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Analysis and Optimization of Boost Converter Parameters in Internal Model Control for Voltage Source Converter-based AC Microgrids

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CSEE Journal of Power and Energy Systems 2024年第5期10卷 2038-2054页

作者： Chiebuka Eyisi Qifeng Li Department of Electrical and Computer Engineering University of Central FloridaOrlandoFL 32816 USA.

This paper investigates integration of distributed energy resources(DERs)in microgrids(MGs)through two-stage power conversion structures consisting of DC-DC boost converter and DC-AC voltage source converter(VSC)*** contrast to existing investigations that treated DC-link voltage as an ideal constant voltage,this paper considers the non-ideal dynamic coupling between both subsystems for completeness and higher accuracy,which introduces additional DC-side dynamics to the *** analysis shows parameters of the boost converter’s power model that impact stability through the *** selecting these parameters can mitigate this effect on stability and improve dynamic performance across the ***,an optimization framework is developed to facilitate in selecting adequate boost converter parameters in designing a stable voltage source converter-based microgrid(VSC-MG).The developed optimization framework,based on particle swarm optimization,considers dynamic coupling between both subsystems and is also effective in avoiding inadequate boost converter parameters capable of propagating instability through the DC-link to the *** are performed with MATLAB/Simulink to validate theoretical analyses.

关键词： AC microgrid boost converter dead-time droop control internal model control particle swarm optimization small-signal analysis time delay virtual impedance voltage source converter

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Enhancing eyeglasses removal in facial images: a novel approach using translation models for eyeglasses mask completion

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Multimedia Tools and Applications 2024年 1-20页

作者： Esmaily, Zahra Ebrahimpour-Komleh, Hossein Department of Electrical and Computer Engineering University of Kashan Kashan Iran

Accurately removing eyeglasses from facial images is crucial for improving the performance of various face-related tasks such as verification, identification, and reconstruction. This paper presents a novel approach to enhancing eyeglasses removal by integrating a mask completion technique into the existing framework. Our method focuses on improving the accuracy of eyeglasses masks, which is essential for subsequent eyeglasses and shadow removal steps. We introduce a unique dataset specifically designed for eyeglasses mask image completion. This dataset is generated by applying Top-Hat morphological operations to existing eyeglasses mask datasets, creating a collection of images containing eyeglasses masks in two states: damaged (incomplete) and complete (ground truth). A Pix2Pix image-to-image translation model is trained on this newly created dataset for the purpose of restoring incomplete eyeglass mask predictions. This restoration step significantly improves the accuracy of eyeglass frame extraction and leads to more realistic results in subsequent eyeglasses and shadow removal. Our method incorporates a post-processing step to refine the completed mask, preventing the formation of artifacts in the background or outside of the eyeglasses frame box, further enhancing the overall quality of the processed image. Experimental results on CelebA, FFHQ, and MeGlass datasets showcase the effectiveness of our method, outperforming state-of-the-art approaches in quantitative metrics (FID, KID, MOS) and qualitative evaluations. © The Author(s), under exclusive licence to Springer Science+Business Media, LLC, part of Springer Nature 2024.

关键词： Image reconstruction

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Maximally Flat Negative Group Delay Prototype Filter Based on Capped Reciprocal Transfer Function of Classical Bessel Filter

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Progress in Electromagnetics Research B 2025年 110卷 91-105页

作者： Kandic, Miodrag Bridges, Greg E. Department of Electrical and Computer Engineering University of Manitoba WinnipegMB Canada

A prototype filter design exhibiting Negative Group Delay (NGD) is presented, based on the ratio of two low-pass classical Bessel filter transfer functions of the same order, but with different 3 dB-bandwidths. The resulting design is a reciprocal-Bessel filter transfer function, capped at a finite out-of-band gain. The proposed capped reciprocal-Bessel design is based on a similar concept applied to previously reported capped reciprocal-Butterworth and reciprocal-Chebyshev NGD designs, which use ratios of corresponding classical low-pass filter transfer functions. It is shown that within the in-band frequency range, the synthesized NGD transfer function exhibits a maximally flat group delay characteristic (Bessel-like property). Due to its near-flat in-band group delay characteristic, the design is suitable for constant phase shifter applications. For high design orders, it is shown that the achieved NGD-bandwidth product has an upper asymptotic limit, given by the square root of the out-of-band gain in decibels. When the prototype baseband transfer function is translated to a non-zero center frequency, it is demonstrated that resonator-based implementations are feasible via Sallen-Key, as well as all-passive ladder topologies. A combined in-band magnitude/phase distortion metric is evaluated for selected design examples and applied Gaussian and sinc input waveforms, and it is shown to be proportional to the design order and out-of-band gain. The proposed design's distortion metric is also shown to be generally lower than the previously reported capped reciprocal-Butterworth and reciprocal-Chebyshev designs. © (2025), (Electromagnetics Academy). All rights reserved.

关键词： Group delay

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Electron beam lithography on nonplanar and irregular surfaces

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Microsystems & Nanoengineering 2024年第2期10卷 1-23页

作者： Chenxu Zhu Huseyin Ekinci Aixi Pan Bo Cui Xiaoli Zhu Department of Electrical and Computer Engineering and Waterloo Institute for Nanotechnology(WIN) University of WaterlooWaterlooONCanada

E-beam lithography is a powerful tool for generating nanostructures and fabricating nanodevices with fine features approaching a few nanometers in ***,alternative approaches to conventional spin coating and development processes are required to optimize the lithography procedure on irregular *** this review,we summarize the state of the art in nanofabrication on irregular substrates using e-beam *** overcome these challenges,unconventional methods have been *** instance,polymeric and nonpolymeric materials can be sprayed or evaporated to form uniform layers of electron-sensitive materials on irregular ***,chemical bonds can be applied to help form polymer brushes or self-assembled monolayers on these *** addition,thermal oxides can serve as resists,as the etching rate in solution changes after e-beam ***,e-beam lithography tools can be combined with cryostages,evaporation systems,and metal deposition chambers for sample development and lift-off while maintaining low *** nanopyramids can be fabricated on an AFM tip by utilizing ice as a positive ***,Ti/Au caps can be patterned around a carbon ***,3D nanostructures can be formed on irregular surfaces by exposing layers of anisole on organic ice surfaces with a focused *** advances in e-beam lithography on irregular substrates,including uniform film coating,instrumentation improvement,and new pattern transferring method development,substantially extend its capabilities in the fabrication and application of nanoscale structures.

关键词： lithography beam coating

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Knowledge distillation on spatial-temporal graph convolutional network for traffic prediction

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International Journal of computers and Applications 2025年第1期47卷 45-56页

作者： Izadi, Mohammad Safayani, Mehran Mirzaei, Abdolreza Department of Electrical and Computer Engineering Isfahan University of Technology Isfahan Iran

Efficient real-time traffic prediction is crucial for reducing transportation time. To predict traffic conditions, we employ a spatio-temporal graph neural network (ST-GNN) to model our real-time traffic data as temporal graphs. Despite its capabilities, it often encounters challenges in delivering efficient real-time predictions for real-world traffic data. Recognizing the significance of timely prediction due to the dynamic nature of real-time data, we employ knowledge distillation (KD) as a solution to enhance the execution time of ST-GNNs for traffic prediction. In this paper, We introduce a cost function designed to train a network with fewer parameters (the student) using distilled data from a complex network (the teacher) while maintaining its accuracy close to that of the teacher. We use knowledge distillation, incorporating spatial-temporal correlations from the teacher network to enable the student to learn the complex patterns perceived by the teacher. However, a challenge arises in determining the student network architecture rather than considering it inadvertently. To address this challenge, we propose an algorithm that utilizes the cost function to calculate pruning scores, addressing small network architecture search issues, and jointly fine-tunes the network resulting from each pruning stage using KD. Ultimately, we evaluate our proposed ideas on two real-world datasets, PeMSD7 and PeMSD8. The results indicate that our method can maintain the student's accuracy close to that of the teacher, even with the retention of only (Formula presented.) of network parameters. © 2024 Informa UK Limited, trading as Taylor & Francis Group.

关键词： Cost functions

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Predicting Distant Metastatic Sites in Cancer Using miRNA and mRNA Expression Data

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Current Bioinformatics 2025年第5期20卷 473-485页

作者： Mamatkarimov, Dostonjon Kang, Jiahui Han, Kyungsook Department of Electrical and Computer Engineering Inha University Incheon Korea Republic of

Background: Cancer patients with metastasis face a much lower survival rate and a higher risk of recurrence than those without metastasis. So far, several learning methods have been proposed to predict cancer metastasis, but most of these methods are intended to predict lymph node metastasis rather than distant metastasis. Distant metastasis is more difficult to predict than lymph node metastasis because distant metastasis is detected after a comprehensive examination of the entire body, and there are not enough publicly available tumor samples with distant metastasis that can be used for training learning methods. Predicting distant metastatic sites is even more challenging than predicting whether distant metastasis will occur or not. Methods: The problem of predicting distant metastatic sites is a multi‐class and multi‐label classification problem;there are more than two classes for distant metastatic sites (bone, brain, liver, lung, and other organs), and a single sample can have multiple labels for multiple metastatic sites. We transformed the multi‐label and multi‐class problem into multiple single‐label binary problems. For each metastatic site, we built a random forest model that deals with binary classification and linked the models along a chain. Results: Testing the model on miRNA and mRNA expression datasets of several cancer types showed a high performance in all performance measures. In the comparison of our model with other methods, our method outperformed the others. Conclusion: We developed a new method for predicting multiple metastatic sites using miRNA and mRNA expression data. The technique will be useful in predicting distant metastatic sites before distant metastasis occurs, which in turn will help clinicians determine treatment options for cancer patients. © 2025 Bentham Science Publishers.

关键词： Diseases

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Infrared Fault Detection Method for Dense Electrolytic Bath Polar Plate Based on YOLOv5s

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computers, Materials & Continua 2024年第9期80卷 4859-4874页

作者： Huiling Yu Yanqiu Hang Shen Shi Kangning Wu Yizhuo Zhang Software Engineering Department of Computer ScienceChangzhou UniversityChangzhou213146China Electrical Engineering Department of Computer ScienceChangzhou UniversityChangzhou213146China

Electrolysis tanks are used to smeltmetals based on electrochemical principles,and the short-circuiting of the pole plates in the tanks in the production process will lead to high temperatures,thus affecting normal *** at the problems of time-consuming and poor accuracy of existing infrared methods for high-temperature detection of dense pole plates in electrolysis tanks,an infrared dense pole plate anomalous target detection network YOLOv5-RMF based on You Only Look Once version 5(YOLOv5)is ***,we modified the Real-Time Enhanced Super-Resolution Generative Adversarial Network(Real-ESRGAN)by changing the U-shaped network(U-Net)to Attention U-Net,to preprocess the images;secondly,we propose a new Focus module that introduces the Marr operator,which can provide more boundary information for the network;again,because Complete Intersection over Union(CIOU)cannot accommodate target borders that are increasing and decreasing,replace CIOU with Extended Intersection over Union(EIOU),while the loss function is changed to Focal and Efficient IOU(Focal-EIOU)due to the different difficulty of sample *** the homemade dataset,the precision of our method is 94%,the recall is 70.8%,and the map@.5 is 83.6%,which is an improvement of 1.3%in precision,9.7%in recall,and 7%in map@.5 over the original *** algorithm can meet the needs of electrolysis tank pole plate abnormal temperature detection,which can lay a technical foundation for improving production efficiency and reducing production waste.

关键词： Infrared polar plate fault detection YOLOv5 Real-ESRGAN Marr boundary detection operator Focal-EIoU loss

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Counting vehicles types using deep learning algorithm in video surveillance systems

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Multimedia Tools and Applications 2024年 1-24页

作者： Akoushideh, Alireza Sadat, Seyed Shafiullah Shahbahrami, Asadollah Electrical and Computer Engineering Department National University of Skill Tehran Iran Computer Engineering Department Kabul Polytechnic University Kabul Afghanistan Computer Engineering Department University of Guilan Rasht Iran

Detection, identification, and automatic counting of vehicles using video surveillance cameras plays an essential role in intelligent transportation management. Despite the progress that researchers have made in these cases, its operational implementation still faces challenges such as various environmental conditions, unbalanced data sets, accuracy, and speed. Therefore, research is fundamental in solving these issues. This research investigates the use of deep convolutional neural networks (CNNs) for vehicle detection, classification, and counting in video surveillance applications. We analyze recent research trends and challenges, examining the suitability of popular datasets like MSCOCO, PASCAL, ImageNet, DAWN, DETRAC, and MIO-TCD for validating proposed algorithms. Our study focuses on overcoming challenges like poor lighting conditions and unbalanced traffic scenarios. We propose a novel approach for counting vehicle types based on the YOLO model. The proposed method leverages the YOLO model for object detection and recognition, the ByteTrack algorithm for tracking vehicles across frames, and the CLAHE pre-processing and the Multiple-Zone-Line approach for addressing video surveillance challenges. Experimental results on three benchmark videos demonstrate the superiority of YOLOv8 over YOLOv9 in our benchmarks. Moreover, the application of CLAHE pre-processing algorithms further enhances performance. This research offers a promising solution for accurate and robust vehicle detection, classification, and counting in real-world video surveillance scenarios. © The Author(s), under exclusive licence to Springer Science+Business Media, LLC, part of Springer Nature 2024.

关键词： Convolutional neural networks

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A new content-aware image resizing based on Rényi entropy and deep learning

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Neural Computing and Applications 2024年第15期36卷 8885-8899页

作者： Ayubi, Jila Chehel Amirani, Mehdi Valizadeh, Morteza Department of Electrical and Computer Engineering Urmia University Urmia Iran

One of the most popular techniques for changing the purpose of an image or resizing a digital image with content awareness is the seam-carving method. The performance of image resizing algorithms based on seam machining shows that these algorithms are highly dependent on the extraction of importance map techniques and the detection of salient objects. So far, various algorithms have been proposed to extract the importance map. In this paper, a new method based on Rényi entropy is proposed to extract the importance map. Also, a deep learning network has been used to detect salient objects. The simulator results showed that combining Rényi’s importance map with a deep network of salient object detection performed better than classical seam-carving and other extended seam-carving algorithms based on deep learning. © The Author(s), under exclusive licence to Springer-Verlag London Ltd., part of Springer Nature 2024.

关键词： Deep learning

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A new multi-input two-output switched-source multilevel inverter based on harvest of maximum energy for photovoltaic applications

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International Journal of Power Electronics 2024年第2期19卷 167-192页

作者： Salehi, Seyed Jafar Shamsi-Nejad, Mohammad Ali Najafi, Hamid Reza Department of Electrical and Computer Engineering University of Birjand Birjand Iran

In multilevel inverters, unused energies are created due to the asynchronous use of the input DC-sources. This means that when the input DC-sources are replaced by renewable systems such as photovoltaic arrays, some of the input energies remain unused by the multilevel inverter. This paper presents a new multi-input two output multilevel inverter topology that can harvest the unused energies and return them to another load which leads to the harvest of the maximum input energy. The harvest of maximum energy (HME)-based multilevel inverter structure consists of two independent terminals both of which can be connected to the AC load. Another merit of the proposed multilevel inverter is that the number of its switches is comparable to other structures where unused energies cannot be harvested. The nearest level control (NLC) has been used as the switching strategy in the proposed multilevel structure. In order to verify the performance of the HME-based multilevel inverter topology, the simulation and experimental results for a type seven-level inverter are provided by MATLAB and TMS320F28379D DSP, respectively. © 2024 Inderscience Enterprises Ltd.

关键词： Level control

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