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arXiv 2025年

作者： Schmidt, Adam Karaoglu, Mert Asim Sinha, Soham Jang, Mingang Ha, Ho-Gun Jung, Kyungmin Gu, Kyeongmo Ullah, Ihsan Lee, Hyunki Šerých, Jonáš Neoral, Michal Matas, Jiří Zhou, Rulin He, Wenlong Wang, An Ren, Hongliang Silva, Bruno Queirós, Sandro Lima, Estêvão Vilaça, João L. Kikuchi, Shunsuke Kouno, Atsushi Matsuzaki, Hiroki Li, Tongtong Chen, Yulu Li, Ling Ma, Xiang Li, Xiaojian Zeinoddin, Mona Sheikh Wang, Xu Tandogdu, Zafer Shaw, Greg Mazomenos, Evangelos Stoyanov, Danail Chen, Yuxin Wu, Zijian Ladikos, Alexander DiMaio, Simon Salcudean, Septimiu E. Mohareri, Omid Intuitive Surgical Inc. Sunnyvale United States ImFusion GmbH Munich Germany Technical University of Munich Munich Germany NVIDIA Santa Clara United States Korea Republic of CMP Visual Recognition Group Faculty of Electrical Engineering Czech Technical University in Prague Czech Republic Shenzhen Research Institute China The Chinese University of Hong Kong China Shenzhen University China School of Medicine University of Minho Braga Portugal ICVS/3B’s - PT Government Associate Laboratory Braga Guimarães Portugal 2Ai –School of Technology IPCA Barcelos Portugal LASI – Associate Laboratory of Intelligent Systems Guimarães Portugal Jmees Inc Japan United States School of Management Hefei University of Technology Hefei230009 China Key Laboratory of Process Optimization and Intelligent Decision-making Ministry of Education Hefei China Hawkes Institute University College London London United Kingdom Dept of Urology University College London Hospitals United Kingdom University of British Columbia Canada

Understanding tissue motion in surgery is crucial to enable applications in downstream tasks such as segmentation, 3D reconstruction, virtual tissue landmarking, autonomous probe-based scanning, and subtask autonomy. labeled data are essential to enabling algorithms in these downstream tasks since they allow us to quantify and train algorithms. This paper introduces a point tracking challenge to address this, wherein participants can submit their algorithms for quantification. The submitted algorithms are evaluated using a dataset named surgical tattoos in infrared (STIR), with the challenge aptly named the STIR Challenge 2024. The STIR Challenge 2024 comprises two quantitative components: accuracy and efficiency. The accuracy component tests the accuracy of algorithms on in vivo and ex vivo sequences. The efficiency component tests the latency of algorithm inference. The challenge was conducted as a part of MICCAI EndoVis 2024. In this challenge, we had 8 total teams, with 4 teams submitting before and 4 submitting after challenge day. This paper details the STIR Challenge 2024, which serves to move the field towards more accurate and efficient algorithms for spatial understanding in surgery. In this paper we summarize the design, submissions, and results from the challenge. The challenge dataset is available here: https://***/records/14803158, and the code for baseline models and metric calculation is available here: https://***/athaddius/STIRMetrics Copyright © 2025, The Authors. All rights reserved.

关键词： Endoscopy

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Novel correlation coefficients for hesitant fuzzy sets and their applications to supplier selection and medical diagnosis

Novel correlation coefficients for hesitant fuzzy sets and t...

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作者： Yang, Jinxin Tang, Xiaoan Yang, Shanlin School of Management Hefei University of Technology Box 270 Hefei Anhui230009 China Key Laboratory of Process Optimization and Intelligent Decision-making Ministry of Education Hefei Anhui China Department of Electrical and Computer Engineering University of Alberta Edmonton Canada

Hesitant fuzzy set theory provides an effective technique for researchers and engineers to cope with vagueness and uncertainty. In recent years, to explore the correlation between hesitant fuzzy sets, traditional correlation measure in statistics has been constantly studied in hesitant fuzzy environments. In this study, extant studies of correlation measures in hesitant fuzzy contexts are recalled and analyzed. In view of the forgoing analysis, we find out that the extant correlation coefficients have some limitations. Moreover, a few correlation coefficients are not in line with the traditional definition of correlation coefficients. In order to address the flaws of the existing proposals, a novel hesitant fuzzy correlation coefficient is proposed in this study. The new proposal of this study can not only overcome the flaws of the old hesitant fuzzy correlation coefficients, but it also shows several desirable characteristics. The weighted form of the newly defined correlation coefficient and its features are also investigated. Finally, three numerical examples concerning supplier selection and medical diagnosis are examined using the developed correlation coefficients to demonstrate their applicability. Comparison analyses with existing proposals highlight the efficiency of our proposals. © 2018 - IOS Press and the authors. All rights reserved.

关键词： decision making

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Novel distance and similarity measures for hesitant fuzzy sets and their applications to multiple attribute decision making

Novel distance and similarity measures for hesitant fuzzy se...

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作者： Tang, Xiaoan Peng, Zhanglin Ding, Haining Cheng, Manli Yang, Shanlin School of Management Hefei University of Technology Hefei Box 270 Hefei Anhui230009 China Key Laboratory of Process Optimization and Intelligent Decision-Making Ministry of Education Anhui China School of Management North Minzu University Ningxia Hui Autonomous Region China

Distance and similarity measures have recently been investigated in-depth within the context of hesitant fuzzy sets. By analyzing the existing studies concerning distance measures for hesitant fuzzy sets, we find that they have some limitations. To address the flaws, this study develops some novel distance measures for hesitant fuzzy sets, including the normalized Euclidean distance measure, the Hausdorff metric distance measure, the normalized generalized distance measure, and their corresponding weighted distance measures. The proposals of this study not only hold many ideal characteristics but also do not consider the lengths of hesitant fuzzy elements as well as the arrangement of their possible values. To deal with the situations where both of the universe of discourse and the weight of element are continuous, some continuous hesitant fuzzy distance measures are also investigated. Based on the relationship between distance measure and similarity measure, some novel similarity measures for hesitant fuzzy sets can be further deduced from the proposed distance measures. Finally, two numerical examples are given to demonstrate the applicability and validity of the proposed hesitant fuzzy distance measures. © 2018 - IOS Press and the authors. All rights reserved.

关键词： decision making

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Network analysis of R&D technology spillovers effect in the Yangtze River Delta Region

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IOP Conference Series: Earth and Environmental Science 2020年第1期615卷

作者： Guili Jiang Jianling Jiao Jingjing Li Chaoping Sun Tourism College of Zhejiang Hangzhou Zhejiang China School of Management Hefei University of Technology Hefei Anhui China Key Laboratory of Process Optimization and Intelligent Decision-making (Hefei University of Technology) Ministry of Education Hefei Anhui 230009 China

This article evaluates the evolution of inter-city R&D technology spillover in the Yangtze River Delta Region (YRDR) using social network analysis method. Empirical results indicate that the inter-city R&D technology spillovers are sparse, but gradually increasing. Four characteristic cohesive subgroups are formed, subgroup I formed by core cities like Shanghai and Nanjing is the technical sender and the subgroup is closely connected. Nanjing's role as a network bridge has been replaced by Jiaxing.

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An Empirical Analysis of Carbon Emission Price in china

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Energy Procedia 2018年 152卷 823-828页

作者： Kaile Zhou Yiwen Li School of Management Hefei University of Technology Hefei 230009 China Key Lab of Process Optimization and Intelligent Decision-making Ministry of Education Hefei 230009 China Department of Public Policy City University of Hong Kong Kowloon Hong Kong SAR China

Carbon emission trading, as an effective economic tool to deal with climate change issues, has received widespread attention in recent years. As a major carbon emitter, china plays an important role in global climate change. This paper uses the Vector Error Correction (VEC) model to explore the dynamic relationship between energy price, macroeconomic indicators, air quality, and carbon emission trading price. The results show that there is a long-term equilibrium relationship between these selected indicators and carbon emission trading price. In addition, this paper also uses the Generalized Auto-Regressive Conditional Heteroskedasticity (GARCH) model to analyze the carbon price fluctuation characteristics. It is found that there is a positive leverage effect on the price fluctuation of the selected carbon emission return series. External bad news will have a greater impact on carbon price fluctuation than good news.

关键词： Carbon market Carbon emission trading GARCH model Price fluctuation

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Single-valued neutrosophic entropy and similarity measures to solve supplier selection problems

Single-valued neutrosophic entropy and similarity measures t...

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作者： Jin, Feifei Ni, Zhiwei Chen, Huayou Langari, Reza Zhu, Xuhui Yuan, Hongjun School of Management Hefei University of Technology Hefei Anhui China Key Laboratory of Process Optimization and Intelligent Decision-Making Ministry of Education Hefei Anhui China Department of Mechanical Engineering Texas AandM University College StationTX United States School of Mathematical Sciences Anhui University Hefei Anhui China School of Statistics and Applied Mathematics Anhui University of Finance and Economics Bengbu Anhui233030 China

The single-valued neutrosophic sets (SVNSs) are useful tools to describe uncertainty and inconsistent information that exist in real world. For SVNSs theory, two important topics are single-valued neutrosophic entropy and single-valued neutrosophic similarity measurer. This paper investigates a multi-attribute decision-making (MADM) method by using single-valued neutrosophic entropy and similarity measure. First, the concepts of single-valued neutrosophic entropy and similarity measure are presented. Then, based on the trigonometric functions (i.e., sine function and cosine function), we introduce two information measure formulas and prove that they satisfy the requirements of the single-valued neutrosophic entropy and similarity measure, respectively. Furthermore, we study the inter-relationship between single-valued neutrosophic entropy and similarity measure. By using Lagrange Multiplier Method and closeness degree, we develop a novel single-valued neutrosophic MADM method. Finally, a numerical example of selecting the desirable supplier is provided, and the comparison with existing approaches is performed to validate the rationality and effectiveness of the proposed method. © 2018 - IOS Press and the authors. All rights reserved.

关键词： Entropy

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Inferential modelling and decision making with data 23

Inferential modelling and decision making with data

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23rd IEEE International Conference on Automation and Computing, ICAC 2017

作者： Yang, Jian-Bo Xu, Dong-Ling Decision and Cognitive Sciences Research Centre University of Manchester ManchesterM13 9SS United Kingdom Key Laboratory of Process Optimization and Intelligent Decision-making Ministry of Education Hefei China

ISBN: (纸本)9780701702618

In this paper, we introduce the main concepts of a new maximum livelihood evidential reasoning (MAKER) framework for data-driven inferential modelling and decision making under different types of uncertainty. It consists of two types of model: state space model (SSM) and evidence space model (ESM), driven by the data that reflects the relationships between system inputs and output. SSM is constructed to describe different system states and changes. ESM is established by mapping data to a set of evidence that is partitioned into evidential elements each pointing to a system state set and together represents system behaviours in a probabilistic and distributed manner. The reliability of evidence and interdependence between a pair of evidence are explicitly measured. It is in the joint evidence-state space that multiple pieces of evidence with different degrees of interdependence and reliability are acquired from system inputs and combined to inference system output. A general optimal learning model is constructed, where evidence reliability can be learnt from historical data by maximising the likelihood of true state. In the MAKER framework, different types of uncertainty can be taken into account for inferential modelling, probabilistic prediction and decision making. © 2017 Chinese Automation and Computing Society in the UK - CACSUK.

关键词： decision making

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Integrated production and delivery withmultiple factories and multiple customers

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International Journal of Systems Science: Operations and Logistics 2017年第3期4卷 219-228页

作者： Li, Kai Zhang, Xun Leung, Joseph Y-T. Cheng, Ba-yi School of Management Hefei University of Technology Hefei China Key Laboratory of Process Optimization and Intelligent Decision-Making of Ministry of Education Hefei China Department of Computer Science New Jersey Institute of Technology Newark NJ United States

This paper considers coordinated scheduling of production and delivery with multiple factories and multiple customers. Due to the variation of cost, the production and delivery costs of a job are dependent on the factory to which it is assigned. Our problem is to find a schedule that minimises the makespan or the total completion time, subject to the constraint that the total cost does not exceed a given threshold. We first describe a linear programming algorithm to solve the preemptive case. The result of the linear program serves as a lower bound of the nonpreemptive case and suggests heuristics to solve the nonpreemptive case. We also show that minimising the total completion time subject to a given threshold of the cost is NP-complete. Computational experiments are conducted and the results show that the heuristics perform very well in practice. © 2016, © 2016 Informa UK Limited, trading as Taylor & Francis Group.

关键词： delivery cost heuristics makespan multiple factories Scheduling total completion time

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Strategic project selection based on evidential reasoning approach for high-end equipment manufacturing industry 3

Strategic project selection based on evidential reasoning ap...

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3rd International Conference on Mechanical, Electronic and Information Technology Engineering, ICMITE 2017

作者： Lu, Guangyan Xue, Min Liu, Yin Chang, Wenjun Department of Operation Management CRRC Qishuyan Institute Co. Ltd Changzhou Jiangsu213011 China School of Management Hefei University of Technology Hefei Box 270 Hefei Anhui230009 China Key Laboratory of Process Optimization and Intelligent Decision-making Ministry of Education Hefei Box 270 Hefei Anhui230009 China

With the rapid development of science and technology, emerging information technologies have significantly changed the daily life of people. In such context, strategic project selection for high-end equipment manufacturing industries faces more and more complexities and uncertainties with the consideration of several complex criteria. For example, a group of experts rather than a single expert should be invited to select strategic project for high-end equipment manufacturing industries and the experts may feel difficulty to express their preferences towards different strategic projects due to their limited cognitive capabilities. In order to handle these complexities and uncertainties, the criteria framework of strategic project selection is firstly constructed based on the characteristics of high-end equipment manufacturing industries and then evidential reasoning (ER) approach is introduced in this paper to help experts express their uncertain preferences and aggregate these preferences to generate an appropriate strategic project. A real case of strategic project selection in a high-speed train manufacturing enterprise is investigated to demonstrate the validity of the ER approach in solving strategic project selection problem. © The Authors, published by EDP Sciences, 2017.

关键词： decision making

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POLYNOMIAL DYNAMIC PROGRAMMING ALGORITHMS FOR LOT SIZING MODELS WITH BOUNDED INVENTORY AND STOCKOUT AND/OR BACKLOGGING

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Journal of Systems Science and Systems Engineering 2016年第3期25卷 370-397页

作者： Jinhong Zhong Feng Chu Chengbin Chu Shanlin Yang School of Management Hefei University of Technology Hefei 230009 China Laboratoire IBISC Universite d'Evry-Val d'Essone France Laboratoire Genie Industriel Ecole Centrale Paris France Key Laboratory of Process Optimization and Intelligent Decision-making of Ministry of Education Hefei China

This paper addresses a dynamic lot sizing problem with bounded inventory and stockout where both no backlogging and backlogging allowed cases are considered. The stockout option means that there is outsourcing in a period only when the inventory level at that period is non-positive. The production capacity is unlimited and production cost functions are linear but with fixed charges. The problem is that of satisfying all demands in the planning horizon at minimal total cost. We show that the no backlogging case can be solved in O（T^2） time with general concave inventory holding and outsourcing cost functions where T is the length of the planning horizon. The complexity can be reduced to O（T） when the inventory holding cost functions are also linear and have some realistic properties, even if the outsourcing cost functions remain general concave functions. When the inventory holding and outsourcing cost functions are linear, the backlogging case can be solved in O（ T^3 logT） time whether the outsourcing level at each period is bounded by the sum of the demand of that period and backlogging level from previous periods, or only by the demand of that period.

关键词： Dynamic lot sizing problem bounded inventory outsourcing backlogging stockout,dynamic programming

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