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A Design of IoT based Integrated Ambient Air Pollutants Measuring System for Non-Attainment Locations 3

A Design of IoT based Integrated Ambient Air Pollutants Meas...

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3rd International Conference on Innovative Mechanisms for Industry Applications, ICIMIA 2023

作者： Rahman, A. Abdul Manivannan, P. Koneru Lakshmaiah Education Foundation Department of Computer Science and Engineering AP Vaddeswaram India SASTRA Deemed to Be University School of Computing Tamilnadu Thanjavur India

ISBN: (纸本)9798350343632

Global warming is one of prominent issues in developing nations like India. As stated by World Health Organization (WHO), there are seven million people losing their life around the world due to air pollution. The report also states that nine out of ten people breathe air that exceeds Air Quality Index (AQI) level prescribed by WHO. The Sulfur dioxide (SO2), Carbon monoxide (CO), Nitrogen dioxide (NO2), Particulate Matter (PM) 2.5, PM10, Ozone (O3), and Ammonia (NH3) are more challenging pollutants, which harms the ambient air quality due to many social activities. However, the State Pollution Control Board (SPCB) and Central Pollution Control Board (CPCB) are extremely active in controlling and reducing air pollution through various national and state pollution programs. But one of the primary challenging tasks is to measure pollutants in non-attainment areas are which are away from state/central pollution control board stations. So it is difficult to measure air quality, particularly, the people living in forest and hills areas are becoming victims of the problem. The aim of the proposed work is to measure the ambient air quality in non-attainment areas using various sensors. It is an IoT based Integrated Ambient Air Pollutants Device (IAAPD), which is to measure the above said 7 different pollutants in air, The result of system can help to local administration/ authorities to plan for remedial and precaution measures to avoid, control and manages the air pollution in non-attainment locations. © 2023 IEEE.

关键词： Air pollutants Air Quality Index Ambient measure Internet of Things Non-attainment

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A Survey Analysis on Decentralized Land Registry System Using Blockchain and Smart Contracts 1

A Survey Analysis on Decentralized Land Registry System Usin...

引用

1st International Conference on computer science and Emerging Technologies, CSET 2023

作者： Narayanaprakash, K. Malarchelvi, P. D. Sheba Kezia Ranjithkumar, S. Sridevi, R. Anitha, P. Kumar, N.Suresh Alliance University Anekal Department of Computer Science and Engineering Bengaluru562 106 India Saranathan College of Engineering Department of Computer Science and Engineering Tiruchirappalli India School of Computer Science and Engineering Vellore Institute of Technology Vellore India Department of Computer Science and Engineering Trichy India Oasys Institute of Technology Department of Computer Science and Engineering Pulivalam Trichy India Bangalore India

ISBN: (纸本)9798350341737

This study investigates the potential use of blockchain technology and smart contracts to construct a decentralised land registry system. It looks at the problems with traditional land registry systems and provides a technical breakdown of how to create a blockchain-based land registry system. The research also evaluates the countries that have already adopted such systems and discusses the possible adoption of a blockchain-based land register system in India. The implementation of a blockchain-based land registration system, per the research, can increase the security and efficacy of land transactions, reduce fraud and mistakes, and promote economic growth. © 2023 IEEE.

关键词： Smart contract

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An Authentication-Based Image Scrambling Algorithm Using Hybrid Chaotic Maps and SHA

An Authentication-Based Image Scrambling Algorithm Using Hyb...

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2023 International Conference on Sustainable Communication Networks and Application, ICSCNA 2023

作者： Ramneshkar, B. Krishnan, R. Bala Kumar, N.Rajesh Karthikeyan, B. Manikandan, G. School of Computing Sastra Deemed University Thanjavur India Srinivasa Ramanujan Centre Sastra Deemed University Department of Computer Science and Engineering Kumbakonam India

ISBN: (纸本)9798350313987

Digital mode of communication is widely used for exchanging various kinds of data through internet. The data that is being transmitted may be used in sensitive applications. Thus, those data have to be secured from various kinds of attacks and must ensure basic security services as well. One such kind of data is Image data which is used in medical imaging and some other sensitive fields as well. There are many algorithms to protect and secure the images during transmission but the algorithm and their security has to be modified constantly to cope up with the technological advancements. So, in this enhanced work, an authentication-based image scrambling algorithm using hybrid chaotic maps and SHA is proposed. RSA provides the initial-values for the chaotic-map. Improved LS will be used to generate random values for XOR operation. SBOX will be generated by using both Improved LS and Henon map. Authentication message will be embedded into the image and it will be XORed and scrambled thrice (SBOX, Arnold and Sub-Image based). Receiver will decrypt and verify the message. This algorithm is expected to be faster, provide good security and resist several attacks. © 2023 IEEE.

关键词： Arnold Transform Authentication Henan Map Image Encryption RSA SHA

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EmoSync: Facial Emotion Detection for Adaptive Music Playback 3

EmoSync: Facial Emotion Detection for Adaptive Music Playbac...

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3rd International Conference on Artificial Intelligence For Internet of Things, AIIoT 2024

作者： Devarajan, Devikanniga Rajkumar, K. GITAM Deemed to be University Computer Science and Engineering Nagadenahalli Doddabalpur Karnataka Bangalore561203 India SRM Institute of Science and Technology Department of Data Science and Business Systems School of Computing Tamil Nadu Kattankulathur603 203 India

ISBN: (纸本)9798350372120

This work investigates using Convolutional Neural Networks (CNN) and VGGNet architecture, for realtime emotion detection. Raw data from the FER-2013 dataset is transformed from CSV format into organized image directories, segmented by distinct emotions. The resulting model, equipped with convolutional, pooling, and dense layers, effectively classifies emotions from 48x48 grayscale images. In application, the model overlays detected emotions onto a webcam stream. An integrated music player module synchronizes music with the subject's emotions. Overall, this research explores a comprehensive interactive system focused on recognizing and responding to human emotions. Without further training data, our model, to the best of our understanding, achieves modern single-network accuracy of 74.57% on FER2013 © 2024 IEEE.

关键词： Python

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Assessment of a Novel Single-Channel EEG Method for Automated Recognition of Sleep Phases 15

Assessment of a Novel Single-Channel EEG Method for Automate...

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15th International Conference on computing Communication and Networking Technologies, ICCCNT 2024

作者： Mahapatra, Rajesh Kumar Upadhyay, Harsh Kondaveeti, Hari Kishan Satapathy, Santosh Kumar Rajput, Nitin Singh Tripathy, Santosh Kumar Pandit Deendayal Energy University Information and Communication Technology Gujarat Gandhinagar India VIT-AP University School of Computer Science Engineering Andhra Pradesh India Vit Bhopal University School of Computing Science and Engineering Sehore India

ISBN: (纸本)9798350370249

Assessing sleep stages is crucial for identifying and managing sleep disorders such as REM sleep disorders and narcolepsy. Automating this process not only expedites detection but also enhances diagnostic accuracy. Thus, this research used the discrete wavelet transform technique and a convolutional neural network to automate sleep stage identification. In this proposed method, the single-channel EEG undergoes decomposition into four levels via discrete wavelet transform, followed by extraction of statistical features from these levels. Subsequently, employing CNN, relevant features are selected and utilized as input to the model. The CNN model achieved high accuracies of 95.81% five-class (five sleep stages). This proposed approach for automated sleep stage detection has the potential to expedite the identification of sleep stages and even sleep disorders, and it can accommodate large-scale EEG datasets. However, it's important to note that this approach was solely evaluated on one dataset, underscoring the need for validation across other databases in future investigations. © 2024 IEEE.

关键词： component formatting insert (key words) style styling

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Prediction of Rental Demands using different Machine Learning Algorithms

Prediction of Rental Demands using different Machine Learnin...

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2023 International Conference on computer Communication and Informatics, ICCCI 2023

作者： Ravikumar, S. Vijay, K. Pavithra, S. Prithi, S. Kannan, Sriram Vel Tech Rangarajan Dr.Sagunthala R&D Institute of Science and Technology Department of Computer Science and Engineeirng Chennai India Rajalakshmi Engineering College Department of Computer Science and Engineering Chennai India VIT University School of Computer Science and Engineering Chennai India SRM IST School of Computing Department of Computational Intelligence Kattankulathur India Sri Sivasubramaniya Nadar College of Engineering Tamil Nadu Chennai India

ISBN: (纸本)9798350348217

A Bike rental expectation conjectures the interest for bikes rentals in reliance of climate conditions like the temperature and calendric data. In bike rental frameworks, it is vital that the managers have to realize the number of bikes to be placed in each and every station. This include empowers them in or-ganizing the necessary number of bikes at each station and choose whether a specific station needs to have additional number of bikes or it is not re-quired. In this venture we will foresee the no of bikes required for explicit climate and climatic conditions. © 2023 IEEE.

关键词： Machine learning

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Impact of Antenna Beam Patterns on the Performance of Satellite Communication Links

Impact of Antenna Beam Patterns on the Performance of Satell...

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2024 International Conference on Optimization computing and Wireless Communication, ICOCWC 2024

作者： Ganesh, D. Upadhyay, Ramakant Saxena, Ashendra Kumar Department of Computer Science and Information Technology Bangalore India Sanskriti University Department of Computer Science Engineering Uttar Pradesh Mathura India Teetthanker Mahaveer University Department of Computing Sciences and Information Technology Uttar Pradesh Moradabad India

ISBN: (纸本)9798350383348

the overall performance of satellite communication links is extraordinarily established upon the spatial distribution of transmitted radiation. This distribution is managed by means of the antenna beam sample, which is a measure of the relative power emitted in one-of-a-kind directions from the antenna. The shape of the beam drastically impacts the efficiency of the hyperlink in addition to its robustness against fading. Numerous beam sample configurations are typically employed in satellite verbal exchange packages;every with it's set of advantages and disadvantages. By characterizing the variations among beam patterns, it is miles feasible to determine the most suitable design for a given utility. The most commonly used beam sample in satellite TV for PC communications is the pencil beam. This has a highly slim fundamental lobe width and presents exact gain traits inside the desired guidelines on the fee of extended aspect lobe power. This may cause better interference levels and fading outcomes, in particular in tremendously Asymmetric Circularly Polarized (HACP) structures. Then again, wider beam styles, which include fan or zone beams, provide decreased aspect lobe electricity on the fee of reduced gain. Broadening the sample will additionally increase the complexity of the link finances and antenna directivity calculations. Currently, extra complex antenna beam styles, including stepped-tapered, nested, and adaptive, have been hired so one can optimize the satellite TV for PC link overall performance. © 2024 IEEE.

关键词： Communication Extraordinarily Numerous Performance Satellite Stablished

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Plant Protein Classification Using K-mer Encoding 1st

Plant Protein Classification Using K-mer Encoding

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1st International Conference on Computational Intelligence and Network Systems, CINS 2023

作者： Veningston, K. Venkateswara Rao, P.V. Pravallika Devi, M. Pranitha Reddy, S. Ronalda, M. Department of Computer Science and Engineering National Institute of Technology Srinagar 190006 Jammu and Kashmir Srinagar India Department of Computer Science and Engineering GITAM School of Technology Andhra Pradesh Visakhapatnam530045 India

ISBN: (纸本)9783031489839

Proteins play an important role in the human body and in plants. A lack of expertise in protein labeling in plants can make it extremely difficult to characterize and comprehend the precise roles and activities of different proteins. Furthermore, it restricts development in fields like biotechnology, disease resistance, and crop enhancement. The presented project focuses on plant protein classification, aiming to overcome the challenges arising from limited protein labeling knowledge. Advanced machine learning techniques, including various classification algorithms such as Logistic Regression, Decision Tree, K-nearest neighbors (KNN), Support Vector Machines (SVM), Random Forest (RF), Multinomial Naive Bayes (NB), AdaBoost, and XGBoost, are employed to accurately classify protein sequences into their respective families. This classification approach provides valuable insights into the functions and roles of proteins within plants, ultimately advancing our understanding of plant biology. This attempt offers new possibilities for advancement in critical sectors such as agriculture, drug discovery, and genomic research by eliminating the limitations associated with limited protein labeling knowledge. © The Author(s), under exclusive license to Springer Nature Switzerland AG 2024.

关键词： Proteins

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Evaluation Method of Object Control Capability for Children Based on Nonlinear Dynamics 23

Evaluation Method of Object Control Capability for Children ...

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3rd International Conference on Bioinformatics and Intelligent computing, BIC 2023

作者： Wang, Huaijun Li, Chao Zhang, Dongsheng Li, Junhuai Key Laboratory of Network Computing and Security Technology School of Computer Science and Engineering Xi an University of Technology Xi'an China

ISBN: (纸本)9798400700200

DCD (Developmental Coordination Disorder) has become a global problem, and several studies have shown that early detection and intervention are important for the prevention and treatment of DCD in children. To address the problems of low intelligence, simple assessment indexes and single dimension in assessing children's motor coordination, a method based on non-linear dynamics is proposed to assess children's object control ability. Using the child's in-situ ball tapping as the test item, the Kinect and inertial sensors are used to collect hand spatial position information and human motion biomechanical signals during the ball tapping process. The complexity of the signal is reflected by the sample entropy of the motion signal. The approach suggested in this thesis, which uses non-linear kinetic characteristics, enhances the accuracy of behavioral and developmental identification by 1% to 3% when compared to existing methods. The experiments prove that the proposed method has a better recognition rate and stability than the traditional assessment methods. © 2023 ACM.

关键词： Principal component analysis

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Comparative Analysis of Machine Learning Algorithms in Thyroid Disease Prediction 23th

Comparative Analysis of Machine Learning Algorithms in Thyro...

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23rd International Conference on Intelligent Systems Design and Applications, ISDA 2023

作者： Preethiya, T. Tyagi, Amit Kumar Pandiarajan, T. Department of Networking and Communications School of Computing College of Engineering and Technology SRM Institute of Science and Technology Kattankulathur Kanchipuram 603203 India Department of Fashion Technology National Institute of Fashion Technology New Delhi India Department of Computer Science Engineering Rajalakshmi Institute of Technology Chennai India

ISBN: (纸本)9783031648120

Thyroid disease is estimated to be the most common illness in the twenty-first century. The thyroid hormones are produced by a butterfly-shaped gland in the throat. The crucial function these hormones play in bodily metabolism, mental health, and general well-being. In this study, we present a method for accurately analysing thyroid function in an unbalanced dataset using Machine Learning (ML) algorithms. This dataset's accuracy score is ambiguous because most target variable classes are 1. Performance measurements are accuracy and recall, but when class distribution is asymmetrical, the F1-score balances the other parameters. The performance is evaluated using the F1-score, which is one of the best output metrics for unbalanced classification tasks. Simulation results shows that the Decision Tree (DT) algorithm outperforms the other algorithms with an F1-score of 0.9957, the Area Under Curve (AUC) score of 0.9917 and the kappa coefficient of 0.978 in the disease prediction. © The Author(s), under exclusive license to Springer Nature Switzerland AG 2024.

关键词： Support vector machines

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