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Deep Learning-Based Model for Detection of Brinjal Weed in the Era of Precision Agriculture

Computers, Materials & Continua 2023年第10期77卷 1281-1301页

作者： Jigna Patel anand Ruparelia Sudeep Tanwar Fayez Alqahtani Amr Tolba Ravi Sharma Maria Simona Raboaca Bogdan Constantin Neagu Department of Computer Science and Engineering Institute of TechnologyNirma UniversityAhmedabad382481India Software Engineering Department College of Computer and Information SciencesKing Saud UniversityRiyadh12372Saudi Arabia Computer Science Department Community CollegeKing Saud UniversityRiyadh11437Saudi Arabia Centre for Inter-Disciplinary Research and Innovation University of Petroleum and Energy StudiesDehradun248001India Doctoral School University Politehnica of BucharestBucharest060042Romania National Research and Development Institute for Cryogenic and Isotopic Technologies-ICSI Rm ValceaRamnicu Valcea240050Romania Power Engineering Department Gheorghe Asachi Technical University of IasiIasi700050Romania

The overgrowth of weeds growing along with the primary crop in the fields reduces crop *** solutions like hand weeding are labor-intensive,costly,and time-consuming;farmers have used *** application of herbicide is effective but causes environmental and health ***,Precision Agriculture(PA)suggests the variable spraying of herbicides so that herbicide chemicals do not affect the primary *** by the gap above,we proposed a Deep Learning(DL)based model for detecting Eggplant(Brinjal)weed in this *** key objective of this study is to detect plant and non-plant(weed)parts from crop *** the help of object detection,the precise location of weeds from images can be *** dataset is collected manually from a private farm in Gandhinagar,Gujarat,*** combined approach of classification and object detection is applied in the proposed *** Convolutional Neural Network(CNN)model is used to classify weed and non-weed images;further DL models are applied for object *** have compared DL models based on accuracy,memory usage,and Intersection over Union(IoU).ResNet-18,YOLOv3,CenterNet,and Faster RCNN are used in the proposed *** outperforms all other models in terms of accuracy,i.e.,88%.Compared to other models,YOLOv3 is the least memory-intensive,utilizing 4.78 GB to evaluate the data.

关键词： Precision Agriculture Deep Learning brinjal weed detection ResNet-18 YOLOv3 CenterNet Faster RCNN

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Fault Pattern Diagnosis and Classification in Sensor Nodes Using Fall Curve

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Computers, Materials & Continua 2022年第7期72卷 1799-1814页

作者： Mudita Uppal Deepali Gupta Divya anand Fahd S.Alharithi Jasem Almotiri Arturo Mansilla Dinesh Singh Nitin Goyal Chitkara University Institute of Engineering and Technology Chitkara UniversityPunjabIndia Computer Science&Engineering Department Lovely Professional UniversityJalandharPunjabIndia Department of Computer Science College of Computers and Information TechnologyTaif UniversityP.O.Box 11099Taif21944Saudi Arabia Higher Polytechnic School/Industrial Organization Engineering Universidad Europea del AtlánticoIsabel Torres 2139011SantanderSpain Department of Project Management Universidad Internacional IberoamericanaCampeche24560Mexico Computer Science and Engineering Department Deenbandhu Chhotu Ram University of Science and TechnologyMurthalSonipatHaryanaIndia

The rapid expansion of Internet of Things(IoT)devices deploys various sensors in different applications like homes,cities and *** applications depend upon the accuracy of sensor ***,it is necessary to predict faults in the sensor and isolate their cause.A novel primitive technique named fall curve is presented in this paper which characterizes sensor *** technique identifies the faulty sensor and determines the correct working of the *** sources of sensor faults are explained in detail whereas various faults that occurred in sensor nodes available in IoT devices are also presented in tabular *** prediction in digital and analog sensors along with methods of sensor fault prediction are *** are several advantages and disadvantages of sensor fault prediction methods and the fall curve ***,some solutions are provided to overcome the limitations of the fall curve *** this paper,a bibliometric analysis is carried out to visually analyze 63 papers fetched from the Scopus database for the past five *** novelty is to predict a fault before its occurrence by looking at the fall *** sensing of current flow in devices is important to prevent a major ***,the fall curves of ACS712 current sensors configured on different devices are drawn for predicting faulty or non-faulty *** analysis result proved that if any of the current sensors gets faulty,then the fall curve will differ and the value will immediately drop to *** evaluation metrics for fault prediction are also described in this *** last,this paper also addresses some possible open research issues which are important to deal with false IoT sensor data.

关键词： Fault identification fault classification IoT sensor nodes analog sensors digital sensors fall curve

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In-line digital holography for dynamic metrology of MEMS(Invited Paper)

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Chinese Optics Letters 2009年第12期7卷 1117-1122页

作者： Vijay Raj Singh anand Asundi School of Mechanical and Aerospace Engineering Nanyang Technological University

In-line digital holography helps to relax the spatial resolution requirement on charge-coupled device sensors for digital recording of holograms and to utilize the full sensing area for image reconstruction which provides larger field of view and better imaging resolution. In this letter, a lensless in-line digital holographic microscopy is presented for dynamic metrology of micro-electro-mechanical system devices. The methodologies of interferometry and time-averaged in-line digital holography are presented for dynamic measurements, which are also useful for simultaneous suppression of in-line waves from real image wave. The experimental results are presented for dynamic thermal characterization of microheater and vibration analysis of cantilevers.

关键词： line MEMS

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Intelligent Approach for Clustering Mutations’ Nature of COVID-19 Genome

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Computers, Materials & Continua 2022年第9期72卷 4453-4466页

作者： Ankur Dumka Parag Verma Rajesh Singh Anuj Bhardwaj Khalid Alsubhi Divya anand Irene Delgado Noya Silvia Aparicio Obregon Computer Science and Engineering Women Institute of TechnologyUttarakhand248007India Chitkara University Institute of Engineering and Technology Chitkara University PunjabPunjab140401India Division of Innovation&Entrepreneurship Lovely Professional UniversityPunjab144411India Computer Science and Engineering Chandigarh UniversityPunjab140413India Faculty of Computing and Information Technology King Abdulaziz UniversityJeddah37848Saudi Arabia Computer Science and Engineering Lovely Professional UniversityPunjab144411India Higher Polytechnic School Universidad Europea del AtlánticoSantander39011Spain Universidad Internacional Iberoamericana Campeche24560MexicoC.P Universidade Internacional do Cuanza Bairro Kaluanda BiéAngola

In December 2019,a group of people in Wuhan city of Hubei province of China were found to be affected by an infection called dark etiology *** outbreak of this pneumonia infection was declared a deadly disease by the China Center for Disease Control and Prevention on January 9,2020,named Novel Coronavirus 2019(nCoV-2019).This nCoV-2019 is now known as *** is a big list of infections of this coronavirus which is present in the form of a big *** virus can cause several diseases that usually develop with a serious *** to the World Health Organization(WHO),2019-nCoV has been placed as the modern generation of Severe Acute Respiratory Syndrome(SARS)and Middle East Respiratory Syndrome(MERS)coronaviruses,so COVID-19 can repeatedly change its internal genome structure to extend its *** and accurately predicting the mutational properties of the genome structure of COVID-19 can form a good leadership role in preventing and fighting against *** this research paper,an analytical approach has been presented which is based on the k-means cluster technique of machine learning to find the clusters over the mutational properties of the COVID-19 viruses’complete *** method would be able to act as a promising tool to monitor and track pathogenic infections in their stable and local genetics/hereditary *** paper identifies five main clusters of mutations with k=5 as best in most cases in the coronavirus that could help scientists and researchers develop disease control vaccines for the transformation of coronaviruses.

关键词： nCoV-2019 SARS-CoV-2 COVID-19 genome structure etiology COVID-19 mutations COVID-19 genomes

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Perioperative mortality and morbidity of hip fractures among COVID-19 infected and non-infected patients: A systematic review and meta-analysis

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Chinese Journal of Traumatology 2023年第3期26卷 162-173页

作者： Sujit Kumar Tripathy Paulson Varghese Sibasish Panigrahi Bijnya Birajita Panda anand Srinivasan Ramesh Kumar Sen Department of Orthopedics All India Institute of Medical SciencesBhubaneswar751019India Department of Ophthalmology Srirama Chandra Bhanja Medical College and HospitalCuttack753007India Department of Pharmacology All India Institute of Medical SciencesBhubaneswar751019India Department of Orthopaedics Max HospitalMohali160055India

Purpose:Hip fractures among elderly patients are surgical *** COVID-19 pandemic time,many such patients could not be operated at early time because of the limitation of the medical resources,the risk of infection and redirection of medical attention to a severe infective health ***:A search of electronic databases(PubMed,Medline,CINAHL,EMBASE and the Cochrane Central Register of Controlled Trials)with the keywords"COVID","COVID-19","SARS-COV-2","Corona","pandemic","hip fracture","trochanteric fracture"and"neck femur fracture"revealed 64 studies evaluating treatment of hip fracture in elderly patients during COVID-19 pandemic *** 30-day mortality rate,inpatient mortality rate,critical care/special care need,readmission rate and complications rate in both groups were *** were analyzed using Review Manager(RevMan)***:After screening,7 studies were identified that described the mortality and morbidity in hip fractures in both COVID-19 infected(COVID-19+)and non-infected(COVID-19-)*** were significantly increased risks of 30-day mortality(32.23%COVID-19+deathvs.8.85%COVID-19-death)and inpatient mortality(29.33%vs.2.62%)among COVID-19+patients with odds ratio(OR)of 4.84(95%CI:3.13-7.47,p<0.001)and 15.12(95%CI:6.12-37.37,p<0.001),*** COVID-19+patients needed more critical care admission(OR=5.08,95%CI:1.49-17.30,p<0.009)and they remain admitted for a longer time in hospital(mean difference=3.6,95% CI:1.74-5.45,p<0.001);but there was no difference in readmission rate between these 2 *** risks of overall complications(OR=17.22),development of pneumonia(OR=22.25),and acute respiratory distress syndrome/acute respiratory failure(OR=32.96)were significantly high among COVID-19+patients compared to ***:There are increased risks of the 30-day mortality,inpatient mortality and critical care admission among hip fracture patients who are COVID-19+.The chances of developing pn

关键词： Hip fracture Femur neck fracture Mortality COVID-19 Pandemic

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Efficient ID-based proxy multi-signature scheme secure in random oracle

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Frontiers of Computer Science 2012年第4期6卷 421-428页

作者： Rajeev anand SAHU Sahadeo PADHYE Department of Mathematics Motilal Nehru National Institute of TechnologyAllahabad-211004India

Proxy signature schemes enable an entity to del- egate its signing rights to any other party, called proxy signer. As a variant of proxy signature primitive, proxy multi- signature allows a group of original signers to delegate their signing capabilities to a single proxy signer in such a way that the proxy signer can sign a message on behalf of the group of original signers. We propose a concrete ID-based proxy multi-signature scheme from bilinear pairings. The proposed scheme is existential unforgeable against adaptively chosen message and given ID-attack in random oracle model under the computational Diltie-Hellman （CDH） assumption. The fascinating property of new scheme is that the size of a proxy multi-signature is independent of the number of original sign- ers. Furthermore the proposed scheme is simple and com- putationally more efficient than other ID-based proxy multi- signature schemes.

关键词： ID-based signature scheme bilinear pairings,proxy multi-signature computational Diffie-Hellman prob-lem (CDHP) random oracle

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Adapted Long Short-Term Memory(LSTM)for Concurrent Human Activity Recognition

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Computers, Materials & Continua 2021年第11期69卷 1653-1670页

作者： keshav Thapa Zubaer Md.Abdhulla AI Yang Sung-Hyun Department of Electronic Engineering Kwangwoon UniversitySeoul139-701Korea

In this era,deep learning methods offer a broad spectrum of efficient and original algorithms to recognize or predict an output when given a sequence of *** current trends,deep learning methods using recent long short-term memory(LSTM)algorithms try to provide superior performance,but they still have limited effectiveness when detecting sequences of complex human *** this work,we adapted the LSTM algorithm into a synchronous algorithm(sync-LSTM),enabling the model to take multiple parallel input sequences to produce multiple parallel synchronized output *** proposed method is implemented for simultaneous human activity recognition(HAR)using heterogeneous sensor data in a smart *** assists artificial intelligence in providing services to users according to their *** sync-LSTM algorithm improves learning performance and sees its potential for real-world applications in complex HAR,such as concurrent activity,with higher accuracy and satisfactory computational *** adapted algorithm for HAR is also applicable in the fields of ambient assistive living,healthcare,robotics,pervasive computing,and *** experimental evaluation with publicly available datasets demonstrates the competitive recognition capabilities of our *** sync-LSTM algorithm improves learning performance and has the potential for real-life applications in complex *** concurrent activity recognition,our proposed method shows an accuracy of more than 97%.

关键词： Concurrent HAR deep learning LSTM sync-LSTM smart home

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Properties of cement grout modified with ultra-fine slag

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Frontiers of Structural and Civil Engineering 2018年第1期12卷 58-66页

作者： Sowmini GOPINATHAN K B anand Department of CiviI Engineering Amrita School of Engineering Coimbatore Amrita ~Tshwa Vidyapeetham Amrita University Pincode 641 112 India

The purpose of the study is to obtain a cement grout with improved performance. The grout mixes of the present study contain cement, ultra-fine slag （UFS）, super plasticizer and water. Properties like flowability, bleeding, compressive strength and shrinkage of cement grouts have been studied. Rheological parameters were also studied in order to explain the grout workability. The results show that, cement replacement with slag in grouts could reduce bleeding substantially without affecting the workability of the mixes. Introduction of slag enhanced the compressive strength and reduced shrinkage reasonably. Ultra-fine slag can be used as a supplementary cementitious material in cementitious grouts in order to improve the grout behavior.

关键词： cement grout ultra-fine slag flowability bleeding viscosity

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Detection of Alzheimer’s Disease Progression Using Integrated Deep Learning Approaches

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Intelligent Automation & Soft Computing 2023年第8期37卷 1345-1362页

作者： Jayashree Shetty Nisha P.Shetty Hrushikesh Kothikar Saleh Mowla Aiswarya anand Veeraj Hegde Department of Information and Communication Technology Manipal Institute of TechnologyManipal Academy of Higher EducationManipal576104India Department of Swasthavritta and Yoga J S Ayurved MahavidyalayNadiad387001India

Alzheimer’s disease(AD)is an intensifying disorder that causes brain cells to degenerate early and *** cognitive impairment(MCI)is one of the early signs of AD that interferes with people’s regular functioning and daily *** proposed work includes a deep learning approach with a multimodal recurrent neural network(RNN)to predict whether MCI leads to Alzheimer’s or *** gated recurrent unit(GRU)RNN classifier is trained using individual and correlated *** vectors are concate-nated based on their correlation strength to improve prediction *** feature vectors generated are given as the input to multiple different classifiers,whose decision function is used to predict the final output,which determines whether MCI progresses onto AD or *** findings demonstrated that,compared to individual modalities,which provided an average accuracy of 75%,our prediction model for MCI conversion to AD yielded an improve-ment in accuracy up to 96%when used with multiple concatenated *** the accuracy of different decision functions,such as Support Vec-tor Machine(SVM),Decision tree,Random Forest,and Ensemble techniques,it was found that that the Ensemble approach provided the highest accuracy(96%)and Decision tree provided the lowest accuracy(86%).

关键词： Alzheimer recurrent neural network gated recurrent unit support vector machine random forest ensemble correlation hyper-parameter tuning decision tree

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Tribological response of waste tire rubber as micro-fillers in automotive brake lining materials

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Friction 2020年第6期8卷 1153-1168页

作者： anand PAI Sayikumar SUBRAMANIAN Tribhuvan SOOD Department of Aeronautical and Automobile Engineering Manipal Institute of TechnologyManipal Academy of Higher Education ManipalKarnataka 576104lIndia Cranfield University CranfieldMilton KeynesBedfordshire MK430ALUK

Elastomeric materials show promise as potential micro-fillers in brake *** can provide vibration damping and acoustic advantages in intermittent and abrupt impact applications such as *** elastomeric material can be salvaged from non-biodegradable automotive tires,thereby providing an opportunity to reuse materials that will otherwise be discarded in *** tribological and thermomechanical performances of the waste tire rubber were assessed to determine their potential for use as micro-fillers in the brake linings of commercial vehicles with a gross weight less than 16 ***,the brake lining materials were fabricated with fine waste tire rubber particulates(WTRPs)as the micro-fillers,phenolic-R resin as the binder,graphite as the dry lubricant,laterite as the co-filler,and coconut coir for natural fiber *** effects of increasing the WTRP weight fraction on the brake response of the linings were analyzed,and the different compositions were benchmarked against a commercial brake *** characterization comprising compressive strength,hardness,density,and porosity studies were carried *** and wear characteristics of the linings were analyzed using a rotary tribometer with simultaneous thermal *** manufactured lining with 15 wt%WTRPs exhibited a mean friction coefficient of^0.38,a specific volumetric loss rate of 1,662μm3/(N?m),and improved thermal *** optical microscopy and scanning electron microscopy(SEM)with energy dispersive spectroscopy(EDS),wear surface morphology studies compared the relative development of primary and secondary plateaus and revealed the redistribution of wear debris,leading to the stability of the coefficient of friction.

关键词： automotive brakes elastomers graphite energy dispersive spectroscopy(EDS) scanning electron microscopy(SEM) wear mechanisms

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