Sis-Based Modeling And Simulation Analysis On Exercise Benefit Perception Transmission,
2022
1.School of Management, Shandong University, Ji'nan 250100, China;
Sis-Based Modeling And Simulation Analysis On Exercise Benefit Perception Transmission, Lei Wang, Jinhai Sun, Tuojian Li
Journal of System Simulation
Abstract: In order to distinguish the relationship between individual health behavior change and collective health behavior emergence, deal with the challenges of mathematical description of typical health information dissemination processes in social networks and social experiments, SIS(susceptible-infected-susceptible)model is introduced to simulate the dissemination process of classical health information exercise effect perception to meet the requirements of social system complexity, individual diversity and intelligence. To carry out numerical experiments on the propagation process of exercise effect perception to identify the phase change process of the collective health behavior emergence, agent-based modeling and simulation are utilized through NetLogo. Experimental results show …
Research On Low Computational Predictive Control Strategy Of Three-Level Four-Arm Apf,
2022
School of Electrical Engineering and Automation, Jiangsu Normal University, Xuzhou 221116, China;
Research On Low Computational Predictive Control Strategy Of Three-Level Four-Arm Apf, Guifeng Wang, Jinxing Guo
Journal of System Simulation
Abstract: Four-arm active power filter(APF) is an ideal device to the power quality of three-phase four-wire distribution network. Owing to the sufficient number of base vectors, three-level four-arm APF has better current tracking performance, but the prediction calculation amount is too large when model predictive current control is applied. A model prediction voltage control strategy based on the idea of space stratification is proposed. Based on the deadbeat control idea and the discrete mathematical model in αβγ coordinate system, the expected reference voltage is predicted from the reference current, and the multiple current predictions are converted into the single voltage …
Computer Simulation Of The Light Absorption Band Of The Jumping Spider Isorhodopsin,
2022
Bowling Green State University
Computer Simulation Of The Light Absorption Band Of The Jumping Spider Isorhodopsin, Noah Zoldak
Honors Projects
In order to simulate the photoisomerization of the 9-cis Jumping Spider Isorhodopsin (JSiR-1) it is necessary to first simulate its light-absorption band. Here we report on the absorption band simulated using protein models constructed using the advanced Automatic Rhodopsin Modeling (a-ARM) program. A population of S0 models was created and the corresponding S0 to S1 transitions were determined for each member of the resulting population. The calculation resulted in a Gaussian plot showing that the wavelength of the absorption maximum of 560 nm (a violet color) that is consistent, but red-shifted, with respect the experimentally observed value.
Hydrogen Bonding In Small Model Peptides; The Dft And Mp2 Study,
2022
Kennesaw State University
Hydrogen Bonding In Small Model Peptides; The Dft And Mp2 Study, Gracie Smith, Martina Kaledin
Symposium of Student Scholars
Formamide is a small model compound for the study of the peptide bond. The peptide bond links amino acids together, specifies rigidity to the protein backbone, and includes the essential docking sites for hydrogen-bond-mediated protein folding and protein aggregation, namely, the C=O acceptor and the N-H donor parts. Therefore, the infrared C=O (amide-I) and N-H (amide-A) vibrations provide sensitive and widely used probes into the structure of peptides. This computational chemistry work, we study hydrogen bonds in formamide dimer isomers. We evaluate the accuracy of the density functional theory (DFT) and many-body perturbation theory to the 2nd order (MP2) …
Data-Driven Deep Learning-Based Analysis On Thz Imaging,
2022
University of Arkansas, Fayetteville
Data-Driven Deep Learning-Based Analysis On Thz Imaging, Haoyan Liu
Graduate Theses and Dissertations
Breast cancer affects about 12.5% of women population in the United States. Surgical operations are often needed post diagnosis. Breast conserving surgery can help remove malignant tumors while maximizing the remaining healthy tissues. Due to lacking effective real-time tumor analysis tools and a unified operation standard, re-excision rate could be higher than 30% among breast conserving surgery patients. This results in significant physical, physiological, and financial burdens to those patients. This work designs deep learning-based segmentation algorithms that detect tissue type in excised tissues using pulsed THz technology. This work evaluates the algorithms for tissue type classification task among freshly …
Probability Distributions Of The Scalar Potential,
2022
University at Albany, State University of New York
Probability Distributions Of The Scalar Potential, Candace Mathews
Legacy Theses & Dissertations (2009 - 2024)
In the study of cosmological inflation, string theory and supersymmetry have motivated a wide range of possible inflationary models. These models can be parameterized by a scalar potential V, which is a function of N scalar fields, and determines cosmological parameters such as the vacuum stability and energy density. In principle, we can determine V through high energy physics, such as string theory. In practice, though we may not know the details of V we might have clues about a distribution of plausible V’s, which we can build statistics on to further analyze. The purpose of this thesis defense is …
Turning Density Functional Theory Calculations Into Molecular Mechanics Simulations : Establishing The Fluctuating Density Model For Rna Nucleobases,
2022
University at Albany, State University of New York
Turning Density Functional Theory Calculations Into Molecular Mechanics Simulations : Establishing The Fluctuating Density Model For Rna Nucleobases, Christopher A. Myers
Legacy Theses & Dissertations (2009 - 2024)
Molecular mechanics (MD) simulations and density functional theory (DFT) have been the backbone of computational chemistry for decades. Due to its accuracy and computational feasibility, DFT has become the go-to method for theoretically predicting interaction energies, polarizability, and other electronic properties of small molecules at the quantum mechanical level. Although less fundamental than DFT, molecular mechanics (MM) algorithms have been just as influential in the fields of biology and chemistry, owing their success to the ability to compute measurable, macroscopic quantities for systems with tens of thousands to hundreds of thousands of atoms at a time. Nevertheless, MD simulations would …
Denoising And Deconvolving Sperm Whale Data In The Northern Gulf Of Mexico Using Fourier And Wavelet Techniques,
2022
University of New Orleans, New Orleans
Denoising And Deconvolving Sperm Whale Data In The Northern Gulf Of Mexico Using Fourier And Wavelet Techniques, Kendal Mccain Leftwich
LSU New Orleans Theses and Dissertations
The use of underwater acoustics can be an important component in obtaining information from the oceans of the world. It is desirable (but difficult) to compile an acoustic catalog of sounds emitted by various underwater objects to complement optical catalogs. For example, the current visual catalog for whale tail flukes of large marine mammals (whales) can identify even individual whales from their individual fluke characteristics. However, since sperm whales, Physeter microcephalus, do not fluke up when they dive, they cannot be identified in this manner. A corresponding acoustic catalog for sperm whale clicks could be compiled to identify individual …
Understanding Sentiment Through Context,
2022
Singapore Management University
Understanding Sentiment Through Context, Richard M.Crowley, M.H. Franco Wong
Research Collection School Of Accountancy
We examine whether empirical results using text-based sentiment of U.S. annual reports depend on the underlying context, within documents, from which sentiment is measured. We construct a clause-level measure of context, showing that sentiment is driven by many different contexts and that positive and negative sentiment are driven by different contexts. We then construct context-level sentiment measures and examine whether sentiment works as expected at the context-level across four prediction problems. Our results demonstrate that document-level sentiment exhibits significant noise in prediction and suggest that document-level aggregation of sentiment leads to missed empirical nuances. The contexts driving sentiment results vary …
Pacific: Towards Proactive Conversational Question Answering Over Tabular And Textual Data In Finance,
2022
Singapore Management University
Pacific: Towards Proactive Conversational Question Answering Over Tabular And Textual Data In Finance, Yang Deng, Wenqiang Lei, Wenxuan Zhang, Wai Lam, Tat-Seng Chua
Research Collection School Of Computing and Information Systems
To facilitate conversational question answering (CQA) over hybrid contexts in finance, we present a new dataset, named PACIFIC. Compared with existing CQA datasets, PACIFIC exhibits three key features: (i) proactivity, (ii) numerical reasoning, and (iii) hybrid context of tables and text. A new task is defined accordingly to study Proactive Conversational Question Answering (PCQA), which combines clarification question generation and CQA. In addition, we propose a novel method, namely UniPCQA, to adapt a hybrid format of input and output content in PCQA into the Seq2Seq problem, including the reformulation of the numerical reasoning process as code generation. UniPCQA performs multi-task …
Detecting Selfish Mining Attacks Against A Blockchain Using Machine Learing,
2022
University of South Alabama
Detecting Selfish Mining Attacks Against A Blockchain Using Machine Learing, Matthew A. Peterson
Graduate Theses and Dissertations (2019 - present)
Selfish mining is an attack against a blockchain where miners hide newly discovered blocks instead of publishing them to the rest of the network. Selfish mining has been a potential issue for blockchains since it was first discovered by Eyal and Sirer. It can be used by malicious miners to earn a disproportionate share of the mining rewards or in conjunction with other attacks to steal money from network users. Several of these attacks were launched in 2018, 2019, and 2020 with the attackers stealing as much as $18 Million. Developers made several different attempts to fix this issue, but …
Dronlomaly: Runtime Detection Of Anomalous Drone Behaviors Via Log Analysis And Deep Learning,
2022
Singapore Management University
Dronlomaly: Runtime Detection Of Anomalous Drone Behaviors Via Log Analysis And Deep Learning, Lwin Khin Shar, Wei Minn, Nguyen Binh Duong Ta, Jianli Fan, Lingxiao Jiang, Daniel Wai Kiat Lim
Research Collection School Of Computing and Information Systems
Drones are increasingly popular and getting used in a variety of missions such as area surveillance, pipeline inspection, cinematography, etc. While the drone is conducting a mission, anomalies such as sensor fault, actuator fault, configuration errors, bugs in controller program, remote cyber- attack, etc., may affect the drone’s physical stability and cause serious safety violations such as crashing into the public. During a flight mission, drones typically log flight status and state units such as GPS coordinates, actuator outputs, accelerator readings, gyroscopic readings, etc. These log data may reflect the above-mentioned anomalies. In this paper, we propose a novel, deep …
A Recommendation On How To Teach K-Means In Introductory Analytics Courses,
2022
Singapore Management University
A Recommendation On How To Teach K-Means In Introductory Analytics Courses, Manoj Thulasidas
Research Collection School Of Computing and Information Systems
We teach K-Means clustering in introductory data analytics courses because it is one of the simplest and most widely used unsupervised machine learning algorithms. However, one drawback of this algorithm is that it does not offer a clear method to determine the appropriate number of clusters; it does not have a built-in mechanism for K selection. What is usually taught as the solution for the K Selection problem is the so-called elbow method, where we look at the incremental changes in some quality metric (usually, the sum of squared errors, SSE), trying to find a sudden change. In addition to …
An Efficient Annealing-Assisted Differential Evolution For Multi-Parameter Adaptive Latent Factor Analysis,
2022
Chongqing University of Post and Telecommunications
An Efficient Annealing-Assisted Differential Evolution For Multi-Parameter Adaptive Latent Factor Analysis, Qing Li, Guansong Pang, Mingsheng Shang
Research Collection School Of Computing and Information Systems
A high-dimensional and incomplete (HDI) matrix is a typical representation of big data. However, advanced HDI data analysis models tend to have many extra parameters. Manual tuning of these parameters, generally adopting the empirical knowledge, unavoidably leads to additional overhead. Although variable adaptive mechanisms have been proposed, they cannot balance the exploration and exploitation with early convergence. Moreover, learning such multi-parameters brings high computational time, thereby suffering gross accuracy especially when solving a bilinear problem like conducting the commonly used latent factor analysis (LFA) on an HDI matrix. Herein, an efficient annealing-assisted differential evolution for multi-parameter adaptive latent factor analysis …
Mining Competitively-Priced Bundle Configurations,
2022
Singapore Management University
Mining Competitively-Priced Bundle Configurations, Ezekiel Ong Young, Hady W. Lauw
Research Collection School Of Computing and Information Systems
We examine the bundle configuration problem in the presence of competition. Given a competitor's bundle configuration and pricing, we determine what to bundle together, and at what prices, to maximize the target firm's revenue. We highlight the difficulty in pricing bundles and propose a scalable alternative and an efficient search heuristic to refine the approximate prices. Furthermore, we extend the heuristics proposed by previous work to accommodate the presence of a competitor. We analyze the effectiveness of our proposed models through experimentation on real-life ratings-based preference data.
Innovative And Effective Spreadsheet Tool For Learning Sentiment Analysis And Prediction,
2022
Singapore Management University
Innovative And Effective Spreadsheet Tool For Learning Sentiment Analysis And Prediction, Michelle L. F. Cheong, Jean Yun-Chen Chen
Research Collection School Of Computing and Information Systems
In this paper, we describe a spreadsheet tool which was developed and implemented to teach sentiment analysis and prediction to university students who are less technically inclined. We adopted the “Use-Modify-Create” cycle to ensure that the students learn the computing concepts and practices in a progressive and active learning manner, and we evaluated the effectiveness of the tool using the Learning Object Evaluation Scale for Students (LOES-S). The evaluation shows that our tool performed well in terms of quality, learn and engagement constructs, and our paired T-test shows strong evidence that, on average, the course module with the tool does …
A Unified Dialogue User Simulator For Few-Shot Data Augmentation,
2022
Tsinghua University
A Unified Dialogue User Simulator For Few-Shot Data Augmentation, Dazhen Wan, Zheng Zhang, Qi Zhu, Lizi Liao, Minlie Huang
Research Collection School Of Computing and Information Systems
Pre-trained language models have shown superior performance in task-oriented dialogues. However, existing datasets are on limited scales, which cannot support large-scale pre-training. Fortunately, various data augmentation methods have been developed to augment largescale task-oriented dialogue corpora. However, they heavily rely on annotated data in the target domain, which require a tremendous amount of data collection and human labeling work. In this paper, we build a unified dialogue user simulation model by pre-training on several publicly available datasets. The model can then be tuned on a target domain with fewshot data. The experiments on a target dataset across multiple domains show …
Conreader: Exploring Implicit Relations In Contracts For Contract Clause Extraction,
2022
Singapore Management University
Conreader: Exploring Implicit Relations In Contracts For Contract Clause Extraction, Weiwen Xu, Yang Deng, Wenqiang Lei, Wenlong Zhao, Tat-Seng Chua, Wai Lam
Research Collection School Of Computing and Information Systems
We study automatic Contract Clause Extraction (CCE) by modeling implicit relations in legal contracts. Existing CCE methods mostly treat contracts as plain text, creating a substantial barrier to understanding contracts of high complexity. In this work, we first comprehensively analyze the complexity issues of contracts and distill out three implicit relations commonly found in contracts, namely, 1) Long-range Context Relation that captures the correlations of distant clauses; 2) Term-Definition Relation that captures the relation between important terms with their corresponding definitions; and 3) Similar Clause Relation that captures the similarities between clauses of the same type. Then we propose a …
Contribution Rate Calculation Method To System-Of-Systems Based On Interval-Valued Intuitionistic Fuzzy Number Anp,
2022
1.School of Software Engineering, South China University of Technology, Guangzhou 510006, China;
Contribution Rate Calculation Method To System-Of-Systems Based On Interval-Valued Intuitionistic Fuzzy Number Anp, Zejian Ding, Songtao Sun, Zhiwen He, Fei Liu
Journal of System Simulation
Abstract: Contribution rate to system-of-systems (CRSoS) is mainly used to measure the contribution of an equipment to system of systems (SoS) in system construction. In order to solve some problems in the calculation of CRSoS, a multi-level equipment indicator architecture of "task-ability-indicator- equipment" is proposed. At the same time, considering the characteristics of the equipment indicator architecture, ANP (analytic network process) and IVIFN (interval-valued intuitionistic fuzzy number), a IVIF-ANP calculation method is proposed to obtain more accurate CRSoS. Experiments show that this method can not only solve the problem of the calculation formula of CRSoS, but also obtain more …
Simulation And Effectiveness Evaluation System For Joint Delivery Mission Planning Of Airlift Fleets,
2022
The First Aircraft Institute of Aviation Industry Corporation of China, Xi’an 710089, China;
Simulation And Effectiveness Evaluation System For Joint Delivery Mission Planning Of Airlift Fleets, Guochen Wang
Journal of System Simulation
Abstract: Airlift fleet plays an important role in modern war. Compared with other countries such as the USA and Russia, China's airlift fleet still has obvious shortcomings and deficiencies. To analysis and optimize the future fleet alternatives, a software tool is established with the modules of model construction and management, scenarios editing, mission planning, simulation deduction, effectiveness analysis. This tool mainly focuses on the interactive relationship between the transport aircraft and cargo, airport and so on, as well as the cooperative relationship of different types of aircraft, which can realize the functions of automatic generation of loading schemes, automatic planning …
