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Self-sensing composites performance largely relies on the sensing fillers property and interface. Our previous work demonstrates that the microwires can enable self-sensing composites but with limited damage detection capabilities. Here, we…

Applied Physics · Physics 2019-05-20 Y. J. Zhao , X. F. Zheng , F. X. Qin , D. Estevez , Y. Luo , H. Wang , H. X. Peng

Biological structural designs in nature, like hoof walls, horns, and antlers, can be used as inspiration for generating structures with excellent mechanical properties. A common theme in these designs is the small percent porosity in the…

Computational Engineering, Finance, and Science · Computer Science 2023-10-03 Shashank Kushwaha , Junyan He , Diab Abueidda , Iwona Jasiuk

Detection with high dimensional multimodal data is a challenging problem when there are complex inter- and intra- modal dependencies. While several approaches have been proposed for dependent data fusion (e.g., based on copula theory),…

Applications · Statistics 2018-02-14 Thakshila Wimalajeewa , Pramod K. Varshney

Recently, there has been a significant interest in developing cooperative sensing systems for certain types of wireless applications. In such systems, a group of sensing nodes periodically collect measurements about the signals being…

Information Theory · Computer Science 2015-06-11 Harish Ganapathy , Constantine Caramanis , Lei Ying

Controlling the strain level in nanowire heterostructures is critical for obtaining coherent interfaces of high crystalline quality and for the setting of functional properties such as photon emission, carrier mobility or piezoelectricity.…

Materials Science · Physics 2020-08-05 D. V. Beznasyuk , P. Stepanov , J. L. Rouvière , F. Glas , M. Verheijen , J. Claudon , M. Hocevar

Compressive sensing (CS) combines data acquisition with compression coding to reduce the number of measurements required to reconstruct a sparse signal. In optics, this usually takes the form of projecting the field onto sequences of random…

Information Theory · Computer Science 2018-10-24 Davood Mardani , H. Esat Kondakci , Lane Martin , Ayman F. Abouraddy , George K. Atia

The paper presents a distributed algorithm, called Prediction-based Opportunistic Sensing for Resilient and Efficient Sensor Networks (POSE.R), where the sensor nodes utilize predictions of the targets positions to probabilistically control…

Systems and Control · Electrical Eng. & Systems 2021-07-28 James Z. Hare , Junnan Song , Shalabh Gupta , Thomas A. Wettergren

Intelligent reflecting surface (IRS) is an emerging technology that is able to significantly improve the performance of wireless communications, by smartly tuning signal reflections at a large number of passive reflecting elements. On the…

Signal Processing · Electrical Eng. & Systems 2023-02-14 Xiaodan Shao , Changsheng You , Rui Zhang

Soft sensing is a way to indirectly obtain information of signals for which direct sensing is difficult or prohibitively expensive. It may not \textit{a priori} be evident which sensors provide useful information about the target signal,…

Systems and Control · Electrical Eng. & Systems 2024-09-17 Le Wang , Ying Wang , Yu Qiu , Mian Li , Håkan Hjalmarsson

Fabrication techniques such as laser patterning offer excellent potential for low cost and large area device fabrication. Conductive polymers can be used to replace expensive metallic inks such as silver and gold nanoparticles for printing…

We consider the optimal distributed controller design problem subject to two structural requirements: locality, i.e. available measurements and sub-controllers' interactions are governed by a graph structure, and relative feedback, i.e.…

Systems and Control · Electrical Eng. & Systems 2022-01-11 Emily Jensen , Bassam Bamieh

This paper presents an innovative Transformer-based deep learning strategy for optimizing the placement of sensors aiming at structural health monitoring of semiconductor probe cards. Failures in probe cards, including substrate cracks and…

Machine Learning · Computer Science 2025-09-10 Mehdi Bejani , Marco Mauri , Daniele Acconcia , Simone Todaro , Stefano Mariani

The accurate and low-cost localization of sensors using a wireless sensor network is critically required in a wide range of today's applications. We propose a novel, robust maximum likelihood-type method for distributed cooperative received…

Signal Processing · Electrical Eng. & Systems 2018-12-12 Luca Carlino , Di Jin , Michael Muma , Abdelhak M. Zoubir

In this paper, we exploit the theory of compressive sensing to perform detection of a random source in a dense sensor network. When the sensors are densely deployed, observations at adjacent sensors are highly correlated while those…

Information Theory · Computer Science 2017-07-27 Thakshila Wimalajeewa , Pramod K. Varshney

Sparse coding networks, which utilize unsupervised learning to maximize coding efficiency, have successfully reproduced response properties found in primary visual cortex \cite{AN:OlshausenField96}. However, conventional sparse coding…

Neurons and Cognition · Quantitative Biology 2011-05-25 William K. Coulter , Christopher J. Hillar , Friedrich T. Sommer

Spatially nonuniform strain is important for engineering the pseudomagnetic field and band structure of graphene. Despite the wide interest in strain engineering, there is still a lack of control on device-compatible strain patterns due to…

To strike a balance between energy efficiency and data quality control, this paper proposes a sensor censoring scheme for distributed sparse signal recovery via compressive-sensing based wireless sensor networks. In the proposed approach,…

Information Theory · Computer Science 2018-01-16 Jwo-Yuh Wu , Ming-Hsun Yang , Tsang-Yi Wang

Designing and fabricating structures with specific mechanical properties requires understanding the intricate relationship between design parameters and performance. Understanding the design-performance relationship becomes increasingly…

Graphics · Computer Science 2024-08-28 Samuel Silverman , Kelsey L. Snapp , Keith A. Brown , Emily Whiting

Parser-based log compression, which separates static templates from dynamic variables, is a promising approach to exploit the unique structure of log data. However, its performance on complex production logs is often unsatisfactory. This…

Software Engineering · Computer Science 2026-01-23 Siyu Yu , Yifan Wu , Junjielong Xu , Ying Fu , Ning Wang , Maoyin Liu , Pancheng Jiang , Xiang Zhang , Tong Jia , Pinjia He , Ying Li

We present a full-spectrum machine learning framework for refractive index sensing using simulated absorption spectra from meta-grating structures composed of titanium or silicon nanorods under TE and TM polarizations. Linear regression was…