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Discrimination of Acacia seeds at species and subspecies levels using an image analyzer

Forestry Studies in China 2013年第4期15卷 253-260页

作者： V.SIVAKUMAr r.ANANDALAKSHMI rekha r.warrier B.G.SINGH M.TIGABU B.NAGArAJAN Division of Seed Technology Institute of Forest Genetics and Tree Breeding Indian Council of Forestry Research and Education Swedish University of Agricultural Sciences Southern Swedish Forest Research Centre

Seeds of Acacia species and subspecies were characterized using an image analyzer and discriminated for the purpose of identification of species, using their seeds. The species considered in the study were Acacia nilotica subsp. indica, A. nilotica subsp. cupressiformis, A. nilotica subsp. tomentosa, A. tortilis subsp. raddiana, A. tortilis subsp. spirocarpa, A. raddiana, A. senegal, A. auriculiformis, A. farnesiana, A. leucophloea, A. mearnsii, A. melanoxylon, A. planifrons and A. mangium. Eight samples each consisting of 25 seeds per species were studied using the image analyzer for physical characteristics of seeds, such as 2D surface area, length, width, perimeter, roundness, aspect ratio and fullness ratio. Discriminant analysis showed that acacias can be discriminated at species and subspecies levels, with 96% accuracy. Exceptions were A. nilotica subsp. tomentosa(75.0%), A. tortilis subsp. spirocarpa(75.0%) and A. raddiana(87.5%) which had relatively low discrimination accuracy. However, discriminant analysis within selected species showed complete recognition of these species except for A. tortilis subsp. spirocarpa, that had still a large overlap with A. leucophloea. The study also revealed that both seed size and shape characteristics were responsible for species discrimination. It can be concluded that rapid analysis of seed size and shape characteristics using image analysis techniques can be used as primary and secondary keys for identification of acacias.

关键词： Acacia image analyzer discriminant analysis seed identification

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Marine yeast rhodotorula paludigena VA 242 a pigment enhancing feed additive for the Ornamental Fish Koi Carp

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Aquaculture and Fisheries 2024年第1期9卷 66-70页

作者： r.rekha K.A.Nimsi K.Manjusha T.K.Sirajudheen Faculty of Ocean Science&Technology Kerala University of Fisheries and Ocean Studies(KUFOS)CochinKerala682506India

Skin colour is an important criterion in determining the aesthetic appeal of ornamental fishes,and thus their market *** the pigment enhancement in ornamental fishes has been the subject of extensive research by using various synthetic as well as natural pigment *** composition is one of the most important elements that influence the development of pigmentation in *** study is an attempt to assess the possibility of using carotenogenic marine yeast as pigment enhancer in fish diet for Koi carp,Cyprinus *** 60 days feeding experiment was done by using feed incorporated with mangrove associated marine yeast rhodotorula paludigena *** pigmentation in the scales of fishes fed with experimental feed was observed than that fed with the control diet(normal pellet feed).Furthermore the improved growth rate and general wellbeing in fishes fed with experimental feed provides scope for further studies in this field with respect to the growth and survival of fishes.

关键词： Marine yeasts Carotenoids Ornamental fishes Pigment enhancer Feed additive rhodotorula sp

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Smart Healthcare Activity recognition Using Statistical regression and Intelligent Learning

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Computers, Materials & Continua 2024年第1期78卷 1189-1205页

作者： K.Akilandeswari Nithya rekha Sivakumar Hend Khalid Alkahtani Shakila Basheer Sara Abdelwahab Ghorashi Department of Computer Sciences Government Arts College(Autonomous)Salem636007India Department of Computer Sciences College of Computer and Information SciencesPrincess Nourah Bint Abdulrahman UniversityRiyadh11671Saudi Arabia Department of Information Systems College of Computer and Information SciencesPrincess Nourah Bint Abdulrahman UniversityRiyadh11671Saudi Arabia

In this present time,Human Activity recognition(HAr)has been of considerable aid in the case of health monitoring and *** exploitation of machine learning with an intelligent agent in the area of health informatics gathered using HAr augments the decision-making quality and *** many research works conducted on Smart Healthcare Monitoring,there remain a certain number of pitfalls such as time,overhead,and falsification involved during ***,this paper proposes a Statistical Partial regression and Support Vector Intelligent Agent Learning(SPr-SVIAL)for Smart Healthcare *** first,the Statistical Partial regression Feature Extraction model is used for data preprocessing along with the dimensionality-reduced features extraction ***,the input dataset the continuous beat-to-beat heart data,triaxial accelerometer data,and psychological characteristics were acquired from IoT wearable *** attain highly accurate Smart Healthcare Monitoring with less time,Partial Least Square helps extract the dimensionality-reduced *** that,with these resulting features,SVIAL is proposed for Smart Healthcare Monitoring with the help of Machine Learning and Intelligent Agents to minimize both analysis falsification and *** evaluation is carried out for factors such as time,overhead,and false positive rate accuracy concerning several *** quantitatively analyzed results indicate the better performance of our proposed SPr-SVIAL method when compared with two state-of-the-art methods.

关键词： Internet of Things smart health care monitoring human activity recognition intelligent agent learning statistical partial regression support vector

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Nonmetric Traits in Permanent Teeth as Clues to Ethnicity in Vidarbha Subpopulation to Aid Forensic Profiling:Pilot Study

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Journal of Forensic Science and Medicine 2024年第1期10卷 11-19页

作者： Vaishali Amarlal Sadhwani Nilima Prakash GLPradeep rekha Patil Shubhechha Anand Khivsara Sabiha Mokashi Khan MGV’S KBH Dental College NashikMaharashtraIndia Oral Cancer Screening and Awareness in Cancer Screening Vertical Indian Cancer SocietyMumbaiMaharashtraIndia

Introduction:Nonmetric dental traits have a crucial role in ethnic classification of populations that help in forensic racial *** studies have demonstrated the differences in the expression and frequency of dental traits between various ethnic groups for ancestry determination in the context of forensic dental *** present study is an attempt to assess the frequency and variation in nonmetric traits for establishing ethnicity in the Vidarbha ***:The aim of the study was to assess the frequency and variation of nonmetric traits in permanent teeth for establishing ethnicity in the Vidarbha *** and Methods:Participants of the Vidarbha subpopulation were selected by random sampling ***,premolars,and incisors were evaluated for frequency of nonmetric traits,and variations were graded according to Dentoanthropological System of State University of Arizona *** statistics,Chi-square test,and Student’s t-test were used for analysis of ***:The most common occlusal morphology in mandibular first and second molar was 5 cusp and 4 cusp,respectively,with the“+”groove *** 3 and cusp 4 were observed frequently in the maxillary *** lingual cusp was most commonly seen in mandibular premolars show while incisors showed faint ***:Our study concludes that nonmetric traits were present and showed variation in permanent maxillary and mandibular teeth among the Vidarbha *** 5 and Cusp 4 in first and second mandibular molars,respectively,groove pattern“+”and grade 1 protostylid were the most frequent grades observed in permanent mandibular *** lingual cusp was most commonly seen in mandibular premolars and faint shoveling was a notable feature in incisors of this population.

关键词： Cusp number ethnicity forensic anthropology molar protostylid

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Mammogram Classification with HanmanNets Using Hanman Transform Classifier

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Journal of Modern Physics 2024年第7期15卷 1045-1067页

作者： Jyoti Dabass Madasu Hanmandlu rekha Vig Shantaram Vasikarla EECE Department The Northcap University Sector 23-A Gurugram India CSE Department MVSR Engineering College Nadergul Hyderabad India CSE Department The Northcap University Sector 23-A Gurugram India CS Department California State University Northridge CA USA

Breast cancer is a deadly disease and radiologists recommend mammography to detect it at the early stages. This paper presents two types of HanmanNets using the information set concept for the derivation of deep information set features from resNet by modifying its kernel functions to yield Type-1 HanmanNets and then AlexNet, GoogLeNet and VGG-16 by changing their feature maps to yield Type-2 HanmanNets. The two types of HanmanNets exploit the final feature maps of these architectures in the generation of deep information set features from mammograms for their classification using the Hanman Transform Classifier. In this work, the characteristics of the abnormality present in the mammograms are captured using the above network architectures that help derive the features of HanmanNets based on information set concept and their performance is compared via the classification accuracies. The highest accuracy of 100% is achieved for the multi-class classifications on the mini-MIAS database thus surpassing the results in the literature. Validation of the results is done by the expert radiologists to show their clinical relevance.

关键词： Mammograms resNet 18 Hanman Transform Classifier Abnormality Diagnosis VGG-16 AlexNet GoogleNet HanmanNets

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腙基席夫碱配体铜(Ⅱ)配合物的合成、结构表征、生物活性和密度泛函理论计算

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无机化学学报 2024年第7期40卷 1409-1422页

作者： Bhattacharjee Maitri Boruah Smriti rekha Dutta Purkayastha r.N. Maniukiewicz Waldemar Chowdhury Shubhamoy Maiti Debasish Akhtar Tamanna Department of Chemistry Tripura UniversitySuryamaninagar‑799022TripuraIndia Institute of General and Ecological Chemistry Lodz University of TechnologyZeromskiego 11690‑924ŁódzPoland Department of Chemistry University of GourbangaMokdumpurMaldaWest Bengal‑732103India Department of Human Physiology Tripura UniversitySuryamaninagar‑799022TripuraIndia

以甲醇为介质,合成了3种新的席夫碱配体HL^(1)(2-hydroxybenzaldehyde2-(2-oxo-1,2-diphenylethylidene)hydrazone)、HL^(2)(4-hydroxybenzaldehyde2-(2-oxo-1,2-diphenylethylidene)hydrazone)和L^(3)(2-methoxybenzaldehyde2-(2-oxo-1,2-diphenylethylidene)hydrazone)的Cu(Ⅱ)配合物1-3。通过元素分析、光谱方法、磁化率测量和密度泛函理论(DFT)计算对配合物进行了表征。通过单晶X射线衍射研究对合成的配体进行了结构表征。通过DFT计算确定了配合物的优化结构。通过紫外可见吸收光谱和荧光发射光谱研究了配合物与小牛胸腺DNA(CT-DNA)的结合能力。吸收光谱研究揭示了增色效应,并提出了与CT-DNA相互作用的可能模式。溴化乙锭(EB)竞争结合研究表明,配合物可以取代DNA-EB加合物中的DNA,且配合物可能以嵌入模式与CTDNA结合。配合物对革兰氏阴性肺炎克雷伯菌、大肠杆菌、鲍氏志贺菌和革兰氏阳性金黄色葡萄球菌的体外抗菌活性研究表明,配合物2对肺炎克雷伯菌和鲍氏志贺菌具有明显抗菌活性,但配合物1和3没有表现出任何显著的抗菌活性。

关键词： Cu(Ⅱ)配合物席夫碱结构生物活性密度泛函理论

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Study of gravitational sedimentation of flexible, permeable circular and planktonic particle applying the immersed boundary method

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International Journal of Sediment research 2023年第5期38卷 643-652页

作者： rekha Panghal Sudeshna Ghosh Department of Mathematics Amity School of Applied Sciences Amity University Haryana

The gravitational settling of a flexible, permeable circular and planktonic particle drenched in a fluid which is assumed to be Newtonian and incompressible along with being viscous was studied. A mathematical formulation and numerical simulations of the studied problem were done by applying the Immersed Boundary Method(IBM) in a two-dimensional fluid domain. Parametric studies were done for analyzing the impact of varying flexibilities and permeabilities with reference to settling velocity(terminal velocity) and shape deformation of the particle. The terminal velocity and permeability of the particle are directly proportional. It was observed that for fixed permeability, the terminal velocity increases when increasing the flexibility of the particle.

关键词： Immersed Boundary Method (IBM) Sedimentation Incompressible fluid Flexible particle Permeable particle Settling velocity

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Growth response of three plantation species of the tropics exposed to elevated CO_2 levels

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Journal of Forestry research 2013年第3期24卷 449-456页

作者： rekha r. warrier C. Buvaneswaran P. Priyadharshini r.S.C. Jayaraj Institute of Forest Genetics and Tree Breeding Forest CampusR. S. Puram Coimbatore 641002 India

The response of forest trees, the largest carbon sinks on the earth, to continuing rise in atmospheric carbon levels is unknown. re- ports state that increasing levels of atmospheric CO2 will stimulate pho- tosynthesis and productivity in most ecosystems. However, the duration and magnitude of this stimulation, particularly in the tropics, remains a question. To investigate the effects of CO2 fertilization on plant growth, seedlings of three common plantation species, Casuarina equisetifolia, Ailanthus excelsa and Tectona grandis were grown in closed chambers enriched with CO2. After 180 days of treatment, morphological traits of seedling height, biomass of root and shoot and root-shoot allometric co-efficient were measured. The activity of carbonic anhydrase and con- tents of chlorophylls, total carbohydrates and soluble proteins were de- termined. In Tectona grandis, significant effects of CO2 supply were found on chlorophylls, root-shoot allometric ratio and seedling quality index. Ailanthus excelsa showed significant effect on only the shoot characteristics on exposure to elevated CO2 but the root characteristics and concentrations of chlorophylls were not significantly different. Ca- suarina equisetifolia also showed significant effects on exposure to ele- vated CO2 in terms of shoot characteristics and concentrations of chlo- rophylls. Total sugars, the major photosynthates, did not show any sig- nificant variation to elevated CO2 in any of the three species. Carbonic anhydrase, the key enzyme responsible for transfer of CO2 into the tis- sues significantly increased in all three species. Overall, all the variables responded to elevated CO2, reflecting the positive effects of one parame- ter of climate change conditions on seedling quality. A positive response of these three plantation species to elevated CO2 content is a good indi- cation for their future existence in potentially changed climatic eonditions.

关键词： Plantation Elevated CO2 Tropical trees India Carbonicanhydrase

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Ensemble Deep Learning for IoT Based COVID 19 Health Care Pollution Monitor

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Intelligent Automation & Soft Computing 2023年第2期35卷 2383-2398页

作者： Nithya rekha Sivakumar Department of Computer Sciences College of Computer and Information SciencesPrincess Nourah Bint Abdulrahman UniversityRiyadh11671Saudi Arabia

Internet of things(IoT)has brought a greater transformation in health-care sector thereby improving patient care,minimizing treatment *** pre-sent method employs classical mechanisms for extracting features and a regression model for *** methods have failed to consider the pollu-tion aspects involved during COVID 19 *** Ensemble Deep Learning and Framingham Feature Extraction(FFE)techniques,a smart health-care system is introduced for COVID-19 pandemic disease *** Col-lected feature or data via predictive mechanisms to form pollution *** maps are used to implement real-time countermeasures,such as storing the extracted data or feature in a Cloud server to minimize concentrations of air *** integrated with patient management systems,this solution would minimize pollution emitted via patient’s sensors by offering spaces in the cloud server when pollution thresholds are ***,the Gini Index factor infor-mation gain technique eliminates unimportant and redundant attributes while selecting the most relevant,reducing computing overhead and optimizing system ***,the COVID-19 disease prognosis ensemble deep learning-based classiﬁer is *** analysis is planned to measure the prediction accuracy,error,precision and recall for different numbers of *** results show that prediction accuracy is improved by 8%,error rate was reduced by 47%and prediction time is minimized by 36%compared to exist-ing methods.

关键词： Internet of Things Covid-19 ensemble deep learning framingham feature extraction

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Deep Neural Artificial Intelligence for IoT Based Tele Health Data Anal

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Computers, Materials & Continua 2022年第3期70卷 4467-4483页

作者： Nithya rekha Sivakumar Ahmed Zohair Ibrahim Department of Computer Sciences College of Computer and Information SciencesPrincess Nourah Bint Abdulrahman UniversityRiyadh11671Saudi Arabia

Tele health utilizes information and communication mechanisms to convey medical information for providing clinical and educational *** makes an effort to get the better of issues of health service delivery involving time factor,space and laborious terrains,validating cost-efficiency and finer ingress in both developed and developing *** health has been categorized into either real-time electronic communication,or store-andforward *** recent years,a third-class has been perceived as remote healthcare monitoring or tele health,presuming data obtained via Internet of Things(IOT).Although,tele health data analytics and machine learning have been researched in great depth,there is a dearth of studies that entirely concentrate on the progress of ML-based techniques for tele health data analytics in the IoT healthcare *** by this fact,in this work a method called,Weighted Bayesian and Polynomial Taylor Deep Network(WB-PTDN)is proposed to improve health prediction in a computationally efficient and accurate ***,the Independent Component Data Arrangement model is designed with the objective of normalizing the data obtained from the Physionet ***,with the normalized data as input,Weighted Bayesian Feature Extraction is applied to minimize the dimensionality involved and therefore extracting the relevant features for further health risk ***,to obtain reliable predictions concerning tele health data analytics,First Order Polynomial Taylor DNN-based Feature Homogenization is proposed that with the aid of First Order Polynomial Taylor function updates the new results based on the result analysis of old values and therefore provides increased transparency in decision *** comparison of proposed and existing methods indicates that the WB-PTDN method achieves higher accuracy,true positive rate and lesser response time for IoT based tele health data analytics than the traditional methods.

关键词： Telehealth internet of things independent component weighted bayesian first order polynomial taylor deep neural network

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