检索结果-南通市图书馆

radiography Image Classification Using Deep Convolutional Neural Networks

维普期刊数据库

同方期刊数据库评论

在线全文

学校读者我要写书评

暂无评论

Journal of Computer and Communications 2024年第6期12卷 199-209页

作者： ahmad Chowdhury Haiyi Zhang Department of Computer Science Acadia University Wolfville Canada

research has shown that chest radiography images of patients with different diseases, such as pneumonia, COVID-19, SArS, pneumothorax, etc., all exhibit some form of abnormality. Several deep learning techniques can be used to identify each of these anomalies in the chest x-ray images. Convolutional neural networks (CNNs) have shown great success in the fields of image recognition and image classification since there are numerous large-scale annotated image datasets available. The classification of medical images, particularly radiographic images, remains one of the biggest hurdles in medical diagnosis because of the restricted availability of annotated medical images. However, such difficulty can be solved by utilizing several deep learning strategies, including data augmentation and transfer learning. The aim was to build a model that would detect abnormalities in chest x-ray images with the highest probability. To do that, different models were built with different features. While making a CNN model, one of the main tasks is to tune the model by changing the hyperparameters and layers so that the model gives out good training and testing results. In our case, three different models were built, and finally, the last one gave out the best-predicted results. From that last model, we got 98% training accuracy, 84% validation, and 81% testing accuracy. The reason behind the final model giving out the best evaluation scores is that it was a well-fitted model. There was no overfitting or underfitting issues. Our aim with this project was to make a tool using the CNN model in r language, which will help detect abnormalities in radiography images. The tool will be able to detect diseases such as Pneumonia, Covid-19, Effusions, Infiltration, Pneumothorax, and others. Because of its high accuracy, this research chose to use supervised multi-class classification techniques as well as Convolutional Neural Networks (CNNs) to classify different chest x-ray images. CNNs are extr

关键词： CNN radiography Image Classification r Keras Chest X-ray Machine Learning

Integrating Virtual reality and Energy Analysis with BIM to Optimize Window-to-Wall ratio and Building’s Orientation for Age-in-Place Design at the Conceptual Stage

在线全文

维普期刊数据库

学校读者我要写书评

暂无评论

Open Journal of Civil Engineering 2024年第3期14卷 305-333页

作者： Vafa rostamiasl ahmad Jrade Department of Civil Engineering University of Ottawa Ottawa Canada

This study unfolds an innovative approach aiming to address the critical role of building design in global energy consumption, focusing on optimizing the Window-to-Wall ratio (WWr), since buildings account for approximately 30% of total energy consumed worldwide. The greatest contributors to energy expenditure in buildings are internal artificial lighting and heating and cooling systems. The WWr, determined by the proportion of the building’s glazed area to its wall area, is a significant factor influencing energy efficiency and minimizing energy load. This study introduces the development of a semi-automated computer model designed to offer a real-time, interactive simulation environment, fostering improving communication and engagement between designers and owners. The said model serves to optimize both the WWr and building orientation to align with occupants’ needs and expectations, subsequently reducing annual energy consumption and enhancing the overall building energy performance. The integrated model incorporates Building Information Modeling (BIM), Virtual reality (Vr), and Energy Analysis tools deployed at the conceptual design stage, allowing for the amalgamation of owners’ inputs in the design process and facilitating the creation of more realistic and effective design strategies.

关键词： Building Information Modeling (BIM) Virtual reality (Vr) Game Engine Energy Analysis Window-to-Wall ratio Building Orientation Computer Integration and Automation

Modelling of debris-flow susceptibility and propagation: a case study from Northwest Himalaya

在线全文

维普期刊数据库

学校读者我要写书评

暂无评论

Journal of Mountain Science 2024年第1期21卷 200-217页

作者： Hamza DAUD Javed Iqbal TANOLI Sardar Muhammad ASIF Muhammad QASIM Muhammad ALI Junaid KHAN Zahid Imran BHATTI Ishtiaq ahmad Khan JADOON Badong National Observation and research Station of Geohazards China University of GeosciencesWuhan 430074China Department of Earth Sciences COMSATS University IslamabadAbbottabad Campus 22010Pakistan Department of Earth Sciences Sultan Qaboos UniversityAl-KhoudMascat 123Oman Faculty of Engineering China University of Geosciences(Wuhan)Wuhan 430074China Department of Earth Sciences Abbottabad University of Science and TechnologyHavelian 22500Pakistan

The geological and geographical position of the Northwest Himalayas makes it a vulnerable area for mass movements particularly landslides and debris flows. Mass movements have had a substantial impact on the study area which is extending along Karakorum Highway(KKH) from Besham to Chilas. Intense seismicity, deep gorges, steep terrain and extreme climatic events trigger multiple mountain hazards along the KKH, among which debris flow is recognized as the most destructive geohazard. This study aims to prepare a field-based debris flow inventory map at a regional scale along a 200 km stretch from Besham to Chilas. A total of 117 debris flows were identified in the field, and subsequently, a point-based debris-flow inventory and catchment delineation were performed through Arc GIS analysis. regional scale debris flow susceptibility and propagation maps were prepared using Weighted Overlay Method(WOM) and Flow-r technique sequentially. Predisposing factors include slope, slope aspect, elevation, Topographic roughness Index(TrI), Topographic Wetness Index(TWI), stream buffer, distance to faults, lithology rainfall, curvature, and collapsed material layer. The dataset was randomly divided into training data(75%) and validation data(25%). results were validated through the receiver Operator Characteristics(rOC) curve. results show that Area Under the Curve(AUC) using WOM model is 79.2%. Flow-r propagation of debris flow shows that the 13.15%, 22.94%, and 63.91% areas are very high, high, and low susceptible to debris flow respectively. The propagation predicated by Flow-r validates the naturally occurring debris flow propagation as observed in the field surveys. The output of this research will provide valuable input to the decision makers for the site selection, designing of the prevention system, and for the protection of current infrastructure.

关键词： North Pakistan Debris flow Flow-r Propagation Susceptibility mapping Debris-flow inventory Weighted Overlay Method

Therapeutic and regenerative potential of different sources of mesenchymal stem cells for cardiovascular diseases

维普期刊数据库

同方期刊数据库评论

在线全文

学校读者我要写书评

暂无评论

BIOCELL 2024年第4期48卷 559-569页

作者： YArA ALZGHOUL HALA J.BANI ISSA ahmad K.SANAJLEH TAQWA ALABDUH FATIMAH rABABAH MAHA AL-SHDAIFAT EJLAL ABU-EL-rUB FATIMAH ALMAHASNEH rAMADA r.KHASAWNEH AYMAN ALZU’BI HUTHAIFA MAGABLEH Department of Basic Medical Sciences Faculty of MedicineYarmouk UniversityIrbidJordan

Mesenchymalstemcells(MSCs)*** the internal cardiac microenvironment to facilitate their immunomodulatory and differentiation abilities,which are essential to restore heart *** can be easily isolated from different sources,including bone marrow,adipose tissues,umbilical cord,and dental *** from various sources differ in their regenerative and therapeutic abilities for cardiovascular *** this review,we will summarize the therapeutic potential of each MSC source for heart diseases and highlight the possible molecular mechanisms of each source to restore cardiac function.

关键词： Bone marrow mesenchymal stem cells Adipose tissue mesenchymal stem cells Dental pulp stem cells Umbilical cord mesenchymal stem cells Cardiomyocytes regeneration Myocardial infarction Mesenchymal stem cells Differentiation Immunomodulation

Suppression of host plant defense by bacterial small rNAs packaged in outer membrane vesicles

在线全文

维普期刊数据库

学校读者我要写书评

暂无评论

Plant Communications 2024年第4期5卷 252-254页

作者： Yan Wu Sai Wang Peihong Wang Wenhan Nie Iftikhar.ahmad Panagiotis F.Sarris Gongyou Chen Bo Zhu Shanghai Yangtze river Delta Eco-Environmental Change and Management Observation and research Station Shanghai Cooperative Innovation Center for Modern Seed Industry School of Agriculture and Biology Shanghai Jiao Tong University Shanghai China Department of Environmental Sciences COMSATS University Islamabad Vehari-Campus Vehari 61100 Pakistan Department of Biology University of Crete 714 09 Heraklion Crete Greece Shanghai Jiao Tong University Chongqing research Institute Shanghai China

(Plant Communications 5,100817;April 82024)After a careful,in-depth examination,the authors found some additional errors in the published *** revision,the authors created a mutant DXosr001(in which the full-length Xosr001 was deleted)and a mutant DXosr001’(in which the predicted binding motif of Xosr001 was deleted)as shown in Figure S4 of the original *** rNA-FISH assays,Xosr001 transcript could not be detected in leaves inoculated with DXosr001-OMVs,while leaves inoculated with WT-and DXosr001’-OMVs could emit green fluorescence.

关键词： deleted Figure outer

Distinct gut microbiomes in Thai patients with colorectal polyps

在线全文

维普期刊数据库

学校读者我要写书评

暂无评论

World Journal of Gastroenterology 2024年第27期30卷 3336-3355页

作者： Thoranin Intarajak ahmad Nuruddin Khoiri Kanthida Kusonmano Weerayuth Kittichotirat Sawannee Sutheeworapong Supapon Cheevadhanarak Wandee Udomchaiprasertkul Chinae Thammarongtham Bioinformatics Unit Chulabhorn Royal AcademyLak Si 10210BangkokThailand Bioinformatics and Systems Biology Program School of Bioresources and Technologyand School of Information TechnologyKing Mongkut’s University of Technology ThonburiBang Khun Thian 10150BangkokThailand Bioinformatics and Systems Biology ProgramSchool of Bioresources and Technologyand School of Information TechnologyKing Mongkut’s University of Technology ThonburiBang Khun Thian 10150BangkokThailand Systems Biology and Bioinformatics Unit Pilot Plant Development and Training InstituteKing Mongkut’s University of Technology ThonburiBang Khun Thian 10150BangkokThailand Molecular Genomic research Laboratory Chulabhorn Royal AcademyLak Si 10210BangkokThailand National Center for Genetic Engineering and Biotechnology King Mongkut's University of Technology ThonburiBang Khun Thian 10150BangkokThailand School of Bioresources and Technology King Mongkut’s University of Technology ThonburiBank Khun Thian 10150BangkokThailand Fungal Biotechnology Unit Pilot Plant Development and Training InstituteKing Mongkut’s University of Technology ThonburiBang Khun Thian 10150BangkokThailand

BACKGrOUND Colorectal polyps that develop via the conventional adenoma-carcinoma sequence[e.g.,tubular adenoma(TA)]often progress to malignancy and are closely associated with changes in the composition of the gut *** is limited research concerning the microbial functions and gut microbiomes associated with colorectal polyps that arise through the serrated polyp pathway,such as hyperplastic polyps(HP).Exploration of microbiome alterations asso-ciated with HP and TA would improve the understanding of mechanisms by which specific microbes and their metabolic pathways contribute to colorectal *** To investigate gut microbiome signatures,microbial associations,and microbial functions in HP and TA *** Full-length 16S rrNA sequencing was used to characterize the gut microbiome in stool samples from control participants without polyps[control group(CT),n=40],patients with HP(n=52),and patients with TA(n=60).Significant differences in gut microbiome composition and functional mechanisms were identified between the CT group and patients with HP or *** techniques in this study included differential abundance analysis,co-occurrence network analysis,and differential pathway *** Colorectal cancer(CrC)-associated bacteria,including Streptococcus gallolyticus(***),Bacteroides fragilis,and Clostridium symbiosum,were identified as characteristic microbial species in TA *** gnavus,associated with dysbiosis and gastrointestinal diseases,was significantly differentially abundant in the HP and TA *** pathway analysis revealed that HP patients exhibited enrichment in the sulfur oxidation pathway exclusively,whereas TA patients showed dominance in pathways related to secondary metabolite biosynthesis(e.g.,mevalonate);*** was a major ***-occurrence network and dynamic network analyses revealed co-occurrence of dysbiosis-associated bacteria in HP patients,wh

关键词： Gut microbiome Colorectal adenoma Hyperplastic polyp Full-length 16s rrNA Microbial correlation networks Predicted functional mechanisms

Financial inclusion and carbon emissions in Asia:Implications for environmental sustainability

在线全文

维普期刊数据库

学校读者我要写书评

暂无评论

Economic and Political Studies 2024年第1期12卷 88-104页

作者： Shahzad Hussain Tanveer.ahmad Sabeeh Ullah Ajid Ur rehmand Syed Jawad Hussain Shahzad Department of Business Administration Rawalpindi Women UniversityRawalpindiPakistan Institute of Business Studies Kohat University of Science and TechnologyKohatPakistan Institute of Business and Management Sciences Faculty of Management and Computer SciencesThe University of AgriculturePeshawarPakistan NUST Business School National University of Sciences and TechnologyIslamabadPakistan Finance Control and Law DepartmentMontpellier Business SchoolMontpellierFrance

This study explores how carbon emissions are affected by financial *** a balanced panel data set of 26 Asian countries,we compute a composite index,through the principal component analysis(PCA)technique,of financial inclusion based on a set of attributes related to financial *** main analysis also delineates the subsamples of developed and developing Asian *** results reveal a long(short)-run positive(negative)impact of financial inclusion on carbon emissions across the Asian *** finding is also true for the developed country subsample,implying nonlinearity in shortand long-run *** the developing countries,a more pronounced long-run positive impact compared to developed countries is ***,the pairwise causality test results indicate the existence of bi-directional causality between financial inclusion and carbon *** findings have important policy implications,especially in the context of the strategic integration of financial inclusion and climate change strategies.

关键词： Financial inclusion CO2 emissions climate change sustainable development Asian countries

Design of a Lightweight Compressed Video Stream-Based Patient Activity Monitoring System

在线全文

维普期刊数据库

学校读者我要写书评

暂无评论

Computers, Materials & Continua 2024年第1期78卷 1253-1274页

作者： Sangeeta Yadav Preeti Gulia Nasib Singh Gill Piyush Kumar Shukla Arfat ahmad Khan Sultan Alharby Ahmed Alhussen Mohd Anul Haq Department of Computer Science&Applications Maharshi Dayanand UniversityRohtak124001India University Institute of Technology Rajiv Gandhi Proudyogiki VishwavidyalayaBhopal462033India Department of Computer Science College of ComputingKhon Kaen UniversityKhon Kaen40002Thailand Department of Computer Science College of Computer and Information SciencesMajmaah UniversityAl Majmaah11952Kingdom of Saudi Arabia Department of Computer Engineering College of Computer and Information SciencesMajmaah UniversityAl Majmaah11952Kingdom of Saudi Arabia

Inpatient falls from beds in hospitals are a common *** falls may result in severe *** problem can be addressed by continuous monitoring of patients using *** advancements in deep learning-based video analytics have made this task of fall detection more effective and *** with fall detection,monitoring of different activities of the patients is also of significant concern to assess the improvement in their *** computation-intensive models are required to monitor every action of the patient *** requirement limits the applicability of such ***,to keep the model lightweight,the already designed fall detection networks can be extended to monitor the general activities of the patients along with the fall *** by the same notion,we propose a novel,lightweight,and efficient patient activity monitoring system that broadly classifies the patients’activities into fall,activity,and rest classes based on their *** whole network comprises three sub-networks,namely a Convolutional Neural Networks(CNN)based video compression network,a Lightweight Pose Network(LPN)and a residual Network(resNet)Mixer block-based activity recognition *** compression network compresses the video streams using deep learning networks for efficient storage and retrieval;after that,LPN estimates human ***,the activity recognition network classifies the patients’activities based on their *** proposed system shows an overall accuracy of approx.99.7% over a standard dataset with 99.63% fall detection accuracy and efficiently monitors different events,which may help monitor the falls and improve the inpatients’health.

关键词： Fall detection activity recognition human pose estimation accuracy

Semantic Segmentation and YOLO Detector over Aerial Vehicle Images

在线全文

维普期刊数据库

学校读者我要写书评

暂无评论

Computers, Materials & Continua 2024年第8期80卷 3315-3332页

作者： Asifa Mehmood Qureshi Abdul Haleem Butt Abdulwahab Alazeb Naif Al Mudawi Mohammad Alonazi Nouf Abdullah Almujally ahmad Jalal Hui Liu Faculty of Computing and AI Air UniversityIslamabad44000Pakistan Department of Computer Science College of Computer Science and Information SystemNajran UniversityNajran55461Saudi Arabia Department of Information Systems College of Computer Engineering and SciencesPrince Sattam bin Abdulaziz UniversityAl-Kharj16273Saudi Arabia Department of Information Technology College of Computer and Information SciencesPrincess Nourah bint Abdulrahman UniversityP.O.Box 84428Riyadh11671Saudi Arabia Cognitive Systems Lab University of BremenBremen28359Germany

Intelligent vehicle tracking and detection are crucial tasks in the realm of highway ***,vehicles come in a range of sizes,which is challenging to detect,affecting the traffic monitoring system’s overall *** learning is considered to be an efficient method for object detection in vision-based *** this paper,we proposed a vision-based vehicle detection and tracking system based on a You Look Only Once version 5(YOLOv5)detector combined with a segmentation *** model consists of six *** the first step,all the extracted traffic sequence images are subjected to pre-processing to remove noise and enhance the contrast level of the *** pre-processed images are segmented by labelling each pixel to extract the uniform regions to aid the detection phase.A single-stage detector YOLOv5 is used to detect and locate vehicles in *** detection was exposed to Speeded Up robust Feature(SUrF)feature extraction to track multiple *** on this,a unique number is assigned to each vehicle to easily locate them in the succeeding image frames by extracting them using the feature-matching ***,we implemented a Kalman filter to track multiple *** the end,the vehicle path is estimated by using the centroid points of the rectangular bounding box predicted by the tracking *** experimental results and comparison reveal that our proposed vehicle detection and tracking system outperformed other state-of-the-art *** proposed implemented system provided 94.1%detection precision for roundabout and 96.1%detection precision for Vehicle Aerial Imaging from Drone(VAID)datasets,respectively.

关键词： Semantic segmentation YOLOv5 vehicle detection and tracking Kalman filter SUrF