Article
Computer Science, Theory & Methods
Mehmet Yamac, Mete Ahishali, Nikolaos Passalis, Jenni Raitoharju, Bulent Sankur, Moncef Gabbouj
Summary: Recent advances in intelligent surveillance systems have brought about a new era of smart monitoring in various fields, but also raised privacy concerns. A proposed data encryption method based on Compressive Sensing can obfuscate sensitive parts of documents selectively and provide different levels of reconstruction quality for users of different classes.
IEEE TRANSACTIONS ON INFORMATION FORENSICS AND SECURITY
(2021)
Article
Computer Science, Artificial Intelligence
Jian-Sheng Wu, Jun-Xiao Gong, Jing-Xin Liu, Weidong Min
Summary: This paper proposes a multi-level correlation learning method for unsupervised feature selection in multi-view data, which takes into account both the global topological consistency and the local geometric consistency, and outperforms other methods according to extensive experiments.
KNOWLEDGE-BASED SYSTEMS
(2023)
Article
Engineering, Mechanical
Xinyu Jia, Costas Papadimitriou
Summary: A hierarchical Bayesian learning framework is proposed for multi-level modeling in structural dynamics, which can effectively quantify uncertainties at different modeling levels and propagate them through the system.
MECHANICAL SYSTEMS AND SIGNAL PROCESSING
(2022)
Article
Chemistry, Analytical
O. Rodionova, A. Pomerantsev
Summary: This research presents a multi-block classification method based on the Data Driven Soft Independent Modeling of Class Analogy (DDSIMCA). A high-level data fusion approach is used to jointly analyze data collected from different analytical instruments. The proposed fusion technique is simple and straightforward, using a Cumulative Analytical Signal to combine the outcomes of individual classification models. Any number of blocks can be combined. Despite the complexity of the high-level fusion model, the analysis of partial distances allows for a meaningful relationship between classification results, individual samples, and specific tools. Two real-world examples demonstrate the applicability of the multi-block algorithm and its consistency with its predecessor, conventional DD-SIMCA.
ANALYTICA CHIMICA ACTA
(2023)
Article
Engineering, Electrical & Electronic
Penghai Li, Juanjuan Huang, Mingji Li, Hongji Li
Summary: In this study, PDMS filled with copper sulphate crystals, TiO2 nanoparticles, and carbon nanotubes was used as a flexible matrix to fabricate semi-dry multi-claws and 19-channel electrodes for EEG recording. These flexible electrodes showed good adhesion and reduced contact resistance, resulting in accurate and stable EEG signal recording.
SENSORS AND ACTUATORS A-PHYSICAL
(2022)
Article
Physics, Applied
Wei-Heng Hsu, R. H. Victora
Summary: In heat-assisted shingled magnetic recording, rotating the read head to match the curvature of asymmetrically curved transitions can significantly improve user density. With optimized rotation angle, the user areal density reaches 6.2 Tb/in(2), exceeding previous projections by more than 30%.
APPLIED PHYSICS LETTERS
(2021)
Article
Materials Science, Multidisciplinary
Chengcheng Zhang, Mingji Li, Xiuwei Xuan, Baozeng Zhou, Penghai Li, Hongji Li
Summary: Nitrogen-doped graphene microtubes synthesized by chemical vapor deposition have the potential to record high-density electroencephalography (EEG) signals. Microtubes with an N-content of 2.22% show low scalp-contact resistance and high signal-to-noise ratio of EEG signals. An EEG sensor with 72 optimized nitrogen-doped graphene microtubes is assembled to easily record spontaneous and visually evoked EEG signals. The sensor is convenient to wear and can identify high-density EEG signals, making it suitable for both peripheral fine control of motion imagination and clinical diagnosis of functional disorders in various brain regions, thereby promoting the development of healthcare electronics.
ADVANCED MATERIALS TECHNOLOGIES
(2023)
Article
Chemistry, Analytical
Lifeng Yin, Yingfeng Wang, Huayue Chen, Wu Deng
Summary: This paper improves the density peak clustering algorithm to achieve better clustering of multi-density data. It uses the K-nearest neighbor idea to select parameters and find the global bifurcation point to divide data with different densities. It also automatically determines the cluster center and the number of cluster centers by calculating the average value of the gamma height difference and finding the largest discontinuity point through two screenings. The clustering results are further improved and integrated using cluster fusion rules.
Article
Engineering, Electrical & Electronic
Seungwook Yoon, Euiseok Hwang
Summary: This study proposes a novel joint multi-track multi-level (MTML) read channel signal processing scheme to enhance data transfer rate in array-reader-based interlaced magnetic recording (ARIMR). Numerical evaluations using a micro-pixelated magnetic channel model show improvements in the cross-track profile of bit error rate with the proposed MTML-ARIMR approach for dual-reader and triple-track readback configurations.
IEEE TRANSACTIONS ON MAGNETICS
(2021)
Article
Chemistry, Analytical
Luis Pelaez Murciego, Abiodun Komolafe, Nikola Perinka, Helga Nunes-Matos, Katja Junker, Ander Garcia Diez, Senentxu Lanceros-Mendez, Russel Torah, Erika G. Spaich, Strahinja Dosen
Summary: In this study, a novel dry electrode called TEX was introduced as a practical solution for high-density electromyography. Compared to traditional electrodes, TEX showed similar signal quality and functional application, while being more convenient for practical use.
Article
Computer Science, Artificial Intelligence
Mingchen Li, Di Zhuang, J. Morris Chang
Summary: With the development of machine learning and data science, data sharing is common to avoid data scarcity, but it can lead to privacy leakage. A reliable solution is to use private synthetic datasets that preserve statistical information. In this paper, we propose MC-GEN, a privacy-preserving synthetic data generation method for machine learning classification tasks. Experimental evaluation shows that MC-GEN achieves significant effectiveness under certain privacy guarantees and outperforms other methods in utility.
KNOWLEDGE-BASED SYSTEMS
(2023)
Article
Engineering, Multidisciplinary
Tim Fabian Korzeniowski, Kerstin Weinberg
Summary: The data-driven finite element analysis proposed by Kirchdoerfer and Ortiz (2016) incorporates material data directly into the optimization problem, which increases computational costs with increasing dimensions and data density. A multi-level method is introduced to reduce costs by starting with a coarser initial subset of data and successively refining it to find an adequate solution using only a fraction of the total data set. This method significantly reduces computational costs, enabling complex data-driven finite element computations.
COMPUTER METHODS IN APPLIED MECHANICS AND ENGINEERING
(2021)
Article
Engineering, Electrical & Electronic
Wenyuan Zhong, Huaxiong Li, Qinghua Hu, Yang Gao, Chunlin Chen
Summary: Deep learning methods have attracted much attention for image classification recently. However, for small-scale data, these methods may not yield optimal results due to the lack of training samples. Sparse representation is efficient and interpretable, but its precision is not competitive. To address this issue, we propose a Multi-Level Cascade Sparse Representation (ML-CSR) learning method that combines the advantages of both deep learning and sparse representation. ML-CSR utilizes a pyramid structure and two core modules, Error-To-Feature (ETF) and Generate-Adaptive-Weight (GAW), to improve precision. Experiments on face databases demonstrate the effectiveness of ML-CSR, and ablation experiments further confirm the benefits of the proposed pyramid structure, ETF, and GAW modules. The code is available at https://github.com/Zhongwenyuan98/ML-CSR.
IEEE TRANSACTIONS ON CIRCUITS AND SYSTEMS FOR VIDEO TECHNOLOGY
(2023)
Article
Remote Sensing
Jiajia Yuan, Jinyun Guo, Chengcheng Zhu, Cheinway Hwang, Daocheng Yu, Mingzhi Sun, Dapeng Mu
Summary: Sea level change varies across different ocean regions, with a new high-resolution model being developed to show detailed patterns of sea level change in the China seas. The study detected a sea level change dipole south of Japan and identified a zonal sea level trend pattern in specific regions. Furthermore, the rate of sea level rise was found to be higher in the nearshore zone compared to the open ocean, highlighting the importance of this finding for coastal protection.
INTERNATIONAL JOURNAL OF APPLIED EARTH OBSERVATION AND GEOINFORMATION
(2021)
Article
Environmental Sciences
Xiaolin Feng, Sirui Tian, Stanley Ebhohimhen Abhadiomhen, Zhiyong Xu, Xiangjun Shen, Jing Wang, Xinming Zhang, Wenyun Gao, Hong Zhang, Chao Wang
Summary: In this paper, a new denoising method called EPLRR-RSID is proposed, which focuses on edge preservation to improve the image quality of details. By considering the low-rank residues as a combination of useful edges and noisy components, multi-level knowledge is designed to further distinguish the edge part and the noise part. A manifold learning framework is introduced to better obtain the edge information and precisely preserve the edge part. Experimental results show that EPLRR-RSID has superior advantages over state-of-the-art approaches, with high mean edge protect index values and the best values in the no-reference index BRISQUE, indicating the improvement of image quality through edge preserving.
Article
Chemistry, Multidisciplinary
Keith M. Carroll, Armin W. Knoll, Heiko Wolf, Urs Duerig
Article
Multidisciplinary Sciences
Michael J. Skaug, Christian Schwemmer, Stefan Fringes, Colin D. Rawlings, Armin W. Knoll
Article
Nanoscience & Nanotechnology
Stefan Fringes, Felix Holzner, Armin W. Knoll
BEILSTEIN JOURNAL OF NANOTECHNOLOGY
(2018)
Article
Nanoscience & Nanotechnology
Colin Rawlings, Yu Kyoung Ryu, Matthieu Ruegg, Nolan Lassaline, Christian Schwemmer, Urs Duerig, Armin W. Knoll, Zahid Durrani, Chen Wang, Dixi Liu, Mervyn E. Jones
Article
Physics, Multidisciplinary
Christian Schwemmer, Stefan Fringes, Urs Duerig, Yu Kyoung Ryu, Armin W. Knoll
PHYSICAL REVIEW LETTERS
(2018)
Article
Chemistry, Multidisciplinary
Jean-Francois de Marneffe, Boon Teik Chan, Martin Spieser, Guy Vereecke, Sergej Naumov, Danielle Vanhaeren, Heiko Wolf, Armin W. Knoll
Article
Physics, Applied
Edoardo Albisetti, Annalisa Calo, Martin Spieser, Armin W. Knoll, Elisa Riedo, Daniela Petti
APPLIED PHYSICS LETTERS
(2018)
Article
Chemistry, Multidisciplinary
Stefan Fringes, C. Schwemmer, Colin D. Rawlings, Armin W. Knoll
Article
Chemistry, Multidisciplinary
Xia Liu, Amit Kumar Sachan, Samuel Tobias Howell, Ana Conde-Rubio, Armin W. Knoll, Giovanni Boero, Renato Zenobi, Jurgen Brugger
Article
Physics, Applied
Philippe Nicollier, Christian Schwemmer, Francesca Ruggeri, Daniel Widmer, Xiaoyu Ma, Armin W. Knoll
Summary: The nanoparticle size-separation device is based on a nanofluidic rocking Brownian motor, utilizing a ratchet-shaped electrostatic particle potential to separate particle suspensions into multiple subpopulations by exploiting the sharp drop of particle current with increasing barrier heights. The separation mechanism is governed by the energy landscape under forward tilt of the ratchet, where the applied force is the only tunable parameter to increase the separation resolution. Experimental conditions of 3.5 V applied voltage and 20 s sorting predict a separation resolution of approximately 2 nm, supported by experimental data for separating spherical gold particles of nominal diameters of 80 and 100 nm.
PHYSICAL REVIEW APPLIED
(2021)
Article
Chemistry, Multidisciplinary
Nolan Lassaline, Deepankur Thureja, Thibault Chervy, Daniel Petter, Puneet A. Murthy, Armin W. Knoll, David J. Norris
Summary: Atomically smooth hexagonal boron nitride (hBN) flakes have revolutionized two-dimensional (2D) optoelectronics by providing crucial components for electronic and photonic devices, with the potential for enhanced control over the flow of photons, electrons, and excitons through the demonstration of freeform hBN landscapes. By combining thermal scanning-probe lithography and reactive-ion etching, researchers have been able to fabricate previously unattainable flake structures, such as photonic microelements and Fourier surfaces for electrons, creating opportunities for advanced technologies such as 2D polaritonics, twistronics, quantum materials, and deep-ultraviolet devices.
Article
Chemistry, Multidisciplinary
Francesca Ruggeri, Christian Schwemmer, Mirko Stauffer, Philippe M. Nicollier, Jacqueline Figueiredo da Silva, Patrick D. Bosshart, Kirstin Kochems, Dimitrios Fotiadis, Armin Knoll, Heiko Wolf
Summary: This study demonstrates that isolated purple membrane patches can be transported and positioned at predefined locations in nanofluidic confinement, with control over their orientation at the target sites. The transport is achieved through a rocking Brownian motor scheme, while the controlled deposition of the membranes is realized by engineering the surface potential of a fluid-filled nanofluidic slit. This controlled manipulation of purple membrane patches provides a new pathway for integrating biological or other delicate supramolecular structures into top-down-fabricated patterns.
ADVANCED MATERIALS INTERFACES
(2022)
Article
Nanoscience & Nanotechnology
L. Forrer, A. Kamber, A. Knoll, M. Poggio, F. R. Braakman
Summary: We have developed a process to fabricate nanoscale metallic gate electrodes on scanning probe cantilevers, including on the irregular surface of protruding cantilever tips. Gate definition is achieved through a lift-off process and an etching process. This method allows the patterning of nanoscale devices on fragile scanning probes, extending their functionality as sensors.
Proceedings Paper
Engineering, Electrical & Electronic
Heiko Wolf, Yu K. Ryu Cho, Siegfried Karg, Philipp Mensch, Christian Schwemmer, Armin Knoll, Martin Spieser, Samuel Bisig, Colin Rawlings, Philip Paul, Felix Holzner, Urs Duerig
2019 PAN PACIFIC MICROELECTRONICS SYMPOSIUM (PAN PACIFIC)
(2019)
