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International Conference on Mathematics and computers in Sciences and in Industry (MCSI)

作者： Rigon Sallauka Umut Arioz Izidor Mlakar Laboratory of Digital Signal Processing University of Maribor Faculty of Electrical Engineering and Computer Science Maribor Slovenia

ISBN: (数字)9798350377224

ISBN: (纸本)9798350377231

In this study, we aim to develop a robust model capable of accurately extracting symptoms from clinical texts written in the Slovenian language. Our methodology involves several steps to achieve this objective. Initially, we identify datasets containing clinical texts in English and select a specialized model designed for symptom extraction from these texts. Then, we annotate the datasets and undertake the translation process into Slovenian, ensuring the preservation of annotations to maintain data integrity. Utilizing the translated dataset, we proceed to fine-tune the selected model specifically for Slovenian texts. Despite our efforts, optimal performance has not yet been attained. Challenges encountered include the translation methodology employed and the architectural limitations of the chosen model, which is primarily optimized for English texts. However, ongoing efforts are underway to address these challenges and enhance the model's performance. Our study represents a step towards improving automated symptom extraction in Slovenian clinical texts, with ongoing work focused on mitigating identified issues to achieve better outcomes.

关键词： Adaptation models Translation Accuracy Text analysis Annotations Computational modeling Data models Mathematical models Reliability Tuning

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Distortion Correction for Imaging Using a Wavefront Sensing Based Multiple-Input Deep Neural Network

Distortion Correction for Imaging Using a Wavefront Sensing ...

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2023 Computational Optical Sensing and Imaging, COSI 2023 in Optica Imaging Congress - Part of Imaging and Applied Optics Congress 2023

作者： Büttner, Lars Gao, Zeyu Yang, Ping Bilsing, Clemens Czarske, Jürgen Faculty of Electrical and Computer Engineering Technische Universität Dresden Dresden01062 Germany Key Laboratory on Adaptive Optics Institute of Optics and Electronics Chinese Academy of Sciences Chengdu610209 China

An actuator-free aberration correction using a multiple-input deep convolutional neural network is presented. It uses an additional wavefront sensor input to correct time-varying low-order aberrations. These advantage... 详细信息

ISBN: (纸本)9781957171289

关键词： Deep neural networks

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Impact of PON network range and laser power on GPON and XGSPON coexistence system 8

Impact of PON network range and laser power on GPON and XGSP...

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8th IEEE International Conference on Image and Signal Processing and their Applications, ISPA 2024

作者： Kherici, Cheikh Kandouci, Malika Bechikh, Amel Benhamidi, Aicha Laboratory of Electromagnetism Photonics and Optronics L.E.P.O Faculty of Mathematics and Computer Science Computer Science Department Sidi Bel Abbes Algeria Ibn Khaldoun University of Tiaret Tiaret Algeria Laboratory of Electromagnetism Photonics and Optronics L.E.P.O Faculty of Electrical Engineering Electronics Department Sidi Bel Abbes Algeria Djillali Liabes University of Sidi Bel Abbes Sidi Bel Abbes Algeria Ibn Khaldoun University of Tiaret Faculty of Mathematics and Computer Science Computer Science Department Tiaret Algeria

ISBN: (纸本)9798350309249

This article discusses the effect of laser emission power and PON network range when GPON and XGSPON systems coexist. The analysis aims to understand how these two factors influence the overall performance and stability of the coexistence between the two optical network technologies. In order to also meet the increasing demand for data rates and new services such as videoconferencing and very high-quality television (4K, 6K,...etc). the coexistence system is preferred, allowing effective collaboration between GPON and XGSPON *** work deals with the performance evaluation of GPON and XGSPON systems, focusing on reconciliations and adjustments related to BER error rates and Q factor. The study explores different scenarios by adjusting the laser power from -12 dBm to 12 dBm and varying the array range from 10 km to 120 km. The main objective is to determine the best combination of laser power and network range to ensure optimal performance for coexistence systems. © 2024 IEEE.

关键词： Q factor measurement

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Enhancing Grape Drying Efficiency: A Thermo-Ecological Analysis of a Hybrid Solar Greenhouse Dryer 4

Enhancing Grape Drying Efficiency: A Thermo-Ecological Analy...

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4th International Conference on Green Energy, Environment and Sustainable Development, GEESD 2023

作者： Ihoume, Ilham Tadili, Rachid Arbaoui, Nora Daoudi, Mohamed Selim, Alaa Solar Energy and Environment Laboratory Faculty of Sciences Mohammed v University in Rabat B.P 1014 Rabat Morocco Electrical and Computer Engineering Department University of Connecticut United States

ISBN: (纸本)9781643684260

Over the past few years, there has been a substantial increase in attention and notable interest in the utilization of solar energy for agricultural applications. This increased attention stems from the recognition of solar energy as a compelling and environmentally conscious alternative to conventional energy sources. Among the various applications, solar drying of crops has emerged as a promising method for preserving agricultural produce while minimizing energy consumption and reducing carbon emissions. In this study, our objective is to assess the thermoeconomic and ecological performance of a solar-electric hybrid greenhouse dryer specifically designed for grape drying. The proposed system integrates solar collectors, an electric heater, and a greenhouse structure to create a controlled and energy-efficient environment for grape drying. The assessment includes a thorough analysis of the thermal performance, energy consumption, and cost-effectiveness of the solar-electric hybrid greenhouse dryer. Additionally, an ecological assessment is performed to assess the environmental impact of the system, considering factors such as carbon emissions and sustainability. The findings of this study are expected to have a significant impact on the advancement of sustainable agricultural practices and the widespread adoption of renewable energy technologies in the field of food production. Moreover, the obtained results serve as valuable insights for designing and optimizing similar solar drying systems intended for different crops and geographical regions. By considering specific crop characteristics and local environmental conditions, researchers and engineers can develop efficient and customized solar drying solutions. This knowledge will ultimately enhance the effectiveness and applicability of solar drying technologies, facilitating sustainable agricultural practices across diverse contexts. © 2023 IOS Press BV. All rights reserved.

关键词： Crops

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Efficient Hardware Design of a Secure Cancellable Biometric Cryptosystem

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Intelligent Automation & Soft Computing 2023年第4期36卷 929-955页

作者： Lamiaa A.Abou Elazm Walid El-Shafai Sameh Ibrahim Mohamed G.Egila H.Shawkey Mohamed K.H.Elsaid Naglaa F.Soliman Hussah Nasser AlEisa Fathi E.Abd El-Samie Department of Microelectronics Electronics Research InstituteAlnozhaEgypt Department of Electronics and Electrical Communications Engineering Ain Shams UniversityCairoEgypt Department of Electronics and Electrical Communications Faculty of Electronic EngineeringMenoufia UniversityMenouf32952Egypt Security Engineering Laboratory Department of Computer SciencePrince Sultan UniversityRiyadh 11586Saudi Arabia Department of Information Technology College of Computer and Information SciencesPrincess Nourah Bint Abdulrahman UniversityP.O.Box 84428Riyadh 11671Saudi Arabia Department of Computer Sciences College of Computer and Information SciencesPrincess Nourah Bint Abdulrahman UniversityRiyadhSaudi Arabia

Biometric security is a growing trend,as it supports the authentication of persons using conﬁdential biometric *** of the transmitted data in multi-media systems are susceptible to attacks,which affect the security of these *** systems provide sufﬁcient protection and privacy for *** recently-introduced cancellable biometric recognition systems have not been investigated in the presence of different types of *** addition,they have not been studied on different and large biometric *** point that deserves consideration is the hardware implementation of cancellable biometric recognition *** paper presents a suggested hybrid cancellable biometric recognition system based on a 3D chaotic *** rationale behind the utilization of the 3D chaotic cryptosystem is to guarantee strong encryption of biometric templates,and hence enhance the security and privacy of *** suggested cryptosystem adds signiﬁcant permutation and diffusion to the encrypted biometric *** introduce some sort of attack analysis in this paper to prove the robustness of the proposed cryptosystem against *** addition,a Field Programmable Gate Array(FPGA)implementation of the pro-posed system is *** obtained results with the proposed cryptosystem are compared with those of the traditional encryption schemes,such as Double Random Phase Encoding(DRPE)to reveal superiority,and hence high recogni-tion performance of the proposed cancellable biometric recognition *** obtained results prove that the proposed cryptosystem enhances the security and leads to better efﬁciency of the cancellable biometric recognition system in the presence of different types of attacks.

关键词： Information security cancellable biometric recognition systems cryptanalysis 3D chaotic map encryption FPGA

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Low-Cost, High-Performance Algorithm and Hardware Architecture for SAO Mode Decision 2

Low-Cost, High-Performance Algorithm and Hardware Architectu...

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2nd IEEE International Conference on Signal, Information and Data Processing, ICSIDP 2024

作者： Hou, Bingjing Liu, Chang Zhang, Yuejun Huang, Leilei Jing, Minge Fan, Yibo Fudan University State Key Laboratory of Integrated Chips and Systems Shanghai China Ningbo University Faculty of Electrical Engineering and Computer Science Ningbo China East China Normal University Institute of Microelectronic Circuits and Systems Shanghai China

ISBN: (纸本)9798331515669

Sample adaptive offset (SAO) is applied for reducing sample distortion and attenuating ringing artifacts in both HEVC and VVC standards. The rate-distortion optimization process is used to select the best SAO parameter. It accounts for the majority of SAO complexity and determines the SAO filtering performance. Therefore, the rate-distortion cost calculation should be well handled to achieve both low cost and high coding performance. In this paper, we propose a simplified and optimized rate estimation algorithm based on the characteristics of SAO parameter syntax and entropy coding process. And we propose a hierarchical flow for rate-distortion cost calculation to further reduce the computational cost and storage cost for SAO mode decision hardware. The results show that the proposed algorithm achieves an average YUV loss of -0.10%, and the proposed SAO mode decision hardware architecture can be implemented by only 21.8k gates using TSMC 65nm process under 400 MHz. © 2024 IEEE.

关键词： Electric distortion

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Effect of thickness of antimony selenide film on its photoelectric properties and microstructure

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Chinese Physics B 2023年第2期32卷 485-492页

作者：刘欣丽翁月飞毛宁张培晴林常规沈祥戴世勋宋宝安 Faculty of Electrical Engineering and Computer Science Ningbo UniversityNingbo 315211China The Research Institute of Advanced Technologies Ningbo UniversityNingbo 315211China Key Laboratory of Photoelectric Detecting Materials and Devices of Zhejiang Province Ningbo 31521China Ningbo Institute of ceangraphy Ningbo UniversityNingbo 315211China Engineering Research Center for Advanced Infrared Photoelectric Materials and Devices of Zhejiang Province Ningbo 315211China

Antimony selenide(Sb2Se3) films are widely used in phase change memory and solar cells due to their stable switching effect and excellent photovoltaic properties. These properties of the films are affected by the film thickness. A method combining the advantages of Levenberg–Marquardt method and spectral fitting method(LM–SFM) is presented to study the dependence of refractive index(RI), absorption coefficient, optical band gap, Wemple–Di Domenico parameters, dielectric constant and optical electronegativity of the Sb2Se3films on their thickness. The results show that the RI and absorption coefficient of the Sb2Se3films increase with the increase of film thickness, while the optical band gap decreases with the increase of film thickness. Finally, the reasons why the optical and electrical properties of the film change with its thickness are explained by x-ray diffractometer(XRD), energy dispersive x-ray spectrometer(EDS), Mott–Davis state density model and Raman microstructure analysis.

关键词： antimony selenide films photoelectric properties Levenberg–Marquardt method and spectral fitting method(LM–SFM) microstructure

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Deep Contrastive Learning Network for Small-Sample Hyperspectral Image Classification

Journal of Remote Sensing

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Journal of Remote Sensing 2023年第1期3卷 74-90页

作者： Quanyong Liu Jiangtao Peng Genwei Zhang Weiwei Sun Qian Du Hubei Key Laboratory of Applied Mathematics Faculty of Mathematics and StatisticsHubei UniversityWuhanChina Department of Gas Sensors and Chemometrics State Key Laboratory of NBC Protection for CivilianBeijingChina Department of Geography and Spatial Information Techniques Ningbo UniversityNingboChina Department of Electrical and Computer Engineering Mississippi State UniversityMississippi StateUSA

Recently,deep learning methods have been widely used in hyperspectral image(HSI)classification and achieved good ***,the performance of these methods may be limited because of the scarcity of labeled samples in HSI *** solve the small-sample classification problem,a deep contrastive learning network(DCLN)method is proposed in this *** proposed DCLN method first constructs contrastive groups and trains the network through contrastive ***,it uses the trained network to extract spectral-spatial features of HSI pixels and generates pseudo-label for each unlabeled sample based on the spatial-spectral mixing ***,the pseudo-labeled samples with higher confidence are selected and added to the original training set to retrain the *** gradually increasing pseudo-labeled samples and refining the contrastive learning network,the model shows good feature learning ability and classification performance with the limited labeled *** results on 4 public HSI datasets demonstrate that the proposed DCLN method can achieve better performance than existing state-of-the-art methods.

关键词： DCL Deep network

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Fuzzy Logic Controller for 4WD/4WS Autonomous Agricultural Robotic 3

Fuzzy Logic Controller for 4WD/4WS Autonomous Agricultural R...

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3rd IEEE International Conference on Electronics, Control, Optimization and computer Science, ICECOCS 2022

作者： Hayat, Ait Dahmad Hassan, Ayad Hajar, Moussanif Ali, El Allaoui Cadi Ayyad University Faculty of Sciences and Technics Electrical Systems and Telecommunication Laboratory Marrakesh Morocco Cadi Ayyad University Faculty of Sciences Semlalia Computer Systems Engineering Laboratory Marrakesh Morocco

ISBN: (数字)9781665457231

ISBN: (纸本)9781665457231

A Type 1 Takagi Sugeno Fuzzy Logic Controller (T1TSFLC) for a weeding agricultural robot with four-wheel steering (4WS) and four-wheel drive (4WD) is proposed in this paper. Two basic behaviors are studied and simulated: Goal-finding and obstacle-avoidance. The simulation results under a variety of scenarios illustrate the effectiveness and robustness of the T1TSFL navigator for controlling a 4WS/4WD robot in an unstructured and uncertain environment. © 2022 IEEE.

关键词： Agricultural robots

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An Efficient Medical Image Deep Fusion Model Based on Convolutional Neural Networks

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computers, Materials & Continua 2023年第2期74卷 2905-2925页

作者： Walid El-Shafai Noha A.El-Hag Ahmed Sedik Ghada Elbanby Fathi E.Abd El-Samie Naglaa F.Soliman Hussah Nasser AlEisa Mohammed E.Abdel Samea Department of Electronics and Electrical Communications Engineering Faculty of Electronic EngineeringMenoufia UniversityMenouf32952Egypt Security Engineering Laboratory Department of Computer SciencePrince Sultan UniversityRiyadh11586Saudi Arabia Higher Institute of Commercial Science Management Information SystemsEl-Mahala El-KobraEgypt Department of the Robotics and Intelligent Machines Faculty of Artificial IntelligenceKafrelsheikh UniversityKafr El-SheikhEgypt Department of Industrial Electronics and Control Engineering Faculty of Electronic EngineeringMenoufia UniversityMenouf32952Egypt Department of Information Technology College of Computer and Information SciencesPrincess Nourah Bint Abdulrahman UniversityP.O.Box 84428Riyadh11671Saudi Arabia Department of Computer Sciences College of Computer and Information SciencesPrincess Nourah Bint Abdulrahman UniversityRiyadhSaudi Arabia Medical Imaging and Interventional Radiology National Liver InstituteMenoufia UniversityEgypt

Medical image fusion is considered the best method for obtaining one image with rich details for efficient medical diagnosis and *** learning provides a high performance for several medical image analysis *** paper proposes a deep learning model for the medical image fusion *** model depends on Convolutional Neural Network(CNN).The basic idea of the proposed model is to extract features from both CT and MR ***,an additional process is executed on the extracted *** that,the fused feature map is reconstructed to obtain the resulting fused ***,the quality of the resulting fused image is enhanced by various enhancement techniques such as Histogram Matching(HM),Histogram Equalization(HE),fuzzy technique,fuzzy type,and Contrast Limited Histogram Equalization(CLAHE).The performance of the proposed fusion-based CNN model is measured by various metrics of the fusion and enhancement *** realistic datasets of different modalities and diseases are tested and ***,real datasets are tested in the simulation analysis.

关键词： Image fusion CNN deep learning feature extraction evaluation metrics medical diagnosis

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