Although micro-mobility has become a popular and indispensable mode of transportation in recent years, it has also introduced a large number of traffic accidents. Timely tracking and predicting the maneuvers hold the ...
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ISBN:
(纸本)9798350386066;9798350386059
Although micro-mobility has become a popular and indispensable mode of transportation in recent years, it has also introduced a large number of traffic accidents. Timely tracking and predicting the maneuvers hold the potential to prevent accidents through prompt warnings and interventions. However, the open and simple structure of micro-mobility makes it hard to install sophisticated infrastructures for maneuver prediction. In this paper, we argue that the micro-mobility body dynamics provide sufficient information for maneuver prediction. Our preliminary study suggests that micro-mobility body dynamic patterns appear beforehand and exhibit the correlation with steering maneuvers. We accordingly present RideGuard, which leverages a built-in Inertial Measurement Unit on smartphones to achieve the prediction of steering maneuvers. Through a dual-stream CNN deep learning architecture, RideGuard effectively captures complex patterns and feature relationships from the time and frequency domain. Our extensive real-traffic experiments involving 20 participants demonstrate the superiority of RideGuard: employing a 3s detection window, RideGuard attains a minimum of 94% precision in maneuver prediction with a 5s prediction time gap. The low-cost and rapid response feature of RideGuard enables feasible deployment and promotes safer riding practices. Additionally, we open-source our well-labeled dataset to facilitate further research.
The significance of cybersecurity resides in its ability to safeguard individuals and enterprises against cyberattacks, as well as the unauthorized acquisition or misplacement of confidential and classified data. Cybe...
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ISBN:
(纸本)9789819780501;9789819780518
The significance of cybersecurity resides in its ability to safeguard individuals and enterprises against cyberattacks, as well as the unauthorized acquisition or misplacement of confidential and classified data. Cybersecurity includes the ability to employ monitoring systems to safeguard personal data, financial information, trade secrets, intellectual property, and any sensitive government information. By establishing robust cybersecurity protocols, we can enhance our ability to safeguard against a wide range of online threats. In the present age, nearly every industry is utilizing the services of diverse machine learning and deep learning models to forecast, analyze, or produce outcomes with greater optimization and efficiency. Thus, we have employed the capacity of machine learning in the task of identifying and classifying malicious software. In this paper, we propose a machine learning-envisioned malware attack detection mechanism for edge computing-based networks. The practical implementation of the proposed technique is also provided, along with the performance comparison of several existing methods for the assigned intrusion detection task. The proposed scheme achieved the highest accuracy value as compared to the other existing methods.
Quantum computing (QC) is a research field that has been in the limelight in recent years. In fact, many researchers and practitioners believe that it can provide benefits in terms of efficiency and effectiveness when...
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ISBN:
(纸本)9783031560682;9783031560699
Quantum computing (QC) is a research field that has been in the limelight in recent years. In fact, many researchers and practitioners believe that it can provide benefits in terms of efficiency and effectiveness when employed to solve certain computationally intensive tasks. In information Retrieval (IR) and Recommender Systems (RS) we are required to process very large and heterogeneous datasets by means of complex operations, it is natural therefore to wonder whether QC could also be applied to boost their performance. The goal of this tutorial is to show how QC works to an audience that is not familiar with the technology, as well as how to apply the QC paradigm of Quantum Annealing (QA) to solve practical problems that are currently faced by IR and RS systems. During the tutorial, participants will be provided with the fundamentals required to understand QC and to apply it in practice by using a real D-Wave quantum annealer through APIs.
As the field of artificial intelligence experiences the emergence of various large-scale models, the computing power requirements are increasing. Simultaneously, Moore’s Law is approaching its limits, which intensifi...
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In the field of power dispatching, there is a substantial amount of textual information, including instructions and operation tickets. Recording and preserving this information is often done manually, resulting in low...
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Terahertz imaging technology has a broad application prospect in the field of security inspection due to its strong penetrability and negligible radiation effect on people. With the development of machine learning in ...
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In the era of pervasive computing, fog computing has emerged as a paradigm that extends cloud services to the edge of the network, enabling real-time data processing and reducing latency for time-sensitive application...
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In order to meet the pressing demand for early diagnosis in healthcare, we proposed a unique hybrid architecture in this study that is intended for the categorization of gastrointestinal (GI) illnesses. With fewer tra...
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Automatic road extraction from high-resolution images has gained research interest due to a wide range of applications like autonomous driving, map updates, and traffic management. Roads have different shapes and patt...
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Natural language processing (NLP) implemented in digital scientific records (EMRs) can substantially enhance the nice and efficiency of affected person care. The purpose of NLP implemented in EMRs is to extract applic...
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