RAN slicing technology is a key aspect of the Open RAN paradigm, allowing simultaneous and independent provision of various services such as ultra-reliable low-latency communications (URLLC), enhanced mobile broadband...
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The security of industrial networks, particularly in industrial automation systems, is critical for ensuring system reliability and protecting sensitive data. This paper proposes a deeper anomaly detection system usin...
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This research proposes a distance estimation method using Mono Camera-based object detection and dept. estimation to generate Point Cloud data. The study aims to enhance the applicability of Mono Cameras in autonomous...
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Road safety and accident prevention are critical concerns in modern transportation. This paper presents a comprehensive survey of driver safety systems, focusing on the latest advancements in this field. We analyze th...
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Road safety and accident prevention are critical concerns in modern transportation. This paper presents a comprehensive survey of driver safety systems, focusing on the latest advancements in this field. We analyze the existing literature to identify key research trends in driver safety systems, encompassing various categories of solutions. Our survey delves into the reasons behind road accidents and assesses the effectiveness of emerging technologies and solutions in accident prevention. By categorizing and evaluating these solutions based on the Internet of Things and Machine Learning, we provide valuable insights into the landscape of road accident detection and prevention systems. This survey not only highlights the current state of the art but also serves as a reference for future research and innovation in the domain of driver safety. Abbreviations IoT: Internet of things;CNN: Convolutional Neural Network;SVM: Support vector machine;HRV: Heart rate variability;RRI: R-R Interval;MSPC: Multivariate Statistical process control;EAR: Eye aspect ratio;HUD: Head-up display;GPS: Global positioning system;CAN: Controller area network;GPU: Graphics processing unit;IR: Infrared;GSM: Global system for mobile communication;EEG: Electroencephalogram;PCA: Principal component analysis;SVC: Support vector classifier;SdsAEs: Stacked denoising sparse autoencoders;ECG: Electrocardiogram;LED: Light emitting diode;NFC: Near field communication;PSO: Personal security officer;PPG: Photoplethysmography;EDA: Electrodermal activity;EMG: Electromyography;LCD: Liquid crystal display;RF SoCs: Radiofrequency system on chip;PLR: Piecewise linear representation;BAC: Blood alcohol content;BPNN: Backpropagation Neural Network;ADSD: Automated driver sleepiness detection;EOG: Electroocoulogram;KNN: K nearest neighbor;CBR: Case-based reasoning;RF: Random forest;NIR: Near-infrared;LBP: Local binary pattern;PERCLOS: Percentage of Eye Closure;SVD: Singular value decomposition;FFT: Fast Fourier transf
In this paper, we present a Deep Neural Network(DNN) based framework that employs Radio Frequency(RF) hologram tensors to locate multiple Ultra-High Frequency(UHF) passive Radio-Frequency Identification(RFID) tags. Th...
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In this paper, we present a Deep Neural Network(DNN) based framework that employs Radio Frequency(RF) hologram tensors to locate multiple Ultra-High Frequency(UHF) passive Radio-Frequency Identification(RFID) tags. The RF hologram tensor exhibits a strong relationship between observation and spatial location, helping to improve the robustness to dynamic environments and equipment. Since RFID data is often marred by noise, we implement two types of deep neural network architectures to clean up the RF hologram tensor. Leveraging the spatial relationship between tags, the deep networks effectively mitigate fake peaks in the hologram tensors resulting from multipath propagation and phase wrapping. In contrast to fingerprinting-based localization systems that use deep networks as classifiers, our deep networks in the proposed framework treat the localization task as a regression problem preserving the ambiguity between fingerprints. We also present an intuitive peak finding algorithm to obtain estimated locations using the sanitized hologram tensors. The proposed framework is implemented using commodity RFID devices, and its superior performance is validated through extensive experiments.
With the increasing prevalence of e-commerce plat-forms, understanding customer sentiments expressed in product reviews is crucial for assessing platform and product performance. However, traditional sentiment analysi...
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This study provides an innovative architectural model for e-Health systems that aims to improve cyber resilience while maintaining high availability under fluctuating traffic loads. We examined typical cybersecurity i...
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This paper examines the iron loss characteristics of a permanent magnet-assisted synchronous reluctance machine (PMa-SynRM) and a fluid-shape synchronous reluctance machine (FS-SynRM) for micro EV applications, emphas...
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With the rapid advancement of large language models, particularly ChatGPT, have had a profound impact both in the academic world and in commercial applications. The innovative solutions offered by this technology in a...
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Skin cancer, like all other types of cancer, is a health problem where early diagnosis saves the patient's life. Successful detection of skin lesions in dermoscopic images enables this process to be managed more q...
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