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Articles 2011 - 2040 of 3476
Full-Text Articles in Computer Sciences
Using Information Theory To Extract Patterns From Categorical Raster Data, David Percy
Using Information Theory To Extract Patterns From Categorical Raster Data, David Percy
Complex Systems Faculty Publications and Presentations
Information theory -- Reconstructability Analysis (RA) implemented in the Occam software -- was used to extract patterns from National Land Cover Data. The aim was to predict temporal change in evergreen forests from time-lagged and spatially adjacent states. The NLCD satellite data were preprocessed with Python and submitted to Occam for analysis, and Occam output was also explored with R-studio. The effectiveness of RA methodology for the analysis of this type of categorical space-time grid data was demonstrated.
Building A Data Washing Machine For Unsupervised Entity Resolution Of Unstandardized References Sources, Awaad K. Al Sarkhi
Building A Data Washing Machine For Unsupervised Entity Resolution Of Unstandardized References Sources, Awaad K. Al Sarkhi
Theses and Dissertations
This dissertation describes a first attempt to build a data washing machine, a system able to take dirty data and through an unsupervised process, output clean data. The washing machine design described here focuses on two main aspects of the data curation process, token correction and data redundancy. It aims to simplify and automate the preparation of data used to create information products. In this approach, all these steps would be automated, thus saving the time and effort of the data analysts who ordinarily perform these actions. In other words, this is the opposite of the current approach to first …
Mlatticeabc: Generic Lattice Constant Prediction Of Crystal Materials Using Machine Learning, Yuxin Li, Wenhui Yang, Rongzhi Dong, Jianjun Hu
Mlatticeabc: Generic Lattice Constant Prediction Of Crystal Materials Using Machine Learning, Yuxin Li, Wenhui Yang, Rongzhi Dong, Jianjun Hu
Faculty Publications
Lattice constants such as unit cell edge lengths and plane angles are important parameters of the periodic structures of crystal materials. Predicting crystal lattice constants has wide applications in crystal structure prediction and materials property prediction. Previous work has used machine learning models such as neural networks and support vector machines combined with composition features for lattice constant prediction and has achieved a maximum performance for cubic structures with an average coefficient of determination (R2) of 0.82. Other models tailored for special materials family of a fixed form such as ABX3 perovskites can achieve much higher performance due …
Exploring Ai And Multiplayer In Java, Ronni Kurtzhals
Exploring Ai And Multiplayer In Java, Ronni Kurtzhals
Student Academic Conference
I conducted research into three topics: artificial intelligence, package deployment, and multiplayer servers in Java. This research came together to form my project presentation on the implementation of these topics, which I felt accurately demonstrated the various things I have learned from my courses at Moorhead State University. Several resources were consulted throughout the project, including the work of W3Schools and StackOverflow as well as relevant assignments and textbooks from previous classes. I found this project relevant to computer science and information systems for several reasons, such as the AI component and use of SQL data tables; but it was …
Student Academic Conference, Caitlin Brooks
Student Academic Conference, Caitlin Brooks
Student Academic Conference
No abstract provided.
Poker Chip Calculator Application, Ryan Illies
Poker Chip Calculator Application, Ryan Illies
Student Academic Conference
Application to help start up in person poker games with friends.
Edmms Temperature Controller, Anthony Kirkland
Edmms Temperature Controller, Anthony Kirkland
Honors Theses
Temperature control systems in consumer appliances like that of a thermostat interfacing with HVAC systems, refrigerators and ovens are oscillatory in nature. There is a temperature at which the machine that causes the change in the system comes on and a different temperature at which it comes off. While sufficient for humans, welding, metal casting, and other metallurgical processes require precise temperature control, more precise than the hysteresis of a consumer system.
Proportional integral derivative (PID) provides a better way of monitoring the way temperature changes when the entity that changes the environment comes on and renders changes in system …
Viability Of Consumer Grade Hardware For Learning Computer Forensics Principles, Lazaro A. Herrera
Viability Of Consumer Grade Hardware For Learning Computer Forensics Principles, Lazaro A. Herrera
Journal of Digital Forensics, Security and Law
We propose utilizing budget consumer hardware and software to teach computer forensics principles and for non-case work, research and developing new techniques. Consumer grade hardware and free / open source software is more easily accessible in most developing markets and can be used as a first purchase for education, technique development and even when developing new techniques. These techniques should allow for small forensics laboratories or classroom settings to have the tooling and framework for trying existing forensics techniques or creating new forensics techniques on consumer grade hardware. We'll be testing how viable each individual piece of hardware is as …
Exploring Complementary Strengths Of Invariant And Equivariant Representations For Few-Shot Learning, Mamshad Nayeem Rizve, Salman Khan, Fahad Shahbaz Khan, Mubarak Shah
Exploring Complementary Strengths Of Invariant And Equivariant Representations For Few-Shot Learning, Mamshad Nayeem Rizve, Salman Khan, Fahad Shahbaz Khan, Mubarak Shah
Computer Vision Faculty Publications
In many real-world problems, collecting a large number of labeled samples is infeasible. Few-shot learning (FSL) is the dominant approach to address this issue, where the objective is to quickly adapt to novel categories in presence of a limited number of samples. FSL tasks have been predominantly solved by leveraging the ideas from gradient-based meta-learning and metric learning approaches. However, recent works have demonstrated the significance of powerful feature representations with a simple embedding network that can outperform existing sophisticated FSL algorithms. In this work, we build on this insight and propose a novel training mechanism that simultaneously enforces equivariance …
A Deep Reinforcement Learning-Based Dynamic Computational Offloading Method For Cloud Robotics, Manoj Penmetcha, Byung-Cheol Min
A Deep Reinforcement Learning-Based Dynamic Computational Offloading Method For Cloud Robotics, Manoj Penmetcha, Byung-Cheol Min
Purdue University Libraries Open Access Publishing Fund
Robots come with a variety of computing capabilities, and running computationally-intense applications on robots is sometimes challenging on account of limited onboard computing, storage, and power capabilities. Meanwhile, cloud computing provides on-demand computing capabilities, and thus combining robots with cloud computing can overcome the resource constraints robots face. The key to effectively offloading tasks is an application solution that does not underutilize the robot's own computational capabilities and makes decisions based on crucial cost parameters such as latency and CPU availability. In this paper, we formulate the application offloading problem as a Markovian decision process and propose a deep reinforcement …
Mpi4py Implementation Of Greedy Algorithm For The Shortest Path Problem, Arianna Martin, Jeremy Evert, Charles Sleeper
Mpi4py Implementation Of Greedy Algorithm For The Shortest Path Problem, Arianna Martin, Jeremy Evert, Charles Sleeper
Student Research
No abstract provided.
Microfluidic-Based Bacterial Molecular Computing On A Chip, Daniel P. Martins, Michael Taynnan Barros, Benjamin O'Sullivan, Ian Seymour, Alan O'Riordan, Lee Coffey, Joseph Sweeney, Sasitharan Balasubramaniam,
Microfluidic-Based Bacterial Molecular Computing On A Chip, Daniel P. Martins, Michael Taynnan Barros, Benjamin O'Sullivan, Ian Seymour, Alan O'Riordan, Lee Coffey, Joseph Sweeney, Sasitharan Balasubramaniam,
School of Computing: Faculty Publications
Biocomputing systems based on engineered bacteria can lead to novel tools for environmental monitoring and detection of metabolic diseases. In this paper, we propose a Bacterial Molecular Computing on a Chip (BMCoC) using microfluidic and electrochemical sensing technologies. The computing can be flexibly integrated into the chip, but we focus on engineered bacterial AND Boolean logic gate and ON-OFF switch sensors that produces secondary signals to change the pH and dissolved oxygen concentrations. We present a prototype with experimental results that shows the electrochemical sensors can detect small pH and dissolved oxygen concentration changes created by the engineered bacterial populations’ …
Non-Hazardous Industrial Solid Waste Tracking System, Justin Tank
Non-Hazardous Industrial Solid Waste Tracking System, Justin Tank
Masters Theses & Doctoral Dissertations
The Olmsted Non-Hazardous Industrial Solid Waste Tracking System allows waste generators of certain materials to electronically have their waste assessments evaluated, approved, and tracked through a simple online process. The current process of manually requesting evaluations, prepopulating tracking forms, and filling them out on triplicate carbonless forms is out of sync with other processes in the department. Complying with audit requirements requires pulling physical copies and providing them physically to fulfill information requests.
Waste generators in Minnesota are required to track their waste disposals for certain types of industrial waste streams. This ensures waste is accounted for at the point …
Automated Evolution Of Feature Logging Statement Levels Using Git Histories And Degree Of Interest, Yiming Tang, Allan Spektor, Raffi Khatchadourian, Mehdi Bagherzadeh
Automated Evolution Of Feature Logging Statement Levels Using Git Histories And Degree Of Interest, Yiming Tang, Allan Spektor, Raffi Khatchadourian, Mehdi Bagherzadeh
Publications and Research
Logging—used for system events and security breaches to more informational yet essential aspects of software features—is pervasive. Given the high transactionality of today’s software, logging effectiveness can be reduced by information overload. Log levels help alleviate this problem by correlating a priority to logs that can be later filtered. As software evolves, however, levels of logs documenting surrounding feature implementations may also require modification as features once deemed important may have decreased in urgency and vice-versa. We present an automated approach that assists developers in evolving levels of such (feature) logs. The approach, based on mining Git histories and manipulating …
The Origin & Evolution Of The Chinese Language, Charity Bullis, Yan Xie
The Origin & Evolution Of The Chinese Language, Charity Bullis, Yan Xie
Liberty University Research Week
Undergraduate
Textual or Investigative
Sql Injection & Web Application Security: A Python-Based Network Traffic Detection Model, Nyki Anderson
Sql Injection & Web Application Security: A Python-Based Network Traffic Detection Model, Nyki Anderson
Cybersecurity Undergraduate Research Showcase
The Internet of Things (IoT) presents a great many challenges in cybersecurity as the world grows more and more digitally dependent. Personally identifiable information (PII) (i,e., names, addresses, emails, credit card numbers) is stored in databases across websites the world over. The greatest threat to privacy, according to the Open Worldwide Application Security Project (OWASP) is SQL injection attacks (SQLIA) [1]. In these sorts of attacks, hackers use malicious statements entered into forms, search bars, and other browser input mediums to trick the web application server into divulging database assets. A proposed technique against such exploitation is convolution neural network …
Mesoscopic Traffic Simulation Model And Calibration Considering Stretching-Segment Design, Zhaocheng He, Xuanhua Lin, Peilin Nie, Ronghui Zhang
Mesoscopic Traffic Simulation Model And Calibration Considering Stretching-Segment Design, Zhaocheng He, Xuanhua Lin, Peilin Nie, Ronghui Zhang
Journal of System Simulation
Abstract: In order to make the simulation model fit the characteristics of urban traffic, both high accuracy and high performance, a lightweight mesoscopic traffic simulation system and the process of calibration are established. The speed-density model and vertical queue model are equivalent to the vehicle movement processes, the simulation accuracy and calibration efficiency are improved by the stretching-segment design at urban intersections of vertical queuing model, and the real individual vehicle information is used as the calibration data source. The application of the model in Xuancheng urban road network shows that, compared with the vertical queuing model, it can …
Modeling And Simulation Of Electric Vehicle Industry Development Based On System Dynamics, Yueqiang Fu, Tiantian Xia
Modeling And Simulation Of Electric Vehicle Industry Development Based On System Dynamics, Yueqiang Fu, Tiantian Xia
Journal of System Simulation
Abstract: New energy electric vehicle are the main trend of automobile industry upgrading. It plays an important role in ensuring the energy security and improving the ecological environment. It is of theoretical and practical significance to carry out research on the development of new energy electric vehicles. The affecting factors are systematically analyzed, the causal relationship model and stock flow model are established, and the dynamic equation of the model are determined and the parameter assignments are made. The model is verified and the system simulation and analysis are performed. The development trend and main influencing factors of …
Unified Multi-Objective Genetic Algorithm For Energy Efficient Job Shop Scheduling, Hongjong Wei, Shaobo Li, Huageng Quan, Dacheng Liu, Shu Rao, Chuanjiang Li, Jianjun Hu
Unified Multi-Objective Genetic Algorithm For Energy Efficient Job Shop Scheduling, Hongjong Wei, Shaobo Li, Huageng Quan, Dacheng Liu, Shu Rao, Chuanjiang Li, Jianjun Hu
Faculty Publications
In recent years, people have paid more and more attention to traditional manufacturing’s environmental impact, especially in terms of energy consumption and related emissions of carbon dioxide. Except for adopting new equipment, production scheduling could play an important role in reducing the total energy consumption of a manufacturing plant. Machine tools waste a considerable amount of energy because of their underutilization. Consequently, energy saving can be achieved by switching machines to standby or off when they lay idle for a comparatively long period. Herein, we first introduce the objectives of minimizing non-processing energy consumption, total weighted tardiness and earliness, and …
Small Fault Detection Based On Cumulative Sum Of Neighbor Statistic, Xiaoping Guo, Jiajun Gao, Jianbin Guo, Li Yuan
Small Fault Detection Based On Cumulative Sum Of Neighbor Statistic, Xiaoping Guo, Jiajun Gao, Jianbin Guo, Li Yuan
Journal of System Simulation
Abstract: Aiming at the small faults and the common data non-linear problems of industrial process, a fault detection method based oncumulative sum of neighbor statistic (CUSUM-NS) is proposed. Mutual information principal component analysis (MIPCA) is used to reduce the dimension of training data, and the principal components based on mutual information are extracted to construct a new sample space. For the new sample space after dimensionality reduction, the nonlinear features of the process data can be fully extracted through the distance square sum statistics of k nearest neighbors. Cumulative summation(CUSUM) method is used to accumulate the sum of squares of …
Visual Simulation Platform For Visible Light Reconnaissance Load Of Unmanned Aerial Vehicle, Yuzhou Chen, Li Yuan, Qinglin Wang, Zhang Qing, Jinyuan Zhang
Visual Simulation Platform For Visible Light Reconnaissance Load Of Unmanned Aerial Vehicle, Yuzhou Chen, Li Yuan, Qinglin Wang, Zhang Qing, Jinyuan Zhang
Journal of System Simulation
Abstract: In view of the simulation and evaluation requirement of the visual system parameters on the performance of video imaging during the operation and reconnaissance of unmanned aerial vehicle, a visual simulation platform for the reconnaissance load is designed and constructed. The collected video is processed according to the visual system parameters and the flight parameters, and the support for the evaluation and the index design of the unmanned aerial vehicle reconnaissance load system is provided, and the guidance is provided for the flight parameters and the flight track setting when the unmanned aerial vehicle reconnaissance and operation …
Research On Some Questions Of Simulation Body Of Knowledge, Xiaogang Qiu, Duan Hong, Xie Xu, Bin Chen
Research On Some Questions Of Simulation Body Of Knowledge, Xiaogang Qiu, Duan Hong, Xie Xu, Bin Chen
Journal of System Simulation
Abstract: Simulation body of knowledge (BOK) is the knowledge required to conduct Modeling and Simulation (M&S) activities, which is a logic system consisting of concepts, propositions, and inferences that are tightly related to each other. The simulation BOK organizes the M&S knowledge in a hierarchical way, reflects the composition and structure of the knowledge in the M&S domain. The establishment of the simulation BOK is crucial to advance the M&S research and education. The requirements for establishing the simulation BOK are summarized, three basic features of the simulation knowledge, practical, systematical, and epochal are discussed, the challenges of establishing the …
Study On Composition Of Simulation Discipline Knowledge Areas, Duan Hong, Xiaogang Qiu, Xie Xu, Rusheng Ju
Study On Composition Of Simulation Discipline Knowledge Areas, Duan Hong, Xiaogang Qiu, Xie Xu, Rusheng Ju
Journal of System Simulation
Abstract: Many disciplines, such as Software Engineering, Automation, have sorted out and formed their own knowledge areas and constructed their Body of Knowledge to steer teaching and study efforts. Describing the composition of Modeling and Simulation body of knowledge from the perspective of knowledge area plays an important role in the simulation engineering education and the development of simulation technology. According to the needs of simulation teaching, the body of knowledge of simulation discipline is divided into three levels, knowledge area, knowledge unit and knowledge topic. On the basis of reviewing the current status of the research and the role …
Research On Combat Simulation Body Of Knowledge, Xie Xu, Xiaogang Qiu, Duan Hong, Kedi Huang
Research On Combat Simulation Body Of Knowledge, Xie Xu, Xiaogang Qiu, Duan Hong, Kedi Huang
Journal of System Simulation
Abstract: Combat simulation is an important research method in modern military domain, since it provides a virtual battlespace for entities of various types that are involved in a battle to interact with each other. Over last several decades, combat simulation has been widely applied in different applications, and as a result the body of knowledge of combat simulation has been extended a lot. The relevant articles and textbooks in combat simulation are extensively investigated, and a three-layer structure to organize the body of knowledge of combat simulation is proposed. Eleven knowledge areas that should be included in the combat simulation …
Personalized Game Recommendation Method Based On Implicit Feedback, Sha Jing, Gongli Zeng, Yang Yang, Wei Yao
Personalized Game Recommendation Method Based On Implicit Feedback, Sha Jing, Gongli Zeng, Yang Yang, Wei Yao
Journal of System Simulation
Abstract: Traditional recommendation systems often use explicit feedback for personalized recommendations. But the explicit feedback data is not easy to obtain, and the quality is poor, and the recommendation results unable to meet the requitrment of the user. Implicit feedback data is easier to obtain and can provide users with the better content. A personalized game recommendation method based on implicit feedback data is proposed. The method builds an implicit feedback recommendation model for game user data based on implicit feedback data such as the game duration and game numbers. A personalized recommendation of the game is implemented through an …
Mesh Solid Construction Algorithm Of Spiral Bevel Gear Based On Virtual Collision Body, Cheng'en Li, Xiangjun Zou, Zeqin Zeng, Jianhua He, Li Hui, Zhaofeng Huang
Mesh Solid Construction Algorithm Of Spiral Bevel Gear Based On Virtual Collision Body, Cheng'en Li, Xiangjun Zou, Zeqin Zeng, Jianhua He, Li Hui, Zhaofeng Huang
Journal of System Simulation
Abstract: In order to improve the production automation, intelligence level and production efficiency of the tractor rear axle, the spiral bevel gear mesh entity based on the virtual collision body is constructed to carry out the human-machine interaction virtual simulation experiment of the tractor rear axle. The spiral bevel gear made by Gleason as is taken an example, the processing technology of arc spur gear is analyzed, the kinematics is used to establish a mathematical model of the spiral bevel gear forming process. The differential and interpolation methods are used to fit the gear curve and surface, the contour point …
Gas-Liquid Two-Phase Flow Pattern Recognition Method Based On Convolutional Neural Network, Weiguo Tong, Xuechun Pang, Genghong Zhu
Gas-Liquid Two-Phase Flow Pattern Recognition Method Based On Convolutional Neural Network, Weiguo Tong, Xuechun Pang, Genghong Zhu
Journal of System Simulation
Abstract: Aiming at the low recognition rate and subjectivity in two-phase flow pattern recognition, a method based on Landweber iterative image reconstruction algorithm and convolutional neural network is proposed. Landweber iterative image reconstruction algorithm is used to obtain the flow pattern images and build the flow pattern image database. By means of the flow pattern identification on, different convolution layers in VGG16 network and different size and resolution of the data set samples, the parameters of network frozen convolutional layer and input image are determined.The experimental results show that the combined method of resistance tomography and convolutional neural network …
Operation Resilience Optimization Of Power System Considering Generalized Energy Storage, Weiqing Sun, Zhang Jie, Ye Lei, Han Dong
Operation Resilience Optimization Of Power System Considering Generalized Energy Storage, Weiqing Sun, Zhang Jie, Ye Lei, Han Dong
Journal of System Simulation
Abstract: Based on the definition and principle of power system resilience, combining the traditional energy storage equipment with the demand response, an optimization method of power system operation resilience considering generalized energy storage is proposed. Five attack schemes based on topology are evaluated according to four indexes, and the most disadvantageous attack strategy is selected to simulate the damage of power system. Taking the minimum operating cost of the system as the objective, a combined scheduling model involving wind power station and energy storage unit is carried out. A generalized energy storage scheduling method is proposed to improve the …
Study On Relay Selection Algorithm Based On Swipt Wireless Cooperative Network, Qun Fang, Xukai Chen, He Xin, Yujun Zhu, Yiyang Liu, Yangyang Fang, Heju Li
Study On Relay Selection Algorithm Based On Swipt Wireless Cooperative Network, Qun Fang, Xukai Chen, He Xin, Yujun Zhu, Yiyang Liu, Yangyang Fang, Heju Li
Journal of System Simulation
Abstract: Although the wireless cooperative networks (WCN) significantly improve the communication quality and network throughput of wireless communications. However, it still faces the challenge of the network lifetime and the energy replenishment due to the energy limitation of relay nodes. In order to tackle this challenge, A multi-relay wireless cooperative network combined with the simultaneous wireless information and power transfer (SWIPT) is proposed and the theoretical performance under the Nakagami-m assumption is analyzed. The selection of the optimal relay node for wireless cooperative networks in the framework of the proposed system is studied. The outage probability of the system …
Compensation Sliding Cross Coupling Control Research Of Cartesian Coordinate Robot, Wang Wei, Zhimei Chen, Zhenyan Wang
Compensation Sliding Cross Coupling Control Research Of Cartesian Coordinate Robot, Wang Wei, Zhimei Chen, Zhenyan Wang
Journal of System Simulation
Abstract: For a typical Cartesian coordinate robot controls precision is low, based on a single-axis mathematical model, a contour error model for a typical robot whose axes are orthogonal to each other is established. An improved double-power approach law is used to design a terminal sliding mode controller to improve the robot. The integral compensation terms are added to stably compensate the position accuracy of each axis to improve the overall trajectory tracking accuracy, and the cross-coupling control between the axes is used to eliminate the contour error between the axes. It not only weakens the chattering of traditional sliding …