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5th IEEE International Conference on Flexible and Printable Sensors and Systems, FLEPS 2023

作者： Ali, Shawkat Khan, Arshad Bermak, Amine College of Science and Engineering Hamad Bin Khalifa University Division of Information and Computing Technology Doha Qatar Computer Electrical and Mathematical Science and Engineering Division Thuwal23955-6900 Saudi Arabia

ISBN: (纸本)9781665457330

In this research, a real-time healthcare and monitoring wireless system is developed to monitor vital signs of a wearer i.e., temperature, respiration rate, and wetting volume on a smartphone. The smart diaper consists of two main units, a detachable electronic module and a disposable printed biosensors patch deployed on a commercial diaper. Custom sensors array was designed and fabricated in a single patch through printed electronics technology by using biocompatible materials on a thermal transfer substrate. The sensors patch was designed in such a way to accurately collect the vital signs data by placing each sensor at appropriate site. Individual sensors were characterized for their electrical and mechanical properties. The overall system was tested, and data was wirelessly transmitted to a smartphone via Bluetooth. The main purpose of the proposed smart diaper is to minimize the effort of caregiver and avoid infection, rashes, and discomfort. We believe this work will open a new window for the printed electronics systems for special needs, elderly, and infant healthcare. © 2023 IEEE.

关键词： Wetting

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Automatic classification of normal/AD brain MRI slices using whale-algorithm optimized hybrid image features

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Journal of Ambient Intelligence and Humanized Computing 2023年第10期14卷 14237-14248页

作者： Kadry, Seifedine Jessy, V. Elizabeth Rajinikanth, Venkatesan Crespo, Rubén González Department of Applied Data Science Noroff University College Kristiansand4612 Norway College of Engineering and Information Technology Ajman University Ajman United Arab Emirates Department of Electrical and Computer Engineering Lebanese American University Byblos Lebanon Division of Research and Innovation Department of Computer Science and Engineering Saveetha School of Engineering SIMATS Tamil Nadu Chennai602105 India Department of Computer Science and Technology Universidad Internacional de La Rioja La Rioja Logroño Spain

In recent years, the prevalence of Age-Related Illnesses (ARL) has been increasing among older individuals, and early recognition and treatment will result in better living conditions. It is well known that Alzheimer's Disease (AD) is among the ARD, and severe cases may result in dementia as well. It is the purpose of this study to propose a technique for distinguishing normal/AD brain MRI slices with improved accuracy utilizing the T2-modality. This scheme consists following phases: (i) Brain MRI collection and preprocessing, (ii) Deep feature extraction with the chosen scheme, (iii) Handcrafted feature extraction, (iv) Whale Algorithm (WA) based feature reduction and serial integration, and (v) binary classification using five-fold cross-validation. A total of 2000 MRI slices (1000 normal and 1000 AD class) are examined during this task using images collected from Alzheimer’s Disease Neuroimaging Initiative (ADNI). This study confirms that the proposed scheme provides a classification accuracy of > 98% when applied with the K-Nearest Classifier. © 2023, The Author(s), under exclusive licence to Springer-Verlag GmbH Germany, part of Springer Nature.

关键词： Feature extraction

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StackAMP: Stacking-Based Ensemble Classifier for Antimicrobial Peptide Identification

IEEE Transactions on Artificial Intelligence

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IEEE Transactions on Artificial Intelligence 2024年第11期5卷 5666-5675页

作者： Karim, Tasmin Shaon, Md. Shazzad Hossain Ali, Md. Mamun Ahmed, Kawsar Bui, Francis M. Chen, Li Department of Computer Science and Engineering Birulia Dhaka Savar1216 Bangladesh University of Saskatchewan Division of Biomedical Engineering SaskatoonSKS7N 5A9 Canada University of Saskatchewan Department of Electrical and Computer Engineering SaskatoonSKS7N 5A9 Canada Health Informatics Research Laboratory Department of Computer Science and Engineering Birulia Dhaka Savar1216 Bangladesh Mawlana Bhashani Science and Technology University Group of Bio-photomati Information and Communication Technology Tangail Santosh1902 Bangladesh

Antimicrobial peptides (AMPs) play a vital role in the immune defence systems of various organisms and have garnered significant attention for their potential applications in biotechnology and medicine. There are several approaches to identifying AMPs including clinical isolation and characterization, functional genomics, microbiology techniques, and others. However, these methods are mostly expensive, time-consuming, and require well-equipped labs. To overcome these challenges, machine learning models are a potential solution due to their robustness and high predictive capability with less time and cost. In this study, we explored the efficacy of stacking-based ensemble machine-learning techniques to identify AMPs with higher accuracy and precision. Five distinct feature extraction methods, namely amino acid composition, dipeptide composition, moran autocorrelation, geary autocorrelation, and pseudoamino acid composition, were employed to represent the sequence characteristics of peptides. To build robust predictive models, different traditional machine learning algorithms were applied. Additionally, we developed a novel stacking classifier, aptly named StackAMP, to harness the collective power of these algorithms. Our results demonstrated the exceptional performance of the proposed StackAMP ensemble method in AMP identification, achieving an accuracy of 99.97%, 99.93% specificity, and 100% sensitivity. This high accuracy underscores the effectiveness of our approach, which has promising outcomes for the rapid and accurate identification of AMPs in various biological contexts. This study not only contributes to the growing body of knowledge in the field of AMP recognition but also offers a practical tool with potential applications in drug discovery, biotechnology, and disease prevention. © 2024 IEEE.

关键词： Amino acids

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Stabilization of Optical Wireless Power Transmission System using Spatial Light Modulator 23

Stabilization of Optical Wireless Power Transmission System ...

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Laser Beam Shaping XXIII 2023

作者： Thu, Khin Myo Maruyama, Takeo Division of Electrical Engineering and Computer Science Kanazawa Univ. Kakuma-machi Ishikawa Kanazawa920-1192 Japan

ISBN: (纸本)9781510665484

Optical Wireless Power Transmission (OWPT) system, using beam shaping, is a promising technology that involves a transmitter side using a laser and a receiver side using solar cells to transfer power wirelessly over long distances. The system faces a challenge of potential mismatch between both sides, which can lead to low efficiency of power transfer. The objective of this research is to improve the mismatch between the beam shape of a semiconductor laser light source and the shape of a photodetector solar cell. The shape of a typical solar cell is rectangular, which does not match the circular beam shape of the light source, resulting in lower power conversion efficiency. To address this, methods have been proposed to beam shape into a rectangle using Fresnel lenses or rectangular core optical fibers. However, the distance from the solar cell and the rotation of the solar cell itself change the size of the beam, resulting in a trapezoidal image as seen from the light source. In this study, we report the results of an evaluation of the change in efficiency with respect to changes in the object, using a spatial light modulator (SLM) that can arbitrarily shape the light beam. Specifically, we evaluate how adjusting the shape of a circular beam onto a solar cell target using the SLM leads to a decrease in photocurrent, and how recognizing an object's beam shape in real-time to control a camera using machine learning can predict object shape for error suppression compared to linear prediction. © 2023 SPIE.

关键词： Light modulators

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A 12-Slot 10-Pole Induction Motor with Wave Winding Rotor 11

A 12-Slot 10-Pole Induction Motor with Wave Winding Rotor

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11th International Conference on Power Electronics - ECCE Asia, ICPE 2023-ECCE Asia

作者： Yokoi, Y. Nagasaki University Division of Electrical Engineering and Computer Science Japan Nagasaki University Organization for Marine Science and Technology Japan

ISBN: (纸本)9788957083505

In this paper, we investigate the effect of rotor winding configurations on driving an induction motor (IM) with a 12-slot 10-pole concentrated winding configuration of the stator, which is one of the fractional slot concentrated winding (FSCW) configurations. For the stator FSCW configuration, conventional rotor squirrel-cage windings are inadequate for sufficient drive torque. To address the issue, we employ rotor wave windings for the stator FSCW configuration to trap driving harmonic and completely eliminate the effects of other dominant harmonics in the stator rotating magnetic field (RMF). The theoretical and numerical analyses confirm the effectiveness of the rotor wave windings in filtering out undesirable stator RMF harmonics and improving the performance of the IM. © 2023 The Korean Institute of Power Electronics.

关键词： Stators

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ECDSA-based tamper detection in medical data using a watermarking technique

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International Journal of Cognitive Computing in engineering 2024年第1期5卷 78-87页

作者： Ch, Rupa Vivek K, Naga Srivastava, Gautam Reddy Gadekallu Department CSE VR Siddhartha Engineering College Andhra Pradesh Vijayawada520 007 India Dept of Math and Computer Science Brandon University MB Canada Dept. of Computer Science and Math Lebanese American University Beirut1102 Lebanon Centre of Research Impact and Outcome Chitkara University Institute of Engineering and Technology Chitkara Punjab Rajpura140401 India Lebanese American University Department of Electrical and Computer Engineering Byblos Lebanon Lovely Professional University Division of Research and development Phagwara India Jiaxing University College of Information Science and Engineering Jiaxing China

Telemedicine is a form of healthcare delivery that employs communication technology to provide medical care to patients remotely. The use of telemedicine has seen a significant increase in recent years, presenting challenges such as patient privacy, data security, the need for reliable communication technology, and the potential for misdiagnosis without a physical examination. Digital Watermarking can assist in addressing such issues by incorporating a unique identifier into an image that can be used to authenticate its validity. To tackle these issues, this study proposes a robust digital watermarking approach tailored to brain medical images, combining hashing, the Elliptic Curve Digital Signature Algorithm (ECDSA), and the Integer Wavelet Transform-Discrete Cosine Transform (IWT-DCT). This method utilizes the Secure Hash Algorithm (SHA-256) to first segment the brain's Region of Interest (RoI). Subsequently, the hashed RoI, along with an ECDSA signature, is embedded into the high-frequency sub-bands of the medical image using IWT-DCT. The embedding process strategically alters the coefficients of the high-frequency sub-bands to accommodate the signature while minimizing perceptual distortion. The technique leverages the robustness of transformed-domain image watermarking techniques against various attacks and combines it with SHA-256 for integrity and ECDSA for authentication purposes. The results demonstrate that the suggested approach is robust to a variety of image processing techniques, including noise addition, filtering, and compression while maintaining high levels of imperceptibility. Key metrics such as the Peak Signal-to-Noise Ratio (PSNR), Mean Squared Error (MSE), and Structural Similarity Index (SSIM) were used to evaluate performance. The suggested strategy exhibited a substantial improvement over existing methods. The PSNR increased to 68.67, indicating higher image quality, while the MSE reduced to 0.96, demonstrating closer pixel values to the or

关键词： Mean square error

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Experimental observation of coherent-perfect-absorber and laser points in anti-PT symmetry

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Physical Review A 2024年第3期110卷 033504页

作者： Minye Yang Qi Zhong Zhilu Ye Şahin K. Özdemir Mohamed Farhat Ramy El-Ganainy Pai-Yen Chen State Key Laboratory for Manufacturing Systems Engineering School of Electronic Science and Engineering Department of Electrical and Computer Engineering Department of Engineering Science and Mechanics The Materials Research Institute Computer Electrical and Mathematical Science and Engineering Division Department of Physics Henes Center for Quantum Phenomena

The coexistence of coherent perfect absorber and laser or amplifier (CPAL) point is a peculiar spectral singularity associated with the scattering matrices of non-Hermitian systems. While the potential of CPAL systems for sensing application has been highlighted recently, the extreme sensitivity of parity-time (PT)-symmetric CPAL devices to the input signal deviations has so far impeded their practical utilization. Here we explore a strategy for implementing CPAL circuits by exploiting another type of non-Hermitian symmetry, namely anti-PT (APT) symmetry. We demonstrate that the condition for building CPAL in our proposed APT-symmetric electronic circuits additionally requires parity symmetry, which simplifies the circuit design and implementation. Additionally, we show that this newly proposed structure is 1.85 times more robust compared to previous CPAL devices studied in the literature.

关键词： Noise Quantum sensing Non-Hermitian systems PT-symmetry

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Design and analysis of SiN optical waveguide for 2D beam steering 23

Design and analysis of SiN optical waveguide for 2D beam ste...

引用

Laser Beam Shaping XXIII 2023

作者： Zhou, Z. Shimeno, Y. Kawai, S. Maruyama, T. Division of Electrical Engineering and Computer Science Kanazawa Univ. Kakuma-machi Ishikawa Kanazawa920-1192 Japan

ISBN: (纸本)9781510665484

This paper presents a method for achieving 2D beam steering using 16-phased array grating couplers through FDTD simulation. The method begins by designing a single grating coupler with a silicon nitride material (depth = 0.15 um, width = 0.2 um, grating pitch = 0.34 um) to achieve 1D beam steering of around 7.6°by changing the input wavelength from 500 nm to 550 nm and changing the TE or TM mode source. The grating pitch of 0.34 um was selected because the input wavelength at 532 nm through the NV center can measure the magnitude field, resulting in a reflected angle of 0°. By changing the input wavelength, positive and negative beam steering directions can be achieved. Subsequently, a total of 16 phased arrays were established, and a multimode interferometer (MMI) was used to split the input beam into 16 grating couplers. With the 16 waveguides, the phase can be changed from 0 to π/8, allowing the 2D steering angle to be altered from 0°to 1.72°. The method was validated using 3D simulations to ensure that the results match those obtained through 2D simulation. © 2023 SPIE.

关键词： Silicon nitride

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Koopman-based Deep Learning for Nonlinear System Estimation

Koopman-based Deep Learning for Nonlinear System Estimation

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IEEE Conference on Decision and Control

作者： Zexin Sun Mingyu Chen John Baillieul Division of Systems Engineering Boston University Department of Electrical and Computer Engineering Boston University Departments of Mechanical Engineering Electrical and Computer Engineering Division of Systems Engineering Boston University Boston MA

ISBN: (数字)9798350316339

ISBN: (纸本)9798350316346

Nonlinear differential equations are encountered as models of fluid flow, spiking neurons, and many other systems of interest in the real world. Common features of these systems are that their behaviors are difficult to describe exactly and invariably unmodeled dynamics present challenges in making precise predictions. In this paper, we present a novel data-driven linear estimator based on Koopman operator theory to extract meaningful finite-dimensional representations of complex non-linear systems. The Koopman model is used together with deep reinforcement networks that learn the optimal stepwise actions to predict future states of nonlinear systems. Our estimator is also adaptive to a diffeomorphic transformation of the estimated nonlinear system, which enables it to compute optimal state estimates without re-learning.

关键词： Neurons Estimation Stochastic processes Reinforcement learning Fluid flow Predictive models Feature extraction Mathematical models Nonlinear dynamical systems Oscillators

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End-to-End Learning of Beam Probing and RSSI-Based Multi-User Hybrid Precoding Design

End-to-End Learning of Beam Probing and RSSI-Based Multi-Use...

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2024 IEEE Global Communications Conference, GLOBECOM 2024

作者： Abdallah, Asmaa Celik, Abdulkadir Alkhateeb, Ahmed Eltawil, Ahmed M. Division Thuwal23955-6900 Saudi Arabia Arizona State University Department of Electrical Computer and Energy Engineering TempeAZ85281 United States

ISBN: (纸本)9798350351255

This paper presents an end-to-end (E2E) autoencoder learning framework that relies on unsupervised deep learning for the joint design of millimeter wave (mmWave) probing beams and hybrid precoding matrices in multi-user communication systems. Our model utilizes prior channel observations to achieve two main objectives: designing a compact set of probing beams and predicting off-grid radio frequency (RF) beamforming vectors. The E2E learning framework optimizes probing beams in an unsupervised manner, concentrating sensing power on promising spatial directions based on the environment. To this aim, we develop a neural network architecture respecting RF chain constraints and model received signal strength (RSS) using complex-valued convolutional layers. The autoencoder is trained to directly produce RF beamforming vectors for hybrid architectures based on projected RSS indicators (RSSIs). Once RF beamforming vectors for multi-users are predicted, baseband digital precoders are designed by accounting for multi-user interference. The autoencoder neural network is trained E2E in an unsupervised manner with a customized loss function aimed at maximizing RSS. In a system with 64 antennas, 4 RF chains, and 4 users, our approach requires only 8 probing beams to design RF beamforming vectors, compared to the conventional predefined codebooks with 64 or 128 beams. © 2024 IEEE.

关键词： Vectors

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