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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

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Network Security Enhanced with Deep Neural Network-Based Intrusion Detection System

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Computers, Materials & Continua 2024年第7期80卷 1457-1490页

作者： Fatma S.alrayes mohammed Zakariah Syed Umar amin Zafar Iqbal Khan Jehad Saad alqurni Information Systems Department College of Computer and Information SciencesPrincess Nourah bint Abdulrahman UniversityRiyadh11671Saudi Arabia College of Computer and Information Sciences King Saud UniversityRiyadh11362Saudi Arabia College of Computer and Information Sciences Prince Sultan UniversityRiyadh11586Saudi Arabia Department of Educational Technologies College of EducationImam Abdulrahman Bin Faisal UniversityP.O.Box 1982Dammam31441Saudi Arabia

This study describes improving network security by implementing and assessing an intrusion detection system(IDS)based on deep neural networks(DNNs).The paper investigates contemporary technical ways for enhancing intrusion detection performance,given the vital relevance of safeguarding computer networks against harmful *** DNN-based IDS is trained and validated by the model using the NSL-KDD dataset,a popular benchmark for IDS *** model performs well in both the training and validation stages,with 91.30%training accuracy and 94.38%validation ***,the model shows good learning and generalization capabilities with minor losses of 0.22 in training and 0.1553 in ***,for both macro and micro averages across class 0(normal)and class 1(anomalous)data,the study evaluates the model using a variety of assessment measures,such as accuracy scores,precision,recall,and F1 *** macro-average recall is 0.9422,the macro-average precision is 0.9482,and the accuracy scores are ***,macro-averaged F1 scores of 0.9245 for class 1 and 0.9434 for class 0 demonstrate the model’s ability to precisely identify anomalies *** research also highlights how real-time threat monitoring and enhanced resistance against new online attacks may be achieved byDNN-based intrusion detection systems,which can significantly improve network *** study underscores the critical function ofDNN-based IDS in contemporary cybersecurity procedures by setting the foundation for further developments in this *** research aims to enhance intrusion detection systems by examining cooperative learning techniques and integrating up-to-date threat knowledge.

关键词： Machine-Learning Deep-Learning intrusion detection system security privacy deep neural network NSL-KDD Dataset

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CNN Channel Attention Intrusion Detection SystemUsing NSL-KDD Dataset

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Computers, Materials & Continua 2024年第6期79卷 4319-4347页

Intrusion detection systems(IDS)are essential in the field of cybersecurity because they protect networks from a wide range of online *** goal of this research is to meet the urgent need for small-footprint,highly-adaptable Network Intrusion Detection Systems(NIDS)that can identify *** NSL-KDD dataset is used in the study;it is a sizable collection comprising 43 variables with the label’s“attack”and“level.”It proposes a novel approach to intrusion detection based on the combination of channel attention and convolutional neural networks(CNN).Furthermore,this dataset makes it easier to conduct a thorough assessment of the suggested intrusion detection ***,maintaining operating efficiency while improving detection accuracy is the primary goal of this ***,typical NIDS examines both risky and typical behavior using a variety of *** the NSL-KDD dataset,our CNN-based approach achieves an astounding 99.728%accuracy rate when paired with channel *** to previous approaches such as ensemble learning,CNN,RBM(Boltzmann machine),ANN,hybrid auto-encoders with CNN,MCNN,and ANN,and adaptive algorithms,our solution significantly improves intrusion detection ***,the results highlight the effectiveness of our suggested method in improving intrusion detection precision,signifying a noteworthy advancement in this *** efforts will focus on strengthening and expanding our approach in order to counteract growing cyberthreats and adjust to changing network circumstances.

关键词： Intrusion detection system(IDS) NSL-KDD dataset deep-learning machine-learning CNN channel Attention network security

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Regulating microstructure and composition by carbonizing in-situ grown metal-organic frameworks on cotton fabrics for boosting electromagnetic wave absorption

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Nano Research 2024年第8期17卷 7290-7300页

作者： Jie Jin Hongsen Long Hu Liu Yan Guo Tiantian Bai Ben Bin Xu mohammed A.amin Hua Qiu Mohamed H.Helal Chuntai Liu Changyu Shen Zeinhom M.El-Bahy Zhanhu Guo State Key Laboratory of Structural Analysis Optimization and CAE Software for Industrial EquipmentNational Engineering Research Center for Advanced Polymer Processing TechnologyZhengzhou UniversityZhengzhou 450002China China State Key Laboratory of Powder Metallurgy Central South UniversityChangsha 410000China School of Electronic Engineering North China University of Water Resources and Electric PowerZhengzhou 450046China Complex Conditions of High-end Tire Technology Innovation Center Shuguang Rubber Industry Research&Design Institute Co.LtdGuilin 541004China Integrated Composites Lab Department of Mechanical and Civil EngineeringNorthumbria UniversityNewcastle Upon TyneNE18STUK Department of Chemistry College of ScienceTaif UniversityP.O.Box 11099Taif 21944Saudi Arabia Shaanxi Key Laboratory of Macromolecular Science and Technology School of Chemistry and Chemical EngineeringNorthwestern Polytechnical UniversityXi’an 710072China Department of Chemistry Faculty of Arts and ScienceNorthern Border UniversityRafha 73213Saudi Arabia Department of Chemistry Faculty of ScienceAl-Azhar UniversityNasr City 11884CairoEgypt

High-temperature carbonized metal-organic frameworks(MOFs)derivatives have demonstrated their superiority for promising electromagnetic wave(EMW)absorbers,but they still suffer from limited EMW absorption capacity and narrow *** the advantage of microstructure and chemical composition regulation for the design of EMW absorber,hierarchical heterostructured MoS_(2)/CoS_(2)-Co_(3)O_(4)@cabonized cotton fabric(CF)(MCC@CCF)is prepared by growing ZIF-67 MOFs onto CF surface,chemical etching,and *** from the dual loss mechanism of magnetic-dielectric multicomponent carbonized MOFs,chemical etching and carbonization process can effectively introduce abundant micro-gap structure that can result in better impedance matching and stronger absorption capacity via internal reflection,doped heteroatoms(Mo,N,S)to supply additional dipolar polarization loss,and numerous heterointerfaces among MoS_(2),CoS_(2),Co_(3)O_(4),and CCF that produce promoted conduction loss and interfacial polarization ***,a minimal reflection loss of−52.87 dB and a broadest effective absorption bandwidth of 6.88 GHz were achieved via tunning the sample thickness and filler loading,showing excellent EMW absorption *** research is of great value for guiding the research on MOFs derivatives based EMW absorbing materials.

关键词： metal-organic frameworks hierarchical structure chemical etching sulfurization electromagnetic wave absorption

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MXene@c-MWCNT Adhesive Silica Nanofiber Membranes Enhancing Electromagnetic Interference Shielding and Thermal Insulation Performance in Extreme Environments

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Nano-Micro Letters 2024年第10期16卷 82-98页

作者： Ziyuan Han Yutao Niu Xuetao Shi Duo Pan Hu Liu Hua Qiu Weihua Chen Ben Bin Xu Zeinhom MEl-Bahy Hua Hou Eman Ramadan Elsharkawy mohammed Aamin Chuntai Liu Zhanhu Guo Key Laboratory of Materials Processing and Mold(Zhengzhou University) Ministry of EducationNational Engineering Research Center for Advanced Polymer Processing TechnologyZhengzhou UniversityZhengzhou 450002People's Republic of China School of Nano-Tech and Nano-Bionics University of Science and Technology of ChinaHefei 230026People's Republic of China Key Laboratory of Multifunctional Nanomaterials and Smart Systems Advanced Materials DivisionSuzhou Institute of Nano-Tech and Nano-BionicsChinese Academy of SciencesSuzhou 215123People's Republic of China Shaanxi Key Laboratory of Macromolecular Science and Technology School of Chemistry and Chemical EngineeringNorthwestern Polytechnical UniversityXi'an 710072People's Republic of China College of Chemistry&Green Catalysis Center Zhengzhou UniversityZhengzhou 450001People's Republic of China Mechanical and Construction Engineering Faculty of Engineering and EnvironmentNorthumbria UniversityNewcastle Upon Tyne NE18UK Department of Chemistry Faculty of ScienceAl-Azhar UniversityNasr City 11884CairoEgypt Department of Chemistry Faculty of ScienceNorthern Border UniversityArarSaudi Arabia Department of Chemistry College of ScienceTaif UniversityP.O.Box 1109921944 TaifSaudi Arabia

A lightweight flexible thermally stable composite is fabricated by com-bining silica nanofiber membranes(SNM)with MXene@c-MWCNT hybrid *** flexible SNM with outstanding thermal insulation are prepared from tetraethyl orthosilicate hydrolysis and condensation by electrospinning and high-temperature calcination;the MXene@c-MWCNT_(x:y)films are prepared by vacuum filtration *** particular,the SNM and MXene@c-MWCNT_(6:4)as one unit layer(SMC_(1))are bonded together with 5 wt%polyvinyl alcohol(PVA)solution,which exhibits low thermal conductivity(0.066 W m^(-1)K^(-1))and good electromagnetic interference(EMI)shielding performance(average EMI SE_(T),37.8 dB).With the increase in func-tional unit layer,the overall thermal insulation performance of the whole composite film(SMC_(x))remains stable,and EMI shielding performance is greatly improved,especially for SMC_(3)with three unit layers,the average EMI SET is as high as 55.4 *** addition,the organic combination of rigid SNM and tough MXene@c-MWCNT_(6:4)makes SMC_(x)exhibit good mechanical tensile ***,SMC_(x)exhibit stable EMI shielding and excellent thermal insulation even in extreme heat and cold ***,this work provides a novel design idea and important reference value for EMI shielding and thermal insulation components used in extreme environmental protection equipment in the future.

关键词： SiO_(2)nanofiber membranes MXene@c-MWCNT Composite film Thermal insulation Electromagnetic interference shielding

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Neuroprotective potential of traditional Ayurvedic Kadha:age-related neurological disorders:a comprehensive literature review

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Traditional Medicine Research 2024年第9期9卷 51-77页

作者： Sarvin Sadreddini Mohammad Javad Emami Kazemabad Sogand Sheikholeslami Kosar Chitzan-Zadeh Mohammad Taha Kouchaki Midia Rashidi Amir Abbas Ghayerin Shahin Sabaghi Ghazal Tavakoli Sepehr Nanbakhsh Tina Mansourian Arefeh Tabashiri Fariba Arbab Mojeni mohammed Namiq amin Zahra Taheri Seyed Esmaeil Sedighi Taraneh Tarkashvand Parham Amirazodi Mobina Fathi Shirin Yaghoobpoor Niloofar Deravi School of Medicine Tabriz University of Medical SciencesTabriz ***Iran School of Medicine Qom University of Medical SciencesQom ***Iran School of Medicine Hamadan University of Medical SciencesHamadan ***Iran School of Medicine Ahvaz Jundishapur University of Medical SciencesAhvaz ***Iran Faculty of Medicine Tabriz University of Medical SciencesTabriz ***Iran School of Medicine Iran University of Medical SciencesTehran ***Iran School of Medicine Shahid Beheshti University of Medical SciencesTehran ***Iran School of Medicine Mazandaran University of Medical SciencesSari ***Iran School of Medicine Kermanshah University of Medical SciencesKermanshah ***Iran Faculty of Pharmacy Pharmaceutical Sciences BranchIslamic Azad UniversityTehran ***Iran Department of Biology Faculty of SciencePayamNoor UniversityTehran ***Iran Faculty of Medicine Islamic Azad University of Medical ScienceTehran 193951495Iran International Campus Shahid Sadoughi University of Medical SciencesYazd ***Iran

Despite modern medicine’s advancements,age-related neurological diseases like alzheimer’s disease and Parkinson’s disease remain challenging due to high costs,side effects,and limited ***,a traditional Indian medicine system,offers Kadha tea as a potential herbal *** review explores Kadha’s components(basil(Ocimum basilicum L.),black pepper(Piper nigrum L.),Cinnamon(Cinnamomum verum ***),ginger(Zingiber officinale Roscoe),and raisin(Vitis vinifera L.))and their interaction with various neurological *** suggest Kadha exhibits anti-inflammatory,antioxidant,and antiviral properties,potentially impacting alzheimer’s disease,Parkinson’s disease,neurotoxicity,neuroinflammation,and brain *** focusing on specific disease mechanisms and Kadha’s intergrade effects,this review aims to elucidate its potential role in managing age-related neurological disorders.

关键词： Ayurveda Kadha neuroprotective neurological disorders traditional medicine

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Hybrid meta-heuristic machine learning methods applied to landslide susceptibility mapping in the Sahel-algiers

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International Journal of Sediment Research 2022年第5期37卷 601-618页

作者： mohammed amin Benbouras Technology Department Ecole Normale Sup erieure D?Enseignement Technologique de Skikda (ENSET) Laboratoire Central des Travaux Publics (LCTP)

Landslides are considered as one among many phenomena jeopardizing human beings as well as their constructions. To prevent this disastrous problem, researchers have used several approaches for landslide susceptibility modeling, for the purpose of preparing accurate maps marking landslide prone *** the most frequently used approaches for landslide susceptibility mapping is the Artificial Neural Network(ANN) method. However, the effectiveness of ANN methods could be enhanced by using hybrid metaheuristic algorithms, which are scarcely applied in landslide mapping. In the current study, nine hybrid metaheuristic algorithms, genetic algorithm(GA)-ANN, evolutionary strategy(ES)-ANN, ant colony optimization(ACO)-ANN, particle swarm optimization(PSO)-ANN, biogeography based optimization(BBO)-ANN, gravitational search algorithm(GHA)-ANN, particle swarm optimization and gravitational search algorithm(PSOGSA)-ANN, grey wolves optimization(GWO)-ANN, and probability based incremental learning(PBIL)-ANN have been used to spatially predict landslide susceptibility in algiers’ Sahel,algeria. The modeling phase was done using a database of 78 landslides collected utilizing Google Earth images, field surveys, and six conditioning factors(lithology, elevation, slope, land cover, distance to stream, and distance to road). Initially, a gamma test was used to decrease the input variable ***, the optimal inputs have been modeled by the mean of hybrid metaheuristic ANN techniques and their performance was assessed through seven statistical indicators. The comparative study proves the effectiveness of the co-evolutionary PSOGSA-ANN model, which yielded higher performance in predicting landslide susceptibility compared to the other models. Sensitivity analysis using the stepby-step technique was done afterward, which revealed that the distance to the stream is the most influential factor on landslide susceptibility, followed by the slope factor which ranked second. L

关键词： Artificial neural network Hybrid metaheuristic optimization algorithms Landslide susceptibility Geographical information system Sensitivity analysis

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Fuzzy-HLSTM(Hierarchical Long Short-Term Memory)for Agricultural Based Information Mining

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Computers, Materials & Continua 2023年第2期74卷 2397-2413页

作者： Ahmed Abdu alattab mohammed Eid Ibrahim Reyazur Rashid Irshad Anwar ali Yahya amin A.al-Awady Department of Computer Science College of Science and ArtsSharurahNajran UniversityNajranSaudi Arabia Department of Computer Science College of Computer Science&Information SystemsNajran UniversityNajranSaudi Arabia Computer Skills Department Deanship of Preparatory YearNajran UniversityNajranSaudi Arabia

This research proposes a machine learning approach using fuzzy logic to build an information retrieval system for the next crop *** case-based reasoning systems,case representation is critical,and thus,researchers have thoroughly investigated textual,attribute-value pair,and ontological *** big databases result in slow case retrieval,this research suggests a fast case retrieval strategy based on an associated representation,so that,cases are interrelated in both either similar or dissimilar *** soon as a new case is recorded,it is compared to prior data to find a relative *** proposed method is worked on the number of cases and retrieval accuracy between the related case representation and conventional *** Long Short-Term Memory(HLSTM)is used to evaluate the efficiency,similarity of the models,and fuzzy rules are applied to predict the environmental condition and soil quality during a particular time of the *** on the results,the proposed approaches allows for rapid case retrieval with high accuracy.

关键词： Machine learning agriculture IoT HLSTM fuzzy rules

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A multi-purpose National Forest Inventory in Bangladesh:design,operationalisation and key results

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Forest Ecosystems 2021年第1期8卷 151-172页

作者： Matieu Henry Zaheer Iqbal Kristofer Johnson Mariam Akhter Liam Costello Charles Scott Rashed Jalal Md.Akhter Hossain Nikhil Chakma Olaf Kuegler Hossain Mahmood Rajib Mahamud Mohammad Raqibul Hasan Siddique Khaled Misbahuzzaman Mohammad Main Uddin mohammed al amin Farid Uddin Ahmed Gael Sola Md.Baktiar Siddiqui Luca Birigazzi Mahmudur Rahman Ilias Animon Saimunnahar Ritu Laskar Muqsudur Rahman aminul Islam Heather Hayden Frida Sidik Mondal Falgoonee Kumar Rakibul Hassan Mukul Hossain Nishad Ariful Hoque Belal Asif Reza Anik Abdul Khaleque Md.Shaheduzzaman Syed Shahadat Hossain Tariq Aziz Md.Tauhidor Rahaman Ruhul Mohaiman Patrick Meyer Purnata Chakma A.Z.M.Manzoor Rashid Sourav Das Shrabanti Hira mohammed Jashimuddin Mohammad Mahfuzur Rahman Karl Wurster Sarder Nasir Uddin Abul Kalam Azad S.M.Zahirul Islam Laurent Saint-André Food and Agriculture Organization of the United Nations Viale delle Terme di Caracalla00153 RomeItaly Forest Department Ministry of EnvironmentForests and Climate ChangeBan BhabanShere Bangla NagarAgargaonDhaka 1207Bangladesh School of Ecosystem and Forest Sciences University of MelbourneParkville VictoriaMelbourne 3010Australia United States Forest Service(USFS)/SilvaCarbon WashingtonD.CUSA Institute of Forestry and Environmental Sciences(IFES) University of ChittagongChattogramBangladesh Department of Forestry and Environmental Science Rangamati Science and Technology UniversityRangamatiBangladesh Forestry and Wood Technology Discipline Khulna UniversityKhulnaBangladesh School of Biological Sciences The University of QueenslandQLDBrisbane 4072Australia Arannyak Foundation DhakaBangladesh United Nations Framework Convention on Climate Change(UNFCCC) BonnGermany Bangladesh Space Research and Remote Sensing Organization(SPARRSO) DhakaBangladesh Institute for Marine Research and Observation Ministry of Marine Affairs and FisheriesNegaraBaliIndonesia Department of Agricultural Economics Bangabandhu Sheikh Mujibur Rahman Agricultural University(BSMRAU)GazipurBangladesh Bangladesh Bureau of Statistics(BBS) DhakaBangladesh Institute of Statistical Research and Training University of DhakaDhakaBangladesh United States Agency for International Development(USAID) DhakaBangladesh Department of Forestry and Environmental Science Shahjalal University of Science and TechnologyKumargaonSylhetBangladesh Department of Biological Sciences Faculty of Science and EngineeringMacquarie UniversitySydneyAustralia Bangladesh National Herbarium(BNH) Zoo RoadMirpurDhakaBangladesh Bangladesh Forest Research Institute(BFRI) SholoshaharChottogramBangladesh National Research Institute for Agriculture Food and Environment(INRAE)ParisFrance

Background:National forest inventory and forest monitoring systems are more important than ever considering continued global degradation of trees and *** systems are especially important in a country like Bangladesh,which is characterised by a large population density,climate change vulnerability and dependence on natural *** the aim of supporting the Government’s actions towards sustainable forest management through reliable information,the Bangladesh Forest Inventory(BFI)was designed and implemented through three components:biophysical inventory,socio-economic survey and remote sensing-based land cover *** article documents the approach undertaken by the Forest Department under the Ministry of Environment,Forests and Climate Change to establish the BFI as a multipurpose,efficient,accurate and replicable national forest *** design,operationalization and some key results of the process are ***:The BFI takes advantage of the latest and most well-accepted technological and methodological ***,it was designed through a collaborative process which drew from the experience and knowledge of multiple national and international ***,1781 field plots were visited,6400 households were surveyed,and a national land cover map for the year 2015 was *** technological enhancements include a semi-automated segmentation approach for developing the wall-to-wall land cover map,an object-based national land characterisation system,consistent estimates between sample-based and mapped land cover areas,use of mobile apps for tree species identification and data collection,and use of differential global positioning system for referencing plot ***:Seven criteria,and multiple associated indicators,were developed for monitoring progress towards sustainable forest management goals,informing management decisions,and national and international reporting needs.A wide range of biophysica

关键词： South-Asia Forest monitoring Innovation Remote sensing Socio-economic Partnership Ecosystem services Carbon sequestration

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Liver Tumor Decision Support System on Human Magnetic Resonance Images:A Comparative Study

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Computer Systems Science & Engineering 2023年第8期46卷 1653-1671页

作者： Hiam alquran Yazan al-Issa mohammed alslatie Isam Abu-Qasmieh amin alqudah Wan Azani Mustafa Yasmin Mohd Yacob Department of Biomedical Systems and Informatics Engineering Yarmouk University 556Irbid21163Jordan Department of Biomedical Engineering Jordan University of Science and TechnologyIrbid22110Jordan Department of Computer Engineering Yarmouk University 556Irbid21163Jordan The of Biomedical Technology King Hussein Medical CenterRoyal Jordanian Medical ServiceAmman11855Jordan Faculty of Electrical Engineering&Technology Campus Pauh PutraUniversiti Malaysia PerlisArau02600PerlisMalaysia Faculty of Electronic Engineering&Technology Campus Pauh PutraUniversiti Malaysia PerlisArau02600PerlisMalaysia Advanced Computing Centre of Excellence(CoE)Universiti Malaysia PerlisArau02600PerlisMalaysia

Liver cancer is the second leading cause of cancer death *** tumor detection may help identify suitable treatment and increase the survival *** imaging is a non-invasive tool that can help uncover abnormalities in human *** Resonance Imaging(MRI),in particular,uses magnetic fields and radio waves to differentiate internal human organs ***,the interpretation of medical images requires the subjective expertise of a radiologist and ***,building an automated diagnosis computer-based system can help specialists reduce incorrect *** paper proposes a hybrid automated system to compare the performance of 3D features and 2D features in classifying magnetic resonance liver tumor *** paper proposed two models;the first one employed the 3D features while the second exploited the 2D *** first system uses 3D texture attributes,3D shape features,and 3D graphical deep descriptors beside an ensemble classifier to differentiate between four 3D tumor *** top of that,the proposed method is applied to 2D slices for comparison *** proposed approach attained 100%accuracy in discriminating between all types of tumors,100%Area Under the Curve(AUC),100%sensitivity,and 100%specificity and precision as well in 3D liver *** the other hand,the performance is lower in 2D *** maximum accuracy reached 96.4%for two classes and 92.1%for four *** top-class performance of the proposed system can be attributed to the exploitation of various types of feature selection methods besides utilizing the ReliefF features selection technique to choose the most relevant features associated with different *** novelty of this work appeared in building a highly accurate system under specific circumstances without any processing for the images and human input,besides comparing the performance between 2D and 3D *** the future,the presented work can be extended to be

关键词： Liver tumors ensemble classifier 3D shape features 3D cooccurrence matrix ResNet101

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