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

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

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5G Resource Allocation Using Feature Selection and Greylag Goose Optimization Algorithm

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Computers, Materials & Continua 2024年第7期80卷 1179-1201页

作者： amel Ali Alhussan S.K.Towfek Department of Computer Sciences College of Computer and Information SciencesPrincess Nourah bint Abdulrahman UniversityP.O.Box 84428Riyadh11671Saudi Arabia Computer Science and Intelligent Systems Research Center BlacksburgVA 24060USA

In the contemporary world of highly efficient technological development,fifth-generation technology(5G)is seen as a vital step forward with theoretical maximum download speeds of up to twenty gigabits per second(Gbps).As far as the current implementations are concerned,they are at the level of slightly below 1 Gbps,but this allowed a great leap forward from fourth generation technology(4G),as well as enabling significantly reduced latency,making 5G an absolute necessity for applications such as gaming,virtual conferencing,and other interactive electronic *** of this change are not limited to connectivity alone;it urges operators to refine their business strategies and offers users better and improved digital *** essential factor is optimization and the application of artificial intelligence throughout the general arrangement of intricate and detailed 5G *** Binary Greylag Goose Optimization(bGGO)to achieve a significant reduction in the feature set while maintaining or improving model performance,leading to more efficient and effective 5G network management,and Greylag Goose Optimization(GGO)increases the efficiency of the machine ***,the model performs and yields more accurate *** work proposes a new method to schedule the resources in the next generation,5G,based on a feature selection using GGO and a regression model that is an ensemble of K-Nearest Neighbors(KNN),Gradient Boosting,and Extra Trees *** ensemble model shows better prediction performance with the coefficient of determination R squared value equal *** proposed framework is supported by several Statistical analyses,such as theWilcoxon signed-rank *** of the benefits of this study are the introduction of new efficient optimization algorithms,the selection of features and more reliable ensemble models which improve the efficiency of 5G technology.

关键词： Optimization ensemble learning 5G technology artificial intelligence greylag goose optimization ANOVA test

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Desmoid Tumor of the Breast as a Manifestation of Gardner’s Syndrome in an Elderly Woman: A Case Report and Review of Literature

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Case Reports in Clinical Medicine 2018年第11期7卷 533-540页

作者： Olfa Zoukar amel khaskhoussy Sonia Hammami Sandra Zribi Awatef Hajjajji Anis Haddad Raja Faleh Maternity and Neonatology Center Monastir University Monastir Tunisia Department of Internal Medicine F Bourguiba University Hospital Monastir Tunisia

Desmoid tumor of the breast is an extremely rare entity. Histologically, it corresponds to a benign fibroblastic proliferation of a local evolution, with a high recurrence potential. We report the first case of elderly woman presented with desmoid-tumor of the breast as a manifestation of Gardner’s syndrome. A brief literature review was provided. We report the case of a 72-year-old woman who presented with five months history of painful and an exophytic mass of her left breast. She is known to have familial polyposis and had a total colectomy with Gardner’s syndrome. She had a history of osteomas of the maxilla. On clinical examination, there was an exophytic painless mass, on the upper medial quadrant of the breast. She had also lipoma in the left leg and pigmented skin lesions in legs. Her mammograms showed a suspicious stellar image. A computed tomography scan showed an ovoid lesion. Excision of the lesion was performed. Histopathology confirms a desmoid-tumor of the breast. Evolution was marked by lesion recurrence. In conclusion, desmoid tumor of the breast is rare, non-metastatic but locally aggressive. Clinical expression is often nonspecific. Treatment remains controversial;surgical excision is the treatment of choice.

关键词： Desmoid-Tumor Gardner’s Syndrome Elderly Breast Familial Polyposis

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Application of Plant-Based Coagulants and Their Mechanisms in Water Treatment:A Review

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Journal of Renewable Materials 2024年第4期12卷 667-698页

作者： Abderrezzaq Benalia Kerroum Derbal Zahra Amrouci Ouiem Baatache amel Khalfaoui Antonio Pizzi Higher Normal School of Constantine Ali Mendjeli Nouvelle VilleConstantine25000Algeria Laboratory of Process Engineering for Sustainable Development and Health Products(GPDDPS) Department of Process EngineeringNational Polytechnic School of ConstantineConstantine25000Algeria Department of Environmental Engineering Laboratoire de Recherche sur le Médicament et le Développement Durable(ReMeDD)University of Salah Boubnider Constantine 3El Khroub25012Algeria Laboratory LIPE Faculty Process EngineeringUniversity of Constantine 3Ali Mendjeli Nouvelle VilleConstantine25000Algeria Laboratoire d’Etude et Recherche sur le Matériau Bois(LERMAB).Ecole Nationale Supérieure des Technologies et Industries du Bois(ENSTIB)—University of Lorraine Epinal88000France

This review describes the mechanisms of natural *** provides a good understanding of the two key processes of coagulation-flocculation:adsorption and charge neutralization,as well as adsorption and *** factors have influence the coagulation/flocculation process,including the effect of pH,coagulant dosage,coagulant type,temperature,initial turbidity,coagulation speed,flocculation speed,coagulation and flocculation time,settling time,colloidal particles,zeta potential,the effects of humic acids,and extraction density are *** bio-coagulants derived from plants are *** impact of organic coagulants on water quality,focusing on their effects on the physicochemical parameters of water,heavy metals removal,and bacteriological water quality,is *** methods of extraction and purification of plant-based coagulants,highlighting techniques such as solvent extraction and ultrasonic extraction,are *** also examines the parameters that influence these *** methods and principles of purification of coagulating agents,including dialysis,freeze-drying,ion exchange,electrophoresis,filtration,and centrifugation,are ***,it evaluates the sustainability of natural coagulants,focusing on the environmental,technical,and economic aspects of their *** the end of this review,the readers should have a comprehensive understanding of the mechanisms,selection,extraction,purification,and sustainability of plant-based natural coagulants in water treatment.

关键词： Bio-coagulants coagulating agents extraction water treatment

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Urban Electric Vehicle Charging Station Placement Optimization with Graylag Goose Optimization Voting Classifier

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Computers, Materials & Continua 2024年第7期80卷 1163-1177页

作者： amel Ali Alhussan Doaa Sami Khafaga El-Sayed M.El-kenawy Marwa M.Eid Abdelhameed Ibrahim Department of Computer Sciences College of Computer and Information SciencesPrincess Nourah bint Abdulrahman UniversityP.O.Box 84428Riyadh11671Saudi Arabia Department of Communications and Electronics Delta Higher Institute for Engineering and TechnologyMansoura35511Egypt Faculty of Artificial Intelligence Delta University for Science and TechnologyMansoura35712Egypt Computer Engineering and Control Systems Department Faculty of EngineeringMansoura UniversityMansoura35516Egypt

To reduce the negative effects that conventional modes of transportation have on the environment,researchers are working to increase the use of electric *** demand for environmentally friendly transportation may be hampered by obstacles such as a restricted range and extended rates of *** establishment of urban charging infrastructure that includes both fast and ultra-fast terminals is essential to address this ***,the powering of these terminals presents challenges because of the high energy requirements,whichmay influence the quality of *** the maximum hourly capacity of each station based on its geographic location is necessary to arrive at an accurate estimation of the resources required for charging *** is vital to do an analysis of specific regional traffic patterns,such as road networks,route details,junction density,and economic zones,rather than making arbitrary conclusions about traffic *** vehicle traffic is simulated using this data and other variables,it is possible to detect limits in the design of the current traffic engineering ***,the binary graylag goose optimization(bGGO)algorithm is utilized for the purpose of feature ***,the graylag goose optimization(GGO)algorithm is utilized as a voting classifier as a decision algorithm to allocate demand to charging stations while taking into consideration the cost variable of traffic *** on the results of the analysis of variance(ANOVA),a comprehensive summary of the components that contribute to the observed variability in the dataset is *** results of the Wilcoxon Signed Rank Test compare the actual median accuracy values of several different algorithms,such as the voting GGO algorithm,the voting grey wolf optimization algorithm(GWO),the voting whale optimization algorithm(WOA),the voting particle swarm optimization(PSO),the voting firefly algorithm(FA),and the voting genetic algori

关键词： Electric vehicle graylag goose optimization metaheuristics optimization machine learning

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模糊数学感官评价结合响应面法优化鲊辣椒混菌发酵工艺

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食品与发酵工业 2024年第7期50卷 83-91,I0004,I0005页

作者：黄璐晗尹小庆阚建全武运戚晨晨彭芸 SAMEH Awad amel Ibrahim 杜木英西南大学食品科学学院重庆400715 西南大学中匈食品科学合作研究中心重庆400715 川渝共建特色食品重庆市重点实验室重庆400715 西藏自治区农牧科学院农产品开发与食品科学研究所西藏拉萨850032 新疆农业大学食品科学与药学学院新疆乌鲁木齐830000 新疆新康农业发展有限公司新疆乌鲁木齐830000 亚历山大大学农学院埃及亚历山大999060

以小米椒和玉米粉为原料,植物乳植杆菌XZ3和生香酵母菌Y50为菌种,制作一款混菌发酵鲊辣椒。以鲊辣椒的模糊感官评分为响应值,采用Box-Behnken中心组合设计试验对鲊辣椒混菌发酵工艺进行优化,并测定其产品的功能性成分。结果表明,混菌发... 详细信息

以小米椒和玉米粉为原料,植物乳植杆菌XZ3和生香酵母菌Y50为菌种,制作一款混菌发酵鲊辣椒。以鲊辣椒的模糊感官评分为响应值,采用Box-Behnken中心组合设计试验对鲊辣椒混菌发酵工艺进行优化,并测定其产品的功能性成分。结果表明,混菌发酵鲊辣椒的最优发酵条件为:植物乳植杆菌XZ3与生香酵母菌Y50的比例为1∶1、混菌添加量为2.5%、食盐添加量为4%、发酵时间6 d。在此优化条件下,鲊辣椒的感官评分为8.45分。与不接种自然发酵鲊辣椒和利用植物乳植杆菌XZ3纯种发酵的鲊辣椒进行对比,发现优化后的混菌发酵鲊辣椒的香气更突出。进一步测定其功能性成分发现,混菌发酵鲊辣椒中多酚组分含量最高且种类检出最多,其总酸含量、辣椒碱含量和总黄酮含量都显著高于自然发酵鲊辣椒。除此之外,相比于其他两种,混菌发酵鲊辣椒中甜味氨基酸的含量上升,苦味氨基酸的比例降低。该研究为混菌发酵鲊辣椒的生产提供了有益参考。

关键词：鲊辣椒响应面分析模糊数学感官评定发酵工艺功能性成分

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Online conflict resolution strategies for human activity recognition in smart homes

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Journal of Control and Decision 2023年第3期10卷 402-416页

作者： Amina Jarraya amel Bouzeghoub amel Borgi Facultédes Sciences de Tunis Universitéde Tunis El ManarTunisTunisia Samovar Télécom SudParisInstitut Polytechnique de ParisPalaiseauFrance Facultédes Sciences de Tunis Institut Supérieur d’InformatiqueUniversitéde Tunis El ManarTunisTunisia

DCR-OL is a Distributed Collaborative Reasoning multi-agent model with an Online Learning thataims to identify human activities in smart homes from distributed, heterogeneous and dynamicsensor data. In this model, distributed learning agents with diverse classifiers, detect sensorstream data, make local predictions, communicate and collaborate to identify current ***, they learn from their collaborations to improve their own performance in activity *** resolution strategies are applied to generate one final predicted activity when thelocal predicted activity of an agent is different from received predicted activities of other *** this paper, two conflict resolution strategies using online learning, w-max-trust and w-maxfreq,are proposed. We experimentally test these strategies by performing an evaluation studyon the Aruba dataset. The obtained results indicate an enhancement in terms of accuracy and Fmeasuremetrics compared to the offline strategies max-trust and max-freq and also to the onlineexisting one max-wPerf .

关键词： Human activity recognition distributed reasoning learning agents smart homes online learning conflict resolution strategies sensor data stream

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Hybrid Optimization Algorithm for Resource Allocation in LTE-Based D2D Communication

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Computer Systems Science & Engineering 2023年第8期46卷 2263-2276页

作者： amel Austine RSuji Pramila Department of Computer Science and Engineering Noorul Islam Centre for Higher EducationKumaracoilTamilnaduIndia

In a cellular network,direct Device-to-Device(D2D)communication enhances Quality of Service(QoS)in terms of coverage,throughput and amount of power *** theD2D pairs involve cellular resources for communication,the chances of interference are high.D2D communications demand minimum interference along with maximum throughput and sum rate which can be achieved by employing optimal resources and efficient power allocation *** this research,a hybrid optimization model called Genetic Algorithm-Adaptive Bat Optimization(GA-ABO)algorithm is proposed for efficient resource allocation in a cellular network with D2D *** analysis demonstrates that the proposed model involves reduced interference with maximum sum rate and *** performance of the proposed model is compared with the existing Ant Colony Optimization-based resource exchange and GAME(ACO-GAME)theory models,Trader-assistedResource EXchange mechanism-RadioAccess Network(TREX-RAN)and De-centralized Radio Access Network(TREXDRAN),and greedy CYcle-Complete preferences(CYC)*** proposed model offers a maximum sum rate of 83 kB/s,which is much better than the existing techniques.

关键词： Device-to-Device communication Genetic Algorithm(GA) Adaptive Bat Optimization(ABO)algorithm resource exchange

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The Use of Aloe vera as Natural Coagulant in Algerian Drinking Water Treatment Plant

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Journal of Renewable Materials 2022年第3期10卷 625-637页

作者： Abderrezzaq Benalia Kerroum Derbal amel Khalfaoui Antonio Pizzi Ghouti Medjahdi Faculty Process Engineering University of Constantine 3Constantine25000Algeria National Polytechnic School of Constantine Constantine25000Algeria LERMAB-ENSTIB University of LorraineEpinal88000France Institut Jean Lamour Universitéde LorraineCNRSNancy54011France

The purpose of this work is the study the ability of the plant material Aloe vera to act as natural coagulant using raw water obtained from a drinking water treatment plant(Mila,Algeria).Different solvents such as:NaCl;NaOH and HCl were used as chemical activators to extract the active components from the Aloe vera plant,and different coagulation-flocculation experiments were conducted in a jar test apparatus to evaluate the perfor-mance of the extracted ***,the effect of coagulant dose on some water parameters such as turbidity,pH,total alkalinity and organic matter were *** results showed that the use of coagulants obtained by using different solvents increases the coagulation efficiency compared to the coagulant obtained from the raw material,for example the maximum turbidity removal efficiency was 28.23,78.07,83.46 and 85.15%when using powdered Aloe vera(raw material),AV-NaCl(0.5 M),AV-NaOH(0.05 M)and AV-HCl(0.05 M),*** results defined,that the residual turbidity obtained in this work,where the Aloe vera was used(after treat-ment by solvents)produced a turbidity lower than the Algerian standard(5 NTU)with initial turbidity(13 NTU).In this study,the infrared spectrum study and analysis has revealed the presence of different functional groups,which are responsible for the coagulation process.

关键词： Actives components coagulant colloidal particles infrared spectrum solvent

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Airstacknet: A Stacking Ensemble-Based Approach for Air Quality Prediction

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Computers, Materials & Continua 2023年第1期74卷 2073-2096页

作者： amel Ksibi Amina Salhi Ala Saleh Alluhaidan Sahar A.El-Rahman Department of Information Systems College of Computer and Information SciencesPrincess Nourah bint Abdulrahman UniversityRiyadhSaudi Arabia Electrical Engineering Department Faculty of Engineering-ShoubraBenha UniversityCairoEgypt

The quality of the airwe breathe during the courses of our daily lives has a significant impact on our health and well-being as ***,personal air quality measurement remains *** this study,we investigate the use of first-person photos for the prediction of air *** main idea is to harness the power of a generalized stacking approach and the importance of haze features extracted from first-person images to create an efficient new stacking model called AirStackNet for air pollution *** consists of two layers and four regression models,where the first layer generates meta-data fromLight Gradient Boosting Machine(Light-GBM),Extreme Gradient Boosting Regression(XGBoost)and CatBoost Regression(CatBoost),whereas the second layer computes the final prediction from the meta-data of the first layer using Extra Tree Regression(ET).The performance of the proposed AirStackNet model is validated using public Personal Air Quality Dataset(PAQD).Our experiments are evaluated using Mean Absolute Error(MAE),Root Mean Square Error(RMSE),Coefficient of Determination(R2),Mean Squared Error(MSE),Root Mean Squared Logarithmic Error(RMSLE),and Mean Absolute Percentage Error(MAPE).Experimental Results indicate that the proposed AirStackNet model not only can effectively improve air pollution prediction performance by overcoming the Bias-Variance tradeoff,but also outperforms baseline and state of the art models.

关键词： Personal air quality prediction airstacknet ensemble learning feature extraction stacking

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