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Malaccha: An R-based end-to-end markov transition matrix extraction for land cover datasets

SOFTWAREX 2023年 21卷

作者： Wijayasari, Winda Rohmat, Faizal Immaddudin Wira Viridi, Sparisoma Bandung Inst Technol Fac Math & Nat Sci Dept Computat Sci Bandung Indonesia Bandung Inst Technol Water Resources Dev Ctr Bandung Indonesia Bandung Inst Technol Fac Civil & Environm Engn Dept Water Resources Engn & Management Bandung Indonesia Bandung Inst Technol Fac Math & Nat Sci Dept Phys Bandung Indonesia CIBE Bldg 5th FloorJalan Ganesa 10 Bandung 40132 West Java Indonesia

The markov chain approach is one of the many methods used in analyzing land cover change. The method is widely used for its ease of use and transparency. Malaccha (markovian Land Cover Change) presents an end-to-end code that processes a land cover dataset into markov transition matrices, presenting the probability of change from one land cover type to another. In this study, the code was built with NASA's readily available MODIS HDF dataset in mind. Malaccha breaks down into several steps: land cover data loading, raster reprojection and cropping, data extraction, and transition matrix calculation. The processes were designed to be done in one run. The end results of the software are the land cover classification and the probability transition matrices. Malaccha's product can be used for subsequent studies, including coupling with other sophisticated methods and future development in understanding land cover change dynamics and projections. (c) 2023 The Author(s). Published by Elsevier B.V. This is an open access article under the CC BY license (http://***/licenses/by/4.0/).

关键词： markov transition matrix MODIS Land cover Remote sensing R programming

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A Hybrid Model for Forecasting Traffic Flow: Using Layerwise Structure and markov transition matrix

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IEEE ACCESS 2019年 7卷 26002-26012页

作者： Zhang, Shaokun Kang, Zejian Zhang, Zhemin Lin, Congren Wang, Cheng Li, Jonathan Xiamen Univ Sch Informat Sci & Engn Fujian Key Lab Sensing & Comp Smart Cites Xiamen 361005 Peoples R China Univ Waterloo Dept Syst Design Engn Waterloo ON N2L 3G1 Canada Univ Waterloo Fac Environm WatMos Lab Waterloo ON N2L 3G1 Canada

Forecasting the traffic flow is greatly significant for traffic safety, energy conservation, and environmental protection. However, in the face of many external uncertainties, making accurate predictions about traffic volumes is a challenging issue. Many previous types of researche only explore the utility of a single factor in their prediction and rarely conduct the multi-factor research. As for the traffic flow prediction, many past types of researche focus primarily on the temporal distribution of the traffic flow on a single point on the road, ignoring the spatial correlation. In terms of global forecasting, it was logically far-fetched to mechanically view traffic as images. In this paper, considering the effects of many exogenous variables and the interaction between monitor sites, we propose a hybrid model to simultaneously predict the traffic flow in multiple positions by combining the layerwise structure and the markov transition matrix (MTM). More specifically, we employ the layerwise structure to capture the periodicity, trend, and nonlinearity characteristics of traffic flow and, then, generate the MTM that captures the dynamics embodied in the data and produces the corresponding distributions. Considering the spatial correlation of traffic data, the real road network distance was thus introduced in our model. We apply the methodology on the real-world traffic data from Xiamen, and the experimental results show that the satisfactory predictions can be achieved using our model, which demonstrates the value of the transition matrix in traffic forecasts. In addition, we also introduce the point of interest and analyze its impact on the prediction results.

关键词： Traffic flow forecast layerwise structure markov transition matrix point of interest

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Binary image steganalysis based on pixel mesh markov transition matrix

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JOURNAL OF VISUAL COMMUNICATION AND IMAGE REPRESENTATION 2015年 26卷 284-295页

作者： Feng, Bingwen Lu, Wei Sun, Wei Sun Yat Sen Univ Sch Informat Sci & Technol Guangzhou 510006 Guangdong Peoples R China Sun Yat Sen Univ Sch Software Guangzhou 510006 Guangdong Peoples R China Chinese Acad Sci Inst Informat Engn State Key Lab Informat Secur Beijing 100093 Peoples R China

Binary image stego systems have already been well developed, which raises the requirement of a steganalytic method that detects these stego systems reliably. In this paper, a steganalytic method based on the pixel mesh markov transition matrix (PMMTM) is presented to detect binary image steganography in the spatial domain. The proposed scheme measures the embedding distortion on the texture consistency. Further, the dependence among texture structures is organized as the markov transition of pixel meshes. The final dimensionality-reduced feature set is formed by shrinking the obtained PMMTM according to its detection performance on the embedding simulators, which are developed to simulate practical stego systems. In the end, experimental results are reported, demonstrating that the proposed approach can effectively and reliably detect state-of-the-art binary image stego systems. (C) 2014 Elsevier Inc. All rights reserved.

关键词： Binary image Steganalysis Generalized embedding simulator Connectivity Smoothness Pixel mesh Texture consistency markov transition matrix

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A new process mining approach based on the markov transition matrix

A new process mining approach based on the Markov transition...

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International Conference on Computational Science and Computational Intelligence (CSCI)

作者： Li, Hong Li, Kunman Yunnan Univ Sch Informat Sci & Engn Kunming Peoples R China Univ Huddersfield Sch Comp & Engn Huddersfield HD1 3DH W Yorkshire England

ISBN: (纸本)9781479930098

According to the situation that many workflow instances may deviate from the predefined model, this paper proposed a new process mining approach based on analyzing the workflow log to realize the workflow process reconstruction. First, build the markov transition matrix based on the workflow log, then design a multi-step process mining algorithm to mine the structural relationships between the activities, finally, this paper verifies the feasibility and applicability of the approach through a simulation example.

关键词： process mining markov transition matrix process reconstruction

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Association of state-level prescription drug monitoring program implementation with opioid prescribing transitions in primary care in Australia

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BRITISH JOURNAL OF CLINICAL PHARMACOLOGY 2024年第4期90卷 1162-1172页

作者： Xia, Ting Picco, Louisa Buchbinder, Rachelle Haas, Romi Nielsen, Suzanne Monash Univ Monash Addict Res Ctr Eastern Hlth Clin Sch Melbourne Australia Monash Univ Sch Publ Hlth & Prevent Med Musculoskeletal Hlth Unit Melbourne Vic Australia Monash Univ Sch Publ Hlth & Prevent Med Sustainable Hlth Care Unit Melbourne Vic Australia Monash Univ Monash Addict Res Ctr Eastern Hlth Clin Sch Level 2Bldg D47-49 Moorooduc Highway Frankston Vic 3199 Australia

AimsThis study aimed to evaluate whether voluntary and mandatory prescription drug monitoring program (PDMP) use in Victoria, Australia, had an impact on prescribing behaviour, focusing on individual patients' prescribed opioid doses and transition to prescribing of nonmonitored *** was a retrospective cross-sectional study using routinely collected primary healthcare data. A 90-day moving average prescribed opioid dose in oral morphine equivalents was used to estimate opioid dosage. A markov transition matrix was used to describe how patients prescribed medications transitioned between opioid dose groups and other nonopioid treatment options during 3 transition periods: transition between 2 control periods prior to PDMP implementation (T1 to T2);during the voluntary PDMP implementation (T2 to T3);and during mandatory PDMP implementation (T3 to T4).ResultsAmong patients prescribed opioids in our study, we noted an increased probability of transitioning to not being prescribed opioids during the mandatory PDMP period (T3 to T4). This increase was attributed mainly to the ceasing of low-dose opioid prescribing. Membership in an opioid dose group remained relatively stable for most patients who were prescribed high opioid doses. For those who were only prescribed nonmonitored medications initially, the probability of being prescribed opioids increased during the mandatory PDMP when compared to other transition *** introduction of PDMP mandates appeared to have an impact on the prescribing for patients who were prescribed low-dose opioids, while its impact on individuals prescribed higher opioid doses was comparatively limited.

关键词： markov transition matrix opioid prescribing prescription drug monitoring programs primary health care

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Identifying loci in mobility networks with applications in New Zealand work commutes: a statistical test for identifying extreme stationary distribution values in markov transition matrices

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APPLIED NETWORK SCIENCE 2024年第1期9卷 57页

作者： Kane, Michael J. Gilani, Owais Khusainova, Elena Urbanek, Simon Univ Texas MD Anderson Canc Ctr Dept Lymphoma & Myeloma Houston TX 77030 USA Bucknell Univ Math Dept Lewisburg PA USA Tufts Univ Publ Hlth & Community Med Boston MA USA AT&T Labs Res New York NY USA Univ Auckland Stat Dept Auckland New Zealand

Human mobility describes physical patterns of movement of people within a spatial system. Many of these patterns, including daily commuting, are cyclic and quantifiable. These patterns capture physical phenomena tied to processes studied in urban planning, epidemiology, and other social, behavioral, and economic sciences. This paper advances human mobility research by proposing a statistical method for identifying locations that individual move to and through at a rate proportionally higher than other locations, using commuting data for the country of New Zealand as a case study. We term these locations mobility loci and they capture a global property of communities in which people commute. The method makes use of a directed-graph representation where vertices correspond to locations, and traffic between locations correspond to edge weights. Following a normalization, the graph can be regarded as a markov chain whose stationary distribution can be calculated. The proposed permutation procedure is then applied to determine which stationary distribution values are larger than what would be expected, given the structure of the directed graph and traffic between locations. The results of this method are evaluated, including a comparison to what is already known about commuting patterns in the area as well as a comparison with similar features.

关键词： Mobility loci Directed Graph Clustering markov transition matrix

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Constrained adaptive markov transition matrix based target tracking with IMMPF

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INTERNATIONAL JOURNAL OF ELECTRONICS 2013年第11期100卷 1569-1578页

作者： Wang, Fei Sellathurai, Mathini Wilcox, David Zhou, Jianjiang Nanjing Univ Aeronaut & Astronaut Coll Elect & Informat Engn Nanjing Jiangsu Peoples R China Queens Univ Belfast Sch Elect Belfast Antrim North Ireland

Interacting multiple models particle filter (IMMPF) has been recently paid great attention for its eminent ability in solving nonlinear target tracking problem. Through improving some filter steps, such as sampling and re-sampling, particle filter can offer more estimation accuracy. This paper proposes a particle filter taking advantage of constrained adaptive markov transition matrix based on post-probability. At the end of each filter iteration process, we study two methods to update markov transition matrix for the next iteration process. One is with the ratio of likelihood function, and the other is with the compress ratio of estimation error. Furthermore, to avoid possible failure resulted from abnormal data during the iteration process;we set the upper bound to constrain markov transition probability. Simulations show that constrained adaptive markov transition matrix is beneficial to improve interacting multiple models particle filter results.

关键词： target tracking particle filter markov transition matrix

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CSR from different perspectives: The global ESG indexes updated

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CORPORATE SOCIAL RESPONSIBILITY AND ENVIRONMENTAL MANAGEMENT 2024年第5期31卷 4694-4714页

作者： Jiang, Ping-Chuan Feng, Gen-Fu Wang, Hai-Jie Chang, Chun-Ping Xi An Jiao Tong Univ Sch Econ & Finance Xian Shaanxi Peoples R China Zhengzhou Univ Business Sch Zhengzhou Peoples R China Shih Chien Univ Dept Mkt Management Kaohsiung Taiwan

The prevailing environmental, social and governance (ESG) framework is currently based on micro-ESG indicators. Research on national ESG is often limited to theory building and policy analysis. Based on previous scholars, this paper constructs a national ESG index framework consisting of 39 indices and updates the national ESG indices for 121 countries worldwide from 1990 to 2021 using the entropy weight method, aiming to provide a set of instrumental indices that capture the status and evolution of national ESG performance. The research findings are as follows: First, the Gini coefficient shows that the gap between national ESG performance has gradually widened over time. Second, the kernel density distribution suggests that global ESG performance is on the rise. High-income countries are placing greater emphasis on ESG growth. Third, the results of the markov transformation matrix suggest that there is a "club convergence" in ESG performance across countries.

关键词： entropy weight method Gini coefficient kernel density estimation markov transition matrix national ESG sustainable development

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Who to Teach a Robot to Facilitate Multi-party Social Interactions? 23

Who to Teach a Robot to Facilitate Multi-party Social Intera...

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18th Annual ACM/IEEE International Conference on Human-Robot Interaction (HRI)

作者： Chew, Jouh Yeong Nakamura, Keisuke Honda Res Inst Japan Wako Saitama Japan

ISBN: (纸本)9781450399708

One salient function of social robots is to play the role of facilitator to enhance the harmony state of multi-party social interactions so that every human participant is encouraged and motivated to engage actively. However, it is challenging to handcraft the behavior of social robots to achieve this objective. One promising approach is for the robot to learn from human teachers. This paper reports the findings of an empirical test to determine the optimal experiment condition for a robot to learn verbal and nonverbal strategies to facilitate a multi-party interaction. First, the modified L8 Orthogonal Array (OA) is used to design a fractional factorial experiment condition using factors like the type of human facilitator, group size and stimulus type. The response of OA is the harmony state explicitly defined using the speech turn-taking between speakers and represented using metrics extracted from the first order markov transition matrix. Analyses of Main Effects and ANOVA suggest the type of human facilitator and group size are significant factors affecting the harmony state. Therefore, we propose the optimal experiment condition to train a facilitator robot using high school teachers as human teachers and group size larger than four participants.

关键词： Multi-party interactions engagements harmony state social cohesion speech turn-taking orthogonal array markov transition matrix facilitator robot

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A searching algorithm based on markov transition matrix in WSN

A searching algorithm based on Markov transition matrix in W...

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3rd IEEE Annual International Conference on Cyber Technology in Automation, Control and Intelligent System (CYBER)

作者： Guo Pengfei Bo Yuming Zhang Jie Nanjing Univ Sci & Technol Sch Automat Nanjing Jiangsu Peoples R China

ISBN: (纸本)9781479906109;9781479906123

In this paper, we present a searching algorithm in Wireless Sensor Network based on markov probability transition matrix. For the unsuitable of maximum degree search algorithm in scale-free network search, we put forward an algorithm combines maximum degree search and randomly walk algorithm, and on this basis, by construct a markov probability transition matrix, select node with maximum transition probability when searching loop emergences until reach the target node. Finally, choose different size of Wireless Sensor Network, simulation verifies the effectiveness of the proposed algorithm.

关键词： Wireless Sensor Network maximum degree search randomly walk search markov transition matrix

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