Results 121 to 130 of about 2,589,900 (302)

BSMD-YOLOv8: Enhancing YOLOv8 for Book Signature Marks Detection

Applied Sciences
In the field of bookbinding, accurately and efficiently detecting signature sequences during the binding process is crucial for enhancing quality, improving production efficiency, and advancing industrial automation.
Long Guo, Lubin Wang, Qiang Yu, Xiaolan Xie   +3 more
doaj   +1 more source

Additive Manufacturing of Continuous Fibre Reinforced Composites: Process, Characterisation, Modelling, and Sustainability

Advanced Engineering Materials, EarlyView.
Additive manufacturing provides precise control over the placement of continuous fibres within polymer matrices, enabling customised mechanical performance in composite components. This article explores processing strategies, mechanical testing, and modelling approaches for additive manufactured continuous fibre‐reinforced composites.
Cherian Thomas, Amir Hosein Sakhaei
wiley   +1 more source

A deep learning radiopathomic signature predicts recurrence risk of hepatocellular carcinoma after hepatectomy

Communications Biology
Accurate prediction of recurrence risk after hepatectomy still remains a clinical challenge for hepatocellular carcinoma (HCC). We develop a deep learning radiopathomic (DLRP) signature to fuse deep features of CT images and histological whole-slide ...
Gongzheng Wang, Wei Chen, Zhuoshuai Liang, Feier Ding, Jin Cui, Zijian Shen, Fan Lin, Xiujuan Li, Ximing Wang, Xinya Zhao   +9 more
doaj   +1 more source

Enhanced Strength and Corrosion Resistance of Ti‐13Nb‐12Ta‐10Zr‐4Sn Alloy by Aging Treatment

Advanced Engineering Materials, EarlyView.
This work systematically investigates the effect of aging treatment on mechanical properties and corrosion behavior of vacuum arc‐melted Ti‐13Nb‐12Ta‐10Zr‐4Sn alloy. Owing to the increased α″ martensite, strength and corrosion resistance were significantly enhanced by aging treatment.
Yuhua Li, Rong Zhao, Qian Zhang, Haojie Wang, Yujing Liu, Lai‐Chang Zhang   +5 more
wiley   +1 more source

Multi-Script Off-Line Signature Verification

, 2014
Signature identification and verification are of great importance in authentication systems. In the field of signature verification, substantial investigation has been undertaken, mainly involving English signatures.
Srikanta, Pal
core   +1 more source

Direct Metal Deposition of Graphene–Ti28Nb35.4Zr Matrix Composites With Enhanced Mechanical, Corrosion, and Biocompatibility Properties for Bone Implants

Advanced Engineering Materials, EarlyView.
Graphene nanoplatelet (0.1 wt.%) reinforcement significantly enhances the performance of β Ti‐28Nb‐35.4Zr alloy. Grain refinement, reduced water contact angle, and improved surface characteristics promote osteoblast adhesion and complete surface coverage after 7 days.
Khurram Munir, Jixing Lin, Yuncang Li, Li Zhu, Paul F. A. Wright, Cuie Wen   +5 more
wiley   +1 more source

multi-authority Attribute-based Signature

工程科学与技术, 2011
:In real life, many attributes of a user are monitored by a single authority, which will inevitably increase its workload and reduce its efficiency. In this paper, the proposed multi-authority Attribute-based Signature scheme is that many attributes are ...
Sun Chang-Xia
doaj  

Designing Polymer Nanocomposites for X‐Ray Shielding: Mechanisms, Architectures, and Scalable Processing

Advanced Engineering Materials, EarlyView.
This review highlights advances in lightweight, lead‐free polymer nanocomposites for diagnostic X‐ray shielding. By linking filler chemistry, dispersion, architecture, and photon interaction mechanisms, it establishes structure–performance relationships guiding material design.
Aklilu G. Messele, Hossein Ipakchi, Tizazu H. Mekonnen   +2 more
wiley   +1 more source

Applying a signature to different objects

, 2006
Flash asset which allows you to add your signature to different ...
Simon James
core  

Machine Learning‐Supported Analysis for Predicting and Visualizing Nonlinear Relationships Between Material Properties in Electroplated Chromium Layers

Advanced Engineering Materials, EarlyView.
This study applies machine learning regression to predict chromium layer thickness in decorative trivalent chromium electroplating, using 441 experiments from laboratory‐scale (1L) and pilot‐scale (14L) setups. Tree‐based models, particularly CatBoost, outperformed linear regression by capturing nonlinear parameter interactions (R2$R^2$ up to 0.77 ...
Christoph Baumer, Christopher Mai, Luca Eisentraut, Andreas Bund, Ricardo Buettner   +4 more
wiley   +1 more source