Petroleum and Natural Gas still represent a considerable share in terms of energy consumption in the current global matrix, so that its exploration/exploitation is present in the market and driving activities in locat...Petroleum and Natural Gas still represent a considerable share in terms of energy consumption in the current global matrix, so that its exploration/exploitation is present in the market and driving activities in locations of specific complexities, as the ones along unconventional hydrocarbon resources from the Brazilian pre-salt. The daily cost of well drilling under harsh conditions can exceed US $1 million a day, turning any type of downtime or necessary maintenance during the activities to be very costly, moment in which processes optimization starts to be a key factor in costs reduction. Thus, new technologies and methods in terms of automating and optimizing the processes may be of great advantages, having its impact in total related project costs. In this context, the goal of this research is to allow a computation tool supporting achieving a more efficient drilling process, by means of drilling mechanics parameters choosiness aiming rate of penetration (ROP) maximization and mechanic specific energy (MSE) minimization. Conceptually, driven by the pre-operational drilling test curve trends, the proposed system allows it to be performed with less human influences and being updateable automatically, allowing more precision and time reduction by selecting optimum parameters. A Web Operating System (Web OS) was designed and implemented, running in online servers, granting accessibility to it with any device that has a browser and internet connection. It allows processing the drilling parameters supplied and feed into it, issuing outcomes with optimum values in a faster and precise way, allowing reducing operating time.展开更多
Lupus Nephritis(LN)is a significant risk factor for morbidity and mortality in systemic lupus erythematosus,and nephropathology is still the gold standard for diagnosing LN.To assist pathologists in evaluating histopa...Lupus Nephritis(LN)is a significant risk factor for morbidity and mortality in systemic lupus erythematosus,and nephropathology is still the gold standard for diagnosing LN.To assist pathologists in evaluating histopathological images of LN,a 2D Rényi entropy multi-threshold image segmentation method is proposed in this research to apply to LN images.This method is based on an improved Cuckoo Search(CS)algorithm that introduces a Diffusion Mechanism(DM)and an Adaptiveβ-Hill Climbing(AβHC)strategy called the DMCS algorithm.The DMCS algorithm is tested on 30 benchmark functions of the IEEE CEC2017 dataset.In addition,the DMCS-based multi-threshold image segmentation method is also used to segment renal pathological images.Experimental results show that adding these two strategies improves the DMCS algorithm's ability to find the optimal solution.According to the three image quality evaluation metrics:PSNR,FSIM,and SSIM,the proposed image segmentation method performs well in image segmentation experiments.Our research shows that the DMCS algorithm is a helpful image segmentation method for renal pathological images.展开更多
文摘Petroleum and Natural Gas still represent a considerable share in terms of energy consumption in the current global matrix, so that its exploration/exploitation is present in the market and driving activities in locations of specific complexities, as the ones along unconventional hydrocarbon resources from the Brazilian pre-salt. The daily cost of well drilling under harsh conditions can exceed US $1 million a day, turning any type of downtime or necessary maintenance during the activities to be very costly, moment in which processes optimization starts to be a key factor in costs reduction. Thus, new technologies and methods in terms of automating and optimizing the processes may be of great advantages, having its impact in total related project costs. In this context, the goal of this research is to allow a computation tool supporting achieving a more efficient drilling process, by means of drilling mechanics parameters choosiness aiming rate of penetration (ROP) maximization and mechanic specific energy (MSE) minimization. Conceptually, driven by the pre-operational drilling test curve trends, the proposed system allows it to be performed with less human influences and being updateable automatically, allowing more precision and time reduction by selecting optimum parameters. A Web Operating System (Web OS) was designed and implemented, running in online servers, granting accessibility to it with any device that has a browser and internet connection. It allows processing the drilling parameters supplied and feed into it, issuing outcomes with optimum values in a faster and precise way, allowing reducing operating time.
基金supported in part by the Natural Science Foundation of Zhejiang Province(LZ22F020005,LTGS23E070001)National Natural Science Foundation of China(62076185,U1809209).
文摘Lupus Nephritis(LN)is a significant risk factor for morbidity and mortality in systemic lupus erythematosus,and nephropathology is still the gold standard for diagnosing LN.To assist pathologists in evaluating histopathological images of LN,a 2D Rényi entropy multi-threshold image segmentation method is proposed in this research to apply to LN images.This method is based on an improved Cuckoo Search(CS)algorithm that introduces a Diffusion Mechanism(DM)and an Adaptiveβ-Hill Climbing(AβHC)strategy called the DMCS algorithm.The DMCS algorithm is tested on 30 benchmark functions of the IEEE CEC2017 dataset.In addition,the DMCS-based multi-threshold image segmentation method is also used to segment renal pathological images.Experimental results show that adding these two strategies improves the DMCS algorithm's ability to find the optimal solution.According to the three image quality evaluation metrics:PSNR,FSIM,and SSIM,the proposed image segmentation method performs well in image segmentation experiments.Our research shows that the DMCS algorithm is a helpful image segmentation method for renal pathological images.
