An Enhanced Hybrid Springback Compensation Approach: Springback Path – Displacement Adjustment Method For Complex Shaped Products of Sheet Metal Forming

Springback compensation is critical in sheet metal forming. Advanced techniques have been adopted in the design stage of various sheet metal forming processes, e.g. stamping, some of which are for complex shaped products. However, the currently available numerical approaches are not always sufficiently accurate and reliable. To improve the accuracy of springback compensation, an enhanced hybrid springback compensation method named Springback Path – Displacement Adjustment (SP-DA) method has been developed in this study based on the well-known conventional displacement adjustment (DA) method. Its effectiveness is demonstrated using FEM analysis of low, medium and high strength steels adopted in automobile industry, in which a symmetrical model owning geometry complexity similar to an auto body panel was established. The results show this new enhanced SP-DA method is able to significantly improve the accuracy of springback compensation comparing to conventional displacement adjustment technique.

Global Estimation and Compensation of Linear Effects in Coherent Optical Systems based on Nonlinear Least Squares

This paper proposes a new estimation and compensation approach to mitigate several linear and widely linear effects in coherent optical systems using digital signal processing (DSP) algorithms. Compared to most of the available strategies that employ local estimation and/or compensation algorithms, this approach performs a global impairments estimation and compensation based on Nonlinear Least Squares. The proposed method estimates and compensates for the chromatic dispersion (CD), carrier frequency offset (CFO), in-phase/quadrature (IQ) imbalance, and laser phase noise (PN) in two steps. Firstly, it estimates the quasi-static parameters related to the CD, CFO, and both transmitter and receiver IQ imbalance. Secondly, it estimates both transmitter and receiver lasers’ phases and compensates for all the imperfections by using a Zero-Forcing (ZF) equalizer. Simulations show the effectiveness of the approach in terms of statistical performance and computational time. The estimation performance is assessed by computing the Cramér Rao Lower Bound (CRLB), while the detection performance is compared to a modified Clairvoyant equalizer.<br>

Global Estimation and Compensation of Linear Effects in Coherent Optical Systems based on Nonlinear Least Squares

This paper proposes a new estimation and compensation approach to mitigate several linear and widely linear effects in coherent optical systems using digital signal processing (DSP) algorithms. Compared to most of the available strategies that employ local estimation and/or compensation algorithms, this approach performs a global impairments estimation and compensation based on Nonlinear Least Squares. The proposed method estimates and compensates for the chromatic dispersion (CD), carrier frequency offset (CFO), in-phase/quadrature (IQ) imbalance, and laser phase noise (PN) in two steps. Firstly, it estimates the quasi-static parameters related to the CD, CFO, and both transmitter and receiver IQ imbalance. Secondly, it estimates both transmitter and receiver lasers’ phases and compensates for all the imperfections by using a Zero-Forcing (ZF) equalizer. Simulations show the effectiveness of the approach in terms of statistical performance and computational time. The estimation performance is assessed by computing the Cramér Rao Lower Bound (CRLB), while the detection performance is compared to a modified Clairvoyant equalizer.<br>

Damaged/missing proximity sensor induces screen mistouch when answering calls: Prediction of smartphone answering status by posture data

When the proximity sensor of a smartphone is impaired, it would easily lead to screen mistouch during conversation, which will significantly affect the user experience. However, there are relatively few studies that have been focused on the quality of user experience following sensor impairment. The purpose of this study was to compare and evaluate different machine learning models in forecasting the user’s posture during a phone call, thereby providing a compensation approach for detecting proximity to the human ear during a phone call following sensor damage. The built-in accelerometer sensors of smartphones were employed to collect posture data while users were employing their smartphones. Three main postures (holding, moving and answering) were identified; the posture data were obtained through training and prediction using five machine learning models. The results showed that the model that utilized triaxial data had better prediction accuracy than the model that used single-axis data. Furthermore, models with time-domain features had a higher accuracy rate. Among the five models, neural networks had the best prediction accuracy (0.982). The proposed approach could be of immense benefit to the users following proximity sensor damage, and would be advantageous in the design of the smartphone, particularly in the early stages of the design process.