Computer Sciences Commons^™

Algoraph But In C++, Adam James Czeranko, Andres Louis Solorzano

21st Annual Celebration of Undergraduate Research and Creative Activity (2022)

Given a configuration of “pebbles” on a graph G, a pebbling move removes two pebbles from a source vertex and one pebble is added to an adjacent vertex. A vertex is reachable if there is a sequence of pebbling moves that places one pebble on that vertex; a graph is solvable if every vertex is reachable. The pebbling number of graph G is the smallest integer π(G), such that any configuration that uses π(G) pebbles is solvable. A graph satisfies the two-pebbling property if for any configuration of more than 2π(G) - q pebbles, where q is the number of …

Machine Learning Applications Using Scikit-Learn And Tensorflow, Trevor Palmatier, Kenneth Munyuza

21st Annual Celebration of Undergraduate Research and Creative Activity (2022)

Machine learning (ML) is a powerful tool with vast applications in pattern-recognition and identification tasks. Our goal was to explore different applications of machine learning and develop a working understanding of the processes required for the effective application of ML models to problem-solving. Using SciKit-Learn for traditional ML models and TensorFlow for neural networks, existing techniques were explored for two major categories of ML tasks: Regression and Classification modeling. This knowledge was then applied in a biomedical engineering pilot research study (in collaboration with Dr. Brooke Odle, Engineering) analyzing manual patient-handling tasks using data from inertial measuring units (IMUs) and …

Data-Driven Design And Analysis Of Next Generation Mobile Networks For Anomaly Detection And Signal Classification With Fast, Robust And Light Machine Learning, Muhammed Furkan Küçük

USF Tampa Graduate Theses and Dissertations

This research focuses on machine (and deep) learning applications (including clustering,anomaly detection and signal classification) for self-organizing and next generation mobile networks in wireless communications. Specifically, this dissertation document will address the three different topics.

First, in the study titled “Performance analysis of neural network topologies and hyperparameters for deep clustering”, we explore the relationship between the clustering performance and network complexity. Deep learning found its initial footing in supervised applications such as image and voice recognition successes of which were followed by deep generative models across similar domains. In recent years, researchers have proposed creative learning representations to utilize …

Three-Heartbeat Multilead Ecg Recognition Method For Arrhythmia Classification, Liang-Hung Wang, Yan-Ting Yu, Wei Liu, Lu Xu, Chao-Xin Xie, Tao Yang, I-Chun Kuo, Xin-Kang Wang, Jie Gao, Patricia Angela R. Abu

Department of Information Systems & Computer Science Faculty Publications

Electrocardiogram (ECG) is the primary basis for the diagnosis of cardiovascular diseases. However, the amount of ECG data of patients makes manual interpretation time-consuming and onerous. Therefore, the intelligent ECG recognition technology is an important means to decrease the shortage of medical resources. This study proposes a novel classification method for arrhythmia that uses for the very first time a three-heartbeat multi-lead (THML) ECG data in which each fragment contains three complete heartbeat processes of multiple ECG leads. The THML ECG data pre-processing method is formulated which makes use of the MIT-BIH arrhythmia database as training samples. Four arrhythmia classification …

Performance Comparison Of The Filesystem And Embedded Key-Value Databases, Jesse Hines, Nicholas Cunningham

Campus Research Month

A common scenario when developing local applications is storing many records and then retrieving them by ID. A developer can simply save the records as files or use an embedded database. Large numbers of files can slow down filesystems, but developers may want to avoid a dependency on an embedded database if it offers little benefit for their use case. We will compare the performance for the insert, update, get and delete operations and the space efficiency of storing records as files vs. using key-value embedded databases including RocksDB, LevelDB, Berkley DB, and SQLite.

*Interactive Earthquake Visualization With Open Data, Matous Hybl

Campus Research Month

Because earthquakes claim thousands of lives and billions of dollars yearly, there is a great need to recognize patterns in seismic data. While some tools for analysis exist, most geological software is expensive and open earthquake visualizations are limited. In this project, we provide accessible earthquake visualizations aimed to encourage geologists, and science enthusiasts in general, to explore open data using accessible, yet powerful, tools.

Chattanooga Crime Over Time: An Analysis Of Police Incident Open Data, Logan Bateman

Campus Research Month

The police and citizens of Chattanooga may want to know where the most crime occurs, what time of day is crime or police incidents most likely to occur over time. This information can help them understand the crime hotspots in the area. This research work presents a dashboard built upon open data in attempt to bring understanding and insights to the police and citizens about police incidents from the city of Chattanooga over the past five years.

Database Query Execution Through Virtual Reality, Logan Bateman, Marc Butler

Campus Research Month

Building database queries often requires technical knowledge of a query language. However, company employees, such as executives, managers, and others (outside of software research and development, generally) may not have the pre-required knowledge to accurately construct and execute database queries. This paper proposes an approach to constructing database queries using virtual reality. This approach utilizes natural hand or controller gestures which map to various components of building and visualizing database queries.

Realtime Visualization Of Kafka Architectures, Matthew Jensen, Miro Manestar

Campus Research Month

Apache Kafka specializes in the transfer of incredibly large amounts of data in real-time between devices. However, it can be difficult to comprehend the inner workings of Kafka. Often, to get real-time data, a user must run complicated commands from within the Kafka CLI. Our contribution is a tool that monitors Kafka consumers, producers, and topics, and displays the flow of events between them in a web-based dashboard. This dashboard serves to reduce the complexity of Kafka and enables users unfamiliar with the platform and protocol to better understand how their architecture is configured.

Einstein-Roscoe Regression For The Slag Viscosity Prediction Problem In Steelmaking, Hiroto Saigo, Dukka Kc, Noritaka Saito

Michigan Tech Publications, Part 1

In classical machine learning, regressors are trained without attempting to gain insight into the mechanism connecting inputs and outputs. Natural sciences, however, are interested in finding a robust interpretable function for the target phenomenon, that can return predictions even outside of the training domains. This paper focuses on viscosity prediction problem in steelmaking, and proposes Einstein-Roscoe regression (ERR), which learns the coefficients of the Einstein-Roscoe equation, and is able to extrapolate to unseen domains. Besides, it is often the case in the natural sciences that some measurements are unavailable or expensive than the others due to physical constraints. To this …

Statistical Study Into The World Of Nft Investing And The Process Behind It, Daon Morris, Teddy Gamboa, Akeisha Belgrave

Harrisburg University Research Symposium: Highlighting Research, Innovation, & Creativity

For the purpose of this project, we gathered data from the young adults and adults of the Harrisburg University campus in support of the fact that NFT’s are not like other forms of investments in terms of the strategy used. Rather, the way people invest in them is by just simply looking at the picture, and whatever NFT people think looks cool is the NFT that will skyrocket in value.(Class Project)

Study On Near-Body Pressure Characteristics Of Bionic Robotic Fish Undulating In Near Wall Region, Ou Xie, Aiguo Song, Qixin Zhu

Journal of System Simulation

Abstract: To avoid unbalanced workload assignment, we studied the vehicle routing problem with refined oil secondary distribution considering workload balance. A bi-objectivemixed integer programming model was built to minimize the total distribution cost and the maximum difference in vehicle route length. A heuristic variable neighborhood tabu search algorithm was designed. An improved Solomon_I1 insertion algorithm was developed to generate afeasible initial solution such that the total distribution cost was as small as possible. Then, the variable neighborhood tabu search algorithm was used to improve the initial solution and thereby obtain the approximate optimal solution. The simulation results show that in …

Volume 13, Payton Davenport, Audrey Lemons, Jacob Shope, Haley Smith, Cassandra Poole, Rachel Cannon, Rachel Boch, Suzanne Stetson

Incite: The Journal of Undergraduate Scholarship

Introduction Dr. Roger A. Byrne, Dean

From the Editor Dr. Larissa “Kat” Tracy

From the Designers Rachel English, Rachel Hanson

The Effect of Compliment Type on the Estimated Value of the Compliment by Payton Davenport, Audrey Lemons, and Jacob Shope

The Imperial Japanese Military: A New Identity in the Twentieth Century, 1853–1922 by Haley Smith

Longwood University’s campus: Human-cultivated Soil has Higher Microbial Diversity than Soil Collected from Wild Sites by Cassandra Poole

Reminiscent Modernism: Poetry Magazine’s Modernist Nostalgia for the Past by Rachel Cannon

Challenges Faced by Healthcare Workers During the COVID-19 Pandemic: A Preliminary Study of Age and …

Multi-Modality Affective Computing Model Based On Personality And Memory Mechanism, Sijin Zhou, Dicheng Chen, Geng Tu, Dazhi Jiang

Journal of System Simulation

Abstract: With the development of affective computing, the correlation of memory, individuation and emotion is more and more important. Focus on the machine emotion shortcomings in the perception, understanding and expression, an emotion computing model integrating the emotion perception, understanding and expression is proposed. The model is a memory-oriented deep network perception model that accepts multiple modal inputs (visual, auditory, lexical) and applies a fuzzy emotion integration decision to realize the understanding of uncertain emotions. The simulation experiments prove that the model has a good performance in all kinds of multimodal affective computing.

Virtual Scene Stereoscopic Panorama Generation And Viewport Rendering Algorithm, Haoxiang Li, Chunyi Chen, Xiaojuan Hu, Yunbiao Liu, Qiwei Xing

Journal of System Simulation

Abstract: Aiming at the nonuniform sampling in map projection and the redundancy in aspheric projection, spherical Fibonacci lattices is used to sample the visible spherical area to generate spherical Fibonacci lattice panorama with low-redundancy and high-quality. On the basis of panoramic stereo imaging model, the binocular ray direction generation algorithm for spherical stereo panorama is proposed. With Fibonacci grid, an adaptive filtering method of light-visibility map for panorama is designed to generate spherical panorama with approximate soft shadow. The nearest neighbor interpolation is used to render the viewport of panorama. Extensive experiments show that the frame frequency of the viewport …

Simulation On Cold Chain Distribution Path Of Fresh Agricultural Products Under Low-Carbon Constraints, Tao Ning, Tao Gou, Xiangdong Liu

Journal of System Simulation

Abstract: The freshness distribution requirements of fresh agricultural products may increase the carbon emissions of the cold chain distribution process. A cold chain distribution scheduling strategy and simulation method for the fresh agricultural products under low-carbon constraints is proposed. Based on the quantitative analysis of the carbon tax mechanism, a mathematical model of minimizing the carbon emissions and minimizing the overall cost of distribution is established. Comprehensively analyzing the conventional factors such as the product delivery volume, delivery time and loading and unloading time in logistics distribution, an improved quantum ant colony algorithm based on adaptive rotation angle …

Simulation Optimization On Joint Production And Preventive Maintenance Scheduling For Distributed Job-Shop, Fei Ye, Ziqing Li, Yuanjun Laili

Journal of System Simulation

Abstract: Distributed job-shop production scheduling is the key to high efficient production. Preventive maintenance, an essential means to ensure the safety and reliability of equipment, should be the necessary content of the production decision-making. Aiming at the production delay caused by equipment maintenance, a simulation-corrected optimization method is proposed. The mathematical model and simulation model for the joint production and preventive maintenance scheduling are established. The sequence exchange-based genetic algorithm is combined with the simulation-corrected optimization method to form a fast simulation optimization scheme. Experimental results on typical cases show that the proposed simulation optimization method can improve the solution …

Research On Discrete Workshop Task Assignment Based On Improved Water Filling Algorithm, Kaituan Feng, Jie Yuan

Journal of System Simulation

Abstract: Aiming at the unsatisfactory the results of the real-time dynamic task allocation in discrete workshops are not ideal, an improved water filling algorithm is proposed. Compared with the equal cost allocation of the water injection algorithm, the processing rate and cost factors are added to the improved water injection algorithm to coordinate the processing rate, the cost and the workpieces. The allocation of the different cost workpieces is realized and the result is adjusted, which can meet the requirements of discrete distribution. The improved water injection algorithm can dynamically allocate the newly added workpieces in real time. The proposed …

Key Technology Research On Stall Spin Simulation Training System Of An Aircraft, Guangxu Xi, Yongyi Liu, Chong Wu, Junjie Zhang, Yinghao Chen

Journal of System Simulation

Abstract: In order to realize the simulation continuity of the multi-state evolution of traffic and to solve the problem that multi-state traffic can only be simulated by single state traffic through multiple times, the middleware model of continuous traffic event simulation is built by the secondary development interface of VISSIM simulation software, and the original two related traffic simulation events are jointly driven. The secondary development of VISSIM-com is carried out by C# and database. The survey data of the intersection of Ganghua Road and Baihua Road in the Yuzhong District of Chongqing is selected as the example, and the …

Simulation On Mutual Interference Of Laser Radar In Road Environments, Xuesong Mao, Runlong Lei, Shaowei Huang, Xuetao Mao

Journal of System Simulation

Abstract: Transmission line inspection is an important work to ensure the safe operation of the power grid. It involves the live-work, the power-outage-maintenance and the fault-diagnosis. Training using only 3D virtual technology cannot achieve realistic results. It is necessary to combine 3D virtual scenes with digital grids. To this end, using the collected monitoring data and multi-time-scale calculation models, a twin state digital power grid has been constructed for the live-work, a parallel state digital power grid has been constructed for the power-outage-maintenance, and corresponding analog devices have been added to the parallel digital power grid to complete the training …

Learning Enriched Features For Fast Image Restoration And Enhancement, Syed Waqas Zamir, Aditya Arora, Salman Khan, Munawar Hayat, Fahad Shahbaz Khan, Ming-Hsuan Yang, Ling Shao

Computer Vision Faculty Publications

Given a degraded input image, image restoration aims to recover the missing high-quality image content. Numerous applications demand effective image restoration, e.g., computational photography, surveillance, autonomous vehicles, and remote sensing. Significant advances in image restoration have been made in recent years, dominated by convolutional neural networks (CNNs). The widely-used CNN-based methods typically operate either on full-resolution or on progressively low-resolution representations. In the former case, spatial details are preserved but the contextual information cannot be precisely encoded. In the latter case, generated outputs are semantically reliable but spatially less accurate. This paper presents a new architecture with a holistic goal …

Cross-Temporal Snapshot Alignment For Dynamic Multi-Relational Networks, Lvjia Chen, Shangsong Liang

Machine Learning Faculty Publications

A dynamic network is often represented as a sequence of snapshots evolving over time. In certain real-world scenarios, the identities of nodes in snapshots of a dynamic network are unknown and need to be figured out. To deal with such a challenge, recently, the task of cross-temporal snapshot alignment for dynamic networks is proposed, which aims to match equivalent nodes across temporal snapshots of a dynamic network given a small set of identified nodes. However, in many dynamic multi-relational networks like temporal knowledge graphs, the relation type information of edges, which can be useful for the alignment task, is neglected …

Research On Credibility Assessment Of Cloud Simulation System, Wei Li, Huan Zhang, Ping Ma, Ming Yang

Journal of System Simulation

Abstract: The cloud simulation platform supports the "cloud simulation" mode, which can automatically find simulation resources and dynamically build the cloud simulation system. Because the cloud simulation platform has the characteristics of simulation services establishment on demand and multi-granularity resources sharing, the credibility evaluation of the cloud simulation system faces new challenges in the credibility of the simulation resources, the credibility of the simulation subsystems and the reliability of the simulation environment, etc. From the whole life cycle perspective of the cloud simulation system, the credibility evaluation process model and the credibility evaluation index system of the cloud simulation system …

Research On Physical Layer Security Of Full-Duplex Uav Relaying, Shu Ye, Xiaodong Ji, Wenhua Li

Journal of System Simulation

Abstract: Aiming at the physical layer security of a full-duplex UAV relaying system, a novel scheme based on the joint optimization of the transmit power and UAV flight trajectory is proposed. Under the condition of limited transmit power and flight trajectory, a joint optimization that maximizing the average secrecy rate of the system is constructed. The non-concave problem that cannot be solved directly is resolved into two sub-problems of transmit power and flight trajectory optimization, which can be transformed into the concave problem by the successive convex approximation method. An iterative algorithm is proposed to obtain the numerical solution of …

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

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

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 …

An Unmanned Swarm Search Method Based On Human-Robot Cooperation, Xin Zhou, Weiping Wang, Yifan Zhu, Tao Wang, Tian Jing

Journal of System Simulation

Abstract: Human-robot collaboration is a research hotspot and the human and unmanned swarm collaborative search is a typical scenario. It can carry out the more complex tasks by combining the human complex reasoning capabilities with repeated and precise execution capabilities of unmanned swarm. Based on the high-value target search of the uncertain scenarios, the concept definition for the collaborative search of human and unmanned swarm is given. A multi-agent dynamic programming model under uncertain with unknown prior knowledge is proposed, established to describe how the multi-agent system carries out the search under human support. A dynamic programming algorithm …

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

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 …