Core i7 8750h

Manufactured by NVIDIA

The Core i7-8750H is a mobile processor from Intel's 8th generation Coffee Lake lineup. It features 6 cores and 12 threads, with a base clock speed of 2.2 GHz and a max turbo frequency of 4.1 GHz. The processor supports up to 32 GB of DDR4 memory and is manufactured using a 14nm process.

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I7 core

2 protocols using core i7 8750h

Training and Benchmarking CRN Model

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The CRN was trained by an Adam optimizer, whose learning rate is 0.0001. The max epoch and batch size were 20 and 64, respectively. The CRN was implemented by Pytorch and trained and tested on a computer with an Intel Core i7-8750H, two 8 GB memory chips (DDR4), and a GPU (Nvidia Geforce GTX 1060 6G).

Zhou Q., Shan J., Ding W., Wang C., Yuan S., Sun F., Li H, & Fang B. (2021). Cough Recognition Based on Mel-Spectrogram and Convolutional Neural Network. Frontiers in Robotics and AI, 8, 580080.

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Tracking Street-Level PD Changes

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Timing: 15 min

The purpose of this step is to calculate the changes of PD across different years for streets and cities.
Resource levels: [Intel Core i7-8750H/16 GB RAM/ 64 bit Windows 10/NVIDIA GeForce RTX 2070].

10.

Based on the correspondence of streets across different years, the improvement and deterioration of PD can be determined.a.

Deteriorating PD is identified when the PD value in the later year is higher than that in the previous year, while improvement occurs when the PD value in the later year is lower than that in the previous year.

Note: Each acquired street and location comes with a unique identifier, which remains the same across years. These identifiers enable PD in different years to be matched, which is a great advantage over other state-of-art methods. Due to the varying city boundaries and streets updated annually, the comparative analysis over multiple years relies entirely on available data points from each respective year.

Note: For each street, considering the varying length and number of street points on each street, the calculation involves determining the proportion of upgraded street points and the proportion of deteriorated points on that street. However, the raw ratio of PD improvement and deterioration is statistically too varied when the denominator is small, so streets with too few street view points (<10) are omitted.

Li Y., Ma Y, & Long Y. (2023). Protocol for assessing neighborhood physical disorder using the YOLOv8 deep learning model. STAR Protocols, 5(1), 102778.

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