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Sunspot Group Detection and Classification by Dual Stream Convolutional Neural Network Method

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Research in Astronomy and Astrophysics 2024年第9期24卷 248-259页

作者： Nyasha mariam Mkwanda Weixin Tian Junlin Li Hubei Key Laboratory of Intelligent Vision Based Monitoring for Hydroelectric Engineering China Three Gorges UniversityYichang 443002China College of Computer and Information Technology China Three Gorges UniversityYichang 443002China

The automatic detection and analysis of sunspots play a crucial role in understanding solar dynamics and predicting space weather *** paper proposes a novel method for sunspot group detection and classification called the dual stream Convolutional Neural Network with Attention Mechanism(DSCNN-AM).The network consists of two parallel streams each processing different input data allowing for joint processing of spatial and temporal information while classifying *** takes in the white light images as well as the corresponding magnetic images that reveal both the optical and magnetic features of *** extracted features are then fused and processed by fully connected layers to perform detection and *** attention mechanism is further integrated to address the“edge dimming”problem which improves the model’s ability to handle sunspots near the edge of the solar *** network is trained and tested on the SOLAR-STORM1 data *** results demonstrate that the DSCNN-AM achieves superior performance compared to existing methods,with a total accuracy exceeding 90%.

关键词： Sun:magnetic fields Sun:flares (Sun:)sunspots DSCNN Attention mechanism Edge dimming

Endoscopic treatment of scarred polyps with a non-thermal device(Endorotor):A review of the literature

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World Journal of Gastroenterology 2024年第12期30卷 1706-1713页

作者： mariam Zaghloul Hameed Rehman Stefano Sansone Konstantinos Argyriou Adolfo Parra-Blanco Department of Hepatology Gastroenterology and Infectious DiseasesKafrelsheikh UniversitKafr-Elshikh 33516Egypt Department of Gastroenterology Service Nottingham City Hospital CampusNottingham University Hospitals NHS TrustNottingham NG51PBUnited Kingdom Department of Gastroenterology University Hospital of LarissaLarissa 41334Greece NIHR Nottingham Biomedical Research Centre Nottingham University Hospitals NHS Trust and University of NottinghamNottingham NG72UHUnited Kingdom

Endoscopic resection(ER)of colorectal polyps has become a daily practice in most endoscopic units providing a colorectal cancer screening program and requires the availability of local experts and high-end endoscopic *** procedures have evolved over the past few years from endoscopic mucosal resection(EMR)to more advanced techniques,such as endoscopic submucosal dissection and endo-scopic full-thickness *** resection and disease eradication are the ultimate goals of ER-based techniques,and novel devices have been developed to achieve these *** EndoRotor®Endoscopic Powered Resection System(Interscope Medical,Inc.,Northbridge,Massachusetts,United States)is one such *** EndoRotor is a powered resection tool for the removal of alimentary tract mucosa,including post-EMR persistent lesions with scarring,and has both CE Mark and FDA *** review covers available published evidence documenting the usefulness of EndoRotor for the management of recurrent colorectal polyps.

关键词： EndoRotor Scarred polyps Recurrent polyps Colorectal cancer Colorectal polyps

Pyomyoma as a Complication of Uterine Artery Embolization (A Case Report)

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Open Journal of Obstetrics and Gynecology 2024年第1期14卷 29-35页

作者： Abrar Tooq Layla Rafeei Nusrat Kazi Safa Hussain Mohamed al-Tabban mariam Mahmood Salmanyia Medical Complex Manama Bahrain

Pyomoyoma is a rare complication of Uterine Artery Embolization (UAE). This case report reflects on this condition. A 45-year-old female, a known case of adenomyosis, presented with intermittent fever and foul vaginal discharge. These symptoms occurred shortly after the patient underwent UAE for menorrhagia secondary to adenomyosis. Computed tomography scan of the abdomen and pelvis aided in the diagnosis of Pyomyoma secondary to UAE. After a trial of broad spectrum antibiotics and Suction and Evacuation of the uterus had little to no help in the patient’s condition, she underwent Total Abdominal Hysterectomy in which a big, organized pus collection was removed from the uterus. Conclusion: Pyomyoma should be considered in the differentials for patients presenting with fever and vaginal discharge post UAE.

关键词： Pyomyoma Uterine Artery Embolization Adenomyosis

Single image super-resolution:a comprehensive review and recent insight

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Frontiers of Computer Science 2024年第1期18卷 139-156页

作者： Hanadi al-MEKHLAFI Shiguang LIU College of Intelligence and Computing Tianjin UniversityTianjin 300350China

Super-resolution(SR)is a long-standing problem in image processing and computer vision and has attracted great attention from researchers over the *** main concept of SR is to reconstruct images from low-resolution(LR)to high-resolution(HR).It is an ongoing process in image technology,through up-sampling,de-blurring,and *** neural network(CNN)has been widely used to enhance the resolution of images in recent *** alternative methods use deep learning to improve the progress of image super-resolution based on ***,we review the recent findings of single image super-resolution using deep learning with an emphasis on distillation knowledge used to enhance image super-resolution.,it is also to highlight the potential applications of image super-resolution in security monitoring,medical diagnosis,microscopy image processing,satellite remote sensing,communication transmission,the digital multimedia industry and video ***,we present the challenges and assess future trends in super-resolution based on deep learning.

关键词： super-resolution deep learning single-image interpolation-based learning-based reconstruction-based

RoGRUT: A Hybrid Deep Learning Model for Detecting Power Trapping in Smart Grids

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Computers, Materials & Continua 2024年第5期79卷 3175-3192页

作者： Farah Mohammad Saad al-Ahmadi Jalal al-Muhtadi Center of Excellence in Information Assurance(CoEIA) King Saud UniversityRiyadh11543Saudi Arabia College of Computer&Information Sciences King Saud UniversityRiyadh11543Saudi Arabia

Electricity theft is a widespread non-technical issue that has a negative impact on both power grids and electricity *** hinders the economic growth of utility companies,poses electrical risks,and impacts the high energy costs borne by *** development of smart grids is crucial for the identification of power theft since these systems create enormous amounts of data,including information on client consumption,which may be used to identify electricity theft using machine learning and deep learning ***,there also exist different solutions such as hardware-based solutions to detect electricity theft that may require human resources and expensive ***-based solutions are presented in the literature to identify electricity theft but due to the dimensionality curse,class imbalance issue and improper hyper-parameter tuning of such models lead to poor *** this research,a hybrid deep learning model abbreviated as RoGRUT is proposed to detect electricity theft as amalicious and non-malicious *** key steps of the RoGRUT are data preprocessing that covers the problem of class imbalance,feature extraction and final theft *** advanced-level models like RoBERTa is used to address the curse of dimensionality issue,the near miss for class imbalance,and transfer learning for *** effectiveness of the RoGRUTis evaluated using the dataset fromactual smartmeters.A significant number of simulations demonstrate that,when compared to its competitors,the RoGRUT achieves the best classification *** performance evaluation of the proposed model revealed exemplary results across *** accuracy achieved was 88%,with precision at an impressive 86%and recall reaching 84%.The F1-Score,a measure of overall performance,stood at 85%.Furthermore,themodel exhibited a noteworthyMatthew correlation coefficient of 78%and excelled with an area under the curve of 91%.

关键词： Electricity theft smart grid RoBERTa GRU transfer learning

Developing a Model for Parkinson’s Disease Detection Using Machine Learning algorithms

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Computers, Materials & Continua 2024年第6期79卷 4945-4962页

作者： Naif al Mudawi Department of Computer Science College of Computer Science and Information SystemNajran UniversityNajran55461Saudi Arabia

Parkinson’s disease(PD)is a chronic neurological condition that progresses over *** start to have trouble speaking,writing,walking,or performing other basic skills as dopamine-generating neurons in some brain regions are injured or *** patient’s symptoms become more severe due to the worsening of their signs over *** this study,we applied state-of-the-art machine learning algorithms to diagnose Parkinson’s disease and identify related risk *** research worked on the publicly available dataset on PD,and the dataset consists of a set of significant characteristics of *** aim to apply soft computing techniques and provide an effective solution for medical professionals to diagnose PD *** research methodology involves developing a model using a machine learning *** the model selection,eight different machine learning techniques were adopted:Namely,Random Forest(RF),Decision Tree(DT),Support Vector Machine(SVM),Naïve Bayes(NB),Light Gradient Boosting Machine(LightGBM),K-Nearest Neighbours(KNN),Extreme Gradient Boosting(XGBoost),and Logistic Regression(LR).Subsequently,the concentrated models were validated through 10-fold Cross-Validation and Receiver Operating Characteristic(ROC)—Area Under the Curve(AUC).In addition,GridSearchCV was utilised to measure each algorithm’s best parameter;eventually,the models were trained through the hyperparameter tuning *** 98%accuracy,LightGBM had the highest accuracy in this ***,KNN,and SVM came in second with 96%***,the performance scores of NB and LR were recorded to be 76%and 83%,*** is to be mentioned that after applying 10-fold cross-validation,the average performance score of LightGBM accounted for 93%.At the same time,the percentage of ROC-AUC appeared at 0.92,which indicates that this LightGBM model reached a satisfactory ***,we extracted meaningful insights and figured out potential gaps on top of *** extracting meaningful in

关键词： Light GBM cross-validation ROC-AUC Parkinson’s disease(PD) SVM and XGBoost

Purification of Produced Water from a Sour Oilfield in South Kuwait. 1. Oil-Water Separation and Industrial Salt Production

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Journal of Water Resource and Protection 2024年第2期16卷 156-180页

作者： Feras al Salem Hessa al Shamsi mariam Mohammed Abdulla alaryani Basmalah Abdelazim Mohamed Khalaf Omnia Elsheikh Vijo Poulose Yosef al Jasem Thies Thiemann Department of Biology United Arab Emirates University Al Ain United Arab Emirates Department of Chemistry United Arab Emirates University Al Ain United Arab Emirates Department of Process & Design Engineering Solid Mechanical Equipment Co Abu Dhabi United Arab Emirates

Produced water from an oil extraction site in South Kuwait was sampled after primary oil – water separation had been carried out. The produced water was filtered through a mixture of activated charcoal and esterified cellulosic material gained from spent coffee grounds as a tertiary adsorption treatment. The earth-alkaline metal ions and heavy metals were separated from the de-oiled produced water by addition of either sodium or potassium hydroxide in the presence of carbon dioxide or by direct addition of solid sodium carbonate. The resulting filtrate gave salt of industrial purity upon selective crystallization on evaporation.

关键词： Produced Water Oil and Gas Adsorption Filtration Crystallization

The optimal semi-analytical modeling for the infinite-conductivity horizontal well performance under rectangular bounded reservoir based on a new instantaneous source function

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Petroleum 2024年第1期10卷 68-84页

作者： Firas A.A.al-Kabbawi Independent scholar LivingstonScotlandUNITED KINGDOM

The main objective of this study is to develop the optimal semi-analytical modeling for the infiniteconductivity horizontal well performance under rectangular bounded reservoir based on a new instantaneous source *** available semi-analytical infinite-conductivity models(ICMs)for horizontal well under rectangular bounded reservoir in literature were developed by applying superposition of pressures in space(SPS).A new instantaneous source function(i.e.,instantaneous uniform-flux segmentary source function under bounded reservoir)is derived to be used instead of SPS to develop the optimal semi-analytical *** new semi-analytical ICM is verified with ICM of Schlumberger[1]and with previous semi-analytical ICMs in terms of bottom hole pressure(BHP)profile and inflow rate distribution along the *** model is also validated with real horizontal wells in terms of inflow rate distribution along the *** results show that the developed model gives the optimal semi-analytical modeling for the infinite-conductivity horizontal well performance under rectangular bounded *** that,high computationalefficiency and high-resolution of wellbore discretization have been achieved(i.e.,wellbore segment number could be tens of hundreds depending on solution requirement).The results also show that at pseudosteady state(PSS)flow regime,inflow rate distribution along the wellbore by previous semi-analytical ICMs is stabilized U-shaped as performance of inflow rate distribution at late radial flow ***,the previous semi-analytical ICMs are incorrectly modeling inflow rate distribution at PSS flow regime due to the negative influence of applying *** optimal semi-analytical ICM is in a general form and real time domain,and can be applicable for 3D horizontal well and 2D vertical fracture well under infinite and rectangular bounded reservoirs,of uniform-flux and infinite-conductivity wellbore conditions at any time of well life.

关键词： Infinite-conductivity model Horizontal well performance Semi-analytical modeling Rectangular bounded reservoir Instantaneous source functions Flow regimes

使用活动形态模型对功能性肺SPECT图像进行自动分割及与相关肺CT图像的比较

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中华核医学与分子影像杂志 2018年第8期38卷 582-582页

作者：唐军 Grigorios-Aris Cheimariotis mariam al-mashat Kostas Haris Anthony H.aletras Jonas J?gi Marika Bajc Nicolaos Maglaveras Einar Heiberg 上海交通大学医学院附属苏州九龙医院核医学科 Laboratory of Computing Medical Informatics and Biomedical-Imaging TechnologiesSchool of MedicineAristotle University of Thessaloniki Department of Clinical Sciences Lund Clinical PhysiologySkane University HospitalLund University Department of Biomedical Engineering Faculty of Engineering Lund University Department of Clinical Physiology Lund University Hospital

目的图像分割对于定量分析肺功能降低、无肺功能区域的范围和程度是必需的。该研究的目的是建立和验证一种肺通气和灌注SPECT图像自动分割方法,并比较自动、手动SPECT图像分割结果与相关CT参考容积的差别。方法 77例患者(69例阻塞性肺... 详细信息

目的图像分割对于定量分析肺功能降低、无肺功能区域的范围和程度是必需的。该研究的目的是建立和验证一种肺通气和灌注SPECT图像自动分割方法,并比较自动、手动SPECT图像分割结果与相关CT参考容积的差别。方法 77例患者(69例阻塞性肺病患者、8例无明显通气、灌注功能受损患者)先行低剂量CT检查,随后行通气/灌注(V/P) SPECT显像。使用57例患者的低剂量CT图像构建2个用于SPECT图像自动分割的活动形态肺模型(右肺和左肺)。在20例患者的SPECT图像中验证相关分割算法,并将其结果与相应的CT图像分割结果进行比较,同时比较SPECT图像自动分割与手动分割的差别。结果左、右肺自动分割与手动分割的Dice系数(一种相似性度量系数)分别为(0.82±0.05)%和(0.83±0.04)%。SPECT图像自动分割的结果与相关CT参考容积比较,左肺(R=0.69, P<0.001)与右肺(R=0.53, P=0.02)差异有统计学意义。SPECT图像手动分割与相关CT参考容积比较的统计结果与自动分割相似,左肺[偏差(-10±491) ml; R=0.60,P=0.005]、右肺[偏差(36±524) ml; R=0.62, P=0.004]。结论 SPECT图像自动分割与手动分割的结果基本一致。SPECT图像手动分割结果与相关CT参考容积间有较大的容积差别,表明功能性SPECT图像的分割是一项具有挑战性的工作。目前的算法只是实现大范围自动定量测定分析的第一步。

关键词：图像分割 V/P SPECT CT 活动形态模型