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Efficient Image Captioning Based on Vision Transformer Models

computers, Materials & Continua 2022年第10期73卷 1483-1500页

作者： Samar Elbedwehy T.Medhat Taher Hamza Mohammed F.Alrahmawy Department of Data Science Faculty of Artificial IntelligenceKafrelsheikh UniversityEgypt Department of Electrical Engineering Faculty of EngineeringKafrelsheikh UniversityEgypt Department of Computer Science Faculty of Computer and Information ScienceMansouraEgypt

Image captioning is an emerging field in machine *** refers to the ability to automatically generate a syntactically and semantically meaningful sentence that describes the content of an *** captioning requires a complex machine learning process as it involves two sub models:a vision sub-model for extracting object features and a language sub-model that use the extracted features to generate meaningful ***-based vision transformers models have a great impact in vision field *** this paper,we studied the effect of using the vision transformers on the image captioning process by evaluating the use of four different vision transformer models for the vision sub-models of the image captioning The first vision transformers used is DINO(self-distillation with no labels).The second is PVT(Pyramid Vision Transformer)which is a vision transformer that is not using convolutional *** third is XCIT(cross-Covariance Image Transformer)which changes the operation in self-attention by focusing on feature dimension instead of token *** last one is SWIN(Shifted windows),it is a vision transformer which,unlike the other transformers,uses shifted-window in splitting the *** a deeper evaluation,the four mentioned vision transformers have been tested with their different versions and different configuration,we evaluate the use of DINO model with five different backbones,PVT with two versions:PVT_v1and PVT_v2,one model of XCIT,SWIN *** results show the high effectiveness of using SWIN-transformer within the proposed image captioning model with regard to the other models.

关键词： Image captioning sequence-to-sequence self-distillation transformer convolutional layer

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Novel add-drop filter based on serial and parallel photonic crystal ring resonators (PCRR)

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Journal of Optical Communications 2024年第2期45卷 235-247页

作者： Fakhruldeen, Hassan Falah Al-Asady, Heba Abdul-Jaleel Mahinroosta, Tayebeh Sohrabi, Foozieh Hamidi, Seyedeh Mehri Computer Techniques Engineering Department Faculty of Information Technology Imam Ja’afar Al-sadiq University Baghdad Iraq Electrical Engineering Department College of Engineering University of Kufa Kufa Iraq Computer Technical Engineering Department College of Technical Engineering The Islamic University Najaf Iraq Magneto-Plasmonic Lab Laser and Plasma Research Institute Shahid Beheshti University Tehran*** Iran

Photonic crystal ring resonators (PCRR) as momentous candidates for future photonic crystal integrated circuits (PCICs) draw worldwide attention. In this paper, different configurations are proposed based on single, parallel, and serial PCRRs. To be precise, the different coupling lengths and alignments have been discussed in double and triple PCRRs in parallel and serial configurations to achieve the highest efficiency concerning the desired applications such as an add-drop filter (ADF) and a power splitter. Moreover, in the achieved optimum double and triple PCRRs, the effect of coupling radius change has been discussed. © 2024 Walter de Gruyter GmbH. All rights reserved.

关键词： Photonic crystals

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A survey of artificial intelligence models for wireless capsule endoscopy videos for superior automatic diagnosis: problems and solutions

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Multimedia Tools and Applications 2025年 1-35页

作者： El-Gammal, Eman M. El-Shafai, Walid Taha, Taha E. El-Fishawy, Adel S. Abd El-Samie, Fathi E. Department of Electronics and Electrical Communications Engineering Faculty of Electronic Engineering Menoufia University Menouf32952 Egypt Center of Advanced Software and Biomedical Clinical Engineering Consultations Faculty of Engineering Cairo University Giza Egypt Computer Science Department Prince Sultan University Riyadh11586 Saudi Arabia Department of Information Technology College of Computer and Information Sciences Princess Nourah Bint Abdulrahman University 84428 Riyadh11671 Saudi Arabia

Wireless Capsule Endoscopy (WCE) emerged as an innovative and patient-centric approach for non-invasive and painless examination of the gastrointestinal (GI) tract. It serves as a pivotal tool in helping medical practitioners in the early detection of anomalies within the intricate domain of the human GI tract. The automated identification of aberrations assumes paramount significance, contributing not only to temporal efficiency but also to timely diagnosis. Within the realm of academic literature, a plethora of Artificial Intelligence (AI) methodologies have been proposed to effectuate the automatic classification, segmentation, and synthesis of anomalies inherent in WCE images. This scholarly endeavor undertakes a comprehensive and meticulous survey, elucidating the spectrum of anomaly classification, summarization, and detection techniques harnessed for computer-Aided Diagnosis (CAD) in the context of WCE images. The survey begins by delineating the methodologies underpinning WCE image classification and video processing. Subsequently, an exhaustive evaluation of techniques for analyzing WCE images is furnished, accompanied by an in-depth exploration of pertinent surveys, in addition to a judicious assessment of their merits and demerits. Furthermore, this study undertakes a rigorous evaluation of prevailing datasets utilized to benchmark the efficacy of various WCE techniques. In summary, this survey serves as a vanguard, delineating promising avenues for future investigations in the realm of WCE image analysis models. © The Author(s), under exclusive licence to Springer Science+Business Media, LLC, part of Springer Nature 2025.

关键词： Endoscopy

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Implementation of a Multipath Fully Differential OTA in 0.18-μm CMOS Process

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IEEE Transactions on Very Large Scale Integration (VLSI) Systems 2023年第1期31卷 147-151页

作者： Akbari, Meysam Hussein, Safwan Mawlood Hashim, Yasir Khateb, Fabian Kulej, Tomasz Tang, Kea-Tiong University of Kurdistan Department of Electrical Engineering Sanandaj66177 Iran Tishk International University Faculty of Engineering Department of Computer Engineering Erbil44001 Iraq Brno University of Defence Department of Electrical Engineering Brno66210 Czech Republic Czech Technical University in Prague Faculty of Biomedical Engineering Kladno16636 Czech Republic Czestochowa University of Technology Department of Electrical Engineering Czestochowa42201 Poland National Tsing Hua University Department of Electrical Engineering Hsinchu30013 Taiwan

This brief implements a highly efficient fully differential transconductance amplifier, based on several input-to-output paths. Some traditional techniques, such as positive feedback, nonlinear tail current sources, and current mirror-based paths, are combined to increase the transconductance, thus leading to larger dc gain and higher gain bandwidth (GBW) product. Two flipped voltage-follower (FVF) cells are employed as variable current sources to provide class-AB operation and adaptive biasing of all other drivers. The proposed structure includes several input-to-output paths that play the role of dynamic current boosters during the slewing phase, thus improving the slew rate (SR) performance. The circuit was fabricated in a TSMC 0.18-μm CMOS process with a silicon area of 54.5×30.1μm. Experimental results show a GBW of 173.3 MHz, a dc gain of 72.7 dB, and an SR of 139.4 V/μs for a capacitive load of 2×5 pF. The proposed circuit consumes 619 μW of power, under a supply voltage of 1.8 V. © 1993-2012 IEEE.

关键词： Operational amplifiers

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Stochastic Programming for Hub Energy Management Considering Uncertainty Using Two-Point Estimate Method and Optimization Algorithm

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computer Modeling in engineering & Sciences 2023年第12期137卷 2163-2192页

作者： Ali S.Alghamdi Mohana Alanazi Abdulaziz Alanazi Yazeed Qasaymeh Muhammad Zubair Ahmed Bilal Awan M.G.B.Ashiq Department of Electrical Engineering College of EngineeringMajmaah UniversityAl-Majmaah11952Saudi Arabia Department of Electrical Engineering College of EngineeringJouf UniversitySakaka72341Saudi Arabia Department of Electrical Engineering College of EngineeringNorthern Border UniversityAr’Ar73222Saudi Arabia Automation and Control Department College of Engineering TechnologyUniversity of Doha for Science and TechnologyDoha24449Qatar Department of Electrical and Computer Engineering College of Engineering and Information TechnologyAjman UniversityAjman20550United Arab Emirates Department of Physics College of ScienceImam Abdulrahman Bin Faisal UniversityDammam31441Saudi Arabia

To maximize energy profit with the participation of electricity,natural gas,and district heating networks in the day-ahead market,stochastic scheduling of energy hubs taking into account the uncertainty of photovoltaic and wind resources,has been carried *** has been done using a new meta-heuristic algorithm,improved artificial rabbits optimization(IARO).In this study,the uncertainty of solar and wind energy sources is modeled using Hang’s two-point estimating method(TPEM).The IARO algorithm is applied to calculate the best capacity of hub energy equipment,such as solar and wind renewable energy sources,combined heat and power(CHP)systems,steamboilers,energy storage,and electric cars in the *** standard ARO algorithmis developed to mimic the foraging behavior of rabbits,and in this work,the algorithm’s effectiveness in avoiding premature convergence is improved by using the dystudynamic inertia weight *** proposed IARO-based scheduling framework’s performance is evaluated against that of traditional ARO,particle swarm optimization(PSO),and salp swarm algorithm(SSA).The findings show that,in comparison to previous approaches,the suggested meta-heuristic scheduling framework based on the IARO has increased energy profit in day-ahead electricity,gas,and heating markets by satisfying the operational and energy hub ***,the results show that TPEM approach dependability consideration decreased hub energy’s profit by 8.995%as compared to deterministic planning.

关键词： Stochastic energy hub scheduling energy profit uncertainty Hong’s two-point estimate method improved artificial rabbits optimization

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Monitoring the processing and supply of clean drinking water using the hybrid gateway method based on the Internet of Things

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International Journal of Water 2024年第2期16卷 118-141页

作者： Yusianto, Rindra Ali, Rabei Raad Suprijono, Herwin Marimin Faculty of Engineering Department of Industrial Engineering Dian Nuswantoro University Central Jawa Semarang50131 Indonesia Department of Computer Engineering Technology Northern Technical University Nineveh Governorate Mosul41002 Iraq Faculty of Engineering Department of Electrical Engineering Dian Nuswantoro University Central Jawa Semarang50131 Indonesia Faculty of Agricultural Engineering and Technology Department of Agro-Industrial Technology IPB University PO Box 220 West Java Bogor16002 Indonesia

This research aims to implement Internet of Things (IoT)-based monitoring in water treatment systems. A Gateway device will be designed to support the integration of a new IoT-based monitoring system based on conditions at the Petanglong, Indonesia. A Raspberry Pi and Node-Red software were used as programming tools to carry out the Gateway function and create a monitoring dashboard display with the message queuing telemetry transport (MQTT) protocol as a communication path that connects the Gateway device with the cloud server. The results show that the Gateway device can work well in the new IoT-based monitoring system. The accuracy level of data reading between the value in the field and the dashboard display results is 99%, which works ideally at a reading time interval of every 5 s, with the difference in data display time and the dashboard display being in the time range of 2–3 s. © 2024 Inderscience Enterprises Ltd.

关键词： Gateways (computer networks)

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Absorptive Microwave Filters: From Narrowband to Wideband Operation

Absorptive Microwave Filters: From Narrowband to Wideband Op...

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2024 International Applied Computational Electromagnetics Society Symposium, ACES-China 2024

作者： Cui, Jiaqian Zhu, Lei University of Macau Faculty of Science and Technology Department of Electrical and Computer Engineering Macau China

ISBN: (纸本)9798350355581

This paper presents a method to control the out-ofband performance of absorptive filters in both narrowband and wideband cases. To verify the method, a narrowband absorptive filter is designed with wideband matching, and a wideband one is proposed to achieve an infinite low-reflection range. Finally, the narrowband filter is implemented in microstrip-line platform, not only attaining symmetrical geometry but also improving impedance-matching performance. © 2024 IEEE.

关键词： Wiener filtering

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Cooperative nonlinear distributed model predictive control with dissimilar control horizons 63

Cooperative nonlinear distributed model predictive control w...

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63rd IEEE Conference on Decision and Control, CDC 2024

作者： Chanfreut, Paula Maestre, Jose M. Zhu, Quanyan Heemels, W.P.M.H. Maurice Eindhoven University of Technology Department of Mechanical Engineering Netherlands University of Seville Department of Systems and Automation Engineering Spain New York University Department of Electrical and Computer Engineering United States

ISBN: (纸本)9798350316339

In this paper, we introduce a nonlinear distributed model predictive control (DMPC) algorithm, which allows for dissimilar and time-varying control horizons among agents, thereby addressing a common limitation in current DMPC schemes. We consider cooperative agents with varying computational capabilities and operational objectives, each willing to manage varying numbers of optimization variables at each time step. Recursive feasibility and a non-increasing evolution of the optimal cost are proven for the proposed algorithm. Through numerical simulations on systems with three agents, we show that our approach effectively approximates the performance of traditional DMPC, while reducing the number of variables to be optimized. This advancement paves the way for a more decentralized yet coordinated control strategy in various applications, including power systems and traffic management. © 2024 IEEE.

关键词： Predictive control systems

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IEconformer: A Robust Convolutional Transformer for EEG-Based Fatigue Driving Detection

IEconformer: A Robust Convolutional Transformer for EEG-Base...

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2024 IEEE International Conference on Service Operations and Logistics, and Informatics, SOLI 2024

作者： Chen, Jie Du, Yipeng Kong, Shuyi Ngai, Edith C. H. Liu, Jian School of Computer and Communication Engineering University of Science and Technology Beijing Beijing China The University of Hong Kong Department of Electrical and Electronic Engineering Hong Kong Electrical Engineering and Automation at the School of Automation Beijing Institute of Technology Beijing China

Fatigue driving detection technology plays a pivotal role in ensuring road safety, and electroencephalography (EEG) signals can be employed as an objective measure of driver fatigue in intelligent vehicles. However, current EEG-based fatigue driving detection methods encounter certain limitations. Firstly, the restricted receptive field of convolutional neural networks struggles to effectively handle the non-stationary nature of fatigue EEG signals for feature extraction. Secondly, real-world training data often suffers from noisy labels, leading to model overfitting on mislabeled data and consequent degradation in the fatigue detection performance. In this paper, we propose the IE conformer ensemble, a robust EEG-based fatigue driving detection model. The IEconformer architecture integrates multi-scale convolutional layers for local feature extraction and the multi-head attention mechanism to capture global feature correlations. To tackle the challenge of noisy data during training, we introduce the co-teaching plus mechanism into our training scheme. This mechanism facilitates cross-updating each IEconformer using disagreement data that yields minimal loss on the respective IEconformer. Experimental results demonstrate the superiority of our proposed IEconformer ensemble over baseline models in fatigue detection. Particularly, the IEconformer ensemble demonstrates high performance even in the presence of noisy data during the training stage, underscoring the practicality of our approach in fatigue driving detection applications for intelligent vehicles. © 2024 IEEE.

关键词： Convolutional neural networks

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A Novel Experimental Approach for Predictive High-Frequency Modeling of Differential-Mode Impedance in Three-Phase Induction Motors 3

A Novel Experimental Approach for Predictive High-Frequency ...

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3rd International Conference on Advanced electrical engineering, ICAEE 2024

作者： Hakmi, Yassine Miloudi, Houcine Miloudi, Mohamed Bendaoud, Abdelber Mendaz, Kheira Bermaki, Mohammed Hamza Djillali Liabes University Apelec Laboratory Faculty of Electrical Engineering Algeria Relizane University Gidd Laboratory Electrical Engineering and Automation Department Algeria University of Belhadj Bouchaib Ain Temouchent Irecom Laboratory Faculty of Science and Technology Electrical Engineering Department Algeria

ISBN: (纸本)9798350349351

High-frequency (HF) models of electrical motors and converters are crucial for electromagnetic compatibility (EMC) characterization of electrical drives and EMI filter design. This paper presents a methodology for predictive modeling of the differential-mode (DM) impedance of a three-phase high-frequency induction motor, considering frequency-dependent parameters. The proposed modeling approach establishes an equivalent circuit for the three-phase high-frequency induction motor, facilitating analysis of the electromagnetic interference (EMI) effect of each parameter and prediction of the main path of differential mode current. Transfer functions have been tuned using an asymptotic identification method to match the behavior of real impedances of motor parameters as a function of frequency in the differential-mode configuration. Prediction results demonstrate satisfactory agreement with measurements across a wide frequency bandwidth [100 Hz-20 MHz]. © 2024 IEEE.

关键词： Asymptotic analysis

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