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An Improved Deep Learning Framework for Automated Optic Disc Localization and Glaucoma Detection

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Computer Modeling in Engineering & Sciences 2024年第8期140卷 1429-1457页

作者： Hela Elmannai Monia Hamdi Souham Meshoul Amel Ali Alhussan Manel Ayadi Amel Ksibi 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 UniversityP.O.Box 84428Riyadh11671Saudi Arabia Department of information System College of Computer and Information SciencesPrincess Nourah bint Abdulrahman UniversityP.O.Box 84428Riyadh11671Saudi Arabia

Glaucoma disease causes irreversible damage to the optical nerve and it has the potential to cause permanent loss of *** ranks as the second most prevalent cause of permanent *** glaucoma diagnosis requires a highly experienced specialist,costly equipment,and a lengthy wait *** automatic glaucoma detection,state-of-the-art glaucoma detection methods include a segmentation-based method to calculate the cup-to-disc *** methods include multi-label segmentation networks and learning-based methods and rely on hand-crafted *** the optic disc(OD)is one of the key features in retinal images for detecting retinal diseases,especially for glaucoma disease *** approach presented in this study is based on deep classifiers for OD segmentation and glaucoma ***,the optic disc detection process is based on object detection using a Mask Region-Based Convolutional Neural Network(Mask-RCNN).The OD detection task was validated using the Dice score,intersection over union,and accuracy *** OD region is then fed into the second stage for glaucoma ***,considering only the OD area for glaucoma detection will reduce the number of classification artifacts by limiting the assessment to the optic disc *** this task,VGG-16(Visual Geometry Group),Resnet-18(Residual Network),and Inception-v3 were pre-trained and *** also used the Support Vector Machine *** feature-based method uses region content features obtained by Histogram of Oriented Gradients(HOG)and Gabor *** final decision is based on weighted fusion.A comparison of the obtained results from all classification approaches is *** metrics including accuracy and ROC curve are compared for each classification *** novelty of this research project is the integration of automatic OD detection and glaucoma diagnosis in a global ***,the fusion-based decision system uses the g

关键词： Optic disc glaucoma fundus image deep learning

ContextAug:model-domain failing test augmentation with contextual information

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Frontiers of Computer Science 2024年第2期18卷 43-60页

作者： Zhuo ZHANG Jianxin XUE Deheng YANG Xiaoguang MAO School of information Technology and Engineering Guangzhou College of CommerceGuangzhou 511363China School of Computer and information Engineering Institute for Artificial IntelligenceShanghai Polytechnic UniversityShanghai 201209China college of Computer National University of Defense TechnologyChangsha 410073China

In the process of software development,the ability to localize faults is crucial for improving the efficiency of *** speaking,detecting and repairing errant behavior at an early stage of the development cycle considerably reduces costs and development *** have tried to utilize various methods to locate the faulty ***,failing test cases usually account for a small portion of the test suite,which inevitably leads to the class-imbalance phenomenon and hampers the effectiveness of fault ***,in this work,we propose a new fault localization approach named *** obtaining dynamic execution through test cases,ContextAug traces these executions to build an information model;subsequently,it constructs a failure context with propagation dependencies to intersect with new model-domain failing test samples synthesized by the minimum variability of the minority feature *** contrast to traditional test generation directly from the input domain,ContextAug seeks a new perspective to synthesize failing test samples from the model domain,which is much easier to augment test *** conducting empirical research on real large-sized programs with 13 state-of-the-art fault localization approaches,ContextAug could significantly improve fault localization effectiveness with up to 54.53%.Thus,ContextAug is verified as able to improve fault localization effectiveness.

关键词： context fault localization test cases

Separation identification of a neural fuzzy Wiener–Hammerstein system using hybrid signals

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Frontiers of information Technology & Electronic Engineering 2024年第6期25卷 856-868页

作者： Feng LI Hao YANG Qingfeng CAO college of Electrical and information Engineering Jiangsu University of TechnologyChangzhou 213001China college of Electrical Energy and Power EngineeringYangzhou UniversityYangzhou 225127China

A novel separation identification strategy for the neural fuzzy Wiener–Hammerstein system using hybrid signals is developed in this *** Wiener–Hammerstein system is described by a model consisting of two linear dynamic elements with a nonlinear static element in *** static nonlinear element is modeled by a neural fuzzy network(NFN)and the two linear dynamic elements are modeled by an autoregressive exogenous(ARX)model and an autoregressive(AR)model,*** the system input is Gaussian signals,the correlation technique is used to decouple the identification of the two linear dynamic elements from the nonlinear ***,based on the input and output of Gaussian signals,the correlation analysis technique is used to identify the input linear element and output linear element,which addresses the problem that the intermediate variable information cannot be measured in the identified Wiener–Hammerstein ***,a zero-pole match method is adopted to separate the parameters of the two linear ***,the recursive least-squares technique is used to identify the nonlinear element based on the input and output of random signals,which avoids the impact of output *** feasibility of the presented identification technique is demonstrated by an illustrative simulation example and a practical nonlinear *** results show that the proposed strategy can obtain higher identification precision than existing identification algorithms.

关键词： Wiener-Hammerstein system Neural fuzzy network Correlation analysis technique Hybrid signals Separation identification

A Robust Approach for Multi Classification-Based Intrusion Detection through Stacking Deep Learning Models

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Computers, Materials & Continua 2024年第6期79卷 4845-4861页

作者： Samia Allaoua Chelloug Department of information Technology College of Computer and Information SciencesPrincess Nourah bint Abdulrahman UniversityRiyadh11671Saudi Arabia

Intrusion detection is a predominant task that monitors and protects the network ***,many datasets have been published and investigated by researchers to analyze and understand the problem of intrusion prediction and *** particular,the Network Security Laboratory-Knowledge Discovery in Databases(NSL-KDD)is an extensively used benchmark dataset for evaluating intrusion detection systems(IDSs)as it incorporates various network traffic *** is worth mentioning that a large number of studies have tackled the problem of intrusion detection using machine learning models,but the performance of these models often decreases when evaluated on new *** has led to the utilization of deep learning techniques,which have showcased significant potential for processing large datasets and therefore improving detection *** that reason,this paper focuses on the role of stacking deep learning models,including convolution neural network(CNN)and deep neural network(DNN)for improving the intrusion detection rate of the NSL-KDD *** base model is trained on the NSL-KDD dataset to extract significant *** the base models have been trained,the stacking process proceeds to the second stage,where a simple meta-model has been trained on the predictions generated from the proposed base *** combination of the predictions allows the meta-model to distinguish different classes of attacks and increase the detection *** experimental evaluations using the NSL-KDD dataset have shown the efficacy of stacking deep learning models for intrusion *** performance of the ensemble of base models,combined with the meta-model,exceeds the performance of individual *** stacking model has attained an accuracy of 99%and an average F1-score of 93%for the multi-classification ***,the training time of the proposed ensemble model is lower than the training time of benchmark techniques,demonstrating its efficien

关键词： Intrusion detection multi classification deep learning stacking NSL-KDD

A New Random Sampling Method and Its Application in Improving Progressive BKZ Algorithm

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Journal of Systems Science & Complexity 2024年第5期37卷 2262-2292页

作者： SUN Minghao WANG Shixiong CHEN Hao QU Longjiang college of Sciences National University of Defense Technology Academy of Military Sciences college of information Science and Technology/Cyber Security Jinan University

Random sampling algorithm was proposed firstly by Schnorr in 2003 to find short lattice vectors, as an alternative to enumeration. The follow-up developments in random sampling were mainly proposed by Fukase and Kashiwabara in 2015 and Aono and Nguyen in 2017. Although they extended the sampling space compared to Schnorr's work through the natural number representation, they did not show how to sample specifically in practice and what vectors should be sampled, in order to find short enough lattice vectors. In this paper, the authors firstly introduce a practical random sampling algorithm under some reasonable assumptions which can find short enough lattice vectors ***, as an application of this new random sampling algorithm, the authors show that it can improve the performance of progressive BKZ algorithm in practice. Finally, the authors solve the Darmstadt's Lattice Challenge and get a series of new records in the dimension from 500 to 825, using the improved progressive BKZ algorithm.

关键词： Darmstadt’s lattice challenge lattice lattice reduction algorithm post-quantum cryptography random sampling

Dynamic Analysis of Incentive Policy Impacts on Recycling of Retired Batteries for Electric Vehicles

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Journal of Systems Science and information 2024年第4期12卷 491-514页

作者： Cuixia WANG Lang WEI School of information Management Jiangxi University of Finance and Economics School of Economics and Management Hunan College of Information

Electric Vehicles(EVs), as a low-carbon means of transportation, have promptly become popular worldwide in the past decade. Since the lifespan of batteries is limited, massive of Electric Vehicle Batteries(EVBs) are being retired, resulting in a rapid increase in the demand for the recycling of retired EVBs in recent years. However, due to high recycling costs and immature recycling technologies, EV manufacturers are facing significant challenges in recycling retired EVBs. China, as the country with the largest number of EV users in the world, is exploring effective incentive policies for the recycling of retired EVBs. In this context, we developed a system dynamics model to analyze the impact of incentive polices such as, recycling subsidies, technological progress, and carbon trading on the retired EVBs recycling. Results show that: 1) recycling subsidies can improve the recycling ratios quickly in the short term, and dynamic subsidies are more efficient than static subsidies; 2) the policy of technological advancement can reduce the recovery and cascade utilization cost, thus having a positive impact on battery recycling, but the policy effect has a time-delay; 3) the carbon trading policy is unable to promote efficient recycling due to the current low carbon prices; 4) dynamic subsidy and technological advancement policies complement each other, therefore, the combination of these two policies is the best way to promote the recycling of retired EVBs and reduce carbon emissions. It is hoped that this study will contribute to the ongoing debate on policies for the industrialization of retired EVBs recycling.

关键词： electric vehicles retired battery recycling policy impact system dynamics

Multicolor emission from lanthanide ions doped lead-free Cs_(3)Sb_(2)Cl_(9) perovskite nanocrystals

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Journal of Rare Earths 2024年第5期42卷 940-946,I0005页

作者： He Shao Lifang Li Xiufeng Wu Lin Xu Biao Dong Donglei Zhou Xue Bai Hongwei Song State Key Laboratory of Organic electronics and information Displays&Institute of Advanced Materials College of Materials Science and EngineeringNanjing University of Posts&TelecommunicationsNanjing210023China State Key Laboratory of Integrated Optoelectronics College of Electronic Science and Engineering Jilin UniversityChangchun130012China

The toxicity of lead ions has become the severe challenge for the all-inorganic lead halide p erovskite materials,although some works have rep orted the lead-free perovskite nanocrystals(NCs),the photoluminescence quantum yield(PLQY)of these materials is still ***,because the halogen ions can be easily exchanged,the controllable multicolor emission in perovskite NCs is difficult to realize in current *** this work,we introduced lanthanide ions into lead-free Cs_(3)Sb_(2)Cl_(9) perovskite *** from the energy transfer between Cs_(3)Sb_(2)Cl_(9) perovskite NC host and lanthanide ions,the multicolor emission was *** on controlling the doping concentration of Tb^(3+)and Eu^(3+)ions,the white light emission under UV excitation would be turned easily in the Tb^(3+)/Eu^(3+)codoped *** addition,efficient energy transfer from perovskite NCs to Tb^(3+)or Eu^(3+)ions is beneficial to improving the optical properties of lead-free perovskite NCs,resulting in maximum PLQYs of red,green and white light emission of 22.6%,19.7%and 28.5%,***,a white light emitting device(WLED)was fabricated with a power efficiency of 18.5 lm/W,which presents the Commission Internationale de l'Eclairage(CIE)of(0.33,0.35).

关键词： Perovskite nanocrystals Lead free Lanthanide ions Energy transfer White light emitting device Rare earths

Tunable hexagonal boron nitride topological optical delay line in the visible region

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Chinese Optics Letters 2024年第5期22卷 124-130页

作者：费宏明武敏林瀚杨毅彪肖连团 college of Physics Taiyuan University of TechnologyTaiyuan 030024China college of information Engineering Shanxi Vocational University of Engineering Science and TechnologyJinzhong 030619China college of Science RMIT UniversityMelbourneVictoria 3000Australia college of Electronic information and Optical Engineering Taiyuan University of TechnologyTaiyuan 030024China

Tunability,ultracompact design,high group index,low loss,and broad bandwidth are desired properties for integrated optical delay lines(ODLs).However,those properties are challenging to achieve simultaneously in the visible *** paper proposes a tunable hexagonal boron nitride topological optical delay line(ODL)in the visible region based on valley photonic *** topological edge state from the beard-type boundary allows the achievement of an ultralow group velocity close to zero,which results in a large group index of 629 at 645 ***,we demonstrate tuning of the slow-light wavelength and optical delay times with electrically tunable liquid crystals by applying external *** device has an ultracompact size of 5μm×2.7μm with an optical delay distance of 25a(a is the lattice constant)and a delay time of 12 *** design can provide a new possibility for designing ODLs working in the visible region for optical communication and quantum computing systems.

关键词： valley photonic crystal topological edge states optical delay lines

Social Media-Based Surveillance Systems for Health Informatics Using Machine and Deep Learning Techniques:A Comprehensive Review and Open Challenges

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Computer Modeling in Engineering & Sciences 2024年第5期139卷 1167-1202页

作者： Samina Amin Muhammad Ali Zeb Hani Alshahrani Mohammed Hamdi Mohammad Alsulami Asadullah Shaikh Institute of Computing Kohat University of Science and TechnologyKohat26000Pakistan Department of Computer Science College of Computer Science and Information SystemsNajran UniversityNajran61441Saudi Arabia Department of information System College of Computer Science and Information SystemsNajran UniversityNajran61441Saudi Arabia

Social media(SM)based surveillance systems,combined with machine learning(ML)and deep learning(DL)techniques,have shown potential for early detection of epidemic *** review discusses the current state of SM-based surveillance methods for early epidemic outbreaks and the role of ML and DL in enhancing their ***,every year,a large amount of data related to epidemic outbreaks,particularly Twitter data is generated by *** paper outlines the theme of SM analysis for tracking health-related issues and detecting epidemic outbreaks in SM,along with the ML and DL techniques that have been configured for the detection of epidemic *** has emerged as a promising ML technique that adaptsmultiple layers of representations or features of the data and yields state-of-the-art extrapolation *** recent years,along with the success of ML and DL in many other application domains,both ML and DL are also popularly used in SM *** paper aims to provide an overview of epidemic outbreaks in SM and then outlines a comprehensive analysis of ML and DL approaches and their existing applications in SM ***,this review serves the purpose of offering suggestions,ideas,and proposals,along with highlighting the ongoing challenges in the field of early outbreak detection that still need to be addressed.

关键词： Social media epidemic machine learning deep learning health informatics pandemic