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17th INDIACom;2023 10th International Conference on Computing for Sustainable Global Development, INDIACom 2023

作者： Dewan, Ritu Polishetty, Rohith Sharan, Bhagwati Goyal, Mayank Kumar Balde, Amadou Mouctar Greynoon, Ameen Mohamad Ahmad Galgotias College of Engineering and Technology Department of Computer Science and Engineering Greater Noida India Sr. Software Engineer Migo India Limited Hyderabad India Srm University-AP School of Engineering and Sciences Department of Computer Science and Engineering Amaravati India Sharda University School of Engineering and Technology Department of Computer Science and Engineering Greater Noida India School of Engineering and Technology Sharda University Department of Computer Science and Applications Greater Noida India

ISBN: (纸本)9789380544472

One of the primary structural materials in the development business is concrete. Compressive strength is the most frequently utilized metric when assessing the strength and nature of cement. This paper clarifies how to make use of technical regression (RT) methodology to decide the legitimate dose of the concrete mixture. Water, Cement, Fly Ash, Blast Furnace, Superplasticizer, Coarse, and Fine Aggregate, were used as input parameters, on the other hand, compressive strength was used as an output parameter. The produced models were evaluated using statistical parameters: Linear Regression, Decision Tree Regression, and Random Forest Regression. In contrast with other applicable models, it was found that the Gaussian process regression model based on the function of the nucleus of radial bases delivered relatively better results. The recommended models should get a good deal on saving money on materials, labor, and time while also improving accuracy. The proposed concrete should be more durable and accordingly more cost-effective. © 2023 Bharati Vidyapeeth, New Delhi.

关键词： Cements

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A Parallel Slime Mould Algorithm with Boundary Rebound and Knowledge-Sharing Mechanism 15th

A Parallel Slime Mould Algorithm with Boundary Rebound and...

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15th International Conference on Genetic and Evolutionary Computing, ICGEC 2023

作者： Fan, HongYe Chu, Shu-Chuan Sui, Xiao Pan, Jeng-Shyang School of Computer Science Northeast Electric Power University Jilin Jilin City132012 China College of Computer Science and Engineering Shandong University of Science and Technology Shandong Qingdao266590 China Department of Information Management Chaoyang University of Technology Taichung41349 Taiwan

ISBN: (纸本)9789819700677

The conventional slime mould method has high global search ability but has certain drawbacks such as sluggish convergence speed, limited accuracy, and the tendency to slip into a locally optimum solution. Aiming at the algorithm’s shortcomings, we propose an improved stochastic optimization algorithm—a parallel Slime Mould Algorithm with Boundary rebound and Knowledge-sharing mechanism (PKB-SMA). The main improvement measures are as follows: (1) Introduce a parallel technique to balance the algorithm’s capacity for exploration and development. (2) Propose a knowledge-sharing system to improve individual quality. (3) Using boundary rebound method to improve individual exploration ability. (4) The population was initialized by Hammersley sampling method. Several test functions are utilized to validate the performance of the PKB-SMA method, and its experimental findings are compared to those of competing algorithms. © 2024, The Author(s), under exclusive license to Springer Nature Singapore Pte Ltd.

关键词： Optimization

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Estimating the Price of the Real Estate Properties with the Help of Online Images 1

Estimating the Price of the Real Estate Properties with the ...

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1st International Conference on Technologies for Smart Green Connected Society 2021, ICTSGS 2021

作者： Ashok, Dasari Lavanya, Chaganti Dept. of Computer Science and Technology Qis College of Engineering and Technology India

ISBN: (纸本)9781607685395

When it comes to property investment pricing, it may be tough for homebuyers to understand and compare. A number of estate evaluation methods have been developed in order to analyse real estate, however they are constrained by the traditional data sources for estate assessment. Potential exists, however, to collect and analyse property-related mobile data when new ways of doing things arise. use estates' geographical dependency to increase the value of a property. "The New York Times" reports that a property's value may be determined by its own characteristics, the value of neighbouring homes in a neighbourhood (individual), and the profitability of its company has to do with (zone). There is a great need for real estate agents these days since they offer easy and fast access to real estate information on the internet, giving clients a broad variety of homes to choose from. As part of our study, we are examining the predictive power of online home forecasts. In the decision-making process of internet users, pictures play a major role in deciding whether or not to visit a website. The development of sophisticated computer vision algorithms has made it possible to analyse visual data. When analysing the findings of a university survey, this research makes use of an RNN. © The Electrochemical Society

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Mobility-Based Optimized Multipath Routing Protocol on Optimal Link State Routing in MANET 1

Mobility-Based Optimized Multipath Routing Protocol on Optim...

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1st IEEE International Conference on Applied Intelligence and Sustainable Computing, ICAISC 2023

作者： Lavanya, K. Indira, R. Velmurugan, A.K. Janani, M. Velammal Engineering College Dept of ECE Chennai India Panimalar Engineering College ECE Department India Koneru Lakshmaiah Education Foundation Department of Computer Science and Engineering Andhra Pradesh Guntur India KPR Institute of Engineering and Technology Computer Science and Engineering Coimbatore India

ISBN: (纸本)9798350323795

Mobile Ad-hoc Networks (MANETs) connect a mobile node for transferring data from a source to a destination. Mobile nodes because no infrastructure network communicates through wireless without an access point. MANET does not have a centralized controller and has a dynamic network topology, which increases link failure and energy consumption resulting in excessive path delay, loss of Quality of service (QoS), and reduced throughput during data communication. Congestion is a significant problem when the QoS of the link carrying the data is degraded. Routing is one of the main problems of MANET due to the very dynamic and distributed nature of MANET. This research proposes a Mobility-Based optimized Multipath Routing Protocol (MBOMRP) and an Efficient, Reliable Link-State Transmission (ERLST) algorithm to overcome these problems. The proposed Mobility-Based optimized Multipath Routing Protocol (MBOMRP) is utilized for route discovery and maintenance to avoid traffic and sleeping nodes efficiently. ERLST algorithm is used for efficient data transmission to improve QoS parameters such as throughput packet delivery rate and minimize end-to-end latency performance. The proposed MBOMRP-ERLST algorithm improves data communication network lifetime, avoids link failures, and provides efficient results compared with previous algorithms. © 2023 IEEE.

关键词： Quality of service

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Identification of Anomaly Scenes in Videos Using Graph Neural Networks

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computers, Materials & Continua 2023年第3期74卷 5417-5430页

作者： Khalid Masood Mahmoud M.Al-Sakhnini Waqas Nawaz Tauqeer Faiz Abdul Salam Mohammad Hamza Kashif Department of Software Engineering Lahore Garrison UniversityLahore54000Pakistan School of Business Skyline University CollegeSharjahUAE Al-Madinah International University–Faculty of Computer and Information Technology Kuala LumpurMalaysia College of Computer and Information Systems Islamic University of MadinahMadinahKingdom of Saudi Arabia School of IT Skyline University CollegeSharjahUAE Faculty of Engineering Computing and Science(FECS)-Swinburne University of TechnologySarawak Department of General Education Skyline University CollegeUniversity City of SharjahUAE Department of Computer Science Lahore Garrison UniversityLahore54000Pakistan

Generally,conventional methods for anomaly detection rely on clustering,proximity,or *** themassive growth in surveillance videos,outliers or anomalies find ingenious ways to obscure themselves in the network and make conventional techniques *** research explores the structure of Graph neural networks(GNNs)that generalize deep learning frameworks to graph-structured *** node in the graph structure is labeled and anomalies,represented by unlabeled nodes,are predicted by performing random walks on the node-based graph *** to their strong learning abilities,GNNs gained popularity in various domains such as natural language processing,social network analytics and *** detection is a challenging task in computer vision but the proposed algorithm using GNNs efficiently performs the identification of *** Graph-based deep learning networks are designed to predict unknown objects and *** our case,they detect unusual objects in the form of malicious *** edges between nodes represent a relationship of nodes among each *** case of anomaly,such as the bike rider in Pedestrians data,the rider node has a negative value for the edge and it is identified as an *** encoding and decoding layers are crucial for determining how statistical measurements affect anomaly identification and for correcting the graph path to the best possible *** show that the proposed framework is a step ahead of the traditional approaches in detecting unusual activities,which shows a huge potential in automatically monitoring surveillance *** autonomous monitoring of CCTV,crime control and damage or destruction by a group of people or crowd can be identified and alarms may be triggered in unusual activities in streets or public *** suggested GNN model improves accuracy by 4%for the Pedestrian 2 dataset and 12%for the Pedestrian 1 dataset compared to a few state-of the-art techniq

关键词： Graph neural network deep learning anomaly detection auto encoders

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A Smart Air Pollutants Monitoring System Using IOT Technologies

A Smart Air Pollutants Monitoring System Using IOT Technolog...

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2023 International Conference on Intelligent Systems for Communication, IoT and Security, ICISCoIS 2023

作者： Pyingkodi, M. Blessing, N R Wilfred Thenmozhi, K. Kanimozhi, K. Pavithira, L. Balakrishnan, P K Sandhya Kongu Engineering College Department of Computer Applications Erode India IT Department Oman Kristu Jayanti College Department of Computer Science Bengaluru India Sri Krishna Adithya College of Arts and Science Department of Information Technology Coimbatore India PSG College of Arts and Science College Department of Computer Science with Data Analytics Coimbatore India CMS College of Science and Commerce Department of Computer Science Coimbatore India

ISBN: (纸本)9798350335835

On international basis, one in all our century's essential problems is air pollutants. Every year, the range of individuals killed via way of means of pollutants climbs, with air pollutants being the main cause. The Internet of Things (IoT) is used worldwide community of 'inventive gadgets' which could sense, and join to, and have interaction with different humans and systems. The solution is furnished via way of means of a sensor-primarily based totally hardware module that can be deployed anywhere. These gadgets, which can be hooked up on mild poles, homes, and different structures, wirelessly speak air pleasant facts to a far flung server. The microprocessor collects facts from IoT sensing gadgets and sends it to a cloud server for processing. These facts can be used to expecting while the vicinity is maximum polluted. The machine additionally gives air pleasant statistics through a cell application, permitting clients to choose alternatives wherein the air pleasant is great. It is likewise a totally less expensive device. © 2023 IEEE.

关键词： Internet of things

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mCNN: An Approach for Plant Disease Detection Using Modified Convolutional Neural Network 1

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International Conference on Intelligent Systems and Human-Machine Collaboration, ICISHMC 2022

作者： Brinthakumari, S. Sivaraja, P.M. Department of Information Technology K.C College of Engineering and Management Studies and Research Maharashtra Thane India Department of Computer Science and Engineering Amrita College of Engineering and Technology Tamilnadu Erachakulam India

ISBN: (数字)9789811984778

ISBN: (纸本)9789811984761

Plant disease is a persistent problem for farmers, and it is one of the most serious risks to income and food security. This initiative aims to cultivate the productivity of agricultural output in the nation by classifying plant leaves into sick and healthy leaf types. The smart farming system is an innovative technology that aids in the improvement of agricultural quality and quantity. Deep learning using Convolutional Neural Networks (CNN) has successfully classified various plant leaf diseases. It represents a contemporary technique that offers cost-effective disease diagnosis. CNN presents a simplified version of a much broader image. In this paper, we proposed a hybrid novel model for detection of plant diseases using mixed Deep Learning (DL) procedures. The UNET based DL framework was used for disease detection and classification. In convolutional neural layer feature extraction was done and the pooling layer optimized those features, and finally a dense layer classifies the test object. Numerous synthetic and real time plan dataset have been used for evaluation. In extensive experimental analysis two ML and two DL classifiers are implemented such as SVM, PCA, CNN and modified CNN (mCNN). The mCNN is the collaboration of VGG16 and VGG16 backbone for classification and YOLOv3 model data pre-processing. The mCNN obtains 96.80% detection and classification accuracy on a heterogenous dataset which is higher than other classifiers as well as conventional classifiers. © 2023, The Author(s), under exclusive license to Springer Nature Singapore Pte Ltd.

关键词： Extraction

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Research on Student's Performance in Virtual Courses in the context of Artificial Intelligence

Research on Student's Performance in Virtual Courses in the ...

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2022 IEEE North Karnataka Subsection Flagship International Conference, NKCon 2022

作者： Seelaboyina, Radha Kalyani, K. Durga Chandrakala Swapna, E. Rani, P. Sobha Geethanjali College of Engineering and Technology Department of Computer Science and Engineering Hyderabad India

ISBN: (纸本)9781665453424

We live in an artificial intelligence era. Virtual reality is an example of artificially intelligent technology. In every field, technology is opening up new possibilities. We will investigate research on student performance in virtual courses in the context of artificial intelligence in this research article A virtual learning environment is one in which the instructor and the learners are divided in time, and space. Course content is delivered using IT applications, digital materials, the Internet, video conferencing, and other technologies. © 2022 IEEE.

关键词： Virtual reality

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A Hybrid Eagle's Web Swarm Optimization (EWSO) technique for effective cloud resource management 12

A Hybrid Eagle's Web Swarm Optimization (EWSO) technique for...

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12th IEEE International Conference on Advanced Computing, ICoAC 2023

作者： Jagadish Kumar, N. Balasubramanian, C. Kumar, A. Naresh Kumar, G.Praveen Sree, S. Jindhiya Sri Sai Ram Engineering College Department of Computer Science and Business Systems West Tambaram Chennai India P.S.R Engineering College Department of Computer Science and Engineering Sivakasi India Velammal Institute of Technology Pancheti Department of Information Technology Chennai India

ISBN: (纸本)9798350318210

encompasses a range of tasks focused on the efficient allocation and administration of resources within a cloud computing environment, all in order to meet the requirements of cloud users. The key components of cloud computing resource management consist of resource allocation, task scheduling, load balancing, and data storage optimization. Cloud resource management poses several challenges, including the optimization of resource allocation, efficient task scheduling, and effective data storage management in distributed file systems like HDFS. These challenges require careful consideration and strategic approaches to ensure optimal utilization of resources, timely execution of tasks, and efficient handling of large-scale data. This paper introduces a novel approach for optimizing cloud resources using Eagle's Web Swarm Optimization (EWSO). The EWSO technique integrates three distinct algorithms, namely the Black Widow optimizer, Golden Eagle optimizer, and Chaotic Leader & Salp optimizer, to address specific aspects of resource optimization in the cloud. By combining these algorithms, the proposed approach aims to enhance the efficiency and the reliability of resource allocation, task scheduling, and HDFS optimization in the cloud environment. To evaluate the effectiveness of the proposed EWSO technique, its efficiency is compared to several other bio-inspired optimization techniques commonly used in cloud resource management. These include WARMS, AARP, ILPEPS and BFDHP. Through this comparison, the performance, and capabilities of the EWSO technique can be assessed in the context of cloud resource management. The findings from experiments prove the effectiveness of the proposed EWSO technique compared to other bio-inspired mechanisms in terms of resource allocation, task scheduling, and HDFS optimization. These findings provide empirical evidence that the EWSO technique outperforms alternative approaches in managing and optimizing cloud resources, highlighting its

关键词： Resource allocation

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A Systematic Review of Thermoelectric Peltier Devices: Applications and Limitations

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Fluid Dynamics & Materials Processing 2023年第1期19卷 187-206页

作者： M.K.Shilpa Md Abdul Raheman Abdul Aabid Muneer Baig R.K.Veeresha Nagesh Kudva Department of Computer Science and Engineering NMAM Institute of TechnologyUdupi574110India Department of Electrical and Electronics Engineering NMAM Institute of TechnologyUdupi574110India Department of Engineering Management College of EngineeringPrince Sultan UniversityRiyadh11586Saudi Arabia Department of Mechanical Engineering NMAM Institute of TechnologyUdupiKarnataka574110India

Conventional refrigeration processes release ammonia and freon into the atmosphere,which results in global *** problems may be overcome by using thermoelectric modules because of the absence of coolants or refrigerants in these ***,the cooling performances of such modules are relatively small in comparison to those of conventional *** this paper,the working principles of thermoelectric modules are discussed together with a review of different relevant aspects,namely:the thermoelectric materials,and their mechanical properties used to build thermoelectric devices,different types of thermoelectric devices available on the market,mathematical modeling of thermoelectric materials,and various applications of thermoelectric materials in different fields.

关键词： TEG peltier module seebeck effect refrigerator CoP TEC

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