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Plastics

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Deep-Learning-Based Character Recognition from Handwriting Motion Data Captured Using IMU and Force Sensors.

Sensors (Basel, Switzerland)
Digitizing handwriting is mostly performed using either image-based methods, such as optical character recognition, or utilizing two or more devices, such as a special stylus and a smart pad. The high-cost nature of this approach necessitates a cheap...

Deep learning based approach for automated characterization of large marine microplastic particles.

Marine environmental research
The rapidly growing concern of marine microplastic pollution has drawn attentions globally. Microplastic particles are normally subjected to visual characterization prior to more sophisticated chemical analyses. However, the misidentification rate of...

Multimodal collective swimming of magnetically articulated modular nanocomposite robots.

Nature communications
Magnetically responsive composites can impart maneuverability to miniaturized robots. However, collective actuation of these composite robots has rarely been achieved, although conducting cooperative tasks is a promising strategy for accomplishing di...

Identifying plastics with photoluminescence spectroscopy and machine learning.

Scientific reports
A quantitative understanding of the worldwide plastics distribution is required not only to assess the extent and possible impact of plastic litter on the environment but also to identify possible counter measures. A systematic collection of data cha...

A strategy to formulate data-driven constitutive models from random multiaxial experiments.

Scientific reports
We present a test technique and an accompanying computational framework to obtain data-driven, surrogate constitutive models that capture the response of isotropic, elastic-plastic materials loaded in-plane stress by combined normal and shear stresse...

Deep learning for detecting macroplastic litter in water bodies: A review.

Water research
Plastic pollution in water bodies is an unresolved environmental issue that damages all aquatic environments, and causes economic and health problems. Accurate detection of macroplastic litter (plastic items >5 mm) in water is essential to estimate t...

A Critical Review on Artificial Intelligence-Based Microplastics Imaging Technology: Recent Advances, Hot-Spots and Challenges.

International journal of environmental research and public health
Due to the rapid artificial intelligence technology progress and innovation in various fields, this research aims to use science mapping tools to comprehensively and objectively analyze recent advances, hot-spots, and challenges in artificial intelli...

The predictive model for COVID-19 pandemic plastic pollution by using deep learning method.

Scientific reports
Pandemic plastics (e.g., masks, gloves, aprons, and sanitizer bottles) are global consequences of COVID-19 pandemic-infected waste, which has increased significantly throughout the world. These hazardous wastes play an important role in environmental...

Analysis and forecasting of national marine litter based on coastal data in South Korea from 2009 to 2021.

Marine pollution bulletin
In this study, statistical analysis and forecasting were performed using coastal litter data of Korea. The analysis indicated that rope and vinyl accounted for the highest proportion of coastal litter items. The statistical analysis of the national c...

The Natural Robotics Contest: crowdsourced biomimetic design.

Bioinspiration & biomimetics
Biomimetic and bioinspired design is not only a potent resource for roboticists looking to develop robust engineering systems or understand the natural world. It is also a uniquely accessible entry point into science and technology. Every person on E...