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This dataset plays a pivotal role in facilitating efficient resource management strategies, catering to the complex needs of modern Fog/Cloud environments. It comprises comprehensive information regarding machine configurations, task requirements, and bandwidth allotments. These details are indispensable for optimizing resource utilization, ensuring tasks are assigned to suitable machines based on their capabilities, and managing bandwidth allocation to prevent bottlenecks and maximize network efficiency.
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478 Views
An IEEE 802.15.4 backscatter communication dataset for Radio Frequency (RF) fingerprinting purposes.
It includes I/Q samples of transmitted frames from six carrier emitters, including two USRP B210 devices (labeled as c#) and four CC2538 chips (labeled as cc#), alongside ten backscatter tags (identified as tag#). The carrier emitters generate an unmodulated carrier signal, while the backscatter tags employ QPSK modulation within the 2.4 GHz frequency band, adhering to the IEEE 802.15.4 protocol standards.
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464 Views
We investigated the long term functionality of the designed PMCS in a practical use case where we monitored plant growth of classical horticulture Dianthus flowers (Dianthus carthusianorum) under the effect of plastic mulching over a period of 4 months. This use case represents a common phenological monitoring case that can be used in agricultural studies. For this, we integrated our PMCS in an embedded vision camera equipped with the openMV H7 Plus board in a waterproof housing [26]. The system shown in Fig.
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78 Views
Inertial sensors are widely used in a variety of applications. A common task is orientation estimation. To tackle such a task, attitude and heading reference system algorithms are applied. Relying on the gyroscope readings, the accelerometer measurements are used to update the attitude angles, and magnetometer measurements are utilized to update the heading angle. In indoor environments, magnetometers suffer from interference that degrades their performance.
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61 Views
Plasma-based semiconductor processing is highly sensitive, thus even minor changes in the procedure can have serious consequences. The monitoring and classification of these equipment anomalies can be performed using fault detection and classification (FDC). However, class imbalance in semiconductor process data poses a significant obstacle to the introduction of FDC into semiconductor equipment. Overfitting can occur in machine learning due to the diversity and imbalance of datasets for normal and abnormal.
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186 Views
This paper focuses on advancements in predictive maintenance driven by artificial intelligence (AI), machine learning (ML), and the Internet of Things (IoT). It explores applications in the predictive maintenance in industries, aiming to provide a comprehensive understanding of current methodologies and future prospects. The discussion focuses on predictive maintenance methodologies, highlighting strengths, limitations, challenges, and opportunities.
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239 Views
Wi-Fi FTM RSSI Localization dataset
Wi-Fi Fine Time Measurement for positioning / Indoor Localization in 3 different locations and using 8 different APs
Custom APs using ESP32C3 and Raw FTM is measured in nanoseconds
Data is only measured at the Router Side
Data is not measured at client side
Has 4 datasets inside the zip folder with over 100,000 data points
Contains processed Wi-Fi FTM packets from various routers in:
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1546 Views
Wi-Fi BLE RSSI SQI Localization dataset
Wi-Fi BLE RSSI for positioning / Indoor Localization in 4 different locations and using 18 different APs
Data is only measured at the Router Side
Data is not measured at client side
Has 12 datasets inside the zip folder with over 1,000,000 data points
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1017 Views
In today's world of online communication and digital media, hate speech has become an alarming problem worldwide. With the advancement of the internet, while people enjoy numerous benefits, there's also a dark side where individuals are subjected to horrendous bullying through hate speech. Tragically, some instances even lead to extreme actions like suicide or self-destructive behavior.
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550 Views
The electroretinogram (ERG) is a clinical test that records the retina's electrical response to light. The ERG is a promising way to study different neurodevelopmental and neurodegenerative disorders, including Autism Spectrum Disorder (ASD) - a neurodevelopmental condition that impacts language, communication, and social interactions. However, privacy issues and a lack of data complicate Artificial Intelligence applications in this domain. Synthetic ERG signals generated from real ERG recordings should carry similar information and could be used as an extension for natural data.
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318 Views