These folders contain images showcasing various aspects of orange fruit and leaf diseases, including black spot, greening, scap, canker diseases, melanose, and healthy leaves. The dataset serves as a valuable resource for research, machine learning model training, and analysis in the field of citrus diseases and nutrient imbalances.
The data covers the period from January 4, 2021, to August 16, 2023. It includes the carbon trading prices from the Hubei carbon market and other relevant feature data that may influence carbon prices. The feature data has undergone preliminary screening and consists of Brent crude oil prices, natural gas prices, Rotterdam coal prices, EU Emission Allowances, the China Securities 300 Index, and the Euro exchange rate.
This dataset was built as part of our study MentalAgora: A Gateway to Advanced Personalized Care in Mental Health through Multi-Agent Debating and Attribute Control. The dataset was sourced from mental health-related posts in Reddit Mental Health Dataset and tagged with responses from mental health professionals to selected posts. For more details on building the dataset, please see the paper.
The sampling rate of laser Doppler vibration measurement data is 250MHZ, and the number of sampling points is 20M.A total of 12 frequency bands of 0.5kHZ, 1kHZ, 2kHZ, 3kHZ, 4kHZ, 5kHZ, 6kHZ, 7kHZ, 8kHZ, 9kHZ, 10kHZ, 11kHZ were collected, which ensured that there were at least 5 vibration samples in each frequency band, and 20 samples were collected in some frequency bands.
Satellite attitude determination is critical for accurately measuring and controlling a satellite’s orientation in orbit using a variety of sensors and methods. Currently, low-low Satellite-to-Satellite Tracking (ll-SST) missions—such as GRACE(-FO)—and upcoming missions like Magic primarily rely on quaternion data from onboard star camera sensors. To enhance attitude determination, we propose a GSCF fusion method.
Astronomical instrumentation and related fields have seen remarkable evolution in recent decades, driving the need for advanced signal acquisition and processing techniques. Current experiments demand readout capabilities beyond traditional approaches, leading to the adoption of a wideband instrumentation system architecture for high-speed Radio Frequency (RF) measurements.
In My study, we evaluate the performance of the proposed clustering method across a wide range of publicly available datasets that represent different data modalities. Specifically, Jaffe, ExtendYaleB, and ORL are employed as facial image datasets to assess the method's capability in handling variations in facial expressions and lighting conditions.
This radar data was collected by a system in Goose Bay, Labrador. This
system consists of a phased array of 16 high-frequency antennas with a
total transmitted power on the order of 6.4 kilowatts. See the paper
for more details. The targets were free electrons in the ionosphere.
"Good" radar returns are those showing evidence of some type of structure
in the ionosphere. "Bad" returns are those that do not; their signals pass
This dataset is derived from the RUG-EGO-FALL dataset and has been processed for feature extraction to support fall detection research. We applied Oriented FAST and Rotated BRIEF (ORB) for keypoint extraction and used optical flow methods to compute motion features, including per-frame X and Y pixel displacement values, representing movement speed and direction.
This dataset consists of 'circles' (or 'friends lists') from Facebook. Facebook data was collected from survey participants using this Facebook app. The dataset includes node features (profiles), circles, and ego networks.
This dataset consists of 'circles' (or 'friends lists') from Facebook. Facebook data was collected from survey participants using this Facebook app. The dataset includes node features (profiles), circles, and ego networks.
Load frequency control is essential for maintaining power system stability, especially under uncertainties and input delays. This paper proposes a reinforcement learning-based dual-channel dynamic event-triggered fixed-time load frequency control approach for uncertain multi-area power systems with input delays. A non-singular fast terminal sliding mode technique is employed to guarantee that the tracking error converges within a fixed time.
This radar signal dataset comprises 10,000 simulated signals, providing a comprehensive resource for radar signal processing research and experiments. The dataset is designed to facilitate the study of various radar phenomena, including signal deinterleaving and modulation recognition analysis. The number of overlapping signals is uniformly distributed between 1 and 5, ensuring a wide range of complexity for testing algorithms under different interference conditions. Each signal file contains detailed pulse information, which supports robust analysis of radar performance.&nbs
Attached Image data set from combined OCT-SLO is used to train AI models and identify features to maximize quality of data set to adjust MZI reference arm, PMT Voltage of Liquid Lens and location of object. Why adjustment is needed is explained below:
We are pleased to submit our manuscript entitled "Hetero-modal Template Guide Search Region for RGBT Tracking" for consideration for publication in IEEE Transactions on Consumer Electronics. This work presents a novel framework for robust RGB-Thermal (RGBT) object tracking, addressing critical challenges in consumer electronics applications such as smart security systems, autonomous navigation, and augmented reality devices.
We are pleased to submit our manuscript entitled "Hetero-modal Template Guide Search Region for RGBT Tracking" for consideration for publication in IEEE Transactions on Consumer Electronics. This work presents a novel framework for robust RGB-Thermal (RGBT) object tracking, addressing critical challenges in consumer electronics applications such as smart security systems, autonomous navigation, and augmented reality devices.
This dataset consists of meteorological and environmental data collected in Riyadh, Saudi Arabia, over multiple years. The variables include solar radiation, temperature (both maximum and minimum in Celsius and Fahrenheit), precipitation, vapor pressure, and snow water equivalent, among others. The data spans from 2010 to the present, providing insights into solar radiation patterns, daily temperature fluctuations, and weather-related factors that can impact solar power generation. Specifically, the dataset contains the following columns:
This study explores the relationship between social media sentiment and stock market movements using a dataset of tweets related to various publicly traded companies. The dataset comprises time-stamped tweets containing company-specific information, stock ticker symbols, and company names. By leveraging natural language processing (NLP) techniques, we analyze the sentiment of tweets to determine their impact on stock price fluctuations. This research aims to develop predictive models that incorporate tweet sentiment and frequency as features to forecast stock price movements.
The NEU-DET dataset is a set of images characterized by surface defects on hot rolled steel strip. These defects are classified into six categories: cracks (cr), inclusions (in), patches (pa), pitted surfaces (ps), rolled scales (rs) and scratches (sc). The dataset contains 300 grayscale images for each category, for a total of 1800 images, each of which is 200×200 pixels in size.
The shift towards cloud-native applications has been accelerating in recent years. Modern applications are increasingly distributed, taking advantage of cloud-native features such as scalability, flexibility, and high availability. However, this evolution also introduces various security challenges. From a networking perspective, the large number of interconnected components and their intricate communication patterns make detecting and mitigating traffic anomalies a complex task.
Spray-cooled shells of electric arc furnaces (EAF) experience dynamic and intense thermal fluctuations that, if undetected, can lead to significant operational challenges, including structural damage and compromised safety. In this study, we demonstrate the use of fiber optic sensors (FOS) for real-time, distributed thermal monitoring of an EAF shell wall.
CubexSoft OLM to PST Converter for Mac and Windows OS Tool, a more reliable and secure way to convert or migrate OLM file to PST file with all mailbox items. This utility enables you to convert OLM files into PST files in bulk without missing any data. You can easily view the OLM file mailbox data and it instantly exports inaccessible Mac Outlook OLM files to Outlook PST files without Outlook. All Outlook editions, including 2021, 2019, 2016, 2013, 2010, and others, are suitable with it. This app also works with every Windows OS and Macintosh OS editions.
This dataset is composed of a range of biomedical voice measurements from 31 people, 23 with Parkinson's disease (PD). Each column in the table is a particular voice measure, and each row corresponds to one of 195 voice recordings from these individuals ("name" column). The main aim of the data is to discriminate healthy people from those with PD, according to the "status" column which is set to 0 for healthy and 1 for PD.
The dataset provided in this study contains variables related to solar power generation, including solar irradiance, temperature, wind speed, and humidity in Riyadh. The data was collected using NASA satellite imagery and various ground stations over a period of time. This dataset is crucial for improving solar radiation forecasting models, particularly by enhancing the prediction of solar power production in Saudi Arabia under varying climatic conditions.
