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SSRN 2024年

作者： Bozyel, Ibrahim Fleming, Derek Won-Jun, Kim Rosen, Peter F. Gelston, Suzanne Ozdemir, Dilara Ay, Suat U. Patel, Robin Beyenal, Haluk The Gene and Linda Voiland School of Chemical Engineering and Bioengineering Washington State University PullmanWA United States Division of Clinical Microbiology Mayo Clinic RochesterMN United States Department of Electrical and Computer Engineering Worcester Polytechnic Institute WorcesterMA United States Division of Infectious Diseases Mayo Clinic RochesterMN United States The Gene and Linda Voiland School of Chemical Engineering and Bioengineering Washington State University 1505 Stadium Way Room 105 P.O. Box 646515 PullmanWA99164-6515 United States

Electrochemical bandages (e-bandages) can be applied to biofilm-infected wounds to generate reactive oxygen species, such as hypochlorous acid (HOCl) or hydrogen peroxide (H2O2). The e-bandage-generated HOCl or H2O2 kills biofilms in vitro and in infected wounds on mice. The HOCl-generating e-bandage is more active against biofilms in vitro, although this distinction is less apparent in vivo. The H2O2-generating e-bandage, more than the HOCl-generating e-bandage, is associated with improved healing of infected wounds. A strategy in which H2O2 and HOCl are generated alternately—for dual action—was explored. The goal was to develop a programmable multimodal wearable potentiostat (PMWP) that could be programmed to generate HOCl or H2O2, as needed. An ultralow-power microcontroller unit managed operation of the PMWP. The system was operated with a 260‑mAh capacity coin battery and weighed 4.6 grams, making it suitable for small animal experiments or human use. The overall cost of a single wearable potentiostat was $6.50 (USD). The device was verified using established electrochemical systems and functioned comparably to a commercial potentiostat. To determine antimicrobial effectiveness, PMWP-controlled e-bandages were tested against clinical isolates of four prevalent chronic wound bacterial pathogens, methicillin-resistant Staphylococcus aureus (MRSA), Pseudomonas aeruginosa, Acinetobacter baumannii, and Enterococcus faecium, and one fungal pathogen of emerging concern, Candida auris. PMWP-controlled e-bandages exhibited broad-spectrum activity against biofilms of all study isolates tested when programmed to deliver HOCl followed by H2O2. These results show that the PMWP operates effectively and is suitable for animal testing. © 2024, The Authors. All rights reserved.

关键词： Biofilms

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Blind image denoising and inpainting using robust Hadamard autoencoders

arXiv

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arXiv 2021年

作者： Karkare, Rasika Paffenroth, Randy Mahindre, Gunjan Data Science Worcester Polytechnic Institute WorcesterMA01609 United States Mathematical Sciences Comp. Science and Data Science Worcester Polytechnic Institute WorcesterMA01609 United States Electrical and Computer Engineering Colorado State University Fort CollinsCO80523 United States

In this paper, we demonstrate how deep autoencoders can be generalized to the case of inpainting and denoising, even when no clean training data is available. In particular, we show how neural networks can be trained to perform all of these tasks simultaneously. While, deep autoencoders implemented by way of neural networks have demonstrated potential for denoising and anomaly detection, standard autoencoders have the drawback that they require access to clean data for training. However, recent work in Robust Deep Autoencoders (RDAEs) shows how autoencoders can be trained to eliminate outliers and noise in a dataset without access to any clean training data. Inspired by this work, we extend RDAEs to the case where data are not only noisy and have outliers, but also only partially observed. Moreover, the dataset we train the neural network on has the properties that all entries have noise, some entries are corrupted by large mistakes, and many entries are not even known. Given such an algorithm, many standard tasks, such as denoising, image inpainting, and unobserved entry imputation can all be accomplished simultaneously within the same framework. Herein we demonstrate these techniques on standard machine learning tasks, such as image inpainting and denoising for the MNIST and CIFAR10 datasets. However, these approaches are not only applicable to image processing problems, but also have wide ranging impacts on datasets arising from real-world problems, such as manufacturing and network processing, where noisy, partially observed data naturally arise. Copyright © 2021, The Authors. All rights reserved.

关键词： Anomaly detection

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Large-Scale Rate-Splitting Multiple Access in Uplink UAV Networks: Effective Secrecy Throughput Maximization Under Limited Feedback Channel

arXiv

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arXiv 2022年

作者： Bastami, Hamed Behroozi, Hamid Moradikia, Majid Abdelhadi, Ahmed Ngand, Derrick Wing Kwan Hanzo, Lajos The Department of Electrical Engineering Sharif University of Technology Tehran Iran Department of Data Science Worcester Polytechnic Institute WorcesterMA United States The Engineering Technology Department University of Houston United States The School of Electrical Engineering and Telecommunications University of New South Wales Sydney Australia The University of Southampton SouthamptonSO17 1BJ United Kingdom

Unmanned aerial vehicles (UAVs) are capable of improving the performance of next generation wireless systems. Specifically, UAVs can be exploited as aerial base-stations (UAV-BS) for supporting legitimate ground users in remote uncovered areas or in environments temporarily requiring high capacity. However, their communication performance is prone to both channel estimation errors and potential eavesdropping. Hence, we investigate the effective secrecy throughput of the UAV-aided uplink, in which rate-splitting multiple access (RSMA) is employed by each legitimate user for secure transmission under the scenario of massive access. To maximize the effective network secrecy throughput in the uplink, the transmission rate vs. power allocation relationship is formulated as a max-min optimization problem, relying on realistic imperfect channel state information (CSI) of both the legitimate users and of the potential eavesdroppers (Eves). We then propose a novel transformation of the associated probabilistic constraints for decoupling the variables, so that our design problem can be solved by alternatively activating the related block coordinate decent programming. In the model considered, each user transmits a superposition of two messages to a UAV-BS, each having different transmit power and the UAV-BS uses a successive interference cancellation (SIC) technique to decode the received messages. Given the non-convexity of the problem, it is decoupled into a pair of sub-problems. In particular, we derive a closed form expression for the optimal rate-splitting fraction of each user. Then, given the optimal rate-splitting fraction of each user, the ǫ-constrainted transmit power of each user is calculated by harnessing sequential parametric convex approximation (SPCA) programming. Finally, the optimal SIC order is determined by an exhaustive search method. Our simulation results confirm that the scheme conceived significantly improves the effective secrecy throughput compared

关键词： Channel state information

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Fluorescent Intensity and Lifetime Measurement of Platinum-Porphyrin Film for Determining the Sensitivity of Transcutaneous Oxygen Sensor

Fluorescent Intensity and Lifetime Measurement of Platinum-P...

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IEEE International Symposium on Circuits and Systems (ISCAS)

作者： Ian Costanzo Devdip Sen Binod Giri Nicholas Pratt Pratap Rao Ulkuhan Guler Department of Electrical and Computer Engineering Worcester Polytechnic Institute Worcester MA 01609 USA Department of Mechanical Engineering Worcester Polytechnic Institute Worcester MA 01609 USA

ISBN: (数字)9781728133201

ISBN: (纸本)9781728133218

In most optical-based oxygen sensors, fluorescent quenching is used as the sensing principle. Intensity and lifetime are two known measurement techniques that are employed to quantify the measured parameter. The lifetime measurement technique has superior features such as little or no sensitivity to changes in the optical path, degradation of the film or photo-bleaching. In this study, we conducted an experiment to analyze the performance of both the intensity and lifetime measurement techniques of a platinum-porphyrin fluorescent film, the sensing material, under different concentrations of oxygen. A prototype that deploys an analog front-end, a light emitting diode driver, and a power management block is implemented on a printed circuit board with commercial off-the-shelf components. The system resolves changes in oxygen pressure from 0.5 mmHg to 500 mmHg with a power consumption of 132 mW. This system could be potentially used to measure the concentration of oxygen diffused through the skin, also known as transcutaneous measurement of oxygen. These measurements are key to developing more sophisticated read-out circuits for reliable and sensitive medical purpose transcutaneous oxygen sensing.

关键词： Light emitting diodes Blood Lifetime estimation Oxygen Optical variables measurement Optical sensors

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LAT-UP: Exposing Layout-Level Analog Hardware Trojans Using Contactless Optical Probing

LAT-UP: Exposing Layout-Level Analog Hardware Trojans Using ...

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IEEE computer Society Annual Symposium on VLSI

作者： Sajjad Parvin Mehran Goli Thilo Krachenfels Shahin Tajik Jean-Pierre Seifert Frank Sill Torres Rolf Drechsler Institute of Computer Science University of Bremen Germany Cyber-Physical Systems DFKI GmbH Germany Chair of Security in Telecommunications Technische Universität Berlin Germany Department of Electrical and Computer Engineering Worcester Polytechnique Institute USA Fraunhofer SIT Germany German Aerospace Center Institute for the Protection of Maritime Infrastructures Germany

The insertion of a Hardware Trojan (HT) into a chip after the in-house layout design is outsourced to a chip manufacturer for fabrication is a major concern, especially for mission-critical applications. While several HT detection methods have been developed based on side-channel analysis and physical measurements to overcome this problem, there exist stealthy analog HTs, i.e., capacitive and dopant-level HTs, which have negligible or even zero overhead on the chip. Thus, these stealthy HTs cannot be detected using the aforementioned methods. In this work, we propose a novel analytical approach to detect these Layout-level Analog Trojans (LAT). Our proposed method uses an extension of Optical Probing (OP) for LAT detection, namely, the Laser Logic State Imaging (LLSI) technique. In principle, to detect LATs using LLSI, we only need the golden design and not a golden chip, which is not typically available. As we take advantage of LLSI to detect HTs, our approach is non-invasive, less costly, and scalable to larger designs. We report experimental results on a malicious RISC-V to demonstrate the effectiveness of our approach in detecting LATs.

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Analysis of Lesion Signals in Reduced-Dose Pediatric Tc-DMSA Renal SPECTImages with Deep Learning Denoising

Analysis of Lesion Signals in Reduced-Dose Pediatric Tc-DMSA...

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IEEE Symposium on Nuclear Science (NSS/MIC)

作者： W. Fu Y. Yang P.H. Pretorius N. Kwatra S.T. Treves F. Fahey M. A. King Electrical and Computer Engineering Department Illinois Institute of Technology Chicago Illinois United States of America Department of Radiology University of Massachusetts Medical School Worcester Massachusetts United States of America Boston Children’s Hospital Boston Massachusetts United States of America

Recently we demonstrated the feasibility of applying a 3D convolutional autoencoder (CAE) network for suppressing the elevated imaging noise in reduced-dose renal studies with single photon emission computed tomography (SPECT) using 99mTc-labelled dimercaptosuccinic acid (DMSA). Built on this prior study, in this work we further investigate how the denoising performance by the 3D CAE network can impact on image features that are important for detection of cortical defects in reduced-dose DMSA renal SPECT images. For this purpose we analyzed the image contrast of a set of small to medium sized focal cortical lesions identified in clinical acquisitions. The quantitative results demonstrate that the denoising network can better preserve the image contrast of defect signals compared to conventional Gaussian filtering. Moreover, the denoising network can also reduce the image variability by 18.35% and 21.03% in defect and normal cortical regions (p-value < 0.05), respectively, in reduced-dose studies.

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Deep Direct Discriminative Decoders for High-dimensional Time-series Data Analysis

arXiv

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arXiv 2022年

作者： Rezaei, Mohammad R. Popovic, Milos R. Lankarany, Milad Yousefi, Ali Eden, Uri T. Krembil Brain Institute University Health Network Toronto Canada KITE Research Institute Rehabilitation Institute University Health Network Toronto Canada Department of Physiology University of Toronto Toronto Canada WorcesterMA United States Institute of Biomedical Engineering University of Toronto Toronto Canada Department of Mathematics and Statistics Boston University BostonMA United States Department of Computer Science Worcester Polytechnic Institute WorcesterMA United States

The state-space models (SSMs) are widely utilized in the analysis of time-series data. SSMs rely on an explicit definition of the state and observation processes. Characterizing these processes is not always easy and becomes a modeling challenge when the dimension of observed data grows or the observed data distribution deviates from the normal distribution. Here, we propose a new formulation of SSM for high-dimensional observation processes. We call this solution the deep direct discriminative decoder (D4). The D4 brings deep neural networks’ expressiveness and scalability to the SSM formulation letting us build a novel solution that efficiently estimates the underlying state processes through high-dimensional observation signal. We demonstrate the D4 solutions in simulated and real data such as Lorenz attractors, Langevin dynamics, random walk dynamics, and rat hippocampus spiking neural data and show that the D4 performs better than traditional SSMs and RNNs The D4 can be applied to a broader class of time-series data where the connection between high-dimensional observation and the underlying latent process is hard to characterize. © 2022, CC BY.

关键词： Normal distribution

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Qualitative planning in imperfect information games with active sensing and reactive sensor attacks: Cost of unawareness

arXiv

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arXiv 2021年

作者： Kulkarni, Abhishek N. Han, Shuo Leslie, Nandi O. Kamhoua, Charles A. Fu, Jie The Robotics Engineering Program Dept. of Electrical and Computer Engineering Worcester Polytechnic Institute WorcesterMA01609 United States The Department of Electrical and Computer Engineering University of Illinois ChicagoIL60607 United States Raytheon Technologies U.S. Army Research Laboratory

We consider the probabilistic planning problem where the agent (called Player 1, or P1) can jointly plan the control actions and sensor queries in a sensor network and an attacker (called player 2, or P2) can carry out attacks on the sensors. We model such an adversarial interaction using a formal model-a reachability game with partially controllable observation functions. The main contribution of this paper is to assess the cost of P1's unawareness: Suppose P1 misinterprets the sensor failures as probabilistic node failures due to unreliable network communication, and P2 is aware of P1's misinterpretation in addition to her partial observability. Then, from which states can P2 carry out sensor attacks to ensure, with probability one, that P1 will not be able to complete her reachability task even though, due to misinterpretation, P1 believes that she can almost-surely achieve her task. We develop an algorithm to solve the almost-sure winning sensor-attack strategy given P1's observation-based strategy. Our attack analysis could be used for attack detection in wireless communication networks and the design of provably secured attack-aware sensor allocation in decision-theoretic models for cyber-physical systems. Copyright © 2021, The Authors. All rights reserved.

关键词： Formal methods

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Finding shortest and nearly shortest path nodes in large substantially incomplete networks

arXiv

引用

arXiv 2022年

作者： Kitsak, Maksim Ganin, Alexander Elmokashfi, Ahmed Cui, Hongzhu Eisenberg, Daniel A. Alderson, David L. Korkin, Dmitry Linkov, Igor Faculty of Electrical Engineering Mathematics and Computer Science Delft University of Technology Delft Netherlands Network Science Institute Northeastern University BostonMA02115 United States Department of Systems and Information Engineering University of Virginia CharlottesvilleVA22904 United States U.S. Army Engineer Research and Development Center Contractor Concord MA01742 United States Simula Metropolitan Center for Digital Engineering Oslo Norway Bioinformatics and Computational Biology Program Worcester Polytechnic Institute WorcesterMA01609 United States Institute for Genomic Medicine Columbia University Medical Center New YorkNY United States Operations Research Department Naval Postgraduate School MontereyCA93943 United States Data Science Program Worcester Polytechnic Institute WorcesterMA01609 United States Computer Science Department Worcester Polytechnic Institute WorcesterMA01609 United States U.S. Army Engineer Research and Development Center Environmental Laboratory Concord MA01742 United States

Dynamic processes on networks, be it information transfer in the Internet, contagious spreading in a social network, or neural signaling, take place along shortest or nearly shortest paths. Unfortunately, our maps of most large networks are substantially incomplete due to either the highly dynamic nature of networks, or high cost of network measurements, or both, rendering traditional path finding methods inefficient. We find that shortest paths in large real networks, such as the network of protein-protein interactions (PPI) and the Internet at the autonomous system (AS) level, are not random but are organized according to latent-geometric rules. If nodes of these networks are mapped to points in latent hyperbolic spaces, shortest paths in them align along geodesic curves connecting endpoint nodes. We find that this alignment is sufficiently strong to allow for the identification of shortest path nodes even in the case of substantially incomplete networks. We demonstrate the utility of latent-geometric path finding in problems of cellular pathway reconstruction and communication security. Copyright © 2022, The Authors. All rights reserved.

关键词： Proteins

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Aerial height prediction and refinement neural networks with semantic and geometric guidance

arXiv

引用

arXiv 2020年

作者： Elhousni, Mahdi Zhang, Ziming Huang, Xinming Department of Electrical and Computer Engineering Worcester Polytechnic Institute WorcesterMA01609 United States

Deep learning provides a powerful new approach to many computer vision tasks. Height prediction from aerial images is one of those tasks which benefited greatly from the deployment of deep learning, thus replacing traditional multi-view geometry techniques. This manuscript proposes a two-stage approach to solve this task, where the first stage is a multi-task neural network whose main branch is used to predict the height map resulting from a single RGB aerial input image, while being augmented with semantic and geometric information from two additional branches. The second stage is a refinement step, where a denoising autoencoder is used to correct some errors in the first stage prediction results, producing a more accurate height map. Experiments on two publicly available datasets show that the proposed method is able to outperform state-of-the-art computer vision based and deep learning-based height prediction methods. Code is publicly available at: https://***/melhousni/DSMNet. Copyright © 2020, The Authors. All rights reserved.

关键词： Unmanned aerial vehicles (UAV)

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