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International Conference on Computer Engineering and Applications（ICCEA 2009）

作者： v.Prasanna venkatesh v.Ranjana v.janani R.Madhav Prashanth St.Joseph's college of Engineering Easwari Engineering College

It has always a great deal of efforts for the human race to operate the heart,which is the source of blood to the entire human *** with advancements in technology like robot-assisted surgeries,a heart operation has always been dreaded by the patients,mainly due to the laceration experienced during surgery and the affliction caused by the persisting *** this paper,we focus mainly on one type of heart surgery for countering heart blocks in the coronary artery,called the CABG（Coronary Artery Bypass Graft）,generally known as the Heart Bypass *** aim to propose a system that combines a heuristic routing approach with available CABG mechanisms,to alleviate the complexities involved in the *** routing mechanism involves a dynamic routing table maintained by different routers,to identify heart blocks and also predict a close replacement for the *** routers are classified as Primary and Secondary routers and are used to monitor different regions of the human *** also introduce a new way of dividing the human body to map the artery location to the router table known as "segment mapping（SM）".

关键词： Coronary Artery Bypass Graft saphenous vein Radial Artery grafts(RA) Coronary Artery Disease(CAD) heuristic routing variable address dynamic routing table Primary router secondary router segment mapping.

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Emission colour tuning in KLnF_(4):Yb^(3+),Er^(3+)/Ho^(3+)phosphor

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Journal of Rare Earths 2024年第1期42卷 57-65,I0002页

作者： janani K Gayathri E vijayatha v Ramasubramanian S Thiyagarajan P Department of Science and Humanities Nehru Institute of TechnologyKaliapuramThirumalayampalayamCoimbatoreIndia Department of Sciences Amrita School of Physical SciencesAmrita Vishwa VidyapeethamCoimbatoreIndia Department of Physics Anna UniversityChennaiIndia

KLnF_(4):Yb^(3+),Er^(3+)/Ho^(3+)(Ln=Y,Yb,Gd)phosphors were prepared by solid-state reaction *** each of the Yb^(3+)/Er^(3+)and Yb^(3+)/Ho^(3+)co-doped phosphors independently,phase confirmation and morphological examination were accomplished using the X-ray diffraction technique and scanning electron microscope analysis.X-ray photoelectron spectroscopy analysis shows the charge state and existence of lanthanides and *** luminescence emissions of green and red colour were detected for the synthesized *** changes in the upconverted emission intensities and colour output pertaining to the change of the lanthanide host matrix along with dopants were investigated for the prepared *** the upconversion luminescence,erbium-doped samples exhibit a predominance of red emission while holmium-doped samples display a prevalence of green *** rare-earth Er/Ho doped KYbF4shows strong red emission compared to other ***_(4):Yb,Er/Ho exhibits relatively significant green upconve rsion emissions,while Yb,Er-doped KGdF_(4)host displays a 10-fold increase in green/red emission ratio with an increase in the input power of 20-780 *** photoluminescence studies and decay curve analysis were carried out using Uv light excitation for the developed phosphors.A higher lifetime of 2.2 ms was measured for the downshifting red emission in the Ho doped KYbF_(4)*** study suggests a potential for colour tunability in the upconversion and downshifting emissions through host modifications to the fluoride phosphor.

关键词： Rare earths Energy transfer upconversion Downshifting Colour coordinates

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Enhancing Wildlife Monitoring Through Infrared Imaging: A Deep Learning Approach for Improved Animal Region Segmentation and Species Identification

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Journal of Harbin Institute of Technology(New series) 2024年

作者： v.janani C Shanthi Department of Computer Science， School of Computing Sciences， vels Institute of Science Technology and Advanced Studies

Infrared imaging has proven to be a powerful tool in various fields， with particular significance in wildlife monitoring. In this paper， we present an extension of our previous research， focusing on advancing the segmentation of animal regions in enhanced infrared images and expanding the scope to include species identification. Our proposed methodology builds upon the success of the R-CNN (Region-based Convolutional Neural Network) object detection to improve the accuracy and robustness of animal region segmentation， while simultaneously extending our model’s capabilities to identify and classify the species within those regions. By fine-tuning the R-CNN model on a larger dataset that includes annotated infrared images and species labels， we enhance its capacity to not only accurately segment animal regions but also classify them into specific species categories. To assess the performance of our extended model， we employ a comprehensive set of evaluation metrics， including pixel-based metrics like Intersection over Union (IoU)， as well as species classification accuracy. Our results demonstrate significant improvements in both region segmentation accuracy and species identification compared to our previous work and existing methods. This research showcases the potential of deep learning techniques， combined with transfer learning， to advance wildlife monitoring applications using infrared imaging.

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Towards automated statistical partial discharge source classification using pattern recognition techniques

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High voltage 2018年第3期3卷 162-169页

作者： Hamed janani Behzad Kordi Department of Electrical and Computer Engineering University of Manitoba75A Chancellor's CircleWinnipegMBCanadaR3T5V6 Powertech Labs Inc. 12388-88 AvenueSurreyBCCanadaV3W 7R7

This study presents a comprehensive review of the automated classification in partial discharge(PD)source identification and probabilistic interpretation of the classification results based on the relationship between the variation of the phase-resolved PD(PRPD)patterns and the source of the *** proposed automated classification system consists of modern,high-performance statistical feature extraction methods and classifier *** application in online monitoring and recognition of the PD patterns is investigated based on their low-processing time and high-performance *** application of modern statistical algorithms and pre-processing methods configured in this automated classification system improves the pattern recognition accuracy of the different PD sources that are suitable to be employed in different high-voltage(Hv)insulation *** evaluate the performance of the different combinations of the feature extraction/classier pairs,laboratory setups are designed and built that simulate various types of *** test cells include three sources of PD in SF6,two sources of PD in transformer oil,and corona in the *** samples for different classes of PD sources are captured under two levels of voltage and two different levels of *** results of this study evaluate the suitability of the proposed classification systems for probabilistic source identification in various insulation ***,of importance to the problem of the PD source identification is to assign a‘degree of membership’to each PRPD pattern,besides assigning a class label to *** of the classifier algorithms studied in this study,such as fuzzy classifiers,are not only able to show high classification accuracy rate,but they also calculate the‘degree of membership’of a sample to a class of *** enables probabilistic interpretation of a new PRPD pattern that is being *** determination of the degree of membership for future PRPD samples allows saf

关键词： pattern membership source

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