Digital signal processing
Electroplating chemicals are the silent architects behind the shiny, corrosion-resistant surfaces we often take for granted. From the gleaming chrome on car parts to the delicate gold plating on jewelry, these chemicals are the backbone of a process that blends chemistry with craftsmanship. At its core, electroplating is the method of depositing a thin layer of metal onto the surface of another material using electric current, and the chemicals involved make all the difference. But this isn’t just science—it’s also art.
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Electroplating chemicals are the silent architects behind the shiny, corrosion-resistant surfaces we often take for granted. From the gleaming chrome on car parts to the delicate gold plating on jewelry, these chemicals are the backbone of a process that blends chemistry with craftsmanship. At its core, electroplating is the method of depositing a thin layer of metal onto the surface of another material using electric current, and the chemicals involved make all the difference. But this isn’t just science—it’s also art.
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To support research on multimodal speech emotion recognition (SER), we developed a dual-channel emotional speech database featuring synchronized recordings of bone-conducted (BC) and air-conducted (AC) speech. The recordings were conducted in a professionally treated anechoic chamber with 100 gender-balanced volunteers. AC speech was captured via a digital microphone on the left channel, while BC speech was recorded from an in-ear BC microphone on the right channel, both at a 44.1 kHz sampling rate to ensure high-fidelity audio.
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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. Field Programmable Gate Array (FPGA) and System on Chip (SoC) devices, owing to their features, are well-suited to perform tasks related to the digital back-end of these types of systems.
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This dataset was collected to support research on the screening and diagnosis of Diabetic Peripheral Neuropathy (DPN) and Cardiac Autonomic Neuropathy (CAN) using wearable sensor technology. It includes synchronized data from gait analysis and physiological signals such as electrocardiogram (ECG), heart rate variability (HRV), and inertial measurement units (IMUs) obtained from individuals with and without DPN and CAN.
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Data from acoustic condition monitoring of a milling process. During the process, several test parts were milled and acoustic data was recorded using a MEMS microphone.
One file shows two different tools used during milling, one for rough (face) milling with five cutting edges, and one with four cutting edges.
The other files show the data from different parts being milled, with the tool having four cutting edges. There were seven parts milled in total.
As the parts progress, it can be seen that the acoustic data changes, indicating wear and damage in the tool.
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This dataset contains electrocardiography (ECG) data recorded under controlled laboratory conditions. The primary objective of the measurement was to evaluate and compare different types of electrodes made from conductive textile materials in terms of their signal quality and performance. The dataset includes recordings from both conventional adhesive electrodes and textile electrodes to assess their suitability for ECG monitoring.
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The dataset contains thousands of signal frames from 60 ZigBee devices. The devices and USRP N210 were placed on two movable cabinets on wheels with a maximum distance of 3 meters between them. Due to distance constraints, a coaxial attenuator with an attenuation of 60 dB was fitted at the receiver in order to obtain signals at low SNR. The SNR of the received signal is changed by adjusting the distance between the two cabinets, which can be reduced to about 0 dB when the distance is about 3 metres.
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The field data set is collected in Hangzhou, Zhejiang Province, China. A linear array of 48 Fairfield Nodal ZLand 3C 5 Hz seismic sensors with approximately 5-m spacing was deployed to continuously record cultural noise from 10:00 am to about 02:45 pm, 24 June, 2019 (Beijing time) at a sampling frequency of 1000 Hz. The raw data includes 48 data files with the size of 201,312 kb and a file of the location information of all the receivers. Noted that the two horizontal components of sensors are oriented in the inline and crossline directions.
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As an important component of inertial guidance and navigation, micro-electro-mechanical-system (MEMS) gyroscope is widely used in many fields. However, the accumulation of noise errors limits the long-term accuracy and further application of MEMS gyroscope. This paper proposes a novel denoising method for MEMS gyroscope based on interpolated complementary ensemble local mean decomposition with adaptive noise (ICELMDAN) and gated recurrent unit-unscented Kalman filter (GRU-UKF).
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