Numerical Analysis and Scientific Computing Commons^™

Verifying Empirical Predictive Modeling Of Societal Vulnerability To Hazardous Events: A Monte Carlo Experimental Approach, Yi Victor Wang, Seung Hee Kim, Menas C. Kafatos

Institute for ECHO Articles and Research

With the emergence of large amounts of historical records on adverse impacts of hazardous events, empirical predictive modeling has been revived as a foundational paradigm for quantifying disaster vulnerability of societal systems. This paradigm models societal vulnerability to hazardous events as a vulnerability curve indicating an expected loss rate of a societal system with respect to a possible spectrum of intensity measure (IM) of an event. Although the empirical predictive models (EPMs) of societal vulnerability are calibrated on historical data, they should not be experimentally tested with data derived from field experiments on any societal system. Alternatively, in this paper, …

Gsprint23/Congressionaltwitternetwork: Data In Brief Article, Gina Sprint

Computer Science Faculty Scholarship

This repository stores the accompanying code and data for the weighted, bidirectional graph (henceforth referred to as a "Twitter Influence Network" graph) presented in the research papers 1. Fink et. al "A centrality measure for quantifying spread on weighted, directed networks" Physica A, 2023 (DOI link: https://doi.org/10.1016/j.physa.2023.129083) and 2. Fink et. al "A Congressional Twitter network dataset quantifying pairwise probability of influence" Data in Brief (https://doi.org/10.1016/j.dib.2023.109521 or https://repository.gonzaga.edu/physicsschol/2). This graph represents the how information flows in a network of US Congress members. Tweets from these members span the date range between February 9, 2022, and June 9, …

Application Of Machine Learning Algorithms For Elucidation Of Biological Networks From Time Series Gene Expression Data, Krupa Nagori

Computational and Data Sciences (PhD) Dissertations

This dissertation provides a deep dive into understanding gene expression, interaction, regulation, and the intricate mechanisms behind heliotropism and phototropism. Additionally, the research accentuates the significance of machine learning techniques, specifically for gene regulatory networks (GRNs).

Chapter 1 offers an exhaustive benchmarking of GRN methodologies, furthering our comprehension of machine-learning models relevant to GRNs. The evaluation revealed that GRNTE, SWING, and BiXGBoost emerged as top-performing methods in GRN inference. The suitability of these models varies depending on specific research criteria such as computational needs, dataset dimensions, and performance metric emphasis. An innovation of this chapter was the introduction of Colab …

Epileptic Seizure Classification Using Image-Based Data Representation, Amber Surles

Graduate Theses and Dissertations (2019 - present)

Epilepsy is a recurrence of seizures caused by a disorder of the brain in over 3.4 million people nationwide. Some people are able to predict their seizures based off prodrome, which is an early sign or symptom that usually resembles mood changes or a euphoric feeling even days to an hour before occurrence. Consequently, the natural instincts of the body to react to an upcoming attack lends credence to the existence of a pre-ictal state that precedes seizure episodes. Physicians and researchers have thus sought for an automated approach for predicting or detecting seizures.

In this research, we evaluate the …

Knowledge Representation For Conceptual, Motivational, And Affective Processes In Natural Language Communication, Seng Beng Ho, Zhaoxia Wang, Boon-Kiat Quek, Erik Cambria

Research Collection School Of Computing and Information Systems

Natural language communication is an intricate and complex process. The speaker usually begins with an intention and motivation of what is to be communicated, and what outcomes are expected from the communication, while taking into consideration the listener’s mental model to concoct an appropriate sentence. Likewise, the listener has to interpret the speaker’s message, and respond accordingly, also with the speaker’s mental model in mind. Doing this successfully entails the appropriate representation of the conceptual, motivational, and affective processes that underlie language generation and understanding. Whereas big-data approaches in language processing (such as chatbots and machine translation) have performed well, …

Mastering Stock Markets With Efficient Mixture Of Diversified Trading Experts, Shuo Sun, Xinrun Wang, Wanqi Xue, Xiaoxuan Lou, Bo An

Research Collection School Of Computing and Information Systems

Quantitative stock investment is a fundamental financial task that highly relies on accurate prediction of market status and profitable investment decision making. Despite recent advances in deep learning (DL) have shown stellar performance on capturing trading opportunities in the stochastic stock market, the performance of existing DL methods is unstable with sensitivity to network initialization and hyperparameter selection. One major limitation of existing works is that investment decisions are made based on one individual neural network predictor with high uncertainty, which is inconsistent with the workflow in real-world trading firms. To tackle this limitation, we propose AlphaMix, a novel three-stage …

Evolve Path Tracer: Early Detection Of Malicious Addresses In Cryptocurrency, Ling Cheng, Feida Zhu, Yong Wang, Ruicheng Liang, Huiwen Liu

Research Collection School Of Computing and Information Systems

With the boom of cryptocurrency and its concomitant financial risk concerns, detecting fraudulent behaviors and associated malicious addresses has been drawing significant research effort. Most existing studies, however, rely on the full history features or full-fledged address transaction networks, both of which are unavailable in the problem of early malicious address detection and therefore failing them for the task. To detect fraudulent behaviors of malicious addresses in the early stage, we present Evolve Path Tracer, which consists of Evolve Path Encoder LSTM, Evolve Path Graph GCN, and Hierarchical Survival Predictor. Specifically, in addition to the general address features, we propose …

Crowdfl: Privacy-Preserving Mobile Crowdsensing System Via Federated Learning, Bowen Zhao, Ximeng Liu, Wei-Neng Chen, Robert H. Deng

Research Collection School Of Computing and Information Systems

As an emerging sensing data collection paradigm, mobile crowdsensing (MCS) enjoys good scalability and low deployment cost but raises privacy concerns. In this paper, we propose a privacy-preserving MCS system called CROWDFL by seamlessly integrating federated learning (FL) into MCS. At a high level, in order to protect participants' privacy and fully explore participants' computing power, participants in CROWDFL locally process sensing data via FL paradigm and only upload encrypted training models to the server. To this end, we design a secure aggregation algorithm (SecAgg) through the threshold Paillier cryptosystem to aggregate training models in an encrypted form. Also, to …

Enhanced Quantum Chemistry With Machine Learning, Brock Dyer

Physics and Astronomy Summer Fellows

This file is a catalogue of the relevant quantum mechanical and computer programming topics that I learned during the summer which will be helping me to generate an artificial intelligence that will be able to perform computational chemical calculations at a much faster rate and comparable or better accuracy than current methods.

Interposition Based Container Optimization For Data Intensive Applications, Rohan Tikmany

College of Computing and Digital Media Dissertations

Reproducibility of applications is paramount in several scenarios such as collaborative work and software testing. Containers provide an easy way of addressing reproducibility by packaging the application's software and data dependencies into one executable unit, which can be executed multiple times in different environments. With the increased use of containers in industry as well as academia, current research has examined the provisioning and storage cost of containers and has shown that container deployments often include unnecessary software packages. Current methods to optimize the container size prune unnecessary data at the granularity of files and thus make binary decisions. We show …

Beyond Anthropomorphism: Unraveling The True Priorities Of Chatbot Usage In Smes, Tamas Makany, Sungjong Roh, Kotaro Hara, Jie Min Hua, Felicia Si Ying Goh, Wilson Yang Jie Teh

Research Collection Lee Kong Chian School Of Business

This study examined business communication practices with chatbots among various Small and Medium Enterprise (SME) stakeholders in Singapore, including business owners/employees, customers, and developers. Through qualitative interviews and chatbot transcript analysis, we investigated two research questions: (1) How do the expectations of SME stakeholders compare to the conversational design of SME chatbots? and (2) What are the business reasons for SMEs to add human-like features to their chatbots? Our findings revealed that functionality is more crucial than anthropomorphic characteristics, such as personality and name. Stakeholders preferred chatbots that explicitly identified themselves as machines to set appropriate expectations. Customers prioritized efficiency, …

Multi-View Hypergraph Contrastive Policy Learning For Conversational Recommendation, Sen Zhao, Wei Wei, Xian-Ling Mao, Shuai: Yang Zhu, Zujie Wen, Dangyang Chen, Feida Zhu, Feida Zhu

Research Collection School Of Computing and Information Systems

Conversational recommendation systems (CRS) aim to interactively acquire user preferences and accordingly recommend items to users. Accurately learning the dynamic user preferences is of crucial importance for CRS. Previous works learn the user preferences with pairwise relations from the interactive conversation and item knowledge, while largely ignoring the fact that factors for a relationship in CRS are multiplex. Specifically, the user likes/dislikes the items that satisfy some attributes (Like/Dislike view). Moreover social influence is another important factor that affects user preference towards the item (Social view), while is largely ignored by previous works in CRS. The user preferences from these …

Machine-Learning Approach To Automated Doubt Identification On Stack Overflow Comments To Guide Programming Learners, Tianhao Chen, Eng Lieh Ouh, Kar Way Tan, Siaw Ling Lo

Research Collection School Of Computing and Information Systems

Stack Overflow is a popular Q&A platform for developers to find solutions to programming problems. However, due to the varying quality of user-generated answers, there is a need for ways to help users find high-quality answers. While Stack Overflow's community-based approach can be effective, important technical aspects of the answer need to be captured, and users’ comments might contain doubts regarding these aspects. In this paper, we showed the feasibility of using a machine learning model to identify doubts and conducted data analysis. We found that highly reputed users tend to raise more doubts; most answers have doubt in the …

Do-Good: Towards Distribution Shift Evaluation For Pre-Trained Visual Document Understanding Models, Jiabang He, Yi Hu, Lei Wang, Xing Xu, Ning Liu, Hui Liu

Research Collection School Of Computing and Information Systems

Numerous pre-training techniques for visual document understanding (VDU) have recently shown substantial improvements in performance across a wide range of document tasks. However, these pre-trained VDU models cannot guarantee continued success when the distribution of test data differs from the distribution of training data. In this paper, to investigate how robust existing pre-trained VDU models are to various distribution shifts, we first develop an out-of-distribution (OOD) benchmark termed Do-GOOD for the fine-Grained analysis on Document image-related tasks specifically. The Do-GOOD benchmark defines the underlying mechanisms that result in different distribution shifts and contains 9 OOD datasets covering 3 VDU related …

A Data-Driven Approach For Scheduling Bus Services Subject To Demand Constraints, Brahmanage Janaka Chathuranga Thilakarathna, Thivya Kandappu, Baihua Zheng

Research Collection School Of Computing and Information Systems

Passenger satisfaction is extremely important for the success of a public transportation system. Many studies have shown that passenger satisfaction strongly depends on the time they have to wait at the bus stop (waiting time) to get on a bus. To be specific, user satisfaction drops faster as the waiting time increases. Therefore, service providers want to provide a bus to the waiting passengers within a threshold to keep them satisfied. It is a two-pronged problem: (a) to satisfy more passengers the transport planner may increase the frequency of the buses, and (b) in turn, the increased frequency may impact …

Optical Response Of 3d Model Topological Nodal-Line Semimetal, Sita Kandel, Godfrey Gumbs, Oleg L. Berman

Publications and Research

Wepresent a semi-analytical expression for both longitudinal and transverse optical conductivities of a model TNLSM employing the Kubo formula with emphasis on the optical spectral weight redistribution, deduced from appropriate Green’s func tions. In this semimetal, the conduction and valence bands cross each other along a one- dimensional curve protected by certain symmetry group in the 3D Brillouin zone. Although the crossing cannot be removed by any perturbations, it can be adjusted by continuous tuning of the Hamiltonian with a parameter α. When α>0, the two bands cross each other near the Γ point in the (kx,ky) plane of …

Opto-Mechanical-Thermal Coupling Analysis Method And Implementation Of High-Precision Optical System, Liang Zhao, Zhigang Zhang, Yao Sun

Journal of System Simulation

High-precision optical system is easy to be affected by space environment. Under the condition of high temperature, structural load, etc., the image quality of the optical system becomes poor, and the opto-mechanical-thermal coupling analysis is needed. Due to the independent development of the optical simulation, structure simulation, thermal simulation and others, the simulation data can not be effectively coupled and transferred.An interdisciplinary coupling analysis method is proposed, in which the integrated analysis idea is adopted and the polynomial fitting is used as the interface to solve the irregular deformation of optical element surface. Through the implement of the best …

Research And Development Of Immersive Aero-Engine Scene Simulation System, Shun Yao, Zhongzhi Hu, Wenyu Cao, Jiali Yang

Journal of System Simulation

The research and development of aero-engines has the characteristics of high precision and interdiscipline. In order to reduce communication costs and to display the engine structure and the state of semi-physical simulator, by applying virtual reality technology,an immersive scene simulation system is built. By studying CAD data lightweight technology and physics-based real-time rendering technology,a rendering optimization method for similar object dynamic batching is proposed, which effectively improves the rendering frame rate. A dynamic parallax adjustment algorithm is proposed to solve the problem of dizziness when having a close look to stereoscopic images. The system achieves the …

Point Cloud Surface Matching Method Based On Precise Matching Of Critical Point, Xiaojuan Ning, Chunxu Li, Jiahao Wang, Jing Tang, Yinghui Wang, Haiyan Jin

Journal of System Simulation

To solve the low matching efficiency and insufficient accuracy of feature-based point cloud surface matching method during critical point matching, a point cloud surface matching method based on the pairing exaction of critical points is proposed.An improved 3D scale-invariant feature transform(3D-SIFT) algorithm based on curvature information is presented to extract the critical points. Fast point feature histograms(FPFH) feature, the angle between the vector from the center to critical points and the principal direction of the model are taken as the constraints to obtain the exact critical point matching point pair set. The initial matching of the model surface is …

Agent-Based Ecosystem Simulation Research Under Forest Fire, Ying Li, Nisuo Du, Zhi Ouyang

Journal of System Simulation

An Agent-based multi-species simulation model under forest fireis proposed to study the effect of forest fire on the balance of animal species population.By abstracting elements of each type of species and fire in the forest fire process as agents, the attributes and behavior rules of each type of agents according to the real characteristics of each type of species and forest fire are refined. ABM model is used to show the characteristics of multi-agent interaction in complex systems, and construct a multi-species forest ecological model and a forest fire model. On the basis of validating the rationality of …

Semantic Segmentation Model Based On Adaptive Fusion And Attention Refinement, Yun Wei, Qi Luo, Yingzhi Zhao

Journal of System Simulation

Aiming at the insufficient use of context information and loss of detail information of the existing semantic segmentation, a model based on adaptive fusion and attention refinement is proposed.The model introduces an adaptive fusion module in the process of coding, and solves the insufficient use of context information by fusing each feature map according to the corresponding weight. An attention thinning module is designed in the process of decoding, so that the low-order features and high-order features can guide and optimize each other to solve the loss of detail information.The experimental results show that the average intersection union …

Multi-Robot Formation Control Based On Improved Virtual Spring Model, Yimei Chen, Xiaofan Shi, Baoquan Li

Journal of System Simulation

Aiming at multi-robot system being difficult to avoid obstacles and maintain formation in unknown environment, a cooperative formation obstacle avoidance control algorithm based on the improved virtual spring model is proposed.The virtual spring model is introduced on the basis of leader-follower formation approach, which solves the problems of easy touch and out of formation. The attractive elastic force formula between the robot and the target point is established, and the virtual spring model of the obstacle with adjustable damping is designed to complete the obstacle avoidance behavior of robot. Aiming at some complex concave obstacles, the concept of additional …

Learning Variable Neighborhood Search Algorithm For Transportation-Assembly Collaborative Optimization Problem, Tengfei Zhang, Rong Hu, Bin Qian, Lü Yang

Journal of System Simulation

Aiming at transportation-assembly collaborative optimization problems,an integer programming model is established, and a learning variable neighborhood search with decomposition strategy (LVNS_DS) is proposed. To reduce the difficulty of solving the problem, a decomposition strategy is designed to decompose the original problem into a path planning problem and an assembly line balance problem. LVNS is used to solve the two subproblems, and the subproblem solutions are merged to obtain the complete solution of the original problem.Compared with the conventional VNS, LVNS transforms the neighborhood structure according to the neighborhood action probability value, and dynamically updates the probability value according …

Fault Indicator Configuration Optimization Based On Cooperative Game Particle Swarm Algorithm, Xu Wang, Weidong Ji, Guohui Zhou

Journal of System Simulation

In order to balance the reliability and economy of distribution network fault indicator, a multispace cooperative game particle swarm optimization algorithm is proposed. Based on the idea of population space grouping, the population activity space is adaptively divided, the particle game evolution in subspace is achieved, and the game calculation of particle fusion cosine similar reverse strategy is carried out, which well balances the convergence and diversity of the algorithm. The simulation results show that the adaptive multi-space division of population is conducive to jumping out of the local extreme value, and the game calculation integrating cosine similar reverse is …

Ar-Assisted Sign Language Letter Recognition Method Based On Improved Mobilenet Network, Chunhong Liu, Song Wang, Fupan Wang, Wensheng Tang, Yunqiang Pei, Dongsheng Tian, Yadong Wu

Journal of System Simulation

An AR-assisted sign language letter recognition algorithm MS-MobileNet is proposed for the problems of sign language gestures needing to be standardized and low recognition rate. A multi-scale convolution module is designed to extract the low-level features and enhance the feature extraction ability. ELU activation function is used to retain the negative feature information, which combined with a lightweight MobileNet model for the web to improve the recognition accuracy and real-time performance for mobile AR applications. Test results show that compared with the original model, the recognition accuracy of MS-MobileNet on the datasets ASL-M, NUS-II and Creative Senz3D is improved by …

Evolution Analysis Of Manufacturing Supply Chain Layout Considering Import Tax Burden And Customs Clearance Delay, Wuqiang Li

Journal of System Simulation

For foreign suppliers located in the special customs supervision area of free trade zone (FTZ), they can avoid the import tax burden of the remaining inventory can be avoided, but the import clearance may affect the timeliness of supply.Considering the widespread application of pull production, evolutionary game is introduced to study the influence of import tax burden and customs clearance delay on supply chain layout in FTZ. Three evolutionary stability strategies (ESS) are researched, which can be determined by the three conditions constructed by the import tax burden and customs clearance delay. The impact of import tax burden …

Summary Of Simulation Technology And Its Application In Training Field, Zhiming Qiu, Heng Li, Yufang Zhou, Duzheng Qing

Journal of System Simulation

High-tech weapons operations and battlefield environment become more and more increasingly sophisticated. It is an effective way to resolve the conflicts between huge equipment training cost and limited resources and improve training quality by building networked systematic and intelligent simulation training equipment and system and conducting systematic countermeasure simulation training based on present simulation technologies and training resources. The current situation and trend of the development of system architecture of simulation simulation modeling enemy simulation information system simulation etc are evaluated and summarized. It initially analyses the application and efficacy on the US Navy's normalized training environment typical systems such …

Application Of Digital Twin In Digital Transformation Of Thermal Power Units, Ze Dong, Wei Jiang, Xiaoyan Wang, Lei Liu

Journal of System Simulation

A new state estimation algorithm is proposed to improve the accuracy to obtain the optimal state estimation of distribution network against FDI attack. In the case of phasor measurement units being attacked and the measurement results being alteredthe optimal Kalman estimate can be decomposed into a weighted sum of local state estimates. Focusing on the insecurity of the weighted sum methoda convex optimization based on local estimation is proposed to replace the method and combine the local estimation into a secure state estimation. The simulation results show that the proposed estimator is consistent with the Kalman …

Simulation Research On Cooperative Control For Aircraft Ground Deicing Operation, Liwen Wang, Biao Li, Zhiwei Xing, Guan Lian

Journal of System Simulation

Aiming at the weak cooperation and low efficiency in aircraft ground deicing operation,a cooperative control method for deicing operations is designed based on the consistency of information states.A two-stage deicing Agent model is proposed and a multi-objective collaborative optimization model with the best deicing effect and the shortest deicing time is established. Lagrangian relaxation algorithm is applied to construct a feasible solution for the optimal operating parameters. Combined with the deicing process and mode, the cooperative graph of deicing operation is studied based on the operating topology, and the cooperative control method of ground deicing is constructed …

Dynamic Simulation Of Urban Agglomeration Passenger Transport Network Vulnerability Based On Multi-Agent, Chengbing Li, Yunfei Li, Peng Wu

Journal of System Simulation

Research on vulnerability of comprehensive passenger transportation network in urban agglomerations helps to ensure the transportation efficiency of intercity travel.A comprehensive passenger transport network model of urban agglomeration is built based on multi-layer complex network theory. Urban transportation transfer factors are considered, actual passenger flow is used to calibrate the station load and capacity and a dynamic model of network cascading failure is constructed. Multi-agents are used to simulate the actual passenger flow, Dijkstra algorithm is used to find the shortest path, and two time-dimensional vulnerability evaluation indicators are proposed.MATLAB is used to carry out the dynamic simulation …