The proceedings contain 52 papers. The special focus in this conference is on internationalconference on intelligent Systems and Sustainable computing. The topics include: Farmers Market—Agricultural Marketing and M...
ISBN:
(纸本)9789819947164
The proceedings contain 52 papers. The special focus in this conference is on internationalconference on intelligent Systems and Sustainable computing. The topics include: Farmers Market—Agricultural Marketing and Management System to Connect Farmers to Retailers;driver Drowsiness Detection System Based on Behavioral Method, Biological Method and Vehicular Feature-Based Method—A Review;a Virtual Machine Protection Framework Against Compromised Hypervisor in Cloud computing;SVM Versus KNN: Prediction of Best Image Classifier;Developing a SVM Model of Big dataanalytics for Healthcare Recommendation System;machine Learning Approach Towards the Breast Cancer Detection with Microwave Imaging;Initial Intrusion Detection in Advanced Persistent Threats (APT’s) Using Machine Learning;feature Selection with Binary Differential Evolution for Microarray datasets;survey on Imbalanced dataset Classification—Machine Learning;implementation of ResNet-50 with the Skip Connection Principle in Transfer Learning Models for Lung Disease Prediction;AI-Based smart Farming Technology Using IoT;deep Learning Approach for Auto Counting Complex Plants;a Survey on smart Contract Vulnerabilities Including Auditing Tools;breast Cancer Prediction by Levaraging Machine Learning Algorithm and Using Adaptive Voting Ensemble Method;Vulnerability Classification Based on Fine-Tuned BERT and Deep Neural Network Approaches;tempRank: Tempo-Textual Ranking of English Text Documents;literature Preprocessing, Term Weighting, Similarity Check, and Language Modeling to Improve Relevance Query Performance Accuracy on Medical Abstracts;EEG-Based intelligent System for Identification of Arm Movement;machine Learning-Based Object Detection Using Raspberry Pi;deep Learning Multi-view Paradigm to Forecast Medical Spending on Patients;Performance Analysis of American Sign Language Using Wavelet Transform and CNN;healthcare Monitoring System for Covid People.
In today’s dynamic and rapidly evolving business landscape, the implementation of artificial intelligence (AI) in marketing has become imperative for achieving swift and effective outcomes. AI marketing encompasses t...
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The smart Passenger Center (SPaCe) is a fully integrated platform that aims to overcome the complexity of centralized management of public transport infrastructure and vehicles. The SPaCe artificial intelligence engin...
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ISBN:
(纸本)9781665416474
The smart Passenger Center (SPaCe) is a fully integrated platform that aims to overcome the complexity of centralized management of public transport infrastructure and vehicles. The SPaCe artificial intelligence engine predicts threats and critical events and proposes countermeasures by examining the daily flows of people and correlating different data and events, thanks to machine learning and big dataanalytics. All this massive data comes from a pervasive smart camera network that constantly monitors activities in stations, trains, buses and other places of interest. In this work, we present the idea of this computer vision distributed sub-system, the state of the art of the techniques involved and the advanced functionalities that this intelligent surveillance system offers to the upper layers. Everything is developed following the privacy-by-design paradigm;namely, no real image is recorded or transmitted, but all the elaborations take place on the edge nodes of the system.
Decentralized finance (DeFi) applications in the Ethereum ecosystem have flourished, attracting more and more users. smart contracts as the logical backend involve transactions and money operations that cannot be chan...
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ISBN:
(纸本)9789819756025;9789819756032
Decentralized finance (DeFi) applications in the Ethereum ecosystem have flourished, attracting more and more users. smart contracts as the logical backend involve transactions and money operations that cannot be changed once deployed. Therefore, detecting vulnerabilities in smart contracts before deployment is vital for securing Ethereum users' funds and preventing hacker attacks. However, current vulnerability detection models only support fixed-length inputs, which breaks the integrity of the data. Therefore, based on deep learning, we propose a neural network model that can handle input sequences with variable length for detecting vulnerabilities in smart contracts. More specifically, we take the sequence of transaction opcodes obtained from replayed Ethereum transactions as our dataset. In order to retain the complete information of the sequence, we utilize a rotation layer without learnable parameters and Multilayer Perceptron to handle the input sequences with variable length, and capture the global features. We then introduce the retention mechanism in the neural network, employing multi-scale retention and feed-forward network to capture the key local characteristics. The experiments demonstrate that our model can efficiently detect vulnerabilities in smart contracts, achieving an accuracy of 93.5% and an F1-score of 90.6%.
In this paper, we present a novel intelligent management system (IMS) for smart retail environments that integrates various components to optimize user experience, energy efficiency, and seamless connectivity. The pro...
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Heart diseases include disordered functioning of heart which can be saved through early diagnosis. This diagnosis needs a lot of time to perceive the patient through an accurate approach for treatment. Technical advan...
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Recently, the development of vehicle computer technology has changed the conventional idea of a car from a simple means of transportation to an intelligent, safe smart vehicle. Additionally, cloud computing has been e...
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Traffic monitoring is an essential component of smart city development in India. Indian cities face significant traffic congestion, which not only results in economic losses but also affects the quality of life of cit...
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This study suggests a novel methodology for intelligent energy management in electric vehicles (EVs) through the integration of neural networks and fuzzy logic. Achieving enhanced energy efficiency for electric vehicl...
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The proliferation of consumer data can be attributed to 'the Internet of Things (IoT),' which makes it easier to access and more detailed than before. In this research our purpose is to evaluate the effectiven...
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