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The WSO (Wilcox Solar Observatory at Stanford University) terrestrial observatory data, spanning 47 years of solar Mean Magnetic Field (MMF) values. The set also includes data from the WIND space mission's magnetometer (MAG), collected at the L1 Lagrangian point over the time interval of 27 years.
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157 Views
Abstract— Pluripotent cell types retain several characteristics that make them optimal cell source material for applications in drug development, disease modeling, and therapeutic applications. Human induced pluripotent stem cells (hiPSCs) are currently the most accessible cell source material to cultivate and derive cell-based therapeutic solutions at scale. However, a disconnect exists between quality characteristics of phenotype in the pluripotent state, and downstream metrics for efficacy.
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86 Views
This dataset contains inertial sensor and optical motion capture data from a trial of 20 healthy adult participants performing various upper limb movements. Each subject had an IMU and cluster of relfective markers attached to their sternum, right upper arm, and right forearm (as in the image attached), and IMU and marker data was recorded simultaneously. This trial was carried out with the intention of investigating alternative sensor-to-segment calibration methods, but may be useful for other areas of inertial sensor research. CAD files for the 3D printed mounts are also included.
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420 Views
We developed a unique and valuable dataset specifically for advancing Brain-Computer Interface (BCI) systems by recording brain activity from a dedicated volunteer. The participant was asked to pronounce 100 carefully selected Malayalam words, along with their English translations, which were chosen for their relevance to astronauts during human space missions. The volunteer pronounced these words both vocally and subvocally, each word being repeated 50 times. Non-invasive Electroencephalography (EEG) sensors were employed to capture the brain activity associated with these tasks.
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634 Views
This is the dataset for "An Efficiently Updatable Path Oracle for Terrain Surfaces" submitted to IEEE Transactions on Knowledge and Data Engineering. For more details, please refer to our code GitHub link https://github.com/yanyinzhao/UpdatedStructureTerrainCode.
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149 Views
This paper presents a dataset of brain Electroencephalogram (EEG) signals created when Malayalam vowels and consonants are spoken. The dataset was created by capturing EEG signals utilizing the OpenBCI Cyton device while a volunteer spoke Malayalam vowels and consonants. It includes recordings obtained from both sub-vocal and vocal. The creation of this dataset aims to support individuals who speak Malayalam and suffer from neurodegenerative diseases.
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2556 Views
This paper introduces a dataset capturing brain signals generated by the recognition of 100 Malayalam words, accompanied by their English translations. The dataset encompasses recordings acquired from both vocal and sub-vocal modalities for the Malayalam vocabulary. For the English equivalents, solely vocal signals were collected. This dataset is created to help Malayalam speaking patients with neuro-degenerative diseases.
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2802 Views
In today’s context, it is essential to develop technologies to help older patients with neurocognitive disorders communicate better with their caregivers. Research in Brain Computer Interface, especially in thought-to-text translation has been carried out in several languages like Chinese, Japanese and others. However, research of this nature has been hindered in India due to scarcity of datasets in vernacular languages, including Malayalam. Malayalam is a South Indian language, spoken primarily in the state of Kerala by bout 34 million people.
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860 Views
The Deepfake face detection task involves a facial image of unknown authenticity for testing. While most deepfake detection methods take only the image as input, our literature demonstrates that conditioning the deepfake detector on identity—i.e., knowing whose deepfake face the picture might be—can enhance detection performance. Existing deepfake detection datasets, such as FaceForensics++ and DFDC, do not include identity information for authentic and deepfake faces.
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2666 Views