Numerical Analysis and Scientific Computing Commons^™

Rollmatch: An R Package For Rolling Entry Matching, Kasey Jones, Rob Chew, Allison Witman, Yiyan Liu

The R Journal

The gold standard of experimental research is the randomized control trial. However, interventions are often implemented without a randomized control group for practical or ethical reasons. Propensity score matching (PSM) is a popular method for minimizing the effects of a randomized experiment from observational data by matching members of a treatment group to similar candidates that did not receive the intervention. Traditional PSM is not designed for studies that enroll participants on a rolling basis and does not provide a solution for interventions in which the baseline and intervention period are undefined in the comparison group. Rolling Entry Matching (REM) …

Editorial, Michael J. Kane

The R Journal

On behalf of the editorial board, I am pleased to present Volume 11, Issue 2 of the R Journal and my first issue as the Editor in Chief. This year, both Colin Gillespie and Catherine Healey join the Editorial Board, and Norm Matloff will rotate out. The R Journal continues to see increases in impact and popularity and this year we plan on making advances to better serve the community and streamline the publishing process to meet the increase in submissions we have seen over the last few years.

Dr4pl: A Stable Convergence Algorithm For The 4 Parameter Logistic Model, Hyowon An, Justin T. Landis, Aubrey G. Bailey, James S. Marron, Dirk P. Dittmer

The R Journal

The 4 Parameter Logistic (4PL) model has been recognized as a major tool to analyze the relationship between doses and responses in pharmacological experiments. A main strength of this model is that each parameter contributes an intuitive meaning enhancing interpretability of a fitted model. However, implementing the 4PL model using conventional statistical software often encounters numerical errors. This paper highlights the issue of convergence failure and presents several causes with solutions. These causes include outliers and a non-logistic data shape, so useful remedies such as robust estimation, outlier diagnostics and constrained optimization are proposed. These features are implemented in a …

Associative Classification In R: Arc, Arulescba, And Rcba, Michael Hahsler, Ian Johnson, Tomáš Kliegr, Jaroslav Kuchař

The R Journal

Several methods for creating classifiers based on rules discovered via association rule mining have been proposed in the literature. These classifiers are called associative classifiers and the best-known algorithm is Classification Based on Associations (CBA). Interestingly, only very few implementations are available and, until recently, no implementation was available for R. Now, three packages provide CBA. This paper introduces associative classification, the CBA algorithm, and how it can be used in R. A comparison of the three packages is provided to give the potential user an idea about the advantages of each of the implementations. We also show how the …

Convergenceclubs: A Package For Performing The Phillips And Sul's Club Convergence Clustering Procedure, Roberto Sichera, Pietro Pizzuto

The R Journal

This paper introduces package ConvergenceClubs, which implements functions to perform the Phillips and Sul (2007, 2009) club convergence clustering procedure in a simple and reproducible manner. The approach proposed by Phillips and Sul to analyse the convergence patterns of groups of economies is formulated as a nonlinear time varying factor model that allows for different time paths as well as individual heterogeneity. Unlike other approaches in which economies are grouped a priori, it also allows the endogenous determination of convergence clubs. The algorithm, usage, and implementation details are discussed.

R News, R Core Team

The R Journal

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The Idspatialstats R Package: Quantifying Spatial Dependence Of Infectious Disease Spread, John R. Giles, Henrik Salje, Justin Lessler

The R Journal

Spatial statistics for infectious diseases are important because the spatial and temporal scale over which transmission operates determine the dynamics of disease spread. Many methods for quantifying the distribution and clustering of spatial point patterns have been developed (e.g. K-function and pair correlation function) and are routinely applied to infectious disease case occurrence data. However, these methods do not explicitly account for overlapping chains of transmission and require knowledge of the underlying population distribution, which can be limiting when analyzing epidemic case occurrence data. Therefore, we developed two novel spatial statistics that account for these effects to estimate: 1) …

Time Series Forecasting With Knn In R: The Tsfknn Package, Francisco Martínez, María P. Frías, Francisco Charte, Antonio J. Rivera

The R Journal

In this paper the tsfknn package for time series forecasting using k-nearest neighbor regression is described. This package allows users to specify a KNN model and to generate its forecasts. The user can choose among different multi-step ahead strategies and among different functions to aggregate the targets of the nearest neighbors. It is also possible to assess the forecast accuracy of the KNN model.

Bondvaluation: An R Package For Fixed Coupon Bond Analysis, Wadim Djatschenko

The R Journal

t The purpose of this paper is to introduce the R package BondValuation for the analysis of large datasets of fixed coupon bonds. The conceptual heterogeneity of fixed coupon bonds traded in the global markets imposes a high degree of complexity on their comparative analysis. Contrary to baseline fixed income theory, in practice, most bonds feature coupon period irregularities. In addition, there are a multitude of day count methods that determine the interest accrual, the cash flows and the discount factors used in bond valuation. Several R packages, e.g., fBonds, RQuantLib, and YieldCurve, provide tools for fixed income analysis. Nevertheless, …

Informing Field Management Decisions To Enhance Alfalfa Seed Production Using Remote Sensing, Thomas V. Van Der Weide

Boise State University Theses and Dissertations

The development rate of alfalfa seed crop depends on both environmental conditions and management decisions. Crop management decisions, such as determining when to release pollinators to optimize pollination, can be informed by the identification of plant development stages from remote sensing data. I first identify what electromagnetic wavelengths are sensitive to alfalfa plant development stages using hyperspectral data. A Random Forest regression is used to determine the best Vegetation Index (VI) to monitor how much of the plant is covered in flower. The results indicate that Blue, Green, and Near-Infrared are the important electromagnetic wavelengths for the VI. Imagery collected …

Sentiment Analysis, Quantification, And Shift Detection, Kevin Labille

Graduate Theses and Dissertations

This dissertation focuses on event detection within streams of Tweets based on sentiment quantification. Sentiment quantification extends sentiment analysis, the analysis of the sentiment of individual documents, to analyze the sentiment of an aggregated collection of documents. Although the former has been widely researched, the latter has drawn less attention but offers greater potential to enhance current business intelligence systems. Indeed, knowing the proportion of positive and negative Tweets is much more valuable than knowing which individual Tweets are positive or negative. We also extend our sentiment quantification research to analyze the evolution of sentiment over time to automatically detect …

Contrasting Geometric Variations Of Mathematical Models Of Self-Assembling Systems, Michael Sharp

Graduate Theses and Dissertations

Self-assembly is the process by which complex systems are formed and behave due to the interactions of relatively simple units. In this thesis, we explore multiple augmentations of well known models of self-assembly to gain a better understanding of the roles that geometry and space play in their dynamics. We begin in the abstract Tile Assembly Model (aTAM) with some examples and a brief survey of previous results to provide a foundation. We then introduce the Geometric Thermodynamic Binding Network model, a model that focuses on the thermodynamic stability of its systems while utilizing geometrically rigid components (dissimilar to other …

Clustering Models For Topic Analysis In Graduate Discussion Forums, Mallika Gokarn Nitin, Swapna Gottipati, Venky Shankararaman

Research Collection School Of Computing and Information Systems

Discussion forums provide the base content for creating a knowledge repository. It contains discussion threads related to key course topics that are debated by the students. In order to better understand the student learning experience, the instructor needs to analyse these discussion threads. This paper proposes the use of clustering models and interactive visualizations to conduct a qualitative analysis of graduate discussion forums. Our goal is to identify the sub-topics and topic evolutions in the discussion forums by applying text mining techniques. Our approach generates insights into the topic analysis in the forums and discovers the students’ cognitive understanding within …

Tracking Political Events In Social Media: A Case Study Of Hong Kong Protests, Haodi Qi, Hanyu Jiang, Wende Bu, Chengzi Zhang, Kyong Jin Shim

Research Collection School Of Computing and Information Systems

In this study, we analyze social conversations about Hong Kong Protests, a series of events that were widely seen and debated in social media in 2019. Our system collects data from Twitter and Reddit using their APIs. It performs sentiment analysis, and the analysis results show changes in public sentiment around major events. Social network analysis reveals influencers - users that are in the center of social conversations. Our interactive Tableau dashboard allows the user to easily monitor live social conversations about Hong Kong protests.

Learning To Self-Train For Semi-Supervised Few-Shot Classification, Xinzhe Li, Qianru Sun, Yaoyao Liu, Shibao Zheng, Qin Zhou, Tat-Seng Chua, Bernt Schiele

Research Collection School Of Computing and Information Systems

Few-shot classification (FSC) is challenging due to the scarcity of labeled training data (e.g. only one labeled data point per class). Meta-learning has shown to achieve promising results by learning to initialize a classification model for FSC. In this paper we propose a novel semi-supervised meta-learning method called learning to self-train (LST) that leverages unlabeled data and specifically meta-learns how to cherry-pick and label such unsupervised data to further improve performance. To this end, we train the LST model through a large number of semi-supervised few-shot tasks. On each task, we train a few-shot model to predict pseudo labels for …

Happy Toilet: A Social Analytics Approach To The Study Of Public Toilet Cleanliness, Eugene W. J. Choy, Winston M. K. Ho, Xiaohang Li, Ragini Verma, Li Jin Sim, Kyong Jin Shim

Research Collection School Of Computing and Information Systems

This study presents a social analytics approach to the study of public toilet cleanliness in Singapore. From popular social media platforms, our system automatically gathers and analyzes relevant public posts that mention about toilet cleanliness in highly frequented locations across the Singapore island - from busy shopping malls to food 'hawker' centers.

A Mathematical Programming Model For The Green Mixed Fleet Vehicle Routing Problem With Realistic Energy Consumption And Partial Recharges, Vincent F. Yu, Panca Jodiwan, Aldy Gunawan, Audrey Tedja Widjaja

Research Collection School Of Computing and Information Systems

A green mixed fleet vehicle routing with realistic energy consumption and partial recharges problem (GMFVRP-REC-PR) is addressed in this paper. This problem involves a fixed number of electric vehicles and internal combustion vehicles to serve a set of customers. The realistic energy consumption which depends on several variables is utilized to calculate the electricity consumption of an electric vehicle and fuel consumption of an internal combustion vehicle. Partial recharging policy is included into the problem to represent the real life scenario. The objective of this problem is to minimize the total travelled distance and the total emission produced by internal …

Punctuation Prediction For Vietnamese Texts Using Conditional Random Fields, Hong Quang Pham, Binh T. Nguyen, Nguyen Viet Cuong

Research Collection School Of Computing and Information Systems

We investigate the punctuation prediction for the Vietnamese language. This problem is crucial as it can be used to add suitable punctuation marks to machine-transcribed speeches, which usually do not have such information. Similar to previous works for English and Chinese languages, we formulate this task as a sequence labeling problem. After that, we apply the conditional random field model for solving the problem and propose a set of appropriate features that are useful for prediction. Moreover, we build two corpora from Vietnamese online news and movie subtitles and perform extensive experiments on these data. Finally, we ask four volunteers …

Robust And Self-Synchronous Steganography For Voice-Over-Ip Based On Ldpc Codes, Zhanzhan Gao, Guangming Tang, Haitao Song

Journal of System Simulation

Abstract: VoIP (Voice over IP) is a kind of voice communication technology based on UDP/IP protocols, so packet loss will inevitably happen when the channel environment deteriorates. Besides that, stego VoIP data flows are real-time and have no head or tail, which pose more challenges to accurately extract the secret messages. This paper proposes a robust and self-synchronous VoIP steganography method, which solves the above two problems under the premise of maintaining good imperceptibility. In this method, low density parity check (LDPC) codes are introduced to preprocess the secret data, and the encoded data are embedded into voice …

No-Collision Curling Trajectory Simulation System, Tian Yu, Xu Ming

Journal of System Simulation

Abstract: In just a few decades, China’s curling accomplished splendid work. But it’s scientific research falling behind a lot. Applying computer simulation technology in sports training can effectively help the athletes to understand the problems that exist in the training. When curling stone slides on the ice, it can be regarded as two-dimensional motion of rigid body, which can be decomposed into two parts: translation of the center of mass and rotation of a fixed axis around the center of mass. Using computer simulation technology to simulate the curling trajectory, and with the help of this system, the athletes can …

Multi-Projector Annular Display Based On Laser Marking Points, Shuiying Ge, Jitao Neng, Shibiao Xu, Xiaopeng Zhang

Journal of System Simulation

Abstract: This paper proposes a software method to construct a multi-projector display system. Based on the known geometric parameters of the projection curve surface such as radius, radian and the height of the circular-screen and the laser marking points, this method calculates the projection matrix of each projector to warp the image of each projector correctly. The Alpha blending and gamma rectification techniques are used to do the color blending. The experimental results show that the geometric warping and color blending effects of the seamless multi-projector display system are stable and effective.

Simulation Analyses Of A Method For Extracting Dynamic Parameters From Forced Vibration Responses, Yumiao Wei, Zhili Zhang, Zhengjun Chang, Junyang Zhao, Xiangyang Li

Journal of System Simulation

Abstract: To characterize the dynamic features of electromechanical system, a method is researched for dynamic parameters extraction from the forced vibration responses. The forced vibration response signals are processed by HVD method, and the free damped oscillation components are acquired. The SSA-FREEVIB analysis is conducted for the obtained components to measure the dynamic characteristics. The equalization procedures are implemented for the backbones and damping data, the resonance frequency and Q value are therefore accurately estimated. Simulation results show that the calculated resonance frequency and Q value coincide well with the theoretical values. A good anti-noise performance of the proposed …

Ground Coverage Stitching Simulation Algorithm For Remote Sensing Satellite, Shuhao Liu, Wang Tong, Zhang Yue

Journal of System Simulation

Abstract: Ground coverage stitching is the base of remote sensing satellite mission simulation. A coverage stitching simulation algorithm is proposed, considering big time step and attitude maneuver simulation. Transient coverage region is computed by light of view intersection and tangent searching methods. Transient coverage boundaries of different simulation times are stitched by two-dimension convex hull algorithm. Between points of the stitched region polygon edges, new vertexes are interpolated. With the method proposed, limb coverage problem and coverage fusion when time step is large can be solved. Computer simulation results show that the algorithm achieves a fine accuracy and …

Temporal Network And Its Application, Mingzhi Zhang, Luo Kai, Wu Xi, Qingjun Zhang

Journal of System Simulation

Abstract: The traditional method which aggregates the information in a period of time to the static network cannot reflect effectively the dynamic features between the network nodes and their relations. The temporal network and its applications were studied. The temporal network was introduced and the differences between temporal network and static network were analyzed. The types and the two kinds of representation methods of temporal network were divided. The model of temporal network was constructed. Temporal path and temporal distance were discussed. Taking the vulnerability analysis of space information network for example, the results show the advantages of temporal network …

Recognition Method On Two-Phase Flow Regime Based On Cross Recursive Analysis, Yongbo He, Yushan Dong, Rongrong Xue

Journal of System Simulation

Abstract: Aiming at the problems that the two-phase flow regime recognition speed is slow and the recognition accuracy is low, a flow regime recognition method is proposed based on cross recursive analysis (CRA) without imaging. The false nearest neighbors are used to analyze flow regime capacitance values measured by capacitance sensor to obtain an optimal embedding dimension; and the embedding dimension of cross recursive plot is established for several typical flow patterns. The capacitance values of the simulation flow regimes and the reference flow regimes are analyzed using cross recursion to get a set of cross recursive plots. The similarity …

Locally Weighted Learning Control For Dynamic Restricted Manipulators, Wang Gang, Tairen Sun, Shengpei Ding

Journal of System Simulation

Abstract: This paper proposes a locally weighted learning control law for a manipulator with state and input constraints and modeling uncertainties. By visualizing the control input as an extended state, the control problem is converted into control design for a state-constraint uncertain nonlinear system. Barrier Lyapunov functions are introduced into a backstepping procedure and a locally weighted learning control is designed, which ensures the exponential convergence of the barrier functions to a small neighborhood of zero and then guarantees satisfaction of system constraints and the tracking error convergence. The control feasibility and effectiveness is validated by theoretical analysis and …

Dynamic Data Reserved Modeling Method Based On Steady-State Component Estimation And State Tracking, Dong Ze, Erxin Yin

Journal of System Simulation

Abstract: Aiming at the existing problems of conventional industrial system modeling methods, a dynamic data reserved modeling method based on steady-state component estimation and state tracking is proposed. The dynamic response data of the system is selected as the modeling data. The input value at the end of the selected data is chosen as steady-state component, and the steady-state component value of output is artificial given. Steady-state component of the modeling data is removed according to the steady-state component of input and output, and the modeling data is divided into three sections. The prediction model and the state observer are …

Design Method Of Tactical Level Hexagonal Wargame Map, Fen Tang, Zhang Xin, You Xiong, Zhiqiang Wu, Kunwei Li

Journal of System Simulation

Abstract: Wargame map is an indispensable component of wargame. The current research on wargame map focused itself on the hexagonal grid segmentation, the terrain quantization models and relevant algorithms, and the technical realization of the application algorithm based on wargame map. However, the wargame map design is inadequate in corresponding instructions and methods. Therefore, based on the traditional map design method and fully taking into account the characteristics of the army tactical level hexagonal wargame map, the principle and process of army tactical level hexagonal wargame map design are proposed, and the critical steps in the process of the wargame …

Remote Real-Time Rendering System Based On Graphics Cluster, Haiyang Liu, Xiaofeng Hu, Lei Xu

Journal of System Simulation

Abstract: In order to solve the problems of rendering application for many remote users with different requirements, according to the multi-user oriented asynchronous distributed application mode in graphics cluster environment, a general framework of remote real-time rendering system based on graphics cluster is proposed, and the main functional modules are designed. The integrated application of key technologies, including GPU rendering based on Docker, dynamic load balancing and real-time transmission control of images, is analyzed. The effectiveness of system solution is demonstrated by concrete examples.

Simulation Analysis Of Vehicle Electromagnetic Environment Under Excitation Of Vhf Antenna, Xiaoying Sun, Hanqing Wang, Jinpeng Yang, Zhao Yu

Journal of System Simulation

Abstract: Aiming at the issue of distribution regularity of field strength in vehicle cab under excitation of vehicle-borne high-power VHF antenna, a method of numerical simulation combining with extreme value theory to predict maximum field strength is proposed, which minimizes sample collecting difficulty and fitting deviation. CST simulation software is applied to get field strength sample in vehicle cab, and generalized extreme value (GEV) is used to fitting entire field strength distribution. peak over threshold (POT) model based on Generalized Pareto distribution is used to research high field strength value sample statistical characteristics. Resultsshow that under antenna excitation of 92.5 …