemes To Find Rowhammer Exploits, Sam Lefforge
Reverse Engineering Post-Quantum Cryptography Schemes To Find Rowhammer Exploits, Sam Lefforge
Computer Science and Computer Engineering Undergraduate Honors Theses
Post-quantum cryptography is a necessary countermeasure to protect against attacks from quantum computer. However, the post-quantum cryptography schemes are potentially vulnerable to side channel attacks. One such method of attacking involves creating bit-flips in victim memory through a process called Rowhammer. These attacks can vary in nature, but can involve rowhammering bits to raise the encryption scheme's decryption failure rate, or modifying the scheme's random seed. With a high enough decryption failure rate, it becomes feasible to generate sufficient information about the secret key to perform a key recovery attack. This thesis proposed two attacks on proposed post-quantum cryptography algorithms, …
Critical Infrastructure Workforce Development Pods For Teaching Cybersecurity Using Netlab+, Gideon Sutterfield
Critical Infrastructure Workforce Development Pods For Teaching Cybersecurity Using Netlab+, Gideon Sutterfield
Computer Science and Computer Engineering Undergraduate Honors Theses
As digital automation for Industrial Control Systems has grown, so has its vulnerability to cyberattacks. The world of industry has responded effectively to this, but the world of academia is still lagging as its emphasis is still almost entirely on information technology. Considering this, we created a workforce development pod that serves as a hands-on learning module for teaching students key cybersecurity ideas surrounding operational technology using the NETLAB+ platform. A pod serves as the virtual environment where the learning exercise takes place. This project’s implementation involved the creation of a segmented network within the pod where a student starts …
Physics-Based Human-In-The-Loop Machine Learning Combined With Genetic Algorithm Search For Multi-Criteria Optimization: Electrochemical Co2 Reduction Reaction, Naohiro Fujinuma, Samuel Lofland
Physics-Based Human-In-The-Loop Machine Learning Combined With Genetic Algorithm Search For Multi-Criteria Optimization: Electrochemical Co2 Reduction Reaction, Naohiro Fujinuma, Samuel Lofland
College of Science & Mathematics Departmental Research
Machine learning (ML) can be a powerful tool to expedite materials research, but the deployment for experimental research is often hindered by data scarcity and model uncertainty. An human-in-the-loop procedure to tailor the implementation of ML for multicriteria optimization is described. The effectiveness of this procedure in the development of a nafion-based membrane electrode assembly for electrochemical CO2 reduction reaction (CO2RR) into CO for two targets is demonstrated: energy efficiency (EE) and partial current density for CO2RR (). Model-agnostic nonlinear correlation analyses identify the 11 features relevant to those targets. The three studied decision tree-based ML models yield similar cross-validation …