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Deep Learning Based Audio Assistive System for Visually Impaired People

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Computers, Materials & Continua 2022年第4期71卷 1205-1219页

作者： S.kiruthika devi C.N.Subalalitha Department of Computer Science and Engineering SRM Institute of Science and TechnologyKattankulathur603203India

Vision impairment is a latent problem that affects numerous people across the *** advancements,particularly the rise of computer processing abilities like Deep Learning(DL)models and emergence of wearables pave a way for assisting visually-impaired *** models developed earlier specifically for visually-impaired people work effectually on single object detection in unconstrained ***,in real-time scenarios,these systems are inconsistent in providing effective guidance for visually-impaired *** addition to object detection,extra information about the location of objects in the scene is essential for visually-impaired *** this in mind,the current research work presents an Efficient Object Detection Model with Audio Assistive System(EODM-AAS)using DL-based YOLO v3 model for visually-impaired *** aim of the research article is to construct a model that can provide a detailed description of the objects around visually-impaired *** presented model involves a DL-based YOLO v3 model for multi-label object ***,the presented model determines the position of object in the scene and finally generates an audio signal to notify the visually-impaired *** order to validate the detection performance of the presented method,a detailed simulation analysis was conducted on four *** simulation results established that the presented model produces effectual outcome over existing methods.

关键词： Deep learning visually impaired people object detection YOLO v3

Intelligent Deep Convolutional Neural Network Based Object DetectionModel for Visually Challenged People

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Computer Systems Science & Engineering 2023年第9期46卷 3191-3207页

作者： S.kiruthika devi Amani Abdulrahman Albraikan Fahd N.Al-Wesabi Mohamed k.Nour Ahmed Ashour Anwer Mustafa Hilal Department of Computing Technology SRM Institute of Science and TechnologyIndia Department of Computer Sciences College of Computer and Information SciencesPrincess Nourah bint Abdulrahman UniversityP.O.Box 84428Riyadh11671Saudi Arabia Department of Computer Science College of Science&Art at MahayilKing Khalid UniversitySaudi Arabia Department of Computer Science College of Computing and Information SystemUmm Al-Qura UniversitySaudi Arabia Department of Engineering Mathematics and Physics Faculty of Engineering and TechnologyFuture University in EgyptNew Cairo11845Egypt Department of Computer and Self Development Preparatory Year DeanshipPrince Sattam bin Abdulaziz UniversityAlKharjSaudi Arabia

Artificial Intelligence(AI)and Computer Vision(CV)advancements have led to many useful methodologies in recent years,particularly to help visually-challenged *** detection includes a variety of challenges,for example,handlingmultiple class images,images that get augmented when captured by a camera and so *** test images include all these variants as *** detection models alert them about their surroundings when they want to walk *** study compares four CNN-based pre-trainedmodels:ResidualNetwork(ResNet-50),Inception v3,DenseConvolutional Network(DenseNet-121),and SqueezeNet,predominantly used in image recognition *** on the analysis performed on these test images,the study infers that Inception V3 outperformed other pre-trained models in terms of accuracy and *** further improve the performance of the Inception v3 model,the thermal exchange optimization(TEO)algorithm is applied to tune the hyperparameters(number of epochs,batch size,and learning rate)showing the novelty of the *** accuracy was achieved owing to the inclusion of an auxiliary classifier as a regularizer,hyperparameter optimizer,and factorization ***,Inception V3 can handle images of different *** makes Inception V3 the optimum model for assisting visually challenged people in real-world communication when integrated with Internet of Things(IoT)-based devices.

关键词： Pre-trained models object detection visually challenged people deep learning Inception V3 DenseNet-121

EXISTENCE OF SOLUTIONS OF NONLINEAR FRACTIONAL PANTOGRAPH EQUATIONS

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Acta Mathematica Scientia 2013年第3期33卷 712-720页

作者： k. BALACHANDRAN S. kiruthika J. TRUJILLO Department of Mathematics Bharathiar University Universidad de La Laguna Departamento de Anlisis Matemtico38271 La Laguna Tenerife Spain

This article deals with the existence of solutions of nonlinear fractional pantograph equations. Such model can be considered suitable to be applied when the corresponding process occurs through strongly anomalous media. The results are obtained using fractional calculus and fixed point theorems. An example is provided to illustrate the main result obtained in this article.

关键词： Fractional differential equations pantograph equations fixed point theorems

Mechanical property and biocompatibility of co-precipitated nano hydroxyapatite-gelatine composites

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Journal of Advanced Ceramics 2015年第3期4卷 237-243页

作者： Huirong LE kiruthika NATESAN Sundaram PRANTI-HARAN School of Marine Science and Engineering Plymouth UniversityUnited Kingdom Peninsular Schools of Medicine and Dentistry Plymouth UniversityUnited Kingdom School of Engineering Physics and MathematicsUniversity of DundeeUnited Kingdom

Uniform and well dispersed nano hydroxyapatite(HA)-gelatine composites were obtained by co-precipitation of hydroxyapatite and denatured calf skin *** process allowed much higher concentration of hydroxyapatite to be produced over conventional hydrothermal process to improve the *** effect of gelatine on the morphology,mechanical properties,and biocompatibility of hydroxyapatite particles was *** cell tests of the consolidated hydroxyapatite-gelatine composites showed that the composites have excellent biocompatibility.

关键词： biomaterials nanocomposites hydroxyapatite(HA) gelatine biocompatibility

Intrahepatic and intra-abdominal splenosis:A case report and review of literature

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World Journal of Hepatology 2019年第12期11卷 773-779页

作者： kiruthika Ananthan Gibran Timothy Yusuf Mayur kumar GkT School of Medical Education King’s College LondonLondon WC2R 2LSUnited Kingdom Department of Radiology Princess Royal University HospitalKing’s College Hospital NHS Foundation TrustKent BR68NDUnited Kingdom Department of Gastroenterology Princess Royal University HospitalKing’s College Hospital NHS Foundation TrustKent BR68NDUnited Kingdom

BACkGROUND Splenosis is defined as the process by which tissue from the spleen disseminates through the body and grows in an ectopic location following trauma or a *** sites of splenosis are *** SUMMARY We report a case of intrahepatic splenosis in a 57-year-old man with a history of trauma over 40 years ago who initially presented with chest *** initially mimicked malignancy but a diagnosis of intrahepatic splenosis was confirmed using computed tomography and scintigraphy with technetium-99m heat-denatured red blood cells(Tc-99 DRBC).CONCLUSION Scintigraphy with Tc-99 DRBC is a reliable technique to diagnose splenosis and should be performed before using more invasive procedures are carried *** should be considered as a possible differential diagnosis for a hepatic nodule in any patient with a history of abdominal trauma,previous splenectomy or atypical radiological features on imaging.

关键词： Intrahepatic splenosis Abdominal splenosis Computed tomography Scintigraphy Hepatocellular carcinoma Case report

Modeling Neuromorphic Persistent Firing Networks

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International Journal of Intelligence Science 2015年第2期5卷 89-101页

作者： Ning Ning Guoqi Li Wei He kejie Huang Li Pan kiruthika Ramanathan Rong Zhao Luping Shi Data Storage Institute Agency for Science Technology and Research Singapore Department of Precision Instrument Tsinghua University Beijing China Center for Brain-Inspired Computing Research (CBICR) Tsinghua University Beijing China Singapore University of Technology and Design Dover Singapore

Neurons are believed to be the brain computational engines of the brain. A recent discovery in neurophysiology reveals that interneurons can slowly integrate spiking, share the output across a coupled network of axons and respond with persistent firing even in the absence of input to the soma or dendrites, which has not been understood and could be very important for exploring the mechanism of human cognition. The conventional models are incapable of simulating the important newly-discovered phenomenon of persistent firing induced by axonal slow integration. In this paper, we propose a computationally efficient model of neurons through modeling the axon as a slow leaky integrator, which captures almost all-known neural behaviors. The model controls the switching of axonal firing dynamics between passive conduction mode and persistent firing mode. The interplay between the axonal integrated potential and its multiple thresholds in axon precisely determines the persistent firing dynamics of neurons. We also present a persistent firing polychronous spiking network which exhibits asynchronous dynamics indicating that this computationally efficient model is not only bio-plausible, but also suitable for large scale spiking network simulations. The implications of this network and the analog circuit design for exploring the relationship between working memory and persistent firing enable developing a spiking network-based memory and bio-inspired computer systems.

关键词： Neuron Model Neuromorphic Persistent Firing Slow Integration Spiking Network Working Memory

Ontology for Modeling E-Citizenship

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通讯和计算机（中英文版） 2012年第1期9卷 15-19页

作者： M.kiruthika kavita Shelke Dakshayani G Computer Department Fr.CRITVashiNavi MumbaiIndia