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Enhancing schizophrenia diagnosis through deep learning: a resting-state fMRI approach

Neural Computing and Applications 2025年 1-33页

作者： Raeisi, Zahra Mehrnia, Mehri Ahmadi Lashaki, Reza Abedi Lomer, Fatemeh Department of Computer Science University of Fairleigh Dickinson Vancouver Campus Vancouver Canada Electrical and Computer Engineering Northwestern University Evanston United States Department of Computer Engineering Faculty of Electrical and Computer Engineering University of Tabriz Tabriz Iran Department of Computer Engineering Faculty of Electrical and Computer Engineering Islamic Azad University Miyaneh Branch Miyaneh Iran

Schizophrenia (SC) is a complex mental disorder with diverse symptoms that make diagnosis challenging. This study aims to enhance diagnostic accuracy for SC using deep learning techniques applied to resting-state functional MRI (rsfMRI) data, capturing both spatial and temporal features of brain activity. We introduced a novel slice-wise classification approach using convolutional neural networks (CNNs) to analyze brain activity from rsfMRI images. Preprocessing included normalization, noise reduction, and contrast enhancement. The study utilized data from 158 subjects, including 83 schizophrenia patients and 75 healthy controls. We combined CNN-extracted features with traditional machine learning models such as support vector machines (SVM), random forest (RF), and gradient boosting (GB) to boost classification performance. Transfer learning using pre-trained models like VGG16, ResNet50, and Xception was applied to leverage advanced feature extraction. Model performance was evaluated based on precision, accuracy, recall, and F1 score. The CNN-based approach achieved significant improvements in classification accuracy, with a peak accuracy of 98.67%. The hybrid models combining CNN features with SVM, RF, and GB achieved accuracies of 97.01%, 98.44%, and 98.84%, respectively. The CNN model alone achieved a precision of 0.9826, recall of 1.0, and F1 score of 0.9912. Pre-trained models also demonstrated high performance, with ResNet50 achieving an accuracy of 98.71%. Brain regions such as the frontal lobe (slices 5 and 9) and temporal lobe (slices 15 and 25) were identified as key areas with significant differences between schizophrenia patients and healthy controls. This study demonstrates the effectiveness of deep learning models, particularly CNNs and hybrid approaches with traditional machine learning models, in enhancing schizophrenia diagnosis using rsfMRI data. Identifying key brain regions provides insights into schizophrenia’s neurobiological underpinnings. Fu

关键词： Support vector machines

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Metaheuristic-Driven Two-Stage Ensemble Deep Learning for Lung/Colon Cancer Classification

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computers, Materials & Continua 2024年第9期80卷 3855-3880页

作者： Pouyan Razmjouei Elaheh Moharamkhani Mohamad Hasanvand Maryam Daneshfar Mohammad Shokouhifar Department of Electrical&Computer Engineering Valie-e-Asr University of RafsanjanKerman***Iran International Academic Relations Office(IRO) Computer Science DepartmentUniversity of HalabjaHalabja46018Iraq Department of Computer Engineering University of Mohaghegh ArdabiliArdabil***Iran Department of Biomedical Engineering Islamic Azad University of MashhadMashhad***Iran Department of Electrical&Computer Engineering Shahid Beheshti UniversityTehran***Iran

This study investigates the application of deep learning,ensemble learning,metaheuristic optimization,and image processing techniques for detecting lung and colon cancers,aiming to enhance treatment efficacy and improve survival *** introduce a metaheuristic-driven two-stage ensemble deep learning model for efficient lung/colon cancer *** diagnosis of lung and colon cancers is attempted using several unique indicators by different versions of deep Convolutional Neural Networks(CNNs)in feature extraction and model constructions,and utilizing the power of various Machine Learning(ML)algorithms for final ***,we consider different scenarios consisting of two-class colon cancer,three-class lung cancer,and fiveclass combined lung/colon cancer to conduct feature extraction using four *** extracted features are then integrated to create a comprehensive feature *** the next step,the optimization of the feature selection is conducted using a metaheuristic algorithm based on the Electric Eel Foraging Optimization(EEFO).This optimized feature subset is subsequently employed in various ML algorithms to determine the most effective ones through a rigorous evaluation *** top-performing algorithms are refined using the High-Performance Filter(HPF)and integrated into an ensemble learning framework employing weighted *** findings indicate that the proposed ensemble learning model significantly surpasses existing methods in classification accuracy across all datasets,achieving accuracies of 99.85%for the two-class,98.70%for the three-class,and 98.96%for the five-class datasets.

关键词： Lung cancer colon cancer feature selection electric eel foraging optimization deep learning ensemble learning

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Component library creation and pixel array generation with micromilled droplet microfluidics

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Microsystems & Nanoengineering 2025年第1期11卷 277-287页

作者： David McIntyre Diana Arguijo Kaede Kawata Douglas Densmore Biomedical Engineering Department Boston UniversityBostonMAUSA Biological Design Center Boston UniversityBostonMAUSA Electrical and Computer Engineering Department Boston UniversityBostonMAUSA

Droplet microfluidics enable high-throughput screening,sequencing,and formulation of biological and chemical systems at the *** devices are generally fabricated in a soft polymer such as polydimethylsiloxane(PDMS).However,developing design masks for PDMS devices can be a slow and expensive process,requiring an internal cleanroom facility or using an external ***,we present the first complete droplet-based component library using low-cost rapid prototyping and electrode *** fabrication method for droplet microfluidic devices costs less than$12 per device and a full design-build-test cycle can be completed within a *** microfluidic components for droplet generation,re-injection,picoinjection,anchoring,fluorescence sensing,and sorting were built and *** devices are biocompatible,low-cost,and *** show its ability to perform multistep workflows,these components were used to assemble droplet"pixel"arrays,where droplets were generated,sensed,sorted,and anchored onto a grid to produce images.

关键词： droplet microfluidics micromilled rapid prototyping electrode integrationthis soft polymer biocompatible component library pixel array

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Glare Mitigation for Enhanced Autonomous Vehicle Perception

IEEE Transactions on Intelligent Vehicles

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IEEE Transactions on Intelligent Vehicles 2024年第11期9卷 1-15页

作者： Alam, Muhammad Z. Kaleem, Zeeshan Kelouwani, Sousso Department of Computer science Brandon University Canada Department of Electrical and Computer Engineering COMSATS University Pakistan Department of Mechanical Engineering UQTR Canada

Vision sensors are versatile and can capture a wide range of visual cues, such as color, texture, shape, and depth. This versatility, along with the relatively inexpensive availability of machine vision cameras, played an important role in adopting vision-based environment perception systems in autonomous vehicles (AVs). However, vision-based perception systems can be easily affected by glare in the presence of a bright source of light, such as the sun or the headlights of the oncoming vehicle at night or simply by light reflecting off snow or ice-covered surfaces;scenarios encountered frequently during driving. In this paper, we investigate various glare reduction techniques, including the proposed saturated pixel-aware glare reduction technique for improved performance of the computer vision (CV) tasks employed by the perception layer of AVs. We evaluate these glare reduction methods based on various performance metrics of the CV algorithms used by the perception layer. Specifically, we considered object detection, object recognition, object tracking, depth estimation, and lane detection which are crucial for autonomous driving. The experimental findings validate the efficacy of the proposed glare reduction approach, showcasing enhanced performance across diverse perception tasks and remarkable resilience against varying levels of glare. IEEE

关键词： Cameras

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An electrical Impedance Imaging System Towards Edge Intelligence for Non-Destructive Testing of Concrete

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Tsinghua science and Technology 2024年第3期29卷 883-896页

作者： Abolfazl Roshanpanah Mahdi Abbasi Hani Attar Ayman Amer Mohammad R.Khosravi Ahmed A.Solyman Department of Electrical Engineering Islamic Azad UniversityScience and Research BranceTehran ***Iran Department of Computer Engineering Bu-Ali Sina UniversityHamedan ***Iran Department of Energy Engineering Zarqa UniversityZarqa 13110Jordan Department of Computer Engineering Persian Gulf UniversityBushehr ***Iran Department of Electrical and Electronics Engineering Faculty of Engineering and ArchitectureNişantaşıUniversityIstanbul 34398Turkey

In the construction industry,to prevent accidents,non-destructive tests are necessary and *** impedance tomography is a new technology in non-invasive imaging in which the image of the inner part of conductive bodies is reconstructed by the arrays of external electrodes that are connected on the periphery of the *** equipment is cheap,fast,and edge *** this imaging method,the image of electrical conductivity distribution(or its opposite;electrical impedance)of the internal parts of the target object is *** image reconstruction process is performed by injecting a precise electric current to the peripheral boundaries of the object,measuring the peripheral voltages induced from it and processing the collected *** an electrical impedance tomography system,the voltages measured in the peripheral boundaries have a non-linear equation with the electrical conductivity *** paper presents a cheap electrical Impedance Tomography(EIT)instrument for detecting impurities in the concrete.A voltage-controlled current source,a micro-controller,a set of multiplexers,a set of electrodes,and a personal computer constitute the structure of the *** conducted tests on concrete with impurities show that the designed EIT system can reveal impurities with a good accuracy in a reasonable time.

关键词： non-destructive testing system concrete electrical impedance tomography

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A State-Migration Particle Swarm Optimizer for Adaptive Latent Factor Analysis of High-Dimensional and Incomplete Data

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IEEE/CAA Journal of Automatica Sinica 2024年第11期11卷 2220-2235页

作者： Jiufang Chen Kechen Liu Xin Luo Ye Yuan Khaled Sedraoui Yusuf Al-Turki MengChu Zhou IEEE the College of Computer Science and Technology Chongqing University of Posts and Telecommunications the Department of Computer Science Columbia University the College of Computer and Information Science Southwest University the Department of Electrical and Computer Engineering Faculty of Engineeringand also with K.A.CARE Energy Research and Innovation CenterKing Abdulaziz University the Center of Research Excellence in Renewable Energy and Power Systems the Department of Electrical and Computer EngineeringFaculty of Engineeringand also with K.A.CARE Energy Research and Innovation CenterKing Abdulaziz University the Department of Electrical and Computer Engineering New Jersey Institute of Technology

High-dimensional and incomplete(HDI) matrices are primarily generated in all kinds of big-data-related practical applications. A latent factor analysis(LFA) model is capable of conducting efficient representation learning to an HDI matrix,whose hyper-parameter adaptation can be implemented through a particle swarm optimizer(PSO) to meet scalable ***, conventional PSO is limited by its premature issues,which leads to the accuracy loss of a resultant LFA model. To address this thorny issue, this study merges the information of each particle's state migration into its evolution process following the principle of a generalized momentum method for improving its search ability, thereby building a state-migration particle swarm optimizer(SPSO), whose theoretical convergence is rigorously proved in this study. It is then incorporated into an LFA model for implementing efficient hyper-parameter adaptation without accuracy loss. Experiments on six HDI matrices indicate that an SPSO-incorporated LFA model outperforms state-of-the-art LFA models in terms of prediction accuracy for missing data of an HDI matrix with competitive computational ***, SPSO's use ensures efficient and reliable hyper-parameter adaptation in an LFA model, thus ensuring practicality and accurate representation learning for HDI matrices.

关键词： Data science generalized momentum high-dimensional and incomplete(HDI)data hyper-parameter adaptation latent factor analysis(LFA) particle swarm optimization(PSO)

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Single- and Dual-Beam Pattern Reconfigurable Patch Antenna With Dual Switchable CP for Internet of Vehicles

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IEEE Internet of Things Journal 2025年第12期12卷 21904-21914页

作者： Wang, Shi-Tong Zhu, Lei University of Macau Department of Electrical and Computer Engineering Faculty of Science and Technology China

In this article, a novel method is proposed to facilitate the design of compact, low-profile, pattern reconfigurable antennas with fixed or switchable circular polarization (CP) for Internet of Vehicles (IoV) applications. The proposed method eliminates the need for a complex beamforming or phase-tuning network by innovatively exploiting four resonant modes of a square patch antenna. Specifically, the TM01 and TM10 modes are utilized to accomplish the single-beam CP pattern, while the dual-beam CP pattern is achieved by combining the TM11 and TM02 modes. An electric current model is developed to investigate the far-field radiation, revealing that the radiation pattern of TM11 mode can be effectively reshaped from quad-beam to dual-beam by manipulating the surface current distribution. The complete design method is verified by an antenna prototype working at 3.5 GHz, which consists of a radiative patch, a pair of open-ended stubs, a pair of slots, and four equivalent switchable pins. Different from the conventional pin-loading method, the proposed equivalent switchable pins attain excellent CP performance during switching by compensating for the detrimental electric coupling. The prototype is fabricated and measured. Its radiation can be switched between single-beam (7.8 dBic) and dual-beam CP pattern (3.5 dBic), exhibiting an overlapped CP coverage from −123° to 73°. Furthermore, another prototype with the extended switchable CP capability is realized. Without increasing the number of p-i-n diodes, this prototype achieves four operating states with independent pattern (single- and dual-beam) and polarization (right- and left-handed CP) reconfiguration. The merits of compact size, low profile, and flexible reconfigurability make the proposed method and design cases excellent candidates for IoV applications and intelligent transportation systems (ITSs). © 2014 IEEE.

关键词： Circular polarization

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Capacity of Summation over a Symmetric Quantum Erasure MAC with Partially Replicated Inputs

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IEEE Transactions on Information Theory 2025年第7期71卷 5371-5386页

作者： Yao, Yuhang Jafar, Syed A. Department of Electrical Engineering and Computer Science IrvineCA92697 United States

The optimal quantum communication cost of computing a classical sum of distributed sources is studied over a quantum erasure multiple access channel (QEMAC). K classical messages comprised of finite-field symbols are distributed across S servers, who also share quantum entanglement in advance. Each server s ∈ [S] manipulates its quantum subsystem Qs according to its own available classical messages and sends Qs to the receiver who then computes the sum of the messages based on a joint quantum measurement. The download cost from Server s ∈ [S] is the logarithm of the dimension of Qs. The rate R is defined as the number of instances of the sum computed at the receiver, divided by the total download cost from all the servers. The main focus is on the symmetric setting with (Formula presented) messages where each message is replicated among a unique subset of α servers, and the answers from any β servers may be erased. If no entanglement is initially available to the receiver, then we show that the capacity (maximal rate) is precisely (Formula presented). The capacity with arbitrary levels of prior entanglement (Δ0) between the S data-servers and the receiver is also characterized, by including an auxiliary server (Server 0) that has no classical data, so that the communication cost from Server 0 is a proxy for the amount of receiver-side entanglement that is available in advance. The challenge on the converse side resides in the optimal application of the weak monotonicity property, while the achievability combines ideas from classical network coding and treating qudits as classical dits, as well as new constructions based on the N-sum box abstraction that rely on absolutely maximally entangled quantum states. © 1963-2012 IEEE.

关键词： Quantum entanglement

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Polarization-encodable photonic memory cells using nextgeneration 2D phase-change materials

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Nano Research 2025年第3期18卷 510-518页

作者： Amin Shafiee Linhong Chen Mahdi Nikdast Jie Yao Department of Electrical and Computer Engineering Colorado State UniversityFort CollinsCO 80523USA Department of Materials Science and Engineering University of CaliforniaBerkeleyCA 94720USA

Integration of phase-change materials(PCMs)created a unique opportunity to implement reconfigurable photonics devices that their performance can be tuned depending on the target *** PCMs such as Ge-Sb-Te(GST)and Ge-Sb-Se-Te(GSST)rely on melt-quench and high temperature annealing processes to change the organization of the molecules in the materials’*** a reorganization leads to different optical,electrical,and thermal properties which can be exploited to implement photonic memory cells that are able to store the data at different resistance or optical transmission *** the great promise of conventional PCMs for realizing reconfigurable photonic memories,their slow and extremely power-hungry thermal mechanisms make scaling the systems based on such devices *** addition,such materials do not offer a stable multi-level response over a long period of *** address these shortcomings,the research carried out in this study shows the proof of concept to implement next-generation photonic memory cells based on two-dimensional(2D)birefringence PCMs such as SnSe,which offer anisotropic optical properties that can be switched *** demonstrate that by leveraging the ultrafast and low-power crystallographic direction change of the material,the optical polarization state of the input optical signal can be *** enables the implementation of next-generation high-speed polarization-encodable photonic memory cells for future photonic computing *** to the conventional PCMs,the proposed SnSe-based photonic memory cells offer an ultrafast switching and low-loss optical response relying on ferroelectric property of SnSe to encode the data on the polarization state of the input optical *** a polarization encoding scheme also reduces memory read-out errors and alleviates the scalability limitations due to the optical insertion loss often seen in optical transmission encoding.

关键词： ferroelectric materials phase-change materials photonic memory optical storage cells polarization encodable photonic memories optical polarization

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Maximizing aged photovoltaic array power:a computer modelling study

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Clean Energy 2024年第1期8卷 171-187页

作者： Fadi N.Sibai Electrical&Computer Engineering Department Gulf University for Science and TechnologyMishrefKuwait

Photovoltaic(PV)modules age with time for various reasons such as corroded joints and terminals and glass coating defects,and their ageing degrades the PV array *** the help of the PV array numerical model,this paper explores the effects of PV module ageing on the PV array power,and the power gains and costs of rearranging and recabling aged PV modules in a PV *** numerical PV array model is first revised to account for module ageing,rearrangement and recabling,with the relevant equations presented *** updated numerical model is then used to obtain the array powers for seven different PV *** power results are then analysed in view of the attributes of the seven PV array examples.A guiding method to recommend recabling after rearranging aged modules is then proposed,leading to further significant power gains,while eliminating intra-row *** certain conditions are met,it was shown that recabling PV modules after rearranging them may lead to further significant power gains,reaching 57%and 98%in two considered PV array *** gains are possible in other arrays.A cost-benefit analysis weighing annual power gains versus estimated recabling costs is also given for the seven considered PV array examples to guide recabling decisions based on technical and economic *** the considered examples,recabling costs can be recovered in<4 *** with the powers of the aged arrays,power gains due to our proposed rearranging and recabling the PV arrays ranged between 73%and 131%in the considered examples—well over the gains reported in the ***,the cost of our static module rearrangement and recabling method outshines the costs of dynamic reconfiguration methods recently published in the literature.

关键词： solar energy optimizing array power photovoltaic array modelling photovoltaic modules ageing photovoltaic module rearrangement module recabling and reconfiguration PV array mismatch

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