Journal of Progress in Engineering and Physical Science

Response to “Cosmological Consequences of the Lorentz and Doppler Transformations”

A. Sfarti — 2026-02-11

The paper “Cosmological Consequences of the Lorentz and Doppler Transformations” by Vaclav Vavryčuk claims that the Lorentz transformation’s physical interpretation is flawed and advocates for a “Doppler metric” instead of the standard Minkowski metric as a better description of spacetime distortion, an idea that contradicts the well-established foundation of Einstein’s Special Relativity and is not supported by mainstream physics.

Application of Wi-Fi Devices for Signal Processing to Send and Receive Data

Chenglu Zhou — 2026-02-24

This paper examines the implementation of Wi-Fi devices in signal-processing methods to transmit and receive data reliably in complex wireless networks. It describes radio signal mechanisms at the physical layer for transmitting digital information and decoding it at the other end, accounting for noise, interference, and multipath fading. Such technologies as Orthogonal Frequency Division Multiplexing (OFDM), Multiple-Input Multiple-Output (MIMO), and Channel State Information (CSI) are examined to demonstrate how contemporary Wi-Fi systems become very fast and powerful. It also discusses how these signal-processing techniques support uses like Wi-Fi sensing, security surveillance, and health tracking.

Deep Integration of Sensing Technology and Smart Manufacturing: Leading the Technological Upgrade of the Precision Manufacturing Industry

Huajun Liu — 2026-03-30

Aiming at the technical bottlenecks in core links of the precision manufacturing industry, such as ultra-precision measurement and flexible production—including insufficient machining accuracy (traditional machining error ≥±0.025 μm), response lag (process adjustment delay >100 ms), and data silos—this paper proposes a full-chain integrated architecture of “perception-modeling-decision-execution”. It reveals the signal crosstalk mechanism of multi-physics field coupled sensing units and systematically elaborates the deep collaboration mechanism between multi-parameter collaborative perception and digital twin, AI adaptive control, and industrial interconnection. By developing a four-parameter integrated MEMS sensing module based on frequency domain isolation, an attention mechanism-improved LSTM algorithm, and a cross-protocol adaptive conversion middleware, three core technological breakthroughs are achieved: (1) The measurement accuracy is improved from ±0.025 μm to ±0.006 μm (a relative increase of 76%), with a complex surface detection error ≤4.2 μm; (2) The response delay is reduced from >100 ms to 0.8 ms (a reduction of 99.2%), and the equipment fault early warning accuracy reaches 94.7%; (3) The changeover efficiency of flexible production lines is increased by 45%, and the product defect rate is reduced from 3.2% to 0.5% (a reduction of 84.4%). Empirical verification in three typical industrial scenarios shows that the integrated system increases production efficiency by 32%-48% and reduces comprehensive manufacturing costs by 18%-26%. The research results provide a systematic solution for the transformation of the precision manufacturing industry. Relevant technologies have formed 15 authorized patents and 11 software copyrights, possessing significant academic value and industrial application prospects.