检索结果-南通市图书馆

World Journal of Pediatric Surgery 2024年第1期7卷 59-65页

作者： abirami Muthumani UCSF Center for Health Equity in Surgery and Anesthesia Universityof California San FranciscoSan FranciscoCaliforniaUSA Department of General Surgery Columbia University Irving Medical CenterNewYorkNew YorkUSA

INTRODUCTION Pediatric surgical interventions may represent more than one-third of the surgical caseload in humanitarian settings.1 The humanitarian crisis in Gaza has taken a devastating toll on children,many of whom have suffered injuries due to indiscriminate and heavy bombardment,resulting in severe polytraumatic injuries necessitating immediate and specialized pediatric surgical *** conflict has strained the region's fragile healthcare system,resulting in a significant number of casualties,a substantial proportion of which are *** exacerbates the demand for specialized pediatric surgical care,especially when the existing healthcare system and infrastructure has nearly collapsed and is under-resourced to handle the influx of pediatric patients.2 The urgency for specialized pediatric surgical care and support for children in Gaza cannot be *** to healthcare in Palestine has been an ongoing challenge.

关键词： pediatric injuries surgical

Junction Point Elimination based Tamil Handwritten Character Recognition:An Experimental Analysis

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 Systems Science and Systems Engineering 2020年第1期29卷 100-123页

作者： M.Antony Robert raj S.abirami Department of Information Science and Technology Anna UniversityChennai 600025

Optical Character Recognition is the mechanical or electronic conversion of images of typed,handwritten or printed text into machine-encoded text for online reading and *** this OCR technique,Tamil handwritten character recognition is one of the most needed and challengeable subjects of *** encounter between selection and extraction of proper features eliminates the issues faced by the Tamil handwritten *** character and the writers complexities are the major difficulties and challenges faced by this recognition ***,the character complexity can be overcome by any pre-extraction or selection process,wherein,structured or statistical pre-extraction algorithm can be designed,discovering the essential features,in the case of writer *** challenges of Tamil handwritten characters are structure over looping;unnecessary character portion;structure discontinuations and so *** character portions in this research are chosen by implementing a new algorithm called the Junction Point Elimination(JPE)after conscientious analysis done on the existing algorithms like Zoning,Zoning and Junction Point(ZJP)and the Junction Point (JP) based feature pre-extraction *** novelty behind this work is introducing an algorithm in order to truncate the problem in the existing feature selection and preextraction *** feature extraction and classification algorithm are chosen and applied on the features extracted by JPE to test whether the same can be reached in successful *** final analysis and experiments shows that the JPE is better than the others.

关键词： Junction point elimination chain code zoning prism tree quad tree support vector machine

Streptomyces ghanaensis VITHM1 mediated green synthesis of silver nanoparticles： Mechanism and biological applications

在线全文

维普期刊数据库

学校读者我要写书评

暂无评论

Frontiers of Chemical Science and Engineering 2016年第4期10卷 542-551页

作者： Mani abirami Krishnan Kannabiran Biomolecules and Genetic Division School of Biosciences and Technology VIT University Tamil Nadu 623014 India

We present the microbial green synthesis of silver nanoparticles （hiPs） by Streptomyces ghanaensis VITHM1 strain （MTCC No. 12465）. The secondary metabolites in the cell free supernatant of this bacterium when incubated with 1 mmol/L AgNO3, mediated the biological synthesis of AgNPs. The synthesized AgNPs were characterized by UV-visible spectrum, X-ray diffrac- tion （XRD）, atomic force microscope, scanning electron microscopy equipped with energy dispersive spectroscopy, transmission electron microscopy, FT-IR spectroscopy, dynamic light scattering and zeta potential. They were highly stable and, spherical in shape with the average size of 30-50 nm. The secondary metabolites involved in the formation of AgNPs were identified gas chromatographymass spectrography. The 3D structure of the unit cell of the synthesized AgNPs was determined using XRD data base. The synthesized AgNPs exhibited significant antibacterial activity against tested bacterial pathogens, and did not show haemolysis on human red blood cells. This green synthesis could provide a new platform to explore and use AgNPs as antibacterial therapeutic agents.

关键词： Streptomyces ghanaensis VITHM1 nanopar-ticles 3D structure antibacterial activity

Efficacy of a Diabetes Specific Nutrition Supplement on Glycemic, Anthropometric, Dietary and Gut Health Markers in Adults with Type 2 Diabetes: An RCT

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

Food and Nutrition Sciences 2024年第8期15卷 846-867页

作者： Deepti Khanna Hema S. Gopalan Kuzhandaivelu abirami Vasudevan Sudha rajagopal Gayatri Kejal Joshi-Reddy Jaladhi Bhatt Raman Ganesh Jeevan Karthikeyan Parkavi Vadivel Deepika Manoj Pareek Ranjit Mohan Anjana Viswanathan Mohan R&D Department Hindustan Unilever Limited Gurugram India Department of Foods Nutrition & Dietetics Research Madras Diabetes Research Foundation Chennai India Department of Diabetology Dr. Mohans Diabetes Specialities Centre Chennai India

With increasing incidence of diabetes, use of diabetes specific nutrition supplements (DSNS) is common for better management of the disease. To study effect of 12-week DSNS supplementation on glycemic markers, anthropometry, lipid profile, SCFAs, and gut microbiome in individuals with diabetes. Markers studied were glycemic [Fasting Blood Glucose (FBG), Post Prandial Glucose (PPG), HbA1c, Incremental Area under curve (iAUC), Mean Amplitude of Glycemic Excursions (MAGE), Time in/above Range (TIR/TAR)], anthropometry [weight, Body Mass Index (BMI), waist circumference (WC)], lipid profile, diet and gut health [plasma short chain fatty acids (SCFAs)]. N = 210 adults were randomized to receive either DSNS with standard care (DSNS + SC;n = 105) or standard care alone (SC alone;n = 105). After 12 weeks, significant differences between DSNS + SC versus SC alone was observed in FBG [−3 ± 6 vs 14 ± 6 mg/dl;p = 0.03], PPG [−35 ± 9 vs −3 ± 9 mg/dl;p = 0.01], weight [−0.6 ± 0.1 vs 0.2 ± 0.1 kg;p = 0.0001], BMI [−0.3 ± 0.1 vs 0.1 ± 0.1 kg/m2;p = 0.0001] and WC [−0.3 ± 0.2 vs 0.2 ± 0.2 cm;p = 0.01]. HbA1C and low-density lipoprotein (LDL) were significantly reduced in DSNS + SC [−0.2 ± 0.9;p = 0.04 and −5 mg/dl;p = 0.03] respectively with no change in control. Continuous Glucose Monitoring (CGM) reported significant differences between DSNS + SC versus SC alone for mean glucose [−12 ± 65 vs 28 ± 93 mg/dl;p < 0.01], TAR 180 [−9 ± 42 vs 7 ± 45 mg/dl;p = 0.04], TAR 250 [−3 ± 27 vs 9 ± 38 mg/dl;p = 0.05], iAUC [−192 (1.1) vs −48 (1.1) mg/dl;p = 0.03]. MAGE was significantly reduced for both DSNS + SC (−19 ± 67;p < 0.001) and SC alone (−8 ± 70;p = 0.04), with reduction being more pronounced for DSNS + SC. DSNS + SC reported a decrease in carbohydrate energy % [−9.4 (−11.3, −7.6) %;p < 0.0001] and amount [−47.4 (−67.1, −27.7) g;p < 0.0001], increased dietary fiber [9.5 (7.2, 11.8) g;p < 0.0001] and protein energy % [0.9 (0.5, 1.3) %;p < 0.0001] versus SC alone. DSNS + SC reported signi

关键词： Diabetes Specific Nutrition Supplement Standard of Care Diabetes Glycemic Markers HbA1C

Deep Learning Convolutional Neural Network for ECG Signal Classification Aggregated Using IoT

在线全文

维普期刊数据库

学校读者我要写书评

暂无评论

Computer Systems Science & Engineering 2022年第9期42卷 851-866页

作者： S.Karthiga A.M.abirami Department of Information Technology Thiagarajar College of Engineering625015Tamil NaduIndia

Much attention has been given to the Internet of Things (IoT) by citizens, industries, governments, and universities for applications like smart buildings, environmental monitoring, health care and so on. With IoT, networkconnectivity is facilitated between smart devices from anyplace and ***-based health monitoring systems are gaining popularity and acceptance forcontinuous monitoring and detect health abnormalities from the data *** (ECG) signals are widely used for heart diseases detection.A novel method has been proposed in this work for ECG monitoring using IoTtechniques. In this work, a two-stage approach is employed. In the first stage, arouting protocol based on Dynamic Source Routing (DSR) and Routing byEnergy and Link quality (REL) for IoT healthcare platform is proposed for effi-cient data collection, and in the second stage, classification of ECG for Arrhythmia. Furthermore, this work has evaluated Support Vector Machine (SVM),Artificial Neural Network (ANN), and Convolution Neural Networks (CNNs)-based approach for ECG signals classification. Deep-ECG will use a deep CNNto extract critical features and then compare through evaluation of simple and fastdistance functions in order to obtain an efficient classification of heart abnormalities. For the identification of abnormal data, this work has proposed techniquesfor the classification of ECG data, which has been obtained from mobile watchusers. For experimental verification of the proposed methods, the Beth Israel Hospital (MIT/BIH) Arrhythmia and Massachusetts Institute of Technology (MIT)Database was used for evaluation. Results confirm the presented method’s superior performance with regards to the accuracy of classification. The CNN achievedan accuracy of 91.92% and has a higher accuracy of 4.98% for the SVM and2.68% for the ANN.

关键词： Internet of things electrocardiographic signals dynamic source routing routing by energy and link quality convolution neural networks

Energy Efficient QoS Aware Cluster Based Multihop Routing Protocol for WSN

在线全文

维普期刊数据库

学校读者我要写书评

暂无评论

Computer Systems Science & Engineering 2022年第6期41卷 1173-1189页

作者： M.S.Maharajan T.abirami Department of Computer Science and Engineering GRT Institute of Engineering and TechnologyTiruttani631209India Department of Information Technology Kongu Engineering CollegeErode638060India

Wireless sensor networks (WSN) have become a hot research areaowing to the unique characteristics and applicability in diverse application *** and routing techniques can be considered as an NP hard optimizationproblem, which can be addressed by metaheuristic optimization algorithms. Withthis motivation, this study presents a chaotic sandpiper optimization algorithmbased clustering with groundwater flow optimization based routing technique(CSPOC-GFLR). The goal of the CSOC-GFLR technique is to cluster the sensornodes in WSN and elect an optimal set of routes with an intention of achievingenergy efficiency and maximizing network lifetime. The CSPOC algorithm isderived by incorporating the concepts of chaos theory to boost the global optimization capability of the SPOC algorithm. The CSPOC technique elects an optimum set of cluster heads (CH) whereas the other sensors are allocated to thenearer CH. Extensive experimentation portrayed the promising performance ofthe CSPOC-GFLR technique by achieving reduced energy utilization, improvedlifetime, and prolonged stability over the existing techniques.

关键词： Clustering routing wireless sensor networks energy efficiency network lifetime metaheuristics

Energy Aware Clustering with Medical Data Classification Model in IoT Environment

在线全文

维普期刊数据库

学校读者我要写书评

暂无评论

Computer Systems Science & Engineering 2023年第1期44卷 797-811页

作者： R.Bharathi T.abirami Department of Computer Science and Engineering Cheran College of EngineeringK.ParamathiKarur639111India Department of Information Technology Kongu Engineering CollegePerunduraiErode638060India

With the exponential developments of wireless networking and inexpensive Internet of Things(IoT),a wide range of applications has been designed to attain enhanced *** to the limited energy capacity of IoT devices,energy-aware clustering techniques can be highly *** the same time,artificial intelligence(AI)techniques can be applied to perform appropriate disease diagnostic *** this motivation,this study designs a novel squirrel search algorithm-based energy-aware clustering with a medical data classification(SSAC-MDC)model in an IoT *** goal of the SSAC-MDC technique is to attain maximum energy efficiency and disease diagnosis in the IoT *** proposed SSAC-MDC technique involves the design of the squirrel search algorithm-based clustering(SSAC)technique to choose the proper set of cluster heads(CHs)and construct ***,the medical data classification process involves three different subprocesses namely pre-processing,autoencoder(AE)based classification,and improved beetle antenna search(IBAS)based parameter *** design of the SSAC technique and IBAS based parameter optimization processes show the novelty of the *** show-casing the improved performance of the SSAC-MDC technique,a series of experiments were performed and the comparative results highlighted the supremacy of the SSAC-MDC technique over the recent methods.

关键词： Internet of things healthcare medical data classification energy efficiency clustering autoencoder

Preliminary study on the antimicrobial activity of Enicostemma littorale using different solvents

在线全文

维普期刊数据库

学校读者我要写书评

暂无评论

Asian Pacific Journal of Tropical Medicine 2012年第7期5卷 552-555页

作者： Pitchamuthu abirami Muthiah Gomathinayagam rajaram Panneerselvam Plant Growth Regulation Lab Department of BotanyAnnamalai UniversityAnnamalainagarTamilnaduIndia

Objective:To study the antimicrobial activity of Enicostemma littorale(***) using different ***:Chloroform,methanol and acetone extracts of different parts of ***(leaf,stem and root) were evaluated for antimicrobial activity using disc diffusion method against some gram-negative species such as Escherichia coli,Klebsiella pnemoniae, Pseudomonas aeruginosa,Salmonella typhi and gram-positive species Staphylococcus aureus, Bacillus cereus,Bacillus subtilis and two fugal species viz.,Aspergillus fumigates and Aspergillus ***:The chloroform extracts showed the highest antibacterial *** leaf, stem and root extracts,the stem extracts showed maximum antibacterial *** of the used extracts had no significant antifungal activity against Aspergillus fumigates and Aspergillus *** chloroform stem extract showed highest activity(about 20 mm inhibition zone) against Bacillus subtilis(at 500 tng/mL) followed by the methanolic stem extract which showed highest activity against the same *** lowest antibacterial activity was observed by the acetone leaf extract(about 8 mm inhibition zone) against Escherichia ***:The findings of the study indicate littorale could also be a new source for antibiotics discovery.

关键词： Antimicrobial activity Enicostemma littorale Extracts Medicinal plants

Optimized Deep Learning Methods for Crop Yield Prediction

在线全文

维普期刊数据库

学校读者我要写书评

暂无评论

Computer Systems Science & Engineering 2023年第2期44卷 1051-1067页

作者： K.Vignesh A.Askarunisa A.M.abirami KLN College of Information Technology Pottapalaiyam630612India Sethu Institute of Technology Kariyapatti626115India Thiagarajar College of Engineering Madurai625015India

Crop yield has been predicted using environmental,land,water,and crop characteristics in a prospective research *** it comes to predicting crop production,there are a number of factors to consider,including weather con-ditions,soil qualities,water levels and the location of the farm.A broad variety of algorithms based on deep learning are used to extract useful crops for *** combination of data mining and deep learning creates a whole crop yield pre-diction system that is able to connect raw data to predicted crop *** sug-gested study uses a Discrete Deep belief network with Visual Geometry Group(VGG)Net classiﬁcation method over the tweak chick swarm optimization approach to estimate agricultural *** Network’s successively stacked layers were fed the data *** on the input parameters,a crop produc-tion prediction environment is constructed using the network *** the tweak chick swarm optimization technique,the best characteristics of input data are preprocessed,and the optimal output is used as input for the classiﬁcation *** Deep belief network with the Visual Geometry Group Net clas-siﬁer is used to classify the data and forecast agricultural *** sug-gested model correctly predicts crop output with 97 percent accuracy,exceeding existing models by maintaining the baseline data distribution.

关键词： Data mining deep learning crop production tweak chick swarm optimization algorithm discrete deep belief network with VGG Net classiﬁer

Improving Recommendation for Effective Personalization in Context-Aware Data Using Novel Neural Network

在线全文

维普期刊数据库

学校读者我要写书评

暂无评论

Computer Systems Science & Engineering 2023年第8期46卷 1775-1787页

作者： R.Sujatha T.abirami Department of Information Technology M.Kumarasamy College of EngineeringKarurTamilnaduIndia Department of Information Technology Kongu Engineering CollegePerunduraiTamilnaduIndia

The digital technologies that run based on users’content provide a platform for users to help air their opinions on various aspects of a particular subject or *** recommendation agents play a crucial role in personalizing the needs of individual ***,it is essential to improve the user *** recommender system focuses on recommending a set of items to a user to help the decision-making process and is prevalent across e-commerce and media *** Context-Aware Recommender Systems(CARS),several influential and contextual variables are identified to provide an effective recommendation.A substantial trade-off is applied in context to achieve the proper accuracy and coverage required for a collaborative *** CARS will generate more recommendations utilizing adapting them to a certain contextual situation of ***,the key issue is how contextual information is used to create good and intelligent recommender *** paper proposes an Artificial Neural Network(ANN)to achieve contextual recommendations based on usergenerated *** ability of ANNs to learn events and make decisions based on similar events makes it effective for personalized recommendations in ***,the most appropriate contexts in which a user should choose an item or service are *** work converts every label set into a Multi-Label Classification(MLC)problem to enhance *** results show that the proposed ANN performs better in the Binary Relevance(BR)Instance-Based Classifier,the BR Decision Tree,and the Multi-label SVM for Trip Advisor and LDOS-CoMoDa ***,the accuracy of the proposed ANN achieves better results by 1.1%to 6.1%compared to other existing methods.

关键词： Recommendation agents context-aware recommender systems collaborative recommendation personalization systems optimized neural network-based contextual recommendation algorithm