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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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The Impact of Total Intravenous Propofol Anaesthesia versus Sevoflurane Anaesthesia on Perioperative Pain in Patients Undergoing Colonic Cancer Surgery

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Open Journal of Anesthesiology 2021年第1期11卷 1-11页

作者： Bahaa Gamal Saad Samy Abdelrahman Amr ashraf amin mohammed Montaser Abdelfattah mohammed Department of Anesthesia Intensive Care and Pain Management South Egypt Cancer Institute Assuit University Assuit Egypt

Background: Cancer colon is one of the most common malignancies. After colon cancer surgery patients may experience severe pain. Several studies have reported that a significant decrease in postoperative pain with propofol while other studies have showed this effect was not significant. Aim: Our goal was to assess the effect of combined epidural anaesthesia either with propofol or sevoflurane on intraoperative fentanyl consumption and postoperative pain in patients undergoing open surgical resection of colon cancer. Patients and Methods: 48 adult patients suffering from cancer colon scheduled for open surgical resection randomly allocated either to receive epidural-propofol by total intra venous anaesthesia (TIVA) (n = 24) or epidural-sevoflurane

关键词： Cancer Colon Epidural Anesthesia Propofol Sevoflurane Postoperative Pain

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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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Effect of Bilateral Ultrasound-Guided Quadratus Lumborum Block versus Lumbar Epidural Block on Postoperative Analgesia following Major Lower Abdominal Cancer Surgery

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Open Journal of Anesthesiology 2021年第12期11卷 335-346页

作者： Moaaz Mohamed Tohamy Samy Abdelrahman Amr ashraf amin mohammed Ahmad Mohamad Abd El-Rahman Basma Rezk Farouk Mohamed Galal Mostafa El-Naggar Mahmoud Mostafa mohammed Montaser A. Mohamed Department of Anesthesia Intensive Care and Pain Management South Egypt Cancer Institute Assiut University Assiut Egypt Department of Biostatistics and Cancer Epidemiology South Egypt Cancer Institute Assiut University Assiut Egypt Department of Clinical Pathology South Egypt Cancer Institute Assiut University Assiut Egypt Department of Surgical Oncology South Egypt Cancer Institute Assiut University Assiut Egypt

Background: Poor postoperative pain control leads to longer postoperative care, longer hospital stay and decreased patient overall satisfaction. Aim: To compare the efficacy and safety of bilateral ultrasound-guided quadratus lumborum block versus lumbar epidural block on the management of postoperative pain following major lower abdominal cancer surgery. Methods: The study was a double-blinded, and randomized study, conducted in South Egypt Cancer Institute, Assiut University, Egypt. It included cancer patients scheduled for major lower abdominal cancer surgery in the period from 2019 to 2020. They were divided into two groups: Group Ι received pre-emptive ultrasound-guided Quadratus Lumborum Block (QLB) with 25 mL of 0.25% bupivacaine on each side of the abdominal wall before induction of General Anesthesia (GA), and Group II received pre-emptive lumbar epidural block with 15 mL of 0.25% bupivacaine before induction of GA. VAS score, and time of the first analgesic request and postoperative total analgesic consumption were evaluated. Results: Sixty patients were included in our study. VAS score at rest was comparable between both studied groups in the first 6 h. At 8 and 10 h, Group II had a significantly higher VAS score at rest (P Limitation:

关键词： Quadratus Lumborum Block Lumbar Epidural Block Postoperative Pain Abdominal Cancer Surgery

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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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An Acceptance Model of Using Mobile-Government Services(AMGS)

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Computer Modeling in Engineering & Sciences 2022年第5期131卷 865-880页

作者： Ahmad Althunibat Mohammad Abdallah mohammed amin Almaiah Nour Alabwaini Thamer Ahmad Alrawashdeh Department of Software Engineering Faculty of Science and Information TechnologyAl-Zaytoonah University of JordanAmmanJordan Faculty of Computer Sciences and Information Technology King Faisal UniversityAl-AhsaSaudi Arabia

In recent years,the telecommunications sector is no longer limited to traditional communications,but has become the backbone for the use of data,content and digital applications by individuals,governments and companies to ensure the continuation of economic and social activity in light of social distancing and total closure inmost countries in the ***,electronic government(e-Government)andmobile government(m-Government)are the results of technological evolution and ***,it is important to investigate the factors that influence the intention to use m-Government services among Jordan’s *** paper proposed a new m-Government acceptance model in Jordan(AMGS);this model combines the Information System(IS)Success Factor Model and Hofstede Cultural Dimensions *** study was conducted by surveying different groups of the Jordanian *** questionnaire was used to collect data from203 *** regression analysis has been conducted to analyze the *** results indicate that the significant predictors of citizen intention to use m-Government services in Jordan are Information Quality,Service Quality,Uncertainty Avoidance,and Indulgence ***,the results also suggest that Power Distance is not a significant predictor of citizen intention to use m-Government services.

关键词： Acceptance test e-Government m-Government acceptance model IS success factor model Hofstede cultural dimensions theory

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