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Structural and optical properties of CZTS nanoparticles prepared by a colloidal process

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rare metals 2021年第9期40卷 2602-2609页

作者： r.Aruna-devi m.Latha S.Velumani JoséÁlvaro Chávez-Carvayar Program on Nanoscience and Nanotechnology CINVESTAV-IPNSan Pedro Zacatenco07360 Mexico CityMexico CIICAp-UAEm Av.Universidad 1001.Col.Chamilpa62209 CuernavacaMorelosMexico Department of Electrical Engineering(SEES) CINVESTAV-IPNSan Pedro Zacatenco07360 Mexico CityMexico Instituto de Investigaciones en materiales UNAM04510 Mexico CityMexico

This research presents the influence of copper(Cu) concentration on the properties of copper zinc tin sulfide(CZTS) nanoparticles(NPs) synthesized by a colloidal method, employing oleylamine as an organic solvent. From the structural analysis, a pure phase of CZTS was obtained at an optimized molar ratio of 1.8:1.1:1:4,and secondary phases were observed as the Cu concentration increased. The increment of the NPs size from 15 to50 nm was noticed as a function of Cu ***, the optical bandgap energy was tuned from1.35 to 1.68 eV with respect to Cu concentration. The sample synthesized at the molar ratio of 1.8:1.1:1:4 showed a pure phase CZTS with desired elemental composition and bandgap. Furthermore, CZTS thin films were prepared by a doctor-blade method using synthesized NPs followed by annealing under a sulfur/nitrogen atmosphere. The annealed CZTS film showed a significant improvement in the morphological, electrical and optoelectronic ***, the annealed CZTS film can be efficiently used as an absorber layer in low-cost thin film solar cells.

关键词： CZTS Copper concentration Nanoparticles Thin film Annealing

Structural characterization of Nd-doped in silica host matrix prepared by wet chemical process

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Journal of rare Earths 2009年第1期27卷 83-86页

作者： Surender Duhan Sunita devi m.Singh materials Science Lab Department of Applied Physics Guru Jambheshwar University of Science & Technology materials Science Lab Department of Physics Department of Chemistry Lajpat rai College Department of Physics Amity School of Engineering and TechnologyAmity University Sec-125

Silica host matrix containing neodymium which is potentially important for the formation of nanocrystalline metal oxides was prepared by solgel method, using tetra-ethoxysilane and Nd（NO3）3 as precursor *** prepared samples were changed from amorphous to nanocrystallites phase at sintered temperature 550 °C（4 h）, 750 °C（8 h） and 950 °C（12 h）.The thermally treated sample microstructures were investigated using X-ray diffraction（XrD）, Fourier transformation infrared spectroscopy（FTIr）, and scanning electron mi-croscopy（SEm）.While a further increase of the temperature at 750 °C and annealing time（8 h） resulted in the formation of cubic and hexagonal Nd2O3 *** constant sintering temperature 950 °C for 12 h, the samples showed sharper and intense *** sizes of Nd2O3 nanocrystallites were characterized by XrD with average size ～46 nm.

关键词： rare earth oxide silica annealing/calcination nanocrystallites

Enhancement of IoT device security using an Improved Elliptic Curve Cryptography algorithm and malware detection utilizing deep LSTm

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High-Confidence Computing 2023年第2期3卷 18-31页

作者： r.Aiyshwariya devi A.r.Arunachalam Department of Computer Science and Engineering Dr.M.G.R.Educational and Research InstituteChennai 600095India

Internet of things(IoT)has become more popular due to the development and potential of smart technology *** concerns against IoT infrastructure,applications,and devices have grown along with the need for IoT *** system security protocols are difficult due to the diverse capabilities of IoT devices and the dynamic,ever-changing environment,and simply applying basic security requirements is ***,this proposed work designs a malware detection and prevention approach for secure data transmission among IoT *** malware detection approach is designed with the aid of a deep learning *** initial process is identifying attack nodes from normal nodes through a trust value using contextual *** discovering attack nodes,these are considered for predicting different kinds of attacks present in the network,while some preprocessing and feature extraction strategies are applied for effective *** Deep LSTm classifier is applied for this malware detection *** completed malware detection,prevention is performed with the help of the Improved Elliptic Curve Cryptography(IECC)algorithm.A hybrid mA-BW optimization is adopted for selecting the optimal key during *** 3.8 software is used to test the performance of the proposed approach,and several existing techniques are considered to evaluate its *** proposed approach obtained 95%of accuracy,5%of error value and 92%of *** addition,the improved ECC algorithm is also compared with some existing algorithm which takes 6.02 s of execution *** to the other methods,the proposed approach provides better security to IoT gadgets during data transmission.

关键词： Deep LSTm Improved Elliptic Curve Cryptography malware detection Prediction of different kinds of attacks IoT gadgets

Student Behavior modeling for an E-Learning System Offering Personalized Learning Experiences

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Computer Systems Science & Engineering 2022年第3期40卷 1127-1144页

作者： K.Abhirami m.K.Kavitha devi Department of Computer Science and Engineering Kings College of EngineeringPudukkottai613303India Department of Computer Science and Engineering Thiagarajar College of EngineeringMadurai625015India

With the advent of computing and communication technologies,it has become possible for a learner to expand his or her knowledge irrespective of the place and ***-based learning promotes active and independent *** scale e-learning platforms revolutionized the concept of studying and it also paved the way for innovative and effective teaching-learning *** digital learning improves the quality of teaching and also promotes educational ***,the challenges in e-learning platforms include dissimilarities in learner’s ability and needs,lack of student motivation towards learning activities and provision for adaptive learning *** quality of learning can be enhanced by analyzing the online learner’s behavioral characteristics and their application of intelligent instructional *** is not possible to identify the difficulties faced during the process through evaluation after the completion of e-learning *** is thus essential for an e-learning system to include component offering adaptive control of learning and maintain user’s interest *** this research work,a framework is proposed to analyze the behavior of online learners and motivate the students towards the learning process accordingly so as to increase the rate of learner’s objective *** to the demands of e-learner,an intelligent model is presented in this study for e-learning system that apply supervised machine learning *** adaptive e-learning system suits every category of learner,improves the learner’s performance and paves way for offering personalized learning experiences.

关键词： Learner behavior modeling e-learning intelligent learning system machine learning algorithm

Blockchain Based Consensus Algorithm and Trustworthy Evaluation of Authenticated Subgraph Queries

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Computer Systems Science & Engineering 2023年第5期45卷 1743-1758页

作者： G.Sharmila m.K.Kavitha devi Department of Computer Science&Engineering Syed Ammal Engineering CollegeRamanathapuram623502India Department of Computer Science&Engineering Thiagarajar College of EngineeringMadurai625015India

Over the past era,subgraph mining from a large collection of graph database is a crucial *** addition,scalability is another big problem due to insufficient *** are several security challenges associated with subgraph mining in today’s on-demand *** address this downside,our proposed work introduces a Blockchain-based Consensus algorithm for Authenticated query search in the Large-Scale Dynamic Graphs(BCCA-LSDG).The two-fold process is handled in the proposed BCCA-LSDG:graph indexing and authenticated query search(query processing).A blockchain-based reputation system is meant to maintain the trust blockchain and cloud server of the proposed *** resolve the issues and provide safe big data transmission,the proposed technique also combines blockchain with a consensus algorithm *** of the big data is ensured by dividing the BC network into distinct networks,each with a restricted number of allowed entities,data kept in the cloud gate server,and data analysis in the *** consensus algorithm is crucial for maintaining the speed,performance and security of the *** Dual Similarity based mapreduce helps in mapping and reducing the relevant subgraphs with the use of optimal feature ***,the graph index refinement process is undertaken to improve the query *** query error,fuzzy logic is used to refine the index of the graph *** proposed technique outperforms advanced methodologies in both blockchain and non-blockchain systems,and the combination of blockchain and subgraph provides a secure communication platform,according to the findings.

关键词： Big data blockchain consensus algorithm trust management graph index

BHGSO:Binary Hunger Games Search Optimization Algorithm for Feature Selection Problem

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Computers, materials & Continua 2022年第1期70卷 557-579页

作者： r.manjula devi m.Premkumar Pradeep Jangir B.Santhosh Kumar Dalal Alrowaili Kottakkaran Sooppy Nisar Department of Computer Science and Engineering Kongu Engineering CollegePerundurai638060Tamil NaduIndia Department of Electrical and Electronics Engineering Dayananda Sagar College of EngineeringBengaluru560078KarnatakaIndia rajasthan rajya Vidyut Prasaran Nigam Sikar332025RajasthanIndia Department of Computer Science and Engineering Guru Nanak Institute of TechnologyHyderabad501506TelanganaIndia mathematics Department College of ScienceJouf UniversitySakakaP.O.Box:2014Saudi Arabia Department of mathematics College of Arts and SciencesPrince Sattam bin Abdulaziz UniversityWadi Aldawaser11991Saudi Arabia

In machine learning and data mining,feature selection(FS)is a traditional and complicated optimization *** the run time increases exponentially,FS is treated as an NP-hard *** researcher’s effort to build a new FS solution was inspired by the ongoing need for an efficient FS framework and the success rates of swarming outcomes in different optimization *** paper presents two binary variants of a Hunger Games Search Optimization(HGSO)algorithm based on V-and S-shaped transfer functions within a wrapper FS model for choosing the best features from a large *** proposed technique transforms the continuous HGSO into a binary variant using V-and S-shaped transfer functions(BHGSO-V and BHGSO-S).To validate the accuracy,16 famous UCI datasets are considered and compared with different state-of-the-art metaheuristic binary *** findings demonstrate that BHGSO-V achieves better performance in terms of the selected number of features,classification accuracy,run time,and fitness values than other state-of-the-art *** results demonstrate that the BHGSO-V algorithm can reduce dimensionality and choose the most helpful features for classification *** proposed BHGSO-V achieves 95%average classification accuracy for most of the datasets,and run time is less than 5 *** low and medium dimensional datasets and less than 10 sec for high dimensional datasets.

关键词： Binary optimization feature selection machine learning hunger games search optimization

An application of blended amendments in monsoon rice field

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Ecological Processes 2017年第1期6卷 373-380页

作者： madhumita Ghosh Ashalata devi Department of Environmental Science Tezpur UniversityP.O-784028 NapaamIndia

Introduction:rice is the main food crop of the world,and the cultivation of rice crop during the monsoon season is hard due to the rain-induced *** from this,farmers in north-eastern regions of India often implement improper crop management leading to poor ***,the development of suitable management practices under improved varieties of rice become essential for increasing rice productivity,improving soil quality status and reducing methane ***:The aim of the study was to investigate the variation in soil properties,crop growth and methane emission under the application of an inorganic fertiliser as well as its mixtures with both inorganic and plant *** such an attempt,a field-based experiment was conducted with the rice variety Chandrama during 2015 in slightly acidic soil having sandy loam *** amendments,*** and NPK,blended separately with magnesium sulphate,fresh neem(Azadirechta indica)leaves,used tea(Camellia sinensis ***)leaves,and fresh karanj(Pongamia glabra)leaves were used for the study with four replications ***:Application of NPK separately with the leaves of neem,tea and karanj separately at the onset of monsoon season markedly affected the soil porosity and the water-holding capacity of the ***,in comparison with sole NPK fertilisation,a significance increase in soil organic matter accumulation(2.48±0.10%)was seen only for karanjblended NPK while magnesium sulphate-blended NPK showed the lowest methane emission(0.30±0.01 mg/m2/h).The rice plants grown on karanj-blended NPK soil showed the highest yield(0.560±0.01 kg/m2)among the five ***:It was found that only the karanj leaves blended NPK could significantly improve the soil organic matter and increase rice yield without intensifying methane emission,while magnesium sulphate blended with NPK could significantly reduce methane emission in the flooded rice paddy soil at 0.5 t/ha application level but

关键词： Inorganic fertiliser Leaves of plants Soil properties rice yield methane emission

IrKO:An Improved runge-Kutta Optimization Algorithm for Global Optimization Problems

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Computers, materials & Continua 2022年第3期70卷 4803-4827页

作者： r.manjula devi m.Premkumar Pradeep Jangir mohamed Abdelghany Elkotb rajvikram madurai Elavarasan Kottakkaran Sooppy Nisar Department of Computer Science and Engineering Kongu Engineering CollegePerundurai638060Tamil NaduIndia Department of Electrical&Electronics Engineering Dayananda Sagar College of EngineeringBengaluru560078KarnatakaIndia rajasthan rajya Vidyut Prasaran Nigam Sikar332025RajasthanIndia mechanical Engineering Department College of EngineeringKing Khalid UniversityAbha61421Saudi Arabia mechanical Engineering Department Faculty of EngineeringKafrelsheikh UniversityEgypt Clean and resilient Energy Systems(CArES)Laboratory Texas A&MUniversityGalveston77553TXUSA College of Arts and Sciences Prince Sattam bin Abdulaziz UniversityWadi Aldawaser11991Saudi Arabia

Optimization is a key technique for maximizing or minimizing functions and achieving optimal cost,gains,energy,mass,and so *** order to solve optimization problems,metaheuristic algorithms are *** of these techniques are influenced by collective knowledge and natural *** is no such thing as the best or worst algorithm;instead,there are more effective algorithms for certain ***,in this paper,a new improved variant of a recently proposed metaphorless runge-Kutta Optimization(rKO)algorithm,called Improved runge-Kutta Optimization(IrKO)algorithm,is suggested for solving optimization *** IrKO is formulated using the basic rKO and local escaping operator to enhance the diversification and intensification capability of the basic rKO *** performance of the proposed IrKO algorithm is validated on 23 standard benchmark functions and three engineering constrained optimization *** outcomes of IrKO are compared with seven state-of-the-art algorithms,including the basic rKO *** to other algorithms,the recommended IrKO algorithm is superior in discovering the optimal results for all selected optimization *** runtime of IrKO is less than 0.5 s for most of the 23 benchmark problems and stands first for most of the selected problems,including real-world optimization problems.

关键词： Engineering design global optimization local escaping operator metaheuristics runge-Kutta optimization algorithm

Intelligent Vehicular Communication Using Vulnerability Scoring Based routing Protocol

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Intelligent Automation & Soft Computing 2023年第1期35卷 31-45页

作者： m.ramya devi I.Jasmine Selvakumari Jeya Department of Computer Science and Engineering Hindusthan College of Engineering and TechnologyCoimbatore641050India

Internet of Vehicles(IoV)is an intelligent vehicular technology that allows vehicles to communicate with each other via *** and the Internet of Things(IoT)enable cutting-edge technologies including such self-driving *** the existing systems,there is a maximum communication delay while transmitting the *** proposed system uses hybrid Cooperative,Vehicular Communication management Framework called CAmINO(CA).Further it uses,energy efficient fast message routing protocol with Common Vulnerability Scoring System(CVSS)methodology for improving the communication delay,*** improves security while transmitting the messages through *** this research,we present a unique intelligent vehicular infrastructure communication management *** framework includes additional stability for both short and long-range mobile *** also includes built-in cooperative intelligent transport system(C-ITS)capabilities for experimental verification in real-world *** addition,an energy efficient-fast message distribution routing protocol(EE-FmDrP)has been *** combines the benefits between both temporal and direction oriented routing *** has been suggested for distributing information from the origin ends to the predetermined objective in a quick,accurate,and effective manner in the event of an *** critical value scale score(CVSS)employ ratings to measure the assault probability in markov *** of chained transitions allow us to statistically evaluate the integrity of a group of *** the proposed method helps to enhance the vehicular *** CAmINO with energy efficient fast protocol using CVSS(CA-EEFP-CVSS)method outperforms in terms of shortest transmission latency achieves 2.6 sec,highest throughput 11.6%,and lowest energy usage 17%and PDr 95.78%.

关键词： Intelligent automation intelligent transport system vehicular networks markov chains internet of vehicles critical value scale score