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Multiway Relay Based Framework for Network Coding in Multi-Hop WSNs

Computers, Materials & Continua 2023年第1期74卷 1199-1216页

作者： Vinod kumar Menaria Anand Nayyar sandeep kumar Ketan Kotecha Department of IT&C(DoIT&C) Govt of RajasthanJaipurIndia Graduate School Faculty of Information TechnologyDuy Tan UniversityDa NangVietnam Department of Computer Science and Engineering CHRIST(Deemed to be University)Bangalore560074India Symbiosis Centre for Applied Artificial Intelligence Symbiosis International UniversityPuneIndia

In today’s information technology(IT)world,the multi-hop wireless sensor networks(MHWSNs)are considered the building block for the Internet of Things(IoT)enabled communication systems for controlling everyday tasks of organizations and industry to provide quality of service(QoS)in a stipulated time slot to end-user over the Internet.Smart city(SC)is an example of one such application which can automate a group of civil services like automatic control of traffic lights,weather prediction,surveillance,etc.,in our daily life.These IoT-based networks with multi-hop communication and multiple sink nodes provide efficient communication in terms of performance parameters such as throughput,energy efficiency,and end-to-end delay,wherein low latency is considered a challenging issue in next-generation networks(NGN).This paper introduces a single and parallels stable server queuing model with amulti-class of packets and native and coded packet flowto illustrate the simple chain topology and complexmultiway relay(MWR)node with specific neighbor topology.Further,for improving data transmission capacity inMHWSNs,an analytical framework for packet transmission using network coding at the MWR node in the network layer with opportunistic listening is performed by considering bi-directional network flow at the MWR node.Finally,the accuracy of the proposed multi-server multi-class queuing model is evaluated with and without network coding at the network layer by transmitting data packets.The results of the proposed analytical framework are validated and proved effective by comparing these analytical results to simulation results.

关键词： Multi-hop wireless sensor networks network coding multiway relay node throughput multi-server multi-class queuing models

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Characterization and validation of a chronic retinal neovascularization rabbit model by evaluating the efficacy of anti-angiogenic and anti-inflammatory drugs

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International Journal of Ophthalmology(English edition) 2022年第1期15卷 15-22页

作者： sandeep kumar John Quach Nicholas Cook Glenwood Gum Vatsala Naageshwaran Department of Ophthalmology Absorption Systems:a Pharmaron company7901 Vickers StSan DiegoCA 92111USA

AIM:To establish a rabbit model with chronic condition of retinal neovascularization(RNV)induced by intravitreal(IVT)injection of DL-2-aminoadipic acid(DL-AAA),a retinal glial(Mül er)cell toxin,extensive characterization of DL-AAA induced angiographic features and the suitability of the model to evaluate anti-angiogenic and anti-inflammatory therapies for ocular vascular diseases.METHODS:DL-AAA(80 mmol/L)was administered IVT into both eyes of Dutch Belted rabbit.Post DL-AAA delivery,clinical ophthalmic examinations were performed weekly following modified Mc Donald-Shadduck Scoring System.Color fundus photography,fluorescein angiography(FA),and optical coherence tomography(OCT)procedures were performed every 2 or 4 wk until stable retinal vascular leakage was observed.Once stable retinal leakage(12 wk post DL-AAA administration)was established,anti-vascular endothelial growth factor(VEGF)(bevacizumab,ranibizumab and aflibercept)and anti-inflammatory(triamcinolone,TAA)drugs were tested for their efficacy after IVT administration.Fluorescein angiograms were scored before and after treatment following a novel grading system,developed for the DL-AAA rabbit model.RESULTS:Post DL-AAA administration,eyes were presented with moderate to severe retinal/choroidal inflammation which was accompanied by intense vitreous flare and presence of inflammatory cells in the vitreous humor.Retinal hemorrhage was restricted to the tips of neo-retinal vessels.FA revealed maximum retinal vascular leakage at 2 wk after DL-AAA injection and then persisted as evidenced by stable mean FA scores in weeks 8 and 12.Retinal vascular angiographic and tomographic features were stable and consistent up to 36 mo among two different staggers induced for RNV at two different occasions.Day 7,mean FA scores showed that 1μg/eye of bevacizumab,ranibizumab,aflibercept and 2μg/eye of TAA suppress 65%,90%,100%and 50%retinal vascular leakage,respectively.Day 30,bevacizumab and TAA continued to show 66%and 44%suppression while ranibizumab effect was becoming

关键词： DL-2-aminoadipic acid chronic wet agerelated macular degeneration retinal neovascularization animal model anti-vascular endothelial growth factor drugs fluorescein angiography

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Plant Identification Using Fitness-Based Position Update in Whale Optimization Algorithm

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Computers, Materials & Continua 2022年第6期71卷 4719-4736页

作者： Ayman Altameem sandeep kumar Ramesh Chandra Poonia Abdul Khader Jilani Saudagar Department of Computer Science College of Applied StudiesKing Saud UniversityRiyadh11495Saudi Arabia Department of Computer Science and Engineering CHRIST(Deemed to be University)Bangalore560074India Department of Computer Science CHRIST(Deemed to be University)Bangalore560029India Information Systems Department Imam Mohammad Ibn Saud Islamic University(IMSIU)Riyadh11432Saudi Arabia

Since the beginning of time,humans have relied on plants for food,energy,and medicine.Plants are recognized by leaf,flower,or fruit and linked to their suitable cluster.Classification methods are used to extract and select traits that are helpful in identifying a plant.In plant leaf image categorization,each plant is assigned a label according to its classification.The purpose of classifying plant leaf images is to enable farmers to recognize plants,leading to the management of plants in several aspects.This study aims to present a modified whale optimization algorithm and categorizes plant leaf images into classes.This modified algorithm works on different sets of plant leaves.The proposed algorithm examines several benchmark functions with adequate performance.On ten plant leaf images,this classification method was validated.The proposed model calculates precision,recall,F-measurement,and accuracy for ten different plant leaf image datasets and compares these parameters with other existing algorithms.Based on experimental data,it is observed that the accuracy of the proposed method outperforms the accuracy of different algorithms under consideration and improves accuracy by 5%.

关键词： Bag-of-features feature optimization plant leaf classification swarm intelligence nature-inspired algorithm

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A case study illustrating the use of an integrated approach to treat secondary Anal Fistula Post I&D of Perianal Abscess

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Clinical Research Communications 2024年第1期7卷 11-17页

作者： sandeep kumar Upadhyay Sheetal Asutkar Shreya Soni Department of Shalya Tantra Mahatma Gandhi Ayurved College Hospital and Research CentreWardha 442001India HOD Shalya Tantra Mahatma Gandhi Ayurved College Hospital and Research CentreWardha 442001India

Background:Anal fistula is a long-term disease characterized by a tubular structure with one end opening in the anorectal canal and the other end opening on the surface of the perineum or perianal skin with chronic pus drainage.It is linked to Bhagandar in Ayurveda,and in Sushruta Samhita,Acharya has mentioned 5 forms of Bhagandar.The boil in the present case was Shukla,sthira i.***.hard and firm,with Picchila strava and Kandu resembling the features of Parisraavi bhagandar.Aim and objective:The current case was diagnosed as Parisravi bhagandar,which resembles trans-sphincteric or intersphincteric fistula in modern ano.In Ayurveda,the management of Parisraavi Bhagandar,Shastra,kshara,and Agnikarma is advised and the use of Ksharasutra,which contributes to complete cutting and healing of the track without reoccurrence,similarly Modern surgeon depends on surgery i.e radical excision of the track,ligation with Seton,and use of chemical irritants like urethane,silver nitrates,etc.A cutting seton(tight)gently slices the confined muscle to close the fistula with the least interruption to continence.This operation is especially advised when a one-stage fistulotomy poses a considerable risk of incontinence.Material and methods:The method performed here was Core Partial Fistulectomy followed by Ksharasutra application till complete healing of the wound.Discussion and conclusion:This case study provides the successful management of Parisraavi Bhagandara(high anal,trans-sphincteric fistula in ano)in 61-year-old male patient with an integrated surgical&Ayurvedic management approach.

关键词： Anal fistula Colonoscopy ligation of trans-sphincteric fistula Methylene blue dye perianal abscess Radical excision Sushrut Samhita

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Robust Facial Biometric Authentication System Using Pupillary Light Reflex for Liveness Detection of Facial Images

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Computer Modeling in Engineering & Sciences 2024年第4期139卷 725-739页

作者： Puja S.Prasad Adepu Sree Lakshmi sandeep Kautish Simar Preet Singh Rajesh kumar Shrivastava Abdulaziz S.Almazyad Hossam M.Zawbaa Ali Wagdy Mohamed CSE Department Geethanjali College of EngineeringHyderabadTelangana501301India Department of Computer Science LBEF CampusKathmandu44600Nepal School of Computer Science Engineering and Technology(SCSET) Bennett UniversityGreater Noida201310India Department of Computer Engineering College of Computer and Information SciencesKing Saud UniversityP.O.Box 51178Riyadh11543Saudi Arabia CeADAR Ireland’s Centre for AI Technological University DublinDublinD07 EWV4Ireland Operations Research Department Faculty of Graduate Studies for Statistical ResearchCairo UniversityGiza12613Egypt Applied Science Research Center Applied Science Private UniversityAmman11937Jordan

Pupil dynamics are the important characteristics of face spoofing detection.The face recognition system is one of the most used biometrics for authenticating individual identity.The main threats to the facial recognition system are different types of presentation attacks like print attacks,3D mask attacks,replay attacks,etc.The proposed model uses pupil characteristics for liveness detection during the authentication process.The pupillary light reflex is an involuntary reaction controlling the pupil’s diameter at different light intensities.The proposed framework consists of two-phase methodologies.In the first phase,the pupil’s diameter is calculated by applying stimulus(light)in one eye of the subject and calculating the constriction of the pupil size on both eyes in different video frames.The above measurement is converted into feature space using Kohn and Clynes model-defined parameters.The Support Vector Machine is used to classify legitimate subjects when the diameter change is normal(or when the eye is alive)or illegitimate subjects when there is no change or abnormal oscillations of pupil behavior due to the presence of printed photograph,video,or 3D mask of the subject in front of the camera.In the second phase,we perform the facial recognition process.Scale-invariant feature transform(SIFT)is used to find the features from the facial images,with each feature having a size of a 128-dimensional vector.These features are scale,rotation,and orientation invariant and are used for recognizing facial images.The brute force matching algorithm is used for matching features of two different images.The threshold value we considered is 0.08 for good matches.To analyze the performance of the framework,we tested our model in two Face antispoofing datasets named Replay attack datasets and CASIA-SURF datasets,which were used because they contain the videos of the subjects in each sample having three modalities(RGB,IR,Depth).The CASIA-SURF datasets showed an 89.9%Equal Error Rate,while the Replay Attack datasets showed

关键词： SIFT pupil CASIA-SURF pupillary light reflex replay attack dataset brute force

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Fundus photography,fluorescein angiography,optical coherence tomography and electroretinography of preclinical animal models of ocular diseases

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Annals of Eye Science 2023年第3期8卷 70-76页

作者： sandeep kumar Pharmaron(US)Lab Services San DiegoCAUSA

The eye is an immune-privileged and sensory organ in humans and animals.Anatomical,physiological,and pathobiological features share significant similarities across divergent species(1).Each compartment of the eye has a unique structure and function.The anterior and posterior compartments of the eye contain endothelium(cornea),epithelium(cornea,ciliary body,iris),muscle(ciliary body),vitreous and neuronal(retina)tissues,which make the eye suitable to evaluate efficacy and safety of tissue specific drugs(2).

关键词： Retinal fundus photography sodium fluorescein and indocyanine green angiography optical coherence tomography(OCT) electroretinography animal models of ocular diseases

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Performance Analysis of Machine Learning Algorithms for Classifying Hand Motion-Based EEG Brain Signals

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Computer Systems Science & Engineering 2022年第9期42卷 1095-1107页

作者： Ayman Altameem Jaideep Singh Sachdev Vijander Singh Ramesh Chandra Poonia sandeep kumar Abdul Khader Jilani Saudagar Department of Computer Science College of Applied StudiesKing Saud UniversityRiyadh11495Saudi Arabia Department of Computer Science and Engineering Manipal University JaipurJaipur303007India Department of Computer Science CHRIST(Deemed to be University)Bangalore560029India Department of Computer Science and Engineering CHRIST(Deemed to be University)Bangalore560074India Information Systems Department Imam Mohammad Ibn Saud Islamic University(IMSIU)Riyadh11432Saudi Arabia

Brain-computer interfaces (BCIs) records brain activity using electroencephalogram (EEG) headsets in the form of EEG signals;these signals can berecorded, processed and classified into different hand movements, which can beused to control other IoT devices. Classification of hand movements will beone step closer to applying these algorithms in real-life situations using EEGheadsets. This paper uses different feature extraction techniques and sophisticatedmachine learning algorithms to classify hand movements from EEG brain signalsto control prosthetic hands for amputated persons. To achieve good classificationaccuracy, denoising and feature extraction of EEG signals is a significant step. Wesaw a considerable increase in all the machine learning models when the movingaverage filter was applied to the raw EEG data. Feature extraction techniques likea fast fourier transform (FFT) and continuous wave transform (CWT) were usedin this study;three types of features were extracted, i.e., FFT Features, CWTCoefficients and CWT scalogram images. We trained and compared differentmachine learning (ML) models like logistic regression, random forest, k-nearestneighbors (KNN), light gradient boosting machine (GBM) and XG boost onFFT and CWT features and deep learning (DL) models like VGG-16, DenseNet201 and ResNet50 trained on CWT scalogram images. XG Boost with FFTfeatures gave the maximum accuracy of 88%.

关键词： Machine learning brain signal hand motion recognition braincomputer interface convolutional neural networks

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Piecewise linear programming approach to solve multi-objective matrix games with I-fuzzy goals

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Journal of Control and Decision 2021年第1期8卷 1-13页

作者： sandeep kumar Department of Mathematics Ch.Charan Singh UniversityMeerut 250004Uttar PradeshIndia

The intuitionistic fuzzy set(I-fuzzy set)plays an effective role in game theory when players face‘neither this nor that’situation to set their goals.This study presents a maxmin–minmax solution to multi-objective two person zero-sum matrix games with I-fuzzy goals.In this article,a class of piecewise linear membership and non-membership functions for I-fuzzy goals is constructed.These functions are more effective in real games because marginal rate of increase(decrease)of such membership functions(non-membership functions)is different in different intervals of tolerance errors.Finally,one numerical example is given to examine the effectiveness and advantages of the proposed results.

关键词： Intuitionistic fuzzy set multi-objective matrix game I-fuzzy goals maxmin-minmax solution piecewise linear function

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Sigmoidal Particle Swarm Optimization for Twitter Sentiment Analysis

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Computers, Materials & Continua 2023年第1期74卷 897-914页

作者： sandeep kumar Muhammad Badruddin Khan Mozaherul Hoque Abul Hasanat Abdul Khader Jilani Saudagar Abdullah AlTameem Mohammed AlKhathami Department of Computer Science and Engineering CHRIST(Deemed to be University)Bangalore560074India Information Systems Department College of Computer and Information SciencesImam Mohammad Ibn Saud Islamic University(IMSIU)Riyadh11432Saudi Arabia

Social media,like Twitter,is a data repository,and people exchange views on global issues like the COVID-19 pandemic.Social media has been shown to influence the low acceptance of vaccines.This work aims to identify public sentiments concerning the COVID-19 vaccines and better understand the individual’s sensitivities and feelings that lead to achievement.This work proposes a method to analyze the opinion of an individual’s tweet about the COVID-19 vaccines.This paper introduces a sigmoidal particle swarm optimization(SPSO)algorithm.First,the performance of SPSO is measured on a set of 12 benchmark problems,and later it is deployed for selecting optimal text features and categorizing sentiment.The proposed method uses TextBlob and VADER for sentiment analysis,CountVectorizer,and term frequency-inverse document frequency(TF-IDF)vectorizer for feature extraction,followed by SPSO-based feature selection.The Covid-19 vaccination tweets dataset was created and used for training,validating,and testing.The proposed approach outperformed considered algorithms in terms of accuracy.Additionally,we augmented the newly created dataset to make it balanced to increase performance.A classical support vector machine(SVM)gives better accuracy for the augmented dataset without a feature selection algorithm.It shows that augmentation improves the overall accuracy of tweet analysis.After the augmentation performance of PSO and SPSO is improved by almost 7%and 5%,respectively,it is observed that simple SVMwith 10-fold cross-validation significantly improved compared to the primary dataset.

关键词： Twitter data analysis sentiment analysis social media analytics swarm intelligence COVID-19 vaccine

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Pharmacokinetic, pharmacodynamic, and neurochemical investigations of lamotrigine-pentylenetetrazole kindled mice to ascertain it as a reliable model for clinical drug-resistant epilepsy

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Animal Models and Experimental Medicine 2020年第3期3卷 245-255页

作者： sandeep kumar Rajesh K.Goel Department of Pharmaceutical Sciences&Drug Research Punjabi UniversityPatialaPunjabIndia

Background:Pentylenetetrazole kindling has long been used for the screening of investigational antiseizure drugs.The presence of lamotrigine,at a very low dose,does not hamper kindling in mice;rather it modifies this epileptogenesis process into drug-resistant epilepsy.The lamotrigine-pentylenetetrazole kindled mice show resistance to lamotrigine,phenytoin,and carbamazepine.It may also be possible that other licensed antiseizure drugs,like the mentioned drugs,remain ineffective in this model;therefore,this was the subject of this study.Methods:Swiss albino mice were kindled with pentylenetetrazole for 35 days in the presence of either methylcellulose vehicle or lamotrigine(subtherapeutic dose,ie,5 mg/kg).Vehicle vs lamotrigine-kindled mice were compared in terms of(a)resistance/response toward nine antiseizure drugs applied as monotherapies and two drug combinations;(b)lamotrigine bioavailability in blood and brain;(c)blood-brain barrier integrity;and(d)amino acids and monoamines in the cerebral cortex and hippocampus.Results:Lamotrigine vs vehicle-kindled mice are similar(or not significantly different P>.05 from each other)in terms of(a)response toward drug combinations;(b)lamotrigine bioavailability;and(c)blood-brain barrier integrity except for,significantly(P<.05)reduced taurine and increased glutamate in the cerebral cortex and hippocampus.Aside from these,lamotrigine-kindled mice show significant(P<.05)resistant to lamotrigine(15 mg/kg),levetiracetam(40 mg/kg);carbamazepine(40 mg/kg),zonisamide(100 mg/kg),gabapentin(224 mg/kg),pregabalin(30 mg/kg),phenytoin(35 mg/kg),and topiramate(300 mg/kg).Conclusion:Lamotrigine-pentylenetetrazole kindling takes longer to develop(~5 weeks)in comparison to lamotrigine-amygdale(~4 weeks)and lamotriginecorneal(~2 weeks)kindling models.However,drug screening through this model may yield superior drugs with novel antiseizure mechanisms.

关键词： animal models drug-resistant epilepsy kindling lamotrigine refractory epilepsy

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