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This research utilized data from the Oxford University Our World in Data Covid 19 Dataset. This dataset contains data points collected on an ongoing basis from Johns Hopkins University, Center for Systems Science and Engineering COVID-19 data, European Centre for Disease Control, and OXFORD COVID-19 Government Response Tracker, from January 2020 to the present.

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Faces and bodies provide critical cues for social interaction and communication. Their structural encoding depends on configural processing, as suggested by the detrimental effect of stimulus inversion for both faces (i.e., face inversion effect - FIE) and bodies (body inversion effect - BIE). An occipito-temporal negative event-related potential (ERP) component peaking around 170 ms after stimulus onset (N170) is consistently elicited by human faces and bodies and it is affected by the inversion of these stimuli.

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Data were obtained from the established Clinical Data Repository (CDR) of Yichang Central People's Hospital, and the master index dataset of AKI sample cases was derived by combining the inclusion-exclusion conditions of the study samples with a query of the relevant conditions in the CDR. The data from the CDR and the AKI contain protected health information and are not subject to public sharing. Currently, 500 pieces of data were randomly selected as a sample for public disclosure, details of which are attached to the paper.

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243 Views

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Since the majority of people have smartphones, the Hb level can be determined using the smartphone's video through PPG signal as opposed to the traditional approaches, which still require the use of a needle to puncture a vein. This study enrolled 108 subjects who underwent a clinical test, with their hemoglobin (Hb) level within the range of 6.6 to 16.5 g/dL.

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Since the majority of people have smartphones, the Hb level can be determined using the smartphone's video through PPG signal as opposed to the traditional approaches, which still require the use of a needle to puncture a vein. This study enrolled 108 subjects who underwent a clinical test, with their hemoglobin (Hb) level within the range of 6.6 to 16.5 g/dL.

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Our released weight dataset for fusion results in edge-cloud collaborative inference contains the corresponding weighted summation weights under 50,000 edge-cloud collaborative DNN inference tasks, listing the five heterogeneous NVIDIA edge devices they use (NVIDIA Jetson Nano, TX2, NX, Orin NX, and AGX Orin), computing power (1.9~275TOPS), DNN model type (EfficientNet-B0, ViT-B16), and network bandwidth (0.5~8Mbps).

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⁤Securing systems with limited resources is crucial for deployment and should not be compromised for other performance metrics like area and throughput. ⁤⁤Physically Unclonable Functions (PUFs) emerge as a cost-effective solution for various security applications, such as preventing IC counterfeiting and enabling lightweight authentication. ⁤⁤In the realm of memory-based PUFs, the physical variations of available memory systems, such as DRAM or SRAM, are exploited to derive an intrinsic response based on the accessed data row.

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This malware dataset collected from Indonesia. The  Malicious Windows Portable Executable has been extracted using LIEF library. The main objective of this dataset is to support research in the field of malware detection by employing machine learning methodologies. The gathered data will aid in the creation of more effective and precise machine-learning algorithms for detecting and reducing malware risks in Windows-operated systems.

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1986 Views

Objective, sensitive, and meaningful disease assessments are critical to support clinical trials and clinical care. Speech changes are one of the earliest and most evident manifestations of cerebellar ataxias. This data set contains features that can be used to train models to identify and quantify clinical signs of ataxic speech. Though raw audio or spectrograms cannot be released due to privacy concerns, this data set contains several OpenSMILE feature sets.

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The dataset utilized in this research originates from two primary sources: the Central Bureau of Statistics of Indonesia, which provides data on Harvested Area and Production, and the Meteorology, Climatology, and Geophysics Agency of Indonesia, responsible for data on Rainfall, Humidity, and Temperature. This dataset encompasses six years of observations, collected annually from 2018 to 2023. It is important to note that the data for December 2023 are predictive estimates from these agencies.

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