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High-Performance Flow Classification of Big Data Using Hybrid CPU-GPU Clusters of Cloud Environments

Tsinghua Science and Technology 2024年第4期29卷 1118-1137页

作者： azam fazel-najafabadi Mahdi Abbasi Hani H.Attar Ayman Amer Amir Taherkordi Azad Shokrollahi Mohammad R.Khosravi Ahmed A.Solyman Department of Computer Engineering Faculty of EngineeringBu-Ali Sina UniversityHamedan ***Iran Department of Energy Engineering Zarqa UniversityZarqa 13132Jordan Department of Informatics University of OsloOslo 0316Norway Department of Computer Science MalmöUniversityMalmö20506Sweden Shandong Provincial University Laboratory for Protected Horticulture Weifang University of Science and TechnologyWeifang 261100China Department of Electrical and Electronics Engineering NişantaşıUniversityIstanbul 34481742Türkiye

The network switches in the data plane of Software Defined Networking (SDN) are empowered by an elementary process, in which enormous number of packets which resemble big volumes of data are classified into specific flows by matching them against a set of dynamic rules. This basic process accelerates the processing of data, so that instead of processing singular packets repeatedly, corresponding actions are performed on corresponding flows of packets. In this paper, first, we address limitations on a typical packet classification algorithm like Tuple Space Search (TSS). Then, we present a set of different scenarios to parallelize it on different parallel processing platforms, including Graphics Processing Units (GPUs), clusters of Central Processing Units (CPUs), and hybrid clusters. Experimental results show that the hybrid cluster provides the best platform for parallelizing packet classification algorithms, which promises the average throughput rate of 4.2 Million packets per second (Mpps). That is, the hybrid cluster produced by the integration of Compute Unified Device Architecture (CUDA), Message Passing Interface (MPI), and OpenMP programming model could classify 0.24 million packets per second more than the GPU cluster scheme. Such a packet classifier satisfies the required processing speed in the programmable network systems that would be used to communicate big medical data.

关键词： OpenMP Compute Unified Device Architecture(CUDA) Message Passing Interface(MPI) packet classification medical data tuple space algorithm Graphics Processing Unit(GPU)cluster

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AGGREGATE SPECIAL FUNCTIONS TO APPROXIMATE PERMUTING TRI-HOMOMORPHISMS AND PERMUTING TRI-DERIVATIONS ASSOCIATED WITH A TRI-ADDITIVEψ-FUNCTIONAL INEQUALITY IN BANACH ALGEBRAS

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Acta Mathematica Scientia 2024年第1期44卷 311-338页

作者： Safoura Rezaei ADERYANI azam AHADI Reza SAADATI Hari M.SRIVASTAVA School of Mathematics Iran University of Science and TechnologyNarmakTehranIran Department of Mathematics and Statistics Universtity of VictoriaVictoriaCanada Department of Medical Research China Medical University HospitalChina Medical UniversityTaichung40402China Department of Mathematics and Informatics Azerbaijan University71 Jeyhun Hajibeyli StreetAZ1007BakuAzerbaijan Section of Mathematics International TelematicUniversity UninettunoI-00186RomeItaly

In this paper,we define a new class of control functions through aggregate special *** class of control functions help us to stabilize and approximate a tri-additiveψ-functional inequality to get a better estimation for permuting tri-homomorphisms and permuting tri-derivations in unital C*-algebras and Banach algebras by the vector-valued alternative fixed point theorem.

关键词： permuting tri-homomorphism in Banach algebra permuting tri-derivation on C*-algebra fixed point theorem Ulam-Hyers-Rassias stability aggregate special functions tri-additiveψ-functional inequality

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Enhanced Topic-Aware Summarization Using Statistical Graph Neural Networks

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Computers, Materials & Continua 2024年第8期80卷 3221-3242页

作者： Ayesha Khaliq Salman Afsar Awan Fahad Ahmad Muhammad azam Zia Muhammad Zafar Iqbal Department of Computer Science University of Agriculture FaisalabadFaisalabadPunjab37300Pakistan School of Computing Faculty of TechnologyUniversity of PortsmouthSouthseaPortsmouthPO12UPUK Department of Mathematics and Statistics University of Agriculture FaisalabadFaisalabadPunjab37300Pakistan

The rapid expansion of online content and big data has precipitated an urgent need for efficient summarization techniques to swiftly comprehend vast textual documents without compromising their original *** approaches in Extractive Text Summarization(ETS)leverage the modeling of inter-sentence relationships,a task of paramount importance in producing coherent *** study introduces an innovative model that integrates Graph Attention Networks(GATs)with Transformer-based Bidirectional Encoder Representa-tions from Transformers(BERT)and Latent Dirichlet Allocation(LDA),further enhanced by Term Frequency-Inverse Document Frequency(TF-IDF)values,to improve sentence selection by capturing comprehensive topical *** approach constructs a graph with nodes representing sentences,words,and topics,thereby elevating the interconnectivity and enabling a more refined understanding of text *** model is stretched to Multi-Document Summarization(MDS)from Single-Document Summarization,offering significant improvements over existing models such as THGS-GMM and Topic-GraphSum,as demonstrated by empirical evaluations on benchmark news datasets like Cable News Network(CNN)/Daily Mail(DM)and *** results consistently demonstrate superior performance,showcasing the model’s robustness in handling complex summarization tasks across single and multi-document *** research not only advances the integration of BERT and LDA within a GATs but also emphasizes our model’s capacity to effectively manage global information and adapt to diverse summarization challenges.

关键词： Summarization graph attention network bidirectional encoder representations from transformers Latent Dirichlet Allocation term frequency-inverse document frequency

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Contemporary Study for Detection of COVID-19 Using Machine Learning with Explainable AI

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Computers, Materials & Continua 2024年第7期80卷 1075-1104页

作者： Saad Akbar Humera azam Sulaiman Sulmi Almutairi Omar Alqahtani Habib Shah Aliya Aleryani Department of Computer Science University of KarachiKarachi75270Pakistan Department of Computing Faculty of Engineering Science and TechnologyHamdard UniversityKarachi75540Pakistan Department of Health Informatics College of Applied Medical SciencesQassim UniversityQassim51452Saudi Arabia Department of Computer Science College of Computer ScienceKing Khalid UniversityAbha61421Saudi Arabia

The prompt spread of COVID-19 has emphasized the necessity for effective and precise diagnostic *** this article,a hybrid approach in terms of datasets as well as the methodology by utilizing a previously unexplored dataset obtained from a private hospital for detecting COVID-19,pneumonia,and normal conditions in chest X-ray images(CXIs)is proposed coupled with Explainable Artificial Intelligence(XAI).Our study leverages less preprocessing with pre-trained cutting-edge models like InceptionV3,VGG16,and VGG19 that excel in the task of feature *** methodology is further enhanced by the inclusion of the t-SNE(t-Distributed Stochastic Neighbor Embedding)technique for visualizing the extracted image features and Contrast Limited Adaptive Histogram Equalization(CLAHE)to improve images before extraction of ***,an AttentionMechanism is utilized,which helps clarify how the modelmakes decisions,which builds trust in artificial intelligence(AI)*** evaluate the effectiveness of the proposed approach,both benchmark datasets and a private dataset obtained with permissions from Jinnah PostgraduateMedical Center(JPMC)in Karachi,Pakistan,are *** 12 experiments,VGG19 showcased remarkable performance in the hybrid dataset approach,achieving 100%accuracy in COVID-19 *** classification and 97%in distinguishing normal ***,across all classes,the approach achieved 98%accuracy,demonstrating its efficiency in detecting COVID-19 and differentiating it fromother chest disorders(Pneumonia and healthy)while also providing insights into the decision-making process of the models.

关键词： COVID-19 detection deep neural networks support vector machine CXIs InceptionV3 VGG16 VGG19 t-SNE embedding CLAHE attention mechanism XAI

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Changes in sexual activity in young women during pregnancy

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Asian pacific Journal of Reproduction 2024年第5期13卷 213-218页

作者： Ghazal Mansouri Mina Zakeri Fatemeh Karami Robati Leila Allahqoli azam Dehghani Department of Obstetrics and Gynecology School of MedicineAfzalipour HospitalKerman University of Medical SciencesKermanIran Clinical Research Development Unit Afzalipour HospitalKerman University of Medical SciencesKermanIran School of Public Health Iran University of Medical Sciences(IUMS)TehranIran Gastroenterology and Hepatology Research Center Institute of Basic and Clinical Physiology SciencesKerman University of Medical SciencesKermanIran

Objective:To conduct changes in sexual activity during pregnancy and its related factors in pregnant ***:The present descriptive cross-sectional study was conducted in 2017 on pregnant women who referred to the women's clinic of Afzalipour Hospital in the southeast of *** were included in the study through convenient *** data collection tool was a researcher-made questionnaire consisting of two parts of personal social information of the couple and questions to measure the level of sexual activity and the attitude of the subjects during pregnancy compared to before ***:201 Pregnant women were *** average age of pregnant women was(27.3±6.1)years and their average gestational age was(24.7±11.8)*** than 62%of women had decreased sexual *** was a significant relationship between the amount of changes in sexual activity and delivery time(P=0.013),abortion history(P=0.001)and premature birth history(P=0.002).Most pregnant women believed that sex during pregnancy caused damage to the fetus(67.7%).A decrease in the intensity of sexual desire was reported in 63%of pregnant *** than 60%of the subjects did not consult with doctors and midwives with regards to sexual issues(63.5%).The most common reason for not consulting was not feeling the need(32%).Most women experienced back pain during(42.8%)and after(39.8%)***:Changes in sex life during pregnancy are often caused by the lack of sexual knowledge and the increase in misconceptions among couples,which can affect the quality of *** role of education is ***,it is suggested that by including sexual counseling along with pregnancy care,wrong beliefs and information among women will be corrected.

关键词： Sexual behavior Women Pregnancy Midwifery Sex counseling Fetus

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Natural resource scarcity,fossil fuel energy consumption,and total greenhouse gas emissions in top emitting countries

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Geoscience Frontiers 2024年第2期15卷 85-99页

作者： Jiannan Wang Waseem azam College of Economics and Management South China Agricultural UniversityGuangzhouChina Groupe Ecole de Commerce de Lyon LyonFrance Institute Supérieur de l’Environnement-ISE LYON France

Natural resource scarcity,fossil fuel energy consumption,and total greenhouse gas emissions are critical issues that require immediate *** the global population steadily increasing and economies expanding,the demand for natural resources,particularly fossil fuels,has experienced an unprecedented *** surge in consumption is directly linked to the alarming rise in greenhouse gas *** study examines the nexus between agricultural nitrous oxide emissions and natural resource scarcity,taking into account the dynamics of agriculture,forestry,fishing value addition,fossil fuels,and total greenhouse gas emissions in top-emitting countries between 1971 and *** resource scarcity positively correlates with agriculture,forestry,fishing,fossil fuel energy consumption,and total greenhouse gas *** is a decrease in natural resource scarcity in countries that emit agricultural nitrous oxide,forestry,fishing emissions,fossil fuel energy consumption,and greenhouse gas ***-makers may promote sustainable development,mitigate climate change,and ensure the longterm viability of agricultural systems by addressing the dynamics of agriculture,forestry,and fishing value addition in top-emitting *** strategic policy interventions,supported by technology transfer,capacity building,and market-based instruments,the agricultural,forestry,and fishing sector can achieve a more sustainable future while addressing the challenges of natural resource scarcity.

关键词： Resource scarcity Non-renewable energy CO_(2)emissions Top-emitting countries

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Examination of the Effective Factors on the Multiple Sclerosis Diseases

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Open Journal of Internal Medicine 2024年第2期14卷 213-227页

作者： Rakeeh Ghaderi azam Alikhademi Sampad Organization Farzanegan High School Tehran Iran Faculty of Foreign Language Islamic Azad University Tehran Iran

This study was an attempt to examine the effective factors of the Multiple Sclerosis diseases. The participants of the study were selected from among a total number of 45 men and women who were treated in a health center in Azarbayegan and Damavand in Iran. In order to study, the researchers applied various procedures to collect the data of the study. The participants were interviewed and filled out the questionnaires. After categorizing and classifying the collected information and data, it was processed and analyzed and the results are found. To test the research questions, a one-sample T-test was used to analyze the data. The role of hypo vitamin D as a possible risk factor for multiple sclerosis was reviewed. First, it was emphasized that hypo vitamin could be only one of the risk factors for multiple sclerosis and that numerous other environmental and genetic risk factors appear to interact and combine to trigger the disease. The main aim of this study was to examine the effective factors of Multiple Sclerosis diseases. The methodology of this research was to test the research questions;one-sample T-test was used to analyze the data. The findings of this study revealed that the factors of gender, cold weather, vitamin D deficiency, and age (between 30 - 59) were effective on the Multiple Sclerosis diseases.

关键词： Multiple Sclerosis Disease Effective Factors

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Glacier area change (1993-2019) and its relationship to debris cover, proglacial lakes, and morphological parameters in the Chandra-Bhaga Basin, Western Himalaya, India

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Journal of Mountain Science 2024年第4期21卷 1287-1306页

作者： VATSAL Sarvagya azam Mohd Farooq BHARDWAJ Anshuman MANDAL Arindan BAHUGUNA Ishmohan RAMANATHAN Alagappan RAJU N.Janardhana TOMAR Sangita Singh Department of Civil Engineering Indian Institute of Technology IndoreSimrol 453552India School of Geosciences University of AberdeenKing’s CollegeAberdeen AB243FXUnited Kingdom Interdisciplinary Centre for Water Research Indian Institute of ScienceBengaluru 560012India Space Application Centre Ahmedabad 380015India School of Environmental Sciences Jawaharlal Nehru UniversityNew Delhi 110067India Department of Geography Norwegian University of Science and TechnologyTrondheim No-7491Norway

Glacier inventories serve as critical baseline data for understanding the impacts of climate change on *** present study maps the outlines of glaciers in the Chandra-Bhaga Basin(western Himalaya)for the years 1993,2000,2010,and 2019 using Landsat Thematic Mapper(TM),Enhanced Thematic Mapper(ETM),and Operational Land Imager(OLI)datasets.A total of 251 glaciers,each having an area above 0.5 km^(2),were identified,which include 216 clean-ice and 35 debris-covered *** changes are estimated for three periods:1993-2000,2000-2010,and *** total glacierized area was 996±62 km^(2) in 1993,which decreased to 973±70 km^(2) in *** mean rate of glacier area loss was higher in the recent decade(2010-2019),at 0.036 km^(2),compared to previous decades(0.029 km^(2) in 2000-2010 and 0.025 km^(2) in 1993-2000).Supraglacial debris cover changes are also mapped over the period of 1993 and *** is found that the supraglacial debris cover increased by 14.12±2.54 km^(2)(15.2%)during *** field surveys on Chhota Shigri,Panchi II,Patsio,Hamtah,Mulkila,and Yoche Lungpa glaciers were carried out to validate the glacier outlines and supraglacial debris cover estimated using satellite *** of various morphological parameters on retreat were also *** is observed that small,clean ice,south oriented glaciers,and glaciers with proglacial lakes are losing area at faster rates than other glaciers in the basin.

关键词： Glacier Area change Debris cover Morphology Proglacial lake

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Federated Machine Learning Based Fetal Health Prediction Empowered with Bio-Signal Cardiotocography

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Computers, Materials & Continua 2024年第3期78卷 3303-3321页

作者： Muhammad Umar Nasir Omar Kassem Khalil Karamath Ateeq Bassam SaleemAllah Almogadwy Muhammad Adnan Khan Muhammad Hasnain azam Khan Muhammad Adnan Department of Computer Sciences Bahria University Lahore CampusLahore54000Pakistan Faculty of Information Technology Liwa CollegeAbu Dhabi00000United Arab Emirates Department of Computing Skyline University CollegeSharjah1797United Arab Emirates Department of Computer Science Taibah UniversityMedina42353Saudi Arabia Riphah School of Computing and Innovation Faculty of ComputingRiphah International UniversityLahore CampusLahore54000Pakistan Department of Engineering and Development Dubizzle LabsLahore54000Pakistan Department of Software Faculty of Artificial Intelligence and SoftwareGachon UniversitySeongnam-si13120Korea

Cardiotocography measures the fetal heart rate in the fetus during pregnancy to ensure physical health because cardiotocography gives data about fetal heart rate and uterine shrinkages which is very beneficial to detect whether the fetus is normal or suspect or *** cardiotocography measures infer wrongly and give wrong predictions because of human *** traditional way of reading the cardiotocography measures is the time taken and belongs to numerous human errors as *** condition is very important to measure at numerous stages and give proper medications to the fetus for its *** the current period Machine learning(ML)is a well-known classification strategy used in the biomedical field on various issues because ML is very fast and gives appropriate results that are better than traditional *** techniques play a pivotal role in detecting fetal disease in its early *** research article uses Federated machine learning(FML)and ML techniques to classify the condition of the *** study proposed a model for the detection of bio-signal cardiotocography that uses FML and ML techniques to train and test the ***,the proposed model of FML used numerous data preprocessing techniques to overcome data deficiency and achieves 99.06%and 0.94%of prediction accuracy and misprediction rate,respectively,and parallel the proposed model applying K-nearest neighbor(KNN)and achieves 82.93%and 17.07%of prediction accuracy and misprediction accuracy,***,by comparing both models FML outperformed the KNN technique and achieved the best and most appropriate prediction results as compared with previous studies the proposed study achieves the best and most accurate results.

关键词： Cardiotocography ML FML fetal disease bio-signal

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Metabolic puzzle: Exploring liver fibrosis differences in Asian metabolic-associated fatty liver disease subtypes

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World Journal of Hepatology 2024年第1期16卷 54-64页

作者： Sabhita Shabir Shaikh Fakhar Ali Qazi-Arisar Saba Nafay Sidra Zaheer Hafeezullah Shaikh Zahid azam National Institute of Liver and GI Diseases Dow University of Health SciencesSindhKarachi 75330Pakistan School of Public Health Dow University of Health SciencesSindhKarachi 75330Pakistan

BACKGROUND Metabolic-associated fatty liver disease(MAFLD)is a liver condition marked by excessive fat buildup in the absence of heavy alcohol *** is primarily linked with metabolic issues like insulin resistance,obesity,and abnormal lipid levels,and is often observed with other conditions such as type 2 diabetes and cardiovascular ***,whether the subtypes of MAFLD based on the metabolic disorder differentially impact liver fibrosis is not well explicated,especially in the Asian *** To compare the severity of liver fibrosis among different MAFLD *** A total of 322 adult patients of either gender with fatty liver on ultrasound were enrolled between January to December *** was defined as per the Asian Pacific Association for the Study of the Liver ***-4 index(Fib-4)and nonalcoholic fatty liver disease fibrosis score(NFS)were employed to evaluate liver *** The mean age was 44.84±11 ***-two percent of the patients were *** hundred and seventy-three patients were classified as having MAFLD,of which 110(40.3%)carried a single,129(47.3%)had two,and 34(12.5%)had all three metabolic *** cumulative number of metabolic conditions was related to elevated body mass index,triglyceride(TG)levels,and glycated hemoglobin,lower high-density lipoprotein(HDL)levels,higher liver inflammation(by aspartate aminotransferase andγ-glutamyl transferase),and higher likelihood of fibrosis(by NFS and Fib-4 scores)(P<0.05 for all).The proportion of advanced fibrosis also increased with an increase in the number of metabolic conditions(4.1%,25.5%,35.6%,and 44.1%by NFS and 6.1%,10.9%,17%,and 26.5%by Fib-4 for no MAFLD and MAFLD with 1,2,and 3 conditions,respectively).Among MAFLD patients,those with diabetes alone were the eldest and had the highest mean value of NFS score and Fib-4 score(P<0.05),while MAFLD patients diagnosed with lean metabolic dysfunction exhibited the highest levels of TG and a

关键词： Metabolic syndrome Diabetes Fatty liver disease Dyslipidemia Obesity

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