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On the gEUD biological optimization objective for organs at risk in Photon Optimizer of Eclipse treatment planning system

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JOURNAL OF APPLIED CLINICAL MEDICAL PHYSICS 2018年第1期19卷 106-114页

作者： Fogliata, Antonella Thompson, Stephen Stravato, Antonella Tomatis, Stefano Scorsetti, Marta Cozzi, Luca Humanitas Res Hosp & Canc Ctr Radiotherapy & Radiosurg Dept Milan Rozzano Italy Oncol Syst Varian Med Syst Palo Alto CA USA Humanitas Univ Biomed Fac Milan Rozzano Italy

Inverse planning optimization using biologically based objectives is becoming part of the intensity modulated optimization process. The performances and efficacy of the biologically based gEUD (generalized Equivalent Uniform Dose) objective implemented in the Photon Optimizer (PO) of Varian Eclipse treatment planning system have been here analyzed. gEUD is associated with the parameter a that accounts for the seriality of a structure, being higher for more serial organs. The PO was used to optimize volumetric modulated arc therapy (VMAT) plans on a virtual homogeneous cylindrical phantom presenting a target and an organ at risk (OAR). The OAR was placed at 4 mm, 1 and 2 cm distance, or cropped at 0, 2 and 4 mm from the target. Homogeneous target dose of 60 Gy in 20 fractions was requested with physical dose-volume objectives, while OAR dose was minimized with the upper gEUD objective. The gEUD specific a parameter was varied from 0.1 to 40 to assess its impact to OAR sparing and target coverage. Actual head and neck and prostate cases, with one parotid and the rectum as test OAR, were also analyzed to translate the results in the more complex clinical environment. Increasing the a parameter value in the gEUD objective, the optimization achieved lower volumes of the OAR which received the highest dose levels. The maximum dose in the OAR was minimized well with a values up to 20, while further increase of a to 40 did not further improve the result. The OAR mean dose was reduced for the OAR located at 1 and 2 cm distance from the target, enforced with increasing a. For cropped OARs, a mean dose reduction was achieved for a values up to 3-5, but mean dose increased for higher a values. The optimal choice of the parameter a depends on the mutual OAR and target position, and seriality of the organ. Today no significant compendium of clinical and biological specific a and gEUD values are available for a wide range of OARs.

关键词： biological optimization gEUD IMRT optimization objective VMAT

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Heat transfer characteristics of topological latent heat storage systems based on optimization objectives

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APPLIED THERMAL ENGINEERING 2024年 252卷

作者： Zhang, Xinyu Yang, Xiaohong Gao, Xiaoyu Xu, Jiakun Inner Mongolia Univ Technol Sch Energy & Power Engn Hohhot 010051 Peoples R China Minist Educ Key Lab Wind & Solar Energy Utilizat Technol Hohhot 010051 Peoples R China Minist Educ Inner Mongolia Autonomous Reg New Energy Prod Prom Hohhot 010051 Peoples R China

In order to improve the heat storage efficiency and shorten the heat storage/release time in latent heat storage (LHS) systems, topology optimization of heat transfer problems has been applied to LHS systems. The choice of the optimization objective determines the structure of the topology fins. In this paper, the topology generation process was analyzed using the mean temperature, the mean square deviation (MSD) of the mean temperature, and the multi -objective entropy depletion as the optimization objectives. In this way, a method for selecting the optimization objectives according to the design requirements was obtained. The multi -objective topological structure (Case 3) with uniform tree -shaped fins (Case 4) and gradient tree -shaped fins (Case 5) was applied to the LHS system, and the finite element analysis method was used to construct a mathematical model of the LHS system to comprehensively analyze the heat storage/release process. The results showed that the complete melting times for Case 3, Case 4, and Case 5 were 751 s, 1005 s, and 920 s, respectively. At 751 s, the average heat storage capacities for Case 3, Case 4, and Case 5 are 296.81 W, 216.94 W, and 238.92 W, respectively. Compared to Case 4, Case 3 decreased the complete melting time by 25.27 % and increased the average heat storage capacity by 36.82 %. At heat -releasing times of 500 s, 1000 s, 1500 s, and 2000 s, the maximum differences in liquid phase rates for the three models were 10.93 %, 11.97 %, 11.51 %, and 9.57 %, respectively. From the perspective of the field synergy, Case 3 showed a better heat transfer path and the optimal heat transfer effect considering the temperature, liquid phase rate, heat storage/release time, and heat storage/release capacity. In addition, the dimensionless criterion equation affecting the liquid phase rate was obtained by segmented fitting of the heat transfer process of the topology -optimized LHS system. The findings of the study can facilitate the promo

关键词： Latent heat storage Topology Heat storage/release optimization objective Entransy Field synergy

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Analysis and Comparison of the Vibration Correction Accuracy of Different optimization objectives for the Classical Absolute Gravimeter

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IEEE TRANSACTIONS ON INSTRUMENTATION AND MEASUREMENT 2021年 70卷 1-10页

作者： Li, Zhenxing Wu, Kang Guo, Meiying Wen, Yi Chen, Yicong Wang, Lijun Tsinghua Univ State Key Lab Precis Measurement Technol & Instru Beijing 100084 Peoples R China Tsinghua Univ Dept Precis Instrument Beijing 100084 Peoples R China

Accurate absolute gravimeters are important instruments in applications, such as metrology, geophysics, and geological exploration. Vibration is one of the limiting factors that cause deterioration in measurement accuracy, which includes trueness and precision. The vibration correction method, in which a seismometer is used to record the vibration, provides an effective method to deal with the disturbances. The theoretical analysis shows that the ultimate correction accuracy is limited by the inherent frequency performance of the seismometer. The correction algorithm is an optimization problem to achieve this ultimate accuracy. The selection of the optimization objectives affects the correction accuracy dramatically. Although the real gravitational acceleration is unknown before the measurement is taken, minimization of the standard deviation of the fitting residual for a single drop (SDFRSD) is proven to realize better trueness. Enhanced precision is achieved through minimization of the Type A uncertainty of gravitational accelerations for all drops (UGAAD). Simulations and experimental measurements with the T-1 absolute gravimeter verify the theoretical analysis results. In addition, the results also show that the SDFRSD correction contains the real gravitational acceleration value, while the UGAAD correction exceeds the valid range. Therefore, the SDFRSD correction approach provides better comprehensive accuracy than the UGAAD correction method.

关键词： Absolute gravimeter accuracy analysis optimization objective vibration correction

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Optimizing Audio-Visual Speech Enhancement Using Multi-Level Distortion Measures for Audio-Visual Speech Recognition

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IEEE-ACM TRANSACTIONS ON AUDIO SPEECH AND LANGUAGE PROCESSING 2024年 32卷 2508-2521页

作者： Chen, Hang Wang, Qing Du, Jun Yin, Bao-Cai Pan, Jia Lee, Chin-Hui Univ Sci & Technol China Natl Engn Res Ctr Speech & Language Informat Proc Hefei 230026 Peoples R China iFLYTEK Res Hefei 230088 Peoples R China Georgia Inst Technol Sch Elect & Comp Engn Atlanta GA 30332 USA

A multi-level distortion measure (MLDM) is proposed as an objective to optimize deep neural network-based speech enhancement (SE) in both audio-only and audio-visual scenarios. The aim is to achieve simultaneous performance improvements in speech quality, intelligibility, and recognition error reductions. Moreover, a comprehensive correlation analysis shows that these three evaluation metrics exhibit high Pearson correlation coefficient (PCC) values with three commonly used optimization objectives: the mean squared error between the ideal ratio and estimated magnitude masks, scale-invariant signal-to-noise ratio, and cross-entropy-guided measure. To further improve the performance, we leverage the complementarities of the three objectives and propose another correlated multi-level distortion measure (C-MLDM) defined as a weighted combination of MLDM and an average correlation measure based on the three PCCs. Experimental results on the TCD-TIMIT corpus corrupted by additive noise demonstrate that MLDM outperforms systems optimized with each objective in both audio-visual and audio-only scenarios, offering improved performances in all three metrics: speech quality, intelligibility, and recognition performance. C-MLDM also consistently outperforms MLDM in all test cases. Finally, the generalizability of both MLDM and C-MLDM is confirmed through extensive testing across diverse datasets, SE model architectures, and linguistic conditions.

关键词： Audio-visual optimization objective robust speech recognition speech enhancement task-generic

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Multilabel Feature Selection Based on Fuzzy Mutual Information and Orthogonal Regression

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IEEE TRANSACTIONS ON FUZZY SYSTEMS 2024年第9期32卷 5136-5148页

作者： Dai, Jianhua Liu, Qi Chen, Wenxiang Zhang, Chucai Hunan Normal Univ Hunan Prov Key Lab Intelligent Comp & Language Inf Changsha 410081 Peoples R China Hunan Normal Univ Coll Informat Sci & Engn Changsha 410081 Peoples R China

With the increase of high-dimensional multilabel data, multilabel feature selection (MFS) has received more and more widespread attention. Embedded feature selection methods have been widely studied due to their high efficiency and low computational cost. Fuzzy mutual information, as an effective tool for processing continuous features, is widely used in filter feature selection, which results in many repeated entropy calculations. Most of the existing multilabel embedded feature selection methods are based on least squares regression, which loses a lot of statistical and structural information. To solve the above-mentioned problems, we established an optimization framework based on fuzzy mutual information that considers global correlation to obtain the weight of each feature. Under this framework, many repeated entropy operations are avoided. Then, the weight of each feature is introduced into the orthogonal regression optimization framework as prior knowledge. Finally, two optimization frameworks are comprehensively considered for MFS. Furthermore, considering the characteristics of multilabel data, we extend the proposed method to feature-specific MFS. We conducted sufficient experiments to demonstrate the efficiency of our proposed method.

关键词： Correlation Mutual information Feature extraction optimization Redundancy Fuzzy systems Vectors Feature selection fuzzy rough sets multilabel learning mutual information optimization objective

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Control of Discrete Event Systems by Using Symbolic Transition Model: An Application to Power Grids

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ARABIAN JOURNAL FOR SCIENCE AND ENGINEERING 2025年第2期50卷 937-949页

作者： Ozbaltan, Mete Erzurum Tech Univ Comp Engn Erzurum Turkiye

In this paper, a new symbolic modeling framework is proposed for the control of discrete event systems (discrete controller synthesis). Reactive infinite-state systems are generally dynamic systems with inputs and outputs. Modeling the outputs in existing symbolic modeling methods for reactive infinite-state systems has not been extensively discussed in the literature. It is crucial to realistically model the outputs and obtain reliable controllers. One of the main contributions and innovations in this study is the ability to symbolically model their output. In this direction, symbolic transition models are offered, where events are defined as guarded symbolic transitions. The framework considers input/output reactive infinite-state systems to satisfy safety and optimization objectives. Effective algorithms and safety control policies are offered to solve the safety control problem (i.e., satisfy the safety objective) for input/output infinite-state systems. Another contribution in this work provides optimization targets within a given cost function based on state transitions, without specifying the target states. The framework is then applied to power grids to demonstrate the effectiveness of the symbolic transition models and experimentally evaluate the new control algorithms. The results showed that the approach is very effective compared to other approaches found in the literature. The computation times required to achieve both safety and optimization objectives are obtained relatively quickly compared to other deterministic methods found in the literature.

关键词： Symbolic discrete controller synthesis Safety objective optimization objective Power grids

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Analysis and optimization of impact energy absorption performance of mine refuge chamber filled with concave triangular negative poisson's ratio material

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LATIN AMERICAN JOURNAL OF SOLIDS AND STRUCTURES 2023年第3期20卷

作者： Yang, Kun Chen, Yiwen Wang, Yibo Chen, Hao Wang, Shourui Liaoning Univ Technol Fac Mech Engn & Automat Jinzhou 121000 Peoples R China

In this paper, negative poisson's ratio material is used to fill the interlayer of mine refuge chamber, and its characteristics such as light weight, thermal insulation, vibration isolation and impact resistance are used to improve the impact resistance and thermal insulation ability of mine refuge chamber. The equivalent density, elastic modulus and yield strength of negative poisson's ratio structure of material Q345 were obtained by simulation analysis. The negative poisson's ratio material was filled into the mine refuge chamber, and the impact energy absorption and explosion transient thermal analysis were carried out. The results show that compared with the prototype, the maximum inner skin temperature of the negative poisson's ratio refuge chamber is reduced by 44.86%, the transverse and longitudinal stiffeners temperature is reduced by nearly 46.77%, and the impact deformation is reduced by 35mm, which has better safety performance. The response surface optimization method was used to optimize the whole refuge chamber filled with negative poisson's ratio material, which was more secure than before.

关键词： Mine refuge chamber Negative poisson's ratio material Thermal insulation Safety performance optimization objective

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optimization strategy using corresponding-point methodology (CPM) concerning finite time and heat conduction rate for CAES systems

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ENERGY 2023年第1期266卷

作者： Guo, Huan Xu, Yujie Huang, Lujing Sun, Jianting Chen, Haisheng Chinese Acad Sci Inst Engn Thermophys 11 Beisihuanxi Rd Beijing 100190 Peoples R China Chinese Acad Sci Nanjing Inst Future Energy Syst Inst Engn Thermophys 266 Chuangyan Rd Nanjing 211135 Peoples R China Univ Chinese Acad Sci 19 A Yuquan Rd Beijing 100049 Peoples R China

System optimization methodology is an effective way to increase the efficiency of thermal system. However, at present, the multi processes of advanced compressed air energy storage (CAES) system are strongly coupled with many parameters, and the previous optimization methods lack considering the physical connection between energy storage and energy release processes, which leads to the unclear optimization direction sometimes and the failure of traditional mathematical optimization algorithm when parameters are strongly coupled and in a large scale. In this paper, an optimization strategy based on the corresponding-point methodology (CPM) for CAES systems is established, and the overall evaluation index, Mg is modified. In order to make the optimization results closer to reality, the concepts of finite time/size are introduced, and the optimization case of under-water CAES system is analyzed. Results show that under the constraint of the corresponding quotient, with the increase of the limit value of the corresponding quotient, the maximum value of the system efficiency gradually increases, which proves the effectiveness of the proposed optimization strategy. The influence mechanism of the key parameters on the optimization results is revealed. When the pressure-effectiveness correlative coefficient, C* changes, there is a compromise between the pressure loss and effectiveness of the heat exchanger. The mixing of hot water at all compression parts breaks the corresponding limit of each compressor and expander, resulting in parameters among all compressor/expanders parts that need to balance due to the mixing.

关键词： Corresponding-point methodology Finite-time thermodynamics Compressed air energy storage optimization optimization objective

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A novel Multi-Label Leaming Approach for Missing and Noisy Labels 5

A novel Multi-Label Leaming Approach for Missing and Noisy L...

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5th International Conference on Robotics, Intelligent Control and Artificial Intelligence, RICAI 2023

作者： Yang, Xiaolei Liu, Kai Gu, Shenming Tan, Anhui Zhejiang Ocean University Key Laboratory of Oceanographic Big Data Mining and Application of Zhejiang Province Zhoushan316022 China

ISBN: (纸本)9798350357950

Recently, many scholars have shown a strong interest in weak-supervised multi-label learning, to solving which idealizing label information is a common approach. However, in real life, we cannot obtain the complete labels of instances. In addition, the obtained labels may contain noise, which can reduce the performance of the algorithms. To address the above issues, we introduce MLML, a novel multi-label learning method which is designed specifically to handle missing labels and noisy labels simultaneously. Our method involves the following several steps. Firstly, we utilize the global information of multi-label data to construct a label correlation matrix. Through this matrix, we can better understand the association and influence between different labels. Secondly, in order to mitigate the impact of noisy labels, we introduce label popularity normalization, which improves the performance of the algorithm by considering the frequency of labels in the data. Finally, we improve the method by integrating positive and negative label information. We also consider the relationship between feature similarity and label similarity, which ensures that our method not only considers the information of a single label, but also the mutual influence between labels and the association between features and labels. Based on extensive experiments conducted on multiple datasets, our algorithm MLML has demonstrated comparable performance to state-of-the-art algorithms. © 2023 IEEE.

关键词： feature collaboration label collaboration multi-label noisy label optimization objective

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The evolution of the cold chain logistics vehicle routing problem:a bibliometric and visualization revie

Digital Transportation and Safety

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Digital Transportation and Safety 2024年第3期3卷 92-114页

作者： Bo Qi Guangyu Li School of Traffic and Transportation Lanzhou Jiaotong UniversityLanzhou 730070China

This paper uses the bibliometric analysis software CiteSpace to examine the current status and evolution of cold-chain logistics vehicle routing problems(CCVRP).7381 relevant articles published in the Web of Science core collection from 2008 to 2024 were analyzed,an in-depth understanding of the publication trends and category distribution were ***,CiteSpace was used to create a scientific knowledge graph and perform visualization *** analysis includes collaboration among authors,countries,and institutions;co-citation analysis of authors,journals,and references;citation burst detection of keywords;and co-citation cluster analysis of *** on a deep understanding of current research hotspots,an in-depth discussion of existing research was conducted from three perspectives:optimization objectives,distribution scenarios,and solution *** results show that CCVRP involves complex factors such as temperature requirements,time window constraints,and multi-objective *** intricate constraints are causing research to become increasingly interdisciplinary and *** evolution of hot topics shows that the research directions span multiple fields,from algorithm design to logistics *** review helps researchers better understand the history,current status,and future development directions of CCVRP research,and provides valuable references and inspiration for academia and practice.

关键词： Cold chain logistics Vehicle routing Carbon emissions optimization objective Solution algorithm

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