Numerical Analysis and Scientific Computing Commons^™

Modeling Repairable System Failure Data Using Nhpp Reliability Growth Mode., Eunice Ofori-Addo

EWU Masters Thesis Collection

Stochastic point processes have been widely used to describe the behaviour of repairable systems. The Crow nonhomogeneous Poisson process (NHPP) often known as the Power Law model is regarded as one of the best models for repairable systems. The goodness-of-fit test rejects the intensity function of the power law model, and so the log-linear model was fitted and tested for goodness-of-fit. The Weibull Time to Failure recurrent neural network (WTTE-RNN) framework, a probabilistic deep learning model for failure data, is also explored. However, we find that the WTTE-RNN framework is only appropriate failure data with independent and identically distributed interarrival …

Exploring High Performance And Energy Efficient Graph Processing On Gpu, Robert P. Watling

Dissertations, Master's Theses and Master's Reports

Parallel graph processing is central to analytical computer science applications, and GPUs have proven to be an ideal platform for parallel graph processing. Existing GPU graph processing frameworks present performance improvements but often neglect two issues: the unpredictability of a given input graph and the energy consumption of the graph processing. Our prototype software, EEGraph (Energy Efficiency of Graph processing), is a flexible system consisting of several graph processing algorithms with configurable parameters for vertex update synchronization, vertex activation, and memory management along with a lightweight software-based GPU energy measurement scheme. We observe relationships between different configurations of our software, …

Phys 275: Intro To Scientific Computing, David Goldberg

Open Educational Resources

No abstract provided.

Anchorage: Visual Analysis Of Satisfaction In Customer Service Videos Via Anchor Events, Kam Kwai Wong, Xingbo Wang, Yong Wang, Jianben He, Rong Zhang, Huamin Qu

Research Collection School Of Computing and Information Systems

Delivering customer services through video communications has brought new opportunities to analyze customer satisfaction for quality management. However, due to the lack of reliable self-reported responses, service providers are troubled by the inadequate estimation of customer services and the tedious investigation into multimodal video recordings. We introduce , a visual analytics system to evaluate customer satisfaction by summarizing multimodal behavioral features in customer service videos and revealing abnormal operations in the service process. We leverage the semantically meaningful operations to introduce structured event understanding into videos which help service providers quickly navigate to events of their interest. supports a comprehensive …

Assessing The Performance Of A Particle Swarm Optimization Mobility Algorithm In A Hybrid Wi-Fi/Lora Flying Ad Hoc Network, William David Paredes

UNF Graduate Theses and Dissertations

Research on Flying Ad-Hoc Networks (FANETs) has increased due to the availability of Unmanned Aerial Vehicles (UAVs) and the electronic components that control and connect them. Many applications, such as 3D mapping, construction inspection, or emergency response operations could benefit from an application and adaptation of swarm intelligence-based deployments of multiple UAVs. Such groups of cooperating UAVs, through the use of local rules, could be seen as network nodes establishing an ad-hoc network for communication purposes.

One FANET application is to provide communication coverage over an area where communication infrastructure is unavailable. A crucial part of a FANET implementation is …

El-Vit: Probing Vision Transformer With Interactive Visualization, Hong Zhou, Rui Zhang, Peifeng Lai, Chaoran Guo, Yong Wang, Zhida Sun, Junjie Li

Research Collection School Of Computing and Information Systems

Nowadays, Vision Transformer (ViT) is widely utilized in various computer vision tasks, owing to its unique self-attention mechanism. However, the model architecture of ViT is complex and often challenging to comprehend, leading to a steep learning curve. ViT developers and users frequently encounter difficulties in interpreting its inner workings. Therefore, a visualization system is needed to assist ViT users in understanding its functionality. This paper introduces EL-VIT, an interactive visual analytics system designed to probe the Vision Transformer and facilitate a better understanding of its operations. The system consists of four layers of visualization views. The first three layers include …

Dual-View Preference Learning For Adaptive Recommendation, Zhongzhou Liu, Yuan Fang, Min Wu

Research Collection School Of Computing and Information Systems

While recommendation systems have been widely deployed, most existing approaches only capture user preferences in the , i.e., the user's general interest across all kinds of items. However, in real-world scenarios, user preferences could vary with items of different natures, which we call the . Both views are crucial for fully personalized recommendation, where an underpinning macro-view governs a multitude of finer-grained preferences in the micro-view. To model the dual views, in this paper, we propose a novel model called Dual-View Adaptive Recommendation (DVAR). In DVAR, we formulate the micro-view based on item categories, and further integrate it with the …

Crowdfa: A Privacy-Preserving Mobile Crowdsensing Paradigm Via Federated Analytics, Bowen Zhao, Xiaoguo Li, Ximeng Liu, Qingqi Pei, Yingjiu Li, Robert H. Deng

Research Collection School Of Computing and Information Systems

Mobile crowdsensing (MCS) systems typically struggle to address the challenge of data aggregation, incentive design, and privacy protection, simultaneously. However, existing solutions usually focus on one or, at most, two of these issues. To this end, this paper presents CROWD FA, a novel paradigm for privacy-preserving MCS through federated analytics (FA), which aims to achieve a well-rounded solution encompassing data aggregation, incentive design, and privacy protection. Specifically, inspired by FA, CROWD FA initiates an MCS computing paradigm that enables data aggregation and incentive design. Participants can perform aggregation operations on their local data, facilitated by CROWD FA, which supports various …

Predictive Taxonomy Analytics (Lasso): Predicting Outcome Types Of Cyber Breach, Jing Rong Goh, Shaun S. Wang, Yaniv Harel, Gabriel Toh

Research Collection School Of Economics

Cyber breaches are costly for the global economy and extensive efforts have gone into improving the cybersecurity infrastructure. There are numerous types of cyber breaches that vary greatly in terms of cause and impact, resulting in an extensive literature for individual cyber breach type. Our paper seeks to provide a general framework that can be easily applied to analyze different types of cyber breaches. Our framework is inspired by the taxonomy approach in the cybersecurity literature, where it was proposed that an effective set of taxonomy can provide a direction on supporting improved decision-making in cyber risk management and selecting …

Efficient Approximate Range Aggregation Over Large-Scale Spatial Data Federation, Yexuan Shi, Yongxin Tong, Yuxiang Zeng, Zimu Zhou, Bolin Ding, Lei Chen

Research Collection School Of Computing and Information Systems

Range aggregation is a primitive operation in spatial data applications and there is a growing demand to support such operations over a data federation, where the entire spatial data are separately held by multiple data providers (a.k.a., data silos). Data federations notably increase the amount of data available for data-intensive applications such as smart mobility planning and public health emergency responses. Yet they also challenge the conventional implementation of range aggregation queries because the raw data cannot be shared within the federation and the data partition at each data silo is fixed during query processing. These constraints limit the design …

Vacsen: A Visualization Approach For Noise Awareness In Quantum Computing, Shaolun Ruan, Yong Wang, Weiwen Jiang, Ying Mao, Qiang Guan

Research Collection School Of Computing and Information Systems

Quantum computing has attracted considerable public attention due to its exponential speedup over classical computing. Despite its advantages, today's quantum computers intrinsically suffer from noise and are error-prone. To guarantee the high fidelity of the execution result of a quantum algorithm, it is crucial to inform users of the noises of the used quantum computer and the compiled physical circuits. However, an intuitive and systematic way to make users aware of the quantum computing noise is still missing. In this paper, we fill the gap by proposing a novel visualization approach to achieve noise-aware quantum computing. It provides a holistic …

Learning Analytics In Informal, Participatory Collaborative Learning, Michelle L. F. Cheong, Aditya Singh, Yun-Chen Chen, Bing Tian Dai

Research Collection School Of Computing and Information Systems

Learning Analytics was recognized to be “the third wave of large-scale developments in instructional technology”. Learning Management Systems (LMSs) have been widely adopted as the learning analytics tools because the captured data represents how the learners’ interact with the system during formal learning. However, most LMSs’ analytics models do not capture learning activities outside the systems. We built an integrated Telegram mobile application and a web-based portal discussion forum, to enable informal, participatory and collaborative learning beyond the classroom. We analyzed student-initiated question-and-answer discussion posts where our machine learning algorithm will predict the quality of the posts, and the system …

Efficient Gpu Implementation Of Automatic Differentiation For Computational Fluid Dynamics, Mohammad Zubair, Desh Ranjan, Aaron Walden, Gabriel Nastac, Eric Nielsen, Boris Diskin, Marc Paterno, Samuel Jung, Joshua Hoke Davis

Computer Science Faculty Publications

Many scientific and engineering applications require repeated calculations of derivatives of output functions with respect to input parameters. Automatic Differentiation (AD) is a method that automates derivative calculations and can significantly speed up code development. In Computational Fluid Dynamics (CFD), derivatives of flux functions with respect to state variables (Jacobian) are needed for efficient solutions of the nonlinear governing equations. AD of flux functions on graphics processing units (GPUs) is challenging as flux computations involve many intermediate variables that create high register pressure and require significant memory traffic because of the need to store the derivatives. This paper presents a …

Claimdistiller: Scientific Claim Extraction With Supervised Contrastive Learning, Xin Wei, Md Reshad Ul Hoque, Jian Wu, Jiang Li

Computer Science Faculty Publications

The growth of scientific papers in the past decades calls for effective claim extraction tools to automatically and accurately locate key claims from unstructured text. Such claims will benefit content-wise aggregated exploration of scientific knowledge beyond the metadata level. One challenge of building such a model is how to effectively use limited labeled training data. In this paper, we compared transfer learning and contrastive learning frameworks in terms of performance, time and training data size. We found contrastive learning has better performance at a lower cost of data across all models. Our contrastive-learning-based model ClaimDistiller has the highest performance, boosting …

Overview Of Research And Application On Autonomous Vehicle Oriented Perception System Simulation, Ruoxuan Wang, Jianping Wu, Hui Xu

Journal of System Simulation

Abstract: Following the rapid progress of science and technology, vehicles with autonomous driving or auxiliary driving function enter into vehicle market. However, in the past decade, traffic accidents still occurred frequently, and the safety of these functions become the focus. Simulation technology provides a good platform to test the perception system of autonomous vehicle. Focus on the sensor simulation modeling of autonomous vehicle perception system, from the perspective of single sensor simulation, multi-sensor simulation and classic simulation platform including millimeter wave radar, lidar and camera, the existing research are reviewed, and the shortcomings and development trends of simulation modeling of …

Anomaly Detection Method Of Electrical Power Consumption Based On Deep Autoencoder, Ningke Sun, Yan Wang, Zhicheng Ji

Journal of System Simulation

Abstract: Aiming at the nonlinear and non-stationary characteristics of electrical power consumption data, an abnormal electrical power consumption detection model based on deep autoencoder is proposed. Gated recurrent unit (GRU) network of the deep learning is combined with autoencoder structure, and the encoder and decoder parts of traditional autoencoder are realized by gated recurrent unit network, which gives full play to the data feature extraction capability of gated recurrent unit and the data reconstruction function of autoencoder structure. Based on the reconstruction error between original data and reconstructed data, abnormal data points of the electrical power consumption are detected. By …

Short-Term Prediction Method Of Wind Power Based On Blp-Alo-Svm, Yefeng Jiao, Yan Wang, Zhicheng Ji

Journal of System Simulation

Abstract: To effectively predict the short-term wind power and its fluctuation range, a prediction method based on hybrid algorithm-optimized support vector machine is proposed. Exploratory data analysis is used to preprocess the original wind speed data to improve the data quality. Chaotic map, Levy flight strategy and particle swarm optimization are used to improve the ant lion algorithm. The support vector machine model optimized by hybrid algorithm is used to predict the wind power. The experimental results show that, compared with the new wind power prediction model, the prediction error of the output results of the method is lower, and …

Long-Term Resilience Simulation On Low-Carbon Urban Grid Based On Evolutionary Game, Zhengda Cui, Weiqiang Yao, Qin Xu, Chen Fang, Ying Chen

Journal of System Simulation

Abstract: Because of the more frequent extreme disasters, the resilience of urban grid becomes more important. In the background of carbon neutralization policy, the decarbonization transition of urban grid also affects the development of grid resilience. An evolutionary game is used to simulate the resilience evolution of low-carbon urban grid and the evolution model is constructed. The decision to install photovoltaic and energy storage system for residents and to upgrade the grid for resilience is considered in the model and the stability conditions of equilibriums of the evolutionary game are analyzed. The resilience evolution simulation model considering disaster stochasticity is …

Simulation-Driven Based Utility Evaluation And Recommendation Of Expressway Proactive Speed Limit, Geqi Qi, Sijin Liu, Yikang He, Meng Wang, Ailing Huang

Journal of System Simulation

Abstract: Outside the specific punishment area, the traditional roadside passive speed limit mode lacks traffic management, and thus which indirectly leads to the inconsistency or even sudden change of vehicle behaviors in time and space, thereby affects the traffic efficiency and safety. Focusing on the proactive speed limit mode at vehicle side, a utility evaluation and recommendation method is proposed, which carries out the multi-scenario traffic simulation for varied proactive and passive speed limit considering road line types, traffic flow and vehicle type proportion. From the two perspectives of safety and efficiency, the utility evaluation indicators and weights are extracted …

Simulation On Flood Disaster In Urban Building Complex System Based On Lbm, Shen Zhang, Zewang Yang, Yifan Wang, Liang Sun, Ming Cheng, Fankai Meng, Ting Li

Journal of System Simulation

Abstract: Because of the extreme climate change, the potential flood disaster risk in the southeast coastal areas of China can not be ignored. Based on lattice Boltzmann computational fluid dynamics method, a three-dimensional simulation study of waterlogging process in tsunami impact scenario is carried out for a coastal city building complex system, and the reliability and accuracy of the numerical simulation method for the flood impact test of an ideal building complex are verified. The results show that the buildings along rivers and coastlines have obvious cloaking effect, while the buildings inside the city are less affected by floods. The …

Research On Modeling And Simulation Technology Of Microwave Radar High Precision Tracking Loop, Jiaji Lou, Jing Ma, Xiaowei Li, Yue Zhao, Youbin Song

Journal of System Simulation

Abstract: Aiming at the key problem of high-precision tracking loop design of a measurement radar for the weak signal (low carrier to noise ratio signal) in dynamic environment, the design and optimization methods of carrier tracking loop and code tracking loop are focused on. A signal structure with a single carrier as a pilot is proposed, and the loop structure of the frequency-locked loop and the phase-locked loop working together is studied. The modeling and simulation on the two structures show that for the week signal tracking in a dynamic environment, the loop combination structure of the frequency-serial auxiliary …

Research On Parameter Construction Method Of Blue Army Equipment Model Based On A Deep Network, Boyuan Zhang, Guanghong Gong, Ze Wang, Ni Li

Journal of System Simulation

Abstract: The modeling of blue army equipment is an indispensable part of adversarial simulation environment construction. Aiming at the limited available parameters of "information-poor" and "small sample" characteristics to the blue system, a deep network-based method is proposed to generate the parameters of blue army equipment model. By injecting the information into the simulation model of the blue army equipment, the simulation data is generated and trained in the deep neural network. The obtained network has a certain generalization ability to the unknown parameters prediction of the same type of equipment and can be used directly in prediction or be …

Multi-Robot Path Planning Based On Cbs Algorithm, Qiao Qiao, Yan Wang, Zhicheng Ji

Journal of System Simulation

Abstract: Aiming at the long multi-robot planning path and long one-way search running time of conflict-based search(CBS) in the multi-agent path finding(MAPF), an improved CBS algorithm is proposed, which in a two-way A^* focus search is used to optimize the search direction and search method. The suboptimal factorωis introduced into the underlying search function of the CBS algorithm to improve the efficiency of path search. The one-way search in the conflict search algorithm is optimized to a two-way A^* search. The experimental results show that the path cost of the improved CBS algorithm is shortened …

Research On Emotional Contagion And Intervention Strategy Of Indoor Evacuation Based On Risk Perception, Yang Zeng, Jinling Li, Haixiang Guo, Weiming Chen

Journal of System Simulation

Abstract: Aiming at the panic emotion contagion in the indoor emergency evacuation with multi-exit and multi-obstacle, an emotional contagion model is constructed on personality traits, risk perception differences of age and gender, and consciousness regulation. The simulation is carried out by using AnyLogic, which combines individual emotions with evacuation speed to realize the real-time updating of emotional state and speed. That personnel intervention in the process of evacuation can effectively alleviate the spread of panic emotion, is verified and can provide the theoretical basis for panic contagion in the process of emergency evacuation. The results show that the degree of …

Research On Complex Combat Network Dynamic Evolution Based On Information Entropy, Lianyi Zhang, Xisheng Shen, Duzheng Qing, Han Zhang, Min Zhou, Xifu Wang

Journal of System Simulation

Abstract: Network-centric warfare, distributed and decentralized command and control gradually replace separately the traditional platform-centric warfare and centralized command and control, and information has become a combat capability. Based on the new information weapon equipment system operation loop, a complex combat network model based on information entropy is constructed, and the combat capability measurement method is proposed. On the basis of the combat capability upgrade being the network driving force, the dynamic evolution rule of the complex combat network is designed and the preferential evolution and stochastic evolution models are constructed. According to a typical system combat example, the influence …

Low Voltage Ride-Through Modeling For Wind Turbines Based On Neural Odes, Qiping Lai, Tannan Xiao, Dongsheng Li, Chen Shen

Journal of System Simulation

Abstract: Considering the difficulty of equivalent modeling of low voltage ride-through(LVRT) characteristics of a wind farm, a neural ordinary differential equation(ODE)-based wind farm LVRT modeling methodis proposed. The input of the model is the voltage and wind speed of each wind turbine at the grid connection point of wind farm, and the output is the current at the grid connection point. The model can better characterize the strong nonlinear switching process and describe LVRT characteristics of wind farms under different wind speed scenarios. A simulation example of a wind farm including three doubly-fed induction generators(DFIGs) is established on …

Simulation Research On Appearance Detection Of Ampoules Based On Lightweight Network And Model Compression, Zhihao Zhu, Yan Wang, Zhicheng Ji

Journal of System Simulation

Abstract: Aiming at the large scale and redundant parameters of target detection network model, which result in the difficult to deploy the ampoule bottle appearance defect detection model to edge devices, an LC-Faster R-CNN defect detection algorithm based on lightweight network and model compression is proposed. MobileNet-V2 is used as the backbone, and the redundant channels in the convolutional network are trimmed by model pruning strategy. The floating-point parameters are quantized into integers through saturation truncation mapping. Knowledge distillation is used to restore the accuracy of the compressed network. Tested on the self-built ampoule appearance defect dataset, the model volume …

Fast Generation Method Of Multi-Sensing Channel Fusion Virtual Experiment, Jingwei Deng, Hanwu He, Yueming Wu, Jianhao Su

Journal of System Simulation

Abstract: Aiming at the low development efficiency and single experience in traditional virtual experiments, a rapid generation method of multi-sensing channel fusion virtual experiment visualization is proposed. The experimental steps and sequence of experimental steps of the virtual experiment are defined. A parameterized description method of experimental elements based on Petri net is proposed to describe the sequence of experimental steps, which breaks through the constraints the established procedure steps of traditional virtual experiments and supports the exploratory virtual experiments. The visual expression method of the routing graph and the conversion method between the routing graph and the Petri …

Research On Iterative Calculation And Optimization Methods Of Aero-Engine On-Board Model, Xinghua Luo, Jia Geng, Ming Li, Bei Liu, Lei Wang, Zhiping Song

Journal of System Simulation

Abstract: Aeroengine is a complex and time-varying multivariable thermophysical system. The research on the convergence accuracy and rate of the component-level model is of great significance to the model-based engine health management, performance and fault-tolerant control. The existing engine component-level models are generally based on the traditional quasi-Newton method to solve the equilibrium equations simultaneously. Compared with the traditional Newton-Raphson method (N-R method), the convergence speed is optimized, but it is difficult to meet accuracy and real-time requirements of the dynamic model airborne applications within the full envelope. An adaptive variable step factor quasi-Newton method is proposed, which can reduce …

Reliability Parameter Optimization Complex System Simulation Based On R-Vikor Method, Zhiguang Wang, Baiting Liu, Xiaolei Wang, Tao Liu, Zhaowei Yang

Journal of System Simulation

Abstract: The operation of complex simulation system is not isolated, and always affected by multiple external factors and its own performance. In simulation reliability calculation, parameters need to be chosen, and different performance indexes need to be taken into account when comparing with the reference model. The research is transformed into the multi-attribute decision. An system simulation trusted parameter optimization method based on R-VIKOR(resist rank reversal of visekriterijumska optimizacija | kompromisno resenje) is proposed. Multiple sets of aerodynamic parameters of the new model are obtained through model migration theory, and similarity calculation is carried out with the optimal parameters of …