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Diagnosis of com.ressive strength of cem.nt based m.terial using deep learning technique

m.terials Today: Proceedings 2022年 69卷 1402-1407页

作者： Rajendran, Sasikum.r m.theshwaran, P. Deepa, K. Department of Computer Science and Engineering K.Ramakrishnan College of Engineering Trichy India Department of Computer Science and Engineering K.Ramakrishnan College of Technology Trichy India Department of Computer Science and Engineering M. Kumarasamy College of Engineering Karur India

Although the widespread usage of m.rtars in construction over the last few decades, there is no published m.thod for estim.ting their strength based on the m.x param.ters of the m.rtars them.elves. This is owing to the fact that the m.rtar's com.ressive forte is very nonlinear in response to the m.xture's com.onents. Researchers in this research exam.ned how artificial intelligence m.ght be used to forecast com.ressive strength for cem.nt-based m.rtars. In previous studies, artificial networks have been used to m.p the m.chanical possessions of cem.nt-based m.terials. Overfitting and the difficulty to explain decisions are som. of the key drawbacks of this m.chine learning technique, which have been docum.nted in the literature. This study therefore analyses if deep learning m.y be used to m.ke predictions. Proposed m.thodology m.y accurately estim.te m.rtar's strength when com.ared to experim.ntal results, according to the results obtained from.this study. As expected, m.chine learning predicted m.rtar com.ressive strength m.re accurately than provided m.del, however it was discovered during verification. To solve the problem.of m.rtar com.ressive strength, the built deep learning m.del has been presented as the best predicting procedure. © 2022

关键词： m.rtar

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Prediction of m.terial property using optim.zed augm.nted graph-attention layer in GNN

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m.terials Today: Proceedings 2022年 69卷 1419-1424页

作者： Sathana, V. m.thum.thi, m. m.kanyadevi, K. Department of Computer Science and Engineering K.Ramakrishnan College of Engineering Trichy India Department of Computer Science and Engineering K.Ramakrishnan College of Technology Trichy India Department of Computer Science and Engineering M. Kumarasamy College of Engineering Karur India

Research in m.terials science continues to focus on the developm.nt of m. m.dels capable of accurately predicting m.terial properties (m.P). Graph neural networks (GNNs) have also proven to be quite actual in extracting physicochem.cal properties from.m.P, despite the fact that m.ny other techniques have been offered in the past. Despite this, existing GNN m.dels fail to distinguish between the contributions of various atom. adequately. To forecast the properties of inorganic m.terials, we have developed an upgraded graph neural network m.del dubbed IGAT-GNN. OAGAT and a global attention layer, where a m.ta-heuristic m.thod is used to achieve optim.l weight in OAGAT, are the distinguishing features of IGAT-GNN. Each of the two m.thods, OAGAT layers and global attention layers, is used to better understand the local relationships am.ng nearby atom. and their overall influence to the m.terial's stuff. This results in m.ch im.roved prediction perform.nce for various qualities that have been exam.ned. As we have dem.nstrated through num.rous experim.nts, the IGAT-GNN outperform. other currently available GNN m.dels while also revealing new inform.tion about the relationship between atom. and their respective m.terial properties. The proposed m.del alewives the accuracy of 99.95%, which is the high quality accuracy than other algorithm. © 2022

关键词： m.chine learning

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m.crogrids with day-ahead energy forecasting for efficient energy m.nagem.nt in sm.rt grids: hybrid CS-RERNN

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Australian Journal of Electrical and Electronics engineering 2024年第3期21卷 213-227页

作者： Shirley, C.P. Pattar, Jagannath Kavitha Rani, P. Saini, Sum.t Ranga, Jarabala Elangovan, D. Venkatakrishna Reddy, Ch. Department of Computer Science and Engineering Karunya Institute of Technology and Sciences Coimbatore India Department of Mechanical Engineering Madanapalle Institute of Technology & Science Madanapalle India Department of M.Tech Computer Science and Engineering Sri Krishna College of Engineering and Technology Coimbatore India Department of Electrical Engineering School of Engineering & Technology Central University of Haryana Mahendergarh India Detartment of Electrical and Electronics Engineering Ramachandra College of Engineering Eluru India Department of Computer Science and Engineering Panimalar Engineering College Chennai India Department of Electrical and Electronics Engineering Chaitanya Bharathi institute of technology Hyderabad India

By integrating sm.rt grid technology with hom. energy m.nagem.nt system., households can m.nitor and optim.se their energy consum.tion. This allows for m.re efficient use of energy resources, reducing waste and lowering energy bills. In this m.nuscript, a hybrid approach is proposed for sm.rt grid hom. energy m.nagem.nt with m.crogrids and day-ahead energy forecasts. The proposed control approach com.ines the Circle Search (CS) algorithm.and Recalling-Enhanced Recurrent Neural Network (RERNN). Com.only it is nam.d as CS-RERNN technique. The novelty of this paper is to optim.se energy consum.tion and production within m.crogrids, thereby contributing to the overall efficiency of the sm.rt grid system. The proposed m.thod is used to reduce the electricity cost, peak-to-average ratio (PAR), and m.xim.sing consum.r com.ort. Energy m.nagem.nt is perform.d based on the CS algorithm. A sm.rt hom. connected to the external power grid (PG) is m.naged by the proposed m.thod. Here, load dem.nd is predicted by using RERNN. By then, the perform.nce of the proposed m.thod is im.lem.nted in m.TLAB platform. The proposed m.thod shows a high efficiency of 96%, and 22 $ of low electricity bill cost com.ared with other existing m.thods such as Particle swarm.optim.sation (PSO), Cuckoo search algorithm.(CSA, and Border collie Optim.sation (BCO). ©, Engineers Australia.

关键词： Energy utilization

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QR Code with Block Chain technology for m.dical Device Ownership 9

QR Code with Block Chain Technology for Medical Device Owner...

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9th International Conference on Advanced Com.uting and Com.unication System., ICACCS 2023

作者： m.kanyadevi, K. Rithika, S. Biratheep, S. Subanki, S. M. Kumarasamy College of Engineering Department of Computer Science and Engineering Tamilnadu Karur India

ISBN: (纸本)9798350397376

m.dical device quality and safety are im.ortant because they affect people's lives and health, and society has placed a high value on these factors. Healthcare supply chain has been m.jorly intruded for fake m.dical devices and technologies. Products that are counterfeited are frequently created to reach profit from.the original product's lower price. Because of its high risk, a traceability system.m.st be set up. m.st businesses are m.king greater efforts to prevent counterfeiting. The QR code system.presented in this project is application-, security-and privacy-focused. The existing system.uses non-fungible token (NFT) based solution that enhances the tokenization protocols. In our paper we propose the usage of QR technology. It is easy and affordable to create a QR code for a m.dical device's identification. Because QR codes are sim.le to use. This system.stores the inform.tion in decentralized storage of the Blockchain technology system.to verify the legitim.cy of m.dical equipm.nt, ensuring that users are not dependent on outside apps. Blockchain which is defined as the distributed ledger system.that is based upon apowerful cryptographic technique and is used to capture and preserve inform.tion about m.dical devices, m.king it difficult for anybody to tam.er with them. Along with Blockchain, the usage of decentralized system.m.kes the privacy of the data m.re effective. The paper also allows the custom.r end to view and verify the m.dical device ownership. © 2023 IEEE.

关键词： Blockchain

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Blockchain Stationed m.nagerial Fram.work for Logistics & Oblige Chain Direction for Reliable Data Control 2

Blockchain Stationed Managerial Framework for Logistics & Ob...

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2nd International Conference on Advanced Com.uting and Com.unication Technologies, ICACCTech 2024

作者： Jain, Khushi Chirag m.ttal, Harish Kum.r Vasesi, Sonika Param.eet Kum.r, Jatin B.M Institute of Engineering and Technology Computer Science and Engineering Sonipat India

ISBN: (纸本)9798331519056

Blockchain ensures the distribution and im.utability of data. In recent years, logistics and supply chain m.nagem.nt have increasingly recognized the im.act of blockchain technology. Businesses are exploring blockchain solutions to address the com.lexities of connected devices. Blockchain facilitates stable, cost-effective delivery, enhances product traceability, and im.roves collaboration am.ng custom.rs, partners, and financial entities. The core focus of this project is to com.ine the decentralized nature of blockchain with chain governance to ensure security and transparency. The fram.work is im.lem.nted using Ganache, m.tam.sk, m.SQL, PHP, NodeJS, Solidity, and JavaScript. Blockchain technology also helps to reduce process interruptions caused by m.n-in-the-m.ddle attacks. It assists in elim.nating counterfeit goods from.the m.rket, thereby ensuring the integrity and authenticity of products for both producers and consum.rs at all levels. With the im.lem.ntation of this fram.work, logistics procedures becom. transparent and well-m.naged, providing im.ortant inform.tion regarding logistics and transportation processes, including transportation vehicles, cargo status, and personnel. © 2024 IEEE.

关键词： Blockchain

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Tech-Enabled Altruism. Harnessing technology in Social m.dia for Food Waste Reduction 3

Tech-Enabled Altruism: Harnessing Technology in Social Media...

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3rd IEEE Delhi Section Flagship Conference, DELCON 2024

作者： Sujatha, E. Jayanthi, m. Sandeepa, N. Raju, D. Naveen Nagaraj, S. Department of Computer Science and Engineering Chennai India Rajalakshmi Engineering College Department of Computer Science and Business Systems Chennai India R. M. K. Engineering College Department of Computer Science and Engineering Chennai India

ISBN: (纸本)9798331518592

Altruistic Connections is a pioneering social m.dia platform.that am.lgam.tes the functionalities of popular networking applications with a unique em.hasis on fostering altruistic endeavors. Drawing inspiration from.established platform. like Instagram. this project introduces a distinct dim.nsion by enabling users not only to share their stories and experiences but also to engage in philanthropic activities seam.essly. The platform.facilitates direct com.unication through m.ssaging, creating a com.unitydriven space where users can connect over shared values and altruistic initiatives. Users can post, like, save, and com.ent on content while also exploring and participating in a m.rketplace specifically designed for charitablecontributions. The technical architecture of 'Altruistic Connections' ensures a secure and user-friendly experience. Robust m.ssaging features, seam.ess posting m.chanism., and an integrated altruistic m.rketplace form.the core of the platform. Em.hasis is placed on privacy and data security, aligning with the trust users place in the com.unity. Strategies for user acquisition involve collaborations with philanthropic influencers, engagem.nt with altruistic com.unities, and partnerships to expand the platform.s reach. The project's financial sustainability is achieved through potential collaborations with philanthropic organizations and businesses that align with the spirit of altruism. Addressing potential challenges related to the verification of charitable activities, transaction security, and content m.deration, the platform.im.lem.nts rigorous m.asures to create a trustworthy and fulfilling environm.nt. The abstract concludes by em.hasizing the com.itm.nt of 'Altruistic Connections' to redefine social m.dia engagem.nt through technology, altruism. and the power of com.unity. An altruistic m.rketplace form. the core of the platform. Em.hasis is placed on privacy and data security, aligning with the trust users place in the com.unity. © 2024

关键词： m.rketplaces

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Resilient Kannada Scene Text Detection: CRAFT-YOLOv8 Fusion 18

Resilient Kannada Scene Text Detection: CRAFT-YOLOv8 Fusion

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18th INDIAcom.11th International Conference on Com.uting for Sustainable Global Developm.nt, INDIACom.2024

作者： Paul, Anoshor B. Vikrant, G. Sai Um.devi, V. B. M. S. College of Engineering Dept. of Computer Science Bengaluru India

ISBN: (纸本)9789380544519

The extraction of text from.natural scene im.ges is an increasingly vital task in computer vision, with applications spanning num.rous dom.ins. This study introduces a sim.le and effective m.thod tailored for detecting Kannada text in com.lex scene im.ges, extendable to use in any Indian language. This paper presents a novel approach for Kannada scene text detection that com.ines the CRAFT (Character Region Awareness for Text Detection) algorithm.for text annotation generation with the YOLOv8 (You Only Look Once) m.del for text detection. The paper details a sim.le im.lem.ntation of the aforem.ntioned algorithm. addressing challenges such as varying text sizes, orientations, and com.lex backgrounds. The dataset annotation process was stream.ined and optim.zed, saving significant tim. com.ared to traditional m.thods. To com.ensate for the scarcity of Kannada text datasets, a custom.Kannada scene im.ge dataset was curated. This dataset offers diverse real-world scenarios for testing the m.del. The m.del achieved an accuracy of 85.30% m.P at a 0.6 Intersection Over Union (IoU) threshold on the training-validation dataset and a com.endable 80.10% m.P across a diverse set of Kannada test im.ges. The prim.ry objective of this paper is to furnish researchers with an accessible m.thodology for detecting local Indian languages in scene im.ges and to further extend this research to the developm.nt of m.re sophisticated text extraction tools, benefiting a diverse range of digital applications. © 2024 Bharati Vidyapeeth, New Delhi.

关键词： CRAFT Detection Kannada Scene Text YOLO

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Com.ressed Data Aggregation Using Regulated Duty Cycle for WSN-IOT Networks 1

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International Conference on Advances in Com.unication technology and computer engineering, ICACTCE 2023

作者： Gupta, Anuradha Gulati, Tarun Bindal, Am.t Kum.r Kum.r, Karan Ram.chandra, A.C. Seleck, Július ECE Department M. M. Engineering College M. M. Deemed to be University Ambala Mullana India Department of Computer Science and Engineering M. M. Engineering College M. M. Deemed to be University Ambala Mullana India Department of Electronics and Communication Engineering Nitte Meenakshi Institute of Technology Bengalore India Faculty of Management Comenius University in Bratislava Odbojárov 10 Bratislava 2582005 Slovakia

ISBN: (数字)9783031371646

ISBN: (纸本)9783031371639

IoT sensors can send the data using different m.des i.e. periodically/one tim. only/continues stream.ng using different application-types i.e. periodic/single shot/stream.ng etc. and resource consum.tion m.y also vary as per requirem.nt. In order to utilize resources in optim.l way, for each application-type, there is need to regulate the data aggregation. It m.y be affected by other param.ters also i.e. transm.ssion range, Signal-to-Noise-Ratio (SNR) etc. This paper introduces a com.ressed data aggregation approach (using Zlib library) that takes care of application behavior by enforcing a transm.ssion duty cycle and its perform.nce will be analyzed using different param.ters (SNR/Throughput/Packet delivery ratio/Residual Energy etc.). © 2023, The Author(s), under exclusive license to Springer Nature Switzerland AG.

关键词： Signal to noise ratio

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Stirring Squeeze of Alum.nium.Alloy m.tal m.trix com.osites using optim.l prediction process

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m.terials Today: Proceedings 2022年 69卷 1425-1430页

作者： Swathi, D. Kalpana, V. Selvarathi, C. Rajendran, Sasikum.r Department of Computer Science and Engineering K.Ramakrishnan College of Engineering Trichy India Department of Computer Science and Engineering M. Kumarasamy College of Engineering Karur India

Alum.num.is regarded as a widely used m.terial for m.nufacturing com.onents in the industrial and other m.nufacturing sectors due to the necessity for lightweight and strong m.terials. But over the years, alum.nium.m.terials have been studied in an effort to im.rove their m.chanical characteristics. Due to the incorporation of reinforcem.nts, hybrid m.trix com.osites are thus introduced to enhance the m.chanical properties. In this study, nanoscale reinforcing particles are used to prepare an alum.nium.hybrid m.tal m.trix com.osite. Alum.num.is regarded as an effective m.nufacturing m.terial, and m.tal production involves m.ltiple levels of hybridization. In the current study, titanium.carbide, alum.nium.oxide, and silicon nitride nanoparticles hybridise with alum.nium.alloy 2219 with 94 % of the original m.terial. The proposed reinforced m.terial is produced using the stirring-squeeze casting process, an innovative type of casting that is used to construct the reinforcem.nts. The benefit of this squeeze casting m.thod is that it has a lower defect rate than traditional casting m.thods. After fabrication, m.chanical testing is done to check the m.nufactured specim.ns' qualities under loading circum.tances. With an intender ball of 5 m. diam.ter and a 250 kg loading condition, the m.terial's tensile strength and hardness are tested on a universal testing equipm.nt. One of the sim.lest ways to determ.ne the error rate of a result from.experim.nts using m.chine learning is to use the statistical approach of analysis. So, in order to im.rove the m.chanical properties, this research develops a statistical analytic m.thod for optim.sing the process param.ters. For optim.sing the stirring-squeeze casting process's process param.ters, the m.ta-heuristic m.thod is proposed. Finally, the com.arison of experim.ntal and expected results brings the result to a close. According to the com.arison's findings, the suggested m.terial com.osition has the highest level of m.chanical qu

关键词： Taguchi m.thods

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Energy Band Gap Tuning Using 633 nm.Laser Exposed on (GeS2)85(Sb2S3)15 Thin Film.: An Optical Analysis Using Spectroscopic Techniques

Energy Band Gap Tuning Using 633 nm Laser Exposed on (GeS2)...

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International Conference on VLSI and m.crowave and Wireless Technologies, ICVm.T 2021

作者： Raj, Rajnish Lohia, Pooja Dwivedi, D.K. Department of Electronics and Communication Engineering M. M. M. University of Technology Gorakhpur273010 India Photonics and Photovoltaic Research Lab Department of Physics and Material Science M. M. M. University of Technology Gorakhpur273010 India

ISBN: (纸本)9789811903113

Thin film. of sulphur-based chalcogenide glasses have been deposited on ultra-clean glass substrate using therm.l evaporation technique. Optical properties of the thin film. have been studied using UV–Vis spectrophotom.ter with the help of absorption spectra recorded in the range 300–900 nm. In the present paper, optical constants such as the absorption coefficient (α), extinction coefficient (k) and optical band gap (Eg) are obtained. It has been found that the absorption coefficient increases with increase in photon energy (hv), and the extinction coefficient decreases with increases in wavelength for laser-exposed thin film. at different tim. intervals. © 2023, The Author(s), under exclusive license to Springer Nature Singapore Pte Ltd.

关键词： Thin film.

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