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Earlier Detection of Alzheimer’s Disease Using 3D-Convolutional Neural Networks

Computer systems science & Engineering 2023年第8期46卷 2601-2618页

作者： V.P.nithya N.Mohanasundaram R.santhosh Department of Computer science and Engineering Karpagam Academy of Higher EducationCoimbatoreIndia

The prediction of mild cognitive impairment or Alzheimer’s disease(AD)has gained the attention of huge researchers as the disease occurrence is increasing,and there is a need for earlier ***,due to the highdimensionality nature of neural data and the least available samples,modelling an efficient computer diagnostic system is highly *** approaches,specifically deep learning approaches,are essential in disease *** Learning(DL)approaches are successfully demonstrated for their higher-level performance in various fields like medical imaging.A novel 3D-Convolutional Neural Network(3D-CNN)architecture is proposed to predict AD with Magnetic resonance imaging(MRI)*** proposed model predicts the AD occurrence while the existing approaches lack prediction accuracy and perform binary *** proposed prediction model is validated using the Alzheimer’s disease Neuro-Imaging Initiative(ADNI)*** outcomes demonstrate that the anticipated model attains superior prediction accuracy and works better than the brain-image dataset’s general *** predicted model reduces the human effort during the prediction process and makes it easier to diagnose it intelligently as the feature learning is ***’experimentation is carried out,and the model’s superiority is compared with various advanced approaches for multi-level *** proposed model gives better prediction accuracy,precision,recall,and F-measure than other systems like Long short Term Memory-Recurrent Neural Networks(LsTM-RNN),stacked Autoencoder with Deep Neural Networks(sAE-DNN),Deep Convolutional Neural Networks(D-CNN),Two Dimensional Convolutional Neural Networks(2D-CNN),Inception-V4,ResNet,and Two Dimensional Convolutional Neural Networks(3D-CNN).

关键词： Alzheimer’s disease 3D CNN ADNI prediction accuracy highdimensionality data

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MIoT Based skin Cancer Detection Using Bregman Recurrent Deep Learning

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Computers, Materials & Continua 2022年第12期73卷 6253-6267页

作者： nithya Rekha sivakumar sara Abdelwahab Ghorashi Faten Khalid Karim Eatedal Alabdulkreem Amal Al-Rasheed 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

Mobile clouds are the most common medium for aggregating,storing,and analyzing data from the medical Internet of Things(MIoT).It is employed to monitor a patient’s essential health signs for earlier disease diagnosis and *** the various disease,skin cancer was the wide variety of cancer,as well as enhances the endurance *** recent years,many skin cancer classification systems using machine and deep learning models have been developed for classifying skin tumors,including malignant melanoma(MM)and other skin ***,accurate cancer detection was not performed with minimum time *** order to address these existing problems,a novel Multidimensional Bregman Divergencive Feature scaling Based Cophenetic Piecewise Regression Recurrent Deep Learning Classification(MBDFs-CPRRDLC)technique is introduced for detecting cancer at an earlier *** MBDFs-CPRRDLC performs skin cancer detection using different layers such as input,hidden,and output for feature selection and *** patient information is composed of *** patient information was stored in mobile clouds server for performing predictive *** collected data are sent to the recurrent deep learning *** the first hidden layer,the feature selection process is carried out using the Multidimensional Bregman Divergencive Feature scaling technique to find the significant features for disease identification resulting in decreases time *** by,the disease classification is carried out in the second hidden layer using cophenetic correlative piecewise regression for analyzing the testing and training *** process is repeatedly performed until the error gets *** this way,disease classification is accurately performed with higher *** evaluation is carried out for factors namely Accuracy,precision,recall,F-measure,as well as cancer detection time,by the amount of patient *** observed result confirms that the pr

关键词： MIoT skin cancer detection recurrent deep learning classification multidimensional bregman divergencive scaling cophenetic correlative piecewise regression

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Artificial Intelligence Enabled Decision support system on E-Healthcare Environment

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Intelligent Automation & soft Computing 2023年第5期36卷 2299-2313页

作者： B.Karthikeyan K.nithya Ahmed Alkhayyat Yousif Kerrar Yousif Department of Information Technology Panimalar Engineering CollegeChennai600123India Department of Information Technology Dr.MGR Educational and Research InstituteChennai600095India College of Technical Engineering The Islamic UniversityNajafIraq Department of Computer Technical Engineering Al-Hadba University CollegeMosulIraq

In today’s digital era,e-healthcare systems exploit digital technologies and telecommunication devices such as mobile devices,computers and the inter-net to provide high-quality healthcare services.E-healthcare decision support sys-tems have been developed to optimize the healthcare services and enhance a patient’s *** systems enable rapid access to the specialized healthcare services via reliable information,retrieved from the cases or the patient *** phenomenon reduces the time taken by the patients to physically visit the healthcare *** the current research work,a new shufﬂed Frog Leap Optimizer with Deep Learning-based Decision support system(sFLODL-Dss)is designed for the diagnosis of the Cardiovascular Diseases(CVD).The aim of the proposed model is to identify and classify the cardiovascular *** proposed sFLODL-Dss technique primarily incorporates the sFLO-based Feature selection(sFLO-Fs)approach for feature subset *** the pur-pose of classiﬁcation,the Autoencoder with Gated Recurrent Unit(AEGRU)model is ***,the Bacterial Foraging Optimization(BFO)algorithm is employed toﬁne-tune the hyperparameters involved in the AEGRU *** demonstrate the enhanced performance of the proposed sFLODL-Dss technique,a series of simulations was *** simulation outcomes established the superiority of the proposed sFLODL-Dss technique as it achieved the highest accuracy of 98.36%.Thus,the proposed sFLODL-Dss technique can be exploited as a proﬁcient tool in the future for the detection and classiﬁcation of CVD.

关键词： E-healthcare decision support system cardiovascular disease feature selection deep learning

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Evaluation and Bulked segregant Analysis of Major Yield QTL qtl12.1 Introgressed into Indigenous Elite Line for Low Water Availability under Water stress

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Rice science 2013年第1期20卷 25-30页

作者： N.Manikanda BOOPATHI Gat sWAPNAsHRI P.KAVITHA s.sATHIsH R.nithya Wickneswari RATNAM Arvind KUMAR Department of Plant Molecular Biology and Bioinformatics CPMB&BTamil Nadu Agricultural UniversityCoimbatore-3India Universiti Kebangsaan Malaysia Bangi SelangorMalaysia Division of Plant Breeding Genetics and BiotechnologyInternational Rice Research InstituteMetro ManilaPhilippines

Near isogenic lines carrying large-effect QTL （qtl2.1）, which has a consistent influence on grain yield under upland drought stress conditions in a wide range of environments, were evaluated under water stress in the fields. The line which gave higher yield under drought was crossed with a local elite line, PMK3, and forwarded to F2：3 generation. significant variation was found among the F2：3 lines for agronomic traits under water stress in the fields. Low to high broad sense heritability （H） for investigated traits was also found. Water stress indicators such as leaf rolling and leaf drying were negatively correlated with plant height, biomass and grain yield under stress. Bulked segregant analysis （BsA） was performed with the markers in the vicinity of qUl2.1, and RM27933 was found to be segregated perfectly well in individual components of drought resistant and drought susceptible bulks which were bulked based on yield under water stress among F2：3 lines. Hence, this simple and breeder friendly marker, RM27933, may be useful as a potentially valuable candidate marker for the transfer of the QTL qtl12.1 in the regional breeding program. Bioinformatic analysis of the DNA sequence of the qtl12.1 region was also done to identify and analyze positional candidate genes associated with this QTL and to ascertain the putative molecular basis of qUl2.1.

关键词： rice bulked segregant analysis water stress quantitative trait locus marker-assisted selection

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Effect of Agricultural seasons on Energy Intake: Evidence from Two Agro-Ecologically Different Rural Districts of India

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Food and Nutrition sciences 2018年第5期9卷 542-555页

作者： D. J. nithya s. Raju Aliza Pradhan Leveraging Agriculture for Nutrition in south Asia M. S. Swaminathan Research Foundation Taramani Institutional Area Chennai India

seasonality is recognised as a constraint to agricultural production and food and nutrition security of rural households. It alters the energy intake from different groups of foods based on the availability. These variations in energy intake affect the nutritional status of the population. Eight villages in Wardha district of Maharashtra state and eleven villages in Koraput district of Odisha state were purposefully selected for the study. Foods consumed by households were collected using a semi-quantitative questionnaire in three rounds in 2013-14 and 2014-15 to cover the lean (January-April), planting (May-August) and harvest (september-December) periods in agriculture. Cereals (wheat and rice), pulses, roots and tubers, fats and sugars were consumed daily in Wardha. In Koraput, the daily diet included cereals (rice and finger millet), other vegetables, fats and sugars. Cereals supplied majority of the total energy intake in both the study area (63% in Wardha and 85% in Koraput);the contribution is higher during lean period in Wardha and during planting in Koraput. significant variation was found in the mean intake of food groups and the energy obtained from them between seasons except for few food groups. It was found to be positive during the planting season in Koraput and negative during lean period and harvest season when compared with the average energy intake across three seasons;in Wardha, energy intake was positive during harvest season followed by lean and was negative during planting season. It was also found that most small land holders (seasonality. The sourcing of foods and the energy contributed by them to the total energy intake also varied depending on seasons and majority of energy intake was sourced from public distribution system. seasonality plays a crucial role in energy intake of individuals through fluctuation in availability and accessibility of food;this in turn will impact the nutritional status of the rural popula

关键词： Agricultural seasons Energy Intake Landholding size sourcing of Foods

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Enhanced Archimedes Optimization Algorithm for Clustered Wireless sensor Networks

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Computers, Materials & Continua 2022年第10期73卷 477-492页

作者： E.Laxmi Lydia T.M.nithya K.Vijayalakshmi Jeya Prakash Kadambaajan Gyanendra Prasad Joshi sung Won Kim Computer science and Engineering Vignan’s Institute of Information Technology(Autonomous)Andhra Pradesh530049India Department of Computer science and Engineering K.Ramakrishnan College of EngineeringTiruchirappalli621112India Department of Electronics&Communication Engineering Saveetha School of EngineeringSaveetha Institute of Medical and Technical SciencesChennai600025India Department of Electronics&Communication Engineering Kalasalingam Academy of Research and EducationKrishnankoil626128India Department of Computer science and Engineering Sejong UniversitySeoul05006Korea Department of Information and Communication Engineering Yeungnam UniversityGyeongsan-siGyeongbuk-do38541Korea

Wireless sensor networks(WsN)encompass a set of inexpensive and battery powered sensor nodes,commonly employed for data gathering and tracking *** energy utilization of the nodes in WsN is essential to capture data effectively and transmit them to *** latest developments of energy efficient clustering techniques can be widely applied to accomplish energy efficiency in the *** this aspect,this paper presents an enhanced Archimedes optimization based cluster head selection(EAOA-CHs)approach for *** goal of the EAOA-CHs method is to optimally choose the CHs from the available nodes in WsN and then organize the nodes into a set of ***,the EAOA is derived by the incorporation of the chaotic map and pseudo-random ***,the EAOA-CHs technique determines a fitness function involving total energy consumption and lifetime of *** design of EAOA for CH election in the WsN depicts the novelty of *** order to exhibit the enhanced efficiency of EAOA-CHs technique,a set of simulations are applied on 3 distinct conditions dependent upon the place of base station(Bs).The simulation results pointed out the better outcomes of the EAOA-CHs technique over the recent methods under all scenarios.

关键词： Wireless sensor network CH selection energy efficiency clustering lifetime

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An Optimized Fuzzy Based Ant Colony Algorithm for 5G-MANET

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Computers, Materials & Continua 2022年第1期70卷 1069-1087页

作者： R.nithya K.Amudha A.syed Musthafa Dilip Kumar sharma Edwin Hernan Ramirez-Asis Priya Velayutham V.subramaniyaswamy sudhakar sengan Department of Computer science and Engineering Vivekananda College of Engineering for WomenTiruchengode637205Tamil NaduIndia Department of Electronics and Communication Engineering Kongunadu College of Engineering and TechnologyThottiam621215Tamil NaduIndia Department of Information Technology M.Kumarasamy College of EngineeringKarur639113Tamil NaduIndia Department of Mathematics Jaypee University of Engineering and TechnologyGuna473226M.P.India Business and Tourism Faculty Universidad Nacional Santiago Antunez De MayoloHuarazPeru Department of Computer science and Engineering Paavai Engineering CollegeNamakkal637018Tamil NaduIndia school of Computing SASTRA Deemed UniversityThanjavur613401Tamil NaduIndia Department of Computer science and Engineering PSN College of Engineering and TechnologyTirunelveli627152Tamil NaduIndia

The 5G demonstrations in a business has a significant role in today’s fast-moving *** in 5G,drives a wireless system intended at an enormously high data rate,lower energy,low latency,and *** this reason,routing protocols of MANET have the possibility of being fundamentally flexible,high performance,and *** 5G communication aims to afford higher data rates and significantly low Over-The-Air *** through supplementary ACO routing processes,a security-aware,fuzzy improved ant colony routing optimization protocol is proposed in *** goal is to develop aMANET routing protocol that could provide a stable packet transmission ratio,less overhead connectivity,and low end-to-end latency in shared standard scenarios and attack *** demonstrates effective results with hybrid architecture and proved to be effective than other state-of-the-art routing protocols of MANETs,like AODV,its routing organization implemented through Optimized Fuzzy based ACO Algorithm for ***-wavelengths are required to perform a significant role in *** research proposed to test the efficiency of MANET consisting of only mmWave User *** reduced packet transmission loss of UEs withmmWave,meaning well-transmitted sNR leads directly to a better packet delivery *** verify results,simulation using the Ns-3 simulator mmWave module is used.

关键词： 5G attacks D2D communications MANET mmWave security

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Nimotuzumab with Induction Chemotherapy and Chemo-Radiation in Patients with Advanced Head and Neck Cancer

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Journal of Cancer Therapy 2015年第2期6卷 146-152页

作者： sundaram subramanium Venkatanarayan Balasundaram sridharan nithya Poojar Kiran Medical Oncology V. S. Hospital Chennai India Radiation Oncology V. S. Hospital Chennai India Clinical Pharmacology Biocon Bangalore India

Background: Head and neck squamous cell carcinoma (HNsCC), is a common malignancy in the Indian Population. In locally advanced disease, chemoradiation is the standard of care. Although induction chemotherapy has been much studied, no clear benefit has been identified apart from laryngeal preservation. A few randomized trials have demonstrated improved response rate, disease free survival, and overall survival, with induction chemotherapy. Nimotuzumab is a humanized monoclonal antibody targeting epidermal growth factor receptors (EGFR). Unlike other Anti-EGFR monoclonal antibodies, it is demonstrated to be safer when combined with chemotherapy and/or radiotherapy. Aim: To evaluate the safety and efficacy of concurrently administered nimotuzumab with chemo-radiotherapy in patients with HNsCC in usual health care setting. Methods: This was an open-label, single arm study, with retrospective analysis of results. Patients above 18 years of age, and having histologically confirmed, advanced HNsCC were included in the study. The patients were treated with 3 cycles of induction chemotherapy consisting of modified TPF regimen along with nimotuzumab (200 mg IV) on Day 1, followed by radiotherapy for a dose of 66 Gy along with concurrent weekly cisplatin (30 mg/m2) and nimotuzumab (200 mg) throughout the course of radiation. Patients were evaluated using RECIsT criteria, 4 weeks after the last cycle of chemotherapy. Results: sixteen patients were included in this study, with mean age of 54 ± 11 years.?Most common sub-site of cancer was oral cavity in 69% (n = 11), followed by pharynx in 19% (n = 3).?Four patients had metastasis at the time of presentation. six patients (37.5%) had progressive disease and four patients (25%) were lost to follow-up. The combination chemotherapy with nimotuzumab was well tolerated. Addition of nimotuzumab to TPF regimen was not associated with added toxicity. Conclusion: Addition of anti-EGFR monocloncal antibody (nimotuzumab) to induction chemo

关键词： Nimotuzumab Head and Neck Cancer Chemoradiotherapy Cisplatin Epidermal Growth Factor Receptors Monoclonal Antibody

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Nutrient Intake of Rural Households That Participated in a Farming system for Nutrition study in India

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Food and Nutrition sciences 2021年第3期12卷 277-289页

作者： D. J. nithya s. Raju R. V. Bhavani Akshaya Kumar Panda Rupal D. Wagh Brinda Viswanathan Ms swaminathan Research Foundation Chennai India Madras school of Economics Chennai India

Food based approach can prove effective in improving access and availability of nutrients from foods required for daily life where most of the people depend on agriculture for their livelihood. A study on feasibility of Farming systems for Nutrition (FsN) approach was undertaken from 2013 to 2018 in a few villages of Koraput district, Odisha state and Wardha district, Maharashtra state in India. Interventions were done to increase crop diversity, intercropping of pulses and cereals, promotion of seasonal vegetables and fruits along span>span>with span>span>span style="font-family:Verdana;">span style="font-family:Verdana;">span style="font-family:Verdana;">nutrition awareness. The endline survey showed increase in production diversity leading to improved household dietary diversity. This paper demonstrates the impact of FsN interventions on household nutrient intake. The results show that the intake of nutrients like protein, vitamin C, iron and calcium increased significantly in Koraput and all the nutrients including energy and vitamin A increased significantly in Wardha. The evidence shows that Farming system for Nutrition approach improves individual nutrient intake which in the long run can address the problem of undernutrition.

关键词： Farming systems for Nutrition Nutrient Intake Recommended Dietary Allowance Nutrient source

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Nutrient Intake of Rural Households That Participated in a Farming system for Nutrition study in India

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Food and Nutrition sciences（食品与营养科学） 2021年第3期

作者： D. J. nithya s. Raju R. V. Bhavani Akshaya Kumar Panda Rupal D. Wagh Brinda Viswanathan

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