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Robust Machine Learning Technique to Classify COVID-19 Using Fusion of Texture and Vesselness of X-Ray Images

Computer Modeling in Engineering & Sciences 2024年第2期138卷 1981-2004页

作者： Shaik Mahaboob Basha victor Hugo Cde Albuquerque Samia Allaoua Chelloug Mohamed Abd Elaziz Shaik Hashmitha Mohisin Suhail Parvaze Pathan Department of Electronics and Communication Engineering N.B.K.R.Institute of Science&TechnologyVidyanagarAndhra Pradesh524413India Department of Teleinformatics Engineering Federal University of CearáFortaleza60455-970Brazil Information Technology Department College of Computer and Information SciencesPrincess Nourah bint Abdulrahman UniversityRiyadh84428Saudi Arabia Department of Mathematics Faculty of ScienceZagazig UniversityZagazig44519Egypt Faculty of Computer Science and Engineering Galala UniversitySuez435611Egypt Artificial Intelligence Research Center(AIRC) College of Engineering and Information TechnologyAjman UniversityAjmanUnited Arab Emirates Department of Electrical and Computer Engineering Lebanese American UniversityByblos13-5053Lebanon Department of Avionics Indian Institute of Space Science and TechnologyThiruvananthapuramKerala695547India Department of Veterinary Clinical Sciences University of MinnesotaSt.PaulMinnesota55108USA

Manual investigation of chest radiography(CXR)images by physicians is crucial for effective decision-making in COVID-19 ***,the high demand during the pandemic necessitates auxiliary help through image analysis and machine learning *** study presents a multi-threshold-based segmentation technique to probe high pixel intensity regions in CXR images of various pathologies,including normal *** information is extracted using gray co-occurrence matrix(GLCM)-based features,while vessel-like features are obtained using Frangi,Sato,and Meijering *** learning models employing Decision Tree(DT)and RandomForest(RF)approaches are designed to categorize CXR images into common lung infections,lung opacity(lo),COVID-19,and viral pneumonia(VP).The results demonstrate that the fusion of texture and vesselbased features provides an effective ML model for aiding *** ML model validation using performance measures,including an accuracy of approximately 91.8%with an RF-based classifier,supports the usefulness of the feature set and classifier model in categorizing the four different ***,the study investigates the importance of the devised features in identifying the underlying pathology and incorporates histogrambased *** analysis reveals varying natural pixel distributions in CXR images belonging to the normal,COVID-19,lo,and VP groups,motivating the incorporation of additional features such as mean,standard deviation,skewness,and percentile based on the filtered ***,the study achieves a considerable improvement in categorizing COVID-19 from lo,with a true positive rate of 97%,further substantiating the effectiveness of the methodology implemented.

关键词： Chest radiography(CXR)image COVID-19 classifier machine learning random forest texture analysis

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Contributions of biofilm and suspended sludge to nitrogen transformation and nitrous oxide emission in hybrid sequencing batch system

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Journal of Environmental Sciences 2010年第7期22卷 953-960页

作者： Ingwei Wayne lo k.ang victor lo Don S Mavinic Dean Shiskowski William Ramey Department of Civil Engineering University of British Columbia Associated Engineering Ltd. Department of Microbiology & Immunology University of British Columbia

Hybrid system combines the nature of suspended growth and attached growth has been widely applied to wastewater treatment. In this research, the contributions to N transformation and N2O emission by biofilm and suspended sludge in the hybrid sequencing- batch reactor for a simultaneous nitrification, denitrification and phosphorus removal process were investigated. For the hybrid system, nitrification occurred mostly in the suspended sludge, while the biofilm played the major role in denitrification. The interaction of the biofilm and the suspended sludge in the same reactor resulted in a better overall nitrogen removal performance with simultaneous nitrification and denitrification. However, N2O emission was the main end product of nitrogen removal for the hybrid system; while it was N2 for the biofilm. The relative low N2O emissions from the pure biofilm and the pure suspended sludge corresponded to the relatively high nitrate at the end of the aeration period compared with the hybrid system.

关键词： N2O emission biofilm suspended sludge hybrid system

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The role of systemic therapy in borderline resectable and locally advanced pancreatic ductal adenocarcinoma

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Journal of Cancer Metastasis and Treatment 2022年第1期8卷 281-292页

作者： victor C.k.lo Rachel A.Goodwin Michael M.Vickers Department of Medicine Division of Medical OncologyThe Ottawa Hospital Cancer CentreOttawaON K1H 8L6Canada

Pancreatic ductal adenocarcinoma(PDAC)remains a deadly disease,even in patients whose cancer is localized and *** resection provides the only option for cure,but long-term survival rates remain *** patients with borderline resectable(BR)disease who undergo upfront resection,many patients are either too unwell for subsequent adjuvant systemic therapy,develop recurrence soon after,or are found to have unresectable disease *** is increasing evidence for a neoadjuvant approach,using more conventional multi-agent chemotherapy regimens,which have demonstrated higher activity in the metastatic setting compared to single *** patients with locally advanced(LA)disease,which is unresectable by current definitions,there is mounting evidence that effective neoadjuvant systemic therapy is able to convert some patients’disease to a resectable state,offering the potential for long-term survival and *** we present a review of key trials focusing on prospective,randomized studies to provide high-level evidence supporting a neoadjuvant approach to both BR and LA ***,many knowledge gaps exist,such as the optimal neoadjuvant multi-agent chemotherapy regimen,the role of radiotherapy,and the safety and efficacy of adding immunotherapy to chemo/radiation *** challenges in determining the optimal approach to patients with BR or LA PDAC include not only overcoming the inherent difficulties in conducting complex,multidisciplinary,multicentre randomized trials in patients with a high-morbidity and mortality disease,but also trying to standardize disease definitions,treatment regimens,and outcome measures.

关键词： Borderline resectable locally advanced pancreatic ductal adenocarcinoma neoadjuvant chemotherapy

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A Dynamic Forecasting System with Applications in Production logistics

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厦门大学学报（自然科学版） 2002年第S1期41卷 133-134页

作者： CHEUNG Chi-fai LEE Wing-bun lo victor Department of Industrial and Systems Engineering The Hong Kong Polytechnic University Hung HomDepartment of Industrial and Systems EngineeringThe Hong Kong Polytechnic University Hung Hom Kowloon Hong Kong ChinaKowloonHong Kong China Kaz (Fast East) Ltd Room 1705-07Kodak House II39 Healthy Street EastNorth Point Hong Kong China

Production logistics involve the co-ordination of ac tivities such as production and materials control (PMC), inventory management, p roduct life cycle management, etc. Those activities demand for an accurate forec asting model. However, the conventional methods of making sell and buy decision based on human forecast or conventional moving average and exponential smoothing methods is no longer be sufficient to meet the future need. Furthermore, the un derlying statistics of the market information change from time to time due to a number of reasons such as change of global economic environment, government poli cies and business risks. This demands for highly adaptive forecasting model which is robust enough to response and adapt well to the fast changes in the dat a characteristics, in other words, the trajectory of the "dynamic characteristic s" of the data. In this paper, an adaptive time-series modelling method was proposed for short -term dynamic forecasting. The method employs an autoregressive (AR) time-seri es model to carry out the forecasting process. A modified least mean square (MLM S) adaptive filter algorithm was established for adjusting the AR model coeffici ents so as to minimise the sum of squared of forecasting errors. A prototype dyn amic forecasting system was built based on the adaptive time-series modelling m ethod. Basically, the dynamic forecasting system can be divided into two phases, i.e. the Learning Phase and the Application Phase. The learning procedures star t with the determination of upper limit of the adaptation gain based on the conv ergence in the mean square criterion. Hence, the optimum ELMS filter parameters are determined using an iteration algorithm which changes each filter parameter i.e. the order, the adaptation gain andthe values initial coefficient vector on e by one inside a predetermined iteration range. The set of parameters which giv es the minimum value for sum of squared errors within the iteration range is sel ecte

关键词： adaptive time-series model dynamic forecasting production logistics modified least mean square algorithm

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Exacerbated VEGF up-regulation accompanies diabetes-aggravated hemorrhage in mice after experimental cerebral ischemia and delayed reperfusion

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Neural Regeneration Research 2022年第7期17卷 1566-1575页

作者： angela ka Wai Lai Tsz Chung Ng victor ka lok Hung ka Cheung Tam Chi Wai Cheung Sookja kim Chung Amy Cheuk Yin lo Department of Ophthalmology Li Ka Shing Faculty of MedicineThe University of Hong KongHong Kong Special Administration RegionChina Department of Anesthesiology Laboratory and Clinical Research Institute for PainThe University of Hong KongHong Kong Special Administration RegionChina Macao University of Science and Technology TaipaMacao Special Administration RegionChinaSchool of Biomedical SciencesThe State Key Laboratory of Pharmaceutical BiotechnologyThe University of Hong KongHong Kong Special Administration RegionChina

Reperfusion therapy is the preferred treatment for ischemic stroke,but is hindered by its short treatment window,especially in patients with diabetes whose reperfusion after prolonged ischemia is often accompanied by exacerbated *** mechanisms underlying exacerbated hemorrhage are not fully *** study aimed to identify this mechanism by inducing prolonged 2-hour transient intraluminal middle cerebral artery occlusion in diabetic Ins2Akita/+mice to mimic patients with diabetes undergoing delayed mechanical *** results showed that at as early as 2 hours after reperfusion,Ins2Akita/+mice exhibited rapid development of neurological deficits,increased infarct and hemorrhagic transformation,together with exacerbated down-regulation of tight-junction protein ZO-1 and upregulation of blood-brain barrier-disrupting matrix metallopeptidase 2 and matrix metallopeptidase 9 when compared with normoglycemic Ins2+/+*** indicated that diabetes led to the rapid compromise of vessel integrity immediately after reperfusion,and consequently earlier death and further aggravation of hemorrhagic transformation 22 hours after *** observation was associated with earlier and stronger up-regulation of pro-angiogenic vascular endothelial growth factor(VEGF)and its downstream phospho-Erk1/2 at 2 hours after reperfusion,which was suggestive of premature angiogenesis induced by early VEGF up-regulation,resulting in rapid vessel disintegration in diabetic *** reticulum stress-related pro-apoptotic C/EBP homologous protein was overexpressed in challenged Ins2Akita/+mice,which suggests that the exacerbated VEGF up-regulation may be caused by overwhelming endoplasmic reticulum stress under diabetic *** conclusion,the results mimicked complications in patients with diabetes undergoing delayed mechanical thrombectomy,and diabetes-induced accelerated VEGF up-regulation is likely to underlie exacerbated hemorrhagic transformat

关键词： blood-brain barrier brain injury diabetes mellitus hemorrhagic transformation infarct ischemia/reperfusion injury middle cerebral artery occlusion mouse model stroke vascular endothelial growth factor

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Aggregator Based RPL for an IoT-Fog Based Power Distribution System with 6loWPAN

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China Communications 2020年第1期17卷 104-117页

作者： Rijo Jackson Tom Suresh Sankaranarayanan victor Hugo C.de Albuquerque Joel J.P.C.Rodrigues CMR Institute of Technology Bengaluru 560037India SRM Institute of Science and Technology Chennai 603203India University of Fortaleza(Unifor) FortalezaCE 60811-905Brazil Federal University of Piaui Teresina-PI64049-550Brazil Instituto de Telecomunicacoes 1049-001 LisboaPortugal

Advanced Metering Infrastructure(AMI)forms an important part in Smart *** the data effectively from smart meters to the Edge/Fog node requires an efficient routing *** Protocol for low Power lossy Area Network(RPL)is a standard routing protocol for IPv6 over low Power Personal Area Network(6loWPAN).In a Power Distribution system all the smart meters together form 6loWPAN *** communicate with the fog router,which acts as the 6loWPAN *** was evaluated using Cooja Network simulator for a power distribution network *** nodes which were far away from the fog node gave low Packet Delivery Ratio(PDR)and large End to End *** paper proposes an aggregation RPL scheme by modifying the existing Contiki *** smart meter nodes communicate to the aggregator,which communicates to the fog *** results show that the aggregation scheme has 35.6%increase in PDR,lesser hop count and 13.24%decrease in End to End delay on an average compared to existing RPL.

关键词： IoT 6loWPAN RPL routing distribution automation smart grid fog computing

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Length-Weight Relationships and Condition Factors of 15 Fish Species from the loémé River Basin (Mayombe, Republic of Congo)

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Open Journal of Ecology 2023年第12期13卷 883-893页

作者： Honest Freedom Poaty Ngot victor Mamonekene Armel Ibala Zamba Leendert Van Den Berg César Ngoulou Dabney Matoko kouediatouka Aulne Lérège Batiabo Mikembi Hélène Dembe louvinguila Tenda Institut National de Recherche en Sciences Exactes et Naturelles IRSEN Brazzaville République du Congo Faculté de Sciences et Techniques (FST) Université Marien Ngouabi Brazzaville République du Congo Ecole Nationale Supérieure Agronomie et de Foresterie (ENSAF) Université Marien Ngouabi Brazzaville République du Congo Institut Nationale de Recherche Agronomique (IRA) Brazzaville République du Congo Groupe Van den Berg Project Management B.V. Utrecht Netherlands Centre National d’Inventaire et d’Aménagement des Ressources Forestières et Fauniques (CIARF) Brazzaville République du Congo

Length-weight relationships and condition factors are among the commonly used parameters to link the length of a fish to its weight. The present study was initiated to find out the growth patterns and overweight status of 15 fish species in the loémé basin in Mayombe, Republic of Congo. In the period from February 2020 to September 2021, sampling was carried out in eight stations, following a standardised capture method using four gillnets of 10, 12, 15, and 25 mm mesh size and a hawk net of 1.90 m radius with 10 mm mesh size. Length-weight relationships were calculated according to P = aLSb and the condition factor, using k = (P/LSb)* 100. A total of 1153 specimens representing 15 species, 10 genera and 6 families were recorded. The number of specimens ranged from 10 to 214 for Chrysichthys auratus and Enteromius camptacanthus, respectively. The allometry coefficient b minimum of 2.697 for Chromidotilapiamelaniae and maximum of 3.589 for Garraornata, with a mean of 3.03 ± 0.2 is significantly not different from 3 at the 0.05 probability threshold and indicates isometric growth for almost all species, except for E. camptacanthus where b = 2.858 was statistically different from 3 at the same threshold. The positive and high values of the coefficients of determination r2 = 0.787-0.989 of the species, obtained during this study, suggest that weight increases with size in the fish of the loémé basin. The average condition factor varies from 0.524 ± 0.064 for G. ornata to 4.917 ± 0.440 for C. melaniae.

关键词： Fish Growth Overweight loémé River Basin lower Guinea

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