Engineering Commons^™

Ct Image Segmentation Using Optimization Techniques Under Neutrosophic Domain, Doaa El-Shahat, Nourhan Talal, Jun Ye, Wen-Hua Cui

Neutrosophic Systems with Applications

In this paper, we introduce a hybrid technique between optimization algorithms and neutrosophic theory. This new hybridization can deal with uncertainties in brain computed tomography (CT) images in three different memberships very effectively. To prove the real-time application of this theory, a new segmentation method for brain CT medical images is presented. The grayscale medical image suffers from uncertainties and inconsistencies in the gray levels due to their bad luminance. The proposed technique addressed this problem by performing neutrosophic operations on gray levels based on the S membership function.

Editorial: Emerging On-Demand Passenger And Logistics Systems: Modelling, Optimization, And Data Analytics, Jintao Ke, Hai Wang, Neda Masoud, Maximilian Schiffer, Goncalo H. A. Correia

Research Collection School Of Computing and Information Systems

The proliferation of smart personal devices and mobile internet access has fueled numerous advancements in on-demand transportation services. These services are facilitated by online digital platforms and range from providing rides to delivering products. Their influence is transforming transportation systems and leaving a mark on changing individual mobility, activity patterns, and consumption behaviors. For instance, on-demand transportation companies such as Uber, Lyft, Grab, and DiDi have become increasingly vital for meeting urban transportation needs by connecting available drivers with passengers in real time. The recent surge in door-to-door food delivery (e.g., Uber Eats, DoorDash, Meituan); grocery delivery (e.g., Amazon Fresh, …

Development Of On-The-Fly Quasi-Steady State Approximation For Chemical Kinetics In Cfd, Abhinav Balamurugan

Doctoral Dissertations and Master's Theses

This study analyzes the feasibility of On-The-Fly Quasi-Steady-State Approximation (OTF-QSSA) application for solving chemical kinetics within Computational Fluid Dynamics (CFD) simulations, aiming to reduce the computational demand of detailed mechanisms. An algorithm that dynamically identifies and designates Quasi-Steady-State (QSS) species at specific grid locations and instances during the simulation was developed. With this information, our method pseudo-delays the advancement of concentrations for these QSS species—effectively setting their rate of concentration change to zero for a set number iteration before updating using the detailed mechanism and thereby omitting the computationally intensive processes typically required for their calculation during those skipped iteration. …

The Impact Of Government Data Open Platform Construction On Promoting The Development Of Digital Government: An Econometric Analysis Based On Psm Model, Taitian Mao, Tang Gan, Jinliang Chen

Journal of Scientific Information Research

[Purpose/significance]Open government data is the direction of the digital development of government, and exploring the impact of the Open Government Data Platform （OGDP） on the development of digital government is of guiding significance in advancing the goal of modernizing the national governance system and governance capacity. [Method/process]Based on the establishment or not of OGDP, this paper uses the propensity score matching method to investigate the causal relationship between OGDP construction and digital government development by using the cross-sectional data of 101 prefecture-level cities across China in 2019 as the research sample for empirical analysis. [Result/conclusion]Overcoming sample selection bias and eliminating …

Objective.Gg: Uniting Scholastic Esports, Douglas Beirne

Posters - 2024

Objective.gg is a startup recruitment platform within the scholastic esports scene that seeks to unite esports prospects with collegiate esports programs in an effective manner. Objective.gg seeks to accomplish its mission by operating an online platform that allows prospects and collegiate coaches to create their own profiles and connect with one another, building a community in the process. This platform will begin with a free tier, but additional features will be offered through a subscription-based model with two additional pricing tiers to choose from. The online platform will be supported by free online and paid in-person tournaments for Objective.gg platform …

Modeling, Characterization, And Machine Learning Algorithm For Rectangular Choke Horn Antennas, Ibrahim N. Alquaydheb, Saleh A. Alfawaz, Amirreza Ghadimi Avval, Sara Ghayouraneh, Samir M. El-Ghazaly

Electrical Engineering and Computer Science Faculty Publications and Presentations

In this work, we present the design and modeling of a new type of choke horn antenna. It incorporates a rectangular waveguide and a rectangular choke acting as a parasitic element. The four-sided geometry of the antenna is applicable to systems that utilize rectangular waveguides. Also, it can overcome the need for rectangular-to-circular transition of transmission line or mode conversion. The main objective of this paper is to develop a model that calculates the far field radiation characteristics of the proposed antenna (analytical part) and to incorporate a finite element method (FEM) solver that adds to the theoretical solution (empirical …

Performing Information Extraction For Mission Engineering Applications, Samuel R. Koski

Engineering Management & Systems Engineering Theses & Dissertations

The process of extracting structured data from unstructured and semi-structured text is manual, time consuming and error prone. Current natural language processing approaches for automating this process are difficult to verify for non-trivial and context-sensitive corpora. Large Language Models (LLMs) like ChatGPT have become a subject of considerable interest, opening a promising avenue of exploration. However, there is limited evidence on the performance of LLMs for information extraction.

In this dissertation, an approach is proposed to evaluate the accuracy of Stanford OpenIE and OpenAI's ChatGPT for this purpose. This includes comparing Resource Description Framework (RDF) triples extracted by each of …

A Trustworthy Self-Sovereign Data And Identity Management Framework, Efat Fathalla

Electrical & Computer Engineering Theses & Dissertations

Data is a fundamental building block in the digital world, providing a basis for decision making and growth across numerous applications. In our modern world, we have become accustomed to collecting data on everything, including devices, machines, and people. The increased value of such data has led to aggressive harvesting mechanisms that prioritize data collection, storage, and pervasiveness while often disregarding security, privacy concerns, and compliance with regulations and standards. Such a pervasive attitude towards data has resulted in a loss of control, prompting concerns among individuals and mobilizing the scientific community towards advocating for data self-sovereignty.

Self-Sovereign Identity (SSI) …

Computational Modeling And Analysis Of Facial Expressions And Gaze For Discovery Of Candidate Behavioral Biomarkers For Children And Young Adults With Autism Spectrum Disorder, Megan Anita Witherow

Electrical & Computer Engineering Theses & Dissertations

Facial expression production and perception in autism spectrum disorder (ASD) suggest the potential presence of behavioral biomarkers that may stratify individuals on the spectrum into prognostic or treatment subgroups. High-speed internet and the ease of technology have enabled remote, scalable, affordable, and timely access to medical care, such as measurements of ASDrelated behaviors in familiar environments to complement clinical observation. Machine and deep learning (DL)-based analysis of video tracking (VT) of expression production and eye tracking (ET) of expression perception may aid stratification biomarker discovery for children and young adults with ASD. However, there are open challenges in 1) facial …

Time Series Models For Predicting Application Gpu Utilization And Power Draw Based On Trace Data, Dorothy Xiaoshuang Parry

Electrical & Computer Engineering Theses & Dissertations

This work explores collecting performance metrics and leveraging various statistical and machine learning time series predictive models on a memory-intensive application, Inception v3. Trace data collected using nvidia-smi measured GPU utilization and power draw for two runs of Inception3. Experimental results from the statistical and machine learning-based time series predictive algorithms showed that the predictions from statistical-based models were unable to capture the complex changes in the trace data. The Probabilistic TNN model provided the best results for the power draw trace, according to the test evaluation metrics. For the GPU utilization trace, the RNN models produced the most accurate …

Convolutional Spiking Neural Networks For Intent Detection Based On Anticipatory Brain Potentials Using Electroencephalogram, Nathan Lutes, V. Sriram Siddhardh Nadendla, K. Krishnamurthy

Computer Science Faculty Research & Creative Works

Spiking neural networks (SNNs) are receiving increased attention because they mimic synaptic connections in biological systems and produce spike trains, which can be approximated by binary values for computational efficiency. Recently, the addition of convolutional layers to combine the feature extraction power of convolutional networks with the computational efficiency of SNNs has been introduced. This paper studies the feasibility of using a convolutional spiking neural network (CSNN) to detect anticipatory slow cortical potentials (SCPs) related to braking intention in human participants using an electroencephalogram (EEG). Data was collected during an experiment wherein participants operated a remote-controlled vehicle on a testbed …

A Gateway To Next-Generation Patient Monitoring System, Kishore Kumar Kadari

USF Tampa Graduate Theses and Dissertations

Healthcare patient monitoring is undergoing a significant digital transformation, and the integration of Cyber-Physical Systems (CPS) and Artificial Intelligence (AI) is becoming increasingly crucial in reshaping patient care. In an era where digital technology is revolutionizing medical practices, this research aims to take a leading role in advancing a fundamental aspect of predictive and sustainable healthcare practices, enhancing patient outcomes and uplifting the practice of medicine.

This research focuses on the study of Digital Twins for precision health, which are designed to monitor and provide intricate, personalized feedback dynamically during a patient's healthcare experience. The architecture of the system is …

Dyvir: Virtual Reality Generated Synthetic Training Datasets For Ai, Garrett Williams

Graduate Student and Postdoctoral Fellow Symposium

Artificial Intelligence (AI) can perform complex tasks quickly such as object detection. To perform these tasks, the AI algorithms are first trained on data. However, some data such as labeled imagery of aerial objects is hard to obtain. Utilizing Virtual Reality (VR) software, a custom tool called DyViR was made to generate synthetic training datasets. Users customize the virtual environment, aerial objects, and sensor modality to produce custom-tailored datasets.

Lrs: Enhancing Adversarial Transferability Through Lipschitz Regularized Surrogate, Tao Wu, Tony Tie Luo, Donald C. Wunsch

Computer Science Faculty Research & Creative Works

The Transferability of Adversarial Examples is of Central Importance to Transfer-Based Black-Box Adversarial Attacks. Previous Works for Generating Transferable Adversarial Examples Focus on Attacking Given Pretrained Surrogate Models While the Connections between Surrogate Models and Adversarial Trasferability Have Been overlooked. in This Paper, We Propose Lipschitz Regularized Surrogate (LRS) for Transfer-Based Black-Box Attacks, a Novel Approach that Transforms Surrogate Models towards Favorable Adversarial Transferability. using Such Transformed Surrogate Models, Any Existing Transfer-Based Black-Box Attack Can Run Without Any Change, Yet Achieving Much Better Performance. Specifically, We Impose Lipschitz Regularization on the Loss Landscape of Surrogate Models to Enable a Smoother …

Cr-Sam: Curvature Regularized Sharpness-Aware Minimization, Tao Wu, Tony Tie Luo, Donald C. Wunsch

Computer Science Faculty Research & Creative Works

The Capacity to Generalize to Future Unseen Data Stands as One of the Utmost Crucial Attributes of Deep Neural Networks. Sharpness-Aware Minimization (SAM) Aims to Enhance the Generalizability by Minimizing Worst-Case Loss using One-Step Gradient Ascent as an Approximation. However, as Training Progresses, the Non-Linearity of the Loss Landscape Increases, Rendering One-Step Gradient Ascent Less Effective. on the Other Hand, Multi-Step Gradient Ascent Will Incur Higher Training Cost. in This Paper, We Introduce a Normalized Hessian Trace to Accurately Measure the Curvature of Loss Landscape on Both Training and Test Sets. in Particular, to Counter Excessive Non-Linearity of Loss Landscape, …

Development Demand, Power Energy Consumption And Green And Low-Carbon Transition For Computing Power In China, Xiaohong Chen, Liaoying Cao, Jiaolong Chen, Jinghui Zhang, Wenzhi Cao, Yangjie Wang

Bulletin of Chinese Academy of Sciences (Chinese Version)

As a critical digital infrastructure, computing power has become the core productivity and a new engine driving economic growth in the digital economy. Nevertheless, the power-hungry nature of computing/data centers, representing the computing infrastructure, consumes a significant amount of electrical energy. Currently, China’s economy is transitioning from high-speed growth to high-quality development. It is imperative to study how to coordinate the development of computing power while ensuring its safety and achieving green and low-carbon goals. Based on an overview of the current status of computing power development, this study predicts the future demand for computing power in China, analyzes the …

Uav Swarm Obstacle Avoidance Algorithm Based On Visual Field And Velocity Guidance, Xueqi Gui, Chuntao Li

Journal of System Simulation

Abstract: In the future aerial combat of multiple unmanned aerial vehicles (UAVs), the safe flight of UAV swarm in unknown airspace is an important content of swarm research. In view of avoiding obstacles and maintaining behavior in the UAV swarm system, this paper presents a UAV swarm collision avoidance algorithm based on visual field and velocity guidance (VFVG). The swarm adaptive communication topology mechanism is designed based on the visual field method. Combined with the principle of far attraction and near repulsion and the consensus method, the mechanism can accelerate the transmission of obstacle avoidance information among UAV swarms while …

Dynamic Digital Twin Modelling And Semi-Physical Simulation Of Wind Turbine Operation, Yang Hu, Weiran Wang, Fang Fang, Ziqiu Song, Yuhan Xu, Jizhen Liu

Journal of System Simulation

Abstract: For the accurate mapping and real-time simulation requirements proposed by digital twin technology, a multi-input multi-output (MIMO) finite difference domain-hybrid semi-mechanical (FDDHSM) digital twin modeling method is proposed, and a semi-physical simulation system of wind turbine digital twin with physical controller is established for the complex nonlinear operation characteristics of large wind turbines. The integrated dynamic MIMO-FDD-HSM model structure is constructed. Finite difference regression vectors are defined to characterize the operating conditions of the wind turbine, and finite difference space tight convex partitioning, parametric model identification, and non-parametric model training are completed under full operating conditions. The wind turbine …

A Distributed Simulation System For Space Operation Missions, Yunzhao Liu, Mingming Wang, Jintao Li, Chuankai Liu, Jianjun Luo

Journal of System Simulation

Abstract: For the ground verification requirements of complex space operation missions such as noncooperative target capture, on-orbit maintenance, and in-space assembly, a distributed simulation system is developed, which mainly consists of a back-end simulation model, a front-end visual demonstration system, and a front-end main controller. In order to realize the multidisciplinary model coupling and interaction among different modeling tools or programming languages, the functional mock-up interface (FMI) standard is introduced for system integration, improving the modularity, generality, and portability of the system. To fully utilize computing resources and improve the simulation efficiency, simulation subsystems and modules are deployed in a …

Modeling And Optimization Of Smart Warehouse Order Sorting Considering Splitting Strategy, Yuze Xu, Linxuan Zhang, Hui Li, Ming Ge, Wanyi He

Journal of System Simulation

Abstract: For an automatic vehicle sorting problem involving mixed sorting of two types of orders, an order splitting strategy and a method for batch adjustment of sub-orders after splitting are proposed by considering the phenomena of blockage of automatic guided vehicles (AGVs) and idleness of manual collection stations in the order sorting process. In addition, with the optimization objective of minimizing the total order completion time, an order sorting integer planning model with order splitting is established. An improved discrete grey wolf optimization algorithm is proposed to jointly optimize the three sub-problems of order batching, batch sorting, and product unloading …

Construction Of Machine Learning Data Set For Analyzing The Replay Of The Wargaming, Dayong Zhang, Jingyu Yang, Jun Ma, Chenye Song

Journal of System Simulation

Abstract: The first problem to be solved in the application of machine learning to the analysis of the replay of the wargaming is the construction of data sets. Due to the standardization requirements of machine learning for data structure, as well as the limitations of computing power and storage, building a machine learning data set through the wargaming data still faces many problems in terms of how to describe the wargaming situation, how to describe the wargaming process, how to handle high dimensional data, and how to prevent data distortion. To solve these problems, this paper constructs a mapping model …

Gesture Recognition For Dynamic Vision Sensor Based On Multi-Dimensional Projection Spatiotemporal Event Frame, Lai Kang, Yakun Zhang

Journal of System Simulation

Abstract: Vision-based gesture recognition is a commonly used means of human-computer interaction in the fields of virtual reality and game simulation. In practical applications, rapid changes in gesture movements will lead to blurred imaging with traditional RGB cameras or depth cameras, which brings great challenges to gesture recognition. To solve the above problems, a dynamic visual data gesture recognition method based on a multi-dimensional projection spatiotemporal event frame (STEF) is proposed by a using dynamic vision sensor to capture high-speed gesture movement information. The spatiotemporal information is embedded in the data projection surface and fused to form a multidimensional projection …

Multi-Agent Path Planning With Obstacle Penalty Factor, Xingyu Yan, Dayan Li, Niya Wang, Kaixiang Zhang, Jianlin Mao

Journal of System Simulation

Abstract: In light load environments, complex obstacle areas will exacerbate local conflicts between agents, leading to a decrease in path solving efficiency. This paper proposes a multi-agent path planning (MAPF) method with obstacle penalty factors in light load environments. First, in the low-level single machine planning process based on the conflict-based search (CBS) algorithm framework, by judging the distribution type of surrounding obstacles that are about to expand the agent's position, corresponding obstacle penalty factors are assigned to them; then, the penalty factors in the path planning process are accumulated and used as the heuristic value of single machine planning …

Research On Optimization Design Method Of Waverider Forebody/Bump Profile Of Aircraft, Jialin Qiu, Jun Huang, Peng Shu, Qingfeng Wang, Zhiqin Liu, Wenyou Qiao

Journal of System Simulation

Abstract: The waverider forebody and Bump profile of aircraft are two classic cases reflecting the waverider idea in aircraft component design. They can effectively improve the overall aerodynamic performance of aircraft and have become the core technology of aircraft overall design. In order to seek the optimal design of the waverider forebody and Bump profile to improve the efficiency of aircraft design, an optimization design method for the waverider forebody and Bump profile is proposed in this paper. The initial waverider forebody and Bump profile are generated by the osculating cone theory and conical flow field, and the aerodynamic performance …

Research On Hybrid Solution Algorithm For Layout Problem Of Rectangular Parts With Multiple Constraints, Ye Liu, Weixi Ji, Xuan Su, Hongxuan Zhao

Journal of System Simulation

Abstract: A hybrid algorithm based on a cutting and matching algorithm and an improved ant colony algorithm was proposed to solve the layout problem of rectangular parts in the process of wood and glass blanking. A layout optimization model was established to maximize the mean square utilization and the remaining processing time; the ant colony algorithm was used as the layout sequence algorithm to determine the layout sequence of some parts and meet the processing time constraint. In order to improve the search efficiency of the ant colony algorithm, an adaptive pheromone updating strategy was proposed, and a hybrid mutation …

Human Action Recognition Based On Skeleton Edge Information Under Projection Subspace, Benyue Su, Peng Zhang, Bangguo Zhu, Mengjuan Guo, Min Sheng

Journal of System Simulation

Abstract: In recent years, human action recognition based on skeleton data has received a lot of attention in the fields of computer vision and human-computer interaction. Most of the existing methods focus on modeling the skeleton points in the original 3D coordinate space. However, skeleton points ignore the physical chain structure of the human body itself, which makes it difficult to portray the local correlation of human motion. In addition, due to the diversity of camera views, it is difficult to explore the comprehensive representation of actions in different views under the original point-based 3D space. In view of this, …

Joint Distribution-Inventory Optimization And Simulation For Cold Chain Logistics Considering Order Substitution, Yuanpeng Wan, Chengji Liang, Sihong Wang, Yu Wang

Journal of System Simulation

Abstract: The most important purpose of cold chain logistics is to ensure product freshness, and how to reduce the cost of order distribution on this basis is an urgent problem for cold chain companies. For consumers, product quality and food safety are their main needs. Therefore, by taking the distribution center as the research object, the products were divided into different grades according to the initial freshness of the products before distribution, and the overall freshness of the products was improved by adopting the grade upward substitution mode for orders that do not meet the delivery requirements so that customers …

Three-Dimensional Path Planning Of Uav Based On All Particles Driving Wild Horse Optimizer Algorithm, Gaoyang Li, Xiangfeng Li, Kang Zhao, Yuchao Jin, Zhidong Yi, Dunwen Zuo

Journal of System Simulation

Abstract: In view of large calculation amounts and difficult convergence in the unmanned aerial vehicle (UAV) path planning, a path planning method based on all particles driving wild horse optimizier (APDWHO) was proposed. A three-dimensional environment model and path cost model were established, by which the path planning problem was transformed into a multi-dimensional function optimization problem. An adaptive neighborhood search strategy (ANSS) was adopted to improve the exploitation ability of the algorithm. The Gaussian random walk strategy was used to search the historical optimal position of the individual to improve the exploration ability of the algorithm. Since the ANSS …

3d Streamline Visualization Method Based On Clustering Fusion, Xuqiang Shao, Ya Cheng, Yizhong Jin

Journal of System Simulation

Abstract: In order to solve the problems of incomplete feature extraction, continuity destruction of flow field by visual results, and poor representation of streamline caused by unstable clustering division when the clustering method is used to realize 3D streamline visualization. A 3D streamline visualization method based on clustering fusion is proposed. It consists of a distance measurement method between features and a clustering fusion method, which takes the inter-feature distance and spatial distance as the similarity between streamlines for clustering and then performs weighted merging and subdivision of the obtained clustering result. The method has been tested on data sets …

Planning Modeling And Optimization Algorithm For 5g Indoor Distribution System, Shaoda Zeng, Hailin Liu

Journal of System Simulation

Abstract: Most of the new services in 5G mobile communication technologies, including smart homes, smart factories, and virtual reality, take place in indoor scenes. Therefore, how to quickly plan and build a 5G indoor distribution system with low construction cost and low power loss is of great significance for telecom operators. This paper establishes a mathematical planning model of a 5G indoor distribution system, which is closer to the actual scenario. The model aims to minimize the deployment cost and the maximum output signal power deviation between antennas, and the constraint is to meet the expected output signal power of …