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Wind speed modeling for cascade clusters of wind turbines part 1: The cascade clusters of wind turbines

ENERGY 2020年 205卷 118097-118097页

作者： Dong, Xinghui Li, Jia Gao, Di Zheng, Kai North China Elect Power Univ Sch Energy Power & Mech Engn Beinong Rd 2 Beijing 102206 Peoples R China

Wind energy conversion efficiency has always been an important issue for wind farms. And wind speed calculation is the basic task and key work of wind energy conversion optimization. The cascade clusters of wind turbines are directly related to wind speed, and affected by the terrain, wake disturbance, location distribution and other factors. So it is very difficult to adopt parameter modeling. The cascade characteristics among cluster wind turbines (WTs) are embodied in historical operation data of the WTs. Taking the input wind direction as the initial parameter, we construct the WTs location correlation matrix of the neighborhood distribution relationship of WTs location;we then obtain the correlation relationship of the WTs production wind speed and power by combining the WTs production monitoring data. At the same time, "coupling element" and "aggregation element" WTs can be obtained from the cascade clusters. By verifying the data of a large wind farm, the model proposed in this paper clarifies the relationship between the wind speed and the cascade clusters;using this model, we can calculate the cluster distribution under different wind conditions. It is highly practical and can be applied to other wind farms to support formulation of the efficiency optimization strategies. (C) 2020 Elsevier Ltd. All rights reserved.

关键词： Cascade clusters of wind turbines Cascade characteristics Spectral clustering segmentation algorithm

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Quantitative characterization of single-phase flow through rough-walled fractures with variable apertures

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GEOMECHANICS AND GEOPHYSICS FOR GEO-ENERGY AND GEO-RESOURCES 2020年第3期6卷 1-14页

作者： Dong, Jiabin Ju, Yang China Univ Min & Technol State Key Lab Geomech & Deep Underground Engn 1 Univ Ave Xuzhou 221116 Jiangsu Peoples R China China Univ Min & Technol Beijing State Key Lab Coal Resources & Safe Min D11 Xueyuan Rd Beijing 100083 Peoples R China China Univ Min & Technol Frontier Sci Res Fluidized Min Deep Underground R 1 Univ Ave Xuzhou 221116 Jiangsu Peoples R China China Univ Min & Technol Beijing State Key Lab Geomech & Deep Underground Engn State Key Lab Coal Resources & Safe Min D11 Xueyuan Rd Beijing 100083 Peoples R China

Fluid flow through rock media is highly significant in underground water management, the geothermal recovery process, and various underground engineering applications. Fractures have a critical effect on the fluid flow through low-permeability rocks since they serve as the major flow channels in the rock formation. Consequently, the evaluation of fracture permeability is crucial to many engineering applications, such as the geothermal recovery process, exploitation of hydrocarbon resources, and various underground engineering applications. However, fluid flow through rough fractures is complex under the effects of rough profiles and variable apertures. The variation of fracture apertures causes the nonlinear distribution of the pressure along the fracture and thus intensifies the difficulties of studying the flow in fractures. In this study, variable-aperture fractures were simplified as axisymmetric fractures using the Weierstrass-Mandelbrot function. To address the nonlinear distribution of pressure caused by aperture variations, a method is proposed to segment fractures with variable lengths by considering the weights of fracture apertures. With the segmented results, we evaluated the permeability of rough fractures using a modified local law. The evaluation results aligned with the lattice Boltzmann simulation results. Finally, combining the analytical solution of flow through asymmetric fractures with sinusoidal profiles, the proposed methods were thereby validated.

关键词： Rough-walled fractures Local cubic law Lattice Boltzmann method segmentation algorithm Variable apertures

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Optimizing rat and human blood cells sampling for in silico morphometric analysis

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ACTA HISTOCHEMICA 2022年第6期124卷 151917页

作者： Zamora-Bello, Isaac Hernandez-Baltazar, Daniel Rodriguez-Landa, Juan Francisco Rivadeneyra-Dominguez, Eduardo Univ Veracruzana Fac Quim Farmaceut Biol Xalapa Veracruz Mexico Consejo Nacl Ciencia & Tecnol CONACyT Mexico City Mexico Univ Veracruzana Inst Neuroetol Xalapa Veracruz Mexico Univ Veracruzana Fac Quim Farmaceut Biol Circuito Gonzalo Aguirre Beltran S-NZona Univ Xalapa 91000 Veracruz Mexico

Measurements of Morphometric Parameters of the Blood Cells (MPBC) are key for the diagnosis of both mental and metabolic diseases. Several manual approaches or computational methodologies are useful to provide reliable clinical diagnosis. The sample processing and data analysis is relevant, however the sample handling on the pre-analytical phase remains scarcely evaluated. The main goal of this study was to favor the preservation of blood smear using a histological resin. This strategy lead us two practical approaches, give a detailed morphometric description of white blood cells and establish reference intervals in male Wistar rats, which are scarcely reported. Blood smears from male Wistar rats (n = 120) and adult men were collected at room temperature. The integrity of Wright-stained cells was evaluated by an in silico image analysis from rat and human blood smear preserved with a toluene-based synthetic resin mounting medium. A single sample of human blood was used as a control of procedure. The reference intervals was established by cell counting. Based on the results of segmentation algorithm followed by an automatic thresholding analysis, the incorporation of resin favor the conservation of cell blood populations, and lead to identify morphologic features such as nucleus/cytoplasmic shape, granules presence and DNA appearance in nucleus of white blood cells. The use of a histological resin could favor a fast and efficient sample handling in silico MPBC measurements both in the species studied as in wild animals.

关键词： Automatic thresholding Blood smear examination Hematic cytometry Human segmentation algorithm Wistar rat

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A Method of Segmenting Apples Based on Gray-Centered RGB Color Space

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REMOTE SENSING 2021年第6期13卷 1211-1211页

作者： Fan, Pan Lang, Guodong Yan, Bin Lei, Xiaoyan Guo, Pengju Liu, Zhijie Yang, Fuzeng Northwest A&F Univ Coll Mech & Elect Engn Yangling 712100 Shaanxi Peoples R China Baoji Univ Arts & Sci Sch Comp Sci & Technol Baoji 721016 Peoples R China Shannxi Key Lab Apple Yangling 712100 Shaanxi Peoples R China Apple Mech Res Base Yangling 712100 Shaanxi Peoples R China State Key Lab Soil Eros & Dryland Farming Loess P Yangling 712100 Shaanxi Peoples R China

In recent years, many agriculture-related problems have been evaluated with the integration of artificial intelligence techniques and remote sensing systems. The rapid and accurate identification of apple targets in an illuminated and unstructured natural orchard is still a key challenge for the picking robot's vision system. In this paper, by combining local image features and color information, we propose a pixel patch segmentation method based on gray-centered red-green-blue (RGB) color space to address this issue. Different from the existing methods, this method presents a novel color feature selection method that accounts for the influence of illumination and shadow in apple images. By exploring both color features and local variation in apple images, the proposed method could effectively distinguish the apple fruit pixels from other pixels. Compared with the classical segmentation methods and conventional clustering algorithms as well as the popular deep-learning segmentation algorithms, the proposed method can segment apple images more accurately and effectively. The proposed method was tested on 180 apple images. It offered an average accuracy rate of 99.26%, recall rate of 98.69%, false positive rate of 0.06%, and false negative rate of 1.44%. Experimental results demonstrate the outstanding performance of the proposed method.

关键词： fruit detection fruit segmentation color space segmentation algorithm

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Robust Iris Recognition Framework Using Computer Vision algorithms 4

Robust Iris Recognition Framework Using Computer Vision Algo...

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4th International Conference on Smart Grid and Smart Cities (ICSGSC)

作者： Hussein, Nashwan Jasim Al Furat Al Awsat Tech Univ Tech Coll Management Najaf Iraq

ISBN: (纸本)9781728194042

Nowadays under human observations iris recognition is playing an essential role, it observed that there are some points are very essential for this method like accuracy, efficiency & processing time. There are several problems has been recorded for this kind of technique. Under previous researches, many concepts have been reported for iris-based segmentation, classification & feature extraction techniques. This research dealt with implementing a novel framework of robust iris segmentation utilizing computer vision technique, FFNN classifier & hybrid feature extraction technique. For the non-iris images method of the novel iris, segmentation has been proposed in this paper. The technique of novel iris segmentation based on 2 methods regards pupil segmentation, after that fusion of enhancing & shrinking visible contour has been framed for segmentation of iris through collaborating novel burden forcing for visible contour model. Moreover, then UN wrapped iris segmentation performed well with the technique of normalization non-circular iris. Whatever, for better iris segmentation research, utilized a proposed method of feature extraction under Discrete Wavelet Transform, letter utilized geometric & texture features of the segmented image. Achieved features have collaborated through a vector of a hybrid feature. For the reason of recognition, we are utilizing a vision algorithm with an FFNN classifier. This paper focused on the concepts related to a robust iris recognition framework using a vision algorithm. Daugman demodulates the yield of the Gabor channels to pack the information. It separates the stage data into four levels and for every conceivable quadrant in-plane to get a minimal 256-byte layout, which takes into consideration proficient capacity and correlation of irises. Experimental outputs have been described as the proposed robust iris segmentation method adopted greater accuracy on the challenging segmentation algorithm thousand databases.

关键词： Iris recognition segmentation algorithm Vision algorithm robust segmentation vision computer method

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Development and clinical validation of a prognostic algorithm for stroma-tumor ratio quantification in non-small cell lung cancer

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Lung Cancer 2025年

作者： Waleed K.M. Ahmad Tillmann Bedau Yuan Wang Sebastian Michels Anna Rasokat Jürgen Wolf Matthias Heldwein Simon Schallenberg Alexander Quaas Reinhard Büttner Yuri Tolkach Institute of Pathology University Hospital Cologne Cologne Germany Medical Faculty University of Cologne Cologne Germany Clinic I of Internal Medicine Center for Integrated Oncology Germany Department of Cardiothoracic Surgery University Hospital Cologne Germany Institute of Pathology Charité University Hospital Berlin Germany

Background and Aim Lung cancer is the leading cause of cancer-related mortality worldwide, highlighting the importance of refining diagnostic modalities. This study’s main focus is the development of a digital pathology, prognostic algorithm for fully automatized quantification of stroma-tumor ratio (STR) in patients with resectable non-small cell lung cancer (NSCLC). Materials and Methods The developed STR algorithm is built upon a powerful multi-class tissue segmentation algorithm that generates precise maps of the full tumor region. One retrospective exploration cohort of NSCLC patients (n = 902) and three validation cohorts (n = 784) of patients with lung adenocarcinoma (LUAD) and squamous cell carcinoma (LUSC) were included to identify and validate optimal prognostic cut-offs and different risk stratification methods with regard to different clinical endpoints: overall survival (OS), cancer-specific survival (CSS) and progression-free survival (PFS). Results For LUAD, we show that the minimal STR value for the whole case is decisive for prognostic evaluation. Different approaches (single STR cut-off, multiple STR cut-offs, using STR as a continuous parameter) allow for robust stratification of patients into prognostic risk groups, independent of the classical clinicopathological variables and conventional histological grading. For LUSC, STR may assist in identifying a small subset of patients with unfavorable prognosis (based on the maximum STR for the whole case), however, its prognostic impact varies between cohorts. Conclusion STR quantification in LUAD NSCLC subtype shows a promising role as a prognostic biomarker. It can be easily implemented in routine diagnostics and could be considered as a component of advanced prognostic systems in LUAD. Our results in LUSC cohorts suggest that STR quantification in its current implementation is of limited value in this subtype

关键词： Stroma-tumor ratio (STR) non-small cell lung cancer (NSCLC) segmentation algorithm Digital pathology

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Refined multi-stage segmenatation of the resistance signal from CNT-based sensors for structural strain warning

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Materials Today Communications 2025年

作者： Yiheng Song Yuzhi Liu Yoji Okabe School of Engineering The University of Tokyo Tokyo 113-0033 Japan Institute of Industrial Science The University of Tokyo Tokyo 153-8505 Japan

Piezoresistive carbon nanotube (CNT) sensors have garnered significant attention in structural health monitoring due to their exceptional sensitivity and design flexibility. Most CNT sensors, particularly those dominated by the tunneling effect, exhibit a nonlinear resistance-strain response under uniaxial tension, where the evolution of the conductive network follows a distinct staged pattern, typically categorized into a gradual increase stage, a rapid increase stage, and a breakdown stage. However, existing studies often oversimplify the resistance-strain relationship, either omitting segmentation entirely or relying on subjectively determined inflection points, which limits the practical utilization of these features. In this study, an inflection point identification algorithm was developed based on the cumulative growth rate, which automatically extracts the transition inflection point between the first two stages and assigns its corresponding strain as the pre-warning strain threshold. This approach has the potential to meet the demand for early warning in structural health monitoring. Experimental validation was conducted using CNT/thermoplastic polyurethane (TPU) sensors fabricated through a coating process, confirming the algorithm's reliability and the reproducibility of the inflection phenomenon. The results indicated that the strain warning threshold of the fabricated sensors falls within the range of 0.44–1.14%, aligning well with the initial damage strain range of carbon fiber-reinforced polymer (CFRP) structures, facilitating the detection of matrix cracking, fiber breakage, and interlayer delamination. Furthermore, by adjusting the coating thickness and CNT content, the tunability of the inflection point position was revealed, leading to an initial parameter design guideline that provides flexible solutions for diverse engineering applications.

关键词： carbon nanotube sensor strain sensor nonlinear signal segmentation algorithm structural strain warning

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A MapX-based segmentation algorithm of Region Feature by Polyline

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INTERNATIONAL JOURNAL OF ONLINE ENGINEERING 2013年第SPL.ISSUE4期9卷 59-63页

作者： Wu, Da-Sheng Zhejiang Univ Inst Remote Sensing & Informat Syst Applicat Hangzhou 310029 Zhejiang Peoples R China Zhejiang A&F Univ Linan Zhejiang Peoples R China

MapX didn't provide a ready function which can be easy to split region feature in the client. The objective of this study was to design a segmentation algorithm for cutting region feature with polyline. In order to convenience the description, during the segmentation, only 2 intersection points were taken into consideration. According to the order of P1(the first intersection point) and P2(the second intersection point) in the R(region feature) and L(polyline feature), 4 kinds of situations had been taken into account, those were respectively, P2 was always after P1 in the R and L, P2 was after P1 in the R but P2 was before P1 in the L, P2 was always before P1 in the R and L, and P2 was before P1 in the R but P2 was after P1 in the L. segmentation results showed that the algorithm was stable and reliable.

关键词： MapX Forest resource Region feature segmentation algorithm

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A Parallelizable Framework for Segmenting Piecewise Signals

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IEEE ACCESS 2019年 7卷 13217-13229页

作者： Duan, Junbo Soussen, Charles Brie, David Idier, Jerome Wang, Yu-Ping Wan, Mingxi Xi An Jiao Tong Univ Dept Biomed Engn Xian Shaanxi Peoples R China Univ Paris Sud Cent Supelec CNRS Univ Paris Saclay Lab Signaux & Syst F-91192 Gif Sur Yvette France Univ Lorraine CNRS Ctr Rech Automat Nancy Lorraine France Ecole Cent Nantes Lab Sci Numer Nantes Nantes France Tulane Univ Dept Biomed Engn New Orleans LA 70118 USA

Piecewise signals appear in many application fields. Here, we propose a framework for segmenting such signals based on the modeling of each piece using a parametric probability distribution. The proposed framework first models the segmentation as an optimization problem with sparsity regularization. Then, an algorithm based on dynamic programming is utilized for finding the optimal solution. However, dynamic programming often suffers from a heavy computational burden. Therefore, we further show that the proposed framework is parallelizable and propose using GPU-based parallel computing to accelerate the computation. This approach is highly desirable for the analysis of large volumes of data that are ubiquitous. The experiments on both the simulated and real genomic datasets from the next-generation sequencing demonstrate an improved performance in terms of both segmentation quality and computational speed.

关键词： Parallel computing piecewise distribution segmentation algorithm dynamic programming next generation sequencing

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A novel image analysis algorithm reveals that media conditioned with chitosan and platelet-rich plasma biomaterial dose dependently increases fibroblast migration in a scratch assay

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BIOMEDICAL PHYSICS & ENGINEERING EXPRESS 2020年第6期6卷 065021-065021页

作者： Ahunon, Laura Milano, Fiona Chevrier, Anik Lavertu, Marc Polytech Montreal Biomed Engn Inst Montreal PQ Canada Ecole Natl Super Mines Mat Sci & Engn Dept Nancy France Polytech Montreal Chem Engn Dept Montreal PQ Canada

Chitosan (CS) and Platelet-Rich Plasma (PRP) both display interesting properties for wound healing applications. A hybrid CS-PRP biomaterial was previously developped, consisting of a freeze dried CS formulation solubilized in PRP that promotes tissue repair and regeneration. The purpose of the current study was to investigate the ability of the CS-PRP biomaterial to stimulate cell migration in vitro. Scratch assays revealed that CS-PRP significantly stimulates the migration rate of cells compared to cells in culture medium but not differently than PRP alone. The increase in the migration rate is dose-dependent at low dose and reaches a plateau corresponding with maximum cell motility. Cell migration rate as a function of the number of platelets that have degranulated in culture medium (to which total concentration of growth factors contributing to cell response is proportionnal), follows a modified Hill model. To analyze photographs taken during the assay and follow cell migration, an open source image analysis algorithm was developed: SAMScratch (Systematic Area Measurement of Scratch - available here: . Compared with other existing analysis tools, the algorithm is precise in the determination of the scratch area and performs equally well with usual and challenging images. This study resulted in the creation of a freely available application for scratch assay analysis and provided evidence that CS-PRP implants hold promise for treatment of wounds.

关键词： chitosan Platelet-rich plasma scratch assay growth factors segmentation algorithm in vitro cell migration Hill binding model

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