Autoencoder-Based System for Detecting Anomalies in Pelletizer Melt Processes.

Effectively identifying and preventing anomalies in the melt process significantly enhances production efficiency and product quality in industrial manufacturing. Consequently, this paper proposes a study on a melt anomaly identification system for pelletizers using autoencoder technology. It discusses the challenges of detecting anomalies in the melt extrusion process of polyester pelletizers, focusing on the limitations of manual monitoring and traditional image detection methods.

AI-Enabled Portable E-Nose Regression Predicting Harmful Molecules in a Gas Mixture.

The biomimetic electronic nose (e-nose) technology is a novel technology used for the identification and monitoring of complex gas molecules, and it is gaining significance in this field. However, due to the complexity and multiplicity of gas mixtures, the accuracy of electronic noses in predicting gas concentrations using traditional regression algorithms is not ideal. This paper presents a solution to the difficulty by introducing a fusion network model that utilizes a transformer-based multikernel feature fusion (TMKFF) module combined with a 1DCNN_LSTM network to enhance the accuracy of regression prediction for gas mixture concentrations using a portable electronic nose.

Paper-Based Sandwich-Structured Wearable Sensor with Sebum Filtering for Continuous Detection of Sweat pH.

Wearable sweat sensors, a product of the development of flexible electronics and microfluidic technologies, can continuously and noninvasively monitor abundant biomarkers in human sweat; however, sweat interferences, such as sebum, can reduce sensor reliability and accuracy. Herein, for the first time, the influence of sebum on the potentiometric response of an all-solid-state pH sensor was studied, and the obtained experimental results show that sebum mixed in sweat can decrease the potential response of the sensor and the slope of its calibration curve. A paper-based sandwich-structured pH sensor that can filter the sebum mixed in sweat was proposed based on commonly used oil-control sheets.

Estimation of pollutant sources in multi-zone buildings through different deconvolution algorithms.

Effective identification of pollution sources is particularly important for indoor air quality. Accurate estimation of source strength is the basis for source effective identification. This paper proposes an optimization method for the deconvolution process in the source strength inverse calculation.

Accuracy assessment and kinematic calibration of the robotic endoscopic microsurgical system.

This paper explores the general stereotactic accuracy of the Robotic Endoscopic Microsurgical System (REMS) by calibrating with a standard optical tracking system. Based on a simple yet effective test protocol, the proposed calibration method combines hand-eye calibration with Bernstein polynomials to improve our kinematic pose accuracy.

Inertia coupling analysis of a self-decoupled wheel force transducer under multi-axis acceleration fields.

Wheel force transducer (WFT), which measures the three-axis forces and three-axis torques applied to the wheel, is an important instrument in the vehicle testing field and has been extremely promoted by researchers with great interests. The transducer, however, is typically mounted on the wheel of a moving vehicle, especially on a high speed car, when abruptly accelerating or braking, the mass/inertia of the transducer/wheel itself will have an extra effect on the sensor response so that the inertia/mass loads will also be detected and coupled into the signal outputs. The effect which is considered to be inertia coupling problem will decrease the sensor accuracy.

[Surface plasmon resonance spectral based fiber optic sensor for detection of total dissolved solids in water quality analysis].

As surface plasmon resonance (SPR) spectrum is sensitive to refractive index of the mediums, we explored its sensitivity characteristic of ions composition detection in a solution so as to measure the total dissolved solid value in water. Seven ionic (NaCl, KCl, CaCl2, MgCl2, Na2CO3, MgSO4 and ZnSO4) and 3 non-ionic (glucose, glycerol and sucrose) liquid samples were studied experimentally with a fiber optic SPR sensor. The influence of ion concentration on the resonance wavelength shift in SPR spectrum was investigated and discussed, and with that, the response curves were established to realize the detection of total dissolved solid in water quality analysis.