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MLPFormer: MLP-integrated transformer for colorectal histopathology whole slide image segmentation

Neural computing and Applications 2025年第6期37卷 4651-4661页

作者： Wang, Yuxuan Li, Dan Li, Xuechen Guo, Yan Zuo, Yanfei Shen, Linlin Department of Computer Science Wenzhou-Kean University Wenzhou China School of Electronics and Information Engineering Wuyi University Jiangmen China Department of Histo Pathology Shanghai Histo Pathology Diagnostic Center Shanghai China College of Computer Sicence and Software Engineering Shenzhen University Shenzhen China National Engineering Laboratory for Big Data System Computing Technology Shenzhen University Shenzhen China

Colorectal intraepithelial neoplasia is a precancerous lesion of colorectal cancer, which is mainly diagnosed using pathological images. According to the characteristics of lesions, precancerous lesions can be classified into four different grades, i.e., background, normal, low and high level. However, due to the continuity of lesion development, tissue in different stages has high similarity. Recently, visual transformers have achieved impressive results in different visual tasks, due to their capacity of capturing long-range dependencies. However, due to computational cost, transformer cannot well extract detailed feature, which is important for lesion grading. To accurately segment pathological tissues with high similarity, in this work, we embed the multi-head MLP mixer module in the transformer network to extract cell and edge information. Furthermore, we propose a hierarchical MLP decoder to facilitate multi-scale feature fusion. The proposed transformer, namely MLPFormer, achieves remarkable results against competitive baselines on the Histo-CRC Biopsy dataset. The experimental results demonstrate that MLPFormer significantly outperforms the competitive baselines, i.e., a 3% dice improvement is achieved over the SegFormer series. © The Author(s), under exclusive licence to Springer-Verlag London Ltd., part of Springer Nature 2024.

关键词： Image segmentation

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Towards an AI-friendly cross-timescale simulation and analysis platform for electric distribution systems

iEnergy

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iEnergy 2022年第1期1卷 133-140页

作者： Dongqi Wu Rayan El Helou Le Xie Department of Electrical and Computer Engineering Texas A&M UniversityCollege StationTexasUSA

Substantial changes are occurring in electric distribution systems due to ambitious targets towards carbonneutrality in many regions around the *** of the key challenges is how to analyze the interactions of massive amount of energy endusers with the electric distribution grid *** this paper,we introduce a comprehensive simulation platform,AI4Dist,that is capable to perform a wide collection of distribution system studies that capture multiple timescales ranging from market planning to transient event ***4Dist is designed to effortlessly integrate with offtheshelf machine learning packages and algorithm *** envision that AI4Dist will serve as a platform to empower researchers with different expertise to contribute to the development of low carbon electricity sector.

关键词： Power distribution system machine learning simulation platform

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Optimal Design of IPT Bipolar Power Pad for Roadway-Powered EV Charging Systems

IEEE Canadian Journal of Electrical and Computer Engineering

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IEEE Canadian Journal of electrical and computer engineering 2021年第3期44卷 350-355页

作者： Jafari, Hassan Olowu, Temitayo O. Mahmoudi, Maryam Sarwat, Arif The Department of Electrical and Computer Engineering College of Engineering and Computing Florida International University MiamiFL33174 United States The Department of Electrical Engineering College of Engineering and Computing Florida International University MiamiFL33174 United States

This article proposes a multiobjective design optimization of rectangular bipolar power pads (BPP) for dynamic inductive power transfer (IPT) with application in electric vehicles. Minimization of IPT’s design cost, loss that includes core and winding, and maximization of the IPT system’s tolerance against horizontal/vertical misalignment are considered as objective functions during the optimization process. The design variables of the proposed algorithm are the shield plate length and width, ferrite bar length and width, the overlapping length of the coils, and the coil width and inner length of the coil. Power electronic limitations by defining the IPT’s quality factor (4 s Max), efficiency of all possible solutions greater than 80% (η > 80%), and upper/lower limits of design parameters are considered as the constraints of this optimization problem. The time-harmonic electromagnetic physics model of the BPP is analyzed using an finite element method magnetics (FEMM) software coupled with MATLAB. A nondominated genetic algorithm (NSGA-II) is employed as the optimization solver, in which the electromagnetic measurements from the FEMM software are used to evaluate the fitness values of the proposed objectives. The proposed BPP design optimization is applied on a 10-kW IPT system as a case study. The optimization results produced 15 Pareto optimal solutions. A validation study of two Pareto front solutions (PFS) is also presented. The Pareto optimal solutions allow the designer to select the best design parameters based on the objectives of highest priority. © 2021 IEEE.

关键词： Finite element method

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Weak and Extremely Low Frequency Magnetic Fields Alter the Growth Rates of HT-1080 Fibrosarcoma

Weak and Extremely Low Frequency Magnetic Fields Alter the G...

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2025 United States National Committee of URSI National Radio Science Meeting, USNC-URSI NRSM 2025

作者： Dang, Nhat Keller, Jason Bajtos, Marek Gurhan, Hakki Barnes, Frank Department of Electrical Computer and Energy Engineering College of Engineering and Applied Science University of Colorado Boulder BoulderCO United States Department of Electromagnetics and Biomedical Engineering Faculty of Electrical Engineering and Information Technology University of Zilina Zilina Slovakia

ISBN: (纸本)9781946815200

This study presents experimental results showing that weak, extremely low frequency electromagnetic (EM) fields influence the growth rates of HT-1080 fibrosarcoma cells in vitro and offers a theoretical explanation for these effects. The results demonstrate that weak magnetic fields both increase and decrease the growth rates of fibrosarcoma cells by altering the mitochondrial superoxide (O2-) and calcium ions (Ca2+) concentrations in living cells. Over a 4-day exposure period, fibrosarcoma growth rates were modulated in the presence of low-level alternating current (AC) magnetic fields at a 10 μT amplitude at 13.5 Hz to 30 Hz frequency, superimposed on a 45 μT static background field. Effects due to changes in amplitude from 10 to 30 μT at selected frequencies are also investigated with the same superimposed static field. © 2025 USNC-URSI.

关键词： Electromagnetic field effects

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Intelligent ADHD Detection Using Explainable Multimodal Fusion Model 4

Intelligent ADHD Detection Using Explainable Multimodal Fusi...

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4th IEEE International Conference on Information Technology, Big Data and Artificial Intelligence, ICIBA 2024

作者： Tsai, Ho-Jung Wu, Hsiao-Kuang Chen, Chun-Chuan Yeh, Chen-Hsin Chu, Tzu-Yueh Yeh, Shih-Ching National Central University Department of Computer Science and Information Engineering Taiwan National Central University Department of Biomedical Sciences and Engineering Taiwan Hunan University College of Computer Science and Electrical Engineering China

ISBN: (纸本)9798350363586

Deep learning has been proved to diagnose Attention Deficit/Hyperactivity Disorder (ADHD) accurately, but it has raised concerns about trustworthiness because of the lack of explainability. Fortunately, the development of explainable artificial intelligence (XAI) offers a solution to this problem. In this study, we employed a VR-based GO/NOGO task with distractions, capturing participants' eye movement, head movement, and electroencephalography (EEG) data. We used the collected data to train an explainable multimodal fusion model. Besides classifying between ADHD and normal children, the proposed model also generates explanation heatmaps. The heatmaps provide the importance of specific variables and timestamps in the EEG data to help us analyze the patterns captured by the model. According to our observations, the model identified specific time intervals that related to specific event-related potentials (ERPs) components. The heatmaps also demonstrate that the impacts of distractions vary between not only the GO and NOGO events but also ADHD and normal children. © 2024 IEEE.

关键词： Eye movements

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Dynamic Watermarking for Cyber-Security of Nonlinear Stochastic Systems 63

Dynamic Watermarking for Cyber-Security of Nonlinear Stochas...

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63rd IEEE Conference on Decision and Control, CDC 2024

作者： Lin, Tzu-Hsiang Kumar, P.R. Texas A&m University College Station Department of Electrical and Computer Engineering TX77843 United States

ISBN: (纸本)9798350316339

As cyber-physical systems form the core of many critical infrastructures, ensuring their safety is essential. The sensor measurements of networked cyber-physical systems can potentially be compromised, resulting in the misbehavior of the overall system. Indeed there have been a number of such attacks. Dynamic Watermarking is a proactive method whose goal is to detect such cyber attacks. It superimposes a small secret stochastic excitation onto signals in the system, such as control inputs of actuators or sensor measurements. Based on an examination of the signals purportedly returned, for example, by the sensors, it determines if the measurements have been tampered with. Previous theory for detection guarantees provided by Dynamic Watermarking has been restricted to linear stochastic systems. This paper examines the Dynamic Watermarking method for nonlinear stochastic systems. We show that Dynamic Watermarking for detecting attacks can be extended to certain systems in backstepping form. We present the analytical proofs, as well as simulation results. © 2024 IEEE.

关键词： Cyber attacks

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PRACL Converters for Motor Drive Applications

PRACL Converters for Motor Drive Applications

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2024 IEEE Energy Conversion Congress and Exposition, ECCE 2024

作者： Naghavi, Farid Tao, Guanhua Toliyat, Hamid A. Texas A&m University Department of Electrical and Computer Engineering College StationTX77843 United States

ISBN: (纸本)9798350376067

Voltage source converters (VSCs), a dominant technology in power conversion, face significant challenges such as short-circuit, voltage bounce-back, high dv/dt, and electromagnetic interference (EMI), especially when integrated with wide-band gap (WBG) devices. The partial resonance ac link (PRACL) converters emerge as a practical alternative, offering advantages like soft-switching, low EMI, single-stage power conversion, and inherent short-circuit protection. This paper details the application of PRACL converters on an induction motor using field-oriented control (FOC) and complex vector representation, aimed at enhancing system reliability and fault tolerance. © 2024 IEEE.

关键词： Induction motors

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Artificial Intelligence and Internet of Things Enabled Intelligent Framework for Active and Healthy Living

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computers, Materials & Continua 2023年第5期75卷 3833-3848页

作者： Saeed Ali Alsareii Mohsin Raza Abdulrahman Manaa Alamri Mansour Yousef AlAsmari Muhammad Irfan Hasan Raza Muhammad Awais Department of Surgery College of MedicineNajran University Saudi ArabiaNajran61441Saudi Arabia Department of Computer Science Edge Hill UniversitySt Helens RdOrmskirkL394QPUnited Kingdom Electrical Engineering Department College of EngineeringNajran University Saudi ArabiaNajran61441Saudi Arabia Department of Electrical Engineering Hamdard UniversityIslamabadPakistan

Obesity poses several challenges to healthcare and the well-being of *** can be linked to several life-threatening *** is a viable option in some instances to reduce obesity-related risks and enable weight ***-of-the-art technologies have the potential for long-term benefits in post-surgery *** this work,an Internet of Things(IoT)framework is proposed to effectively communicate the daily living data and exercise routine of surgery patients and patients with excessive *** proposed IoT framework aims to enable seamless communications from wearable sensors and body networks to the cloud to create an accurate profile of the *** also attempts to automate the data analysis and represent the facts about a *** IoT framework proposes a co-channel interference avoidance mechanism and the ability to communicate higher activity data with minimal impact on the bandwidth requirements of the *** proposed IoT framework also benefits from machine learning based activity classification systems,with relatively high accuracy,which allow the communicated data to be translated into meaningful information.

关键词： Artificial intelligence healthcare obesity Internet of Things machine learning physical activity classification activity monitoring

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DDoS Attacks Detection in IoT Networks using Naive Bayes and Random Forest 3

DDoS Attacks Detection in IoT Networks using Naive Bayes and...

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3rd International Conference on Applied Artificial Intelligence and computing, ICAAIC 2024

作者： Srivastava, Animesh Tiwari, Shweta Rawat, Bhupender Singh Dhondiyal, Shiv Ashish Graphic Era Hill University Department of Computer Science & Engineering Dehradun India Institute of Engineering Chandigarh University Department of Computer Science & Engineering Department / University Punjab Gharuan Mohali India Coer University College of Smart Computing Roorkee India Department of Computer Science & Engineering Dehradun India

ISBN: (纸本)9798350375190

The proliferation of Internet of Things (IoT) devices has resulted in numerous benefits, including streamlined tasks and improved connectivity but has also raised concerns regarding security vulnerabilities. Distributed Denial of Service (DDoS) attacks targeting IoT systems pose a significant threat, potentially disrupting operational activities. This study conducts a comparative analysis of existing methodologies to detect DDoS attacks in IoT environments, focusing on the efficacy of machine learning algorithms. Specifically, this study evaluates the performance of Random Forest and Naive Bayes classifiers in detecting DDoS attacks using an IoT dataset. The evaluation involves training and testing these classifiers and assessing their accuracy as a key performance metric. Empirical findings demonstrate enhanced precision in identifying DDoS attacks in IoT environment, indicating the effectiveness of the proposed approach. By leveraging machine learning algorithms, particularly Random Forest and Naive Bayes, traditional techniques for detecting and mitigating DDoS attacks in IoT environments are accelerated, thus enhancing the security of IoT systems. © 2024 IEEE.

关键词： Internet of things

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A Voltage Hexa-Lift and Output Triple Stacked Boost Converter Suitable for Renewable Applications 50

A Voltage Hexa-Lift and Output Triple Stacked Boost Converte...

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50th Annual Conference of the IEEE Industrial Electronics Society, IECON 2024

作者： Gholizadeh, Hossein Zare, Mehrdad Doroudiani, Hadi Fazeli, Seyyed Erfan Gharehpetian, Gevork B. Yazdani, Atousa School of Electrical and Computer Engineering College of Engineering University of Tehran Tehran Iran Electrical Engineering Department Islamic Azad University Tehran Iran Electrical Engineering Department Amirkabir University of Technology Tehran Iran Electrical and Electronic Engineering California State University Sacramento United States

ISBN: (纸本)9781665464543

Please take note of the following text: The boost topology is the most popular non-isolated DC-DC converter with step-up capability. It’s worth noting that lower duty cycle percentages, which lead to higher efficiencies, can only provide a voltage gain from unity to two, which may not be suitable in some cases. This study introduces an improved topology of the boost converter. The provided voltage gain is six times that of a traditional boost converter. This means that a 50 % duty cycle provides a 12-times voltage gain. Similar to the boost converter, the input current is continuous, and only one switch with a simple drive circuit is used. The output voltage of the converter is divided among three capacitors, resulting in decreased output capacitor voltage stress due to the provided triple-stacked structure. The converter is discussed in both ideal and non-ideal modes. Finally, experimental results for a 150 W output power and 600 V output voltage are presented. © 2024 IEEE.

关键词： Capacitor bank

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