Article
Chemistry, Analytical
AiYun Sun, WenBao Jia, DaQian Hei, MengCheng Qiu, Can Cheng, JiaTong Li
Summary: This study introduces a weighted library least squares approach (WLLS) that reduces fluctuations in statistical uncertainty in spectra by using the square root of the count for weighting. The method also decreases the average standard deviation of the results to at least 0.37 times that of the traditional approach.
ANALYTICAL METHODS
(2021)
Article
Green & Sustainable Science & Technology
Li Cui, Ke Yang, Zhimei Lei, Ming K. Lim, Ying Hou
Summary: This paper proposes a methodology for studying stakeholder collaboration in the sharing economy by analyzing the network structure of stakeholders and sustainability factors. The research finds that the core stakeholders in the sharing economy include individual suppliers, firm suppliers, and sharing economy platforms. Social motivation, security mechanism, industry supervision, economic benefits, and level of cooperation are key factors for sustainable development.
SUSTAINABLE PRODUCTION AND CONSUMPTION
(2022)
Article
Engineering, Mechanical
Kuo Liu, Jiakun Wu, Haibo Liu, Mingjia Sun, Yongqing Wang
Summary: A physically-based thermal error model of the servo axis was established, and a new method for calculating model reliability using deep belief network (DBN) and the Monte Carlo method was proposed. The study validated the robustness of the model and the accuracy of the proposed reliability calculation method through experiments.
MECHANICAL SYSTEMS AND SIGNAL PROCESSING
(2021)
Article
Engineering, Mechanical
Congfang Hu, Gaode Geng, Pol D. Spanos
Summary: The closed differential planetary transmission system features a high-speed ratio and compact structure, but suffers from uneven load sharing and excessive errors. This study investigates the impact of error randomness on load-sharing behavior through establishing a stochastic multi-body dynamics model and comparing different methods.
MECHANISM AND MACHINE THEORY
(2021)
Article
Green & Sustainable Science & Technology
Jian Wang, Xiang Gao, Zhili Sun
Summary: The paper introduces a method called multilevel Monte Carlo (MLMC) for time-variant reliability analysis, aiming to enhance computational efficiency while maintaining accuracy and robustness. By discretizing the time interval using a geometric sequence of different timesteps and estimating the cumulative probability of failure with corrections from all levels, the method optimizes the number of random samples at each level to minimize computational complexity. Independently computed corrections at each level allow achieving accuracy at a lower cost compared to crude Monte Carlo simulation, while maintaining robustness to nonlinearity and dimensions.
Article
Computer Science, Information Systems
Alfredo Nespoli, Emanuele Ogliari, Sonia Leva
Summary: The increasing adoption of electric vehicles presents challenges for the electrical distribution network. Accurate forecasting of electric vehicle charging sessions is crucial for predictive energy management systems that improve grid operation. This paper proposes a comprehensive methodology that clusters historical charging sessions based on user characteristics and predicts each session using arrival time, duration, and expected power parameters. The method is evaluated using a real case study, showing significant improvements in energy accuracy and predicted charging sessions compared to a benchmark. The overall Skill Score for 2019 is 0.37.
Article
Energy & Fuels
Jessica N. Castillo, Verny F. Resabala, Luigi O. Freire, Byron P. Corrales
Summary: Research and algorithms are being developed worldwide to predict and estimate the consumption of electrical energy in buildings and other facilities. This particular study developed a mathematical model to simulate the energy consumption of a building's main electrical loads. By collecting and analyzing data, the researchers proposed a solution to optimize the building's energy consumption profile.
Article
Nuclear Science & Technology
Jinlong Huang, Liangzhi Cao, Qingming He, Chenghui Wan, Hongchun Wu
Summary: The IFP and CLUTCH methods commonly used in Monte-Carlo codes have a problem of large variance of sensitivity coefficients for scattering reactions with small cross sections. To address this issue, a novel technique called CLUTCH-FC is proposed to reduce the variance by forced collisions. Experimental results show that this method improves the efficiency of sensitivity coefficient calculation.
PROGRESS IN NUCLEAR ENERGY
(2023)
Article
Energy & Fuels
Jiaqiao Li, Guobang Wang, Tiancheng Tang, Jinjin Fan, Shengyuan Liu, Zhenzhi Lin
Summary: This paper proposes an optimization strategy for distribution network reconfiguration based on the Markov chain Monte Carlo method, which achieves peak load shaving and load balancing of low voltage distribution lines. By using load characteristic curve clustering and optimization model, the line load rate and resource utilization are improved.
Article
Spectroscopy
Shaohui Yu, Jing Liu
Summary: This paper proposes an ensemble calibration model FDA-EM-PLS (functional data analysis-ensemble learning-partial least squares) for near-infrared spectroscopy, based on the functional data analysis method. By dividing the near-infrared spectroscopy into intervals and conducting functional data analysis, clustering, and Monte Carlo sampling, this model achieves accurate detection of corn and soil data.
SPECTROCHIMICA ACTA PART A-MOLECULAR AND BIOMOLECULAR SPECTROSCOPY
(2022)
Article
Mechanics
Haibing Peng
Summary: Despite the widespread use of Navier-Stokes equations in computational-fluid-dynamics (CFD), there are still unanswered questions due to the absence of considering the statistical nature of discrete air molecules. In this study, we propose a statistical mechanics-based approach called the volume-element method, which allows for the numerical evaluation of aerodynamic lift and drag. We obtained pressure and friction values as a function of the angle of attack for flat-plate airfoils, and this method can be directly applied to convex-shape airfoils and combined with Monte Carlo simulations for concave-shape airfoils. This approach not only has implications for aerodynamic applications, but also opens up possibilities for further applications in Boson or Fermi gases.
Article
Statistics & Probability
V. Roshan Joseph, Akhil Vakayil
Summary: In this article, an optimal method named SPlit for splitting a dataset into training and testing sets is proposed, which is based on the support points algorithm and can be applied to both regression and classification problems. The implementation on real datasets shows substantial improvement compared to the commonly used random splitting procedure.
Article
Mathematics
Tinghuai Ma, Yuming Su, Huan Rong, Yurong Qian, Najla Al-Nabhan
Summary: With the rapid development of social networks, personal privacy leakage has become more serious. This paper proposes a rule fusion method of privacy protection for the co-ownership of data shared in social networks, which can better protect personal privacy.
Article
Genetics & Heredity
Kaixian Yu, Zihan Cui, Xin Sui, Xing Qiu, Jinfeng Zhang
Summary: Bayesian networks provide a probabilistic, graphical framework for modeling high-dimensional joint distributions with complex correlation structures and have wide applications in various disciplines. Researchers introduced a three-stage approach named GRASP based on sequential Monte Carlo, with a double filtering strategy and adaptive SMC algorithm to learn network structures of BNs. GRASP showed promising results when tested on benchmark networks, demonstrating its potential in discovering novel biological relationships in integrative genomic studies.
FRONTIERS IN GENETICS
(2021)
Article
Engineering, Industrial
Gulsum Kubra Kaya, Fatih Ozturk, Emine Emel Sariguzel
Summary: Safety management in tram systems is considered effective, but there is still room for improvement. This study used the Functional Resonance Analysis Method (FRAM) to explore how a system-based perspective could enhance risk analysis in a tram operating system. The findings showed that daily tram operations involve variability, particularly in tram driver- and pedestrian-related actions, in response to unforeseen changes. The system's performance variability was crucial for successful operation but also exposed it to risks.
RELIABILITY ENGINEERING & SYSTEM SAFETY
(2021)
Article
Computer Science, Information Systems
Yaqian Wu, Xiangming Xiao, Rangqian Chen, Jun Ma, Xinxin Wang, Yanan Zhang, Bin Zhao, Bo Li
MULTIMEDIA TOOLS AND APPLICATIONS
(2020)
Article
Environmental Sciences
Xinxin Wang, Xiangming Xiao, Zhenhua Zou, Bangqian Chen, Jun Ma, Jinwei Dong, Russell B. Doughty, Qiaoyan Zhong, Yuanwei Qin, Shengqi Dai, Xiangping Li, Bin Zhao, Bo Li
REMOTE SENSING OF ENVIRONMENT
(2020)
Article
Environmental Sciences
Fengfei Xin, Xiangming Xiao, Jinwei Dong, Geli Zhang, Yao Zhang, Xiaocui Wu, Xiangping Li, Zhenhua Zou, Jun Ma, Guoming Du, Russell B. Doughty, Bin Zhao, Bo Li
SCIENCE OF THE TOTAL ENVIRONMENT
(2020)
Article
Forestry
Jun Ma, Xiangming Xiao, Ronghui Li, Bin Zhao, Soe W. Myint
FOREST ECOLOGY AND MANAGEMENT
(2020)
Article
Biodiversity Conservation
Sheng-Lan Zeng, Bin Zhao, Ting-Ting Zhang, Zu-Tao Ouyang
LANDSCAPE AND ECOLOGICAL ENGINEERING
(2020)
Article
Ecology
Jinjin Hou, Yifei Liu, James D. Fraser, Lei Li, Bin Zhao, Zhichun Lan, Jiefeng Jin, Guanhua Liu, Nianhua Dai, Wenjuan Wang
ECOLOGY AND EVOLUTION
(2020)
Article
Environmental Sciences
Ya-Lei Li, Hai-Qiang Guo, Zhen-Ming Ge, Dong-Qi Wang, Wen-Liang Liu, Li-Na Xie, Shi-Hua Li, Li-Shan Tan, Bin Zhao, Xiu-Zhen Li, Jian-Wu Tang
SCIENCE OF THE TOTAL ENVIRONMENT
(2020)
Article
Remote Sensing
Wan-Ben Wu, Jun Ma, Michael E. Meadows, Ellen Banzhaf, Tian-Yuan Huang, Yi-Fei Liu, Bin Zhao
Summary: This study investigates the dynamics of urban green space (UGS) in 107 medium-sized and large cities in China from 1990 to 2019, revealing significant greening in long-term built-up and non-built-up areas, and notable browning in newly developed areas. The Normalized Urban Development Index (NUDI) showed high effectiveness in mapping urban development gradients with an overall accuracy of 89%.
INTERNATIONAL JOURNAL OF APPLIED EARTH OBSERVATION AND GEOINFORMATION
(2021)
Article
Ecology
Evelyn E. Gaiser, John S. Kominoski, Diane M. McKnight, Christie A. Bahlai, Chingwen Cheng, Sydne Record, Wilfred M. Wollheim, Kyle R. Christianson, Martha R. Downs, Peter A. Hawman, Sally J. Holbrook, Abhishek Kumar, Deepak R. Mishra, Noah P. Molotch, Richard B. Primack, Andrew Rassweiler, Russell J. Schmitt, Lori A. Sutter
Summary: The COVID-19 pandemic disrupted human activity, leading to changes in human-ecosystem interactions, known as the anthropause. The effects of the anthropause on ecosystem states and functions, as well as its feedback to human systems through ecosystem services, are still uncertain. This study proposes new investigation pathways using a disturbance framework to capture the effects of the anthropause through coordinated, long-term social-ecological research. Although it is still early to comprehensively evaluate these effects, case studies using long-term data show changes in air and water quality, as well as wildlife populations and behavior coinciding with the anthropause. These findings highlight the importance of long-term data in understanding the impacts of the anthropause and separating them from natural variation and long-term trends.
Article
Computer Science, Interdisciplinary Applications
Tian-Yuan Huang, Liying Yang
Summary: This paper presents the superior identification index (SII), a metric that quantifies the capability of academic journals to recognize top papers in a specific time window and study field. The SII provides a flexible framework to balance journal quality and quantity, and introduces extended metrics to describe other dimensions of journal performance.
Article
Ecology
Benjamin S. Halpern, Carl Boettiger, Michael C. Dietze, Jessica A. Gephart, Patrick Gonzalez, Nancy B. Grimm, Peter M. Groffman, Jessica Gurevitch, Sarah E. Hobbie, Kimberly J. Komatsu, Kristy J. Kroeker, Heather J. Lahr, David M. Lodge, Christopher J. Lortie, Julie S. S. Lowndes, Fiorenza Micheli, Hugh P. Possingham, Mary H. Ruckelshaus, Courtney Scarborough, Chelsea L. Wood, Grace C. Wu, Lina Aoyama, Eva E. Arroyo, Christie A. Bahlai, Erin E. Beller, Rachael E. Blake, Karrigan S. Bork, Trevor A. Branch, Norah E. M. Brown, Julien Brun, Emilio M. Bruna, Lauren B. Buckley, Jessica L. Burnett, Max C. N. Castorani, Samantha H. Cheng, Sarah C. Cohen, Jessica L. Couture, Larry B. Crowder, Laura E. Dee, Arildo S. Dias, Ignacio J. Diaz-Maroto, Martha R. Downs, Joan C. Dudney, Erle C. Ellis, Kyle A. Emery, Jacob G. Eurich, Bridget E. Ferriss, Alexa Fredston, Hikaru Furukawa, Sara A. Gagne, Sarah R. Garlick, Colin J. Garroway, Kaitlyn M. Gaynor, Angelica L. Gonzalez, Eliza M. Grames, Tamar Guy-Haim, Ed Hackett, Lauren M. Hallett, Tamara K. Harms, Danielle E. Haulsee, Kyle J. Haynes, Elliott L. Hazen, Rebecca M. Jarvis, Kristal Jones, Gaurav S. Kandlikar, Dustin W. Kincaid, Matthew L. Knope, Anil Koirala, Jurek Kolasa, John S. Kominoski, Julia Koricheva, Lesley T. Lancaster, Jake A. Lawlor, Heili E. Lowman, Frank E. Muller-Karger, Kari E. A. Norman, Nan Nourn, Casey C. O'Hara, Suzanne X. Ou, Jacqueline L. Padilla-Gamino, Paula Pappalardo, Ryan A. Peek, Dominique Pelletier, Stephen Plont, Lauren C. Ponisio, Cristina Portales-Reyes, Diogo B. Provete, Eric J. Raes, Carlos Ramirez-Reyes, Irene Ramos, Sydne Record, Anthony J. Richardson, Roberto Salguero-Gomez, Erin Satterthwaite, Chloe Schmidt, Aaron J. Schwartz, Craig R. See, Brendan D. Shea, Rachel S. Smith, Eric R. Sokol, Christopher T. Solomon, Trisha Spanbauer, Paris Stefanoudis, Beckett W. Sterner, Vitor Sudbrack, Jonathan D. Tonkin, Ashley R. Townes, Mireia Valle, Jonathan A. Walter, Kathryn Wheeler, William R. Wieder, David R. Williams, Marten Winter, Barbora Winterova, Lucy C. Woodall, Adam S. Wymore, Casey Youngflesh
Summary: Synthesis research in ecology and environmental science is important for improving understanding, advancing theory, identifying research priorities, and supporting management strategies. A virtual workshop with participants from different countries and disciplines was held to discuss how synthesis can address key questions and themes in the field in the next decade. Seven priority research topics and two issues regarding synthesis practices were identified, providing a strategic vision for future synthesis in ecology and environmental science.
Proceedings Paper
Computer Science, Artificial Intelligence
Liangping Ding, Tian-Yuan Huang, Huan Liu, Yufei Wang, Zhixiong Zhang
Summary: Named entity recognition is crucial for extracting valuable information from digital libraries. However, there is a lack of annotated NER datasets for scientific literature, except in the medical domain. This study focuses on noisy-labeled named entity recognition under a distant supervision setting and proposes a category-oriented confidence calibration strategy to improve model performance.
FROM BORN-PHYSICAL TO BORN-VIRTUAL: AUGMENTING INTELLIGENCE IN DIGITAL LIBRARIES, ICADL 2022
(2022)
Article
Computer Science, Interdisciplinary Applications
Tian-Yuan Huang, Li Li, Liying Yang
Summary: This paper introduces the tidy framework for automatic knowledge classification supported by the akc package, which has powerful support from the R ecosystem and can handle multiple steps in the data science workflow. Additionally, the package can be extended to other contexts.
