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检索条件"任意字段=7th International Conference on Computing in Engineering and Technology, ICCET 2022"

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Computer Controlled Letter Writing Robotic Arm Using Speech Recognition 7

Computer Controlled Letter Writing Robotic Arm Using Speech ...

引用

2023 7th international conference On computing, Communication, Control And Automation, ICCUBEA 2023

作者： Patil, Aditya Khatavkar, Rujul Kardile, Sourabh Kakade, Pratap Pawar, Rajendra School of Computer Engineering and Technology Mit World Peace University Pune India

ISBN: (纸本)9798350304268

In this research paper, we propose a robotic arm for writing using speech recognition, which uses a stepper motor and a NodeMCU. the robotic arm is capable of being controlled through voice commands, allowing it to write texts and draw images on paper. the stepper motor controls the arm's movements, while the NodeMCU acts as the microcontroller, responsible for interpreting voice commands and controlling the motor. the voice is recorded using an Android application, and then it is converted to text using a speech recognition Natural Language Processing Model. through a Firebase database, this translated text is forwarded to Nodemcu. We have tested the accuracy and precision of the system, and the results are promising. © 2023 IEEE.

关键词： accuracy NodeMCU board precision Robotic arm speech recognition stepper motor

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Comparative Analysis of Different Machine Learning Algorithms on Different Datasets 7

Comparative Analysis of Different Machine Learning Algorithm...

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7th international conference on Intelligent computing and Control Systems, ICICCS 2023

作者： Raju, G. S Bapi Manasa, Chintala Bhavani, Nandikatti Durga Amulya, Jadi Shirisha, Dangatla Gokaraju Rangaraju Institute of Engineering and Technology Computer Science and Engineering Department Hyderabad India

ISBN: (纸本)9798350397253

Machine Learning is used to train models and machines without the help of any human interventions and guides. Here the models and machines are trained using algorithms. As it is difficult to train the algorithms one by one and get the analysis of the best algorithm. this research study intends to compare different algorithms used in different datasets to know the best algorithm according to different domains and the overall best algorithm. In this study, most popular supervised algorithms like SVM, Decision Tree, Random Forest, KNN, Logistic Regression, XGBoost, Adaboost, Voting Classifier (Decision Tree + Random Forest), Bagging Classifier (KNN + SVM) and Naïve Bayes. this research study has chosen three different domains for datasets. Different datasets were used to check the efficiency of algorithms. Comparative analysis of the classifiers shows that all algorithms outperform the existing methods with a high accuracy. © 2023 IEEE.

关键词： Adaptive boosting

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Sign Language Recognition using LSTM and Media Pipe 7

Sign Language Recognition using LSTM and Media Pipe

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7th international conference on Intelligent computing and Control Systems, ICICCS 2023

作者： Rao, G. Mallikarjuna Sowmya, Cheguri Mamatha, Dharavath Sujasri, P.A. Anitha, Soma Alivela, Ramavath Gokaraju Rangaraju Institute of Engineering and Technology Department of Computer Science and Engineering Hyderabad India

ISBN: (纸本)9798350397253

there are learning aids available for those who are deaf or have trouble speaking or hearing, but they are rarely used. Live sign motions would be handled via image processing in the suggested system, which would operate in real-time. Classifiers would then be employed to distinguish between distinct signs, and the translated output would show text. On the set of data, machine learning algorithms will be trained. With the use of effective algorithms, top-notch data sets, and improved sensors, the system aims to enhance the performance of the current system in this area in terms of response time and accuracy. Due to the fact that they solely employ image processing, the current systems can identify movements with considerable latency. In this project, our research aims to create a cognitive system that is sensitive and reliable so that persons with hearing and speech impairments may utilize it in day-to-day applications © 2023 IEEE.

关键词： Audition

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Privacy and Security of Healthcare Data in Cloud based on the Blockchain technology 7

Privacy and Security of Healthcare Data in Cloud based on th...

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7th international conference on computing Methodologies and Communication, ICCMC 2023

作者： Agarwal, Abhinav Joshi, Ravi Arora, Himanshu Kaushik, Rajkumar Department of CSE Amity University Rajasthan Jaipur India Department of ECE Jaipur Institute of Technology Rajasthan Jaipur India Department of CSE Arya Institute of Engineering & Technology Rajasthan Jaipur India Department of Electrical Engineering Arya Institute of Engineering & Technology Rajasthan Jaipur India

ISBN: (纸本)9781665464086

Blockchain is basically a conveyed database that contains records and public record for all exchanges or computerized occasions that have been performed and shared among members. Every transaction in the public record is checked by agreement of most individuals in the system. When the data is placed, the data won't ever vanish. Block chain contains a conclusive and undeniable record of each and every transaction ever. the primary rationale of this of this proposed work is safely store and keeps up with the patient records in cloud database. Healthcare is a data serious space where a lot of data is created, dispersed, put away, and got to day to day. the Blockchain innovation is utilized to safeguard the healthcare data facilitated inside the cloud. the blockchain that contains the clinical data and Distributed computing will associate different healthcare suppliers. It permits healthcare supplier to get to the patient subtleties all the more safely from anyplace. It secures the data from attackers. the data is encrypted before moving to the cloud. the healthcare supplier needs to decrypt the data before downloading the information. the information is finally obtained by involving cryptography in the encryption stage and can be simply acquired by the client and server. In this proposed study, a healthcare record-based protection and security of healthcare-related information in the cloud has been performed on java platform. © 2023 IEEE.

关键词： Blockchain

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Blockchain-Based Solutions for Enhancing Data Integrity and Security 7

Blockchain-Based Solutions for Enhancing Data Integrity and ...

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7th international conference on Contemporary computing and Informatics, IC3I 2024

作者： Mohan, Chinnem Rama Saxena, Rashi thilagham, K.T. Solleti, Phani Kumar Sivasubramanian, S. Dharamvir Narayana Engineering College Department of Computer Science and Engineering Andhra Pradesh Nellore524004 India Gokaraju Rangaraju Institute of Engineering and technology Department of Data Science Hyderabad India Government College of Engineering Tamil Nadi Salem11 India 522302 India New Prince Shri Bhavani College Autonomous to Anna University Artificial Intelligence and Data Science Tamil Nadu Chennai India The Oxford College of Engineering Department of Mca Bommanhalli Bengaluru560068 India

ISBN: (纸本)9798350350067

the study emphasizes evaluating the effectiveness of blockchain-based solutions in improving data security and data integrity. By analysing the fundamental aspects of blockchain technologies, the significant roles of blockchain have been discussed in ensuring data transparency, auditability, and immutability. the study also investigates the potential business solutions across various industries along with its contribution in safeguarding sensitive information. the potential limitations and challenges of implementing blockchain-enabled solutions are effectively addressed while providing significant mitigation strategies. the analysis highlights the potential of blockehain in transforming the data landscape by enhancing data integrity and security. © 2024 IEEE.

关键词： Data integrity

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Federated Learning for Long-term Forecasting of Electricity Consumption towards a Carbon-neutral Future 7

Federated Learning for Long-term Forecasting of Electricity ...

引用

7th international conference on Intelligent computing and Signal Processing, ICSP 2022

作者： Shen, Zhiheng Wu, Qiaofeng Qian, Jiajia Gu, Chenlin Sun, Feifei Tan, Jia Economic and Technology Research Institute State Grid Zhejiang Electric Power Co. Ltd Hangzhou China Zhejiang University College of Electrical Engineering Hangzhou China

ISBN: (纸本)9781665478571

In this paper, we propose an approach for long-term forecasting of electricity consumption based on federated learning. Basically, federated training was conducted on electricity consumption forecast models of several regions simultaneously, which can not only enrich training samples but also improve the generalization ability of the forecast model. More specifically, long short-term memory neural network (LSTM) is adopted as the local model for federated learning, in which carbon emission is one of the input features, so that the electricity consumption forecast results are more consistent with the carbon-neutral development path. In this study, we forecast electricity consumption of a certain area in China from 2022 to 2035, and experiment results verify the effectiveness of the proposed method compared with traditional time series method. © 2022 IEEE.

关键词： Long short-term memory

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Enhancing Efficiency and Empowering Institutions: Leveraging Wireless Sensor Devices, IoT Edge computing, and Fog computing in Educational Systems 7

Enhancing Efficiency and Empowering Institutions: Leveraging...

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7th IEEE international conference on Computational Systems and Information technology for Sustainable Solutions, CSITSS 2023

作者： Siddiqui, Shams Tabrez Ali Sohail, Md Mohammed Aftab, Aasif Sarfaraz, Mohd Alam, Mohammad Imran Salim, Abu College of Cs It Jazan University Department of Computer Science Jazan Saudi Arabia College of Cs It Jazan University Department of Computer & Network Engineering Jazan Saudi Arabia College of Cs It Jazan University Department of Information Technology and Security Jazan Saudi Arabia

ISBN: (纸本)9798350343144

Wireless sensor devices, edge computing, and fog computing can transform education by improving efficiency and empowering institutions. this research paper explores the application of these technologies in educational settings and investigates their benefits, challenges, and potential solutions. Educational institutions can track classroom occupancy, ambient conditions, and student participation using wireless sensor systems. loT edge computing allows data processing and analysis at the network edge for rapid insights and decision-making. Fog computing integrates cloud resources with edge computing to support complicated computations and data storage. Wireless sensor devices, loT edge computing, and fog computing are used to optimize educational processes like resource management, student tracking, personalized learning, and campus security. Data privacy, security, scalability, and interoperability issues are studied and solutions suggested. this research shows how wireless sensor devices, loT edge computing, and fog computing may alter educational systems, helping institutions improve efficiency and empower stakeholders. © 2023 IEEE.

关键词： Fog computing

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Video Reversible Data Hiding Based on Motion Vector 7

Video Reversible Data Hiding Based on Motion Vector

引用

7th international conference on Intelligent computing and Signal Processing, ICSP 2022

作者： Ning, Zhiqiang Niu, Ke Lin, Yangping Pan, Feng Engineering University of Pap College of Cryptography Engineering Xi'an China

ISBN: (纸本)9781665478571

Aiming at the problem that the existing motion vector data hiding algorithms based on two-dimensional histogram modification do not fully utilize the embedding space, a large-capacity video reversible data hiding algorithm is proposed. Firstly, the prediction error is calculated by using the prediction algorithm based on the spatial location of the motion vector, and the prediction error pair is obtained. then, the secret information is embedded by the designed embedding strategy combining two-dimensional and one-dimensional histograms. Finally, the idea of two-layer embedding is combined to further increase the embedding capacity. Compared with the latest data hiding algorithms of the same type, the embedding capacity of this algorithm is increased by an average of 2.23 times. © 2022 IEEE.

关键词： Steganography

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the Latest Progress of Research on the Urban Functional Areas Based on CiteSpace Methods 23

The Latest Progress of Research on the Urban Functional Area...

引用

23rd IEEE international conference on High Performance computing and Communications, 7th IEEE international conference on Data Science and Systems, 19th IEEE international conference on Smart City and 7th IEEE international conference on Dependability in Sensor, Cloud and Big Data Systems and Applications, HPCC-DSS-SmartCity-DependSys 2021

作者： Hu, Yanru Jing, Changfeng School of Geomatics and Urban Spatial Informatics Beijing University of Civil Engineering and Architecture Beijing China

ISBN: (纸本)9781665494571

With the rapid development of Information Communication technology (ICT), research on urban functional areas has been one of the hot research issue in urban study domain. CiteSpace as the bibliometric tools was widely used to detect the studies tendency toward several dimensions like country/institution, authors, cited references and keywords. therefore, the aim at this work is set to understand the research progress of urban functional areas in recent 30 years. this article explored the research hot-spots and development trended, and visualized the literature measurements of domestic and foreign literature. Finally, we tried to propose the challenge and research direction for future work based on the literature quantity and quality analysis. © 2021 IEEE.

关键词： Visualization Statistical analysis Smart cities Bibliometrics Collaboration Market research Software

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Parasitisation Prediction in Malarial Cell Images using Transfer Learning- driven Vision Transformers 8

Parasitisation Prediction in Malarial Cell Images using Tran...

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8th international conference on computing in engineering and technology, iccet 2023

作者： Sinha, Sanya Sinha, Sanjeev Department of Electronics and Communications Engineering Birla Institute of Technology Patna India Department of Civil Engineering National Institute of Technology Patna Patna India

ISBN: (纸本)9781839539237

the World Malaria Report 2022 stated that nearly 247 million cases of malaria and 619,000 deaths were reported annually as of 2021. this emphasizes on the tremendous impact the disease has, especially in third-world countries. through efficient and timely diagnosis, the disease could be accurately identified and suitable lines-of-treatment could be initiated. the requirement for systematic diagnosis benchmarked the arrival of the computer-aided diagnosis landscape through imaging and Machine Learning (ML) techniques. Deep learning-based backbones are particularly efficient for image classification and disease detection. through this paper, we propose a Deep Neural Network (DNN) backbone VGG16 for extracting the local and global features of blood smear cell images marked with the Giemsa stain, followed by a Vision Transformer (ViT) neural network architecture for classifying the coloured malarial cell images into the parasitized and uninfected classes of images based on the extracted features. this novel approach returned 97.72% classification accuracy with leading sensitivity, specificity, precision, recall, and area under curve metrics. © the Institution of engineering & technology 2023.

关键词： Diseases

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