Computer Sciences Commons^™

Aerial Flight Paths For Communication, Alisha Bevins

School of Computing: Dissertations, Theses, and Student Research

This body of work presents an iterative process of refinement to understand naive perception of communication using the motion of an unmanned aerial vehicle (UAV). This includes what people believe the UAV is trying to communicate, and how they expect to respond through physical action or emotional response. Previous work in this area sought to communicate without clear definitions of the states attempting to be conveyed. In an attempt to present more concrete states and better understand specific motion perception, this work goes through multiple iterations of state elicitation and label assignment. The lessons learned in this work will be …

Learning And Exploiting Shaped Reward Models For Large Scale Multiagent Rl, Arambam James Singh, Akshat Kumar, Hoong Chuin Lau

Research Collection School Of Computing and Information Systems

Many real world systems involve interaction among large number of agents to achieve a common goal, for example, air traffic control. Several model-free RL algorithms have been proposed for such settings. A key limitation is that the empirical reward signal in model-free case is not very effective in addressing the multiagent credit assignment problem, which determines an agent's contribution to the team's success. This results in lower solution quality and high sample complexity. To address this, we contribute (a) an approach to learn a differentiable reward model for both continuous and discrete action setting by exploiting the collective nature of …

Vehicle Routing: Review Of Benchmark Datasets, Aldy Gunawan, Graham Kendall, Barry Mccollum, Hsin-Vonn Seow, Lai Soon Lee

Research Collection School Of Computing and Information Systems

The Vehicle Routing Problem (VRP) was formally presented to the scientific literature in 1959 by Dantzig and Ramser (DOI:10.1287/mnsc.6.1.80). Sixty years on, the problem is still heavily researched, with hundreds of papers having been published addressing this problem and the many variants that now exist. Many datasets have been proposed to enable researchers to compare their algorithms using the same problem instances where either the best known solution is known or, in some cases, the optimal solution is known. In this survey paper, we provide a list of Vehicle Routing Problem datasets, categorized to enable researchers to have easy access …

Rotten With Prediction, Serena Raquel Hicks

UNLV Theses, Dissertations, Professional Papers, and Capstones

This project focuses on the relationship between religion and technology as it is portrayed in Science Fiction (SF). This thesis explores the SF genre rhetorically by examining the 2002 movie Minority Report (MR), which signaled the importance of surveillance and the need to predict future crimes following 9/11. The events of 9/11 played a significant role in post 9/11 SF films, which reflect and critique our communal and cultural values. 9/11 created a new relationship between the U.S justice system, predictive technologies (PTs), and data gathering. Through the Bush Doctrine of “preemptive action,” the U.S government attempted to use Dataism, …

Industrial Control System Data Resiliency, Daniel A. Bovard

Boise State University Theses and Dissertations

This thesis identifies and fortifies against a critical vulnerability in industrial control system (ICS) security. A properly designed ICS security framework consists of a multi-layered approach starting with heavy fortifications in information technology and ending with control information of operational technology. Currently, ICS security frameworks lack visibility and place blind trust in devices at the lowest level of the control hierarchy. Attaining control data visibility at the lowest level of the control hierarchy is critical to increasing the resiliency of an ICS security posture. This thesis demonstrates how this data can be captured at the lowest level of the control …

Movement Analysis For Neurological And Musculoskeletal Disorders Using Graph Convolutional Neural Network, Ibsa K. Jalata, Thanh-Dat Truong, Jessica L. Allen, Han-Seok Seo, Khoa Luu

Computer Science and Computer Engineering Faculty Publications and Presentations

Using optical motion capture and wearable sensors is a common way to analyze impaired movement in individuals with neurological and musculoskeletal disorders. However, using optical motion sensors and wearable sensors is expensive and often requires highly trained professionals to identify specific impairments. In this work, we proposed a graph convolutional neural network that mimics the intuition of physical therapists to identify patient-specific impairments based on video of a patient. In addition, two modeling approaches are compared: a graph convolutional network applied solely on skeleton input data and a graph convolutional network accompanied with a 1-dimensional convolutional neural network (1D-CNN). Experiments …

Learning And Exploiting Shaped Reward Models For Large Scale Multiagent Rl, Arambam James Singh, Akshat Kumar, Hoong Chuin Lau

Research Collection School Of Computing and Information Systems

Many real world systems involve interaction among large number of agents to achieve a common goal, for example, air traffic control. Several model-free RL algorithms have been proposed for such settings. A key limitation is that the empirical reward signal in model-free case is not very effective in addressing the multiagent credit assignment problem, which determines an agent's contribution to the team's success. This results in lower solution quality and high sample complexity. To address this, we contribute (a) an approach to learn a differentiable reward model for both continuous and discrete action setting by exploiting the collective nature of …

Thunderrw: An In-Memory Graph Random Walk Engine, Shixuan Sun, Yuhang Chen, Shengliang Lu, Bingsheng He, Yuchen Li

Research Collection School Of Computing and Information Systems

As random walk is a powerful tool in many graph processing, mining and learning applications, this paper proposes an efficient inmemory random walk engine named ThunderRW. Compared with existing parallel systems on improving the performance of a single graph operation, ThunderRW supports massive parallel random walks. The core design of ThunderRW is motivated by our profiling results: common RW algorithms have as high as 73.1% CPU pipeline slots stalled due to irregular memory access, which suffers significantly more memory stalls than the conventional graph workloads such as BFS and SSSP. To improve the memory efficiency, we first design a generic …

Automated Taxi Queue Management At High-Demand Venues, Mengyu Ji, Shih-Fen Cheng

Research Collection School Of Computing and Information Systems

In this paper, we seek to identify an effective management policy that could reduce supply-demand gaps at taxi queues serving high-density locations where demand surges frequently happen. Unlike current industry practice, which relies on broadcasting to attract taxis to come and serve the queue, we propose more proactive and adaptive approaches to handle demand surges. Our design objective is to reduce the cumulative supply-demand gaps as much as we could by sending notifications to individual taxis. To address this problem, we first propose a highly effective passenger demand prediction system that is based on the real-time flight arrival information. By …

A Lagrangian Column Generation Approach For The Probabilistic Crowdsourced Logistics Planning, Chung-Kyun Han, Shih-Fen Cheng

Research Collection School Of Computing and Information Systems

In recent years we have increasingly seen the movement for the retail industry to move their operations online. Along the process, it has created brand new patterns for the fulfillment service, and the logistics service providers serving these retailers have no choice but to adapt. The most challenging issues faced by all logistics service providers are the highly fluctuating demands and the shortening response times. All these challenges imply that maintaining a fixed fleet will either be too costly or insufficient. One potential solution is to tap into the crowdsourced workforce. However, existing industry practices of relying on human planners …

Estimating Homophily In Social Networks Using Dyadic Predictions, George Berry, Antonio Sirianni, Ingmar Weber, Jisun An, Michael Macy

Research Collection School Of Computing and Information Systems

Predictions of node categories are commonly used to estimate homophily and other relational properties in networks. However, little is known about the validity of using predictions for this task. We show that estimating homophily in a network is a problem of predicting categories of dyads (edges) in the graph. Homophily estimates are unbiased when predictions of dyad categories are unbiased. Node-level prediction models, such as the use of names to classify ethnicity or gender, do not generally produce unbiased predictions of dyad categories and therefore produce biased homophily estimates. Bias comes from three sources: sampling bias, correlation between model errors …

Context-Aware Outstanding Fact Mining From Knowledge Graphs, Yueji Yang, Yuchen Li, Panagiotis Karras, Anthony Tung

Research Collection School Of Computing and Information Systems

An Outstanding Fact (OF) is an attribute that makes a target entity stand out from its peers. The mining of OFs has important applications, especially in Computational Journalism, such as news promotion, fact-checking, and news story finding. However, existing approaches to OF mining: (i) disregard the context in which the target entity appears, hence may report facts irrelevant to that context; and (ii) require relational data, which are often unavailable or incomplete in many application domains. In this paper, we introduce the novel problem of mining Contextaware Outstanding Facts (COFs) for a target entity under a given context specified by …

Fast Magnetic Resonance Image Reconstruction With Deep Learning Using An Efficientnet Encoder, Tahsin Rahman

Open Access Theses & Dissertations

This thesis aims to develop an efficient, deep network based method for Magnetic Resonance Imaging (MRI) acceleration through undersampled MR image reconstruction. Deep Neural Networks, particularly Deep Convolutional Networks, have been demonstrated to be highly effective in a wide variety of computer vision tasks, including MRI reconstruction. However, modern highly efficient encoder structures, such as the EfficientNet can potentially reduce reconstruction times further while improving reconstruction quality. To that end, we have developed a multi-channel U-Net MRI reconstruction network which uses an EfficientNet encoder and a custom asymmetric. The network was trained and tested using 5x undersampled multi-channel brain MR …

Hardware For Quantized Mixed-Precision Deep Neural Networks, Andres Rios

Open Access Theses & Dissertations

Recently, there has been a push to perform deep learning (DL) computations on the edge rather than the cloud due to latency, network connectivity, energy consumption, and privacy issues. However, state-of-the-art deep neural networks (DNNs) require vast amounts of computational power, data, and energyâ??resources that are limited on edge devices. This limitation has brought the need to design domain-specific architectures (DSAs) that implement DL-specific hardware optimizations. Traditionally DNNs have run on 32-bit floating-point numbers; however, a body of research has shown that DNNs are surprisingly robust and do not require all 32 bits. Instead, using quantization, networks can run on …

Non-Invasive In-Vitro Glucose Monitoring Using Optical Sensor And Machine Learning Techniques For Diabetes Applications, Maryamsadat Shokrekhodaei

Open Access Theses & Dissertations

Diabetes is a major public health challenge affecting more than 451 million people. Physiological and experimental factors influence the accuracy of non-invasive glucose monitoring, and these need to be addressed before replacing the finger prick method with a non-invasive glucose measurement technique. Also, the suitable employment of machine learning techniques on experimental data can significantly improve the accuracy of glucose predictions.

This work includes the design, development, testing and data analysis of an optical based sensor for glucose measurements. The feasibility of non-invasive measurement of glucose within aqueous solutions that assimilate the composition of human blood plasma is investigated. The …

Socio-Technical Perspective For Electronic Tax Information System In Tanzania, Lucas Ngowi, Ellen Kalinga

Tanzania Journal of Engineering and Technology (TJET)

Socio-technical systems theory has rarely been used by system architects in setting up computing systems. However, the role of socio-technical concepts in computing, which is becoming social in nature, has made the concepts more relevant and commercial. Tax information systems are examples of such systems because they are influenced by external variables such as the political environment, technological trends, and social environment, introducing complexity in their deployment and determining the type of e-services and their delivery to a diverse group of people. It was observed that in Tanzania there is resistance, reluctance and minimal use of electronic tax system because …

Graphical Models In Reconstructability Analysis And Bayesian Networks, Marcus Harris, Martin Zwick

Complex Systems Faculty Publications and Presentations

Reconstructability Analysis (RA) and Bayesian Networks (BN) are both probabilistic graphical modeling methodologies used in machine learning and artificial intelligence. There are RA models that are statistically equivalent to BN models and there are also models unique to RA and models unique to BN. The primary goal of this paper is to unify these two methodologies via a lattice of structures that offers an expanded set of models to represent complex systems more accurately or more simply. The conceptualization of this lattice also offers a framework for additional innovations beyond what is presented here. Specifically, this paper integrates RA and …

Simulation Of Cooperative Control Process For Multiple Uavs Based On Local Information Connection, Xiangyang Li, Zhili Zhang, Zhang Ning, Gui Yi, Li Jia

Journal of System Simulation

Abstract: Aiming at the requirements of cooperative control for multiple UAVs based on local information connection, the distributed architecture of Multi-UAV system is established on the basis of multilayer structure. The communication network topology, state control information model and intelligent Ad-Hoc network mechanism are proposed to ensure the reliable interactive communication among multiple UAVs under local information connection. The cooperative collision avoidance strategy with local state prediction and distributed iterative optimization, combined with the cooperative on-line track planning and threat avoidance control methods, are applied to realize the cooperative control of Multi-UAV's task execution process. Simulation experiments verify the …

Fast Maritime Simulator Scene Modeling Method Based On Aerial Images, Lijia Chen, Wang Kai, Shigang Li, Yanfei Tian

Journal of System Simulation

Abstract: Artificial Modeling using Computer Aid Design software are frequently applied in maritime simulator scene modeling,but with low accuracy, low efficiency and complicate workflow. It's not the ideal method of modeling a large-scale area. A modeling method is proposed based on aerial images in combination with tilt photography modeling, procedural modeling and image semantic segmentation method. It's a fast and highly automated modeling method specially for the maritime simulator. A water area near Tianxingzhou Yangtze River Bridge is chosen as the model. Experiment results show that the proposed method is of fast speed, high precision, high degree of automation, …

Research On Performance Modeling And Simulation Method Based On Dense Crowd, Yihao Li, Tianyu Huang, Li Peng, Gangyi Ding

Journal of System Simulation

Abstract: Due to the high complexity of crowd organization and the difficulty of abstracting the performance, the performance simulation of dense crowds relies heavily on manual work, and it is difficult to establish a highly automated simulation model. In order to reduce the sensitivity of creative modification and design risks, a performance model based on dense crowd is proposed. Through the strategy of time dimension slicing and spatial layering, a highly automated crowd performance simulation method that could meet the director's creativity is realized. Through the construction of simulation experiments, the generation effect and calculation efficiency of the crowd …

Design And Engine Implementation Of Submarine Combat System Simulation Based On Lvc, Jinping Wu, Minghua Lu, Changyou Xue

Journal of System Simulation

Abstract: Submarine combat system simulation is one of the key and most important content in submarine combat simulation. On the basis of LVC simulation technology, practicing simulation-as-a-service idea, the LVC integration simulation method of submarine combat system is proposed and the LVC integration simulation environment is constructed. The composition and relationship of LVC simulation system are researched. The compositional structure of LVC simulation engine was designed. Based on the component design and development specifications in Java/EJB technological infrastructure, in use of software component technology, the simulation engine components are designed and implemented. The LVC integration simulation of submarine combat system …

Networked Simulation And It's Development Trend, Duan Hong, Xiaogang Qiu

Journal of System Simulation

Abstract: Carrying out simulating whenever and wherever possible as well as the large-scale trend of simulation lead to the demand of networked simulation.. Through the changes of range, from model interconnection, experimental collaboration and domain simulation collaboration, three layers of meanings of networked simulation are analyzed; The characteristics of networked simulation are summarized from five aspects, pattern, application, target, focus, and morphology. The idea that the networked simulation will bring changes to the simulation application of the activity scope and method, resource construction, resource verification, organizational structure, and so on is proposed. By sorting out the development process …

Study On Universal Characteristics Of Insect Population Ecological Network, Guilan Luo, Hongjun Hao, Wang Xiao, Zhang Mei

Journal of System Simulation

Abstract: In order to evaluate the current state of insect ecological development in Erhai wetland, complex network theory is used to construct a topological structure model of insect ecological network with insect populations as network nodes and correlations as edges. By analyzing the characteristic parameters of the model, it is concluded that the insect ecological network conforms to the characteristics of small world and scale-free network, and the node degree distribution obeys the power law distribution. The method of destroying the topology is used to simulate the dynamic evolution of the network ecology. The study shows that the disappearance of …

Study On Task Allocation Of Uav Swarm Based On Cognitive Control, Ruixuan Wei, Zichen Wu

Journal of System Simulation

Abstract: A centralized allocation method for Unmanned Aerial Vehicle (UAV) swarm real-time task allocation is proposed. Based on the real-time battlefield situation, this method relies on the coordination scheduling layer to make allocation decisions, generates the strike order according to the strike efficiency ratio, and makes rolling optimization for real-time battlefield situation, so that the allocation results can always maintain the balance between optimization and efficiency within the current cognitive range. Particle swarm optimization (PSO) is used to solve the task assignment problem. In particular, a 2-D particle 0-1 coding and correction method for nonstandard particles is designed. The simulation …

Study On Interior Space Pedestrian Evacuation Model Elite Chaos Search Strategy, Wei Juan, Zhongyu Li, You Lei, Yangyong Guo, Zhihai Tang, Zhouyi Hu

Journal of System Simulation

Abstract: In order to improve traditional field model of easily falling into the queue problem during simulating the evacuation of dense crowds, an improved pedestrian evacuation model in interior space is proposed based on the elite chaos search strategy. The pedestrian mobile income at each moment is calculated in combination with the field value, capacity and average speed, and a field model for pedestrian evacuation is presented. On this basis, the objective optimization function of the minimum evacuation time and minimum queue length is given, and the elite chaos search strategy is used to achieve the above objective function solution, …

Fast Alignment Of Bim Products Based On Structure Matching, Xiaojun Liu, Changyan He, Liu Chang, Jinyuan Jia

Journal of System Simulation

Abstract: The fast alignment of BIM products based on structure matching is realized. An Item-based Structure Graph (ISG) is proposed as the structure-aware shape descriptor for BIM products. An improved graph matching algorithm upon Factorized Graph Matching (FGM) is implemented in ISG matching, in which the mismatch caused by symmetry switching is avoided. Further extension is made to support the alignment under partial matching for BIM products from the same family. The experiment result shows that ISG can meet the characteristics of BIM products, improve the efficiency and accuracy, and can be applied in dealing with products alignment, BIM data …

Position And Attitude Estimation Based On Combination Matching In Calibration Area, Cai Peng, Chaoping Shen, Hongyan Li

Journal of System Simulation

Abstract: Vision navigation technology of scene matching needs hardware to measure the distance and attitude of the camera. A method of position and attitude estimation based on the combination of feature points in the calibration area is proposed. The software can get the camera position and attitude of the real-time image by selecting the best set of Scale-Invariant Feature Transform(SIFT) feature matching points of the reference image calibration area of the real-time image, and calculating the local coordinates of the ground of SIFT feature matching points based on the triangle internal linear interpolation method, using space resection, avoids the defect …

Numerical Simulation Of Aerodynamic Characteristics For Double-All-Wing Unmanned Aerial Vehicle Based On Computational Fluid Dynamics Theory, Kuizhi Yue, Zhang Yuan, Liangliang Cheng, Dazhao Yu

Journal of System Simulation

Abstract: Follow the rapid progress of the nation's blue ocean strategic projection capability of sea power, an Unmanned Aerial Vehicle (UAV) with double-all-wing configuration is studied to match the trend. The UAV is conceptually designed by CATIA software, the aerodynamic characteristic of the model is numerically simulated by computational fluid dynamics (Computational Fluid Dynamics, CFD) theory, and the performance of the UAV to take off from the aircraft carrier is also analyzed. The lift coefficient, drag coefficient and lift-drag ratio of the double-all-wing UAV model with a angle of attack of 0 can reach 0.596 2, 0.037 6 and 15.824 …

High Adaptability Vehicle Network Communication Protocol Based On Aodv, Wang Tong, Gao Shan, Tianshu Dai

Journal of System Simulation

Abstract: Routing protocol is an essential part of vehicular ad-hoc network (VANET). According to the characteristics of frequent changes of vehicle node location in urban environment, an AODV routing protocol based on Network Topology Changes (NTCAODV) is proposed. According to the speed and relative position information, by calculating the stability coefficient of nodes, the link connection is established on the basis of principle of "optimal stability", and the idea of extended loop is improved according to recorded the link establishment time. Simulation results show that NTCAODV routing protocol has good performance in various urban environments, improves …

Evaluation Method On Multi-Stage Bayes Information Fusion For Scatters Hwil Simulation, Yecheng Wang, Ma Jing, Congjun Jin, Jie Li, Bin Shi

Journal of System Simulation

Abstract: In order to simulate the complex 3D target in the RF HWIL (hardware in the loop simulation) system, the equivalence framework of multiple scattering centers of complex 3D target for three stages of outfield test data, mathematics simulation data and HWIL data are introduced. Using the pre-test information as each stage for transmission, evaluation method is designed by multi-stage Bayes information fusion for HWIL simulation. Based on prior information of outfield test data and mathematics simulation data, by using Bayes information fusion theory, the average data reconstruction of each stage is obtained and compared and high reliability …