S, and physical parts. These strategies perform virtual manufacturing, volume rendering, and image processing to extract watermarks from these contents at first. Then, they employ similarity evaluation and visual comparison to verify the extracted signatures. Some experiments had been conducted to validify the proposed watermarking strategy. The test outcomes, analysis, discussion, and comparisons are also presented in this report. Keywords and phrases: watermarking; Melperone Autophagy Additive manufacturing; geometric modelling; self-organizing mappingAcademic Editor: Marco Mandolini Received: 14 August 2021 Accepted: 28 September 2021 Published: two OctoberCitation: Ueng, S.-K.; Hsieh, Y.-F.; Kao, Y.-C. A Voxel-Based Watermarking Scheme for Additive Manufacturing. Appl. Sci. 2021, 11, 9177. https://doi.org/10.3390/ app1. Introduction Additive manufacturing (AM) strategies have already been broadly made use of in scientific, engineering, medical, and other applications [1]. An AM method is composed of 3 stages: geometrical modelling, G-code generation, and 3D printing [2,3]. The resultant geometric models, G-code applications, and physical objects consume valuable resources, including human efforts, computing charges, energies, and raw materials. If these contents are illegally distributed, reproduced, and modified, the owners could encounter important economic losses [4,5], and they will hesitate to invest more resources in AM. Consequently, the innovation and progression of AM industries is going to be in danger. In some volunteer AM communities, their members are prepared to share their perform and expertise with other people. Therefore, ownership protection just isn’t a concern [6]. However, in this scenario, authentication and annotation of contents are nonetheless essential to prevent misusage on the products. Watermarking procedures had long been utilized to boost the securities of digital information, which includes texts, music, photos, and videos [91]. By analogy, in AM industries, men and women inserted identification signals into digital and physical models to safe their intellectual properties [124]. Nonetheless, mechanisms for safeguarding G-code programs had been seldom discussed in these publications. In an AM approach, the top quality from the resultant objectPublisher’s Note: MDPI stays neutral with regard to jurisdictional claims in published maps and institutional affiliations.Copyright: 2021 by the authors. Licensee MDPI, Basel, Switzerland. This short article is an open access article distributed beneath the terms and conditions on the Creative Commons Attribution (CC BY) license (https:// creativecommons.org/licenses/by/ 4.0/).Appl. Sci. 2021, 11, 9177. https://doi.org/10.3390/apphttps://www.mdpi.com/journal/applsciAppl. Sci. 2021, 11,two ofis primarily decided by the G-code system. Hence, we commit loads of efforts to determine the printing path, construct the supporting structures, slice the geometric model, select the hatching patterns, and schedule the toolpaths before creating the G-code program. In addition to, to make sure a high-quality 3D printing, we should also conduct experiments, calculations, and simulations to receive feasible printing parameters, including the nozzle temperature, raw material variety, printing speed, and so on. Therefore, for the sake of economy, G-code programs are precious properties. Furthermore, well-tuned G-code programs could be utilized to repeatedly make physical models to cut down Melagatran supplier production charges. As a result, G-code programs are one of many crucial gradients for mass-production in AM applications. Primarily based on these factors, G-code pr.
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